MitoSNO inhibits mitochondrial hydrogen peroxide generation by α-ketoglutarate dehydrogenase
Bibliographic record
Abstract
Here, we demonstrate mitochondrial hydrogen peroxide (mtH 2 O 2 ) production by α-ketoglutarate dehydrogenase (KGDH) can be inhibited by mitochondria-targeted S-nitrosating agent (MitoSNO), alleviating lipotoxicity. MitoSNO in the nanomolar range inhibits mtH 2 O 2 by ∼50% in isolated liver mitochondria without disrupting respiration, whereas the mitochondria-selective derivative used to synthesize MitoSNO, mitochondria-selective N-acetyl-penicillamine, had no effect on either mtH 2 O 2 generation or oxidative phosphorylation. Additionally, mtH 2 O 2 generation in isolated liver mitochondria was almost abolished when MitoSNO was administered in the low micromolar range. The potent inhibitory effect of MitoSNO was comparable to 2-keto-3-methyl-valeric acid and valproic acid, selective inhibitors for KGDH-mediated mtH 2 O 2 production. S1QEL 1.1 (S1) and S3QEL (S3), which are known to selectively suppress mtH 2 O 2 genesis through inhibition of complex I and complex III, respectively, without disrupting respiration, had little to no effect on mtH 2 O 2 production by liver mitochondria. The MitoSNO also suppressed mtH 2 O 2 production and partially rescued mitochondrial respiration in Huh-7 cells subjected to palmitate- and fructose-induced lipotoxicity. MitoSNO also prevented cell death and abrogated intrahepatic lipid accumulation in these Huh-7 cells. MitoSNO nullified mtH 2 O 2 overgeneration and partially rescued oxidative phosphorylation in liver mitochondria from mice fed a high-fat diet. Our findings demonstrate that MitoSNO interferes with mtH 2 O 2 production through KGDH S-nitrosation and may be useful in alleviating nonalcoholic fatty liver disease.
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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".