Optimizing the vaginal microbiome as a potential strategy to reduce heterosexual HIV transmission
Bibliographic record
Abstract
Abstract Bacterial vaginosis (BV) is a proinflammatory genital condition characterized by high vaginal bacterial diversity and a paucity of Lactobacillus species. BV has been linked to an elevated risk of HIV acquisition among HIV‐negative women and of forward HIV transmission to male sex partners among women living with HIV (adjusted hazard ratios of 1.69 and 3.17, respectively), potentially by eliciting genital inflammation in women with BV and their male sex partners. BV is also highly prevalent among women in sub‐Saharan Africa, suggesting that BV treatment may have potential as an HIV prevention strategy. BV is typically treated with antibiotics but recurrence rates are high, possibly because treatment does not directly promote Lactobacillus growth. More recently, BV treatment strategies incorporating live biotherapeutic lactobacilli have led to sustained optimization of the vaginal microbiome and a decrease in inflammatory biomarkers previously associated with HIV susceptibility. Future studies are urgently needed to evaluate BV treatment strategies that can optimize the vaginal microbiome in the long term through colonization with H 2 O 2 ‐producing vaginal lactobacilli and to assess whether vaginal microbiota optimization is able to reduce the risk of HIV transmission.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".