Rectal 1% Tenofovir Gel Use Associates with Altered Epidermal Protein Expression
Bibliographic record
Abstract
Rectal use of a 1% tenofovir (TFV) gel is currently being evaluated for HIV prevention. While careful assessment of mucosal safety of candidate microbicides is a primary concern, tools to assess mucosal toxicity are limited. Mass spectrometry-based proteomics is a sensitive and high-throughput technique that can provide in-depth information on inflammation processes in biological systems. In this study, we utilized a proteomics approach to characterize mucosal responses in study participants involved in a phase 1 clinical trial of a rectal TFV-based gel. Project Gel was a phase 1 randomized (1:1), double-blind, multisite, placebo-controlled trial in which 24 participants received rectal TFV or a universal placebo [hydroxyethyl cellulose (HEC)] over a course of 8 daily doses. Rectal mucosal swabs were collected after 0, 1, and 8 doses and were analyzed by label-free tandem mass spectrometry. Differential protein expression was evaluated using a combination of paired (time-effects) and unpaired (across study arm) t-tests, and multivariate [least absolute shrinkage and selection operator (LASSO)] modeling. Within the TFV arm, 7% (17/249, p < .05) and 10% (25/249, p < .05) of total proteins changed after 1 and 8 daily applications of TFV gel, respectively, compared to 3% (7/249, p < .05) and 6% (16/249, p < .05) in the HEC arm. Biofunctional analysis associated TFV use with a decrease in epidermal barrier proteins (adj. p = 1.21 × 10−10). Multivariate modeling identified 13 proteins that confidently separated TFV gel users (100% calibration and 96% cross-validation accuracy), including the epithelial integrity factors (FLMNB, CRNN, CALM), serpins (SPB13, SPB5), and cytoskeletal proteins (VILI, VIME, WRD1). This study suggested that daily rectal applications of a 1% TFV gel may be associated with mucosal proteome changes involving epidermal development. Further assessment of more extended use of TFV-gel is recommended to validate these initial associations.
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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) | 0.001 | 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".