Six1 Regulates MyoD Expression in Adult Muscle Progenitor Cells
Bibliographic record
Abstract
Quiescent satellite cells are myogenic progenitors that enable regeneration of skeletal muscle. One of the early events of satellite cell activation following myotrauma is the induction of the myogenic regulatory factor MyoD, which eventually induces terminal differentiation and muscle function gene expression. The purpose of this study was to elucidate the mechanism by which MyoD is induced during activation of satellite cells in mouse muscle undergoing regeneration. We show that Six1, a transcription factor essential for embryonic myogenesis, also regulates MyoD expression in muscle progenitor cells. Six1 knock-down by RNA interference leads to decreased expression of MyoD in myoblasts. Chromatin immunoprecipitation assays reveal that Six1 binds the Core Enhancer Region of MyoD. Further, transcriptional reporter assays demonstrate that Core Enhancer Region reporter gene activity in myoblasts and in regenerating muscle depends on the expression of Six1 and on Six1 binding sites. Finally, we provide evidence indicating that Six1 is required for the proper chromatin structure at the Core Enhancer Region, as well as for MyoD binding at its own enhancer. Together, our results reveal that MyoD expression in satellite cells depends on Six1, supporting the idea that Six1 plays an important role in adult myogenesis, in addition to its role in embryonic muscle formation.
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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) | 0.001 | 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".