Multidrug‐Resistant Virulent <i>Escherichia coli</i> Strains in Cattle: Implications on Food Safety and Public Health
Bibliographic record
Abstract
Escherichia coli inhabit the gastrointestinal tract of mammals, including cattle, where they occur as commensals. However, some strains have evolved as highly virulent pathogens that also harbor a variety of multidrug‐resistant determinants. In the present study, from cattle fecal samples, a total of 636 confirmed E. coli strains were obtained based on the presence of the uidA housekeeping gene. Of the seven antibiotics tested, 120 isolates displayed multiple antibiotic‐resistant (MAR) traits, with two strains (ERO138 and EKL68) showing resistance to six antibiotics. The hlyA (62.5%) was the most prevalent among the MAR isolates. In addition, 11 (9.1%) isolates harbored all four screened virulence genes ( eaeA , stx1 , stx2 , and hlyA ). Seven of the 120 MAR isolates displayed moderate biofilm‐producing properties, and two of these isolates (ERO157 and EKL127) harbored all four virulence genes tested. Pulsed field gel electrophoresis (PFGE) analysis revealed that all 120 MAR isolates clustered into eight groups, displaying high genetic variability. These findings are important for screening and monitoring of diverse E. coli isolates from cattle in the Northwest region of South that harbors virulence and multiple antibiotic resistance traits.
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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 | 0.001 | 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".