Mutations in SOD1 induce ALS-related phenotypes in 3D iPSC-derived motor neuron (MN) spheroids
Bibliographic record
Abstract
A significant challenge in ALS research is the heterogeneity of the disease. Even mutations within the same gene can lead to different disease prognosis. For instance, in silico protein modeling predicts distinct properties for distinct SOD1 mutations. With this in mind, in this study, we generated and characterized 3D iPSC-derived MN spheroids carrying homozygous knock-in SOD1 mutations (D90A and G93A), as well as a double mutation (D90A/G93A), to evaluate potential synergistic effects. An isogenic control line with the same genetic background was used for phenotypic comparisons with the knock-in variants. Mutant SOD1 MN spheroids exhibited multiple ALS-related phenotypes including altered SOD1 expression, reduced cell viability, downregulation of neurofilament (NF) subunit expression, hypoactivity, and altered burst activity. Our results highlight the advantages of using 3D MN spheroids as a disease model and stress the importance of considering phenotype variability at the genetic level in 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 | 0.001 |
| 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".