Molecular mechanisms of antimicrobial resistance in fecal <i>Escherichia coli</i> of healthy dogs after enrofloxacin or amoxicillin administration
Bibliographic record
Abstract
Escherichia coli respond to selective pressure of antimicrobial therapy by developing resistance through a variety of mechanisms. The purpose of this study was to characterize the genetic mechanisms of antimicrobial resistance in fecal E. coli after the routine use of 2 popular antimicrobials. Fourteen resistant E. coli isolates, representing predominant clones that emerged in healthy dogs' feces after treatment with either amoxicillin (11 E. coli isolates) or enrofloxacin (3 E. coli isolates), were tested for mutations in DNA gyrase (gyrA and gyrB) and in topoisomerase IV (parC) and for the presence of β-lactamases (bla(TEM), bla(SHV), bla(PSE-1) and bla(CTX-M)) and plasmid-mediated quinolone resistance (qnrA, qnrB, qnrS, aac(6')-Ib, and qepA), by polymerase chain reaction. Escherichia coli isolates cultured following amoxicillin therapy only expressed single-drug resistance to β-lactams, while the isolates cultured from dogs receiving enrofloxacin therapy expressed multidrug resistance (MDR). The use of RND efflux pump inhibitors increased the susceptibility of the 3 MDR E. coli isolates to doxycycline, chloramphenicol, enrofloxacin, and ciprofloxacin, which indicates a role of the efflux pump in the acquisition of the MDR phenotype. Amplification and sequencing of AcrAB efflux pump regulators (soxR, soxS, marR, and acrR) revealed only the presence of a single mutation in soxS in the 3 MDR isolates.
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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".