Impact of subtherapeutic administration of tylosin and chlortetracycline on antimicrobial resistance in farrow-to-finish swine
Bibliographic record
Abstract
The use of antimicrobial agents in swine production at subtherapeutic concentrations for the purpose of growth promotion remains controversial due to the potential impact on public health. Beginning at weaning (3 weeks), pigs received either nonmedicated feed or feed supplemented with subtherapeutic levels of either tylosin (11-44 ppm) or chlortetracycline (5.5 ppm). After only 3 weeks, pigs given feed supplemented with tylosin had significantly higher levels of tylosin-resistant anaerobes (P < 0.0001) compared with the control group, increasing from 11.8% to 89.6%, a level which was stable for the duration of the study, even after a 2-week withdrawal prior to slaughter. Tylosin-fed pigs had a higher incidence of detection for erm(A), erm(F), and erm(G), as well as significantly (P < 0.001) higher concentrations of erm(B) in their feces. The continuous administration of chlortetracycline-supplemented feed, however, had no significant effect on the population of chlortetracycline-resistant anaerobes in comparison with nontreated pigs (P > 0.05). The resistance genes tet(O), tet(Q), and erm(B) were detected in all pigs at each sampling time, while tet(G), tet(L), and tet(M) were also frequently detected. Neither chlortetracycline nor tylosin increased the growth rate of pigs.
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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 | 0.000 | 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 | 0.001 |
| 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".