Extrinsic regulation of satellite cell specification
Bibliographic record
Abstract
Cellular commitment during vertebrate embryogenesis is controlled by an interplay of intrinsic regulators and morphogenetic signals. These mechanisms recruit a subset of cells in the developing organism to become the ancestors of skeletal muscle. Signals that control progression through the myogenic lineage converge on a battery of hierarchically organized transcription factors which modulate the cells to either remain in a primitive state or allow their commitment and differentiation into skeletal muscle fibers. A small population of cells will retain a largely unspecified state throughout development. Such stem cells, in conjunction with more committed myogenic progenitors, form a heterogeneous population that colonizes adult skeletal muscle as satellite cells. The satellite cell pool is responsible for the remarkable regenerative capacity of skeletal muscle. Similar to their counterparts during embryonic development, satellite cells are capable of self-renewal and can give rise to myogenic progeny. Impaired satellite cell homeostasis has been associated with numerous muscular disorders. Due to intense research efforts in the past two decades, the complex biology of muscle stem cells has now revealed some of its secrets and new avenues for the development of therapeutic molecules have emerged. In the present review we focus on the extrinsic mechanisms that control self-renewal, specification and differentiation of satellite cells and their significance for the development of biologic drugs.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".