Endurance Exercise Rescues Cardiomyopathy in Mitochondrial DNA Mutator Mouse Model of Aging
Bibliographic record
Abstract
A causal role for mitochondrial DNA (mtDNA) mutagenesis in the etiology of age associated cardiomyopathy is supported by the polymerase gamma (PolG) mutator mouse, harbouring a proofreading‐deficient copy of PolG, which exhibits cardiac hypertrophy, mitochondrial dysfunction in cardiomyocytes, and reduced lifespan. Longitudinal studies demonstrate that endurance (END) training reduces risk of cardiovascular diseases and extends life expectancy. We aimed to delineate if END training can prevent cardiac abnormalities and attenuate mitochondrial dysfunction in heart of PolG mice. At 3‐mo, 36 PolG mice (♀ = ♂) were randomly assigned to sedentary (SED) or endurance training (15m/min for 45 min, 3x/week for 5 months) group. END suppressed cardiac hypertrophy (30%) and pathology (abnormal interventricular septal and free wall thickness), and increased mtDNA copy number (2‐fold), COX activity (38%) and lifespan of PolG mice (P<0.05). Using Roche NimbleGen mouse microarray platform, we observed that PolG‐SED hearts had ~100 DE genes (5% FDR) vs. wild‐type (WT) controls (P<0.05). END training normalized 22 DE genes in PolG heart to WT levels (P<0.05). We conclude that END training promotes cardiac mitochondrial oxidative capacity and partially normalizes the transcriptional signature to WT, contributing to the cardiac rejuvenation of PolG mice. We propose that END training is a valuable therapeutic intervention for attenuating cardiac pathology and related morbidity and mortality. (Funded by CIHR)
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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 | 0.001 |
| 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) | 0.002 | 0.001 |
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".