Intramuscular Transplantation of Human Postnatal Myoblasts Generates Functional Donor-Derived Satellite Cells
Bibliographic record
Abstract
Myogenic cell transplantation is an experimental approach for the treatment of myopathies. In this approach, transplanted cells need to fuse with pre-existing myofibers, form new myofibers, and generate new muscle precursor cells (MPCs). The last property was fully reported following myoblast transplantation in mice but remains poorly studied with human myoblasts. In this study, we provide evidence that the intramuscular transplantation of postnatal human myoblasts in immunodeficient mice generates donor-derived MPCs and specifically donor-derived satellite cells. In a first experiment, cells isolated from mouse muscles 1 month after the transplantation of human myoblasts proliferated in vitro as human myoblasts. These cells were retransplanted in mice and formed myofibers expressing human dystrophin. In a second experiment, we observed that inducing muscle regeneration 2 months following transplantation of human myoblasts led to myofiber regeneration by human-derived MPCs. In a third experiment, we detected by immunohistochemistry abundant human-derived satellite cells in mouse muscles 1 month after transplantation of postnatal human myoblasts. These human-derived satellite cells may correspond totally or partially to the human-derived MPCs evidenced in the first two experiments. Finally, we present evidence that donor-derived satellite cells may be produced in patients that received myoblast transplantation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".