Aerobic exercise elicits clinical adaptations in myotonic dystrophy type 1 patients independently of pathophysiological changes
Bibliographic record
Abstract
BackgroundMyotonic dystrophy type 1 (DM1) is a complex life-limiting neuromuscular disorder characterized by severe skeletal muscle atrophy, weakness, and cardiorespiratory defects. Exercised DM1 mice exhibit numerous physiological benefits that are underpinned by reduced CUG foci and improved alternative splicing. However, the efficacy of physical activity in patients is unknown.MethodsEleven genetically diagnosed DM1 patients were recruited to examine the extent to which 12 weeks of cycling can recuperate clinical and physiological metrics. Furthermore, we studied the underlying molecular mechanisms through which exercise elicits benefits in skeletal muscle of DM1 patients.RESULTSDM1 was associated with impaired muscle function, fitness, and lung capacity. Cycling evoked several clinical, physical, and metabolic advantages in DM1 patients. We highlight that exercise-induced molecular and cellular alterations in patients do not conform with previously published data in murine models and propose a significant role of mitochondrial function in DM1 pathology. Finally, we discovered a subset of small nucleolar RNAs (snoRNAs) that correlated to indicators of disease severity.ConclusionWith no available cures, our data support the efficacy of exercise as a primary intervention to partially mitigate the clinical progression of DM1. Additionally, we provide evidence for the involvement of snoRNAs and other noncoding RNAs in DM1 pathophysiology.Trial registrationThis trial was approved by the HiREB committee (no. 7901) and registered under ClinicalTrials.gov (NCT04187482).FundingNeil and Leanne Petroff. Canadian Institutes of Health Research Foundation (no. 143325).
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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) | 0.003 | 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".