Exogenous hydrogen sulfide prevents SOD2 degradation to safeguard renal function in diabetic kidney disease
Bibliographic record
Abstract
Diabetic kidney disease (DKD) is a major contributor to chronic kidney disease. Hydrogen sulfide (H2S) serves as an endogenous gaseous signaling molecule capable of safeguarding renal function within the context of DKD. However, the underlying mechanisms need to be elucidated. This study was undertaken to unveil the mechanisms by which H2S counteracts against DKD. Utilizing mice and human renal tubular epithelial (HK-2) cells, we demonstrated a reduction in cystathionine-γ-lyase/H2S levels within renal tissues of db/db mice and in HK-2 cells subjected to hyperglycemic and hyperlipidemic environments. Notably, we observed that sodium hydrosulfide (NaHS) supplementation could serve as an exogenous source of H2S. Exogenous H2S exhibited the capacity to mitigate the accumulation of reactive oxygen species and attenuate the degradation of superoxide dismutase 2 (SOD2) by Lon protease homolog 1 induced by hyperglycemia and hyperlipidemia, thus affording cellular protection against mitochondrial apoptosis. Consequently, NaHS treatment led to decreased serum levels of blood urea nitrogen and serum creatinine, reflecting alleviated renal damage and thereby preserving renal function in db/db mice. Based on these findings, we propose that exogenous H2S exerts a protective role against DKD by inhibiting SOD2 degradation.
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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 | 0.000 |
| 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) | 0.001 | 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".