Characterization of Antimicrobial Resistance in <i>Campylobacter</i> Species from Broiler Chicken Litter
Bibliographic record
Abstract
Campylobacteriosis in human populations has been an ongoing issue in both developed and developing countries over the last 10 years. There is a grave concern whether poultry production plays an intermediate role as a reservoir and source of transmission. In this study, sixty-five broiler chicken Campylobacter isolates were isolated from fecal samples collected from 17 flocks in Alberta, Canada over two years (2015-2016). Campylobacter jejuni was the predominantly recovered Campylobacter species in both years. Approximately 33% (8/24) Campylobacter coli was identified in year 2016. The two most common antimicrobial resistance patterns in Campylobacter in year 2015 were tetracycline resistance (39%) and azithromycin/clindamycin/erythromycin/telithromycin resistance (29%). Only one isolate in 2015 displayed resistance to ciprofloxacin/nalidixic acid/tetracycline. The tetO gene was detected in all tetracycline resistant isolates in 2015. The cmeB gene was detected in all isolates with resistance to azithromycin/clindamycin/erythromycin/ telithromycin, and two isolates with resistance to tetracycline. Comparing the sequence of the cmeB genes from isolates with different resistance patterns revealed several single nucleotide polymorphisms. Transconjugants with three distinctly combined resistance patterns were obtained via in vitro conjugation. In conclusion, our study suggested that poultry can be a potential reservoir for and source of transmission of Campylobacter for human infection and requires an ongoing monitoring.
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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".