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Record W2084299306 · doi:10.1097/nen.0b013e3180515319

Multifocal Atrophy of Cerebellar Internal Granular Neurons in Lesch-Nyhan Disease

2007· review· en· W2084299306 on OpenAlexaff
Marc R. Del Bigio, William Halliday

Bibliographic record

VenueJournal of Neuropathology & Experimental Neurology · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoSickKids FoundationUniversity of Manitoba
Fundersnot available
KeywordsCerebellumGranular layerAtrophyPathologyAbnormalityMedicineBasal gangliaNeuroscienceLesch–Nyhan syndromeCerebrumHypoxanthine-guanine phosphoribosyltransferasePsychologyCentral nervous systemBiology

Abstract

fetched live from OpenAlex

The neuropathologic findings in 31 cases (aged 6 months to 33 years) of Lesch-Nyhan disease (hypoxanthine-guanine phosphoribosyltransferase deficiency) have been previously reported. Herein 2 additional cases, a 10-year-old boy and a 21-year-old man, are described. Both cases had unusual cerebellar abnormalities comprising multifocal internal granular layer atrophy with sparing of the Purkinje layer, one had a slightly small brain, and neither had striatal abnormalities. Careful review of the literature indicates that the most prevalent neuropathologic abnormalities are small cerebrum (13 of 33 cases) and multifocal cerebellar lesions (9 of 33 cases), although these could be underreported. Other authors have disregarded these abnormalities, focusing on the apparently normal basal nuclei, and they have suggested that the clinical neurologic abnormalities are based solely on changes in neurotransmitters. We discuss potential mechanisms of cerebellar damage, suggest that the cerebellar abnormality could in part explain the clinical syndrome, and recommend that cerebellar structure and function should be more carefully studied in Lesch-Nyhan disease.

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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.035
GPT teacher head0.360
Teacher spread0.325 · 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
GenreReview

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

Citations23
Published2007
Admission routes1
Has abstractyes

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