Myogenic specification of side population cells in skeletal muscle
Bibliographic record
Abstract
Skeletal muscle contains myogenic progenitors called satellite cells and muscle-derived stem cells that have been suggested to be pluripotent. We further investigated the differentiation potential of muscle-derived stem cells and satellite cells to elucidate relationships between these two populations of cells. FACS(R) analysis of muscle side population (SP) cells, a fraction of muscle-derived stem cells, revealed expression of hematopoietic stem cell marker Sca-1 but did not reveal expression of any satellite cell markers. Muscle SP cells were greatly enriched for cells competent to form hematopoietic colonies. Moreover, muscle SP cells with hematopoietic potential were CD45 positive. However, muscle SP cells did not differentiate into myocytes in vitro. By contrast, satellite cells gave rise to myocytes but did not express Sca-1 or CD45 and never formed hematopoietic colonies. Importantly, muscle SP cells exhibited the potential to give rise to both myocytes and satellite cells after intramuscular transplantation. In addition, muscle SP cells underwent myogenic specification after co-culture with myoblasts. Co-culture with myoblasts or forced expression of MyoD also induced muscle differentiation of muscle SP cells prepared from mice lacking Pax7 gene, an essential gene for satellite cell development. Therefore, these data document that satellite cells and muscle-derived stem cells represent distinct populations and demonstrate that muscle-derived stem cells have the potential to give rise to myogenic cells via a myocyte-mediated inductive interaction.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".