Transplantation to study satellite cell heterogeneity in skeletal muscle
Bibliographic record
Abstract
Skeletal muscle has a remarkable capacity to regenerate throughout life, which is mediated by its resident muscle stem cells, also called satellite cells. Satellite cells, located periphery to the muscle fibers and underneath the basal lamina, are an indispensable cellular source for muscle regeneration. Satellite cell transplantation into regenerating muscle contributes robustly to muscle repair, thereby indicating that satellite cells indeed function as adult muscle stem cells. Moreover, satellite cells are a heterogenous population in adult tissue, with subpopulations that can be distinguished based on gene expression, cell-cycle progression, ability to self-renew, and bi-potential ability. Transplantation assays provide a powerful tool to better understand satellite cell function in vivo enabling the separation of functionally distinct satellite cell subpopulations. In this review, we focus on transplantation strategies to explore satellite cells’ functional heterogeneity, approaches targeting the recipient tissue to improve transplantation efficiency, and common strategies to monitor the behaviour of the transplanted cells. Lastly, we discuss some recent approaches to overcome challenges to enhance the transplantation potential of muscle stem cells.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".