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Record W2899168417 · doi:10.3389/fnmol.2018.00394

ALS Yeast Models—Past Success Stories and New Opportunities

2018· review· nl· W2899168417 on OpenAlexaff
Sonja E. Di Gregorio, Martin L. Duennwald

Bibliographic record

VenueFrontiers in Molecular Neuroscience · 2018
Typereview
Languagenl
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsWestern University
Fundersnot available
KeywordsYeastAmyotrophic lateral sclerosisDECIPHERModel organismBiologyNeuroscienceComputational biologyProtein aggregationBioinformaticsMedicineCell biologyGeneticsDiseaseGenePathology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.665
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.153
GPT teacher head0.347
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations25
Published2018
Admission routes1
Has abstractyes

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