PPARα activation in portal hypertension
Bibliographic record
Abstract
Abstract Peroxisome proliferator-activated receptor α (PPARα) is a transcription factor activated by ligands that regulates genes related to vascular tone, oxidative stress, and fibrogenesis, pathways implicated in the development of cirrhosis and portal hypertension. This study aims at evaluating the effects of PPARα activation with fenofibrate on hepatic and systemic hemodynamics, hepatic endothelial dysfunction, and hepatic fibrosis in CCl(4)-cirrhotic rats. Mean arterial pressure (MAP), portal pressure (PP), and portal blood flow (PBF) were measured in cirrhotic rats treated with oral fenofibrate (25mg/kg/day, n=10) or its vehicle (n=12) for 7 days. The liver was then perfused and dose-relaxation curves to acetylcholine (Ach) were performed. We also evaluated Sirius Red staining of liver sections, collagen-I mRNA expression, and smooth muscle actin (α-SMA) protein expression, cyclo-oxygenase-1 (COX-1) protein expression, and cGMP levels in liver homogenates, and TXB(2) production in perfusates. Nitric oxide (NO) bioavailability and eNOS activation were measured in hepatic endothelial cells (HEC) isolated from cirrhotic rat livers. CCl(4) cirrhotic rats treated with fenofibrate had a significantly lower PP (-29%) and higher MAP than those treated with vehicle. These effects were associated with a significant reduction in hepatic fibrosis and improved vasodilatory response to acetylcholine. Moreover, a reduction in COX-1 expression and TXB(2) production in rats receiving fenofibrate and a significant increase in NO bioavailability in HEC with fenofibrate were observed. PPARα activation markedly reduced PP and liver fibrosis and improved hepatic endothelial dysfunction in cirrhotic rats, suggesting it may represent a new therapeutic strategy for portal hypertension in cirrhosis.
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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 | 0.001 |
| 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".