Feasibility and Safety of Cervical Biopsy Sampling for Mucosal Immune Studies in Female Sex Workers from Nairobi, Kenya
Bibliographic record
Abstract
BACKGROUND: There is an urgent need to improve our understanding of the mucosal immuno-pathogenesis of HIV acquisition in the female genital tract, particularly in high-risk women such as female sex workers (FSWs). Cervical biopsy samples offer technical advantages over cytobrush sampling, but there are concerns that this might increase HIV acquisition, particularly if healing is slow and/or women do not abstain from sex during healing. METHODOLOGY/PRINCIPAL FINDINGS: Cervical biopsy samples and cervico-vaginal swabs for co-infection diagnostics, prostate specific antigen (PSA) and immune studies were collected from 59 women, including HIV seropositive and HIV-exposed seronegative (HESN) FSWs as well as lower risk women from Nairobi, Kenya. A clinical-demographic questionnaire was administered and women were instructed to avoid sexual intercourse, douching and the insertion of tampons for 14 days. All participants underwent a repeat exam to assess healing within the 14 days, and had HIV diagnostics at six months. Cervical sampling was well tolerated, and 82% of participants had healed macroscopically by 5 days. Both self-report and PSA screening suggested high levels of compliance with pre- and post-procedure abstinence. Delayed healing was associated with vulvovaginal candidiasis (VVC) and HESN status. At six-month follow up all low-risk and HESN participants remained HIV seronegative. CONCLUSION: Cervical biopsy sampling is a safe and well-tolerated method to obtain cervical biopsies in this context, particularly if participants with VVC are excluded. As healing could be delayed up to 11 days, it is important to support (both financially and with rigorous counseling) a period of post-procedure abstinence to minimize HIV risk.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".