Bibliographic record
Abstract
The aim of this chapter is to provide an overview on the role of miRNAs in myocardial ischemia, ischemia/reperfusion injury and ischemic preconditioning. Myocardial ischemia due to occlusion of coronary arteries constitutes the major cause of mortality and morbidity of humans worldwide by causing an array of injuries. Timely myocardial reperfusion remains the most effective treatment strategy for reducing myocardial infarct size, preventing left ventricular remodelling, preserving left ventricular systolic function and improving clinical outcomes. However, the full benefits of myocardial reperfusion are not realized, given that the actual process of reperfusing ischemic myocardium can independently induce myocardial injury. On the other hand, heart has endogenous cardioprotective capability against myocardial/reperfusion injury, called ischemic preconditioning. Recent studies indicate that miRNAs are implicated in all these different aspects of myocardial ischemia. This chapter describes the role of miR-1 and mR-133 in myocardial ischemia, miR-21, miR-29 and miR-320 in ischemia/reperfusion injury, and miR-21 and miR-199a in preconditioning.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.002 |
| 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".