Frequency and antimicrobial susceptibility of <i>Staphylococcus aureus</i> isolated from clinical bovine mastitis cases in British Columbia, Canada
Bibliographic record
Abstract
Staphylococcus aureus is one of the most important bacteria responsible for clinical bovine mastitis globally, leading to significant economic losses in the dairy industry. Antimicrobials used to treat and prevent mastitis can lead to antimicrobial resistance (AMR) in S. aureus . We retrospectively evaluated AMR of S. aureus isolates from clinical bovine mastitis cases submitted to the Animal Health Centre in British Columbia from 2013 to May 2024. S. aureus was isolated from 15.0% of submitted bovine milk samples. Antimicrobial susceptibility testing was done on 611 of 1,347 S. aureus isolates. No methicillin-resistant S. aureus isolates were detected based on cefoxitin susceptibility test results, which is encouraging. The highest frequencies of resistance were found for penicillin (46.6%) and ampicillin (42.1%). The lowest frequencies of resistance were to ceftiofur and sulfamethoxazole–trimethoprim (0.2% each) and cephalothin (0.3%). AMR trends over our study period were generally stable, except for penicillin and ampicillin; penicillin resistance increased from 15.2% to 71.1%, and ampicillin resistance increased from 18.2% to 70.1%. The information in our study could help guide clinicians when choosing antimicrobial treatments to treat mastitis caused by S. aureus , particularly in the province of British Columbia. Because S. aureus has a broad host range and is of importance to both human and veterinary medicine, continued monitoring to detect the emergence of resistance is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".