CYP epoxygenase metabolites of docosahexaenoic acid protect HL-1 cardiac cells against LPS-induced cytotoxicity through SIRT1
Bibliographic record
Abstract
Bacterial LPS is an environmental toxin capable of promoting various cardiac complications. Current evidence suggests that LPS-induced myocardial dysfunction emerges as a consequence of compromised quality of cardiac mitochondria. Docosahexaenoic acid (DHA, 22:6n3) is an n-3 polyunsaturated fatty acid (PUFA), which produces a broad spectrum of intrinsic physiological effects including regulation of cell survival and death mechanisms. Although, numerous studies revealed fundamentally beneficial effects of DHA on cardiovascular system, it remains unknown whether these effects were produced by DHA or one of its possibly more potent metabolites. Emerging evidence indicates that cytochrome P450 (CYP) epoxygenase metabolites of DHA, epoxydocosapentaenoic acids (EDPs), produce more potent biological activity compared to its precursor DHA. In this study we investigated whether DHA and its metabolite 19,20-EDP could protect HL-1 cardiac cells against LPS-induced cytotoxicity. We provide evidence that exogenously added or DHA-derived EDPs promote mitochondrial biogenesis and function in HL-1 cardiac cells. Our results illustrate the CYP epoxygenase metabolite of DHA, 19,20-EDP, confers extensive protection to HL-1 cardiac cells against LPS-induced cytotoxicity via activation of SIRT1.
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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) | 0.000 | 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) | 0.002 | 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".