Antimicrobial Resistance in Generic<i>Escherichia coli</i>Isolates from Wild Small Mammals Living in Swine Farm, Residential, Landfill, and Natural Environments in Southern Ontario, Canada
Bibliographic record
Abstract
To assess the impacts of different types of human activity on the development of resistant bacteria in the feces of wild small mammals, we compared the prevalences and patterns of antimicrobial resistance and resistance genes in generic Escherichia coli and Salmonella enterica isolates from fecal samples collected from wild small mammals living in four environments: swine farms, residential areas, landfills, and natural habitats. Resistance to antimicrobials was observed in E. coli isolates from animals in all environments: 25/52 (48%) animals trapped at swine farms, 6/69 (9%) animals trapped in residential areas, 3/20 (15%) animals trapped at landfills, and 1/22 (5%) animals trapped in natural habitats. Animals trapped on farms were significantly more likely to carry E. coli isolates with resistance to tetracycline, ampicillin, sulfisoxazole, and streptomycin than animals trapped in residential areas. The resistance genes sul2, aadA, and tet(A) were significantly more likely to be detected in E. coli isolates from animals trapped on farms than from those trapped in residential areas. Three S. enterica serotypes (Give, Typhimurium, and Newport) were recovered from the feces of 4/302 (1%) wild small mammals. All Salmonella isolates were pansusceptible. Our results show that swine farm origin is significantly associated with the presence of resistant bacteria and resistance genes in wild small mammals in southern Ontario, Canada. However, resistant fecal bacteria were found in small mammals living in all environments studied, indicating that environmental exposure to antimicrobials, antimicrobial residues, resistant bacteria, or resistance genes is widespread.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".