Association of Sex Work With Reduced Activation of the Mucosal Immune System
Bibliographic record
Abstract
BACKGROUND: Unprotected intercourse and seminal discharge are powerful activators of the mucosal immune system and are important risk factors for transmission of human immunodeficiency virus (HIV). This study was designed to determine if female sex work is associated with changes in the mucosal immunity. METHODS: Cervicovaginal lavage and plasma from 122 HIV-uninfected female sex workers (FSW) and 44 HIV-uninfected low-risk non-FSW from the same socioeconomic district of Nairobi were analyzed for evidence of immune activation (IA). The cervico-mononuclear cells (CMC) were analyzed for cellular activation by flow cytometry. RESULTS: Lower IA was observed in FSW compared to the low-risk women as demonstrated by the lower level of MIP-3α (P < .001), ITAC (P < .001), MIG (p.0001), IL-1α (P < .001), IL-1β (P < .001), IL-1Rα (P = .0002), IL-6 (P < .001), IL-8 (P < .001), IL-10 (P = .01), IP-10 (P = .0001), MDC (P < .001), MIP-1α, (P < .001), MIP-1β (P = .005), MCP-1 (P = .03), and TNF-α (P = .006). Significant differences were noted as early as 1 year following initiation of sex work and increased with duration of sex work. CONCLUSION: This study showed that sex work is associated with important changes in the mucosal immune system. By analyzing chemokine/cytokine levels and CMC activation, we observed a lower mucosal IA in HIV-uninfected FSW compared to low-risk women.
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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 | 0.000 |
| 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) | 0.004 | 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".