MicroRNA-124a Protects the Myocardium Against Ischemia Reperfusion Injury Through Regulation of the Notch Signaling Pathway
Bibliographic record
Abstract
Abstract Introduction: This study’s objective is to investigate the effect of downregulation of micro ribonucleic acid (miR)-124a on myocardial injury after ischemia reperfusion (I/R) in rats. Methods: Sprague Dawley (SD) rats (n=20) were divided into four groups - sham, I/R, I/R+miR-124a antagomir (I/R+ant-miR-124a), and I/R+ant-normal control (NC). The pathomorphological and infarct size variance of injured myocardial tissues with IR were conducted with hematoxylin (HE) and triphenyltetrazolium chloride (TTC) staining. The expression levels of miR-124a, BAX, nuclear factor kappa B (NF-KB), Notch1, and Hes1 were examined by quantitative real-time polymerase chain reaction or Western blot in myocardium. The inflammatory cytokines interleukin (IL)-6, IL-1β, and tumor necrosis factor alpha (TNF-α) were detected by the enzyme-linked immunosorbent assay, as well as the activity of lactate dehydrogenase (LDH) and creatine kinase (CK) in serum by colorimetry. Results: The expression of miR-124a was increased in the I/R group. Compared with I/R and I/R+ant-NC groups, after downregulating miR-124a, the expression of IL-6, IL-1β, TNF-α, BAX, NF-KB, LDH, and CK were decreased, but the expression of Notch1 and Hes1 were increased. In HE staining, myocardial tissue edema, red blood cell exudation, and myocardial fiber arrangement disorder were accompanied by inflammatory cell infiltration and local necrosis in the I/R group. However, the pathological injury of myocardial tissue was alleviated after downregulating miR-124a. Additionally, TTC results showed that the myocardial infarction area was decreased in the I/R+ant-miR-124a group. Conclusion: Downregulation of miR-124a expression through Notch pathway can significantly reduce myocardial damage after 24 hours of I/R in SD rats. Therefore, miR-124a may become a potential therapeutic target for I/R injury.
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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".