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Record W3033381727 · doi:10.1002/1873-3468.13858

Knockdown of genes involved in axonal transport enhances the toxicity of human neuromuscular disease‐linked MATR3 mutations in <i>Drosophila</i>

2020· article· en· W3033381727 on OpenAlexafffund
Melody Zhao, Ching Serena Kao, Claudia Arndt, David Duc Tran, Woo In Cho, Katarina Maksimovic, Xiao Xiao Chen, Mashiat Khan, Hongxian Zhu, Julia Qiao, Kailong Peng, Jingyao Hong, Jialu Xu, Deanna Kim, Jihye Rachel Kim, Jooyun Lee, Rebekah van Bruggen, Wan Hee Yoon, Jeehye Park

Bibliographic record

VenueFEBS Letters · 2020
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersHospital for Sick ChildrenCanada Research ChairsFondation Brain CanadaALS Society of Canada
KeywordsAmyotrophic lateral sclerosisBiologyGene knockdownMutantGeneticsGenetic screenPhenotypeCell biologyMutationGeneDisease

Abstract

fetched live from OpenAlex

Mutations in the nuclear matrix protein Matrin 3 (MATR3) have been identified in amyotrophic lateral sclerosis and myopathy. To investigate the mechanisms underlying MATR3 mutations in neuromuscular diseases and efficiently screen for modifiers of MATR3 toxicity, we generated transgenic MATR3 flies. Our findings indicate that expression of wild-type or mutant MATR3 in motor neurons reduces climbing ability and lifespan of flies, while their expression in indirect flight muscles (IFM) results in abnormal wing positioning and muscle degeneration. In both motor neurons and IFM, mutant MATR3 expression results in more severe phenotypes than wild-type MATR3, demonstrating that the disease-linked mutations confer pathogenicity. We conducted a targeted candidate screen for modifiers of the MATR3 abnormal wing phenotype and identified multiple enhancers involved in axonal transport. Knockdown of these genes enhanced protein levels and insolubility of mutant MATR3. These results suggest that accumulation of mutant MATR3 contributes to toxicity and implicate axonal transport dysfunction in disease pathogenesis.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.410

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 head0.039
GPT teacher head0.281
Teacher spread0.242 · 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

Citations11
Published2020
Admission routes2
Has abstractyes

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