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Record W2996462599 · doi:10.1111/dmcn.14428

<i><scp>BRAT</scp>1</i> encephalopathy: a recessive cause of epilepsy of infancy with migrating focal seizures

2019· article· en· W2996462599 on OpenAlexaff
Ingrid E. Scheffer, Katja Boysen, Amy Schneider, Candace T. Myers, Michele G. Mehaffey, Anne Rochtus, Yuet‐Ping Yuen, Gabriel M. Ronen, Wai Km Chak, Deepak Gill, Annapurna Poduri, Heather C. Mefford

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEpilepsyMicrocephalyEncephalopathyHypertoniaEtiologyMedicinePediatricsPsychologyNeurosciencePathologyInternal medicine

Abstract

fetched live from OpenAlex

Epilepsy of infancy with migrating focal seizures (EIMFS), one of the most severe developmental and epileptic encephalopathy syndromes, is characterized by seizures that migrate from one hemisphere to the other. EIMFS is genetically heterogeneous with 33 genes. We report five patients with EIMFS caused by recessive BRAT1 variants, identified via next generation sequencing. Recessive pathogenic variants in BRAT1 cause the rigidity and multifocal seizure syndrome, lethal neonatal with hypertonia, microcephaly, and intractable multifocal seizures. The epileptology of BRAT1 encephalopathy has not been well described. All five patients were profoundly impaired with seizure onset in the first week of life and focal seizure migration between hemispheres. We show that BRAT1 is an important recessive cause of EIMFS with onset in the first week of life, profound impairment, and early death. Early recognition of this genetic aetiology will inform management and reproductive counselling.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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

Citations22
Published2019
Admission routes1
Has abstractyes

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