Role of cytochrome P450–mediated arachidonic acid metabolites in the pathogenesis of cardiac hypertrophy
Bibliographic record
Abstract
A plethora of studies have demonstrated the expression of cytochrome P450 (CYP) and soluble epoxide hydrolase (sEH) enzymes in the heart and other cardiovascular tissues. In addition, the expression of these enzymes is altered during several cardiovascular diseases (CVDs), including cardiac hypertrophy (CH). The alteration in CYP and sEH expression results in derailed CYP-mediated arachidonic acid (AA) metabolism. In animal models of CH, it has been reported that there is an increase in 20-hydroxyeicosatetraenoic acid (20-HETE) and a decrease in epoxyeicosatrienoic acids (EETs). Further, inhibiting 20-HETE production by CYP ω-hydroxylase inhibitors and increasing EET stability by sEH inhibitors have been proven to protect against CH as well as other CVDs. Therefore, CYP-mediated AA metabolites 20-HETE and EETs are potential key players in the pathogenesis of CH. Some studies have investigated the molecular mechanisms by which these metabolites mediate their effects on cardiomyocytes and vasculature leading to pathological CH. Activation of several intracellular signaling cascades, such as nuclear factor of activated T cells, nuclear factor kappa B, mitogen-activated protein kinases, Rho-kinases, Gp130/signal transducer and activator of transcription, extracellular matrix degradation, apoptotic cascades, inflammatory cytokines, and oxidative stress, has been linked to the pathogenesis of CH. In this review, we discuss how 20-HETE and EETs can affect these signaling pathways to result in, or protect from, CH, respectively. However, further understanding of these metabolites and their effects on intracellular cascades will be required to assess their potential translation to therapeutic approaches for the prevention and/or treatment of CH and heart failure.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".