Impact of doxycycline pre-exposure prophylaxis (doxyPrEP) for sexually transmitted infections on the microbiome of men who have sex with men on HIV PrEP
Bibliographic record
Abstract
Doxycycline pre-exposure prophylaxis (doxyPrEP) has shown potential in preventing bacterial sexually transmitted infections, but the impact on the microbiome is unknown. This study assessed rectal microbiome changes over 48 weeks in 41 participants on HIV PrEP (tenofovir disoproxil fumarate/emtricitabine) enrolled in an open-label, randomized pilot trial comparing immediate (100 mg PO daily started immediately and continued to week 48) versus deferred doxyPrEP (100 mg PO daily starting at week 24, continued to week 48) in HIV-negative gay and bisexual men (Clinical Trial #: NCT02844634). Primary study outcomes included feasibility, adherence, and tolerability of the dual PrEP regimen, while exploratory outcomes included rectal microbiome changes. We performed 16S rRNA sequencing from participants that collected baseline, week 24, and week 48 samples. Microbial composition did not significantly change over time in either study arm as measured by individual taxa levels, or alpha and beta diversity at the genus level. A slight decrease ( < 10%) in alpha diversity was observed at the phylum level in the immediate arm, but not the deferred arm. This study shows doxyPrEP use results in minimal compositional changes in the microbiome over 12 months. Further research is needed to explore the impact of doxycycline for STI prevention on microbiome function and antimicrobial resistance.
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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 | 0.001 |
| 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) | 0.002 | 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".