High-density lipoprotein protects cardiomyocytes against necrosis induced by oxygen and glucose deprivation through SR-B1, PI3K, and AKT1 and 2
Bibliographic record
Abstract
The cardioprotective lipoprotein HDL (high-density lipoprotein) prevents myocardial infarction and cardiomyocyte death due to ischemia/reperfusion injury. The scavenger receptor class B, type 1 (SR-B1) is a high-affinity HDL receptor and has been shown to mediate HDL-dependent lipid transport as well as signaling in a variety of different cell types. The contribution of SR-B1 in cardiomyocytes to the protective effects of HDL on cardiomyocyte survival following ischemia has not yet been studied. Here, we use a model of simulated ischemia (oxygen and glucose deprivation, OGD) to assess the mechanistic involvement of SR-B1, PI3K (phosphatidylinositol-3-kinase), and AKT in HDL-mediated protection of cardiomyocytes from cell death. Neonatal mouse cardiomyocytes and immortalized human ventricular cardiomyocytes, subjected to OGD for 4 h, underwent substantial cell death due to necrosis but not necroptosis or apoptosis. Pretreatment of cells with HDL, but not low-density lipoprotein, protected them against OGD-induced necrosis. HDL-mediated protection was lost in cardiomyocytes from SR-B1−/− mice or when SR-B1 was knocked down in human immortalized ventricular cardiomyocytes. HDL treatment induced the phosphorylation of AKT in cardiomyocytes in an SR-B1-dependent manner. Finally, chemical inhibition of PI3K or AKT or silencing of either AKT1 or AKT2 gene expression abolished HDL-mediated protection against OGD-induced necrosis of cardiomyocytes. These results are the first to identify a role of SR-B1 in mediating the protective effects of HDL against necrosis in cardiomyocytes, and to identify AKT activation downstream of SR-B1 in cardiomyocytes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".