The Skeletal Muscle Satellite Cell: The Stem Cell That Came in From the Cold
Bibliographic record
Abstract
The muscle satellite cell was first described and actually named on the basis of its anatomic location under the basement membrane surrounding each myofiber. For many years following its discovery, electron microscopy provided the only definitive method of identification. More recently, several molecular markers have been described that can be used to detect satellite cells, making them more accessible for study at the light microscope level. Satellite cells supply myonuclei to growing myofibers before becoming mitotically quiescent in muscle as it matures. They are then activated from this quiescent state to fulfill their roles in routine maintenance, hypertrophy, and repair of adult muscle. Because muscle is able to efficiently regenerate after repeated bouts of damage, systems must be in place to maintain a viable satellite cell pool, and it was proposed over 30 years ago that self-renewal was the primary mechanism. Self-renewal entails either a stochastic event or an asymmetrical cell division, where one daughter cell is committed to differentiation whereas the second continues to proliferate or becomes quiescent. This classic model of satellite cell self-renewal and the importance of satellite cells in muscle maintenance and repair have been challenged during the past few years as bone marrow-derived cells and various intramuscular populations were shown to be able to contribute myonuclei and occupy the satellite cell niche. This is a fast-moving and dynamic field, however, and in this review we discuss the evidence that we think puts this enigmatic cell firmly back at the center of adult myogenesis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".