Vaginal microbiome-hormonal contraceptive interactions associate with the mucosal proteome and HIV acquisition
Bibliographic record
Abstract
Alterations to the mucosal environment of the female genital tract, such as genital inflammation, have been associated with increased HIV acquisition in women. As the microbiome and hormonal contraceptives can affect vaginal mucosal immunity, we hypothesized these components may interact in the context of HIV susceptibility. Using previously published microbiome data from 685 women in the CAPRISA-004 trial, we compared relative risk of HIV acquisition in this cohort who were using injectable depot medroxyprogesterone acetate (DMPA), norethisterone enanthate (NET-EN), and combined oral contraceptives (COC). In women who were Lactobacillus-dominant, HIV acquisition was 3-fold higher in women using DMPA relative to women using NET-EN or COC (OR: 3.27; 95% CI: 1.24-11.24, P = 0.0305). This was not observed in non-Lactobacillus-dominant women (OR: 0.95, 95% CI: 0.44-2.15, P = 0.895) (interaction P = 0.0686). Higher serum MPA levels associated with increased molecular pathways of inflammation in the vaginal mucosal fluid of Lactobacillus-dominant women, but no differences were seen in non-Lactobacillus dominant women. This study provides data suggesting an interaction between the microbiome, hormonal contraceptives, and HIV susceptibility.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".