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Record W4413007040 · doi:10.1097/wco.0000000000001412

Is amyotrophic lateral sclerosis less severe in mice than in humans?

2025· article· en· W4413007040 on OpenAlexaff
Luc Dupuis, Janice Robertson

Bibliographic record

VenueCurrent Opinion in Neurology · 2025
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsOccupational Cancer Research CentreUniversity of Toronto
Fundersnot available
KeywordsAmyotrophic lateral sclerosisPhenotypeNeuroscienceDiseaseBiologyGeneMutationGeneticsMedicinePathology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: We review here novel knock-in models of amyotrophic lateral sclerosis (ALS). RECENT FINDINGS: Knock-in mouse models of various familial forms of ALS generally display a mild motor phenotype, with limited progression, that do not recapitulate the full-blown clinical picture of ALS. SUMMARY: ALS is a devastating neurodegenerative disease in humans. Typically manifesting in the fifth or sixth decade of life, ALS leads to progressive motor dysfunction and death, usually within 2-5 years from symptom onset. A subset of ALS cases are dominantly inherited. Over the last 30 years, multiple mouse models of ALS have been generated, and recent advances in mouse genome editing techniques have enabled the generation of mouse strains carrying orthologous mutations in endogenous genes that mirror those causing familial forms of ALS. Intriguingly, many of these knock-in mouse models develop much milder phenotypes than patients with ALS carrying the same mutations. A full-blown ALS clinical phenotype seems to be only elicited upon overexpression of mutant genes beyond the endogenous levels. Here, we review these novel models and argue that these models could represent how ALS manifests in the mouse species. We also evaluate how these models could be used for characterizing mechanisms and preclinical drug evaluation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.110
GPT teacher head0.375
Teacher spread0.265 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes1
Has abstractyes

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