Transplanted Mouse Embryonic Stem-Cell-Derived Motoneurons Form Functional Motor Units and Reduce Muscle Atrophy
Bibliographic record
Abstract
Prolonged muscle denervation resulting from motor neuron (MN) damage leads to atrophy and degeneration of neuromuscular junctions (NMJs), which can impart irreversible damage. In this study, we ask whether transplanted embryonic stem (ES) cells differentiated into MNs can form functional synapses with host muscle, and if so what effects do they have on the muscle. After transplantation into transected tibial nerves of adult mice, ES-cell-derived MNs formed functional synapses with denervated host muscle, which resulted in the ability to produce average tetanic forces of 44% of nonlesioned controls. ES-cell-derived motor units (MUs) had mean force values and ranges similar to control muscles. The number of type I fibers and fatigue resistance of the MUs were increased, and denervation-associated muscle atrophy was significantly reduced. These results demonstrate the capacity for ES-cell-derived MNs not only to incorporate into the adult host tissue, but also to exert changes in the target tissue. By providing the signals normally active during embryonic development and placing the cells in an environment with their target tissue, ES cells differentiate into MNs that give rise to functional MU output which resembles the MU output of endogenous MNs. This suggests that these signals combined with those present in the graft environment, lead to the activation of a program intended to produce a normal range of MU forces.
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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 | 0.000 |
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".