Immune parameters of HIV susceptibility in the female genital tract before and after penile-vaginal sex
Bibliographic record
Abstract
Background: In women, most HIV infections are acquired through penile-vaginal sex. Inflammation in the female genital tract (FGT) increases the risk of HIV acquisition and transmission, likely through recruitment of HIV target cells and disruption of epithelial barrier integrity. Although sex may have important immune and epithelial effects, the impact of receptive penile-vaginal sex on the immune correlates of HIV susceptibility in the female genital tract is not well described. Methods: = 8) penile-vaginal sex. Immune cells were characterized by flow cytometry, and immune factors including cytokines and soluble E-cadherin (sE-cad; a marker of epithelial disruption) were quantified by multiplex immunoassay. Co-primary endpoints were defined as levels of IP-10 and IL-1α, cytokines previously associated with increased HIV susceptibility. Results: Here we show that cervicovaginal levels of vaginal IP-10, sE-cad and several other cytokines increase rapidly after sex, regardless of condom use. The proportion of endocervical HIV target cells, including Th17 cells, activated T cells, and activated or mature dendritic cells (DCs) also increase, particularly after condomless sex. Although most of these immune changes resolve within 72 h, increases in activated cervical CD4 + T cells and Tcm persist beyond this time. Conclusions: Penile-vaginal sex induces multiple genital immune changes that may enhance HIV susceptibility during the 72 h post-sex window that is critical for virus acquisition. This has important implications for the mucosal immunopathogenesis of 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) | 0.004 | 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".