Phenotypic and Genotypic Anti‐Microbial Resistance Profiles of <i>Campylobacters</i> from Untreated Feedlot Cattle and Their Environment
Bibliographic record
Abstract
Anti-microbial resistance is an emerging public health issue. Farmed animals may act as reservoirs and potential sources of anti-microbial resistant Campylobacters. The aim of this study was to investigate the anti-microbial resistance profile of cattle and environmental Campylobacter isolates from normal untreated feedlot cattle, the role of the gyrA Thr-86-Ile mutation in ciprofloxacin-resistant Campylobacter jejuni isolates and the involvement of the tripartite CmeABC efflux system for multi-resistant C. jejuni isolates. The phenotypic anti-microbial resistance testing was carried out on 500 Campylobacter isolates (445 cattle isolates and 55 environmental isolates). In general, there was a higher level of anti-microbial resistance for the environmental isolates compared with the animal isolates, 45% of the animal isolates were resistant to one or more of the seven anti-microbials compared with 84% of the environmental isolates. The combined cattle and environmental Campylobacters had 34 (6.8%) isolates resistant to three or more of the seven anti-microbials tested on all isolates and 11 (2.2%) isolates were resistant to the seven anti-microbials. There was a substantial level of ciprofloxacin-resistant Campylobacters in both animal (8.5%) and environmental (21.8%) isolates. The gyrA Thr-86-Ile mutation was only present in five of 22 ciprofloxacin-resistant C. jejuni isolates investigated. No multi-drug-resistant associated mutation was detected in the CmeB or the CmeR regions investigated. In conclusion, our study observed a substantial level of Campylobacter anti-microbial resistance, highlighting the need for an active anti-microbial surveillance program for food animals in Ireland and the importance of the chosen sampling point can have on the findings of such a program.
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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 | 0.000 |
| 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".