Cervical Intraepithelial Neoplasia Is Associated With Genital Tract Mucosal Inflammation
Bibliographic record
Abstract
BACKGROUND: Clinical studies demonstrate increased prevalence of human papillomavirus (HPV)-associated disease in HIV-infected individuals and an increased risk of HIV acquisition in HPV-infected individuals. The mechanisms underlying this synergy are not defined. We hypothesize that women with cervical intraepithelial neoplasia (CIN) will exhibit changes in soluble mucosal immunity that may promote HPV persistence and facilitate HIV infection. METHODS: The concentrations of immune mediators and endogenous anti-Escherichia coli activity in genital tract secretions collected by cervicovaginal lavage were compared in HIV-negative women with high-risk HPV-positive (HRHPV+) CIN-3 (n = 37), HRHPV+ CIN-1 (n = 12), or PAP-negative control subjects (n = 57). RESULTS: Compared with control subjects, women with CIN-3 or CIN-1 displayed significantly higher levels of proinflammatory cytokines including interleukin (IL)-1α, IL-1β, and IL-8 (P < 0.002) and significantly lower levels of anti-inflammatory mediators and antimicrobial peptides, including IL-1 receptor antagonist, secretory leukocyte protease inhibitor (P < 0.01), and human β defensins 2 and 3 (P < 0.02). There was no significant difference in endogenous anti-E. coli activity after controlling for age and sample storage time. CONCLUSION: HRHPV+ CIN is characterized by changes in soluble mucosal immunity that could contribute to HPV persistence. The observed mucosal inflammation suggests a mechanism that may also contribute to the epidemiologic link between persistent HPV and HIV.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".