S-Sulfhydration of SIRT3 by Hydrogen Sulfide Attenuates Mitochondrial Dysfunction in Cisplatin-Induced Acute Kidney Injury
Bibliographic record
Abstract
Aims: Clinical use of cisplatin (Cisp), one of the most widely used, common, and effective chemotherapeutic agents, is limited by its side effects, particularly tubular injury-associated nephrotoxicity. Previous studies suggest that hydrogen sulfide (H 2 S) alleviates Cisp-induced acute kidney injury (AKI). However, the underlying mechanism remains largely unclear. Results: A single intraperitoneal injection of Cisp is employed to induce AKI, and the mice exhibit severe kidney dysfunction and histological damage at day 4 after Cisp injection. Here, we reported that H 2 S alleviated Cisp-caused renal toxicity via SIRT3 activation and subsequent improvement of mitochondrial ATP production. Using a biotin-switch assay, we showed that H 2 S increased S-sulfhydration of SIRT3 and induced deacetylation of its target proteins (OPA1, ATP synthase β, and superoxide dismutase 2). These effects of H 2 S were associated with a reduction of mitochondrial fragmentation, an increase in ATP generation, and less oxidative injury. Notably, the S-sulfhydration of SIRT3 induced by H 2 S was abrogated when Cys256, Cys259, Cys280, and Cys283 residues on SIRT3 (two zinc finger domains) were mutated. Innovation and Conclusion: Our data suggest that H 2 S attenuates Cisp-induced AKI by preventing mitochondrial dysfunction via SIRT3 sulfhydrylation. Antioxid. Redox Signal. 31, 1302–1319.
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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".