Metabolic remodeling of dystrophic skeletal muscle reveals biological roles for dystrophin and utrophin in adaptation and plasticity
Bibliographic record
Abstract
OBJECTIVES: Preferential damage to fast, glycolytic myofibers is common in many muscle-wasting diseases, including Duchenne muscular dystrophy (DMD). Promoting an oxidative phenotype could protect muscles from damage and ameliorate the dystrophic pathology with therapeutic relevance, but developing efficacious strategies requires understanding currently unknown biological roles for dystrophin and utrophin in dystrophic muscle adaptation and plasticity. METHODS: Combining whole transcriptome RNA sequencing and mitochondrial proteomics with assessments of metabolic and contractile function, we investigated the roles of dystrophin and utrophin in fast-to-slow muscle remodeling with low-frequency electrical stimulation (LFS, 10 Hz, 12 h/d, 7 d/wk, 28 d) in mdx (dystrophin null) and dko (dystrophin/utrophin null) mice, two established preclinical models of DMD. RESULTS: Novel biological roles in adaptation were demonstrated by impaired transcriptional activation of estrogen-related receptor alpha-responsive genes supporting oxidative phosphorylation in dystrophic muscles. Further, utrophin expression in dystrophic muscles was required for LFS-induced remodeling of mitochondrial respiratory chain complexes, enhanced fiber respiration, and conferred protection from eccentric contraction-mediated damage. CONCLUSIONS: These findings reveal novel roles for dystrophin and utrophin during LFS-induced metabolic remodeling of dystrophic muscle and highlight the therapeutic potential of LFS to ameliorate the dystrophic pathology and protect from contraction-induced injury with important implications for DMD and related muscle disorders.
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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".