Meta-analyses of the global multilocus genotypes of the human pathogen <i>Campylobacter jejuni</i>
Bibliographic record
Abstract
Campylobacter infections are a leading cause of bacterial diarrheal illness worldwide, with increasing reports of outbreaks in both developing and developed countries. Most studies investigating strain genotypes and epidemiology of Campylobacter jejuni examined on a local scale. Using the archived multilocus sequence typing data at seven loci, and associated strain metadata from the PubMLST database, here we investigated the spatial and temporal genetic structure of the global population of C. jejuni. Our analyses revealed evidence for clonal dispersals of multiple sequence types (STs) among countries and continents. However, despite the observed clonal dispersal and that most genetic variations were found within individual geographic subpopulations, both the non-clone-corrected and clone-corrected samples showed evidence of significant genetic differentiation among national and continental subpopulations, with non-clone-corrected samples showing greater differentiation than clone-corrected samples. Phylogenetic incompatibility analyses provided evidence for recombination within each continental subpopulation. However, linkage disequilibrium analyses rejected the hypothesis of random recombination across the samples. Temporally, multiple STs were found to persist across four decades and the five globally most common STs showed relatively stable frequencies over the last two decades. We discussed the implications of our results to food security, disease transmission, and public health management.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".