The Role of European Starlings (Sturnus vulgaris) in the Dissemination of Multidrug-Resistant Escherichia coli among Concentrated Animal Feeding Operations
Bibliographic record
Abstract
Antimicrobial use in livestock production is a driver for the development and proliferation of antimicrobial resistance (AMR). Wildlife interactions with livestock, acquiring associated AMR bacteria and genes, and wildlife's subsequent dispersal across the landscape are hypothesized to play an important role in the ecology of AMR. Here, we examined priority AMR phenotypes and genotypes of Escherichia coli isolated from the gastrointestinal tracts of European starlings (Sturnus vulgaris) found on concentrated animal feeding operations (CAFOs). European starlings may be present in high numbers on CAFOs (>100,000 birds), interact with urban environments, and can migrate distances exceeding 1,500 km in North America. In this study, 1,477 European starlings from 31 feedlots in five U.S. states were sampled for E. coli resistant to third generation cephalosporins (3G-C) and fluoroquinolones. The prevalence of 3G-C and fluoroquinolone-resistant E. coli was 4% and 10%, respectively. Multidrug resistance in the E. coli isolates collected (n = 236) was common, with the majority of isolates displaying resistance to six or more classes of antibiotics. Genetic analyses of a subset of these isolates identified 94 genes putatively contributing to AMR, including seven class A and C β-lactamases as well as mutations in gyrA and parC recognized to confer resistance to quinolones. Phylogenetic and subtyping assessments showed that highly similar isolates (≥99.4% shared core genome, ≥99.6% shared coding sequence) with priority AMR were found in birds on feedlots separated by distances exceeding 150 km, suggesting that European starlings could be involved in the interstate dissemination of priority AMR bacteria.
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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) | 0.000 | 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 | 0.000 |
| 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".