Potentially Pathogenic Bacteria and Antimicrobial Resistance in Bioaerosols from Cage-Housed and Floor-Housed Poultry Operations
Bibliographic record
Abstract
BACKGROUND: Antibiotics are used in animal confinement buildings, such as cage-housed (CH) and floor-housed (FH) poultry operations, to lower the likeliness of disease transmission. In FH facilities, antibiotics may also be used at sub-therapeutic levels for growth promotion. Low levels of antibiotic create a selective pressure toward antimicrobial resistance (AMR) in chicken fecal bacteria. OBJECTIVE: The objective of this study was to compare bacteria and AMR genes in bioaerosols from CH and FH poultry facilities. METHODS: Bioaerosols were collected from 15 CH and 15 FH poultry operations, using stationary area samplers as well as personal sampling devices. Bacteria concentrations were determined by genus- or species-specific quantitative polymerase chain reaction (PCR) and AMR genes were detected using endpoint PCR. RESULTS: Enterococcus spp., Escherichia coli, and Staphylococcus spp. were significantly higher in bioaerosols of FH poultry operations than CH bioaerosols (P < 0.001) while Clostridium perfringens was significantly higher in area bioaerosols of CH operations than FH area bioaerosols (P < 0.05). Campylobacter spp. were detected only in bioaerosols of FH facilities. Zinc bacitracin resistance gene, bcrR, erythromycin resistance gene, ermA, and tetracycline resistance gene, tetA/C, were more prevalent in bioaerosols of FH facilities than CH bioaerosols (P < 0.01, P < 0.01, and P < 0.05, respectively). CONCLUSIONS: Most bacteria are more concentrated and most AMR genes are more prevalent in bioaerosols of FH poultry operations, where growth-promoting antibiotics may be used.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".