S14.3 Immune activation, gene expression and hiv acquisition risk
Bibliographic record
Abstract
Background Sexual transmission of HIV is actually fairly inefficient and when it does occur usually a single virus is responsible for establishing the infection. Since activated HIV target cells (CD4+CCR5+) are known to be 1000x more susceptible to HIV infection than quiescent cells, one of the known risk factors for HIV acquisition is elevated baseline levels of immune activation. This study was designed to determine if oral administration of low doses of anti-inflammatory agents, acetylsalicylic acid (ASA) and hydroxychloroquine (HCQ), would reduce the number of HIV target cells in the female genital tract. Methods 80 low-risk women from Nairobi, Kenya established baseline immune activation levels and then were randomized to 6 weeks oral administration of low doses of either ASA (81 mg/day) or HCQ (200 mg/day). Cellular activation (CD69, HLA-DR, CD95, CCR5) was assessed by flow cytometry of peripheral blood mononuclear cells (PBMC) and cervical mononuclear cells (CMC). Results In PBMCs, a reduction in the percentage of CD4+CD69+ (p = 0.01) and CD4+CCR5+ (p = 0.03) T cells was observed in the ASA arm and a significant decrease of CD95 (p < 0.0001) and CCR5 (p = 0.01) expression on CD4+ T cells was observed following HCQ treatment. At the mucosal level, CMCs showed reduced levels of CD4+CCR5+ T cells following ASA treatment (p -0.02) and lower expression of the activation marker CD69 on CD4+ cells in the HCQ arm (p = 0.05). Conclusions Reducing the number of HIV target cells in the female genital tract, represents a new approach to reducing HIV risk. This study showed that daily administration of low-dose anti-inflammatory drugs reduces the number of HIV target cells in the female genital tract. Further studies are required to determine if a similar reduction in mucosal HIV target cells can be observed in women at high-risk of acquiring HIV and if those reduction provide any protective benefit.
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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) | 0.026 | 0.002 |
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".