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Record W3112316077 · doi:10.1002/ajmg.a.62011

<scp><i>CHRNB1</i></scp>‐associated congenital myasthenia syndrome: Expanding the clinical spectrum

2020· article· en· W3112316077 on OpenAlexaff
Amanda S. Freed, Anisha C. Schwarz, Brianna K. Brei, Sarah V. Clowes Candadai, Jenny Thies, Jean K. Mah, Shilpi Chabra, Leo Wang, A. Micheil Innes, James T. Bennett

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2020
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersNational Institutes of HealthNational Institute of General Medical SciencesBurroughs Wellcome Fund
KeywordsCongenital myasthenic syndromeExome sequencingGenetic heterogeneityMyasthenia gravisNeuromuscular junctionExonAcetylcholine receptorExomeGeneticsMedicineBiologyMutationBioinformaticsGeneInternal medicineReceptorNeurosciencePhenotype

Abstract

fetched live from OpenAlex

CHRNB1 encodes the β subunit of the acetylcholine receptor (AChR) at the neuromuscular junction. Inherited defects in the neuromuscular junction can lead to congenital myasthenia syndrome (CMS), a clinically and genetically heterogeneous group of disorders which includes fetal akinesia deformation sequence (FADS) on the severe end of the spectrum. Here, we report two unrelated families with biallelic CHRNB1 variants, and in each family, one child presented with lethal FADS. We contrast the diagnostic odysseys in the two families, one of which lasted 16 years while the other, utilizing rapid exome sequencing, led to specific treatment in the first 2 weeks of life. Furthermore, we note that CHRNB1 variants may be under-recognized because in both families, one of the variants is a single exon deletion that has been previously described but may not easily be detected in clinically available genetic testing.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.326
Teacher spread0.292 · 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 designCase report
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

Citations13
Published2020
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Medical Genetics Part ASame topicMyasthenia Gravis and ThymomaFrench-language works237,207