SIRT3 Mediates the Antioxidant Effect of Hydrogen Sulfide in Endothelial Cells
Bibliographic record
Abstract
AIM: Oxidative stress is a key contributor to endothelial dysfunction and associated cardiovascular pathogenesis. Hydrogen sulfide (H2S) is an antioxidant gasotransmitter that protects endothelial cells against oxidative stress. Sirtuin3 (SIRT3), which belongs to the silent information regulator 2 (SIR2) family, is an important deacetylase under oxidative stress. H2S is able to regulate the activity of several sirtuins. The present study aims to investigate the role of SIRT3 in the antioxidant effect of H2S in endothelial cells. RESULTS: Cultured EA.hy926 endothelial cells were exposed to hydrogen peroxide (H2O2) as a model of oxidative stress-induced cell injury. GYY4137, a slow-releasing H2S donor, improved cell viability, reduced oxidative stress and apoptosis, and improved mitochondrial function following H2O2 treatment. H2S reversed the stimulation of MAPK phosphorylation, downregulation of SIRT3 mRNA and reduction of the superoxide dismutase 2 and isocitrate dehydrogenase 2 expression which were induced by H2O2. H2S also increased activator protein 1 (AP-1) binding activity with SIRT3 promoter and this effect was absent in the presence of the specific AP-1 inhibitor, SR11302 or curcumin. Paraquat administration to mice induced a defected endothelium-dependent aortic vasodilatation and increased oxidative stress in both mouse aorta and small mesenteric artery, which were alleviated by GYY4137 treatment. This vasoprotective effect of H2S was absent in SIRT3 knockout mice. INNOVATION: The present results highlight a novel role for SIRT3 in the protective effect of H2S against oxidant damage in the endothelium both in vitro and in vivo. CONCLUSION: H2S enhances AP-1 binding activity with the SIRT3 promoter, thereby upregulating SIRT3 expression and ultimately reducing oxidant-provoked vascular endothelial dysfunction. Antioxid. Redox Signal. 24, 329-343.
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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 | 0.001 |
| 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) | 0.004 | 0.001 |
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".