The Long Non-Coding RNA SNHG1 Attenuates Cell Apoptosis by Regulating miR-195 and BCL2-Like Protein 2 in Human Cardiomyocytes
Bibliographic record
Abstract
BACKGROUND/AIMS: Long non-coding RNAs (lncRNAs) are theorized to play key roles in the development of heart diseases. However, the role of lncRNAs in cardiomyocyte apoptosis is largely unknown. The present study examined the role of lncRNA SNHG1 in the human cardiomyocytes (HCMs) apoptosis and explored the underlying molecular mechanisms. METHODS: SNHG1, miR-195 and mRNA expression was detected by qRT-PCR; protein level was determined by western blot; cell viability was detected by MTT assay; cell apoptosis was evaluated by flow cytometry and caspase-3 activity assay; the interaction between SNHG1 and miR195 was examined by using luciferase reporter assay. RESULTS: Hydrogen peroxide (H2O2) treatment significantly suppressed cell viability and increased cell apoptotic rate and caspase-3 activity in HCMs. Overexpression of SNHG1 attenuated the effects of H2O2 on HCMs viability and apoptosis; while SNHG1 exerted the opposite effects. SNHG1 was found to sponge miR-195 and suppress the expression of miR-195 in HCMs. Overexpression of miR-195 suppressed cell viability and induced apoptosis in HCMs, and miR-195 was found to negatively regulate the expression of BCL-2 like protein 2 (BCL2L2) via targeting its 3' untranslated region. Overexpression of BCL2L2 partially reversed the effects of miR-195 overexpression on cell viability and cell apoptosis of HCMs. MiR-195 overexpression or BCL2L2 knockdown attenuated the effects of SNHG1 overexpression on cell viability, cell apoptosis and protein levels of cleaved caspase-3, cleaved caspase-9 and Bax in H2O2-treated HCMs. CONCLUSION: Our results suggest a novel SNHG1/miR-195/BCL2L2 axis in the regulation of cardiomyocyte apoptosis. Modulation of SNHG1 may represent a novel strategy to treat cardiomyocyte apoptosis-related heart diseases.
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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".