The skeletal muscle fiber periphery: A nexus of mTOR-related anabolism
Bibliographic record
Abstract
Skeletal muscle anabolism is driven by numerous stimuli such as growth factors, nutrients (i.e., amino acids, glucose), and mechanical stress. These stimuli are integrated by the mechanistic target of rapamycin (mTOR) complex 1 (mTORC1) signal transduction cascade. In recent years, work from our laboratory and elsewhere has sought to unravel the molecular mechanisms underpinning the mTOR-related activation of muscle protein synthesis (MPS), as well as the spatial regulation of these mechanisms within the skeletal muscle cell. These studies have suggested that the skeletal muscle fiber periphery is a region of central importance in anabolism (i.e., growth/MPS). Indeed, the fiber periphery is replete with the substrates, molecular machinery, and translational apparatus necessary to facilitate MPS. This review provides a summary of the mechanisms underpinning the mTOR-associated activation of MPS from cell, rodent, and human studies. It also presents an overview of the spatial regulation of mTORC1 in response to anabolic stimuli and outlines the factors that distinguish the periphery of the cell as a highly notable region of skeletal muscle for the induction of MPS. Future research should seek to further explore the nutrient-induced activation of mTORC1 at the periphery of skeletal muscle fibers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".