Population Genetics of Antimicrobial Resistance in Campylobacter isolates from across Canada
Bibliographic record
Abstract
Campylobacter jejuni is a leading cause of gastroenteritis in the world.Widespread use of macrolide and fluoroquinolone antibiotics in animals and humans has resulted in the evolution of antimicrobial resistance (AMR) within Campylobacter, leading to increased costs in healthcare.The objective of this study is to provide insight into the contributions of populations genetics factors including mutation, recombination, and population size and structure on the evolution of virulence and AMR.These processes are investigated to evaluate the potential for local hotspots to contribute disproportionally to antimicrobial resistance in Campylobacter.To test these predictions, 1789 assemblies of Campylobacter jejuni from all across Canada were analyzed to assess rates of recombination and its effect on resulting population structure, and in particular its association antimicrobial resistance alleles.A thorough exploratory analysis has provided limited evidence of positive selection in virulence genes, evidence for one or a few origins of fluoroquinolone resistance as well as high levels of recombination and complex population substructure across the Campylobacter genome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".