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Record W4390990050 · doi:10.1016/j.stemcr.2023.12.007

Mutations in FUS lead to synaptic dysregulation in ALS-iPSC derived neurons

2024· article· en· W4390990050 on OpenAlexafffund
Carole Shum, Erin C. Hedges, Joseph Allison, Youn‐Bok Lee, Natalia Arias, Graham Cocks, Siddharthan Chandran, Marc‐David Ruepp, Christopher E. Shaw, Agnes L. Nishimura

Bibliographic record

VenueStem Cell Reports · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsHospital for Sick Children
FundersMedical Research CouncilAlzheimer’s Research UKMotor Neurone Disease AssociationAlzheimer's SocietyMedical Research Council CanadaUK Dementia Research InstituteAlzheimer Society
KeywordsBiologyExcitotoxicityAmyotrophic lateral sclerosisNeuroscienceGlutamate receptorSynapseSynaptic plasticitySynaptic vesicleCell biologyGeneticsPathology

Abstract

fetched live from OpenAlex

Amyotrophic lateral sclerosis (ALS) is a fatal, adult-onset neurodegenerative disorder characterized by progressive muscular weakness due to the selective loss of motor neurons. Mutations in the gene Fused in Sarcoma (FUS) were identified as one cause of ALS. Here, we report that mutations in FUS lead to upregulation of synaptic proteins, increasing synaptic activity and abnormal release of vesicles at the synaptic cleft. Consequently, FUS-ALS neurons showed greater vulnerability to glutamate excitotoxicity, which raised neuronal swellings (varicose neurites) and led to neuronal death. Fragile X mental retardation protein (FMRP) is an RNA-binding protein known to regulate synaptic protein translation, and its expression is reduced in the FUS-ALS lines. Collectively, our data suggest that a reduction of FMRP levels alters the synaptic protein dynamics, leading to synaptic dysfunction and glutamate excitotoxicity. Here, we present a mechanistic hypothesis linking dysregulation of peripheral translation with synaptic vulnerability in the pathogenesis of FUS-ALS.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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 designBench or experimental
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

Citations12
Published2024
Admission routes2
Has abstractyes

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