Motoneurons Derived from Induced Pluripotent Stem Cells Develop Mature Phenotypes Typical of Endogenous Spinal Motoneurons
Bibliographic record
Abstract
Induced pluripotent cell-derived motoneurons (iPSCMNs) are sought for use in cell replacement therapies and treatment strategies for motoneuron diseases such as amyotrophic lateral sclerosis (ALS). However, much remains unknown about the physiological properties of iPSCMNs and how they compare with endogenous spinal motoneurons or embryonic stem cell-derived motoneurons (ESCMNs). In the present study, we first used a proteomic approach and compared protein expression profiles between iPSCMNs and ESCMNs to show that <4% of the proteins identified were differentially regulated. Like ESCs, we found that mouse iPSCs treated with retinoic acid and a smoothened agonist differentiated into motoneurons expressing the LIM homeodomain protein Lhx3. When transplanted into the neural tube of developing chick embryos, iPSCMNs selectively targeted muscles normally innervated by Lhx3 motoneurons. In vitro studies showed that iPSCMNs form anatomically mature and functional neuromuscular junctions (NMJs) when cocultured with chick myofibers for several weeks. Electrophysiologically, iPSCMNs developed passive membrane and firing characteristic typical of postnatal motoneurons after several weeks in culture. Finally, iPSCMNs grafted into transected mouse tibial nerve projected axons to denervated gastrocnemius muscle fibers, where they formed functional NMJs, restored contractile force. and attenuated denervation atrophy. Together, iPSCMNs possess many of the same cellular and physiological characteristics as ESCMNs and endogenous spinal motoneurons. These results further justify using iPSCMNs as a source of motoneurons for cell replacement therapies and to study motoneuron diseases such as ALS.
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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) | 0.001 | 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".