Effect of Ischemia Reperfusion Injury and Epoxyeicosatrienoic Acids on Caveolin Expression in Mouse Myocardium
Bibliographic record
Abstract
BACKGROUND: Caveolins (Cav) are structural proteins that insert into the plasma membrane to form caveolae that can bind molecules important in cardiac signal transduction and function. Cytochrome P450 epoxygenases can metabolize arachidonic acid to epoxyeicosatrienoic acids (EETs) which have known cardioprotective effects. Subsequent metabolism of EETs by soluble epoxide hydrolase reduces the protective effect. AIMS: (1) To assess the effect of ischemia-reperfusion injury on expression and subcellular localization of caveolins. (2) To study the effect of EETs on caveolins. METHODS: Hearts from soluble epoxide hydrolase null (KO) and littermate control (WT) mice were perfused in Langendorff mode and subjected to 20 minutes ischemia followed by 40 minutes reperfusion. Immunohistochemistry, immunoblot, and electron microscopy were performed to study localization of caveolins and changes in ultrastructure. RESULTS: In WT heart, Cav-1 and Cav-3 were present in cardiomyocyte and capillary endothelial cell at baseline. After ischemia, Cav-1 but not Cav-3, disappeared from cardiomyocyte; moreover, caveolae were absent and mitochondrial cristae were damaged. Improved postischemic functional recovery observed in KO or WT hearts treated with 11,12-EET corresponded to higher Cav-1 expression and maintained caveolae structure. In addition, KO mice preserved the Cav-1 signaling after ischemia that lost in WT mice. CONCLUSIONS: Taken together, our data suggest that ischemia-reperfusion injury causes loss of Cav-1 and caveolins, and EETs-mediated cardioprotection involves preservation of Cav-1.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".