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Record W3186499020 · doi:10.1177/2329048x211027438

A Novel <i>De Novo</i> Variant in <i>DYNC1H1</i> Causes Spinal Muscular Atrophy Lower Extremity Predominant in Identical Twins: A Case Report

2021· article· en· W3186499020 on OpenAlex
Alexa Derksen, Amytice Mirchi, Luan T. Tran, Lei Cao-Lei, Maryam Oskoui, Myriam Srour, Chantal Poulin, Geneviève Bernard

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChild Neurology Open · 2021
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersFonds de Recherche du Québec - Santé
KeywordsSpinal muscular atrophyMotor neuronSpinal cordExome sequencingMedicinePhenotypeLower motor neuronWeaknessAtrophyUpper motor neuronAnatomyNeurosciencePathologyBiologyGeneticsAmyotrophic lateral sclerosisGene

Abstract

fetched live from OpenAlex

Mutations in DYNC1H1 have been shown to cause spinal muscular atrophy lower extremity predominant type 1 (SMALED1), an autosomal dominant genetic neuromuscular disorder characterized by degeneration of spinal cord motor neurons resulting in muscle weakness. Here, we describe monozygotic twins, one with a more severe upper motor neuron phenotype as a result of a suspected perinatal hypoxic-ischemic event and the other presenting a typical lower motor neuron phenotype. Using exome sequencing, we identified the novel de novo variant c.752G&gt;T; p.Arg251Leu in DYNC1H1. We thereby add this variant to the growing list of mutations in DYNC1H1 that cause SMALED1.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.027
GPT teacher head0.327
Teacher spread0.300 · 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