Transcriptional response of vaginal epithelial cells to medroxyprogesterone acetate treatment results in decreased barrier integrity
Bibliographic record
Abstract
Medroxyprogesterone acetate (MPA) is a frequently used hormonal contraceptive that has been shown to significantly increase HIV-1 susceptibility by approximately 40 %. However, the underlying mechanism by which this occurs remains unknown. Here, we examined the biological response to MPA by vaginal epithelial cells, the first cells to encounter HIV-1 during sexual transmission, in order to understand the potential mechanism(s) of MPA-mediated increase of HIV-1 infection. Using microarray analysis and in vitro assays, we characterized the response of vaginal epithelial cells, grown in biologically relevant air-liquid interface (ALI) cultures, to physiological levels of female sex hormones, estradiol (E2), progesterone (P4), or MPA. Transcriptional profiling of E2, P4 or MPA-treated vaginal epithelial cells indicated unique transcriptional profiles associated with each hormone. MPA treatment increased transcripts of genes related to cholesterol/sterol synthesis and decreased transcripts related to cell division and cell-cell adhesion, results not seen with E2 or P4 treatments. MPA treatment also resulted in unique gene expression indicative of decreased barrier integrity. Functional assays confirmed that MPA, but not E2 or P4 treatments, resulted in increased epithelial barrier permeability and inhibited cell cycle progression. The effects of MPA on vaginal epithelial cells seen in this study may help explain the increase of HIV-1 infection in women who use MPA as a hormonal contraceptive.
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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 | 0.000 | 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".