Reduced HIV-1 latent reservoir outgrowth and distinct immune correlates among women in Rakai, Uganda
Bibliographic record
Abstract
HIV-1 infection remains incurable owing to the persistence of a viral reservoir that harbors integrated provirus within host cellular DNA. Increasing evidence links sex-based differences in HIV-1 immune responses and pathogenesis; however, little is known about differences in HIV-1 infection persistence. Here, we quantified persistent HIV-1 infection in 90 adults on suppressive antiretroviral therapy in Rakai, Uganda (57 female patients). Total HIV-1 DNA was quantified by PCR, and replication-competent provirus by quantitative viral outgrowth assay (QVOA). Immune phenotyping of T cell subsets and plasma biomarkers was also performed. We found that whereas both sexes had similar total HIV DNA levels, female patients had significantly fewer resting CD4+ T cells harboring replication-competent virus, as measured by viral outgrowth in the QVOA. Factors associated with viral outgrowth differed by sex; notably, frequency of programmed cell death 1 (PD1+) CD4+ T cells correlated with reservoir size in male but not female patients. The sex-based differences in HIV-1 persistence observed in this cohort warrant additional research, especially given the widespread use of the QVOA to assess reservoir size and current explorations of PD1 agonists in cure protocols. Efforts should be made to power future cure studies to assess outcomes in both male and female patients.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".