Molecular hydrogen downregulates acute exhaustive exercise-induced skeletal muscle damage
Bibliographic record
Abstract
Physical exercise-induced skeletal muscle damage may be characterized by increased oxidative stress, inflammation, and apoptosis which may be beneficial when exercise is regular, but it is rather harmful when exercise is exhaustive and performed acutely by unaccustomed individuals. Molecular hydrogen (H2) has emerged as a potent antioxidant, anti-inflammatory, and anti-apoptotic agent, but its action on the deleterious effects of acute exhaustive exercise in muscle damage remain unknown. Therefore, we tested the hypothesis that H2 decreases acute exhaustive exercise-induced skeletal muscle damage of sedentary rats. Rats ran to exhaustion on a sealed treadmill inhaling an H2-containing mixture or the control gas. We measured oxidative stress (SOD, GSH, and TBARS), inflammatory (TNF-α, IL-1β, IL-6, IL-10, and NF-κB phosphorylation), and apoptotic (expression of caspase-3, Bcl-2, and HSP70) markers. Exercise caused no changes in SOD activity but increased TBARS levels. H2 caused increases in exercise-induced SOD activity and blunted exercise-induced increased TBARS levels. We observed exercise-induced TNF-α and IL-6 surges as well as NF-κB phosphorylation, which were blunted by H2. Exercise increased cleaved caspase-3 expression, and H2 reduced this response. In conclusion, H2 effectively downregulates muscle damage, reducing oxidative stress, inflammation, and apoptosis after acute exhaustive exercise performed by an unaccustomed organism.
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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".