Zfp423 Regulates Skeletal Muscle Regeneration and Proliferation
Bibliographic record
Abstract
Satellite cells (SCs) are skeletal muscle stem cells that proliferate in response to injury and provide myogenic precursors for growth and repair. Zfp423 is a transcriptional cofactor expressed in multiple immature cell populations, such as neuronal precursors, mesenchymal stem cells, and preadipocytes, where it regulates lineage allocation, proliferation, and differentiation. Here, we show that Zfp423 regulates myogenic progression during muscle regeneration. Zfp423 is undetectable in quiescent SCs but becomes expressed during SC activation. After expansion, Zfp423 is gradually downregulated as committed SCs terminally differentiate. Mice with satellite-cell-specific Zfp423 deletion exhibit severely impaired muscle regeneration following injury, with aberrant SC expansion, defective cell cycle exit, and failure to transition efficiently from the proliferative stage toward commitment. Consistent with a cell-autonomous role of Zfp423, shRNA-mediated knockdown of Zfp423 in myoblasts inhibits differentiation. Surprisingly, forced expression of Zfp423 in myoblasts induces differentiation into adipocytes and arrests myogenesis. Affinity purification of Zfp423 in myoblasts identified Satb2 as a nuclear partner of Zfp423 that cooperatively enhances Zfp423 transcriptional activity, which in turn affects myoblast differentiation. In conclusion, by controlling SC expansion and proliferation, Zfp423 is essential for muscle regeneration. Tight regulation of Zfp423 expression is essential for normal progression of muscle progenitors from proliferation to differentiation.
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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) | 0.000 | 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) | 0.001 | 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".