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Record W1686747255 · doi:10.1002/mds.25833

A Novel <i>DCTN1</i> mutation with late‐onset parkinsonism and frontotemporal atrophy

2014· article· en· W1686747255 on OpenAlexaff
Eiichi Araki, Yoshio Tsuboi, Justus Daechsel, Austen J. Milnerwood, Carles Vilariño‐Güell, Naoki Fujii, Takayasu Mishima, Takayuki Oka, Hideo Hara, Jiro Fukae, Matthew J. Farrer

Bibliographic record

VenueMovement Disorders · 2014
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsParkinsonismDynactinFrontotemporal dementiaAtrophyNeurodegenerationAmyotrophic lateral sclerosisProbandProgressive supranuclear palsyMutationPathologyNeuroscienceBiologyMedicineGeneticsDiseaseGeneDementiaProtein subunit

Abstract

fetched live from OpenAlex

BACKGROUND: Depression, parkinsonism, and hypoventilation (Perry syndrome) or familial motor neuron disease have been linked to mutations in dynactin P150(Glued) (DCTN1). METHODS: We employed genealogic, clinical, neurologic, and MRI investigations, as well as analysis of genes implicated in parkinsonism. Cellular transfection, immunocytochemistry, and immunoprecipitation analysis of wild-type (WT) and mutant DCTN1 were also performed. RESULTS: A novel heterozygous mutation, DCTN1 c.156T>G, encoding p.Phe52Leu, segregates with parkinsonism in a Japanese family. The substitution was not observed in affected probands with familial parkinsonism or control subjects and is evolutionarily conserved. In contrast to Perry syndrome, affected carriers have late-onset disease and slower progression, with frontotemporal atrophy revealed by MRI. In vitro studies suggest the mutant protein has impaired microtubule binding, compared to WT dynactin p150(Glued) . CONCLUSIONS: DCTN1 mutations may contribute to disparate neurodegenerative diagnoses, including familial motor neuron disease, parkinsonism, and frontotemporal atrophy, and further studies of dynactin-mediated cargo transport may prove insightful.

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 score0.177
Threshold uncertainty score0.683

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 head0.007
GPT teacher head0.216
Teacher spread0.210 · 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

Citations44
Published2014
Admission routes1
Has abstractyes

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