Notch signaling deficiency underlies age-dependent depletion of satellite cells in muscular dystrophy
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Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is a devastating disease characterized by muscle wasting, loss of mobility and death in early adulthood. Satellite cells are muscle-resident stem cells responsible for the repair and regeneration of damaged muscles. One pathological feature of DMD is the progressive depletion of satellite cells, leading to the failure of muscle repair. Here, we attempted to explore the molecular mechanisms underlying satellite cell ablation in the dystrophin mutant mdx mouse, a well-established model for DMD. Initial muscle degeneration activates satellite cells, resulting in increased satellite cell number in young mdx mice. This is followed by rapid loss of satellite cells with age due to the reduced self-renewal ability of mdx satellite cells. In addition, satellite cell composition is altered even in young mdx mice, with significant reductions in the abundance of non-committed (Pax7+ and Myf5-) satellite cells. Using a Notch-reporter mouse, we found that the mdx satellite cells have reduced activation of Notch signaling, which has been shown to be necessary to maintain satellite cell quiescence and self-renewal. Concomitantly, the expression of Notch1, Notch3, Jag1, Hey1 and HeyL are reduced in the mdx primary myoblast. Finally, we established a mouse model to constitutively activate Notch signaling in satellite cells, and show that Notch activation is sufficient to rescue the self-renewal deficiencies of mdx satellite cells. These results demonstrate that Notch signaling is essential for maintaining the satellite cell pool and that its deficiency leads to depletion of satellite cells in DMD.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it