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Record W2949920898 · doi:10.1055/s-0039-1684994

Update on inherited neuromuscular transmission disorders (congenital myasthenic syndromes)

2019· article· en· W2949920898 on OpenAlexaff
Hanns Lochmüller

Bibliographic record

VenueNervenheilkunde · 2019
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsNeuromuscular transmissionMyasthenia gravisNeuromuscular junctionMedicineCongenital myasthenic syndromeWeaknessArthrogryposisBioinformaticsPhysical medicine and rehabilitationNeuroscienceBiologyAnatomyInternal medicineAcetylcholine receptor

Abstract

fetched live from OpenAlex

Neuromuscular junction disorders are a heterogeneous group of acquired (Myasthenia Gravis, MG) and inherited (Congenital Myasthenic Syndromes, CMS) disorders associated with distinctive clinical, electrophysiological, laboratory and ultrastructural abnormalities. The genetic defects in CMS either impair neuromuscular transmission directly or result in secondary impairments, which eventually compromise the safety margin of neuromuscular transmission. More recently, we have identified two genes (DOK7, GFPT1) that cause fatigable weakness of muscles in a limb-girdle distribution, but rarely affecting facial or eye muscles. Next-generation sequencing and deep phenotyping, in combination with international data sharing, reveals new genetic causes of CMS, but also unusual, overlapping clinical phenotypes which blur the boundaries with primary myopathies and motor neuropathies. Patients with biallelic variants in MUSK have rarely been described so far. Through international collaborative efforts we identified several patients with MuSK-CMS showing salbutamol-responsive muscle weakness in a limb girdle distribution. This highlights the importance of sharing genomics data for diagnosis and research through a secure platform such as RD-Connect. We will cover the significant progress made in understanding the molecular pathogenesis of CMS, which is important for both patients and clinicians in terms of reaching a definite diagnosis and selecting the most appropriate treatment.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score1.000

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)0.0030.002

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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations0
Published2019
Admission routes1
Has abstractyes

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