Resistance training in patients with single, large-scale deletions of mitochondrial DNA
Bibliographic record
Abstract
Dramatic tissue variation in mitochondrial heteroplasmy has been found to exist in patients with sporadic mitochondrial DNA (mtDNA) mutations. Despite high abundance in mature skeletal muscle, levels of the causative mutation are low or undetectable in satellite cells. The activation of these typically quiescent mitotic cells and subsequent shifting of wild-type mtDNA templates to mature muscle have been proposed as a means of restoring a more normal mitochondrial genotype and function in these patients. Because resistance exercise is known to serve as a stimulus for satellite cell induction within active skeletal muscle, this study sought to assess the therapeutic potential of resistance training in eight patients with single, large-scale mtDNA deletions by assessing: physiological determinants of peak muscle strength and oxidative capacity and muscle biopsy-derived measures of damage, mtDNA mutation load, level of oxidative impairment and satellite cell numbers. Our results show that 12 weeks of progressive overload leg resistance training led to: (i) increased muscle strength; (ii) myofibre damage and regeneration; (iii) increased proportion of neural cell adhesion molecule (NCAM)-positive satellite cells; (iv) improved muscle oxidative capacity. Taken together, we believe these findings support the hypothesis of resistance exercise-induced mitochondrial gene-shifting in muscle containing satellite cells which have low or absent levels of deleted mtDNA. Further investigation is warranted to refine parameters of the exercise training protocol in order to maximize the training effect on mitochondrial genotype and treatment potential for patients with selected, sporadic mutations of mtDNA in skeletal muscle.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".