HIV‐Exposed Seronegative Female Sex Workers Show Different Cellular Immune Profiles Across the Menstrual Cycle
Bibliographic record
Abstract
PROBLEM: Female sex workers (FSWs) are at higher risk of acquiring HIV. Interestingly, some FSWs who are highly exposed remain seronegative for HIV (HESN). This natural resistance to HIV infection has been attributed to an immune quiescence (IQ) phenotype. Our study investigates how the menstrual cycle phases (follicular and luteal) impact the immune responses in Kenyan FSWs. METHODS: This is a part of the Longitudinal Assessment of Mucosal Immune Quiescence study (LAMIQ), 48 FSWs not living with HIV and not using hormonal contraception were followed for a menstrual cycle and divided into two groups based on duration of sex work: New Negative (NN) with 3 years or less and HESN with at least 7 years of involvement in sex work. We obtained blood and cervicovaginal samples and measured sex hormone, cytokine, and chemokine levels, and blood and endocervical T-cell and NK-cell phenotypes. RESULTS: We observed differences in how the immune response of NN and HESN responds to sex hormones. Indeed, the level of mucosal Annexin A3 measured was higher during the luteal phase in HESN, which was not observed in NN. HESN exhibited a higher CD39 expression on their Treg during the luteal phase, while maintaining CTLA-4 expression compared to NN. Furthermore, in HESN, NK cell activation varied across the menstrual cycle phases. They had a higher expression of NKG2D and an increase in the cluster of CD95+ HLA-DR+ NK cells during the follicular phase. This suggests stronger innate immune activation in HESN during the follicular phase of the menstrual cycle. CONCLUSION: Our data indicate that, in HESN, there is a modulation of the immune response based on the menstrual cycle, which potentially limits the availability of HIV target cells at the female genital tract during the luteal phase of the menstrual cycle (window of susceptibility).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".