Nitric oxide‐dependence of satellite stem cell activation and quiescence on normal skeletal muscle fibers
Bibliographic record
Abstract
Satellite cells (quiescent precursors in normal adult skeletal muscle) are activated for growth and regeneration. Signaling by nitric oxide (NO) and hepatocyte growth factor (HGF) during activation has not been examined in a model that can distinguish quiescent from activated satellite cells. We tested the hypothesis that NO and HGF are required to regulate activation using the single-fiber culture model. In normal fibers, HGF and inhibition of NO synthase (NOS) each increased activation without stretching, and NOS inhibition reduced stretch-activation. Activation in unstretched mdx and NOS-I(-/-) fibers was three- to fourfold higher than normal, and was reduced by stretching. Distinctions were not due to different pax7-expressing populations on normal and mdx fibers. The population of c-met-expressing satellite cells on normal fibers was increased by stretch, demonstrating functional heterogeneity among normal satellite cells. Cycloheximide did not prevent the stretch-related increase in c-met expression, suggesting c-met may be an immediate-early gene in satellite cell activation. Results have important implications for designing new therapies that target the role of exercise in health, aging, and disease.
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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".