Non-Alcoholic Fatty Liver Disease in HIV Infection Associated with Altered Hepatic Fatty Acid Composition
Bibliographic record
Abstract
Hepatic fatty acid (FA) composition, especially a reduction in n-3 polyunsaturated FA (PUFA) may contribute to the pathogenesis of non-alcoholic fatty liver disease (NAFLD), which is common in HIV-infection.. In a cross-sectional study we compared hepatic FA composition between 20 HIV-infected men with NAFLD (HIV/NAFLD), 21 HIV-negative men with NAFLD (NAFLD), and 7 healthy controls. Within HIV/NAFLD we compared simple steatosis (HIV/SS) to steatohepatitis (HIV/NASH). FA composition in liver and erythrocytes, oxidative stress, diet, and exercise were assessed. Major findings (P<0.05) were: 1) higher hepatic n-6/n-3 ratio in HIV/NAFLD [median (range)] [8.08 (1.08-21.52)] compared to controls [5.83 (3.58-6.93)] and NAFLD [5.97 (1.46-10.40)], with higher n-6 PUFA in HIV/NAFLD compared to NAFLD; 2) lower n-3 PUFA in erythrocytes (mol%), a marker for dietary intake, in HIV/NAFLD [5.26 (1.04-11.75)] compared to controls [8.92 (4.79-12.67)]; 3) the ratios of long-chain PUFA products to essential FA precursors of the n-6 and n-3 series were lower in HIV/NAFLD and NAFLD compared to controls. In contrast, the ratio of oleic/stearic acid was higher in HIV/NAFLD compared to the other groups. These ratios are indirect markers of enzymatic FA desaturation and elongation. Hepatic PUFA, especially biologically active long-chain PUFA, were also lower in HIV/NASH compared to HIV/SS. Oxidative stress was not different among the groups. We conclude that HIV/NAFLD is associated with altered hepatic FA composition. Changes may be due to impaired FA metabolism or suboptimal n-3 PUFA intake. The potential role of n-3 PUFA (e.g. fish oil) to treat or prevent HIV/NAFLD warrants further investigation.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".