Synergistic vascular protective effects of combined low doses of PPARα and PPARγ activators in angiotensin II‐induced hypertension in rats
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Protective cardiovascular effects of peroxisome proliferator activated receptor (PPAR)alpha and PPARgamma activators have been demonstrated. If used as vasoprotective agents in high risk vascular patients rather than for their metabolic benefits, these agents could be associated with unwanted side effects. As a proof of concept to support the use of combined low doses of PPARalpha and PPARgamma as vascular protective agents in high risk vascular patients, we tested the hypothesis that combined low doses of PPARalpha (fenofibrate) and PPARgamma (rosiglitazone) activators would provide vascular protective benefits similar to full individual doses of these PPAR agonists. EXPERIMENTAL APPROACH: Male Sprague-Dawley rats infused with Ang II (120 ng kg(-1) min(-1)) were treated with rosiglitazone (1 or 2 mg kg(-1) day(-1)) alone or concomitantly with fenofibrate (30 mg kg(-1) day(-1)) for 7 days. Thereafter, vessels was assessed on a pressurized myograph, while NAD(P)H oxidase activity was determined by lucigenin chemiluminescence. Inflammation was evaluated using ELISA for NFkappaB and Western blotting for adhesion molecules. KEY RESULTS: Ang II-induced blood pressure increase, impaired acetylcholine-induced vasorelaxation, altered vascular structure, and enhanced vascular NAD(P)H oxidase activity and inflammation were significantly reduced by low dose rosiglitazone+fenofibrate. CONCLUSIONS AND IMPLICATIONS: Combined low doses of PPARalpha and PPARgamma activators attenuated development of hypertension, corrected vascular structural abnormalities, improved endothelial function, oxidative stress, and vascular inflammation. These agents used in low-dose combination have synergistic vascular protective effects. The clinical effects of combined low-dose PPARalpha and PPARgamma activators as vascular protective therapy, potentially with reduced side-effects and drug interactions, should be assessed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".