502 Dissipation of antimicrobials and resistance genes in compost originating from cattle manure after direct oral administration or post-excretion fortification of antimicrobials
Bibliographic record
Abstract
Our study compared the dissipation of antimicrobials and resistance genes (ARG) during composting of cattle manure fortified with antimicrobials versus manure from cattle administered the same antimicrobials in feed. Manure was collected from cattle fed diets containing (kg-1 dry feed): (1) 44 mg chlortetracycline (CTC), (2) a mixture of 44 mg each of chlortetracycline and sulfamethazine (CTCSMZ), (3) 11 mg tylosin (TYL) or (4) Control, no antimicrobials. Fortified treatments were generated by adding antimicrobials to control manure. All manures were composted for 30 d with a single mixing after 16 d. Quantitative PCR (qPCR) measured the concentration of 16S rDNA and genes associated with tetracycline (tet), erythromycin (erm), and sulfamethazine (sul) resistance. Over 95% of antimicrobials dissipated over 30 d of composting, but CTC and SMZ remained higher in fed than fortified treatments, with a reverse trend observed for tylosin. Copy numbers of 16S rDNA decreased (P < 0.05) over 30 d, but were not altered by the presence of antimcrobials. Levels of all ARG except tet(L) decreased by 0.1-1.6 log10 copies g dry matter-1 in the first compost cycle, but some genes [tet(B), tet(L), erm(F), and erm(X)] increased (P < 0.05) by 1.0-3.1 log10 copies g dry matter-1 in the second. This pattern aligned with the positive correlation of these ARG with residue concentrations in the first cycle and the negative correlation in the second. During 30 d of composting, levels of tet(M) and tet(W) in CTC, erm(A), erm(B) and erm(X) in TYL, and sul(1) in CTCSMZ remained higher (P < 0.05) in fed than fortified treatments. Our results suggest that dissipation of ARG during composting of manure fortified with antimicrobials differs from manure generated by cattle that are administered antimicrobials in feed and does not always align with the dissipation of antimicrobial residues.
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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 | 0.000 |
| 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 | 0.001 | 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".