Silencing of lncRNA PVT1 ameliorates streptozotocin-induced pancreatic β cell injury and enhances insulin secretory capacity by regulating miR-181a-5p
Bibliographic record
Abstract
Diabetes mellitus (DM) is a type of metabolic disorder characterized by long-term hyperglycemia. Accumulating evidence shows that long noncoding RNAs (lncRNAs) play significant roles in the occurrence and development of DM. This study intended to investigate the role of lncRNA plasmacytoma variant translocation 1 (PVT1) in rat insulinoma (INS-1) cells damaged by streptozotocin (STZ) and to identify the potential mechanisms. Firstly, PVT1 expression in INS-1 cells was assessed using RT-qPCR after STZ stimulation. After PVT1-knockdown, cell apoptosis, the contents of oxidative stress related markers, and changes in insulin secretion were detected. Results indicated that PVT1 was remarkably upregulated after STZ stimulation. PVT1-knockdown inhibited STZ-induced oxidative stress and apoptosis of INS-1 cells. Moreover, the insulin secretory capacity was notably elevated following PVT1 silencing. Subsequently, a luciferase reporter assay verified that miR-181a-5p was directly targeted by PVT1. The rescue assays revealed that miR-181a-5p inhibitor dramatically abrogated the effects of PVT1 silencing on oxidative stress, apoptosis, and insulin secretion. Taken together, these findings demonstrated that PVT1-knockdown could ameliorate STZ-induced oxidative stress and apoptosis and elevate insulin secretory capacity in pancreatic β cells by regulating miR-181a-5p, suggesting a promising biomarker in DM diagnosis and treatment.
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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) | 0.001 | 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 | 0.001 |
| 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".