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Record W2097963973 · doi:10.1093/brain/awv082

Mutation analysis of<i>CHCHD10</i>in different neurodegenerative diseases

2015· letter· en· W2097963973 on OpenAlexafffund
Ming Zhang, Zhengrui Xi, Lorne Zinman, Amalia C. Bruni, Raffaele Maletta, Sabrina A.M. Curcio, Innocenzo Rainero, Elisa Rubino, Lorenzo Pinessi, Benedetta Nacmias, Sandro Sorbi, Daniela Galimberti, Anthony E. Lang, Susan H. Fox, Ezequiel Surace, Mahdi Ghani, Jing Guo, Christine Sato, Danielle Moreno, Yan Liang, Julia Keith, Bryan J. Traynor, Peter St George‐Hyslop, Ekaterina Rogaeva

Bibliographic record

VenueBrain · 2015
Typeletter
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersMedical Research CouncilCanadian Institutes of Health ResearchW. Garfield Weston FoundationAlzheimer SocietyWellcome Trust
KeywordsNeuroscienceMutationMedicineGeneticsComputational biologyBiologyGene

Abstract

fetched live from OpenAlex

A recent study by Bannwarth et al. (2014) implicated CHCHD10 as a novel gene for amyotrophic lateral sclerosis/frontotemporal lobar degeneration (ALS/FTLD), reporting a p.S59L substitution (c.176C &gt; T; NM_213720.2) in a large French kindred. Affected family members were presented with a complex phenotype that included symptoms of amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTLD), cerebellar ataxia, Parkinson's disease and a mitochondrial myopathy associated with multiple mitochondrial DNA deletions. So far, seven missense CHCHD10 mutations have been reported in patients with a broad phenotypic range, including ALS/FTLD (p.S59L and p.P34S) (Bannwarth et al., 2014; Chaussenot et al., 2014), ALS (p.R15L and p.G66V) (Johnson et al., 2014; Muller et al., 2014), myopathy (p.R15S and p.G58R) (Ajroud-Driss et al., 2015) and late-onset spinal motor neuronopathy (p.G66V) (Penttila et al., 2015). All of them affect exon 2 (a mutational hotspot of CHCHD10).

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.919
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.044
GPT teacher head0.324
Teacher spread0.280 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations125
Published2015
Admission routes2
Has abstractyes

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