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Record W1979352823 · doi:10.1620/tjem.209.263

Niemann-Pick Disease Type C: Cataplexy and Hypocretin in Cerebrospinal Fluid

2006· article· en· W1979352823 on OpenAlexaboutno aff
Katsuyuki Oyama, Tsutomu Takahashi, Yutaka Shoji, Mika Oyamada, Atsuko Noguchi, Hiroaki Tamura, Goro Takada, Takashi Kanbayashi

Bibliographic record

VenueThe Tohoku Journal of Experimental Medicine · 2006
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsnot available
Fundersnot available
KeywordsNPC1Niemann–Pick disease, type CCerebrospinal fluidCataplexyInternal medicineEndocrinologyNiemann–Pick diseaseGlycineMedicineCholesterolChemistryNarcolepsyPharmacologyBiochemistryModafinilAmino acidReceptor

Abstract

fetched live from OpenAlex

Niemann-Pick disease type C (NPC) is an inherited lipid storage disorder, characterized by a defect in intracellular trafficking of exogenous cholesterol that leads to the lysosomal accumulation of unesterified cholesterol. We report a Japanese patient with NPC caused by a homozygous c.2974 G > T mutation of the NPC1 gene, which predicts a glycine (GGG) to tryptophan (TGG) change at codon 992 (designated as p.G992W). This is a well-known NPC1 gene mutation that causes a unique phenotype of NPC, which has been limited to a single Acadian ancestor in Nova Scotia, Canada. Our patient characteristically started presenting with cataplexy at the age of 9 years. Recent studies have shown reduced hypocretin-1 levels in the cerebrospinal fluid (CSF) of narcoleptic patients with cataplexy. In our patient, the level of hypocretin-1 was determined as moderately low, 174 pg/ml (normal, > 200 pg/ml). To date, CSF levels of hypocretin-1 have been determined by using an identical assay method in 7 cases of NPC, including our case. All of the NPC cases with cataplexy demonstrated low levels of CSF hypocretin-1, confirming the association of reduced CSF hypocretin-1 levels with cataplexy in NPC.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.367

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 studies0.0000.001
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 head0.039
GPT teacher head0.326
Teacher spread0.287 · 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 designBench or experimental
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

Citations52
Published2006
Admission routes1
Has abstractyes

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