ALS Yeast Models—Past Success Stories and New Opportunities
Bibliographic record
Abstract
In the past two decades, yeast models have delivered profound insights into basic mechanisms of protein misfolding and the dysfunction of key cellular pathways associated with amyotrophic lateral sclerosis (ALS). Expressing ALS-associated proteins, such as superoxide dismutase (SOD1), TAR DNA binding protein 43 (TDP-43) and Fused in sarcoma (FUS), in yeast recapitulates major hallmarks of ALS pathology, including protein aggregation, mislocalization and cellular toxicity. Results from yeast have consistently been recapitulated in other model systems and even specimens from human patients, thus providing evidence for the power and validity of ALS yeast models. Focusing on impaired ribonucleic acid (RNA) metabolism and protein misfolding and their cytotoxic consequences in ALS, we summarize exemplary discoveries that originated from work in yeast. We also propose previously unexplored experimental strategies to modernize ALS yeast models, which will help to decipher the basic pathomechanisms underlying ALS and thus, possibly contribute to finding a cure.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".