The Molecular Regulation of Muscle Stem Cell Function
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Muscle satellite cells are responsible for the postnatal growth and robust regeneration capacity of adult skeletal muscle. A subset of satellite cells purified from adult skeletal muscle is capable of repopulating the satellite cell pool, suggesting that it has direct therapeutic potential for treating degenerative muscle disease. Satellite cells uniformly express the transcription factor Pax7, and Pax7 is required for satellite cell viability and to give rise to myogenic precursors that express the basic helix-loop-helic (bHLH) transcription factors Myf5 and MyoD. Pax7 activates expression of target genes such as Myf5 and MyoD through recruitment of the Wdr5/Ash2L/MLL2 histone methyltransferase complex. Extensive genetic analysis has revealed that Myf5 and MyoD are required for myogenic determination, whereas myogenin and MRF4 have roles in terminal differentiation. Using a Myf5-Cre knockin allele and an R26R-YFP Cre reporter, we observed that in vivo about 10% of satellite cells only express Pax7 and have never expressed Myf5. Moreover, we found that Pax7(+)/Myf5(-) satellite cells give rise to Pax7(+)/Myf5(+) satellite cells through basal-apical asymmetric cell divisions. Therefore, satellite cells in skeletal muscle are a heterogeneous population composed of satellite stem cells (Pax7(+)/Myf5(-)) and satellite myogenic cells (Pax7(+)/Myf5(+)). Evidence is accumulating that indicates that satellite stem cells represent a true stem cell reservoir, and targeting mechanisms that regulate their function represents an important therapeutic strategy for the treatment of neuromuscular disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 | 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