Pre–Human Immunodeficiency Virus (HIV) α4β7hi CD4+ T Cells and HIV Risk Among Heterosexual Individuals in Africa
Bibliographic record
Abstract
BACKGROUND: CD4+ T cells expressing α4β7 are optimal targets for human immunodeficiency virus (HIV) infections, with higher pre-HIV α4β7hi expression linked to increased HIV acquisition and progression in South African women. However, similar associations were not observed in men who have sex with men or people who inject drugs in the Americas, indicating need for further research. METHODS: This retrospective case-control study enrolled heterosexual men and women from South Africa (HIV Vaccine Trials Network [HVTN] 503) and East Africa (Partners Preexposure Prophylaxis/Couples' Observational Study [PP/COS]), quantifying α4β7 expression on CD4+ T cells as a predictor of subsequent HIV risk using flow cytometry analyses. RESULTS: Associations between α4β7hi expression and HIV acquisition varied across cohorts. In HVTN 503, women had a higher risk estimate compared to men, but this was not significant. In PP/COS, α4β7hi expression was generally protective, particularly in Ugandans. Additionally, α4β7hi expression inversely correlated with peak viral load in PP/COS but not in HVTN 503; in the latter cohort, α4β7hi expression was inversely correlated with the CD4/CD8 ratio and predicted rapid CD4+ T-cell decline, similar to what was observed previously in South Africa. CONCLUSIONS: These findings suggest that α4β7hi expression on CD4+ T cells may not predict HIV acquisition and progression in all contexts, which may be due to cohort effects, modes of transmission, viral clade, or other factors.
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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) | 0.001 | 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".