Effect of Subtherapeutic Administration of Antibiotics on the Prevalence of Antibiotic-Resistant <i>Escherichia coli</i> Bacteria in Feedlot Cattle
Bibliographic record
Abstract
Antibiotic-resistant Escherichia coli in 300 feedlot steers receiving subtherapeutic levels of antibiotics was investigated through the collection of 3,300 fecal samples over a 314-day period. Antibiotics were selected based on the commonality of use in the industry and included chlortetracycline plus sulfamethazine (TET-SUL), chlortetracycline (TET), virginiamycin, monensin, tylosin, or no antibiotic supplementation (control). Steers were initially fed a barley silage-based diet, followed by transition to a barley grain-based diet. Despite not being administered antibiotics prior to arrival at the feedlot, the prevalences of steers shedding TET- and ampicillin (AMP)-resistant E. coli were >40 and <30%, respectively. Inclusion of TET-SUL in the diet increased the prevalence of steers shedding TET- and AMP-resistant E. coli and the percentage of TET- and AMP-resistant E. coli in the total generic E. coli population. Irrespective of treatment, the prevalence of steers shedding TET-resistant E. coli was higher in animals fed grain-based compared to silage-based diets. All steers shed TET-resistant E. coli at least once during the experiment. A total of 7,184 isolates were analyzed for MIC of antibiotics. Across antibiotic treatments, 1,009 (13.9%), 7 (0.1%), and 3,413 (47.1%) E. coli isolates were resistant to AMP, gentamicin, or TET, respectively. In addition, 131 (1.8%) and 143 (2.0%) isolates exhibited potential resistance to extended-spectrum beta-lactamases, as indicated by either ceftazidime or cefpodoxime resistance. No isolates were resistant to ciprofloxacin. The findings of the present study indicated that subtherapeutic administration of tetracycline in combination with sulfamethazine increased the prevalence of tetracycline- and AMP-resistant E. coli in cattle. However, resistance to antibiotics may be related to additional environmental factors such as diet.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".