More than just a garbage can: emerging roles of the lysosome as an anabolic organelle in skeletal muscle
Bibliographic record
Abstract
Skeletal muscle is a highly plastic tissue capable of remodeling in response to a range of physiological stimuli, including nutrients and exercise. Historically, the lysosome has been considered an essentially catabolic organelle contributing to autophagy, phagocytosis, and exo-/endocytosis in skeletal muscle. However, recent evidence has emerged of several anabolic roles for the lysosome, including the requirement for autophagy in skeletal muscle mass maintenance, the discovery of the lysosome as an intracellular signaling hub for mechanistic target of rapamycin complex 1 (mTORC1) activation, and the importance of transcription factor EB/lysosomal biogenesis-related signaling in the regulation of mTORC1-mediated protein synthesis. We, therefore, propose that the lysosome is an understudied organelle with the potential to underpin the skeletal muscle adaptive response to anabolic stimuli. Within this review, we describe the molecular regulation of lysosome biogenesis and detail the emerging anabolic roles of the lysosome in skeletal muscle with particular emphasis on how these roles may mediate adaptations to chronic resistance exercise. Furthermore, given the well-established role of amino acids to support muscle protein remodeling, we describe how dietary proteins "labeled" with stable isotopes could provide a complementary research tool to better understand how lysosomal biogenesis, autophagy regulation, and/or mTORC1-lysosomal repositioning can mediate the intracellular usage of dietary amino acids in response to anabolic stimuli. Finally, we provide avenues for future research with the aim of elucidating how the regulation of this important organelle could mediate skeletal muscle anabolism.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".