Identification of drug-resistant phenotypes and resistance genes in <i>Enterococcus faecalis</i> isolates from animal feces originating in Xinjiang, People’s Republic of China
Bibliographic record
Abstract
This study examined the presence and the antibiotic resistance patterns of Enterococcus faecalis isolated from the feces of 285 animals. Polymerase chain reaction tests verified the presence of E. faecalis from 49 pigs, 20 cows, 174 sheep, 17 horses, 21 chickens, and four dung beetles. Bacterial strains from different animals showed differences in susceptibility and resistance to the tested antimicrobials. The isolates exhibited resistance to ampicillin (6.32%), ciprofloxacin (40.00%), nitrofurantoin (1.40%), erythromycin (54.04%), streptomycin (82.11%), tetracycline (45.26%), amoxicillin (64.91%), penicillin (92.28%), and vancomycin (0.35%). The resistant strains also possessed varying complements of resistance genes including tem (77.89%), tetM (33.68%), gyrA (37.54%), parC (34.74%), aph(3′)-III (22.46%), aac(6′)/aph2″ (10.88%), and ant(6′)-I (8.42%). Genes for vancomycin resistance (vanB and vanC) and erythromycin resistance (mefA) were not detected. These results indicate high levels of antibiotic resistance among the isolates, although no positive correlation was observed between resistance genes and antibiotic resistance spectrum.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".