Susceptibility to antimicrobial agents among bovine mastitis pathogens isolated from North American dairy cattle, 2002–2010
Bibliographic record
Abstract
Approximately 8,000 isolates of Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Staphylococcus aureus, and Escherichia coli, isolated by 25 veterinary laboratories across North America between 2002 and 2010, were tested for in vitro susceptibility to beta-lactam, macrolide, and lincosamide drugs. The minimal inhibitory concentrations (MICs) of the beta-lactam drugs remained low against most of the Gram-positive strains tested, and no substantial changes in the MIC distributions were seen over time. Of the beta-lactam antimicrobial agents tested, only ceftiofur showed good in vitro activity against E. coli. The MICs of the macrolides and lincosamides also remained low against Gram-positive mastitis pathogens. While the MIC values given by 50% of isolates (MIC50) for erythromycin and pirlimycin and the streptococci were all low (≤0.5 µg/ml), the MIC values given by 90% of isolates (MIC90) were higher and more variable, but with no apparent increase over time. Staphylococcus aureus showed little change in erythromycin susceptibility over time, but there may be a small, numerical increase in pirlimycin MIC50 and MIC90 values. Overall, the results suggest that mastitis pathogens in the United States and Canada have not shown any substantial changes in the in vitro susceptibility to beta-lactam, macrolide, and lincosamide drugs tested over the 9 years of the study.
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 | 0.001 | 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 | 0.001 | 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".