Analysis of human satellite cell dynamics on cultured adult skeletal muscle myofibers
Bibliographic record
Abstract
BACKGROUND: Maintaining stem cells in physiologically relevant states is necessary to understand cell and context-specific signalling paradigms and to understand complex interfaces between cells in situ. Understanding human stem cell function is largely based on tissue biopsies, cell culture, and transplantation into model organisms. METHODS: Here, we describe a method to isolate post-mortem intact human muscle myofibers and culture muscle stem cells within the niche microenvironment to assay cellular dynamics, stem cell identity, stem cell hierarchy, and differentiation potential. RESULTS: We show human myofiber culture maintains complex cell-cell contacts and extracellular niche composition during culture. Human satellite cells can be cultured at least 8 days, which represents a timepoint of activation, differentiation, and de novo human myofiber formation. We demonstrate that adult human muscle stem cells undergo apicobasal and planar cell divisions and express polarized dystrophin and EGFR. Furthermore, we validate that stimulation of the EGFR pathway stimulates the generation of myogenic progenitors and myogenic differentiation. CONCLUSIONS: This method provides proof of principle evidence for the use of human muscle to evaluate satellite cell dynamics and has applications in pre-clinical evaluation of therapeutics targeting muscle repair.
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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) | 0.002 | 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".