Wnt/β-catenin controls follistatin signalling to regulate satellite cell myogenic potential
Bibliographic record
Abstract
BACKGROUND: Adult skeletal muscle regeneration is a highly orchestrated process involving the activation and proliferation of satellite cells, an adult skeletal muscle stem cell. Activated satellite cells generate a transient amplifying progenitor pool of myoblasts that commit to differentiation and fuse into multinucleated myotubes. During regeneration, canonical Wnt signalling is activated and has been implicated in regulating myogenic lineage progression and terminal differentiation. METHODS: Here, we have undertaken a gene expression analysis of committed satellite cell-derived myoblasts to examine their ability to respond to canonical Wnt/β-catenin signalling. RESULTS: We found that activation of canonical Wnt signalling induces follistatin expression in myoblasts and promotes myoblast fusion in a follistatin-dependent manner. In growth conditions, canonical Wnt/β-catenin signalling prime myoblasts for myogenic differentiation by stimulating myogenin and follistatin expression. We further found that myogenin binds elements in the follistatin promoter and thus acts downstream of myogenin during differentiation. Finally, ectopic activation of canonical Wnt signalling in vivo promoted premature differentiation during muscle regeneration following acute injury. CONCLUSIONS: Together, these data reveal a novel mechanism by which myogenin mediates the canonical Wnt/β-catenin-dependent activation of follistatin and induction of the myogenic differentiation process.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".