Tumor prevention facilitates delayed transplant of stem cell‐derived motoneurons
Bibliographic record
Abstract
OBJECTIVE: Nerve injuries resulting in prolonged periods of denervation result in poor recovery of motor function. We have previously shown that embryonic stem cell-derived motoneurons transplanted at the time of transection into a peripheral nerve can functionally reinnervate muscle. For clinical relevance, we now focused on delaying transplantation to assess reinnervation after prolonged denervation. METHODS: Embryonic stem cell-derived motoneurons were transplanted into the distal segments of transected tibial nerves in adult mice after prolonged denervation of 1-8 weeks. Twitch and tetanic forces were measured ex vivo 3 months posttransplantation. Tissue was harvested from the transplants for culture and immunohistochemical analysis. RESULTS: In this delayed reinnervation model, teratocarcinomas developed in about one half of transplants. A residual multipotent cell population (~ 6% of cells) was found despite neural differentiation. Exposure to the alkylating drug mitomycin C eliminated this multipotent population in vitro while preserving motoneurons. Treating neural differentiated stem cells prior to delayed transplantation prevented tumor formation and resulted in twitch and tetanic forces similar to those in animals transplanted acutely after denervation. INTERPRETATION: Despite a neural differentiation protocol, embryonic stem cell-derived motoneurons still carry a risk of tumorigenicity. Pretreating with an antimitotic agent leads to survival and functional muscle reinnervation if performed within 4 weeks of denervation in the mouse.
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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) | 0.001 | 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".