Using safe, affordable and accessible non‐steroidal anti‐inflammatory drugs to reduce the number of HIV target cells in the blood and at the female genital tract
Bibliographic record
Abstract
INTRODUCTION: At its basic level, HIV infection requires a replication-competent virus and a susceptible target cell. Elevated levels of vaginal inflammation has been associated with the increased risk of HIV infection as it brings highly activated HIV target cells (CCR5+CD4+ T cells; CCR5+CD4+CD161+ Th17 T cells) to the female genital tract (FGT) where they interact with HIV. Decreased HIV risk has been associated with a phenotype of decreased immune activation, called immune quiescence, described among Kenyan female sex workers who were intensely exposed to HIV yet remain uninfected. Current prevention approaches focus on limiting viral access. We took the novel HIV prevention approach of trying to limit the number of HIV target cells in the genital tract by reducing inflammation using safe, affordable and globally accessible anti-inflammatory drugs. METHODS: We hypothesized that the daily administration of low doses of acetylsalicylic acid (ASA 81 mg) or hydroxychloroquine (HCQ 200 mg) would reduce inflammation thereby decreasing HIV target cells at the FGT. Low-risk HIV seronegative women from Nairobi, Kenya were randomized for six weeks therapy of ASA (n = 37) or HCQ (n = 39) and tested to determine the impact on their systemic and mucosal immune environment. RESULTS: The results showed that HCQ use was associated with a significant reduction in the proportion of systemic T cells that were CCR5+CD4+ (p = 0.01) and Th17 (p = 0.01). In the ASA arm, there was a 35% and 28% decrease in the proportion of genital T cells that were CD4+CCR5+ (p = 0.017) and Th17 (p = 0.04) respectively. Proteomic analyses of the cervical lavage showed ASA use was associated with significantly reduced amount of proteins involved in the inflammatory response and cell recruitment at the mucosa, although none of the individual proteins passed multiple comparison correction. These changes were more apparent in women with Lactobacillus dominant microbiomes. CONCLUSION: Together, these data indicate that taking low-dose ASA daily was associated with significant reduction in HIV target cells at the FGT. This study provides proof-of-concept for a novel HIV-prevention approach that reducing inflammation using safe, affordable and globally accessible non-steroidal anti-inflammatory agents is associated with significant reduction in the proportion of HIV-target cells at the FGT.
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 | 0.000 |
| 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 | 0.001 |
| 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".