The relationship between sex hormones, the vaginal microbiome and immunity in HIV-1 susceptibility in women
Bibliographic record
Abstract
ABSTRACT The role of sex hormones in regulating immune responses in the female genital tract has been recognized for decades. More recently, it has become increasingly clear that sex hormones regulate susceptibility to sexually transmitted infections through direct and indirect mechanisms involving inflammation and immune responses. The reproductive cycle can influence simian/human immunodeficiency virus (SHIV) infections in primates and HIV-1 infection in ex vivo cervical tissues from women. Exogenous hormones, such as those found in hormonal contraceptives, have come under intense scrutiny because of the increased susceptibility to sexually transmitted infections seen in women using medroxyprogesterone acetate, a synthetic progestin-based contraceptive. Recent meta-analyses concluded that medroxyprogesterone acetate enhanced HIV-1 susceptibility in women by 40%. In contrast, estradiol-containing hormonal contraceptives were not associated with increased susceptibility and some studies reported a protective effect of estrogen on HIV/SIV infection, although the underlying mechanisms remain incompletely understood. Recent studies describe a key role for the vaginal microbiota in determining susceptibility to sexually transmitted infections, including HIV-1. While Lactobacillus spp.-dominated vaginal microbiota is associated with decreased susceptibility, complex microbiota, such as those seen in bacterial vaginosis, correlates with increased susceptibility to HIV-1. Interestingly, sex hormones are inherently linked to microbiota regulation in the vaginal tract. Estrogen has been postulated to play a key role in establishing a Lactobacillus-dominated microenvironment, whereas medroxyprogesterone acetate is linked to hypo-estrogenic effects. The aim of this Review is to contribute to a better understanding of the sex-hormone–microbiome–immunity axis, which can provide key information on the determinants of HIV-1 susceptibility in the female genital tract and, consequently, inform HIV-1 prevention strategies.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".