Vaginal epithelial dysfunction is mediated by the microbiome, metabolome, and mTOR signaling
Bibliographic record
Abstract
Bacterial vaginosis (BV) is characterized by depletion of Lactobacillus and overgrowth of anaerobic and facultative bacteria, leading to increased mucosal inflammation, epithelial disruption, and poor reproductive health outcomes. However, the molecular mediators contributing to vaginal epithelial dysfunction are poorly understood. Here we utilize proteomic, transcriptomic, and metabolomic analyses to characterize biological features underlying BV in 405 African women and explore functional mechanisms in vitro. We identify five major vaginal microbiome groups: L. crispatus (21%), L. iners (18%), Lactobacillus (9%), Gardnerella (30%), and polymicrobial (22%). Using multi-omics we show that BV-associated epithelial disruption and mucosal inflammation link to the mammalian target of rapamycin (mTOR) pathway and associate with Gardnerella, M. mulieris, and specific metabolites including imidazole propionate. Experiments in vitro confirm that type strain G. vaginalis and M. mulieris supernatants and imidazole propionate directly affect epithelial barrier function and activation of mTOR pathways. These results find that the microbiome-mTOR axis is a central feature of epithelial dysfunction in BV.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".