The emergence of protein arginine methyltransferases in skeletal muscle and metabolic disease
Bibliographic record
Abstract
Protein arginine methyltransferases (PRMTs) are a family of enzymes that catalyze the methylation of arginine residues on target proteins and thus alter the stability, localization, or activity of the substrate. In doing so, PRMTs mediate a variety of intracellular functions that are essential for survival. Additionally, PRMT dysregulation is involved in a number of the most prevalent health disorders, including cancer and neurodegenerative and cardiovascular diseases, as well as in the aging process. Investigations of PRMT biology in skeletal muscle cells began in 2002, and since then these enzymes have emerged as regulators of skeletal muscle phenotype determination, maintenance, and remodeling. Specifically, more recent in vivo studies have revealed that PRMTs impact multiple aspects of skeletal muscle biology, including satellite cell function and phenotypic plasticity in response to exercise and disuse. Skeletal muscle plays critically important roles in regulating whole body metabolism, and recent investigations have also begun elucidating PRMT expression and function under conditions of metabolic dysfunction. The goals of this review are to 1) summarize the literature on PRMT biology in skeletal muscle with a particular emphasis on the in vivo evidence and 2) survey PRMTs in metabolic disorders, namely, obesity and type 2 diabetes mellitus. We also identify notable knowledge gaps therein and present opportunities to further expand our understanding of these enzymes so critical to health and disease.
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 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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".