Emerging role of non-coding RNAs and extracellular vesicles in cardioprotection by remote ischemic conditioning of the heart
Bibliographic record
Abstract
Remote ischemic conditioning of the heart (including pre-, per-, and post-conditioning) is a phenomenon where short episodes of non-lethal ischemia in the distant vessels within the heart or distant organs from the heart protects the myocardium against sustained ischemia/reperfusion injury. Several pathways have been proposed to be involved in the mechanisms of Remote ischemic conditioning. While triggers of Remote ischemic conditioning act in preconditioned areas, its mediators transduce protective signals via humoral or neuronal pathways to the heart. Remote ischemic conditioning is mediated via receptor and nonreceptor signaling through secondary mediators, which transfer the signal within the cardiomyocyte and activate cardioprotective pathways that lead to higher resistance of the heart to ischemia/reperfusion. Apparently, identification of endogenous signal molecules involved in the mechanisms of Remote ischemic conditioning have therapeutic implications in the management of patients suffering from myocardial ischemia through the development of diverse beneficial effects. Recently, different non-coding RNAs such as microRNAs or long non-coding RNAs have been identified as emerging factors that trigger protective mechanisms in the heart. These non-coding RNAs are transferred to the heart via extracellular vesicles that exert remote cardioprotection. This review is intended to summarize the existing knowledge about the potential role of extracellular vesicles as humoral transmitters of Remote ischemic conditioning and emphasize the involvement of non-coding RNAs in the mechanism of cardioprotection by Remote ischemic conditioning.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".