Version 2.0 on CRAN

check for 2.0
patient ID in first isolate
2026-09-25 02:18:20 +02:00 · 2023-03-12 14:07:45 +01:00 · 2023-03-12 13:02:37 +01:00 · 2023-03-11 17:13:19 +01:00 · 2023-03-11 16:54:02 +01:00 · 2023-03-11 14:43:31 +01:00
209 changed files with 18277 additions and 9347 deletions
@@ -36,7 +36,7 @@ if command -v Rscript > /dev/null; then
  if [ "$(Rscript -e 'cat(all(c('"'pkgload'"', '"'devtools'"', '"'dplyr'"') %in% rownames(installed.packages())))')" = "TRUE" ]; then
    Rscript -e "source('data-raw/_pre_commit_hook.R')"
    currentpkg=$(Rscript -e "cat(pkgload::pkg_name())")
-    echo "-> Adding files in 'data-raw' and 'man' to this commit"
+    echo "- Adding changed files in ./data-raw and ./man to this commit"
    git add data-raw/*
    git add man/*
    git add R/sysdata.rda
@@ -65,7 +65,7 @@ if [ "$currenttag" = "" ]; then
  # there is no tag, so set tag to 0.0.1 and commit index to current count
  currenttag="0.0.1"
  currentcommit=$(git rev-list --count ${defaultbranch})
-  echo "- no git tags found, create one in format 'v(x).(y).(z)' - curently ${currentcommit} previous commits in ${defaultbranch}"
+  echo "- no git tags found, create one in format 'v(x).(y).(z)' - curently ${currentcommit} previous commits in '${defaultbranch}'"
 else
  # there is a tag, so base version number on that
  currentcommit=$(git rev-list --count ${currenttagfull}..${defaultbranch})
@@ -73,7 +73,7 @@ else
    # tag is new, so this must become the version number
    currentversion="$currenttag"
  fi
-  echo "- latest tag is '${currenttagfull}', with ${currentcommit} previous commits in ${defaultbranch}"
+  echo "- latest tag is '${currenttagfull}', with ${currentcommit} previous commits in '${defaultbranch}'"
 fi
 if [ "$currentversion" = "" ]; then
  # combine tag (e.g. 1.2.3) and commit number (like 5) increased by 9000 to indicate beta version
@@ -84,7 +84,7 @@ echo "- ${currentpkg} pkg version set to ${currentversion}"
 # set version number and date to DESCRIPTION file
 sed -i -- "s/^Version: .*/Version: ${currentversion}/" DESCRIPTION
 sed -i -- "s/^Date: .*/Date: $(date '+%Y-%m-%d')/" DESCRIPTION
-echo "- updated DESCRIPTION"
+echo "- updated version number and date in ./DESCRIPTION"
 # remove leftover on macOS
 rm -f DESCRIPTION--
 # add to commit
@@ -96,7 +96,7 @@ if [ -e "NEWS.md" ]; then
    currentpkg=""
  fi
  sed -i -- "1s/.*/# ${currentpkg} ${currentversion}/" NEWS.md
-  echo "- updated NEWS.md"
+  echo "- updated version number in ./NEWS.md"
  # remove leftover on macOS
  rm -f NEWS.md--
  # add to commit
@@ -25,4 +25,4 @@ data-raw/DSMZ_bactnames.xlsx
 data-raw/country_analysis_url_token.R
 data-raw/country_analysis2.R
 data-raw/taxonomy.csv
-data-raw/WHONET
+data-raw/WHONET/*
@@ -1,3 +1,3 @@
-Version: 1.8.2
-Date: 2022-09-27 12:18:42 UTC
-SHA: ccb09706e4f168ab6133de3d2294bcaeed0d3fc8
+Version: 2.0.0
+Date: 2023-03-12 12:42:08 UTC
+SHA: 80cfc503c29ad48806e526b97d4570600bbd5420
@@ -1,6 +1,6 @@
 Package: AMR
-Version: 1.8.2.9096
-Date: 2023-01-21
+Version: 2.0.0
+Date: 2023-03-12
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)
  data analysis and to work with microbial and antimicrobial properties by
@@ -26,7 +26,8 @@ Authors@R: c(
  person(family = "Salm",        c("Jonas"), role = "ctb"),
  person(family = "Schade",      c("Rogier", "P."), role = "ctb"),
  person(family = "Sinha",       c("Bhanu", "N.", "M."), role = "ths", comment = c(ORCID = "0000-0003-1634-0010")),
-  person(family = "Underwood",   c("Anthony"), role = "ctb", comment = c(ORCID = "0000-0002-8547-4277")))
+  person(family = "Underwood",   c("Anthony"), role = "ctb", comment = c(ORCID = "0000-0002-8547-4277")),
+  person(family = "Williams",    c("Anita"), role = "ctb", comment = c(ORCID = "0000-0002-5295-8451")))
 Depends: R (>= 3.0.0)
 Enhances:
  cleaner,
@@ -73,6 +73,7 @@ S3method(asin,mic)
 S3method(asinh,mic)
 S3method(atan,mic)
 S3method(atanh,mic)
+S3method(barplot,antibiogram)
 S3method(barplot,disk)
 S3method(barplot,mic)
 S3method(barplot,rsi)
@@ -123,6 +124,7 @@ S3method(mean_amr_distance,mic)
 S3method(mean_amr_distance,sir)
 S3method(median,mic)
 S3method(min,mic)
+S3method(plot,antibiogram)
 S3method(plot,disk)
 S3method(plot,mic)
 S3method(plot,resistance_predict)
@@ -216,6 +218,7 @@ export(aminoglycosides)
 export(aminopenicillins)
 export(amr_distance_from_row)
 export(anti_join_microorganisms)
+export(antibiogram)
 export(antifungals)
 export(antimicrobials_equal)
 export(antimycobacterials)
@@ -1,19 +1,17 @@
-# AMR 1.8.2.9096
-
-*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*
+# AMR 2.0.0

 This is a new major release of the AMR package, with great new additions but also some breaking changes for current users. These are all listed below.

 **[TL;DR](https://en.wikipedia.org/wiki/TL;DR)**

 * All functions and arguments with 'rsi' were replaced with 'sir', such as the interpretation of MIC values (now `as.sir()` instead of `as.rsi()`) - all old functions still work for now
+* Many new interesting functions, such as `antibiogram()` (for generating traditional/combined/syndromic/WISCA antibiograms), `sir_confidence_interval()` and `mean_amr_distance()`, and `add_custom_microorganisms()` to add custom microorganisms to this package
+* Clinical breakpoints added for EUCAST 2022 and CLSI 2022
 * Microbiological taxonomy (`microorganisms` data set) updated to 2022 and now based on LPSN and GBIF
 * Much increased algorithms to translate user input to valid taxonomy, e.g. by using [recent scientific work](https://doi.org/10.1099/mic.0.001269) about per-species human pathogenicity
-* Clinical breakpoints added for EUCAST 2022 and CLSI 2022
 * 20 new antibiotics added and updated all DDDs and ATC codes
 * Extended support for antiviral agents (`antivirals` data set), with many new functions
-* Now available in 16 languages
-* Many new interesting functions, such as `sir_confidence_interval()` and `mean_amr_distance()`, and `add_custom_microorganisms()` to add custom microorganisms to this package
+* Now available in 20 languages
 * Many small bug fixes

 ## New
@@ -26,17 +24,33 @@ While existing functions such as `as.rsi()`, `rsi_df()` and `ggplot_rsi()` still

 The 'RSI functions' will be removed in a future version, but not before late 2023 / early 2024.

+### New antibiogram function
+
+With the new `antibiogram()` function, users can now generate traditional, combined, syndromic, and even weighted-incidence syndromic combination antibiograms (WISCA). With this, we follow the logic in the previously described work of Klinker *et al.* (2021, DOI [10.1177/20499361211011373](https://doi.org/10.1177/20499361211011373)) and Barbieri *et al.* (2021, DOI [10.1186/s13756-021-00939-2](https://doi.org/10.1186/s13756-021-00939-2)).
+
+The help page for `antibiogram()` extensively elaborates on use cases, and `antibiogram()` also supports printing in R Markdown and Quarto, with support for 20 languages.
+
+Furthermore, different plotting methods were implemented to allow for graphical visualisations as well.
+
 ### Interpretation of MIC and disk diffusion values

 The clinical breakpoints and intrinsic resistance of EUCAST 2022 and CLSI 2022 have been added for `as.sir()`. EUCAST 2022 (v12.0) is now the new default guideline for all MIC and disks diffusion interpretations, and for `eucast_rules()` to apply EUCAST Expert Rules. The default guideline (EUCAST) can now be changed with the new `AMR_guideline` option, such as: `options(AMR_guideline = "CLSI 2020")`.
+
+With the new arguments `include_PKPD` (default: `TRUE`) and `include_screening` (default: `FALSE`), users can now specify whether breakpoints for screening and from the PK/PD table should be included when interpreting MICs and disks diffusion values. These options can be set globally, which can be read in [our new manual](https://msberends.github.io/AMR/reference/AMR-options.html).
 
 Interpretation guidelines older than 10 years were removed, the oldest now included guidelines of EUCAST and CLSI are from 2013.

 ### Supported languages

-We added support for the following languages: Chinese, Greek, Japanese, Polish, Turkish and Ukrainian. All antibiotic names are now available in these languages, and the AMR package will automatically determine a supported language based on the user system language.
+We added support for the following ten languages: Chinese (simplified), Czech, Finnish, Greek, Japanese, Norwegian (bokmål), Polish, Romanian, Turkish and Ukrainian. All antibiotic names are now available in these languages, and the AMR package will automatically determine a supported language based on the user's system language.

-We are very grateful for the valuable input by our colleagues from other countries. The `AMR` package is now available in 16 languages and according to download stats used in almost all countries in the world!
+We are very grateful for the valuable input by our colleagues from other countries. The `AMR` package is now available in 20 languages in total, and according to download stats used in almost all countries in the world!
+
+### Outbreak management
+
+For analysis in outbreak management, we updated the `get_episode()` and `is_new_episode()` functions: they now contain an argument `case_free_days`. This argument can be used to quantify the duration of case-free days (the inter-epidemic interval), after which a new episode will start. 
+
+This is common requirement in outbreak management, e.g. when determining the number of norovirus outbreaks in a hospital. The case-free period could then be 14 or 28 days, so that new norovirus cases after that time will be considered a different (or new) episode.

 ### Microbiological taxonomy

@@ -49,6 +63,7 @@ The new function `add_custom_microorganisms()` allows users to add custom microo
 We also made the following changes regarding the included taxonomy or microorganisms functions:

 * Updated full microbiological taxonomy according to the latest daily LPSN data set (December 2022) and latest yearly GBIF taxonomy backbone (November 2022)
+* Added function `mo_current()` to get the currently valid taxonomic name of a microorganism
 * Support for all 1,516 city-like serovars of *Salmonella*, such as *Salmonella* Goldcoast. Formally, these are serovars belonging to the *S. enterica* species, but they are reported with only the name of the genus and the city. For this reason, the serovars are in the `subspecies` column of the `microorganisms` data set and "enterica" is in the `species` column, but the full name does not contain the species name (*enterica*).
 * All new algorithm for `as.mo()` (and thus all `mo_*()` functions) while still following our original set-up as described in our recently published JSS paper (DOI [10.18637/jss.v104.i03](https://doi.org/10.18637/jss.v104.i03)).
  * A new argument `keep_synonyms` allows to *not* correct for updated taxonomy, in favour of the now deleted argument `allow_uncertain`
@@ -90,11 +105,14 @@ We now added extensive support for antiviral agents! For the first time, the `AM
 * Function `sir_confidence_interval()` to add confidence intervals in AMR calculation. This is now also included in `sir_df()` and `proportion_df()`.
 * Function `mean_amr_distance()` to calculate the mean AMR distance. The mean AMR distance is a normalised numeric value to compare AMR test results and can help to identify similar isolates, without comparing antibiograms by hand.
 * Function `sir_interpretation_history()` to view the history of previous runs of `as.sir()` (previously `as.rsi()`). This returns a 'logbook' with the selected guideline, reference table and specific interpretation of each row in a data set on which `as.sir()` was run.
-* Function `mo_current()` to get the currently valid taxonomic name of a microorganism
-* Function `add_custom_antimicrobials()` to add custom antimicrobial codes and names to the `AMR` package
+

 ## Changes

+* `get_episode()` (and its wrapper `is_new_episode()`):
+  * Fix for working with `NA` values
+  * Fix for unsorted dates of length 2
+  * Now returns class `integer` instead of `numeric` since they are always whole numbers
 * Argument `combine_IR` has been removed from this package (affecting functions `count_df()`, `proportion_df()`, and `sir_df()` and some plotting functions), since it was replaced with `combine_SI` three years ago
 * Using `units` in `ab_ddd(..., units = "...")` had been deprecated for some time and is now not supported anymore. Use `ab_ddd_units()` instead.
 * Support for `data.frame`-enhancing R packages, more specifically: `data.table::data.table`, `janitor::tabyl`, `tibble::tibble`, and `tsibble::tsibble`. AMR package functions that have a data set as output (such as `sir_df()` and `bug_drug_combinations()`), will now return the same data type as the input.
@@ -123,14 +141,16 @@ We now added extensive support for antiviral agents! For the first time, the `AM
 * Antimicrobial interpretation 'SDD' (susceptible dose-dependent, coined by CLSI) will be interpreted as 'I' to comply with EUCAST's 'I' in `as.sir()`
 * Fix for `mo_shortname()` in case of higher taxonomic ranks (order, class, phylum)
 * Cleaning columns with `as.sir()`, `as.mic()`, or `as.disk()` will now show the column name in the warning for invalid results
+* Fix for using `g.test()` with zeroes in a 2x2 table
+* `mo_synonyns()` now contains the scientific reference as names

 ## Other

-* Added Peter Dutey-Magni, Dmytro Mykhailenko, Anton Mymrikov, Andrew Norgan, and Jonas Salm as contributors, to thank them for their valuable input
+* Added Peter Dutey-Magni, Dmytro Mykhailenko, Anton Mymrikov, Andrew Norgan, Jonas Salm, and Anita Williams as contributors, to thank them for their valuable input
 * New website to make use of the new Bootstrap 5 and pkgdown 2.0. The website now contains results for all examples and will be automatically regenerated with every change to our repository, using GitHub Actions
 * All R and Rmd files in this project are now styled using the `styler` package
 * Set scalar conditional expressions (`&&` and `||`) where possible to comply with the upcoming R 4.3
-* An enormous lot of code cleaning, fixing some small bugs on the way
+* An enormous lot of code cleaning, fixing some small bugs along the way

 ----

@@ -33,12 +33,12 @@
 #' Welcome to the `AMR` package.
 #'
 #' The `AMR` package is a [free and open-source](https://msberends.github.io/AMR/#copyright) R package with [zero dependencies](https://en.wikipedia.org/wiki/Dependency_hell) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. [Many different researchers](https://msberends.github.io/AMR/authors.html) from around the globe are continually helping us to make this a successful and durable project!
-#' 
-#' This work was published in the Journal of Statistical Software (Volume 104(3); [DOI 10.18637/jss.v104.i03](https://doi.org/10.18637/jss.v104.i03)) and formed the basis of two PhD theses ([DOI 10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and [DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)).
-#' 
-#' After installing this package, R knows [**`r format_included_data_number(AMR::microorganisms)`**](https://msberends.github.io/AMR/reference/microorganisms.html) (updated December 2022) and all [**~600 antibiotic, antimycotic and antiviral drugs**](https://msberends.github.io/AMR/reference/antibiotics.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl).
-#' 
-#' The `AMR` package is available in English, Chinese, Danish, Dutch, French, German, Greek, Italian, Japanese, Polish, Portuguese, Russian, Spanish, Swedish, Turkish and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
+#'
+#' This work was published in the Journal of Statistical Software (Volume 104(3); \doi{jss.v104.i03}) and formed the basis of two PhD theses (\doi{10.33612/diss.177417131} and \doi{10.33612/diss.192486375}).
+#'
+#' After installing this package, R knows [**`r format_included_data_number(AMR::microorganisms)` microorganisms**](https://msberends.github.io/AMR/reference/microorganisms.html) (updated `r format(TAXONOMY_VERSION$GBIF$accessed_date, "%B %Y")`) and all [**`r format_included_data_number(nrow(AMR::antibiotics) + nrow(AMR::antivirals))` antibiotic, antimycotic and antiviral drugs**](https://msberends.github.io/AMR/reference/antibiotics.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl).
+#'
+#' The `AMR` package is available in `r vector_and(vapply(FUN.VALUE = character(1), LANGUAGES_SUPPORTED_NAMES, function(x) x$exonym), quotes = FALSE, sort = FALSE)`. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
 #' @section Reference Data Publicly Available:
 #' All data sets in this `AMR` package (about microorganisms, antibiotics, SIR interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
 #' @source
@@ -94,7 +94,9 @@ TAXONOMY_VERSION <- list(
 )

 globalVariables(c(
+  ".mo",
  ".rowid",
+  ".syndromic_group",
  "ab",
  "ab_txt",
  "affect_ab_name",
@@ -105,8 +107,9 @@ globalVariables(c(
  "atc_group1",
  "atc_group2",
  "base_ab",
-  "ci_min",
  "ci_max",
+  "ci_min",
+  "clinical_breakpoints",
  "code",
  "cols",
  "count",
@@ -130,31 +133,34 @@ globalVariables(c(
  "language",
  "lookup",
  "method",
-  "mic",
  "mic ",
+  "mic",
  "microorganism",
  "microorganisms",
  "microorganisms.codes",
  "mo",
  "name",
  "new",
+  "numerator",
  "observations",
  "old",
  "old_name",
  "pattern",
  "R",
  "rank_index",
+  "ref_tbl",
  "reference.rule",
  "reference.rule_group",
  "reference.version",
  "rowid",
-  "sir",
-  "clinical_breakpoints",
  "rule_group",
  "rule_name",
  "se_max",
  "se_min",
+  "SI",
+  "sir",
  "species",
+  "syndromic_group",
  "total",
  "txt",
  "type",
@@ -49,12 +49,13 @@ pm_left_join <- function(x, y, by = NULL, suffix = c(".x", ".y")) {

  merged <- cbind(
    x,
-    y[match(
-      x[, by[1], drop = TRUE],
-      y[, by[2], drop = TRUE]
-    ),
-    colnames(y)[!colnames(y) %in% colnames(x) & !colnames(y) == by[2]],
-    drop = FALSE
+    y[
+      match(
+        x[, by[1], drop = TRUE],
+        y[, by[2], drop = TRUE]
+      ),
+      colnames(y)[!colnames(y) %in% colnames(x) & !colnames(y) == by[2]],
+      drop = FALSE
    ]
  )

@@ -62,27 +63,34 @@ pm_left_join <- function(x, y, by = NULL, suffix = c(".x", ".y")) {
  merged
 }

-# support where() like tidyverse:
-# adapted from https://github.com/nathaneastwood/poorman/blob/52eb6947e0b4430cd588976ed8820013eddf955f/R/where.R#L17-L32
+# support where() like tidyverse (this function will also be used when running `antibiogram()`):
 where <- function(fn) {
+  # based on https://github.com/nathaneastwood/poorman/blob/52eb6947e0b4430cd588976ed8820013eddf955f/R/where.R#L17-L32
  if (!is.function(fn)) {
-    stop(pm_deparse_var(fn), " is not a valid predicate function.")
+    stop_("`", deparse(substitute(fn)), "()` is not a valid predicate function.")
+  }
+  df <- pm_select_env$.data
+  cols <- pm_select_env$get_colnames()
+  if (is.null(df)) {
+    df <- get_current_data("where", call = FALSE)
+    cols <- colnames(df)
  }
  preds <- unlist(lapply(
-    pm_select_env$.data,
+    df,
    function(x, fn) {
      do.call("fn", list(x))
    },
    fn
  ))
-  if (!is.logical(preds)) stop("`where()` must be used with functions that return `TRUE` or `FALSE`.")
-  data_cols <- pm_select_env$get_colnames()
+  if (!is.logical(preds)) stop_("`where()` must be used with functions that return `TRUE` or `FALSE`.")
+  data_cols <- cols
  cols <- data_cols[preds]
  which(data_cols %in% cols)
 }

-# copied and slightly rewritten from poorman under same license (2021-10-15)
-quick_case_when <- function(...) {
+# copied and slightly rewritten from {poorman} under permissive license (2021-10-15)
+# https://github.com/nathaneastwood/poorman, MIT licensed, Nathan Eastwood, 2020
+case_when_AMR <- function(...) {
  fs <- list(...)
  lapply(fs, function(x) {
    if (!inherits(x, "formula")) {
@@ -155,6 +163,22 @@ quick_case_when <- function(...) {
  out
 }

+rbind_AMR <- function(...) {
+  # this is just rbind(), but with the functionality of dplyr::bind_rows(),
+  # to allow differences in available columns
+  l <- list(...)
+  l_names <- unique(unlist(lapply(l, names)))
+  l_new <- lapply(l, function(df) {
+    rownames(df) <- NULL
+    for (col in l_names[!l_names %in% colnames(df)]) {
+      # create the new column, could also be length 0
+      df[, col] <- rep(NA, NROW(df))
+    }
+    df
+  })
+  do.call(rbind, l_new)
+}
+
 # No export, no Rd
 addin_insert_in <- function() {
  import_fn("insertText", "rstudioapi")(" %in% ")
@@ -190,12 +214,13 @@ addin_insert_like <- function() {
    )
  }
  replace_pos <- function(old, with) {
-    modifyRange(document_range(
-      document_position(current_row, current_col - nchar(old)),
-      document_position(current_row, current_col)
-    ),
-    text = with,
-    id = context$id
+    modifyRange(
+      document_range(
+        document_position(current_row, current_col - nchar(old)),
+        document_position(current_row, current_col)
+      ),
+      text = with,
+      id = context$id
    )
  }

@@ -226,7 +251,7 @@ search_type_in_df <- function(x, type, info = TRUE) {
  # -- mo
  if (type == "mo") {
    add_MO_lookup_to_AMR_env()
-    
+
    if (any(vapply(FUN.VALUE = logical(1), x, is.mo))) {
      # take first 'mo' column
      found <- colnames(x)[vapply(FUN.VALUE = logical(1), x, is.mo)]
@@ -253,11 +278,12 @@ search_type_in_df <- function(x, type, info = TRUE) {
      # WHONET support
      found <- sort(colnames(x)[colnames_formatted %like_case% "^(specimen date|specimen_date|spec_date)"])
      if (!inherits(pm_pull(x, found), c("Date", "POSIXct"))) {
-        stop(font_red(paste0(
-          "Found column '", font_bold(found), "' to be used as input for `col_", type,
-          "`, but this column contains no valid dates. Transform its values to valid dates first."
-        )),
-        call. = FALSE
+        stop(
+          font_red(paste0(
+            "Found column '", font_bold(found), "' to be used as input for `col_", type,
+            "`, but this column contains no valid dates. Transform its values to valid dates first."
+          )),
+          call. = FALSE
        )
      }
    } else if (any(vapply(FUN.VALUE = logical(1), x, function(x) inherits(x, c("Date", "POSIXct"))))) {
@@ -319,21 +345,23 @@ search_type_in_df <- function(x, type, info = TRUE) {
 }

 is_valid_regex <- function(x) {
-  regex_at_all <- tryCatch(vapply(
-    FUN.VALUE = logical(1),
-    X = strsplit(x, "", fixed = TRUE),
-    FUN = function(y) {
-      any(y %in% c(
-        "$", "(", ")", "*", "+", "-",
-        ".", "?", "[", "]", "^", "{",
-        "|", "}", "\\"
-      ),
-      na.rm = TRUE
-      )
-    },
-    USE.NAMES = FALSE
-  ),
-  error = function(e) rep(TRUE, length(x))
+  regex_at_all <- tryCatch(
+    vapply(
+      FUN.VALUE = logical(1),
+      X = strsplit(x, "", fixed = TRUE),
+      FUN = function(y) {
+        any(
+          y %in% c(
+            "$", "(", ")", "*", "+", "-",
+            ".", "?", "[", "]", "^", "{",
+            "|", "}", "\\"
+          ),
+          na.rm = TRUE
+        )
+      },
+      USE.NAMES = FALSE
+    ),
+    error = function(e) rep(TRUE, length(x))
  )
  regex_valid <- vapply(
    FUN.VALUE = logical(1),
@@ -360,7 +388,7 @@ stop_ifnot_installed <- function(package) {
  }
 }

-pkg_is_available <- function(pkg, also_load = TRUE, min_version = NULL) {
+pkg_is_available <- function(pkg, also_load = FALSE, min_version = NULL) {
  if (also_load == TRUE) {
    out <- suppressWarnings(require(pkg, character.only = TRUE, warn.conflicts = FALSE))
  } else {
@@ -381,7 +409,7 @@ import_fn <- function(name, pkg, error_on_fail = TRUE) {
    getExportedValue(name = name, ns = asNamespace(pkg)),
    error = function(e) {
      if (isTRUE(error_on_fail)) {
-        stop_("function ", name, "() is not an exported object from package '", pkg,
+        stop_("function `", name, "()` is not an exported object from package '", pkg,
          "'. Please create an issue at ", font_url("https://github.com/msberends/AMR/issues"), ". Many thanks!",
          call = FALSE
        )
@@ -410,16 +438,17 @@ word_wrap <- function(...,

  if (msg %like% "\n") {
    # run word_wraps() over every line here, bind them and return again
-    return(paste0(vapply(
-      FUN.VALUE = character(1),
-      trimws(unlist(strsplit(msg, "\n", fixed = TRUE)), which = "right"),
-      word_wrap,
-      add_fn = add_fn,
-      as_note = FALSE,
-      width = width,
-      extra_indent = extra_indent
-    ),
-    collapse = "\n"
+    return(paste0(
+      vapply(
+        FUN.VALUE = character(1),
+        trimws(unlist(strsplit(msg, "\n", fixed = TRUE)), which = "right"),
+        word_wrap,
+        add_fn = add_fn,
+        as_note = FALSE,
+        width = width,
+        extra_indent = extra_indent
+      ),
+      collapse = "\n"
    ))
  }

@@ -429,11 +458,12 @@ word_wrap <- function(...,
  # we need to correct for already applied style, that adds text like "\033[31m\"
  msg_stripped <- font_stripstyle(msg)
  # where are the spaces now?
-  msg_stripped_wrapped <- paste0(strwrap(msg_stripped,
-    simplify = TRUE,
-    width = width
-  ),
-  collapse = "\n"
+  msg_stripped_wrapped <- paste0(
+    strwrap(msg_stripped,
+      simplify = TRUE,
+      width = width
+    ),
+    collapse = "\n"
  )
  msg_stripped_wrapped <- paste0(unlist(strsplit(msg_stripped_wrapped, "(\n|\\*\\|\\*)")),
    collapse = "\n"
@@ -487,11 +517,12 @@ message_ <- function(...,
                     appendLF = TRUE,
                     add_fn = list(font_blue),
                     as_note = TRUE) {
-  message(word_wrap(...,
-    add_fn = add_fn,
-    as_note = as_note
-  ),
-  appendLF = appendLF
+  message(
+    word_wrap(...,
+      add_fn = add_fn,
+      as_note = as_note
+    ),
+    appendLF = appendLF
  )
 }

@@ -499,12 +530,13 @@ warning_ <- function(...,
                     add_fn = list(),
                     immediate = FALSE,
                     call = FALSE) {
-  warning(word_wrap(...,
-    add_fn = add_fn,
-    as_note = FALSE
-  ),
-  immediate. = immediate,
-  call. = call
+  warning(
+    trimws2(word_wrap(...,
+      add_fn = add_fn,
+      as_note = FALSE
+    )),
+    immediate. = immediate,
+    call. = call
  )
 }

@@ -522,7 +554,7 @@ stop_ <- function(..., call = TRUE) {
    }
    msg <- paste0("in ", call, "(): ", msg)
  }
-  msg <- word_wrap(msg, add_fn = list(), as_note = FALSE)
+  msg <- trimws2(word_wrap(msg, add_fn = list(), as_note = FALSE))
  stop(msg, call. = FALSE)
 }

@@ -601,7 +633,9 @@ documentation_date <- function(d) {
 }

 format_included_data_number <- function(data) {
-  if (is.data.frame(data)) {
+  if (is.numeric(data) && length(data) == 1) {
+    n <- data
+  } else if (is.data.frame(data)) {
    n <- nrow(data)
  } else {
    n <- length(unique(data))
@@ -613,7 +647,7 @@ format_included_data_number <- function(data) {
  } else {
    rounder <- -1 # round on tens
  }
-  paste0("~", format(round(n, rounder), decimal.mark = ".", big.mark = ","))
+  paste0("~", format(round(n, rounder), decimal.mark = ".", big.mark = " "))
 }

 # for eucast_rules() and mdro(), creates markdown output with URLs and names
@@ -671,6 +705,10 @@ vector_or <- function(v, quotes = TRUE, reverse = FALSE, sort = TRUE, initial_ca
    # class 'sir' should be sorted like this
    v <- c("S", "I", "R")
  }
+  # oxford comma
+  if (last_sep %in% c(" or ", " and ") && length(v) > 2) {
+    last_sep <- paste0(",", last_sep)
+  }
  # all commas except for last item, so will become '"val1", "val2", "val3" or "val4"'
  paste0(
    paste0(quotes, v[seq_len(length(v) - 1)], quotes, collapse = ", "),
@@ -713,15 +751,15 @@ format_class <- function(class, plural = FALSE) {
    class <- "input created with `custom_eucast_rules()`"
  }
  if (any(c("mo", "ab", "sir") %in% class)) {
-    class <- paste0("of class <", class[1L], ">")
+    class <- paste0("of class '", class[1L], "'")
  }
-  class[class == class.bak] <- paste0("of class <", class[class == class.bak], ">")
+  class[class == class.bak] <- paste0("of class '", class[class == class.bak], "'")
  # output
  vector_or(class, quotes = FALSE, sort = FALSE)
 }

 # a check for every single argument in all functions
-meet_criteria <- function(object,
+meet_criteria <- function(object, # can be literally `list(...)` for `allow_arguments_from`
                          allow_class = NULL,
                          has_length = NULL,
                          looks_like = NULL,
@@ -733,6 +771,7 @@ meet_criteria <- function(object,
                          allow_NULL = FALSE,
                          allow_NA = FALSE,
                          ignore.case = FALSE,
+                          allow_arguments_from = NULL, # 1 function, or a list of functions
                          .call_depth = 0) { # depth in calling

  obj_name <- deparse(substitute(object))
@@ -836,17 +875,36 @@ meet_criteria <- function(object,
    )
  }
  if (!is.null(contains_column_class)) {
-    stop_ifnot(any(vapply(
-      FUN.VALUE = logical(1),
-      object,
-      function(col, columns_class = contains_column_class) {
-        inherits(col, columns_class)
-      }
-    ), na.rm = TRUE),
-    "the data provided in argument `", obj_name,
-    "` must contain at least one column of class <", contains_column_class, ">. ",
-    "See ?as.", contains_column_class, ".",
-    call = call_depth
+    stop_ifnot(
+      any(vapply(
+        FUN.VALUE = logical(1),
+        object,
+        function(col, columns_class = contains_column_class) {
+          inherits(col, columns_class)
+        }
+      ), na.rm = TRUE),
+      "the data provided in argument `", obj_name,
+      "` must contain at least one column of class '", contains_column_class[1L], "'. ",
+      "See `?as.", contains_column_class[1L], "`.",
+      call = call_depth
+    )
+  }
+  if (!is.null(allow_arguments_from) && !is.null(names(object))) {
+    args_given <- names(object)
+    if (is.function(allow_arguments_from)) {
+      allow_arguments_from <- list(allow_arguments_from)
+    }
+    args_allowed <- sort(unique(unlist(lapply(allow_arguments_from, function(x) names(formals(x))))))
+    args_allowed <- args_allowed[args_allowed != "..."]
+    disallowed <- args_given[!args_given %in% args_allowed]
+    stop_if(length(disallowed) > 0,
+      ifelse(length(disallowed) == 1,
+        paste("the argument", vector_and(disallowed), "is"),
+        paste("the arguments", vector_and(disallowed), "are")
+      ),
+      " not valid. Valid arguments are: ",
+      vector_and(args_allowed), ".",
+      call = call_depth
    )
  }
  return(invisible())
@@ -856,35 +914,48 @@ get_current_data <- function(arg_name, call) {
  valid_df <- function(x) {
    !is.null(x) && is.data.frame(x)
  }
-  # try dplyr::cur_data_all() first to support dplyr groups
-  # only useful for e.g. dplyr::filter(), dplyr::mutate() and dplyr::summarise()
-  # not useful (throws error) with e.g. dplyr::select(), dplyr::across(), or dplyr::vars(),
-  # but that will be caught later on in this function
-  cur_data_all <- import_fn("cur_data_all", "dplyr", error_on_fail = FALSE)
-  if (!is.null(cur_data_all)) {
-    out <- tryCatch(cur_data_all(), error = function(e) NULL)
-    if (valid_df(out)) {
-      return(out)
+
+  frms <- sys.frames()
+
+  # check dplyr environments to support dplyr groups
+  with_mask <- vapply(FUN.VALUE = logical(1), frms, function(e) !is.null(e$mask))
+  for (env in frms[which(with_mask)]) {
+    if (is.function(env$mask$current_rows) && (valid_df(env$data) || valid_df(env$`.data`))) {
+      # an element `.data` or `data` (containing all data) and `mask` (containing functions) will be in the environment when using dplyr verbs
+      # we use their mask$current_rows() to get the group rows, since dplyr::cur_data_all() is deprecated and will be removed in the future
+      # e.g. for `example_isolates %>% group_by(ward) %>% mutate(first = first_isolate(.))`
+      if (valid_df(env$data)) {
+        # support for dplyr 1.1.x
+        df <- env$data
+      } else {
+        # support for dplyr 1.0.x
+        df <- env$`.data`
+      }
+      rows <- tryCatch(env$mask$current_rows(), error = function(e) seq_len(NROW(df)))
+      return(df[rows, , drop = FALSE])
    }
  }

-  # try a manual (base R) method, by going over all underlying environments with sys.frames()
-  for (env in sys.frames()) {
-    if (!is.null(env$`.Generic`)) {
-      # don't check `".Generic" %in% names(env)`, because in R < 3.2, `names(env)` is always NULL
+  # now go over all underlying environments looking for other dplyr, data.table and base R selection environments
+  with_generic <- vapply(FUN.VALUE = logical(1), frms, function(e) !is.null(e$`.Generic`))
+  for (env in frms[which(with_generic)]) {
+    if (valid_df(env$`.data`)) {
+      # an element `.data` will be in the environment when using dplyr::select()
+      return(env$`.data`)
+    } else if (valid_df(env$xx)) {
+      # an element `xx` will be in the environment for rows + cols in base R, e.g. `example_isolates[c(1:3), carbapenems()]`
+      return(env$xx)
+    } else if (valid_df(env$x)) {
+      # an element `x` will be in the environment for only cols in base R, e.g. `example_isolates[, carbapenems()]`
+      # this element will also be present in data.table environments where there's a .Generic available
+      return(env$x)
+    }
+  }

-      if (valid_df(env$`.data`)) {
-        # an element `.data` will be in the environment when using `dplyr::select()`
-        # (but not when using `dplyr::filter()`, `dplyr::mutate()` or `dplyr::summarise()`)
-        return(env$`.data`)
-      } else if (valid_df(env$xx)) {
-        # an element `xx` will be in the environment for rows + cols, e.g. `example_isolates[c(1:3), carbapenems()]`
-        return(env$xx)
-      } else if (valid_df(env$x)) {
-        # an element `x` will be in the environment for only cols, e.g. `example_isolates[, carbapenems()]`
-        return(env$x)
-      }
-    } else if (!is.null(names(env)) && all(c(".tbl", ".vars", ".cols") %in% names(env), na.rm = TRUE) && valid_df(env$`.tbl`)) {
+  # now a special case for dplyr's 'scoped' variants
+  with_tbl <- vapply(FUN.VALUE = logical(1), frms, function(e) valid_df(e$`.tbl`))
+  for (env in frms[which(with_tbl)]) {
+    if (!is.null(names(env)) && all(c(".tbl", ".vars", ".cols") %in% names(env), na.rm = TRUE)) {
      # an element `.tbl` will be in the environment when using scoped dplyr variants, with or without `dplyr::vars()`
      # (e.g. `dplyr::summarise_at()` or `dplyr::mutate_at()`)
      return(env$`.tbl`)
@@ -918,11 +989,9 @@ get_current_data <- function(arg_name, call) {
 get_current_column <- function() {
  # try dplyr::cur_columns() first
  cur_column <- import_fn("cur_column", "dplyr", error_on_fail = FALSE)
-  if (!is.null(cur_column)) {
-    out <- tryCatch(cur_column(), error = function(e) NULL)
-    if (!is.null(out)) {
-      return(out)
-    }
+  out <- tryCatch(cur_column(), error = function(e) NULL)
+  if (!is.null(out)) {
+    return(out)
  }

  # cur_column() doesn't always work (only allowed for certain conditions set by dplyr), but it's probably still possible:
@@ -955,8 +1024,20 @@ get_current_column <- function() {
 }

 is_null_or_grouped_tbl <- function(x) {
-  # class "grouped_df" might change at one point, so only set in one place; here.
-  is.null(x) || inherits(x, "grouped_df")
+  # class "grouped_data" is from {poorman}, see aa_helper_pm_functions.R
+  # class "grouped_df" is from {dplyr} and might change at one point, so only set in one place; here.
+  is.null(x) || inherits(x, "grouped_data") || inherits(x, "grouped_df")
+}
+
+get_group_names <- function(x) {
+  if ("pm_groups" %in% names(attributes(x))) {
+    pm_get_groups(x)
+  } else if (!is.null(x) && is_null_or_grouped_tbl(x)) {
+    grps <- colnames(attributes(x)$groups)
+    grps[!grps %in% c(".group_id", ".rows")]
+  } else {
+    character(0)
+  }
 }

 unique_call_id <- function(entire_session = FALSE, match_fn = NULL) {
@@ -1084,7 +1165,7 @@ try_colour <- function(..., before, after, collapse = " ") {
 }
 is_dark <- function() {
  if (is.null(AMR_env$is_dark_theme)) {
-    AMR_env$is_dark_theme <- tryCatch(isTRUE(getExportedValue("getThemeInfo", ns = asNamespace("rstudioapi"))()$dark), error = function(e) FALSE)
+    AMR_env$is_dark_theme <- !has_colour() || tryCatch(isTRUE(getExportedValue("getThemeInfo", ns = asNamespace("rstudioapi"))()$dark), error = function(e) FALSE)
  }
  isTRUE(AMR_env$is_dark_theme)
 }
@@ -1262,20 +1343,24 @@ create_pillar_column <- function(x, ...) {
  new_pillar_shaft_simple(x, ...)
 }

-as_original_data_class <- function(df, old_class = NULL) {
-  if ("tbl_df" %in% old_class && pkg_is_available("tibble", also_load = FALSE)) {
+as_original_data_class <- function(df, old_class = NULL, extra_class = NULL) {
+  if ("tbl_df" %in% old_class && pkg_is_available("tibble")) {
    # this will then also remove groups
    fn <- import_fn("as_tibble", "tibble")
-  } else if ("tbl_ts" %in% old_class && pkg_is_available("tsibble", also_load = FALSE)) {
+  } else if ("tbl_ts" %in% old_class && pkg_is_available("tsibble")) {
    fn <- import_fn("as_tsibble", "tsibble")
-  } else if ("data.table" %in% old_class && pkg_is_available("data.table", also_load = FALSE)) {
+  } else if ("data.table" %in% old_class && pkg_is_available("data.table")) {
    fn <- import_fn("as.data.table", "data.table")
-  } else if ("tabyl" %in% old_class && pkg_is_available("janitor", also_load = FALSE)) {
+  } else if ("tabyl" %in% old_class && pkg_is_available("janitor")) {
    fn <- import_fn("as_tabyl", "janitor")
  } else {
    fn <- function(x) base::as.data.frame(df, stringsAsFactors = FALSE)
  }
-  fn(df)
+  out <- fn(df)
+  if (!is.null(extra_class)) {
+    class(out) <- c(extra_class, class(out))
+  }
+  out
 }

 # works exactly like round(), but rounds `round2(44.55, 1)` to 44.6 instead of 44.5
@@ -1314,7 +1399,6 @@ round2 <- function(x, digits = 1, force_zero = TRUE) {

 # percentage from our other package: 'cleaner'
 percentage <- function(x, digits = NULL, ...) {
-
  # getdecimalplaces() function
  getdecimalplaces <- function(x, minimum = 0, maximum = 3) {
    if (maximum < minimum) {
@@ -1330,12 +1414,13 @@ percentage <- function(x, digits = NULL, ...) {
      ), ".", fixed = TRUE),
      function(y) ifelse(length(y) == 2, nchar(y[2]), 0)
    )), na.rm = TRUE)
-    max(min(max_places,
-      maximum,
+    max(
+      min(max_places,
+        maximum,
+        na.rm = TRUE
+      ),
+      minimum,
      na.rm = TRUE
-    ),
-    minimum,
-    na.rm = TRUE
    )
  }

@@ -1366,11 +1451,12 @@ percentage <- function(x, digits = NULL, ...) {
    # max one digit if undefined
    digits <- getdecimalplaces(x, minimum = 0, maximum = 1)
  }
-  format_percentage(structure(
-    .Data = as.double(x),
-    class = c("percentage", "numeric")
-  ),
-  digits = digits, ...
+  format_percentage(
+    structure(
+      .Data = as.double(x),
+      class = c("percentage", "numeric")
+    ),
+    digits = digits, ...
  )
 }

@@ -1385,7 +1471,7 @@ add_MO_lookup_to_AMR_env <- function() {
  # for all MO functions, saves a lot of time on package load and in package size
  if (is.null(AMR_env$MO_lookup)) {
    MO_lookup <- AMR::microorganisms
-    
+
    MO_lookup$kingdom_index <- NA_real_
    MO_lookup[which(MO_lookup$kingdom == "Bacteria" | MO_lookup$mo == "UNKNOWN"), "kingdom_index"] <- 1
    MO_lookup[which(MO_lookup$kingdom == "Fungi"), "kingdom_index"] <- 2
@@ -1393,7 +1479,7 @@ add_MO_lookup_to_AMR_env <- function() {
    MO_lookup[which(MO_lookup$kingdom == "Archaea"), "kingdom_index"] <- 4
    # all the rest
    MO_lookup[which(is.na(MO_lookup$kingdom_index)), "kingdom_index"] <- 5
-    
+
    # the fullname lowercase, important for the internal algorithms in as.mo()
    MO_lookup$fullname_lower <- tolower(trimws(paste(
      MO_lookup$genus,
@@ -1405,7 +1491,7 @@ add_MO_lookup_to_AMR_env <- function() {
    MO_lookup$fullname_lower <- trimws(gsub("[^.a-z0-9/ \\-]+", "", MO_lookup$fullname_lower, perl = TRUE))
    # special for Salmonella - they have cities as subspecies but not the species (enterica) in the fullname:
    MO_lookup$fullname_lower[which(MO_lookup$subspecies %like_case% "^[A-Z]")] <- gsub(" enterica ", " ", MO_lookup$fullname_lower[which(MO_lookup$subspecies %like_case% "^[A-Z]")], fixed = TRUE)
-    
+
    MO_lookup$full_first <- substr(MO_lookup$fullname_lower, 1, 1)
    MO_lookup$species_first <- tolower(substr(MO_lookup$species, 1, 1)) # tolower for groups (Streptococcus, Salmonella)
    MO_lookup$subspecies_first <- tolower(substr(MO_lookup$subspecies, 1, 1)) # tolower for Salmonella serovars
@@ -1414,11 +1500,11 @@ add_MO_lookup_to_AMR_env <- function() {
 }

 trimws2 <- function(..., whitespace = "[\u0009\u000A\u000B\u000C\u000D\u0020\u0085\u00A0\u1680\u180E\u2000\u2001\u2002\u2003\u2004\u2005\u2006\u2007\u2008\u2009\u200A\u200B\u200C\u200D\u2028\u2029\u202F\u205F\u2060\u3000\uFEFF]") {
-  # this is even faster than trimws() itself which sets " \t\n\r".
+  # this is even faster than trimws() itself which sets "[ \t\r\n]".
  trimws(..., whitespace = whitespace)
 }

-readRDS2 <- function(file, refhook = NULL) {
+readRDS_AMR <- function(file, refhook = NULL) {
  # this is readRDS with remote file support
  con <- file(file)
  on.exit(close(con))
@@ -1430,7 +1516,7 @@ readRDS2 <- function(file, refhook = NULL) {
 match <- function(x, table, ...) {
  chmatch <- import_fn("chmatch", "data.table", error_on_fail = FALSE)
  if (!is.null(chmatch) && is.character(x) && is.character(table)) {
-    # data.table::chmatch() is 35% faster than base::match() for character
+    # data.table::chmatch() is much faster than base::match() for character
    chmatch(x, table, ...)
  } else {
    base::match(x, table, ...)
@@ -1439,7 +1525,7 @@ match <- function(x, table, ...) {
 `%in%` <- function(x, table) {
  chin <- import_fn("%chin%", "data.table", error_on_fail = FALSE)
  if (!is.null(chin) && is.character(x) && is.character(table)) {
-    # data.table::`%chin%`() is 20-50% faster than base::`%in%`() for character
+    # data.table::`%chin%`() is much faster than base::`%in%`() for character
    chin(x, table)
  } else {
    base::`%in%`(x, table)
@@ -988,7 +988,7 @@ pm_summarise.default <- function(.data, ...) {
      if (is.list(x_res)) I(x_res) else x_res
    }
  )
-  res <- as.data.frame(res)
+  res <- as.data.frame(res, stringsAsFactors = FALSE)
  fn_names <- names(fns)
  colnames(res) <- if (is.null(fn_names)) fns else fn_names
  if (pm_groups_exist) res <- cbind(group, res, row.names = NULL)
@@ -0,0 +1,79 @@
+# ==================================================================== #
+# TITLE                                                                #
+# AMR: An R Package for Working with Antimicrobial Resistance Data     #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# CITE AS                                                              #
+# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C    #
+# (2022). AMR: An R Package for Working with Antimicrobial Resistance  #
+# Data. Journal of Statistical Software, 104(3), 1-31.                 #
+# doi:10.18637/jss.v104.i03                                            #
+#                                                                      #
+# Developed at the University of Groningen and the University Medical  #
+# Center Groningen in The Netherlands, in collaboration with many      #
+# colleagues from around the world, see our website.                   #
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+#' Options for the AMR package
+#'
+#' This is an overview of all the package-specific [options()] you can set in the `AMR` package.
+#' @section Options:
+#' * `AMR_custom_ab` \cr Allows to use custom antimicrobial drugs with this package. This is explained in [add_custom_antimicrobials()].
+#' * `AMR_custom_mo` \cr Allows to use custom microorganisms with this package. This is explained in [add_custom_microorganisms()].
+#' * `AMR_eucastrules` \cr Used for setting the default types of rules for [eucast_rules()] function, must be one or more of: `"breakpoints"`, `"expert"`, `"other"`, `"custom"`, `"all"`, and defaults to `c("breakpoints", "expert")`.
+#' * `AMR_guideline` \cr Used for setting the default guideline for interpreting MIC values and disk diffusion diameters with [as.sir()]. Can be only the guideline name (e.g., `"CLSI"`) or the name with a year (e.g. `"CLSI 2019"`). The default to the latest implemented EUCAST guideline, currently \code{"`r clinical_breakpoints$guideline[1]`"}. Supported guideline are currently EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`).
+#' * `AMR_ignore_pattern` \cr A [regular expression][base::regex] to ignore (i.e., make `NA`) any match given in [as.mo()] and all [`mo_*`][mo_property()] functions.
+#' * `AMR_include_PKPD` \cr A [logical] to use in [as.sir()], to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is `TRUE`.
+#' * `AMR_include_screening` \cr A [logical] to use in [as.sir()], to indicate that clinical breakpoints for screening are allowed - the default is `FALSE`.
+#' * `AMR_keep_synonyms` \cr A [logical] to use in [as.mo()] and all [`mo_*`][mo_property()] functions, to indicate if old, previously valid taxonomic names must be preserved and not be corrected to currently accepted names. The default is `FALSE`.
+#' * `AMR_cleaning_regex` \cr A [regular expression][base::regex] (case-insensitive) to use in [as.mo()] and all [`mo_*`][mo_property()] functions, to clean the user input. The default is the outcome of [mo_cleaning_regex()], which removes texts between brackets and texts such as "species" and "serovar".
+#' * `AMR_locale` \cr A language to use for the `AMR` package, can be one of these supported language names or ISO-639-1 codes: `r vector_or(paste0(sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), " (" , LANGUAGES_SUPPORTED, ")"), quotes = FALSE, sort = FALSE)`. The default is the current system language (if supported).
+#' * `AMR_mo_source` \cr A file location for a manual code list to be used in [as.mo()] and all [`mo_*`][mo_property()] functions. This is explained in [set_mo_source()].
+#'
+#' @section Saving Settings Between Sessions:
+#' Settings in \R are not saved globally and are thus lost when \R is exited. You can save your options to your own `.Rprofile` file, which is a user-specific file. You can edit it using:
+#'
+#' ```r
+#'   utils::file.edit("~/.Rprofile")
+#' ```
+#'
+#' In this file, you can set options such as:
+#'
+#' ```r
+#'  options(AMR_locale = "pt")
+#'  options(AMR_include_PKPD = TRUE)
+#'  ```
+#'
+#' to add Portuguese language support of antibiotics, and allow PK/PD rules when interpreting MIC values with [as.sir()].
+#'
+#' ### Share Options Within Team
+#'
+#' For a more global approach, e.g. within a data team, save an options file to a remote file location, such as a shared network drive. This would work in this way:
+#'
+#' 1. Save a plain text file to e.g. "X:/team_folder/R_options.R" and fill it with preferred settings.
+#'
+#' 2. For each user, open the `.Rprofile` file using `utils::file.edit("~/.Rprofile")` and put in there:
+#'
+#'    ```r
+#'      source("X:/team_folder/R_options.R")
+#'    ```
+#'
+#' 3. Reload R/RStudio and check the settings with [getOption()], e.g. `getOption("AMR_locale")` if you have set that value.
+#'
+#' Now the team settings are configured in only one place, and can be maintained there.
+#' @keywords internal
+#' @name AMR-options
+NULL
@@ -32,7 +32,7 @@
 #' Use this function to determine the antibiotic drug code of one or more antibiotics. The data set [antibiotics] will be searched for abbreviations, official names and synonyms (brand names).
 #' @param x a [character] vector to determine to antibiotic ID
 #' @param flag_multiple_results a [logical] to indicate whether a note should be printed to the console that probably more than one antibiotic drug code or name can be retrieved from a single input value.
-#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
+#' @param info a [logical] to indicate whether a progress bar should be printed - the default is `TRUE` only in interactive mode
 #' @param ... arguments passed on to internal functions
 #' @rdname as.ab
 #' @inheritSection WHOCC WHOCC
@@ -87,7 +87,6 @@
 #'
 #' \donttest{
 #' if (require("dplyr")) {
-#'
 #'   # you can quickly rename 'sir' columns using set_ab_names() with dplyr:
 #'   example_isolates %>%
 #'     set_ab_names(where(is.sir), property = "atc")
@@ -134,11 +133,11 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
  note_if_more_than_one_found <- function(found, index, from_text) {
    if (isTRUE(initial_search) && isTRUE(length(from_text) > 1)) {
      abnames <- ab_name(from_text, tolower = TRUE, initial_search = FALSE)
-      if (ab_name(found[1L], language = NULL) %like% "(clavulanic acid|avibactam)") {
-        abnames <- abnames[!abnames %in% c("clavulanic acid", "avibactam")]
+      if (ab_name(found[1L], language = NULL) %like% "(clavulanic acid|(avi|tazo|mono|vabor)bactam)") {
+        abnames <- abnames[!abnames %in% c("clavulanic acid", "avibactam", "tazobactam", "vaborbactam", "monobactam")]
      }
      if (length(abnames) > 1) {
-        warning_(
+        message_(
          "More than one result was found for item ", index, ": ",
          vector_and(abnames, quotes = FALSE)
        )
@@ -338,22 +337,23 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
      }

      # transform back from other languages and try again
-      x_translated <- paste(lapply(
-        strsplit(x[i], "[^A-Z0-9]"),
-        function(y) {
-          for (i in seq_len(length(y))) {
-            for (lang in LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]) {
-              y[i] <- ifelse(tolower(y[i]) %in% tolower(TRANSLATIONS[, lang, drop = TRUE]),
-                TRANSLATIONS[which(tolower(TRANSLATIONS[, lang, drop = TRUE]) == tolower(y[i]) &
-                  !isFALSE(TRANSLATIONS$fixed)), "pattern"],
-                y[i]
-              )
+      x_translated <- paste(
+        lapply(
+          strsplit(x[i], "[^A-Z0-9]"),
+          function(y) {
+            for (i in seq_len(length(y))) {
+              for (lang in LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]) {
+                y[i] <- ifelse(tolower(y[i]) %in% tolower(TRANSLATIONS[, lang, drop = TRUE]),
+                  TRANSLATIONS[which(tolower(TRANSLATIONS[, lang, drop = TRUE]) == tolower(y[i]) &
+                    !isFALSE(TRANSLATIONS$fixed)), "pattern"],
+                  y[i]
+                )
+              }
            }
+            generalise_antibiotic_name(y)
          }
-          generalise_antibiotic_name(y)
-        }
-      )[[1]],
-      collapse = "/"
+        )[[1]],
+        collapse = "/"
      )
      x_translated_guess <- suppressWarnings(as.ab(x_translated, initial_search = FALSE))
      if (!is.na(x_translated_guess)) {
@@ -362,20 +362,21 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
      }

      # now also try to coerce brandname combinations like "Amoxy/clavulanic acid"
-      x_translated <- paste(lapply(
-        strsplit(x_translated, "[^A-Z0-9 ]"),
-        function(y) {
-          for (i in seq_len(length(y))) {
-            y_name <- suppressWarnings(ab_name(y[i], language = NULL, initial_search = FALSE))
-            y[i] <- ifelse(!is.na(y_name),
-              y_name,
-              y[i]
-            )
+      x_translated <- paste(
+        lapply(
+          strsplit(x_translated, "[^A-Z0-9 ]"),
+          function(y) {
+            for (i in seq_len(length(y))) {
+              y_name <- suppressWarnings(ab_name(y[i], language = NULL, initial_search = FALSE))
+              y[i] <- ifelse(!is.na(y_name),
+                y_name,
+                y[i]
+              )
+            }
+            generalise_antibiotic_name(y)
          }
-          generalise_antibiotic_name(y)
-        }
-      )[[1]],
-      collapse = "/"
+        )[[1]],
+        collapse = "/"
      )
      x_translated_guess <- suppressWarnings(as.ab(x_translated, initial_search = FALSE))
      if (!is.na(x_translated_guess)) {
@@ -494,14 +495,14 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
  # save to package env to save time for next time
  if (isTRUE(initial_search)) {
    AMR_env$ab_previously_coerced <- AMR_env$ab_previously_coerced[which(!AMR_env$ab_previously_coerced$x %in% x), , drop = FALSE]
-    AMR_env$ab_previously_coerced <- unique(rbind(AMR_env$ab_previously_coerced,
+    AMR_env$ab_previously_coerced <- unique(rbind_AMR(
+      AMR_env$ab_previously_coerced,
      data.frame(
        x = x,
        ab = x_new,
        x_bak = x_bak[match(x, x_bak_clean)],
        stringsAsFactors = FALSE
-      ),
-      stringsAsFactors = FALSE
+      )
    ))
  }

@@ -513,8 +514,10 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
    )
  }
  x_unknown <- x_unknown[!x_unknown %in% x_unknown_ATCs]
-  x_unknown <- c(x_unknown,
-                 AMR_env$ab_previously_coerced$x_bak[which(AMR_env$ab_previously_coerced$x %in% x & is.na(AMR_env$ab_previously_coerced$ab))])
+  x_unknown <- c(
+    x_unknown,
+    AMR_env$ab_previously_coerced$x_bak[which(AMR_env$ab_previously_coerced$x %in% x & is.na(AMR_env$ab_previously_coerced$ab))]
+  )
  if (length(x_unknown) > 0 && fast_mode == FALSE) {
    warning_(
      "in `as.ab()`: these values could not be coerced to a valid antimicrobial ID: ",
@@ -660,9 +663,9 @@ get_translate_ab <- function(translate_ab) {
  } else {
    translate_ab <- tolower(translate_ab)
    stop_ifnot(translate_ab %in% colnames(AMR::antibiotics),
-               "invalid value for 'translate_ab', this must be a column name of the antibiotics data set\n",
-               "or TRUE (equals 'name') or FALSE to not translate at all.",
-               call = FALSE
+      "invalid value for 'translate_ab', this must be a column name of the antibiotics data set\n",
+      "or TRUE (equals 'name') or FALSE to not translate at all.",
+      call = FALSE
    )
    translate_ab
  }
@@ -33,9 +33,9 @@
 #' @param text text to analyse
 #' @param type type of property to search for, either `"drug"`, `"dose"` or `"administration"`, see *Examples*
 #' @param collapse a [character] to pass on to `paste(, collapse = ...)` to only return one [character] per element of `text`, see *Examples*
-#' @param translate_ab if `type = "drug"`: a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]. Defaults to `FALSE`. Using `TRUE` is equal to using "name".
+#' @param translate_ab if `type = "drug"`: a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]. The default is `FALSE`. Using `TRUE` is equal to using "name".
 #' @param thorough_search a [logical] to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to `TRUE` will take considerably more time than when using `FALSE`. At default, it will turn `TRUE` when all input elements contain a maximum of three words.
-#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
+#' @param info a [logical] to indicate whether a progress bar should be printed - the default is `TRUE` only in interactive mode
 #' @param ... arguments passed on to [as.ab()]
 #' @details This function is also internally used by [as.ab()], although it then only searches for the first drug name and will throw a note if more drug names could have been returned. Note: the [as.ab()] function may use very long regular expression to match brand names of antimicrobial drugs. This may fail on some systems.
 #'
@@ -33,7 +33,7 @@
 #' @param x any (vector of) text that can be coerced to a valid antibiotic drug code with [as.ab()]
 #' @param tolower a [logical] to indicate whether the first [character] of every output should be transformed to a lower case [character]. This will lead to e.g. "polymyxin B" and not "polymyxin b".
 #' @param property one of the column names of one of the [antibiotics] data set: `vector_or(colnames(antibiotics), sort = FALSE)`.
-#' @param language language of the returned text, defaults to system language (see [get_AMR_locale()]) and can also be set with `getOption("AMR_locale")`. Use `language = NULL` or `language = ""` to prevent translation.
+#' @param language language of the returned text - the default is the current system language (see [get_AMR_locale()]) and can also be set with the [package option][AMR-options] [`AMR_locale`][AMR-options]. Use `language = NULL` or `language = ""` to prevent translation.
 #' @param administration way of administration, either `"oral"` or `"iv"`
 #' @param open browse the URL using [utils::browseURL()]
 #' @param ... in case of [set_ab_names()] and `data` is a [data.frame]: columns to select (supports tidy selection such as `column1:column4`), otherwise other arguments passed on to [as.ab()]
@@ -102,18 +102,15 @@
 #' \donttest{
 #' if (require("dplyr")) {
 #'   example_isolates %>%
-#'     set_ab_names() %>%
-#'     head()
+#'     set_ab_names()
 #'
 #'   # this does the same:
 #'   example_isolates %>%
-#'     rename_with(set_ab_names) %>%
-#'     head()
+#'     rename_with(set_ab_names)
 #'
 #'   # set_ab_names() works with any AB property:
 #'   example_isolates %>%
-#'     set_ab_names(property = "atc") %>%
-#'     head()
+#'     set_ab_names(property = "atc")
 #'
 #'   example_isolates %>%
 #'     set_ab_names(where(is.sir)) %>%
@@ -338,7 +335,7 @@ ab_url <- function(x, open = FALSE, ...) {
 ab_property <- function(x, property = "name", language = get_AMR_locale(), ...) {
  meet_criteria(x, allow_NA = TRUE)
  meet_criteria(property, is_in = colnames(AMR::antibiotics), has_length = 1)
-  meet_criteria(language, is_in = c(LANGUAGES_SUPPORTED, ""), has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
+  language <- validate_language(language)
  translate_into_language(ab_validate(x = x, property = property, ...), language = language)
 }

@@ -362,13 +359,14 @@ set_ab_names <- function(data, ..., property = "name", language = get_AMR_locale
  }

  if (is.data.frame(data)) {
-    if (tryCatch(length(list(...)) > 0, error = function(e) TRUE)) {
-      out <- tryCatch(suppressWarnings(c(...)), error = function(e) NULL)
-      if (!is.null(out)) {
-        df <- data[, out, drop = FALSE]
-      } else {
-        df <- pm_select(data, ...)
-      }
+    if (tryCatch(length(c(...)) > 1, error = function(e) TRUE)) {
+      df <- tryCatch(suppressWarnings(pm_select(data, ...)),
+        error = function(e) {
+          data[, c(...), drop = FALSE]
+        }
+      )
+    } else if (tryCatch(is.character(c(...)), error = function(e) FALSE)) {
+      df <- data[, c(...), drop = FALSE]
    } else {
      df <- data
    }
@@ -29,14 +29,16 @@

 #' Antibiotic Selectors
 #'
-#' These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group, without the need to define the columns or antibiotic abbreviations. In short, if you have a column name that resembles an antimicrobial drug, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "CZO" and "J01DB04" will all be picked up by [cephalosporins()].
+#' @description These functions allow for filtering rows and selecting columns based on antibiotic test results that are of a specific antibiotic class or group (according to the [antibiotics] data set), without the need to define the columns or antibiotic abbreviations.
+#'
+#' In short, if you have a column name that resembles an antimicrobial drug, it will be picked up by any of these functions that matches its pharmaceutical class: "cefazolin", "kefzol", "CZO" and "J01DB04" will all be picked up by [cephalosporins()].
 #' @param ab_class an antimicrobial class or a part of it, such as `"carba"` and `"carbapenems"`. The columns `group`, `atc_group1` and `atc_group2` of the [antibiotics] data set will be searched (case-insensitive) for this value.
 #' @param filter an [expression] to be evaluated in the [antibiotics] data set, such as `name %like% "trim"`
-#' @param only_sir_columns a [logical] to indicate whether only columns of class `sir` must be selected (defaults to `FALSE`), see [as.sir()]
-#' @param only_treatable a [logical] to indicate whether antimicrobial drugs should be excluded that are only for laboratory tests (defaults to `TRUE`), such as gentamicin-high (`GEH`) and imipenem/EDTA (`IPE`)
+#' @param only_sir_columns a [logical] to indicate whether only columns of class `sir` must be selected (default is `FALSE`), see [as.sir()]
+#' @param only_treatable a [logical] to indicate whether antimicrobial drugs should be excluded that are only for laboratory tests (default is `TRUE`), such as gentamicin-high (`GEH`) and imipenem/EDTA (`IPE`)
 #' @param ... ignored, only in place to allow future extensions
 #' @details
-#' These functions can be used in data set calls for selecting columns and filtering rows. They are heavily inspired by the [Tidyverse selection helpers][tidyselect::language] such as [`everything()`][tidyselect::everything()], but also work in base \R and not only in `dplyr` verbs. Nonetheless, they are very convenient to use with `dplyr` functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()], see *Examples*.
+#' These functions can be used in data set calls for selecting columns and filtering rows. They work with base \R, the Tidyverse, and `data.table`. They are heavily inspired by the [Tidyverse selection helpers][tidyselect::language] such as [`everything()`][tidyselect::everything()], but are not limited to `dplyr` verbs. Nonetheless, they are very convenient to use with `dplyr` functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()], see *Examples*.
 #'
 #' All columns in the data in which these functions are called will be searched for known antibiotic names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) according to the [antibiotics] data set. This means that a selector such as [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
 #'
@@ -49,12 +51,15 @@
 #' @return (internally) a [character] vector of column names, with additional class `"ab_selector"`
 #' @export
 #' @inheritSection AMR Reference Data Publicly Available
-
 #' @examples
 #' # `example_isolates` is a data set available in the AMR package.
 #' # See ?example_isolates.
 #' example_isolates
 #'
+#'
+#' # Examples sections below are split into 'base R', 'dplyr', and 'data.table':
+#'
+#'
 #' # base R ------------------------------------------------------------------
 #'
 #' # select columns 'IPM' (imipenem) and 'MEM' (meropenem)
@@ -77,7 +82,7 @@
 #' # filter with multiple antibiotic selectors using c()
 #' example_isolates[all(c(carbapenems(), aminoglycosides()) == "R"), ]
 #'
-#' # filter + select in one go: get penicillins in carbapenems-resistant strains
+#' # filter + select in one go: get penicillins in carbapenem-resistant strains
 #' example_isolates[any(carbapenems() == "R"), penicillins()]
 #'
 #' # You can combine selectors with '&' to be more specific. For example,
@@ -87,28 +92,31 @@
 #' # and erythromycin is not a penicillin:
 #' example_isolates[, penicillins() & administrable_per_os()]
 #'
-#' # ab_selector() applies a filter in the `antibiotics` data set and is thus very
-#' # flexible. For instance, to select antibiotic columns with an oral DDD of at
-#' # least 1 gram:
+#' # ab_selector() applies a filter in the `antibiotics` data set and is thus
+#' # very flexible. For instance, to select antibiotic columns with an oral DDD
+#' # of at least 1 gram:
 #' example_isolates[, ab_selector(oral_ddd > 1 & oral_units == "g")]
 #'
-#' # dplyr -------------------------------------------------------------------
 #' \donttest{
-#' if (require("dplyr")) {
+#' # dplyr -------------------------------------------------------------------
 #'
+#' if (require("dplyr")) {
+#'   tibble(kefzol = random_sir(5)) %>%
+#'     select(cephalosporins())
+#' }
+#'
+#' if (require("dplyr")) {
 #'   # get AMR for all aminoglycosides e.g., per ward:
 #'   example_isolates %>%
 #'     group_by(ward) %>%
 #'     summarise(across(aminoglycosides(), resistance))
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # You can combine selectors with '&' to be more specific:
 #'   example_isolates %>%
 #'     select(penicillins() & administrable_per_os())
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # get AMR for only drugs that matter - no intrinsic resistance:
 #'   example_isolates %>%
 #'     filter(mo_genus() %in% c("Escherichia", "Klebsiella")) %>%
@@ -116,7 +124,6 @@
 #'     summarise(across(not_intrinsic_resistant(), resistance))
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # get susceptibility for antibiotics whose name contains "trim":
 #'   example_isolates %>%
 #'     filter(first_isolate()) %>%
@@ -124,19 +131,16 @@
 #'     summarise(across(ab_selector(name %like% "trim"), susceptibility))
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
 #'   example_isolates %>%
 #'     select(carbapenems())
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
 #'   example_isolates %>%
 #'     select(mo, aminoglycosides())
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # any() and all() work in dplyr's filter() too:
 #'   example_isolates %>%
 #'     filter(
@@ -145,25 +149,21 @@
 #'     )
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # also works with c():
 #'   example_isolates %>%
 #'     filter(any(c(carbapenems(), aminoglycosides()) == "R"))
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # not setting any/all will automatically apply all():
 #'   example_isolates %>%
 #'     filter(aminoglycosides() == "R")
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
 #'   example_isolates %>%
 #'     select(mo, ab_class("mycobact"))
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # get bug/drug combinations for only glycopeptides in Gram-positives:
 #'   example_isolates %>%
 #'     filter(mo_is_gram_positive()) %>%
@@ -179,13 +179,45 @@
 #'     select(penicillins()) # only the 'J01CA01' column will be selected
 #' }
 #' if (require("dplyr")) {
-#'
-#'   # with recent versions of dplyr this is all equal:
+#'   # with recent versions of dplyr, this is all equal:
 #'   x <- example_isolates[carbapenems() == "R", ]
 #'   y <- example_isolates %>% filter(carbapenems() == "R")
 #'   z <- example_isolates %>% filter(if_all(carbapenems(), ~ .x == "R"))
 #'   identical(x, y) && identical(y, z)
 #' }
+#'
+#'
+#' # data.table --------------------------------------------------------------
+#'
+#' # data.table is supported as well, just use it in the same way as with
+#' # base R, but add `with = FALSE` if using a single AB selector.
+#'
+#' if (require("data.table")) {
+#'   dt <- as.data.table(example_isolates)
+#'
+#'   # this does not work, it returns column *names*
+#'   dt[, carbapenems()]
+#' }
+#' if (require("data.table")) {
+#'   # so `with = FALSE` is required
+#'   dt[, carbapenems(), with = FALSE]
+#' }
+#'
+#' # for multiple selections or AB selectors, `with = FALSE` is not needed:
+#' if (require("data.table")) {
+#'   dt[, c("mo", aminoglycosides())]
+#' }
+#' if (require("data.table")) {
+#'   dt[, c(carbapenems(), aminoglycosides())]
+#' }
+#'
+#' # row filters are also supported:
+#' if (require("data.table")) {
+#'   dt[any(carbapenems() == "S"), ]
+#' }
+#' if (require("data.table")) {
+#'   dt[any(carbapenems() == "S"), penicillins(), with = FALSE]
+#' }
 #' }
 ab_class <- function(ab_class,
                     only_sir_columns = FALSE,
@@ -194,6 +226,10 @@ ab_class <- function(ab_class,
  meet_criteria(ab_class, allow_class = "character", has_length = 1, allow_NULL = TRUE)
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
  meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec(NULL, only_sir_columns = only_sir_columns, ab_class_args = ab_class, only_treatable = only_treatable)
 }

@@ -206,6 +242,10 @@ ab_selector <- function(filter,
                        ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
  meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }

  # get_current_data() has to run each time, for cases where e.g., filter() and select() are used in same call
  # but it only takes a couple of milliseconds
@@ -237,6 +277,10 @@ ab_selector <- function(filter,
 aminoglycosides <- function(only_sir_columns = FALSE, only_treatable = TRUE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
  meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("aminoglycosides", only_sir_columns = only_sir_columns, only_treatable = only_treatable)
 }

@@ -244,6 +288,10 @@ aminoglycosides <- function(only_sir_columns = FALSE, only_treatable = TRUE, ...
 #' @export
 aminopenicillins <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("aminopenicillins", only_sir_columns = only_sir_columns)
 }

@@ -251,6 +299,10 @@ aminopenicillins <- function(only_sir_columns = FALSE, ...) {
 #' @export
 antifungals <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("antifungals", only_sir_columns = only_sir_columns)
 }

@@ -258,6 +310,10 @@ antifungals <- function(only_sir_columns = FALSE, ...) {
 #' @export
 antimycobacterials <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("antimycobacterials", only_sir_columns = only_sir_columns)
 }

@@ -266,6 +322,10 @@ antimycobacterials <- function(only_sir_columns = FALSE, ...) {
 betalactams <- function(only_sir_columns = FALSE, only_treatable = TRUE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
  meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("betalactams", only_sir_columns = only_sir_columns, only_treatable = only_treatable)
 }

@@ -274,6 +334,10 @@ betalactams <- function(only_sir_columns = FALSE, only_treatable = TRUE, ...) {
 carbapenems <- function(only_sir_columns = FALSE, only_treatable = TRUE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
  meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("carbapenems", only_sir_columns = only_sir_columns, only_treatable = only_treatable)
 }

@@ -281,6 +345,10 @@ carbapenems <- function(only_sir_columns = FALSE, only_treatable = TRUE, ...) {
 #' @export
 cephalosporins <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("cephalosporins", only_sir_columns = only_sir_columns)
 }

@@ -288,6 +356,10 @@ cephalosporins <- function(only_sir_columns = FALSE, ...) {
 #' @export
 cephalosporins_1st <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("cephalosporins_1st", only_sir_columns = only_sir_columns)
 }

@@ -295,6 +367,10 @@ cephalosporins_1st <- function(only_sir_columns = FALSE, ...) {
 #' @export
 cephalosporins_2nd <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("cephalosporins_2nd", only_sir_columns = only_sir_columns)
 }

@@ -302,6 +378,10 @@ cephalosporins_2nd <- function(only_sir_columns = FALSE, ...) {
 #' @export
 cephalosporins_3rd <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("cephalosporins_3rd", only_sir_columns = only_sir_columns)
 }

@@ -309,6 +389,10 @@ cephalosporins_3rd <- function(only_sir_columns = FALSE, ...) {
 #' @export
 cephalosporins_4th <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("cephalosporins_4th", only_sir_columns = only_sir_columns)
 }

@@ -316,6 +400,10 @@ cephalosporins_4th <- function(only_sir_columns = FALSE, ...) {
 #' @export
 cephalosporins_5th <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("cephalosporins_5th", only_sir_columns = only_sir_columns)
 }

@@ -323,6 +411,10 @@ cephalosporins_5th <- function(only_sir_columns = FALSE, ...) {
 #' @export
 fluoroquinolones <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("fluoroquinolones", only_sir_columns = only_sir_columns)
 }

@@ -330,6 +422,10 @@ fluoroquinolones <- function(only_sir_columns = FALSE, ...) {
 #' @export
 glycopeptides <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("glycopeptides", only_sir_columns = only_sir_columns)
 }

@@ -337,6 +433,10 @@ glycopeptides <- function(only_sir_columns = FALSE, ...) {
 #' @export
 lincosamides <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("lincosamides", only_sir_columns = only_sir_columns)
 }

@@ -344,6 +444,10 @@ lincosamides <- function(only_sir_columns = FALSE, ...) {
 #' @export
 lipoglycopeptides <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("lipoglycopeptides", only_sir_columns = only_sir_columns)
 }

@@ -351,6 +455,10 @@ lipoglycopeptides <- function(only_sir_columns = FALSE, ...) {
 #' @export
 macrolides <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("macrolides", only_sir_columns = only_sir_columns)
 }

@@ -358,6 +466,10 @@ macrolides <- function(only_sir_columns = FALSE, ...) {
 #' @export
 oxazolidinones <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("oxazolidinones", only_sir_columns = only_sir_columns)
 }

@@ -365,6 +477,10 @@ oxazolidinones <- function(only_sir_columns = FALSE, ...) {
 #' @export
 penicillins <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("penicillins", only_sir_columns = only_sir_columns)
 }

@@ -373,6 +489,10 @@ penicillins <- function(only_sir_columns = FALSE, ...) {
 polymyxins <- function(only_sir_columns = FALSE, only_treatable = TRUE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
  meet_criteria(only_treatable, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("polymyxins", only_sir_columns = only_sir_columns, only_treatable = only_treatable)
 }

@@ -380,6 +500,10 @@ polymyxins <- function(only_sir_columns = FALSE, only_treatable = TRUE, ...) {
 #' @export
 streptogramins <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("streptogramins", only_sir_columns = only_sir_columns)
 }

@@ -387,6 +511,10 @@ streptogramins <- function(only_sir_columns = FALSE, ...) {
 #' @export
 quinolones <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("quinolones", only_sir_columns = only_sir_columns)
 }

@@ -394,6 +522,10 @@ quinolones <- function(only_sir_columns = FALSE, ...) {
 #' @export
 tetracyclines <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("tetracyclines", only_sir_columns = only_sir_columns)
 }

@@ -401,6 +533,10 @@ tetracyclines <- function(only_sir_columns = FALSE, ...) {
 #' @export
 trimethoprims <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("trimethoprims", only_sir_columns = only_sir_columns)
 }

@@ -408,6 +544,10 @@ trimethoprims <- function(only_sir_columns = FALSE, ...) {
 #' @export
 ureidopenicillins <- function(only_sir_columns = FALSE, ...) {
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  ab_select_exec("ureidopenicillins", only_sir_columns = only_sir_columns)
 }

@@ -433,14 +573,16 @@ administrable_per_os <- function(only_sir_columns = FALSE, ...) {
    ab_group = "administrable_per_os",
    examples = paste0(
      " (such as ",
-      vector_or(ab_name(sample(agents_all,
-        size = min(5, length(agents_all)),
-        replace = FALSE
-      ),
-      tolower = TRUE,
-      language = NULL
-      ),
-      quotes = FALSE
+      vector_or(
+        ab_name(
+          sample(agents_all,
+            size = min(5, length(agents_all)),
+            replace = FALSE
+          ),
+          tolower = TRUE,
+          language = NULL
+        ),
+        quotes = FALSE
      ),
      ")"
    )
@@ -491,20 +633,21 @@ not_intrinsic_resistant <- function(only_sir_columns = FALSE, col_mo = NULL, ver
    sort = FALSE, fn = "not_intrinsic_resistant"
  )
  # intrinsic vars
-  vars_df_R <- tryCatch(sapply(
-    eucast_rules(vars_df,
-      col_mo = col_mo,
-      version_expertrules = version_expertrules,
-      rules = "expert",
-      info = FALSE
+  vars_df_R <- tryCatch(
+    sapply(
+      eucast_rules(vars_df,
+        col_mo = col_mo,
+        version_expertrules = version_expertrules,
+        rules = "expert",
+        info = FALSE
+      ),
+      function(col) {
+        tryCatch(!any(is.na(col)) && all(col == "R"),
+          error = function(e) FALSE
+        )
+      }
    ),
-    function(col) {
-      tryCatch(!any(is.na(col)) && all(col == "R"),
-        error = function(e) FALSE
-      )
-    }
-  ),
-  error = function(e) stop_("in not_intrinsic_resistant(): ", e$message, call = FALSE)
+    error = function(e) stop_("in not_intrinsic_resistant(): ", e$message, call = FALSE)
  )

  agents <- ab_in_data[ab_in_data %in% names(vars_df_R[which(vars_df_R)])]
@@ -549,12 +692,13 @@ ab_select_exec <- function(function_name,
      if (message_not_thrown_before(function_name, "ab_class", "untreatable", entire_session = TRUE)) {
        warning_(
          "in `", function_name, "()`: some drugs were ignored since they cannot be used for treating patients: ",
-          vector_and(ab_name(names(ab_in_data)[names(ab_in_data) %in% untreatable],
-            language = NULL,
-            tolower = TRUE
-          ),
-          quotes = FALSE,
-          sort = TRUE
+          vector_and(
+            ab_name(names(ab_in_data)[names(ab_in_data) %in% untreatable],
+              language = NULL,
+              tolower = TRUE
+            ),
+            quotes = FALSE,
+            sort = TRUE
          ), ". They can be included using `", function_name, "(only_treatable = FALSE)`. ",
          "This warning will be shown once per session."
        )
@@ -593,11 +737,12 @@ ab_select_exec <- function(function_name,
      }
      ab_group <- function_name
    }
-    examples <- paste0(" (such as ", vector_or(ab_name(sample(abx, size = min(2, length(abx)), replace = FALSE),
-      tolower = TRUE,
-      language = NULL
-    ),
-    quotes = FALSE
+    examples <- paste0(" (such as ", vector_or(
+      ab_name(sample(abx, size = min(2, length(abx)), replace = FALSE),
+        tolower = TRUE,
+        language = NULL
+      ),
+      quotes = FALSE
    ), ")")
  } else {
    # this for the 'manual' ab_class() function
@@ -821,11 +966,12 @@ find_ab_names <- function(ab_group, n = 3) {
  if (length(drugs) == 0) {
    return("??")
  }
-  vector_or(ab_name(sample(drugs, size = min(n, length(drugs)), replace = FALSE),
-    tolower = TRUE,
-    language = NULL
-  ),
-  quotes = FALSE
+  vector_or(
+    ab_name(sample(drugs, size = min(n, length(drugs)), replace = FALSE),
+      tolower = TRUE,
+      language = NULL
+    ),
+    quotes = FALSE
  )
 }

@@ -31,7 +31,7 @@
 #'
 #' Calculates age in years based on a reference date, which is the system date at default.
 #' @param x date(s), [character] (vectors) will be coerced with [as.POSIXlt()]
-#' @param reference reference date(s) (defaults to today), [character] (vectors) will be coerced with [as.POSIXlt()]
+#' @param reference reference date(s) (default is today), [character] (vectors) will be coerced with [as.POSIXlt()]
 #' @param exact a [logical] to indicate whether age calculation should be exact, i.e. with decimals. It divides the number of days of [year-to-date](https://en.wikipedia.org/wiki/Year-to-date) (YTD) of `x` by the number of days in the year of `reference` (either 365 or 366).
 #' @param na.rm a [logical] to indicate whether missing values should be removed
 #' @param ... arguments passed on to [as.POSIXlt()], such as `origin`
@@ -83,11 +83,12 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
  # add decimals
  if (exact == TRUE) {
    # get dates of `x` when `x` would have the year of `reference`
-    x_in_reference_year <- as.POSIXlt(paste0(
-      format(as.Date(reference), "%Y"),
-      format(as.Date(x), "-%m-%d")
-    ),
-    format = "%Y-%m-%d"
+    x_in_reference_year <- as.POSIXlt(
+      paste0(
+        format(as.Date(reference), "%Y"),
+        format(as.Date(x), "-%m-%d")
+      ),
+      format = "%Y-%m-%d"
    )
    # get differences in days
    n_days_x_rest <- as.double(difftime(as.Date(reference),
@@ -129,7 +130,7 @@ age <- function(x, reference = Sys.Date(), exact = FALSE, na.rm = FALSE, ...) {
 #'
 #' Split ages into age groups defined by the `split` argument. This allows for easier demographic (antimicrobial resistance) analysis.
 #' @param x age, e.g. calculated with [age()]
-#' @param split_at values to split `x` at, defaults to age groups 0-11, 12-24, 25-54, 55-74 and 75+. See *Details*.
+#' @param split_at values to split `x` at - the default is age groups 0-11, 12-24, 25-54, 55-74 and 75+. See *Details*.
 #' @param na.rm a [logical] to indicate whether missing values should be removed
 #' @details To split ages, the input for the `split_at` argument can be:
 #'
@@ -0,0 +1,608 @@
+# ==================================================================== #
+# TITLE                                                                #
+# AMR: An R Package for Working with Antimicrobial Resistance Data     #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# CITE AS                                                              #
+# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C    #
+# (2022). AMR: An R Package for Working with Antimicrobial Resistance  #
+# Data. Journal of Statistical Software, 104(3), 1-31.                 #
+# doi:10.18637/jss.v104.i03                                            #
+#                                                                      #
+# Developed at the University of Groningen and the University Medical  #
+# Center Groningen in The Netherlands, in collaboration with many      #
+# colleagues from around the world, see our website.                   #
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+#' Generate Antibiogram: Traditional, Combined, Syndromic, or Weighted-Incidence Syndromic Combination (WISCA)
+#'
+#' Generate an antibiogram, and communicate the results in plots or tables. These functions follow the logic of Klinker *et al.* and Barbieri *et al.* (see *Source*), and allow reporting in e.g. R Markdown and Quarto as well.
+#' @param x a [data.frame] containing at least a column with microorganisms and columns with antibiotic results (class 'sir', see [as.sir()])
+#' @param antibiotics vector of any antibiotic name or code (will be evaluated with [as.ab()], column name of `x`, or (any combinations of) [antibiotic selectors][antibiotic_class_selectors] such as [aminoglycosides()] or [carbapenems()]. For combination antibiograms, this can also be set to values separated with `"+"`, such as "TZP+TOB" or "cipro + genta", given that columns resembling such antibiotics exist in `x`. See *Examples*.
+#' @param mo_transform a character to transform microorganism input - must be "name", "shortname", "gramstain", or one of the column names of the [microorganisms] data set: `r vector_or(colnames(microorganisms), sort = FALSE, quotes = TRUE)`. Can also be `NULL` to not transform the input.
+#' @param ab_transform a character to transform antibiotic input - must be one of the column names of the [antibiotics] data set: `r vector_or(colnames(antibiotics), sort = FALSE, quotes = TRUE)`. Can also be `NULL` to not transform the input.
+#' @param syndromic_group a column name of `x`, or values calculated to split rows of `x`, e.g. by using [ifelse()] or [`case_when()`][dplyr::case_when()]. See *Examples*.
+#' @param add_total_n a [logical] to indicate whether total available numbers per pathogen should be added to the table (default is `TRUE`). This will add the lowest and highest number of available isolate per antibiotic (e.g, if for *E. coli* 200 isolates are available for ciprofloxacin and 150 for amoxicillin, the returned number will be "150-200").
+#' @param only_all_tested (for combination antibiograms): a [logical] to indicate that isolates must be tested for all antibiotics, see *Details*
+#' @param digits number of digits to use for rounding
+#' @param col_mo column name of the names or codes of the microorganisms (see [as.mo()]) - the default is the first column of class [`mo`]. Values will be coerced using [as.mo()].
+#' @param language language to translate text, which defaults to the system language (see [get_AMR_locale()])
+#' @param minimum the minimum allowed number of available (tested) isolates. Any isolate count lower than `minimum` will return `NA` with a warning. The default number of `30` isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see *Source*.
+#' @param combine_SI a [logical] to indicate whether all susceptibility should be determined by results of either S or I, instead of only S (default is `TRUE`)
+#' @param sep a separating character for antibiotic columns in combination antibiograms
+#' @param info 	a [logical] to indicate info should be printed - the default is `TRUE` only in interactive mode
+#' @param object an [antibiogram()] object
+#' @param ... when used in [R Markdown or Quarto][knitr::kable()]: arguments passed on to [knitr::kable()] (otherwise, has no use)
+#' @details This function returns a table with values between 0 and 100 for *susceptibility*, not resistance.
+#'
+#' **Remember that you should filter your data to let it contain only first isolates!** This is needed to exclude duplicates and to reduce selection bias. Use [first_isolate()] to determine them in your data set with one of the four available algorithms.
+#'
+#' All types of antibiograms as listed below can be plotted (using [ggplot2::autoplot()] or base \R [plot()]/[barplot()]). The `antibiogram` object can also be used directly in R Markdown / Quarto (i.e., `knitr`) for reports. In this case, [knitr::kable()] will be applied automatically and microorganism names will even be printed in italics at default (see argument `italicise`). You can also use functions from specific 'table reporting' packages to transform the output of [antibiogram()] to your needs, e.g. with `flextable::as_flextable()` or `gt::gt()`.
+#'
+#' ### Antibiogram Types
+#'
+#' There are four antibiogram types, as proposed by Klinker *et al.* (2021, \doi{10.1177/20499361211011373}), and they are all supported by [antibiogram()]:
+#'
+#' 1. **Traditional Antibiogram**
+#'
+#'    Case example: Susceptibility of *Pseudomonas aeruginosa* to piperacillin/tazobactam (TZP)
+#'
+#'    Code example:
+#'
+#'    ```r
+#'    antibiogram(your_data,
+#'                antibiotics = "TZP")
+#'    ```
+#'
+#' 2. **Combination Antibiogram**
+#'
+#'    Case example: Additional susceptibility of *Pseudomonas aeruginosa* to TZP + tobramycin versus TZP alone
+#'
+#'    Code example:
+#'
+#'    ```r
+#'    antibiogram(your_data,
+#'                antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
+#'    ```
+#'
+#' 3. **Syndromic Antibiogram**
+#'
+#'    Case example: Susceptibility of *Pseudomonas aeruginosa* to TZP among respiratory specimens (obtained among ICU patients only)
+#'
+#'    Code example:
+#'
+#'    ```r
+#'    antibiogram(your_data,
+#'                antibiotics = penicillins(),
+#'                syndromic_group = "ward")
+#'    ```
+#'
+#' 4. **Weighted-Incidence Syndromic Combination Antibiogram (WISCA)**
+#'
+#'    Case example: Susceptibility of *Pseudomonas aeruginosa* to TZP among respiratory specimens (obtained among ICU patients only) for male patients age >=65 years with heart failure
+#'
+#'    Code example:
+#'
+#'    ```r
+#'    library(dplyr)
+#'    your_data %>%
+#'      filter(ward == "ICU" & specimen_type == "Respiratory") %>%
+#'      antibiogram(antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
+#'                  syndromic_group = ifelse(.$age >= 65 &
+#'                                             .$gender == "Male" &
+#'                                             .$condition == "Heart Disease",
+#'                                           "Study Group", "Control Group"))
+#'    ```
+#'
+#' Note that for combination antibiograms, it is important to realise that susceptibility can be calculated in two ways, which can be set with the `only_all_tested` argument (default is `FALSE`). See this example for two antibiotics, Drug A and Drug B, about how [antibiogram()] works to calculate the %SI:
+#'
+#' ```
+#' --------------------------------------------------------------------
+#'                     only_all_tested = FALSE  only_all_tested = TRUE
+#'                     -----------------------  -----------------------
+#'  Drug A    Drug B   include as  include as   include as  include as
+#'                     numerator   denominator  numerator   denominator
+#' --------  --------  ----------  -----------  ----------  -----------
+#'  S or I    S or I       X            X            X            X
+#'    R       S or I       X            X            X            X
+#'   <NA>     S or I       X            X            -            -
+#'  S or I      R          X            X            X            X
+#'    R         R          -            X            -            X
+#'   <NA>       R          -            -            -            -
+#'  S or I     <NA>        X            X            -            -
+#'    R        <NA>        -            -            -            -
+#'   <NA>      <NA>        -            -            -            -
+#' --------------------------------------------------------------------
+#' ```
+#'
+#' @source
+#' * Klinker KP *et al.* (2021). **Antimicrobial stewardship and antibiograms: importance of moving beyond traditional antibiograms**. *Therapeutic Advances in Infectious Disease*, May 5;8:20499361211011373; \doi{10.1177/20499361211011373}
+#' * Barbieri E *et al.* (2021). **Development of a Weighted-Incidence Syndromic Combination Antibiogram (WISCA) to guide the choice of the empiric antibiotic treatment for urinary tract infection in paediatric patients: a Bayesian approach** *Antimicrobial Resistance & Infection Control* May 1;10(1):74; \doi{10.1186/s13756-021-00939-2}
+#' * **M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 5th Edition**, 2022, *Clinical and Laboratory Standards Institute (CLSI)*. <https://clsi.org/standards/products/microbiology/documents/m39/>.
+#' @rdname antibiogram
+#' @name antibiogram
+#' @export
+#' @examples
+#' # example_isolates is a data set available in the AMR package.
+#' # run ?example_isolates for more info.
+#' example_isolates
+#'
+#' \donttest{
+#' # Traditional antibiogram ----------------------------------------------
+#'
+#' antibiogram(example_isolates,
+#'   antibiotics = c(aminoglycosides(), carbapenems())
+#' )
+#'
+#' antibiogram(example_isolates,
+#'   antibiotics = aminoglycosides(),
+#'   ab_transform = "atc",
+#'   mo_transform = "gramstain"
+#' )
+#'
+#' antibiogram(example_isolates,
+#'   antibiotics = carbapenems(),
+#'   ab_transform = "name",
+#'   mo_transform = "name"
+#' )
+#'
+#'
+#' # Combined antibiogram -------------------------------------------------
+#'
+#' # combined antibiotics yield higher empiric coverage
+#' antibiogram(example_isolates,
+#'   antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
+#'   mo_transform = "gramstain"
+#' )
+#'
+#' # names of antibiotics do not need to resemble columns exactly:
+#' antibiogram(example_isolates,
+#'   antibiotics = c("Cipro", "cipro + genta"),
+#'   mo_transform = "gramstain",
+#'   ab_transform = "name",
+#'   sep = " & "
+#' )
+#'
+#'
+#' # Syndromic antibiogram ------------------------------------------------
+#'
+#' # the data set could contain a filter for e.g. respiratory specimens
+#' antibiogram(example_isolates,
+#'   antibiotics = c(aminoglycosides(), carbapenems()),
+#'   syndromic_group = "ward"
+#' )
+#'
+#' # now define a data set with only E. coli
+#' ex1 <- example_isolates[which(mo_genus() == "Escherichia"), ]
+#'
+#' # with a custom language, though this will be determined automatically
+#' # (i.e., this table will be in Spanish on Spanish systems)
+#' antibiogram(ex1,
+#'   antibiotics = aminoglycosides(),
+#'   ab_transform = "name",
+#'   syndromic_group = ifelse(ex1$ward == "ICU",
+#'     "UCI", "No UCI"
+#'   ),
+#'   language = "es"
+#' )
+#'
+#'
+#' # Weighted-incidence syndromic combination antibiogram (WISCA) ---------
+#'
+#' # the data set could contain a filter for e.g. respiratory specimens/ICU
+#' antibiogram(example_isolates,
+#'   antibiotics = c("AMC", "AMC+CIP", "TZP", "TZP+TOB"),
+#'   mo_transform = "gramstain",
+#'   minimum = 10, # this should be >=30, but now just as example
+#'   syndromic_group = ifelse(example_isolates$age >= 65 &
+#'     example_isolates$gender == "M",
+#'   "WISCA Group 1", "WISCA Group 2"
+#'   )
+#' )
+#'
+#'
+#' # Print the output for R Markdown / Quarto -----------------------------
+#'
+#' ureido <- antibiogram(example_isolates,
+#'   antibiotics = ureidopenicillins(),
+#'   ab_transform = "name"
+#' )
+#'
+#' # in an Rmd file, you would just need to return `ureido` in a chunk,
+#' # but to be explicit here:
+#' if (requireNamespace("knitr")) {
+#'   knitr::knit_print(ureido)
+#' }
+#'
+#'
+#' # Generate plots with ggplot2 or base R --------------------------------
+#'
+#' ab1 <- antibiogram(example_isolates,
+#'   antibiotics = c("AMC", "CIP", "TZP", "TZP+TOB"),
+#'   mo_transform = "gramstain"
+#' )
+#' ab2 <- antibiogram(example_isolates,
+#'   antibiotics = c("AMC", "CIP", "TZP", "TZP+TOB"),
+#'   mo_transform = "gramstain",
+#'   syndromic_group = "ward"
+#' )
+#'
+#' if (requireNamespace("ggplot2")) {
+#'   ggplot2::autoplot(ab1)
+#' }
+#' if (requireNamespace("ggplot2")) {
+#'   ggplot2::autoplot(ab2)
+#' }
+#'
+#' plot(ab1)
+#' plot(ab2)
+#' }
+antibiogram <- function(x,
+                        antibiotics = where(is.sir),
+                        mo_transform = "shortname",
+                        ab_transform = NULL,
+                        syndromic_group = NULL,
+                        add_total_n = TRUE,
+                        only_all_tested = FALSE,
+                        digits = 0,
+                        col_mo = NULL,
+                        language = get_AMR_locale(),
+                        minimum = 30,
+                        combine_SI = TRUE,
+                        sep = " + ",
+                        info = interactive()) {
+  meet_criteria(x, allow_class = "data.frame", contains_column_class = c("sir", "rsi"))
+  meet_criteria(mo_transform, allow_class = "character", has_length = 1, is_in = c("name", "shortname", "gramstain", colnames(AMR::microorganisms)), allow_NULL = TRUE)
+  meet_criteria(ab_transform, allow_class = "character", has_length = 1, is_in = colnames(AMR::antibiotics), allow_NULL = TRUE)
+  meet_criteria(syndromic_group, allow_class = "character", allow_NULL = TRUE, allow_NA = TRUE)
+  meet_criteria(add_total_n, allow_class = "logical", has_length = 1)
+  meet_criteria(only_all_tested, allow_class = "logical", has_length = 1)
+  meet_criteria(digits, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
+  meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
+  language <- validate_language(language)
+  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
+  meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
+  meet_criteria(sep, allow_class = "character", has_length = 1)
+  meet_criteria(info, allow_class = "logical", has_length = 1)
+
+  # try to find columns based on type
+  if (is.null(col_mo)) {
+    col_mo <- search_type_in_df(x = x, type = "mo", info = interactive())
+    stop_if(is.null(col_mo), "`col_mo` must be set")
+  }
+  # transform MOs
+  x$`.mo` <- x[, col_mo, drop = TRUE]
+  if (is.null(mo_transform)) {
+    # leave as is
+  } else if (mo_transform == "gramstain") {
+    x$`.mo` <- mo_gramstain(x$`.mo`, language = language)
+  } else if (mo_transform == "shortname") {
+    x$`.mo` <- mo_shortname(x$`.mo`, language = language)
+  } else if (mo_transform == "name") {
+    x$`.mo` <- mo_name(x$`.mo`, language = language)
+  } else {
+    x$`.mo` <- mo_property(x$`.mo`, language = language)
+  }
+  x$`.mo`[is.na(x$`.mo`)] <- "(??)"
+
+  # get syndromic groups
+  if (!is.null(syndromic_group)) {
+    if (length(syndromic_group) == 1 && syndromic_group %in% colnames(x)) {
+      x$`.syndromic_group` <- x[, syndromic_group, drop = TRUE]
+    } else if (!is.null(syndromic_group)) {
+      x$`.syndromic_group` <- syndromic_group
+    }
+    x$`.syndromic_group`[is.na(x$`.syndromic_group`) | x$`.syndromic_group` == ""] <- paste0("(", translate_AMR("unknown", language = language), ")")
+    has_syndromic_group <- TRUE
+  } else {
+    has_syndromic_group <- FALSE
+  }
+
+  # get antibiotics
+  if (tryCatch(is.character(antibiotics), error = function(e) FALSE)) {
+    antibiotics.bak <- antibiotics
+    # split antibiotics on separator and make it a list
+    antibiotics <- strsplit(gsub(" ", "", antibiotics), "+", fixed = TRUE)
+    # get available antibiotics in data set
+    df_ab <- get_column_abx(x, verbose = FALSE, info = FALSE)
+    # get antibiotics from user
+    user_ab <- suppressMessages(suppressWarnings(lapply(antibiotics, as.ab, flag_multiple_results = FALSE, info = FALSE)))
+    non_existing <- character(0)
+    user_ab <- lapply(user_ab, function(x) {
+      out <- unname(df_ab[match(x, names(df_ab))])
+      non_existing <<- c(non_existing, x[is.na(out) & !is.na(x)])
+      # remove non-existing columns
+      out[!is.na(out)]
+    })
+    user_ab <- user_ab[unlist(lapply(user_ab, length)) > 0]
+
+    if (length(non_existing) > 0) {
+      warning_("The following antibiotics were not available and ignored: ", vector_and(ab_name(non_existing, language = NULL, tolower = TRUE), quotes = FALSE))
+    }
+
+    # make list unique
+    antibiotics <- unique(user_ab)
+    # go through list to set AMR in combinations
+    for (i in seq_len(length(antibiotics))) {
+      abx <- antibiotics[[i]]
+      for (ab in abx) {
+        # make sure they are SIR columns
+        x[, ab] <- as.sir(x[, ab, drop = TRUE])
+      }
+      new_colname <- paste0(trimws(abx), collapse = sep)
+      if (length(abx) == 1) {
+        next
+      } else {
+        # determine whether this new column should contain S, I, R, or NA
+        if (isTRUE(combine_SI)) {
+          S_values <- c("S", "I")
+        } else {
+          S_values <- "S"
+        }
+        other_values <- setdiff(c("S", "I", "R"), S_values)
+        x_transposed <- as.list(as.data.frame(t(x[, abx, drop = FALSE]), stringsAsFactors = FALSE))
+        if (isTRUE(only_all_tested)) {
+          x[new_colname] <- as.sir(vapply(FUN.VALUE = character(1), x_transposed, function(x) ifelse(anyNA(x), NA_character_, ifelse(any(x %in% S_values), "S", "R")), USE.NAMES = FALSE))
+        } else {
+          x[new_colname] <- as.sir(vapply(
+            FUN.VALUE = character(1), x_transposed, function(x) ifelse(any(x %in% S_values, na.rm = TRUE), "S", ifelse(anyNA(x), NA_character_, "R")),
+            USE.NAMES = FALSE
+          ))
+        }
+      }
+      antibiotics[[i]] <- new_colname
+    }
+    antibiotics <- unlist(antibiotics)
+  } else {
+    antibiotics <- colnames(suppressWarnings(x[, antibiotics, drop = FALSE]))
+  }
+
+  if (isTRUE(has_syndromic_group)) {
+    out <- x %pm>%
+      pm_select(.syndromic_group, .mo, antibiotics) %pm>%
+      pm_group_by(.syndromic_group)
+  } else {
+    out <- x %pm>%
+      pm_select(.mo, antibiotics)
+  }
+
+  # get numbers of S, I, R (per group)
+  out <- out %pm>%
+    bug_drug_combinations(
+      col_mo = ".mo",
+      FUN = function(x) x
+    )
+  counts <- out
+
+  if (isTRUE(combine_SI)) {
+    out$numerator <- out$S + out$I
+  } else {
+    out$numerator <- out$S
+  }
+  if (any(out$total < minimum, na.rm = TRUE)) {
+    if (isTRUE(info)) {
+      message_("NOTE: ", sum(out$total < minimum, na.rm = TRUE), " combinations had less than `minimum = ", minimum, "` results and were ignored", add_fn = font_red)
+    }
+    out <- out %pm>%
+      subset(total >= minimum)
+  }
+
+  # regroup for summarising
+  if (isTRUE(has_syndromic_group)) {
+    colnames(out)[1] <- "syndromic_group"
+    out <- out %pm>%
+      pm_group_by(syndromic_group, mo, ab)
+  } else {
+    out <- out %pm>%
+      pm_group_by(mo, ab)
+  }
+  out <- out %pm>%
+    pm_summarise(SI = numerator / total)
+
+  # transform names of antibiotics
+  ab_naming_function <- function(x, t, l, s) {
+    x <- strsplit(x, s, fixed = TRUE)
+    out <- character(length = length(x))
+    for (i in seq_len(length(x))) {
+      a <- x[[i]]
+      if (is.null(t)) {
+        # leave as is
+      } else if (t == "atc") {
+        a <- ab_atc(a, only_first = TRUE, language = l)
+      } else {
+        a <- ab_property(a, property = t, language = l)
+      }
+      if (length(a) > 1) {
+        a <- paste0(trimws(a), collapse = sep)
+      }
+      out[i] <- a
+    }
+    out
+  }
+  out$ab <- ab_naming_function(out$ab, t = ab_transform, l = language, s = sep)
+
+  # transform long to wide
+  long_to_wide <- function(object, digs) {
+    object$SI <- round(object$SI * 100, digits = digs)
+    object <- object %pm>%
+      # an unclassed data.frame is required for stats::reshape()
+      as.data.frame(stringsAsFactors = FALSE) %pm>%
+      stats::reshape(direction = "wide", idvar = "mo", timevar = "ab", v.names = "SI")
+    colnames(object) <- gsub("^SI?[.]", "", colnames(object))
+    return(object)
+  }
+
+  # ungroup for long -> wide transformation
+  attr(out, "pm_groups") <- NULL
+  attr(out, "groups") <- NULL
+  class(out) <- class(out)[!class(out) %in% c("grouped_df", "grouped_data")]
+  long <- out
+
+  if (isTRUE(has_syndromic_group)) {
+    grps <- unique(out$syndromic_group)
+    for (i in seq_len(length(grps))) {
+      grp <- grps[i]
+      if (i == 1) {
+        new_df <- long_to_wide(out[which(out$syndromic_group == grp), , drop = FALSE], digs = digits)
+      } else {
+        new_df <- rbind_AMR(
+          new_df,
+          long_to_wide(out[which(out$syndromic_group == grp), , drop = FALSE], digs = digits)
+        )
+      }
+    }
+    # sort rows
+    new_df <- new_df %pm>% pm_arrange(mo, syndromic_group)
+    # sort columns
+    new_df <- new_df[, c("syndromic_group", "mo", sort(colnames(new_df)[!colnames(new_df) %in% c("syndromic_group", "mo")])), drop = FALSE]
+    colnames(new_df)[1:2] <- translate_AMR(c("Syndromic Group", "Pathogen"), language = language)
+  } else {
+    new_df <- long_to_wide(out, digs = digits)
+    # sort rows
+    new_df <- new_df %pm>% pm_arrange(mo)
+    # sort columns
+    new_df <- new_df[, c("mo", sort(colnames(new_df)[colnames(new_df) != "mo"])), drop = FALSE]
+    colnames(new_df)[1] <- translate_AMR("Pathogen", language = language)
+  }
+
+  # add total N if indicated
+  if (isTRUE(add_total_n)) {
+    if (isTRUE(has_syndromic_group)) {
+      n_per_mo <- counts %pm>%
+        pm_group_by(mo, .syndromic_group) %pm>%
+        pm_summarise(paste0(min(total, na.rm = TRUE), "-", max(total, na.rm = TRUE)))
+      colnames(n_per_mo) <- c("mo", "syn", "count")
+      count_group <- n_per_mo$count[match(paste(new_df[[2]], new_df[[1]]), paste(n_per_mo$mo, n_per_mo$syn))]
+      edit_col <- 2
+    } else {
+      n_per_mo <- counts %pm>%
+        pm_group_by(mo) %pm>%
+        pm_summarise(paste0(min(total, na.rm = TRUE), "-", max(total, na.rm = TRUE)))
+      colnames(n_per_mo) <- c("mo", "count")
+      count_group <- n_per_mo$count[match(new_df[[1]], n_per_mo$mo)]
+      edit_col <- 1
+    }
+    if (NCOL(new_df) == edit_col + 1) {
+      # only 1 antibiotic
+      new_df[[edit_col]] <- paste0(new_df[[edit_col]], " (", unlist(lapply(strsplit(x = count_group, split = "-", fixed = TRUE), function(x) x[1])), ")")
+      colnames(new_df)[edit_col] <- paste(colnames(new_df)[edit_col], "(N)")
+    } else {
+      # more than 1 antibiotic
+      new_df[[edit_col]] <- paste0(new_df[[edit_col]], " (", count_group, ")")
+      colnames(new_df)[edit_col] <- paste(colnames(new_df)[edit_col], "(N min-max)")
+    }
+  }
+
+  out <- as_original_data_class(new_df, class(x), extra_class = "antibiogram")
+  rownames(out) <- NULL
+  structure(out,
+    has_syndromic_group = has_syndromic_group,
+    long = long,
+    combine_SI = combine_SI
+  )
+}
+
+#' @export
+#' @rdname antibiogram
+plot.antibiogram <- function(x, ...) {
+  df <- attributes(x)$long
+  if ("syndromic_group" %in% colnames(df)) {
+    # barplot in base R does not support facets - paste columns together
+    df$mo <- paste(df$mo, "-", df$syndromic_group)
+    df$syndromic_group <- NULL
+    df <- df[order(df$mo), , drop = FALSE]
+  }
+  mo_levels <- unique(df$mo)
+  mfrow_old <- graphics::par()$mfrow
+  sqrt_levels <- sqrt(length(mo_levels))
+  graphics::par(mfrow = c(ceiling(sqrt_levels), floor(sqrt_levels)))
+  for (i in seq_along(mo_levels)) {
+    mo <- mo_levels[i]
+    df_sub <- df[df$mo == mo, , drop = FALSE]
+
+    barplot(
+      height = df_sub$SI * 100,
+      xlab = NULL,
+      ylab = ifelse(isTRUE(attributes(x)$combine_SI), "%SI", "%S"),
+      names.arg = df_sub$ab,
+      col = "#aaaaaa",
+      beside = TRUE,
+      main = mo,
+      legend = NULL
+    )
+  }
+  graphics::par(mfrow = mfrow_old)
+}
+
+#' @export
+#' @noRd
+barplot.antibiogram <- function(height, ...) {
+  plot(height, ...)
+}
+
+#' @method autoplot antibiogram
+#' @rdname antibiogram
+# will be exported using s3_register() in R/zzz.R
+autoplot.antibiogram <- function(object, ...) {
+  df <- attributes(object)$long
+  ggplot2::ggplot(df) +
+    ggplot2::geom_col(
+      ggplot2::aes(
+        x = ab,
+        y = SI * 100,
+        fill = if ("syndromic_group" %in% colnames(df)) {
+          syndromic_group
+        } else {
+          NULL
+        }
+      ),
+      position = ggplot2::position_dodge2(preserve = "single")
+    ) +
+    ggplot2::facet_wrap("mo") +
+    ggplot2::labs(
+      y = ifelse(isTRUE(attributes(object)$combine_SI), "%SI", "%S"),
+      x = NULL,
+      fill = if ("syndromic_group" %in% colnames(df)) {
+        colnames(object)[1]
+      } else {
+        NULL
+      }
+    )
+}
+
+# will be exported in zzz.R
+#' @method knit_print antibiogram
+#' @param italicise a [logical] to indicate whether the microorganism names in the [knitr][knitr::kable()] table should be made italic, using [italicise_taxonomy()].
+#' @param na character to use for showing `NA` values
+#' @rdname antibiogram
+knit_print.antibiogram <- function(x, italicise = TRUE, na = getOption("knitr.kable.NA", default = ""), ...) {
+  stop_ifnot_installed("knitr")
+  meet_criteria(italicise, allow_class = "logical", has_length = 1)
+  meet_criteria(na, allow_class = "character", has_length = 1, allow_NA = TRUE)
+
+  if (isTRUE(italicise)) {
+    # make all microorganism names italic, according to nomenclature
+    names_col <- ifelse(isTRUE(attributes(x)$has_syndromic_group), 2, 1)
+    x[[names_col]] <- italicise_taxonomy(x[[names_col]], type = "markdown")
+  }
+
+  old_option <- getOption("knitr.kable.NA")
+  options(knitr.kable.NA = na)
+  on.exit(options(knitr.kable.NA = old_option))
+
+  out <- paste(c("", "", knitr::kable(x, ..., output = FALSE)), collapse = "\n")
+  knitr::asis_output(out)
+}
@@ -32,7 +32,7 @@
 #' Use this function to determine the antiviral drug code of one or more antiviral drugs. The data set [antivirals] will be searched for abbreviations, official names and synonyms (brand names).
 #' @param x a [character] vector to determine to antiviral drug ID
 #' @param flag_multiple_results a [logical] to indicate whether a note should be printed to the console that probably more than one antiviral drug code or name can be retrieved from a single input value.
-#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
+#' @param info a [logical] to indicate whether a progress bar should be printed - the default is `TRUE` only in interactive mode
 #' @param ... arguments passed on to internal functions
 #' @rdname as.av
 #' @inheritSection WHOCC WHOCC
@@ -308,22 +308,23 @@ as.av <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
      }

      # transform back from other languages and try again
-      x_translated <- paste(lapply(
-        strsplit(x[i], "[^A-Z0-9]"),
-        function(y) {
-          for (i in seq_len(length(y))) {
-            for (lang in LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]) {
-              y[i] <- ifelse(tolower(y[i]) %in% tolower(TRANSLATIONS[, lang, drop = TRUE]),
-                TRANSLATIONS[which(tolower(TRANSLATIONS[, lang, drop = TRUE]) == tolower(y[i]) &
-                  !isFALSE(TRANSLATIONS$fixed)), "pattern"],
-                y[i]
-              )
+      x_translated <- paste(
+        lapply(
+          strsplit(x[i], "[^A-Z0-9]"),
+          function(y) {
+            for (i in seq_len(length(y))) {
+              for (lang in LANGUAGES_SUPPORTED[LANGUAGES_SUPPORTED != "en"]) {
+                y[i] <- ifelse(tolower(y[i]) %in% tolower(TRANSLATIONS[, lang, drop = TRUE]),
+                  TRANSLATIONS[which(tolower(TRANSLATIONS[, lang, drop = TRUE]) == tolower(y[i]) &
+                    !isFALSE(TRANSLATIONS$fixed)), "pattern"],
+                  y[i]
+                )
+              }
            }
+            generalise_antibiotic_name(y)
          }
-          generalise_antibiotic_name(y)
-        }
-      )[[1]],
-      collapse = "/"
+        )[[1]],
+        collapse = "/"
      )
      x_translated_guess <- suppressWarnings(as.av(x_translated, initial_search = FALSE))
      if (!is.na(x_translated_guess)) {
@@ -332,20 +333,21 @@ as.av <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
      }

      # now also try to coerce brandname combinations like "Amoxy/clavulanic acid"
-      x_translated <- paste(lapply(
-        strsplit(x_translated, "[^A-Z0-9 ]"),
-        function(y) {
-          for (i in seq_len(length(y))) {
-            y_name <- suppressWarnings(av_name(y[i], language = NULL, initial_search = FALSE))
-            y[i] <- ifelse(!is.na(y_name),
-              y_name,
-              y[i]
-            )
+      x_translated <- paste(
+        lapply(
+          strsplit(x_translated, "[^A-Z0-9 ]"),
+          function(y) {
+            for (i in seq_len(length(y))) {
+              y_name <- suppressWarnings(av_name(y[i], language = NULL, initial_search = FALSE))
+              y[i] <- ifelse(!is.na(y_name),
+                y_name,
+                y[i]
+              )
+            }
+            generalise_antibiotic_name(y)
          }
-          generalise_antibiotic_name(y)
-        }
-      )[[1]],
-      collapse = "/"
+        )[[1]],
+        collapse = "/"
      )
      x_translated_guess <- suppressWarnings(as.av(x_translated, initial_search = FALSE))
      if (!is.na(x_translated_guess)) {
@@ -459,14 +461,14 @@ as.av <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
  # save to package env to save time for next time
  if (isTRUE(initial_search)) {
    AMR_env$av_previously_coerced <- AMR_env$av_previously_coerced[which(!AMR_env$av_previously_coerced$x %in% x), , drop = FALSE]
-    AMR_env$av_previously_coerced <- unique(rbind(AMR_env$av_previously_coerced,
+    AMR_env$av_previously_coerced <- unique(rbind_AMR(
+      AMR_env$av_previously_coerced,
      data.frame(
        x = x,
        av = x_new,
        x_bak = x_bak[match(x, x_bak_clean)],
        stringsAsFactors = FALSE
-      ),
-      stringsAsFactors = FALSE
+      )
    ))
  }

@@ -478,8 +480,10 @@ as.av <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
    )
  }
  x_unknown <- x_unknown[!x_unknown %in% x_unknown_ATCs]
-  x_unknown <- c(x_unknown,
-                 AMR_env$av_previously_coerced$x_bak[which(AMR_env$av_previously_coerced$x %in% x & is.na(AMR_env$av_previously_coerced$av))])
+  x_unknown <- c(
+    x_unknown,
+    AMR_env$av_previously_coerced$x_bak[which(AMR_env$av_previously_coerced$x %in% x & is.na(AMR_env$av_previously_coerced$av))]
+  )
  if (length(x_unknown) > 0 && fast_mode == FALSE) {
    warning_(
      "in `as.av()`: these values could not be coerced to a valid antiviral drug ID: ",
@@ -604,9 +608,9 @@ get_translate_av <- function(translate_av) {
  } else {
    translate_av <- tolower(translate_av)
    stop_ifnot(translate_av %in% colnames(AMR::antivirals),
-               "invalid value for 'translate_av', this must be a column name of the antivirals data set\n",
-               "or TRUE (equals 'name') or FALSE to not translate at all.",
-               call = FALSE
+      "invalid value for 'translate_av', this must be a column name of the antivirals data set\n",
+      "or TRUE (equals 'name') or FALSE to not translate at all.",
+      call = FALSE
    )
    translate_av
  }
@@ -33,9 +33,9 @@
 #' @param text text to analyse
 #' @param type type of property to search for, either `"drug"`, `"dose"` or `"administration"`, see *Examples*
 #' @param collapse a [character] to pass on to `paste(, collapse = ...)` to only return one [character] per element of `text`, see *Examples*
-#' @param translate_av if `type = "drug"`: a column name of the [antivirals] data set to translate the antibiotic abbreviations to, using [av_property()]. Defaults to `FALSE`. Using `TRUE` is equal to using "name".
+#' @param translate_av if `type = "drug"`: a column name of the [antivirals] data set to translate the antibiotic abbreviations to, using [av_property()]. The default is `FALSE`. Using `TRUE` is equal to using "name".
 #' @param thorough_search a [logical] to indicate whether the input must be extensively searched for misspelling and other faulty input values. Setting this to `TRUE` will take considerably more time than when using `FALSE`. At default, it will turn `TRUE` when all input elements contain a maximum of three words.
-#' @param info a [logical] to indicate whether a progress bar should be printed, defaults to `TRUE` only in interactive mode
+#' @param info a [logical] to indicate whether a progress bar should be printed - the default is `TRUE` only in interactive mode
 #' @param ... arguments passed on to [as.av()]
 #' @details This function is also internally used by [as.av()], although it then only searches for the first drug name and will throw a note if more drug names could have been returned. Note: the [as.av()] function may use very long regular expression to match brand names of antiviral drugs. This may fail on some systems.
 #'
@@ -69,26 +69,26 @@ av_from_text <- function(text,
  if (missing(type)) {
    type <- type[1L]
  }
-  
+
  meet_criteria(text)
  meet_criteria(type, allow_class = "character", has_length = 1)
  meet_criteria(collapse, has_length = 1, allow_NULL = TRUE)
  meet_criteria(translate_av, allow_NULL = FALSE) # get_translate_av() will be more informative about what's allowed
  meet_criteria(thorough_search, allow_class = "logical", has_length = 1, allow_NULL = TRUE)
  meet_criteria(info, allow_class = "logical", has_length = 1)
-  
+
  type <- tolower(trimws2(type))
-  
+
  text <- tolower(as.character(text))
  text_split_all <- strsplit(text, "[ ;.,:\\|]")
  progress <- progress_ticker(n = length(text_split_all), n_min = 5, print = info)
  on.exit(close(progress))
-  
+
  if (type %like% "(drug|ab|anti)") {
    translate_av <- get_translate_av(translate_av)
-    
+
    if (isTRUE(thorough_search) ||
-        (isTRUE(is.null(thorough_search)) && max(vapply(FUN.VALUE = double(1), text_split_all, length), na.rm = TRUE) <= 3)) {
+      (isTRUE(is.null(thorough_search)) && max(vapply(FUN.VALUE = double(1), text_split_all, length), na.rm = TRUE) <= 3)) {
      text_split_all <- text_split_all[nchar(text_split_all) >= 4 & grepl("[a-z]+", text_split_all)]
      result <- lapply(text_split_all, function(text_split) {
        progress$tick()
@@ -125,9 +125,9 @@ av_from_text <- function(text,
        )
      })
    }
-    
+
    close(progress)
-    
+
    result <- lapply(result, function(out) {
      out <- out[!is.na(out)]
      if (length(out) == 0) {
@@ -149,7 +149,7 @@ av_from_text <- function(text,
      text_split <- as.double(gsub("[^0-9.]", "", text_split))
      # minimal 100 units/mg and no years that unlikely doses
      text_split <- text_split[text_split >= 100 & !text_split %in% c(1951:1999, 2001:2049)]
-      
+
      if (length(text_split) > 0) {
        text_split
      } else {
@@ -170,7 +170,7 @@ av_from_text <- function(text,
  } else {
    stop_("`type` must be either 'drug', 'dose' or 'administration'")
  }
-  
+
  # collapse text if needed
  if (!is.null(collapse)) {
    result <- vapply(FUN.VALUE = character(1), result, function(x) {
@@ -181,6 +181,6 @@ av_from_text <- function(text,
      }
    })
  }
-  
+
  result
 }
@@ -33,7 +33,7 @@
 #' @param x any (vector of) text that can be coerced to a valid antiviral drug code with [as.av()]
 #' @param tolower a [logical] to indicate whether the first [character] of every output should be transformed to a lower case [character].
 #' @param property one of the column names of one of the [antivirals] data set: `vector_or(colnames(antivirals), sort = FALSE)`.
-#' @param language language of the returned text, defaults to system language (see [get_AMR_locale()]) and can also be set with `getOption("AMR_locale")`. Use `language = NULL` or `language = ""` to prevent translation.
+#' @param language language of the returned text - the default is system language (see [get_AMR_locale()]) and can also be set with the [package option][AMR-options] [`AMR_locale`][AMR-options]. Use `language = NULL` or `language = ""` to prevent translation.
 #' @param administration way of administration, either `"oral"` or `"iv"`
 #' @param open browse the URL using [utils::browseURL()]
 #' @param ... other arguments passed on to [as.av()]
@@ -84,7 +84,7 @@ av_name <- function(x, language = get_AMR_locale(), tolower = FALSE, ...) {
  meet_criteria(x, allow_NA = TRUE)
  language <- validate_language(language)
  meet_criteria(tolower, allow_class = "logical", has_length = 1)
-  
+
  x <- translate_into_language(av_validate(x = x, property = "name", ...), language = language, only_affect_ab_names = TRUE)
  if (tolower == TRUE) {
    # use perl to only transform the first character
@@ -155,11 +155,11 @@ av_loinc <- function(x, ...) {
 av_ddd <- function(x, administration = "oral", ...) {
  meet_criteria(x, allow_NA = TRUE)
  meet_criteria(administration, is_in = c("oral", "iv"), has_length = 1)
-  
+
  x <- as.av(x, ...)
  ddd_prop <- paste0(administration, "_ddd")
  out <- av_validate(x = x, property = ddd_prop)
-  
+
  if (any(av_name(x, language = NULL) %like% "/" & is.na(out))) {
    warning_(
      "in `av_ddd()`: DDDs of some combined products are available for different dose combinations and not (yet) part of the AMR package.",
@@ -175,11 +175,11 @@ av_ddd <- function(x, administration = "oral", ...) {
 av_ddd_units <- function(x, administration = "oral", ...) {
  meet_criteria(x, allow_NA = TRUE)
  meet_criteria(administration, is_in = c("oral", "iv"), has_length = 1)
-  
+
  x <- as.av(x, ...)
  ddd_prop <- paste0(administration, "_units")
  out <- av_validate(x = x, property = ddd_prop)
-  
+
  if (any(av_name(x, language = NULL) %like% "/" & is.na(out))) {
    warning_(
      "in `av_ddd_units()`: DDDs of some combined products are available for different dose combinations and not (yet) part of the AMR package.",
@@ -195,7 +195,7 @@ av_ddd_units <- function(x, administration = "oral", ...) {
 av_info <- function(x, language = get_AMR_locale(), ...) {
  meet_criteria(x, allow_NA = TRUE)
  language <- validate_language(language)
-  
+
  x <- as.av(x, ...)
  list(
    av = as.character(x),
@@ -224,18 +224,18 @@ av_info <- function(x, language = get_AMR_locale(), ...) {
 av_url <- function(x, open = FALSE, ...) {
  meet_criteria(x, allow_NA = TRUE)
  meet_criteria(open, allow_class = "logical", has_length = 1)
-  
+
  av <- as.av(x = x, ...)
  atcs <- av_atc(av, only_first = TRUE)
  u <- paste0("https://www.whocc.no/atc_ddd_index/?code=", atcs, "&showdescription=no")
  u[is.na(atcs)] <- NA_character_
  names(u) <- av_name(av)
-  
+
  NAs <- av_name(av, tolower = TRUE, language = NULL)[!is.na(av) & is.na(atcs)]
  if (length(NAs) > 0) {
    warning_("in `av_url()`: no ATC code available for ", vector_and(NAs, quotes = FALSE), ".")
  }
-  
+
  if (open == TRUE) {
    if (length(u) > 1 && !is.na(u[1L])) {
      warning_("in `av_url()`: only the first URL will be opened, as `browseURL()` only suports one string.")
@@ -252,7 +252,7 @@ av_url <- function(x, open = FALSE, ...) {
 av_property <- function(x, property = "name", language = get_AMR_locale(), ...) {
  meet_criteria(x, allow_NA = TRUE)
  meet_criteria(property, is_in = colnames(AMR::antivirals), has_length = 1)
-  meet_criteria(language, is_in = c(LANGUAGES_SUPPORTED, ""), has_length = 1, allow_NULL = TRUE, allow_NA = TRUE)
+  language <- validate_language(language)
  translate_into_language(av_validate(x = x, property = property, ...), language = language)
 }

@@ -264,9 +264,9 @@ av_validate <- function(x, property, ...) {
    # try to catch an error when inputting an invalid argument
    # so the 'call.' can be set to FALSE
    tryCatch(x[1L] %in% AMR_env$AV_lookup[1, property, drop = TRUE],
-             error = function(e) stop(e$message, call. = FALSE)
+      error = function(e) stop(e$message, call. = FALSE)
    )
-    
+
    if (!all(x %in% AMR_env$AV_lookup[, property, drop = TRUE])) {
      x <- as.av(x, ...)
      if (all(is.na(x)) && is.list(AMR_env$AV_lookup[, property, drop = TRUE])) {
@@ -276,7 +276,7 @@ av_validate <- function(x, property, ...) {
      }
    }
  }
-  
+
  if (property == "av") {
    return(set_clean_class(x, new_class = c("av", "character")))
  } else if (property == "cid") {
@@ -31,7 +31,7 @@
 #'
 #' Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. [susceptibility()] and [resistance()].
 #' @param tbl a [data.frame] or [list]
-#' @param width number of characters to present the visual availability, defaults to filling the width of the console
+#' @param width number of characters to present the visual availability - the default is filling the width of the console
 #' @details The function returns a [data.frame] with columns `"resistant"` and `"visual_resistance"`. The values in that columns are calculated with [resistance()].
 #' @return [data.frame] with column names of `tbl` as row names
 #' @export
@@ -31,19 +31,23 @@
 #'
 #' Determine antimicrobial resistance (AMR) of all bug-drug combinations in your data set where at least 30 (default) isolates are available per species. Use [format()] on the result to prettify it to a publishable/printable format, see *Examples*.
 #' @inheritParams eucast_rules
-#' @param combine_SI a [logical] to indicate whether values S and I should be summed, so resistance will be based on only R, defaults to `TRUE`
+#' @param combine_SI a [logical] to indicate whether values S and I should be summed, so resistance will be based on only R - the default is `TRUE`
 #' @param add_ab_group a [logical] to indicate where the group of the antimicrobials must be included as a first column
 #' @param remove_intrinsic_resistant [logical] to indicate that rows and columns with 100% resistance for all tested antimicrobials must be removed from the table
-#' @param FUN the function to call on the `mo` column to transform the microorganism codes, defaults to [mo_shortname()]
+#' @param FUN the function to call on the `mo` column to transform the microorganism codes - the default is [mo_shortname()]
 #' @param translate_ab a [character] of length 1 containing column names of the [antibiotics] data set
 #' @param ... arguments passed on to `FUN`
 #' @inheritParams sir_df
 #' @inheritParams base::formatC
-#' @details The function [format()] calculates the resistance per bug-drug combination. Use `combine_SI = TRUE` (default) to test R vs. S+I and `combine_SI = FALSE` to test R+I vs. S.
+#' @details The function [format()] calculates the resistance per bug-drug combination and returns a table ready for reporting/publishing. Use `combine_SI = TRUE` (default) to test R vs. S+I and `combine_SI = FALSE` to test R+I vs. S. This table can also directly be used in R Markdown / Quarto without the need for e.g. [knitr::kable()].
 #' @export
 #' @rdname bug_drug_combinations
 #' @return The function [bug_drug_combinations()] returns a [data.frame] with columns "mo", "ab", "S", "I", "R" and "total".
 #' @examples
+#' # example_isolates is a data set available in the AMR package.
+#' # run ?example_isolates for more info.
+#' example_isolates
+#'
 #' \donttest{
 #' x <- bug_drug_combinations(example_isolates)
 #' head(x)
@@ -67,7 +71,7 @@ bug_drug_combinations <- function(x,
                                  col_mo = NULL,
                                  FUN = mo_shortname,
                                  ...) {
-  meet_criteria(x, allow_class = "data.frame", contains_column_class = "sir")
+  meet_criteria(x, allow_class = "data.frame", contains_column_class = c("sir", "rsi"))
  meet_criteria(col_mo, allow_class = "character", is_in = colnames(x), has_length = 1, allow_NULL = TRUE)
  meet_criteria(FUN, allow_class = "function", has_length = 1)

@@ -89,7 +93,7 @@ bug_drug_combinations <- function(x,
  # select only groups and antibiotics
  if (is_null_or_grouped_tbl(x.bak)) {
    data_has_groups <- TRUE
-    groups <- setdiff(names(attributes(x.bak)$groups), ".rows")
+    groups <- get_group_names(x.bak)
    x <- x[, c(groups, col_mo, colnames(x)[vapply(FUN.VALUE = logical(1), x, is.sir)]), drop = FALSE]
  } else {
    data_has_groups <- FALSE
@@ -120,7 +124,7 @@ bug_drug_combinations <- function(x,
        m <- as.matrix(table(x))
        data.frame(S = m["S", ], I = m["I", ], R = m["R", ], stringsAsFactors = FALSE)
      })
-      merged <- do.call(rbind, pivot)
+      merged <- do.call(rbind_AMR, pivot)
      out_group <- data.frame(
        mo = rep(unique_mo[i], NROW(merged)),
        ab = rownames(merged),
@@ -140,14 +144,14 @@ bug_drug_combinations <- function(x,
        }
        out_group <- cbind(group_values, out_group)
      }
-      out <- rbind(out, out_group, stringsAsFactors = FALSE)
+      out <- rbind_AMR(out, out_group)
    }
    out
  }
  # based on pm_apply_grouped_function
  apply_group <- function(.data, fn, groups, drop = FALSE, ...) {
    grouped <- pm_split_into_groups(.data, groups, drop)
-    res <- do.call(rbind, unname(lapply(grouped, fn, ...)))
+    res <- do.call(rbind_AMR, unname(lapply(grouped, fn, ...)))
    if (any(groups %in% colnames(res))) {
      class(res) <- c("grouped_data", class(res))
      res <- pm_set_groups(res, groups[groups %in% colnames(res)])
@@ -160,8 +164,9 @@ bug_drug_combinations <- function(x,
  } else {
    out <- run_it(x)
  }
-  rownames(out) <- NULL
+  out <- out %pm>% pm_arrange(mo, ab)
  out <- as_original_data_class(out, class(x.bak)) # will remove tibble groups
+  rownames(out) <- NULL
  structure(out, class = c("bug_drug_combinations", ifelse(data_has_groups, "grouped", character(0)), class(out)))
 }

@@ -181,7 +186,7 @@ format.bug_drug_combinations <- function(x,
  meet_criteria(x, allow_class = "data.frame")
  meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
  language <- validate_language(language)
-  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
+  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
  meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
  meet_criteria(add_ab_group, allow_class = "logical", has_length = 1)
  meet_criteria(remove_intrinsic_resistant, allow_class = "logical", has_length = 1)
@@ -322,7 +327,15 @@ format.bug_drug_combinations <- function(x,
  }

  rownames(y) <- NULL
-  as_original_data_class(y, class(x.bak)) # will remove tibble groups
+  as_original_data_class(y, class(x.bak), extra_class = "formatted_bug_drug_combinations") # will remove tibble groups
+}
+
+# will be exported in zzz.R
+knit_print.formatted_bug_drug_combinations <- function(x, ...) {
+  stop_ifnot_installed("knitr")
+  # make columns with MO names italic according to nomenclature
+  colnames(x)[3:NCOL(x)] <- italicise_taxonomy(colnames(x)[3:NCOL(x)], type = "markdown")
+  knitr::asis_output(paste("", "", knitr::kable(x, ...), collapse = "\n"))
 }

 #' @method print bug_drug_combinations
@@ -31,33 +31,32 @@
 #'
 #' With [add_custom_antimicrobials()] you can add your own custom antimicrobial drug names and codes.
 #' @param x a [data.frame] resembling the [antibiotics] data set, at least containing columns "ab" and "name"
-#' @details **Important:** Due to how \R works, the [add_custom_antimicrobials()] function has to be run in every \R session - added antimicrobials are not stored between sessions and are thus lost when \R is exited. 
-#' 
-#' There are two ways to automate this process:
-#' 
-#' **Method 1:** Save the antimicrobials to a local or remote file (can even be the internet). To use this method:
-#' 
+#' @details **Important:** Due to how \R works, the [add_custom_antimicrobials()] function has to be run in every \R session - added antimicrobials are not stored between sessions and are thus lost when \R is exited.
+#'
+#' There are two ways to circumvent this and automate the process of adding antimicrobials:
+#'
+#' **Method 1:** Using the [package option][AMR-options] [`AMR_custom_ab`][AMR-options], which is the preferred method. To use this method:
+#'
 #'    1. Create a data set in the structure of the [antibiotics] data set (containing at the very least columns "ab" and "name") and save it with [saveRDS()] to a location of choice, e.g. `"~/my_custom_ab.rds"`, or any remote location.
-#'    
-#'    2. Set the file location to the `AMR_custom_ab` \R option: `options(AMR_custom_ab = "~/my_custom_ab.rds")`. This can even be a remote file location, such as an https URL. Since options are not saved between \R sessions, it is best to save this option to the `.Rprofile` file so that it will loaded on start-up of \R. To do this, open the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`, add this text and save the file:
+#'
+#'    2. Set the file location to the [package option][AMR-options] [`AMR_custom_ab`][AMR-options]: `options(AMR_custom_ab = "~/my_custom_ab.rds")`. This can even be a remote file location, such as an https URL. Since options are not saved between \R sessions, it is best to save this option to the `.Rprofile` file so that it will be loaded on start-up of \R. To do this, open the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`, add this text and save the file:
 #'
 #'       ```r
-#'       # Add custom antibiotic drug codes:
+#'       # Add custom antimicrobial codes:
 #'       options(AMR_custom_ab = "~/my_custom_ab.rds")
 #'       ```
-#'       
+#'
 #'       Upon package load, this file will be loaded and run through the [add_custom_antimicrobials()] function.
-#' 
-#' **Method 2:** Save the antimicrobial additions directly to your `.Rprofile` file. An important downside is that this requires to load the `AMR` package at every start-up. To use this method:
-#' 
+#'
+#' **Method 2:** Loading the antimicrobial additions directly from your `.Rprofile` file. Note that the definitions will be stored in a user-specific \R file, which is a suboptimal workflow. To use this method:
+#'
 #'    1. Edit the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`.
 #'
 #'    2. Add a text like below and save the file:
 #'
 #'       ```r
 #'        # Add custom antibiotic drug codes:
-#'        library(AMR)
-#'        add_custom_antimicrobials(
+#'        AMR::add_custom_antimicrobials(
 #'          data.frame(ab = "TESTAB",
 #'                     name = "Test Antibiotic",
 #'                     group = "Test Group")
@@ -139,10 +138,10 @@ add_custom_antimicrobials <- function(x) {
      x[, col] <- as.list(x[, col, drop = TRUE])
    }
  }
-  
+
  AMR_env$custom_ab_codes <- c(AMR_env$custom_ab_codes, x$ab)
  class(AMR_env$AB_lookup$ab) <- "character"
-  
+
  new_df <- AMR_env$AB_lookup[0, , drop = FALSE][seq_len(NROW(x)), , drop = FALSE]
  rownames(new_df) <- NULL
  list_cols <- vapply(FUN.VALUE = logical(1), new_df, is.list)
@@ -154,8 +153,8 @@ add_custom_antimicrobials <- function(x) {
    # assign new values
    new_df[, col] <- x[, col, drop = TRUE]
  }
-  AMR_env$AB_lookup <- unique(rbind(AMR_env$AB_lookup, new_df))
-  
+  AMR_env$AB_lookup <- unique(rbind_AMR(AMR_env$AB_lookup, new_df))
+
  AMR_env$ab_previously_coerced <- AMR_env$ab_previously_coerced[which(!AMR_env$ab_previously_coerced$ab %in% x$ab), , drop = FALSE]
  class(AMR_env$AB_lookup$ab) <- c("ab", "character")
  message_("Added ", nr2char(nrow(x)), " record", ifelse(nrow(x) > 1, "s", ""), " to the internal `antibiotics` data set.")
@@ -240,11 +240,12 @@ print.custom_eucast_rules <- function(x, ...) {
      " (", rule$result_group, ")"
    )
    agents <- sort(agents)
-    rule_if <- word_wrap(paste0(
-      i, ". ", font_bold("If "), font_blue(rule$query), font_bold(" then "),
-      "set to {result}:"
-    ),
-    extra_indent = 5
+    rule_if <- word_wrap(
+      paste0(
+        i, ". ", font_bold("If "), font_blue(rule$query), font_bold(" then "),
+        "set to {result}:"
+      ),
+      extra_indent = 5
    )
    rule_if <- gsub("{result}", val, rule_if, fixed = TRUE)
    rule_then <- paste0("     ", word_wrap(paste0(agents, collapse = ", "), extra_indent = 5))
@@ -32,26 +32,26 @@
 #' With [add_custom_microorganisms()] you can add your own custom microorganisms, such the non-taxonomic outcome of laboratory analysis.
 #' @param x a [data.frame] resembling the [microorganisms] data set, at least containing column "genus" (case-insensitive)
 #' @details This function will fill in missing taxonomy for you, if specific taxonomic columns are missing, see *Examples*.
-#' 
-#' **Important:** Due to how \R works, the [add_custom_microorganisms()] function has to be run in every \R session - added microorganisms are not stored between sessions and are thus lost when \R is exited. 
-#' 
-#' There are two ways to automate this process:
-#' 
-#' **Method 1:** Using the option [`AMR_custom_mo`][AMR-options], which is the preferred method. To use this method:
-#' 
+#'
+#' **Important:** Due to how \R works, the [add_custom_microorganisms()] function has to be run in every \R session - added microorganisms are not stored between sessions and are thus lost when \R is exited.
+#'
+#' There are two ways to circumvent this and automate the process of adding microorganisms:
+#'
+#' **Method 1:** Using the [package option][AMR-options] [`AMR_custom_mo`][AMR-options], which is the preferred method. To use this method:
+#'
 #'    1. Create a data set in the structure of the [microorganisms] data set (containing at the very least column "genus") and save it with [saveRDS()] to a location of choice, e.g. `"~/my_custom_mo.rds"`, or any remote location.
-#'    
-#'    2. Set the file location to the `AMR_custom_mo` \R option: `options(AMR_custom_mo = "~/my_custom_mo.rds")`. This can even be a remote file location, such as an https URL. Since options are not saved between \R sessions, it is best to save this option to the `.Rprofile` file so that it will be loaded on start-up of \R. To do this, open the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`, add this text and save the file:
+#'
+#'    2. Set the file location to the [package option][AMR-options] [`AMR_custom_mo`][AMR-options]: `options(AMR_custom_mo = "~/my_custom_mo.rds")`. This can even be a remote file location, such as an https URL. Since options are not saved between \R sessions, it is best to save this option to the `.Rprofile` file so that it will be loaded on start-up of \R. To do this, open the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`, add this text and save the file:
 #'
 #'       ```r
 #'       # Add custom microorganism codes:
 #'       options(AMR_custom_mo = "~/my_custom_mo.rds")
 #'       ```
-#'       
+#'
 #'       Upon package load, this file will be loaded and run through the [add_custom_microorganisms()] function.
-#' 
-#' **Method 2:** Loading the microorganism directly from your `.Rprofile` file. An important downside is that this requires the `AMR` package to be installed or else this method will fail. To use this method:
-#' 
+#'
+#' **Method 2:** Loading the microorganism directly from your `.Rprofile` file. Note that the definitions will be stored in a user-specific \R file, which is a suboptimal workflow. To use this method:
+#'
 #'    1. Edit the `.Rprofile` file using e.g. `utils::file.edit("~/.Rprofile")`.
 #'
 #'    2. Add a text like below and save the file:
@@ -64,7 +64,7 @@
 #'        )
 #'       ```
 #'
-#' Use [clear_custom_microorganisms()] to clear the previously added antimicrobials.
+#' Use [clear_custom_microorganisms()] to clear the previously added microorganisms.
 #' @seealso [add_custom_antimicrobials()] to add custom antimicrobials.
 #' @rdname add_custom_microorganisms
 #' @export
@@ -77,44 +77,49 @@
 #' # now add a custom entry - it will be considered by as.mo() and
 #' # all mo_*() functions
 #' add_custom_microorganisms(
-#'   data.frame(genus = "Enterobacter",
-#'              species = "asburiae/cloacae"
+#'   data.frame(
+#'     genus = "Enterobacter",
+#'     species = "asburiae/cloacae"
 #'   )
 #' )
 #'
 #' # E. asburiae/cloacae is now a new microorganism:
 #' mo_name("Enterobacter asburiae/cloacae")
-#' 
+#'
 #' # its code:
 #' as.mo("Enterobacter asburiae/cloacae")
-#' 
+#'
 #' # all internal algorithms will work as well:
 #' mo_name("Ent asburia cloacae")
-#' 
+#'
 #' # and even the taxonomy was added based on the genus!
 #' mo_family("E. asburiae/cloacae")
 #' mo_gramstain("Enterobacter asburiae/cloacae")
 #'
 #' mo_info("Enterobacter asburiae/cloacae")
-#' 
-#' 
+#'
+#'
 #' # the function tries to be forgiving:
 #' add_custom_microorganisms(
-#'   data.frame(GENUS = "BACTEROIDES / PARABACTEROIDES SLASHLINE",
-#'              SPECIES = "SPECIES")
+#'   data.frame(
+#'     GENUS = "BACTEROIDES / PARABACTEROIDES SLASHLINE",
+#'     SPECIES = "SPECIES"
+#'   )
 #' )
 #' mo_name("BACTEROIDES / PARABACTEROIDES")
 #' mo_rank("BACTEROIDES / PARABACTEROIDES")
-#' 
+#'
 #' # taxonomy still works, although a slashline genus was given as input:
 #' mo_family("Bacteroides/Parabacteroides")
-#' 
-#' 
+#'
+#'
 #' # for groups and complexes, set them as species or subspecies:
 #' add_custom_microorganisms(
-#'   data.frame(genus = "Citrobacter", 
-#'              species = c("freundii", "braakii complex"),
-#'              subspecies = c("complex", ""))
+#'   data.frame(
+#'     genus = "Citrobacter",
+#'     species = c("freundii", "braakii complex"),
+#'     subspecies = c("complex", "")
+#'   )
 #' )
 #' mo_name(c("C. freundii complex", "C. braakii complex"))
 #' mo_species(c("C. freundii complex", "C. braakii complex"))
@@ -123,9 +128,9 @@
 add_custom_microorganisms <- function(x) {
  meet_criteria(x, allow_class = "data.frame")
  stop_ifnot("genus" %in% tolower(colnames(x)), paste0("`x` must contain column 'genus'."))
-  
+
  add_MO_lookup_to_AMR_env()
-  
+
  # remove any extra class/type, such as grouped tbl, or data.table:
  x <- as.data.frame(x, stringsAsFactors = FALSE)
  colnames(x) <- tolower(colnames(x))
@@ -135,7 +140,7 @@ add_custom_microorganisms <- function(x) {
  }
  # keep only columns available in the microorganisms data set
  x <- x[, colnames(AMR_env$MO_lookup)[colnames(AMR_env$MO_lookup) %in% colnames(x)], drop = FALSE]
-  
+
  # clean the input ----
  for (col in c("genus", "species", "subspecies")) {
    if (!col %in% colnames(x)) {
@@ -152,7 +157,7 @@ add_custom_microorganisms <- function(x) {
    col_ <- gsub(" *([/-]) *", "\\1", col_, perl = TRUE)
    # groups are in our taxonomic table with a capital G
    col_ <- gsub(" group( |$)", " Group\\1", col_, perl = TRUE)
-    
+
    col_[is.na(col_)] <- ""
    if (col == "genus") {
      substr(col_, 1, 1) <- toupper(substr(col_, 1, 1))
@@ -163,19 +168,27 @@ add_custom_microorganisms <- function(x) {
    x[, col] <- col_
  }
  # if subspecies is a group or complex, add it to the species and empty the subspecies
-  x$species[which(x$subspecies %in% c("group", "Group", "complex"))] <- paste(x$species[which(x$subspecies %in% c("group", "Group", "complex"))],
-                                                                              x$subspecies[which(x$subspecies %in% c("group", "Group", "complex"))])
+  x$species[which(x$subspecies %in% c("group", "Group", "complex"))] <- paste(
+    x$species[which(x$subspecies %in% c("group", "Group", "complex"))],
+    x$subspecies[which(x$subspecies %in% c("group", "Group", "complex"))]
+  )
  x$subspecies[which(x$subspecies %in% c("group", "Group", "complex"))] <- ""
-  
+
  if ("rank" %in% colnames(x)) {
-    stop_ifnot(all(x$rank %in% AMR_env$MO_lookup$rank),
-               "the 'rank' column can only contain these values: ", vector_or(AMR_env$MO_lookup$rank))
+    stop_ifnot(
+      all(x$rank %in% AMR_env$MO_lookup$rank),
+      "the 'rank' column can only contain these values: ", vector_or(AMR_env$MO_lookup$rank)
+    )
  } else {
    x$rank <- ifelse(x$subspecies != "", "subspecies",
-                     ifelse(x$species != "", "species",
-                            ifelse(x$genus != "", "genus",
-                                   stop("in add_custom_microorganisms(): only microorganisms up to the genus level can be added",
-                                        call. = FALSE))))
+      ifelse(x$species != "", "species",
+        ifelse(x$genus != "", "genus",
+          stop("in add_custom_microorganisms(): only microorganisms up to the genus level can be added",
+            call. = FALSE
+          )
+        )
+      )
+    )
  }
  x$source <- "Added by user"
  if (!"fullname" %in% colnames(x)) {
@@ -191,7 +204,7 @@ add_custom_microorganisms <- function(x) {
  x$class[is.na(x$class)] <- ""
  x$order[is.na(x$order)] <- ""
  x$family[is.na(x$family)] <- ""
-  
+
  for (col in colnames(x)) {
    if (is.factor(x[, col, drop = TRUE])) {
      x[, col] <- as.character(x[, col, drop = TRUE])
@@ -200,7 +213,7 @@ add_custom_microorganisms <- function(x) {
      x[, col] <- as.list(x[, col, drop = TRUE])
    }
  }
-  
+
  # fill in taxonomy based on genus
  genus_to_check <- gsub("^(.*)[^a-zA-Z].*", "\\1", x$genus, perl = TRUE)
  x$kingdom[which(x$kingdom == "" & genus_to_check != "")] <- AMR_env$MO_lookup$kingdom[match(genus_to_check[which(x$kingdom == "" & genus_to_check != "")], AMR_env$MO_lookup$genus)]
@@ -208,7 +221,7 @@ add_custom_microorganisms <- function(x) {
  x$class[which(x$class == "" & genus_to_check != "")] <- AMR_env$MO_lookup$class[match(genus_to_check[which(x$class == "" & genus_to_check != "")], AMR_env$MO_lookup$genus)]
  x$order[which(x$order == "" & genus_to_check != "")] <- AMR_env$MO_lookup$order[match(genus_to_check[which(x$order == "" & genus_to_check != "")], AMR_env$MO_lookup$genus)]
  x$family[which(x$family == "" & genus_to_check != "")] <- AMR_env$MO_lookup$family[match(genus_to_check[which(x$family == "" & genus_to_check != "")], AMR_env$MO_lookup$genus)]
-  
+
  # fill in other columns that are used in internal algorithms
  x$prevalence <- NA_real_
  x$prevalence[which(genus_to_check != "")] <- AMR_env$MO_lookup$prevalence[match(genus_to_check[which(genus_to_check != "")], AMR_env$MO_lookup$genus)]
@@ -222,7 +235,7 @@ add_custom_microorganisms <- function(x) {
  x$full_first <- substr(x$fullname_lower, 1, 1)
  x$species_first <- tolower(substr(x$species, 1, 1))
  x$subspecies_first <- tolower(substr(x$subspecies, 1, 1))
-  
+
  if (!"mo" %in% colnames(x)) {
    # create the mo code
    x$mo <- NA_character_
@@ -230,19 +243,27 @@ add_custom_microorganisms <- function(x) {
  x$mo <- trimws2(as.character(x$mo))
  x$mo[x$mo == ""] <- NA_character_
  current <- sum(AMR_env$MO_lookup$source == "Added by user", na.rm = TRUE)
-  x$mo[is.na(x$mo)] <- paste0("CUSTOM",
-                              seq.int(from = current + 1, to = current + nrow(x), by = 1),
-                              "_",
-                              toupper(unname(abbreviate(gsub(" +", " _ ",
-                                                             gsub("[^A-Za-z0-9-]", " ",
-                                                                  trimws2(paste(x$genus, x$species, x$subspecies)))),
-                                                        minlength = 10))))
+  x$mo[is.na(x$mo)] <- paste0(
+    "CUSTOM",
+    seq.int(from = current + 1, to = current + nrow(x), by = 1),
+    "_",
+    toupper(unname(abbreviate(
+      gsub(
+        " +", " _ ",
+        gsub(
+          "[^A-Za-z0-9-]", " ",
+          trimws2(paste(x$genus, x$species, x$subspecies))
+        )
+      ),
+      minlength = 10
+    )))
+  )
  stop_if(anyDuplicated(c(as.character(AMR_env$MO_lookup$mo), x$mo)), "MO codes must be unique and not match existing MO codes of the AMR package")
-  
+
  # add to package ----
  AMR_env$custom_mo_codes <- c(AMR_env$custom_mo_codes, x$mo)
  class(AMR_env$MO_lookup$mo) <- "character"
-  
+
  new_df <- AMR_env$MO_lookup[0, , drop = FALSE][seq_len(NROW(x)), , drop = FALSE]
  rownames(new_df) <- NULL
  list_cols <- vapply(FUN.VALUE = logical(1), new_df, is.list)
@@ -254,11 +275,11 @@ add_custom_microorganisms <- function(x) {
    # assign new values
    new_df[, col] <- x[, col, drop = TRUE]
  }
-  
+
  # clear previous coercions
  suppressMessages(mo_reset_session())
-  
-  AMR_env$MO_lookup <- unique(rbind(AMR_env$MO_lookup, new_df))
+
+  AMR_env$MO_lookup <- unique(rbind_AMR(AMR_env$MO_lookup, new_df))
  class(AMR_env$MO_lookup$mo) <- c("mo", "character")
  if (nrow(x) <= 3) {
    message_("Added ", vector_and(italicise(x$fullname), quotes = FALSE), " to the internal `microorganisms` data set.")
@@ -271,11 +292,14 @@ add_custom_microorganisms <- function(x) {
 #' @export
 clear_custom_microorganisms <- function() {
  n <- nrow(AMR_env$MO_lookup)
-  
+
  # reset
  AMR_env$MO_lookup <- NULL
  add_MO_lookup_to_AMR_env()
-  
+
+  # clear previous coercions
+  suppressMessages(mo_reset_session())
+
  n2 <- nrow(AMR_env$MO_lookup)
  AMR_env$custom_mo_codes <- character(0)
  AMR_env$mo_previously_coerced <- AMR_env$mo_previously_coerced[which(AMR_env$mo_previously_coerced$mo %in% AMR_env$MO_lookup$mo), , drop = FALSE]
@@ -27,7 +27,7 @@
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #

-#' Data Sets with `r format(nrow(antibiotics) + nrow(antivirals), big.mark = ",")` Antimicrobial Drugs
+#' Data Sets with `r format(nrow(antibiotics) + nrow(antivirals), big.mark = " ")` Antimicrobial Drugs
 #'
 #' Two data sets containing all antibiotics/antimycotics and antivirals. Use [as.ab()] or one of the [`ab_*`][ab_property()] functions to retrieve values from the [antibiotics] data set. Three identifiers are included in this data set: an antibiotic ID (`ab`, primarily used in this package) as defined by WHONET/EARS-Net, an ATC code (`atc`) as defined by the WHO, and a Compound ID (`cid`) as found in PubChem. Other properties in this data set are derived from one or more of these codes. Note that some drugs have multiple ATC codes.
 #' @format
@@ -65,10 +65,10 @@
 #'
 #' ### Direct download
 #' Like all data sets in this package, these data sets are publicly available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. Please visit [our website for the download links](https://msberends.github.io/AMR/articles/datasets.html). The actual files are of course available on [our GitHub repository](https://github.com/msberends/AMR/tree/main/data-raw).
-#' @source 
-#' 
+#' @source
+#'
 #' * World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology (WHOCC): <https://www.whocc.no/atc_ddd_index/>
-#' 
+#'
 #' * `r TAXONOMY_VERSION$LOINC$citation` Accessed from <`r TAXONOMY_VERSION$LOINC$url`> on `r documentation_date(TAXONOMY_VERSION$LOINC$accessed_date)`.
 #'
 #' * European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: <https://ec.europa.eu/health/documents/community-register/html/reg_hum_atc.htm>
@@ -82,10 +82,10 @@
 #' @rdname antibiotics
 "antivirals"

-#' Data Set with `r format(nrow(microorganisms), big.mark = ",")` Microorganisms
+#' Data Set with `r format(nrow(microorganisms), big.mark = " ")` Microorganisms
 #'
 #' A data set containing the full microbial taxonomy (**last updated: `r documentation_date(max(TAXONOMY_VERSION$GBIF$accessed_date, TAXONOMY_VERSION$LPSN$accessed_date))`**) of `r nr2char(length(unique(microorganisms$kingdom[!microorganisms$kingdom %like% "unknown"])))` kingdoms from the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF). This data set is the backbone of this `AMR` package. MO codes can be looked up using [as.mo()].
-#' @format A [tibble][tibble::tibble] with `r format(nrow(microorganisms), big.mark = ",")` observations and `r ncol(microorganisms)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(microorganisms), big.mark = " ")` observations and `r ncol(microorganisms)` variables:
 #' - `mo`\cr ID of microorganism as used by this package
 #' - `fullname`\cr Full name, like `"Escherichia coli"`. For the taxonomic ranks genus, species and subspecies, this is the 'pasted' text of genus, species, and subspecies. For all taxonomic ranks higher than genus, this is the name of the taxon.
 #' - `status` \cr Status of the taxon, either `r vector_or(microorganisms$status)`
@@ -141,19 +141,19 @@
 #' * `r TAXONOMY_VERSION$GBIF$citation` Accessed from <`r TAXONOMY_VERSION$GBIF$url`> on `r documentation_date(TAXONOMY_VERSION$GBIF$accessed_date)`.
 #'
 #' * `r TAXONOMY_VERSION$SNOMED$citation` URL: <`r TAXONOMY_VERSION$SNOMED$url`>
-#' 
+#'
 #' * Grimont *et al.* (2007). Antigenic Formulae of the Salmonella Serovars, 9th Edition. WHO Collaborating Centre for Reference and Research on *Salmonella* (WHOCC-SALM).
-#' 
+#'
 #' * Bartlett *et al.* (2022). **A comprehensive list of bacterial pathogens infecting humans** *Microbiology* 168:001269; \doi{10.1099/mic.0.001269}
 #' @seealso [as.mo()], [mo_property()], [microorganisms.codes], [intrinsic_resistant]
 #' @examples
 #' microorganisms
 "microorganisms"

-#' Data Set with `r format(nrow(microorganisms.codes), big.mark = ",")` Common Microorganism Codes
+#' Data Set with `r format(nrow(microorganisms.codes), big.mark = " ")` Common Microorganism Codes
 #'
 #' A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with [set_mo_source()]. They will all be searched when using [as.mo()] and consequently all the [`mo_*`][mo_property()] functions.
-#' @format A [tibble][tibble::tibble] with `r format(nrow(microorganisms.codes), big.mark = ",")` observations and `r ncol(microorganisms.codes)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(microorganisms.codes), big.mark = " ")` observations and `r ncol(microorganisms.codes)` variables:
 #' - `code`\cr Commonly used code of a microorganism
 #' - `mo`\cr ID of the microorganism in the [microorganisms] data set
 #' @details
@@ -163,10 +163,10 @@
 #' microorganisms.codes
 "microorganisms.codes"

-#' Data Set with `r format(nrow(example_isolates), big.mark = ",")` Example Isolates
+#' Data Set with `r format(nrow(example_isolates), big.mark = " ")` Example Isolates
 #'
-#' A data set containing `r format(nrow(example_isolates), big.mark = ",")` microbial isolates with their full antibiograms. This data set contains randomised fictitious data, but reflects reality and can be used to practise AMR data analysis. For examples, please read [the tutorial on our website](https://msberends.github.io/AMR/articles/AMR.html).
-#' @format A [tibble][tibble::tibble] with `r format(nrow(example_isolates), big.mark = ",")` observations and `r ncol(example_isolates)` variables:
+#' A data set containing `r format(nrow(example_isolates), big.mark = " ")` microbial isolates with their full antibiograms. This data set contains randomised fictitious data, but reflects reality and can be used to practise AMR data analysis. For examples, please read [the tutorial on our website](https://msberends.github.io/AMR/articles/AMR.html).
+#' @format A [tibble][tibble::tibble] with `r format(nrow(example_isolates), big.mark = " ")` observations and `r ncol(example_isolates)` variables:
 #' - `date`\cr Date of receipt at the laboratory
 #' - `patient`\cr ID of the patient
 #' - `age`\cr Age of the patient
@@ -182,8 +182,8 @@

 #' Data Set with Unclean Data
 #'
-#' A data set containing `r format(nrow(example_isolates_unclean), big.mark = ",")` microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice.
-#' @format A [tibble][tibble::tibble] with `r format(nrow(example_isolates_unclean), big.mark = ",")` observations and `r ncol(example_isolates_unclean)` variables:
+#' A data set containing `r format(nrow(example_isolates_unclean), big.mark = " ")` microbial isolates that are not cleaned up and consequently not ready for AMR data analysis. This data set can be used for practice.
+#' @format A [tibble][tibble::tibble] with `r format(nrow(example_isolates_unclean), big.mark = " ")` observations and `r ncol(example_isolates_unclean)` variables:
 #' - `patient_id`\cr ID of the patient
 #' - `date`\cr date of receipt at the laboratory
 #' - `hospital`\cr ID of the hospital, from A to C
@@ -195,10 +195,10 @@
 #' example_isolates_unclean
 "example_isolates_unclean"

-#' Data Set with `r format(nrow(WHONET), big.mark = ",")` Isolates - WHONET Example
+#' Data Set with `r format(nrow(WHONET), big.mark = " ")` Isolates - WHONET Example
 #'
-#' This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antibiotic results are from our [example_isolates] data set. All patient names are created using online surname generators and are only in place for practice purposes.
-#' @format A [tibble][tibble::tibble] with `r format(nrow(WHONET), big.mark = ",")` observations and `r ncol(WHONET)` variables:
+#' This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The antibiotic results are from our [example_isolates] data set. All patient names were created using online surname generators and are only in place for practice purposes.
+#' @format A [tibble][tibble::tibble] with `r format(nrow(WHONET), big.mark = " ")` observations and `r ncol(WHONET)` variables:
 #' - `Identification number`\cr ID of the sample
 #' - `Specimen number`\cr ID of the specimen
 #' - `Organism`\cr Name of the microorganism. Before analysis, you should transform this to a valid microbial class, using [as.mo()].
@@ -234,7 +234,7 @@
 #' Data Set with Clinical Breakpoints for SIR Interpretation
 #'
 #' Data set containing clinical breakpoints to interpret MIC and disk diffusion to SIR values, according to international guidelines. Currently implemented guidelines are EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`). Use [as.sir()] to transform MICs or disks measurements to SIR values.
-#' @format A [tibble][tibble::tibble] with `r format(nrow(clinical_breakpoints), big.mark = ",")` observations and `r ncol(clinical_breakpoints)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(clinical_breakpoints), big.mark = " ")` observations and `r ncol(clinical_breakpoints)` variables:
 #' - `guideline`\cr Name of the guideline
 #' - `method`\cr Either `r vector_or(clinical_breakpoints$method)`
 #' - `site`\cr Body site, e.g. "Oral" or "Respiratory"
@@ -258,7 +258,7 @@
 #' Data Set with Bacterial Intrinsic Resistance
 #'
 #' Data set containing defined intrinsic resistance by EUCAST of all bug-drug combinations.
-#' @format A [tibble][tibble::tibble] with `r format(nrow(intrinsic_resistant), big.mark = ",")` observations and `r ncol(intrinsic_resistant)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(intrinsic_resistant), big.mark = " ")` observations and `r ncol(intrinsic_resistant)` variables:
 #' - `mo`\cr Microorganism ID
 #' - `ab`\cr Antibiotic ID
 #' @details
@@ -275,7 +275,7 @@
 #' Data Set with Treatment Dosages as Defined by EUCAST
 #'
 #' EUCAST breakpoints used in this package are based on the dosages in this data set. They can be retrieved with [eucast_dosage()].
-#' @format A [tibble][tibble::tibble] with `r format(nrow(dosage), big.mark = ",")` observations and `r ncol(dosage)` variables:
+#' @format A [tibble][tibble::tibble] with `r format(nrow(dosage), big.mark = " ")` observations and `r ncol(dosage)` variables:
 #' - `ab`\cr Antibiotic ID as used in this package (such as `AMC`), using the official EARS-Net (European Antimicrobial Resistance Surveillance Network) codes where available
 #' - `name`\cr Official name of the antimicrobial drug as used by WHONET/EARS-Net or the WHO
 #' - `type`\cr Type of the dosage, either `r vector_or(dosage$type)`
@@ -120,13 +120,13 @@ as.disk <- function(x, na.rm = FALSE) {
        vector_and(quotes = TRUE)
      cur_col <- get_current_column()
      warning_("in `as.disk()`: ", na_after - na_before, " result",
-               ifelse(na_after - na_before > 1, "s", ""),
-               ifelse(is.null(cur_col), "", paste0(" in column '", cur_col, "'")),
-               " truncated (",
-               round(((na_after - na_before) / length(x)) * 100),
-               "%) that were invalid disk zones: ",
-               list_missing,
-               call = FALSE
+        ifelse(na_after - na_before > 1, "s", ""),
+        ifelse(is.null(cur_col), "", paste0(" in column '", cur_col, "'")),
+        " truncated (",
+        round(((na_after - na_before) / length(x)) * 100),
+        "%) that were invalid disk zones: ",
+        list_missing,
+        call = FALSE
      )
    }
  }
@@ -1,212 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# AMR: An R Package for Working with Antimicrobial Resistance Data     #
-#                                                                      #
-# SOURCE                                                               #
-# https://github.com/msberends/AMR                                     #
-#                                                                      #
-# CITE AS                                                              #
-# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C    #
-# (2022). AMR: An R Package for Working with Antimicrobial Resistance  #
-# Data. Journal of Statistical Software, 104(3), 1-31.                 #
-# doi:10.18637/jss.v104.i03                                            #
-#                                                                      #
-# Developed at the University of Groningen and the University Medical  #
-# Center Groningen in The Netherlands, in collaboration with many      #
-# colleagues from around the world, see our website.                   #
-#                                                                      #
-# This R package is free software; you can freely use and distribute   #
-# it for both personal and commercial purposes under the terms of the  #
-# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
-# the Free Software Foundation.                                        #
-# We created this package for both routine data analysis and academic  #
-# research and it was publicly released in the hope that it will be    #
-# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
-#                                                                      #
-# Visit our website for the full manual and a complete tutorial about  #
-# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
-# ==================================================================== #
-
-#' Determine (New) Episodes for Patients
-#'
-#' These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument `episode_days`. This can be used to determine clinical episodes for any epidemiological analysis. The [get_episode()] function returns the index number of the episode per group, while the [is_new_episode()] function returns values `TRUE`/`FALSE` to indicate whether an item in a vector is the start of a new episode.
-#' @param x vector of dates (class `Date` or `POSIXt`), will be sorted internally to determine episodes
-#' @param episode_days required episode length in days, can also be less than a day or `Inf`, see *Details*
-#' @param ... ignored, only in place to allow future extensions
-#' @details
-#' Dates are first sorted from old to new. The oldest date will mark the start of the first episode. After this date, the next date will be marked that is at least `episode_days` days later than the start of the first episode. From that second marked date on, the next date will be marked that is at least `episode_days` days later than the start of the second episode which will be the start of the third episode, and so on. Before the vector is being returned, the original order will be restored.
-#'
-#' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but is more efficient for data sets containing microorganism codes or names and allows for different isolate selection methods.
-#'
-#' The `dplyr` package is not required for these functions to work, but these functions do support [variable grouping][dplyr::group_by()] and work conveniently inside `dplyr` verbs such as [`filter()`][dplyr::filter()], [`mutate()`][dplyr::mutate()] and [`summarise()`][dplyr::summarise()].
-#' @return
-#' * [get_episode()]: a [double] vector
-#' * [is_new_episode()]: a [logical] vector
-#' @seealso [first_isolate()]
-#' @rdname get_episode
-#' @export
-#' @examples
-#' # `example_isolates` is a data set available in the AMR package.
-#' # See ?example_isolates
-#' df <- example_isolates[sample(seq_len(2000), size = 200), ]
-#'
-#' get_episode(df$date, episode_days = 60) # indices
-#' is_new_episode(df$date, episode_days = 60) # TRUE/FALSE
-#'
-#' # filter on results from the third 60-day episode only, using base R
-#' df[which(get_episode(df$date, 60) == 3), ]
-#'
-#' # the functions also work for less than a day, e.g. to include one per hour:
-#' get_episode(c(
-#'   Sys.time(),
-#'   Sys.time() + 60 * 60
-#' ),
-#' episode_days = 1 / 24
-#' )
-#'
-#' \donttest{
-#' if (require("dplyr")) {
-#'   # is_new_episode() can also be used in dplyr verbs to determine patient
-#'   # episodes based on any (combination of) grouping variables:
-#'   df %>%
-#'     mutate(condition = sample(
-#'       x = c("A", "B", "C"),
-#'       size = 200,
-#'       replace = TRUE
-#'     )) %>%
-#'     group_by(condition) %>%
-#'     mutate(new_episode = is_new_episode(date, 365)) %>%
-#'     select(patient, date, condition, new_episode)
-#' }
-#' if (require("dplyr")) {
-#'   df %>%
-#'     group_by(ward, patient) %>%
-#'     transmute(date,
-#'       patient,
-#'       new_index = get_episode(date, 60),
-#'       new_logical = is_new_episode(date, 60)
-#'     )
-#' }
-#' if (require("dplyr")) {
-#'   df %>%
-#'     group_by(ward) %>%
-#'     summarise(
-#'       n_patients = n_distinct(patient),
-#'       n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),
-#'       n_episodes_60 = sum(is_new_episode(date, episode_days = 60)),
-#'       n_episodes_30 = sum(is_new_episode(date, episode_days = 30))
-#'     )
-#' }
-#' if (require("dplyr")) {
-#'
-#'   # grouping on patients and microorganisms leads to the same
-#'   # results as first_isolate() when using 'episode-based':
-#'   x <- df %>%
-#'     filter_first_isolate(
-#'       include_unknown = TRUE,
-#'       method = "episode-based"
-#'     )
-#'
-#'   y <- df %>%
-#'     group_by(patient, mo) %>%
-#'     filter(is_new_episode(date, 365)) %>%
-#'     ungroup()
-#'
-#'   identical(x, y)
-#' }
-#' if (require("dplyr")) {
-#'
-#'   # but is_new_episode() has a lot more flexibility than first_isolate(),
-#'   # since you can now group on anything that seems relevant:
-#'   df %>%
-#'     group_by(patient, mo, ward) %>%
-#'     mutate(flag_episode = is_new_episode(date, 365)) %>%
-#'     select(group_vars(.), flag_episode)
-#' }
-#' }
-get_episode <- function(x, episode_days, ...) {
-  meet_criteria(x, allow_class = c("Date", "POSIXt"), allow_NA = TRUE)
-  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
-
-  exec_episode(
-    x = x,
-    type = "sequential",
-    episode_days = episode_days,
-    ... = ...
-  )
-}
-
-#' @rdname get_episode
-#' @export
-is_new_episode <- function(x, episode_days, ...) {
-  meet_criteria(x, allow_class = c("Date", "POSIXt"), allow_NA = TRUE)
-  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE)
-
-  exec_episode(
-    x = x,
-    type = "logical",
-    episode_days = episode_days,
-    ... = ...
-  )
-}
-
-exec_episode <- function(x, type, episode_days, ...) {
-  x <- as.double(as.POSIXct(x)) # as.POSIXct() required for Date classes
-  # since x is now in seconds, get seconds from episode_days as well
-  episode_seconds <- episode_days * 60 * 60 * 24
-
-  if (length(x) == 1) { # this will also match 1 NA, which is fine
-    if (type == "logical") {
-      return(TRUE)
-    } else if (type == "sequential") {
-      return(1)
-    }
-  } else if (length(x) == 2 && !all(is.na(x))) {
-    if (max(x) - min(x) >= episode_seconds) {
-      if (type == "logical") {
-        return(c(TRUE, TRUE))
-      } else if (type == "sequential") {
-        return(c(1, 2))
-      }
-    } else {
-      if (type == "logical") {
-        return(c(TRUE, FALSE))
-      } else if (type == "sequential") {
-        return(c(1, 1))
-      }
-    }
-  }
-
-  # I asked on StackOverflow:
-  # https://stackoverflow.com/questions/42122245/filter-one-row-every-year
-  run_episodes <- function(x, episode_seconds) {
-    indices <- integer()
-    start <- x[1]
-    ind <- 1
-    indices[1] <- 1
-    for (i in 2:length(x)) {
-      if (isTRUE((x[i] - start) >= episode_seconds)) {
-        ind <- ind + 1
-        if (type == "logical") {
-          indices[ind] <- i
-        }
-        start <- x[i]
-      }
-      if (type == "sequential") {
-        indices[i] <- ind
-      }
-    }
-    if (type == "logical") {
-      result <- rep(FALSE, length(x))
-      result[indices] <- TRUE
-      result
-    } else if (type == "sequential") {
-      indices
-    }
-  }
-
-  ord <- order(x)
-  out <- run_episodes(x[ord], episode_seconds)[order(ord)]
-  out[is.na(x) & ord != 1] <- NA # every NA but the first must remain NA
-  out
-}
@@ -60,16 +60,16 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
 #'
 #' To improve the interpretation of the antibiogram before EUCAST rules are applied, some non-EUCAST rules can applied at default, see *Details*.
 #' @param x a data set with antibiotic columns, such as `amox`, `AMX` and `AMC`
-#' @param info a [logical] to indicate whether progress should be printed to the console, defaults to only print while in interactive sessions
-#' @param rules a [character] vector that specifies which rules should be applied. Must be one or more of `"breakpoints"`, `"expert"`, `"other"`, `"custom"`, `"all"`, and defaults to `c("breakpoints", "expert")`. The default value can be set to another value, e.g. using `options(AMR_eucastrules = "all")`. If using `"custom"`, be sure to fill in argument `custom_rules` too. Custom rules can be created with [custom_eucast_rules()].
+#' @param info a [logical] to indicate whether progress should be printed to the console - the default is only print while in interactive sessions
+#' @param rules a [character] vector that specifies which rules should be applied. Must be one or more of `"breakpoints"`, `"expert"`, `"other"`, `"custom"`, `"all"`, and defaults to `c("breakpoints", "expert")`. The default value can be set to another value using the [package option][AMR-options] [`AMR_eucastrules`][AMR-options]: `options(AMR_eucastrules = "all")`. If using `"custom"`, be sure to fill in argument `custom_rules` too. Custom rules can be created with [custom_eucast_rules()].
 #' @param verbose a [logical] to turn Verbose mode on and off (default is off). In Verbose mode, the function does not apply rules to the data, but instead returns a data set in logbook form with extensive info about which rows and columns would be effected and in which way. Using Verbose mode takes a lot more time.
 #' @param version_breakpoints the version number to use for the EUCAST Clinical Breakpoints guideline. Can be either `r vector_or(names(EUCAST_VERSION_BREAKPOINTS), reverse = TRUE)`.
 #' @param version_expertrules the version number to use for the EUCAST Expert Rules and Intrinsic Resistance guideline. Can be either `r vector_or(names(EUCAST_VERSION_EXPERT_RULES), reverse = TRUE)`.
-#' @param ampc_cephalosporin_resistance a [character] value that should be applied to cefotaxime, ceftriaxone and ceftazidime for AmpC de-repressed cephalosporin-resistant mutants, defaults to `NA`. Currently only works when `version_expertrules` is `3.2` and higher; these version of '*EUCAST Expert Rules on Enterobacterales*' state that results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these three drugs. A value of `NA` (the default) for this argument will remove results for these three drugs, while e.g. a value of `"R"` will make the results for these drugs resistant. Use `NULL` or `FALSE` to not alter results for these three drugs of AmpC de-repressed cephalosporin-resistant mutants. Using `TRUE` is equal to using `"R"`. \cr For *EUCAST Expert Rules* v3.2, this rule applies to: `r vector_and(gsub("[^a-zA-Z ]+", "", unlist(strsplit(EUCAST_RULES_DF[which(EUCAST_RULES_DF$reference.version %in% c(3.2, 3.3) & EUCAST_RULES_DF$reference.rule %like% "ampc"), "this_value"][1], "|", fixed = TRUE))), quotes = "*")`.
+#' @param ampc_cephalosporin_resistance a [character] value that should be applied to cefotaxime, ceftriaxone and ceftazidime for AmpC de-repressed cephalosporin-resistant mutants - the default is `NA`. Currently only works when `version_expertrules` is `3.2` and higher; these version of '*EUCAST Expert Rules on Enterobacterales*' state that results of cefotaxime, ceftriaxone and ceftazidime should be reported with a note, or results should be suppressed (emptied) for these three drugs. A value of `NA` (the default) for this argument will remove results for these three drugs, while e.g. a value of `"R"` will make the results for these drugs resistant. Use `NULL` or `FALSE` to not alter results for these three drugs of AmpC de-repressed cephalosporin-resistant mutants. Using `TRUE` is equal to using `"R"`. \cr For *EUCAST Expert Rules* v3.2, this rule applies to: `r vector_and(gsub("[^a-zA-Z ]+", "", unlist(strsplit(EUCAST_RULES_DF[which(EUCAST_RULES_DF$reference.version %in% c(3.2, 3.3) & EUCAST_RULES_DF$reference.rule %like% "ampc"), "this_value"][1], "|", fixed = TRUE))), quotes = "*")`.
 #' @param ... column name of an antibiotic, see section *Antibiotics* below
 #' @param ab any (vector of) text that can be coerced to a valid antibiotic drug code with [as.ab()]
 #' @param administration route of administration, either `r vector_or(dosage$administration)`
-#' @param only_sir_columns a [logical] to indicate whether only antibiotic columns must be detected that were transformed to class `sir` (see [as.sir()]) on beforehand (defaults to `FALSE`)
+#' @param only_sir_columns a [logical] to indicate whether only antibiotic columns must be detected that were transformed to class `sir` (see [as.sir()]) on beforehand (default is `FALSE`)
 #' @param custom_rules custom rules to apply, created with [custom_eucast_rules()]
 #' @inheritParams first_isolate
 #' @details
@@ -98,7 +98,7 @@ format_eucast_version_nr <- function(version, markdown = TRUE) {
 #'
 #' Important examples include amoxicillin and amoxicillin/clavulanic acid, and trimethoprim and trimethoprim/sulfamethoxazole. Needless to say, for these rules to work, both drugs must be available in the data set.
 #'
-#' Since these rules are not officially approved by EUCAST, they are not applied at default. To use these rules, include `"other"` to the `rules` argument, or use `eucast_rules(..., rules = "all")`. You can also set the option `AMR_eucastrules`, i.e. run `options(AMR_eucastrules = "all")`.
+#' Since these rules are not officially approved by EUCAST, they are not applied at default. To use these rules, include `"other"` to the `rules` argument, or use `eucast_rules(..., rules = "all")`. You can also set the [package option][AMR-options] [`AMR_eucastrules`][AMR-options], i.e. run `options(AMR_eucastrules = "all")`.
 #' @section Antibiotics:
 #' To define antibiotics column names, leave as it is to determine it automatically with [guess_ab_col()] or input a text (case-insensitive), or use `NULL` to skip a column (e.g. `TIC = NULL` to skip ticarcillin). Manually defined but non-existing columns will be skipped with a warning.
 #'
@@ -181,6 +181,7 @@ eucast_rules <- function(x,
  meet_criteria(ampc_cephalosporin_resistance, allow_class = c("logical", "character", "sir"), has_length = 1, allow_NA = TRUE, allow_NULL = TRUE)
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
  meet_criteria(custom_rules, allow_class = "custom_eucast_rules", allow_NULL = TRUE)
+  if ("only_rsi_columns" %in% names(list(...))) only_sir_columns <- list(...)$only_rsi_columns

  add_MO_lookup_to_AMR_env()

@@ -236,7 +237,7 @@ eucast_rules <- function(x,
  }

  decimal.mark <- getOption("OutDec")
-  big.mark <- ifelse(decimal.mark != ",", ",", ".")
+  big.mark <- ifelse(decimal.mark != ",", ",", " ")
  formatnr <- function(x, big = big.mark, dec = decimal.mark) {
    trimws(format(x, big.mark = big, decimal.mark = dec))
  }
@@ -475,7 +476,7 @@ eucast_rules <- function(x,
    amox$base_ab <- "AMX"
    amox$base_name <- ab_name("AMX", language = NULL)
    # merge and sort
-    ab_enzyme <- rbind(ab_enzyme, ampi, amox)
+    ab_enzyme <- rbind_AMR(ab_enzyme, ampi, amox)
    ab_enzyme <- ab_enzyme[order(ab_enzyme$enzyme_name), , drop = FALSE]

    for (i in seq_len(nrow(ab_enzyme))) {
@@ -702,11 +703,12 @@ eucast_rules <- function(x,
      # Print rule  -------------------------------------------------------------
      if (rule_current != rule_previous) {
        # is new rule within group, print its name
-        cat(italicise_taxonomy(word_wrap(rule_current,
-          width = getOption("width") - 30,
-          extra_indent = 6
-        ),
-        type = "ansi"
+        cat(italicise_taxonomy(
+          word_wrap(rule_current,
+            width = getOption("width") - 30,
+            extra_indent = 6
+          ),
+          type = "ansi"
        ))
        warned <- FALSE
      }
@@ -721,21 +723,23 @@ eucast_rules <- function(x,
    if (mo_value %like% "coagulase" && any(x$genus == "Staphylococcus", na.rm = TRUE)) {
      if (mo_value %like% "negative") {
        eucast_rules_df[i, "this_value"] <- paste0(
-          "^(", paste0(all_staph[which(all_staph$CNS_CPS %like% "negative"),
-            "fullname",
-            drop = TRUE
-          ],
-          collapse = "|"
+          "^(", paste0(
+            all_staph[which(all_staph$CNS_CPS %like% "negative"),
+              "fullname",
+              drop = TRUE
+            ],
+            collapse = "|"
          ),
          ")$"
        )
      } else {
        eucast_rules_df[i, "this_value"] <- paste0(
-          "^(", paste0(all_staph[which(all_staph$CNS_CPS %like% "positive"),
-            "fullname",
-            drop = TRUE
-          ],
-          collapse = "|"
+          "^(", paste0(
+            all_staph[which(all_staph$CNS_CPS %like% "positive"),
+              "fullname",
+              drop = TRUE
+            ],
+            collapse = "|"
          ),
          ")$"
        )
@@ -745,11 +749,12 @@ eucast_rules <- function(x,
    # be sure to comprise all beta-haemolytic Streptococci (Lancefield groups A, B, C and G) when they are mentioned
    if (mo_value %like% "group [ABCG]" && any(x$genus == "Streptococcus", na.rm = TRUE)) {
      eucast_rules_df[i, "this_value"] <- paste0(
-        "^(", paste0(all_strep[which(all_strep$Lancefield %like% "group [ABCG]"),
-          "fullname",
-          drop = TRUE
-        ],
-        collapse = "|"
+        "^(", paste0(
+          all_strep[which(all_strep$Lancefield %like% "group [ABCG]"),
+            "fullname",
+            drop = TRUE
+          ],
+          collapse = "|"
        ),
        ")$"
      )
@@ -789,15 +794,17 @@ eucast_rules <- function(x,
      if (length(source_antibiotics) == 0) {
        rows <- integer(0)
      } else if (length(source_antibiotics) == 1) {
-        rows <- tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value &
-          as.sir_no_warning(x[, source_antibiotics[1L]]) == source_value[1L]),
-        error = function(e) integer(0)
+        rows <- tryCatch(
+          which(x[, if_mo_property, drop = TRUE] %like% mo_value &
+            as.sir_no_warning(x[, source_antibiotics[1L]]) == source_value[1L]),
+          error = function(e) integer(0)
        )
      } else if (length(source_antibiotics) == 2) {
-        rows <- tryCatch(which(x[, if_mo_property, drop = TRUE] %like% mo_value &
-          as.sir_no_warning(x[, source_antibiotics[1L]]) == source_value[1L] &
-          as.sir_no_warning(x[, source_antibiotics[2L]]) == source_value[2L]),
-        error = function(e) integer(0)
+        rows <- tryCatch(
+          which(x[, if_mo_property, drop = TRUE] %like% mo_value &
+            as.sir_no_warning(x[, source_antibiotics[1L]]) == source_value[1L] &
+            as.sir_no_warning(x[, source_antibiotics[2L]]) == source_value[2L]),
+          error = function(e) integer(0)
        )
        # nolint start
        # } else if (length(source_antibiotics) == 3) {
@@ -872,11 +879,12 @@ eucast_rules <- function(x,
      )
      if (isTRUE(info)) {
        # print rule
-        cat(italicise_taxonomy(word_wrap(format_custom_query_rule(rule$query, colours = FALSE),
-          width = getOption("width") - 30,
-          extra_indent = 6
-        ),
-        type = "ansi"
+        cat(italicise_taxonomy(
+          word_wrap(format_custom_query_rule(rule$query, colours = FALSE),
+            width = getOption("width") - 30,
+            extra_indent = 6
+          ),
+          type = "ansi"
        ))
        warned <- FALSE
      }
@@ -1117,14 +1125,15 @@ edit_sir <- function(x,
      },
      error = function(e) {
        txt_error()
-        stop(paste0(
-          "In row(s) ", paste(rows[seq_len(min(length(rows), 10))], collapse = ","),
-          ifelse(length(rows) > 10, "...", ""),
-          " while writing value '", to,
-          "' to column(s) `", paste(cols, collapse = "`, `"),
-          "`:\n", e$message
-        ),
-        call. = FALSE
+        stop(
+          paste0(
+            "In row(s) ", paste(rows[seq_len(min(length(rows), 10))], collapse = ","),
+            ifelse(length(rows) > 10, "...", ""),
+            " while writing value '", to,
+            "' to column(s) `", paste(cols, collapse = "`, `"),
+            "`:\n", e$message
+          ),
+          call. = FALSE
        )
      }
    )
@@ -1153,9 +1162,9 @@ edit_sir <- function(x,
        )
        verbose_new <- verbose_new %pm>% pm_filter(old != new | is.na(old) | is.na(new) & !is.na(old))
        # save changes to data set 'verbose_info'
-        track_changes$verbose_info <- rbind(track_changes$verbose_info,
-          verbose_new,
-          stringsAsFactors = FALSE
+        track_changes$verbose_info <- rbind_AMR(
+          track_changes$verbose_info,
+          verbose_new
        )
        # count adds and changes
        track_changes$added <- track_changes$added + verbose_new %pm>%
@@ -1207,11 +1216,11 @@ eucast_dosage <- function(ab, administration = "iv", version_breakpoints = 12.0)
      )
    )
  }
-  out <- do.call("rbind", lapply(lst, as.data.frame, stringsAsFactors = FALSE))
+  out <- do.call(rbind_AMR, lapply(lst, as.data.frame, stringsAsFactors = FALSE))
  rownames(out) <- NULL
  out$ab <- ab
  out$name <- ab_name(ab, language = NULL)
-  if (pkg_is_available("tibble", also_load = FALSE)) {
+  if (pkg_is_available("tibble")) {
    import_fn("as_tibble", "tibble")(out)
  } else {
    out
@@ -31,13 +31,13 @@
 #'
 #' Determine first isolates of all microorganisms of every patient per episode and (if needed) per specimen type. These functions support all four methods as summarised by Hindler *et al.* in 2007 (\doi{10.1086/511864}). To determine patient episodes not necessarily based on microorganisms, use [is_new_episode()] that also supports grouping with the `dplyr` package.
 #' @param x a [data.frame] containing isolates. Can be left blank for automatic determination, see *Examples*.
-#' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column with a date class
-#' @param col_patient_id column name of the unique IDs of the patients, defaults to the first column that starts with 'patient' or 'patid' (case insensitive)
-#' @param col_mo column name of the IDs of the microorganisms (see [as.mo()]), defaults to the first column of class [`mo`]. Values will be coerced using [as.mo()].
+#' @param col_date column name of the result date (or date that is was received on the lab) - the default is the first column with a date class
+#' @param col_patient_id column name of the unique IDs of the patients - the default is the first column that starts with 'patient' or 'patid' (case insensitive)
+#' @param col_mo column name of the names or codes of the microorganisms (see [as.mo()]) - the default is the first column of class [`mo`]. Values will be coerced using [as.mo()].
 #' @param col_testcode column name of the test codes. Use `col_testcode = NULL` to **not** exclude certain test codes (such as test codes for screening). In that case `testcodes_exclude` will be ignored.
 #' @param col_specimen column name of the specimen type or group
 #' @param col_icu column name of the logicals (`TRUE`/`FALSE`) whether a ward or department is an Intensive Care Unit (ICU). This can also be a [logical] vector with the same length as rows in `x`.
-#' @param col_keyantimicrobials (only useful when `method = "phenotype-based"`) column name of the key antimicrobials to determine first isolates, see [key_antimicrobials()]. Defaults to the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use `col_keyantimicrobials = FALSE` to prevent this. Can also be the output of [key_antimicrobials()].
+#' @param col_keyantimicrobials (only useful when `method = "phenotype-based"`) column name of the key antimicrobials to determine first isolates, see [key_antimicrobials()]. The default is the first column that starts with 'key' followed by 'ab' or 'antibiotics' or 'antimicrobials' (case insensitive). Use `col_keyantimicrobials = FALSE` to prevent this. Can also be the output of [key_antimicrobials()].
 #' @param episode_days episode in days after which a genus/species combination will be determined as 'first isolate' again. The default of 365 days is based on the guideline by CLSI, see *Source*.
 #' @param testcodes_exclude a [character] vector with test codes that should be excluded (case-insensitive)
 #' @param icu_exclude a [logical] to indicate whether ICU isolates should be excluded (rows with value `TRUE` in the column set with `col_icu`)
@@ -46,7 +46,7 @@
 #' @param method the method to apply, either `"phenotype-based"`, `"episode-based"`, `"patient-based"` or `"isolate-based"` (can be abbreviated), see *Details*. The default is `"phenotype-based"` if antimicrobial test results are present in the data, and `"episode-based"` otherwise.
 #' @param ignore_I [logical] to indicate whether antibiotic interpretations with `"I"` will be ignored when `type = "keyantimicrobials"`, see *Details*
 #' @param points_threshold minimum number of points to require before differences in the antibiogram will lead to inclusion of an isolate when `type = "points"`, see *Details*
-#' @param info a [logical] to indicate info should be printed, defaults to `TRUE` only in interactive mode
+#' @param info a [logical] to indicate info should be printed - the default is `TRUE` only in interactive mode
 #' @param include_unknown a [logical] to indicate whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
 #' @param include_untested_sir a [logical] to indicate whether also rows without antibiotic results are still eligible for becoming a first isolate. Use `include_untested_sir = FALSE` to always return `FALSE` for such rows. This checks the data set for columns of class `sir` and consequently requires transforming columns with antibiotic results using [as.sir()] first.
 #' @param ... arguments passed on to [first_isolate()] when using [filter_first_isolate()], otherwise arguments passed on to [key_antimicrobials()] (such as `universal`, `gram_negative`, `gram_positive`)
@@ -133,7 +133,7 @@
 #' # `example_isolates` is a data set available in the AMR package.
 #' # See ?example_isolates.
 #'
-#' example_isolates[first_isolate(), ]
+#' example_isolates[first_isolate(info = TRUE), ]
 #' \donttest{
 #' # get all first Gram-negatives
 #' example_isolates[which(first_isolate(info = FALSE) & mo_is_gram_negative()), ]
@@ -141,20 +141,18 @@
 #' if (require("dplyr")) {
 #'   # filter on first isolates using dplyr:
 #'   example_isolates %>%
-#'     filter(first_isolate())
+#'     filter(first_isolate(info = TRUE))
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # short-hand version:
 #'   example_isolates %>%
 #'     filter_first_isolate(info = FALSE)
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # flag the first isolates per group:
 #'   example_isolates %>%
 #'     group_by(ward) %>%
-#'     mutate(first = first_isolate()) %>%
+#'     mutate(first = first_isolate(info = TRUE)) %>%
 #'     select(ward, date, patient, mo, first)
 #' }
 #' }
@@ -179,7 +177,7 @@ first_isolate <- function(x = NULL,
                          include_untested_sir = TRUE,
                          ...) {
  if (is_null_or_grouped_tbl(x)) {
-    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
+    # when `x` is left blank, auto determine it (get_current_data() searches underlying data within call)
    # is also fix for using a grouped df as input (a dot as first argument)
    x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
  }
@@ -228,6 +226,10 @@ first_isolate <- function(x = NULL,
  meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
  meet_criteria(info, allow_class = "logical", has_length = 1)
  meet_criteria(include_unknown, allow_class = "logical", has_length = 1)
+  if ("include_untested_rsi" %in% names(list(...))) {
+    deprecation_warning("include_untested_rsi", "include_untested_sir", is_function = FALSE)
+    include_untested_sir <- list(...)$include_untested_rsi
+  }
  meet_criteria(include_untested_sir, allow_class = "logical", has_length = 1)

  # remove data.table, grouping from tibbles, etc.
@@ -244,18 +246,19 @@ first_isolate <- function(x = NULL,
    method <- "episode-based"
  }
  if (isTRUE(info) && message_not_thrown_before("first_isolate", "method")) {
-    message_(paste0(
-      "Determining first isolates ",
-      ifelse(method %in% c("episode-based", "phenotype-based"),
-        ifelse(is.infinite(episode_days),
-          "without a specified episode length",
-          paste("using an episode length of", episode_days, "days")
-        ),
-        ""
-      )
-    ),
-    as_note = FALSE,
-    add_fn = font_black
+    message_(
+      paste0(
+        "Determining first isolates ",
+        ifelse(method %in% c("episode-based", "phenotype-based"),
+          ifelse(is.infinite(episode_days),
+            "without a specified episode length",
+            paste("using an episode length of", episode_days, "days")
+          ),
+          ""
+        )
+      ),
+      as_note = FALSE,
+      add_fn = font_black
    )
  }

@@ -347,7 +350,7 @@ first_isolate <- function(x = NULL,
  x$newvar_mo <- as.mo(x[, col_mo, drop = TRUE])
  x$newvar_genus_species <- paste(mo_genus(x$newvar_mo), mo_species(x$newvar_mo))
  x$newvar_date <- x[, col_date, drop = TRUE]
-  x$newvar_patient_id <- x[, col_patient_id, drop = TRUE]
+  x$newvar_patient_id <- as.character(x[, col_patient_id, drop = TRUE])

  if (is.null(col_testcode)) {
    testcodes_exclude <- NULL
@@ -375,7 +378,7 @@ first_isolate <- function(x = NULL,
    }
  }
  if (!is.null(col_keyantimicrobials)) {
-    x$newvar_key_ab <- x[, col_keyantimicrobials, drop = TRUE]
+    x$newvar_key_ab <- as.character(x[, col_keyantimicrobials, drop = TRUE])
  }

  if (is.null(testcodes_exclude)) {
@@ -469,15 +472,17 @@ first_isolate <- function(x = NULL,
  x$other_pat_or_mo <- !(x$newvar_patient_id == pm_lag(x$newvar_patient_id) & x$newvar_genus_species == pm_lag(x$newvar_genus_species))

  x$episode_group <- paste(x$newvar_patient_id, x$newvar_genus_species)
-  x$more_than_episode_ago <- unlist(lapply(split(
-    x$newvar_date,
-    x$episode_group
-  ),
-  exec_episode, # this will skip meet_criteria() in is_new_episode(), saving time
-  type = "logical",
-  episode_days = episode_days
-  ),
-  use.names = FALSE
+
+  x$more_than_episode_ago <- unlist(
+    lapply(
+      split(
+        x$newvar_date,
+        x$episode_group
+      ),
+      is_new_episode,
+      episode_days = episode_days
+    ),
+    use.names = FALSE
  )

  if (!is.null(col_keyantimicrobials)) {
@@ -489,24 +494,16 @@ first_isolate <- function(x = NULL,
      ignore_I = ignore_I,
      points_threshold = points_threshold
    )
-    x$newvar_first_isolate <- pm_if_else(
-      x$newvar_row_index_sorted >= row.start &
-        x$newvar_row_index_sorted <= row.end &
-        x$newvar_genus_species != "" &
-        (x$other_pat_or_mo | x$more_than_episode_ago | x$other_key_ab),
-      TRUE,
-      FALSE
-    )
+    x$newvar_first_isolate <- x$newvar_row_index_sorted >= row.start &
+      x$newvar_row_index_sorted <= row.end &
+      x$newvar_genus_species != "" &
+      (x$other_pat_or_mo | x$more_than_episode_ago | x$other_key_ab)
  } else {
    # no key antibiotics
-    x$newvar_first_isolate <- pm_if_else(
-      x$newvar_row_index_sorted >= row.start &
-        x$newvar_row_index_sorted <= row.end &
-        x$newvar_genus_species != "" &
-        (x$other_pat_or_mo | x$more_than_episode_ago),
-      TRUE,
-      FALSE
-    )
+    x$newvar_first_isolate <- x$newvar_row_index_sorted >= row.start &
+      x$newvar_row_index_sorted <= row.end &
+      x$newvar_genus_species != "" &
+      (x$other_pat_or_mo | x$more_than_episode_ago)
  }

  # first one as TRUE
@@ -515,14 +512,17 @@ first_isolate <- function(x = NULL,
  if (!is.null(col_testcode)) {
    x[which(x[, col_testcode] %in% tolower(testcodes_exclude)), "newvar_first_isolate"] <- FALSE
  }
+
  if (!is.null(col_icu)) {
    if (icu_exclude == TRUE) {
-      message_("Excluding ", format(sum(col_icu, na.rm = TRUE), big.mark = ","), " isolates from ICU.",
-        add_fn = font_black,
-        as_note = FALSE
-      )
+      if (isTRUE(info)) {
+        message_("Excluding ", format(sum(col_icu, na.rm = TRUE), big.mark = " "), " isolates from ICU.",
+          add_fn = font_black,
+          as_note = FALSE
+        )
+      }
      x[which(col_icu), "newvar_first_isolate"] <- FALSE
-    } else {
+    } else if (isTRUE(info)) {
      message_("Including isolates from ICU.",
        add_fn = font_black,
        as_note = FALSE
@@ -531,7 +531,7 @@ first_isolate <- function(x = NULL,
  }

  decimal.mark <- getOption("OutDec")
-  big.mark <- ifelse(decimal.mark != ",", ",", ".")
+  big.mark <- ifelse(decimal.mark != ",", ",", " ")

  if (isTRUE(info)) {
    # print group name if used in dplyr::group_by()
@@ -606,21 +606,22 @@ first_isolate <- function(x = NULL,
    }
    # mark up number of found
    n_found <- format(n_found, big.mark = big.mark, decimal.mark = decimal.mark)
-    message_(paste0(
-      "=> Found ",
-      font_bold(paste0(
-        n_found,
-        ifelse(method == "isolate-based", "", paste0(" '", method, "'")),
-        " first isolates"
-      )),
-      " (",
-      ifelse(p_found_total != p_found_scope,
-        paste0(p_found_scope, " within scope and "),
-        ""
+    message_(
+      paste0(
+        "=> Found ",
+        font_bold(paste0(
+          n_found,
+          ifelse(method == "isolate-based", "", paste0(" '", method, "'")),
+          " first isolates"
+        )),
+        " (",
+        ifelse(p_found_total != p_found_scope,
+          paste0(p_found_scope, " within scope and "),
+          ""
+        ),
+        p_found_total, " of total where a microbial ID was available)"
      ),
-      p_found_total, " of total where a microbial ID was available)"
-    ),
-    add_fn = font_black, as_note = FALSE
+      add_fn = font_black, as_note = FALSE
    )
  }

@@ -637,7 +638,7 @@ filter_first_isolate <- function(x = NULL,
                                 method = c("phenotype-based", "episode-based", "patient-based", "isolate-based"),
                                 ...) {
  if (is_null_or_grouped_tbl(x)) {
-    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
+    # when `x` is left blank, auto determine it (get_current_data() searches underlying data within call)
    # is also fix for using a grouped df as input (a dot as first argument)
    x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
  }
@@ -179,7 +179,7 @@ g.test <- function(x,
    V <- outer(sr, sc, v, n)
    dimnames(E) <- dimnames(x)

-    STATISTIC <- 2 * sum(x * log(x / E)) # sum((abs(x - E) - YATES)^2/E) for chisq.test
+    STATISTIC <- 2 * sum(x * log(x / E), na.rm = TRUE) # sum((abs(x - E) - YATES)^2/E) for chisq.test
    PARAMETER <- (nr - 1L) * (nc - 1L)
    PVAL <- pchisq(STATISTIC, PARAMETER, lower.tail = FALSE)
  } else {
@@ -0,0 +1,268 @@
+# ==================================================================== #
+# TITLE                                                                #
+# AMR: An R Package for Working with Antimicrobial Resistance Data     #
+#                                                                      #
+# SOURCE                                                               #
+# https://github.com/msberends/AMR                                     #
+#                                                                      #
+# CITE AS                                                              #
+# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C    #
+# (2022). AMR: An R Package for Working with Antimicrobial Resistance  #
+# Data. Journal of Statistical Software, 104(3), 1-31.                 #
+# doi:10.18637/jss.v104.i03                                            #
+#                                                                      #
+# Developed at the University of Groningen and the University Medical  #
+# Center Groningen in The Netherlands, in collaboration with many      #
+# colleagues from around the world, see our website.                   #
+#                                                                      #
+# This R package is free software; you can freely use and distribute   #
+# it for both personal and commercial purposes under the terms of the  #
+# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
+# the Free Software Foundation.                                        #
+# We created this package for both routine data analysis and academic  #
+# research and it was publicly released in the hope that it will be    #
+# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
+#                                                                      #
+# Visit our website for the full manual and a complete tutorial about  #
+# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
+# ==================================================================== #
+
+#' Determine Clinical or Epidemic Episodes
+#'
+#' These functions determine which items in a vector can be considered (the start of) a new episode. This can be used to determine clinical episodes for any epidemiological analysis. The [get_episode()] function returns the index number of the episode per group, while the [is_new_episode()] function returns `TRUE` for every new [get_episode()] index. Both absolute and relative episode determination are supported.
+#' @param x vector of dates (class `Date` or `POSIXt`), will be sorted internally to determine episodes
+#' @param episode_days episode length in days to specify the time period after which a new episode begins, can also be less than a day or `Inf`, see *Details*
+#' @param case_free_days (inter-epidemic) interval length in days after which a new episode will start, can also be less than a day or `Inf`, see *Details*
+#' @param ... ignored, only in place to allow future extensions
+#' @details Episodes can be determined in two ways: absolute and relative.
+#'
+#' 1. Absolute
+#'
+#'    This method uses `episode_days` to define an episode length in days, after which a new episode will start. A common use case in AMR data analysis is microbial epidemiology: episodes of *S. aureus* bacteraemia in ICU patients for example. The episode length could then be 30 days, so that new *S. aureus* isolates after an ICU episode of 30 days will be considered a different (or new) episode.
+#'
+#'    Thus, this method counts **since the start of the previous episode**.
+#'
+#' 2. Relative
+#'
+#'    This method uses `case_free_days` to quantify the duration of case-free days (the inter-epidemic interval), after which a new episode will start. A common use case is infectious disease epidemiology: episodes of norovirus outbreaks in a hospital for example. The case-free period could then be 14 days, so that new norovirus cases after that time will be considered a different (or new) episode.
+#'
+#'    Thus, this methods counts **since the last case in the previous episode**.
+#'
+#' In a table:
+#'
+#' |    Date    | Using `episode_days = 7` | Using `case_free_days = 7` |
+#' |:----------:|:------------------------:|:--------------------------:|
+#' | 2023-01-01 |             1            |              1             |
+#' | 2023-01-02 |             1            |              1             |
+#' | 2023-01-05 |             1            |              1             |
+#' | 2023-01-08 |             2**          |              1             |
+#' | 2023-02-21 |             3            |              2***          |
+#' | 2023-02-22 |             3            |              2             |
+#' | 2023-02-23 |             3            |              2             |
+#' | 2023-02-24 |             3            |              2             |
+#' | 2023-03-01 |             4            |              2             |
+#'
+#' ** This marks the start of a new episode, because 8 January 2023 is more than 7 days since the start of the previous episode (1 January 2023). \cr
+#' *** This marks the start of a new episode, because 21 January 2023 is more than 7 days since the last case in the previous episode (8 January 2023).
+#'
+#' Either `episode_days` or `case_free_days` must be provided in the function.
+#'
+#' ### Difference between `get_episode()` and `is_new_episode()`
+#'
+#' The [get_episode()] function returns the index number of the episode, so all cases/patients/isolates in the first episode will have the number 1, all cases/patients/isolates in the second episode will have the number 2, etc.
+#'
+#' The [is_new_episode()] function on the other hand, returns `TRUE` for every new [get_episode()] index.
+#'
+#' To specify, when setting `episode_days = 365` (using method 1 as explained above), this is how the two functions differ:
+#'
+#' | patient   | date       | `get_episode()` | `is_new_episode()` |
+#' |:---------:|:----------:|:---------------:|:------------------:|
+#' | A         | 2019-01-01 |               1 | TRUE               |
+#' | A         | 2019-03-01 |               1 | FALSE              |
+#' | A         | 2021-01-01 |               2 | TRUE               |
+#' | B         | 2008-01-01 |               1 | TRUE               |
+#' | B         | 2008-01-01 |               1 | FALSE              |
+#' | C         | 2020-01-01 |               1 | TRUE               |
+#'
+#' ### Other
+#'
+#' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but is more efficient for data sets containing microorganism codes or names and allows for different isolate selection methods.
+#'
+#' The `dplyr` package is not required for these functions to work, but these episode functions do support [variable grouping][dplyr::group_by()] and work conveniently inside `dplyr` verbs such as [`filter()`][dplyr::filter()], [`mutate()`][dplyr::mutate()] and [`summarise()`][dplyr::summarise()].
+#' @return
+#' * [get_episode()]: an [integer] vector
+#' * [is_new_episode()]: a [logical] vector
+#' @seealso [first_isolate()]
+#' @rdname get_episode
+#' @export
+#' @examples
+#' # difference between absolute and relative determination of episodes:
+#' x <- data.frame(dates = as.Date(c(
+#'   "2021-01-01",
+#'   "2021-01-02",
+#'   "2021-01-05",
+#'   "2021-01-08",
+#'   "2021-02-21",
+#'   "2021-02-22",
+#'   "2021-02-23",
+#'   "2021-02-24",
+#'   "2021-03-01",
+#'   "2021-03-01"
+#' )))
+#' x$absolute <- get_episode(x$dates, episode_days = 7)
+#' x$relative <- get_episode(x$dates, case_free_days = 7)
+#' x
+#'
+#'
+#' # `example_isolates` is a data set available in the AMR package.
+#' # See ?example_isolates
+#' df <- example_isolates[sample(seq_len(2000), size = 100), ]
+#'
+#' get_episode(df$date, episode_days = 60) # indices
+#' is_new_episode(df$date, episode_days = 60) # TRUE/FALSE
+#'
+#' # filter on results from the third 60-day episode only, using base R
+#' df[which(get_episode(df$date, 60) == 3), ]
+#'
+#' # the functions also work for less than a day, e.g. to include one per hour:
+#' get_episode(
+#'   c(
+#'     Sys.time(),
+#'     Sys.time() + 60 * 60
+#'   ),
+#'   episode_days = 1 / 24
+#' )
+#'
+#' \donttest{
+#' if (require("dplyr")) {
+#'   # is_new_episode() can also be used in dplyr verbs to determine patient
+#'   # episodes based on any (combination of) grouping variables:
+#'   df %>%
+#'     mutate(condition = sample(
+#'       x = c("A", "B", "C"),
+#'       size = 100,
+#'       replace = TRUE
+#'     )) %>%
+#'     group_by(patient, condition) %>%
+#'     mutate(new_episode = is_new_episode(date, 365)) %>%
+#'     select(patient, date, condition, new_episode) %>%
+#'     arrange(patient, condition, date)
+#' }
+#'
+#' if (require("dplyr")) {
+#'   df %>%
+#'     group_by(ward, patient) %>%
+#'     transmute(date,
+#'       patient,
+#'       new_index = get_episode(date, 60),
+#'       new_logical = is_new_episode(date, 60)
+#'     ) %>%
+#'     arrange(patient, ward, date)
+#' }
+#'
+#' if (require("dplyr")) {
+#'   df %>%
+#'     group_by(ward) %>%
+#'     summarise(
+#'       n_patients = n_distinct(patient),
+#'       n_episodes_365 = sum(is_new_episode(date, episode_days = 365)),
+#'       n_episodes_60 = sum(is_new_episode(date, episode_days = 60)),
+#'       n_episodes_30 = sum(is_new_episode(date, episode_days = 30))
+#'     )
+#' }
+#'
+#' # grouping on patients and microorganisms leads to the same
+#' # results as first_isolate() when using 'episode-based':
+#' if (require("dplyr")) {
+#'   x <- df %>%
+#'     filter_first_isolate(
+#'       include_unknown = TRUE,
+#'       method = "episode-based"
+#'     )
+#'
+#'   y <- df %>%
+#'     group_by(patient, mo) %>%
+#'     filter(is_new_episode(date, 365)) %>%
+#'     ungroup()
+#'
+#'   identical(x, y)
+#' }
+#'
+#' # but is_new_episode() has a lot more flexibility than first_isolate(),
+#' # since you can now group on anything that seems relevant:
+#' if (require("dplyr")) {
+#'   df %>%
+#'     group_by(patient, mo, ward) %>%
+#'     mutate(flag_episode = is_new_episode(date, 365)) %>%
+#'     select(group_vars(.), flag_episode)
+#' }
+#' }
+get_episode <- function(x, episode_days = NULL, case_free_days = NULL, ...) {
+  meet_criteria(x, allow_class = c("Date", "POSIXt"), allow_NA = TRUE)
+  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE, allow_NULL = TRUE)
+  meet_criteria(case_free_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE, allow_NULL = TRUE)
+  as.integer(exec_episode(x, episode_days, case_free_days, ...))
+}
+
+#' @rdname get_episode
+#' @export
+is_new_episode <- function(x, episode_days = NULL, case_free_days = NULL, ...) {
+  meet_criteria(x, allow_class = c("Date", "POSIXt"), allow_NA = TRUE)
+  meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE, allow_NULL = TRUE)
+  meet_criteria(case_free_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = FALSE, allow_NULL = TRUE)
+  !duplicated(exec_episode(x, episode_days, case_free_days, ...))
+}
+
+exec_episode <- function(x, episode_days, case_free_days, ...) {
+  stop_ifnot(is.null(episode_days) || is.null(case_free_days),
+    "either argument `episode_days` or argument `case_free_days` must be set.",
+    call = -2
+  )
+
+  # running as.double() on a POSIXct object will return its number of seconds since 1970-01-01
+  x <- as.double(as.POSIXct(x)) # as.POSIXct() required for Date classes
+
+  # since x is now in seconds, get seconds from episode_days as well
+  episode_seconds <- episode_days * 60 * 60 * 24
+  case_free_seconds <- case_free_days * 60 * 60 * 24
+
+  if (length(x) == 1) { # this will also match 1 NA, which is fine
+    return(1)
+  } else if (length(x) == 2 && all(!is.na(x))) {
+    if ((length(episode_seconds) > 0 && (max(x) - min(x)) >= episode_seconds) ||
+      (length(case_free_seconds) > 0 && (max(x) - min(x)) >= case_free_seconds)) {
+      if (x[1] <= x[2]) {
+        return(c(1, 2))
+      } else {
+        return(c(2, 1))
+      }
+    } else {
+      return(c(1, 1))
+    }
+  }
+
+  run_episodes <- function(x, episode_seconds, case_free) {
+    NAs <- which(is.na(x))
+    x[NAs] <- 0
+
+    indices <- integer(length = length(x))
+    start <- x[1]
+    ind <- 1
+    indices[ind] <- 1
+    for (i in 2:length(x)) {
+      if ((length(episode_seconds) > 0 && (x[i] - start) >= episode_seconds) ||
+        (length(case_free_seconds) > 0 && (x[i] - x[i - 1]) >= case_free_seconds)) {
+        ind <- ind + 1
+        start <- x[i]
+      }
+      indices[i] <- ind
+    }
+    indices[NAs] <- NA
+    indices
+  }
+
+  ord <- order(x)
+  out <- run_episodes(x[ord], episode_seconds, case_free_seconds)[order(ord)]
+  out[is.na(x) & ord != 1] <- NA # every NA expect for the first must remain NA
+  out
+}
@@ -414,13 +414,14 @@ pca_calculations <- function(pca_model,
      sigma <- var(cbind(x$xvar, x$yvar))
      mu <- c(mean(x$xvar), mean(x$yvar))
      ed <- sqrt(qchisq(ellipse_prob, df = 2))
-      data.frame(sweep(circle %*% chol(sigma) * ed,
-        MARGIN = 2,
-        STATS = mu,
-        FUN = "+"
-      ),
-      groups = x$groups[1],
-      stringsAsFactors = FALSE
+      data.frame(
+        sweep(circle %*% chol(sigma) * ed,
+          MARGIN = 2,
+          STATS = mu,
+          FUN = "+"
+        ),
+        groups = x$groups[1],
+        stringsAsFactors = FALSE
      )
    })
    ell <- do.call(rbind, df.groups)
@@ -40,7 +40,7 @@
 #' @inheritParams proportion
 #' @param nrow (when using `facet`) number of rows
 #' @param colours a named vactor with colour to be used for filling. The default colours are colour-blind friendly.
-#' @param aesthetics aesthetics to apply the colours to, defaults to "fill" but can also be (a combination of) "alpha", "colour", "fill", "linetype", "shape" or "size"
+#' @param aesthetics aesthetics to apply the colours to - the default is "fill" but can also be (a combination of) "alpha", "colour", "fill", "linetype", "shape" or "size"
 #' @param datalabels show datalabels using [labels_sir_count()]
 #' @param datalabels.size size of the datalabels
 #' @param datalabels.colour colour of the datalabels
@@ -71,13 +71,11 @@
 #' @examples
 #' \donttest{
 #' if (require("ggplot2") && require("dplyr")) {
-#'
 #'   # get antimicrobial results for drugs against a UTI:
 #'   ggplot(example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)) +
 #'     geom_sir()
 #' }
 #' if (require("ggplot2") && require("dplyr")) {
-#'
 #'   # prettify the plot using some additional functions:
 #'   df <- example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)
 #'   ggplot(df) +
@@ -88,21 +86,18 @@
 #'     theme_sir()
 #' }
 #' if (require("ggplot2") && require("dplyr")) {
-#'
 #'   # or better yet, simplify this using the wrapper function - a single command:
 #'   example_isolates %>%
 #'     select(AMX, NIT, FOS, TMP, CIP) %>%
 #'     ggplot_sir()
 #' }
 #' if (require("ggplot2") && require("dplyr")) {
-#'
 #'   # get only proportions and no counts:
 #'   example_isolates %>%
 #'     select(AMX, NIT, FOS, TMP, CIP) %>%
 #'     ggplot_sir(datalabels = FALSE)
 #' }
 #' if (require("ggplot2") && require("dplyr")) {
-#'
 #'   # add other ggplot2 arguments as you like:
 #'   example_isolates %>%
 #'     select(AMX, NIT, FOS, TMP, CIP) %>%
@@ -115,14 +110,12 @@
 #'     )
 #' }
 #' if (require("ggplot2") && require("dplyr")) {
-#'
 #'   # you can alter the colours with colour names:
 #'   example_isolates %>%
 #'     select(AMX) %>%
 #'     ggplot_sir(colours = c(SI = "yellow"))
 #' }
 #' if (require("ggplot2") && require("dplyr")) {
-#'
 #'   # but you can also use the built-in colour-blind friendly colours for
 #'   # your plots, where "S" is green, "I" is yellow and "R" is red:
 #'   data.frame(
@@ -135,7 +128,6 @@
 #'     scale_sir_colours(Value4 = "S", Value5 = "I", Value6 = "R")
 #' }
 #' if (require("ggplot2") && require("dplyr")) {
-#'
 #'   # resistance of ciprofloxacine per age group
 #'   example_isolates %>%
 #'     mutate(first_isolate = first_isolate()) %>%
@@ -149,14 +141,12 @@
 #'     ggplot_sir(x = "age_group")
 #' }
 #' if (require("ggplot2") && require("dplyr")) {
-#'
 #'   # a shorter version which also adjusts data label colours:
 #'   example_isolates %>%
 #'     select(AMX, NIT, FOS, TMP, CIP) %>%
 #'     ggplot_sir(colours = FALSE)
 #' }
 #' if (require("ggplot2") && require("dplyr")) {
-#'
 #'   # it also supports groups (don't forget to use the group var on `x` or `facet`):
 #'   example_isolates %>%
 #'     filter(mo_is_gram_negative(), ward != "Outpatient") %>%
@@ -203,7 +193,7 @@ ggplot_sir <- function(data,
                       y.title = "Proportion",
                       ...) {
  stop_ifnot_installed("ggplot2")
-  meet_criteria(data, allow_class = "data.frame", contains_column_class = "sir")
+  meet_criteria(data, allow_class = "data.frame", contains_column_class = c("sir", "rsi"))
  meet_criteria(position, allow_class = "character", has_length = 1, is_in = c("fill", "stack", "dodge"), allow_NULL = TRUE)
  meet_criteria(x, allow_class = "character", has_length = 1)
  meet_criteria(fill, allow_class = "character", has_length = 1)
@@ -212,7 +202,7 @@ ggplot_sir <- function(data,
  meet_criteria(limits, allow_class = c("numeric", "integer"), has_length = 2, allow_NULL = TRUE, allow_NA = TRUE)
  meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
  meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
-  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
+  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
  language <- validate_language(language)
  meet_criteria(nrow, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
  meet_criteria(colours, allow_class = c("character", "logical"))
@@ -310,7 +300,7 @@ geom_sir <- function(position = NULL,
  meet_criteria(x, allow_class = "character", has_length = 1)
  meet_criteria(fill, allow_class = "character", has_length = 1)
  meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
-  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
+  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
  language <- validate_language(language)
  meet_criteria(combine_SI, allow_class = "logical", has_length = 1)

@@ -496,7 +486,7 @@ labels_sir_count <- function(position = NULL,
  meet_criteria(position, allow_class = "character", has_length = 1, is_in = c("fill", "stack", "dodge"), allow_NULL = TRUE)
  meet_criteria(x, allow_class = "character", has_length = 1)
  meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
-  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
+  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
  language <- validate_language(language)
  meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
  meet_criteria(datalabels.size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
@@ -33,7 +33,7 @@
 #' @param x a [data.frame]
 #' @param search_string a text to search `x` for, will be checked with [as.ab()] if this value is not a column in `x`
 #' @param verbose a [logical] to indicate whether additional info should be printed
-#' @param only_sir_columns a [logical] to indicate whether only antibiotic columns must be detected that were transformed to class `sir` (see [as.sir()]) on beforehand (defaults to `FALSE`)
+#' @param only_sir_columns a [logical] to indicate whether only antibiotic columns must be detected that were transformed to class `sir` (see [as.sir()]) on beforehand (default is `FALSE`)
 #' @details You can look for an antibiotic (trade) name or abbreviation and it will search `x` and the [antibiotics] data set for any column containing a name or code of that antibiotic.
 #' @return A column name of `x`, or `NULL` when no result is found.
 #' @export
@@ -274,14 +274,15 @@ get_column_abx <- function(x,
      }
      if (names(out[i]) %in% names(duplicates)) {
        already_set_as <- out[unname(out) == unname(out[i])][1L]
-        warning_(paste0(
-          "Column '", font_bold(out[i]), "' will not be used for ",
-          names(out)[i], " (", ab_name(names(out)[i], tolower = TRUE, language = NULL), ")",
-          ", as it is already set for ",
-          names(already_set_as), " (", ab_name(names(already_set_as), tolower = TRUE, language = NULL), ")"
-        ),
-        add_fn = font_red,
-        immediate = verbose
+        warning_(
+          paste0(
+            "Column '", font_bold(out[i]), "' will not be used for ",
+            names(out)[i], " (", ab_name(names(out)[i], tolower = TRUE, language = NULL), ")",
+            ", as it is already set for ",
+            names(already_set_as), " (", ab_name(names(already_set_as), tolower = TRUE, language = NULL), ")"
+          ),
+          add_fn = font_red,
+          immediate = verbose
        )
      }
    }
@@ -307,11 +308,12 @@ get_column_abx <- function(x,
    if (isTRUE(info) && !all(soft_dependencies %in% names(out))) {
      # missing a soft dependency may lower the reliability
      missing <- soft_dependencies[!soft_dependencies %in% names(out)]
-      missing_msg <- vector_and(paste0(
-        ab_name(missing, tolower = TRUE, language = NULL),
-        " (", font_bold(missing, collapse = NULL), ")"
-      ),
-      quotes = FALSE
+      missing_msg <- vector_and(
+        paste0(
+          ab_name(missing, tolower = TRUE, language = NULL),
+          " (", font_bold(missing, collapse = NULL), ")"
+        ),
+        quotes = FALSE
      )
      message_(
        "Reliability would be improved if these antimicrobial results would be available too: ",
@@ -355,10 +357,11 @@ generate_warning_abs_missing <- function(missing, any = FALSE) {
  } else {
    any_txt <- c("", "are")
  }
-  warning_(paste0(
-    "Introducing NAs since", any_txt[1], " these antimicrobials ", any_txt[2], " required: ",
-    vector_and(missing, quotes = FALSE)
-  ),
-  immediate = TRUE
+  warning_(
+    paste0(
+      "Introducing NAs since", any_txt[1], " these antimicrobials ", any_txt[2], " required: ",
+      vector_and(missing, quotes = FALSE)
+    ),
+    immediate = TRUE
  )
 }
@@ -73,41 +73,44 @@ italicise_taxonomy <- function(string, type = c("markdown", "ansi")) {
      search_strings <- gsub("[^a-zA-Z-]", "", s_split)

      ind_species <- search_strings != "" &
-        search_strings %in% AMR_env$MO_lookup[which(AMR_env$MO_lookup$rank %in% c(
-          "family",
-          "genus",
+        search_strings %in% AMR_env$MO_lookup[
+          which(AMR_env$MO_lookup$rank %in% c(
+            "family",
+            "genus",
+            "species",
+            "subspecies",
+            "infraspecies",
+            "subsp."
+          )),
          "species",
-          "subspecies",
-          "infraspecies",
-          "subsp."
-        )),
-        "species",
-        drop = TRUE
+          drop = TRUE
        ]

      ind_fullname <- search_strings != "" &
        search_strings %in% c(
-          AMR_env$MO_lookup[which(AMR_env$MO_lookup$rank %in% c(
-            "family",
-            "genus",
-            "species",
-            "subspecies",
-            "infraspecies",
-            "subsp."
-          )),
-          "fullname",
-          drop = TRUE
+          AMR_env$MO_lookup[
+            which(AMR_env$MO_lookup$rank %in% c(
+              "family",
+              "genus",
+              "species",
+              "subspecies",
+              "infraspecies",
+              "subsp."
+            )),
+            "fullname",
+            drop = TRUE
          ],
-          AMR_env$MO_lookup[which(AMR_env$MO_lookup$rank %in% c(
-            "family",
-            "genus",
-            "species",
+          AMR_env$MO_lookup[
+            which(AMR_env$MO_lookup$rank %in% c(
+              "family",
+              "genus",
+              "species",
+              "subspecies",
+              "infraspecies",
+              "subsp."
+            )),
            "subspecies",
-            "infraspecies",
-            "subsp."
-          )),
-          "subspecies",
-          drop = TRUE
+            drop = TRUE
          ]
        )

@@ -128,9 +128,9 @@ anti_join_microorganisms <- function(x, by = NULL, ...) {

 join_microorganisms <- function(type, x, by, suffix, ...) {
  add_MO_lookup_to_AMR_env()
-  
+
  if (!is.data.frame(x)) {
-    if (pkg_is_available("tibble", also_load = FALSE)) {
+    if (pkg_is_available("tibble")) {
      x <- import_fn("tibble", "tibble")(mo = x)
    } else {
      x <- data.frame(mo = x, stringsAsFactors = FALSE)
@@ -37,7 +37,7 @@
 #' @param gram_negative names of antibiotic drugs for **Gram-positives**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default antibiotic drugs
 #' @param gram_positive names of antibiotic drugs for **Gram-negatives**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default antibiotic drugs
 #' @param antifungal names of antifungal drugs for **fungi**, case-insensitive. Set to `NULL` to ignore. See *Details* for the default antifungal drugs
-#' @param only_sir_columns a [logical] to indicate whether only columns must be included that were transformed to class `sir` (see [as.sir()]) on beforehand (defaults to `FALSE`)
+#' @param only_sir_columns a [logical] to indicate whether only columns must be included that were transformed to class `sir` (see [as.sir()]) on beforehand (default is `FALSE`)
 #' @param ... ignored, only in place to allow future extensions
 #' @details
 #' The [key_antimicrobials()] and [all_antimicrobials()] functions are context-aware. This means that the `x` argument can be left blank if used inside a [data.frame] call, see *Examples*.
@@ -138,7 +138,7 @@ key_antimicrobials <- function(x = NULL,
                               only_sir_columns = FALSE,
                               ...) {
  if (is_null_or_grouped_tbl(x)) {
-    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
+    # when `x` is left blank, auto determine it (get_current_data() searches underlying data within call)
    # is also fix for using a grouped df as input (a dot as first argument)
    x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
  }
@@ -149,6 +149,10 @@ key_antimicrobials <- function(x = NULL,
  meet_criteria(gram_positive, allow_class = "character", allow_NULL = TRUE)
  meet_criteria(antifungal, allow_class = "character", allow_NULL = TRUE)
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }

  # force regular data.frame, not a tibble or data.table
  x <- as.data.frame(x, stringsAsFactors = FALSE)
@@ -250,7 +254,7 @@ all_antimicrobials <- function(x = NULL,
                               only_sir_columns = FALSE,
                               ...) {
  if (is_null_or_grouped_tbl(x)) {
-    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
+    # when `x` is left blank, auto determine it (get_current_data() searches underlying data within call)
    # is also fix for using a grouped df as input (a dot as first argument)
    x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
  }
@@ -178,7 +178,7 @@ mdro <- function(x = NULL,
                 only_sir_columns = FALSE,
                 ...) {
  if (is_null_or_grouped_tbl(x)) {
-    # when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
+    # when `x` is left blank, auto determine it (get_current_data() searches underlying data within call)
    # is also a fix for using a grouped df as input (i.e., a dot as first argument)
    x <- tryCatch(get_current_data(arg_name = "x", call = -2), error = function(e) x)
  }
@@ -192,18 +192,22 @@ mdro <- function(x = NULL,
  meet_criteria(pct_required_classes, allow_class = "numeric", has_length = 1)
  meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
  meet_criteria(verbose, allow_class = "logical", has_length = 1)
+  if ("only_rsi_columns" %in% names(list(...))) {
+    deprecation_warning("only_rsi_columns", "only_sir_columns", is_function = FALSE)
+    only_sir_columns <- list(...)$only_rsi_columns
+  }
  meet_criteria(only_sir_columns, allow_class = "logical", has_length = 1)
-  
+
  if (!any(is_sir_eligible(x))) {
    stop_("There were no possible SIR columns found in the data set. Transform columns with `as.sir()` for valid antimicrobial interpretations.")
  }
-  
+
  info.bak <- info
  # don't thrown info's more than once per call
  if (isTRUE(info)) {
    info <- message_not_thrown_before("mdro")
  }
-  
+
  if (interactive() && isTRUE(verbose) && isTRUE(info)) {
    txt <- paste0(
      "WARNING: In Verbose mode, the mdro() function does not return the MDRO results, but instead returns a data set in logbook form with extensive info about which isolates would be MDRO-positive, or why they are not.",
@@ -221,7 +225,7 @@ mdro <- function(x = NULL,
      return(x)
    }
  }
-  
+
  group_msg <- ""
  if (isTRUE(info.bak)) {
    # print group name if used in dplyr::group_by()
@@ -243,15 +247,15 @@ mdro <- function(x = NULL,
      }
    }
  }
-  
+
  # force regular [data.frame], not a tibble or data.table
  x <- as.data.frame(x, stringsAsFactors = FALSE)
-  
+
  if (pct_required_classes > 1) {
    # allow pct_required_classes = 75 -> pct_required_classes = 0.75
    pct_required_classes <- pct_required_classes / 100
  }
-  
+
  guideline.bak <- guideline
  if (is.list(guideline)) {
    # Custom MDRO guideline ---------------------------------------------------
@@ -260,8 +264,8 @@ mdro <- function(x = NULL,
      txt <- paste0(
        "Determining MDROs based on custom rules",
        ifelse(isTRUE(attributes(guideline)$as_factor),
-               paste0(", resulting in factor levels: ", paste0(attributes(guideline)$values, collapse = " < ")),
-               ""
+          paste0(", resulting in factor levels: ", paste0(attributes(guideline)$values, collapse = " < ")),
+          ""
        ),
        "."
      )
@@ -314,7 +318,7 @@ mdro <- function(x = NULL,
    "invalid guideline: ", guideline.bak
  )
  guideline <- list(code = guideline)
-  
+
  # try to find columns based on type
  # -- mo
  if (is.null(col_mo)) {
@@ -329,7 +333,7 @@ mdro <- function(x = NULL,
    col_mo <- "mo"
  }
  stop_if(is.null(col_mo), "`col_mo` must be set")
-  
+
  if (guideline$code == "cmi2012") {
    guideline$name <- "Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance."
    guideline$author <- "Magiorakos AP, Srinivasan A, Carey RB, ..., Vatopoulos A, Weber JT, Monnet DL"
@@ -360,7 +364,7 @@ mdro <- function(x = NULL,
    guideline$version <- "WHO/HTM/TB/2014.11, 2014"
    guideline$source_url <- font_url("https://www.who.int/publications/i/item/9789241548809", "Direct download")
    guideline$type <- "MDR-TB's"
-    
+
    # support per country:
  } else if (guideline$code == "mrgn") {
    guideline$name <- "Cross-border comparison of the Dutch and German guidelines on multidrug-resistant Gram-negative microorganisms"
@@ -377,7 +381,7 @@ mdro <- function(x = NULL,
  } else {
    stop("This guideline is currently unsupported: ", guideline$code, call. = FALSE)
  }
-  
+
  if (guideline$code == "cmi2012") {
    cols_ab <- get_column_abx(
      x = x,
@@ -456,7 +460,7 @@ mdro <- function(x = NULL,
    }
    cols_ab <- c(cols_ab, c(AMP = unname(cols_ab[names(cols_ab) == "AMX"])))
  }
-  
+
  # nolint start
  AMC <- cols_ab["AMC"]
  AMK <- cols_ab["AMK"]
@@ -601,13 +605,13 @@ mdro <- function(x = NULL,
  abx_tb <- abx_tb[!is.na(abx_tb)]
  stop_if(guideline$code == "tb" & length(abx_tb) == 0, "no antimycobacterials found in data set")
  # nolint end
-  
+
  if (isTRUE(combine_SI)) {
    search_result <- "R"
  } else {
    search_result <- c("R", "I")
  }
-  
+
  if (isTRUE(info)) {
    if (isTRUE(combine_SI)) {
      cat(font_red("\nOnly results with 'R' are considered as resistance. Use `combine_SI = FALSE` to also consider 'I' as resistance.\n"))
@@ -615,18 +619,18 @@ mdro <- function(x = NULL,
      cat(font_red("\nResults with 'R' or 'I' are considered as resistance. Use `combine_SI = TRUE` to only consider 'R' as resistance.\n"))
    }
    cat("\n", word_wrap("Determining multidrug-resistant organisms (MDRO), according to:"), "\n",
-        word_wrap(paste0(font_bold("Guideline: "), font_italic(guideline$name)), extra_indent = 11, as_note = FALSE), "\n",
-        word_wrap(paste0(font_bold("Author(s): "), guideline$author), extra_indent = 11, as_note = FALSE), "\n",
-        ifelse(!is.na(guideline$version),
-               paste0(word_wrap(paste0(font_bold("Version:   "), guideline$version), extra_indent = 11, as_note = FALSE), "\n"),
-               ""
-        ),
-        paste0(font_bold("Source:    "), guideline$source_url),
-        "\n\n",
-        sep = ""
+      word_wrap(paste0(font_bold("Guideline: "), font_italic(guideline$name)), extra_indent = 11, as_note = FALSE), "\n",
+      word_wrap(paste0(font_bold("Author(s): "), guideline$author), extra_indent = 11, as_note = FALSE), "\n",
+      ifelse(!is.na(guideline$version),
+        paste0(word_wrap(paste0(font_bold("Version:   "), guideline$version), extra_indent = 11, as_note = FALSE), "\n"),
+        ""
+      ),
+      paste0(font_bold("Source:    "), guideline$source_url),
+      "\n\n",
+      sep = ""
    )
  }
-  
+
  ab_missing <- function(ab) {
    isTRUE(ab %in% c(NULL, NA)) | length(ab) == 0
  }
@@ -638,7 +642,7 @@ mdro <- function(x = NULL,
    out[is.na(out)] <- FALSE
    out
  }
-  
+
  # antibiotic classes
  # nolint start
  aminoglycosides <- c(TOB, GEN)
@@ -649,17 +653,18 @@ mdro <- function(x = NULL,
  carbapenems <- c(DOR, ETP, IPM, MEM, MEV)
  fluoroquinolones <- c(CIP, ENX, FLE, GAT, GEM, GRX, LVX, LOM, MFX, NOR, OFX, PAZ, PEF, PRU, RFL, SPX, TMX, TVA)
  # nolint end
-  
+
  # helper function for editing the table
  trans_tbl <- function(to, rows, cols, any_all) {
    cols <- cols[!ab_missing(cols)]
    cols <- cols[!is.na(cols)]
    if (length(rows) > 0 && length(cols) > 0) {
-      x[, cols] <- as.data.frame(lapply(
-        x[, cols, drop = FALSE],
-        function(col) as.sir(col)
-      ),
-      stringsAsFactors = FALSE
+      x[, cols] <- as.data.frame(
+        lapply(
+          x[, cols, drop = FALSE],
+          function(col) as.sir(col)
+        ),
+        stringsAsFactors = FALSE
      )
      x[rows, "columns_nonsusceptible"] <<- vapply(
        FUN.VALUE = character(1),
@@ -670,22 +675,23 @@ mdro <- function(x = NULL,
            x[row, group_vct, drop = FALSE],
            function(y) y %in% search_result
          )
-          paste(sort(c(
-            unlist(strsplit(x[row, "columns_nonsusceptible", drop = TRUE], ", ", fixed = TRUE)),
-            names(cols_nonsus)[cols_nonsus]
-          )),
-          collapse = ", "
+          paste(
+            sort(c(
+              unlist(strsplit(x[row, "columns_nonsusceptible", drop = TRUE], ", ", fixed = TRUE)),
+              names(cols_nonsus)[cols_nonsus]
+            )),
+            collapse = ", "
          )
        }
      )
-      
+
      if (any_all == "any") {
        search_function <- any
      } else if (any_all == "all") {
        search_function <- all
      }
      x_transposed <- as.list(as.data.frame(t(x[, cols, drop = FALSE]),
-                                            stringsAsFactors = FALSE
+        stringsAsFactors = FALSE
      ))
      rows_affected <- vapply(
        FUN.VALUE = logical(1),
@@ -704,7 +710,7 @@ mdro <- function(x = NULL,
      )
    }
  }
-  
+
  trans_tbl2 <- function(txt, rows, lst) {
    if (isTRUE(info)) {
      message_(txt, "...", appendLF = FALSE, as_note = FALSE)
@@ -714,12 +720,13 @@ mdro <- function(x = NULL,
      lst_vector <- unlist(lst)[!is.na(unlist(lst))]
      # keep only unique ones:
      lst_vector <- lst_vector[!duplicated(paste(lst_vector, names(lst_vector)))]
-      
-      x[, lst_vector] <- as.data.frame(lapply(
-        x[, lst_vector, drop = FALSE],
-        function(col) as.sir(col)
-      ),
-      stringsAsFactors = FALSE
+
+      x[, lst_vector] <- as.data.frame(
+        lapply(
+          x[, lst_vector, drop = FALSE],
+          function(col) as.sir(col)
+        ),
+        stringsAsFactors = FALSE
      )
      x[rows, "classes_in_guideline"] <<- length(lst)
      x[rows, "classes_available"] <<- vapply(
@@ -733,7 +740,7 @@ mdro <- function(x = NULL,
          ))
        }
      )
-      
+
      if (isTRUE(verbose)) {
        x[rows, "columns_nonsusceptible"] <<- vapply(
          FUN.VALUE = character(1),
@@ -748,30 +755,31 @@ mdro <- function(x = NULL,
        FUN.VALUE = double(1),
        rows,
        function(row, group_tbl = lst) {
-          sum(vapply(
-            FUN.VALUE = logical(1),
-            group_tbl,
-            function(group) {
-              any(unlist(x[row, group[!is.na(group)], drop = TRUE]) %in% search_result, na.rm = TRUE)
-            }
-          ),
-          na.rm = TRUE
+          sum(
+            vapply(
+              FUN.VALUE = logical(1),
+              group_tbl,
+              function(group) {
+                any(unlist(x[row, group[!is.na(group)], drop = TRUE]) %in% search_result, na.rm = TRUE)
+              }
+            ),
+            na.rm = TRUE
          )
        }
      )
      # for PDR; all drugs are R (or I if combine_SI = FALSE)
      x_transposed <- as.list(as.data.frame(t(x[rows, lst_vector, drop = FALSE]),
-                                            stringsAsFactors = FALSE
+        stringsAsFactors = FALSE
      ))
      row_filter <- vapply(FUN.VALUE = logical(1), x_transposed, function(y) all(y %in% search_result, na.rm = TRUE))
      x[which(row_filter), "classes_affected"] <<- 999
    }
-    
+
    if (isTRUE(info)) {
      message_(" OK.", add_fn = list(font_green, font_bold), as_note = FALSE)
    }
  }
-  
+
  x[, col_mo] <- as.mo(as.character(x[, col_mo, drop = TRUE]))
  # rename col_mo to prevent interference with joined columns
  colnames(x)[colnames(x) == col_mo] <- ".col_mo"
@@ -782,12 +790,12 @@ mdro <- function(x = NULL,
  x$row_number <- seq_len(nrow(x))
  x$reason <- paste0("not covered by ", toupper(guideline$code), " guideline")
  x$columns_nonsusceptible <- ""
-  
+
  if (guideline$code == "cmi2012") {
    # CMI, 2012 ---------------------------------------------------------------
    # Non-susceptible = R and I
    # (see header 'Approaches to Creating Definitions for MDR, XDR and PDR' in paper)
-    
+
    # take amoxicillin if ampicillin is unavailable
    if (is.na(AMP) && !is.na(AMX)) {
      if (isTRUE(verbose)) {
@@ -808,87 +816,87 @@ mdro <- function(x = NULL,
      }
      CTX <- CRO
    }
-    
+
    # intrinsic resistant must not be considered for the determination of MDR,
    # so let's just remove them, meticulously following the paper
    x[which(x$genus == "Enterococcus" & x$species == "faecium"), ab_NA(IPM)] <- NA
    x[which(x$genus == "Enterococcus" & x$species == "faecalis"), ab_NA(QDA)] <- NA
    x[which((x$genus == "Providencia" & x$species == "rettgeri") |
-              (x$genus == "Providencia" & x$species == "stuartii")), ab_NA(c(GEN, TOB, NET))] <- NA
+      (x$genus == "Providencia" & x$species == "stuartii")), ab_NA(c(GEN, TOB, NET))] <- NA
    x[which(x$genus == "Escherichia" & x$species == "hermannii"), ab_NA(c(TCC, TZP))] <- NA
    x[which((x$genus == "Citrobacter" & x$species == "freundii") |
-              (x$genus == "Enterobacter" & x$species == "aerogenes") |
-              (x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
-            | (x$genus == "Enterobacter" & x$species == "cloacae") |
-              (x$genus == "Hafnia" & x$species == "alvei") |
-              (x$genus == "Morganella" & x$species == "morganii") |
-              (x$genus == "Proteus" & x$species == "penneri") |
-              (x$genus == "Proteus" & x$species == "vulgaris") |
-              (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(CZO)] <- NA
+      (x$genus == "Enterobacter" & x$species == "aerogenes") |
+      (x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
+    | (x$genus == "Enterobacter" & x$species == "cloacae") |
+      (x$genus == "Hafnia" & x$species == "alvei") |
+      (x$genus == "Morganella" & x$species == "morganii") |
+      (x$genus == "Proteus" & x$species == "penneri") |
+      (x$genus == "Proteus" & x$species == "vulgaris") |
+      (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(CZO)] <- NA
    x[which((x$genus == "Morganella" & x$species == "morganii") |
-              (x$genus == "Proteus" & x$species == "penneri") |
-              (x$genus == "Proteus" & x$species == "vulgaris") |
-              (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(CXM)] <- NA
+      (x$genus == "Proteus" & x$species == "penneri") |
+      (x$genus == "Proteus" & x$species == "vulgaris") |
+      (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(CXM)] <- NA
    x[which((x$genus == "Morganella" & x$species == "morganii") |
-              (x$genus == "Proteus" & x$species == "mirabilis") |
-              (x$genus == "Proteus" & x$species == "penneri") |
-              (x$genus == "Proteus" & x$species == "vulgaris") |
-              (x$genus == "Providencia" & x$species == "rettgeri") |
-              (x$genus == "Providencia" & x$species == "stuartii")), ab_NA(TGC)] <- NA
+      (x$genus == "Proteus" & x$species == "mirabilis") |
+      (x$genus == "Proteus" & x$species == "penneri") |
+      (x$genus == "Proteus" & x$species == "vulgaris") |
+      (x$genus == "Providencia" & x$species == "rettgeri") |
+      (x$genus == "Providencia" & x$species == "stuartii")), ab_NA(TGC)] <- NA
    x[which((x$genus == "Citrobacter" & x$species == "koseri") |
-              (x$genus == "Citrobacter" & x$species == "freundii") |
-              (x$genus == "Enterobacter" & x$species == "aerogenes") |
-              (x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
-            | (x$genus == "Enterobacter" & x$species == "cloacae") |
-              (x$genus == "Escherichia" & x$species == "hermannii") |
-              (x$genus == "Hafnia" & x$species == "alvei") |
-              (x$genus == "Klebsiella") |
-              (x$genus == "Morganella" & x$species == "morganii") |
-              (x$genus == "Proteus" & x$species == "penneri") |
-              (x$genus == "Proteus" & x$species == "vulgaris") |
-              (x$genus == "Providencia" & x$species == "rettgeri") |
-              (x$genus == "Providencia" & x$species == "stuartii") |
-              (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(AMP)] <- NA
+      (x$genus == "Citrobacter" & x$species == "freundii") |
+      (x$genus == "Enterobacter" & x$species == "aerogenes") |
+      (x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
+    | (x$genus == "Enterobacter" & x$species == "cloacae") |
+      (x$genus == "Escherichia" & x$species == "hermannii") |
+      (x$genus == "Hafnia" & x$species == "alvei") |
+      (x$genus == "Klebsiella") |
+      (x$genus == "Morganella" & x$species == "morganii") |
+      (x$genus == "Proteus" & x$species == "penneri") |
+      (x$genus == "Proteus" & x$species == "vulgaris") |
+      (x$genus == "Providencia" & x$species == "rettgeri") |
+      (x$genus == "Providencia" & x$species == "stuartii") |
+      (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(AMP)] <- NA
    x[which((x$genus == "Citrobacter" & x$species == "freundii") |
-              (x$genus == "Enterobacter" & x$species == "aerogenes") |
-              (x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
-            | (x$genus == "Enterobacter" & x$species == "cloacae") |
-              (x$genus == "Hafnia" & x$species == "alvei") |
-              (x$genus == "Morganella" & x$species == "morganii") |
-              (x$genus == "Providencia" & x$species == "rettgeri") |
-              (x$genus == "Providencia" & x$species == "stuartii") |
-              (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(AMC)] <- NA
+      (x$genus == "Enterobacter" & x$species == "aerogenes") |
+      (x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
+    | (x$genus == "Enterobacter" & x$species == "cloacae") |
+      (x$genus == "Hafnia" & x$species == "alvei") |
+      (x$genus == "Morganella" & x$species == "morganii") |
+      (x$genus == "Providencia" & x$species == "rettgeri") |
+      (x$genus == "Providencia" & x$species == "stuartii") |
+      (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(AMC)] <- NA
    x[which((x$genus == "Citrobacter" & x$species == "freundii") |
-              (x$genus == "Citrobacter" & x$species == "koseri") |
-              (x$genus == "Enterobacter" & x$species == "aerogenes") |
-              (x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
-            | (x$genus == "Enterobacter" & x$species == "cloacae") |
-              (x$genus == "Hafnia" & x$species == "alvei") |
-              (x$genus == "Providencia" & x$species == "rettgeri") |
-              (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(SAM)] <- NA
+      (x$genus == "Citrobacter" & x$species == "koseri") |
+      (x$genus == "Enterobacter" & x$species == "aerogenes") |
+      (x$genus == "Klebsiella" & x$species == "aerogenes") # new name (2017)
+    | (x$genus == "Enterobacter" & x$species == "cloacae") |
+      (x$genus == "Hafnia" & x$species == "alvei") |
+      (x$genus == "Providencia" & x$species == "rettgeri") |
+      (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(SAM)] <- NA
    x[which((x$genus == "Morganella" & x$species == "morganii") |
-              (x$genus == "Proteus" & x$species == "mirabilis") |
-              (x$genus == "Proteus" & x$species == "penneri") |
-              (x$genus == "Proteus" & x$species == "vulgaris") |
-              (x$genus == "Providencia" & x$species == "rettgeri") |
-              (x$genus == "Providencia" & x$species == "stuartii") |
-              (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(COL)] <- NA
+      (x$genus == "Proteus" & x$species == "mirabilis") |
+      (x$genus == "Proteus" & x$species == "penneri") |
+      (x$genus == "Proteus" & x$species == "vulgaris") |
+      (x$genus == "Providencia" & x$species == "rettgeri") |
+      (x$genus == "Providencia" & x$species == "stuartii") |
+      (x$genus == "Serratia" & x$species == "marcescens")), ab_NA(COL)] <- NA
    x[which((x$genus == "Morganella" & x$species == "morganii") |
-              (x$genus == "Proteus" & x$species == "mirabilis") |
-              (x$genus == "Proteus" & x$species == "penneri") |
-              (x$genus == "Proteus" & x$species == "vulgaris") |
-              (x$genus == "Providencia" & x$species == "rettgeri") |
-              (x$genus == "Providencia" & x$species == "stuartii")), ab_NA(TCY)] <- NA
+      (x$genus == "Proteus" & x$species == "mirabilis") |
+      (x$genus == "Proteus" & x$species == "penneri") |
+      (x$genus == "Proteus" & x$species == "vulgaris") |
+      (x$genus == "Providencia" & x$species == "rettgeri") |
+      (x$genus == "Providencia" & x$species == "stuartii")), ab_NA(TCY)] <- NA
    x[which((x$genus == "Morganella" & x$species == "morganii") |
-              (x$genus == "Proteus" & x$species == "penneri") |
-              (x$genus == "Proteus" & x$species == "vulgaris") |
-              (x$genus == "Providencia" & x$species == "rettgeri") |
-              (x$genus == "Providencia" & x$species == "stuartii")), ab_NA(c(DOX, MNO))] <- NA
-    
+      (x$genus == "Proteus" & x$species == "penneri") |
+      (x$genus == "Proteus" & x$species == "vulgaris") |
+      (x$genus == "Providencia" & x$species == "rettgeri") |
+      (x$genus == "Providencia" & x$species == "stuartii")), ab_NA(c(DOX, MNO))] <- NA
+
    x$classes_in_guideline <- NA_integer_
    x$classes_available <- NA_integer_
    x$classes_affected <- NA_integer_
-    
+
    # now add the MDR levels to the data
    trans_tbl(
      2,
@@ -990,7 +998,7 @@ mdro <- function(x = NULL,
        c(TCY, DOX, MNO)
      )
    )
-    
+
    # now set MDROs:
    # MDR (=2): >=3 classes affected
    x[which(x$classes_affected >= 3), "MDRO"] <- 2
@@ -1002,7 +1010,7 @@ mdro <- function(x = NULL,
        " out of ", x$classes_available[which(x$classes_affected >= 3)], " available classes"
      )
    }
-    
+
    # XDR (=3): all but <=2 classes affected
    x[which((x$classes_in_guideline - x$classes_affected) <= 2), "MDRO"] <- 3
    if (isTRUE(verbose)) {
@@ -1011,7 +1019,7 @@ mdro <- function(x = NULL,
        " out of ", x$classes_in_guideline[which(x$MDRO == 3)], " classes)"
      )
    }
-    
+
    # PDR (=4): all drugs are R
    x[which(x$classes_affected == 999 & x$classes_in_guideline == x$classes_available), "MDRO"] <- 4
    if (isTRUE(verbose)) {
@@ -1022,7 +1030,7 @@ mdro <- function(x = NULL,
        ifelse(!isTRUE(combine_SI), " or I", "")
      )
    }
-    
+
    # not enough classes available
    x[which(x$MDRO %in% c(1, 3) & x$classes_available < floor(x$classes_in_guideline * pct_required_classes)), "MDRO"] <- -1
    if (isTRUE(verbose)) {
@@ -1032,18 +1040,18 @@ mdro <- function(x = NULL,
        " (~", percentage(pct_required_classes), " of ", x$classes_in_guideline[which(x$MDRO == -1)], ")"
      )
    }
-    
+
    # add antibiotic names of resistant ones to verbose output
  }
-  
+
  if (guideline$code == "eucast3.1") {
    # EUCAST 3.1 --------------------------------------------------------------
    # Table 5
    trans_tbl(
      3,
      which(x$order == "Enterobacterales" |
-              (x$genus == "Pseudomonas" & x$species == "aeruginosa") |
-              x$genus == "Acinetobacter"),
+        (x$genus == "Pseudomonas" & x$species == "aeruginosa") |
+        x$genus == "Acinetobacter"),
      COL,
      "all"
    )
@@ -1128,17 +1136,17 @@ mdro <- function(x = NULL,
      "any"
    )
  }
-  
+
  if (guideline$code == "eucast3.2") {
    # EUCAST 3.2 --------------------------------------------------------------
    # Table 6
    trans_tbl(
      3,
      which((x$order == "Enterobacterales" &
-               !x$family == "Morganellaceae" &
-               !(x$genus == "Serratia" & x$species == "marcescens")) |
-              (x$genus == "Pseudomonas" & x$species == "aeruginosa") |
-              x$genus == "Acinetobacter"),
+        !x$family == "Morganellaceae" &
+        !(x$genus == "Serratia" & x$species == "marcescens")) |
+        (x$genus == "Pseudomonas" & x$species == "aeruginosa") |
+        x$genus == "Acinetobacter"),
      COL,
      "all"
    )
@@ -1229,7 +1237,7 @@ mdro <- function(x = NULL,
      "any"
    )
  }
-  
+
  if (guideline$code == "eucast3.3") {
    # EUCAST 3.3 --------------------------------------------------------------
    # note: this guideline is equal to EUCAST 3.2 - no MDRO insights changed
@@ -1237,10 +1245,10 @@ mdro <- function(x = NULL,
    trans_tbl(
      3,
      which((x$order == "Enterobacterales" &
-               !x$family == "Morganellaceae" &
-               !(x$genus == "Serratia" & x$species == "marcescens")) |
-              (x$genus == "Pseudomonas" & x$species == "aeruginosa") |
-              x$genus == "Acinetobacter"),
+        !x$family == "Morganellaceae" &
+        !(x$genus == "Serratia" & x$species == "marcescens")) |
+        (x$genus == "Pseudomonas" & x$species == "aeruginosa") |
+        x$genus == "Acinetobacter"),
      COL,
      "all"
    )
@@ -1331,72 +1339,72 @@ mdro <- function(x = NULL,
      "any"
    )
  }
-  
+
  if (guideline$code == "mrgn") {
    # Germany -----------------------------------------------------------------
-    
+
    # Table 1
    trans_tbl(
      2, # 3MRGN
      which((x$order == "Enterobacterales" | # following in fact the old Enterobacteriaceae classification
-               (x$genus == "Acinetobacter" & x$species == "baumannii")) &
-              try_ab(x[, PIP, drop = TRUE] == "R") &
-              (try_ab(x[, CTX, drop = TRUE] == "R") | try_ab(x[, CAZ, drop = TRUE] == "R")) &
-              (try_ab(x[, IPM, drop = TRUE] != "R") | try_ab(x[, MEM, drop = TRUE] != "R")) &
-              try_ab(x[, CIP, drop = TRUE] == "R")),
+        (x$genus == "Acinetobacter" & x$species == "baumannii")) &
+        try_ab(x[, PIP, drop = TRUE] == "R") &
+        (try_ab(x[, CTX, drop = TRUE] == "R") | try_ab(x[, CAZ, drop = TRUE] == "R")) &
+        (try_ab(x[, IPM, drop = TRUE] != "R") | try_ab(x[, MEM, drop = TRUE] != "R")) &
+        try_ab(x[, CIP, drop = TRUE] == "R")),
      c(PIP, CTX, CAZ, IPM, MEM, CIP),
      "any"
    )
-    
+
    trans_tbl(
      3, # 4MRGN, overwrites 3MRGN if applicable
      which((x$order == "Enterobacterales" | # following in fact the old Enterobacteriaceae classification
-               (x$genus == "Acinetobacter" & x$species == "baumannii")) &
-              try_ab(x[, PIP, drop = TRUE] == "R") &
-              (try_ab(x[, CTX, drop = TRUE] == "R") | try_ab(x[, CAZ, drop = TRUE] == "R")) &
-              (try_ab(x[, IPM, drop = TRUE] == "R") | try_ab(x[, MEM, drop = TRUE] == "R")) &
-              try_ab(x[, CIP, drop = TRUE] == "R")),
+        (x$genus == "Acinetobacter" & x$species == "baumannii")) &
+        try_ab(x[, PIP, drop = TRUE] == "R") &
+        (try_ab(x[, CTX, drop = TRUE] == "R") | try_ab(x[, CAZ, drop = TRUE] == "R")) &
+        (try_ab(x[, IPM, drop = TRUE] == "R") | try_ab(x[, MEM, drop = TRUE] == "R")) &
+        try_ab(x[, CIP, drop = TRUE] == "R")),
      c(PIP, CTX, CAZ, IPM, MEM, CIP),
      "any"
    )
-    
+
    trans_tbl(
      3, # 4MRGN, overwrites 3MRGN if applicable
      which((x$order == "Enterobacterales" | # following in fact the old Enterobacteriaceae classification
-               (x$genus == "Acinetobacter" & x$species == "baumannii")) &
-              (try_ab(x[, IPM, drop = TRUE] == "R") | try_ab(x[, MEM, drop = TRUE] == "R"))),
+        (x$genus == "Acinetobacter" & x$species == "baumannii")) &
+        (try_ab(x[, IPM, drop = TRUE] == "R") | try_ab(x[, MEM, drop = TRUE] == "R"))),
      c(IPM, MEM),
      "any"
    )
-    
+
    trans_tbl(
      2, # 3MRGN, if only 1 group is S
      which(x$genus == "Pseudomonas" & x$species == "aeruginosa" &
-              try_ab(x[, PIP, drop = TRUE] == "S") +
-              try_ab(x[, CTX, drop = TRUE] == "S") +
-              try_ab(x[, CAZ, drop = TRUE] == "S") +
-              try_ab(x[, IPM, drop = TRUE] == "S") +
-              try_ab(x[, MEM, drop = TRUE] == "S") +
-              try_ab(x[, CIP, drop = TRUE] == "S") == 1),
+        try_ab(x[, PIP, drop = TRUE] == "S") +
+          try_ab(x[, CTX, drop = TRUE] == "S") +
+          try_ab(x[, CAZ, drop = TRUE] == "S") +
+          try_ab(x[, IPM, drop = TRUE] == "S") +
+          try_ab(x[, MEM, drop = TRUE] == "S") +
+          try_ab(x[, CIP, drop = TRUE] == "S") == 1),
      c(PIP, CTX, CAZ, IPM, MEM, CIP),
      "any"
    )
-    
+
    trans_tbl(
      3, # 4MRGN otherwise
      which((x$genus == "Pseudomonas" & x$species == "aeruginosa") &
-              try_ab(x[, PIP, drop = TRUE] == "R") &
-              (try_ab(x[, CTX, drop = TRUE] == "R") | try_ab(x[, CAZ, drop = TRUE] == "R")) &
-              (try_ab(x[, IPM, drop = TRUE] == "R") | try_ab(x[, MEM, drop = TRUE] == "R")) &
-              try_ab(x[, CIP, drop = TRUE] == "R")),
+        try_ab(x[, PIP, drop = TRUE] == "R") &
+        (try_ab(x[, CTX, drop = TRUE] == "R") | try_ab(x[, CAZ, drop = TRUE] == "R")) &
+        (try_ab(x[, IPM, drop = TRUE] == "R") | try_ab(x[, MEM, drop = TRUE] == "R")) &
+        try_ab(x[, CIP, drop = TRUE] == "R")),
      c(PIP, CTX, CAZ, IPM, MEM, CIP),
      "any"
    )
-    
+
    x[which(x$MDRO == 2), "reason"] <- "3MRGN"
    x[which(x$MDRO == 3), "reason"] <- "4MRGN"
  }
-  
+
  if (guideline$code == "brmo") {
    # Netherlands -------------------------------------------------------------
    aminoglycosides <- aminoglycosides[!is.na(aminoglycosides)]
@@ -1409,7 +1417,7 @@ mdro <- function(x = NULL,
    if (length(ESBLs) != 2) {
      ESBLs <- character(0)
    }
-    
+
    # Table 1
    trans_tbl(
      3,
@@ -1417,21 +1425,21 @@ mdro <- function(x = NULL,
      c(aminoglycosides, fluoroquinolones),
      "all"
    )
-    
+
    trans_tbl(
      2,
      which(x$order == "Enterobacterales"), # following in fact the old Enterobacteriaceae classification
      carbapenems,
      "any"
    )
-    
+
    trans_tbl(
      2,
      which(x$order == "Enterobacterales"), # following in fact the old Enterobacteriaceae classification
      ESBLs,
      "all"
    )
-    
+
    # Table 2
    trans_tbl(
      2,
@@ -1445,19 +1453,19 @@ mdro <- function(x = NULL,
      c(aminoglycosides, fluoroquinolones),
      "all"
    )
-    
+
    trans_tbl(
      3,
      which(x$genus == "Stenotrophomonas" & x$species == "maltophilia"),
      SXT,
      "all"
    )
-    
+
    if (!ab_missing(MEM) && !ab_missing(IPM) &&
-        !ab_missing(GEN) && !ab_missing(TOB) &&
-        !ab_missing(CIP) &&
-        !ab_missing(CAZ) &&
-        !ab_missing(TZP)) {
+      !ab_missing(GEN) && !ab_missing(TOB) &&
+      !ab_missing(CIP) &&
+      !ab_missing(CAZ) &&
+      !ab_missing(TZP)) {
      x$psae <- 0
      x[which(x[, MEM, drop = TRUE] == "R" | x[, IPM, drop = TRUE] == "R"), "psae"] <- 1 + x[which(x[, MEM, drop = TRUE] == "R" | x[, IPM, drop = TRUE] == "R"), "psae"]
      x[which(x[, GEN, drop = TRUE] == "R" & x[, TOB, drop = TRUE] == "R"), "psae"] <- 1 + x[which(x[, GEN, drop = TRUE] == "R" & x[, TOB, drop = TRUE] == "R"), "psae"]
@@ -1477,7 +1485,7 @@ mdro <- function(x = NULL,
      x$genus == "Pseudomonas" & x$species == "aeruginosa" &
        x$psae >= 3
    ), "reason"] <- paste0("at least 3 classes contain R", ifelse(!isTRUE(combine_SI), " or I", ""))
-    
+
    # Table 3
    trans_tbl(
      3,
@@ -1498,7 +1506,7 @@ mdro <- function(x = NULL,
      "all"
    )
  }
-  
+
  if (guideline$code == "tb") {
    # Tuberculosis ------------------------------------------------------------
    prepare_drug <- function(ab) {
@@ -1535,7 +1543,7 @@ mdro <- function(x = NULL,
        ab != "R"
      }
    }
-    
+
    x$mono_count <- 0
    x[drug_is_R(INH), "mono_count"] <- x[drug_is_R(INH), "mono_count", drop = TRUE] + 1
    x[drug_is_R(RIF), "mono_count"] <- x[drug_is_R(RIF), "mono_count", drop = TRUE] + 1
@@ -1543,7 +1551,7 @@ mdro <- function(x = NULL,
    x[drug_is_R(PZA), "mono_count"] <- x[drug_is_R(PZA), "mono_count", drop = TRUE] + 1
    x[drug_is_R(RIB), "mono_count"] <- x[drug_is_R(RIB), "mono_count", drop = TRUE] + 1
    x[drug_is_R(RFP), "mono_count"] <- x[drug_is_R(RFP), "mono_count", drop = TRUE] + 1
-    
+
    x$mono <- x$mono_count > 0
    x$poly <- x$mono_count > 1 & drug_is_not_R(RIF) & drug_is_not_R(INH)
    x$mdr <- drug_is_R(RIF) & drug_is_R(INH)
@@ -1551,19 +1559,19 @@ mdro <- function(x = NULL,
    x$second <- drug_is_R(CAP) | drug_is_R(KAN) | drug_is_R(AMK)
    x$xdr <- x$mdr & x$xdr & x$second
    x$MDRO <- ifelse(x$xdr, 5,
-                     ifelse(x$mdr, 4,
-                            ifelse(x$poly, 3,
-                                   ifelse(x$mono, 2,
-                                          1
-                                   )
-                            )
-                     )
+      ifelse(x$mdr, 4,
+        ifelse(x$poly, 3,
+          ifelse(x$mono, 2,
+            1
+          )
+        )
+      )
    )
    # keep all real TB, make other species NA
    x$MDRO <- ifelse(x$fullname == "Mycobacterium tuberculosis", x$MDRO, NA_real_)
    x$reason <- "PDR/MDR/XDR criteria were met"
  }
-  
+
  # some more info on negative results
  if (isTRUE(verbose)) {
    if (guideline$code == "cmi2012") {
@@ -1579,7 +1587,7 @@ mdro <- function(x = NULL,
      x[which(x$MDRO == 1), "reason"] <- "too few antibiotics are R"
    }
  }
-  
+
  if (isTRUE(info.bak)) {
    cat(group_msg)
    if (sum(!is.na(x$MDRO)) == 0) {
@@ -1591,11 +1599,11 @@ mdro <- function(x = NULL,
      )))
    }
  }
-  
+
  # Fill in blanks ----
  # for rows that have no results
  x_transposed <- as.list(as.data.frame(t(x[, cols_ab, drop = FALSE]),
-                                        stringsAsFactors = FALSE
+    stringsAsFactors = FALSE
  ))
  rows_empty <- which(vapply(
    FUN.VALUE = logical(1),
@@ -1609,7 +1617,7 @@ mdro <- function(x = NULL,
  } else {
    cat("\n")
  }
-  
+
  # Results ----
  if (guideline$code == "cmi2012") {
    if (any(x$MDRO == -1, na.rm = TRUE)) {
@@ -1656,7 +1664,7 @@ mdro <- function(x = NULL,
      ordered = TRUE
    )
  }
-  
+
  if (isTRUE(verbose)) {
    colnames(x)[colnames(x) == col_mo] <- "microorganism"
    x$microorganism <- mo_name(x$microorganism, language = NULL)
@@ -1678,9 +1686,9 @@ mdro <- function(x = NULL,
 #' @export
 custom_mdro_guideline <- function(..., as_factor = TRUE) {
  meet_criteria(as_factor, allow_class = "logical", has_length = 1)
-  
+
  dots <- tryCatch(list(...),
-                   error = function(e) "error"
+    error = function(e) "error"
  )
  stop_if(
    identical(dots, "error"),
@@ -1694,7 +1702,7 @@ custom_mdro_guideline <- function(..., as_factor = TRUE) {
      inherits(dots[[i]], "formula"),
      "rule ", i, " must be a valid formula input (e.g., using '~'), see `?mdro`"
    )
-    
+
    # Query
    qry <- dots[[i]][[2]]
    if (inherits(qry, "call")) {
@@ -1710,14 +1718,14 @@ custom_mdro_guideline <- function(..., as_factor = TRUE) {
    qry <- gsub(" *([&|+-/*^><==]+) *", " \\1 ", qry)
    qry <- gsub("'", "\"", qry, fixed = TRUE)
    out[[i]]$query <- as.expression(qry)
-    
+
    # Value
    val <- tryCatch(eval(dots[[i]][[3]]), error = function(e) NULL)
    stop_if(is.null(val), "rule ", i, " must return a valid value, it now returns an error: ", tryCatch(eval(dots[[i]][[3]]), error = function(e) e$message))
    stop_if(length(val) > 1, "rule ", i, " must return a value of length 1, not ", length(val))
    out[[i]]$value <- as.character(val)
  }
-  
+
  names(out) <- paste0("rule", seq_len(n_dots))
  out <- set_clean_class(out, new_class = c("custom_mdro_guideline", "list"))
  attr(out, "values") <- unname(c("Negative", vapply(FUN.VALUE = character(1), unclass(out), function(x) x$value)))
@@ -1739,8 +1747,8 @@ c.custom_mdro_guideline <- function(x, ..., as_factor = NULL) {
  }
  for (g in list(...)) {
    stop_ifnot(inherits(g, "custom_mdro_guideline"),
-               "for combining custom MDRO guidelines, all rules must be created with `custom_mdro_guideline()`",
-               call = FALSE
+      "for combining custom MDRO guidelines, all rules must be created with `custom_mdro_guideline()`",
+      call = FALSE
    )
    vals <- attributes(x)$values
    if (!all(attributes(g)$values %in% vals)) {
@@ -1790,28 +1798,28 @@ run_custom_mdro_guideline <- function(df, guideline, info) {
  reasons <- character(length = NROW(df))
  for (i in seq_len(n_dots)) {
    qry <- tryCatch(eval(parse(text = guideline[[i]]$query), envir = df, enclos = parent.frame()),
-                    error = function(e) {
-                      AMR_env$err_msg <- e$message
-                      return("error")
-                    }
+      error = function(e) {
+        AMR_env$err_msg <- e$message
+        return("error")
+      }
    )
    if (identical(qry, "error")) {
      warning_("in `custom_mdro_guideline()`: rule ", i,
-               " (`", as.character(guideline[[i]]$query), "`) was ignored because of this error message: ",
-               AMR_env$err_msg,
-               call = FALSE,
-               add_fn = font_red
+        " (`", as.character(guideline[[i]]$query), "`) was ignored because of this error message: ",
+        AMR_env$err_msg,
+        call = FALSE,
+        add_fn = font_red
      )
      next
    }
    stop_ifnot(is.logical(qry), "in custom_mdro_guideline(): rule ", i, " (`", guideline[[i]]$query,
-               "`) must return `TRUE` or `FALSE`, not ",
-               format_class(class(qry), plural = FALSE),
-               call = FALSE
+      "`) must return `TRUE` or `FALSE`, not ",
+      format_class(class(qry), plural = FALSE),
+      call = FALSE
    )
-    
+
    new_mdros <- which(qry == TRUE & out == "")
-    
+
    if (isTRUE(info)) {
      cat(word_wrap(
        "- Custom MDRO rule ", i, ": `", as.character(guideline[[i]]$query),
@@ -1827,11 +1835,11 @@ run_custom_mdro_guideline <- function(df, guideline, info) {
  }
  out[out == ""] <- "Negative"
  reasons[out == "Negative"] <- "no rules matched"
-  
+
  if (isTRUE(attributes(guideline)$as_factor)) {
    out <- factor(out, levels = attributes(guideline)$values, ordered = TRUE)
  }
-  
+
  columns_nonsusceptible <- as.data.frame(t(df[, is.sir(df), drop = FALSE] == "R"))
  columns_nonsusceptible <- vapply(
    FUN.VALUE = character(1),
@@ -1839,7 +1847,7 @@ run_custom_mdro_guideline <- function(df, guideline, info) {
    function(x) paste0(rownames(columns_nonsusceptible)[which(x)], collapse = " ")
  )
  columns_nonsusceptible[is.na(out)] <- NA_character_
-  
+
  data.frame(
    row_number = seq_len(NROW(df)),
    MDRO = out,
@@ -32,7 +32,7 @@
 #' Calculates a normalised mean for antimicrobial resistance between multiple observations, to help to identify similar isolates without comparing antibiograms by hand.
 #' @param x a vector of class [sir][as.sir()], [mic][as.mic()] or [disk][as.disk()], or a [data.frame] containing columns of any of these classes
 #' @param ... variables to select (supports [tidyselect language][tidyselect::language] such as `column1:column4` and `where(is.mic)`, and can thus also be [antibiotic selectors][ab_selector()]
-#' @param combine_SI 	a [logical] to indicate whether all values of S and I must be merged into one, so the input only consists of S+I vs. R (susceptible vs. resistant), defaults to `TRUE`
+#' @param combine_SI 	a [logical] to indicate whether all values of S and I must be merged into one, so the input only consists of S+I vs. R (susceptible vs. resistant) - the default is `TRUE`
 #' @details The mean AMR distance is effectively [the Z-score](https://en.wikipedia.org/wiki/Standard_score); a normalised numeric value to compare AMR test results which can help to identify similar isolates, without comparing antibiograms by hand.
 #'
 #' MIC values (see [as.mic()]) are transformed with [log2()] first; their distance is thus calculated as `(log2(x) - mean(log2(x))) / sd(log2(x))`.
@@ -49,13 +49,13 @@
 #' sir <- random_sir(10)
 #' sir
 #' mean_amr_distance(sir)
-#' 
+#'
 #' mic <- random_mic(10)
 #' mic
 #' mean_amr_distance(mic)
 #' # equal to the Z-score of their log2:
 #' (log2(mic) - mean(log2(mic))) / sd(log2(mic))
-#' 
+#'
 #' disk <- random_disk(10)
 #' disk
 #' mean_amr_distance(disk)
@@ -143,7 +143,7 @@ mean_amr_distance.data.frame <- function(x, ..., combine_SI = TRUE) {
  df_classes <- colnames(df)[vapply(FUN.VALUE = logical(1), df, function(x) is.disk(x) | is.mic(x) | is.disk(x), USE.NAMES = FALSE)]
  df_antibiotics <- unname(get_column_abx(df, info = FALSE))
  df <- df[, colnames(df)[colnames(df) %in% union(df_classes, df_antibiotics)], drop = FALSE]
-  
+
  stop_if(ncol(df) < 2,
    "data set must contain at least two variables",
    call = -2
@@ -151,7 +151,7 @@ mean_amr_distance.data.frame <- function(x, ..., combine_SI = TRUE) {
  if (message_not_thrown_before("mean_amr_distance", "groups")) {
    message_("Calculating mean AMR distance based on columns ", vector_and(colnames(df), sort = FALSE))
  }
-  
+
  res <- vapply(
    FUN.VALUE = double(nrow(df)),
    df,
@@ -230,13 +230,13 @@ as.mic <- function(x, na.rm = FALSE) {
        vector_and(quotes = TRUE)
      cur_col <- get_current_column()
      warning_("in `as.mic()`: ", na_after - na_before, " result",
-               ifelse(na_after - na_before > 1, "s", ""),
-               ifelse(is.null(cur_col), "", paste0(" in column '", cur_col, "'")),
-               " truncated (",
-               round(((na_after - na_before) / length(x)) * 100),
-               "%) that were invalid MICs: ",
-               list_missing,
-               call = FALSE
+        ifelse(na_after - na_before > 1, "s", ""),
+        ifelse(is.null(cur_col), "", paste0(" in column '", cur_col, "'")),
+        " truncated (",
+        round(((na_after - na_before) / length(x)) * 100),
+        "%) that were invalid MICs: ",
+        list_missing,
+        call = FALSE
      )
    }

@@ -286,7 +286,7 @@ as.numeric.mic <- function(x, ...) {

 #' @rdname as.mic
 #' @method droplevels mic
-#' @param as.mic a [logical] to indicate whether the `mic` class should be kept, defaults to `FALSE`
+#' @param as.mic a [logical] to indicate whether the `mic` class should be kept - the default is `FALSE`
 #' @export
 droplevels.mic <- function(x, as.mic = FALSE, ...) {
  x <- droplevels.factor(x, ...)
@@ -27,23 +27,23 @@
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #

-#' Transform Input to a Microorganism Code
+#' Transform Arbitrary Input to Valid Microbial Taxonomy
 #'
-#' Use this function to determine a valid microorganism code ([`mo`]). Determination is done using intelligent rules and the complete taxonomic kingdoms `r vector_and(unique(microorganisms$kingdom[which(!grepl("(unknown|Fungi)", microorganisms$kingdom))]), quotes = FALSE)`, and most microbial species from the kingdom Fungi (see *Source*). The input can be almost anything: a full name (like `"Staphylococcus aureus"`), an abbreviated name (such as `"S. aureus"`), an abbreviation known in the field (such as `"MRSA"`), or just a genus. See *Examples*.
+#' Use this function to get a valid microorganism code ([`mo`]) based on arbitrary user input. Determination is done using intelligent rules and the complete taxonomic tree of the kingdoms `r vector_and(unique(microorganisms$kingdom[which(!grepl("(unknown|Fungi)", microorganisms$kingdom))]), quotes = FALSE)`, and most microbial species from the kingdom Fungi (see *Source*). The input can be almost anything: a full name (like `"Staphylococcus aureus"`), an abbreviated name (such as `"S. aureus"`), an abbreviation known in the field (such as `"MRSA"`), or just a genus. See *Examples*.
 #' @param x a [character] vector or a [data.frame] with one or two columns
-#' @param Becker a [logical] to indicate whether staphylococci should be categorised into coagulase-negative staphylococci ("CoNS") and coagulase-positive staphylococci ("CoPS") instead of their own species, according to Karsten Becker *et al.* (see Source).
+#' @param Becker a [logical] to indicate whether staphylococci should be categorised into coagulase-negative staphylococci ("CoNS") and coagulase-positive staphylococci ("CoPS") instead of their own species, according to Karsten Becker *et al.* (see *Source*). Please see *Details* for a full list of staphylococcal species that will be converted.
 #'
 #' This excludes *Staphylococcus aureus* at default, use `Becker = "all"` to also categorise *S. aureus* as "CoPS".
-#' @param Lancefield a [logical] to indicate whether a beta-haemolytic *Streptococcus* should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield (see Source). These streptococci will be categorised in their first group, e.g. *Streptococcus dysgalactiae* will be group C, although officially it was also categorised into groups G and L.
+#' @param Lancefield a [logical] to indicate whether a beta-haemolytic *Streptococcus* should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield (see *Source*). These streptococci will be categorised in their first group, e.g. *Streptococcus dysgalactiae* will be group C, although officially it was also categorised into groups G and L. . Please see *Details* for a full list of streptococcal species that will be converted.
 #'
 #' This excludes enterococci at default (who are in group D), use `Lancefield = "all"` to also categorise all enterococci as group D.
 #' @param minimum_matching_score a numeric value to set as the lower limit for the [MO matching score][mo_matching_score()]. When left blank, this will be determined automatically based on the character length of `x`, its [taxonomic kingdom][microorganisms] and [human pathogenicity][mo_matching_score()].
-#' @param keep_synonyms a [logical] to indicate if old, previously valid taxonomic names must be preserved and not be corrected to currently accepted names. The default is `FALSE`, which will return a note if old taxonomic names were processed. The default can be set with `options(AMR_keep_synonyms = TRUE)` or `options(AMR_keep_synonyms = FALSE)`.
+#' @param keep_synonyms a [logical] to indicate if old, previously valid taxonomic names must be preserved and not be corrected to currently accepted names. The default is `FALSE`, which will return a note if old taxonomic names were processed. The default can be set with the [package option][AMR-options] [`AMR_keep_synonyms`][AMR-options], i.e. `options(AMR_keep_synonyms = TRUE)` or `options(AMR_keep_synonyms = FALSE)`.
 #' @param reference_df a [data.frame] to be used for extra reference when translating `x` to a valid [`mo`]. See [set_mo_source()] and [get_mo_source()] to automate the usage of your own codes (e.g. used in your analysis or organisation).
-#' @param ignore_pattern a [regular expression][base::regex] (case-insensitive) of which all matches in `x` must return `NA`. This can be convenient to exclude known non-relevant input and can also be set with the option `AMR_ignore_pattern`, e.g. `options(AMR_ignore_pattern = "(not reported|contaminated flora)")`.
-#' @param remove_from_input a [regular expression][base::regex] (case-insensitive) to clean the input of `x`. Everything matched in `x` will be removed. At default, this is the outcome of [mo_cleaning_regex()], which removes texts between brackets and texts such as "species" and "serovar".
+#' @param ignore_pattern a Perl-compatible [regular expression][base::regex] (case-insensitive) of which all matches in `x` must return `NA`. This can be convenient to exclude known non-relevant input and can also be set with the [package option][AMR-options] [`AMR_ignore_pattern`][AMR-options], e.g. `options(AMR_ignore_pattern = "(not reported|contaminated flora)")`.
+#' @param cleaning_regex a Perl-compatible [regular expression][base::regex] (case-insensitive) to clean the input of `x`. Every matched part in `x` will be removed. At default, this is the outcome of [mo_cleaning_regex()], which removes texts between brackets and texts such as "species" and "serovar". The default can be set with the [package option][AMR-options] [`AMR_cleaning_regex`][AMR-options].
 #' @param language language to translate text like "no growth", which defaults to the system language (see [get_AMR_locale()])
-#' @param info a [logical] to indicate if a progress bar should be printed if more than 25 items are to be coerced, defaults to `TRUE` only in interactive mode
+#' @param info a [logical] to indicate if a progress bar should be printed if more than 25 items are to be coerced - the default is `TRUE` only in interactive mode
 #' @param ... other arguments passed on to functions
 #' @rdname as.mo
 #' @aliases mo
@@ -68,13 +68,17 @@
 #'
 #' Use the [`mo_*`][mo_property()] functions to get properties based on the returned code, see *Examples*.
 #'
-#' The [as.mo()] function uses a novel [matching score algorithm][mo_matching_score()] (see *Matching Score for Microorganisms* below) to match input against the [available microbial taxonomy][microorganisms] in this package. This will lead to the effect that e.g. `"E. coli"` (a microorganism highly prevalent in humans) will return the microbial ID of *Escherichia coli* and not *Entamoeba coli* (a microorganism less prevalent in humans), although the latter would alphabetically come first. The algorithm uses data from the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF) (see [microorganisms]).
+#' The [as.mo()] function uses a novel [matching score algorithm][mo_matching_score()] (see *Matching Score for Microorganisms* below) to match input against the [available microbial taxonomy][microorganisms] in this package. This will lead to the effect that e.g. `"E. coli"` (a microorganism highly prevalent in humans) will return the microbial ID of *Escherichia coli* and not *Entamoeba coli* (a microorganism less prevalent in humans), although the latter would alphabetically come first.
+#'
+#' With `Becker = TRUE`, the following `r length(MO_CONS[MO_CONS != "B_STPHY_CONS"])` staphylococci will be converted to the **coagulase-negative group**: `r vector_and(gsub("Staphylococcus", "S.", mo_name(MO_CONS[MO_CONS != "B_STPHY_CONS"], keep_synonyms = TRUE)), quotes = "*")`.\cr The following `r length(MO_COPS[MO_COPS != "B_STPHY_COPS"])` staphylococci will be converted to the **coagulase-positive group**: `r vector_and(gsub("Staphylococcus", "S.", mo_name(MO_COPS[MO_COPS != "B_STPHY_COPS"], keep_synonyms = TRUE)), quotes = "*")`.
+#'
+#' With `Lancefield = TRUE`, the following streptococci will be converted to their corresponding Lancefield group: `r vector_and(gsub("Streptococcus", "S.", paste0("*", mo_name(MO_LANCEFIELD, keep_synonyms = TRUE), "* (", mo_species(MO_LANCEFIELD, keep_synonyms = TRUE, Lancefield = TRUE), ")")), quotes = FALSE)`.
 #'
 #' ### Coping with Uncertain Results
 #'
 #' Results of non-exact taxonomic input are based on their [matching score][mo_matching_score()]. The lowest allowed score can be set with the `minimum_matching_score` argument. At default this will be determined based on the character length of the input, and the [taxonomic kingdom][microorganisms] and [human pathogenicity][mo_matching_score()] of the taxonomic outcome. If values are matched with uncertainty, a message will be shown to suggest the user to evaluate the results with [mo_uncertainties()], which returns a [data.frame] with all specifications.
 #'
-#' To increase the quality of matching, the `remove_from_input` argument can be used to clean the input (i.e., `x`). This must be a [regular expression][base::regex] that matches parts of the input that should be removed before the input is matched against the [available microbial taxonomy][microorganisms]. It will be matched Perl-compatible and case-insensitive. The default value of `remove_from_input` is the outcome of the helper function [mo_cleaning_regex()].
+#' To increase the quality of matching, the `cleaning_regex` argument can be used to clean the input (i.e., `x`). This must be a [regular expression][base::regex] that matches parts of the input that should be removed before the input is matched against the [available microbial taxonomy][microorganisms]. It will be matched Perl-compatible and case-insensitive. The default value of `cleaning_regex` is the outcome of the helper function [mo_cleaning_regex()].
 #'
 #' There are three helper functions that can be run after using the [as.mo()] function:
 #' - Use [mo_uncertainties()] to get a [data.frame] that prints in a pretty format with all taxonomic names that were guessed. The output contains the matching score for all matches (see *Matching Score for Microorganisms* below).
@@ -150,17 +154,18 @@ as.mo <- function(x,
                  keep_synonyms = getOption("AMR_keep_synonyms", FALSE),
                  reference_df = get_mo_source(),
                  ignore_pattern = getOption("AMR_ignore_pattern", NULL),
-                  remove_from_input = mo_cleaning_regex(),
+                  cleaning_regex = getOption("AMR_cleaning_regex", mo_cleaning_regex()),
                  language = get_AMR_locale(),
                  info = interactive(),
                  ...) {
  meet_criteria(x, allow_class = c("mo", "data.frame", "list", "character", "numeric", "integer", "factor"), allow_NA = TRUE)
  meet_criteria(Becker, allow_class = c("logical", "character"), has_length = 1)
  meet_criteria(Lancefield, allow_class = c("logical", "character"), has_length = 1)
+  meet_criteria(minimum_matching_score, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive_or_zero = TRUE, is_finite = TRUE)
  meet_criteria(keep_synonyms, allow_class = "logical", has_length = 1)
-  meet_criteria(minimum_matching_score, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE)
  meet_criteria(reference_df, allow_class = "data.frame", allow_NULL = TRUE)
  meet_criteria(ignore_pattern, allow_class = "character", has_length = 1, allow_NULL = TRUE)
+  meet_criteria(cleaning_regex, allow_class = "character", has_length = 1, allow_NULL = TRUE)
  language <- validate_language(language)
  meet_criteria(info, allow_class = "logical", has_length = 1)

@@ -174,7 +179,6 @@ as.mo <- function(x,
    return(set_clean_class(x, new_class = c("mo", "character")))
  }

-
  # start off with replaced language-specific non-ASCII characters with ASCII characters
  x <- parse_and_convert(x)
  # replace mo codes used in older package versions
@@ -183,12 +187,12 @@ as.mo <- function(x,
  x <- replace_ignore_pattern(x, ignore_pattern)

  x_lower <- tolower(x)
-  
+
  complexes <- x[trimws2(x_lower) %like_case% " (complex|group)$"]
-  if (length(complexes) > 0 && identical(remove_from_input, mo_cleaning_regex()) && !any(AMR_env$MO_lookup$fullname[which(AMR_env$MO_lookup$source == "Added by user")] %like% "(group|complex)", na.rm = TRUE)) {
+  if (length(complexes) > 0 && identical(cleaning_regex, mo_cleaning_regex()) && !any(AMR_env$MO_lookup$fullname[which(AMR_env$MO_lookup$source == "Added by user")] %like% "(group|complex)", na.rm = TRUE)) {
    warning_("in `as.mo()`: 'complex' and 'group' were ignored from the input in ", length(complexes), " case", ifelse(length(complexes) > 1, "s", ""), ", as they are currently not supported.\nYou can add your own microorganism with `add_custom_microorganisms()`.", call = FALSE)
  }
-  
+
  # WHONET: xxx = no growth
  x[x_lower %in% c("", "xxx", "na", "nan")] <- NA_character_

@@ -210,7 +214,7 @@ as.mo <- function(x,
  # From known codes ----
  out[is.na(out) & toupper(x) %in% AMR::microorganisms.codes$code] <- AMR::microorganisms.codes$mo[match(toupper(x)[is.na(out) & toupper(x) %in% AMR::microorganisms.codes$code], AMR::microorganisms.codes$code)]
  # From SNOMED ----
-  if (any(is.na(out) & !is.na(x)) && any(is.na(out) & x %in% unlist(microorganisms$snomed), na.rm = TRUE)) {
+  if (any(is.na(out) & !is.na(x)) && any(is.na(out) & x %in% unlist(AMR_env$MO_lookup$snomed), na.rm = TRUE)) {
    # found this extremely fast gem here: https://stackoverflow.com/a/11002456/4575331
    out[is.na(out) & x %in% unlist(AMR_env$MO_lookup$snomed)] <- AMR_env$MO_lookup$mo[rep(seq_along(AMR_env$MO_lookup$snomed), vapply(FUN.VALUE = double(1), AMR_env$MO_lookup$snomed, length))[match(x[is.na(out) & x %in% unlist(AMR_env$MO_lookup$snomed)], unlist(AMR_env$MO_lookup$snomed))]]
  }
@@ -256,8 +260,8 @@ as.mo <- function(x,

      # some required cleaning steps
      x_out <- trimws2(x_search)
-      # this applies the `remove_from_input` argument, which defaults to mo_cleaning_regex()
-      x_out <- gsub(remove_from_input, " ", x_out, ignore.case = TRUE, perl = TRUE)
+      # this applies the `cleaning_regex` argument, which defaults to mo_cleaning_regex()
+      x_out <- gsub(cleaning_regex, " ", x_out, ignore.case = TRUE, perl = TRUE)
      x_out <- trimws2(gsub(" +", " ", x_out, perl = TRUE))
      x_search_cleaned <- x_out
      x_out <- tolower(x_out)
@@ -274,7 +278,7 @@ as.mo <- function(x,

      # take out the parts, split by space
      x_parts <- strsplit(gsub("-", " ", x_out, fixed = TRUE), " ", fixed = TRUE)[[1]]
-      
+
      # do a pre-match on first character (and if it contains a space, first chars of first two terms)
      if (length(x_parts) %in% c(2, 3)) {
        # for genus + species + subspecies
@@ -313,39 +317,39 @@ as.mo <- function(x,
      } else {
        minimum_matching_score_current <- minimum_matching_score
      }
-      
+
      if (sum(m >= minimum_matching_score_current) > 10) {
        # at least 10 are left over, make the ones under `m` NA
-        m[m < minimum_matching_score_current] <- NA_real_  
+        m[m < minimum_matching_score_current] <- NA_real_
      }
-      
-      top_hits <- mo_to_search[order(m, decreasing = TRUE, na.last = NA)] # na.last = NA will remove the NAs  
+
+      top_hits <- mo_to_search[order(m, decreasing = TRUE, na.last = NA)] # na.last = NA will remove the NAs
      if (length(top_hits) == 0) {
        warning_("No hits found for \"", x_search, "\" with minimum_matching_score = ", ifelse(is.null(minimum_matching_score), paste0("NULL (=", round(min(minimum_matching_score_current, na.rm = TRUE), 3), ")"), minimum_matching_score), ". Try setting this value lower or even to 0.", call = FALSE)
        result_mo <- NA_character_
      } else {
        result_mo <- AMR_env$MO_lookup$mo[match(top_hits[1], AMR_env$MO_lookup$fullname)]
-        AMR_env$mo_uncertainties <- rbind(AMR_env$mo_uncertainties,
+        AMR_env$mo_uncertainties <- rbind_AMR(
+          AMR_env$mo_uncertainties,
          data.frame(
            original_input = x_search,
            input = x_search_cleaned,
            fullname = top_hits[1],
            mo = result_mo,
-            candidates = ifelse(length(top_hits) > 1, paste(top_hits[2:min(26, length(top_hits))], collapse = ", "), ""),
+            candidates = ifelse(length(top_hits) > 1, paste(top_hits[2:min(99, length(top_hits))], collapse = ", "), ""),
            minimum_matching_score = ifelse(is.null(minimum_matching_score), "NULL", minimum_matching_score),
            keep_synonyms = keep_synonyms,
            stringsAsFactors = FALSE
-          ),
-          stringsAsFactors = FALSE
+          )
        )
        # save to package env to save time for next time
-        AMR_env$mo_previously_coerced <- unique(rbind(AMR_env$mo_previously_coerced,
+        AMR_env$mo_previously_coerced <- unique(rbind_AMR(
+          AMR_env$mo_previously_coerced,
          data.frame(
            x = paste(x_search, minimum_matching_score),
            mo = result_mo,
            stringsAsFactors = FALSE
-          ),
-          stringsAsFactors = FALSE
+          )
        ))
      }
      # the actual result:
@@ -365,18 +369,19 @@ as.mo <- function(x,
          plural <- c("s", "these uncertainties")
        }
        if (length(AMR_env$mo_uncertainties$original_input) <= 3) {
-          examples <- vector_and(paste0(
-            '"', AMR_env$mo_uncertainties$original_input,
-            '" (assumed ', italicise(AMR_env$mo_uncertainties$fullname), ")"
-          ),
-          quotes = FALSE
+          examples <- vector_and(
+            paste0(
+              '"', AMR_env$mo_uncertainties$original_input,
+              '" (assumed ', italicise(AMR_env$mo_uncertainties$fullname), ")"
+            ),
+            quotes = FALSE
          )
        } else {
          examples <- paste0(nr2char(length(AMR_env$mo_uncertainties$original_input)), " microorganism", plural[1])
        }
        msg <- c(msg, paste0(
          "Microorganism translation was uncertain for ", examples,
-          ". Run `mo_uncertainties()` to review ", plural[2], ", or use `add_custom_microorganisms()` to add own entries."
+          ". Run `mo_uncertainties()` to review ", plural[2], ", or use `add_custom_microorganisms()` to add custom entries."
        ))

        for (m in msg) {
@@ -442,7 +447,7 @@ as.mo <- function(x,
  # Apply Lancefield ----
  if (isTRUE(Lancefield) || Lancefield == "all") {
    # (using `%like_case%` to also match subspecies)
-    
+
    # group A - S. pyogenes
    out[out %like_case% "^B_STRPT_PYGN(_|$)"] <- "B_STRPT_GRPA"
    # group B - S. agalactiae
@@ -560,7 +565,7 @@ pillar_shaft.mo <- function(x, ...) {
  # markup NA and UNKNOWN
  out[is.na(x)] <- font_na("  NA")
  out[x == "UNKNOWN"] <- font_na("  UNKNOWN")
-  
+
  # markup manual codes
  out[x %in% AMR_env$MO_lookup$mo & !x %in% AMR::microorganisms$mo] <- font_blue(out[x %in% AMR_env$MO_lookup$mo & !x %in% AMR::microorganisms$mo], collapse = NULL)

@@ -577,10 +582,11 @@ pillar_shaft.mo <- function(x, ...) {
  if (!all(x %in% all_mos) ||
    (!is.null(df) && !all(unlist(df[, which(mo_cols), drop = FALSE]) %in% all_mos))) {
    # markup old mo codes
-    out[!x %in% all_mos] <- font_italic(font_na(x[!x %in% all_mos],
+    out[!x %in% all_mos] <- font_italic(
+      font_na(x[!x %in% all_mos],
+        collapse = NULL
+      ),
      collapse = NULL
-    ),
-    collapse = NULL
    )
    # throw a warning with the affected column name(s)
    if (!is.null(mo_cols)) {
@@ -625,7 +631,7 @@ freq.mo <- function(x, ...) {
    .add_header = list(
      `Gram-negative` = paste0(
        format(sum(grams == "Gram-negative", na.rm = TRUE),
-          big.mark = ",",
+          big.mark = " ",
          decimal.mark = "."
        ),
        " (", percentage(sum(grams == "Gram-negative", na.rm = TRUE) / length(grams),
@@ -635,7 +641,7 @@ freq.mo <- function(x, ...) {
      ),
      `Gram-positive` = paste0(
        format(sum(grams == "Gram-positive", na.rm = TRUE),
-          big.mark = ",",
+          big.mark = " ",
          decimal.mark = "."
        ),
        " (", percentage(sum(grams == "Gram-positive", na.rm = TRUE) / length(grams),
@@ -792,38 +798,49 @@ rep.mo <- function(x, ...) {
 #' @method print mo_uncertainties
 #' @export
 #' @noRd
-print.mo_uncertainties <- function(x, ...) {
+print.mo_uncertainties <- function(x, n = 10, ...) {
  if (NROW(x) == 0) {
    cat(word_wrap("No uncertainties to show. Only uncertainties of the last call of `as.mo()` or any `mo_*()` function are stored.\n\n", add_fn = font_blue))
    return(invisible(NULL))
  }
-  
-  add_MO_lookup_to_AMR_env()

  cat(word_wrap("Matching scores are based on the resemblance between the input and the full taxonomic name, and the pathogenicity in humans. See `?mo_matching_score`.\n\n", add_fn = font_blue))
+
+  add_MO_lookup_to_AMR_env()
+
+  col_red <- function(x) font_rose_bg(font_black(x, collapse = NULL), collapse = NULL)
+  col_orange <- function(x) font_orange_bg(font_black(x, collapse = NULL), collapse = NULL)
+  col_yellow <- function(x) font_yellow_bg(font_black(x, collapse = NULL), collapse = NULL)
+  col_green <- function(x) font_green_bg(font_black(x, collapse = NULL), collapse = NULL)
+
  if (has_colour()) {
    cat(word_wrap("Colour keys: ",
-      font_red_bg(" 0.000-0.499 "),
-      font_orange_bg(" 0.500-0.599 "),
-      font_yellow_bg(" 0.600-0.699 "),
-      font_green_bg(" 0.700-1.000"),
+      col_red(" 0.000-0.499 "),
+      col_orange(" 0.500-0.599 "),
+      col_yellow(" 0.600-0.699 "),
+      col_green(" 0.700-1.000"),
      add_fn = font_blue
    ), font_green_bg(" "), "\n", sep = "")
  }

  score_set_colour <- function(text, scores) {
    # set colours to scores
-    text[scores >= 0.7] <- font_green_bg(text[scores >= 0.7], collapse = NULL)
-    text[scores >= 0.6 & scores < 0.7] <- font_yellow_bg(text[scores >= 0.6 & scores < 0.7], collapse = NULL)
-    text[scores >= 0.5 & scores < 0.6] <- font_orange_bg(text[scores >= 0.5 & scores < 0.6], collapse = NULL)
-    text[scores < 0.5] <- font_red_bg(text[scores < 0.5], collapse = NULL)
+    text[scores >= 0.7] <- col_green(text[scores >= 0.7])
+    text[scores >= 0.6 & scores < 0.7] <- col_yellow(text[scores >= 0.6 & scores < 0.7])
+    text[scores >= 0.5 & scores < 0.6] <- col_orange(text[scores >= 0.5 & scores < 0.6])
+    text[scores < 0.5] <- col_red(text[scores < 0.5])
    text
  }
-  
+
  txt <- ""
+  any_maxed_out <- FALSE
  for (i in seq_len(nrow(x))) {
    if (x[i, ]$candidates != "") {
      candidates <- unlist(strsplit(x[i, ]$candidates, ", ", fixed = TRUE))
+      if (length(candidates) > n) {
+        any_maxed_out <- TRUE
+        candidates <- candidates[seq_len(n)]
+      }
      scores <- mo_matching_score(x = x[i, ]$input, n = candidates)
      n_candidates <- length(candidates)

@@ -835,21 +852,19 @@ print.mo_uncertainties <- function(x, ...) {
      candidates_formatted <- candidates_formatted[order(1 - scores)]
      scores_formatted <- scores_formatted[order(1 - scores)]

-      candidates <- word_wrap(paste0(
-        "Also matched: ",
-        vector_and(paste0(
-          candidates_formatted,
-          font_blue(paste0(" (", scores_formatted, ")"), collapse = NULL)
+      candidates <- word_wrap(
+        paste0(
+          "Also matched: ",
+          vector_and(
+            paste0(
+              candidates_formatted,
+              font_blue(paste0(" (", scores_formatted, ")"), collapse = NULL)
+            ),
+            quotes = FALSE, sort = FALSE
+          )
        ),
-        quotes = FALSE, sort = FALSE
-        ),
-        ifelse(n_candidates == 25,
-          font_grey(" [showing first 25]"),
-          ""
-        )
-      ),
-      extra_indent = nchar("Also matched: "),
-      width = 0.9 * getOption("width", 100)
+        extra_indent = nchar("Also matched: "),
+        width = 0.9 * getOption("width", 100)
      )
    } else {
      candidates <- ""
@@ -891,7 +906,11 @@ print.mo_uncertainties <- function(x, ...) {
    txt <- gsub("(^[\n]|[\n]$)", "", txt)
    txt <- paste0("\n", txt, "\n")
  }
+
  cat(txt)
+  if (isTRUE(any_maxed_out)) {
+    cat(font_blue(word_wrap("\nOnly the first ", n, " other matches of each record are shown. Run `print(mo_uncertainties(), n = ...)` to view more entries, or save `mo_uncertainties()` to an object.")))
+  }
 }

 #' @method print mo_renamed
@@ -954,17 +973,17 @@ convert_colloquial_input <- function(x) {
  out[x %like_case% "mil+er+i gr"] <- "B_STRPT_MILL"
  out[x %like_case% "((strepto|^s).* viridans|^vgs[^a-z]*$)"] <- "B_STRPT_VIRI"
  out[x %like_case% "(viridans.* (strepto|^s).*|^vgs[^a-z]*$)"] <- "B_STRPT_VIRI"
-  
+
  # Salmonella in different languages, like "Salmonella grupo B"
-  out[x %like_case% "salmonella.* [bcd]$"] <- gsub(".*salmonella.* ([bcd])$",
-                                                               "B_SLMNL_GRP\\U\\1",
-                                                               x[x %like_case% "salmonella.* [bcd]$"],
-                                                               perl = TRUE
+  out[x %like_case% "salmonella.* [abcd]$"] <- gsub(".*salmonella.* ([abcd])$",
+    "B_SLMNL_GRP\\U\\1",
+    x[x %like_case% "salmonella.* [abcd]$"],
+    perl = TRUE
  )
-  out[x %like_case% "group [bcd] salmonella"] <- gsub(".*group ([bcd]) salmonella*",
-                                                                  "B_SLMNL_GRP\\U\\1",
-                                                                  x[x %like_case% "group [bcd] salmonella"],
-                                                                  perl = TRUE
+  out[x %like_case% "group [abcd] salmonella"] <- gsub(".*group ([abcd]) salmonella*",
+    "B_SLMNL_GRP\\U\\1",
+    x[x %like_case% "group [abcd] salmonella"],
+    perl = TRUE
  )

  # CoNS/CoPS in different languages (support for German, Dutch, Spanish, Portuguese)
@@ -999,10 +1018,14 @@ convert_colloquial_input <- function(x) {

 italicise <- function(x) {
  out <- font_italic(x, collapse = NULL)
-  out[x %like_case% "Salmonella [A-Z]"] <- paste(font_italic("Salmonella"), 
-                                                 gsub("Salmonella ", "", x[x %like_case% "Salmonella [A-Z]"]))
-  out[x %like_case% "Streptococcus [A-Z]"] <- paste(font_italic("Streptococcus"), 
-                                                    gsub("Streptococcus ", "", x[x %like_case% "Streptococcus [A-Z]"]))
+  out[x %like_case% "Salmonella [A-Z]"] <- paste(
+    font_italic("Salmonella"),
+    gsub("Salmonella ", "", x[x %like_case% "Salmonella [A-Z]"])
+  )
+  out[x %like_case% "Streptococcus [A-Z]"] <- paste(
+    font_italic("Streptococcus"),
+    gsub("Streptococcus ", "", x[x %like_case% "Streptococcus [A-Z]"])
+  )
  if (has_colour()) {
    out <- gsub("(Group|group|Complex|complex)(\033\\[23m)?", "\033[23m\\1", out, perl = TRUE)
  }
@@ -34,13 +34,13 @@
 #' @param x Any user input value(s)
 #' @param n A full taxonomic name, that exists in [`microorganisms$fullname`][microorganisms]
 #' @note This algorithm was originally described in: Berends MS *et al.* (2022). **AMR: An R Package for Working with Antimicrobial Resistance Data**. *Journal of Statistical Software*, 104(3), 1-31; \doi{10.18637/jss.v104.i03}.
-#' 
+#'
 #' Later, the work of Bartlett A *et al.* about bacterial pathogens infecting humans (2022, \doi{10.1099/mic.0.001269}) was incorporated.
 #' @section Matching Score for Microorganisms:
 #' With ambiguous user input in [as.mo()] and all the [`mo_*`][mo_property()] functions, the returned results are chosen based on their matching score using [mo_matching_score()]. This matching score \eqn{m}, is calculated as:
 #'
 #' \ifelse{latex}{\deqn{m_{(x, n)} = \frac{l_{n} - 0.5 \cdot \min \begin{cases}l_{n} \\ \textrm{lev}(x, n)\end{cases}}{l_{n} \cdot p_{n} \cdot k_{n}}}}{
-#' 
+#'
 #' \ifelse{html}{\figure{mo_matching_score.png}{options: width="300" alt="mo matching score"}}{m(x, n) = ( l_n * min(l_n, lev(x, n) ) ) / ( l_n * p_n * k_n )}}
 #'
 #' where:
@@ -53,12 +53,12 @@
 #' * \eqn{k_n} is the taxonomic kingdom of \eqn{n}, set as Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5.
 #'
 #' The grouping into human pathogenic prevalence \eqn{p} is based on recent work from Bartlett *et al.* (2022, \doi{10.1099/mic.0.001269}) who extensively studied medical-scientific literature to categorise all bacterial species into these groups:
-#' 
+#'
 #' - **Established**, if a taxonomic species has infected at least three persons in three or more references. These records have `prevalence = 1.0` in the [microorganisms] data set;
 #' - **Putative**, if a taxonomic species has fewer than three known cases. These records have `prevalence = 1.25` in the [microorganisms] data set.
-#' 
+#'
 #' Furthermore,
-#' 
+#'
 #' - Any genus present in the **established** list also has `prevalence = 1.0` in the [microorganisms] data set;
 #' - Any other genus present in the **putative** list has `prevalence = 1.25` in the [microorganisms] data set;
 #' - Any other species or subspecies of which the genus is present in the two aforementioned groups, has `prevalence = 1.5` in the [microorganisms] data set;
@@ -72,7 +72,7 @@
 #' @inheritSection AMR Reference Data Publicly Available
 #' @examples
 #' mo_reset_session()
-#' 
+#'
 #' as.mo("E. coli")
 #' mo_uncertainties()
 #'
@@ -95,7 +95,7 @@ mo_matching_score <- function(x, n) {

  # force a capital letter, so this conversion will not count as a substitution
  substr(x, 1, 1) <- toupper(substr(x, 1, 1))
-  
+
  # n is always a taxonomically valid full name
  if (length(n) == 1) {
    n <- rep(n, length(x))
@@ -103,7 +103,7 @@ mo_matching_score <- function(x, n) {
  if (length(x) == 1) {
    x <- rep(x, length(n))
  }
-  
+
  # length of fullname
  l_n <- nchar(n)
  lev <- double(length = length(x))
@@ -126,7 +126,7 @@ mo_matching_score <- function(x, n) {
  p_n <- AMR_env$MO_lookup[match(n, AMR_env$MO_lookup$fullname), "prevalence", drop = TRUE]
  # kingdom index (Bacteria = 1, Fungi = 2, Protozoa = 3, Archaea = 4, others = 5)
  k_n <- AMR_env$MO_lookup[match(n, AMR_env$MO_lookup$fullname), "kingdom_index", drop = TRUE]
-  
+
  # matching score:
  (l_n - 0.5 * l_n.lev) / (l_n * p_n * k_n)
 }
@@ -58,7 +58,7 @@
 #'
 #' SNOMED codes ([mo_snomed()]) are from the version of `r documentation_date(TAXONOMY_VERSION$SNOMED$accessed_date)`. See *Source* and the [microorganisms] data set for more info.
 #'
-#' Old taxonomic names (so-called 'synonyms') can be retrieved with [mo_synonyms()], the current taxonomic name can be retrieved with [mo_current()]. Both functions return full names.
+#' Old taxonomic names (so-called 'synonyms') can be retrieved with [mo_synonyms()] (which will have the scientific reference as [name][base::names()]), the current taxonomic name can be retrieved with [mo_current()]. Both functions return full names.
 #'
 #' All output [will be translated][translate] where possible.
 #' @section Matching Score for Microorganisms:
@@ -69,9 +69,8 @@
 #' @return
 #' - An [integer] in case of [mo_year()]
 #' - An [ordered factor][factor] in case of [mo_pathogenicity()]
-#' - A [list] in case of [mo_taxonomy()], [mo_synonyms()] and [mo_info()]
+#' - A [list] in case of [mo_taxonomy()], [mo_synonyms()], [mo_snomed()] and [mo_info()]
 #' - A named [character] in case of [mo_url()]
-#' - A [numeric] in case of [mo_snomed()]
 #' - A [character] in all other cases
 #' @export
 #' @seealso Data set [microorganisms]
@@ -109,12 +108,12 @@
 #'
 #' # scientific reference -----------------------------------------------------
 #'
-#' mo_ref("Klebsiella pneumoniae")
-#' mo_authors("Klebsiella pneumoniae")
-#' mo_year("Klebsiella pneumoniae")
-#' mo_lpsn("Klebsiella pneumoniae")
-#' mo_gbif("Klebsiella pneumoniae")
-#' mo_synonyms("Klebsiella pneumoniae")
+#' mo_ref("Klebsiella aerogenes")
+#' mo_authors("Klebsiella aerogenes")
+#' mo_year("Klebsiella aerogenes")
+#' mo_lpsn("Klebsiella aerogenes")
+#' mo_gbif("Klebsiella aerogenes")
+#' mo_synonyms("Klebsiella aerogenes")
 #'
 #'
 #' # abbreviations known in the field -----------------------------------------
@@ -125,7 +124,8 @@
 #' mo_gramstain("VISA")
 #'
 #' mo_genus("EHEC")
-#' mo_species("EHEC")
+#' mo_species("EIEC")
+#' mo_name("UPEC")
 #'
 #'
 #' # known subspecies ---------------------------------------------------------
@@ -133,7 +133,6 @@
 #' mo_fullname("K. pneu rh")
 #' mo_shortname("K. pneu rh")
 #'
-#'
 #' \donttest{
 #' # Becker classification, see ?as.mo ----------------------------------------
 #'
@@ -158,7 +157,7 @@
 #' mo_gramstain("Klebsiella pneumoniae", language = "es") # Spanish
 #' mo_gramstain("Klebsiella pneumoniae", language = "el") # Greek
 #' mo_gramstain("Klebsiella pneumoniae", language = "uk") # Ukrainian
-#' 
+#'
 #' # mo_type is equal to mo_kingdom, but mo_kingdom will remain untranslated
 #' mo_kingdom("Klebsiella pneumoniae")
 #' mo_type("Klebsiella pneumoniae")
@@ -426,17 +425,23 @@ mo_pathogenicity <- function(x, language = get_AMR_locale(), keep_synonyms = get
  kngd <- AMR_env$MO_lookup$kingdom[match(x.mo, AMR_env$MO_lookup$mo)]
  rank <- AMR_env$MO_lookup$rank[match(x.mo, AMR_env$MO_lookup$mo)]

-  out <- factor(ifelse(prev == 1 & kngd == "Bacteria" & rank != "genus",
-                       "Pathogenic",
-                       ifelse(prev < 2 & kngd == "Fungi",
-                              "Potentially pathogenic",
-                              ifelse(prev == 2 & kngd == "Bacteria",
-                                     "Non-pathogenic",
-                                     ifelse(kngd == "Bacteria",
-                                            "Potentially pathogenic",
-                                            "Unknown")))),
-                levels = c("Pathogenic", "Potentially pathogenic", "Non-pathogenic", "Unknown"),
-                ordered = TRUE)
+  out <- factor(
+    ifelse(prev == 1 & kngd == "Bacteria" & rank != "genus",
+      "Pathogenic",
+      ifelse(prev < 2 & kngd == "Fungi",
+        "Potentially pathogenic",
+        ifelse(prev == 2 & kngd == "Bacteria",
+          "Non-pathogenic",
+          ifelse(kngd == "Bacteria",
+            "Potentially pathogenic",
+            "Unknown"
+          )
+        )
+      )
+    ),
+    levels = c("Pathogenic", "Potentially pathogenic", "Non-pathogenic", "Unknown"),
+    ordered = TRUE
+  )

  load_mo_uncertainties(metadata)
  out
@@ -727,7 +732,7 @@ mo_synonyms <- function(x, language = get_AMR_locale(), keep_synonyms = getOptio
  meet_criteria(x, allow_NA = TRUE)
  language <- validate_language(language)
  meet_criteria(keep_synonyms, allow_class = "logical", has_length = 1)
-  
+
  add_MO_lookup_to_AMR_env()

  x.mo <- as.mo(x, language = language, keep_synonyms = keep_synonyms, ...)
@@ -736,23 +741,22 @@ mo_synonyms <- function(x, language = get_AMR_locale(), keep_synonyms = getOptio
  syns <- lapply(x.mo, function(y) {
    gbif <- AMR_env$MO_lookup$gbif[match(y, AMR_env$MO_lookup$mo)]
    lpsn <- AMR_env$MO_lookup$lpsn[match(y, AMR_env$MO_lookup$mo)]
-    out <- AMR_env$MO_lookup[which(AMR_env$MO_lookup$lpsn_renamed_to == lpsn | AMR_env$MO_lookup$gbif_renamed_to == gbif), "fullname", drop = TRUE]
-    if (length(out) == 0) {
+    fullname <- AMR_env$MO_lookup[which(AMR_env$MO_lookup$lpsn_renamed_to == lpsn | AMR_env$MO_lookup$gbif_renamed_to == gbif), "fullname", drop = TRUE]
+    if (length(fullname) == 0) {
      NULL
    } else {
-      out
+      ref <- AMR_env$MO_lookup[which(AMR_env$MO_lookup$lpsn_renamed_to == lpsn | AMR_env$MO_lookup$gbif_renamed_to == gbif), "ref", drop = TRUE]
+      names(fullname) <- ref
+      fullname
    }
  })

-  if (length(syns) > 1) {
-    names(syns) <- mo_name(x, language = language)
-    result <- syns
-  } else {
-    result <- unlist(syns)
+  if (length(syns) == 1) {
+    syns <- unlist(syns)
  }

  load_mo_uncertainties(metadata)
-  result
+  syns
 }

 #' @rdname mo_property
@@ -815,7 +819,7 @@ mo_url <- function(x, open = FALSE, language = get_AMR_locale(), keep_synonyms =
  meet_criteria(open, allow_class = "logical", has_length = 1)
  language <- validate_language(language)
  meet_criteria(keep_synonyms, allow_class = "logical", has_length = 1)
-  
+
  add_MO_lookup_to_AMR_env()

  x.mo <- as.mo(x = x, language = language, keep_synonyms = keep_synonyms, ... = ...)
@@ -862,7 +866,7 @@ mo_property <- function(x, property = "fullname", language = get_AMR_locale(), k

 mo_validate <- function(x, property, language, keep_synonyms = keep_synonyms, ...) {
  add_MO_lookup_to_AMR_env()
-  
+
  # try to catch an error when inputting an invalid argument
  # so the 'call.' can be set to FALSE
  tryCatch(x[1L] %in% unlist(AMR_env$MO_lookup[1, property, drop = TRUE]),
@@ -895,12 +899,16 @@ mo_validate <- function(x, property, language, keep_synonyms = keep_synonyms, ..
  }

  # get property reeaaally fast using match()
-  x <- AMR_env$MO_lookup[[property]][match(x, AMR_env$MO_lookup$mo)]
+  if (property == "snomed") {
+    x <- lapply(x, function(y) unlist(AMR_env$MO_lookup$snomed[match(y, AMR_env$MO_lookup$mo)]))
+  } else {
+    x <- AMR_env$MO_lookup[[property]][match(x, AMR_env$MO_lookup$mo)]
+  }

  if (property == "mo") {
    return(set_clean_class(x, new_class = c("mo", "character")))
  } else if (property == "snomed") {
-    return(sort(as.character(eval(parse(text = x)))))
+    return(x)
  } else if (property == "prevalence") {
    return(as.double(x))
  } else {
@@ -33,13 +33,13 @@
 #'
 #' This is **the fastest way** to have your organisation (or analysis) specific codes picked up and translated by this package, since you don't have to bother about it again after setting it up once.
 #' @param path location of your reference file, this can be any text file (comma-, tab- or pipe-separated) or an Excel file (see *Details*). Can also be `""`, `NULL` or `FALSE` to delete the reference file.
-#' @param destination destination of the compressed data file, default to the user's home directory.
+#' @param destination destination of the compressed data file - the default is the user's home directory.
 #' @rdname mo_source
 #' @name mo_source
 #' @aliases set_mo_source get_mo_source
 #' @details The reference file can be a text file separated with commas (CSV) or tabs or pipes, an Excel file (either 'xls' or 'xlsx' format) or an \R object file (extension '.rds'). To use an Excel file, you will need to have the `readxl` package installed.
 #'
-#' [set_mo_source()] will check the file for validity: it must be a [data.frame], must have a column named `"mo"` which contains values from [`microorganisms$mo`][microorganisms] or [`microorganisms$fullname`][microorganisms] and must have a reference column with your own defined values. If all tests pass, [set_mo_source()] will read the file into \R and will ask to export it to `"~/mo_source.rds"`. The CRAN policy disallows packages to write to the file system, although '*exceptions may be allowed in interactive sessions if the package obtains confirmation from the user*'. For this reason, this function only works in interactive sessions so that the user can **specifically confirm and allow** that this file will be created. The destination of this file can be set with the `destination` argument and defaults to the user's home directory. It can also be set as an \R option, using `options(AMR_mo_source = "my/location/file.rds")`.
+#' [set_mo_source()] will check the file for validity: it must be a [data.frame], must have a column named `"mo"` which contains values from [`microorganisms$mo`][microorganisms] or [`microorganisms$fullname`][microorganisms] and must have a reference column with your own defined values. If all tests pass, [set_mo_source()] will read the file into \R and will ask to export it to `"~/mo_source.rds"`. The CRAN policy disallows packages to write to the file system, although '*exceptions may be allowed in interactive sessions if the package obtains confirmation from the user*'. For this reason, this function only works in interactive sessions so that the user can **specifically confirm and allow** that this file will be created. The destination of this file can be set with the `destination` argument and defaults to the user's home directory. It can also be set with the [package option][AMR-options] [`AMR_mo_source`][AMR-options], e.g. `options(AMR_mo_source = "my/location/file.rds")`.
 #'
 #' The created compressed data file `"mo_source.rds"` will be used at default for MO determination (function [as.mo()] and consequently all `mo_*` functions like [mo_genus()] and [mo_gramstain()]). The location and timestamp of the original file will be saved as an [attribute][base::attributes()] to the compressed data file.
 #'
@@ -149,7 +149,7 @@ set_mo_source <- function(path, destination = getOption("AMR_mo_source", "~/mo_s

  df <- NULL
  if (path %like% "[.]rds$") {
-    df <- readRDS2(path)
+    df <- readRDS_AMR(path)
  } else if (path %like% "[.]xlsx?$") {
    # is Excel file (old or new)
    stop_ifnot_installed("readxl")
@@ -248,7 +248,7 @@ get_mo_source <- function(destination = getOption("AMR_mo_source", "~/mo_source.
    return(NULL)
  }
  if (is.null(AMR_env$mo_source)) {
-    AMR_env$mo_source <- readRDS2(path.expand(destination))
+    AMR_env$mo_source <- readRDS_AMR(path.expand(destination))
  }

  old_time <- attributes(AMR_env$mo_source)$mo_source_timestamp
@@ -262,7 +262,7 @@ get_mo_source <- function(destination = getOption("AMR_mo_source", "~/mo_source.

 check_validity_mo_source <- function(x, refer_to_name = "`reference_df`", stop_on_error = TRUE) {
  add_MO_lookup_to_AMR_env()
-  
+
  if (paste(deparse(substitute(x)), collapse = "") == "get_mo_source()") {
    return(TRUE)
  }
@@ -1,39 +0,0 @@
-# ==================================================================== #
-# TITLE                                                                #
-# AMR: An R Package for Working with Antimicrobial Resistance Data     #
-#                                                                      #
-# SOURCE                                                               #
-# https://github.com/msberends/AMR                                     #
-#                                                                      #
-# CITE AS                                                              #
-# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C    #
-# (2022). AMR: An R Package for Working with Antimicrobial Resistance  #
-# Data. Journal of Statistical Software, 104(3), 1-31.                 #
-# doi:10.18637/jss.v104.i03                                            #
-#                                                                      #
-# Developed at the University of Groningen and the University Medical  #
-# Center Groningen in The Netherlands, in collaboration with many      #
-# colleagues from around the world, see our website.                   #
-#                                                                      #
-# This R package is free software; you can freely use and distribute   #
-# it for both personal and commercial purposes under the terms of the  #
-# GNU General Public License version 2.0 (GNU GPL-2), as published by  #
-# the Free Software Foundation.                                        #
-# We created this package for both routine data analysis and academic  #
-# research and it was publicly released in the hope that it will be    #
-# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY.              #
-#                                                                      #
-# Visit our website for the full manual and a complete tutorial about  #
-# how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
-# ==================================================================== #
-
-#' Options for the AMR package
-#'
-#' This is an overview of the package-specific [options()] you can set in the `AMR` package.
-#' @section Options:
-#' * `AMR_custom_ab`: allows to use custom antimicrobial drugs with this package. This is explained in [add_custom_antimicrobials()].
-#' * `AMR_custom_mo`: allows to use custom microorganisms with this package. This is explained in [add_custom_microorganisms()].
-#' @keywords internal
-#' @name AMR-options
-# @export
-NULL
@@ -34,11 +34,11 @@
 #' @param x,object values created with [as.mic()], [as.disk()] or [as.sir()] (or their `random_*` variants, such as [random_mic()])
 #' @param mo any (vector of) text that can be coerced to a valid microorganism code with [as.mo()]
 #' @param ab any (vector of) text that can be coerced to a valid antimicrobial drug code with [as.ab()]
-#' @param guideline interpretation guideline to use, defaults to the latest included EUCAST guideline, see *Details*
+#' @param guideline interpretation guideline to use - the default is the latest included EUCAST guideline, see *Details*
 #' @param main,title title of the plot
 #' @param xlab,ylab axis title
 #' @param colours_SIR colours to use for filling in the bars, must be a vector of three values (in the order S, I and R). The default colours are colour-blind friendly.
-#' @param language language to be used to translate 'Susceptible', 'Increased exposure'/'Intermediate' and 'Resistant', defaults to system language (see [get_AMR_locale()]) and can be overwritten by setting the option `AMR_locale`, e.g. `options(AMR_locale = "de")`, see [translate]. Use `language = NULL` or `language = ""` to prevent translation.
+#' @param language language to be used to translate 'Susceptible', 'Increased exposure'/'Intermediate' and 'Resistant' - the default is system language (see [get_AMR_locale()]) and can be overwritten by setting the [package option][AMR-options] [`AMR_locale`][AMR-options], e.g. `options(AMR_locale = "de")`, see [translate]. Use `language = NULL` or `language = ""` to prevent translation.
 #' @param expand a [logical] to indicate whether the range on the x axis should be expanded between the lowest and highest value. For MIC values, intermediate values will be factors of 2 starting from the highest MIC value. For disk diameters, the whole diameter range will be filled.
 #' @details
 #' The interpretation of "I" will be named "Increased exposure" for all EUCAST guidelines since 2019, and will be named "Intermediate" in all other cases.
@@ -88,8 +88,8 @@ plot.mic <- function(x,
                     ab = NULL,
                     guideline = "EUCAST",
                     main = deparse(substitute(x)),
-                     ylab = "Frequency",
-                     xlab = "Minimum Inhibitory Concentration (mg/L)",
+                     ylab = translate_AMR("Frequency", language = language),
+                     xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
                     colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
                     language = get_AMR_locale(),
                     expand = TRUE,
@@ -100,18 +100,14 @@ plot.mic <- function(x,
  meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
  meet_criteria(ylab, allow_class = "character", has_length = 1)
  meet_criteria(xlab, allow_class = "character", has_length = 1)
+  if ("colours_RSI" %in% names(list(...))) {
+    deprecation_warning(extra_msg = "The 'colours_RSI' argument has been replaced with 'colours_SIR'.")
+    colours_SIR <- list(...)$colours_RSI
+  }
  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
  language <- validate_language(language)
  meet_criteria(expand, allow_class = "logical", has_length = 1)

-  # translate if not specifically set
-  if (missing(ylab)) {
-    ylab <- translate_into_language(ylab, language = language)
-  }
-  if (missing(xlab)) {
-    xlab <- translate_into_language(xlab, language = language)
-  }
-
  if (length(colours_SIR) == 1) {
    colours_SIR <- rep(colours_SIR, 3)
  }
@@ -127,6 +123,7 @@ plot.mic <- function(x,
    colours_SIR = colours_SIR,
    fn = as.mic,
    language = language,
+    type = "MIC",
    ...
  )
  barplot(x,
@@ -146,15 +143,15 @@ plot.mic <- function(x,
    legend_txt <- character(0)
    legend_col <- character(0)
    if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) {
-      legend_txt <- "Susceptible"
+      legend_txt <- c(legend_txt, "(S) Susceptible")
      legend_col <- colours_SIR[1]
    }
    if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) {
-      legend_txt <- c(legend_txt, plot_name_of_I(cols_sub$guideline))
+      legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
      legend_col <- c(legend_col, colours_SIR[2])
    }
    if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
-      legend_txt <- c(legend_txt, "Resistant")
+      legend_txt <- c(legend_txt, "(R) Resistant")
      legend_col <- c(legend_col, colours_SIR[3])
    }

@@ -179,8 +176,8 @@ barplot.mic <- function(height,
                        ab = NULL,
                        guideline = "EUCAST",
                        main = deparse(substitute(height)),
-                        ylab = "Frequency",
-                        xlab = "Minimum Inhibitory Concentration (mg/L)",
+                        ylab = translate_AMR("Frequency", language = language),
+                        xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
                        colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
                        language = get_AMR_locale(),
                        expand = TRUE,
@@ -191,18 +188,14 @@ barplot.mic <- function(height,
  meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
  meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
  meet_criteria(guideline, allow_class = "character", has_length = 1)
+  if ("colours_RSI" %in% names(list(...))) {
+    deprecation_warning(extra_msg = "The 'colours_RSI' argument has been replaced with 'colours_SIR'.")
+    colours_SIR <- list(...)$colours_RSI
+  }
  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
  language <- validate_language(language)
  meet_criteria(expand, allow_class = "logical", has_length = 1)

-  # translate if not specifically set
-  if (missing(ylab)) {
-    ylab <- translate_into_language(ylab, language = language)
-  }
-  if (missing(xlab)) {
-    xlab <- translate_into_language(xlab, language = language)
-  }
-
  main <- gsub(" +", " ", paste0(main, collapse = " "))

  plot(
@@ -226,8 +219,8 @@ autoplot.mic <- function(object,
                         ab = NULL,
                         guideline = "EUCAST",
                         title = deparse(substitute(object)),
-                         ylab = "Frequency",
-                         xlab = "Minimum Inhibitory Concentration (mg/L)",
+                         ylab = translate_AMR("Frequency", language = language),
+                         xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
                         colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
                         language = get_AMR_locale(),
                         expand = TRUE,
@@ -239,18 +232,14 @@ autoplot.mic <- function(object,
  meet_criteria(title, allow_class = "character", allow_NULL = TRUE)
  meet_criteria(ylab, allow_class = "character", has_length = 1)
  meet_criteria(xlab, allow_class = "character", has_length = 1)
+  if ("colours_RSI" %in% names(list(...))) {
+    deprecation_warning(extra_msg = "The 'colours_RSI' argument has been replaced with 'colours_SIR'.")
+    colours_SIR <- list(...)$colours_RSI
+  }
  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
  language <- validate_language(language)
  meet_criteria(expand, allow_class = "logical", has_length = 1)

-  # translate if not specifically set
-  if (missing(ylab)) {
-    ylab <- translate_into_language(ylab, language = language)
-  }
-  if (missing(xlab)) {
-    xlab <- translate_into_language(xlab, language = language)
-  }
-
  if ("main" %in% names(list(...))) {
    title <- list(...)$main
  }
@@ -267,16 +256,22 @@ autoplot.mic <- function(object,
    colours_SIR = colours_SIR,
    fn = as.mic,
    language = language,
+    type = "MIC",
    ...
  )
  df <- as.data.frame(x, stringsAsFactors = TRUE)
  colnames(df) <- c("mic", "count")
  df$cols <- cols_sub$cols
-  df$cols[df$cols == colours_SIR[1]] <- "Susceptible"
-  df$cols[df$cols == colours_SIR[2]] <- plot_name_of_I(cols_sub$guideline)
-  df$cols[df$cols == colours_SIR[3]] <- "Resistant"
+  df$cols[df$cols == colours_SIR[1]] <- "(S) Susceptible"
+  df$cols[df$cols == colours_SIR[2]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
+  df$cols[df$cols == colours_SIR[3]] <- "(R) Resistant"
  df$cols <- factor(translate_into_language(df$cols, language = language),
-    levels = translate_into_language(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
+    levels = translate_into_language(
+      c(
+        "(S) Susceptible",
+        paste("(I)", plot_name_of_I(cols_sub$guideline)),
+        "(R) Resistant"
+      ),
      language = language
    ),
    ordered = TRUE
@@ -285,10 +280,10 @@ autoplot.mic <- function(object,

  if (any(colours_SIR %in% cols_sub$cols)) {
    vals <- c(
-      "Susceptible" = colours_SIR[1],
-      "Susceptible, incr. exp." = colours_SIR[2],
-      "Intermediate" = colours_SIR[2],
-      "Resistant" = colours_SIR[3]
+      "(S) Susceptible" = colours_SIR[1],
+      "(I) Susceptible, incr. exp." = colours_SIR[2],
+      "(I) Intermediate" = colours_SIR[2],
+      "(R) Resistant" = colours_SIR[3]
    )
    names(vals) <- translate_into_language(names(vals), language = language)
    p <- p +
@@ -324,8 +319,8 @@ fortify.mic <- function(object, ...) {
 #' @rdname plot
 plot.disk <- function(x,
                      main = deparse(substitute(x)),
-                      ylab = "Frequency",
-                      xlab = "Disk diffusion diameter (mm)",
+                      ylab = translate_AMR("Frequency", language = language),
+                      xlab = translate_AMR("Disk diffusion diameter (mm)", language = language),
                      mo = NULL,
                      ab = NULL,
                      guideline = "EUCAST",
@@ -339,18 +334,14 @@ plot.disk <- function(x,
  meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
  meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
  meet_criteria(guideline, allow_class = "character", has_length = 1)
+  if ("colours_RSI" %in% names(list(...))) {
+    deprecation_warning(extra_msg = "The 'colours_RSI' argument has been replaced with 'colours_SIR'.")
+    colours_SIR <- list(...)$colours_RSI
+  }
  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
  language <- validate_language(language)
  meet_criteria(expand, allow_class = "logical", has_length = 1)

-  # translate if not specifically set
-  if (missing(ylab)) {
-    ylab <- translate_into_language(ylab, language = language)
-  }
-  if (missing(xlab)) {
-    xlab <- translate_into_language(xlab, language = language)
-  }
-
  if (length(colours_SIR) == 1) {
    colours_SIR <- rep(colours_SIR, 3)
  }
@@ -366,6 +357,7 @@ plot.disk <- function(x,
    colours_SIR = colours_SIR,
    fn = as.disk,
    language = language,
+    type = "disk",
    ...
  )

@@ -386,15 +378,15 @@ plot.disk <- function(x,
    legend_txt <- character(0)
    legend_col <- character(0)
    if (any(cols_sub$cols == colours_SIR[3] & cols_sub$count > 0)) {
-      legend_txt <- "Resistant"
+      legend_txt <- "(R) Resistant"
      legend_col <- colours_SIR[3]
    }
    if (any(cols_sub$cols == colours_SIR[2] & cols_sub$count > 0)) {
-      legend_txt <- c(legend_txt, plot_name_of_I(cols_sub$guideline))
+      legend_txt <- c(legend_txt, paste("(I)", plot_name_of_I(cols_sub$guideline)))
      legend_col <- c(legend_col, colours_SIR[2])
    }
    if (any(cols_sub$cols == colours_SIR[1] & cols_sub$count > 0)) {
-      legend_txt <- c(legend_txt, "Susceptible")
+      legend_txt <- c(legend_txt, "(S) Susceptible")
      legend_col <- c(legend_col, colours_SIR[1])
    }
    legend("top",
@@ -415,8 +407,8 @@ plot.disk <- function(x,
 #' @noRd
 barplot.disk <- function(height,
                         main = deparse(substitute(height)),
-                         ylab = "Frequency",
-                         xlab = "Disk diffusion diameter (mm)",
+                         ylab = translate_AMR("Frequency", language = language),
+                         xlab = translate_AMR("Disk diffusion diameter (mm)", language = language),
                         mo = NULL,
                         ab = NULL,
                         guideline = "EUCAST",
@@ -430,18 +422,14 @@ barplot.disk <- function(height,
  meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
  meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
  meet_criteria(guideline, allow_class = "character", has_length = 1)
+  if ("colours_RSI" %in% names(list(...))) {
+    deprecation_warning(extra_msg = "The 'colours_RSI' argument has been replaced with 'colours_SIR'.")
+    colours_SIR <- list(...)$colours_RSI
+  }
  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
  language <- validate_language(language)
  meet_criteria(expand, allow_class = "logical", has_length = 1)

-  # translate if not specifically set
-  if (missing(ylab)) {
-    ylab <- translate_into_language(ylab, language = language)
-  }
-  if (missing(xlab)) {
-    xlab <- translate_into_language(xlab, language = language)
-  }
-
  main <- gsub(" +", " ", paste0(main, collapse = " "))

  plot(
@@ -464,8 +452,8 @@ autoplot.disk <- function(object,
                          mo = NULL,
                          ab = NULL,
                          title = deparse(substitute(object)),
-                          ylab = "Frequency",
-                          xlab = "Disk diffusion diameter (mm)",
+                          ylab = translate_AMR("Frequency", language = language),
+                          xlab = translate_AMR("Disk diffusion diameter (mm)", language = language),
                          guideline = "EUCAST",
                          colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
                          language = get_AMR_locale(),
@@ -478,18 +466,14 @@ autoplot.disk <- function(object,
  meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE)
  meet_criteria(ab, allow_class = c("ab", "character"), allow_NULL = TRUE)
  meet_criteria(guideline, allow_class = "character", has_length = 1)
+  if ("colours_RSI" %in% names(list(...))) {
+    deprecation_warning(extra_msg = "The 'colours_RSI' argument has been replaced with 'colours_SIR'.")
+    colours_SIR <- list(...)$colours_RSI
+  }
  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
  language <- validate_language(language)
  meet_criteria(expand, allow_class = "logical", has_length = 1)

-  # translate if not specifically set
-  if (missing(ylab)) {
-    ylab <- translate_into_language(ylab, language = language)
-  }
-  if (missing(xlab)) {
-    xlab <- translate_into_language(xlab, language = language)
-  }
-
  if ("main" %in% names(list(...))) {
    title <- list(...)$main
  }
@@ -506,17 +490,23 @@ autoplot.disk <- function(object,
    colours_SIR = colours_SIR,
    fn = as.disk,
    language = language,
+    type = "disk",
    ...
  )
  df <- as.data.frame(x, stringsAsFactors = TRUE)
  colnames(df) <- c("disk", "count")
  df$cols <- cols_sub$cols

-  df$cols[df$cols == colours_SIR[1]] <- "Susceptible"
-  df$cols[df$cols == colours_SIR[2]] <- plot_name_of_I(cols_sub$guideline)
-  df$cols[df$cols == colours_SIR[3]] <- "Resistant"
+  df$cols[df$cols == colours_SIR[1]] <- "(S) Susceptible"
+  df$cols[df$cols == colours_SIR[2]] <- paste("(I)", plot_name_of_I(cols_sub$guideline))
+  df$cols[df$cols == colours_SIR[3]] <- "(R) Resistant"
  df$cols <- factor(translate_into_language(df$cols, language = language),
-    levels = translate_into_language(c("Susceptible", plot_name_of_I(cols_sub$guideline), "Resistant"),
+    levels = translate_into_language(
+      c(
+        "(S) Susceptible",
+        paste("(I)", plot_name_of_I(cols_sub$guideline)),
+        "(R) Resistant"
+      ),
      language = language
    ),
    ordered = TRUE
@@ -525,10 +515,10 @@ autoplot.disk <- function(object,

  if (any(colours_SIR %in% cols_sub$cols)) {
    vals <- c(
-      "Susceptible" = colours_SIR[1],
-      "Susceptible, incr. exp." = colours_SIR[2],
-      "Intermediate" = colours_SIR[2],
-      "Resistant" = colours_SIR[3]
+      "(S) Susceptible" = colours_SIR[1],
+      "(I) Susceptible, incr. exp." = colours_SIR[2],
+      "(I) Intermediate" = colours_SIR[2],
+      "(R) Resistant" = colours_SIR[3]
    )
    names(vals) <- translate_into_language(names(vals), language = language)
    p <- p +
@@ -563,8 +553,8 @@ fortify.disk <- function(object, ...) {
 #' @importFrom graphics plot text axis
 #' @rdname plot
 plot.sir <- function(x,
-                     ylab = "Percentage",
-                     xlab = "Antimicrobial Interpretation",
+                     ylab = translate_AMR("Percentage", language = language),
+                     xlab = translate_AMR("Antimicrobial Interpretation", language = language),
                     main = deparse(substitute(x)),
                     language = get_AMR_locale(),
                     ...) {
@@ -572,32 +562,18 @@ plot.sir <- function(x,
  meet_criteria(xlab, allow_class = "character", has_length = 1)
  meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)

-  # translate if not specifically set
-  if (missing(ylab)) {
-    ylab <- translate_into_language(ylab, language = language)
-  }
-  if (missing(xlab)) {
-    xlab <- translate_into_language(xlab, language = language)
-  }
-
  data <- as.data.frame(table(x), stringsAsFactors = FALSE)
  colnames(data) <- c("x", "n")
  data$s <- round((data$n / sum(data$n)) * 100, 1)

  if (!"S" %in% data$x) {
-    data <- rbind(data, data.frame(x = "S", n = 0, s = 0, stringsAsFactors = FALSE),
-      stringsAsFactors = FALSE
-    )
+    data <- rbind_AMR(data, data.frame(x = "S", n = 0, s = 0, stringsAsFactors = FALSE))
  }
  if (!"I" %in% data$x) {
-    data <- rbind(data, data.frame(x = "I", n = 0, s = 0, stringsAsFactors = FALSE),
-      stringsAsFactors = FALSE
-    )
+    data <- rbind_AMR(data, data.frame(x = "I", n = 0, s = 0, stringsAsFactors = FALSE))
  }
  if (!"R" %in% data$x) {
-    data <- rbind(data, data.frame(x = "R", n = 0, s = 0, stringsAsFactors = FALSE),
-      stringsAsFactors = FALSE
-    )
+    data <- rbind_AMR(data, data.frame(x = "R", n = 0, s = 0, stringsAsFactors = FALSE))
  }

  data$x <- factor(data$x, levels = c("S", "I", "R"), ordered = TRUE)
@@ -633,8 +609,8 @@ plot.sir <- function(x,
 #' @noRd
 barplot.sir <- function(height,
                        main = deparse(substitute(height)),
-                        xlab = "Antimicrobial Interpretation",
-                        ylab = "Frequency",
+                        xlab = translate_AMR("Antimicrobial Interpretation", language = language),
+                        ylab = translate_AMR("Frequency", language = language),
                        colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
                        language = get_AMR_locale(),
                        expand = TRUE,
@@ -642,18 +618,14 @@ barplot.sir <- function(height,
  meet_criteria(xlab, allow_class = "character", has_length = 1)
  meet_criteria(main, allow_class = "character", has_length = 1, allow_NULL = TRUE)
  meet_criteria(ylab, allow_class = "character", has_length = 1)
+  if ("colours_RSI" %in% names(list(...))) {
+    deprecation_warning(extra_msg = "The 'colours_RSI' argument has been replaced with 'colours_SIR'.")
+    colours_SIR <- list(...)$colours_RSI
+  }
  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))
  language <- validate_language(language)
  meet_criteria(expand, allow_class = "logical", has_length = 1)

-  # translate if not specifically set
-  if (missing(ylab)) {
-    ylab <- translate_into_language(ylab, language = language)
-  }
-  if (missing(xlab)) {
-    xlab <- translate_into_language(xlab, language = language)
-  }
-
  if (length(colours_SIR) == 1) {
    colours_SIR <- rep(colours_SIR, 3)
  }
@@ -676,8 +648,8 @@ barplot.sir <- function(height,
 # will be exported using s3_register() in R/zzz.R
 autoplot.sir <- function(object,
                         title = deparse(substitute(object)),
-                         xlab = "Antimicrobial Interpretation",
-                         ylab = "Frequency",
+                         xlab = translate_AMR("Antimicrobial Interpretation", language = language),
+                         ylab = translate_AMR("Frequency", language = language),
                         colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
                         language = get_AMR_locale(),
                         ...) {
@@ -687,14 +659,6 @@ autoplot.sir <- function(object,
  meet_criteria(xlab, allow_class = "character", has_length = 1)
  meet_criteria(colours_SIR, allow_class = "character", has_length = c(1, 3))

-  # translate if not specifically set
-  if (missing(ylab)) {
-    ylab <- translate_into_language(ylab, language = language)
-  }
-  if (missing(xlab)) {
-    xlab <- translate_into_language(xlab, language = language)
-  }
-
  if ("main" %in% names(list(...))) {
    title <- list(...)$main
  }
@@ -780,33 +744,44 @@ plot_name_of_I <- function(guideline) {
  }
 }

-plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_SIR, fn, language, ...) {
+plot_colours_subtitle_guideline <- function(x, mo, ab, guideline, colours_SIR, fn, language, type, ...) {
  guideline <- get_guideline(guideline, AMR::clinical_breakpoints)
  if (!is.null(mo) && !is.null(ab)) {
    # interpret and give colour based on MIC values
    mo <- as.mo(mo)
-    ab <- as.ab(ab)
-    sir <- suppressWarnings(suppressMessages(as.sir(fn(names(x)), mo = mo, ab = ab, guideline = guideline, ...)))
-    cols <- character(length = length(sir))
-    cols[is.na(sir)] <- "#BEBEBE"
-    cols[sir == "S"] <- colours_SIR[1]
-    cols[sir == "I"] <- colours_SIR[2]
-    cols[sir == "R"] <- colours_SIR[3]
    moname <- mo_name(mo, language = language)
+    ab <- as.ab(ab)
    abname <- ab_name(ab, language = language)
-    if (all(cols == "#BEBEBE")) {
-      message_(
-        "No ", guideline, " interpretations found for ",
-        ab_name(ab, language = NULL, tolower = TRUE), " in ", moname
-      )
-      guideline_txt <- ""
+
+    sir <- suppressWarnings(suppressMessages(as.sir(fn(names(x)), mo = mo, ab = ab, guideline = guideline, include_screening = FALSE, include_PKPD = TRUE, ...)))
+    guideline_txt <- guideline
+    if (all(is.na(sir))) {
+      sir_screening <- suppressWarnings(suppressMessages(as.sir(fn(names(x)), mo = mo, ab = ab, guideline = guideline, include_screening = TRUE, include_PKPD = TRUE, ...)))
+      if (!all(is.na(sir_screening))) {
+        message_(
+          "Only ", guideline, " ", type, " interpretations found for ",
+          ab_name(ab, language = NULL, tolower = TRUE), " in ", italicise(moname), " for screening"
+        )
+        sir <- sir_screening
+        guideline_txt <- paste0("(Screen, ", guideline_txt, ")")
+      } else {
+        message_(
+          "No ", guideline, " ", type, " interpretations found for ",
+          ab_name(ab, language = NULL, tolower = TRUE), " in ", italicise(moname)
+        )
+        guideline_txt <- ""
+      }
    } else {
-      guideline_txt <- guideline
      if (isTRUE(list(...)$uti)) {
        guideline_txt <- paste("UTIs,", guideline_txt)
      }
      guideline_txt <- paste0("(", guideline_txt, ")")
    }
+    cols <- character(length = length(sir))
+    cols[is.na(sir)] <- "#BEBEBE"
+    cols[sir == "S"] <- colours_SIR[1]
+    cols[sir == "I"] <- colours_SIR[2]
+    cols[sir == "R"] <- colours_SIR[3]
    sub <- bquote(.(abname) ~ "-" ~ italic(.(moname)) ~ .(guideline_txt))
  } else {
    cols <- "#BEBEBE"
@@ -27,7 +27,7 @@
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #

-#' Calculate Microbial Resistance
+#' Calculate Antimicrobial Resistance
 #'
 #' @description These functions can be used to calculate the (co-)resistance or susceptibility of microbial isolates (i.e. percentage of S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, see *Examples*.
 #'
@@ -39,17 +39,18 @@
 #' @param data a [data.frame] containing columns with class [`sir`] (see [as.sir()])
 #' @param translate_ab a column name of the [antibiotics] data set to translate the antibiotic abbreviations to, using [ab_property()]
 #' @inheritParams ab_property
-#' @param combine_SI a [logical] to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant), defaults to `TRUE`
+#' @param combine_SI a [logical] to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant) - the default is `TRUE`
 #' @param ab_result antibiotic results to test against, must be one or more values of "S", "I", or "R"
 #' @param confidence_level the confidence level for the returned confidence interval. For the calculation, the number of S or SI isolates, and R isolates are compared with the total number of available isolates with R, S, or I by using [binom.test()], i.e., the Clopper-Pearson method.
-#' @param side the side of the confidence interval to return. Defaults to `"both"` for a length 2 vector, but can also be (abbreviated as) `"min"`/`"left"`/`"lower"`/`"less"` or `"max"`/`"right"`/`"higher"`/`"greater"`.
+#' @param side the side of the confidence interval to return. The default is `"both"` for a length 2 vector, but can also be (abbreviated as) `"min"`/`"left"`/`"lower"`/`"less"` or `"max"`/`"right"`/`"higher"`/`"greater"`.
+#' @param collapse a [logical] to indicate whether the output values should be 'collapsed', i.e. be merged together into one value, or a character value to use for collapsing
 #' @inheritSection as.sir Interpretation of SIR
 #' @details
 #' The function [resistance()] is equal to the function [proportion_R()]. The function [susceptibility()] is equal to the function [proportion_SI()].
 #'
 #' Use [sir_confidence_interval()] to calculate the confidence interval, which relies on [binom.test()], i.e., the Clopper-Pearson method. This function returns a vector of length 2 at default for antimicrobial *resistance*. Change the `side` argument to "left"/"min" or "right"/"max" to return a single value, and change the `ab_result` argument to e.g. `c("S", "I")` to test for antimicrobial *susceptibility*, see Examples.
 #'
-#' **Remember that you should filter your data to let it contain only first isolates!** This is needed to exclude duplicates and to reduce selection bias. Use [first_isolate()] to determine them in your data set.
+#' **Remember that you should filter your data to let it contain only first isolates!** This is needed to exclude duplicates and to reduce selection bias. Use [first_isolate()] to determine them in your data set with one of the four available algorithms.
 #'
 #' These functions are not meant to count isolates, but to calculate the proportion of resistance/susceptibility. Use the [`count()`][AMR::count()] functions to count isolates. The function [susceptibility()] is essentially equal to `count_susceptible() / count_all()`. *Low counts can influence the outcome - the `proportion` functions may camouflage this, since they only return the proportion (albeit being dependent on the `minimum` argument).*
 #'
@@ -57,6 +58,7 @@
 #' @section Combination Therapy:
 #' When using more than one variable for `...` (= combination therapy), use `only_all_tested` to only count isolates that are tested for all antibiotics/variables that you test them for. See this example for two antibiotics, Drug A and Drug B, about how [susceptibility()] works to calculate the %SI:
 #'
+#'
 #' ```
 #' --------------------------------------------------------------------
 #'                     only_all_tested = FALSE  only_all_tested = TRUE
@@ -77,11 +79,14 @@
 #' ```
 #'
 #' Please note that, in combination therapies, for `only_all_tested = TRUE` applies that:
+#'
 #' ```
 #'     count_S()    +   count_I()    +   count_R()    = count_all()
 #'   proportion_S() + proportion_I() + proportion_R() = 1
 #' ```
+#'
 #' and that, in combination therapies, for `only_all_tested = FALSE` applies that:
+#'
 #' ```
 #'     count_S()    +   count_I()    +   count_R()    >= count_all()
 #'   proportion_S() + proportion_I() + proportion_R() >= 1
@@ -98,6 +103,8 @@
 #' @examples
 #' # example_isolates is a data set available in the AMR package.
 #' # run ?example_isolates for more info.
+#' example_isolates
+#'
 #'
 #' # base R ------------------------------------------------------------
 #' # determines %R
@@ -106,6 +113,10 @@
 #' sir_confidence_interval(example_isolates$AMX,
 #'   confidence_level = 0.975
 #' )
+#' sir_confidence_interval(example_isolates$AMX,
+#'   confidence_level = 0.975,
+#'   collapse = ", "
+#' )
 #'
 #' # determines %S+I:
 #' susceptibility(example_isolates$AMX)
@@ -140,7 +151,6 @@
 #'     )
 #' }
 #' if (require("dplyr")) {
-#'
 #'   # scoped dplyr verbs with antibiotic selectors
 #'   # (you could also use across() of course)
 #'   example_isolates %>%
@@ -255,10 +265,16 @@ sir_confidence_interval <- function(...,
                                    as_percent = FALSE,
                                    only_all_tested = FALSE,
                                    confidence_level = 0.95,
-                                    side = "both") {
+                                    side = "both",
+                                    collapse = FALSE) {
  meet_criteria(ab_result, allow_class = c("character", "sir"), has_length = c(1, 2, 3), is_in = c("S", "I", "R"))
+  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
+  meet_criteria(as_percent, allow_class = "logical", has_length = 1)
+  meet_criteria(only_all_tested, allow_class = "logical", has_length = 1)
  meet_criteria(confidence_level, allow_class = "numeric", is_positive = TRUE, has_length = 1)
  meet_criteria(side, allow_class = "character", has_length = 1, is_in = c("both", "b", "left", "l", "lower", "lowest", "less", "min", "right", "r", "higher", "highest", "greater", "g", "max"))
+  meet_criteria(collapse, allow_class = c("logical", "character"), has_length = 1)
+
  x <- tryCatch(
    sir_calc(...,
      ab_result = ab_result,
@@ -276,19 +292,7 @@ sir_confidence_interval <- function(...,
    error = function(e) stop_(gsub("in sir_calc(): ", "", e$message, fixed = TRUE), call = -5)
  )

-  if (n < minimum) {
-    warning_("Introducing NA: ",
-      ifelse(n == 0, "no", paste("only", n)),
-      " results available for `sir_confidence_interval()` (`minimum` = ", minimum, ").",
-      call = FALSE
-    )
-    if (as_percent == TRUE) {
-      return(NA_character_)
-    } else {
-      return(NA_real_)
-    }
-  }
-
+  # this applies the Clopper-Pearson method
  out <- stats::binom.test(x = x, n = n, conf.level = confidence_level)$conf.int
  out <- set_clean_class(out, "double")

@@ -297,11 +301,30 @@ sir_confidence_interval <- function(...,
  } else if (side %in% c("right", "r", "higher", "highest", "greater", "g", "max")) {
    out <- out[2]
  }
-  if (as_percent == TRUE) {
-    percentage(out, digits = 1)
-  } else {
-    out
+  if (isTRUE(as_percent)) {
+    out <- percentage(out, digits = 1)
  }
+  if (!isFALSE(collapse) && length(out) > 1) {
+    if (is.numeric(out)) {
+      out <- round(out, digits = 3)
+    }
+    out <- paste(out, collapse = ifelse(isTRUE(collapse), "-", collapse))
+  }
+
+  if (n < minimum) {
+    warning_("Introducing NA: ",
+      ifelse(n == 0, "no", paste("only", n)),
+      " results available for `sir_confidence_interval()` (`minimum` = ", minimum, ").",
+      call = FALSE
+    )
+    if (is.character(out)) {
+      return(NA_character_)
+    } else {
+      return(NA_real_)
+    }
+  }
+
+  out
 }

 #' @rdname proportion
@@ -83,6 +83,10 @@ random_disk <- function(size = NULL, mo = NULL, ab = NULL, ...) {
 #' @export
 random_sir <- function(size = NULL, prob_SIR = c(0.33, 0.33, 0.33), ...) {
  meet_criteria(size, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE, allow_NULL = TRUE)
+  if ("prob_RSI" %in% names(list(...))) {
+    deprecation_warning("prob_RSI", "prob_SIR", is_function = FALSE)
+    prob_SIR <- list(...)$prob_RSI
+  }
  meet_criteria(prob_SIR, allow_class = c("numeric", "integer"), has_length = 3)
  if (is.null(size)) {
    size <- NROW(get_current_data(arg_name = "size", call = -3))
@@ -91,7 +95,7 @@ random_sir <- function(size = NULL, prob_SIR = c(0.33, 0.33, 0.33), ...) {
 }

 random_exec <- function(type, size, mo = NULL, ab = NULL) {
-  df <- clinical_breakpoints %pm>%
+  df <- AMR::clinical_breakpoints %pm>%
    pm_filter(guideline %like% "EUCAST") %pm>%
    pm_arrange(pm_desc(guideline)) %pm>%
    subset(guideline == max(guideline) &
@@ -32,9 +32,9 @@
 #' Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns `se_min` and `se_max`. See *Examples* for a real live example.
 #' @param object model data to be plotted
 #' @param col_ab column name of `x` containing antimicrobial interpretations (`"R"`, `"I"` and `"S"`)
-#' @param col_date column name of the date, will be used to calculate years if this column doesn't consist of years already, defaults to the first column of with a date class
+#' @param col_date column name of the date, will be used to calculate years if this column doesn't consist of years already - the default is the first column of with a date class
 #' @param year_min lowest year to use in the prediction model, dafaults to the lowest year in `col_date`
-#' @param year_max highest year to use in the prediction model, defaults to 10 years after today
+#' @param year_max highest year to use in the prediction model - the default is 10 years after today
 #' @param year_every unit of sequence between lowest year found in the data and `year_max`
 #' @param minimum minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.
 #' @param model the statistical model of choice. This could be a generalised linear regression model with binomial distribution (i.e. using `glm(..., family = binomial)`, assuming that a period of zero resistance was followed by a period of increasing resistance leading slowly to more and more resistance. See *Details* for all valid options.
@@ -125,7 +125,7 @@ resistance_predict <- function(x,
  meet_criteria(year_min, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
  meet_criteria(year_max, allow_class = c("numeric", "integer"), has_length = 1, allow_NULL = TRUE, is_positive = TRUE, is_finite = TRUE)
  meet_criteria(year_every, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
-  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
+  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
  meet_criteria(model, allow_class = c("character", "function"), has_length = 1, allow_NULL = TRUE)
  meet_criteria(I_as_S, allow_class = "logical", has_length = 1)
  meet_criteria(preserve_measurements, allow_class = "logical", has_length = 1)
@@ -274,7 +274,7 @@ resistance_predict <- function(x,
  df_prediction$value <- ifelse(df_prediction$value > 1, 1, pmax(df_prediction$value, 0))
  df_prediction <- df_prediction[order(df_prediction$year), , drop = FALSE]

-  out <- as_original_data_class(df_prediction, class(x.bak))  # will remove tibble groups
+  out <- as_original_data_class(df_prediction, class(x.bak)) # will remove tibble groups
  structure(out,
    class = c("resistance_predict", class(out)),
    I_as_S = I_as_S,
@@ -29,16 +29,20 @@

 #' Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data
 #'
-#' Interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI, or clean up existing SIR values. This transforms the input to a new class [`sir`], which is an ordered [factor] with levels `S < I < R`.
+#' @description Interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI, or clean up existing SIR values. This transforms the input to a new class [`sir`], which is an ordered [factor] with levels `S < I < R`.
+#'
+#' All breakpoints used for interpretation are publicly available in the [clinical_breakpoints] data set.
 #' @rdname as.sir
 #' @param x vector of values (for class [`mic`]: MIC values in mg/L, for class [`disk`]: a disk diffusion radius in millimetres)
 #' @param mo any (vector of) text that can be coerced to valid microorganism codes with [as.mo()], can be left empty to determine it automatically
 #' @param ab any (vector of) text that can be coerced to a valid antimicrobial drug code with [as.ab()]
 #' @param uti (Urinary Tract Infection) A vector with [logical]s (`TRUE` or `FALSE`) to specify whether a UTI specific interpretation from the guideline should be chosen. For using [as.sir()] on a [data.frame], this can also be a column containing [logical]s or when left blank, the data set will be searched for a column 'specimen', and rows within this column containing 'urin' (such as 'urine', 'urina') will be regarded isolates from a UTI. See *Examples*.
 #' @inheritParams first_isolate
-#' @param guideline defaults to EUCAST `r  max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))` (the latest implemented EUCAST guideline in the [clinical_breakpoints] data set), but can be set with the [option][options()] `AMR_guideline`. Supports EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`), see *Details*.
+#' @param guideline defaults to EUCAST `r  max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))` (the latest implemented EUCAST guideline in the [AMR::clinical_breakpoints] data set), but can be set with the [package option][AMR-options] [`AMR_guideline`][AMR-options]. Currently supports EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`), see *Details*.
 #' @param conserve_capped_values a [logical] to indicate that MIC values starting with `">"` (but not `">="`) must always return "R" , and that MIC values starting with `"<"` (but not `"<="`) must always return "S"
 #' @param add_intrinsic_resistance *(only useful when using a EUCAST guideline)* a [logical] to indicate whether intrinsic antibiotic resistance must also be considered for applicable bug-drug combinations, meaning that e.g. ampicillin will always return "R" in *Klebsiella* species. Determination is based on the [intrinsic_resistant] data set, that itself is based on `r format_eucast_version_nr(3.3)`.
+#' @param include_screening a [logical] to indicate that clinical breakpoints for screening are allowed - the default is `FALSE`. Can also be set with the [package option][AMR-options] [`AMR_include_screening`][AMR-options].
+#' @param include_PKPD a [logical] to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is `TRUE`. Can also be set with the [package option][AMR-options] [`AMR_include_PKPD`][AMR-options].
 #' @param reference_data a [data.frame] to be used for interpretation, which defaults to the [clinical_breakpoints] data set. Changing this argument allows for using own interpretation guidelines. This argument must contain a data set that is equal in structure to the [clinical_breakpoints] data set (same column names and column types). Please note that the `guideline` argument will be ignored when `reference_data` is manually set.
 #' @param threshold maximum fraction of invalid antimicrobial interpretations of `x`, see *Examples*
 #' @param ... for using on a [data.frame]: names of columns to apply [as.sir()] on (supports tidy selection such as `column1:column4`). Otherwise: arguments passed on to methods.
@@ -64,16 +68,16 @@
 #'      ```
 #' 4. For **interpreting a complete data set**, with automatic determination of MIC values, disk diffusion diameters, microorganism names or codes, and antimicrobial test results. This is done very simply by running `as.sir(your_data)`.
 #'
-#' For points 2, 3 and 4: Use [sir_interpretation_history()] to retrieve a [data.frame] (or [tibble][tibble::tibble()] if the `tibble` package is installed) with all results of the last [as.sir()] call.
+#' **For points 2, 3 and 4: Use [sir_interpretation_history()]** to retrieve a [data.frame] (or [tibble][tibble::tibble()] if the `tibble` package is installed) with all results of the last [as.sir()] call.
 #'
 #' ### Supported Guidelines
 #'
-#' For interpreting MIC values as well as disk diffusion diameters, currently implemented guidelines are EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`).
+#' For interpreting MIC values as well as disk diffusion diameters, currently implemented guidelines are EUCAST (`r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`) and CLSI (`r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`).
+#'
+#' Thus, the `guideline` argument must be set to e.g., ``r paste0('"', subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline[1], '"')`` or ``r paste0('"', subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline[1], '"')``. By simply using `"EUCAST"` (the default) or `"CLSI"` as input, the latest included version of that guideline will automatically be selected. You can set your own data set using the `reference_data` argument. The `guideline` argument will then be ignored.
+#'
+#' You can set the default guideline with the [package option][AMR-options] [`AMR_guideline`][AMR-options] (e.g. in your `.Rprofile` file), such as:
 #'
-#' Thus, the `guideline` argument must be set to e.g., ``r paste0('"', subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline[1], '"')`` or ``r paste0('"', subset(clinical_breakpoints, guideline %like% "CLSI")$guideline[1], '"')``. By simply using `"EUCAST"` (the default) or `"CLSI"` as input, the latest included version of that guideline will automatically be selected. You can set your own data set using the `reference_data` argument. The `guideline` argument will then be ignored.
-#' 
-#' You can set the default guideline with the `AMR_guideline` [option][options()] (e.g. in your `.Rprofile` file), such as:
-#' 
 #' ```
 #'   options(AMR_guideline = "CLSI")
 #'   options(AMR_guideline = "CLSI 2018")
@@ -86,9 +90,9 @@
 #'
 #' After using [as.sir()], you can use the [eucast_rules()] defined by EUCAST to (1) apply inferred susceptibility and resistance based on results of other antimicrobials and (2) apply intrinsic resistance based on taxonomic properties of a microorganism.
 #'
-#' ### Machine-Readable Interpretation Guidelines
+#' ### Machine-Readable Clinical Breakpoints
 #'
-#' The repository of this package [contains a machine-readable version](https://github.com/msberends/AMR/blob/main/data-raw/clinical_breakpoints.txt) of all guidelines. This is a CSV file consisting of `r format(nrow(AMR::clinical_breakpoints), big.mark = ",")` rows and `r ncol(AMR::clinical_breakpoints)` columns. This file is machine-readable, since it contains one row for every unique combination of the test method (MIC or disk diffusion), the antimicrobial drug and the microorganism. **This allows for easy implementation of these rules in laboratory information systems (LIS)**. Note that it only contains interpretation guidelines for humans - interpretation guidelines from CLSI for animals were removed.
+#' The repository of this package [contains a machine-readable version](https://github.com/msberends/AMR/blob/main/data-raw/clinical_breakpoints.txt) of all guidelines. This is a CSV file consisting of `r format(nrow(AMR::clinical_breakpoints), big.mark = " ")` rows and `r ncol(AMR::clinical_breakpoints)` columns. This file is machine-readable, since it contains one row for every unique combination of the test method (MIC or disk diffusion), the antimicrobial drug and the microorganism. **This allows for easy implementation of these rules in laboratory information systems (LIS)**. Note that it only contains interpretation guidelines for humans - interpretation guidelines from CLSI for animals were removed.
 #'
 #' ### Other
 #'
@@ -104,7 +108,7 @@
 #'   A microorganism is categorised as "Susceptible, Increased exposure*" when there is a high likelihood of therapeutic success because exposure to the agent is increased by adjusting the dosing regimen or by its concentration at the site of infection.
 #' - **R = Resistant**\cr
 #'   A microorganism is categorised as "Resistant" when there is a high likelihood of therapeutic failure even when there is increased exposure.
-#'   
+#'
 #'   * *Exposure* is a function of how the mode of administration, dose, dosing interval, infusion time, as well as distribution and excretion of the antimicrobial agent will influence the infecting organism at the site of infection.
 #'
 #' This AMR package honours this insight. Use [susceptibility()] (equal to [proportion_SI()]) to determine antimicrobial susceptibility and [count_susceptible()] (equal to [count_SI()]) to count susceptible isolates.
@@ -115,9 +119,9 @@
 #' @source
 #' For interpretations of minimum inhibitory concentration (MIC) values and disk diffusion diameters:
 #'
-#' - **M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data**, `r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`, *Clinical and Laboratory Standards Institute* (CLSI). <https://clsi.org/standards/products/microbiology/documents/m39/>.
-#' - **M100 Performance Standard for Antimicrobial Susceptibility Testing**, `r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "CLSI")$guideline)))`, *Clinical and Laboratory Standards Institute* (CLSI). <https://clsi.org/standards/products/microbiology/documents/m100/>.
-#' - **Breakpoint tables for interpretation of MICs and zone diameters**, `r min(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`, *European Committee on Antimicrobial Susceptibility Testing* (EUCAST). <https://www.eucast.org/clinical_breakpoints>.
+#' - **M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data**, `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`, *Clinical and Laboratory Standards Institute* (CLSI). <https://clsi.org/standards/products/microbiology/documents/m39/>.
+#' - **M100 Performance Standard for Antimicrobial Susceptibility Testing**, `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI")$guideline)))`, *Clinical and Laboratory Standards Institute* (CLSI). <https://clsi.org/standards/products/microbiology/documents/m100/>.
+#' - **Breakpoint tables for interpretation of MICs and zone diameters**, `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST")$guideline)))`, *European Committee on Antimicrobial Susceptibility Testing* (EUCAST). <https://www.eucast.org/clinical_breakpoints>.
 #' @inheritSection AMR Reference Data Publicly Available
 #' @examples
 #' example_isolates
@@ -228,7 +232,12 @@ is.sir <- function(x) {
  if (inherits(x, "data.frame")) {
    unname(vapply(FUN.VALUE = logical(1), x, is.sir))
  } else {
-    inherits(x, "sir")
+    rsi <- inherits(x, "rsi")
+    sir <- inherits(x, "sir")
+    if (isTRUE(rsi) && message_not_thrown_before("is.sir-rsi")) {
+      deprecation_warning(extra_msg = "The 'rsi' class has been replaced with 'sir'. Transform your 'rsi' columns to 'sir' with `as.sir()`, e.g.:\n  your_data %>% mutate_if(is.rsi, as.sir)")
+    }
+    isTRUE(rsi) || isTRUE(sir)
  }
 }

@@ -291,13 +300,13 @@ is_sir_eligible <- function(x, threshold = 0.05) {
 #' @export
 # extra param: warn (logical, to never throw a warning)
 as.sir.default <- function(x, ...) {
-  if (is.sir(x)) {
+  if (inherits(x, "sir")) {
    return(x)
  }

  x.bak <- x
  x <- as.character(x) # this is needed to prevent the vctrs pkg from throwing an error
-  
+
  if (inherits(x.bak, c("integer", "numeric", "double")) && all(x %in% c(1:3, NA))) {
    # support haven package for importing e.g., from SPSS - it adds the 'labels' attribute
    lbls <- attributes(x.bak)$labels
@@ -328,7 +337,7 @@ as.sir.default <- function(x, ...) {
    x <- trimws2(as.character(unlist(x)))
    x[x %in% c(NA, "", "-", "NULL")] <- NA_character_
    x.bak <- x
-    
+
    na_before <- length(x[is.na(x)])

    # correct for translations
@@ -417,6 +426,8 @@ as.sir.mic <- function(x,
                       conserve_capped_values = FALSE,
                       add_intrinsic_resistance = FALSE,
                       reference_data = AMR::clinical_breakpoints,
+                       include_screening = getOption("AMR_include_screening", FALSE),
+                       include_PKPD = getOption("AMR_include_PKPD", TRUE),
                       ...) {
  as_sir_method(
    method_short = "mic",
@@ -429,6 +440,8 @@ as.sir.mic <- function(x,
    conserve_capped_values = conserve_capped_values,
    add_intrinsic_resistance = add_intrinsic_resistance,
    reference_data = reference_data,
+    include_screening = include_screening,
+    include_PKPD = include_PKPD,
    ...
  )
 }
@@ -442,6 +455,8 @@ as.sir.disk <- function(x,
                        uti = NULL,
                        add_intrinsic_resistance = FALSE,
                        reference_data = AMR::clinical_breakpoints,
+                        include_screening = getOption("AMR_include_screening", FALSE),
+                        include_PKPD = getOption("AMR_include_PKPD", TRUE),
                        ...) {
  as_sir_method(
    method_short = "disk",
@@ -454,6 +469,8 @@ as.sir.disk <- function(x,
    conserve_capped_values = FALSE,
    add_intrinsic_resistance = add_intrinsic_resistance,
    reference_data = reference_data,
+    include_screening = include_screening,
+    include_PKPD = include_PKPD,
    ...
  )
 }
@@ -467,7 +484,9 @@ as.sir.data.frame <- function(x,
                              uti = NULL,
                              conserve_capped_values = FALSE,
                              add_intrinsic_resistance = FALSE,
-                              reference_data = AMR::clinical_breakpoints) {
+                              reference_data = AMR::clinical_breakpoints,
+                              include_screening = getOption("AMR_include_screening", FALSE),
+                              include_PKPD = getOption("AMR_include_PKPD", TRUE)) {
  meet_criteria(x, allow_class = "data.frame") # will also check for dimensions > 0
  meet_criteria(col_mo, allow_class = "character", is_in = colnames(x), allow_NULL = TRUE)
  meet_criteria(guideline, allow_class = "character", has_length = 1)
@@ -604,6 +623,8 @@ as.sir.data.frame <- function(x,
          conserve_capped_values = conserve_capped_values,
          add_intrinsic_resistance = add_intrinsic_resistance,
          reference_data = reference_data,
+          include_screening = include_screening,
+          include_PKPD = include_PKPD,
          is_data.frame = TRUE
        )
    } else if (types[i] == "disk") {
@@ -619,6 +640,8 @@ as.sir.data.frame <- function(x,
          uti = uti,
          add_intrinsic_resistance = add_intrinsic_resistance,
          reference_data = reference_data,
+          include_screening = include_screening,
+          include_PKPD = include_PKPD,
          is_data.frame = TRUE
        )
    } else if (types[i] == "sir") {
@@ -686,6 +709,8 @@ as_sir_method <- function(method_short,
                          conserve_capped_values,
                          add_intrinsic_resistance,
                          reference_data,
+                          include_screening,
+                          include_PKPD,
                          ...) {
  meet_criteria(x, allow_NA = TRUE, .call_depth = -2)
  meet_criteria(mo, allow_class = c("mo", "character"), allow_NULL = TRUE, .call_depth = -2)
@@ -695,7 +720,9 @@ as_sir_method <- function(method_short,
  meet_criteria(conserve_capped_values, allow_class = "logical", has_length = 1, .call_depth = -2)
  meet_criteria(add_intrinsic_resistance, allow_class = "logical", has_length = 1, .call_depth = -2)
  meet_criteria(reference_data, allow_class = "data.frame", .call_depth = -2)
-  check_reference_data(reference_data)
+  meet_criteria(include_screening, allow_class = "logical", has_length = 1, .call_depth = -2)
+  meet_criteria(include_PKPD, allow_class = "logical", has_length = 1, .call_depth = -2)
+  check_reference_data(reference_data, .call_depth = -2)

  # for dplyr's across()
  cur_column_dplyr <- import_fn("cur_column", "dplyr", error_on_fail = FALSE)
@@ -748,7 +775,7 @@ as_sir_method <- function(method_short,
  } else {
    mo.bak <- mo
  }
-  # be sure to take current taxonomy, as the clinical_breakpoints data set only contains current taxonomy
+  # be sure to take current taxonomy, as the 'clinical_breakpoints' data set only contains current taxonomy
  mo <- suppressWarnings(suppressMessages(as.mo(mo, keep_synonyms = FALSE, inf0 = FALSE)))
  guideline_coerced <- get_guideline(guideline, reference_data)
  if (is.na(ab)) {
@@ -768,13 +795,13 @@ as_sir_method <- function(method_short,
  if (length(uti) == 1) {
    uti <- rep(uti, length(x))
  }
-  
+
  if (isTRUE(add_intrinsic_resistance) && guideline_coerced %unlike% "EUCAST") {
    if (message_not_thrown_before("as.sir", "intrinsic")) {
      warning_("in `as.sir()`: using 'add_intrinsic_resistance' is only useful when using EUCAST guidelines, since the rules for intrinsic resistance are based on EUCAST.")
    }
  }
-  
+
  agent_formatted <- paste0("'", font_bold(ab.bak), "'")
  agent_name <- ab_name(ab, tolower = TRUE, language = NULL)
  if (generalise_antibiotic_name(ab.bak) == generalise_antibiotic_name(agent_name)) {
@@ -801,27 +828,31 @@ as_sir_method <- function(method_short,
    appendLF = FALSE,
    as_note = FALSE
  )
-  
+
  msg_note <- function(messages) {
    for (i in seq_len(length(messages))) {
      messages[i] <- word_wrap(extra_indent = 5, messages[i])
    }
-    message(font_green(font_bold(" Note:\n")),
-            paste0("   ", font_black(AMR_env$bullet_icon)," ", font_black(messages, collapse = NULL) , collapse = "\n"))
+    message(
+      font_green(font_bold(" Note:\n")),
+      paste0("   ", font_black(AMR_env$bullet_icon), " ", font_black(messages, collapse = NULL), collapse = "\n")
+    )
  }

  method <- method_short

  metadata_mo <- get_mo_uncertainties()

-  df <- data.frame(values = x,
-                   mo = mo,
-                   result = NA_sir_,
-                   uti = uti,
-                   stringsAsFactors = FALSE)
+  df <- data.frame(
+    values = x,
+    mo = mo,
+    result = NA_sir_,
+    uti = uti,
+    stringsAsFactors = FALSE
+  )
  if (method == "mic") {
    # when as.sir.mic is called directly
-    df$values <- as.mic(df$values) 
+    df$values <- as.mic(df$values)
  } else if (method == "disk") {
    # when as.sir.disk is called directly
    df$values <- as.disk(df$values)
@@ -832,7 +863,7 @@ as_sir_method <- function(method_short,
  method_coerced <- toupper(method)
  ab_coerced <- ab
  mo_coerced <- mo
-  
+
  if (identical(reference_data, AMR::clinical_breakpoints)) {
    breakpoints <- reference_data %pm>%
      subset(guideline == guideline_coerced & method == method_coerced & ab == ab_coerced)
@@ -845,30 +876,42 @@ as_sir_method <- function(method_short,
    breakpoints <- reference_data %pm>%
      subset(method == method_coerced & ab == ab_coerced)
  }
-  
+
+  if (isFALSE(include_screening)) {
+    # remove screening rules from the breakpoints table
+    breakpoints <- breakpoints %pm>%
+      subset(site %unlike% "screen" & ref_tbl %unlike% "screen")
+  }
+  if (isFALSE(include_PKPD)) {
+    # remove PKPD rules from the breakpoints table
+    breakpoints <- breakpoints %pm>%
+      subset(mo != "UNKNOWN" & ref_tbl %unlike% "PK.*PD")
+  }
+
  msgs <- character(0)
  if (nrow(breakpoints) == 0) {
    # apparently no breakpoints found
-    msg_note(paste0("No ", method_coerced, " breakpoints available for ",
-                    suppressMessages(suppressWarnings(ab_name(ab_coerced, language = NULL, tolower = TRUE))),
-                    " (", ab_coerced, ")"))
+    msg_note(paste0(
+      "No ", method_coerced, " breakpoints available for ",
+      suppressMessages(suppressWarnings(ab_name(ab_coerced, language = NULL, tolower = TRUE))),
+      " (", ab_coerced, ")"
+    ))
    load_mo_uncertainties(metadata_mo)
    return(rep(NA_sir_, nrow(df)))
  }
-  
+
  if (guideline_coerced %like% "EUCAST") {
    any_is_intrinsic_resistant <- FALSE
    add_intrinsic_resistance_to_AMR_env()
  }
-  
+
  # run the rules
  for (mo_unique in unique(df$mo)) {
-    
    rows <- which(df$mo == mo_unique)
    values <- df[rows, "values", drop = TRUE]
    uti <- df[rows, "uti", drop = TRUE]
    new_sir <- rep(NA_sir_, length(rows))
-    
+
    # find different mo properties
    mo_current_genus <- as.mo(mo_genus(mo_unique, language = NULL))
    mo_current_family <- as.mo(mo_family(mo_unique, language = NULL))
@@ -890,18 +933,22 @@ as_sir_method <- function(method_short,
    if (!mo_rank(mo_unique) %in% c("kingdom", "phylum", "class", "order")) {
      mo_formatted <- font_italic(mo_formatted)
    }
-    ab_formatted <- paste0(suppressMessages(suppressWarnings(ab_name(ab_coerced, language = NULL, tolower = TRUE))), 
-                           " (", ab_coerced, ")")
-    
-    # gather all available breakpoints for current MO and sort on taxonomic rank 
+    ab_formatted <- paste0(
+      suppressMessages(suppressWarnings(ab_name(ab_coerced, language = NULL, tolower = TRUE))),
+      " (", ab_coerced, ")"
+    )
+
+    # gather all available breakpoints for current MO and sort on taxonomic rank
    # (this will prefer species breakpoints over order breakpoints)
    breakpoints_current <- breakpoints %pm>%
-      subset(mo %in% c(mo_current_genus, mo_current_family,
-                       mo_current_order, mo_current_class,
-                       mo_current_becker, mo_current_lancefield,
-                       mo_current_other))
-    
-    if (any(df[rows, "uti", drop = TRUE], na.rm = TRUE)) {
+      subset(mo %in% c(
+        mo_current_genus, mo_current_family,
+        mo_current_order, mo_current_class,
+        mo_current_becker, mo_current_lancefield,
+        mo_current_other
+      ))
+
+    if (any(uti, na.rm = TRUE)) {
      breakpoints_current <- breakpoints_current %pm>%
        # be as specific as possible (i.e. prefer species over genus):
        # the below `pm_desc(uti)` will put `TRUE` on top and FALSE on bottom
@@ -911,7 +958,7 @@ as_sir_method <- function(method_short,
        # sort UTI = FALSE first, then UTI = TRUE
        pm_arrange(rank_index, uti)
    }
-    
+
    # throw notes for different body sites
    if (nrow(breakpoints_current) == 1 && all(breakpoints_current$uti == TRUE) && any(uti %in% c(FALSE, NA)) && message_not_thrown_before("as.sir", "uti", ab_coerced)) {
      # only UTI breakpoints available
@@ -932,18 +979,27 @@ as_sir_method <- function(method_short,
      }
      msgs <- c(msgs, paste0("Multiple breakpoints available for ", ab_formatted, " in ", mo_formatted, " - assuming ", site, "."))
    }
-    
+
    # first check if mo is intrinsic resistant
    if (isTRUE(add_intrinsic_resistance) && guideline_coerced %like% "EUCAST" && paste(mo_unique, ab_coerced) %in% AMR_env$intrinsic_resistant) {
      msgs <- c(msgs, paste0("Intrinsic resistance applied for ", ab_formatted, " in ", mo_formatted, ""))
      new_sir <- rep(as.sir("R"), length(rows))
-      
+    } else if (nrow(breakpoints_current) == 0) {
+      # no rules available
+      new_sir <- rep(NA_sir_, length(rows))
    } else {
      # then run the rules
      breakpoints_current <- breakpoints_current[1L, , drop = FALSE]
-      
+
+      if (any(breakpoints_current$mo == "UNKNOWN", na.rm = TRUE) | any(breakpoints_current$ref_tbl %like% "PK.*PD", na.rm = TRUE)) {
+        msgs <- c(msgs, "(Some) PK/PD breakpoints were applied - use `include_PKPD = FALSE` to prevent this")
+      }
+      if (any(breakpoints_current$site %like% "screen", na.rm = TRUE) | any(breakpoints_current$ref_tbl %like% "screen", na.rm = TRUE)) {
+        msgs <- c(msgs, "(Some) screening breakpoints were applied - use `include_screening = FALSE` to prevent this")
+      }
+
      if (method == "mic") {
-        new_sir <- quick_case_when(
+        new_sir <- case_when_AMR(
          is.na(values) ~ NA_sir_,
          values <= breakpoints_current$breakpoint_S ~ as.sir("S"),
          guideline_coerced %like% "EUCAST" & values > breakpoints_current$breakpoint_R ~ as.sir("R"),
@@ -953,9 +1009,8 @@ as_sir_method <- function(method_short,
          # and NA otherwise
          TRUE ~ NA_sir_
        )
-        
      } else if (method == "disk") {
-        new_sir <- quick_case_when(
+        new_sir <- case_when_AMR(
          is.na(values) ~ NA_sir_,
          as.double(values) >= as.double(breakpoints_current$breakpoint_S) ~ as.sir("S"),
          guideline_coerced %like% "EUCAST" & as.double(values) < as.double(breakpoints_current$breakpoint_R) ~ as.sir("R"),
@@ -968,7 +1023,7 @@ as_sir_method <- function(method_short,
      }

      # write to verbose output
-      AMR_env$sir_interpretation_history <- rbind(
+      AMR_env$sir_interpretation_history <- rbind_AMR(
        AMR_env$sir_interpretation_history,
        # recycling 1 to 2 rows does not seem to work, which is why rep() was added
        data.frame(
@@ -988,10 +1043,10 @@ as_sir_method <- function(method_short,
        )
      )
    }
-    
+
    df[rows, "result"] <- new_sir
  }
-  
+
  if (isTRUE(rise_warning)) {
    message(font_yellow(font_bold(" * WARNING *")))
  } else if (length(msgs) == 0) {
@@ -999,9 +1054,9 @@ as_sir_method <- function(method_short,
  } else {
    msg_note(sort(msgs))
  }
-  
+
  load_mo_uncertainties(metadata_mo)
-  
+
  df$result
 }

@@ -1027,7 +1082,10 @@ sir_interpretation_history <- function(clean = FALSE) {
    AMR_env$sir_interpretation_history <- out.bak
  }

-  if (pkg_is_available("tibble", also_load = FALSE)) {
+  # sort descending on time
+  out <- out[order(out$datetime, decreasing = TRUE), , drop = FALSE]
+
+  if (pkg_is_available("tibble")) {
    import_fn("as_tibble", "tibble")(out)
  } else {
    out
@@ -1156,6 +1214,9 @@ summary.sir <- function(object, ...) {
  I <- sum(x == "I", na.rm = TRUE)
  R <- sum(x == "R", na.rm = TRUE)
  pad <- function(x) {
+    if (is.na(x)) {
+      return("??")
+    }
    if (x == "0%") {
      x <- " 0.0%"
    }
@@ -1218,16 +1279,15 @@ rep.sir <- function(x, ...) {
  y
 }

-check_reference_data <- function(reference_data) {
+check_reference_data <- function(reference_data, .call_depth) {
  if (!identical(reference_data, AMR::clinical_breakpoints)) {
-    class_sir <- vapply(FUN.VALUE = character(1), clinical_breakpoints, function(x) paste0("<", class(x), ">", collapse = " and "))
+    class_sir <- vapply(FUN.VALUE = character(1), AMR::clinical_breakpoints, function(x) paste0("<", class(x), ">", collapse = " and "))
    class_ref <- vapply(FUN.VALUE = character(1), reference_data, function(x) paste0("<", class(x), ">", collapse = " and "))
    if (!all(names(class_sir) == names(class_ref))) {
-      stop_("`reference_data` must have the same column names as the 'clinical_breakpoints' data set.", call = -2)
+      stop_("`reference_data` must have the same column names as the 'clinical_breakpoints' data set.", call = .call_depth)
    }
    if (!all(class_sir == class_ref)) {
-      class_sir[class_sir != class_ref][1]
-      stop_("`reference_data` must be the same structure as the 'clinical_breakpoints' data set. Column '", names(class_ref[class_sir != class_ref][1]), "' is of class ", class_ref[class_sir != class_ref][1], ", but should be of class ", class_sir[class_sir != class_ref][1], ".", call = -2)
+      stop_("`reference_data` must be the same structure as the 'clinical_breakpoints' data set. Column '", names(class_ref[class_sir != class_ref][1]), "' is of class ", class_ref[class_sir != class_ref][1], ", but should be of class ", class_sir[class_sir != class_ref][1], ".", call = .call_depth)
    }
  }
 }
@@ -31,7 +31,8 @@ dots2vars <- function(...) {
  # this function is to give more informative output about
  # variable names in count_* and proportion_* functions
  dots <- substitute(list(...))
-  as.character(dots)[2:length(dots)]
+  dots <- as.character(dots)[2:length(dots)]
+  paste0(dots[dots != "."], collapse = "+")
 }

 sir_calc <- function(...,
@@ -41,7 +42,7 @@ sir_calc <- function(...,
                     only_all_tested = FALSE,
                     only_count = FALSE) {
  meet_criteria(ab_result, allow_class = c("character", "numeric", "integer"), has_length = c(1, 2, 3))
-  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
+  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
  meet_criteria(as_percent, allow_class = "logical", has_length = 1)
  meet_criteria(only_all_tested, allow_class = "logical", has_length = 1)
  meet_criteria(only_count, allow_class = "logical", has_length = 1)
@@ -133,7 +134,7 @@ sir_calc <- function(...,
    }

    x_transposed <- as.list(as.data.frame(t(x), stringsAsFactors = FALSE))
-    if (only_all_tested == TRUE) {
+    if (isTRUE(only_all_tested)) {
      # no NAs in any column
      y <- apply(
        X = as.data.frame(lapply(x, as.integer), stringsAsFactors = FALSE),
@@ -222,10 +223,10 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
                        combine_SI = TRUE,
                        confidence_level = 0.95) {
  meet_criteria(type, is_in = c("proportion", "count", "both"), has_length = 1)
-  meet_criteria(data, allow_class = "data.frame", contains_column_class = "sir")
+  meet_criteria(data, allow_class = "data.frame", contains_column_class = c("sir", "rsi"))
  meet_criteria(translate_ab, allow_class = c("character", "logical"), has_length = 1, allow_NA = TRUE)
-  meet_criteria(language, has_length = 1, is_in = c(LANGUAGES_SUPPORTED, ""), allow_NULL = TRUE, allow_NA = TRUE)
-  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_finite = TRUE)
+  language <- validate_language(language)
+  meet_criteria(minimum, allow_class = c("numeric", "integer"), has_length = 1, is_positive_or_zero = TRUE, is_finite = TRUE)
  meet_criteria(as_percent, allow_class = "logical", has_length = 1)
  meet_criteria(combine_SI, allow_class = "logical", has_length = 1)
  meet_criteria(confidence_level, allow_class = "numeric", has_length = 1)
@@ -236,7 +237,7 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
  # select only groups and antibiotics
  if (is_null_or_grouped_tbl(data)) {
    data_has_groups <- TRUE
-    groups <- setdiff(names(attributes(data)$groups), ".rows")
+    groups <- get_group_names(data)
    data <- data[, c(groups, colnames(data)[vapply(FUN.VALUE = logical(1), data, is.sir)]), drop = FALSE]
  } else {
    data_has_groups <- FALSE
@@ -321,7 +322,7 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
          }
          out_new <- cbind(group_values, out_new)
        }
-        out <- rbind(out, out_new, stringsAsFactors = FALSE)
+        out <- rbind_AMR(out, out_new)
      }
    }
    out
@@ -330,7 +331,7 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
  # based on pm_apply_grouped_function
  apply_group <- function(.data, fn, groups, drop = FALSE, ...) {
    grouped <- pm_split_into_groups(.data, groups, drop)
-    res <- do.call(rbind, unname(lapply(grouped, fn, ...)))
+    res <- do.call(rbind_AMR, unname(lapply(grouped, fn, ...)))
    if (any(groups %in% colnames(res))) {
      class(res) <- c("grouped_data", class(res))
      res <- pm_set_groups(res, groups[groups %in% colnames(res)])
@@ -29,12 +29,12 @@

 #' Translate Strings from the AMR Package
 #'
-#' For language-dependent output of AMR functions, like [mo_name()], [mo_gramstain()], [mo_type()] and [ab_name()].
+#' For language-dependent output of `AMR` functions, such as [mo_name()], [mo_gramstain()], [mo_type()] and [ab_name()].
 #' @param x text to translate
 #' @param language language to choose. Use one of these supported language names or ISO-639-1 codes: `r vector_or(paste0(sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), " (" , LANGUAGES_SUPPORTED, ")"), quotes = FALSE, sort = FALSE)`.
 #' @details The currently `r length(LANGUAGES_SUPPORTED)` supported languages are `r vector_and(paste0(sapply(LANGUAGES_SUPPORTED_NAMES, function(x) x[[1]]), " (" , LANGUAGES_SUPPORTED, ")"), quotes = FALSE, sort = FALSE)`. All these languages have translations available for all antimicrobial drugs and colloquial microorganism names.
 #'
-#' To permanently silence the once-per-session language note on a non-English operating system, you can set the option `AMR_locale` in your `.Rprofile` file like this:
+#' To permanently silence the once-per-session language note on a non-English operating system, you can set the [package option][AMR-options] [`AMR_locale`][AMR-options] in your `.Rprofile` file like this:
 #'
 #' ```r
 #' # Open .Rprofile file
@@ -51,12 +51,12 @@
 #' ### Changing the Default Language
 #' The system language will be used at default (as returned by `Sys.getenv("LANG")` or, if `LANG` is not set, [`Sys.getlocale("LC_COLLATE")`][Sys.getlocale()]), if that language is supported. But the language to be used can be overwritten in two ways and will be checked in this order:
 #'
-#'   1. Setting the R option `AMR_locale`, either by using e.g. `set_AMR_locale("German")` or by running e.g. `options(AMR_locale = "German")`.
+#'   1. Setting the [package option][AMR-options] [`AMR_locale`][AMR-options], either by using e.g. `set_AMR_locale("German")` or by running e.g. `options(AMR_locale = "German")`.
 #'
 #'      Note that setting an \R option only works in the same session. Save the command `options(AMR_locale = "(your language)")` to your `.Rprofile` file to apply it for every session. Run `utils::file.edit("~/.Rprofile")` to edit your `.Rprofile` file.
 #'   2. Setting the system variable `LANGUAGE` or `LANG`, e.g. by adding `LANGUAGE="de_DE.utf8"` to your `.Renviron` file in your home directory.
 #'
-#' Thus, if the R option `AMR_locale` is set, the system variables `LANGUAGE` and `LANG` will be ignored.
+#' Thus, if the [package option][AMR-options] [`AMR_locale`][AMR-options] is set, the system variables `LANGUAGE` and `LANG` will be ignored.
 #' @rdname translate
 #' @name translate
 #' @export
@@ -141,10 +141,11 @@ reset_AMR_locale <- function() {
 #' @export
 translate_AMR <- function(x, language = get_AMR_locale()) {
  translate_into_language(x,
-                          language = language,
-                          only_unknown = FALSE,
-                          only_affect_ab_names = FALSE,
-                          only_affect_mo_names = FALSE)
+    language = language,
+    only_unknown = FALSE,
+    only_affect_ab_names = FALSE,
+    only_affect_mo_names = FALSE
+  )
 }


@@ -170,14 +171,15 @@ find_language <- function(language, fallback = TRUE) {
  language <- Map(LANGUAGES_SUPPORTED_NAMES,
    LANGUAGES_SUPPORTED,
    f = function(l, n, check = language) {
-      grepl(paste0(
-        "^(", l[1], "|", l[2], "|",
-        n, "(_|$)|", toupper(n), "(_|$))"
-      ),
-      check,
-      ignore.case = TRUE,
-      perl = TRUE,
-      useBytes = FALSE
+      grepl(
+        paste0(
+          "^(", l[1], "|", l[2], "|",
+          n, "(_|$)|", toupper(n), "(_|$))"
+        ),
+        check,
+        ignore.case = TRUE,
+        perl = TRUE,
+        useBytes = FALSE
      )
    },
    USE.NAMES = TRUE
@@ -196,7 +198,6 @@ translate_into_language <- function(from,
                                    only_unknown = FALSE,
                                    only_affect_ab_names = FALSE,
                                    only_affect_mo_names = FALSE) {
-
  # get ISO-639-1 of language
  lang <- validate_language(language)
  if (lang == "en") {
@@ -245,7 +246,8 @@ translate_into_language <- function(from,
  }

  lapply(
-    seq_len(nrow(df_trans)),
+    # starting with longest pattern, since more general translations are shorter, such as 'Group'
+    order(nchar(df_trans$pattern), decreasing = TRUE),
    function(i) {
      from_unique_translated <<- gsub(
        pattern = df_trans$pattern[i],
@@ -260,10 +262,10 @@ translate_into_language <- function(from,

  # force UTF-8 for diacritics
  from_unique_translated <- enc2utf8(from_unique_translated)
-  
+
  # a kind of left join to get all results back
  out <- from_unique_translated[match(from.bak, from_unique)]
-  
+
  if (!identical(from.bak, out) && get_AMR_locale() == lang && message_not_thrown_before("translation", entire_session = TRUE) && interactive()) {
    message(word_wrap(
      "Assuming the ", LANGUAGES_SUPPORTED_NAMES[[lang]]$exonym, " language (",
@@ -271,6 +273,6 @@ translate_into_language <- function(from,
      add_fn = list(font_blue), as_note = TRUE
    ))
  }
-  
+
  out
 }
@@ -35,7 +35,8 @@
 #' @rdname AMR-deprecated
 #' @export
 NA_rsi_ <- set_clean_class(factor(NA_character_, levels = c("S", "I", "R"), ordered = TRUE),
-                           new_class = c("rsi", "ordered", "factor"))
+  new_class = c("rsi", "ordered", "factor")
+)
 #' @rdname AMR-deprecated
 #' @export
 as.rsi <- function(x, ...) {
@@ -89,13 +90,9 @@ ggplot_rsi_predict <- function(...) {
 }
 #' @rdname AMR-deprecated
 #' @export
-is.rsi <- function(x, ...) {
-  # this is an exception, so mutate_if(is.rsi, as.sir) can be used
-  if (inherits(x, "data.frame")) {
-    unname(vapply(FUN.VALUE = logical(1), x, is.rsi))
-  } else {
-    inherits(x, "rsi")
-  }
+is.rsi <- function(...) {
+  # REMINDER: change as.sir() to remove the deprecation warning there
+  suppressWarnings(is.sir(...))
 }
 #' @rdname AMR-deprecated
 #' @export
@@ -149,15 +146,17 @@ theme_rsi <- function(...) {
 # will be exported using s3_register() in R/zzz.R
 pillar_shaft.rsi <- pillar_shaft.sir
 type_sum.rsi <- function(x, ...) {
-  deprecation_warning(extra_msg = "* Transform your old 'rsi' class to the new 'sir' class with `as.sir()` using e.g.:\n  your_data %>% mutate_if(is.rsi, as.sir)")
-  paste0("rsi", font_bold(font_red("[!]")))
+  if (message_not_thrown_before("type_sum.rsi")) {
+    deprecation_warning(extra_msg = "The 'rsi' class has been replaced with 'sir'. Transform your 'rsi' columns to 'sir' with `as.sir()`, e.g.:\n  your_data %>% mutate_if(is.rsi, as.sir)")
+  }
+  "rsi"
 }

 #' @method print rsi
 #' @export
 #' @noRd
 print.rsi <- function(x, ...) {
-  deprecation_warning(extra_msg = "Transform your old 'rsi' class to the new 'sir' class with `as.sir()`")
+  deprecation_warning(extra_msg = "The 'rsi' class has been replaced with 'sir' - transform your 'rsi' data with `as.sir()`")
  cat("Class 'rsi'", font_bold(font_red("[!]\n")))
  print(as.character(x), quote = FALSE)
 }
@@ -190,21 +189,39 @@ summary.rsi <- summary.sir
 #' @export
 unique.rsi <- unique.sir

-deprecation_warning <- function(old = NULL, new = NULL, extra_msg = NULL) {
+# WHEN REMOVING RSI, DON'T FORGET TO REMOVE :
+# - THE "rsi_df" CLASS FROM R/sir_calc.R
+# - CODE CONTAINING only_rsi_columns, colours_RSI, include_untested_rsi, prob_RSI
+
+deprecation_warning <- function(old = NULL, new = NULL, extra_msg = NULL, is_function = TRUE) {
  if (is.null(old)) {
    warning_(extra_msg)
  } else {
    env <- paste0("deprecated_", old)
    if (!env %in% names(AMR_env)) {
      AMR_env[[paste0("deprecated_", old)]] <- 1
-      warning_(ifelse(is.null(new), 
-                      paste0("The `", old, "()` function is no longer in use"),
-                      paste0("The `", old, "()` function has been replaced with `", new, "()`")),
-               ", see `?AMR-deprecated`.",
-               ifelse(!is.null(extra_msg),
-                      paste0(" ", extra_msg),
-                      ""),
-               "\nThis warning will be shown once per session.")
+      if (isTRUE(is_function)) {
+        old <- paste0(old, "()")
+        new <- paste0(new, "()")
+        type <- "function"
+      } else {
+        type <- "argument"
+      }
+      warning_(
+        ifelse(is.null(new),
+          paste0("The `", old, "` ", type, " is no longer in use"),
+          paste0("The `", old, "` ", type, " has been replaced with `", new, "`")
+        ),
+        ifelse(type == "argument",
+          ". While the old argument still works, it will be removed in a future version, so please update your code.",
+          ", see `?AMR-deprecated`."
+        ),
+        ifelse(!is.null(extra_msg),
+          paste0(" ", extra_msg),
+          ""
+        ),
+        "\nThis warning will be shown once per session."
+      )
    }
  }
 }
@@ -112,7 +112,7 @@ if (utf8_supported && !is_latex) {
  s3_register("cleaner::freq", "mo")
  s3_register("cleaner::freq", "sir")
  # Support for skim() from the skimr package
-  if (pkg_is_available("skimr", also_load = FALSE, min_version = "2.0.0")) {
+  if (pkg_is_available("skimr", min_version = "2.0.0")) {
    s3_register("skimr::get_skimmers", "mo")
    s3_register("skimr::get_skimmers", "sir")
    s3_register("skimr::get_skimmers", "mic")
@@ -123,10 +123,14 @@ if (utf8_supported && !is_latex) {
  s3_register("ggplot2::autoplot", "mic")
  s3_register("ggplot2::autoplot", "disk")
  s3_register("ggplot2::autoplot", "resistance_predict")
+  s3_register("ggplot2::autoplot", "antibiogram")
  # Support for fortify from the ggplot2 package
  s3_register("ggplot2::fortify", "sir")
  s3_register("ggplot2::fortify", "mic")
  s3_register("ggplot2::fortify", "disk")
+  # Support for knitr (R Markdown/Quarto)
+  s3_register("knitr::knit_print", "antibiogram")
+  s3_register("knitr::knit_print", "formatted_bug_drug_combinations")
  # Support vctrs package for use in e.g. dplyr verbs
  # S3: ab_selector
  s3_register("vctrs::vec_ptype2", "character.ab_selector")
@@ -177,7 +181,7 @@ if (utf8_supported && !is_latex) {
    try(invisible(get_mo_source()), silent = TRUE)
  }
  # be sure to print tibbles as tibbles
-  if (pkg_is_available("tibble", also_load = FALSE)) {
+  if (pkg_is_available("tibble")) {
    try(loadNamespace("tibble"), silent = TRUE)
  }

@@ -191,19 +195,25 @@ if (utf8_supported && !is_latex) {
  # if custom ab option is available, load it
  if (!is.null(getOption("AMR_custom_ab")) && file.exists(getOption("AMR_custom_ab", default = ""))) {
    packageStartupMessage("Adding custom antimicrobials from '", getOption("AMR_custom_ab"), "'...", appendLF = FALSE)
-    x <- readRDS2(getOption("AMR_custom_ab"))
-    tryCatch({
-      suppressWarnings(suppressMessages(add_custom_antimicrobials(x)))
-      packageStartupMessage("OK.")
-    }, error = function(e) packageStartupMessage("Failed: ", e$message))
+    x <- readRDS_AMR(getOption("AMR_custom_ab"))
+    tryCatch(
+      {
+        suppressWarnings(suppressMessages(add_custom_antimicrobials(x)))
+        packageStartupMessage("OK.")
+      },
+      error = function(e) packageStartupMessage("Failed: ", e$message)
+    )
  }
  # if custom mo option is available, load it
  if (!is.null(getOption("AMR_custom_mo")) && file.exists(getOption("AMR_custom_mo", default = ""))) {
    packageStartupMessage("Adding custom microorganisms from '", getOption("AMR_custom_mo"), "'...", appendLF = FALSE)
-    x <- readRDS2(getOption("AMR_custom_mo"))
-    tryCatch({
-      suppressWarnings(suppressMessages(add_custom_microorganisms(x)))
-      packageStartupMessage("OK.")
-    }, error = function(e) packageStartupMessage("Failed: ", e$message))
+    x <- readRDS_AMR(getOption("AMR_custom_mo"))
+    tryCatch(
+      {
+        suppressWarnings(suppressMessages(add_custom_microorganisms(x)))
+        packageStartupMessage("OK.")
+      },
+      error = function(e) packageStartupMessage("Failed: ", e$message)
+    )
  }
 }
@@ -27,26 +27,8 @@ install.packages("AMR")

 It will be downloaded and installed automatically. For RStudio, click on the menu *Tools* > *Install Packages...* and then type in "AMR" and press <kbd>Install</kbd>.

-### Copyright
+----

-This R package is licensed under the [GNU General Public License (GPL) v2.0](https://github.com/msberends/AMR/blob/main/LICENSE). In a nutshell, this means that this package:
-
- May be used for commercial purposes
-
- May be used for private purposes
-
- May **not** be used for patent purposes
-
- May be modified, although:
-
-  - Modifications **must** be released under the same license when distributing the package
-  - Changes made to the code **must** be documented
-
- May be distributed, although:
-
-  - Source code **must** be made available when the package is distributed
-  - A copy of the license and copyright notice **must** be included with the package.
-
- Comes with a LIMITATION of liability
-
- Comes with NO warranty
+<small>
+This AMR package for R is free, open-source software and licensed under the [GNU General Public License v2.0 (GPL-2)](https://msberends.github.io/AMR/LICENSE-text.html). These requirements are consequently legally binding: modifications must be released under the same license when distributing the package, changes made to the code must be documented, source code must be made available when the package is distributed, and a copy of the license and copyright notice must be included with the package.
+</small>
@@ -41,6 +41,10 @@ template:
    # the green "success" colour of this bootstrap theme should be the same as the green in our logo
    success: "#128f76"
    link-color: "#128f76"
+    light: "#128f76a6" # this is success with 60% alpha
+    # the template "info" is blue - this should be a green fitting our theme
+    info: "#60a799"
+    # make top bar a bit wider
    navbar-padding-y: "0.5rem"
  opengraph:
    twitter:
@@ -72,37 +76,43 @@ navbar:
    - text: "How to"
      icon: "fa-question-circle"
      menu:
-      - text: "Conduct AMR analysis"
+      - text: "Conduct AMR Analysis"
        icon: "fa-directions"
        href: "articles/AMR.html"
-      - text: "Predict antimicrobial resistance"
+      - text: "Generate Antibiogram (Trad./Syndromic/WISCA)"
+        icon: "fa-file-prescription"
+        href: "reference/antibiogram.html" # reference instead of an article
+      - text: "Predict Antimicrobial Resistance"
        icon: "fa-dice"
        href: "articles/resistance_predict.html"
-      - text: "Data sets for download / own use"
+      - text: "Download Data Sets for Own Use"
        icon: "fa-database"
        href: "articles/datasets.html"
-      - text: "Conduct principal component analysis for AMR"
+      - text: "Set User- Or Team-specific Package Settings"
+        icon: "fa-gear"
+        href: "reference/AMR-options.html"
+      - text: "Conduct Principal Component Analysis for AMR"
        icon: "fa-compress"
        href: "articles/PCA.html"
-      - text: "Determine multi-drug resistance (MDR)"
+      - text: "Determine Multi-Drug Resistance (MDR)"
        icon: "fa-skull-crossbones"
        href: "articles/MDR.html"
-      - text: "Work with WHONET data"
+      - text: "Work with WHONET Data"
        icon: "fa-globe-americas"
        href: "articles/WHONET.html"
-      - text: "Import data from SPSS/SAS/Stata"
+      - text: "Import Data From SPSS/SAS/Stata"
        icon: "fa-file-upload"
        href: "articles/SPSS.html"
-      - text: "Apply EUCAST rules"
+      - text: "Apply Eucast Rules"
        icon: "fa-exchange-alt"
        href: "articles/EUCAST.html"
-      - text: "Get taxonomy of a microorganism"
+      - text: "Get Taxonomy of a Microorganism"
        icon: "fa-bug"
        href: "reference/mo_property.html" # reference instead of an article
-      - text: "Get properties of an antibiotic drug"
+      - text: "Get Properties of an Antibiotic Drug"
        icon: "fa-capsules"
        href: "reference/ab_property.html" # reference instead of an article
-      - text: "Get properties of an antiviral drug"
+      - text: "Get Properties of an Antiviral Drug"
        icon: "fa-capsules"
        href: "reference/av_property.html" # reference instead of an article
    - text: "Manual"
@@ -158,9 +168,12 @@ reference:
  - title: "Analysing data: antimicrobial resistance"
    desc: >
      Use these function for the analysis part. You can use `susceptibility()` or `resistance()` on any antibiotic column.
+      With `antibiogram()`, you can generate a traditional, combined, syndromic, or weighted-incidence syndromic combination
+      antibiogram(WISCA). This function also comes with support for R Markdown and Quarto.
      Be sure to first select the isolates that are appropiate for analysis, by using `first_isolate()` or `is_new_episode()`.
      You can also filter your data on certain resistance in certain antibiotic classes (`carbapenems()`, `aminoglycosides()`), or determine multi-drug resistant microorganisms (MDRO, `mdro()`).
    contents:
+    - "`antibiogram`"
    - "`proportion`"
    - "`count`"
    - "`is_new_episode`"
@@ -176,6 +189,15 @@ reference:
    - "`resistance_predict`"
    - "`guess_ab_col`"
    
+  - title: "Other: AMR-specific options"
+    desc: >
+      The AMR package is customisable, by providing settings that can be set per user or per team. For
+      example, the default interpretation guideline can be changed from EUCAST to CLSI, or a supported
+      language can be set for the whole team (system-language independent) for antibiotic names in a
+      foreign language.
+    contents:
+    - "`AMR-options`"
+    
  - title: "Other: antiviral drugs"
    desc: >
      This package also provides extensive support for antiviral agents, even though it is not the primary
@@ -1,2 +1,5 @@
-Extra release for fixing image options, as requested by CRAN team on 17 February 2022 (Kurt Hornik).
+As with all previous >20 releases, some CHECKs might return a NOTE for *just* hitting the installation size limit, though its size has been brought down to a minimum in collaboration with CRAN maintainers previously.

+We consider this a high-impact package: it was published in the Journal of Statistical Software (2022), is including in a CRAN Task View (Epidemiology), and is according to download stats used in almost all countries in the world. If there is anything to note, please let us know up-front without directly archiving the current version. That said, we continually unit test our package extensively and have no reason to assume that anything is wrong.
+
+Thanks for maintaining and hosting CRAN! It's empowering R and its use enormously!
@@ -101,56 +101,59 @@ create_species_cons_cops <- function(type = c("CoNS", "CoPS")) {
  MO_staph <- AMR::microorganisms
  MO_staph <- MO_staph[which(MO_staph$genus == "Staphylococcus"), , drop = FALSE]
  if (type == "CoNS") {
-    MO_staph[which(MO_staph$species %in% c(
-      "coagulase-negative", "argensis", "arlettae",
-      "auricularis", "borealis", "caeli", "capitis", "caprae",
-      "carnosus", "casei", "caseolyticus", "chromogenes", "cohnii", "condimenti",
-      "croceilyticus",
-      "debuckii", "devriesei", "edaphicus", "epidermidis",
-      "equorum", "felis", "fleurettii", "gallinarum",
-      "haemolyticus", "hominis", "jettensis", "kloosii",
-      "lentus", "lugdunensis", "massiliensis", "microti",
-      "muscae", "nepalensis", "pasteuri", "petrasii",
-      "pettenkoferi", "piscifermentans", "pragensis", "pseudoxylosus",
-      "pulvereri", "rostri", "saccharolyticus", "saprophyticus",
-      "sciuri", "simulans", "stepanovicii", "succinus",
-      "ureilyticus",
-      "vitulinus", "vitulus", "warneri", "xylosus",
-      "caledonicus", "canis",
-      "durrellii", "lloydii",
-      "ratti", "taiwanensis", "veratri", "urealyticus"
-    ) |
-      # old, now renamed to S. schleiferi (but still as synonym in our data of course):
-      (MO_staph$species == "schleiferi" & MO_staph$subspecies %in% c("schleiferi", ""))),
-    "mo",
-    drop = TRUE
+    MO_staph[
+      which(MO_staph$species %in% c(
+        "coagulase-negative", "argensis", "arlettae",
+        "auricularis", "borealis", "caeli", "capitis", "caprae",
+        "carnosus", "casei", "caseolyticus", "chromogenes", "cohnii", "condimenti",
+        "croceilyticus",
+        "debuckii", "devriesei", "edaphicus", "epidermidis",
+        "equorum", "felis", "fleurettii", "gallinarum",
+        "haemolyticus", "hominis", "jettensis", "kloosii",
+        "lentus", "lugdunensis", "massiliensis", "microti",
+        "muscae", "nepalensis", "pasteuri", "petrasii",
+        "pettenkoferi", "piscifermentans", "pragensis", "pseudoxylosus",
+        "pulvereri", "rostri", "saccharolyticus", "saprophyticus",
+        "sciuri", "simulans", "stepanovicii", "succinus",
+        "ureilyticus",
+        "vitulinus", "vitulus", "warneri", "xylosus",
+        "caledonicus", "canis",
+        "durrellii", "lloydii",
+        "ratti", "taiwanensis", "veratri", "urealyticus"
+      ) |
+        # old, now renamed to S. schleiferi (but still as synonym in our data of course):
+        (MO_staph$species == "schleiferi" & MO_staph$subspecies %in% c("schleiferi", ""))),
+      "mo",
+      drop = TRUE
    ]
  } else if (type == "CoPS") {
-    MO_staph[which(MO_staph$species %in% c(
-      "coagulase-positive", "coagulans",
-      "agnetis", "argenteus",
-      "cornubiensis",
-      "delphini", "lutrae",
-      "hyicus", "intermedius",
-      "pseudintermedius", "pseudointermedius",
-      "schweitzeri", "simiae",
-      "roterodami",
-      "singaporensis"
-    ) |
-      # old, now renamed to S. coagulans (but still as synonym in our data of course):
-      (MO_staph$species == "schleiferi" & MO_staph$subspecies == "coagulans")),
-    "mo",
-    drop = TRUE
+    MO_staph[
+      which(MO_staph$species %in% c(
+        "coagulase-positive", "coagulans",
+        "agnetis", "argenteus",
+        "cornubiensis",
+        "delphini", "lutrae",
+        "hyicus", "intermedius",
+        "pseudintermedius", "pseudointermedius",
+        "schweitzeri", "simiae",
+        "roterodami",
+        "singaporensis"
+      ) |
+        # old, now renamed to S. coagulans (but still as synonym in our data of course):
+        (MO_staph$species == "schleiferi" & MO_staph$subspecies == "coagulans")),
+      "mo",
+      drop = TRUE
    ]
  }
 }
 MO_CONS <- create_species_cons_cops("CoNS")
 MO_COPS <- create_species_cons_cops("CoPS")
-MO_STREP_ABCG <- AMR_env$MO_lookup$mo[which(AMR_env$MO_lookup$genus == "Streptococcus" &
-  AMR_env$MO_lookup$species %in% c(
+MO_STREP_ABCG <- AMR::microorganisms$mo[which(AMR::microorganisms$genus == "Streptococcus" &
+  tolower(AMR::microorganisms$species) %in% c(
    "pyogenes", "agalactiae", "dysgalactiae", "equi", "canis",
-    "group A", "group B", "group C", "group G"
+    "group a", "group b", "group c", "group g"
  ))]
+MO_LANCEFIELD <- AMR::microorganisms$mo[which(AMR::microorganisms$mo %like% "^(B_STRPT_PYGN(_|$)|B_STRPT_AGLC(_|$)|B_STRPT_(DYSG|EQUI)(_|$)|B_STRPT_ANGN(_|$)|B_STRPT_(DYSG|CANS)(_|$)|B_STRPT_SNGN(_|$)|B_STRPT_SLVR(_|$))")]
 MO_PREVALENT_GENERA <- c(
  "Absidia", "Acanthamoeba", "Acremonium", "Aedes", "Alternaria", "Amoeba", "Ancylostoma", "Angiostrongylus",
  "Anisakis", "Anopheles", "Apophysomyces", "Aspergillus", "Aureobasidium", "Basidiobolus", "Beauveria",
@@ -254,14 +257,15 @@ create_AB_AV_lookup <- function(df) {
  }
  new_df$generalised_loinc <- lapply(new_df$loinc, generalise_antibiotic_name)
  new_df$generalised_all <- unname(lapply(
-    as.list(as.data.frame(t(new_df[,
-      c(
-        colnames(new_df)[colnames(new_df) %in% c("ab", "av", "atc", "cid", "name")],
-        colnames(new_df)[colnames(new_df) %like% "generalised"]
-      ),
-      drop = FALSE
-    ]),
-    stringsAsFactors = FALSE
+    as.list(as.data.frame(
+      t(new_df[,
+        c(
+          colnames(new_df)[colnames(new_df) %in% c("ab", "av", "atc", "cid", "name")],
+          colnames(new_df)[colnames(new_df) %like% "generalised"]
+        ),
+        drop = FALSE
+      ]),
+      stringsAsFactors = FALSE
    )),
    function(x) {
      x <- generalise_antibiotic_name(unname(unlist(x)))
@@ -282,6 +286,7 @@ suppressMessages(usethis::use_data(EUCAST_RULES_DF,
  MO_CONS,
  MO_COPS,
  MO_STREP_ABCG,
+  MO_LANCEFIELD,
  MO_PREVALENT_GENERA,
  AB_LOOKUP,
  AV_LOOKUP,
@@ -472,7 +477,7 @@ suppressMessages(devtools::document(quiet = TRUE))
 if (!"styler" %in% rownames(utils::installed.packages())) {
  message("Package 'styler' not installed!")
 } else if (interactive()) {
-  # # only when sourcing this file ourselves
+  # only when sourcing this file ourselves
  # usethis::ui_info("Styling package")
  # styler::style_pkg(
  #   style = styler::tidyverse_style,
@@ -1 +1 @@
-43220347c34d06a5c57f2014a8ecaa82
+8bf97fd5f1d8d82486902d05916ebca0
@@ -0,0 +1,54 @@
+---
+title: "Generating antibiograms with the AMR package"
+author: "AMR package developers"
+date: "`r Sys.Date()`"
+output: pdf_document
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = TRUE, message = FALSE)
+library(AMR)
+```
+
+This is an example R Markdown file to show the use of `antibiogram()` of the AMR package.
+
+For starters, this is what our `example_isolates` data set looks like:
+
+```{r}
+example_isolates
+```
+
+
+### Traditional Antibiogram
+
+```{r trad}
+antibiogram(example_isolates,
+            antibiotics = c(aminoglycosides(), carbapenems()))
+```
+
+### Combined Antibiogram
+
+```{r comb}
+antibiogram(example_isolates,
+            antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"))
+```
+
+### Syndromic Antibiogram
+
+```{r synd}
+antibiogram(example_isolates,
+             antibiotics = c(aminoglycosides(), carbapenems()),
+             syndromic_group = "ward")
+```
+
+### Weighted-Incidence Syndromic Combination Antibiogram (WISCA)
+
+```{r wisca}
+antibiogram(example_isolates,
+            antibiotics = c("AMC", "AMC+CIP", "TZP", "TZP+TOB"),
+            mo_transform = "gramstain",
+            minimum = 10, # this should be >= 30, but now just as example
+            syndromic_group = ifelse(example_isolates$age >= 65 &
+                                       example_isolates$gender == "M",
+                                     "WISCA Group 1", "WISCA Group 2"))
+```
@@ -410,7 +410,7 @@
 "SLT3"		"Sulfamerazine/trimethoprim"	"Trimethoprims"	"J01EE07"	"Sulfonamides and trimethoprim"	"Combinations of sulfonamides and trimethoprim, incl. derivatives"	""	""					""
 "SUM"	5327	"Sulfamethazine"	"Other antibacterials"	"NA"			""	"azolmetazin,benzene sulfonamide,calfspan,calfspan tablets,cremomethazine,diazil,diazilsulfadine,dimezathine,intradine,kelametazine,mermeth,metazin,neasina,neazina,nsulfanilamide,panazin,pirmazin,primazin,sa iii,solfadimidina,spanbolet,sulfadimerazine,sulfadimesin,sulfadimesine,sulfadimethyldiazine,sulfadimezin,sulfadimezine,sulfadimezinum,sulfadimidin,sulfadimidina,sulfadimidine,sulfadimidinum,sulfadine,sulfametazina,sulfametazyny,sulfamethazine,sulfamethiazine,sulfamezathine,sulfamidine,sulfasure sr bolus,sulfodimesin,sulfodimezine,sulka k boluses,sulka s boluses,sulmet,sulphadimidine,sulphamethasine,sulphamethazine,sulphamezathine,sulphamidine,sulphodimezine,superseptil,superseptyl,vertolan"					"87592-2"
 "SLF4"	5328	"Sulfamethizole"	"Trimethoprims"	"B05CA04,D06BA04,J01EB02,S01AB01"	"Sulfonamides and trimethoprim"	"Short-acting sulfonamides"	"sfmz"	"ayerlucil,lucosil,methazol,microsul,nsulfanilamide,proklar,renasul,salimol,solfametizolo,sulamethizole,sulfa gram,sulfamethizol,sulfamethizole,sulfamethizolum,sulfametizol,sulfapyelon,sulfstat,sulfurine,sulphamethizole,tetracid,thidicur,thiosulfil,thiosulfil forte,ultrasul,urocydal,urodiaton,urolucosil,urosulfin"	4	"g"			"60175-7,60176-5,60177-3"
-"SMX"	5329	"Sulfamethoxazole"	"Trimethoprims"	"J01EC01"	"Sulfonamides and trimethoprim"	"Intermediate-acting sulfonamides"	"sfmx,sulf"	"azo gantanol,bactrim,bactrimel,cotrimoxazole,eusaprim,gamazole,gantanol,gantanol ds,metoxal,nsulfanilamide,nsulphanilamide,radonil,septran,septrin,simsinomin,sinomin,solfametossazolo,sulfamethalazole,sulfamethoxazol,sulfamethoxazole,sulfamethoxazolum,sulfamethoxizole,sulfamethylisoxazole,sulfametoxazol,sulfisomezole,sulmeprim,sulphamethalazole,sulphamethoxazol,sulphamethoxazole,sulphisomezole,urobak"	2	"g"			"10342-4,25271-8,39772-9,59971-2,59972-0,60333-2,72674-5,80549-9,80974-9"
+"SMX"	5329	"Sulfamethoxazole"	"Trimethoprims"	"J01EC01"	"Sulfonamides and trimethoprim"	"Intermediate-acting sulfonamides"	"sfmx,sulf"	"azo gantanol,gamazole,gantanol,gantanol ds,metoxal,nsulfanilamide,nsulphanilamide,radonil,septran,simsinomin,sinomin,solfametossazolo,sulfamethalazole,sulfamethoxazol,sulfamethoxazole,sulfamethoxazolum,sulfamethoxizole,sulfamethylisoxazole,sulfametoxazol,sulfisomezole,sulmeprim,sulphamethalazole,sulphamethoxazol,sulphamethoxazole,sulphisomezole,urobak"	2	"g"			"10342-4,25271-8,39772-9,59971-2,59972-0,60333-2,72674-5,80549-9,80974-9"
 "SLF5"	5330	"Sulfamethoxypyridazine"	"Trimethoprims"	"J01ED05"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"altezol,davosin,depovernil,kineks,lederkyn,lentac,lisulfen,longin,medicel,midicel,midikel,myasul,nsulfanilamide,opinsul,paramid,paramid supra,petrisul,piridolo,quinoseptyl,retamid,retasulfin,retasulphine,slosul,spofadazine,sulfalex,sulfapyridazine,sulfdurazin,sulfozona,sultirene,vinces"	0.5	"g"			""
 "SLF6"	19596	"Sulfametomidine"	"Trimethoprims"	"J01ED03"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"duroprocin,methofadin,methofazine,nsulfanilamide,solfametomidina,sulfamethomidine,sulfametomidin,sulfametomidina,sulfametomidine,sulfametomidinum"					""
 "SLF7"	5326	"Sulfametoxydiazine"	"Trimethoprims"	"J01ED04"	"Sulfonamides and trimethoprim"	"Long-acting sulfonamides"	""	"bayrena,berlicid,dairena,durenat,juvoxin,kinecid,kirocid,longasulf,methoxypyrimal,nsulfanilamide,solfametossidiazina,sulfameter,sulfamethorine,sulfamethoxine,sulfamethoxydiazin,sulfamethoxydiazine,sulfamethoxydin,sulfamethoxydine,sulfametin,sulfametinum,sulfametorin,sulfametorine,sulfametorinum,sulfametoxidiazina,sulfametoxidine,sulfametoxydiazine,sulfametoxydiazinum,sulphameter,sulphamethoxydiazine,supramid,ultrax"	0.5	"g"			""
@@ -1,4 +1,3 @@
-
 license_text <- readLines("docs/LICENSE-text.html")
 license_text <- paste(license_text, collapse = "|||")
 license_text <- gsub("licen(s|c)e", "Survey", license_text, ignore.case = TRUE)
@@ -1 +1 @@
-810cc621f75ee69a51cfe6726ab46398
+7846247d4113c4e8f550cfd2cb87467f
@@ -1,8 +1,8 @@
 "mo"	"fullname"	"status"	"kingdom"	"phylum"	"class"	"order"	"family"	"genus"	"species"	"subspecies"	"rank"	"ref"	"source"	"lpsn"	"lpsn_parent"	"lpsn_renamed_to"	"gbif"	"gbif_parent"	"gbif_renamed_to"	"prevalence"	"snomed"
-"B_ANAER"	"(unknown anaerobic bacteria)"	"accepted"	"Bacteria"	"(unknown phylum)"	"(unknown class)"	"(unknown order)"	"(unknown family)"	"(unknown Gram-negatives)"	"(unknown species)"	"(unknown subspecies)"	"subspecies"		"manually added"							2	""
-"F_FUNGUS"	"(unknown fungus)"	"accepted"	"Fungi"	"(unknown phylum)"	"(unknown class)"	"(unknown order)"	"(unknown family)"	"(unknown genus)"	"(unknown species)"	"(unknown subspecies)"	"subspecies"		"manually added"							2	""
 "B_GRAMN"	"(unknown Gram-negatives)"	"accepted"	"Bacteria"	"(unknown phylum)"	"(unknown class)"	"(unknown order)"	"(unknown family)"	"(unknown Gram-negatives)"	"(unknown species)"	"(unknown subspecies)"	"subspecies"		"manually added"							2	""
 "B_GRAMP"	"(unknown Gram-positives)"	"accepted"	"Bacteria"	"(unknown phylum)"	"(unknown class)"	"(unknown order)"	"(unknown family)"	"(unknown Gram-positives)"	"(unknown species)"	"(unknown subspecies)"	"subspecies"		"manually added"							2	""
+"B_ANAER"	"(unknown anaerobic bacteria)"	"accepted"	"Bacteria"	"(unknown phylum)"	"(unknown class)"	"(unknown order)"	"(unknown family)"	"(unknown Gram-negatives)"	"(unknown species)"	"(unknown subspecies)"	"subspecies"		"manually added"							2	""
+"F_FUNGUS"	"(unknown fungus)"	"accepted"	"Fungi"	"(unknown phylum)"	"(unknown class)"	"(unknown order)"	"(unknown family)"	"(unknown genus)"	"(unknown species)"	"(unknown subspecies)"	"subspecies"		"manually added"							2	""
 "UNKNOWN"	"(unknown name)"	"accepted"	"(unknown kingdom)"	"(unknown phylum)"	"(unknown class)"	"(unknown order)"	"(unknown family)"	"(unknown genus)"	"(unknown species)"	"(unknown subspecies)"	"subspecies"		"manually added"							2	""
 "F_YEAST"	"(unknown yeast)"	"accepted"	"Fungi"	"(unknown phylum)"	"(unknown class)"	"(unknown order)"	"(unknown family)"	"(unknown genus)"	"(unknown species)"	"(unknown subspecies)"	"subspecies"		"manually added"							2	""
 "B_[FAM]_ABDTBCTR"	"Abditibacteriaceae"	"accepted"	"Bacteria"	"Abditibacteriota"	"Abditibacteriia"	"Abditibacteriales"	"Abditibacteriaceae"	""	""	""	"family"	"Tahon et al., 2018"	"LPSN"	"4812"	"4982"		"10678443"	"10853930"		2	""
@@ -6477,6 +6477,7 @@
 "B_AZYRT"	"Azyrtalia"	"accepted"	"Bacteria"	"Cyanobacteria"	"Cyanobacteriia"	"Cyanobacteriales"	"Rivulariaceae"	"Azyrtalia"	""	""	"genus"	"Vologdin et al., 1969"	"GBIF"				"3237706"	"4306626"		2	""
 "B_AZYRT_ZNLT"	"Azyrtalia zonulata"	"accepted"	"Bacteria"	"Cyanobacteria"	"Cyanobacteriia"	"Cyanobacteriales"	"Rivulariaceae"	"Azyrtalia"	"zonulata"	""	"species"	"Vologdin et al., 1969"	"GBIF"				"11176322"	"3237706"		2	""
 "A_B-DKE"	"B-DKE"	"accepted"	"Archaea"	"Euryarchaeota"	"Thermoplasmata"	"Thermoplasmatales"	"Thermoplasmataceae"	"B-DKE"	""	""	"genus"		"GBIF"				"11214677"	"3810"		2	""
+"A_BE-D"	"BE-D"	"accepted"	"Archaea"	"Thermoproteota"	"Thermoproteia"	"Marsarchaeales"	"Marsarchaeaceae"	"BE-D"	""	""	"genus"		"GBIF"				"11119914"	"10885120"		2	""
 "B_BABEL"	"Babela"	"accepted"	"Bacteria"	"Dependentiae"	"Babeliae"	"Babeliales"	"Babeliaceae"	"Babela"	""	""	"genus"		"GBIF"				"10699249"	"10857700"		2	""
 "B_BABEL_MSSL"	"Babela massiliensis"	"accepted"	"Bacteria"	"Dependentiae"	"Babeliae"	"Babeliales"	"Babeliaceae"	"Babela"	"massiliensis"	""	"species"		"GBIF"				"10816215"	"10699249"		2	""
 "B_[FAM]_BABELIAC"	"Babeliaceae"	"accepted"	"Bacteria"	"Dependentiae"	"Babeliae"	"Babeliales"	"Babeliaceae"	""	""	""	"family"		"GBIF"				"10857700"	"10791973"		2	""
@@ -7288,7 +7289,6 @@
 "B_BDLLV_STLP"	"Bdellovibrio stolpii"	"synonym"	"Bacteria"	"Pseudomonadota"	"Oligoflexia"	"Bdellovibrionales"	"Bdellovibrionaceae"	"Bdellovibrio"	"stolpii"	""	"species"	"Seidler et al., 1972"	"LPSN"	"773991"	"516977"	"773917"				2	"9752009"
 "B_[FAM]_BDLLVBRN"	"Bdellovibrionaceae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Oligoflexia"	"Bdellovibrionales"	"Bdellovibrionaceae"	""	""	""	"family"	"Garrity et al., 2006"	"LPSN"	"203"	"5078"		"8932"	"652"		2	"427516001"
 "B_[ORD]_BDLLVBRN"	"Bdellovibrionales"	"accepted"	"Bacteria"	"Pseudomonadota"	"Oligoflexia"	"Bdellovibrionales"	""	""	""	""	"order"	"Garrity et al., 2006"	"LPSN"	"5078"	"111"		"652"	"10808561"		2	"426331002"
-"A_BE-D"	"BE-D"	"accepted"	"Archaea"	"Thermoproteota"	"Thermoproteia"	"Marsarchaeales"	"Marsarchaeaceae"	"BE-D"	""	""	"genus"		"GBIF"				"11119914"	"10885120"		2	""
 "F_BEAVR"	"Beauveria"	"accepted"	"Fungi"	"Ascomycota"	"Sordariomycetes"	"Hypocreales"	"Cordycipitaceae"	"Beauveria"	""	""	"genus"	"Vuill, 1912"	"GBIF"				"2560584"	"8418"		1.5	"66193005"
 "F_BEAVR_ACRD"	"Beauveria acridophila"	"accepted"	"Fungi"	"Ascomycota"	"Sordariomycetes"	"Hypocreales"	"Cordycipitaceae"	"Beauveria"	"acridophila"	""	"species"	"Sanjuan et al."	"GBIF"				"10753468"	"2560584"		1.5	""
 "F_BEAVR_AMRP"	"Beauveria amorpha"	"accepted"	"Fungi"	"Ascomycota"	"Sordariomycetes"	"Hypocreales"	"Cordycipitaceae"	"Beauveria"	"amorpha"	""	"species"	"Minnis et al."	"GBIF"				"7417312"	"2560584"		1.5	""
@@ -19169,6 +19169,7 @@
 "B_FSBCTR_VARM"	"Fusobacterium varium"	"accepted"	"Bacteria"	"Fusobacteriota"	"Fusobacteriia"	"Fusobacteriales"	"Fusobacteriaceae"	"Fusobacterium"	"varium"	""	"species"	"Moore et al., 1969"	"LPSN"	"783893"	"515666"		"3225872"	"4903731"		1	"1972005"
 "B_FSBCTR_VNCN"	"Fusobacterium vincentii"	"accepted"	"Bacteria"	"Fusobacteriota"	"Fusobacteriia"	"Fusobacteriales"	"Fusobacteriaceae"	"Fusobacterium"	"vincentii"	""	"species"	"Kook et al., 2022"	"LPSN"	"28103"	"515666"		"10808231"	"4903731"		1.5	""
 "B_FSBCTR_WTNB"	"Fusobacterium watanabei"	"accepted"	"Bacteria"	"Fusobacteriota"	"Fusobacteriia"	"Fusobacteriales"	"Fusobacteriaceae"	"Fusobacterium"	"watanabei"	""	"species"	"Tomida et al., 2021"	"LPSN"	"17647"	"515666"					1.5	""
+"B_GBCHB"	"GBChlB"	"accepted"	"Bacteria"	"Chlorobiota"	"Chlorobiia"	"Chlorobiales"	"Chloroherpetonaceae"	"GBChlB"	""	""	"genus"		"GBIF"				"11171983"	"10775177"		2	""
 "B_GBNBC"	"Gabonibacter"	"accepted"	"Bacteria"	"Bacteroidota"	"Bacteroidia"	"Bacteroidales"	"Odoribacteraceae"	"Gabonibacter"	""	""	"genus"	"Mourembou et al., 2017"	"LPSN"	"519111"	"2047"		"9240178"			2	"785729002"
 "B_GBNBC_JSTS"	"Gabonibacter justesenii"	"synonym"	"Bacteria"	"Bacteroidota"	"Bacteroidia"	"Bacteroidales"	"Odoribacteraceae"	"Gabonibacter"	"justesenii"	""	"species"		"GBIF"				"11090238"	"9240178"	"9415109"	2	""
 "B_GBNBC_MSSL"	"Gabonibacter massiliensis"	"accepted"	"Bacteria"	"Bacteroidota"	"Bacteroidia"	"Bacteroidales"	"Odoribacteraceae"	"Gabonibacter"	"massiliensis"	""	"species"	"Mourembou et al., 2017"	"LPSN"	"795002"	"519111"		"9415109"	"9240178"		2	""
@@ -19282,7 +19283,6 @@
 "B_GSTRN_PHSC"	"Gastranaerophilus phascolarctosicola"	"accepted"	"Bacteria"	"Cyanobacteria"	"Vampirovibrionia"	"Gastranaerophilales"	"Gastranaerophilaceae"	"Gastranaerophilus"	"phascolarctosicola"	""	"species"		"GBIF"				"10876363"	"10700903"		2	""
 "P_GDRYN"	"Gaudryina"	"accepted"	"Protozoa"	"Sarcomastigophora"	""	""	"Verneulidae"	"Gaudryina"	""	""	"genus"		"GBIF"				"10167887"	"6123475"		2	""
 "P_GDRYN_KKSN"	"Gaudryina kokuseiensis"	"accepted"	"Protozoa"	"Sarcomastigophora"	""	""	"Verneulidae"	"Gaudryina"	"kokuseiensis"	""	"species"	"Ishizaki"	"GBIF"				"6123479"	"10167887"		2	""
-"B_GBCHB"	"GBChlB"	"accepted"	"Bacteria"	"Chlorobiota"	"Chlorobiia"	"Chlorobiales"	"Chloroherpetonaceae"	"GBChlB"	""	""	"genus"		"GBIF"				"11171983"	"10775177"		2	""
 "P_GMPHR"	"Geamphorella"	"accepted"	"Protozoa"	"Amoebozoa"	"Lobosa"	"Arcellinida"	"Nebelidae"	"Geamphorella"	""	""	"genus"	"Bonnet, 1959"	"GBIF"				"4888795"	"2170"		2	""
 "P_GMPHR_LUCD"	"Geamphorella lucida"	"accepted"	"Protozoa"	"Amoebozoa"	"Lobosa"	"Arcellinida"	"Nebelidae"	"Geamphorella"	"lucida"	""	"species"	"Bonnet, 1959"	"GBIF"				"10677162"	"4888795"		2	""
 "B_GEHNG"	"Gehongia"	"accepted"	"Bacteria"	"Bacillota"	"Clostridia"	"Eubacteriales"	"Christensenellaceae"	"Gehongia"	""	""	"genus"	"Liu et al., 2022"	"LPSN"	"28816"	"1935"					2	""
@@ -22583,6 +22583,7 @@
 "B_HYNSN_UDNS"	"Hyunsoonleella udoensis"	"synonym"	"Bacteria"	"Bacteroidota"	"Flavobacteriia"	"Flavobacteriales"	"Flavobacteriaceae"	"Hyunsoonleella"	"udoensis"	""	"species"	"Kim et al., 2016"	"LPSN"	"793695"	"517944"	"793694"				2	""
 "B_HYNSN_UDNN"	"Hyunsoonleella udonensis"	"accepted"	"Bacteria"	"Bacteroidota"	"Flavobacteriia"	"Flavobacteriales"	"Flavobacteriaceae"	"Hyunsoonleella"	"udonensis"	""	"species"	"Kim et al., 2016"	"LPSN"	"793694"	"517944"		"8797340"	"7660455"		2	""
 "B_HYNSN_ULVA"	"Hyunsoonleella ulvae"	"accepted"	"Bacteria"	"Bacteroidota"	"Flavobacteriia"	"Flavobacteriales"	"Flavobacteriaceae"	"Hyunsoonleella"	"ulvae"	""	"species"	"Wang et al., 2022"	"LPSN"	"28379"	"517944"					2	""
+"B_ISDG"	"ISDg"	"accepted"	"Bacteria"	"Bacillota"	"Clostridia"	"Eubacteriales"	"Lachnospiraceae"	"ISDg"	""	""	"genus"		"GBIF"				"11121283"	"4713"		2	""
 "A_[FAM]_IAINRCHC"	"Iainarchaeaceae"	"accepted"	"Archaea"	"Iainarchaeota"	"Iainarchaeia"	"Iainarchaeales"	"Iainarchaeaceae"	""	""	""	"family"		"GBIF"				"10843220"	"10672343"		2	""
 "A_[ORD]_IANRCHLS"	"Iainarchaeales"	"accepted"	"Archaea"	"Iainarchaeota"	"Iainarchaeia"	"Iainarchaeales"	""	""	""	""	"order"		"GBIF"				"10672343"	"10847779"		2	""
 "A_[CLS]_IAINARCH"	"Iainarchaeia"	"accepted"	"Archaea"	"Iainarchaeota"	"Iainarchaeia"	""	""	""	""	""	"class"		"GBIF"				"10847779"	"10776132"		2	""
@@ -22792,7 +22793,6 @@
 "B_ISCHN_ALKL"	"Isachenkonia alkalipeptolytica"	"accepted"	"Bacteria"	"Bacillota"	"Clostridia"	"Eubacteriales"	"Clostridiaceae"	"Isachenkonia"	"alkalipeptolytica"	""	"species"	"Zavarzina et al., 2020"	"LPSN"	"8748"	"8742"					2	""
 "B_ISCTS"	"Isactis"	"accepted"	"Bacteria"	"Cyanobacteria"	"Cyanobacteriia"	"Cyanobacteriales"	"Rivulariaceae"	"Isactis"	""	""	"genus"	"Thuret et al., 1886"	"GBIF"				"3219609"	"4306626"		2	""
 "B_ISCTS_PLAN"	"Isactis plana"	"accepted"	"Bacteria"	"Cyanobacteria"	"Cyanobacteriia"	"Cyanobacteriales"	"Rivulariaceae"	"Isactis"	"plana"	""	"species"	"Thur et al."	"GBIF"				"3219610"	"3219609"		2	""
-"B_ISDG"	"ISDg"	"accepted"	"Bacteria"	"Bacillota"	"Clostridia"	"Eubacteriales"	"Lachnospiraceae"	"ISDg"	""	""	"genus"		"GBIF"				"11121283"	"4713"		2	""
 "B_ISHKW"	"Ishikawaella"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Ishikawaella"	""	""	"genus"		"GBIF"				"10797324"	"11158430"		2	""
 "B_ISHKW_CPSL"	"Ishikawaella capsulata"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Ishikawaella"	"capsulata"	""	"species"		"GBIF"				"10718144"	"10797324"		2	""
 "B_ISBCL"	"Isobaculum"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Carnobacteriaceae"	"Isobaculum"	""	""	"genus"	"Collins et al., 2002"	"LPSN"	"515857"	"279"		"3227154"			2	"432998006"
@@ -23653,6 +23653,7 @@
 "B_KYTCC_AERL"	"Kytococcus aerolatus"	"accepted"	"Bacteria"	"Actinomycetota"	"Actinomycetes"	"Micrococcales"	"Kytococcaceae"	"Kytococcus"	"aerolatus"	""	"species"	"Nouioui et al., 2018"	"LPSN"	"788155"	"515905"		"7687887"	"3225662"		1.5	""
 "B_KYTCC_SCHR"	"Kytococcus schroeteri"	"accepted"	"Bacteria"	"Actinomycetota"	"Actinomycetes"	"Micrococcales"	"Kytococcaceae"	"Kytococcus"	"schroeteri"	""	"species"	"Becker et al., 2002"	"LPSN"	"777226"	"515905"		"3225663"	"3225662"		1	"428721003"
 "B_KYTCC_SDNT"	"Kytococcus sedentarius"	"accepted"	"Bacteria"	"Actinomycetota"	"Actinomycetes"	"Micrococcales"	"Kytococcaceae"	"Kytococcus"	"sedentarius"	""	"species"	"Nouioui et al., 2018"	"LPSN"	"777227"	"515905"		"3225664"	"3225662"		1	"113775009"
+"B_LS-NO"	"LS-NOB"	"accepted"	"Bacteria"	"Nitrospinota"	"Nitrospinia"	"Nitrospinales"	"Nitrospinaceae"	"LS-NOB"	""	""	"genus"		"GBIF"				"11159629"	"5444"		2	""
 "B_LABED"	"Labedaea"	"accepted"	"Bacteria"	"Actinomycetota"	"Actinomycetes"	"Pseudonocardiales"	"Pseudonocardiaceae"	"Labedaea"	""	""	"genus"	"2012"	"LPSN"	"518231"	"1137"		"7668340"	"3841"		2	""
 "B_LABED_RHZS"	"Labedaea rhizosphaerae"	"accepted"	"Bacteria"	"Actinomycetota"	"Actinomycetes"	"Pseudonocardiales"	"Pseudonocardiaceae"	"Labedaea"	"rhizosphaerae"	""	"species"	"2012"	"LPSN"	"790047"	"518231"		"7830525"	"7668340"		2	""
 "B_LBDLL"	"Labedella"	"accepted"	"Bacteria"	"Actinomycetota"	"Actinomycetes"	"Micrococcales"	"Microbacteriaceae"	"Labedella"	""	""	"genus"	"Li et al., 2019"	"LPSN"	"517689"	"875"		"4899919"			2	""
@@ -25497,7 +25498,6 @@
 "B_LTTDB"	"Lottiidibacillus"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Caryophanales"	"Bacillaceae"	"Lottiidibacillus"	""	""	"genus"	"Liu et al., 2020"	"LPSN"	"9035"	"191"					2	""
 "B_LTTDB_PTLL"	"Lottiidibacillus patelloidae"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Caryophanales"	"Bacillaceae"	"Lottiidibacillus"	"patelloidae"	""	"species"	"Liu et al., 2020"	"LPSN"	"15262"	"9035"					2	""
 "P_[PHL]_LOUKOZOA"	"Loukozoa"	"accepted"	"Protozoa"	"Loukozoa"	""	""	""	""	""	""	"phylum"		"GBIF"				"7872314"	"7"		2	""
-"B_LS-NO"	"LS-NOB"	"accepted"	"Bacteria"	"Nitrospinota"	"Nitrospinia"	"Nitrospinales"	"Nitrospinaceae"	"LS-NOB"	""	""	"genus"		"GBIF"				"11159629"	"5444"		2	""
 "B_LUCBCTRM"	"Lucibacterium"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Vibrionales"	"Vibrionaceae"	"Lucibacterium"	""	""	"genus"	"Hendrie et al., 1970"	"LPSN"	"515980"	"1543"	"517157"				1	""
 "B_LUCBCTRM_HRVY"	"Lucibacterium harveyi"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Vibrionales"	"Vibrionaceae"	"Lucibacterium"	"harveyi"	""	"species"	"Hendrie et al., 1970"	"LPSN"	"777606"	"515980"	"783009"				1	""
 "B_LUCFR"	"Lucifera"	"accepted"	"Bacteria"	"Bacillota"	"Negativicutes"	"Selenomonadales"	"Sporomusaceae"	"Lucifera"	""	""	"genus"	"Sanchez-Andrea et al., 2019"	"LPSN"	"521634"	"2041"					2	""
@@ -25850,6 +25850,9 @@
 "B_LYTCM"	"Lyticum"	"accepted"	"Bacteria"	"Pseudomonadota"	"Alphaproteobacteria"	"Rickettsiales"	"Ehrlichiaceae"	"Lyticum"	""	""	"genus"	"Preer et al., 1982"	"LPSN"	"517271"	"473"		"3221463"	"4901684"		2	"433004006"
 "B_LYTCM_FLGL"	"Lyticum flagellatum"	"accepted"	"Bacteria"	"Pseudomonadota"	"Alphaproteobacteria"	"Rickettsiales"	"Ehrlichiaceae"	"Lyticum"	"flagellatum"	""	"species"	"Preer et al., 1982"	"LPSN"	"784168"	"517271"		"3221464"	"3221463"		2	"433754005"
 "B_LYTCM_SNSM"	"Lyticum sinuosum"	"accepted"	"Bacteria"	"Pseudomonadota"	"Alphaproteobacteria"	"Rickettsiales"	"Ehrlichiaceae"	"Lyticum"	"sinuosum"	""	"species"	"Preer et al., 1982"	"LPSN"	"784169"	"517271"		"3221465"	"3221463"		2	"434353007"
+"A_MGII-"	"MGIIa-I"	"accepted"	"Archaea"	"Thermoplasmatota"	"Poseidoniia"	"Poseidoniales"	"Poseidoniaceae"	"MGIIa-I"	""	""	"genus"		"GBIF"				"11196009"	"10685831"		2	""
+"A_GII-P"	"MGIIb-P"	"accepted"	"Archaea"	"Thermoplasmatota"	"Poseidoniia"	"Poseidoniales"	"Thalassarchaeaceae"	"MGIIb-P"	""	""	"genus"		"GBIF"				"11123790"	"10752789"		2	""
+"B_MZ-XQ"	"MZ-XQ"	"accepted"	"Bacteria"	"Mycoplasmatota"	"Mollicutes"	"Acholeplasmatales"	"Acholeplasmataceae"	"MZ-XQ"	""	""	"genus"		"GBIF"				"11137212"			2	""
 "B_MBKBC"	"Mabikibacter"	"synonym"	"Bacteria"	"Pseudomonadota"	"Alphaproteobacteria"	"Hyphomicrobiales"	"Notoacmeibacteraceae"	"Mabikibacter"	""	""	"genus"	"Choi et al., 2017"	"LPSN"	"519257"	"2084"	"519233"				2	""
 "B_MBKBC_RUBR"	"Mabikibacter ruber"	"synonym"	"Bacteria"	"Pseudomonadota"	"Alphaproteobacteria"	"Hyphomicrobiales"	"Notoacmeibacteraceae"	"Mabikibacter"	"ruber"	""	"species"	"Choi et al., 2017"	"LPSN"	"795890"	"519257"	"795709"	"9791970"			2	""
 "B_MCLLB"	"Macellibacteroides"	"accepted"	"Bacteria"	"Bacteroidota"	"Bacteroidia"	"Bacteroidales"	"Porphyromonadaceae"	"Macellibacteroides"	""	""	"genus"	"Jabari et al., 2012"	"LPSN"	"518264"	"1100"		"8021701"			2	""
@@ -27856,8 +27859,6 @@
 "F_MYRZY_PRPS_TXTL"	"Meyerozyma parapsilosis tuxtlensis"	"synonym"	"Fungi"	"Ascomycota"	"Saccharomycetes"	"Saccharomycetales"	"Debaryomycetaceae"	"Meyerozyma"	"parapsilosis"	"tuxtlensis"	"subspecies"	"Herrera et al."	"GBIF"				"3479713"		"5893383"	1.5	""
 "F_MYRZY_PSDG"	"Meyerozyma pseudoguilliermondii"	"synonym"	"Fungi"	"Ascomycota"	"Saccharomycetes"	"Saccharomycetales"	"Debaryomycetaceae"	"Meyerozyma"	"pseudoguilliermondii"	""	"species"		"GBIF"				"3556778"	"5893380"	"5893383"	1.5	""
 "F_MYRZY_SMTH"	"Meyerozyma smithsonii"	"accepted"	"Fungi"	"Ascomycota"	"Saccharomycetes"	"Saccharomycetales"	"Debaryomycetaceae"	"Meyerozyma"	"smithsonii"	""	"species"	"Yurkov et al."	"GBIF"				"10712206"	"5893380"		1.5	""
-"A_MGII-"	"MGIIa-I"	"accepted"	"Archaea"	"Thermoplasmatota"	"Poseidoniia"	"Poseidoniales"	"Poseidoniaceae"	"MGIIa-I"	""	""	"genus"		"GBIF"				"11196009"	"10685831"		2	""
-"A_GII-P"	"MGIIb-P"	"accepted"	"Archaea"	"Thermoplasmatota"	"Poseidoniia"	"Poseidoniales"	"Thalassarchaeaceae"	"MGIIb-P"	""	""	"genus"		"GBIF"				"11123790"	"10752789"		2	""
 "B_MCVBR"	"Micavibrio"	"accepted"	"Bacteria"	"Pseudomonadota"	"Oligoflexia"	"Bdellovibrionales"	"Bdellovibrionaceae"	"Micavibrio"	""	""	"genus"	"Lambina et al., 1989"	"LPSN"	"517285"	"203"		"11199699"	"8932"		2	"429897008"
 "B_MCVBR_ADMR"	"Micavibrio admirandus"	"accepted"	"Bacteria"	"Pseudomonadota"	"Oligoflexia"	"Bdellovibrionales"	"Bdellovibrionaceae"	"Micavibrio"	"admirandus"	""	"species"	"Lambina et al., 1989"	"LPSN"	"784260"	"517285"					2	"433368001"
 "A_[FAM]_MICRRCHC"	"Micrarchaeaceae"	"accepted"	"Archaea"	"Micrarchaeota"	"Micrarchaeia"	"Micrarchaeales"	"Micrarchaeaceae"	""	""	""	"family"		"GBIF"				"10878041"	"10702512"		2	""
@@ -30316,7 +30317,6 @@
 "B_MYXSR_BRMN"	"Myxosarcina burmensis"	"accepted"	"Bacteria"	"Cyanobacteria"	"Cyanobacteriia"	"Cyanobacteriales"	"Xenococcaceae"	"Myxosarcina"	"burmensis"	""	"species"	"Skuja"	"GBIF"				"3216275"	"7729673"		2	""
 "B_MYXSR_CNCN"	"Myxosarcina concinna"	"accepted"	"Bacteria"	"Cyanobacteria"	"Cyanobacteriia"	"Cyanobacteriales"	"Xenococcaceae"	"Myxosarcina"	"concinna"	""	"species"		"GBIF"				"3217367"	"7729673"		2	""
 "B_MYXSR_GLCP"	"Myxosarcina gloeocapsoides"	"accepted"	"Bacteria"	"Cyanobacteria"	"Cyanobacteriia"	"Cyanobacteriales"	"Xenococcaceae"	"Myxosarcina"	"gloeocapsoides"	""	"species"	"Komarek et al."	"GBIF"				"3217365"	"7729673"		2	""
-"B_MZ-XQ"	"MZ-XQ"	"accepted"	"Bacteria"	"Mycoplasmatota"	"Mollicutes"	"Acholeplasmatales"	"Acholeplasmataceae"	"MZ-XQ"	""	""	"genus"		"GBIF"				"11137212"			2	""
 "B_MZBMY"	"Mzabimyces"	"synonym"	"Bacteria"	"Actinomycetota"	"Actinomycetes"	"Pseudonocardiales"	"Pseudonocardiaceae"	"Mzabimyces"	""	""	"genus"	"Saker et al., 2015"	"LPSN"	"518817"	"1137"	"518590"				2	""
 "B_MZBMY_ALGR"	"Mzabimyces algeriensis"	"synonym"	"Bacteria"	"Actinomycetota"	"Actinomycetes"	"Pseudonocardiales"	"Pseudonocardiaceae"	"Mzabimyces"	"algeriensis"	""	"species"	"Saker et al., 2015"	"LPSN"	"793403"	"518817"	"795677"				2	""
 "B_NAASI"	"Naasia"	"accepted"	"Bacteria"	"Actinomycetota"	"Actinomycetes"	"Micrococcales"	"Microbacteriaceae"	"Naasia"	""	""	"genus"	"Weon et al., 2013"	"LPSN"	"518394"	"875"		"8305219"			2	""
@@ -41270,7 +41270,6 @@
 "B_SLMNL_ARPH"	"Salmonella Arapahoe"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Arapahoe"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_ARCH"	"Salmonella Arechavaleta"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Arechavaleta"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_ARGN"	"Salmonella Argenteuil"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Argenteuil"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_ARZN"	"Salmonella arizonae"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"arizonae"	""	"species"	"Kauffmann, 1964"	"LPSN"	"780744"	"516547"	"780755"	"5427588"	"3221815"		1.5	""
 "B_SLMNL_ARSH"	"Salmonella Arusha"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Arusha"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_ASCH"	"Salmonella Aschersleben"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Aschersleben"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_ASHN"	"Salmonella Ashanti"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Ashanti"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
@@ -41379,7 +41378,6 @@
 "B_SLMNL_BLTN"	"Salmonella Bolton"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Bolton"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_BNMS"	"Salmonella Bonames"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Bonames"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_BNRN"	"Salmonella Bonariensis"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Bonariensis"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_BNGR"	"Salmonella bongori"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"bongori"	""	"species"	"Reeves et al., 1989"	"LPSN"	"780745"	"516547"		"5427596"	"3221815"		1	"398393000"
 "B_SLMNL_BONN"	"Salmonella Bonn"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Bonn"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_BOTL"	"Salmonella Bootle"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Bootle"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_BRBC"	"Salmonella Borbeck"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Borbeck"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
@@ -41482,14 +41480,6 @@
 "B_SLMNL_CHNG"	"Salmonella Chingola"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Chingola"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_CHRD"	"Salmonella Chiredzi"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Chiredzi"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_CHTT"	"Salmonella Chittagong"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Chittagong"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_CHLR"	"Salmonella choleraesuis"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	""	"species"	"Weldin, 1927"	"LPSN"	"780746"	"516547"	"784857"	"7515106"	"3221815"	"9701185"	1	""
-"B_SLMNL_CHLR_ARZN"	"Salmonella choleraesuis arizonae"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"arizonae"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780747"	"780746"	"780755"	"5427587"	"7515106"	"5427586"	1	""
-"B_SLMNL_CHLR_BNGR"	"Salmonella choleraesuis bongori"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"bongori"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780748"	"780746"	"780745"	"5427597"	"7515106"	"5427596"	1	""
-"B_SLMNL_CHLR_CHLR"	"Salmonella choleraesuis choleraesuis"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"choleraesuis"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780749"	"780746"	"780758"	"5427590"	"7515106"	"5427589"	1	""
-"B_SLMNL_CHLR_DRZN"	"Salmonella choleraesuis diarizonae"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"diarizonae"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780750"	"780746"	"780757"	"5427579"	"7515106"	"5427578"	1	""
-"B_SLMNL_CHLR_HOTN"	"Salmonella choleraesuis houtenae"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"houtenae"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780751"	"780746"	"780759"	"5427581"	"7515106"	"5427580"	1	""
-"B_SLMNL_CHLR_INDC"	"Salmonella choleraesuis indica"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"indica"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780752"	"780746"	"780760"	"5427583"	"7515106"	"5427582"	1	""
-"B_SLMNL_CHLR_SALM"	"Salmonella choleraesuis salamae"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"salamae"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780753"	"780746"	"780761"	"5427585"	"7515106"	"5427584"	1	""
 "B_SLMNL_CHMD"	"Salmonella Chomedey"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Chomedey"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_CHRS"	"Salmonella Christiansborg"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Christiansborg"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_CLCK"	"Salmonella Clackamas"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Clackamas"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
@@ -41552,7 +41542,6 @@
 "B_SLMNL_DESS"	"Salmonella Dessau"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Dessau"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_DTML"	"Salmonella Detmold"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Detmold"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_DVRS"	"Salmonella Deversoir"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Deversoir"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_DRZN"	"Salmonella diarizonae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"diarizonae"	""	"species"		"GBIF"				"10672082"	"3221815"		1.5	""
 "B_SLMNL_DIBR"	"Salmonella Dibra"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Dibra"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_DTRC"	"Salmonella Dietrichsdorf"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Dietrichsdorf"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_DPPL"	"Salmonella Dieuppeul"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Dieuppeul"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
@@ -41614,15 +41603,6 @@
 "B_SLMNL_ENCN"	"Salmonella Encino"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Encino"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_ENSC"	"Salmonella Enschede"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Enschede"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_ENTB"	"Salmonella Entebbe"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Entebbe"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_ENTR"	"Salmonella enterica"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	""	"species"	"Le Minor et al., 1987"	"LPSN"	"784857"	"516547"		"9701185"	"3221815"		1	"110378009,397502001,398428002,398508004,398371005,398620001,398488004"
-"B_SLMNL_ENTR_ARZN"	"Salmonella enterica arizonae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"arizonae"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780755"	"784857"		"5427586"	"9701185"		1	""
-"B_SLMNL_ENTR_BNGR"	"Salmonella enterica bongori"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"bongori"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780756"	"784857"	"780745"	"5427598"	"9701185"	"5427596"	1	""
-"B_SLMNL_ENTR_DRZN"	"Salmonella enterica diarizonae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"diarizonae"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780757"	"784857"		"5427578"	"9701185"		1	""
-"B_SLMNL_ENTR_ENTR"	"Salmonella enterica enterica"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"enterica"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780758"	"784857"		"5427589"	"9701185"		1	""
-"B_SLMNL_ENTR_HOTN"	"Salmonella enterica houtenae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"houtenae"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780759"	"784857"		"5427580"	"9701185"		1	""
-"B_SLMNL_ENTR_INDC"	"Salmonella enterica indica"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"indica"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780760"	"784857"		"5427582"	"9701185"		1	""
-"B_SLMNL_ENTR_SALM"	"Salmonella enterica salamae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"salamae"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780761"	"784857"		"5427584"	"9701185"		1	""
-"B_SLMNL_RTDS"	"Salmonella enteritidis"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enteritidis"	""	"species"	"Castellani et al., 1919"	"LPSN"	"780762"	"516547"	"784857"	"5427592"	"3221815"	"9701185"	1	""
 "B_SLMNL_ENUG"	"Salmonella Enugu"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Enugu"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_EPLN"	"Salmonella Epalinges"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Epalinges"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_EPCR"	"Salmonella Epicrates"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Epicrates"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
@@ -41741,9 +41721,10 @@
 "B_SLMNL_GRAZ"	"Salmonella Graz"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Graz"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_GREZ"	"Salmonella Greiz"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Greiz"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_GRNK"	"Salmonella Groenekan"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Groenekan"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_GRPB"	"Salmonella Group B"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Group B"	""	"species"		"manually added"							1.5	""
-"B_SLMNL_GRPC"	"Salmonella Group C"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Group C"	""	"species"		"manually added"							1.5	""
-"B_SLMNL_GRPD"	"Salmonella Group D"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Group D"	""	"species"		"manually added"							1.5	""
+"B_SLMNL_GRPA"	"Salmonella Group A"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Group A"	""	"species"		"manually added"		"516547"			"3221815"		1.5	""
+"B_SLMNL_GRPB"	"Salmonella Group B"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Group B"	""	"species"		"manually added"		"516547"			"3221815"		1.5	""
+"B_SLMNL_GRPC"	"Salmonella Group C"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Group C"	""	"species"		"manually added"		"516547"			"3221815"		1.5	""
+"B_SLMNL_GRPD"	"Salmonella Group D"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Group D"	""	"species"		"manually added"		"516547"			"3221815"		1.5	""
 "B_SLMNL_GNSS"	"Salmonella Grumpensis"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Grumpensis"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_GRPR"	"Salmonella Guarapiranga"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Guarapiranga"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_GURN"	"Salmonella Guerin"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Guerin"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
@@ -41807,7 +41788,6 @@
 "B_SLMNL_HNGK"	"Salmonella Hongkong"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Hongkong"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_HRSH"	"Salmonella Horsham"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Horsham"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_HSTN"	"Salmonella Houston"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Houston"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_HOTN"	"Salmonella houtenae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"houtenae"	""	"species"		"GBIF"				"7617321"	"3221815"		1.5	""
 "B_SLMNL_HDDN"	"Salmonella Huddinge"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Huddinge"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_HTTW"	"Salmonella Huettwilen"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Huettwilen"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_HULL"	"Salmonella Hull"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Hull"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
@@ -42277,13 +42257,12 @@
 "B_SLMNL_PKST"	"Salmonella Pakistan"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Pakistan"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_PLMN"	"Salmonella Palamaner"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Palamaner"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_PALM"	"Salmonella Palime"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Palime"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_PANM"	"Salmonella panama"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"panama"	""	"species"	"Kauffmann, 1934"	"GBIF"				"9407232"	"3221815"		1.5	""
 "B_SLMNL_PAPN"	"Salmonella Papuana"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Papuana"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_PARK"	"Salmonella Parakou"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Parakou"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_PRTY"	"Salmonella paratyphi"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"paratyphi"	""	"species"	"Ezaki et al., 2000"	"LPSN"	"784858"	"516547"	"784857"	"5427593"	"3221815"	"9701185"	1	"840687007"
-"B_SLMNL_PRTA"	"Salmonella Paratyphi A"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Paratyphi A"	""	"species"		"manually added"							1.5	""
-"B_SLMNL_PRTB"	"Salmonella Paratyphi B"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Paratyphi B"	""	"species"		"manually added"							1.5	""
-"B_SLMNL_PRTC"	"Salmonella Paratyphi C"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Paratyphi C"	""	"species"		"manually added"							1.5	""
+"B_SLMNL_PRTY"	"Salmonella Paratyphi"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Paratyphi"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
+"B_SLMNL_PRTA"	"Salmonella Paratyphi A"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Paratyphi A"	""	"species"		"manually added"		"516547"			"3221815"		1.5	""
+"B_SLMNL_PRTB"	"Salmonella Paratyphi B"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Paratyphi B"	""	"species"		"manually added"		"516547"			"3221815"		1.5	""
+"B_SLMNL_PRTC"	"Salmonella Paratyphi C"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"Paratyphi C"	""	"species"		"manually added"		"516547"			"3221815"		1.5	""
 "B_SLMNL_PARS"	"Salmonella Paris"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Paris"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_PRKR"	"Salmonella Parkroyal"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Parkroyal"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_PSNG"	"Salmonella Pasing"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Pasing"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
@@ -42480,7 +42459,6 @@
 "B_SLMNL_STVN"	"Salmonella Stuivenberg"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Stuivenberg"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_STTT"	"Salmonella Stuttgart"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Stuttgart"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_SUBR"	"Salmonella Suberu"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Suberu"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_SBTR"	"Salmonella subterranea"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"subterranea"	""	"species"	"Shelobolina et al., 2005"	"LPSN"	"780769"	"516547"		"5427595"	"3221815"		1.5	""
 "B_SLMNL_SUDN"	"Salmonella Sudan"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Sudan"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_SLLD"	"Salmonella Suelldorf"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Suelldorf"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_SNDS"	"Salmonella Sundsvall"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Sundsvall"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
@@ -42574,8 +42552,8 @@
 "B_SLMNL_TCSN"	"Salmonella Tucson"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Tucson"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_TUDU"	"Salmonella Tudu"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Tudu"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_TUMD"	"Salmonella Tumodi"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Tumodi"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
-"B_SLMNL_TYPH"	"Salmonella typhi"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"typhi"	""	"species"	"Warren et al., 1930"	"LPSN"	"784859"	"516547"	"784857"	"5427594"	"3221815"	"9701185"	1	"712764007"
-"B_SLMNL_HMRM"	"Salmonella typhimurium"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"typhimurium"	""	"species"	"Castellani et al., 1919"	"LPSN"	"780770"	"516547"	"784857"	"5427591"	"3221815"	"9701185"	1	""
+"B_SLMNL_TYPH"	"Salmonella Typhi"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Typhi"	"subspecies"		"manually added"		"784857"			"9701185"		1	"840687007"
+"B_SLMNL_HMRM"	"Salmonella Typhimurium"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Typhimurium"	"subspecies"		"manually added"		"784857"			"9701185"		1	"712764007"
 "B_SLMNL_THSS"	"Salmonella Typhisuis"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Typhisuis"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_TYRS"	"Salmonella Tyresoe"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Tyresoe"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_UCCL"	"Salmonella Uccle"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Uccle"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
@@ -42718,6 +42696,29 @@
 "B_SLMNL_ZONG"	"Salmonella Zongo"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Zongo"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_ZULN"	"Salmonella Zuilen"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Zuilen"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
 "B_SLMNL_ZWCK"	"Salmonella Zwickau"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"Zwickau"	"subspecies"		"manually added"		"784857"			"9701185"		1	""
+"B_SLMNL_ARZN"	"Salmonella arizonae"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"arizonae"	""	"species"	"Kauffmann, 1964"	"LPSN"	"780744"	"516547"	"780755"	"5427588"	"3221815"		1.5	""
+"B_SLMNL_BNGR"	"Salmonella bongori"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"bongori"	""	"species"	"Reeves et al., 1989"	"LPSN"	"780745"	"516547"		"5427596"	"3221815"		1	"398393000"
+"B_SLMNL_CHLR"	"Salmonella choleraesuis"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	""	"species"	"Weldin, 1927"	"LPSN"	"780746"	"516547"	"784857"	"7515106"	"3221815"	"9701185"	1	""
+"B_SLMNL_CHLR_ARZN"	"Salmonella choleraesuis arizonae"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"arizonae"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780747"	"780746"	"780755"	"5427587"	"7515106"	"5427586"	1	""
+"B_SLMNL_CHLR_BNGR"	"Salmonella choleraesuis bongori"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"bongori"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780748"	"780746"	"780745"	"5427597"	"7515106"	"5427596"	1	""
+"B_SLMNL_CHLR_CHLR"	"Salmonella choleraesuis choleraesuis"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"choleraesuis"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780749"	"780746"	"780758"	"5427590"	"7515106"	"5427589"	1	""
+"B_SLMNL_CHLR_DRZN"	"Salmonella choleraesuis diarizonae"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"diarizonae"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780750"	"780746"	"780757"	"5427579"	"7515106"	"5427578"	1	""
+"B_SLMNL_CHLR_HOTN"	"Salmonella choleraesuis houtenae"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"houtenae"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780751"	"780746"	"780759"	"5427581"	"7515106"	"5427580"	1	""
+"B_SLMNL_CHLR_INDC"	"Salmonella choleraesuis indica"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"indica"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780752"	"780746"	"780760"	"5427583"	"7515106"	"5427582"	1	""
+"B_SLMNL_CHLR_SALM"	"Salmonella choleraesuis salamae"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"choleraesuis"	"salamae"	"subspecies"	"Le Minor et al., 1985"	"LPSN"	"780753"	"780746"	"780761"	"5427585"	"7515106"	"5427584"	1	""
+"B_SLMNL_DRZN"	"Salmonella diarizonae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"diarizonae"	""	"species"		"GBIF"		"516547"		"10672082"	"3221815"		1.5	""
+"B_SLMNL_ENTR"	"Salmonella enterica"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	""	"species"	"Le Minor et al., 1987"	"LPSN"	"784857"	"516547"		"9701185"	"3221815"		1	"110378009,397502001,398428002,398508004,398371005,398620001,398488004"
+"B_SLMNL_ENTR_ARZN"	"Salmonella enterica arizonae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"arizonae"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780755"	"784857"		"5427586"	"9701185"		1	""
+"B_SLMNL_ENTR_BNGR"	"Salmonella enterica bongori"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"bongori"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780756"	"784857"	"780745"	"5427598"	"9701185"	"5427596"	1	""
+"B_SLMNL_ENTR_DRZN"	"Salmonella enterica diarizonae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"diarizonae"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780757"	"784857"		"5427578"	"9701185"		1	""
+"B_SLMNL_ENTR_ENTR"	"Salmonella enterica enterica"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"enterica"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780758"	"784857"		"5427589"	"9701185"		1	""
+"B_SLMNL_ENTR_HOTN"	"Salmonella enterica houtenae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"houtenae"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780759"	"784857"		"5427580"	"9701185"		1	""
+"B_SLMNL_ENTR_INDC"	"Salmonella enterica indica"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"indica"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780760"	"784857"		"5427582"	"9701185"		1	""
+"B_SLMNL_ENTR_SALM"	"Salmonella enterica salamae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enterica"	"salamae"	"subspecies"	"Le Minor et al., 1987"	"LPSN"	"780761"	"784857"		"5427584"	"9701185"		1	""
+"B_SLMNL_RTDS"	"Salmonella enteritidis"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"enteritidis"	""	"species"	"Castellani et al., 1919"	"LPSN"	"780762"	"516547"	"784857"	"5427592"	"3221815"	"9701185"	1	""
+"B_SLMNL_HOTN"	"Salmonella houtenae"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"houtenae"	""	"species"		"GBIF"		"516547"		"7617321"	"3221815"		1.5	""
+"B_SLMNL_PANM"	"Salmonella panama"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"panama"	""	"species"	"Kauffmann, 1934"	"GBIF"		"516547"		"9407232"	"3221815"		1.5	""
+"B_SLMNL_SBTR"	"Salmonella subterranea"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Enterobacterales"	"Enterobacteriaceae"	"Salmonella"	"subterranea"	""	"species"	"Shelobolina et al., 2005"	"LPSN"	"780769"	"516547"		"5427595"	"3221815"		1.5	""
 "B_SLSPL"	"Salsipaludibacter"	"accepted"	"Bacteria"	"Actinomycetota"	"Nitriliruptoria"	"Salsipaludibacterales"	"Salsipaludibacteraceae"	"Salsipaludibacter"	""	""	"genus"	"Almeida et al., 2022"	"LPSN"	"25963"	"25953"					2	""
 "B_SLSPL_ALBS"	"Salsipaludibacter albus"	"accepted"	"Bacteria"	"Actinomycetota"	"Nitriliruptoria"	"Salsipaludibacterales"	"Salsipaludibacteraceae"	"Salsipaludibacter"	"albus"	""	"species"	"Almeida et al., 2022"	"LPSN"	"25977"	"25963"					2	""
 "B_[FAM]_SLSPLDBC"	"Salsipaludibacteraceae"	"accepted"	"Bacteria"	"Actinomycetota"	"Nitriliruptoria"	"Salsipaludibacterales"	"Salsipaludibacteraceae"	""	""	""	"family"	"Almeida et al., 2022"	"LPSN"	"25953"	"25966"					2	""
@@ -45278,7 +45279,7 @@
 "B_STNTR_INDC"	"Stenotrophomonas indicatrix"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Lysobacterales"	"Lysobacteraceae"	"Stenotrophomonas"	"indicatrix"	""	"species"	"Weber et al., 2018"	"LPSN"	"797782"	"516670"		"10701219"			1.5	""
 "B_STNTR_KRNS"	"Stenotrophomonas koreensis"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Lysobacterales"	"Lysobacteraceae"	"Stenotrophomonas"	"koreensis"	""	"species"	"Yang et al., 2006"	"LPSN"	"781248"	"516670"		"3222376"			1.5	""
 "B_STNTR_LCTT"	"Stenotrophomonas lactitubi"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Lysobacterales"	"Lysobacteraceae"	"Stenotrophomonas"	"lactitubi"	""	"species"	"Weber et al., 2018"	"LPSN"	"797783"	"516670"		"10788780"			1.5	""
-"B_STNTR_MLTP"	"Stenotrophomonas maltophilia"	"synonym"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Lysobacterales"	"Lysobacteraceae"	"Stenotrophomonas"	"maltophilia"	""	"species"	"Palleroni et al., 1993"	"LPSN"	"781249"	"516670"	"783141"	"10912104"			1	"113697002"
+"B_STNTR_MLTP"	"Stenotrophomonas maltophilia"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Lysobacterales"	"Lysobacteraceae"	"Stenotrophomonas"	"maltophilia"	""	"species"	"Palleroni et al., 1993"	"LPSN"	"781249"	"516670"		"10912104"			1	"113697002"
 "B_STNTR_NTRT"	"Stenotrophomonas nitritireducens"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Lysobacterales"	"Lysobacteraceae"	"Stenotrophomonas"	"nitritireducens"	""	"species"	"Finkmann et al., 2000"	"LPSN"	"781250"	"516670"		"3222370"			1.5	"416746005"
 "B_STNTR_PNCH"	"Stenotrophomonas panacihumi"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Lysobacterales"	"Lysobacteraceae"	"Stenotrophomonas"	"panacihumi"	""	"species"	"Yi et al., 2010"	"GBIF"				"11141735"			1.5	""
 "B_STNTR_PAVN"	"Stenotrophomonas pavanii"	"accepted"	"Bacteria"	"Pseudomonadota"	"Gammaproteobacteria"	"Lysobacterales"	"Lysobacteraceae"	"Stenotrophomonas"	"pavanii"	""	"species"	"Ramos et al., 2011"	"LPSN"	"789171"	"516670"		"8102737"			1.5	"704977000"
@@ -45427,6 +45428,15 @@
 "B_STRPTB_RATT"	"Streptobacillus ratti"	"accepted"	"Bacteria"	"Fusobacteriota"	"Fusobacteriia"	"Fusobacteriales"	"Leptotrichiaceae"	"Streptobacillus"	"ratti"	""	"species"	"Eisenberg et al., 2016"	"LPSN"	"794063"	"516688"		"9144099"	"3225903"		1.5	""
 "B_[FAM]_STRPTCCC"	"Streptococcaceae"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	""	""	""	"family"	"Deibel et al., 1974"	"LPSN"	"1344"	"5123"		"4899829"	"577"	"7798"	2	"115107007"
 "B_STRPT"	"Streptococcus"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	""	""	"genus"	"Rosenbach, 1884"	"LPSN"	"517118"	"1344"		"3223465"	"4899829"		1	"58800005,414871004,70160008"
+"B_STRPT_GRPA"	"Streptococcus Group A"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group A"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
+"B_STRPT_GRPB"	"Streptococcus Group B"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group B"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
+"B_STRPT_GRPC"	"Streptococcus Group C"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group C"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
+"B_STRPT_GRPD"	"Streptococcus Group D"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group D"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
+"B_STRPT_GRPF"	"Streptococcus Group F"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group F"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
+"B_STRPT_GRPG"	"Streptococcus Group G"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group G"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
+"B_STRPT_GRPH"	"Streptococcus Group H"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group H"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
+"B_STRPT_GRPK"	"Streptococcus Group K"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group K"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
+"B_STRPT_GRPL"	"Streptococcus Group L"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group L"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
 "B_STRPT_ACDM"	"Streptococcus acidominimus"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"acidominimus"	""	"species"	"Ayers et al., 1922"	"LPSN"	"781295"	"517118"					1	"51182006"
 "B_STRPT_ADJC"	"Streptococcus adjacens"	"synonym"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"adjacens"	""	"species"	"Bouvet et al., 1989"	"LPSN"	"781296"	"517118"	"776611"				1.5	""
 "B_STRPT_AGLC"	"Streptococcus agalactiae"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"agalactiae"	""	"species"	"Lehmann et al., 1896"	"LPSN"	"781297"	"517118"					1	"713924007,43492007"
@@ -45496,15 +45506,6 @@
 "B_STRPT_GLLL_PSTR"	"Streptococcus gallolyticus pasteurianus"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"gallolyticus"	"pasteurianus"	"subspecies"	"Beck et al., 2008"	"LPSN"	"781340"	"781337"		"3227070"			1.25	""
 "B_STRPT_GARV"	"Streptococcus garvieae"	"synonym"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"garvieae"	""	"species"	"Collins et al., 1984"	"LPSN"	"781341"	"517118"	"777418"				1	""
 "B_STRPT_GRDN"	"Streptococcus gordonii"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"gordonii"	""	"species"	"Kilian et al., 1989"	"LPSN"	"781342"	"517118"					1	"113986004"
-"B_STRPT_GRPA"	"Streptococcus Group A"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group A"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
-"B_STRPT_GRPB"	"Streptococcus Group B"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group B"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
-"B_STRPT_GRPC"	"Streptococcus Group C"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group C"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
-"B_STRPT_GRPD"	"Streptococcus Group D"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group D"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
-"B_STRPT_GRPF"	"Streptococcus Group F"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group F"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
-"B_STRPT_GRPG"	"Streptococcus Group G"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group G"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
-"B_STRPT_GRPH"	"Streptococcus Group H"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group H"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
-"B_STRPT_GRPK"	"Streptococcus Group K"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group K"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
-"B_STRPT_GRPL"	"Streptococcus Group L"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"Group L"	""	"species"	"Lancefield, 1933"	"manually added"							1.5	""
 "B_STRPT_GWNG"	"Streptococcus gwangjuense"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"gwangjuense"	""	"species"		"GBIF"				"11190550"	"3223465"		1.5	""
 "B_STRPT_HLCH"	"Streptococcus halichoeri"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"halichoeri"	""	"species"	"Shewmaker et al., 2016"	"LPSN"	"781344"	"517118"					1.25	"438161002"
 "B_STRPT_HLTS"	"Streptococcus halitosis"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"halitosis"	""	"species"		"GBIF"				"10822581"	"3223465"		1.5	""
@@ -45554,7 +45555,7 @@
 "B_STRPT_ORLX"	"Streptococcus oriloxodontae"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"oriloxodontae"	""	"species"	"Shinozaki-Kuwahara et al., 2014"	"LPSN"	"792340"	"517118"					1.5	""
 "B_STRPT_ORSS"	"Streptococcus orisasini"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"orisasini"	""	"species"	"Takada et al., 2013"	"LPSN"	"790987"	"517118"					1.5	""
 "B_STRPT_ORSR"	"Streptococcus orisratti"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"orisratti"	""	"species"	"Zhu et al., 2000"	"LPSN"	"781365"	"517118"					1.5	"438034004"
-"B_STRPT_sirS"	"Streptococcus orisuis"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"orisuis"	""	"species"	"Takada et al., 2007"	"LPSN"	"781314"	"517118"					1.5	"6441000146108"
+"B_STRPT_RSIS"	"Streptococcus orisuis"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"orisuis"	""	"species"	"Takada et al., 2007"	"LPSN"	"781314"	"517118"					1.5	"6441000146108"
 "B_STRPT_OVIS"	"Streptococcus ovis"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"ovis"	""	"species"	"Collins et al., 2001"	"LPSN"	"781366"	"517118"					1.5	"438035003"
 "B_STRPT_OVBR"	"Streptococcus ovuberis"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"ovuberis"	""	"species"	"Zamora et al., 2017"	"LPSN"	"796216"	"517118"					1.5	""
 "B_STRPT_PCFC"	"Streptococcus pacificus"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Lactobacillales"	"Streptococcaceae"	"Streptococcus"	"pacificus"	""	"species"	"Volokhov et al., 2021"	"LPSN"	"19573"	"517118"					1.5	""
@@ -51721,6 +51722,7 @@
 "A_WKNGR_YPNS"	"Wukongarchaeum yapensis"	"accepted"	"Archaea"	"Asgardarchaeota"	"Wukongarchaeia"	"Wukongarchaeales"	"Wukongarchaeaceae"	"Wukongarchaeum"	"yapensis"	""	"species"		"GBIF"				"11649514"	"11817462"		2	""
 "B_WKNGB"	"Wukongibacter"	"accepted"	"Bacteria"	"Bacillota"	"Clostridia"	"Eubacteriales"	"Peptostreptococcaceae"	"Wukongibacter"	""	""	"genus"	"Li et al., 2016"	"LPSN"	"519079"	"1053"		"9506110"	"7800"		2	""
 "B_WKNGB_BDNS"	"Wukongibacter baidiensis"	"accepted"	"Bacteria"	"Bacillota"	"Clostridia"	"Eubacteriales"	"Peptostreptococcaceae"	"Wukongibacter"	"baidiensis"	""	"species"	"Li et al., 2016"	"LPSN"	"794822"	"519079"		"9479445"	"9506110"		2	""
+"B_XYC"	"XYC"	"accepted"	"Bacteria"	"Nitrospirota"	"Thermodesulfovibrionia"	"Thermodesulfovibrionales"	"Magnetobacteriaceae"	"XYC"	""	""	"genus"		"GBIF"				"11695901"	"10718264"		2	""
 "P_XNTHS"	"Xanthiosphaera"	"accepted"	"Protozoa"	"Sarcomastigophora"	""	""	""	"Xanthiosphaera"	""	""	"genus"		"GBIF"				"9472186"			2	""
 "P_XNTHS_LPPC"	"Xanthiosphaera lappacea"	"accepted"	"Protozoa"	"Sarcomastigophora"	""	""	""	"Xanthiosphaera"	"lappacea"	""	"species"	"Haeckel"	"GBIF"				"6123506"	"9472186"		2	""
 "B_XNTHB"	"Xanthobacter"	"accepted"	"Bacteria"	"Pseudomonadota"	"Alphaproteobacteria"	"Hyphomicrobiales"	"Xanthobacteraceae"	"Xanthobacter"	""	""	"genus"	"Wiegel et al., 1978"	"LPSN"	"516929"	"1568"					2	"439120008"
@@ -51890,7 +51892,6 @@
 "B_[FAM]_XPHNMTBC"	"Xiphinematobacteraceae"	"accepted"	"Bacteria"	"Verrucomicrobiota"	"Verrucomicrobiae"	"Chthoniobacterales"	"Xiphinematobacteraceae"	""	""	""	"family"		"GBIF"				"10770063"	"10733345"		2	""
 "B_XUHSH"	"Xuhuaishuia"	"synonym"	"Bacteria"	"Pseudomonadota"	"Alphaproteobacteria"	"Rhodobacterales"	"Rhodobacteraceae"	"Xuhuaishuia"	""	""	"genus"	"Wang et al., 2016"	"LPSN"	"518921"	"1175"	"518801"				2	""
 "B_XUHSH_MNGN"	"Xuhuaishuia manganoxidans"	"synonym"	"Bacteria"	"Pseudomonadota"	"Alphaproteobacteria"	"Rhodobacterales"	"Rhodobacteraceae"	"Xuhuaishuia"	"manganoxidans"	""	"species"	"Wang et al., 2016"	"LPSN"	"793971"	"518921"	"793304"				2	""
-"B_XYC"	"XYC"	"accepted"	"Bacteria"	"Nitrospirota"	"Thermodesulfovibrionia"	"Thermodesulfovibrionales"	"Magnetobacteriaceae"	"XYC"	""	""	"genus"		"GBIF"				"11695901"	"10718264"		2	""
 "B_XYLNB"	"Xylanibacillus"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Caryophanales"	"Paenibacillaceae"	"Xylanibacillus"	""	""	"genus"	"Kukolya et al., 2018"	"LPSN"	"520351"	"1013"					2	""
 "B_XYLNB_CMPS"	"Xylanibacillus composti"	"accepted"	"Bacteria"	"Bacillota"	"Bacilli"	"Caryophanales"	"Paenibacillaceae"	"Xylanibacillus"	"composti"	""	"species"	"Kukolya et al., 2018"	"LPSN"	"797542"	"520351"					2	""
 "B_XBCTR"	"Xylanibacter"	"synonym"	"Bacteria"	"Bacteroidota"	"Bacteroidia"	"Bacteroidales"	"Prevotellaceae"	"Xylanibacter"	""	""	"genus"	"Hitch et al., 2022"	"LPSN"	"516940"	"1105"	"516385"				2	""
@@ -32,11 +32,11 @@
 # Source file: data-raw/reproduction_of_poorman.R
 # ------------------------------------------------

-# poorman: a package to replace all dplyr functions with base R so we can lose dependency on dplyr.
+# {poorman}: a package to replace all dplyr functions with base R so we can lose dependency on {dplyr}.
 # These functions were downloaded from https://github.com/nathaneastwood/poorman,
 # from this commit: https://github.com/nathaneastwood/poorman/tree/{commit}.
 #
-# All functions are prefixed with 'pm_' to make it obvious that they are dplyr substitutes.
+# All functions are prefixed with 'pm_' to make it obvious that they are {dplyr} substitutes.
 #
 # All code below was released under MIT license, that permits 'free of charge, to any person obtaining a
 # copy of the software and associated documentation files (the "Software"), to deal in the Software
@@ -66,33 +66,36 @@ read_EUCAST <- function(sheet, file, guideline_name) {

  # in the info header in the Excel file, EUCAST mentions which genera are targeted
  if (sheet %like% "anaerob.*Gram.*posi") {
-    sheet <- paste0(c(
-      "Actinomyces", "Bifidobacterium", "Clostridioides",
-      "Clostridium", "Cutibacterium", "Eggerthella",
-      "Eubacterium", "Lactobacillus", "Propionibacterium",
-      "Staphylococcus saccharolyticus"
-    ),
-    collapse = "_"
+    sheet <- paste0(
+      c(
+        "Actinomyces", "Bifidobacterium", "Clostridioides",
+        "Clostridium", "Cutibacterium", "Eggerthella",
+        "Eubacterium", "Lactobacillus", "Propionibacterium",
+        "Staphylococcus saccharolyticus"
+      ),
+      collapse = "_"
    )
  } else if (sheet %like% "anaerob.*Gram.*nega") {
-    sheet <- paste0(c(
-      "Bacteroides",
-      "Bilophila",
-      "Fusobacterium",
-      "Mobiluncus",
-      "Parabacteroides",
-      "Porphyromonas",
-      "Prevotella"
-    ),
-    collapse = "_"
+    sheet <- paste0(
+      c(
+        "Bacteroides",
+        "Bilophila",
+        "Fusobacterium",
+        "Mobiluncus",
+        "Parabacteroides",
+        "Porphyromonas",
+        "Prevotella"
+      ),
+      collapse = "_"
    )
  } else if (sheet == "Streptococcus A,B,C,G") {
-    sheet <- paste0(microorganisms %>%
-      filter(genus == "Streptococcus") %>%
-      mutate(lancefield = mo_name(mo, Lancefield = TRUE)) %>%
-      filter(lancefield %like% "^Streptococcus group") %>%
-      pull(fullname),
-    collapse = "_"
+    sheet <- paste0(
+      microorganisms %>%
+        filter(genus == "Streptococcus") %>%
+        mutate(lancefield = mo_name(mo, Lancefield = TRUE)) %>%
+        filter(lancefield %like% "^Streptococcus group") %>%
+        pull(fullname),
+      collapse = "_"
    )
  } else if (sheet %like% "PK.*PD") {
    sheet <- "UNKNOWN"
@@ -142,14 +142,15 @@ abx2 <- bind_rows(abx_atc1, abx_atc2)
 rm(abx_atc1)
 rm(abx_atc2)

-abx2$ab[is.na(abx2$ab)] <- toupper(abbreviate(gsub(
-  "[/0-9-]",
-  " ",
-  abx2$name[is.na(abx2$ab)]
-),
-minlength = 3,
-method = "left.kept",
-strict = TRUE
+abx2$ab[is.na(abx2$ab)] <- toupper(abbreviate(
+  gsub(
+    "[/0-9-]",
+    " ",
+    abx2$name[is.na(abx2$ab)]
+  ),
+  minlength = 3,
+  method = "left.kept",
+  strict = TRUE
 ))

 n_distinct(abx2$ab)
@@ -187,7 +188,7 @@ abx2 <- abx2 %>%

 abx2$abbr <- lapply(as.list(abx2$abbr), function(x) unlist(strsplit(x, "|", fixed = TRUE)))

-# Update Compound IDs and Trade Names ----
+# Update Compound IDs and Synonyms ----

 # vector with official names, returns vector with CIDs
 get_CID <- function(ab) {
@@ -197,24 +198,26 @@ get_CID <- function(ab) {
    p$tick()

    CID[i] <- tryCatch(
-      data.table::fread(paste0(
-        "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
-        URLencode(ab[i], reserved = TRUE),
-        "/cids/TXT?name_type=complete"
-      ),
-      showProgress = FALSE
+      data.table::fread(
+        paste0(
+          "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
+          URLencode(ab[i], reserved = TRUE),
+          "/cids/TXT?name_type=complete"
+        ),
+        showProgress = FALSE
      )[[1]][1],
      error = function(e) NA_integer_
    )
    if (is.na(CID[i])) {
      # try with removing the text in brackets
      CID[i] <- tryCatch(
-        data.table::fread(paste0(
-          "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
-          URLencode(trimws(gsub("[(].*[)]", "", ab[i])), reserved = TRUE),
-          "/cids/TXT?name_type=complete"
-        ),
-        showProgress = FALSE
+        data.table::fread(
+          paste0(
+            "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
+            URLencode(trimws(gsub("[(].*[)]", "", ab[i])), reserved = TRUE),
+            "/cids/TXT?name_type=complete"
+          ),
+          showProgress = FALSE
        )[[1]][1],
        error = function(e) NA_integer_
      )
@@ -223,12 +226,13 @@ get_CID <- function(ab) {
      # try match on word and take the lowest CID value (sorted)
      ab[i] <- gsub("[^a-z0-9]+", " ", ab[i], ignore.case = TRUE)
      CID[i] <- tryCatch(
-        data.table::fread(paste0(
-          "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
-          URLencode(ab[i], reserved = TRUE),
-          "/cids/TXT?name_type=word"
-        ),
-        showProgress = FALSE
+        data.table::fread(
+          paste0(
+            "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/",
+            URLencode(ab[i], reserved = TRUE),
+            "/cids/TXT?name_type=word"
+          ),
+          showProgress = FALSE
        )[[1]][1],
        error = function(e) NA_integer_
      )
@@ -260,13 +264,14 @@ get_synonyms <- function(CID, clean = TRUE) {
    }

    synonyms_txt <- tryCatch(
-      data.table::fread(paste0(
-        "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/fastidentity/cid/",
-        CID[i],
-        "/synonyms/TXT"
-      ),
-      sep = "\n",
-      showProgress = FALSE
+      data.table::fread(
+        paste0(
+          "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/fastidentity/cid/",
+          CID[i],
+          "/synonyms/TXT"
+        ),
+        sep = "\n",
+        showProgress = FALSE
      )[[1]],
      error = function(e) NA_character_
    )
@@ -302,6 +307,7 @@ get_synonyms <- function(CID, clean = TRUE) {
 # get brand names from PubChem (3-4 min)
 synonyms <- get_synonyms(CIDs)
 synonyms.bak <- synonyms
+
 # add existing ones (will be cleaned later)
 for (i in seq_len(length(synonyms))) {
  old <- antibiotics$synonyms[[i]]
@@ -313,6 +319,13 @@ for (i in seq_len(length(synonyms))) {

 antibiotics$synonyms <- synonyms

+stop("remember to remove co-trimoxazole as synonyms from SXT (Sulfamethoxazole), so it only exists in SXT!")
+sulfa <- antibiotics[which(antibiotics$ab == "SMX"), "synonyms", drop = TRUE][[1]]
+cotrim <- antibiotics[which(antibiotics$ab == "SXT"), "synonyms", drop = TRUE][[1]]
+sulfa <- sulfa[!sulfa %in% cotrim]
+antibiotics[which(antibiotics$ab == "SMX"), "synonyms"][[1]][[1]] <- sulfa
+
+
 # now go to end of this file


@@ -106,31 +106,32 @@ antivirals <- antivirals %>%
    oral_units,
    iv_ddd,
    iv_units
-  ) %>% 
+  ) %>%
  AMR:::dataset_UTF8_to_ASCII()

 av_codes <- tibble(name = antivirals$name %>%
-                     strsplit("(, | and )") %>%
-                     unlist() %>%
-                     unique() %>%
-                     sort()) %>% 
-  mutate(av_1st = toupper(abbreviate(name, minlength = 3, use.classes = FALSE))) %>% 
+  strsplit("(, | and )") %>%
+  unlist() %>%
+  unique() %>%
+  sort()) %>%
+  mutate(av_1st = toupper(abbreviate(name, minlength = 3, use.classes = FALSE))) %>%
  filter(!name %in% c("acid", "dipivoxil", "disoproxil", "marboxil", "alafenamide"))

 replace_with_av_code <- function(name) {
  unname(av_codes$av_1st[match(name, av_codes$name)])
 }

-names_codes <- antivirals %>% 
+names_codes <- antivirals %>%
  separate(name,
-           into = paste0("name", c(1:7)),
-           sep = "(, | and )",
-           remove = FALSE,
-           fill = "right") %>%
+    into = paste0("name", c(1:7)),
+    sep = "(, | and )",
+    remove = FALSE,
+    fill = "right"
+  ) %>%
  # remove empty columns
-  select(!where(function(x) all(is.na(x)))) %>% 
-  mutate_at(vars(matches("name[1-9]")), replace_with_av_code) %>% 
-  unite(av, matches("name[1-9]"), sep = "+", na.rm = TRUE) %>% 
+  select(!where(function(x) all(is.na(x)))) %>%
+  mutate_at(vars(matches("name[1-9]")), replace_with_av_code) %>%
+  unite(av, matches("name[1-9]"), sep = "+", na.rm = TRUE) %>%
  mutate(name = gsub("(, | and )", "/", name))
 substr(names_codes$name, 1, 1) <- toupper(substr(names_codes$name, 1, 1))

@@ -143,8 +144,9 @@ antivirals <- antivirals %>% AMR:::dataset_UTF8_to_ASCII()

 # add loinc, see 'data-raw/loinc.R'
 loinc_df <- read.csv("data-raw/Loinc.csv",
-                     row.names = NULL,
-                     stringsAsFactors = FALSE)
+  row.names = NULL,
+  stringsAsFactors = FALSE
+)

 loinc_df <- loinc_df %>% filter(CLASS == "DRUG/TOX")
 av_names <- antivirals %>%
@@ -95,8 +95,8 @@ new_mo_codes <- breakpoints %>%
 new_mo_codes %>%
  mutate(code = toupper(ORGANISM_CODE)) %>%
  rename(mo_new = mo) %>%
-  left_join(microorganisms.codes) %>%
-  filter(mo != mo_new)
+  left_join(microorganisms.codes %>% rename(mo_old = mo)) %>%
+  filter(mo_old != mo_new)

 microorganisms.codes <- microorganisms.codes %>%
  filter(!code %in% toupper(new_mo_codes$ORGANISM_CODE)) %>%
@@ -173,7 +173,7 @@ dosage_new <- bind_rows(
  as.data.frame(stringsAsFactors = FALSE)
 rownames(dosage_new) <- NULL

-dosage <- bind_rows(dosage_new, AMR::dosage) %>% 
+dosage <- bind_rows(dosage_new, AMR::dosage) %>%
  dataset_UTF8_to_ASCII()

 usethis::use_data(dosage, internal = FALSE, overwrite = TRUE, version = 2)
@@ -37,10 +37,10 @@
 #    CSV file (~12,5 MB) as "taxonomy.csv". Their API unfortunately does
 #    not include the full taxonomy and is currently (2022) pretty worthless.
 # 3. For data about human pathogens, we use Bartlett et al. (2022),
-#    https://doi.org/10.1099/mic.0.001269. Their latest supplementary material 
+#    https://doi.org/10.1099/mic.0.001269. Their latest supplementary material
 #    can be found here: https://github.com/padpadpadpad/bartlett_et_al_2022_human_pathogens.
-#.   Download their latest xlsx file in the `data` folder and save it to our
-#.   `data-raw` folder.
+# .   Download their latest xlsx file in the `data` folder and save it to our
+# .   `data-raw` folder.
 # 4. Set this folder_location to the path where these two files are:
 folder_location <- "~/Downloads/backbone/"
 file_gbif <- paste0(folder_location, "Taxon.tsv")
@@ -65,7 +65,7 @@ devtools::load_all(".") # load AMR package

 get_author_year <- function(ref) {
  # Only keep first author, e.g. transform 'Smith, Jones, 2011' to 'Smith et al., 2011'
-  
+
  authors2 <- iconv(ref, from = "UTF-8", to = "ASCII//TRANSLIT")
  authors2 <- gsub(" ?\\(Approved Lists [0-9]+\\) ?", " () ", authors2)
  authors2 <- gsub(" [)(]+ $", "", authors2)
@@ -73,21 +73,21 @@ get_author_year <- function(ref) {
  authors2 <- trimws(gsub("^[(](.*)[)]$", "\\1", authors2))
  # only take part after brackets if there's a name
  authors2 <- ifelse(grepl(".*[)] [a-zA-Z]+.*", authors2),
-                     gsub(".*[)] (.*)", "\\1", authors2),
-                     authors2
+    gsub(".*[)] (.*)", "\\1", authors2),
+    authors2
  )
  # replace parentheses with emend. to get the latest authors
  authors2 <- gsub("(", " emend. ", authors2, fixed = TRUE)
  authors2 <- gsub(")", "", authors2, fixed = TRUE)
  authors2 <- gsub(" +", " ", authors2)
  authors2 <- trimws(authors2)
-  
+
  # get year from last 4 digits
  lastyear <- as.integer(gsub(".*([0-9]{4})$", "\\1", authors2))
  # can never be later than now
  lastyear <- ifelse(lastyear > as.integer(format(Sys.Date(), "%Y")),
-                     NA,
-                     lastyear
+    NA,
+    lastyear
  )
  # get authors without last year
  authors <- gsub("(.*)[0-9]{4}$", "\\1", authors2)
@@ -119,8 +119,8 @@ get_author_year <- function(ref) {
  authors[nchar(authors) <= 3] <- ""
  # combine author and year if year is available
  ref <- ifelse(!is.na(lastyear),
-                paste0(authors, ", ", lastyear),
-                authors
+    paste0(authors, ", ", lastyear),
+    authors
  )
  # fix beginning and ending
  ref <- gsub(", $", "", ref)
@@ -128,7 +128,7 @@ get_author_year <- function(ref) {
  ref <- gsub("^(emend|et al.,?)", "", ref)
  ref <- trimws(ref)
  ref <- gsub("'", "", ref)
-  
+
  # a lot start with a lowercase character - fix that
  ref[!grepl("^d[A-Z]", ref)] <- gsub("^([a-z])", "\\U\\1", ref[!grepl("^d[A-Z]", ref)], perl = TRUE)
  # specific one for the French that are named dOrbigny
@@ -222,9 +222,9 @@ include_fungal_orders <- c(
 # get latest taxonomic names of these fungal orders
 include_fungal_orders_ids <- taxonomy_gbif.bak %>%
  filter(order %in% include_fungal_orders)
-include_fungal_orders <- taxonomy_gbif.bak %>% 
-  filter(taxonID %in% c(include_fungal_orders_ids$taxonID, include_fungal_orders_ids$acceptedNameUsageID)) %>% 
-  distinct(order) %>% 
+include_fungal_orders <- taxonomy_gbif.bak %>%
+  filter(taxonID %in% c(include_fungal_orders_ids$taxonID, include_fungal_orders_ids$acceptedNameUsageID)) %>%
+  distinct(order) %>%
  pull(order)

 # check some columns to validate below filters
@@ -361,7 +361,7 @@ for (page in LETTERS) {
    names <- names[ranks != "species"]
    ranks <- ranks[ranks != "species"]
    ranks[ranks == "domain"] <- "kingdom"
-    
+
    df <- names %>%
      tibble() %>%
      t() %>%
@@ -369,7 +369,7 @@ for (page in LETTERS) {
      setNames(ranks) %>%
      # no candidates please
      filter(genus %unlike% "^(Candidatus|\\[)")
-    
+
    taxonomy_lpsn_missing <- taxonomy_lpsn_missing %>%
      bind_rows(df)
  }
@@ -491,14 +491,14 @@ saveRDS(taxonomy_lpsn, "data-raw/taxonomy_lpsn.rds", version = 2)
 taxonomy_gbif <- taxonomy_gbif %>%
  # clean NAs and add fullname
  mutate(across(kingdom:subspecies, function(x) ifelse(is.na(x), "", x)),
-         fullname = trimws(case_when(
-           rank == "family" ~ family,
-           rank == "order" ~ order,
-           rank == "class" ~ class,
-           rank == "phylum" ~ phylum,
-           rank == "kingdom" ~ kingdom,
-           TRUE ~ paste(genus, species, subspecies)
-         )), .before = 1
+    fullname = trimws(case_when(
+      rank == "family" ~ family,
+      rank == "order" ~ order,
+      rank == "class" ~ class,
+      rank == "phylum" ~ phylum,
+      rank == "kingdom" ~ kingdom,
+      TRUE ~ paste(genus, species, subspecies)
+    )), .before = 1
  ) %>%
  # keep only one GBIF taxon ID per full name
  arrange(fullname, gbif) %>%
@@ -507,14 +507,14 @@ taxonomy_gbif <- taxonomy_gbif %>%
 taxonomy_lpsn <- taxonomy_lpsn %>%
  # clean NAs and add fullname
  mutate(across(kingdom:subspecies, function(x) ifelse(is.na(x), "", x)),
-         fullname = trimws(case_when(
-           rank == "family" ~ family,
-           rank == "order" ~ order,
-           rank == "class" ~ class,
-           rank == "phylum" ~ phylum,
-           rank == "kingdom" ~ kingdom,
-           TRUE ~ paste(genus, species, subspecies)
-         )), .before = 1
+    fullname = trimws(case_when(
+      rank == "family" ~ family,
+      rank == "order" ~ order,
+      rank == "class" ~ class,
+      rank == "phylum" ~ phylum,
+      rank == "kingdom" ~ kingdom,
+      TRUE ~ paste(genus, species, subspecies)
+    )), .before = 1
  ) %>%
  # keep only one LPSN record ID per full name
  arrange(fullname, lpsn) %>%
@@ -536,23 +536,25 @@ taxonomy_lpsn$lpsn_parent[taxonomy_lpsn$rank == "subspecies"] <- taxonomy_lpsn$l
 taxonomy <- taxonomy_lpsn %>%
  # join GBIF identifiers to them
  left_join(taxonomy_gbif %>% select(kingdom, fullname, starts_with("gbif")),
-            by = c("kingdom", "fullname")
+    by = c("kingdom", "fullname")
  )

 # for everything else, add the GBIF data
 taxonomy <- taxonomy %>%
  bind_rows(taxonomy_gbif %>%
-              filter(!paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname))) %>%
+    filter(!paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname))) %>%
  arrange(fullname) %>%
  filter(fullname != "")

 # get missing entries from existing microorganisms data set
 taxonomy <- taxonomy %>%
  bind_rows(AMR::microorganisms %>%
-              select(all_of(colnames(taxonomy))) %>% 
-              filter(!paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname),
-                     # these will be added later:
-                     source != "manually added")) %>%
+    select(all_of(colnames(taxonomy))) %>%
+    filter(
+      !paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname),
+      # these will be added later:
+      source != "manually added"
+    )) %>%
  arrange(fullname) %>%
  filter(fullname != "")

@@ -602,9 +604,10 @@ taxonomy <- taxonomy %>%
        source = "manually added"
      ) %>%
      filter(!paste(kingdom, rank) %in% paste(taxonomy$kingdom, taxonomy$rank)) %>%
-      left_join(current_gbif %>%
-                  select(kingdom, rank = taxonRank, ref = scientificNameAuthorship, gbif = taxonID, gbif_parent = parentNameUsageID),
-                by = c("kingdom", "rank")
+      left_join(
+        current_gbif %>%
+          select(kingdom, rank = taxonRank, ref = scientificNameAuthorship, gbif = taxonID, gbif_parent = parentNameUsageID),
+        by = c("kingdom", "rank")
      ) %>%
      mutate(source = ifelse(!is.na(gbif), "GBIF", source))
  )
@@ -625,17 +628,18 @@ for (i in 2:6) {
      source = "manually added"
    ) %>%
    filter(!paste(kingdom, .[[ncol(.) - 4]], rank) %in% paste(taxonomy$kingdom, taxonomy[[i + 1]], taxonomy$rank)) %>%
-  # get GBIF identifier where available
-  left_join(current_gbif %>%
-    select(kingdom, all_of(i_name), rank = taxonRank, ref = scientificNameAuthorship, gbif = taxonID, gbif_parent = parentNameUsageID),
-  by = c("kingdom", "rank", i_name)
-  ) %>%
-  mutate(source = ifelse(!is.na(gbif), "GBIF", source))
+    # get GBIF identifier where available
+    left_join(
+      current_gbif %>%
+        select(kingdom, all_of(i_name), rank = taxonRank, ref = scientificNameAuthorship, gbif = taxonID, gbif_parent = parentNameUsageID),
+      by = c("kingdom", "rank", i_name)
+    ) %>%
+    mutate(source = ifelse(!is.na(gbif), "GBIF", source))
  message("n = ", nrow(to_add))
  if (is.null(taxonomy_all_missing)) {
    taxonomy_all_missing <- to_add
  } else {
-    taxonomy_all_missing <- taxonomy_all_missing %>% 
+    taxonomy_all_missing <- taxonomy_all_missing %>%
      bind_rows(to_add)
  }
 }
@@ -645,20 +649,24 @@ taxonomy <- taxonomy %>%
  bind_rows(taxonomy_all_missing)

 # fix for duplicate fullnames within a kingdom (such as Nitrospira which is the name of the genus AND its class)
-taxonomy <- taxonomy %>% 
-  mutate(rank_index = case_when(rank == "subspecies" ~ 1,
-                                rank == "species" ~ 2,
-                                rank == "genus" ~ 3,
-                                rank == "family" ~ 4,
-                                rank == "order" ~ 5,
-                                rank == "class" ~ 6,
-                                TRUE ~ 7),
-         fullname_rank = paste0(fullname, " {", rank, "}")) %>% 
-  arrange(kingdom, fullname, rank_index) %>% 
-  group_by(kingdom, fullname) %>% 
-  mutate(fullname = if_else(row_number() > 1, fullname_rank, fullname)) %>% 
-  ungroup() %>% 
-  select(-fullname_rank, -rank_index) %>% 
+taxonomy <- taxonomy %>%
+  mutate(
+    rank_index = case_when(
+      rank == "subspecies" ~ 1,
+      rank == "species" ~ 2,
+      rank == "genus" ~ 3,
+      rank == "family" ~ 4,
+      rank == "order" ~ 5,
+      rank == "class" ~ 6,
+      TRUE ~ 7
+    ),
+    fullname_rank = paste0(fullname, " {", rank, "}")
+  ) %>%
+  arrange(kingdom, fullname, rank_index) %>%
+  group_by(kingdom, fullname) %>%
+  mutate(fullname = if_else(row_number() > 1, fullname_rank, fullname)) %>%
+  ungroup() %>%
+  select(-fullname_rank, -rank_index) %>%
  arrange(fullname)

 # now also add missing species (requires combination with genus)
@@ -676,12 +684,13 @@ taxonomy <- taxonomy %>%
      ) %>%
      filter(!paste(kingdom, genus, species, rank) %in% paste(taxonomy$kingdom, taxonomy$genus, taxonomy$species, taxonomy$rank)) %>%
      # get GBIF identifier where available
-      left_join(current_gbif %>%
-                  select(kingdom, genus, species = specificEpithet, rank = taxonRank, ref = scientificNameAuthorship, gbif = taxonID, gbif_parent = parentNameUsageID),
-                by = c("kingdom", "rank", "genus", "species")
+      left_join(
+        current_gbif %>%
+          select(kingdom, genus, species = specificEpithet, rank = taxonRank, ref = scientificNameAuthorship, gbif = taxonID, gbif_parent = parentNameUsageID),
+        by = c("kingdom", "rank", "genus", "species")
      ) %>%
      mutate(source = ifelse(!is.na(gbif), "GBIF", source))
-    )
+  )


 # remove NAs from taxonomy again, and keep unique full names
@@ -702,7 +711,7 @@ manually_added <- AMR::microorganisms %>%
  filter(source == "manually added", !paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname)) %>%
  select(fullname:subspecies, ref, source, rank)

-manually_added <- manually_added %>% 
+manually_added <- manually_added %>%
  bind_rows(salmonellae)

 # get latest taxonomy for those entries
@@ -805,76 +814,83 @@ taxonomy <- taxonomy %>%
 pathogens <- read_excel(file_bartlett, sheet = "Tab 6 Full List")

 # get all established, both old and current taxonomic names
-established <- pathogens %>% 
-  filter(status == "established") %>% 
+established <- pathogens %>%
+  filter(status == "established") %>%
  mutate(fullname = paste(genus, species)) %>%
-  pull(fullname) %>% 
-  c(unlist(mo_current(.)),
-    unlist(mo_synonyms(., keep_synonyms = FALSE))) %>% 
-  strsplit(" ", fixed = TRUE) %>% 
-  sapply(function(x) ifelse(length(x) == 1, x, paste(x[1], x[2]))) %>% 
-  sort() %>% 
+  pull(fullname) %>%
+  c(
+    unlist(mo_current(.)),
+    unlist(mo_synonyms(., keep_synonyms = FALSE))
+  ) %>%
+  strsplit(" ", fixed = TRUE) %>%
+  sapply(function(x) ifelse(length(x) == 1, x, paste(x[1], x[2]))) %>%
+  sort() %>%
  unique()

 # get all putative, both old and current taxonomic names
-putative <- pathogens %>% 
-  filter(status == "putative") %>% 
+putative <- pathogens %>%
+  filter(status == "putative") %>%
  mutate(fullname = paste(genus, species)) %>%
-  pull(fullname) %>% 
-  c(unlist(mo_current(.)),
-    unlist(mo_synonyms(., keep_synonyms = FALSE))) %>% 
-  strsplit(" ", fixed = TRUE) %>% 
-  sapply(function(x) ifelse(length(x) == 1, x, paste(x[1], x[2]))) %>% 
-  sort() %>% 
+  pull(fullname) %>%
+  c(
+    unlist(mo_current(.)),
+    unlist(mo_synonyms(., keep_synonyms = FALSE))
+  ) %>%
+  strsplit(" ", fixed = TRUE) %>%
+  sapply(function(x) ifelse(length(x) == 1, x, paste(x[1], x[2]))) %>%
+  sort() %>%
  unique()

 established <- established[established %unlike% "unknown"]
 putative <- putative[putative %unlike% "unknown"]

-established_genera <- established %>% 
-  strsplit(" ", fixed = TRUE) %>% 
-  sapply(function(x) x[1]) %>% 
-  sort() %>% 
+established_genera <- established %>%
+  strsplit(" ", fixed = TRUE) %>%
+  sapply(function(x) x[1]) %>%
+  sort() %>%
  unique()

-putative_genera <- putative %>% 
-  strsplit(" ", fixed = TRUE) %>% 
-  sapply(function(x) x[1]) %>% 
-  sort() %>% 
+putative_genera <- putative %>%
+  strsplit(" ", fixed = TRUE) %>%
+  sapply(function(x) x[1]) %>%
+  sort() %>%
  unique()

-nonbacterial_genera <- AMR:::MO_PREVALENT_GENERA %>% 
-  c(unlist(mo_current(.)),
-    unlist(mo_synonyms(., keep_synonyms = FALSE))) %>% 
-  strsplit(" ", fixed = TRUE) %>% 
-  sapply(function(x) x[1]) %>% 
-  sort() %>% 
+nonbacterial_genera <- AMR:::MO_PREVALENT_GENERA %>%
+  c(
+    unlist(mo_current(.)),
+    unlist(mo_synonyms(., keep_synonyms = FALSE))
+  ) %>%
+  strsplit(" ", fixed = TRUE) %>%
+  sapply(function(x) x[1]) %>%
+  sort() %>%
  unique()
 nonbacterial_genera <- nonbacterial_genera[nonbacterial_genera %unlike% "unknown"]

 # update prevalence based on taxonomy (following the recent and thorough work of Bartlett et al., 2022)
 # see https://doi.org/10.1099/mic.0.001269
-taxonomy <- taxonomy %>% 
+taxonomy <- taxonomy %>%
  mutate(prevalence = case_when(
    # 'established' means 'have infected at least three persons in three or more references'
    paste(genus, species) %in% established & rank %in% c("species", "subspecies") ~ 1.0,
    # other genera in the 'established' group
    genus %in% established_genera & rank == "genus" ~ 1.0,
-    
+
    # 'putative' means 'fewer than three known cases'
    paste(genus, species) %in% putative & rank %in% c("species", "subspecies") ~ 1.25,
    # other genera in the 'putative' group
    genus %in% putative_genera & rank == "genus" ~ 1.25,
-    
+
    # species and subspecies in 'established' and 'putative' groups
    genus %in% c(established_genera, putative_genera) & rank %in% c("species", "subspecies") ~ 1.5,
    # other species from a genus in either group
    genus %in% nonbacterial_genera & rank %in% c("genus", "species", "subspecies") ~ 1.5,
    # we keep track of prevalent genera too of non-bacterial species
    genus %in% AMR:::MO_PREVALENT_GENERA & kingdom != "Bacteria" & rank %in% c("genus", "species", "subspecies") ~ 1.5,
-    
+
    # all others
-    TRUE ~ 2.0))
+    TRUE ~ 2.0
+  ))

 table(taxonomy$prevalence, useNA = "always")
 # (a lot will be removed further below)
@@ -909,13 +925,14 @@ mo_kingdom <- taxonomy %>%
 mo_phylum <- taxonomy %>%
  filter(rank == "phylum") %>%
  distinct(kingdom, phylum) %>%
-  left_join(AMR::microorganisms %>%
-              filter(rank == "phylum") %>%
-              transmute(kingdom,
-                        phylum = fullname,
-                        mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo))
-              ),
-            by = c("kingdom", "phylum")
+  left_join(
+    AMR::microorganisms %>%
+      filter(rank == "phylum") %>%
+      transmute(kingdom,
+        phylum = fullname,
+        mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo))
+      ),
+    by = c("kingdom", "phylum")
  ) %>%
  group_by(kingdom) %>%
  mutate(
@@ -935,13 +952,14 @@ mo_phylum <- mo_phylum %>%
 mo_class <- taxonomy %>%
  filter(rank == "class") %>%
  distinct(kingdom, class) %>%
-  left_join(AMR::microorganisms %>%
-              filter(rank == "class") %>%
-              transmute(kingdom,
-                        class = fullname,
-                        mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo))
-              ),
-            by = c("kingdom", "class")
+  left_join(
+    AMR::microorganisms %>%
+      filter(rank == "class") %>%
+      transmute(kingdom,
+        class = fullname,
+        mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo))
+      ),
+    by = c("kingdom", "class")
  ) %>%
  group_by(kingdom) %>%
  mutate(
@@ -961,13 +979,14 @@ mo_class <- mo_class %>%
 mo_order <- taxonomy %>%
  filter(rank == "order") %>%
  distinct(kingdom, order) %>%
-  left_join(AMR::microorganisms %>%
-              filter(rank == "order") %>%
-              transmute(kingdom,
-                        order = fullname,
-                        mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo))
-              ),
-            by = c("kingdom", "order")
+  left_join(
+    AMR::microorganisms %>%
+      filter(rank == "order") %>%
+      transmute(kingdom,
+        order = fullname,
+        mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo))
+      ),
+    by = c("kingdom", "order")
  ) %>%
  group_by(kingdom) %>%
  mutate(
@@ -987,13 +1006,14 @@ mo_order <- mo_order %>%
 mo_family <- taxonomy %>%
  filter(rank == "family") %>%
  distinct(kingdom, family) %>%
-  left_join(AMR::microorganisms %>%
-              filter(rank == "family") %>%
-              transmute(kingdom,
-                        family = fullname,
-                        mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo))
-              ),
-            by = c("kingdom", "family")
+  left_join(
+    AMR::microorganisms %>%
+      filter(rank == "family") %>%
+      transmute(kingdom,
+        family = fullname,
+        mo_old = gsub("[A-Z]{1,2}_", "", as.character(mo))
+      ),
+    by = c("kingdom", "family")
  ) %>%
  group_by(kingdom) %>%
  mutate(
@@ -1014,11 +1034,12 @@ mo_genus <- taxonomy %>%
  filter(rank == "genus") %>%
  distinct(kingdom, genus) %>%
  # get available old MO codes
-  left_join(AMR::microorganisms %>%
-              filter(rank == "genus") %>%
-              transmute(mo_genus_old = gsub("^[A-Z]+_", "", as.character(mo)), kingdom, genus) %>%
-              distinct(kingdom, genus, .keep_all = TRUE),
-            by = c("kingdom", "genus")
+  left_join(
+    AMR::microorganisms %>%
+      filter(rank == "genus") %>%
+      transmute(mo_genus_old = gsub("^[A-Z]+_", "", as.character(mo)), kingdom, genus) %>%
+      distinct(kingdom, genus, .keep_all = TRUE),
+    by = c("kingdom", "genus")
  ) %>%
  distinct(kingdom, genus, .keep_all = TRUE) %>%
  # since kingdom is part of the code, genus abbreviations may be duplicated between kingdoms
@@ -1060,12 +1081,13 @@ mo_genus <- mo_genus %>%
 mo_species <- taxonomy %>%
  filter(rank == "species") %>%
  distinct(kingdom, genus, species) %>%
-  left_join(AMR::microorganisms %>%
-              filter(rank == "species") %>%
-              transmute(mo_species_old = gsub("^[A-Z]+_[A-Z]+_", "", as.character(mo)), kingdom, genus, species) %>%
-              filter(mo_species_old %unlike% "-") %>%
-              distinct(kingdom, genus, species, .keep_all = TRUE),
-            by = c("kingdom", "genus", "species")
+  left_join(
+    AMR::microorganisms %>%
+      filter(rank == "species") %>%
+      transmute(mo_species_old = gsub("^[A-Z]+_[A-Z]+_", "", as.character(mo)), kingdom, genus, species) %>%
+      filter(mo_species_old %unlike% "-") %>%
+      distinct(kingdom, genus, species, .keep_all = TRUE),
+    by = c("kingdom", "genus", "species")
  ) %>%
  distinct(kingdom, genus, species, .keep_all = TRUE) %>%
  group_by(kingdom, genus) %>%
@@ -1108,12 +1130,13 @@ mo_species <- mo_species %>%
 mo_subspecies <- taxonomy %>%
  filter(rank == "subspecies") %>%
  distinct(kingdom, genus, species, subspecies) %>%
-  left_join(AMR::microorganisms %>%
-              filter(rank %in% c("subspecies", "subsp.", "infraspecies")) %>%
-              transmute(mo_subspecies_old = gsub("^[A-Z]+_[A-Z]+_[A-Z]+_", "", as.character(mo)), kingdom, genus, species, subspecies) %>%
-              filter(mo_subspecies_old %unlike% "-") %>%
-              distinct(kingdom, genus, species, subspecies, .keep_all = TRUE),
-            by = c("kingdom", "genus", "species", "subspecies")
+  left_join(
+    AMR::microorganisms %>%
+      filter(rank %in% c("subspecies", "subsp.", "infraspecies")) %>%
+      transmute(mo_subspecies_old = gsub("^[A-Z]+_[A-Z]+_[A-Z]+_", "", as.character(mo)), kingdom, genus, species, subspecies) %>%
+      filter(mo_subspecies_old %unlike% "-") %>%
+      distinct(kingdom, genus, species, subspecies, .keep_all = TRUE),
+    by = c("kingdom", "genus", "species", "subspecies")
  ) %>%
  distinct(kingdom, genus, species, subspecies, .keep_all = TRUE) %>%
  group_by(kingdom, genus, species) %>%
@@ -1187,20 +1210,26 @@ taxonomy <- taxonomy %>%
  arrange(fullname)

 # now check these - e.g. Nitrospira is the name of a genus AND its class
-taxonomy %>% filter(fullname %in% .[duplicated(fullname), "fullname", drop = TRUE]) %>% View()
+taxonomy %>%
+  filter(fullname %in% .[duplicated(fullname), "fullname", drop = TRUE]) %>%
+  View()
 taxonomy <- taxonomy %>%
-  mutate(rank_index = case_when(kingdom == "Bacteria" ~ 1,
-                                kingdom == "Fungi" ~ 2,
-                                kingdom == "Protozoa" ~ 3,
-                                kingdom == "Archaea" ~ 4,
-                                TRUE ~ 5)) %>% 
-  arrange(fullname, rank_index) %>% 
-  distinct(fullname, .keep_all = TRUE) %>% 
-  select(-rank_index) %>% 
+  mutate(rank_index = case_when(
+    kingdom == "Bacteria" ~ 1,
+    kingdom == "Fungi" ~ 2,
+    kingdom == "Protozoa" ~ 3,
+    kingdom == "Archaea" ~ 4,
+    TRUE ~ 5
+  )) %>%
+  arrange(fullname, rank_index) %>%
+  distinct(fullname, .keep_all = TRUE) %>%
+  select(-rank_index) %>%
  filter(mo != "")

 # this must not exist:
-taxonomy %>% filter(mo %like% "__") %>% View()
+taxonomy %>%
+  filter(mo %like% "__") %>%
+  View()
 taxonomy <- taxonomy %>% filter(mo %unlike% "__")


@@ -1214,14 +1243,20 @@ taxonomy <- taxonomy %>% distinct(mo, .keep_all = TRUE)
 taxonomy %>% filter(fullname %in% .[duplicated(fullname), "fullname", drop = TRUE])

 # are all GBIFs available?
-taxonomy %>% filter(!gbif_parent %in% gbif) %>% count(rank)
+taxonomy %>%
+  filter(!gbif_parent %in% gbif) %>%
+  count(rank)
 # try to find the right gbif IDs
 taxonomy$gbif_parent[which(!taxonomy$gbif_parent %in% taxonomy$gbif & taxonomy$rank == "species")] <- taxonomy$gbif[match(taxonomy$genus[which(!taxonomy$gbif_parent %in% taxonomy$gbif & taxonomy$rank == "species")], taxonomy$genus)]
 taxonomy$gbif_parent[which(!taxonomy$gbif_parent %in% taxonomy$gbif & taxonomy$rank == "class")] <- taxonomy$gbif[match(taxonomy$phylum[which(!taxonomy$gbif_parent %in% taxonomy$gbif & taxonomy$rank == "class")], taxonomy$phylum)]
-taxonomy %>% filter(!gbif_parent %in% gbif) %>% count(rank)
+taxonomy %>%
+  filter(!gbif_parent %in% gbif) %>%
+  count(rank)

 # are all LPSNs available?
-taxonomy %>% filter(!lpsn_parent %in% lpsn) %>% count(rank)
+taxonomy %>%
+  filter(!lpsn_parent %in% lpsn) %>%
+  count(rank)
 # make GBIF refer to newest renaming according to LPSN
 taxonomy$gbif_renamed_to[which(!is.na(taxonomy$gbif_renamed_to) & !is.na(taxonomy$lpsn_renamed_to))] <- taxonomy$gbif[match(taxonomy$lpsn_renamed_to[which(!is.na(taxonomy$gbif_renamed_to) & !is.na(taxonomy$lpsn_renamed_to))], taxonomy$lpsn)]

@@ -1251,21 +1286,33 @@ taxonomy <- taxonomy %>%

 # no ghost families, orders classes, phyla
 taxonomy <- taxonomy %>%
-  group_by(kingdom, family) %>% filter(n() > 1 |  fullname %like% "unknown" | rank == "kingdom") %>%
-  group_by(kingdom, order) %>% filter(n() > 1 |  fullname %like% "unknown" | rank == "kingdom") %>%
-  group_by(kingdom, class) %>% filter(n() > 1 |  fullname %like% "unknown" | rank == "kingdom") %>%
-  group_by(kingdom, phylum) %>% filter(n() > 1 |  fullname %like% "unknown" | rank == "kingdom") %>% 
+  group_by(kingdom, family) %>%
+  filter(n() > 1 | fullname %like% "unknown" | rank == "kingdom") %>%
+  group_by(kingdom, order) %>%
+  filter(n() > 1 | fullname %like% "unknown" | rank == "kingdom") %>%
+  group_by(kingdom, class) %>%
+  filter(n() > 1 | fullname %like% "unknown" | rank == "kingdom") %>%
+  group_by(kingdom, phylum) %>%
+  filter(n() > 1 | fullname %like% "unknown" | rank == "kingdom") %>%
  ungroup()


-message("\nCongratulations! The new taxonomic table will contain ", format(nrow(taxonomy), big.mark = ","), " rows.\n",
-        "This was ", format(nrow(AMR::microorganisms), big.mark = ","), " rows.\n")
+message(
+  "\nCongratulations! The new taxonomic table will contain ", format(nrow(taxonomy), big.mark = " "), " rows.\n",
+  "This was ", format(nrow(AMR::microorganisms), big.mark = " "), " rows.\n"
+)

 # these are the new ones:
-taxonomy %>% filter(!paste(kingdom, fullname) %in% paste(AMR::microorganisms$kingdom, AMR::microorganisms$fullname)) %>% View()
+taxonomy %>%
+  filter(!paste(kingdom, fullname) %in% paste(AMR::microorganisms$kingdom, AMR::microorganisms$fullname)) %>%
+  View()
 # these were removed:
-AMR::microorganisms %>% filter(!paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname)) %>% View()
-AMR::microorganisms %>% filter(!fullname %in% taxonomy$fullname) %>% View()
+AMR::microorganisms %>%
+  filter(!paste(kingdom, fullname) %in% paste(taxonomy$kingdom, taxonomy$fullname)) %>%
+  View()
+AMR::microorganisms %>%
+  filter(!fullname %in% taxonomy$fullname) %>%
+  View()


 # Add SNOMED CT -----------------------------------------------------------
@@ -1310,19 +1357,29 @@ taxonomy <- taxonomy %>%

 # set class <mo>
 class(taxonomy$mo) <- c("mo", "character")
+microorganisms <- taxonomy

-### this was previously needed?? Since 2022 M. catarrhalis seems to be "accepted" again
-# # Moraxella catarrhalis was named Branhamella catarrhalis (Catlin, 1970), but this is unaccepted in clinical microbiology
-# # we keep them both
-# taxonomy$status[which(taxonomy$fullname == "Moraxella catarrhalis")]
-# taxonomy$lpsn_renamed_to[which(taxonomy$fullname == "Moraxella catarrhalis")]
-# taxonomy$status[which(taxonomy$fullname == "Moraxella catarrhalis")] <- "accepted"
-# taxonomy$lpsn_renamed_to[which(taxonomy$fullname == "Moraxella catarrhalis")] <- NA_character_
+
+# Restore 'synonym' microorganisms to 'accepted' --------------------------
+
+# according to LPSN: Stenotrophomonas maltophilia is the correct name if this species is regarded as a separate species (i.e., if its nomenclatural type is not assigned to another species whose name is validly published, legitimate and not rejected and has priority) within a separate genus Stenotrophomonas.
+# https://lpsn.dsmz.de/species/stenotrophomonas-maltophilia
+
+# all MO's to keep as 'accepted', not as 'synonym':
+to_restore <- c(
+  "Stenotrophomonas maltophilia",
+  "Moraxella catarrhalis"
+)
+all(to_restore %in% microorganisms$fullname)
+for (nm in to_restore) {
+  microorganisms$lpsn_renamed_to[which(microorganisms$fullname == nm)] <- NA
+  microorganisms$gbif_renamed_to[which(microorganisms$fullname == nm)] <- NA
+  microorganisms$status[which(microorganisms$fullname == nm)] <- "accepted"
+}


 # Save to package ---------------------------------------------------------

-microorganisms <- taxonomy
 usethis::use_data(microorganisms, overwrite = TRUE, version = 2, compress = "xz")
 rm(microorganisms)

@@ -1,22 +1,31 @@
 # get complete filenames of all R files in the GitHub repository of nathaneastwood/poorman

-commit <- "52eb6947e0b4430cd588976ed8820013eddf955f"
+library(magrittr)
+`%like%` <- function(x, y) grepl(y, x, ignore.case = TRUE, perl = TRUE)
+`%unlike%` <- function(x, y) !grepl(y, x, ignore.case = TRUE, perl = TRUE)
+
+commit <- "3cc0a9920b1eb559dd166f548561244189586b3a"

 files <- xml2::read_html(paste0("https://github.com/nathaneastwood/poorman/tree/", commit, "/R")) %>%
  rvest::html_nodes("a") %>%
  rvest::html_attr("href")
+files <- files[files %like% "/blob/.*R$"]

 # get full URLs of all raw R files
 files <- sort(paste0("https://raw.githubusercontent.com", gsub("blob/", "", files[files %like% "/R/.*.R$"])))
 # remove files with only pkg specific code
 files <- files[files %unlike% "(zzz|init)[.]R$"]
 # also, there's a lot of functions we don't use
-files <- files[files %unlike% "(slice|glimpse|recode|replace_na|coalesce)[.]R$"]
+files <- files[files %unlike% "/(between|coalesce|cumulative|fill|glimpse|group_cols|na_if|near|nest_by|check_filter|poorman-package|print|recode|reconstruct|replace_na|replace_with|rownames|slice|union_all|unite|window_rank|with_groups)[.]R$"]

 # add our prepend file, containing info about the source of the data
-intro <- readLines("data-raw/poorman_prepend.R")
+intro <- readLines("data-raw/poorman_prepend.R") %>%
+  # add commit to intro part
+  gsub("{commit}", commit, ., fixed = TRUE) %>%
+  # add date to intro part
+  gsub("{date}", trimws(format(Sys.Date(), "%e %B %Y")), ., fixed = TRUE)
 # copyright info:
-copyright <- paste0("# ", readLines("https://raw.githubusercontent.com/nathaneastwood/poorman/master/LICENSE"))
+copyright <- paste0("# ", readLines(paste0("https://raw.githubusercontent.com/nathaneastwood/poorman/", commit, "/LICENSE")))

 # read all contents to a character vector
 contents <- character(0)
@@ -25,31 +34,35 @@ sapply(files, function(file) {
  contents <<- c(contents, readLines(file))
  invisible()
 })
-contents <- c(
-  intro,
-  copyright,
-  "",
-  contents
-)

 # remove lines starting with "#'" and NULL and write to file
 contents <- contents[!grepl("^(#'|NULL|\"_PACKAGE)", contents)]
+contents.bak <- contents

+# grouped attributes same as dplyr
+contents <- gsub("grouped_data", "grouped_df", contents, fixed = TRUE)
 # now make it independent on UseMethod, since we will not export these functions
-contents <- gsub('UseMethod[(]"(.*?)"[)]',
-  'if ("grouped_data" %in% class(.data)) {|||    \\1.grouped_data(.data, ...)|||  } else {|||    \\1.default(.data, ...)|||  }',
-  paste(contents, collapse = "|||"),
-  perl = TRUE
-) %>%
-  # add commit to intro part
-  gsub("{commit}", commit, ., fixed = TRUE) %>%
-  # add date to intro part
-  gsub("{date}", format(Sys.Date(), "%e %B %Y"), ., fixed = TRUE) %>%
-  strsplit(split = "|||", fixed = TRUE) %>%
-  unlist() %>%
-  # add "pm_" as prefix to all functions
-  gsub("^([a-z_.]+) <- function", "pm_\\1 <- function", .)
-
+has_usemethods <- gsub("^([a-z_]+).*", "\\1", contents[which(contents %like% "usemethod") - 1])
+for (use in has_usemethods) {
+  relevant_row <- which(contents %like% paste0("^", use, " <- function")) + 1
+  function_call <- trimws(gsub(".*function(.*)\\{.*", "\\1", contents[relevant_row - 1]))
+  function_call1 <- trimws(gsub("[()]", "", strsplit(function_call, ",")[[1]][1]))
+  if (any(contents %like% paste0(use, ".grouped_df"))) {
+    # this function will have methods for data.frame and grouped_df
+    contents[relevant_row] <- paste0("  if (\"grouped_df\" %in% class(", function_call1, ")) ", use, ".grouped_df", function_call, " else ", use, ".data.frame", function_call)
+  } else {
+    # this function will only have data.frame as method
+    contents[relevant_row] <- paste0("  ", use, ".data.frame", function_call)
+  }
+  # add pm_ prefix
+  contents[relevant_row - 1] <- paste0("pm_", contents[relevant_row - 1])
+}
+# correct for NextMethod
+contents <- gsub("NextMethod\\(\"(.*)\"\\)", "\\1.data.frame(...)", contents)
+# correct for 'default' method
+contents <- gsub(".default <-", ".data.frame <-", contents, fixed = TRUE)
+contents <- gsub("pm_group_by_drop.data.frame", "pm_group_by_drop", contents, fixed = TRUE)
+contents <- gsub("(stats::)?setNames", "stats::setNames", contents)
 # now get all those pm_* functions to replace all untransformed function name calls as well
 new_pm_names <- sort(gsub("pm_(.*?) <-.*", "\\1", contents[grepl("^pm_", contents)]))
 for (i in seq_len(length(new_pm_names))) {
@@ -57,29 +70,41 @@ for (i in seq_len(length(new_pm_names))) {
  # starting with a space or a straight bracket or an opening parenthesis, ending with nothing or a non-character or a closing parenthesis
  contents <- gsub(paste0("( |\\[|\\()", new_pm_names[i], "($|[^a-z]|\\))"), paste0("\\1pm_", new_pm_names[i], "\\2"), contents)
 }
-
 # replace %>% with %pm>%
+contents[which(contents %like% "^\\|\\|") - 1] <- paste0(contents[which(contents %like% "^\\|\\|") - 1], " ||")
+contents[which(contents %like% "^\\|\\|")] <- gsub("^\\|\\|", "", contents[which(contents %like% "^\\|\\|")])
 contents <- gsub("%>%", "%pm>%", contents, fixed = TRUE)
 # fix for new lines, since n() also existed
 contents <- gsub("\\pm_n", "\\n", contents, fixed = TRUE)
 # prefix other functions also with "pm_"
 contents <- gsub("^([a-z_]+)(\\$|)", "pm_\\1\\2", contents)
-# prefix environments
-contents <- gsub("eval_env", "pm_eval_env", contents, fixed = TRUE)
-contents <- gsub("select_env", "pm_select_env", contents, fixed = TRUE)
-contents <- gsub("context", "pm_context", contents, fixed = TRUE)
-# now some items are overprefixed
+# prefix environmental objects and functions
+contents <- gsub("(add_group_columns|add_tally|apply_grouped_function|as_function|as_symbols|build_data_frame|calculate_groups|check_filter|check_if_types|check_name|check_context|collapse_to_sentence|context|deparse_|dotdotdot|drop_dup_list|eval_call|eval_env|eval_expr|eval_select_pos|find_used|flatten|get_group_details|gluestick|group_|groups|groups_set|has_groups|have_name|insert_dot|is.grouped_df|is_df_or_vector|is_empty_list|is_formula|is_named|is_negated_colon|is_nested|is_string|is_wholenumber|join_message|join_worker|names_are_invalid|nth|peek_vars|reconstruct_attrs|replace_na|replace_with|select_|select_context|select_env|select_positions|setup_|split_into_groups|squash|tally|tally_n|validate_case_when_length)", "pm_\\1", contents)
+# now a lot of items are overprefixed
 contents <- gsub("(pm_)+", "pm_", contents)
-# special case for pm_distinct(), we need '.keep_all' to work
-contents <- gsub("pm_distinct <- function(.data, ..., .keep_all = FALSE)", "pm_distinct <- function(.data, ...)", contents, fixed = TRUE)
-# pm_pull does not correct for tibbles, misses the drop argument
-contents[contents == ".data[, var]"] <- ".data[, var, drop = TRUE]"
+contents <- gsub("_pm_", "_", contents)
+contents <- gsub("pm_if (\"grouped_df", "if (\"grouped_df", contents, fixed = TRUE)
+# remove comments and empty lines
+contents <- gsub("#.*", "", contents)
+contents <- contents[trimws(contents) != ""]
+# fix for their relocate()
+contents <- gsub("if (!missing(.before))", "if (!missing(.before) && !is.null(.before))", contents, fixed = TRUE)
+contents <- gsub("if (!missing(.after))", "if (!missing(.after) && !is.null(.after))", contents, fixed = TRUE)
+contents[which(contents %like% "reshape\\($") + 1] <- gsub("data", "as.data.frame(data, stringsAsFactors = FALSE)", contents[which(contents %like% "reshape\\($") + 1])
+contents <- gsub("pm_relocate(.data = long, values_to, .after = -1)", 'pm_relocate(.data = long, "value", .after = -1)', contents, fixed = TRUE)

 # who needs US spelling?
-contents <- contents[!grepl("summarize", contents)]
+contents <- contents[contents %unlike% "summarize"]
+
+# add intro
+contents <- c(
+  intro,
+  copyright,
+  "",
+  contents
+)

 writeLines(contents, "R/aa_helper_pm_functions.R")

-# after this, comment out:
-# pm_left_join() since we use a faster version
-# pm_group_split() since we don't use it and it relies on R 3.5.0 for the use of ...length(), which is hard to support without C++ code
+# note: pm_left_join() will be overwritten by aaa_helper_functions.R, which contains a faster implementation
+# replace `res <- as.data.frame(res)` with  `res <- as.data.frame(res, stringsAsFactors = FALSE)`
@@ -0,0 +1,33 @@
+snomed2 <- microorganisms %>%
+  filter(mo %in% c("B_SLMNL_TYPH", "B_SLMNL_HMRM", "B_SLMNL_PRTY")) %>%
+  pull(snomed)
+
+new_typhi <- microorganisms %>%
+  filter(mo == "B_SLMNL_THSS") %>%
+  slice(c(1, 1, 1)) %>%
+  mutate(
+    mo = c("B_SLMNL_TYPH", "B_SLMNL_HMRM", "B_SLMNL_PRTY"),
+    fullname = c("Salmonella Typhi", "Salmonella Typhimurium", "Salmonella Paratyphi"),
+    subspecies = c("Typhi", "Typhimurium", "Paratyphi"),
+    snomed = snomed2
+  )
+
+new_groupa <- microorganisms %>%
+  filter(mo == "B_SLMNL_GRPB") %>%
+  mutate(
+    mo = "B_SLMNL_GRPA",
+    fullname = gsub("roup B", "roup A", fullname),
+    species = gsub("roup B", "roup A", species)
+  )
+
+microorganisms$mo <- as.character(microorganisms$mo)
+
+microorganisms <- microorganisms %>%
+  filter(!mo %in% c("B_SLMNL_TYPH", "B_SLMNL_HMRM", "B_SLMNL_PRTY")) %>%
+  bind_rows(new_typhi, new_groupa) %>%
+  arrange(fullname)
+
+microorganisms$lpsn_parent[which(microorganisms$genus == "Salmonella" & microorganisms$rank == "species")] <- "516547"
+microorganisms$gbif_parent[which(microorganisms$genus == "Salmonella" & microorganisms$rank == "species")] <- "3221815"
+
+class(microorganisms$mo) <- c("mo", "character")
@@ -1,273 +1,278 @@
-pattern	regular_expr	case_sensitive	affect_ab_name	affect_mo_name	zh	da	nl	fr	de	el	it	ja	pl	pt	ru	es	sv	tr	uk
-language name English	FALSE	FALSE	FALSE	FALSE	Chinese	Danish	Dutch	French	German	Greek	Italian	Japanese	Polish	Portuguese	Russian	Spanish	Swedish	Turkish	Ukrainian
-language name	FALSE	FALSE	FALSE	FALSE	汉语	Dansk	Nederlands	Français	Deutsch	Ελληνικά	Italiano	日本語	Polski	Português	Русский	Español	Svenska	Türkçe	Українська
-Coagulase-negative Staphylococcus	TRUE	TRUE	FALSE	TRUE	凝固酶阴性葡萄球菌	Koagulase-negative stafylokokker	Coagulase-negatieve Staphylococcus	Staphylococcus à coagulase négative	Koagulase-negative Staphylococcus	Σταφυλόκοκκος με αρνητική πηκτικότητα	Staphylococcus negativo coagulasi	コアグラーゼ陰性ブドウ球菌	Staphylococcus koagulazoujemny	Staphylococcus coagulase negativo	Коагулазоотрицательный стафилококк	Staphylococcus coagulasa negativo	Koagulasnegativa stafylokocker	Koagülaz-negatif Stafilokok	Коагулазонегативний стафілокок
-Coagulase-positive Staphylococcus	TRUE	TRUE	FALSE	TRUE	凝固酶阳性葡萄球菌	Koagulase-positive stafylokokker	Coagulase-positieve Staphylococcus	Staphylococcus à coagulase positif	Koagulase-positive Staphylococcus	Σταφυλόκοκκος θετικός στην πήξη	Staphylococcus positivo coagulasi	コアグラーゼ陽性ブドウ球菌	Staphylococcus koagulazo-dodatni	Staphylococcus coagulase positivo	Коагулазоположительный стафилококк	Staphylococcus coagulasa positivo	Koagulaspositiva stafylokocker	Koagülaz-pozitif Stafilokok	Коагулазопозитивний стафілокок
-Beta-haemolytic Streptococcus	TRUE	TRUE	FALSE	TRUE	β-溶血性链球菌	Beta-haemolytiske streptokokker	Beta-hemolytische Streptococcus	Streptococcus Bêta-hémolytique	Beta-hämolytischer Streptococcus	Β-αιμολυτικός στρεπτόκοκκος	Streptococcus Beta-emolitico	ベータ溶血性レンサ球菌	Streptococcus beta-hemolityczny	Streptococcus Beta-hemolítico	Бета-гемолитический стрептококк	Streptococcus Beta-hemolítico	Beta-hemolytiska streptokocker	Beta-hemolitik Streptokok	Бета-гемолітичний стрептокок
-unknown Gram-negatives	TRUE	TRUE	FALSE	TRUE	不明革兰氏阴性菌	ukendte Gram-negative	onbekende Gram-negatieven	Gram négatifs inconnus	unbekannte Gramnegativen	άγνωστοι αρνητικοί κατά Gram	Gram negativi sconosciuti	不明なグラム陰性菌	Nieznane bakterie Gram-ujemne	Gram negativos desconhecidos	неизвестные грамотрицательные	Gram negativos desconocidos	okända gramnegativa bakterier	bilinmeyen Gram-negatifler	невідомі грамнегативні
-unknown Gram-positives	TRUE	TRUE	FALSE	TRUE	不明革兰氏阳性菌	ukendte Gram-positive	onbekende Gram-positieven	Gram positifs inconnus	unbekannte Grampositiven	άγνωστοι θετικοί κατά Gram	Gram positivi sconosciuti	未知のグラム陽性菌	Nieznane bakterie Gram-dodatnie	Gram positivos desconhecidos	неизвестные грамположительные	Gram positivos desconocidos	okända Gram-positiva	bilinmeyen Gram-pozitifler	невідомі грампозитивні
-unknown fungus	TRUE	TRUE	FALSE	TRUE	未知真菌	ukendt svamp	onbekende schimmel	champignon inconnu	unbekannter Pilze	άγνωστος μύκητας	fungo sconosciuto	未知真菌	Nieznany grzyb	fungo desconhecido	неизвестный грибок	hongo desconocido	Okänd svamp	bilinmeyen mantar	невідомий гриб
-unknown yeast	TRUE	TRUE	FALSE	TRUE	未知酵母菌	ukendt gær	onbekende gist	levure inconnue	unbekannte Hefe	άγνωστος ζυμομύκητας	lievito sconosciuto	未知酵母	Nieznany drożdżak	levedura desconhecida	неизвестные дрожжи	levadura desconocida	Okänd jäst	bilinmeyen maya	невідомі дріжджі
-unknown name	TRUE	TRUE	FALSE	TRUE	不明名称	ukendt navn	onbekende naam	nom inconnu	unbekannte Name	άγνωστο όνομα	nome sconosciuto	名称未知	nieznana nazwa	nome desconhecido	неизвестное название	nombre desconocido	okänt namn	bilinmeyen isim	невідома назва
-unknown kingdom	TRUE	TRUE	FALSE	TRUE	未知王国	ukendt kongerige	onbekend koninkrijk	règme inconnu	unbekanntes Reich	άγνωστο βασίλειο	regno sconosciuto	未知の王国	nieznane królestwo	reino desconhecido	неизвестное царство	reino desconocido	okänt rike	bilinmeyen krallık	невідоме царство
-unknown phylum	TRUE	TRUE	FALSE	TRUE	未知门	ukendt stamme	onbekend fylum	embranchement inconnu	unbekannter Stamm	άγνωστο φύλο	phylum sconosciuto	未知の門	nieznany azyl	filo desconhecido	неизвестный филум	filo desconocido	okänt fylum	bilinmeyen filum	невідомий відділ
-unknown class	TRUE	TRUE	FALSE	TRUE	未知类	ukendt klasse	onbekende klasse	classe inconnue	unbekannte Klasse	άγνωστη τάξη	classe sconosciuta	未知のクラス	Nieznana klasa	classe desconhecida	неизвестный класс	clase desconocida	okänd klass	bilinmeyen sınıf	невідомий клас
-unknown order	TRUE	TRUE	FALSE	TRUE	未知目	ukendt orden	onbekende orde	ordre inconnu	unbekannte Ordnung	άγνωστη τάξη	ordine sconosciuto	未知の目	nieznany rząd	ordem desconhecido	неизвестный порядок	orden desconocido	okänd ordning	bilinmeyen sipariş	невідомий порядок
-unknown family	TRUE	TRUE	FALSE	TRUE	未知科	ukendt familie	onbekende familie	famille inconnue	unbekannte Familie	άγνωστη οικογένεια	famiglia sconosciuta	未知ファミリー	nieznana rodzina	família desconhecida	неизвестное семейство	familia desconocida	okänd familj	bilinmeyen aile	невідома родина
-unknown genus	TRUE	TRUE	FALSE	TRUE	未知属	ukendt slægt	onbekend geslacht	genre inconnu	unbekannte Gattung	άγνωστο γένος	genere sconosciuto	未知属	nieznany rodzaj	gênero desconhecido	неизвестный род	género desconocido	okänt släkte	bilinmeyen cins	невідомий рід
-unknown species	TRUE	TRUE	FALSE	TRUE	未知种	ukendt art	onbekende soort	espèce inconnue	unbekannte Art	άγνωστο είδος	specie sconosciute	未知種	nieznany gatunek	espécies desconhecida	неизвестный вид	especie desconocida	okänd art	bilinmeyen türler	невідомий вид
-unknown subspecies	TRUE	TRUE	FALSE	TRUE	未知亚种	ukendt underart	onbekende ondersoort	sous-espèce inconnue	unbekannte Unterart	άγνωστο υποείδος	sottospecie sconosciute	亜種不明	nieznany podgatunek	subespécies desconhecida	неизвестный подвид	subespecie desconocida	okänd underart	bilinmeyen alt türler	невідомий підвид
-unknown rank	TRUE	TRUE	FALSE	TRUE	未知等级	ukendt rang	onbekende rang	rang inconnu	unbekannter Rang	άγνωστη τάξη	grado sconosciuto	未知ランク	nieznany stopień	classificação desconhecido	неизвестный ранг	rango desconocido	okänd rang	bilinmeyen rütbe	невідомий ранг
- group 	TRUE	TRUE	FALSE	TRUE	 组 	 gruppe 	 groep 	 groupe 	 Gruppe 	 ομάδα 	 gruppo 	 グループ	 grupa 	 grupo 	 группа 	 grupo 	 grupp 	 Grup 	 група
- Group 	TRUE	TRUE	FALSE	TRUE	 组 	 Gruppe 	 groep 	 groupe 	 Gruppe 	 Ομάδα 	 Gruppo 	 グループ	 Grupa 	 Grupo 	 Группа 	 Grupo 	 Grupp 	 Grup 	 Група
-CoNS	FALSE	TRUE	FALSE	TRUE		KNS	CNS		KNS	CoNS		グラム陰性	CoNS		КОС	SCN	KNS	KNS	КНС
-CoPS	FALSE	TRUE	FALSE	TRUE		KPS	CPS		KPS	CoPS		グラム陽性	CoPS		КПС	SCP	KPS	KPS	КПС
-Gram-negative	TRUE	TRUE	FALSE	FALSE	革兰氏阴性	Gram-negativ	Gram-negatief	Gram négatif	Gramnegativ	Αρνητικό κατά Gram	Gram negativo	^細菌$	Gram-ujemne	Gram negativo	Грамотрицательные	Gram negativo	Gram-negativ	Gram-negatif	Грамнегативні
-Gram-positive	TRUE	TRUE	FALSE	FALSE	革兰氏阳性	Gram-positiv	Gram-positief	Gram positif	Grampositiv	Θετικό κατά Gram	Gram positivo	^真菌$	Gram-dodatnie	Gram positivo	Грамположительные	Gram positivo	Gram-positiv	Gram-pozitif	Грампозитивні
-^Bacteria$	TRUE	TRUE	FALSE	FALSE	细菌	Bakterier	Bacteriën	Bactéries	Bakterien	Βακτήρια	Batteri	酵母	Bakterie	Bactérias	Бактерии	Bacterias	Bakterier	Bakteri	Бактерії
-^Fungi$	TRUE	TRUE	FALSE	FALSE	真菌	Støbeforme	Schimmels	Champignons	Pilze	Μύκητες	Funghi	原生動物	Grzyby	Fungos	Грибы	Hongos	Svampar	Mantarlar	Гриби
-^Yeasts$	TRUE	TRUE	FALSE	FALSE	酵母菌	Gær	Gisten	Levures	Hefen	Ζυμομύκητες	Lieviti	バイオグループ	Drożdże	Leveduras	Животные	Levaduras	Jästdjur	Mayalar	Дріжджі
-^Protozoa$	TRUE	TRUE	FALSE	FALSE	^原生动物$	Protozoer	Protozoën	Protozoaires	Protozoen	Πρωτόζωα	Protozoi	生物型	Protozoa	Protozoários	Протозоа	Protozoarios	Protozoer	Protozoa	Найпростіші
-biogroup	TRUE	TRUE	FALSE	FALSE	生物群	biogruppe	biogroep	biogroupe	Biogruppe	βιοομάδα	biogruppo	植物型	biogrupa	biogrupo	биогруппа	biogrupo	biogrupp	biyogrup	біогрупа
-biotype	TRUE	TRUE	FALSE	FALSE	生物型	biotype			Biotyp	βιότυπος	biotipo	([([ ]*?))) グループ	biotyp	biótipo	биотип	biotipo	biotyp	biyotip	біотип
-vegetative	TRUE	TRUE	FALSE	FALSE	无性系	vegetativ	vegetatief	végétatif	vegetativ	βλαστικός	vegetativo	([[ ]*?)グループ	wegetatywna	vegetativo	вегетативный	vegetativo	vegetativ	vejetatif	вегетативний
-([([ ]*?)group	TRUE	TRUE	FALSE	FALSE	([([]*?)组	\\1gruppe	\\1groep	\\1groupe	\\1Gruppe	([([ ]*?)ομάδα	\\1gruppo		([([ ]*?)grupa	\\1grupo	\\1группа	\\1grupo	\\1grupp	([([ ]*?)grup	\\1група
-([([ ]*?)Group	TRUE	TRUE	FALSE	FALSE	([([]*?)组	\\1Gruppe	\\1Groep	\\1Groupe	\\1Gruppe	([([ ]*;)ομάδα	\\1Gruppo	ない	([([ ]*?)Grupa	\\1Grupo	\\1Группа	\\1Grupo	\\1Grupp	([([ ]*?)Grup	\\1Група
-no .*growth	FALSE	FALSE	FALSE	FALSE	无.*生长	ingen .*vækst	geen .*groei	pas .*croissance	keine(|n|m|r|s)|nicht .*wachstum	όχι .*αύξηση	sem .*crescimento	中間体	brak .*wzrostu	sem .*crescimento	отсутствие.*роста	no .*crecimientonon	ingen .*tillväxt	büyüme yok	відсутність .*росту
-no|not	FALSE	FALSE	FALSE	FALSE	不|不	nej|ikke	geen|niet	non	keine?	no|not	sem	感受性の高い、被ばく量の増加	nie|nie	sem	нет?	no|sin	nej|inte	hayır|değil|hayir|degil	ні
-Intermediate	TRUE	FALSE	FALSE	FALSE	中级	Mellemliggende	Intermediair		Mittlere	Ενδιάμεση		影響を受けやすい。	Pośrednia			Intermedio		Orta seviye	Знижена чутливість
-Susceptible, incr. exp.	FALSE	TRUE	FALSE	FALSE	易感，暴露增加	Modtagelig, øget eksp.	Gevoelig bij verh. blootstelling		Empfindlich, erh Belastung	Ευάλωτος, αυξημένη έκθεση		影響を受けやすい	Podatne, zwiększone narażenie					Duyarlı, enk. maruziyet	Чутливий до підвищеної експозиції
-susceptible, incr. exp.	FALSE	TRUE	FALSE	FALSE	易感，接触增加	modtagelig, øget eksp.	gevoelig bij verh. blootstelling		empfindlich, erh Belastung	Ευαίσθητος, αυξημένη έκθεση		曝露量増加	podatny, zwiększone narażenie					duyarlı, enk. maruziyet	чутливий до підвищеної експозиції
-Susceptible	TRUE	FALSE	FALSE	FALSE	易受影响	Modtagelig	Gevoelig		Empfindlich	Ευαίσθητο		耐性	Podatny			Susceptible		Duyarlı	Чутливий
-Incr. exposure	TRUE	FALSE	FALSE	FALSE	暴露增加	Øget eksponering	'Incr. exposure'		Empfindlich, erh Belastung	Αυξημένη έκθεση		抗生物質	Większe narażenie			'Incr. exposure'		Enk. maruziyet	Підвищена експозиція
-Resistant	TRUE	FALSE	FALSE	FALSE	耐药性	Resistent	Resistent		Resistent	Ανθεκτικός		抗生物質	Odporny			Resistente		Dayanıklı	Стійкий
-antibiotic	TRUE	TRUE	FALSE	FALSE	抗生素	antibiotikum	antibioticum	antibiotique	Antibiotikum	αντιβιοτικό	antibiotico	薬剤	antybiotyk	antibiótico	антибиотик	antibiótico	antibiotika	Antibiyotik	антибіотик
-Antibiotic	TRUE	TRUE	FALSE	FALSE	抗生素	Antibiotikum	Antibioticum	Antibiotique	Antibiotikum	Αντιβιοτικό	Antibiotico	薬剤	Antybiotyk	Antibiótico	Антибиотик	Antibiótico	Antibiotika	Antibiyotik	Антибіотик
-Drug	TRUE	TRUE	FALSE	FALSE	药物	Lægemiddel	Middel	Médicament	Medikament	Φάρμακο	Droga	頻度	Lek	Droga	Лекарство	Fármaco	Läkemedel	İlaç	Лікарський засіб
-drug	TRUE	TRUE	FALSE	FALSE	药物	lægemiddel	middel	médicament	Medikament	φάρμακο	droga	最小発育阻止濃度(mg / L)	lek	droga	лекарство	fármaco	läkemedel	İlaç	лікарський засіб
-Frequency	FALSE	TRUE	FALSE	FALSE	使用频率	Frekvens	Aantal	Fréquence	Zahl	Συχνότητα	Frequenza	ディスク拡散径(mm)	Częstotliwość	Frequência	Частота	Frecuencia	Frekvens	Frekans	Частота
-Minimum Inhibitory Concentration (mg/L)	FALSE	FALSE	FALSE	FALSE	最小抑菌浓度(mg/L)	Mindste hæmmende koncentration (mg/L)	Minimale inhiberende concentratie (mg/L)	Concentration minimale inhibitrice (mg/L)	Minimale Hemm-Konzentration (mg/L)	Ελάχιστη ανασταλτική συγκέντρωση (mg/L)	Concentrazione minima inibitoria (mg/L)	抗菌性解釈	Minimalne stężenie hamujące (mg/L)	Concentração Inibitória Mínima (mg/L)	Минимальная ингибирующая концентрация (мг/л)	Concentración mínima inhibitoria (mg/L)	Minsta hämmande koncentration (mg/L)	Minimum İnhibitör Konsantrasyon (mg/L)	Мінімальна інгібуюча концентрація (мг/мл)
-Disk diffusion diameter (mm)	FALSE	FALSE	FALSE	FALSE	磁盘扩散直径(mm)	Diskdiffusionsdiameter (mm)	Diameter diskzone (mm)	Diamètre de diffusion en disque (mm)	Durchmesser der Scheibenzone (mm)	Διάμετρος διάχυσης δίσκου (mm)	Diametro di diffusione del disco (mm)	割合	Średnica dyfuzji dysku (mm)	Diâmetro de difusão do disco (mm)	Диаметр диффузии диска (мм)	Diámetro de difusión en disco (mm)	Diskdiffusionsdiameter (mm)	Disk difüzyon çapı (mm)	Зона затримки росту (мм)
-Antimicrobial Interpretation	FALSE	FALSE	FALSE	FALSE	抗菌性解释	Antimikrobiel fortolkning	Antimicrobiële interpretatie	Interprétation antimicrobienne	Antimikrobielle Auswertung	Αντιμικροβιακή ερμηνεία	Interpretazione antimicrobica	4-アミノサリチル酸	Interpretacja antybakteryjna	Interpretação Antimicrobiana	Антимикробная интерпретация	Interpretación antimicrobiana	Antimikrobiell tolkning	Antimikrobiyal Yorumlama	Фенотипи чутливості
-Percentage	FALSE	FALSE	FALSE	FALSE	百分比	Procentdel	Percentage	Pourcentage	Prozentsatz	Ποσοστό	Percentuale	アデホビル・ジピボキシル	Procent	Percentagem	Процент	Porcentaje	Procentuell andel	Yüzde	Відсоток
-4-aminosalicylic acid	FALSE	TRUE	TRUE	FALSE	4-氨基水杨酸	4-aminosalicylsyre	4-aminosalicylzuur	Acide 4-aminosalicylique	4-Aminosalicylsäure	4-αμινοσαλικυλικό οξύ	Acido 4-aminosalicilico	アルデスルホンナトリウム	Kwas 4-aminosalicylowy	Ácido 4-aminosalicílico	4-аминосалициловая кислота	Ácido 4-aminosalicílico	4-aminosalicylsyra	4-aminosalisilik asit	4-Аміносаліцилова кислота
-Adefovir dipivoxil	FALSE	TRUE	TRUE	FALSE	阿德福韦酯	Adefovir dipivoxil	Adefovir	Adéfovir dipivoxil	Adefovir Dipivoxil	Adefovir dipivoxil	Adefovir dipivoxil	アミカシン	Adefovir dipivoxil	Adefovir dipivoxil	Адефовир дипивоксил	Adefovir dipivoxil	Adefovir dipivoxil	Adefovir dipivoksil	Адефовір діпівоксил
-Aldesulfone sodium	FALSE	TRUE	TRUE	FALSE	醛缩酮钠	Aldesulfon-natrium	Aldesulfon	Aldésulfone sodique	Aldesulfon-Natrium	Αλδεσουλφονικό νάτριο	Aldesulfone sodio	アモキシシリン	Sól sodowa aldesulfonu	Aldesulfona de sódio	Альдесульфон натрия	Aldesulfona sódica	Aldesulfonnatrium	Aldesülfon sodyum	Альденсульфон натрію
-Amikacin	FALSE	TRUE	TRUE	FALSE	阿米卡星	Amikacin	Amikacine	Amikacine	Amikacin	Amikacin	Amikacin	アモキシシリン／β-ラクタマーゼ阻害剤	Amikacyna	Amikacin	Амикацин	Amikacina	Amikacin	Amikasin	Амікацин
-Amoxicillin	FALSE	TRUE	TRUE	FALSE	阿莫西林	Amoxicillin	Amoxicilline	Amoxicilline	Amoxicillin	Αμοξικιλλίνη	Amoxicillina	アムホテリシンB	Amoxicillin	Amoxicilina	Амоксициллин	Amoxicilina	Amoxicillin	Amoksisilin	Амоксицилін
-Amoxicillin/beta-lactamase inhibitor	FALSE	TRUE	TRUE	FALSE	阿莫西林/β-内酰胺酶抑制剂	Amoxicillin/beta-lactamasehæmmer	Amoxicilline/enzymremmer	Amoxicilline/inhib. de bêta-lactamase	Amoxicillin/Beta-Lactamase-Hemmer	Αμοξικιλλίνη/αναστολέας της β-λακταμάσης	Amoxicillina/inib. d. beta-lattamasi	アンピシリン	Amoksycylina/inhibitor beta-laktamazy	Amoxicilina/inibid. da beta-lactamase	Амоксициллин/ингибитор бета-лактамаз	Amoxicilina/inhib. de la beta-lactamasa	Amoxicillin/betalaktamashämmare	Amoksisilin/beta-laktamaz inhibitörü	Амоксицилін/інгібітор бета-лактамаз
-Amphotericin B	FALSE	TRUE	TRUE	FALSE	两性霉素B	Amfotericin B	Amfotericine B	Amphotéricine B	Amphotericin B	Αμφοτερικίνη Β	Amfotericina B	アンピシリン／β-ラクタマーゼ阻害剤	Amfoterycyna B	Anfotericina B	Амфотерицин В	Anfotericina B	Amfotericin B	Amfoterisin B	Амфотерицин В
-Ampicillin	FALSE	TRUE	TRUE	FALSE	氨苄西林	Ampicillin	Ampicilline	Ampicilline	Ampicillin	Αµπικιλλίνη	Ampicillina	アニデュラファンギン	Ampicylina	Ampicilina	Ампициллин	Ampicilina	Ampicillin	Ampisilin	Ампіцилін
-Ampicillin/beta-lactamase inhibitor	FALSE	TRUE	TRUE	FALSE	氨苄西林/β-内酰胺酶抑制剂	Ampicillin/beta-lactamasehæmmer	Ampicilline/enzymremmer	Ampicilline/inhib. de bêta-lactamase	Ampicillin/Beta-Laktamase-Hemmer	Αμπικιλλίνη/αναστολέας β-λακταμάσης	Ampicillina/inib. d. beta-lattamasi	アジドシリン	Ampicylina/inhibitor beta-laktamazy	Ampicilina/inibid. da beta-lactamase	Ампициллин/ингибитор бета-лактамазы	Ampicilina/inhib. de la beta-lactamasa	Ampicillin/beta-laktamashämmare	Ampisilin/beta-laktamaz inhibitörü	Ампіцилін/інгібітор бета-лактамаз
-Anidulafungin	FALSE	TRUE	TRUE	FALSE	阿尼芬净	Anidulafungin	Anidulafungine	Anidulafungine	Anidulafungin	Ανιδουλαφουνγκίνη	Anidulafungin	アジスロマイシン	Anidulafungina	Anidulafungin	Анидулафунгин	Anidulafungina	Anidulafungin	Anidulafungin	Анідулафунгін
-Azidocillin	FALSE	TRUE	TRUE	FALSE	阿奇霉素	Azidocillin	Azidocilline	Azidocilline	Azidocillin	Αζιδοκιλλίνη	Azidocillina	アズロシリン	Azidocillin	Azidocillin	Азидоциллин	Azidocilina	Azidocillin	Azidosilin	Азидоцилін
-Azithromycin	FALSE	TRUE	TRUE	FALSE	阿奇霉素	Azithromycin	Azitromycine	Azithromycine	Azithromycin	Αζιθρομυκίνη	Azitromicina	バカンピシリン	Azithromycin	Azitromicina	Азитромицин	Azitromicina	Azitromycin	Azitromisin	Азитроміцин
-Azlocillin	FALSE	TRUE	TRUE	FALSE	阿洛西林	Azlocillin	Azlocilline	Azlocilline	Azlocillin	Αζλοκιλλίνη	Azlocillina	バシトラシン	Azlocillin	Azlocillin	Азлоциллин	Azlocilina	Azlocillin	Azlocillin	Азлоцилін
-Bacampicillin	FALSE	TRUE	TRUE	FALSE	巴卡比林	Bacampicillin	Bacampicilline	Bacampicilline	Bacampicillin	Μπακαμπικιλλίνη	Bacampicillina	ベンズシン・ベンジルペニシリン	Bakampicylina	Bacampicilina	Бакампициллин	Bacampicilina	Bacampicillin	Bacampicillin	Бакампіцилін
-Bacitracin	FALSE	TRUE	TRUE	FALSE	阿奇霉素	Bacitracin	Bacitracine	Bacitracine	Bacitracin	Bacitracin	Bacitracina	ベンザチンフェノキシメチルペニシリン	Bacytracyna	Bacitracin	Бацитрацин	Bacitracina	Bacitracin	Basitrasin	Бацитрацин
-Benzathine benzylpenicillin	FALSE	TRUE	TRUE	FALSE	苄丝肼青霉素	Benzathinbenzylpenicillin	Benzylpenicillinebenzathine	Benzathine benzylpénicilline	Benzathin-Benzylpenicillin	Βενζαθίνη βενζυλπενικιλλίνη	Benzatina benzilpenicillina	ベンジルペニシリン	Benzylpenicylina benzylowa	Benzatina benzatina benzilpenicilina	Бензатин бензилпенициллин	Bencilpenicilina benzatínica	Benzathinbenzylpenicillin	Benzatin benzilpenisilin	Бензатину бензилпеніцилін
-Benzathine phenoxymethylpenicillin	FALSE	TRUE	TRUE	FALSE	苄星苯氧甲基青霉素	Benzathinfenoxymethylpenicillin	Fenoxymethylpenicillinebenzathine	Phénoxyméthylpénicilline benzathine	Benzathin-Phenoxymethylpenicillin	Βενζαθίνη φαινοξυμεθυλοπενικιλλίνη	Benzatina fenossimetilpenicillina	アミノサリチル酸カルシウム	Fenoksymetylopenicylina benzylowa	Benzatina fenoximetilpenicilina	Бензатин феноксиметилпенициллин	Fenoximetilpenicilina benzatínica	Bensathinfenoximetylpenicillin	Benzatin fenoksimetilpenisilin	Бензатину феноксиметилпеніцилін
-Benzylpenicillin	FALSE	TRUE	TRUE	FALSE	苄基青霉素	Benzylpenicillin	Benzylpenicilline	Benzylpénicilline	Benzylpenicillin	Benzylpenicillin	Benzilpenicillina	カプレオマイシン	Benzylpenicylina	Benzilpenicilina	Бензилпенициллин	Bencilpenicilina	Bensylpenicillin	Benzilpenisilin	Бензилпеніцилін
-Calcium aminosalicylate	FALSE	TRUE	TRUE	FALSE	氨基水杨酸钙	Calciumaminosalicylat	Aminosalicylzuur	Aminosalicylate de calcium	Kalzium-Aminosalicylat	Αμινοσαλικυλικό ασβέστιο	Calcio aminosalicilato	カルベニシリン	Aminosalicylan wapnia	Aminosalicilato de cálcio	Аминосалицилат кальция	Aminosalicilato de calcio	Kalciumaminosalicylat	Kalsiyum aminosalisilat	Кальцію аміносаліцилат
-Capreomycin	FALSE	TRUE	TRUE	FALSE	氨水杨酸钙	Capreomycin	Capreomycine	Capréomycine	Capreomycin	Καπρεομυκίνη	Capreomicina	カリンダシリン	Kapreomycyna	Capreomicina	Капреомицин	Capreomicina	Kapreomycin	Kapreomisin	Капреоміцин
-Carbenicillin	FALSE	TRUE	TRUE	FALSE	羧基青霉素	Carbenicillin	Carbenicilline	Carbénicilline	Carbenicillin	Καρβενικιλλίνη	Carbenicillina	カスポファンギン	Karbenicylina	Carbenicilina	Карбенициллин	Carbenicilina	Karbenicillin	Karbenisilin	Карбеніцилін
-Carindacillin	FALSE	TRUE	TRUE	FALSE	卡林达西林	Carindacillin	Carindacilline	Carindacilline	Carindacillin	Carindacillin	Carindacillina	セファセトリル	Karindacillin	Carindacillin	Кариндациллин	Carindacilina	Carindacillin	Karindasilin	Кариндацилін
-Caspofungin	FALSE	TRUE	TRUE	FALSE	氨苄青霉素	Caspofungin	Caspofungine	Caspofungine	Caspofungin	Caspofungin	Caspofungin	セファロチン	Kaspofungina	Caspofungin	Каспофунгин	Caspofungina	Caspofungin	Caspofungin	Каспофунгін
-Ce(f|ph)acetrile	TRUE	TRUE	TRUE	FALSE	头孢乙腈	Cephacetril	Cefacetril	Céphacétrile	Cefacetril	Κεφακετρίλη	Cefacetrile	セファマンドール	Cefacetrile	Cephacetrile	Цефацетрил	Cefacetrilo	Cephacetril	Sefasetril	Цефацетрил
-Ce(f|ph)alotin	TRUE	TRUE	TRUE	FALSE	头孢罗丁	Cephalotin	Cefalotine	Céphalotine	Cefalotin	Κεφαλοτίνη	Cefalotina	セファピリン	Cefalotyna	Cefalotina	Цефалотин	Cefalotina	Cefalotin	Sefalotin	Цефалотин
-Ce(f|ph)amandole	TRUE	TRUE	TRUE	FALSE	头孢曼多	Cephamandol	Cefamandol	Céphamandole	Cefamandol	Κεφαμανδόλη	Cephamandole	セファゼドン	Cefamandol	Cephamandole	Цефамандол	Cefamandole	Cephamandol	Cefamandole	Цефамандол
-Ce(f|ph)apirin	TRUE	TRUE	TRUE	FALSE	头孢匹林	Cephapirin	Cefapirine	Céphapirine	Cefapirin	Κεφαπιρίνη	Cefapirina	セファゾリン	Cefapiryna	Cephapirin	Цефапирин	Cefapirina	Cephapirin	Sefapirin	Цефапірин
-Ce(f|ph)azedone	TRUE	TRUE	TRUE	FALSE	头孢唑酮	Cephazedon	Cefazedon	Céphazédone	Cefazedon	Κεφαζεδόνη	Cefazedone	セファロチン	Cefazedon	Cephazedone	Цефазедон	Cefazedona	Cephazedon	Sefazedon	Цефазедон
-Ce(f|ph)azolin	TRUE	TRUE	TRUE	FALSE	头孢唑啉	Cephazolin	Cefazoline	Céphazoline	Cefazolin	Κεφαζολίνη	Cephazolin	セファレキシン	Cefazolin	Cephazolin	Цефазолин	Cefazolina	Cephazolin	Sefazolin	Цефазолін
-Ce(f|ph)alothin	TRUE	TRUE	TRUE	FALSE	头孢罗丁	Cephalothin	Cefalotine	Céphalothine	Cefalothin	Κεφαλοθίνη	Cefalotina	セフェパイム	Cefalotyna	Cephalothin	Цефалотин	Cefalotina	Kefalotin	Cefalothin	Цефалотин
-Ce(f|ph)alexin	TRUE	TRUE	TRUE	FALSE	头孢莱辛	Cephalexin	Cefalexine	Céphalexine	Cefalexin	Κεφαλεξίνη	Cephalexin	セフィキシム	Cefaleksyna	Cephalexin	Цефалексин	Cefalexina	Cephalexin	Cefalexin	Цефалексин
-Ce(f|ph)epime	TRUE	TRUE	TRUE	FALSE	头孢吡肟	Cephepime	Cefepim	Céphépime	Cefepim	Κεφεπίμη	Cephepime	セフメノキシム	Cefepime	Cephepime	Цефепим	Cefepime	Cephepim	Sefepim	Цефепім
-Ce(f|ph)ixime	TRUE	TRUE	TRUE	FALSE	头孢克肟	Cephixim	Cefixim	Céphixime	Cefixim	Cefixime	Cephixime	セフメタゾール	Cefixime	Cephixime	Цефиксим	Cefixima	Cephixim	Cefixime	Цефіксим
-Ce(f|ph)menoxime	TRUE	TRUE	TRUE	FALSE	头孢米诺肟	Cephmenoxim	Cefmenoxim	Céphénoxime	Cefmenoxim	Cefmenoxime	Cephmenoxime	セフォジジム	Cefmenoksym	Cephmenoxime	Цефменоксим	Cefmenoxima	Cephmenoxim	Sefmenoksim	Цефменоксим
-Ce(f|ph)metazole	TRUE	TRUE	TRUE	FALSE	头孢美唑	Cephmetazol	Cefmetazol	Céphmétazole	Cefmetazol	Cefmetazole	Cephmetazole	セフォニキッド	Cefmetazol	Cefmetazole	Цефметазол	Cefmetazol	Cephmetazol	Sefmetazol	Цефметазол
-Ce(f|ph)odizime	TRUE	TRUE	TRUE	FALSE	头孢地嗪	Cephodizim	Cefodizim	Céphodizime	Cefodizim	Cefodizime	Cephodizime	セフォペラゾン	Cefodizime	Cephodizime	Цефодизим	Cefodixima	Cephodizim	Sefodizim	Цефодізим
-Ce(f|ph)onicid	TRUE	TRUE	TRUE	FALSE	头孢尼西	Cephonicid	Cefonicide	Céphonicide	Cefonicid	Cefonicid	Cephonicid		Cefonicid	Cefonicid	Цефонизид	Cefonicida	Cephonicid	Cefonicid	Цефоніцид
-Ce(f|ph)operazone	TRUE	TRUE	TRUE	FALSE	头孢哌酮	Cephoperazon	Cefoperazon	Céphopérazone	Cefoperazon	Κεφοπεραζόνη	Cephoperazone	セフォタキシム	Cefoperazon	Cephoperazone	Цефоперазон	Cefoperazona	Cephoperazon	Sefoperazon	Цефоперазон
-Ce(f|ph)operazone/beta-lactamase inhibitor	TRUE	TRUE	TRUE	FALSE	头孢哌酮/β-内酰胺酶抑制剂	Cephoperazon/beta-lactamasehæmmer	Cefoperazon/enzymremmer	Céphopérazone/inhib. de bêta-lactamase	Cefoperazon/Beta-Lactamase-Hemmer	Κεφοπεραζόνη/αναστολέας της β-λακταμάσης	Cephoperazone/inib. d. beta-lattamasi		Cefoperazon/inhibitor beta-laktamazy	Cephoperazona/inibid. da beta-lactamase	Цефоперазон/ингибитор бета-лактамаз	Cefoperazona/inhib. de betalactamasas	Cefoperazon/beta-laktamashämmare	Sefoperazon/beta-laktamaz inhibitörü	Цефоперазон/інгібітор бета-лактамаз
-Ce(f|ph)otaxime	TRUE	TRUE	TRUE	FALSE	头孢噻肟	Cephotaxim	Cefotaxim	Céphotaxime	Cefotaxim	Κεφοταξίμη	Cephotaxime	セフピロム	Cefotaksym	Cephotaxime	Цефотаксим	Cefotaxima	Cephotaxim	Sefotaksim	Цефотаксим
-Ce(f|ph)oxitin	TRUE	TRUE	TRUE	FALSE	头孢西丁	Cephoxitin	Cefoxitine	Céphoxitine	Cefoxitin	Κεφοξιτίνη	Cefossitina	セフポドキシム	Cefoksytyna	Cephoxitin	Цефокситин	Cefoxitina	Cephoxitin	Cefoxitin	Цефокситин
-Ce(f|ph)pirome	TRUE	TRUE	TRUE	FALSE	头孢匹罗	Cephpirom	Cefpirom	Céphpirome	Cefpirom	Κεφπιρόμη	Cephpirome	セフラジン	Cefpirom	Cefpirome	Цефпиром	Cephpirome	Cephpirom	Sefpirom	Цефпіром
-Ce(f|ph)podoxime	TRUE	TRUE	TRUE	FALSE	头孢泊肟	Cephpodoxim	Cefpodoxim	Céphpodoxime	Cefpodoxim	Κεφποδοξίμη	Cephpodoxime	セフスロジン	Cefpodoxime	Cephpodoxime	Цефподоксим	Cefpodoxima	Cephpodoxim	Sefpodoksim	Цефподоксим
-Ce(f|ph)radine	TRUE	TRUE	TRUE	FALSE	头孢拉定	Cephradin	Cefradine	Céphradine	Cefradin	Cefradine	Cefradina	セフタジジム	Cefradyna	Cephradine	Цефрадин	Cefradina	Cephradin	Sefradin	Цефрадін
-Ce(f|ph)sulodin	TRUE	TRUE	TRUE	FALSE	头孢苏洛丁	Cephsulodin	Cefsulodine	Céphsulodine	Cefsulodin	Cefsulodin	Cephsulodin	セフテゾール	Cefsulodin	Cephsulodin	Цефсулодин	Cefsulodina	Cephsulodin	Cefsulodin	Цефсулодин
-Ce(f|ph)tazidime	TRUE	TRUE	TRUE	FALSE	头孢噻肟	Cephtazidim	Ceftazidim	Céphtazidime	Ceftazidim	Κεφταζιδίμη	Ceftazidima	セフティゾキシム	Ceftazidime	Ceftazidima	Цефтазидим	Ceftazidima	Cephtazidim	Seftazidim	Цефтазидим
-Ce(f|ph)tezole	TRUE	TRUE	TRUE	FALSE	头孢特唑	Cephtezol	Ceftezol	Céphtézole	Ceftezol	Ceftezole	Cephtezole	セフトリアキソン	Ceftezol	Ceftezole	Цефтезол	Ceftezol	Cephtezole	Seftezol	Цефтезол
-Ce(f|ph)tizoxime	TRUE	TRUE	TRUE	FALSE	头孢唑肟	Cephtizoxim	Ceftizoxim	Céphtizoxime	Ceftizoxim	Ceftizoxime	Cephtizoxime	セフロキシム	Ceftizoxime	Cephtizoxime	Цефтизоксим	Ceftizoxima	Cephtizoxim	Seftizoksim	Цефтизоксим
-Ce(f|ph)triaxone	TRUE	TRUE	TRUE	FALSE	头孢曲松	Cephtriaxon	Ceftriaxon	Céphtriaxone	Ceftriaxon	Ceftriaxone	Ceftriaxone		Ceftriakson	Cefhtriaxone	Цефтриаксон	Ceftriaxona	Ceftriaxon	Ceftriaxone	Цефтриаксон
-Ce(f|ph)uroxime	TRUE	TRUE	TRUE	FALSE	头孢呋辛	Cephuroxim	Cefuroxim	Céphuroxime	Cefuroxim	Κεφουροξίμη	Cefuroxima	クロラムフェニコール	Cefuroksym	Cephuroxime	Цефуроксим	Cefuroxima	Cefuroxim	Sefuroksim	Цефуроксим
-Ce(f|ph)uroxime/metronidazole	TRUE	TRUE	TRUE	FALSE	头孢呋辛/甲硝唑	Cefuroxim/metronidazol	Cefuroxim/andere antibacteriele middelen	Céphuroxime/métronidazole	Cefuroxim/Metronidazol	Κεφουροξίμη/μετρονιδαζόλη	Cefuroxima/metronidazolo	クロルテトラサイクリン	Cefuroksym/metronidazol	Cephuroxime/metronidazol	Цефуроксим/метронидазол	Cefuroxima/metronidazol	Cefuroxim/metronidazol	Sefuroksim/metronidazol	Цефуроксим/метронідазол
-Chloramphenicol	FALSE	TRUE	TRUE	FALSE	氯霉素	Kloramfenicol	Chlooramfenicol	Chloramphénicol	Chloramphenicol	Χλωραμφενικόλη	Cloramfenicolo	シノキサシン	Chloramfenikol	Cloranfenicol	Хлорамфеникол	Cloranfenicol	Kloramfenikol	Kloramfenikol	Хлорамфенікол
-Chlortetracycline	FALSE	TRUE	TRUE	FALSE	金霉素	Chlortetracyclin	Chloortetracycline	Chlortétracycline	Chlortetracyclin	Χλωροτετρακυκλίνη	Clorotetraciclina	シプロフロキサシン	Chlortetracyklina	Chlortetracycline	Хлортетрациклин	Clortetraciclina	Klortetracyklin	Klortetrasiklin	Хлортетрациклін
-Cinoxacin	FALSE	TRUE	TRUE	FALSE	西诺沙星	Cinoxacin	Cinoxacine	Cinoxacine	Cinoxacin	Cinoxacin	Cinoxacina	クラリスロマイシン	Cinoxacin	Cinoxacin	Циноксацин	Cinoxacina	Cinoxacin	Cinoxacin	Циноксацин
-Ciprofloxacin	FALSE	TRUE	TRUE	FALSE	环丙沙星	Ciprofloxacin	Ciprofloxacine	Ciprofloxacine	Ciprofloxacin	Σιπροφλοξασίνη	Ciprofloxacina	クラビュラン酸	Ciprofloksacyna	Ciprofloxacin	Ципрофлоксацин	Ciprofloxacina	Ciprofloxacin	Siprofloksasin	Ципрофлоксацин
-Clarithromycin	FALSE	TRUE	TRUE	FALSE	克拉霉素	Clarithromycin	Claritromycine	Clarithromycine	Clarithromycin	Κλαριθρομυκίνη	Claritromicina	クラビュラン酸	Klarytromycyna	Claritromicina	Кларитромицин	Claritromicina	Claritromycin	Klaritromisin	Кларитроміцин
-Clavulanic acid	FALSE	TRUE	TRUE	FALSE	克拉维酸	Clavulansyre	Clavulaanzuur	Acide clavulanique	Clavulansäure	Κλαβουλανικό οξύ	Acido clavulanico	クリンダマイシン	Kwas klawulanowy	Ácido clavulânico	Клавулановая кислота	Ácido clavulánico	Clavulansyra	Klavulanik asit	Клавуланова кислота
-clavulanic acid	FALSE	TRUE	TRUE	FALSE	克拉维酸	clavulansyre	clavulaanzuur	acide clavulanique	Clavulansäure	Κλαβουλανικό οξύ	acido clavulanico	クロメトシリン	kwas klawulanowy	ácido clavulânico	клавулановая кислота	ácido clavulánico	clavulansyra	klavulanik asit	клавуланова кислота
-Clindamycin	FALSE	TRUE	TRUE	FALSE	克林霉素	Clindamycin	Clindamycine	Clindamycine	Clindamycin	Clindamycin	Clindamicina	クロトリマゾール	Klindamycyna	Clindamicina	Клиндамицин	Clindamicina	Clindamycin	Klindamisin	Кліндаміцин
-Clometocillin	FALSE	TRUE	TRUE	FALSE	克罗米修斯（	Clometocillin	Clometocilline	Clométocilline	Clometocillin	Clometocillin	Clometocillina	クロキサシリン	Clometocillin	Clometocillin	Клометоциллин	Clometocilina	Klometocillin	Clometocillin	Клометоцилін
-Clotrimazole	FALSE	TRUE	TRUE	FALSE	克霉唑	Clotrimazol	Clotrimazol	Clotrimazole	Clotrimazol	Κλοτριμαζόλη	Clotrimazolo	コリスチン	Klotrimazol	Clotrimazole	Клотримазол	Clotrimazol	Klotrimazol	Klotrimazol	Клотримазол
-Cloxacillin	FALSE	TRUE	TRUE	FALSE	克罗西林	Cloxacillin	Cloxacilline	Cloxacilline	Cloxacillin	Κλοξακιλλίνη	Cloxacillina	ダプソン	Cloxacillin	Cloxacillin	Клоксациллин	Cloxacilina	Kloxacillin	Cloxacillin	Клоксацилін
-Colistin	FALSE	TRUE	TRUE	FALSE	唑啉酮	Colistin	Colistine	Colistine	Colistin	Κολιστίνη	Colistina	ダプトマイシン	Kolistyna	Colistin	Колистин	Colistina	Kolistin	Kolistin	Колістин
-Dapsone	FALSE	TRUE	TRUE	FALSE	多普生	Dapson	Dapson	Dapsone	Dapson	Δαψόνη	Dapsone	ジベカシン	Dapson	Dapsone	Дапсон	Dapsona	Dapson	Dapson	Дапсон
-Daptomycin	FALSE	TRUE	TRUE	FALSE	达托霉素	Daptomycin	Daptomycine	Daptomycine	Daptomycin	Daptomycin	Daptomicina	ジクロキサシリン	Daptomycyna	Daptomicina	Даптомицин	Daptomicina	Daptomycin	Daptomisin	Даптоміцин
-Dibekacin	FALSE	TRUE	TRUE	FALSE	迪贝卡星	Dibekacin	Dibekacine	Dibekacine	Dibekacin	Dibekacin	Dibekacin	ジリスロマイシン	Dibekacin	Dibekacin	Дибекацин	Dibekacina	Dibekacin	Dibekacin	Дібекацин
-Dicloxacillin	FALSE	TRUE	TRUE	FALSE	迪卡西林	Dicloxacillin	Dicloxacilline	Dicloxacilline	Dicloxacillin	Dicloxacillin	Dicloxacillina	エコナゾール	Dikloxacillin	Dicloxacilina	Диклоксациллин	Dicloxacilina	Dikloxacillin	Dikloksasilin	Диклоксацилін
-Dirithromycin	FALSE	TRUE	TRUE	FALSE	迪里红霉素	Dirithromycin	Diritromycine	Dirithromycine	Dirithromycin	Dirithromycin	Diritromicina	エノキサシン	Dirytromycyna	Diritromicina	Диритромицин	Diritromicina	Diritromycin	Diritromisin	Диритроміцин
-Econazole	FALSE	TRUE	TRUE	FALSE	胺鲜胺	Econazol	Econazol	Econazole	Econazol	Econazole	Econazolo	エピシリン	Ekonazol	Econazole	Эконазол	Econazol	Ekonazol	Ekonazol	Еконазол
-Enoxacin	FALSE	TRUE	TRUE	FALSE	伊诺沙星	Enoxacin	Enoxacine	Enoxacine	Enoxacin	Enoxacin	Enoxacina	エリスロマイシン	Enoxacin	Enoxacin	Эноксацин	Enoxacina	Enoxacin	Enoksasin	Еноксацин
-Epicillin	FALSE	TRUE	TRUE	FALSE	伊比西林	Epicillin	Epicilline	Epicilline	Epicillin	Epicillin	Epicillina	エタンブトール／イソニアジド	Epicillin	Epicilina	Эпициллин	Epicilina	Epicillin	Episilin	Епіцилін
-Erythromycin	FALSE	TRUE	TRUE	FALSE	红霉素	Erythromycin	Erytromycine	Erythromycine	Erythromycin	Ερυθρομυκίνη	Eritromicina	フレロキサシン	Erytromycyna	Eritromicina	Эритромицин	Eritromicina	Erytromycin	Eritromisin	Еритроміцин
-Ethambutol/isoniazid	FALSE	TRUE	TRUE	FALSE	乙胺丁醇/异烟肼	Ethambutol/isoniazid	Ethambutol/isoniazide	Ethambutol/isoniazide	Ethambutol/Isoniazid	Αιθαμβουτόλη/ισονιαζίδη	Etambutolo/isoniazide	フルクロキサシリン	Etambutol/izoniazyd	Ethambutol/isoniazid	Этамбутол/изониазид	Etambutol/isoniazida	Etambutol/isoniazid	Etambutol/izoniazid	Етамбутол/ізоніазид
-Fleroxacin	FALSE	TRUE	TRUE	FALSE	氨甲喋呤	Fleroxacin	Fleroxacine	Fléroxacine	Fleroxacin	Φλεροξακίνη	Fleroxacina	フルコナゾール	Fleroksacyna	Fleroxacina	Флероксацин	Fleroxacina	Fleroxacin	Fleroxacin	Флероксацин
-Flucloxacillin	FALSE	TRUE	TRUE	FALSE	氟氯西林	Flucloxacillin	Flucloxacilline	Flucloxacilline	Flucloxacillin	Flucloxacillin	Flucloxacillina	フルシトシン	Flucloxacillin	Flucloxacillin	Флуклоксациллин	Flucloxacilina	Flucloxacillin	Flukloksasilin	Флуклоксацилін
-Fluconazole	FALSE	TRUE	TRUE	FALSE	氟康唑	Fluconazol	Fluconazol	Fluconazole	Fluconazol	Φλουκοναζόλη	Fluconazolo	フルリスロマイシン	Flukonazol	Fluconazole	Флуконазол	Fluconazol	Flukonazol	Flukonazol	Флуконазол
-Flucytosine	FALSE	TRUE	TRUE	FALSE	氨甲喋呤	Flucytosin	Fluorocytosine	Flucytosine	Flucytosin	Φλουκυτοσίνη	Flucytosine	ホスホマイシン	Flucytozyna	Flucytosine	Флуцитозин	Flucitosina	Flucytosin	Flusitozin	Флуцитозин
-Flurithromycin	FALSE	TRUE	TRUE	FALSE	氟利霉素	Flurithromycin	Fluritromycine	Flurithromycine	Flurithromycin	Φλουριθρομυκίνη	Fluritromicina	フシジン酸	Flurithromycin	Fluritromicina	Флуритромицин	Fluritromicina	Fluritromycin	Fluritromisin	Флуритроміцин
-Fosfomycin	FALSE	TRUE	TRUE	FALSE	福斯霉素	Fosfomycin	Fosfomycine	Fosfomycine	Fosfomycin	Φοσφομυκίνη	Fosfomicina	ガチフロキサシン	Fosfomycyna	Fosfomycin	Фосфомицин	Fosfomicina	Fosfomycin	Fosfomisin	Фосфоміцин
-Fusidic acid	FALSE	TRUE	TRUE	FALSE	夫西地酸	Fusidinsyre	Fusidinezuur	Acide fusidique	Fusidinsäure	Φουσιδικό οξύ	Acido fusidico	ゲミフロキサシン	Kwas fusydynowy	Ácido fusídico	Фузидовая кислота	Ácido fusídico	Fusidinsyra	Fusidik asit	Фузидова кислота
-Gatifloxacin	FALSE	TRUE	TRUE	FALSE	加替沙星	Gatifloxacin	Gatifloxacine	Gatifloxacine	Gatifloxacin	Gatifloxacin	Gatifloxacina	ゲンタマイシン	Gatifloxacin	Gatifloxacin	Гатифлоксацин	Gatifloxacina	Gatifloxacin	Gatifloksasin	Гатифлоксацин
-Gemifloxacin	FALSE	TRUE	TRUE	FALSE	吉非沙星	Gemifloxacin	Gemifloxacine	Gemifloxacine	Gemifloxacin	Gemifloxacin	Gemifloxacina	グレパフロキサシン	Gemifloksacyna	Gemifloxacin	Гемифлоксацин	Gemifloxacina	Gemifloxacin	Gemifloksasin	Геміфлоксацин
-Gentamicin	FALSE	TRUE	TRUE	FALSE	庆大霉素	Gentamicin	Gentamicine	Gentamicine	Gentamicin	Gentamicin	Gentamicina	ハチマイシン	Gentamicin	Gentamicina	Гентамицин	Gentamicina	Gentamicin	Gentamisin	Гентаміцин
-Grepafloxacin	FALSE	TRUE	TRUE	FALSE	格雷帕沙星	Grepafloxacin	Grepafloxacine	Grepafloxacine	Grepafloxacin	Grepafloxacin	Grepafloxacina	ヘタシリン	Grepafloksacyna	Grepafloxacin	Грепафлоксацин	Grepafloxacina	Grepafloxacin	Grepafloksasin	Грепафлоксацин
-Hachimycin	FALSE	TRUE	TRUE	FALSE	哈奇霉素	Hachimycin	Hachimycine	Hachimycine	Hachimycin	Hachimycin	Hachimycin	イミペネム／シラスタチン	Hachimycin	Hachimycin	Хатимицин	Hachimycin	Hachimycin	Hachimycin	Хачиміцин
-Hetacillin	FALSE	TRUE	TRUE	FALSE	赫拉西林	Hetacillin	Hetacilline	Hétacilline	Hetacillin	Hetacillin	Hetacillin	イノシン・プラノベックス	Hetacylina	Hetacillin	Гетациллин	Hetacilina	Hetacillin	Hetasilin	Гетацилін
-Imipenem/cilastatin	FALSE	TRUE	TRUE	FALSE	亚胺培南/西司他丁	Imipenem/cilastatin	Imipenem/enzymremmer	Imipénème/cilastatine	Imipenem/Cilastatin	Ιμιπενέμη/σιλαστατίνη	Imipenem/cilastatina	イセパマイシン	Imipenem/cilastatyna	Imipenem/coteltelatina	Имипенем/циластатин	Imipenem/cilastatina	Imipenem/cilastatin	İmipenem/silastatin	Іміпенем/циластатин
-Inosine pranobex	FALSE	TRUE	TRUE	FALSE	肌苷帕诺贝斯	Inosin pranobex	Inosiplex	Inosine pranobex	Inosin-Pranobex	Ινοσίνη pranobex	Inosina pranobex	イソコナゾール	Pranobeks inozyny	Pranobex inosine	Инозин пранобекс	Inosina pranobex	Inosin pranobex	İnosin pranobeks	Інозин пранобекс
-Isepamicin	FALSE	TRUE	TRUE	FALSE	伊西帕米星	Isepamicin	Isepamicine	Isepamicine	Isepamicin	Isepamicin	Isepamicina	イソニアジド	Isepamicin	Isepamicina	Исепамицин	Isepamicina	Isepamicin	İzepamisin	Ізепаміцин
-Isoconazole	FALSE	TRUE	TRUE	FALSE	氨甲蝶呤	Isoconazol	Isoconazol	Isoconazole	Isoconazol	Ισοκοναζόλη	Isoconazolo	イトラコナゾール	Izokonazol	Isoconazole	Изоконазол	Isoconazol	Isokonazol	İzokonazol	Ізоконазол
-Isoniazid	FALSE	TRUE	TRUE	FALSE	伊索尼克酸	Isoniazid	Isoniazide	Isoniazide	Isoniazid	Ιζονιαζίδη	Isoniazide	ホサマイシン	Izoniazyd	Isoniazid	Изониазид	Isoniazida	Isoniazid	İzoniazid	Ізоніазид
-Itraconazole	FALSE	TRUE	TRUE	FALSE	伊曲康唑	Itraconazol	Itraconazol	Itraconazole	Itraconazol	Ιτρακοναζόλη	Itraconazolo	カナマイシン	Itrakonazol	Itraconazole	Итраконазол	Itraconazol	Itrakonazol	İtrakonazol	Ітраконазол
-Josamycin	FALSE	TRUE	TRUE	FALSE	肌注	Josamycin	Josamycine	Josamycine	Josamycin	Josamycin	Josamicina	ケトコナゾール	Josamycin	Josamycin	Джозамицин	Josamicina	Josamycin	Josamycin	Джозаміцин
-Kanamycin	FALSE	TRUE	TRUE	FALSE	卡那霉素	Kanamycin	Kanamycine	Kanamycine	Kanamycin	Kanamycin	Kanamicina	レボフロキサシン	Kanamycin	Kanamycin	Канамицин	Kanamicina	Kanamycin	Kanamisin	Канаміцин
-Ketoconazole	FALSE	TRUE	TRUE	FALSE	酮康唑	Ketoconazol	Ketoconazol	Kétoconazole	Ketoconazol	Κετοκοναζόλη	Ketoconazolo	リンコマイシン	Ketokonazol	Ketoconazole	Кетоконазол	Ketoconazol	Ketokonazol	Ketokonazol	Кетоконазол
-Levofloxacin	FALSE	TRUE	TRUE	FALSE	氧氟沙星	Levofloxacin	Levofloxacine	Lévofloxacine	Levofloxacin	Λεβοφλοξασίνη	Levofloxacina	ロメフロキサシン	Levofloxacin	Levofloxacin	Левофлоксацин	Levofloxacina	Levofloxacin	Levofloksasin	Левофлоксацин
-Lincomycin	FALSE	TRUE	TRUE	FALSE	林可霉素	Lincomycin	Lincomycine	Lincomycine	Lincomycin	Lincomycin	Lincomicina	リゾチーム	Lincomycyna	Lincomycin	Линкомицин	Lincomicina	Lincomycin	Lincomycin	Лінкоміцин
-Lomefloxacin	FALSE	TRUE	TRUE	FALSE	洛美沙星	Lomefloxacin	Lomefloxacine	Loméfloxacine	Lomefloxacin	Λομεφλοξασίνη	Lomefloxacina	マンデル酸	Lomefloxacin	Lomefloxacin	Ломефлоксацин	Lomefloxacina	Lomefloxacin	Lomefloksasin	Ломефлоксацин
-Lysozyme	FALSE	TRUE	TRUE	FALSE	硫酸钠	Lysozym	Lysozym	Lysozyme	Lysozym	Λυσοζύμη	Lisozima	メタンピシリン	Lizozym	Lysozyme	Лизоцим	Lisozima	Lysozym	Lizozim	Лізоцим
-Mandelic acid	FALSE	TRUE	TRUE	FALSE	扁桃酸	Mandelinsyre	Amandelzuur	Acide mandélique	Mandelsäure	Μανδελικό οξύ	Acido mandelico	メチシリン	Kwas migdałowy	Ácido mandélico	Мандаловая кислота	Ácido mandélico	Mandelsyra	Mandelik asit	Мигдалева кислота
-Metampicillin	FALSE	TRUE	TRUE	FALSE	氨苄青霉素	Metampicillin	Metampicilline	Métampicilline	Metampicillin	Metampicillin	Metampicillina	メチサゾン	Metampicylina	Metampicilina	Метампициллин	Metampicilina	Metampicillin	Metampisilin	Метампіцилін
-Meticillin	FALSE	TRUE	TRUE	FALSE	美西林	Meticillin	Meticilline	Méticilline	Meticillin	Μετικιλλίνη	Meticillina	メトロニダゾール	Meticillin	Meticillin	Метициллин	Meticilina	Meticillin	Metisilin	Метицилін
-Metisazone	FALSE	TRUE	TRUE	FALSE	氨甲喋呤	Metisazon	Metisazon	Métisazone	Metisazon	Μετισαζόνη	Metisazone	メスロシリン	Metisazon	Metisazone	Метисазон	Metisazona	Metisazon	Metisazon	Метисазон
-Metronidazole	FALSE	TRUE	TRUE	FALSE	甲硝唑	Metronidazol	Metronidazol	Métronidazole	Metronidazol	Μετρονιδαζόλη	Metronidazolo	ミカファンギン	Metronidazol	Metronidazol	Метронидазол	Metronidazol	Metronidazol	Metronidazol	Метронідазол
-Mezlocillin	FALSE	TRUE	TRUE	FALSE	氨甲蝶呤	Mezlocillin	Mezlocilline	Mezlocilline	Mezlocillin	Mezlocillin	Mezlocillina	ミコナゾール	Mezlocillin	Mezlocillin	Мезлоциллин	Mezlocilina	Mezlocillin	Mezlosilin	Мезлоцилін
-Micafungin	FALSE	TRUE	TRUE	FALSE	咪蒙灵	Micafungin	Micafungine	Micafungine	Micafungin	Micafungin	Micafungin	ミデカマイシン	Micafungin	Micafungin	Микафунгин	Micafungina	Micafungin	Mikafungin	Мікафунгін
-Miconazole	FALSE	TRUE	TRUE	FALSE	米康唑	Miconazol	Miconazol	Miconazole	Miconazol	Miconazole	Miconazolo	ミオカマイシン	Mikonazol	Miconazole	Миконазол	Miconazol	Miconazol	Mikonazol	Міконазол
-Midecamycin	FALSE	TRUE	TRUE	FALSE	咪康霉素	Midecamycin	Midecamycine	Midecamycine	Midecamycin	Μεδεκαμυκίνη	Midecamicina	モキシフロキサシン	Midecamycin	Midecamycin	Мидекамицин	Midecamicina	Midecamycin	Midecamycin	Мідекаміцин
-Miocamycin	FALSE	TRUE	TRUE	FALSE	米卡霉素	Miocamycin	Miocamycine	Miocamycine	Miocamycin	Miocamycin	Miocamicina	ムピロシン	Miocamycin	Miocamicina	Миокамицин	Miocamycin	Miocamycin	Miocamycin	Міокаміцин
-Moxifloxacin	FALSE	TRUE	TRUE	FALSE	莫西沙星	Moxifloxacin	Moxifloxacine	Moxifloxacine	Moxifloxacin	Moxifloxacin	Moxifloxacin	ナリディキシック酸	Moxifloxacin	Moxifloxacina	Моксифлоксацин	Moxifloxacina	Moxifloxacin	Moksifloksasin	Моксифлоксацин
-Mupirocin	FALSE	TRUE	TRUE	FALSE	莫匹罗星	Mupirocin	Mupirocine	Mupirocine	Mupirocin	Mupirocin	Mupirocina	ネオマイシン	Mupirocyna	Mupirocina	Мупироцин	Mupirocina	Mupirocin	Mupirosin	Мупіроцин
-Nalidixic acid	FALSE	TRUE	TRUE	FALSE	萘啶酸	Nalidixinsyre	Nalidixinezuur	Acide nalidixique	Nalidixinsäure	Ναλιδιξικό οξύ	Acido nalidixico	ネチルミシン	Kwas nalidyksowy	Ácido nalidíxico	Налидиксовая кислота	Ácido nalidíxico	Nalidixinsyra	Nalidiksik asit	Налідиксова кислота
-Neomycin	FALSE	TRUE	TRUE	FALSE	霉素	Neomycin	Neomycine	Néomycine	Neomycin	Νεομυκίνη	Neomicina	ニトロフラントイン	Neomycyna	Neomicina	Неомицин	Neomicina	Neomycin	Neomisin	Неоміцин
-Netilmicin	FALSE	TRUE	TRUE	FALSE	硝苯地平	Netilmicin	Netilmicine	Netilmicine	Netilmicin	Netilmicin	Netilmicin	ノルフロキサシン	Netilmicin	Netilmicin	Нетилмицин	Netilmicina	Netilmicin	Netilmisin	Нетилміцин
-Nitrofurantoin	FALSE	TRUE	TRUE	FALSE	硝呋太尔	Nitrofurantoin	Nitrofurantoine	Nitrofurantoïne	Nitrofurantoin	Νιτροφουραντοΐνη	Nitrofurantoina	ノボビオシン	Nitrofurantoina	Nitrofurantoína	Нитрофурантоин	Nitrofurantoína	Nitrofurantoin	Nitrofurantoin	Нітрофурантоїн
-Norfloxacin	FALSE	TRUE	TRUE	FALSE	诺氟沙星	Norfloxacin	Norfloxacine	Norfloxacine	Norfloxacin	Norfloxacin	Norfloxacina	ナイスタチン	Norfloxacin	Norfloxacin	Норфлоксацин	Norfloxacina	Norfloxacin	Norfloksasin	Норфлоксацин
-Novobiocin	FALSE	TRUE	TRUE	FALSE	诺氟沙星	Novobiocin	Novobiocine	Novobiocine	Novobiocin	Novobiocin	Novobiocin	オフロキサシン	Nowobiocyna	Novobiocin	Новобиоцин	Novobiocina	Novobiocin	Novobiocin	Новобіоцин
-Nystatin	FALSE	TRUE	TRUE	FALSE	囊肿	Nystatin	Nystatine	Nystatine	Nystatin	Νυστατίνη	Nystatin	オレアンドマイシン	Nystatyna	Nystatin	Нистатин	Nistatina	Nystatin	Nistatin	Ністатин
-Ofloxacin	FALSE	TRUE	TRUE	FALSE	氧氟沙星	Ofloxacin	Ofloxacine	Ofloxacine	Ofloxacin	Ofloxacin	Ofloxacin	オルニダゾール	Ofloxacin	Ofloxacin	Офлоксацин	Ofloxacina	Ofloxacin	Ofloksasin	Офлоксацин
-Oleandomycin	FALSE	TRUE	TRUE	FALSE	奥兰多霉素	Oleandomycin	Oleandomycine	Oleandomycine	Oleandomycin	Oleandomycin	Oleandomicina	オキサシリン	Oleandomycin	Oleandomicina	Олеандомицин	Oleandomicina	Oleandomycin	Oleandomisin	Олеандоміцин
-Ornidazole	FALSE	TRUE	TRUE	FALSE	奥硝唑	Ornidazol	Ornidazol	Ornidazole	Ornidazol	Ορνιδαζόλη	Ornidazolo	オキソリニック酸	Ornidazol	Ornidazole	Орнидазол	Ornidazol	Ornidazol	Ornidazol	Орнідазол
-Oxacillin	FALSE	TRUE	TRUE	FALSE	奥沙西林	Oxacillin	Oxacilline	Oxacilline	Oxacillin	Οξακιλλίνη	Oxacillina	オキシテトラサイクリン	Oksacylina	Oxacillin	Оксациллин	Oxacilina	Oxacillin	Oksasilin	Оксацилін
-Oxolinic acid	FALSE	TRUE	TRUE	FALSE	氧氟沙星	Oxolinsyre	Oxolinezuur	Acide oxolinique	Oxolinsäure	Οξολινικό οξύ	Acido ossolinico	パズフロキサシン	Kwas oksolinowy	Ácido oxolínico	Оксолиновая кислота	Ácido oxolínico	Oxolinsyra	Oksolinik asit	Оксолінова кислота
-Oxytetracycline	FALSE	TRUE	TRUE	FALSE	土四环素	Oxytetracyclin	Oxytetracycline	Oxytétracycline	Oxytetracyclin	Οξυτετρακυκλίνη	Ossitetraciclina	ペフロキサシン	Oksytetracyklina	Oxitetraciclina	Окситетрациклин	Oxitetraciclina	Oxytetracyklin	Oksitetrasiklin	Окситетрациклін
-Pazufloxacin	FALSE	TRUE	TRUE	FALSE	帕唑沙星	Pazufloxacin	Pazufloxacine	Pazufloxacine	Pazufloxacin	Παζουφλοξασίνη	Pazufloxacin	ペナメシリン	Pazufloxacin	Pazufloxacin	Пазуфлоксацин	Pazufloxacina	Pazufloxacin	Pazufloksasin	Пазуфлоксацин
-Pefloxacin	FALSE	TRUE	TRUE	FALSE	培氟沙星	Pefloxacin	Pefloxacine	Péfloxacine	Pefloxacin	Pefloxacin	Pefloxacina	ペニシリン	Pefloksacyna	Pefloxacin	Пефлоксацин	Pefloxacina	Pefloxacin	Pefloksasin	Пефлоксацин
-Penamecillin	FALSE	TRUE	TRUE	FALSE	青霉素	Penamecillin	Penamecilline	Pénamécilline	Penamecillin	Πεναμεσιλλίνη	Penamecillina	フェネチシリン	Penamecylina	Penamecilina	Пенамециллин	Penamecilina	Penamecillin	Penamecillin	Пенамецилін
-Penicillin	FALSE	TRUE	TRUE	FALSE	青霉素	Penicillin	Penicilline	Pénicilline	Penicillin	Πενικιλλίνη	Penicillina	フェノキシメチルペニシリン	Penicylina	Penicilina	Пенициллин	Penicilina	Penicillin	Penisilin	Пеніцилін
-Pheneticillin	FALSE	TRUE	TRUE	FALSE	菲尼克斯	Pheneticillin	Feneticilline	Phénéticilline	Pheneticillin	Φαινετικιλλίνη	Feneticillina	ピペミド酸	Fenicylina	Pheneticillin	Фенетициллин	Feneticilina	Feneticillin	Pheneticillin	Фенетіцилін
-Phenoxymethylpenicillin	FALSE	TRUE	TRUE	FALSE	苯氧甲基青霉素	Phenoxymethylpenicillin	Fenoxymethylpenicilline	Phénoxyméthylpénicilline	Phenoxymethylpenicillin	Φαινοξυμεθυλοπενικιλλίνη	Fenossimetilpenicillina	ピペラシリン	Fenoksymetylopenicylina	Fenoximetilpenicilina	Феноксиметилпенициллин	Fenoximetilpenicilina	Fenoximetylpenicillin	Fenoksimetilpenisilin	Феноксиметилпеніцилін
-Pipemidic acid	FALSE	TRUE	TRUE	FALSE	吡哌酸	Pipemidinsyre	Pipemidinezuur	Acide pipémidique	Pipemidinsäure	Πιπεμιδικό οξύ	Acido pipemidico	ピペラシリン／β-ラクタマーゼ阻害剤	Kwas pipemidowy	Ácido pipemídico	Пипемидовая кислота	Ácido pipemídico	Pipemidinsyra	Pipemidik asit	Піпемідова кислота
-Piperacillin	FALSE	TRUE	TRUE	FALSE	哌拉西林	Piperacillin	Piperacilline	Pipéracilline	Piperacillin	Πιπερακιλλίνη	Piperacillina	ピロミジン酸	Piperacillin	Piperacilina	Пиперациллин	Piperacilina	Piperacillin	Piperasilin	Піперацилін
-Piperacillin/beta-lactamase inhibitor	FALSE	TRUE	TRUE	FALSE	哌拉西林/β-内酰胺酶抑制剂	Piperacillin/beta-lactamasehæmmer	Piperacilline/enzymremmer	Pipéracilline/inhib. de bêta-lactamase	Piperacillin/Beta-Lactamase-Hemmer	Πιπερακιλλίνη/αναστολέας της β-λακταμάσης	Piperacillina/inib. d. beta-lattamasi	ピバンピシリン	Piperacylina/inhibitor beta-laktamazy	Piperacilina/inibid. da beta-lactamase	Пиперациллин/ингибитор бета-лактамазы	Piperacilina/inhib. de la beta-lactamasa	Piperacillin/betalaktamashämmare	Piperasilin/beta-laktamaz inhibitörü	Піперацилін/інгібітор бета-лактамаз
-Piromidic acid	FALSE	TRUE	TRUE	FALSE	吡罗米酸	Piromidinsyre	Piromidinezuur	Acide piromidique	Piromidinsäure	Πηρομιδικό οξύ	Acido piromidico	ポリミキシンB	Kwas piromidowy	Ácido piromídico	Пиромидовая кислота	Ácido piromídico	Piromidinsyra	Piromidik asit	Піромідова кислота
-Pivampicillin	FALSE	TRUE	TRUE	FALSE	哌拉西林	Pivampicillin	Pivampicilline	Pivampicilline	Pivampicillin	Pivampicillin	Pivampicillina	ポサコナゾール	Pivampicillin	Pivampicilina	Пивампициллин	Pivampicilina	Pivampicillin	Pivampisilin	Півампіцилін
-Polymyxin B	FALSE	TRUE	TRUE	FALSE	多粘菌素B	Polymyxin B	Polymyxine B	Polymyxine B	Polymyxin B	Πολυμυξίνη Β	Polimixina B	プリスチナマイシン	Polimyksyna B	Polimixina B	Полимиксин В	Polimixina B	Polymyxin B	Polimiksin B	Поліміксин B
-Posaconazole	FALSE	TRUE	TRUE	FALSE	泊沙康唑	Posaconazol	Posaconazol	Posaconazole	Posaconazol	Ποσακοναζόλη	Posaconazolo	プロカインベンジルペニシリン	Posaconazol	Posaconazole	Посаконазол	Posaconazol	Posakonazol	Posakonazol	Позаконазол
-Pristinamycin	FALSE	TRUE	TRUE	FALSE	普利司特霉素	Pristinamycin	Pristinamycine	Pristinamycine	Pristinamycin	Πριστιναμυκίνη	Pristinamicina	プロピシリン	Pristinamycin	Pristinamicina	Пристинамицин	Pristinamicina	Pristinamycin	Pristinamisin	Пристинаміцин
-Procaine benzylpenicillin	FALSE	TRUE	TRUE	FALSE	普鲁卡因青霉素	Prokainbenzylpenicillin	Benzylpenicillineprocaine	Procaïne benzylpénicilline	Procain-Benzylpenicillin	Βενζυλοπενικιλλίνη προκαΐνης	Procaina benzilpenicillina	プルリフロキサシン	Benzylopenicylina prokainowa	Procaína benzilpenicilina	Прокаин бензилпенициллин	Bencilpenicilina procaína	Prokainbenzylpenicillin	Prokain benzilpenisilin	Прокаїну бензилпеніцилін
-Propicillin	FALSE	TRUE	TRUE	FALSE	普利西林	Propicillin	Propicilline	Propicilline	Propicillin	Προπικιλλίνη	Propicillina	キヌプリスチン／ダルフォプリスチン	Propicylina	Propicilina	Пропициллин	Propicilina	Propicillin	Propisilin	Пропіцилін
-Prulifloxacin	FALSE	TRUE	TRUE	FALSE	普利沙星	Prulifloxacin	Prulifloxacine	Prulifloxacine	Prulifloxacin	Προυλιφλοξασίνη	Prulifloxacina	リボスタマイシン	Prulifloksacyna	Prulifloxacina	Прулифлоксацин	Prulifloxacina	Prulifloxacin	Prulifloksasin	Пруліфлоксацин
-Quinupristin/dalfopristin	FALSE	TRUE	TRUE	FALSE	奎宁斯丁/达夫普利斯丁	Quinupristin/dalfopristin	Quinupristine/dalfopristine	Quinupristine/dalfopristine	Quinupristin/Dalfopristin	Κινουπριστίνη/δαλφοπριστίνη	Quinupristina/dalfopristina	リファブチン	Quinupristin/dalfopristin	Quinupristin/dalfopristin	Квинупристин/дальфопристин	Quinupristina/dalfopristina	Quinupristin/dalfopristin	Quinupristin/dalfopristin	Хінупристин/дальфопристин
-Ribostamycin	FALSE	TRUE	TRUE	FALSE	利波霉素	Ribostamycin	Ribostamycine	Ribostamycine	Ribostamycin	Ριμποσταμυκίνη	Ribostamicina	リファンピシン	Ribostamycyna	Ribostamicina	Рибостамицин	Ribostamicina	Ribostamycin	Ribostamisin	Рибостаміцин
-Rifabutin	FALSE	TRUE	TRUE	FALSE	利福布汀	Rifabutin	Rifabutine	Rifabutine	Rifabutin	Rifabutin	Rifabutina	リファンピシン／ピラジナミド／エタンブトール／イソニアジド	Rifabutin	Rifabutin	Рифабутин	Rifabutina	Rifabutin	Rifabutin	Рифабутин
-Rifampicin	FALSE	TRUE	TRUE	FALSE	利福平	Rifampicin	Rifampicine	Rifampicine	Rifampicin	Ριφαμπικίνη	Rifampicina	リファンピシン／ピラジナミド／イソニアジド	Rifampicyna	Rifampicina	Рифампицин	Rifampicina	Rifampicin	Rifampisin	Рифампіцин
-Rifampicin/pyrazinamide/ethambutol/isoniazid	FALSE	TRUE	TRUE	FALSE	利福平/吡嗪酰胺/乙胺丁醇/异烟肼	Rifampicin/pyrazinamid/ethambutol/isoniazid	Rifampicine/pyrazinamide/ethambutol/isoniazide	Rifampicine/pyrazinamide/éthambutol/isoniazide	Rifampicin/Pyrazinamid/Ethambutol/Isoniazid	Ριφαμπικίνη/πυραζιναμίδη/αιθαμβουτόλη/ισονιαζίδη	Rifampicina/pirazinamide/etambutolo/isoniazide	リファンピシン／イソニアジド	Rifampicyna/pirazinamid/etambutol/izoniazyd	Rifampicina/pirazinamida/etambutol/isoniazida	Рифампицин/пиразинамид/этамбутол/исониазид	Rifampicina/pirazinamida/etambutol/isoniazida	Rifampicin/pyrazinamid/ethambutol/isoniazid	Rifampisin/pirazinamid/etambutol/izoniazid	Рифампіцин/піразинамід/етамбутол/ізоніазид
-Rifampicin/pyrazinamide/isoniazid	FALSE	TRUE	TRUE	FALSE	利福平/吡嗪酰胺/异烟肼	Rifampicin/pyrazinamid/isoniazid	Rifampicine/pyrazinamide/isoniazide	Rifampicine/pyrazinamide/isoniazide	Rifampicin/Pyrazinamid/Isoniazid	Ριφαμπικίνη/πυραζιναμίδη/ισονιαζίδη	Rifampicina/pirazinamide/isoniazide	リファマイシン	Rifampicyna/pirazynamid/izoniazyd	Rifampicina/pirazinamida/isoniazida	Рифампицин/пиразинамид/изониазид	Rifampicina/pirazinamida/isoniazida	Rifampicin/pyrazinamid/isoniazid	Rifampisin/pirazinamid/izoniazid	Рифампіцин/піразинамід/ізоніазид
-Rifampicin/isoniazid	FALSE	TRUE	TRUE	FALSE	利福平/异烟肼	Rifampicin/isoniazid	Rifampicine/isoniazide	Rifampicine/isoniazide	Rifampicin/Isoniazid	Ριφαμπικίνη/ισονιαζίδη	Rifampicina/isoniazide	リファキシミン	Rifampicyna/izoniazyd	Rifampicina/isoniazida	Рифампицин/изониазид	Rifampicina/isoniazida	Rifampicin/isoniazid	Rifampisin/izoniazid	Рифампіцин/ізоніазид
-Rifamycin	FALSE	TRUE	TRUE	FALSE	利福霉素	Rifamycin	Rifamycine	Rifamycine	Rifamycin	Ριφαμυκίνη	Rifamicina	ロキタマイシン	Rifamycyna	Rifamycin	Рифамицин	Rifamicina	Rifamycin	Rifamisin	Рифаміцин
-Rifaximin	FALSE	TRUE	TRUE	FALSE	利福昔明	Rifaximin	Rifaximine	Rifaximine	Rifaximin	Rifaximin	Rifaximina	ロソキサシン	Rifaximin	Rifaximin	Рифаксимин	Rifaximina	Rifaximin	Rifaximin	Рифаксимін
-Rokitamycin	FALSE	TRUE	TRUE	FALSE	罗奇霉素	Rokitamycin	Rokitamycine	Rokitamycine	Rokitamycin	Ροκιταμυκίνη	Rokitamicina	ロキシスロマイシン	Rokitamycyna	Rokitamycin	Рокитамицин	Rokitamicina	Rokitamycin	Rokitamisin	Рокітаміцин
-Rosoxacin	FALSE	TRUE	TRUE	FALSE	罗红霉素	Rosoxacin	Rosoxacine	Rosoxacine	Rosoxacin	Rosoxacin	Rosoxacina	ルフロキサシン	Rosoxacin	Rosoxacina	Розоксацин	Rosoxacina	Rosoxacin	Rosoxacin	Розоксацин
-Roxithromycin	FALSE	TRUE	TRUE	FALSE	罗红霉素	Roxithromycin	Roxitromycine	Roxithromycine	Roxithromycin	Roxithromycin	Roxitromicina	シソマイシン	Roksytromycyna	Roxitromicina	Рокситромицин	Roxitromicina	Roxitromycin	Roxithromycin	Рокситроміцин
-Rufloxacin	FALSE	TRUE	TRUE	FALSE	罗氟沙星	Rufloxacin	Rufloxacine	Rufloxacine	Rufloxacin	Rufloxacin	Rufloxacina	アミノサリチル酸ソーダ	Rufloxacin	Rufloxacin	Руфлоксацин	Rufloxacina	Rufloxacin	Rufloksasin	Руфлоксацин
-Sisomicin	FALSE	TRUE	TRUE	FALSE	西索米星	Sisomicin	Sisomicine	Sisomicine	Sisomicin	Sisomicin	Sisomicina	スパルフロキサシン	Sisomicin	Sisomicina	Сизомицин	Sisomicina	Sisomicin	Sisomisin	Сизоміцин
-Sodium aminosalicylate	FALSE	TRUE	TRUE	FALSE	氨基水杨酸钠	Natriumaminosalicylat	Aminosalicylzuur	Aminosalicylate de sodium	Natrium-Aminosalicylat	Αμινοσαλικυλικό νάτριο	Sodio aminosalicilato	スペクチノマイシン	Aminosalicylan sodu	Aminosalicilato de sódio	Аминосалицилат натрия	Aminosalicilato de sodio	Natriumaminosalicylat	Sodyum aminosalisilat	Натрію аміносаліцилат
-Sparfloxacin	FALSE	TRUE	TRUE	FALSE	氨水杨酸钠	Sparfloxacin	Sparfloxacine	Sparfloxacine	Sparfloxacin	Sparfloxacin	Sparfloxacina	スピラマイシン	Sparfloxacin	Sparfloxacin	Спарфлоксацин	Esparfloxacina	Sparfloxacin	Sparfloksasin	Спарфлоксацин
-Spectinomycin	FALSE	TRUE	TRUE	FALSE	大观霉素	Spectinomycin	Spectinomycine	Spectinomycine	Spectinomycin	Spectinomycin	Spectinomycin	スピラマイシン／メトロニダゾール	Spektynomycyna	Spectinomycin	Спектиномицин	Espectinomicina	Spektinomycin	Spektinomisin	Спектиноміцин
-Spiramycin	FALSE	TRUE	TRUE	FALSE	斯皮拉菌素	Spiramycin	Spiramycine	Spiramycine	Spiramycin	Σπιραμυκίνη	Spiramicina	ブドウ球菌免疫グロブリン	Spiramycyna	Spiramycin	Спирамицин	Espiramicina	Spiramycin	Spiramisin	Спіраміцин
-Spiramycin/metronidazole	FALSE	TRUE	TRUE	FALSE	螺旋霉素/甲硝唑	Spiramycin/metronidazol	Spiramycine/metronidazol	Spiramycine/métronidazole	Spiramycin/Metronidazol	Σπιραμυκίνη/μετρονιδαζόλη	Spiramicina/metronidazolo	ストレプトデュオシン	Spiramycyna/metronidazol	Spiramycin/metronidazol	Спирамицин/метронидазол	Espiramicina/metronidazol	Spiramycin/metronidazol	Spiramisin/metronidazol	Спіраміцин/метронідазол
-Staphylococcus immunoglobulin	FALSE	TRUE	TRUE	FALSE	葡萄球菌免疫球蛋白	Stafylokok-immunglobulin	Stafylokokkenimmunoglobuline	Immunoglobuline staphylococcique	Staphylococcus-Immunoglobulin	Σταφυλόκοκκος ανοσοσφαιρίνη	Immunoglobulina per stafilococco	ストレプトマイシン	Immunoglobulina gronkowcowa	Imunoglobulina de Staphylococcus	Стафилококковый иммуноглобулин	Inmunoglobulina estafilocócica	Immunoglobulin mot stafylokocker	Staphylococcus immünoglobulin	Стафілококовий імуноглобулін
-Streptoduocin	FALSE	TRUE	TRUE	FALSE	链霉素	Streptoduocin	Streptoduocine	Streptoduocine	Streptoduocin	Streptoduocin	Streptoduocin	ストレプトマイシン／イソニアジド	Streptoduocin	Estreptoduocina	Стрептодуоцин	Estreptoduocina	Streptoduocin	Streptoduosin	Стрептодуоцин
-Streptomycin	FALSE	TRUE	TRUE	FALSE	霉素	Streptomycin	Streptomycine	Streptomycine	Streptomycin	Στρεπτομυκίνη	Streptomicina	スルベニシリン	Streptomycyna	Streptomycin	Стрептомицин	Estreptomicina	Streptomycin	Streptomisin	Стрептоміцин
-Streptomycin/isoniazid	FALSE	TRUE	TRUE	FALSE	链霉素/异烟肼	Streptomycin/isoniazid	Streptomycine/isoniazide	Streptomycine/isoniazide	Streptomycin/Isoniazid	Στρεπτομυκίνη/ισονιαζίδη	Streptomicina/isoniazide	スルファダイアジン／テトロキソプリム	Streptomycyna/izoniazyd	Streptomicina/isoniazida	Стрептомицин/изониазид	Estreptomicina/isoniazida	Streptomycin/isoniazid	Streptomisin/izoniazid	Стрептоміцин/ізоніазид
-Sulbenicillin	FALSE	TRUE	TRUE	FALSE	磺苄西林	Sulbenicillin	Sulbenicilline	Sulbenicilline	Sulbenicillin	Sulbenicillin	Sulbenicillina	スルファジアジン／トリメトプリム	Sulbenicylina	Sulbenicilina	Сульбенициллин	Sulbenicilina	Sulbenicillin	Sulbenisilin	Сульбеніцилін
-Sulfadiazine/tetroxoprim	FALSE	TRUE	TRUE	FALSE	磺胺嘧啶/四氧嘧啶	Sulfadiazin/tetroxoprim	Sulfadiazine/tetroxoprim	Sulfadiazine/tetroxoprime	Sulfadiazin/Tetroxoprim	Σουλφαδιαζίνη/τετροξοπρίμη	Sulfadiazina/tetroxoprim	スルファジミジン／トリメトプリム	Sulfadiazyna/tetroksoprim	Sulfadiazina/tetroxoprim	Сульфадиазин/тетроксоприм	Sulfadiazina/tetroxoprim	Sulfadiazin/tetroxoprim	Sülfadiazin/tetroksoprim	Сульфадіазин/тетроксоприм
-Sulfadiazine/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺嘧啶/三甲氧苄啶	Sulfadiazin/trimethoprim	Sulfadiazine/trimethoprim	Sulfadiazine/triméthoprime	Sulfadiazin/Trimethoprim	Σουλφαδιαζίνη/τριμεθοπρίμη	Sulfadiazina/trimetoprim	スルファフラゾール	Sulfadiazyna/trimetoprim	Sulfadiazina/trimethoprim	Сульфадиазин/триметоприм	Sulfadiazina/trimetoprima	Sulfadiazin/trimetoprim	Sülfadiazin/trimetoprim	Сульфадіазин/триметоприм
-Sulfadimidine/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺嘧啶/三甲氧苄啶	Sulfadimidin/trimethoprim	Sulfadimidine/trimethoprim	Sulfadimidine/triméthoprime	Sulfadimidin/Trimethoprim	Σουλφαδιμιδίνη/τριμεθοπρίμη	Sulfadimidina/trimetoprim	スルファイソジミジン	Sulfadimidyna/trimetoprim	Sulfadimidina/trimethoprim	Сульфадимидин/триметоприм	Sulfadimidina/trimetoprima	Sulfadimidin/trimetoprim	Sülfadimidin/trimetoprim	Сульфадимідин/триметоприм
-Sulfafurazole	FALSE	TRUE	TRUE	FALSE	磺胺呋喃唑	Sulfafurazol	Sulfafurazol	Sulfafurazole	Sulfafurazol	Σουλφαφουραζόλη	Sulfafurazolo	スルファレン	Sulfafurazol	Sulfafurazole	Сульфафуразол	Sulfafurazol	Sulfafurazol	Sülfafurazol	Сульфафуразол
-Sulfaisodimidine	FALSE	TRUE	TRUE	FALSE	磺胺二甲嘧啶	Sulfaisodimidin	Sulfisomidine	Sulfaisodimidine	Sulfaisodimidin	Sulfaisodimidine	Sulfaisodimidina	スルファマゾン	Sulfaisodimidine	Sulfaisodimidina	Сульфаизодимидин	Sulfaisodimidina	Sulfaisodimidin	Sülfaizodimidin	Сульфаізодимідин
-Sulfalene	FALSE	TRUE	TRUE	FALSE	磺胺类药物	Sulfalen	Sulfaleen	Sulfalène	Sulfalene	Sulfalene	Sulfalene	スルファメラジン／トリメトプリム	Sulfalen	Sulfaleno	Сульфален	Sulfaleno	Sulfen	Sülfalen	Сульфален
-Sulfamazone	FALSE	TRUE	TRUE	FALSE	磺胺脒	Sulfamazon	Sulfamazon	Sulfamazone	Sulfamazon	Sulfamazone	Sulfamazone	スルファメチゾール	Sulfamazon	Sulfamazona	Сульфамазон	Sulfamazona	Sulfamazon	Sülfamazon	Сульфамазон
-Sulfamerazine/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺脒/三甲氧苄氨嘧啶	Sulfamerazin/trimethoprim	Sulfamerazine/trimethoprim	Sulfamérazine/triméthoprime	Sulfamerazin/Trimethoprim	Σουλφαμεραζίνη/τριμεθοπρίμη	Sulfamerazina/trimetoprim	スルファメトキサゾール	Sulfamerazyna/trimetoprim	Sulfamerazina/trimethoprim	Сульфамеразин/триметоприм	Sulfamerazina/trimetoprima	Sulfamerazin/trimetoprim	Sülfamerazin/trimetoprim	Сульфамеразин/триметоприм
-Sulfamethizole	FALSE	TRUE	TRUE	FALSE	磺胺甲基咪唑	Sulfamethizol	Sulfamethizol	Sulfaméthizole	Sulfamethizol	Sulfamethizole	Sulfamethizolo	スルファメトキサゾール／トリメトプリム	Sulfamethizole	Sulfametizole	Сульфаметизол	Sulfametozol	Sulfamethizol	Sülfametizol	Сульфаметізол
-Sulfamethoxazole	FALSE	TRUE	TRUE	FALSE	磺胺甲噁唑	Sulfamethoxazol	Sulfamethoxazol	Sulfaméthoxazole	Sulfamethoxazol	Σουλφαμεθοξαζόλη	Sulfametossazolo	スルファメトキシジアジン	Sulfametoksazol	Sulfamethoxazole	Сульфаметоксазол	Sulfametoxazol	Sulfametoxazol	Sülfametoksazol	Сульфаметоксазол
-Sulfamethoxazole/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺甲噁唑/三甲氧苄啶	Sulfamethoxazol/trimethoprim	Sulfamethoxazol/trimethoprim	Sulfaméthoxazole/triméthoprime	Sulfamethoxazol/Trimethoprim	Σουλφαμεθοξαζόλη/τριμεθοπρίμη	Sulfametossazolo/trimetoprim	スルファメトロール／トリメトプリム	Sulfametoksazol/trimetoprim	Sulfametoxazol/trimethoprim	Сульфаметоксазол/триметоприм	Sulfametoxazol/trimetoprima	Sulfametoxazol/trimetoprim	Sülfametoksazol/trimetoprim	Сульфаметоксазол/триметоприм
-Sulfametoxydiazine	FALSE	TRUE	TRUE	FALSE	磺胺甲噁唑	Sulfametoxydiazin	Sulfamethoxydiazine	Sulfamétoxydiazine	Sulfametoxydiazin	Sulfametoxydiazine	Sulfametoxydiazine	スルファモキソール	Sulfametoksydiazyna	Sulfametoxidiazina	Сульфаметоксидиазин	Sulfametoxidiazina	Sulfametoxydiazin	Sulfametoksidiyazin	Сульфаметоксидіазин
-Sulfametrole/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺甲醚/三甲氧嘧啶	Sulfametrol/trimethoprim	Sulfametrol/trimethoprim	Sulfamétrole/triméthoprime	Sulfametrole/Trimethoprim	Σουλφαμετρόλη/τριμεθοπρίμη	Sulfametrole/trimetoprim	スルファモキソール／トリメトプリム	Sulfametrol/trimetoprim	Sulfametrole/trimethoprim	Сульфаметрол/триметоприм	Sulfametrol/trimetoprima	Sulfametrol/trimetoprim	Sülfametrol/trimetoprim	Сульфаметрол/триметоприм
-Sulfamoxole	FALSE	TRUE	TRUE	FALSE	磺胺甲噁唑	Sulfamoxol	Sulfamoxol	Sulfamoxole	Sulfamoxol	Sulfamoxole	Sulfamoxolo	スルファペリン	Sulfamoksol	Sulfamoxole	Сульфамоксол	Sulfamoxole	Sulfamoxol	Sülfamoksol	Сульфамоксол
-Sulfamoxole/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺甲噁唑/三甲氧苄啶	Sulfamoxol/trimethoprim	Sulfamoxol/trimethoprim	Sulfamoxole/triméthoprime	Sulfamoxol/Trimethoprim	Σουλφαμοξόλη/τριμεθοπρίμη	Sulfamoxolo/trimetoprim	スルファフェナゾール	Sulfamoksol/trimetoprim	Sulfamoxole/trimethoprim	Сульфамоксол/триметоприм	Sulfamoxol/trimetoprima	Sulfamoxol/trimetoprim	Sülfamoksol/trimetoprim	Сульфамоксол/триметоприм
-Sulfaperin	FALSE	TRUE	TRUE	FALSE	磺胺类药物	Sulfaperin	Sulfaperine	Sulfapérine	Sulfaperin	Sulfaperin	Sulfaperin	スルファチアゾール	Sulfaperin	Sulfaperin	Сульфаперин	Sulfametoxazol	Sulfaperin	Sülfaperin	Сульфаперин
-Sulfaphenazole	FALSE	TRUE	TRUE	FALSE	磺胺苯吡唑	Sulfaphenazol	Sulfafenazol	Sulfaphénazole	Sulfaphenazol	Σουλφαφαιναζόλη	Sulfafenazolo	スルファチオ尿素	Sulfafenazol	Sulfafenazol	Сульфафеназол	Sulfafenazol	Sulfafenazol	Sülfafenazol	Сульфафеназол
-Sulfathiazole	FALSE	TRUE	TRUE	FALSE	磺胺噻唑	Sulfathiazol	Sulfathiazol	Sulfathiazole	Sulfathiazol	Sulfathiazole	Sulfathiazole	スルタミシリン	Sulfatiazol	Sulfatazol	Сульфатиазол	Sulfatiazol	Sulfathiazol	Sulfathiazole	Сульфатіазол
-Sulfathiourea	FALSE	TRUE	TRUE	FALSE	磺胺硫脲	Sulfathiourea	Sulfathioureum	Sulfathiourée	Sulfathioharnstoff	Sulfathiourea	Sulfathiourea	タランピシリン	Sulfathiourea	Sulfathiourea	Сульфатиомочевина	Sulfathiourea	Sulfatiourea	Sulfathiourea	Сульфатіосечовина
-Sultamicillin	FALSE	TRUE	TRUE	FALSE	苏打米林	Sultamicillin	Sultamicilline	Sultamicilline	Sultamicillin	Sultamicillin	Sultamicillina	テイコプラニン	Sultamicillin	Sultamicillin	Сультамициллин	Sultamicilina	Sultamicillin	Sultamicillin	Сультаміцилін
-Talampicillin	FALSE	TRUE	TRUE	FALSE	塔拉比西林	Talampicillin	Talampicilline	Talampicilline	Talampicillin	Talampicillin	Talampicillina	テリスロマイシン	Talampicylina	Talampicilina	Талампициллин	Talampicilina	Talampicillin	Talampisilin	Талампіцилін
-Teicoplanin	FALSE	TRUE	TRUE	FALSE	泰科普兰素	Teicoplanin	Teicoplanine	Teicoplanine	Teicoplanin	Teicoplanin	Teicoplanina	テマフロキサシン	Teicoplanin	Teicoplanin	Тейкопланин	Teicoplanina	Teicoplanin	Teikoplanin	Тейкопланін
-Telithromycin	FALSE	TRUE	TRUE	FALSE	泰利霉素	Telithromycin	Telitromycine	Télithromycine	Telithromycin	Τελιθρομυκίνη	Telitromicina	テモシリン	Telitromycyna	Telitromicina	Телитромицин	Telitromicina	Telitromycin	Telitromisin	Телітроміцин
-Temafloxacin	FALSE	TRUE	TRUE	FALSE	氨甲环酸	Temafloxacin	Temafloxacine	Temafloxacine	Temafloxacin	Temafloxacin	Temafloxacina	テノホビルジソプロキシル	Temafloksacyna	Temafloxacin	Темафлоксацин	Temafloxacina	Temafloxacin	Temafloksasin	Темафлоксацин
-Temocillin	FALSE	TRUE	TRUE	FALSE	氨甲蝶呤	Temocillin	Temocilline	Temocillin	Temocillin	Temocillin	Temocillina	テリジドン	Temocillin	Temocillin	Темоциллин	Temocilina	Temocillin	Temocillin	Темоцилін
-Tenofovir disoproxil	FALSE	TRUE	TRUE	FALSE	特诺福韦酯	Tenofovir disoproxil	Tenofovir	Tenofovir disoproxil	Tenofovir Disoproxil	Tenofovir disoproxil	Tenofovir disoproxil	チアンフェニコール	Tenofovir disoproxil	Tenofovir disoproxil	Тенофовир дизопроксил	Tenofovir disoproxil	Tenofovir disoproxil	Tenofovir disoproksil	Тенофовір дизопроксил
-Terizidone	FALSE	TRUE	TRUE	FALSE	特立兹酮	Terizidon	Terizidon	Terizidone	Terizidon	Terizidone	Terizidone	チオアセタゾン／イソニアジド	Terizidon	Terizidone	Теризидон	Terizidona	Terizidon	Terizidon	Теризидон
-Thiamphenicol	FALSE	TRUE	TRUE	FALSE	硫苯尼考	Thiamphenicol	Thiamfenicol	Thiamphénicol	Thiamphenicol	Thiamphenicol	Tiamfenicolo	チカルシリン	Tiamfenikol	Tiamfenicol	Тиамфеникол	Tiamfenicol	Tiamfenikol	Thiamphenicol	Тіамфенікол
-Thioacetazone/isoniazid	FALSE	TRUE	TRUE	FALSE	硫乙酰唑酮/异烟肼	Thioacetazon/isoniazid	Thioacetazon/isoniazide	Thioacétazone/isoniazide	Thioacetazon/Isoniazid	Θειοακεταζόνη/ισονιαζίδη	Tioacetazone/isoniazide	チカルシリン／β-ラクタマーゼ阻害剤	Tioacetazon/izoniazyd	Thioacetazone/isoniazid	Тиоацетазон/изониазид	Tioacetazona/isoniazida	Thioacetazon/isoniazid	Tiyoasetazon/izoniazid	Тіоацетазон/ізоніазид
-Ticarcillin	FALSE	TRUE	TRUE	FALSE	替卡西林	Ticarcillin	Ticarcilline	Ticarcilline	Ticarcillin	Τικαρκιλλίνη	Ticarcillina	チカルシリン／クラブラン酸	Ticarcillin	Ticarcilina	Тикарциллин	Ticarcilina	Ticarcillin	Ticarcillin	Тикарцилін
-Ticarcillin/beta-lactamase inhibitor	FALSE	TRUE	TRUE	FALSE	替卡西林/β-内酰胺酶抑制剂	Ticarcillin/beta-lactamasehæmmer	Ticarcilline/enzymremmer	Ticarcilline/inhib. de bêta-lactamase	Ticarcillin/Beta-Lactamase-Hemmer	Τικαρκιλλίνη/αναστολέας της β-λακταμάσης	Ticarcillina/inib. d. beta-lattamasi	チニダゾール	Tikarcylina/inhibitor beta-laktamazy	Ticarcilina/inibid. da beta-lactamase	Тикарциллин/ингибитор бета-лактамазы	Ticarcilina/inhib. de la betalactamasa	Ticarcillin/beta-laktamashämmare	Tikarsilin/beta-laktamaz inhibitörü	Тикарцилін/інгібітор бета-лактамаз
-Ticarcillin/clavulanic acid	FALSE	TRUE	TRUE	FALSE	替卡西林/克拉维酸	Ticarcillin/clavulansyre	Ticarcilline/clavulaanzuur	Ticarcilline/acide clavulanique	Ticarcillin/Clavulansäure	Τικαρκιλλίνη/κλαβουλανικό οξύ	Ticarcillina/acido clavulanico	トブラマイシン	Tikarcylina/kwas klawulanowy	Ticarcilina/ácido clavulanico	Тикарциллин/клавулановая кислота	Ticarcilina/ácido clavulánico	Ticarcillin/clavulansyra	Tikarsilin/klavulanik asit	Тикарцилін/клавуланова кислота
-Tinidazole	FALSE	TRUE	TRUE	FALSE	替尼唑	Tinidazol	Tinidazol	Tinidazole	Tinidazol	Τινιδαζόλη	Tinidazolo	トリメトプリム／スルファメトキサゾール	Tinidazol	Tinidazole	Тинидазол	Tinidazol	Tinidazol	Tinidazol	Тинідазол
-Tobramycin	FALSE	TRUE	TRUE	FALSE	妥布霉素	Tobramycin	Tobramycine	Tobramycine	Tobramycin	Τομπραμυκίνη	Tobramicina	トロレアンドマイシン	Tobramycyna	Tobramycin	Тобрамицин	Tobramicina	Tobramycin	Tobramisin	Тобраміцин
-Trimethoprim/sulfamethoxazole	FALSE	TRUE	TRUE	FALSE	三甲氧嘧啶/磺胺甲恶唑	Trimethoprim/sulfamethoxazol	Cotrimoxazol	Triméthoprime/sulfaméthoxazole	Trimethoprim/Sulfamethoxazol	Τριμεθοπρίμη/σουλφαμεθοξαζόλη	Trimetoprim/sulfametossazolo	トロバフロキサシン	Trimetoprim/sulfametoksazol	Trimethoprim/sulfametoxazol	Триметоприм/сульфаметоксазол	Trimetoprima/sulfametoxazol	Trimetoprim/sulfametoxazol	Trimetoprim/sülfametoksazol	Триметоприм/сульфаметоксазол
-Troleandomycin	FALSE	TRUE	TRUE	FALSE	托拉多霉素	Troleandomycin	Troleandomycine	Troleandomycine	Troleandomycin	Τρολεαντομυκίνη	Troleandomicina	バンコマイシン	Troleandomycyna	Troleandomicina	Тролеандомицин	Troleandomicina	Troleandomycin	Troleandomisin	Тролеандоміцин
-Trovafloxacin	FALSE	TRUE	TRUE	FALSE	特戊沙星	Trovafloxacin	Trovafloxacine	Trovafloxacine	Trovafloxacin	Τροβαφλοξασίνη	Trovafloxacin	ボリコナゾール	Trovafloxacin	Trovafloxacin	Тровафлоксацин	Trovafloxacina	Trovafloxacin	Trovafloksasin	Тровафлоксацин
-Vancomycin	FALSE	TRUE	TRUE	FALSE	唑啉酮	Vancomycin	Vancomycine	Vancomycine	Vancomycin	Βανκομυκίνη	Vancomicina	アミノグリコシド系抗生物質	Wankomycyna	Vancomycin	Ванкомицин	Vancomicina	Vancomycin	Vankomisin	Ванкоміцин
-Voriconazole	FALSE	TRUE	TRUE	FALSE	伏立康唑	Voriconazol	Voriconazol	Voriconazole	Voriconazol	Voriconazole	Voriconazolo	アンフェニコール	Worikonazol	Voriconazol	Вориконазол	Voriconazol	Vorikonazol	Vorikonazol	Вориконазол
-Aminoglycosides	FALSE	TRUE	TRUE	FALSE	氨基糖苷类	Aminoglykosider	Aminoglycosiden	Aminoglycosides	Aminoglykoside	Αμινογλυκοσίδες	Aminoglicosidi	抗真菌剤／抗真菌剤	Aminoglikozydy	Aminoglycosides	Аминогликозиды	Aminoglucósidos	Aminoglykosider	Aminoglikozidler	Аміноглікозиди
-Amphenicols	FALSE	TRUE	TRUE	FALSE	安息香醇	Amphenicoler	Amfenicolen	Amphénicols	Amphenicole	Αμφενικόλες	Amphenicols	抗マイコバクテリア薬	Amfenikol	Anfenicóis	Амфениколы	Anfenicoles	Amfenikoler	Amphenicols	Амфеніколи
-Antifungals/antimycotics	FALSE	TRUE	TRUE	FALSE	抗真菌药/抗真菌药	Antimykotika/antimykotika	Antifungica/antimycotica	Antifongiques/antimycotiques	Antimykotika/Antimykotika	Αντιμυκητιασικά/αντιμυκητιασικά	Antifungini/antimicotici	β-ラクタム系/ペニシリン系	Środki przeciwgrzybicze/przeciwmikotyczne	Antifúngicos/antimicóticos	Противогрибковые препараты/антимикотики	Antifúngicos/antimicóticos	Antimykotika/antimykotika	Antifungaller/antimikotikler	Протигрибкові засоби/антимікотики
-Antimycobacterials	FALSE	TRUE	TRUE	FALSE	抗霉菌素类	Antimycobakterier	Antimycobacteriele middelen	Antimycobactériens	Antimykobakterielle Mittel	Αντιμυκοβακτηριακά	Antimicobatterici	セファロスポリン系（第1世代）	Środki przeciwgrzybicze	Antimycobacterials	Антимикобактериальные препараты	Antimicrobianos	Antimykobakterier	Antimikobakteriyeller	Засоби, що діють на мікобактерії
-Beta-lactams/penicillins	FALSE	TRUE	TRUE	FALSE	β-内酰胺类/青霉素类	Beta-lactamer/penicilliner	Beta-lactams/penicillines	Bêta-lactamines/pénicillines	Beta-Lactame/Penicilline	Β-λακτάμες/πενικιλλίνες	Beta-lattami/penicilline	セファロスポリン（第2世代）	Beta-laktamy/penicyliny	Beta-lactâmicas/penicilinas	Бета-лактамы/пенициллины	Beta-lactámicos/penicilinas	Beta-laktamer/penicilliner	Beta-laktamlar/penisilinler	Бета-лактами/пеніциліни
-Cephalosporins (1st gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素类（第一代）	Cefalosporiner (1. gen.)	Cefalosporines (1e gen.)	Céphalosporines (1ère génération)	Cephalosporine (1. Gen.)	Κεφαλοσπορίνες (1ης γενιάς)	Cefalosporine (1° gen.)	セファロスポリン（第3世代）	Cefalosporyny (1. gen.)	Cefalosporinas (1º género)	Цефалоспорины (1-го пок.)	Cefalosporinas (1er gen.)	Kefalosporiner (första gen.)	Sefalosporinler (1. kuşak)	Цефалоспорини (1 пок.)
-Cephalosporins (2nd gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素类（第二代）	Cefalosporiner (2. gen.)	Cefalosporines (2e gen.)	Céphalosporines (2ème génération)	Cephalosporine (2. Gen.)	Κεφαλοσπορίνες (2ης γενιάς)	Cefalosporine (2° gen.)	セファロスポリン（第4世代）	Cefalosporyny (2. gen.)	Cefalosporinas (2ª gen.)	Цефалоспорины (2-го пок.)	Cefalosporinas (2do gen.)	Kefalosporiner (andra gen.)	Sefalosporinler (2. kuşak)	Цефалоспорини (2 пок.)
-Cephalosporins (3rd gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素类（第三代）	Cefalosporiner (3. gen.)	Cefalosporines (3e gen.)	Céphalosporines (3ème génération)	Cephalosporine (3. Gen.)	Κεφαλοσπορίνες (3ης γενιάς)	Cefalosporine (3° gen.)	セファロスポリン（第5世代）	Cefalosporyny (3 gen.)	Cefalosporinas (3ª gen.)	Цефалоспорины (3-го пок.)	Cefalosporinas (3er gen.)	Kefalosporiner (tredje gen.)	Sefalosporinler (3. kuşak)	Цефалоспорини (3 пок.)
-Cephalosporins (4th gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素类（第四代）	Cefalosporiner (4. gen.)	Cefalosporines (4e gen.)	Céphalosporines (4ème génération)	Cephalosporine (4. Gen.)	Κεφαλοσπορίνες (4ης γενιάς)	Cefalosporine (4° gen.)	セファロスポリン（未分類の世代）	Cefalosporyny (4 gen.)	Cefalosporinas (4.ª gen.)	Цефалоспорины (4-го пок.)	Cefalosporinas (4ª gen.)	Kefalosporiner (4:e gen.)	Sefalosporinler (4. kuşak)	Цефалоспорини (4 пок.)
-Cephalosporins (5th gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素（第五代）	Cefalosporiner (5. gen.)	Cefalosporines (5e gen.)	Céphalosporines (5e gén.)	Cephalosporine (5. Gen.)	Κεφαλοσπορίνες (5ης γενιάς)	Cefalosporine (5° gen.)	セファロスポリン	Cefalosporyny (5. gen.)	Cefalosporinas (5.ª gen.)	Цефалоспорины (5-го пок.)	Cefalosporinas (5º gen.)	Kefalosporiner (5:e gen.)	Sefalosporinler (5. kuşak)	Цефалоспорини (5 пок.)
-Cephalosporins (unclassified gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素类（未分类的一代）	Cefalosporiner (uklassificeret gen.)	Cefalosporines (ongeclassificeerd)	Céphalosporines (genre non classifié)	Cephalosporine (unklassifiziert)	Κεφαλοσπορίνες (μη ταξινομημένη γενιά)	Cefalosporine (gen. non classificato)	糖ペプチド系	Cefalosporyny (niesklasyfikowana gen.)	Cefalosporinas (não classificado gen.)	Цефалоспорины (неклассифицированный род)	Cefalosporinas (gen. no clasificado)	Kefalosporiner (oklassificerad gen.)	Sefalosporinler (sınıflandırılmamış nesil)	Цефалоспорини (некласифікованого пок.)
-Cephalosporins	FALSE	TRUE	TRUE	FALSE	头孢菌素类	Cefalosporiner	Cefalosporines	Céphalosporines	Cephalosporine	Κεφαλοσπορίνες	Cefalosporine	マクロライド系／リンコサミド系	Cefalosporyny	Cefalosporinas	Цефалоспорины	Cefalosporinas	Kefalosporiner	Sefalosporinler	Цефалоспорини
-Glycopeptides	FALSE	TRUE	TRUE	FALSE	糖肽类药物	Glykopeptider	Glycopeptiden	Glycopeptides	Glykopeptide	Γλυκοπεπτίδια	Glicopeptidi	その他の抗菌薬	Glikopeptydy	Glycopeptides	Гликопептиды	Glicopéptidos	Glykopeptider	Glikopeptitler	Глікопептиди
-Macrolides/lincosamides	FALSE	TRUE	TRUE	FALSE	大环内酯类/林可酰胺类	Makrolider/lincosamider	Macroliden/lincosamiden	Macrolides/lincosamides	Makrolide/Linkosamide	Μακρολίδια/λινκοσαμίδια	Macrolidi/lincosamidi	ポリミキシン	Makrolidy/linkozamidy	Macrolides/lincosamidas	Макролиды/линкозамиды	Macrólidos/lincosamidas	Makrolider/linkosamider	Makrolidler/linkozamidler	Макроліди/лінкозаміди
-Other antibacterials	FALSE	TRUE	TRUE	FALSE	其他抗菌剂	Andre antibakterielle stoffer	Overige antibiotica	Autres antibactériens	Andere Antibiotika	Άλλα αντιβακτηριακά	Altri antibatterici	キノロン	Inne środki przeciwbakteryjne	Outros antibacterianos	Другие антибактериальные препараты	Otros antibacterianos	Andra antibakteriella medel	Diğer antibakteriyeller	Інші антибактеріальні засоби
-Polymyxins	FALSE	TRUE	TRUE	FALSE	多粘菌素类	Polymyxiner	Polymyxines	Polymyxines	Polymyxine	Πολυμυξίνες	Polimixine	ポリミキシン	Polimyksyny	Polimixinas	Полимиксины	Polimixinas	Polymyxiner	Polimiksinler	Поліміксини
-Quinolones	FALSE	TRUE	TRUE	FALSE	喹诺酮类	Kinoloner	Quinolonen	Quinolones	Quinolone	Κινολόνες	Chinoloni	キノロン	Quinolony	Quinolones	Хинолоны	Quinolonas	Kinoloner	Kinolonlar	Хінолони
+pattern	regular_expr	case_sensitive	affect_ab_name	affect_mo_name	zh	cs	da	nl	fi	fr	de	el	it	ja	no	pl	pt	ro	ru	es	sv	tr	uk
+language name English	FALSE	FALSE	FALSE	FALSE	Chinese	Czech	Danish	Dutch	Finnish	French	German	Greek	Italian	Japanese	Norwegian	Polish	Portuguese	Romanian	Russian	Spanish	Swedish	Turkish	Ukrainian
+language name	FALSE	FALSE	FALSE	FALSE	汉语	Čeština	Dansk	Nederlands	Suomi	Français	Deutsch	Ελληνικά	Italiano	日本語	Norsk	Polski	Português	Română	Русский	Español	Svenska	Türkçe	Українська
+Coagulase-negative Staphylococcus	TRUE	TRUE	FALSE	TRUE	凝固酶阴性葡萄球菌	Koaguláza-negativní stafylokok	Koagulase-negative stafylokokker	Coagulase-negatieve Staphylococcus	Koagulaasinegatiivinen stafylokokki	Staphylococcus à coagulase négative	Koagulase-negative Staphylococcus	Σταφυλόκοκκος με αρνητική πηκτικότητα	Staphylococcus negativo coagulasi	コアグラーゼ陰性ブドウ球菌	Koagulase-negative stafylokokker	Staphylococcus koagulazoujemny	Staphylococcus coagulase negativo	Stafilococ coagulazo-negativ	Коагулазоотрицательный стафилококк	Staphylococcus coagulasa negativo	Koagulasnegativa stafylokocker	Koagülaz-negatif Stafilokok	Коагулазонегативний стафілокок
+Coagulase-positive Staphylococcus	TRUE	TRUE	FALSE	TRUE	凝固酶阳性葡萄球菌	Koagulázopozitivní stafylokok	Koagulase-positive stafylokokker	Coagulase-positieve Staphylococcus	Koagulaasipositiivinen stafylokokki	Staphylococcus à coagulase positif	Koagulase-positive Staphylococcus	Σταφυλόκοκκος θετικός στην πήξη	Staphylococcus positivo coagulasi	コアグラーゼ陽性ブドウ球菌	Koagulase-positive stafylokokker	Staphylococcus koagulazo-dodatni	Staphylococcus coagulase positivo	Stafilococul coagulazo-pozitiv	Коагулазоположительный стафилококк	Staphylococcus coagulasa positivo	Koagulaspositiva stafylokocker	Koagülaz-pozitif Stafilokok	Коагулазопозитивний стафілокок
+Beta-haemolytic Streptococcus	TRUE	TRUE	FALSE	TRUE	β-溶血性链球菌	Beta-hemolytický streptokok	Beta-haemolytiske streptokokker	Beta-hemolytische Streptococcus	Beeta-hemolyyttinen streptokokki	Streptococcus Bêta-hémolytique	Beta-hämolytischer Streptococcus	Β-αιμολυτικός στρεπτόκοκκος	Streptococcus Beta-emolitico	ベータ溶血性レンサ球菌	Beta-hemolytiske streptokokker	Streptococcus beta-hemolityczny	Streptococcus Beta-hemolítico	Streptococ beta-hemolitic	Бета-гемолитический стрептококк	Streptococcus Beta-hemolítico	Beta-hemolytiska streptokocker	Beta-hemolitik Streptokok	Бета-гемолітичний стрептокок
+unknown Gram-negatives	TRUE	TRUE	FALSE	TRUE	不明革兰氏阴性菌	neznámé gramnegativní	ukendte Gram-negative	onbekende Gram-negatieven	tuntemattomat gramnegatiiviset	Gram négatifs inconnus	unbekannte Gramnegativen	άγνωστοι αρνητικοί κατά Gram	Gram negativi sconosciuti	不明なグラム陰性菌	ukjent Gram-negative	Nieznane bakterie Gram-ujemne	Gram negativos desconhecidos	Gram-negative necunoscute	неизвестные грамотрицательные	Gram negativos desconocidos	okända gramnegativa bakterier	bilinmeyen Gram-negatifler	невідомі грамнегативні
+unknown Gram-positives	TRUE	TRUE	FALSE	TRUE	不明革兰氏阳性菌	neznámé grampozitivní	ukendte Gram-positive	onbekende Gram-positieven	tuntemattomat grampositiiviset	Gram positifs inconnus	unbekannte Grampositiven	άγνωστοι θετικοί κατά Gram	Gram positivi sconosciuti	未知のグラム陽性菌	ukjent Gram-positive	Nieznane bakterie Gram-dodatnie	Gram positivos desconhecidos	Gram-pozitive necunoscute	неизвестные грамположительные	Gram positivos desconocidos	okända Gram-positiva	bilinmeyen Gram-pozitifler	невідомі грампозитивні
+unknown fungus	TRUE	TRUE	FALSE	TRUE	未知真菌	neznámé houby	ukendt svamp	onbekende schimmel	tuntematon sieni	champignon inconnu	unbekannter Pilze	άγνωστος μύκητας	fungo sconosciuto	未知真菌	ukjent sopp	Nieznany grzyb	fungo desconhecido	ciuperci necunoscute	неизвестный грибок	hongo desconocido	Okänd svamp	bilinmeyen mantar	невідомий гриб
+unknown yeast	TRUE	TRUE	FALSE	TRUE	未知酵母菌	neznámé kvasinky	ukendt gær	onbekende gist	tuntematon hiiva	levure inconnue	unbekannte Hefe	άγνωστος ζυμομύκητας	lievito sconosciuto	未知酵母	ukjent gjær	Nieznany drożdżak	levedura desconhecida	drojdie necunoscută	неизвестные дрожжи	levadura desconocida	Okänd jäst	bilinmeyen maya	невідомі дріжджі
+unknown name	TRUE	TRUE	FALSE	TRUE	不明名称	neznámý název	ukendt navn	onbekende naam	tuntematon nimi	nom inconnu	unbekannte Name	άγνωστο όνομα	nome sconosciuto	名称未知	ukjent navn	nieznana nazwa	nome desconhecido	nume necunoscut	неизвестное название	nombre desconocido	okänt namn	bilinmeyen isim	невідома назва
+unknown kingdom	TRUE	TRUE	FALSE	TRUE	未知王国	neznámá říše	ukendt kongerige	onbekend koninkrijk	tuntematon valtakunta	règme inconnu	unbekanntes Reich	άγνωστο βασίλειο	regno sconosciuto	未知の王国	ukjent rike	nieznane królestwo	reino desconhecido	regn necunoscut	неизвестное царство	reino desconocido	okänt rike	bilinmeyen krallık	невідоме царство
+unknown phylum	TRUE	TRUE	FALSE	TRUE	未知门	neznámý fylém	ukendt stamme	onbekend fylum	tuntematon kantasuku	embranchement inconnu	unbekannter Stamm	άγνωστο φύλο	phylum sconosciuto	未知の門	ukjent fylum	nieznany azyl	filo desconhecido	phylum necunoscut	неизвестный филум	filo desconocido	okänt fylum	bilinmeyen filum	невідомий відділ
+unknown class	TRUE	TRUE	FALSE	TRUE	未知类	neznámá třída	ukendt klasse	onbekende klasse	tuntematon luokka	classe inconnue	unbekannte Klasse	άγνωστη τάξη	classe sconosciuta	未知のクラス	ukjent klasse	Nieznana klasa	classe desconhecida	clasă necunoscută	неизвестный класс	clase desconocida	okänd klass	bilinmeyen sınıf	невідомий клас
+unknown order	TRUE	TRUE	FALSE	TRUE	未知目	neznámý řád	ukendt orden	onbekende orde	tuntematon järjestys	ordre inconnu	unbekannte Ordnung	άγνωστη τάξη	ordine sconosciuto	未知の目	ukjent orden	nieznany rząd	ordem desconhecido	ordin necunoscut	неизвестный порядок	orden desconocido	okänd ordning	bilinmeyen sipariş	невідомий порядок
+unknown family	TRUE	TRUE	FALSE	TRUE	未知科	neznámá čeleď	ukendt familie	onbekende familie	tuntematon perhe	famille inconnue	unbekannte Familie	άγνωστη οικογένεια	famiglia sconosciuta	未知ファミリー	ukjent familie	nieznana rodzina	família desconhecida	familie necunoscută	неизвестное семейство	familia desconocida	okänd familj	bilinmeyen aile	невідома родина
+unknown genus	TRUE	TRUE	FALSE	TRUE	未知属	neznámý rod	ukendt slægt	onbekend geslacht	tuntematon suku	genre inconnu	unbekannte Gattung	άγνωστο γένος	genere sconosciuto	未知属	ukjent slekt	nieznany rodzaj	gênero desconhecido	gen necunoscut	неизвестный род	género desconocido	okänt släkte	bilinmeyen cins	невідомий рід
+unknown species	TRUE	TRUE	FALSE	TRUE	未知种	neznámý druh	ukendt art	onbekende soort	tuntematon laji	espèce inconnue	unbekannte Art	άγνωστο είδος	specie sconosciute	未知種	ukjent art	nieznany gatunek	espécies desconhecida	specie necunoscută	неизвестный вид	especie desconocida	okänd art	bilinmeyen türler	невідомий вид
+unknown subspecies	TRUE	TRUE	FALSE	TRUE	未知亚种	neznámý poddruh	ukendt underart	onbekende ondersoort	tuntematon alalaji	sous-espèce inconnue	unbekannte Unterart	άγνωστο υποείδος	sottospecie sconosciute	亜種不明	ukjent underart	nieznany podgatunek	subespécies desconhecida	subspecie necunoscută	неизвестный подвид	subespecie desconocida	okänd underart	bilinmeyen alt türler	невідомий підвид
+unknown rank	TRUE	TRUE	FALSE	TRUE	未知等级	neznámý stupeň	ukendt rang	onbekende rang	tuntematon sukuluokka	rang inconnu	unbekannter Rang	άγνωστη τάξη	grado sconosciuto	未知ランク	ukjent rang	nieznany stopień	classificação desconhecido	rang necunoscut	неизвестный ранг	rango desconocido	okänd rang	bilinmeyen rütbe	невідомий ранг
+unknown	FALSE	TRUE	FALSE	FALSE	未知	neznámý	ukendt	onbekend	tuntematon	inconnu	unbekannt	άγνωστο	sconosciuto	未知	ukjent	nieznany	desconhecido	necunoscut	неизвестно	desconocido	okänd	bilinmiyor	невідомий
+ group 	TRUE	TRUE	FALSE	TRUE	 组 	 skupina 	 gruppe 	 groep 	 ryhmä 	 groupe 	 Gruppe 	 ομάδα 	 gruppo 	 グループ	 gruppe 	 grupa 	 grupo 	 grup 	 группа 	 grupo 	 grupp 	 Grup 	 група
+ Group 	TRUE	TRUE	FALSE	TRUE	 组 	 Skupina 	 Gruppe 	 groep 	 Ryhmä 	 groupe 	 Gruppe 	 Ομάδα 	 Gruppo 	 グループ	 Gruppe 	 Grupa 	 Grupo 	 Grup 	 Группа 	 Grupo 	 Grupp 	 Grup 	 Група
+CoNS	FALSE	TRUE	FALSE	TRUE		KNS	KNS	CNS	KNS		KNS	CoNS		グラム陰性	KNS	CoNS		SCN	КОС	SCN	KNS	KNS	КНС
+CoPS	FALSE	TRUE	FALSE	TRUE		KPS	KPS	CPS	KPS		KPS	CoPS		グラム陽性	KPS	CoPS		SCP	КПС	SCP	KPS	KPS	КПС
+Gram-negative	TRUE	TRUE	FALSE	FALSE	革兰氏阴性	Gramnegativní	Gram-negativ	Gram-negatief	Gramnegatiiviset	Gram négatif	Gramnegativ	Αρνητικό κατά Gram	Gram negativo	^細菌$	Gram-negativ	Gram-ujemne	Gram negativo	Gram-negativ	Грамотрицательные	Gram negativo	Gram-negativ	Gram-negatif	Грамнегативні
+Gram-positive	TRUE	TRUE	FALSE	FALSE	革兰氏阳性	Grampozitivní	Gram-positiv	Gram-positief	Gram-positiiviset	Gram positif	Grampositiv	Θετικό κατά Gram	Gram positivo	^真菌$	Gram-positive	Gram-dodatnie	Gram positivo	Gram-pozitiv	Грамположительные	Gram positivo	Gram-positiv	Gram-pozitif	Грампозитивні
+^Bacteria$	TRUE	TRUE	FALSE	FALSE	细菌	Bakterie	Bakterier	Bacteriën	Bakteerit	Bactéries	Bakterien	Βακτήρια	Batteri	酵母	Bakterier	Bakterie	Bactérias	Bacterii	Бактерии	Bacterias	Bakterier	Bakteri	Бактерії
+^Fungi$	TRUE	TRUE	FALSE	FALSE	真菌	Houby	Støbeforme	Schimmels	Sienet	Champignons	Pilze	Μύκητες	Funghi	原生動物	Sopp	Grzyby	Fungos	Ciuperci	Грибы	Hongos	Svampar	Mantarlar	Гриби
+^Yeasts$	TRUE	TRUE	FALSE	FALSE	酵母菌	Kvasinky	Gær	Gisten	Hiivat	Levures	Hefen	Ζυμομύκητες	Lieviti	バイオグループ	Gjærsopp	Drożdże	Leveduras	Drojdii	Животные	Levaduras	Jästdjur	Mayalar	Дріжджі
+^Protozoa$	TRUE	TRUE	FALSE	FALSE	^原生动物$	Prvoci	Protozoer	Protozoën	Alkueläimet	Protozoaires	Protozoen	Πρωτόζωα	Protozoi	生物型	Protozoer	Protozoa	Protozoários	Protozoare	Протозоа	Protozoarios	Protozoer	Protozoa	Найпростіші
+biogroup	TRUE	TRUE	FALSE	FALSE	生物群	bioskupina	biogruppe	biogroep	Bioryhmä	biogroupe	Biogruppe	βιοομάδα	biogruppo	植物型	biogruppe	biogrupa	biogrupo	biogrupul	биогруппа	biogrupo	biogrupp	biyogrup	біогрупа
+biotype	TRUE	TRUE	FALSE	FALSE	生物型	biotyp	biotype		biotyyppi		Biotyp	βιότυπος	biotipo	([([ ]*?))) グループ	biotype	biotyp	biótipo	biotip	биотип	biotipo	biotyp	biyotip	біотип
+vegetative	TRUE	TRUE	FALSE	FALSE	无性系	vegetativní	vegetativ	vegetatief	kasvullinen	végétatif	vegetativ	βλαστικός	vegetativo	([[ ]*?)グループ	vegetativ	wegetatywna	vegetativo	vegetativ	вегетативный	vegetativo	vegetativ	vejetatif	вегетативний
+([([ ]*?)group	TRUE	TRUE	FALSE	FALSE	([([]*?)组	\\1skupina	\\1gruppe	\\1groep	\\1ryhmä	\\1groupe	\\1Gruppe	([([ ]*?)ομάδα	\\1gruppo	\\1グループ	\\1gruppe	([([ ]*?)grupa	\\1grupo	\\1grup	\\1группа	\\1grupo	\\1grupp	([([ ]*?)grup	\\1група
+([([ ]*?)Group	TRUE	TRUE	FALSE	FALSE	([([]*?)组	\\1Skupina	\\1Gruppe	\\1Groep	\\1Ryhmä	\\1Groupe	\\1Gruppe	([([ ]*;)ομάδα	\\1Gruppo	\\1グループ	\\1Gruppe	([([ ]*?)Grupa	\\1Grupo	\\1Grup	\\1Группа	\\1Grupo	\\1Grupp	([([ ]*?)Grup	\\1Група
+no .*growth	FALSE	FALSE	FALSE	FALSE	无.*生长	žádný .*růst	ingen .*vækst	geen .*groei	ei .*kasvua	pas .*croissance	keine(|n|m|r|s)|nicht .*wachstum	όχι .*αύξηση	sem .*crescimento	成長なし	nei .*vekst	brak .*wzrostu	sem .*crescimento	fără creștere	отсутствие.*роста	no .*crecimientonon	ingen .*tillväxt	büyüme yok	відсутність .*росту
+no|not	FALSE	FALSE	FALSE	FALSE	不|不	ne	nej|ikke	geen|niet	ei	non	keine?	no|not	sem	no|ない	nei|ikke	nie|nie	sem	nu	нет?	no|sin	nej|inte	hayır|değil|hayir|degil	ні
+Intermediate	TRUE	FALSE	FALSE	FALSE	中级	Meziprodukt	Mellemliggende	Intermediair	Väliaikainen		Mittlere	Ενδιάμεση		中間体	Mellomliggende	Pośrednia		Intermediar		Intermedio	Mellanliggande	Orta seviye	Знижена чутливість
+Susceptible, incr. exp.	FALSE	TRUE	FALSE	FALSE	易感，暴露增加	Vnímavý, zvýš. expozice	Modtagelig, øget eksp.	Gevoelig bij verh. blootstelling	Altis, lisääntynyt altist.		Empfindlich, erh Belastung	Ευάλωτος, αυξημένη έκθεση		感受性、曝露量増加	Mottakelig, økt eksp.	Podatne, zwiększone narażenie		Susceptibil, exp. crescută		Susceptible, mayor exposición	Mottaglig, inkr. exponering	Duyarlı, enk. maruziyet	Чутливий до підвищеної експозиції
+susceptible, incr. exp.	FALSE	TRUE	FALSE	FALSE	易感，接触增加	náchylná,zvýš. Expozice	modtagelig, øget eksp.	gevoelig bij verh. blootstelling	altis, lisääntynyt altist.		empfindlich, erh Belastung	Ευαίσθητος, αυξημένη έκθεση		影響を受けやすい、露出が増える	mottakelig, økt eksp.	podatny, zwiększone narażenie		susceptibil, exp. crescută		susceptible, mayor exposición	mottaglig, inkr. exponering	duyarlı, enk. maruziyet	чутливий до підвищеної експозиції
+Susceptible	TRUE	FALSE	FALSE	FALSE	易受影响	Susceptible	Modtagelig	Gevoelig	Altis		Empfindlich	Ευαίσθητο		影響を受けやすい	Mottakelig	Podatny		Susceptibil		Susceptible	Mottaglig	Duyarlı	Чутливий
+Incr. exposure	TRUE	FALSE	FALSE	FALSE	暴露增加	zvýšená expozice	Øget eksponering	'Incr. exposure'	Lisääntynyt altistuminen		Empfindlich, erh Belastung	Αυξημένη έκθεση		曝露量増加	Økt eksp.	Większe narażenie		Exp. crescută		Mayor exposición	Inkr. exponering	Enk. maruziyet	Підвищена експозиція
+Resistant	TRUE	FALSE	FALSE	FALSE	耐药性	Rezistentní	Resistent	Resistent	Kestävä		Resistent	Ανθεκτικός		耐性	Resistent	Odporny		Rezistent		Resistente	Resistent	Dayanıklı	Стійкий
+antibiotic	TRUE	TRUE	FALSE	FALSE	抗生素	antibiotikum	antibiotikum	antibioticum	antibiootti	antibiotique	Antibiotikum	αντιβιοτικό	antibiotico	抗生物質	Antibiotikum	antybiotyk	antibiótico	antibiotic	антибиотик	antibiótico	antibiotika	Antibiyotik	антибіотик
+Antibiotic	TRUE	TRUE	FALSE	FALSE	抗生素	Antibiotikum	Antibiotikum	Antibioticum	Antibiootti	Antibiotique	Antibiotikum	Αντιβιοτικό	Antibiotico	抗生物質	Antibiotikum	Antybiotyk	Antibiótico	Antibiotic	Антибиотик	Antibiótico	Antibiotika	Antibiyotik	Антибіотик
+Drug	TRUE	TRUE	FALSE	FALSE	药物	Lék	Lægemiddel	Middel	Lääke	Médicament	Medikament	Φάρμακο	Droga	薬剤	Legemiddel	Lek	Droga	Medicament	Лекарство	Fármaco	Läkemedel	İlaç	Лікарський засіб
+drug	TRUE	TRUE	FALSE	FALSE	药物	lék	lægemiddel	middel	lääke	médicament	Medikament	φάρμακο	droga	薬剤	legemiddel	lek	droga	medicament	лекарство	fármaco	läkemedel	İlaç	лікарський засіб
+Frequency	FALSE	TRUE	FALSE	FALSE	使用频率	Frekvence	Frekvens	Aantal	Frekvenssi	Fréquence	Zahl	Συχνότητα	Frequenza	頻度	Hyppighet	Częstotliwość	Frequência	Frecvență	Частота	Frecuencia	Frekvens	Frekans	Частота
+Minimum Inhibitory Concentration (mg/L)	FALSE	FALSE	FALSE	FALSE	最小抑菌浓度(mg/L)	Minimální inhibiční koncentrace (mg/l)	Mindste hæmmende koncentration (mg/L)	Minimale inhiberende concentratie (mg/L)	Pienin estävä pitoisuus (mg/l)	Concentration minimale inhibitrice (mg/L)	Minimale Hemm-Konzentration (mg/L)	Ελάχιστη ανασταλτική συγκέντρωση (mg/L)	Concentrazione minima inibitoria (mg/L)	最小発育阻止濃度(mg/L)	Minste hemmende konsentrasjon (mg/L)	Minimalne stężenie hamujące (mg/L)	Concentração Inibitória Mínima (mg/L)	Concentrația minimă inhibitorie (mg/L)	Минимальная ингибирующая концентрация (мг/л)	Concentración mínima inhibitoria (mg/L)	Minsta hämmande koncentration (mg/L)	Minimum İnhibitör Konsantrasyon (mg/L)	Мінімальна інгібуюча концентрація (мг/мл)
+Disk diffusion diameter (mm)	FALSE	FALSE	FALSE	FALSE	磁盘扩散直径(mm)	Diskový difuzní průměr (mm)	Diskdiffusionsdiameter (mm)	Diameter diskzone (mm)	Levyn diffuusion halkaisija (mm)	Diamètre de diffusion en disque (mm)	Durchmesser der Scheibenzone (mm)	Διάμετρος διάχυσης δίσκου (mm)	Diametro di diffusione del disco (mm)	ディスク拡散径(mm)	Diskdiffusjonsdiameter (mm)	Średnica dyfuzji dysku (mm)	Diâmetro de difusão do disco (mm)	Diametrul de difuzie a discului (mm)	Диаметр диффузии диска (мм)	Diámetro de difusión en disco (mm)	Diskdiffusionsdiameter (mm)	Disk difüzyon çapı (mm)	Зона затримки росту (мм)
+Antimicrobial Interpretation	FALSE	FALSE	FALSE	FALSE	抗菌性解释	Antimikrobiální interpretace	Antimikrobiel fortolkning	Antimicrobiële interpretatie	Mikrobilääkkeiden tulkinta	Interprétation antimicrobienne	Antimikrobielle Auswertung	Αντιμικροβιακή ερμηνεία	Interpretazione antimicrobica	抗菌性解釈	Antimikrobiell tolkning	Interpretacja antybakteryjna	Interpretação Antimicrobiana	Interpretare antimicrobiană	Антимикробная интерпретация	Interpretación antimicrobiana	Antimikrobiell tolkning	Antimikrobiyal Yorumlama	Фенотипи чутливості
+Percentage	FALSE	FALSE	FALSE	FALSE	百分比	Procento	Procentdel	Percentage	Prosenttiosuus	Pourcentage	Prozentsatz	Ποσοστό	Percentuale	割合(%)	Prosentandel	Procent	Percentagem	Procentaj	Процент	Porcentaje	Procentuell andel	Yüzde	Відсоток
+Syndromic Group	FALSE	FALSE	FALSE	FALSE	合并症候群	Syndromová skupina	Syndromisk gruppe	Syndroomgroep	Syndrooma Ryhmä	Groupe syndromique	Syndromische Gruppe	Συνδρομική ομάδα	Gruppo sindromico	シンドロームグループ	Syndromgruppe	Grupa syndromiczna	Grupo sindrómico	Grup sindromic	Синдромная группа	Grupo sindrómico	Syndromisk grupp	Sendromik Grup	Синдромна група
+Pathogen	FALSE	FALSE	FALSE	FALSE	病原体	Patogen	Patogen	Pathogeen	Taudinaiheuttaja	Agent pathogène	Erreger	Παθογόνο	Agente patogeno	病原体	Patogen	Patogen	Pathogen	Agenți patogeni	Возбудитель	Patógeno	Patogen	Patojen	Збудник
+4-aminosalicylic acid	FALSE	TRUE	TRUE	FALSE	4-氨基水杨酸	kyselina 4-aminosalicylová	4-aminosalicylsyre	4-aminosalicylzuur	4-aminosalisyylihappo	Acide 4-aminosalicylique	4-Aminosalicylsäure	4-αμινοσαλικυλικό οξύ	Acido 4-aminosalicilico	4-アミノサリチル酸	4-aminosalisylsyre	Kwas 4-aminosalicylowy	Ácido 4-aminosalicílico	Acid 4-aminosalicilic	4-аминосалициловая кислота	Ácido 4-aminosalicílico	4-aminosalicylsyra	4-aminosalisilik asit	4-Аміносаліцилова кислота
+Adefovir dipivoxil	FALSE	TRUE	TRUE	FALSE	阿德福韦酯	Adefovir dipivoxil	Adefovir dipivoxil	Adefovir	Adefoviiridipivoksiili	Adéfovir dipivoxil	Adefovir Dipivoxil	Adefovir dipivoxil	Adefovir dipivoxil	アデホビル・ジピボキシル	Adefovirdipivoksil	Adefovir dipivoxil	Adefovir dipivoxil	Adefovir dipivoxil	Адефовир дипивоксил	Adefovir dipivoxil	Adefovir dipivoxil	Adefovir dipivoksil	Адефовір діпівоксил
+Aldesulfone sodium	FALSE	TRUE	TRUE	FALSE	醛缩酮钠	Aldesulfon sodný	Aldesulfon-natrium	Aldesulfon	Aldesulfoninatrium	Aldésulfone sodique	Aldesulfon-Natrium	Αλδεσουλφονικό νάτριο	Aldesulfone sodio	アルデスルホンナトリウム	Aldesulfon-natrium	Sól sodowa aldesulfonu	Aldesulfona de sódio	Aldesulfonă sodică	Альдесульфон натрия	Aldesulfona sódica	Aldesulfonnatrium	Aldesülfon sodyum	Альденсульфон натрію
+Amikacin	FALSE	TRUE	TRUE	FALSE	阿米卡星	Amikacin	Amikacin	Amikacine	Amikasiini	Amikacine	Amikacin	Αμικασίνη	Amikacin	アミカシン	Amikacin	Amikacyna	Amikacin	Amikacin	Амикацин	Amikacina	Amikacin	Amikasin	Амікацин
+Amoxicillin	FALSE	TRUE	TRUE	FALSE	阿莫西林	Amoxicilin	Amoxicillin	Amoxicilline	Amoksisilliini	Amoxicilline	Amoxicillin	Αμοξικιλλίνη	Amoxicillina	アモキシシリン	Amoxicillin	Amoxicillin	Amoxicilina	Amoxicilină	Амоксициллин	Amoxicilina	Amoxicillin	Amoksisilin	Амоксицилін
+Amoxicillin/beta-lactamase inhibitor	FALSE	TRUE	TRUE	FALSE	阿莫西林/β-内酰胺酶抑制剂	Amoxicilin/inhibitor beta-laktamázy	Amoxicillin/beta-lactamasehæmmer	Amoxicilline/enzymremmer	Amoksisilliini/beeta-laktamaasin estäjä	Amoxicilline/inhib. de bêta-lactamase	Amoxicillin/Beta-Lactamase-Hemmer	Αμοξικιλλίνη/αναστολέας της β-λακταμάσης	Amoxicillina/inib. d. beta-lattamasi	アモキシシリン／β-ラクタマーゼ阻害剤	Amoxicillin/betalaktamase-hemmer	Amoksycylina/inhibitor beta-laktamazy	Amoxicilina/inibid. da beta-lactamase	Amoxicilină/inhibitor de beta-lactamază	Амоксициллин/ингибитор бета-лактамаз	Amoxicilina/inhib. de la beta-lactamasa	Amoxicillin/betalaktamashämmare	Amoksisilin/beta-laktamaz inhibitörü	Амоксицилін/інгібітор бета-лактамаз
+Amphotericin B	FALSE	TRUE	TRUE	FALSE	两性霉素B	Amfotericin B	Amfotericin B	Amfotericine B	Amfoterisiini B	Amphotéricine B	Amphotericin B	Αμφοτερικίνη Β	Amfotericina B	アムホテリシンB	Amfotericin B	Amfoterycyna B	Anfotericina B	Amfotericină B	Амфотерицин В	Anfotericina B	Amfotericin B	Amfoterisin B	Амфотерицин В
+Ampicillin	FALSE	TRUE	TRUE	FALSE	氨苄西林	Ampicilin	Ampicillin	Ampicilline	Ampisilliini	Ampicilline	Ampicillin	Αµπικιλλίνη	Ampicillina	アンピシリン	Ampicillin	Ampicylina	Ampicilina	Ampicilină	Ампициллин	Ampicilina	Ampicillin	Ampisilin	Ампіцилін
+Ampicillin/beta-lactamase inhibitor	FALSE	TRUE	TRUE	FALSE	氨苄西林/β-内酰胺酶抑制剂	Inhibitor ampicilinu/beta-laktamázy	Ampicillin/beta-lactamasehæmmer	Ampicilline/enzymremmer	Ampisilliini/beeta-laktamaasin estäjä	Ampicilline/inhib. de bêta-lactamase	Ampicillin/Beta-Laktamase-Hemmer	Αμπικιλλίνη/αναστολέας β-λακταμάσης	Ampicillina/inib. d. beta-lattamasi	アンピシリン／β-ラクタマーゼ阻害剤	Ampicillin/betalaktamasehemmer	Ampicylina/inhibitor beta-laktamazy	Ampicilina/inibid. da beta-lactamase	Ampicilină/inhibitor de beta-lactamază	Ампициллин/ингибитор бета-лактамазы	Ampicilina/inhib. de la beta-lactamasa	Ampicillin/beta-laktamashämmare	Ampisilin/beta-laktamaz inhibitörü	Ампіцилін/інгібітор бета-лактамаз
+Anidulafungin	FALSE	TRUE	TRUE	FALSE	阿尼芬净	Anidulafungin	Anidulafungin	Anidulafungine	Anidulafungiini	Anidulafungine	Anidulafungin	Ανιδουλαφουνγκίνη	Anidulafungin	アニデュラファンギン	Anidulafungin	Anidulafungina	Anidulafungin	Anidulafungin	Анидулафунгин	Anidulafungina	Anidulafungin	Anidulafungin	Анідулафунгін
+Azidocillin	FALSE	TRUE	TRUE	FALSE	阿奇霉素	Azidocillin	Azidocillin	Azidocilline	Azidosilliini	Azidocilline	Azidocillin	Αζιδοκιλλίνη	Azidocillina	アジドシリン	Azidocillin	Azidocillin	Azidocillin	Azidocilină	Азидоциллин	Azidocilina	Azidocillin	Azidosilin	Азидоцилін
+Azithromycin	FALSE	TRUE	TRUE	FALSE	阿奇霉素	Azitromycin	Azithromycin	Azitromycine	Atsitromysiini	Azithromycine	Azithromycin	Αζιθρομυκίνη	Azitromicina	アジスロマイシン	Azitromycin	Azithromycin	Azitromicina	Azitromicină	Азитромицин	Azitromicina	Azitromycin	Azitromisin	Азитроміцин
+Azlocillin	FALSE	TRUE	TRUE	FALSE	阿洛西林	Azlocillin	Azlocillin	Azlocilline	Azlocillin	Azlocilline	Azlocillin	Αζλοκιλλίνη	Azlocillina	アズロシリン	Azlocillin	Azlocillin	Azlocillin	Azlocilină	Азлоциллин	Azlocilina	Azlocillin	Azlocillin	Азлоцилін
+Bacampicillin	FALSE	TRUE	TRUE	FALSE	巴卡比林	Bacampicilin	Bacampicillin	Bacampicilline	Bacampicillin	Bacampicilline	Bacampicillin	Μπακαμπικιλλίνη	Bacampicillina	バカンピシリン	Bacampicillin	Bakampicylina	Bacampicilina	Bacampicilină	Бакампициллин	Bacampicilina	Bacampicillin	Bacampicillin	Бакампіцилін
+Bacitracin	FALSE	TRUE	TRUE	FALSE	阿奇霉素	Bacitracin	Bacitracin	Bacitracine	Bacitrasiini	Bacitracine	Bacitracin	Βακιτρακίνη	Bacitracina	バシトラシン	Bacitracin	Bacytracyna	Bacitracin	Bacitracină	Бацитрацин	Bacitracina	Bacitracin	Basitrasin	Бацитрацин
+Benzathine benzylpenicillin	FALSE	TRUE	TRUE	FALSE	苄丝肼青霉素	Benzathine benzylpenicillin	Benzathinbenzylpenicillin	Benzylpenicillinebenzathine	Bentsatiinibentsyylipenisilliini	Benzathine benzylpénicilline	Benzathin-Benzylpenicillin	Βενζαθίνη βενζυλπενικιλλίνη	Benzatina benzilpenicillina	ベンズシン・ベンジルペニシリン	Benzathine benzylpenicillin	Benzylpenicylina benzylowa	Benzatina benzatina benzilpenicilina	Benzatină benzilpenicilină	Бензатин бензилпенициллин	Bencilpenicilina benzatínica	Benzathinbenzylpenicillin	Benzatin benzilpenisilin	Бензатину бензилпеніцилін
+Benzathine phenoxymethylpenicillin	FALSE	TRUE	TRUE	FALSE	苄星苯氧甲基青霉素	Benzatinový fenoxymethylpenicilin	Benzathinfenoxymethylpenicillin	Fenoxymethylpenicillinebenzathine	Bentsatiinifenoksimetyylipenisilliini	Phénoxyméthylpénicilline benzathine	Benzathin-Phenoxymethylpenicillin	Βενζαθίνη φαινοξυμεθυλοπενικιλλίνη	Benzatina fenossimetilpenicillina	ベンザチンフェノキシメチルペニシリン	Benzathine fenoksymetylpenicillin	Fenoksymetylopenicylina benzylowa	Benzatina fenoximetilpenicilina	Benzatină fenoximetilpenicilină	Бензатин феноксиметилпенициллин	Fenoximetilpenicilina benzatínica	Bensathinfenoximetylpenicillin	Benzatin fenoksimetilpenisilin	Бензатину феноксиметилпеніцилін
+Benzylpenicillin	FALSE	TRUE	TRUE	FALSE	苄基青霉素	Benzylpenicilin	Benzylpenicillin	Benzylpenicilline	Bentsyylipenisilliini	Benzylpénicilline	Benzylpenicillin	Βενζυλοπενικιλλίνη	Benzilpenicillina	ベンジルペニシリン	Benzylpenicillin	Benzylpenicylina	Benzilpenicilina	Benzilpenicilină	Бензилпенициллин	Bencilpenicilina	Bensylpenicillin	Benzilpenisilin	Бензилпеніцилін
+Calcium aminosalicylate	FALSE	TRUE	TRUE	FALSE	氨基水杨酸钙	Aminosalicylát vápenatý	Calciumaminosalicylat	Aminosalicylzuur	Kalsiumaminosalisylaatti	Aminosalicylate de calcium	Kalzium-Aminosalicylat	Αμινοσαλικυλικό ασβέστιο	Calcio aminosalicilato	アミノサリチル酸カルシウム	Kalsiumaminosalicylat	Aminosalicylan wapnia	Aminosalicilato de cálcio	Aminosalicilat de calciu	Аминосалицилат кальция	Aminosalicilato de calcio	Kalciumaminosalicylat	Kalsiyum aminosalisilat	Кальцію аміносаліцилат
+Capreomycin	FALSE	TRUE	TRUE	FALSE	氨水杨酸钙	Kapreomycin	Capreomycin	Capreomycine	Kapreomysiini	Capréomycine	Capreomycin	Καπρεομυκίνη	Capreomicina	カプレオマイシン	Capreomycin	Kapreomycyna	Capreomicina	Capreomicină	Капреомицин	Capreomicina	Kapreomycin	Kapreomisin	Капреоміцин
+Carbenicillin	FALSE	TRUE	TRUE	FALSE	羧基青霉素	Karbenicilin	Carbenicillin	Carbenicilline	Karbenisilliini	Carbénicilline	Carbenicillin	Καρβενικιλλίνη	Carbenicillina	カルベニシリン	Karbenicillin	Karbenicylina	Carbenicilina	Carbenicilină	Карбенициллин	Carbenicilina	Karbenicillin	Karbenisilin	Карбеніцилін
+Carindacillin	FALSE	TRUE	TRUE	FALSE	卡林达西林	Karindacilin	Carindacillin	Carindacilline	Karindasilliini	Carindacilline	Carindacillin	Καρινδακιλλίνη	Carindacillina	カリンダシリン	Karindacillin	Karindacillin	Carindacillin	Carindacilină	Кариндациллин	Carindacilina	Carindacillin	Karindasilin	Кариндацилін
+Caspofungin	FALSE	TRUE	TRUE	FALSE	氨苄青霉素	Kaspofungin	Caspofungin	Caspofungine	Kaspofungiini	Caspofungine	Caspofungin	Κασποφουνγκίνη	Caspofungin	カスポファンギン	Caspofungin	Kaspofungina	Caspofungin	Caspofungin	Каспофунгин	Caspofungina	Caspofungin	Caspofungin	Каспофунгін
+Ce(f|ph)acetrile	TRUE	TRUE	TRUE	FALSE	头孢乙腈	Cefacetril	Cephacetril	Cefacetril	Kefasetriili	Céphacétrile	Cefacetril	Κεφακετρίλη	Cefacetrile	セファセトリル	Cefacetril	Cefacetrile	Cephacetrile	Cefacetril	Цефацетрил	Cefacetrilo	Cephacetril	Sefasetril	Цефацетрил
+Ce(f|ph)alotin	TRUE	TRUE	TRUE	FALSE	头孢罗丁	Cefalotin	Cephalotin	Cefalotine	Kefalotin	Céphalotine	Cefalotin	Κεφαλοτίνη	Cefalotina	セファロチン	Cefalotin	Cefalotyna	Cefalotina	Cefalotin	Цефалотин	Cefalotina	Cefalotin	Sefalotin	Цефалотин
+Ce(f|ph)amandole	TRUE	TRUE	TRUE	FALSE	头孢曼多	Cefamandol	Cephamandol	Cefamandol	Kefamandoli	Céphamandole	Cefamandol	Κεφαμανδόλη	Cephamandole	セファマンドール	Cefamandol	Cefamandol	Cephamandole	Cefamandole	Цефамандол	Cefamandole	Cephamandol	Cefamandole	Цефамандол
+Ce(f|ph)apirin	TRUE	TRUE	TRUE	FALSE	头孢匹林	Cefapirin	Cephapirin	Cefapirine	Kefapiriini	Céphapirine	Cefapirin	Κεφαπιρίνη	Cefapirina	セファピリン	Cefapirin	Cefapiryna	Cephapirin	Cefapirină	Цефапирин	Cefapirina	Cephapirin	Sefapirin	Цефапірин
+Ce(f|ph)azedone	TRUE	TRUE	TRUE	FALSE	头孢唑酮	Cefazedon	Cephazedon	Cefazedon	Kefatsedoni	Céphazédone	Cefazedon	Κεφαζεδόνη	Cefazedone	セファゼドン	Cefazedon	Cefazedon	Cephazedone	Cefazedonă	Цефазедон	Cefazedona	Cephazedon	Sefazedon	Цефазедон
+Ce(f|ph)azolin	TRUE	TRUE	TRUE	FALSE	头孢唑啉	Cefazolin	Cephazolin	Cefazoline	Kefatsoliini	Céphazoline	Cefazolin	Κεφαζολίνη	Cephazolin	セファゾリン	Cefazolin	Cefazolin	Cephazolin	Cefazolin	Цефазолин	Cefazolina	Cephazolin	Sefazolin	Цефазолін
+Ce(f|ph)alothin	TRUE	TRUE	TRUE	FALSE	头孢罗丁	Cefalotin	Cephalothin	Cefalotine	Kefalotiini	Céphalothine	Cefalothin	Κεφαλοθίνη	Cefalotina	セファロチン	Cefalotin	Cefalotyna	Cephalothin	Cefalotin	Цефалотин	Cefalotina	Kefalotin	Cefalothin	Цефалотин
+Ce(f|ph)alexin	TRUE	TRUE	TRUE	FALSE	头孢莱辛	Cefalexin	Cephalexin	Cefalexine	Kefaleksiini	Céphalexine	Cefalexin	Κεφαλεξίνη	Cephalexin	セファレキシン	Cefalexin	Cefaleksyna	Cephalexin	Cefalexină	Цефалексин	Cefalexina	Cephalexin	Cefalexin	Цефалексин
+Ce(f|ph)epime	TRUE	TRUE	TRUE	FALSE	头孢吡肟	Cefepim	Cephepime	Cefepim	Kefepiimi	Céphépime	Cefepim	Κεφεπίμη	Cephepime	セフェパイム	Cefepime	Cefepime	Cephepime	Cefepime	Цефепим	Cefepime	Cephepim	Sefepim	Цефепім
+Ce(f|ph)ixime	TRUE	TRUE	TRUE	FALSE	头孢克肟	Cefixim	Cephixim	Cefixim	Kefiksiimi	Céphixime	Cefixim	Cefixime	Cephixime	セフィキシム	Cefixime	Cefixime	Cephixime	Cefixime	Цефиксим	Cefixima	Cephixim	Cefixime	Цефіксим
+Ce(f|ph)menoxime	TRUE	TRUE	TRUE	FALSE	头孢米诺肟	Cefmenoxim	Cephmenoxim	Cefmenoxim	Cefmenoksiimi	Céphénoxime	Cefmenoxim	Κεφμενοξίμη	Cephmenoxime	セフメノキシム	Cefmenoxime	Cefmenoksym	Cephmenoxime	Cefmenoxime	Цефменоксим	Cefmenoxima	Cephmenoxim	Sefmenoksim	Цефменоксим
+Ce(f|ph)metazole	TRUE	TRUE	TRUE	FALSE	头孢美唑	Cefmetazol	Cephmetazol	Cefmetazol	Kefmetatsoli	Céphmétazole	Cefmetazol	Κεφμεταζόλη	Cephmetazole	セフメタゾール	Cefmetazole	Cefmetazol	Cefmetazole	Cefmetazol	Цефметазол	Cefmetazol	Cephmetazol	Sefmetazol	Цефметазол
+Ce(f|ph)odizime	TRUE	TRUE	TRUE	FALSE	头孢地嗪	Cefodizim	Cephodizim	Cefodizim	Kefodisiimi	Céphodizime	Cefodizim	Κεφοδιζίμη	Cephodizime	セフォジジム	Cefodizim	Cefodizime	Cephodizime	Cefodizime	Цефодизим	Cefodixima	Cephodizim	Sefodizim	Цефодізим
+Ce(f|ph)onicid	TRUE	TRUE	TRUE	FALSE	头孢尼西	Cefonicid	Cephonicid	Cefonicide	Cefonicid	Céphonicide	Cefonicid	Κεφονικίδη	Cephonicid	セフォニキッド	Cefonicid	Cefonicid	Cefonicid	Cefonicid	Цефонизид	Cefonicida	Cephonicid	Cefonicid	Цефоніцид
+Ce(f|ph)operazone	TRUE	TRUE	TRUE	FALSE	头孢哌酮	Cefoperazon	Cephoperazon	Cefoperazon	Kefoperatsoni	Céphopérazone	Cefoperazon	Κεφοπεραζόνη	Cephoperazone	セフペラゾン	Cefoperazon	Cefoperazon	Cephoperazone	Cefoperazonă	Цефоперазон	Cefoperazona	Cephoperazon	Sefoperazon	Цефоперазон
+Ce(f|ph)operazone/beta-lactamase inhibitor	TRUE	TRUE	TRUE	FALSE	头孢哌酮/β-内酰胺酶抑制剂	Cefoperazon/inhibitor beta-laktamázy	Cephoperazon/beta-lactamasehæmmer	Cefoperazon/enzymremmer	Kefoperatsoni/beeta-laktamaasin estäjä	Céphopérazone/inhib. de bêta-lactamase	Cefoperazon/Beta-Lactamase-Hemmer	Κεφοπεραζόνη/αναστολέας της β-λακταμάσης	Cephoperazone/inib. d. beta-lattamasi	Cefoperazone/β-ラクタマーゼ阻害剤	Cefoperazon/beta-laktamasehemmere	Cefoperazon/inhibitor beta-laktamazy	Cephoperazona/inibid. da beta-lactamase	Cefoperazonă/inhibitor de beta-lactamază	Цефоперазон/ингибитор бета-лактамаз	Cefoperazona/inhib. de betalactamasas	Cefoperazon/beta-laktamashämmare	Sefoperazon/beta-laktamaz inhibitörü	Цефоперазон/інгібітор бета-лактамаз
+Ce(f|ph)otaxime	TRUE	TRUE	TRUE	FALSE	头孢噻肟	Cefotaxim	Cephotaxim	Cefotaxim	Kefotaksiimi	Céphotaxime	Cefotaxim	Κεφοταξίμη	Cephotaxime	セフォタキシム	Cefotaxim	Cefotaksym	Cephotaxime	Cefotaximă	Цефотаксим	Cefotaxima	Cephotaxim	Sefotaksim	Цефотаксим
+Ce(f|ph)oxitin	TRUE	TRUE	TRUE	FALSE	头孢西丁	Cefoxitin	Cephoxitin	Cefoxitine	Kefoksitiini	Céphoxitine	Cefoxitin	Κεφοξιτίνη	Cefossitina	Cefoxitin	Cefoxitin	Cefoksytyna	Cephoxitin	Cefoxitină	Цефокситин	Cefoxitina	Cephoxitin	Cefoxitin	Цефокситин
+Ce(f|ph)pirome	TRUE	TRUE	TRUE	FALSE	头孢匹罗	Cefpirom	Cephpirom	Cefpirom	Kefpiromi	Céphpirome	Cefpirom	Κεφπιρόμη	Cephpirome	セフピロム	Cefpirom	Cefpirom	Cefpirome	Cefpirom	Цефпиром	Cephpirome	Cephpirom	Sefpirom	Цефпіром
+Ce(f|ph)podoxime	TRUE	TRUE	TRUE	FALSE	头孢泊肟	Cefpodoxim	Cephpodoxim	Cefpodoxim	Kefpodoksiimi	Céphpodoxime	Cefpodoxim	Κεφποδοξίμη	Cephpodoxime	セフポドキシム	Cefpodoxime	Cefpodoxime	Cephpodoxime	Cefpodoximă	Цефподоксим	Cefpodoxima	Cephpodoxim	Sefpodoksim	Цефподоксим
+Ce(f|ph)radine	TRUE	TRUE	TRUE	FALSE	头孢拉定	Cefradin	Cephradin	Cefradine	Cefradiini	Céphradine	Cefradin	Κεφραντίνη	Cefradina	セフラジン	Cefradin	Cefradyna	Cephradine	Cefradina	Цефрадин	Cefradina	Cephradin	Sefradin	Цефрадін
+Ce(f|ph)sulodin	TRUE	TRUE	TRUE	FALSE	头孢苏洛丁	Cefsulodin	Cephsulodin	Cefsulodine	Kefsulodiini	Céphsulodine	Cefsulodin	Κεφσουλοδίνη	Cephsulodin	セフスロジン	Cefsulodin	Cefsulodin	Cephsulodin	Cefsulodin	Цефсулодин	Cefsulodina	Cephsulodin	Cefsulodin	Цефсулодин
+Ce(f|ph)tazidime	TRUE	TRUE	TRUE	FALSE	头孢噻肟	Ceftazidim	Cephtazidim	Ceftazidim	Keftatsidiimi	Céphtazidime	Ceftazidim	Κεφταζιδίμη	Ceftazidima	セフタジジム	Ceftazidim	Ceftazidime	Ceftazidima	Ceftazidime	Цефтазидим	Ceftazidima	Cephtazidim	Seftazidim	Цефтазидим
+Ce(f|ph)tezole	TRUE	TRUE	TRUE	FALSE	头孢特唑	Ceftezol	Cephtezol	Ceftezol	Ceftezole	Céphtézole	Ceftezol	Τζεφεζόλη	Cephtezole	セフテゾール	Ceftezole	Ceftezol	Ceftezole	Ceftezol	Цефтезол	Ceftezol	Cephtezole	Seftezol	Цефтезол
+Ce(f|ph)tizoxime	TRUE	TRUE	TRUE	FALSE	头孢唑肟	Ceftizoxim	Cephtizoxim	Ceftizoxim	Keftatsoksiimi	Céphtizoxime	Ceftizoxim	Κεφτιζοξίμη	Cephtizoxime	セフティゾキシム	Ceftizoxim	Ceftizoxime	Cephtizoxime	Ceftizoxime	Цефтизоксим	Ceftizoxima	Cephtizoxim	Seftizoksim	Цефтизоксим
+Ce(f|ph)triaxone	TRUE	TRUE	TRUE	FALSE	头孢曲松	Ceftriaxon	Cephtriaxon	Ceftriaxon	Ceftriaksoni	Céphtriaxone	Ceftriaxon	Κεφτριαξόνη	Ceftriaxone	セフトリアキソン	Ceftriaxone	Ceftriakson	Cefhtriaxone	Ceftriaxonă	Цефтриаксон	Ceftriaxona	Ceftriaxon	Ceftriaxone	Цефтриаксон
+Ce(f|ph)uroxime	TRUE	TRUE	TRUE	FALSE	头孢呋辛	Cefuroxim	Cephuroxim	Cefuroxim	Kefuroksiimi	Céphuroxime	Cefuroxim	Κεφουροξίμη	Cefuroxima	セフロキシム	Cefuroxim	Cefuroksym	Cephuroxime	Cefuroxime	Цефуроксим	Cefuroxima	Cefuroxim	Sefuroksim	Цефуроксим
+Ce(f|ph)uroxime/metronidazole	TRUE	TRUE	TRUE	FALSE	头孢呋辛/甲硝唑	Cefuroxim/metronidazol	Cefuroxim/metronidazol	Cefuroxim/andere antibacteriele middelen	Kefuroksiimi/metronidatsoli	Céphuroxime/métronidazole	Cefuroxim/Metronidazol	Κεφουροξίμη/μετρονιδαζόλη	Cefuroxima/metronidazolo	セフロキシム/メトロニダゾール	Cefuroxim/metronidazol	Cefuroksym/metronidazol	Cephuroxime/metronidazol	Cefuroximă/metronidazol	Цефуроксим/метронидазол	Cefuroxima/metronidazol	Cefuroxim/metronidazol	Sefuroksim/metronidazol	Цефуроксим/метронідазол
+Chloramphenicol	FALSE	TRUE	TRUE	FALSE	氯霉素	Chloramfenikol	Kloramfenicol	Chlooramfenicol	Kloramfenikoli	Chloramphénicol	Chloramphenicol	Χλωραμφενικόλη	Cloramfenicolo	クロラムフェニコール	Kloramfenikol	Chloramfenikol	Cloranfenicol	Cloramfenicol	Хлорамфеникол	Cloranfenicol	Kloramfenikol	Kloramfenikol	Хлорамфенікол
+Chlortetracycline	FALSE	TRUE	TRUE	FALSE	金霉素	Chlortetracyklin	Chlortetracyclin	Chloortetracycline	Klortetasykliini	Chlortétracycline	Chlortetracyclin	Χλωροτετρακυκλίνη	Clorotetraciclina	クロルテトラサイクリン	Klortetracyklin	Chlortetracyklina	Chlortetracycline	Clortetraciclină	Хлортетрациклин	Clortetraciclina	Klortetracyklin	Klortetrasiklin	Хлортетрациклін
+Cinoxacin	FALSE	TRUE	TRUE	FALSE	西诺沙星	Cinoxacin	Cinoxacin	Cinoxacine	Kinoksasiini	Cinoxacine	Cinoxacin	Τσινοξακίνη	Cinoxacina	シノキサシン	Cinoxacin	Cinoxacin	Cinoxacin	Cinoxacină	Циноксацин	Cinoxacina	Cinoxacin	Cinoxacin	Циноксацин
+Ciprofloxacin	FALSE	TRUE	TRUE	FALSE	环丙沙星	Ciprofloxacin	Ciprofloxacin	Ciprofloxacine	Siprofloksasiini	Ciprofloxacine	Ciprofloxacin	Σιπροφλοξασίνη	Ciprofloxacina	シプロフロキサシン	Ciprofloxacin	Ciprofloksacyna	Ciprofloxacin	Ciprofloxacină	Ципрофлоксацин	Ciprofloxacina	Ciprofloxacin	Siprofloksasin	Ципрофлоксацин
+Clarithromycin	FALSE	TRUE	TRUE	FALSE	克拉霉素	Klaritromycin	Clarithromycin	Claritromycine	Klaritromysiini	Clarithromycine	Clarithromycin	Κλαριθρομυκίνη	Claritromicina	クラリスロマイシン	Klaritromycin	Klarytromycyna	Claritromicina	Claritromicină	Кларитромицин	Claritromicina	Claritromycin	Klaritromisin	Кларитроміцин
+Clavulanic acid	FALSE	TRUE	TRUE	FALSE	克拉维酸	Kyselina klavulanová	Clavulansyre	Clavulaanzuur	Klavulaanihappo	Acide clavulanique	Clavulansäure	Κλαβουλανικό οξύ	Acido clavulanico	クラビュラン酸	Klavulansyre	Kwas klawulanowy	Ácido clavulânico	Acid clavulanic	Клавулановая кислота	Ácido clavulánico	Clavulansyra	Klavulanik asit	Клавуланова кислота
+clavulanic acid	FALSE	TRUE	TRUE	FALSE	克拉维酸	kyselina klavulanová	clavulansyre	clavulaanzuur	klavulaanihappo	acide clavulanique	Clavulansäure	Κλαβουλανικό οξύ	acido clavulanico	クラビュラン酸	klavulansyre	kwas klawulanowy	ácido clavulânico	acid clavulanic	клавулановая кислота	ácido clavulánico	clavulansyra	klavulanik asit	клавуланова кислота
+Clindamycin	FALSE	TRUE	TRUE	FALSE	克林霉素	Klindamycin	Clindamycin	Clindamycine	Klindamysiini	Clindamycine	Clindamycin	Κλινδαμυκίνη	Clindamicina	クリンダマイシン	Klindamycin	Klindamycyna	Clindamicina	Clindamicină	Клиндамицин	Clindamicina	Clindamycin	Klindamisin	Кліндаміцин
+Clometocillin	FALSE	TRUE	TRUE	FALSE	克罗米修斯（	Clometocillin	Clometocillin	Clometocilline	Klometosilliini	Clométocilline	Clometocillin	Κλομετοκιλλίνη	Clometocillina	クロメトシリン	Klometocillin	Clometocillin	Clometocillin	Clometocilină	Клометоциллин	Clometocilina	Klometocillin	Clometocillin	Клометоцилін
+Clotrimazole	FALSE	TRUE	TRUE	FALSE	克霉唑	Klotrimazol	Clotrimazol	Clotrimazol	Klotrimatsoli	Clotrimazole	Clotrimazol	Κλοτριμαζόλη	Clotrimazolo	クロトリマゾール	Klotrimazol	Klotrimazol	Clotrimazole	Clotrimazol	Клотримазол	Clotrimazol	Klotrimazol	Klotrimazol	Клотримазол
+Cloxacillin	FALSE	TRUE	TRUE	FALSE	克罗西林	Kloxacilin	Cloxacillin	Cloxacilline	Kloksasilliini	Cloxacilline	Cloxacillin	Κλοξακιλλίνη	Cloxacillina	クロキサシリン	Cloxacillin	Cloxacillin	Cloxacillin	Cloxacilină	Клоксациллин	Cloxacilina	Kloxacillin	Cloxacillin	Клоксацилін
+Colistin	FALSE	TRUE	TRUE	FALSE	唑啉酮	Kolistin	Colistin	Colistine	Kolistiini	Colistine	Colistin	Κολιστίνη	Colistina	コリスチン	Kolistin	Kolistyna	Colistin	Colistină	Колистин	Colistina	Kolistin	Kolistin	Колістин
+Dapsone	FALSE	TRUE	TRUE	FALSE	多普生	Dapson	Dapson	Dapson	Dapsoni	Dapsone	Dapson	Δαψόνη	Dapsone	ダプソン	Dapsone	Dapson	Dapsone	Dapsone	Дапсон	Dapsona	Dapson	Dapson	Дапсон
+Daptomycin	FALSE	TRUE	TRUE	FALSE	达托霉素	Daptomycin	Daptomycin	Daptomycine	Daptomysiini	Daptomycine	Daptomycin	Δαπτομυκίνη	Daptomicina	ダプトマイシン	Daptomycin	Daptomycyna	Daptomicina	Daptomicină	Даптомицин	Daptomicina	Daptomycin	Daptomisin	Даптоміцин
+Dibekacin	FALSE	TRUE	TRUE	FALSE	迪贝卡星	Dibekacin	Dibekacin	Dibekacine	Dibekasiini	Dibekacine	Dibekacin	Διβεκακίνη	Dibekacin	ジベカシン	Dibekacin	Dibekacin	Dibekacin	Dibekacin	Дибекацин	Dibekacina	Dibekacin	Dibekacin	Дібекацин
+Dicloxacillin	FALSE	TRUE	TRUE	FALSE	迪卡西林	Dikloxacilin	Dicloxacillin	Dicloxacilline	Dikloksasilliini	Dicloxacilline	Dicloxacillin	Δικλοξακιλλίνη	Dicloxacillina	ジクロキサシリン	Dikloxacillin	Dikloxacillin	Dicloxacilina	Dicloxacilină	Диклоксациллин	Dicloxacilina	Dikloxacillin	Dikloksasilin	Диклоксацилін
+Dirithromycin	FALSE	TRUE	TRUE	FALSE	迪里红霉素	Dirithromycin	Dirithromycin	Diritromycine	Diritromysiini	Dirithromycine	Dirithromycin	Διριθρομυκίνη	Diritromicina	ジリスロマイシン	Diritromycin	Dirytromycyna	Diritromicina	Diritromicină	Диритромицин	Diritromicina	Diritromycin	Diritromisin	Диритроміцин
+Econazole	FALSE	TRUE	TRUE	FALSE	胺鲜胺	Ekonazol	Econazol	Econazol	Ekonatsoli	Econazole	Econazol	Εκοναζόλη	Econazolo	エコナゾール	Econazol	Ekonazol	Econazole	Econazol	Эконазол	Econazol	Ekonazol	Ekonazol	Еконазол
+Enoxacin	FALSE	TRUE	TRUE	FALSE	伊诺沙星	Enoxacin	Enoxacin	Enoxacine	Enoksasiini	Enoxacine	Enoxacin	Ενοξακίνη	Enoxacina	エノキサシン	Enoksacin	Enoxacin	Enoxacin	Enoxacin	Эноксацин	Enoxacina	Enoxacin	Enoksasin	Еноксацин
+Epicillin	FALSE	TRUE	TRUE	FALSE	伊比西林	Epicilin	Epicillin	Epicilline	Episilliini	Epicilline	Epicillin	Επικιλλίνη	Epicillina	エピシリン	Epikillin	Epicillin	Epicilina	Epicilină	Эпициллин	Epicilina	Epicillin	Episilin	Епіцилін
+Erythromycin	FALSE	TRUE	TRUE	FALSE	红霉素	Erytromycin	Erythromycin	Erytromycine	Erytromysiini	Erythromycine	Erythromycin	Ερυθρομυκίνη	Eritromicina	エリスロマイシン	Erytromycin	Erytromycyna	Eritromicina	Eritromicină	Эритромицин	Eritromicina	Erytromycin	Eritromisin	Еритроміцин
+Ethambutol/isoniazid	FALSE	TRUE	TRUE	FALSE	乙胺丁醇/异烟肼	Ethambutol/isoniazid	Ethambutol/isoniazid	Ethambutol/isoniazide	Etambutoli/isonitsidi	Ethambutol/isoniazide	Ethambutol/Isoniazid	Αιθαμβουτόλη/ισονιαζίδη	Etambutolo/isoniazide	エタンブトール／イソニアジド	Etambutol/isoniazid	Etambutol/izoniazyd	Ethambutol/isoniazid	Etambutol/isoniazidă	Этамбутол/изониазид	Etambutol/isoniazida	Etambutol/isoniazid	Etambutol/izoniazid	Етамбутол/ізоніазид
+Fleroxacin	FALSE	TRUE	TRUE	FALSE	氨甲喋呤	Fleroxacin	Fleroxacin	Fleroxacine	Fleroksasiini	Fléroxacine	Fleroxacin	Φλεροξακίνη	Fleroxacina	フレロキサシン	Fleroksacin	Fleroksacyna	Fleroxacina	Fleroxacin	Флероксацин	Fleroxacina	Fleroxacin	Fleroxacin	Флероксацин
+Flucloxacillin	FALSE	TRUE	TRUE	FALSE	氟氯西林	Flucloxacillin	Flucloxacillin	Flucloxacilline	Flukloksasilliini	Flucloxacilline	Flucloxacillin	Φλουκλοξακιλλίνη	Flucloxacillina	フルクロキサシリン	Flukloxacillin	Flucloxacillin	Flucloxacillin	Flucloxacilină	Флуклоксациллин	Flucloxacilina	Flucloxacillin	Flukloksasilin	Флуклоксацилін
+Fluconazole	FALSE	TRUE	TRUE	FALSE	氟康唑	Flukonazol	Fluconazol	Fluconazol	Flukonatsoli	Fluconazole	Fluconazol	Φλουκοναζόλη	Fluconazolo	フルコナゾール	Flukonazol	Flukonazol	Fluconazole	Fluconazol	Флуконазол	Fluconazol	Flukonazol	Flukonazol	Флуконазол
+Flucytosine	FALSE	TRUE	TRUE	FALSE	氨甲喋呤	Flucytosin	Flucytosin	Fluorocytosine	Flukosiini	Flucytosine	Flucytosin	Φλουκυτοσίνη	Flucytosine	フルシトシン	Flucytosin	Flucytozyna	Flucytosine	Flucitozină	Флуцитозин	Flucitosina	Flucytosin	Flusitozin	Флуцитозин
+Flurithromycin	FALSE	TRUE	TRUE	FALSE	氟利霉素	Fluritromycin	Flurithromycin	Fluritromycine	Fluritromysiini	Flurithromycine	Flurithromycin	Φλουριθρομυκίνη	Fluritromicina	フルリスロマイシン	Fluritromycin	Flurithromycin	Fluritromicina	Fluritromicină	Флуритромицин	Fluritromicina	Fluritromycin	Fluritromisin	Флуритроміцин
+Fosfomycin	FALSE	TRUE	TRUE	FALSE	福斯霉素	Fosfomycin	Fosfomycin	Fosfomycine	Fosfomysiini	Fosfomycine	Fosfomycin	Φοσφομυκίνη	Fosfomicina	ホスホマイシン	Fosfomycin	Fosfomycyna	Fosfomycin	Fosfomicină	Фосфомицин	Fosfomicina	Fosfomycin	Fosfomisin	Фосфоміцин
+Fusidic acid	FALSE	TRUE	TRUE	FALSE	夫西地酸	Kyselina fusidová	Fusidinsyre	Fusidinezuur	Fusidiinihappo	Acide fusidique	Fusidinsäure	Φουσιδικό οξύ	Acido fusidico	フシジン酸	Fusidinsyre	Kwas fusydynowy	Ácido fusídico	Acid fuzidic	Фузидовая кислота	Ácido fusídico	Fusidinsyra	Fusidik asit	Фузидова кислота
+Gatifloxacin	FALSE	TRUE	TRUE	FALSE	加替沙星	Gatifloxacin	Gatifloxacin	Gatifloxacine	Gatifloksasiini	Gatifloxacine	Gatifloxacin	Gatifloxacin	Gatifloxacina	ガチフロキサシン	Gatifloxacin	Gatifloxacin	Gatifloxacin	Gatifloxacină	Гатифлоксацин	Gatifloxacina	Gatifloxacin	Gatifloksasin	Гатифлоксацин
+Gemifloxacin	FALSE	TRUE	TRUE	FALSE	吉非沙星	Gemifloxacin	Gemifloxacin	Gemifloxacine	Gemifloksasiini	Gemifloxacine	Gemifloxacin	Γεμιφλοξασίνη	Gemifloxacina	ゲミフロキサシン	Gemifloxacin	Gemifloksacyna	Gemifloxacin	Gemifloxacin	Гемифлоксацин	Gemifloxacina	Gemifloxacin	Gemifloksasin	Геміфлоксацин
+Gentamicin	FALSE	TRUE	TRUE	FALSE	庆大霉素	Gentamicin	Gentamicin	Gentamicine	Gentamysiini	Gentamicine	Gentamicin	Γενταμικίνη	Gentamicina	ゲンタマイシン	Gentamicin	Gentamicin	Gentamicina	Gentamicină	Гентамицин	Gentamicina	Gentamicin	Gentamisin	Гентаміцин
+Grepafloxacin	FALSE	TRUE	TRUE	FALSE	格雷帕沙星	Grepafloxacin	Grepafloxacin	Grepafloxacine	Grepafloksasiini	Grepafloxacine	Grepafloxacin	Γρεπαφλοξασίνη	Grepafloxacina	グレパフロキサシン	Grepafloxacin	Grepafloksacyna	Grepafloxacin	Grepafloxacină	Грепафлоксацин	Grepafloxacina	Grepafloxacin	Grepafloksasin	Грепафлоксацин
+Hachimycin	FALSE	TRUE	TRUE	FALSE	哈奇霉素	Hachimycin	Hachimycin	Hachimycine	Hachimysiini	Hachimycine	Hachimycin	Χαχιμυκίνη	Hachimycin	ハチマイシン	Hachimycin	Hachimycin	Hachimycin	Hachimicină	Хатимицин	Hachimycin	Hachimycin	Hachimycin	Хачиміцин
+Hetacillin	FALSE	TRUE	TRUE	FALSE	赫拉西林	Hetacilin	Hetacillin	Hetacilline	Hetasilliini	Hétacilline	Hetacillin	Ετακιλλίνη	Hetacillin	ヘタシリン	Hetacillin	Hetacylina	Hetacillin	Hetacilină	Гетациллин	Hetacilina	Hetacillin	Hetasilin	Гетацилін
+Imipenem	FALSE	TRUE	TRUE	FALSE	亚胺培南/西司他丁	Imipenem	Imipenem	Imipenem	Imipeneemi	Imipénème	Imipenem	Ιμιπενέμη	Imipenem	イミペネム	Imipenem	Imipenem	Imipenem	Imipenem	Имипенем	Imipenem	Imipenem	İmipenem	Іміпенем
+Imipenem/cilastatin	FALSE	TRUE	TRUE	FALSE	亚胺培南/西司他丁	Imipenem/cilastatin	Imipenem/cilastatin	Imipenem/enzymremmer	Imipeneemi/cilastatiini	Imipénème/cilastatine	Imipenem/Cilastatin	Ιμιπενέμη/σιλαστατίνη	Imipenem/cilastatina	イミペネム／シラスタチン	Imipenem/cilastatin	Imipenem/cilastatyna	Imipenem/coteltelatina	Imipenem/cilastatină	Имипенем/циластатин	Imipenem/cilastatina	Imipenem/cilastatin	İmipenem/silastatin	Іміпенем/циластатин
+Inosine pranobex	FALSE	TRUE	TRUE	FALSE	肌苷帕诺贝斯	Inosin pranobex	Inosin pranobex	Inosiplex	Inosiinipranobeksi	Inosine pranobex	Inosin-Pranobex	Ινοσίνη pranobex	Inosina pranobex	イノシン・プラノベックス	Inosin pranobex	Pranobeks inozyny	Pranobex inosine	Inosină pranobex	Инозин пранобекс	Inosina pranobex	Inosin pranobex	İnosin pranobeks	Інозин пранобекс
+Isepamicin	FALSE	TRUE	TRUE	FALSE	伊西帕米星	Isepamicin	Isepamicin	Isepamicine	Isepamysiini	Isepamicine	Isepamicin	Ισεπαµικίνη	Isepamicina	イセパマイシン	Isepamicin	Isepamicin	Isepamicina	Isepamicină	Исепамицин	Isepamicina	Isepamicin	İzepamisin	Ізепаміцин
+Isoconazole	FALSE	TRUE	TRUE	FALSE	氨甲蝶呤	Isokonazol	Isoconazol	Isoconazol	Isokonatsoli	Isoconazole	Isoconazol	Ισοκοναζόλη	Isoconazolo	イソコナゾール	Isokonazol	Izokonazol	Isoconazole	Isoconazol	Изоконазол	Isoconazol	Isokonazol	İzokonazol	Ізоконазол
+Isoniazid	FALSE	TRUE	TRUE	FALSE	伊索尼克酸	Isoniazid	Isoniazid	Isoniazide	Isoniatsidi	Isoniazide	Isoniazid	Ιζονιαζίδη	Isoniazide	イソニアジド	Isoniazid	Izoniazyd	Isoniazid	Isoniazidă	Изониазид	Isoniazida	Isoniazid	İzoniazid	Ізоніазид
+Itraconazole	FALSE	TRUE	TRUE	FALSE	伊曲康唑	Itrakonazol	Itraconazol	Itraconazol	Itrakonatsoli	Itraconazole	Itraconazol	Ιτρακοναζόλη	Itraconazolo	イトラコナゾール	Itrakonazol	Itrakonazol	Itraconazole	Itraconazol	Итраконазол	Itraconazol	Itrakonazol	İtrakonazol	Ітраконазол
+Josamycin	FALSE	TRUE	TRUE	FALSE	肌注	Josamycin	Josamycin	Josamycine	Josamysiini	Josamycine	Josamycin	Ζοζαμυκίνη	Josamicina	ホサマイシン	Josamycin	Josamycin	Josamycin	Josamicină	Джозамицин	Josamicina	Josamycin	Josamycin	Джозаміцин
+Kanamycin	FALSE	TRUE	TRUE	FALSE	卡那霉素	Kanamycin	Kanamycin	Kanamycine	Kanamysiini	Kanamycine	Kanamycin	Καναμυκίνη	Kanamicina	カナマイシン	Kanamycin	Kanamycin	Kanamycin	Kanamicină	Канамицин	Kanamicina	Kanamycin	Kanamisin	Канаміцин
+Ketoconazole	FALSE	TRUE	TRUE	FALSE	酮康唑	Ketokonazol	Ketoconazol	Ketoconazol	Ketokonatsoli	Kétoconazole	Ketoconazol	Κετοκοναζόλη	Ketoconazolo	ケトコナゾール	Ketokonazol	Ketokonazol	Ketoconazole	Ketoconazol	Кетоконазол	Ketoconazol	Ketokonazol	Ketokonazol	Кетоконазол
+Levofloxacin	FALSE	TRUE	TRUE	FALSE	氧氟沙星	Levofloxacin	Levofloxacin	Levofloxacine	Levofloksasiini	Lévofloxacine	Levofloxacin	Λεβοφλοξασίνη	Levofloxacina	レボフロキサシン	Levofloxacin	Levofloxacin	Levofloxacin	Levofloxacină	Левофлоксацин	Levofloxacina	Levofloxacin	Levofloksasin	Левофлоксацин
+Lincomycin	FALSE	TRUE	TRUE	FALSE	林可霉素	Linkomycin	Lincomycin	Lincomycine	Lincomycin	Lincomycine	Lincomycin	Λινκομυκίνη	Lincomicina	リンコマイシン	Lincomycin	Lincomycyna	Lincomycin	Lincomicină	Линкомицин	Lincomicina	Lincomycin	Lincomycin	Лінкоміцин
+Lomefloxacin	FALSE	TRUE	TRUE	FALSE	洛美沙星	Lomefloxacin	Lomefloxacin	Lomefloxacine	Lomefloksasiini	Loméfloxacine	Lomefloxacin	Λομεφλοξασίνη	Lomefloxacina	ロメフロキサシン	Lomefloksacin	Lomefloxacin	Lomefloxacin	Lomefloxacină	Ломефлоксацин	Lomefloxacina	Lomefloxacin	Lomefloksasin	Ломефлоксацин
+Lysozyme	FALSE	TRUE	TRUE	FALSE	硫酸钠	Lysozym	Lysozym	Lysozym	Lysotsyymi	Lysozyme	Lysozym	Λυσοζύμη	Lisozima	リゾチーム	Lysozym	Lizozym	Lysozyme	Lizozimă	Лизоцим	Lisozima	Lysozym	Lizozim	Лізоцим
+Mandelic acid	FALSE	TRUE	TRUE	FALSE	扁桃酸	Kyselina mandlová	Mandelinsyre	Amandelzuur	Mandelihappo	Acide mandélique	Mandelsäure	Μανδελικό οξύ	Acido mandelico	マンデル酸	Mandelsyre	Kwas migdałowy	Ácido mandélico	Acid mandelic	Мандаловая кислота	Ácido mandélico	Mandelsyra	Mandelik asit	Мигдалева кислота
+Meropenem	FALSE	TRUE	TRUE	FALSE	美罗培南	Meropenem	Meropenem	Meropenem	Meropeneemi	Méropénème	Meropenem	Μεροπενέμη	Meropenem	メロペネム	Meropenem	Meropenem	Meropenem	Meropenem	Меропенем	Meropenem	Meropenem	Meropenem	Меропенем
+Metampicillin	FALSE	TRUE	TRUE	FALSE	氨苄青霉素	Metampicilin	Metampicillin	Metampicilline	Metampisilliini	Métampicilline	Metampicillin	Μεταμπικιλλίνη	Metampicillina	メタンピシリン	Metampicillin	Metampicylina	Metampicilina	Metampicilină	Метампициллин	Metampicilina	Metampicillin	Metampisilin	Метампіцилін
+Meticillin	FALSE	TRUE	TRUE	FALSE	美西林	Meticilin	Meticillin	Meticilline	Metisilliini	Méticilline	Meticillin	Μετικιλλίνη	Meticillina	メチシリン	Meticillin	Meticillin	Meticillin	Meticilină	Метициллин	Meticilina	Meticillin	Metisilin	Метицилін
+Metisazone	FALSE	TRUE	TRUE	FALSE	氨甲喋呤	Metisazon	Metisazon	Metisazon	Metisatsoni	Métisazone	Metisazon	Μετισαζόνη	Metisazone	メチサゾン	Metisazon	Metisazon	Metisazone	Metisazonă	Метисазон	Metisazona	Metisazon	Metisazon	Метисазон
+Metronidazole	FALSE	TRUE	TRUE	FALSE	甲硝唑	Metronidazol	Metronidazol	Metronidazol	Metronidatsoli	Métronidazole	Metronidazol	Μετρονιδαζόλη	Metronidazolo	メトロニダゾール	Metronidazol	Metronidazol	Metronidazol	Metronidazol	Метронидазол	Metronidazol	Metronidazol	Metronidazol	Метронідазол
+Mezlocillin	FALSE	TRUE	TRUE	FALSE	氨甲蝶呤	Mezlocillin	Mezlocillin	Mezlocilline	Mezlocillin	Mezlocilline	Mezlocillin	Μεζλοκιλλίνη	Mezlocillina	メスロシリン	Mezlocillin	Mezlocillin	Mezlocillin	Mezlocilină	Мезлоциллин	Mezlocilina	Mezlocillin	Mezlosilin	Мезлоцилін
+Micafungin	FALSE	TRUE	TRUE	FALSE	咪蒙灵	Mikafungin	Micafungin	Micafungine	Mikafungiini	Micafungine	Micafungin	Μικαφουνγκίνη	Micafungin	ミカファンギン	Micafungin	Micafungin	Micafungin	Micafungin	Микафунгин	Micafungina	Micafungin	Mikafungin	Мікафунгін
+Miconazole	FALSE	TRUE	TRUE	FALSE	米康唑	Mikonazol	Miconazol	Miconazol	Miconazole	Miconazole	Miconazol	Μικροναζόλη	Miconazolo	ミコナゾール	Miconazol	Mikonazol	Miconazole	Miconazol	Миконазол	Miconazol	Miconazol	Mikonazol	Міконазол
+Midecamycin	FALSE	TRUE	TRUE	FALSE	咪康霉素	Midekamycin	Midecamycin	Midecamycine	Midecamycin	Midecamycine	Midecamycin	Μεδεκαμυκίνη	Midecamicina	ミデカマイシン	Midecamycin	Midecamycin	Midecamycin	Midecamicină	Мидекамицин	Midecamicina	Midecamycin	Midecamycin	Мідекаміцин
+Miocamycin	FALSE	TRUE	TRUE	FALSE	米卡霉素	Miocamycin	Miocamycin	Miocamycine	Miocamycin	Miocamycine	Miocamycin	Μειοκαμυκίνη	Miocamicina	ミオカマイシン	Miocamycin	Miocamycin	Miocamicina	Miocamicină	Миокамицин	Miocamycin	Miocamycin	Miocamycin	Міокаміцин
+Moxifloxacin	FALSE	TRUE	TRUE	FALSE	莫西沙星	Moxifloxacin	Moxifloxacin	Moxifloxacine	Moksifloksasiini	Moxifloxacine	Moxifloxacin	Μοξιφλοξασίνη	Moxifloxacin	モキシフロキサシン	Moxifloxacin	Moxifloxacin	Moxifloxacina	Moxifloxacin	Моксифлоксацин	Moxifloxacina	Moxifloxacin	Moksifloksasin	Моксифлоксацин
+Mupirocin	FALSE	TRUE	TRUE	FALSE	莫匹罗星	Mupirocin	Mupirocin	Mupirocine	Mupirosiini	Mupirocine	Mupirocin	Μουπιροκίνη	Mupirocina	ムピロシン	Mupirocin	Mupirocyna	Mupirocina	Mupirocin	Мупироцин	Mupirocina	Mupirocin	Mupirosin	Мупіроцин
+Nalidixic acid	FALSE	TRUE	TRUE	FALSE	萘啶酸	Kyselina nalidixová	Nalidixinsyre	Nalidixinezuur	Nalidiksiinihappo	Acide nalidixique	Nalidixinsäure	Ναλιδιξικό οξύ	Acido nalidixico	ナリディキシック酸	Nalidixinsyre	Kwas nalidyksowy	Ácido nalidíxico	Acid nalidixic	Налидиксовая кислота	Ácido nalidíxico	Nalidixinsyra	Nalidiksik asit	Налідиксова кислота
+Neomycin	FALSE	TRUE	TRUE	FALSE	霉素	Neomycin	Neomycin	Neomycine	Neomysiini	Néomycine	Neomycin	Νεομυκίνη	Neomicina	ネオマイシン	Neomycin	Neomycyna	Neomicina	Neomicină	Неомицин	Neomicina	Neomycin	Neomisin	Неоміцин
+Netilmicin	FALSE	TRUE	TRUE	FALSE	硝苯地平	Netilmicin	Netilmicin	Netilmicine	Netilmisiini	Netilmicine	Netilmicin	Νετιλµικίνη	Netilmicin	ネチルミシン	Netilmicin	Netilmicin	Netilmicin	Netilmicină	Нетилмицин	Netilmicina	Netilmicin	Netilmisin	Нетилміцин
+Nitrofurantoin	FALSE	TRUE	TRUE	FALSE	硝呋太尔	Nitrofurantoin	Nitrofurantoin	Nitrofurantoine	Nitrofurantoiini	Nitrofurantoïne	Nitrofurantoin	Νιτροφουραντοΐνη	Nitrofurantoina	ニトロフラントイン	Nitrofurantoin	Nitrofurantoina	Nitrofurantoína	Nitrofurantoină	Нитрофурантоин	Nitrofurantoína	Nitrofurantoin	Nitrofurantoin	Нітрофурантоїн
+Norfloxacin	FALSE	TRUE	TRUE	FALSE	诺氟沙星	Norfloxacin	Norfloxacin	Norfloxacine	Norfloksasiini	Norfloxacine	Norfloxacin	Νορφλοξασίνη	Norfloxacina	ノルフロキサシン	Norfloxacin	Norfloxacin	Norfloxacin	Norfloxacină	Норфлоксацин	Norfloxacina	Norfloxacin	Norfloksasin	Норфлоксацин
+Novobiocin	FALSE	TRUE	TRUE	FALSE	诺氟沙星	Novobiocin	Novobiocin	Novobiocine	Novobiosiini	Novobiocine	Novobiocin	Νοβοβιοκίνη	Novobiocin	ノボビオシン	Novobiocin	Nowobiocyna	Novobiocin	Novobiocin	Новобиоцин	Novobiocina	Novobiocin	Novobiocin	Новобіоцин
+Nystatin	FALSE	TRUE	TRUE	FALSE	囊肿	Nystatin	Nystatin	Nystatine	Nystatin	Nystatine	Nystatin	Νυστατίνη	Nystatin	ナイスタチン	Nystatin	Nystatyna	Nystatin	Nistatină	Нистатин	Nistatina	Nystatin	Nistatin	Ністатин
+Ofloxacin	FALSE	TRUE	TRUE	FALSE	氧氟沙星	Ofloxacin	Ofloxacin	Ofloxacine	Ofloksasiini	Ofloxacine	Ofloxacin	Οφλοξασίνη	Ofloxacin	オフロキサシン	Ofloxacin	Ofloxacin	Ofloxacin	Ofloxacin	Офлоксацин	Ofloxacina	Ofloxacin	Ofloksasin	Офлоксацин
+Oleandomycin	FALSE	TRUE	TRUE	FALSE	奥兰多霉素	Oleandomycin	Oleandomycin	Oleandomycine	Oleandomysiini	Oleandomycine	Oleandomycin	Ολεαντομυκίνη	Oleandomicina	オレアンドマイシン	Oleandomycin	Oleandomycin	Oleandomicina	Oleandomicină	Олеандомицин	Oleandomicina	Oleandomycin	Oleandomisin	Олеандоміцин
+Ornidazole	FALSE	TRUE	TRUE	FALSE	奥硝唑	Ornidazol	Ornidazol	Ornidazol	Ornidatsoli	Ornidazole	Ornidazol	Ορνιδαζόλη	Ornidazolo	オルニダゾール	Ornidazol	Ornidazol	Ornidazole	Ornidazol	Орнидазол	Ornidazol	Ornidazol	Ornidazol	Орнідазол
+Oxacillin	FALSE	TRUE	TRUE	FALSE	奥沙西林	Oxacilin	Oxacillin	Oxacilline	Oksasilliini	Oxacilline	Oxacillin	Οξακιλλίνη	Oxacillina	オキサシリン	Oksacillin	Oksacylina	Oxacillin	Oxacilină	Оксациллин	Oxacilina	Oxacillin	Oksasilin	Оксацилін
+Oxolinic acid	FALSE	TRUE	TRUE	FALSE	氧氟沙星	Kyselina oxolinová	Oxolinsyre	Oxolinezuur	Oksoliinihappo	Acide oxolinique	Oxolinsäure	Οξολινικό οξύ	Acido ossolinico	オキソリニック酸	Oksolinsyre	Kwas oksolinowy	Ácido oxolínico	Acid oxolinic	Оксолиновая кислота	Ácido oxolínico	Oxolinsyra	Oksolinik asit	Оксолінова кислота
+Oxytetracycline	FALSE	TRUE	TRUE	FALSE	土四环素	Oxytetracyklin	Oxytetracyclin	Oxytetracycline	Oksitetrasykliini	Oxytétracycline	Oxytetracyclin	Οξυτετρακυκλίνη	Ossitetraciclina	オキシテトラサイクリン	Oksytetracyklin	Oksytetracyklina	Oxitetraciclina	Oxitetraciclină	Окситетрациклин	Oxitetraciclina	Oxytetracyklin	Oksitetrasiklin	Окситетрациклін
+Pazufloxacin	FALSE	TRUE	TRUE	FALSE	帕唑沙星	Pazufloxacin	Pazufloxacin	Pazufloxacine	Pazufloksasiini	Pazufloxacine	Pazufloxacin	Παζουφλοξασίνη	Pazufloxacin	パズフロキサシン	Pazufloxacin	Pazufloxacin	Pazufloxacin	Pazufloxacin	Пазуфлоксацин	Pazufloxacina	Pazufloxacin	Pazufloksasin	Пазуфлоксацин
+Pefloxacin	FALSE	TRUE	TRUE	FALSE	培氟沙星	Pefloxacin	Pefloxacin	Pefloxacine	Pefloksasiini	Péfloxacine	Pefloxacin	Πεφλοξασίνη	Pefloxacina	ペフロキサシン	Pefloxacin	Pefloksacyna	Pefloxacin	Pefloxacina	Пефлоксацин	Pefloxacina	Pefloxacin	Pefloksasin	Пефлоксацин
+Penamecillin	FALSE	TRUE	TRUE	FALSE	青霉素	Penamecilin	Penamecillin	Penamecilline	Penamekilliini	Pénamécilline	Penamecillin	Πεναμεσιλλίνη	Penamecillina	ペナメシリン	Penamecillin	Penamecylina	Penamecilina	Penamecilină	Пенамециллин	Penamecilina	Penamecillin	Penamecillin	Пенамецилін
+Penicillin	FALSE	TRUE	TRUE	FALSE	青霉素	Penicilin	Penicillin	Penicilline	Penisilliini	Pénicilline	Penicillin	Πενικιλλίνη	Penicillina	ペニシリン	Penicillin	Penicylina	Penicilina	Penicilină	Пенициллин	Penicilina	Penicillin	Penisilin	Пеніцилін
+Pheneticillin	FALSE	TRUE	TRUE	FALSE	菲尼克斯	Feneticilin	Pheneticillin	Feneticilline	Fenetisilliini	Phénéticilline	Pheneticillin	Φαινετικιλλίνη	Feneticillina	フェネチシリン	Feneticillin	Fenicylina	Pheneticillin	Feneticilină	Фенетициллин	Feneticilina	Feneticillin	Pheneticillin	Фенетіцилін
+Phenoxymethylpenicillin	FALSE	TRUE	TRUE	FALSE	苯氧甲基青霉素	Fenoxymethylpenicilin	Phenoxymethylpenicillin	Fenoxymethylpenicilline	Fenoksimetyylipenisilliini	Phénoxyméthylpénicilline	Phenoxymethylpenicillin	Φαινοξυμεθυλοπενικιλλίνη	Fenossimetilpenicillina	フェノキシメチルペニシリン	Fenoksymetylpenicillin	Fenoksymetylopenicylina	Fenoximetilpenicilina	Fenoximetilpenicilină	Феноксиметилпенициллин	Fenoximetilpenicilina	Fenoximetylpenicillin	Fenoksimetilpenisilin	Феноксиметилпеніцилін
+Pipemidic acid	FALSE	TRUE	TRUE	FALSE	吡哌酸	Kyselina pipemidová	Pipemidinsyre	Pipemidinezuur	Pipemidiinihappo	Acide pipémidique	Pipemidinsäure	Πιπεμιδικό οξύ	Acido pipemidico	ピペミド酸	Pipemidinsyre	Kwas pipemidowy	Ácido pipemídico	Acid pipemidic	Пипемидовая кислота	Ácido pipemídico	Pipemidinsyra	Pipemidik asit	Піпемідова кислота
+Piperacillin	FALSE	TRUE	TRUE	FALSE	哌拉西林	Piperacilin	Piperacillin	Piperacilline	Piperasilliini	Pipéracilline	Piperacillin	Πιπερακιλλίνη	Piperacillina	ピペラシリン	Piperacillin	Piperacillin	Piperacilina	Piperacilină	Пиперациллин	Piperacilina	Piperacillin	Piperasilin	Піперацилін
+Piperacillin/beta-lactamase inhibitor	FALSE	TRUE	TRUE	FALSE	哌拉西林/β-内酰胺酶抑制剂	Piperacilin/inhibitor beta-laktamázy	Piperacillin/beta-lactamasehæmmer	Piperacilline/enzymremmer	Piperasilliini/beeta-laktamaasin estäjä	Pipéracilline/inhib. de bêta-lactamase	Piperacillin/Beta-Lactamase-Hemmer	Αναστολέας της πιπερακιλλίνης/β-λακταμάσης	Piperacillina/inib. d. beta-lattamasi	ピペラシリン／β-ラクタマーゼ阻害剤	Piperacillin/beta-laktamasehemmer	Piperacylina/inhibitor beta-laktamazy	Piperacilina/inibid. da beta-lactamase	Inhibitor de piperacilină/beta-lactamază	Пиперациллин/ингибитор бета-лактамазы	Piperacilina/inhib. de la beta-lactamasa	Piperacillin/betalaktamashämmare	Piperasilin/beta-laktamaz inhibitörü	Піперацилін/інгібітор бета-лактамаз
+Piromidic acid	FALSE	TRUE	TRUE	FALSE	吡罗米酸	Kyselina piromidová	Piromidinsyre	Piromidinezuur	Piromidiinihappo	Acide piromidique	Piromidinsäure	Πηρομιδικό οξύ	Acido piromidico	ピロミジン酸	Piromidinsyre	Kwas piromidowy	Ácido piromídico	Acid piromidic	Пиромидовая кислота	Ácido piromídico	Piromidinsyra	Piromidik asit	Піромідова кислота
+Pivampicillin	FALSE	TRUE	TRUE	FALSE	哌拉西林	Pivampicilin	Pivampicillin	Pivampicilline	Pivampisilliini	Pivampicilline	Pivampicillin	Πιβαµπικιλλίνη	Pivampicillina	ピバンピシリン	Pivampicillin	Pivampicillin	Pivampicilina	Pivampicilină	Пивампициллин	Pivampicilina	Pivampicillin	Pivampisilin	Півампіцилін
+Polymyxin B	FALSE	TRUE	TRUE	FALSE	多粘菌素B	Polymyxin B	Polymyxin B	Polymyxine B	Polymysiini B	Polymyxine B	Polymyxin B	Πολυμυξίνη Β	Polimixina B	ポリミキシンB	Polymyxin B	Polimyksyna B	Polimixina B	Polimixină B	Полимиксин В	Polimixina B	Polymyxin B	Polimiksin B	Поліміксин B
+Posaconazole	FALSE	TRUE	TRUE	FALSE	泊沙康唑	Posakonazol	Posaconazol	Posaconazol	Posakonatsoli	Posaconazole	Posaconazol	Ποσακοναζόλη	Posaconazolo	ポサコナゾール	Posakonazol	Posaconazol	Posaconazole	Posaconazol	Посаконазол	Posaconazol	Posakonazol	Posakonazol	Позаконазол
+Pristinamycin	FALSE	TRUE	TRUE	FALSE	普利司特霉素	Pristinamycin	Pristinamycin	Pristinamycine	Pristinamysiini	Pristinamycine	Pristinamycin	Πριστιναμυκίνη	Pristinamicina	プリスチナマイシン	Pristinamycin	Pristinamycin	Pristinamicina	Pristinamicină	Пристинамицин	Pristinamicina	Pristinamycin	Pristinamisin	Пристинаміцин
+Procaine benzylpenicillin	FALSE	TRUE	TRUE	FALSE	普鲁卡因青霉素	Prokain benzylpenicilin	Prokainbenzylpenicillin	Benzylpenicillineprocaine	Prokaiinibentsyylipenisilliini	Procaïne benzylpénicilline	Procain-Benzylpenicillin	Βενζυλοπενικιλλίνη προκαΐνης	Procaina benzilpenicillina	プロカインベンジルペニシリン	Prokain benzylpenicillin	Benzylopenicylina prokainowa	Procaína benzilpenicilina	Benzilpenicilină procaină	Прокаин бензилпенициллин	Bencilpenicilina procaína	Prokainbenzylpenicillin	Prokain benzilpenisilin	Прокаїну бензилпеніцилін
+Propicillin	FALSE	TRUE	TRUE	FALSE	普利西林	Propicilin	Propicillin	Propicilline	Propisilliini	Propicilline	Propicillin	Προπικιλλίνη	Propicillina	プロピシリン	Propicillin	Propicylina	Propicilina	Propicilină	Пропициллин	Propicilina	Propicillin	Propisilin	Пропіцилін
+Prulifloxacin	FALSE	TRUE	TRUE	FALSE	普利沙星	Prulifloxacin	Prulifloxacin	Prulifloxacine	Prulifloksasiini	Prulifloxacine	Prulifloxacin	Προυλιφλοξασίνη	Prulifloxacina	プルリフロキサシン	Prulifloxacin	Prulifloksacyna	Prulifloxacina	Prulifloxacină	Прулифлоксацин	Prulifloxacina	Prulifloxacin	Prulifloksasin	Пруліфлоксацин
+Quinupristin/dalfopristin	FALSE	TRUE	TRUE	FALSE	奎宁斯丁/达夫普利斯丁	Chinupristin/dalfopristin	Quinupristin/dalfopristin	Quinupristine/dalfopristine	Kinupristiini/dalfopristiini	Quinupristine/dalfopristine	Quinupristin/Dalfopristin	Κινουπριστίνη/νταλφοπριστίνη	Quinupristina/dalfopristina	キヌプリスチン／ダルフォプリスチン	Quinupristin/dalfopristin	Quinupristin/dalfopristin	Quinupristin/dalfopristin	Quinupristin/dalfopristin	Квинупристин/дальфопристин	Quinupristina/dalfopristina	Quinupristin/dalfopristin	Quinupristin/dalfopristin	Хінупристин/дальфопристин
+Ribostamycin	FALSE	TRUE	TRUE	FALSE	利波霉素	Ribostamycin	Ribostamycin	Ribostamycine	Ribostamysiini	Ribostamycine	Ribostamycin	Ριμποσταμυκίνη	Ribostamicina	リボスタマイシン	Ribostamycin	Ribostamycyna	Ribostamicina	Ribostamicină	Рибостамицин	Ribostamicina	Ribostamycin	Ribostamisin	Рибостаміцин
+Rifabutin	FALSE	TRUE	TRUE	FALSE	利福布汀	Rifabutin	Rifabutin	Rifabutine	Rifabutiini	Rifabutine	Rifabutin	Ριφαμπουτίνη	Rifabutina	リファブチン	Rifabutin	Rifabutin	Rifabutin	Rifabutină	Рифабутин	Rifabutina	Rifabutin	Rifabutin	Рифабутин
+Rifampicin	FALSE	TRUE	TRUE	FALSE	利福平	Rifampicin	Rifampicin	Rifampicine	Rifampisiini	Rifampicine	Rifampicin	Ριφαμπικίνη	Rifampicina	リファンピシン	Rifampicin	Rifampicyna	Rifampicina	Rifampicină	Рифампицин	Rifampicina	Rifampicin	Rifampisin	Рифампіцин
+Rifampicin/pyrazinamide/ethambutol/isoniazid	FALSE	TRUE	TRUE	FALSE	利福平/吡嗪酰胺/乙胺丁醇/异烟肼	Rifampicin/pyrazinamid/ethambutol/isoniazid	Rifampicin/pyrazinamid/ethambutol/isoniazid	Rifampicine/pyrazinamide/ethambutol/isoniazide	Rifampisiini/pyratsiiniamidi/etambutoli/isonatsidi Rifampisiini/pyratsiiniamidi/etambutoli/isonatsidi	Rifampicine/pyrazinamide/éthambutol/isoniazide	Rifampicin/Pyrazinamid/Ethambutol/Isoniazid	Ριφαμπικίνη/πυραζιναμίδη/εθαμβουτόλη/ισονιαζίδη	Rifampicina/pirazinamide/etambutolo/isoniazide	リファンピシン／ピラジナミド／エタンブトール／イソニアジド	Rifampicin/pyrazinamid/etambutol/isoniazid	Rifampicyna/pirazinamid/etambutol/izoniazyd	Rifampicina/pirazinamida/etambutol/isoniazida	Rifampicină/pirazinamidă/etambutol/isoniazidă	Рифампицин/пиразинамид/этамбутол/исониазид	Rifampicina/pirazinamida/etambutol/isoniazida	Rifampicin/pyrazinamid/ethambutol/isoniazid	Rifampisin/pirazinamid/etambutol/izoniazid	Рифампіцин/піразинамід/етамбутол/ізоніазид
+Rifampicin/pyrazinamide/isoniazid	FALSE	TRUE	TRUE	FALSE	利福平/吡嗪酰胺/异烟肼	Rifampicin/pyrazinamid/isoniazid	Rifampicin/pyrazinamid/isoniazid	Rifampicine/pyrazinamide/isoniazide	Rifampisiini/pyratsiiniamidi/isonitsidi Rifampisiini/pyratsiiniamidi/isonitsidi	Rifampicine/pyrazinamide/isoniazide	Rifampicin/Pyrazinamid/Isoniazid	Ριφαμπικίνη/πυραζιναμίδη/ισονιαζίδη	Rifampicina/pirazinamide/isoniazide	リファンピシン/ピラジナミド/イソニアジド	Rifampicin/pyrazinamid/isoniazid	Rifampicyna/pirazynamid/izoniazyd	Rifampicina/pirazinamida/isoniazida	Rifampicină/pirazinamidă/isoniazidă	Рифампицин/пиразинамид/изониазид	Rifampicina/pirazinamida/isoniazida	Rifampicin/pyrazinamid/isoniazid	Rifampisin/pirazinamid/izoniazid	Рифампіцин/піразинамід/ізоніазид
+Rifampicin/isoniazid	FALSE	TRUE	TRUE	FALSE	利福平/异烟肼	Rifampicin/isoniazid	Rifampicin/isoniazid	Rifampicine/isoniazide	Rifampisiini/isonitsidi	Rifampicine/isoniazide	Rifampicin/Isoniazid	Ριφαμπικίνη/ισονιαζίδη	Rifampicina/isoniazide	リファンピシン/イソニアジド	Rifampicin/isoniazid	Rifampicyna/izoniazyd	Rifampicina/isoniazida	Rifampicină/isoniazidă	Рифампицин/изониазид	Rifampicina/isoniazida	Rifampicin/isoniazid	Rifampisin/izoniazid	Рифампіцин/ізоніазид
+Rifamycin	FALSE	TRUE	TRUE	FALSE	利福霉素	Rifamycin	Rifamycin	Rifamycine	Rifamysiini	Rifamycine	Rifamycin	Ριφαμυκίνη	Rifamicina	リファマイシン	Rifamycin	Rifamycyna	Rifamycin	Rifamicină	Рифамицин	Rifamicina	Rifamycin	Rifamisin	Рифаміцин
+Rifaximin	FALSE	TRUE	TRUE	FALSE	利福昔明	Rifaximin	Rifaximin	Rifaximine	Rifaksimiini	Rifaximine	Rifaximin	Ριφαξιμίνη	Rifaximina	リファキシミン	Rifaximin	Rifaximin	Rifaximin	Rifaximin	Рифаксимин	Rifaximina	Rifaximin	Rifaximin	Рифаксимін
+Rokitamycin	FALSE	TRUE	TRUE	FALSE	罗奇霉素	Rokitamycin	Rokitamycin	Rokitamycine	Rokitamysiini	Rokitamycine	Rokitamycin	Ροκιταμυκίνη	Rokitamicina	ロキタマイシン	Rokitamycin	Rokitamycyna	Rokitamycin	Rokitamicină	Рокитамицин	Rokitamicina	Rokitamycin	Rokitamisin	Рокітаміцин
+Rosoxacin	FALSE	TRUE	TRUE	FALSE	罗红霉素	Rosoxacin	Rosoxacin	Rosoxacine	Rosoksasiini	Rosoxacine	Rosoxacin	Ροζοξακίνη	Rosoxacina	ロソキサシン	Rosoksacin	Rosoxacin	Rosoxacina	Rosoxacin	Розоксацин	Rosoxacina	Rosoxacin	Rosoxacin	Розоксацин
+Roxithromycin	FALSE	TRUE	TRUE	FALSE	罗红霉素	Roxithromycin	Roxithromycin	Roxitromycine	Roksitromysiini	Roxithromycine	Roxithromycin	Ροξιθρομυκίνη	Roxitromicina	ロキシスロマイシン	Roxitromycin	Roksytromycyna	Roxitromicina	Roxitromicină	Рокситромицин	Roxitromicina	Roxitromycin	Roxithromycin	Рокситроміцин
+Rufloxacin	FALSE	TRUE	TRUE	FALSE	罗氟沙星	Rufloxacin	Rufloxacin	Rufloxacine	Rufloksasiini	Rufloxacine	Rufloxacin	Ρουφλοξασίνη	Rufloxacina	ルフロキサシン	Rufloxacin	Rufloxacin	Rufloxacin	Rufloxacin	Руфлоксацин	Rufloxacina	Rufloxacin	Rufloksasin	Руфлоксацин
+Sisomicin	FALSE	TRUE	TRUE	FALSE	西索米星	Sisomicin	Sisomicin	Sisomicine	Sisomisiini	Sisomicine	Sisomicin	Σισομικίνη	Sisomicina	シソマイシン	Sisomicin	Sisomicin	Sisomicina	Sisomicină	Сизомицин	Sisomicina	Sisomicin	Sisomisin	Сизоміцин
+Sodium aminosalicylate	FALSE	TRUE	TRUE	FALSE	氨基水杨酸钠	Aminosalicylát sodný	Natriumaminosalicylat	Aminosalicylzuur	Natriumaminosalisylaatti	Aminosalicylate de sodium	Natrium-Aminosalicylat	Αμινοσαλικυλικό νάτριο	Sodio aminosalicilato	アミノサリチル酸ソーダ	Natriumaminosalicylat	Aminosalicylan sodu	Aminosalicilato de sódio	Aminosalicilat de sodiu	Аминосалицилат натрия	Aminosalicilato de sodio	Natriumaminosalicylat	Sodyum aminosalisilat	Натрію аміносаліцилат
+Sparfloxacin	FALSE	TRUE	TRUE	FALSE	氨水杨酸钠	Sparfloxacin	Sparfloxacin	Sparfloxacine	Sparfloksasiini	Sparfloxacine	Sparfloxacin	Σπαρφλοξασίνη	Sparfloxacina	スパルフロキサシン	Sparfloxacin	Sparfloxacin	Sparfloxacin	Sparfloxacina	Спарфлоксацин	Esparfloxacina	Sparfloxacin	Sparfloksasin	Спарфлоксацин
+Spectinomycin	FALSE	TRUE	TRUE	FALSE	大观霉素	Spectinomycin	Spectinomycin	Spectinomycine	Spectinomycin	Spectinomycine	Spectinomycin	Σπεκτινομυκίνη	Spectinomycin	スペクチノマイシン	Spectinomycin	Spektynomycyna	Spectinomycin	Spectinomicină	Спектиномицин	Espectinomicina	Spektinomycin	Spektinomisin	Спектиноміцин
+Spiramycin	FALSE	TRUE	TRUE	FALSE	斯皮拉菌素	Spiramycin	Spiramycin	Spiramycine	Spiramysiini	Spiramycine	Spiramycin	Σπιραμυκίνη	Spiramicina	スピラマイシン	Spiramycin	Spiramycyna	Spiramycin	Spiramicină	Спирамицин	Espiramicina	Spiramycin	Spiramisin	Спіраміцин
+Spiramycin/metronidazole	FALSE	TRUE	TRUE	FALSE	螺旋霉素/甲硝唑	Spiramycin/metronidazol	Spiramycin/metronidazol	Spiramycine/metronidazol	Spiramysiini/metronidatsoli	Spiramycine/métronidazole	Spiramycin/Metronidazol	Σπιραμυκίνη/μετρονιδαζόλη	Spiramicina/metronidazolo	スピラマイシン／メトロニダゾール	Spiramycin/metronidazol	Spiramycyna/metronidazol	Spiramycin/metronidazol	Spiramicină/metronidazol	Спирамицин/метронидазол	Espiramicina/metronidazol	Spiramycin/metronidazol	Spiramisin/metronidazol	Спіраміцин/метронідазол
+Staphylococcus immunoglobulin	FALSE	TRUE	TRUE	FALSE	葡萄球菌免疫球蛋白	Stafylokokový imunoglobulin	Stafylokok-immunglobulin	Stafylokokkenimmunoglobuline	Staphylococcus-immunoglobuliini	Immunoglobuline staphylococcique	Staphylococcus-Immunoglobulin	Σταφυλόκοκκος ανοσοσφαιρίνη	Immunoglobulina per stafilococco	ブドウ球菌免疫グロブリン	Staphylococcus immunglobulin	Immunoglobulina gronkowcowa	Imunoglobulina de Staphylococcus	Imunoglobulină stafilococică	Стафилококковый иммуноглобулин	Inmunoglobulina estafilocócica	Immunoglobulin mot stafylokocker	Staphylococcus immünoglobulin	Стафілококовий імуноглобулін
+Streptoduocin	FALSE	TRUE	TRUE	FALSE	链霉素	Streptoduocin	Streptoduocin	Streptoduocine	Streptoduocin	Streptoduocine	Streptoduocin	Στρεπτοδουοκίνη	Streptoduocin	ストレプトデュオシン	Streptoduocin	Streptoduocin	Estreptoduocina	Streptoduocin	Стрептодуоцин	Estreptoduocina	Streptoduocin	Streptoduosin	Стрептодуоцин
+Streptomycin	FALSE	TRUE	TRUE	FALSE	霉素	Streptomycin	Streptomycin	Streptomycine	Streptomysiini	Streptomycine	Streptomycin	Στρεπτομυκίνη	Streptomicina	ストレプトマイシン	Streptomycin	Streptomycyna	Streptomycin	Streptomicină	Стрептомицин	Estreptomicina	Streptomycin	Streptomisin	Стрептоміцин
+Streptomycin/isoniazid	FALSE	TRUE	TRUE	FALSE	链霉素/异烟肼	Streptomycin/izoniazid	Streptomycin/isoniazid	Streptomycine/isoniazide	Streptomysiini/isoniasidi	Streptomycine/isoniazide	Streptomycin/Isoniazid	Στρεπτομυκίνη/ισονιαζίδη	Streptomicina/isoniazide	ストレプトマイシン/イソニアジド	Streptomycin/isoniazid	Streptomycyna/izoniazyd	Streptomicina/isoniazida	Streptomicină/isoniazidă	Стрептомицин/изониазид	Estreptomicina/isoniazida	Streptomycin/isoniazid	Streptomisin/izoniazid	Стрептоміцин/ізоніазид
+Sulbenicillin	FALSE	TRUE	TRUE	FALSE	磺苄西林	Sulbenicillin	Sulbenicillin	Sulbenicilline	Sulbenisilliini	Sulbenicilline	Sulbenicillin	Σουλμπενικιλλίνη	Sulbenicillina	スルベニシリン	Sulbenicillin	Sulbenicylina	Sulbenicilina	Sulbenicilină	Сульбенициллин	Sulbenicilina	Sulbenicillin	Sulbenisilin	Сульбеніцилін
+Sulfadiazine/tetroxoprim	FALSE	TRUE	TRUE	FALSE	磺胺嘧啶/四氧嘧啶	Sulfadiazin/tetroxoprim	Sulfadiazin/tetroxoprim	Sulfadiazine/tetroxoprim	Sulfadiatsiini/tetroksopriimi	Sulfadiazine/tetroxoprime	Sulfadiazin/Tetroxoprim	Σουλφαδιαζίνη/τετροξοπρίμη	Sulfadiazina/tetroxoprim	スルファジアジン/テトロキソプリム	Sulfadiazin/tetroksoprim	Sulfadiazyna/tetroksoprim	Sulfadiazina/tetroxoprim	Sulfadiazină/tetroxoprim	Сульфадиазин/тетроксоприм	Sulfadiazina/tetroxoprim	Sulfadiazin/tetroxoprim	Sülfadiazin/tetroksoprim	Сульфадіазин/тетроксоприм
+Sulfadiazine/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺嘧啶/三甲氧苄啶	Sulfadiazin/trimetoprim	Sulfadiazin/trimethoprim	Sulfadiazine/trimethoprim	Sulfadiatsiini/trimetopriimi	Sulfadiazine/triméthoprime	Sulfadiazin/Trimethoprim	Σουλφαδιαζίνη/τριμεθοπρίμη	Sulfadiazina/trimetoprim	スルファジアジン/トリメトプリム	Sulfadiazin/trimetoprim	Sulfadiazyna/trimetoprim	Sulfadiazina/trimethoprim	Sulfadiazină/trimetoprim	Сульфадиазин/триметоприм	Sulfadiazina/trimetoprima	Sulfadiazin/trimetoprim	Sülfadiazin/trimetoprim	Сульфадіазин/триметоприм
+Sulfadimidine/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺嘧啶/三甲氧苄啶	Sulfadimidin/trimetoprim	Sulfadimidin/trimethoprim	Sulfadimidine/trimethoprim	Sulfadimidiini/trimetopriimi	Sulfadimidine/triméthoprime	Sulfadimidin/Trimethoprim	Σουλφαδιμιδίνη/τριμεθοπρίμη	Sulfadimidina/trimetoprim	スルファジミジン／トリメトプリム	Sulfadimidin/trimetoprim	Sulfadimidyna/trimetoprim	Sulfadimidina/trimethoprim	Sulfadimidină/trimetoprim	Сульфадимидин/триметоприм	Sulfadimidina/trimetoprima	Sulfadimidin/trimetoprim	Sülfadimidin/trimetoprim	Сульфадимідин/триметоприм
+Sulfafurazole	FALSE	TRUE	TRUE	FALSE	磺胺呋喃唑	Sulfafurazol	Sulfafurazol	Sulfafurazol	Sulfafuratsoli	Sulfafurazole	Sulfafurazol	Σουλφαφουραζόλη	Sulfafurazolo	スルファフラゾール	Sulfafurazol	Sulfafurazol	Sulfafurazole	Sulfafurazol	Сульфафуразол	Sulfafurazol	Sulfafurazol	Sülfafurazol	Сульфафуразол
+Sulfaisodimidine	FALSE	TRUE	TRUE	FALSE	磺胺二甲嘧啶	Sulfaisodimidin	Sulfaisodimidin	Sulfisomidine	Sulfaisodimidiini	Sulfaisodimidine	Sulfaisodimidin	Σουλφαϊζοδιμιδίνη	Sulfaisodimidina	スルファイソジミジン	Sulfaisodimidin	Sulfaisodimidine	Sulfaisodimidina	Sulfaisodimidină	Сульфаизодимидин	Sulfaisodimidina	Sulfaisodimidin	Sülfaizodimidin	Сульфаізодимідин
+Sulfalene	FALSE	TRUE	TRUE	FALSE	磺胺类药物	Sulfalen	Sulfalen	Sulfaleen	Sulfaleeni	Sulfalène	Sulfalene	Σουλφαλένιο	Sulfalene	スルファレン	Sulfen	Sulfalen	Sulfaleno	Sulfalenă	Сульфален	Sulfaleno	Sulfen	Sülfalen	Сульфален
+Sulfamazone	FALSE	TRUE	TRUE	FALSE	磺胺脒	Sulfamazon	Sulfamazon	Sulfamazon	Sulfamatsoni	Sulfamazone	Sulfamazon	Σουλφαμαζόνη	Sulfamazone	スルファマゾン	Sulfamazon	Sulfamazon	Sulfamazona	Sulfamazonă	Сульфамазон	Sulfamazona	Sulfamazon	Sülfamazon	Сульфамазон
+Sulfamerazine/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺脒/三甲氧苄氨嘧啶	Sulfamerazin/trimetoprim	Sulfamerazin/trimethoprim	Sulfamerazine/trimethoprim	Sulfameratsiini/trimetopriimi	Sulfamérazine/triméthoprime	Sulfamerazin/Trimethoprim	Σουλφαμεραζίνη/τριμεθοπρίμη	Sulfamerazina/trimetoprim	スルファメラジン／トリメトプリム	Sulfamerazin/trimetoprim	Sulfamerazyna/trimetoprim	Sulfamerazina/trimethoprim	Sulfamerazină/trimetoprim	Сульфамеразин/триметоприм	Sulfamerazina/trimetoprima	Sulfamerazin/trimetoprim	Sülfamerazin/trimetoprim	Сульфамеразин/триметоприм
+Sulfamethizole	FALSE	TRUE	TRUE	FALSE	磺胺甲基咪唑	Sulfamethizol	Sulfamethizol	Sulfamethizol	Sulfametatsoli	Sulfaméthizole	Sulfamethizol	Sulfamethizole	Sulfamethizolo	スルファメチゾール	Sulfametizol	Sulfamethizole	Sulfametizole	Sulfamețizol	Сульфаметизол	Sulfametozol	Sulfamethizol	Sülfametizol	Сульфаметізол
+Sulfamethoxazole	FALSE	TRUE	TRUE	FALSE	磺胺甲噁唑	Sulfamethoxazol	Sulfamethoxazol	Sulfamethoxazol	Sulfametoksatsoli	Sulfaméthoxazole	Sulfamethoxazol	Σουλφαμεθοξαζόλη	Sulfametossazolo	スルファメトキサゾール	Sulfametoksazol	Sulfametoksazol	Sulfamethoxazole	Sulfametoxazol	Сульфаметоксазол	Sulfametoxazol	Sulfametoxazol	Sülfametoksazol	Сульфаметоксазол
+Sulfamethoxazole/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺甲噁唑/三甲氧苄啶	Sulfamethoxazol/trimethoprim	Sulfamethoxazol/trimethoprim	Sulfamethoxazol/trimethoprim	Sulfametoksatsoli/trimetopriimi	Sulfaméthoxazole/triméthoprime	Sulfamethoxazol/Trimethoprim	Σουλφαμεθοξαζόλη/τριμεθοπρίμη	Sulfametossazolo/trimetoprim	スルファメトキサゾール／トリメトプリム	Sulfametoksazol/trimetoprim	Sulfametoksazol/trimetoprim	Sulfametoxazol/trimethoprim	Sulfametoxazol/trimetoprim	Сульфаметоксазол/триметоприм	Sulfametoxazol/trimetoprima	Sulfametoxazol/trimetoprim	Sülfametoksazol/trimetoprim	Сульфаметоксазол/триметоприм
+Sulfametoxydiazine	FALSE	TRUE	TRUE	FALSE	磺胺甲噁唑	Sulfametoxydiazin	Sulfametoxydiazin	Sulfamethoxydiazine	Sulfametoksidiatsiini	Sulfamétoxydiazine	Sulfametoxydiazin	Σουλφαμετοξυδιαζίνη	Sulfametoxydiazine	スルファメトキシジアジン	Sulfametoksydiazin	Sulfametoksydiazyna	Sulfametoxidiazina	Sulfametoxidiazină	Сульфаметоксидиазин	Sulfametoxidiazina	Sulfametoxydiazin	Sulfametoksidiyazin	Сульфаметоксидіазин
+Sulfametrole/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺甲醚/三甲氧嘧啶	Sulfametrol/trimetoprim	Sulfametrol/trimethoprim	Sulfametrol/trimethoprim	Sulfametroli/trimetopriimi	Sulfamétrole/triméthoprime	Sulfametrole/Trimethoprim	Σουλφαμετρόλη/τριμεθοπρίμη	Sulfametrole/trimetoprim	スルファメトロール/トリメトプリム	Sulfametrol/trimetoprim	Sulfametrol/trimetoprim	Sulfametrole/trimethoprim	Sulfametrole/trimetoprim	Сульфаметрол/триметоприм	Sulfametrol/trimetoprima	Sulfametrol/trimetoprim	Sülfametrol/trimetoprim	Сульфаметрол/триметоприм
+Sulfamoxole	FALSE	TRUE	TRUE	FALSE	磺胺甲噁唑	Sulfamoxol	Sulfamoxol	Sulfamoxol	Sulfamoksoli	Sulfamoxole	Sulfamoxol	Σουλφαμοξόλη	Sulfamoxolo	スルファモキソール	Sulfamoksol	Sulfamoksol	Sulfamoxole	Sulfamoxol	Сульфамоксол	Sulfamoxole	Sulfamoxol	Sülfamoksol	Сульфамоксол
+Sulfamoxole/trimethoprim	FALSE	TRUE	TRUE	FALSE	磺胺甲噁唑/三甲氧苄啶	Sulfamoxol/trimetoprim	Sulfamoxol/trimethoprim	Sulfamoxol/trimethoprim	Sulfamoksoli/trimetopriimi	Sulfamoxole/triméthoprime	Sulfamoxol/Trimethoprim	Σουλφαμοξόλη/τριμεθοπρίμη	Sulfamoxolo/trimetoprim	スルファモキソール/トリメトプリム	Sulfamoksol/trimetoprim	Sulfamoksol/trimetoprim	Sulfamoxole/trimethoprim	Sulfamoxol/trimetoprim	Сульфамоксол/триметоприм	Sulfamoxol/trimetoprima	Sulfamoxol/trimetoprim	Sülfamoksol/trimetoprim	Сульфамоксол/триметоприм
+Sulfaperin	FALSE	TRUE	TRUE	FALSE	磺胺类药物	Sulfaperin	Sulfaperin	Sulfaperine	Sulfaperiini	Sulfapérine	Sulfaperin	Σουλφαπερίνη	Sulfaperin	スルファペリン	Sulfaperin	Sulfaperin	Sulfaperin	Sulfaperin	Сульфаперин	Sulfametoxazol	Sulfaperin	Sülfaperin	Сульфаперин
+Sulfaphenazole	FALSE	TRUE	TRUE	FALSE	磺胺苯吡唑	Sulfafenazol	Sulfaphenazol	Sulfafenazol	Sulfafenatsoli	Sulfaphénazole	Sulfaphenazol	Σουλφαφαιναζόλη	Sulfafenazolo	スルファフェナゾール	Sulfafenazol	Sulfafenazol	Sulfafenazol	Sulfafenazol	Сульфафеназол	Sulfafenazol	Sulfafenazol	Sülfafenazol	Сульфафеназол
+Sulfathiazole	FALSE	TRUE	TRUE	FALSE	磺胺噻唑	Sulfathiazol	Sulfathiazol	Sulfathiazol	Sulfatiatsoli	Sulfathiazole	Sulfathiazol	Σουλφαθειαζόλη	Sulfathiazole	スルファチアゾール	Sulfatiazol	Sulfatiazol	Sulfatazol	Sulfatiazol	Сульфатиазол	Sulfatiazol	Sulfathiazol	Sulfathiazole	Сульфатіазол
+Sulfathiourea	FALSE	TRUE	TRUE	FALSE	磺胺硫脲	Sulfathiomočovina	Sulfathiourea	Sulfathioureum	Sulfathiourea	Sulfathiourée	Sulfathioharnstoff	Σουλφαθειουρία	Sulfathiourea	スルファチオ尿素	Sulfathiourea	Sulfathiourea	Sulfathiourea	Sulfathiourea	Сульфатиомочевина	Sulfathiourea	Sulfatiourea	Sulfathiourea	Сульфатіосечовина
+Sultamicillin	FALSE	TRUE	TRUE	FALSE	苏打米林	Sultamicilin	Sultamicillin	Sultamicilline	Sultamisilliini	Sultamicilline	Sultamicillin	Σουλταμικιλλίνη	Sultamicillina	スルタミシリン	Sultamicillin	Sultamicillin	Sultamicillin	Sultamicilină	Сультамициллин	Sultamicilina	Sultamicillin	Sultamicillin	Сультаміцилін
+Talampicillin	FALSE	TRUE	TRUE	FALSE	塔拉比西林	Talampicilin	Talampicillin	Talampicilline	Talampisilliini	Talampicilline	Talampicillin	Ταλαμπικιλλίνη	Talampicillina	タランピシリン	Talampicillin	Talampicylina	Talampicilina	Talampicilină	Талампициллин	Talampicilina	Talampicillin	Talampisilin	Талампіцилін
+Teicoplanin	FALSE	TRUE	TRUE	FALSE	泰科普兰素	Teicoplanin	Teicoplanin	Teicoplanine	Teikoplaniini	Teicoplanine	Teicoplanin	Τεϊκοπλανίνη	Teicoplanina	テイコプラニン	Teicoplanin	Teicoplanin	Teicoplanin	Teicoplanin	Тейкопланин	Teicoplanina	Teicoplanin	Teikoplanin	Тейкопланін
+Telithromycin	FALSE	TRUE	TRUE	FALSE	泰利霉素	Telithromycin	Telithromycin	Telitromycine	Telitromysiini	Télithromycine	Telithromycin	Τελιθρομυκίνη	Telitromicina	テリスロマイシン	Telitromycin	Telitromycyna	Telitromicina	Telitromicină	Телитромицин	Telitromicina	Telitromycin	Telitromisin	Телітроміцин
+Temafloxacin	FALSE	TRUE	TRUE	FALSE	氨甲环酸	Temafloxacin	Temafloxacin	Temafloxacine	Temafloksasiini	Temafloxacine	Temafloxacin	Τεμαφλοξασίνη	Temafloxacina	テマフロキサシン	Temafloxacin	Temafloksacyna	Temafloxacin	Temafloxacin	Темафлоксацин	Temafloxacina	Temafloxacin	Temafloksasin	Темафлоксацин
+Temocillin	FALSE	TRUE	TRUE	FALSE	氨甲蝶呤	Temocillin	Temocillin	Temocilline	Temosilliini	Temocillin	Temocillin	Τεμοκιλλίνη	Temocillina	テモシリン	Temocillin	Temocillin	Temocillin	Temocilină	Темоциллин	Temocilina	Temocillin	Temocillin	Темоцилін
+Tenofovir disoproxil	FALSE	TRUE	TRUE	FALSE	特诺福韦酯	Tenofovir disoproxil	Tenofovir disoproxil	Tenofovir	Tenofoviiridisoproksiili	Tenofovir disoproxil	Tenofovir Disoproxil	Τενοφοβίρη δισοπροξίλη	Tenofovir disoproxil	テノホビルジソプロキシル	Tenofovir disoproxil	Tenofovir disoproxil	Tenofovir disoproxil	Tenofovir disoproxil	Тенофовир дизопроксил	Tenofovir disoproxil	Tenofovir disoproxil	Tenofovir disoproksil	Тенофовір дизопроксил
+Terizidone	FALSE	TRUE	TRUE	FALSE	特立兹酮	Terizidon	Terizidon	Terizidon	Teritsidoni	Terizidone	Terizidon	Τεριζιδόνη	Terizidone	テリジドン	Terizidon	Terizidon	Terizidone	Terizidonă	Теризидон	Terizidona	Terizidon	Terizidon	Теризидон
+Thiamphenicol	FALSE	TRUE	TRUE	FALSE	硫苯尼考	Thiamfenikol	Thiamphenicol	Thiamfenicol	Tiamfenikoli	Thiamphénicol	Thiamphenicol	Θειαμφενικόλη	Tiamfenicolo	チアンフェニコール	Tiamfenikol	Tiamfenikol	Tiamfenicol	Tiamfenicol	Тиамфеникол	Tiamfenicol	Tiamfenikol	Thiamphenicol	Тіамфенікол
+Thioacetazone/isoniazid	FALSE	TRUE	TRUE	FALSE	硫乙酰唑酮/异烟肼	Thioacetazon/isoniazid	Thioacetazon/isoniazid	Thioacetazon/isoniazide	Tioasetatsoni/isonatsidi	Thioacétazone/isoniazide	Thioacetazon/Isoniazid	Θειοακεταζόνη/ισονιαζίδη	Tioacetazone/isoniazide	チオアセタゾン／イソニアジド	Thioacetazon/isoniazid	Tioacetazon/izoniazyd	Thioacetazone/isoniazid	Tioacetazonă/isoniazidă	Тиоацетазон/изониазид	Tioacetazona/isoniazida	Thioacetazon/isoniazid	Tiyoasetazon/izoniazid	Тіоацетазон/ізоніазид
+Ticarcillin	FALSE	TRUE	TRUE	FALSE	替卡西林	Tykarcilinu	Ticarcillin	Ticarcilline	Ticarcillin	Ticarcilline	Ticarcillin	Τικαρκιλλίνη	Ticarcillina	チカルシリン	Ticarcillin	Ticarcillin	Ticarcilina	Ticarcilină	Тикарциллин	Ticarcilina	Ticarcillin	Ticarcillin	Тикарцилін
+Ticarcillin/beta-lactamase inhibitor	FALSE	TRUE	TRUE	FALSE	替卡西林/β-内酰胺酶抑制剂	Tykarcilinu/beta-laktamázy Inhibitor	Ticarcillin/beta-lactamasehæmmer	Ticarcilline/enzymremmer	Tikarsilliini/beeta-laktamaasin estäjä	Ticarcilline/inhib. de bêta-lactamase	Ticarcillin/Beta-Lactamase-Hemmer	Αναστολέας της τικαρκιλλίνης/β-λακταμάσης	Ticarcillina/inib. d. beta-lattamasi	チカルシリン／β-ラクタマーゼ阻害剤	Ticarcillin/betalaktamaseinhibitor	Tikarcylina/inhibitor beta-laktamazy	Ticarcilina/inibid. da beta-lactamase	Inhibitor de ticarcilină/beta-lactamază	Тикарциллин/ингибитор бета-лактамазы	Ticarcilina/inhib. de la betalactamasa	Ticarcillin/beta-laktamashämmare	Tikarsilin/beta-laktamaz inhibitörü	Тикарцилін/інгібітор бета-лактамаз
+Ticarcillin/clavulanic acid	FALSE	TRUE	TRUE	FALSE	替卡西林/克拉维酸	Ticarcillin/kyselina klavulanová	Ticarcillin/clavulansyre	Ticarcilline/clavulaanzuur	Tikarsilliini/klavulaanihappo	Ticarcilline/acide clavulanique	Ticarcillin/Clavulansäure	Τικαρκιλλίνη/κλαβουλανικό οξύ	Ticarcillina/acido clavulanico	チカルシリン／クラブラン酸	Ticarcillin/klavulansyre	Tikarcylina/kwas klawulanowy	Ticarcilina/ácido clavulanico	Ticarcilină/acid clavulanic	Тикарциллин/клавулановая кислота	Ticarcilina/ácido clavulánico	Ticarcillin/clavulansyra	Tikarsilin/klavulanik asit	Тикарцилін/клавуланова кислота
+Tinidazole	FALSE	TRUE	TRUE	FALSE	替尼唑	Tinidazol	Tinidazol	Tinidazol	Tinidatsoli	Tinidazole	Tinidazol	Τινιδαζόλη	Tinidazolo	チニダゾール	Tinidazol	Tinidazol	Tinidazole	Tinidazol	Тинидазол	Tinidazol	Tinidazol	Tinidazol	Тинідазол
+Tobramycin	FALSE	TRUE	TRUE	FALSE	妥布霉素	Tobramycin	Tobramycin	Tobramycine	Tobramysiini	Tobramycine	Tobramycin	Τομπραμυκίνη	Tobramicina	トブラマイシン	Tobramycin	Tobramycyna	Tobramycin	Tobramicină	Тобрамицин	Tobramicina	Tobramycin	Tobramisin	Тобраміцин
+Trimethoprim/sulfamethoxazole	FALSE	TRUE	TRUE	FALSE	三甲氧嘧啶/磺胺甲恶唑	Trimethoprim/sulfametoxazol	Trimethoprim/sulfamethoxazol	Cotrimoxazol	Trimetopriimi/sulfametoksatsoli	Triméthoprime/sulfaméthoxazole	Trimethoprim/Sulfamethoxazol	Τριµεθοπρίµη/σουλφαµεθοξαζόλη	Trimetoprim/sulfametossazolo	トリメトプリム／スルファメトキサゾール	Trimetoprim/sulfametoksazol	Trimetoprim/sulfametoksazol	Trimethoprim/sulfametoxazol	Trimetoprim/sulfametoxazol	Триметоприм/сульфаметоксазол	Trimetoprima/sulfametoxazol	Trimetoprim/sulfametoxazol	Trimetoprim/sülfametoksazol	Триметоприм/сульфаметоксазол
+Troleandomycin	FALSE	TRUE	TRUE	FALSE	托拉多霉素	Troleandomycin	Troleandomycin	Troleandomycine	Troleandomysiini	Troleandomycine	Troleandomycin	Τρολεαντομυκίνη	Troleandomicina	トロレアンドマイシン	Troleandomycin	Troleandomycyna	Troleandomicina	Troleandomicină	Тролеандомицин	Troleandomicina	Troleandomycin	Troleandomisin	Тролеандоміцин
+Trovafloxacin	FALSE	TRUE	TRUE	FALSE	特戊沙星	Trovafloxacin	Trovafloxacin	Trovafloxacine	Trovafloksasiini	Trovafloxacine	Trovafloxacin	Τροβαφλοξασίνη	Trovafloxacin	トロバフロキサシン	Trovafloxacin	Trovafloxacin	Trovafloxacin	Trovafloxacină	Тровафлоксацин	Trovafloxacina	Trovafloxacin	Trovafloksasin	Тровафлоксацин
+Vancomycin	FALSE	TRUE	TRUE	FALSE	唑啉酮	Vankomycin	Vancomycin	Vancomycine	Vankomysiini	Vancomycine	Vancomycin	Βανκομυκίνη	Vancomicina	バンコマイシン	Vancomycin	Wankomycyna	Vancomycin	Vancomicină	Ванкомицин	Vancomicina	Vancomycin	Vankomisin	Ванкоміцин
+Voriconazole	FALSE	TRUE	TRUE	FALSE	伏立康唑	Vorikonazol	Voriconazol	Voriconazol	Vorikonatsoli	Voriconazole	Voriconazol	Βορικοναζόλη	Voriconazolo	ボリコナゾール	Vorikonazol	Worikonazol	Voriconazol	Voriconazol	Вориконазол	Voriconazol	Vorikonazol	Vorikonazol	Вориконазол
+Aminoglycosides	FALSE	TRUE	TRUE	FALSE	氨基糖苷类	Aminoglykosidy	Aminoglykosider	Aminoglycosiden	Aminoglykosidit	Aminoglycosides	Aminoglykoside	Αμινογλυκοσίδες	Aminoglicosidi	アミノグリコシド系抗生物質	Aminoglykosider	Aminoglikozydy	Aminoglycosides	Aminoglicozide	Аминогликозиды	Aminoglucósidos	Aminoglykosider	Aminoglikozidler	Аміноглікозиди
+Amphenicols	FALSE	TRUE	TRUE	FALSE	安息香醇	Amfenikoly	Amphenicoler	Amfenicolen	Amfenikolit	Amphénicols	Amphenicole	Αμφενικόλες	Amphenicols	アンフェニコール	Amfenikoler	Amfenikol	Anfenicóis	Amfenicoli	Амфениколы	Anfenicoles	Amfenikoler	Amphenicols	Амфеніколи
+Antifungals/antimycotics	FALSE	TRUE	TRUE	FALSE	抗真菌药/抗真菌药	Antimykotika/antimykotika	Antimykotika/antimykotika	Antifungica/antimycotica	Sienilääkkeet/antimykootit	Antifongiques/antimycotiques	Antimykotika/Antimykotika	Αντιμυκητιασικά/αντιμυκητιασικά	Antifungini/antimicotici	抗真菌剤／抗真菌剤	Soppdrepende midler/antimykotika	Środki przeciwgrzybicze/przeciwmikotyczne	Antifúngicos/antimicóticos	Antifungice/antimicrotice	Противогрибковые препараты/антимикотики	Antifúngicos/antimicóticos	Antimykotika/antimykotika	Antifungaller/antimikotikler	Протигрибкові засоби/антимікотики
+Antimycobacterials	FALSE	TRUE	TRUE	FALSE	抗霉菌素类	Antimykobakteriální látky	Antimycobakterier	Antimycobacteriele middelen	Antimykobakteerit	Antimycobactériens	Antimykobakterielle Mittel	Αντιμυκοβακτηριακά	Antimicobatterici	抗マイコバクテリア薬	Antimykobakterielle midler	Środki przeciwgrzybicze	Antimycobacterials	Antimicobacteriene	Антимикобактериальные препараты	Antimicrobianos	Antimykobakterier	Antimikobakteriyeller	Засоби, що діють на мікобактерії
+Beta-lactams/penicillins	FALSE	TRUE	TRUE	FALSE	β-内酰胺类/青霉素类	Beta-laktamy/peniciliny	Beta-lactamer/penicilliner	Beta-lactams/penicillines	Beetalaktaamit/penisilliinit	Bêta-lactamines/pénicillines	Beta-Lactame/Penicilline	Β-λακτάμες/πενικιλλίνες	Beta-lattami/penicilline	β-ラクタム系／ペニシリン系抗菌薬	Betalaktamer/penicilliner	Beta-laktamy/penicyliny	Beta-lactâmicas/penicilinas	Beta-lactame/peniciline	Бета-лактамы/пенициллины	Beta-lactámicos/penicilinas	Beta-laktamer/penicilliner	Beta-laktamlar/penisilinler	Бета-лактами/пеніциліни
+Cephalosporins (1st gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素类（第一代）	Cefalosporiny (1. gen.)	Cefalosporiner (1. gen.)	Cefalosporines (1e gen.)	Kefalosporiinit (1. suk.)	Céphalosporines (1ère génération)	Cephalosporine (1. Gen.)	Κεφαλοσπορίνες (1ου γένους)	Cefalosporine (1° gen.)	セファロスポリン系抗生物質（第1世代）	Cefalosporiner (1. generasjon)	Cefalosporyny (1. gen.)	Cefalosporinas (1º género)	Cefalosporine (prima generație)	Цефалоспорины (1-го пок.)	Cefalosporinas (1er gen.)	Kefalosporiner (första gen.)	Sefalosporinler (1. kuşak)	Цефалоспорини (1 пок.)
+Cephalosporins (2nd gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素类（第二代）	Cefalosporiny (2. gen.)	Cefalosporiner (2. gen.)	Cefalosporines (2e gen.)	Kefalosporiinit (2. suk.)	Céphalosporines (2ème génération)	Cephalosporine (2. Gen.)	Κεφαλοσπορίνες (2ο γένος)	Cefalosporine (2° gen.)	セファロスポリン（第2世代）	Cefalosporiner (2. generasjon)	Cefalosporyny (2. gen.)	Cefalosporinas (2ª gen.)	Cefalosporine (a doua generație)	Цефалоспорины (2-го пок.)	Cefalosporinas (2do gen.)	Kefalosporiner (andra gen.)	Sefalosporinler (2. kuşak)	Цефалоспорини (2 пок.)
+Cephalosporins (3rd gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素类（第三代）	Cefalosporiny (3. gen.)	Cefalosporiner (3. gen.)	Cefalosporines (3e gen.)	Kefalosporiinit (3. suk.)	Céphalosporines (3ème génération)	Cephalosporine (3. Gen.)	Κεφαλοσπορίνες (3ο γένος)	Cefalosporine (3° gen.)	セファロスポリン（第3世代）	Cefalosporiner (3. generasjon)	Cefalosporyny (3 gen.)	Cefalosporinas (3ª gen.)	Cefalosporine (a treia generație)	Цефалоспорины (3-го пок.)	Cefalosporinas (3er gen.)	Kefalosporiner (tredje gen.)	Sefalosporinler (3. kuşak)	Цефалоспорини (3 пок.)
+Cephalosporins (4th gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素类（第四代）	Cefalosporiny (4. gen.)	Cefalosporiner (4. gen.)	Cefalosporines (4e gen.)	Kefalosporiinit (4. suk.)	Céphalosporines (4ème génération)	Cephalosporine (4. Gen.)	Κεφαλοσπορίνες (4ο γένος)	Cefalosporine (4° gen.)	セファロスポリン（第4世代）	Cefalosporiner (4. generasjon)	Cefalosporyny (4 gen.)	Cefalosporinas (4.ª gen.)	Cefalosporine (a 4-a generație)	Цефалоспорины (4-го пок.)	Cefalosporinas (4ª gen.)	Kefalosporiner (4:e gen.)	Sefalosporinler (4. kuşak)	Цефалоспорини (4 пок.)
+Cephalosporins (5th gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素（第五代）	Cefalosporiny (5. gen.)	Cefalosporiner (5. gen.)	Cefalosporines (5e gen.)	Kefalosporiinit (5. suk.)	Céphalosporines (5e gén.)	Cephalosporine (5. Gen.)	Κεφαλοσπορίνες (5ο γένος)	Cefalosporine (5° gen.)	セファロスポリン（第5世代）	Cefalosporiner (5. generasjon)	Cefalosporyny (5. gen.)	Cefalosporinas (5.ª gen.)	Cefalosporine (a 5-a generație)	Цефалоспорины (5-го пок.)	Cefalosporinas (5º gen.)	Kefalosporiner (5:e gen.)	Sefalosporinler (5. kuşak)	Цефалоспорини (5 пок.)
+Cephalosporins (unclassified gen.)	FALSE	TRUE	TRUE	FALSE	头孢菌素类（未分类的一代）	Cefalosporiny (nezařazené)	Cefalosporiner (uklassificeret gen.)	Cefalosporines (ongeclassificeerd)	Kefalosporiinit (luokittelematon suk.)	Céphalosporines (genre non classifié)	Cephalosporine (unklassifiziert)	Κεφαλοσπορίνες (μη ταξινομημένο γένος)	Cefalosporine (gen. non classificato)	セファロスポリン（未分類の世代）	Cefalosporiner (uklassifisert generasjon)	Cefalosporyny (niesklasyfikowana gen.)	Cefalosporinas (não classificado gen.)	Cefalosporine (generație neclasificată)	Цефалоспорины (неклассифицированный род)	Cefalosporinas (gen. no clasificado)	Kefalosporiner (oklassificerad gen.)	Sefalosporinler (sınıflandırılmamış nesil)	Цефалоспорини (некласифікованого пок.)
+Cephalosporins	FALSE	TRUE	TRUE	FALSE	头孢菌素类	Cefalosporiny	Cefalosporiner	Cefalosporines	Kefalosporiinit	Céphalosporines	Cephalosporine	Κεφαλοσπορίνες	Cefalosporine	セファロスポリン	Cefalosporiner	Cefalosporyny	Cefalosporinas	Cefalosporine	Цефалоспорины	Cefalosporinas	Kefalosporiner	Sefalosporinler	Цефалоспорини
+Glycopeptides	FALSE	TRUE	TRUE	FALSE	糖肽类药物	Glykopeptidy	Glykopeptider	Glycopeptiden	Glykopeptidit	Glycopeptides	Glykopeptide	Γλυκοπεπτίδια	Glicopeptidi	糖ペプチド系	Glykopeptider	Glikopeptydy	Glycopeptides	Glicopeptide	Гликопептиды	Glicopéptidos	Glykopeptider	Glikopeptitler	Глікопептиди
+Macrolides/lincosamides	FALSE	TRUE	TRUE	FALSE	大环内酯类/林可酰胺类	Makrolidy/linkosamidy	Makrolider/lincosamider	Macroliden/lincosamiden	Makrolidit/linkosamidit	Macrolides/lincosamides	Makrolide/Linkosamide	Μακρολίδια/λινκοσαμίδια	Macrolidi/lincosamidi	マクロライド系/リンコサミド系	Makrolider/lincosamider	Makrolidy/linkozamidy	Macrolides/lincosamidas	Macrolide/lincosamide	Макролиды/линкозамиды	Macrólidos/lincosamidas	Makrolider/linkosamider	Makrolidler/linkozamidler	Макроліди/лінкозаміди
+Other antibacterials	FALSE	TRUE	TRUE	FALSE	其他抗菌剂	Ostatní antibakteriální látky	Andre antibakterielle stoffer	Overige antibiotica	Muut antibakteeriset aineet	Autres antibactériens	Andere Antibiotika	Άλλα αντιβακτηριακά	Altri antibatterici	その他の抗菌薬	Andre antibakterielle midler	Inne środki przeciwbakteryjne	Outros antibacterianos	Alte antibacteriene	Другие антибактериальные препараты	Otros antibacterianos	Andra antibakteriella medel	Diğer antibakteriyeller	Інші антибактеріальні засоби
+Polymyxins	FALSE	TRUE	TRUE	FALSE	多粘菌素类	Polymyxiny	Polymyxiner	Polymyxines	Polymysiinit	Polymyxines	Polymyxine	Πολυμυξίνες	Polimixine	ポリミキシン	Polymyxiner	Polimyksyny	Polimixinas	Polimixine	Полимиксины	Polimixinas	Polymyxiner	Polimiksinler	Поліміксини
+Quinolones	FALSE	TRUE	TRUE	FALSE	喹诺酮类	Chinolony	Kinoloner	Quinolonen	Kinolonit	Quinolones	Quinolone	Κινολόνες	Chinoloni	キノロン	Kinoloner	Quinolony	Quinolones	Quinolone	Хинолоны	Quinolonas	Kinoloner	Kinolonlar	Хінолони
@@ -1,12 +1,13 @@
 # The `AMR` Package for R <a href="https://msberends.github.io/AMR/"><img src="./logo.svg" align="right" height="139" /></a>

+* Generates **antibiograms** - traditional, combined, syndromic, and even WISCA
 * Provides the **full microbiological taxonomy** and data on **all antimicrobial drugs**
 * Applies all recent **CLSI and EUCAST clinical breakpoints** for MICs and disk zones
 * Corrects for duplicate isolates, **calculates and predicts AMR** per antibiotic class
 * Integrates with **WHONET**, ATC, **EARS-Net**, PubChem, **LOINC** and **SNOMED CT**
 * Works on Windows, macOS and Linux with **all versions of R** since R-3.0 and is completely **dependency-free**, highly suitable for places with **limited resources**

-<div style="display: flex;">
+<div style="display: flex; font-size: 0.8em;">
 <p style="text-align:left; width: 50%;"><small><a href="https://msberends.github.io/AMR/">https://msberends.github.io/AMR</a></small></p>
 <p style="text-align:right; width: 50%;"><small><a href="https://doi.org/10.18637/jss.v104.i03">https://doi.org/10.18637/jss.v104.i03</a></small></p>
 </div>
@@ -21,18 +22,20 @@ This work was published in the Journal of Statistical Software (Volume 104(3); [

 After installing this package, R knows [**~52,000 distinct microbial species**](./reference/microorganisms.html) (updated December 2022) and all [**~600 antibiotic, antimycotic and antiviral drugs**](./reference/antibiotics.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl).

-##### Used in 175 countries, translated to 16 languages
+##### Used in over 175 countries, translated into 20 languages

 <a href="./countries_large.png"><img src="./countries.png" target="_blank" align="right" style="max-width: 300px;" /></a>

 Since its first public release in early 2018, this R package has been used in almost all countries in the world. Click the map to enlarge and to see the country names.

-With the help of contributors from all corners of the world, the `AMR` package is available in <img src="lang_en.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> English, <img src="lang_zh.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Chinese, <img src="lang_da.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Danish, <img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Dutch, <img src="lang_fr.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> French, <img src="lang_de.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> German, <img src="lang_el.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Greek, <img src="lang_it.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Italian, <img src="lang_ja.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Japanese, <img src="lang_pl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Polish, <img src="lang_pt.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Portuguese, <img src="lang_ru.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Russian, <img src="lang_es.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Spanish, <img src="lang_sv.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Swedish, <img src="lang_tr.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Turkish, and <img src="lang_uk.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
+With the help of contributors from all corners of the world, the `AMR` package is available in <img src="lang_en.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> English, <img src="lang_cs.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Czech, <img src="lang_zh.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Chinese, <img src="lang_da.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Danish, <img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Dutch, <img src="lang_fi.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Finnish, <img src="lang_fr.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> French, <img src="lang_de.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> German, <img src="lang_el.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Greek, <img src="lang_it.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Italian, <img src="lang_ja.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Japanese, <img src="lang_no.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Norwegian, <img src="lang_pl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Polish, <img src="lang_pt.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Portuguese, <img src="lang_ro.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Romanian, <img src="lang_ru.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Russian, <img src="lang_es.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Spanish, <img src="lang_sv.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Swedish, <img src="lang_tr.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Turkish, and <img src="lang_uk.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.

 ### Practical examples

 #### Filtering and selecting data

+One of the most powerful functions of this package, aside from calculating and plotting AMR, is selecting and filtering based on antibiotic columns. This can be done using the so-called [antibiotic class selectors](https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html) that work in base R, `dplyr` and `data.table`:
+
 ```r
 # AMR works great with dplyr, but it's not required or neccesary
 library(AMR)
@@ -40,8 +43,10 @@ library(dplyr)

 example_isolates %>%
  mutate(bacteria = mo_fullname()) %>%
+  # filtering functions for microorganisms:
  filter(mo_is_gram_negative(),
         mo_is_intrinsic_resistant(ab = "cefotax")) %>%
+  # antibiotic selectors:
  select(bacteria,
         aminoglycosides(),
         carbapenems())
@@ -65,16 +70,95 @@ With only having defined a row filter on Gram-negative bacteria with intrinsic r
 A base R equivalent would be:

 ```r
+library(AMR)
 example_isolates$bacteria <- mo_fullname(example_isolates$mo)
 example_isolates[which(mo_is_gram_negative() &
                         mo_is_intrinsic_resistant(ab = "cefotax")),
                 c("bacteria", aminoglycosides(), carbapenems())]
 ```

-This base R snippet will work in any version of R since April 2013 (R-3.0).
+This base R code will work in any version of R since April 2013 (R-3.0). Moreover, this code works identically with the `data.table` package, only by starting with:
+
+```r
+example_isolates <- data.table::as.data.table(example_isolates)
+```
+
+#### Generating antibiograms
+
+The `AMR` package supports generating traditional, combined, syndromic, and even weighted-incidence syndromic combination antibiograms (WISCA).
+
+If used inside R Markdown or Quarto, the table will be printed in the right output format automatically (such as markdown, LaTeX, HTML, etc.).
+
+```r
+antibiogram(example_isolates,
+            antibiotics = c(aminoglycosides(), carbapenems()))
+```
+
+|Pathogen (N min-max)     | AMK| GEN| IPM| KAN| MEM| TOB|
+|:------------------------|---:|---:|---:|---:|---:|---:|
+|CoNS (43-309)            |   0|  86|  52|   0|  52|  22|
+|*E. coli* (0-462)        | 100|  98| 100|    | 100|  97|
+|*E. faecalis* (0-39)     |   0|   0| 100|   0|    |   0|
+|*K. pneumoniae* (0-58)   |    |  90| 100|    | 100|  90|
+|*P. aeruginosa* (17-30)  |    | 100|    |   0|    | 100|
+|*P. mirabilis* (0-34)    |    |  94|  94|    |    |  94|
+|*S. aureus* (2-233)      |    |  99|    |    |    |  98|
+|*S. epidermidis* (8-163) |   0|  79|    |   0|    |  51|
+|*S. hominis* (3-80)      |    |  92|    |    |    |  85|
+|*S. pneumoniae* (11-117) |   0|   0|    |   0|    |   0|
+
+In combination antibiograms, it is clear that combined antibiotics yield higher empiric coverage:
+
+```r
+antibiogram(example_isolates,
+            antibiotics = c("TZP", "TZP+TOB", "TZP+GEN"),
+            mo_transform = "gramstain")
+```
+
+|Pathogen (N min-max)     | TZP| TZP + GEN| TZP + TOB|
+|:------------------------|---:|---------:|---------:|
+|Gram-negative (641-693)  |  88|        99|        98|
+|Gram-positive (345-1044) |  86|        98|        95|
+
+Like many other functions in this package, `antibiogram()` comes with support for 20 languages that are often detected automatically based on system language:
+
+```r
+antibiogram(example_isolates,
+            antibiotics = c("cipro", "tobra", "genta"), # any arbitrary name or code will work
+            mo_transform = "gramstain",
+            ab_transform = "name",
+            language = "uk") # Ukrainian
+```
+
+|Збудник (N min-max)      | Гентаміцин| Тобраміцин| Ципрофлоксацин|
+|:------------------------|----------:|----------:|--------------:|
+|Грамнегативні (684-686)  |         96|         96|             91|
+|Грампозитивні (665-1170) |         63|         34|             77|
+

 #### Calculating resistance per group

+For a manual approach, you can use the `resistance` or `susceptibility()` function:
+
+```r
+example_isolates %>%
+  # group by ward:
+  group_by(ward) %>%
+  # calculate AMR using resistance() for gentamicin and tobramycin
+  # and get their 95% confidence intervals using sir_confidence_interval():
+  summarise(across(c(GEN, TOB),
+                   list(total_R = resistance,
+                        conf_int = function(x) sir_confidence_interval(x, collapse = "-"))))
+```
+
+|ward       | GEN_total_R|GEN_conf_int | TOB_total_R|TOB_conf_int |
+|:---------:|:----------:|:-----------:|:----------:|:-----------:|
+|Clinical   |   0.229    |0.205-0.254  |   0.315    |0.284-0.347  |
+|ICU        |   0.290    |0.253-0.330  |   0.400    |0.353-0.449  |
+|Outpatient |   0.200    |0.131-0.285  |   0.368    |0.254-0.493  |
+
+Or use [antibiotic class selectors](https://msberends.github.io/AMR/reference/antibiotic_class_selectors.html) to select a series of antibiotic columns:
+
 ```r
 library(AMR)
 library(dplyr)
@@ -82,8 +166,7 @@ library(dplyr)
 out <- example_isolates %>%
  # group by ward:
  group_by(ward) %>%
-  # calculate AMR using resistance(), over all aminoglycosides
-  # and polymyxins:
+  # calculate AMR using resistance(), over all aminoglycosides and polymyxins:
  summarise(across(c(aminoglycosides(), polymyxins()),
            resistance))
 out
@@ -93,7 +176,7 @@ out
 |:-----------|------:|------:|------:|------:|------:|
 | Clinical   | 0.229 | 0.315 | 0.626 |     1 | 0.780 |
 | ICU        | 0.290 | 0.400 | 0.662 |     1 | 0.857 |
-| Outpatient | 0.200 | 0.368 | 0.605 |    NA | 0.889 |
+| Outpatient | 0.200 | 0.368 | 0.605 |       | 0.889 |

 ```r
 # transform the antibiotic columns to names:
@@ -104,7 +187,7 @@ out %>% set_ab_names()
 |:-----------|-----------:|-----------:|----------|----------:|----------:|
 | Clinical   | 0.229      | 0.315      | 0.626    |     1     | 0.780     |
 | ICU        | 0.290      | 0.400      | 0.662    |     1     | 0.857     |
-| Outpatient | 0.200      | 0.368      | 0.605    |    NA     | 0.889     |
+| Outpatient | 0.200      | 0.368      | 0.605    |           | 0.889     |

 ```r
 # transform the antibiotic column to ATC codes:
@@ -115,7 +198,7 @@ out %>% set_ab_names(property = "atc")
 |:-----------|-----------:|-----------:|----------|----------:|----------:|
 | Clinical   | 0.229      | 0.315      | 0.626    |     1     | 0.780     |
 | ICU        | 0.290      | 0.400      | 0.662    |     1     | 0.857     |
-| Outpatient | 0.200      | 0.368      | 0.605    |    NA     | 0.889     |
+| Outpatient | 0.200      | 0.368      | 0.605    |           | 0.889     |

 ### What else can you do with this package?

@@ -26,3 +26,39 @@
 # Visit our website for the full manual and a complete tutorial about  #
 # how to conduct AMR data analysis: https://msberends.github.io/AMR/   #
 # ==================================================================== #
+
+sir <- random_sir(100)
+rsi <- sir
+class(rsi) <- gsub("sir", "rsi", class(rsi))
+mic <- random_mic(100)
+disk <- random_disk(100)
+
+expect_identical(summary(sir), summary(rsi))
+expect_identical(c(sir), c(rsi))
+
+expect_identical(suppressWarnings(suppressMessages(as.rsi(as.character(rsi)))),
+                 suppressWarnings(suppressMessages(as.sir(as.character(sir)))))
+expect_identical(suppressWarnings(suppressMessages(as.rsi(mic, mo = "Escherichia coli", ab = "CIP"))),
+                 suppressWarnings(suppressMessages(as.sir(mic, mo = "Escherichia coli", ab = "CIP"))))
+expect_identical(suppressWarnings(suppressMessages(as.rsi(disk, mo = "Escherichia coli", ab = "CIP"))),
+                 suppressWarnings(suppressMessages(as.sir(disk, mo = "Escherichia coli", ab = "CIP"))))
+expect_identical(suppressWarnings(suppressMessages(as.rsi(data.frame(CIP = mic, mo = "Escherichia coli")))),
+                 suppressWarnings(suppressMessages(as.sir(data.frame(CIP = mic, mo = "Escherichia coli")))))
+
+expect_identical(suppressWarnings(n_rsi(example_isolates$CIP)),
+                 suppressWarnings(n_sir(example_isolates$CIP)))
+
+expect_identical(suppressWarnings(rsi_df(example_isolates)),
+                 suppressWarnings(sir_df(example_isolates)))
+
+expect_identical(suppressWarnings(is.rsi.eligible(example_isolates)),
+                 suppressWarnings(is_sir_eligible(example_isolates)))
+
+if (AMR:::pkg_is_available("ggplot2")) {
+  expect_equal(suppressWarnings(ggplot_rsi(example_isolates[, c("CIP", "GEN", "TOB")])),
+               suppressWarnings(ggplot_sir(example_isolates[, c("CIP", "GEN", "TOB")])))
+  
+  p <- ggplot2::ggplot(example_isolates[, c("CIP", "GEN", "TOB")])
+  expect_equal(suppressWarnings(p + geom_rsi() + scale_rsi_colours() + labels_rsi_count() + facet_rsi() + theme_rsi()),
+               suppressWarnings(p + geom_sir() + scale_sir_colours() + labels_sir_count() + facet_sir() + theme_sir()))
+}
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
dr. M.S. (Matthijs) Berends	dee675e717	Version 2.0 on CRAN	2023-03-12 14:07:45 +01:00
dr. M.S. (Matthijs) Berends	80cfc503c2	check for 2.0	2023-03-12 13:02:37 +01:00
dr. M.S. (Matthijs) Berends	9179e98e12	patient ID in first isolate	2023-03-11 17:13:19 +01:00
dr. M.S. (Matthijs) Berends	7ad8635994	documentation for 'data.table' AB selectors	2023-03-11 16:54:02 +01:00
dr. M.S. (Matthijs) Berends	45e840c02f	update NEWS	2023-03-11 14:43:31 +01:00
dr. M.S. (Matthijs) Berends	262598b8d7	support for old rsi arguments	2023-03-11 14:24:34 +01:00
dr. M.S. (Matthijs) Berends	4416394e10	website update	2023-02-26 21:26:58 +01:00
dr. M.S. (Matthijs) Berends	1d3d7d40bc	get episode unit tests	2023-02-24 19:54:56 +01:00
dr. M.S. (Matthijs) Berends	2c5a9bb622	new relative episode determination in `get_episode()`, fix for plotting disk/MIC values	2023-02-24 17:06:30 +01:00
dr. M.S. (Matthijs) Berends	92029c9e95	remove note	2023-02-24 10:31:36 +01:00
dr. M.S. (Matthijs) Berends	049baf0a71	fix for antibiograms on R < 3.5	2023-02-24 09:43:10 +01:00
dr. M.S. (Matthijs) Berends	e70f2cd32c	knitr format	2023-02-23 16:27:40 +01:00
dr. M.S. (Matthijs) Berends	a84101db08	N for only 1 AB in	2023-02-22 16:26:13 +01:00
dr. M.S. (Matthijs) Berends	551aaf6517	auto-remove missing ABs in `antibiogram()`	2023-02-22 16:00:52 +01:00
dr. M.S. (Matthijs) Berends	c2cfc5ef84	fix for `antibiogram()`, transform `WHONET` data set to `sir`	2023-02-22 15:40:05 +01:00
dr. M.S. (Matthijs) Berends	dad25302f2	make `rsi` work in more cases, documentation update	2023-02-22 14:38:57 +01:00
dr. M.S. (Matthijs) Berends	380cbec0e8	prehook	2023-02-18 14:58:02 +01:00
dr. M.S. (Matthijs) Berends	8d902410f9	unit tests	2023-02-18 14:56:06 +01:00
dr. M.S. (Matthijs) Berends	8dcf101a9c	website	2023-02-18 13:08:08 +01:00
dr. M.S. (Matthijs) Berends	ba255ddb00	website	2023-02-18 11:57:17 +01:00
dr. M.S. (Matthijs) Berends	e890360986	website syntax update	2023-02-17 11:39:00 +01:00
dr. M.S. (Matthijs) Berends	714a048fa9	italicise antibiogram	2023-02-17 09:42:51 +01:00
dr. M.S. (Matthijs) Berends	db2830124f	fix for using `dplyr::select()`	2023-02-15 19:48:34 +01:00
dr. M.S. (Matthijs) Berends	a82552dd88	fix for group selections	2023-02-15 17:37:49 +01:00
dr. M.S. (Matthijs) Berends	ef716f6ee3	doc fix	2023-02-15 17:16:40 +01:00
dr. M.S. (Matthijs) Berends	d4ae174c28	docs	2023-02-15 17:03:34 +01:00
dr. M.S. (Matthijs) Berends	6016547f1f	support for dplyr 1.1.0	2023-02-15 17:02:10 +01:00
dr. M.S. (Matthijs) Berends	fe41fc2e35	font size	2023-02-14 16:57:48 +01:00
dr. M.S. (Matthijs) Berends	8d37c75860	unit tests	2023-02-14 15:59:40 +01:00
dr. M.S. (Matthijs) Berends	a4cd38c433	fix for R < 3.2, `expect_warning()` on hold	2023-02-14 10:41:01 +01:00
dr. M.S. (Matthijs) Berends	3396236eef	unit test fixes	2023-02-13 16:56:25 +01:00
dr. M.S. (Matthijs) Berends	b6d2b1398d	Fix for `antibiogram()` in R <=3.4	2023-02-13 10:21:43 +01:00
dr. M.S. (Matthijs) Berends	45a9697c84	unit tests	2023-02-12 17:10:48 +01:00
dr. M.S. (Matthijs) Berends	68abb00c59	add include_screening to `as.sir()`	2023-02-12 15:09:54 +01:00
dr. M.S. (Matthijs) Berends	c740967cf2	fix for binding rows	2023-02-12 11:20:14 +01:00
dr. M.S. (Matthijs) Berends	c51fb24363	pm_bind_rows	2023-02-11 22:28:48 +01:00
dr. M.S. (Matthijs) Berends	b146de6d7f	fix for bind_rows2, added 4 langs	2023-02-11 21:57:12 +01:00
dr. M.S. (Matthijs) Berends	2007c3eef3	bind_rows	2023-02-10 17:09:48 +01:00
dr. M.S. (Matthijs) Berends	03294c7901	fix for Salmonella group A, unit tests	2023-02-10 16:47:25 +01:00
dr. M.S. (Matthijs) Berends	bc434db835	bring back `antibiogram()`, without deps	2023-02-10 16:18:00 +01:00
dr. M.S. (Matthijs) Berends	70a7ba0206	fix first isolate	2023-02-10 13:13:17 +01:00
dr. M.S. (Matthijs) Berends	1a0dc4bf46	revert back to pre-antibiogram	2023-02-09 13:07:39 +01:00
dr. M.S. (Matthijs) Berends	aa48c6bf53	pm fixes	2023-02-08 16:51:41 +01:00
dr. M.S. (Matthijs) Berends	822e9de82c	pm update, unit test fix?	2023-02-08 13:48:06 +01:00
dr. M.S. (Matthijs) Berends	4a54d59f70	tinytest	2023-02-06 14:36:31 +01:00
dr. M.S. (Matthijs) Berends	75a4c1ef3e	fixes2	2023-02-06 14:34:38 +01:00
dr. M.S. (Matthijs) Berends	f7dd890b79	fixes	2023-02-06 12:38:52 +01:00
dr. M.S. (Matthijs) Berends	9e99e66f01	use dplyr where available, new `antibiogram()` for WISCA, fixed Salmonella Typhi/Paratyphi	2023-02-06 11:57:22 +01:00
dr. M.S. (Matthijs) Berends	4b133d4c96	unit tests	2023-01-30 17:24:03 +01:00
dr. M.S. (Matthijs) Berends	89a577805f	prelim fix for g.test	2023-01-30 12:26:48 +01:00
dr. M.S. (Matthijs) Berends	126afb01a4	unit tests 2	2023-01-24 16:31:00 +01:00
dr. M.S. (Matthijs) Berends	c0d8888ab7	unit tests	2023-01-24 16:09:48 +01:00
dr. M.S. (Matthijs) Berends	7b00b4f34a	unit tests	2023-01-24 14:52:15 +01:00
dr. M.S. (Matthijs) Berends	830c67f1bf	documentation, unit tests	2023-01-24 10:20:27 +01:00
dr. M.S. (Matthijs) Berends	eef00069fd	add all options to documentation	2023-01-23 20:07:57 +01:00
dr. M.S. (Matthijs) Berends	19fd0ef121	sort sir history	2023-01-23 15:01:21 +01:00