Copper‐catalyzed ascorbate oxidation results in glyoxal/AGE formation and cytotoxicity
Bibliographic record
Abstract
Previously we showed that 10 muM glyoxal compromised hepatocyte resistance to hydrogen peroxide (H(2)O(2)) by increasing glutathione (GSH) and NADPH oxidation and decreasing mitochondrial membrane potential (MMP) before cytotoxicity ensued. Since transition metal-catalyzed oxidation of ascorbate (Asc) has been shown to result in the generation of both glyoxal and H(2)O(2), we hypothesized that glyoxal formation during this process compromises hepatocyte resistance to H(2)O(2). We used isolated rat hepatocytes and incubated them with Asc/copper and measured cytotoxicity, glyoxal levels, H(2)O(2), GSH levels, and MMP. To investigate the role of Asc/copper on glyoxal-BSA adducts, we measured the appearance of advanced glycation end-products (AGE) in the presence and absence of catalase or aminoguanidine (AG). Asc/copper increased glyoxal and H(2)O(2) formation. Hepatocyte GSH levels were decreased and cytotoxicity ensued after a collapse of the hepatocyte MMP. Glyoxal traps protected hepatocytes against Asc/copper-induced cytotoxicity. In cell-free studies with BSA, incubation with Asc and copper resulted in glyoxal-hydroimidazolone formation, which was decreased by both AG and catalase. To the best of our knowledge, this is the first study that illustrates the importance of glyoxal production by transition metal-catalyzed Asc autoxidation. Understanding this mechanism of toxicity could lead to the development of novel copper chelating drug therapies to treat diabetic complications.
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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) | 0.001 | 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".