Antimicrobial resistance in non-aureus staphylococci isolated from milk is associated with systemic but not intramammary administration of antimicrobials in dairy cattle
Bibliographic record
Abstract
Non- aureus staphylococci (NAS) are the bacteria most frequently isolated from bovine milk. Objectives of this study were to determine herd-level associations between antimicrobial use (AMU) and prevalence of antimicrobial resistance (AMR) and antimicrobial resistance genes in NAS according to antimicrobials and routes of administration. The AMR profile was determined using a micro-broth dilution method against a panel of 23 antimicrobials for 1,702 NAS isolates obtained from 89 herds. A subset of these isolates (n = 405) was submitted to whole-genome sequencing, and the presence of AMR genes was determined using data from 4 databases. Antimicrobial use was determined for all herds using an inventory of empty drug containers and quantified for each antimicrobial as the number of antimicrobial daily doses administered. Generalized linear models were used to estimate antimicrobial and route-specific associations between AMR in NAS and AMU. Prevalence of multidrug resistance in NAS was associated with systemic use of antimicrobials. Estimated relative risk associated with a 1-unit increase in antimicrobial daily doses per cow-year administered systemically was 1.28. No association was present with either intramammary or intrauterine use. Three drug classes, all of high or very high importance for human medicine, were associated with drug-specific AMR when administered systemically: penicillins, third-generation cephalosporins, and macrolides. Prevalence of tet , erm , and bla ARL genes in NAS was higher in herds that used more tetracyclines, macrolides, and third-generation cephalosporins, respectively. No association between drug-specific AMU and prevalence of blaZ , mphC , and msrA was identified, irrespective of route of administration. The either weak or nonexistent association between AMR and antimicrobials administered intramammarily suggest that a decrease in AMR of NAS following implementation of selective dry cow therapy would be minimal in comparison to reduced use of systemic antimicrobials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".