Human Motor Neurons Generated from Neural Stem Cells Delay Clinical Onset and Prolong Life in ALS Mouse Model
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is the most common adult onset motor neuron disease. The etiology and pathogenic mechanisms of the disease remain unknown, and there is no effective treatment. Here we show that intrathecal transplantation of human motor neurons derived from neural stem cells (NSCs) in spinal cord of the SOD1G93A mouse ALS model delayed disease onset and extended life span of the animals. When HB1.F3.Olig2 (F3.Olig2) cells, stable immortalized human NSCs encoding the human Olig2 gene, were treated with sonic hedgehog (Shh) protein for 5-7 days, the cells expressed motor neuron cell type-specific phenotypes Hb9, Isl-1 and choline acetyltransferase (ChAT). These F3.Olig2-Shh human motor neurons were transplanted intrathecally in L5-L6 spinal cord of SOD1G93A mice, and at 4 weeks post-transplantation, transplanted F3.Olig2-Shh motor neurons expressing the neuronal phenotype markers NF, MAP2, Hb9, and ChAT were found in the ventral horn of the spinal cord. Onset of clinical signs in ALS mice with F3.Olig2-Shh motor neuron implants was delayed for 7 days and life span of animals was significantly extended by 20 days. Our results indicate that this treatment modality of intrathecal transplantation of human motor neurons derived from NSCs might be of value in the treatment of ALS patients without significant adverse effects.
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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) | 0.001 | 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".