Urinary Eicosanoid Metabolites in HIV-Infected Women with Central Obesity Switching to Raltegravir: An Analysis from the Women, Integrase, and Fat Accumulation Trial
Bibliographic record
Abstract
Chronic inflammation is a hallmark of HIV infection. Eicosanoids reflect inflammation, oxidant stress, and vascular health and vary by sex and metabolic parameters. Raltegravir (RAL) is an HIV-1 integrase inhibitor that may have limited metabolic effects. We assessed urinary F2-isoprostanes (F2-IsoPs), prostaglandin E2 (PGE-M), prostacyclin (PGI-M), and thromboxane B2 (TxB2) in HIV-infected women switching to RAL-containing antiretroviral therapy (ART). Thirty-seven women (RAL = 17; PI/NNRTI = 20) with a median age of 43 years and BMI 32 kg/m(2) completed week 24. TxB2 increased in the RAL versus PI/NNRTI arm (+0.09 versus -0.02; P = 0.06). Baseline PGI-M was lower in the RAL arm (P = 0.005); no other between-arm cross-sectional differences were observed. In the PI/NNRTI arm, 24-week visceral adipose tissue change correlated with PGI-M (rho = 0.45; P = 0.04) and TxB2 (rho = 0.44; P = 0.005) changes, with a trend seen for PGE-M (rho = 0.41; P = 0.07). In an adjusted model, age ≥ 50 years (N = 8) was associated with increased PGE-M (P = 0.04). In this randomized trial, a switch to RAL did not significantly affect urinary eicosanoids over 24 weeks. In women continuing PI/NNRTI, increased visceral adipose tissue correlated with increased PGI-M and PGE-M. Older age (≥ 50) was associated with increased PGE-M. Relationships between aging, adiposity, ART, and eicosanoids during HIV-infection require further study.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".