Effects of glutathione depletion on apoptotic signaling in slow and fast skeletal muscle of young and old rats
Bibliographic record
Abstract
Oxidative stress has been associated with aging and can also induce apoptosis. Glutathione is an antioxidant widely expressed in mammalian tissue; however, its role in skeletal muscle apoptosis is currently unclear. Young (34.85 ± 0.68 wks) and old (69.11 ± 3.61 wks) male Sprague‐Dawley rats were provided either drinking water alone or drinking water supplemented with L‐buthionine‐[S,R]‐sulfoximine (BSO) for 10 days. BSO treatment significantly (p<0.05) decreased reduced glutathione (GSH) content in white gastrocnemius (WG) and soleus muscle by 96% and 89%, respectively, compared to age‐matched controls. Furthermore, reactive oxygen species generation was significantly (p<0.05) elevated in soleus muscle of young and old BSO‐treated animals. Western blot analysis revealed that heat shock protein‐70 (Hsp70) protein expression was significantly (p<0.05) elevated in old soleus muscle; however, BSO treatment had no effect. There was also a trend towards increased CuZnSOD (p=0.08) protein levels in BSO‐treated animals compared to age‐matched controls. In addition, caspases‐3, ‐8, and ‐9 activity was significantly (p<0.05) increased in old soleus muscle compared to young animals. This data indicates that caspase‐mediated apoptotic signaling is elevated in skeletal muscle during aging, but may not be influenced by glutathione content. Research supported by NSERC of Canada.
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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 | 0.001 | 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".