Antimicrobial resistance in fecal generic Escherichia coli and Salmonella spp. obtained from Ontario sheep flocks and associations between antimicrobial use and resistance.
Bibliographic record
Abstract
The purpose of this study was to examine the prevalence and patterns of antimicrobial resistance (AMR) in enteric bacteria obtained from Ontario sheep flocks, and associations between antimicrobial use (AMU) and AMR. Forty-nine sheep producers participated for a 1-year interval between 2006 and 2008. Two-hundred and eighty-three pooled fecal samples were collected from the flocks during initial and final visits. Up to 3 isolates of Salmonella spp. and generic E. coli per pooled fecal sample were tested for susceptibility to 15 antimicrobials. Resistance was infrequent among Salmonella (0%, n = 7 isolates) and low among E. coli (13.1%; n = 849) isolates. A small number of isolates were resistant to antimicrobials classified as being of very high importance to human health. Tetracycline resistance was most frequently observed (12.0%). Logistic regression was used to model potential AMU (qualitative and quantitative) risk factors for tetracycline resistance in generic E. coli from final visits. Qualitative analysis indicated that the use of injectable sulfonamides [including trimethoprim-sulfonamide combinations (TMS)] and tetracycline in the feed and water were significantly associated with tetracycline resistance (OR = 2.6, P = 0.01; and OR = 4.8, P ≤ 0.01, respectively). Quantitative analysis also indicated that TMS exposure rate was significantly associated with tetracycline resistance, which varied depending on the exposure rate. The exposure rate of tetracycline in the feed and water was only significant after the removal of one influential flock, warranting further research examining flocks with higher tetracycline exposure rates. Although the prevalence of AMR in participating flocks was relatively low, risk factors for resistance were identified.
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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 | 0.000 | 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 | 0.000 | 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".