In Vitro Characterization of Motor Neurons and Purkinje Cells Differentiated from Induced Pluripotent Stem Cells Generated from Patients with Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay
Bibliographic record
Abstract
Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is an early-onset neurodegenerative disease mainly characterized by spasticity in the lower limbs and poor muscle control. The disease is caused by mutations in the SACS gene leading in most cases to a loss of function of the sacsin protein, which is highly expressed in motor neurons and Purkinje cells. To investigate the impact of the mutated sacsin protein in these cells in vitro, induced pluripotent stem cell- (iPSC-) derived motor neurons and iPSC-derived Purkinje cells were generated from three ARSACS patients. Both types of iPSC-derived neurons expressed the characteristic neuronal markers β3-tubulin, neurofilaments M and H, as well as specific markers like Islet-1 for motor neurons, and parvalbumin or calbindin for Purkinje cells. Compared to controls, iPSC-derived mutated SACS neurons expressed lower amounts of sacsin. In addition, characteristic neurofilament aggregates were detected along the neurites of both iPSC-derived neurons. These results indicate that it is possible to recapitulate in vitro, at least in part, the ARSACS pathological signature in vitro using patient-derived motor neurons and Purkinje cells differentiated from iPSCs. Such an in vitro personalized model of the disease could be useful for the screening of new drugs for the treatment of ARSACS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".