Modeling ALS with Patient-Derived iPSCs: Recent Advances and Future Potentials
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is a terminal complex neurodegenerative disease, with 10–15% of cases being familial and the majority being sporadic with no known cause. There are no animal models for the 85–90% of sporadic ALS cases. More creative, sophisticated models of ALS disease are required to unravel the mysteries of this complicated disease. While ALS patients urgently require new medications and treatments, suitable preclinical in vitro models for drug screening are lacking. Therefore, human-derived induced pluripotent stem cell (hiPSC) technology offers the opportunity to model diverse and unreachable cell types in a culture dish. In this review, we focus on recent hiPSC-derived ALS neuronal and non-neuronal models to examine the research progress of current ALS 2D monocultures, co-cultures, and more complex 3D-model organoids. Despite the challenges inherent to hiPSC-based models, their application to preclinical drug studies is enormous.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".