20-Hydroxyeicosatetraenoic Acid is a Potential Therapeutic Target in Cardiovascular Diseases
Bibliographic record
Abstract
Arachidonic acid (AA) is metabolized by enzymes of the cytochrome P450 (CYP) 4A and CYP4F subfamilies to 20- hydroxyeicosatetraeonic acid (20-HETE), which plays an important role in the cardiovascular system. In the current work, we reviewed the formation of 20-HETE in different species by different CYPs; 20-HETE metabolism by cyclooxygenases (COXs) and different isomerases; and the current available inducers and inhibitors of 20-HETE formation in addition to its agonists and antagonists. Moreover we reviewed the negative role of 20-HETE in cardiac hypertrophy, cardiotoxicity, diabetic cardiomyopathy, and in ischemia/reperfusion (I/R) injury. Lastly, we reviewed the role of 20-HETE in different hypertension models such as the renin/angiotensin II model, Goldblatt model, spontaneously hypertensive rat model, androgen-induced model, slat- and deoxycorticosterone acetate (DOCA)-salt-induced models, and high fat diet model. 20-HETE can affect pro- and anti-hypertensive mechanisms dependent upon where, when, and by which isoform it has been produced. In contrast to hypertension we also reviewed the role of 20-HETE in endotoxin-induced hypotension and the natriuretic effects of 20-HETE. Based on the recent studies, 20-HETE production and/or action might be a therapeutic target to protect against the initiation and progression of cardiovascular diseases.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".