Regulation of Skeletal Muscle Satellite Cell Differentiation by Omega-3 Polyunsaturated Fatty Acids: A Critical Review
Bibliographic record
Abstract
Skeletal muscle is composed of multinuclear cells called myofibres, which are formed by the fusion of myoblasts during development. The size of the muscle fiber and mass of skeletal muscle are altered in response to several pathological and physiological conditions. Skeletal muscle regeneration is primarily mediated by muscle stem cells called satellite cells (SCs). In response to injury, these SCs replenish myogenic progenitor cells to form new myofibers to repair damaged muscle. During myogenesis, activated SCs proliferate and differentiate to myoblast and then fuse with one another to form muscle fibers. A reduced number of SCs and an inability to undergo myogenesis may contribute to skeletal muscle disorders such as atrophy, cachexia, and sarcopenia. Myogenic regulatory factors (MRF) are transcription factors that regulate myogenesis and determines whether SCs will be in the quiescent, activated, committed, or differentiated state. Mitochondria oxidative phosphorylation and oxidative stress play a role in the determination of the fate of SCs. The potential activation and function of SCs are also affected by inflammation during skeletal muscle regeneration. Omega-3 polyunsaturated fatty acids (PUFAs) show promise to reduce inflammation, maintain muscle mass during aging, and increase the functional capacity of the muscle. The aim of this critical review is to highlight the role of omega-3 PUFAs on the myogenic differentiation of SCs and pathways affected during the differentiation process, including mitochondrial function and inflammation from the current body of literature.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".