Ameliorative Role of Fluconazole Against Abdominal Aortic Constriction–Induced Cardiac Hypertrophy in Rats
Bibliographic record
Abstract
ABSTRACT: Cytochrome P450 1B1 (CYP1B1) is known to be involved in the pathogenesis of several cardiovascular diseases, including cardiac hypertrophy and heart failure, through the formation of cardiotoxic metabolites named as mid-chain hydroxyeicosatetraenoic acids (HETEs). Recently, we have demonstrated that fluconazole decreases the level of mid-chain HETEs in human liver microsomes, inhibits human recombinant CYP1B1 activity, and protects against angiotensin II-induced cellular hypertrophy in H9c2 cells. Therefore, the overall purpose of this study was to elucidate the potential cardioprotective effect of fluconazole against cardiac hypertrophy induced by abdominal aortic constriction (AAC) in rats. Male Sprague-Dawley rats were randomly assigned into 4 groups such as sham control rats, fluconazole-treated (20 mg/kg daily for 4 weeks, intraperitoneal) sham rats, AAC rats, and fluconazole-treated (20 mg/kg) AAC rats. Baseline and 5 weeks post-AAC echocardiography were performed. Gene and protein expressions were measured using real-time PCR and Western blot analysis, respectively. The level of mid-chain HETEs was determined using liquid chromatography-mass spectrometry. Echocardiography results showed that fluconazole significantly prevented AAC-induced left ventricular hypertrophy because it ameliorated the AAC-mediated increase in left ventricular mass and wall measurements. In addition, fluconazole significantly prevented the AAC-mediated increase of hypertrophic markers. The antihypertrophic effect of fluconazole was associated with a significant inhibition of CYP1B1, CYP2C23, and 12-LOX and a reduction in the formation rate of mid-chain HETEs. This study demonstrates that fluconazole protects against left ventricular hypertrophy, and it highlights the potential repurposing of fluconazole as a mid-chain HETEs forming enzymes' inhibitor for the protection against cardiac hypertrophy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".