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Record W2053200073 · doi:10.1002/humu.9376

Lafora progressive myoclonus epilepsy mutation database-EPM2A and NHLRC1 (EMP2B) genes

2005· article· en· W2053200073 on OpenAlexafffund
Leonarda Ianzano, Junjun Zhang, Elayne M. Chan, Xiao-Chu Zhao, Hannes Lohi, Stephen W. Scherer, Berge A. Minassian

Bibliographic record

VenueHuman Mutation · 2005
Typearticle
Languageen
FieldMedicine
TopicGlycogen Storage Diseases and Myoclonus
Canadian institutionsHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsLafora diseaseProgressive myoclonus epilepsyFrameshift mutationMissense mutationBiologyGeneticsMyoclonusNonsense mutationEpilepsyGeneMutationNeurosciencePhosphatase

Abstract

fetched live from OpenAlex

Progressive Myoclonus Epilepsy (PME) of the Lafora type is an autosomal recessive disease, which presents in teenage years with myoclonia and generalized seizures leading to death within a decade of onset. It is characterized by pathognomonic inclusions, Lafora bodies (LB), in neurons and other cell types. Two genes causing Lafora disease (LD), EPM2A on chromosome 6q24 and NHLRC1 (EPM2B) on chromosome 6p22.3 have been identified, and our recent results indicate there is at least one other gene causing the disease. The EPM2A gene product, laforin, is a protein tyrosine phosphatase (PTP) with a carbohydrate-binding domain (CBD) in the N-terminus. NHLRC1 encodes a protein named malin, containing a zinc finger of the RING type in the N-terminal half and 6 NHL-repeat domains in the C-terminal direction. To date 43 different variations in EPM2A and 23 in NHLRC1 are known, including missense, nonsense, frameshift, and deletions. We have developed a human LD mutation database using a new generic biological database cross-referencing platform. The database, which currently contains 66 entries is accessible on the World Wide Web (http://projects.tcag.ca/lafora). Entries can be submitted via the curator of the database or via a web-based form.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score0.737

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)0.0000.000

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 head0.020
GPT teacher head0.310
Teacher spread0.290 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations64
Published2005
Admission routes2
Has abstractyes

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