Antimicrobial resistance among canine enteric Escherichia coli isolates and prevalence of attaching–effacing and extraintestinal pathogenic virulence factors in Spain
Bibliographic record
Abstract
The aim of this study was to estimate the prevalence of antimicrobial resistance (AMR) in Escherichia coli from a dog population in Spain and assess specific virulence factors. Susceptibility to 22 antimicrobials was tested along with the production of extended-spectrum β-lactamases (ESBLs) and AmpC in faecal isolates from 100 dogs. Virulence-related genes associated with attaching and effacing E. coli (eae, Stx1, Stx2) and extraintestinal pathogenic E. coli - ExPEC - (papC, hlyA and cnf1) were detected by PCR. At least one kind of AMR was observed in 73% of the isolates. The highest prevalences corresponded to penicillin (45%), aminoglycoside (40%) and non-extended spectrum cephalosporin (39%) classes. Multidrug resistance (MDR) was observed in 53.4% of the resistant isolates. No resistance to colistin was found. Production of ESBL/AmpC enzymes was detected in 5% of E. coli. Shiga toxin-producing E. coli were not observed, enteropathogenic E. coli were identified in only 12% of them, and ExPEC were found in 25%. Dog faeces can be a source of E. coli strains potentially presenting a threat to humans through their virulence factors or AMR. The non-hygienic keeping of animals may increase the risk of colonisation of such pathogens in humans.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".