Cardioprotective effects of CYP-derived epoxy metabolites of docosahexaenoic acid involve limiting NLRP3 inflammasome activation
Bibliographic record
Abstract
Impaired mitochondrial function and activation of NLRP3 inflammasome cascade has a significant role in the pathogenesis of myocardial ischemia–reperfusion (IR) injury. The current study investigated whether eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), or their corresponding CYP epoxygenase metabolites 17,18-epoxyeicosatetraenoic acid (17,18-EEQ) and 19,20-epoxydocosapentaenoic acid (19,20-EDP) protect against IR injury. Isolated mouse hearts were perfused in the Langendorff mode with vehicle, DHA, 19,20-EDP, EPA, or 17,18-EEQ and subjected to 30 min of ischemia and followed by 40 min of reperfusion. In contrast with EPA and 17,18-EEQ, DHA and 19,20-EDP exerted cardioprotection, as shown by a significant improvement in postischemic functional recovery associated with significant attenuation of NLRP3 inflammasome complex activation and preserved mitochondrial function. Hearts perfused with DHA or 19,20-EDP displayed a marked reduction in localization of mitochondrial Drp-1 and Mfn-2 as well as maintained Opa-1 levels. DHA and 19,20-EDP preserved the activities of both the cytosolic Trx-1 and mitochondrial Trx-2. DHA cardioprotective effect was attenuated by the CYP epoxygenase inhibitor N-(methysulfonyl)-2-(2-propynyloxy)-benzenehexanamide. In conclusion, our data indicate a differential cardioprotective response between DHA, EPA, and their active metabolites toward IR injury. Interestingly, 19,20-EDP provided the best protection against IR injury via maintaining mitochondrial function and thereby reducing the detrimental NLRP3 inflammasome responses.
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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) | 0.001 | 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".