Megf10 regulates the progression of the satellite cell myogenic program
Bibliographic record
Abstract
We identify here the multiple epidermal growth factor repeat transmembrane protein Megf10 as a quiescent satellite cell marker that is also expressed in skeletal myoblasts but not in differentiated myofibers. Retroviral expression of Megf10 in myoblasts results in enhanced proliferation and inhibited differentiation. Infected myoblasts that fail to differentiate undergo cell cycle arrest and can reenter the cell cycle upon serum restimulation. Moreover, experimental modulations of Megf10 alter the expression levels of Pax7 and the myogenic regulatory factors. In contrast, Megf10 silencing in activated satellite cells on individual fibers or in cultured myoblasts results in a dramatic reduction in the cell number, caused by myogenin activation and precocious differentiation as well as a depletion of the self-renewing Pax7+/MyoD- population. Additionally, Megf10 silencing in MyoD-/- myoblasts results in down-regulation of Notch signaling components. We conclude that Megf10 represents a novel transmembrane protein that impinges on Notch signaling to regulate the satellite cell population balance between proliferation and 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) | 0.000 | 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 | 0.000 |
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".