<b>Migration and standing variation in vaginal and rectal yeast populations in recurrent vulvovaginal candidiasis</b>
Bibliographic record
Abstract
Vulvovaginal candidiasis is one of the most common vaginal and fungal infections. The majority of infections are successfully treated with antifungal drugs. However, ~ 8% of cases lead to chronic recurrent vulvovaginal candidiasis ("RVVC"), and approximately half of RVVC cases are idiopathic. Previous research has generally found closely-related isolates within vaginal and rectal populations and between subsequent infections. However, their coarse methods preclude assessing the fine-scale relationships among closely related isolates and measuring standing genetic variation, a fundamental property of populations with implications for evolutionary potential. To address this gap, we isolated 12 vaginal and 12 rectal yeast isolates during symptomatic relapse from four individuals with a history of RVVC. Three participants had Candida albicans infections, while the fourth had Nakaseomyces glabratus . All isolates were whole-genome sequenced and phenotyped. The isolates were placed into the global phylogenies, which included constructing an updated N. glabratus tree containing over 500 isolates. Multiple analyses were consistent with frequent migration between sites. Although there are extremely few comparables, C. albicans population nucleotide diversity was similar to most commensal oral and rectal populations, while N. glabratus was similar to some bloodstream infections, yet higher than others. Diversity was largely driven by single nucleotide changes; no aneuploidies were found, and although loss-of-heterozygosity tracts were common in the populations, only a single region on chr1L varied among isolates from one participant. There was very little phenotypic diversity for drug response or growth and no consistent difference between isolates from different sites for invasive growth. Combined, this study provides baseline measurements and describes analysis techniques to quantify within-population diversity. We highlight a critical need for comparable studies that use the same sampling effort, sequencing, and analysis methods to understand the interplay between selection, drift, and migration in shaping fungal microbial communities in this and other important contexts.
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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 | 0.001 |
| 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) | 0.001 | 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".