Fenofibrate Modulates Cytochrome P450 and Arachidonic Acid Metabolism in the Heart and Protects Against Isoproterenol-induced Cardiac Hypertrophy
Bibliographic record
Abstract
It has been previously shown that the cytochrome P450 (P450) modulator, fenofibrate, protects against cardiovascular diseases. P450 and their metabolites, epoxyeicosatrienoic acids (EETs) and 20-hydroxyeicosatetraenoic acid (20-HETE) were found to play an important role in cardiovascular diseases. Therefore, it is important to examine whether fenofibrate would modulate the cardiac P450 and its associated arachidonic acid metabolites and whether this modulation protects against isoproterenol-induced cardiac hypertrophy. For this purpose, male Sprague-Dawley rats were treated with fenofibrate (30 mg·kg·d), isoproterenol (4.2 mg·kg·d), or the combination of both. The expression of hypertrophic markers and different P450s along with their metabolites was determined. Our results showed that fenofibrate significantly induced the cardiac P450 epoxygenases, such as CYP2B1, CYP2B2, CYP2C11, and CYP2C23, whereas it decreased the cardiac ω-hydroxylase, CYP4A3. Moreover, fenofibrate significantly increased the formation of 14,15-EET, 11,12-EET, and 8,9-EET, whereas it decreased the formation of 20-HETE in the heart. Furthermore, fenofibrate significantly decreased the hypertrophic markers and the increase in heart-to-body weight ratio induced by isoproterenol. This study demonstrates that fenofibrate alters the expression of cardiac P450s and their metabolites and partially protects against isoproterenol-induced cardiac hypertrophy, which further confirms the role of P450s, EETs, and 20-HETE in the development of cardiac hypertrophy.
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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".