Negative mucosal synergy between Herpes simplex type 2 and HIV in the female genital tract
Bibliographic record
Abstract
OBJECTIVE: There is substantial epidemiological evidence that infection by Herpes simplex virus type 2 (HSV2) enhances both HIV susceptibility and subsequent sexual transmission. Both infections are extremely common in female sex workers (FSWs) in sub-Saharan Africa, and up to 80% of new HIV infections in urban men in the region are acquired via transactional sex. The present study aimed to elucidate the mucosal immune interactions between HIV and HSV2 in the genital tract. METHODS: Endocervical immune cell populations, cytokine/chemokine protein levels in cervico-vaginal secretions and cervical immune gene expression profiles were measured in a well-defined cohort of HIV-infected and uninfected Kenyan FSWs. Associations between the genital immune milieu and infection by and/or shedding of common genital co-pathogens were examined. RESULTS: HIV-infected FSWs were much more likely to be infected by HSV2, and to shed HSV2 DNA in the genital tract. There was also a profound negative 'mucosal synergy' between these viruses. In HIV uninfected FSWs, HSV2 infection was associated with a ten-fold increase in cervical immature dendritic cells (iDC) expressing DC-SIGN, and a three-fold increase in cervical CD4+ T cells expressing CCR5. HIV infection was associated with iDC depletion in the cervix, and with increased HSV2 genital reactivation, which in turn was associated with HIV shedding levels. CONCLUSIONS: The findings suggest a mucosal vicious circle in which HSV2 infection increases HIV target cells in the genital mucosa, subsequent HIV infection impairs HSV2 mucosal immune control, and local HSV2 reactivation enhances both HSV2 and HIV transmission.
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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) | 0.002 | 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".