MicroRNA-760-mediated low expression of DUSP1 impedes the protective effect of NaHS on myocardial ischemia–reperfusion injury
Bibliographic record
Abstract
Myocardial ischemia–reperfusion injury (MIRI) is the leading cause of the poor prognosis for patients undergoing clinical cardiac surgery. Micro-RNAs are involved in MIRI; however, the effect of miR-760 on MIRI and the molecular mechanisms behind it have not yet been described. For our in-vivo experiments, 20 rats were randomly distributed between 2 groups (n = 10): the sham-treatment group and the ischemia–reperfusion (I/R) group. For our in-vitro experiments, H9C2 cells were subjected to hypoxia for 6 h, and then reoxygenated to establish an hypoxia–reoxygenation (H/R) model. High expression levels of of miR-760 were observed in the rats subjected to MIRI and the H9C2 cells subjected to H/R. Further, the levels of lactate dehydrogenase (LDH) and malonaldehyde (MDA) were increased, and the size of the myocardial infarct was notably greater in the rats subjected to MIRI, suggesting that miR-760 worsens the effects of MIRI. The inhibitory effects from NaHS on apoptosis were enhanced, as were the expression levels of cleaved caspase 3 and cleaved PARP in H9C2 cells exposed to H/R, and with low-expression levels of miR-760. TargetScan and dual luciferase reporter assays further confirmed the targeted relationship between dual-specificity protein phosphatase (DUSP1) and miR-760. Additionally, miR-760 overexpression and H/R treatment of H9C2 cells inhibited the expression of DUSP1, which further promoted apoptosis. Furthermore, DUSP1 enhanced the anti-apoptotic effects of NaHS in rats subjected to MIRI. Taken together, these findings suggest that miR-760 inhibits the protective effect of NaHS against MIRI.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".