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Record W2523971777 · doi:10.1177/2329048x16669912

Further Validation of the <i>SIGMAR1</i> c.151+1G&gt;T Mutation as Cause of Distal Hereditary Motor Neuropathy

2016· article· en· W2523971777 on OpenAlexaff
Jessica J. Y. Lee, Clara van Karnebeek, Britt I. Drögemöller, Casper Shyr, Maja Tarailo‐Graovac, Patrice Eydoux, Colin J.D. Ross, Wyeth W. Wasserman, Bruce Björnson, John K. Wu

Bibliographic record

VenueChild Neurology Open · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPharmacological Receptor Mechanisms and Effects
Canadian institutionsUniversity of British ColumbiaBC Children's HospitalPacific Centre for Reproductive Medicine
Fundersnot available
KeywordsExome sequencingHereditary motor and sensory neuropathyWeaknessMedicineDiseaseGeneticsPhenotypeBiologyGenePathologySurgery

Abstract

fetched live from OpenAlex

Distal hereditary motor neuropathies represent a group of rare genetic disorders characterized by progressive distal motor weakness without sensory loss. Their genetic heterogeneity is high and thus eligible for diagnostic whole exome sequencing. The authors report successful application of whole exome sequencing in diagnosing a second consanguineous family with distal hereditary motor neuropathy due to a homozygous c.151+1G>T variant in SIGMAR1. This variant was recently proposed as causal for the same condition in a consanguineous Chinese family. Compared to this family, the Afghan ethnic origin of our patient is distinct, yet the features are identical, validating the SIGMAR1 deficiency phenotype: progressive muscle wasting/weakness in lower and upper limbs without sensory loss. Rapid disease progression during adolescent growth is similar and may be due to SIGMAR1’s role in regulating axon elongation and tau phosphorylation. Finally, the authors conclude that SIGMAR1 deficiency should be added to the differential diagnosis of distal hereditary motor neuropathies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.252
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2016
Admission routes1
Has abstractyes

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