Hormonal influence on <scp>HIV</scp>‐1 transmission in the female genital tract: New insights from systems biology
Bibliographic record
Abstract
Although anti-retroviral treatments have significantly slowed down the spread of the HIV-1 pandemic, approximately 2 million new infections occur every year. The majority of new infections are in sub-Saharan Africa where rates of infection are much higher in women than men. Young women are disproportionately affected and have higher susceptibility to HIV-1. The complex interactions between HIV-1 and the female genital tract (FGT) and the mechanisms regulating susceptibility in women remain incompletely understood. In this review, we focus on the current understanding of the acute events that occur in the FGT following HIV-1 exposure with a particular focus on the effect of endogenous and exogenous sex hormones on HIV-1 susceptibility. We highlight the contribution of the recent transcriptomic and proteomic studies in providing new insights.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".