Association of high-risk sexual behaviour with diversity of the vaginal microbiota and abundance of Lactobacillus
Bibliographic record
Abstract
OBJECTIVE: To compare the vaginal microbiota of women engaged in high-risk sexual behaviour (sex work) with women who are not engaged in high-risk sexual behaviour. Diverse vaginal microbiota, low in Lactobacillus species, like those in bacterial vaginosis (BV), are associated with increased prevalence of sexually transmitted infections (STIs) and human immunodeficiency virus (HIV) acquisition. Although high-risk sexual behaviour increases risk for STIs, the vaginal microbiota of sex workers is understudied. METHODS: A retrospective cross-sectional study was conducted comparing vaginal microbiota of women who are not engaged in sex work (non-sex worker controls, NSW, N = 19) and women engaged in sex work (female sex workers, FSW, N = 48), using Illumina sequencing (16S rRNA, V3 region). RESULTS: Bacterial richness and diversity were significantly less in controls, than FSW. Controls were more likely to have Lactobacillus as the most abundant genus (58% vs. 17%; P = 0.002) and composition of their vaginal microbiota differed from FSW (PERMANOVA, P = 0.001). Six microbiota clusters were detected, including a high diversity cluster with three sub-clusters, and 55% of women with low Nugent Scores fell within this cluster. High diversity was observed by 16S sequencing in FSW, regardless of Nugent Scores, suggesting that Nugent Score may not be capable of capturing the diversity present in the FSW vaginal microbiota. CONCLUSIONS: High-risk sexual behaviour is associated with diversity of the vaginal microbiota and lack of Lactobacillus. These factors could contribute to increased risk of STIs and HIV in women engaged in high-risk sexual behaviour.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".