LncRNA-ANRIL inhibits cell senescence of vascular smooth muscle cells by regulating miR-181a/Sirt1
Bibliographic record
Abstract
BACKGROUND: locus (ANRIL) is a kind of long non-coding RNA (lncRNA) that plays important roles in cell senescence. However, the role and mechanism of ANRIL in senescence of vascular smooth muscle cells (VSMCs) are unclear. METHODS: Cell viability and cell cycle were evaluated using an MTT assay and flow cytometry analysis, respectively. Senescence-associated (SA)-β-galactosidase (gal) staining was used to determine cell senescence. Dual luciferase reporter assays were conducted to confirm the binding of ANRIL and miR-181a, as well as miR-181a and Sirt1. The expression of ANRIL, miR-181a, and Sirt1 was determined using qRT-PCR and protein levels of SA-β-gal and p53-p21 pathway-related proteins were evaluated by Western blotting. RESULTS: ANRIL and Sirt1 were down-regulated, whereas miR-181a was up-regulated in aging VSMCs. In young and aging VSMCs, over-expression of ANRIL could down-regulate miR-181a and up-regulate Sirt1. MTT and SA-β-gal staining assays showed that over-expression of ANRIL and inhibition of miR-181a promoted cell viability and inhibited VSMC senescence. The dual-luciferase reporter assay determined that miR-181a directly targets ANRIL and the 3'-UTR of Sirt1. Furthermore, over-expression of ANRIL inhibited cell cycle arrest and the p53-p21 pathway. CONCLUSION: ANRIL promotes cell viability and inhibits senescence in VSMCs, possibly by regulating miR-181a/Sirt1, and alleviating cell cycle arrest by inhibiting the p53-p21 pathway. This study provides novel insights for the role of ANRIL in the development of cell senescence.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| 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".