Glucose‐induced oxidative stress and accelerated aging in endothelial cells are mediated by the depletion of mitochondrial SIRTs
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Bibliographic record
Abstract
Diabetic complications cause significant morbidity and mortality. Dysfunction of vascular endothelial cells (ECs), caused by oxidative stress, is a main mechanism of cellular damage. Oxidative stress accelerates EC senescence and DNA damage. In this study, we examined the role of mitochondrial sirtuins (SIRTs) in glucose-induced oxidative stress, EC senescence, and their regulation by miRNAs. Human retinal microvascular endothelial cells (HRECs) were exposed to 5 mmol/L (normoglycemia; NG) or 25 mmol/L glucose (hyperglycemia; HG) with or without transfection of miRNA antagomirs (miRNA-1, miRNA-19b, and miRNA-320; specific SIRT-targeting miRNAs). Expressions of SIRT3, 4 and 5 and their targeting miRNAs were examined using qRT-PCR and ELISAs were used to study SIRT proteins. Cellular senescence was investigated using senescence-associated β-gal stain; while, oxidative stress and mitochondrial alterations were examined using 8-OHdG staining and cytochrome B expressions, respectively. A streptozotocin-induced diabetic mouse model was also used and animal retinas and hearts were collected at 2 months of diabetes. In HRECs, HG downregulated the mRNAs of SIRTs, while SIRT-targeting miRNAs were upregulated. ELISA analyses confirmed such downregulation of SIRTs at the protein level. HG additionally caused early senescence, endothelial-to-mesenchymal transition and oxidative DNA damage in ECs. These changes were prevented by the transfection of specific miRNA antagomirs and by resveratrol. Retinal and cardiac tissues from diabetic mice also showed similar reductions of mitochondrial SIRTs. Collectively, these findings demonstrate a novel mechanism in which mitochondrial SIRTs regulate glucose-induced cellular aging through oxidative stress and how these SIRTs are regulated by specific miRNAs. Identifying such mechanisms may lead to the discovery of novel treatments for diabetic complications.
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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 | 0.001 |
| 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 | 0.000 |
| 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 it