Foreskin inflammation is associated with HIV and herpes simplex virus type-2 infections in Rakai, Uganda
Bibliographic record
Abstract
DESIGN: We assessed foreskin inflammation associated with HIV and herpes simplex virus type 2 (HSV-2) in circumcised men. METHODS: Foreskin tissues were assessed in 97 HIV-infected and 135 HIV-uninfected men enrolled in randomized trials of circumcision in Rakai, Uganda. Inflammation was quantified using an ordinal score evaluating extent, intensity, and cellular composition of infiltrates in the epithelium and stroma. Prevalence rate ratios of inflammation were estimated by multivariate Poisson regression. RESULTS: Foreskin inflammation was primarily focal. Epithelial inflammation was present in 4.2% of men with neither HIV nor HSV-2 infection; 7.8% of men with only HSV-2; 19.0% with HIV alone (P = 0.04); and 31.6% in HIV/HSV-2 coinfected men [prevalence rate ratio (PRR) 7.5, 95% confidence interval (CI) 2.3-23.8, P < 0.001]. Stromal inflammation was present in 14.1% of HIV/HSV-2 uninfected men, compared with 29.7% in men with HSV-2 alone (P = 0.03), 33.3% in men with HIV alone (P = 0.04), and 61.0% in men with HIV/HSV-2 coinfection (PRR 4.3, 95% CI 2.3-7.9, P < 0.001). In HIV-infected men, epithelial inflammation was associated with higher HIV viral load. Epithelial inflammation was more frequent among men reporting recent genital ulceration. Both epithelial and stromal inflammation were more common among men with smegma on physical examination. CONCLUSION: Foreskin inflammation is increased with HIV and HSV-2 infections, higher HIV viral load and presence of smegma. Foreskin inflammation may have implications for HIV transmission and acquisition in uncircumcised men.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".