Endurance Exercise, Mitochondrial Rejuvenescence and Aging: On Your Mark, Get Set, GO!
Bibliographic record
Abstract
The role of mitochondrial abnormalities has been extensively characterized in the etiology of systemic decline with aging. A causal role for mitochondrial DNA (mtDNA) mutagenesis in mammalian ageing is supported by recent studies demonstrating that the polymerase gamma (PolG) mutator mouse, harbouring a proofreading‐deficient copy of PolG, exhibits an accelerated aging phenotype, systemic mitochondrial dysfunction, multisystem failure, and reduced lifespan. Longitudinal studies in humans have demonstrated that endurance training reduces the risk of chronic diseases and extends life expectancy. We aimed to delineate if endurance training can prevent the premature aging, and reverse and/or attenuate systemic mitochondrial decline in PolG mice. At 3 months of age, 36 PolG mice (♀ = ♂) were randomly assigned to a sedentary (SED) or forced‐endurance training (END; 15m/min for 45 min, 3x/week for 5 months) group. END induced systemic mitochondrial biogenesis, increased oxidative capacity, restored mitochondrial morphology, and prevented mtDNA depletion in multiple tissues in PolG mice. These adaptations synergistically conferred complete phenotypic protection, rescued multisystem pathology (sarcopenia, cardiac hypertrophy, macrocytic anemia and splenomegaly), and increased lifespan of these mice. We conclude that endurance exercise promotes systemic mitochondrial oxidative capacity, contributing to the complete rejuvenation of PolG mice. However, it seems unlikely that the multi‐organ mitochondrial biogenesis observed is attributable to a single factor which can be mimicked by an “exercise pill.” (Funded by CIHR, and Mr. Warren Lammert and family)
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.008 |
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".