Glutathione Protects Against Exercise‐Induced Oxidative Stress In Mature db/db Mice Hearts
Bibliographic record
Abstract
Low‐intensity exercise improves cardiac antioxidants in young animals irrespective of metabolic changes in type 2 diabetes (T2D). As diabetes and aging synergistically can decrease antioxidants, if exercises can increase antioxidants in mature T2D hearts, is unknown. 8‐month old db/db and wild‐type (WT) mice were moderately exercised for 3 weeks, and cardiac redox regulation was evaluated. Without altering metabolic status, exercise increased cardiac antioxidants and attenuated stress in mature WT mice. In contrast, exercise in db/db mice worsened oxidative damage, which was not explained by superoxide dismutase or catalase activities. Instead, loss of the antioxidant, glutathione (GSH) was noted. Further, GSH biosynthesis [γ‐glutamylcysteine synthase] and recycling [NADPH/NADP, glutathione reductase] were impaired while GSH‐dependent stress (GPX, 4‐hydroxynonenal, TGF‐β) was increased in these hearts. To validate the causal role for GSH, exercising db/db mice were administered exogenous GSH, which attenuated cardiac damage. This study shows that unlike younger animals, short‐term exercise may induce oxidative stress in mature animals and GSH supplementation can inhibit such stress in these hearts. Therefore, recent assertions of detrimental impact of antioxidants during exercise in healthy individuals should be extrapolated with caution in mature T2D patients undergoing exercise.
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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) | 0.001 | 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".