Regulation of Skeletal Muscle Plasticity by Protein Arginine Methyltransferases and Their Potential Roles in Neuromuscular Disorders
Bibliographic record
Abstract
Protein arginine methyltransferases (PRMTs) are a family of enzymes that catalyze the methylation of arginine residues on target proteins, thereby mediating a diverse set of intracellular functions that are indispensable for survival. Indeed, full-body knockouts of specific PRMTs are lethal and PRMT dysregulation has been implicated in the most prevalent chronic disorders, such as cancers and cardiovascular disease (CVD). PRMTs are now emerging as important mediators of skeletal muscle phenotype and plasticity. Since their first description in muscle in 2002, a number of studies employing wide varieties of experimental models support the hypothesis that PRMTs regulate multiple aspects of skeletal muscle biology, including development and regeneration, glucose metabolism, as well as oxidative metabolism. Furthermore, investigations in non-muscle cell types strongly suggest that proteins, such as peroxisome proliferator-activated receptor-γ coactivator-1α, E2F transcription factor 1, receptor interacting protein 140, and the tumor suppressor protein p53, are putative downstream targets of PRMTs that regulate muscle phenotype determination and remodeling. Recent studies demonstrating that PRMT function is dysregulated in Duchenne muscular dystrophy (DMD), spinal muscular atrophy (SMA), and amyotrophic lateral sclerosis (ALS) suggests that altering PRMT expression and/or activity may have therapeutic value for neuromuscular disorders (NMDs). This review summarizes our understanding of PRMT biology in skeletal muscle, and identifies uncharted areas that warrant further investigation in this rapidly expanding field of research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".