Highly-Exposed HIV-1 seronegative Female Commercial Sex Workers sustain in their genital mucosa increased frequencies of tolerogenic myeloid and regulatory T-cells
Bibliographic record
Abstract
Abstract We and others have shown that HIV-1 highly-exposed seronegative (HESN) female commercial sex workers (CSWs) maintain low genital inflammatory conditions to prevent HIV infection. HIV-1 interacts with toll-like receptors (TLR)-7/8 to induce interferon (IFN)-α, an important antiviral and immunomodulatory cytokine, which act together with interleukin (IL)-10, human leukocyte antigen (HLA)-G and immunoglobulin-like transcript (ILT)-4 to initiate a “tolerogenic/regulatory” anti-inflammatory loop. In view of further unravelling elements associated with natural immunity to HIV-1, we have characterised TLR-7, IFN-α, IL-10, HLA-G and ILT-4 expression profiles in the genital tract of female CSWs and HIV-1-uninfected non-CSWs from Benin. Endocervical myeloid HLA-DR+ cells from HESN CSWs expressed higher levels of IFN-α, TLR-7, IL-10 and HLA-G than those from both HIV-1-infected CSWs and HIV-1-uninfected non-CSWs. Further characterization of the endocervical myeloid HLA-DR+ cells in HESN CSWs revealed a population of “tolerogenic” CD103+ CD14+ CD11c+ myeloid cells expressing high levels of IFN-α and IL-10. Concomitantly, HESN CSWs had higher frequencies of endocervical regulatory CD4+ T-cells when compared to those from the two other groups of women. These novel findings provide strong evidence to support the implication of tolerogenic myeloid cells expressing high levels of antiviral molecules in shaping the genital mucosal immune response to prevent HIV infection.
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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 | 0.000 |
| 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) | 0.003 | 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".