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Record W2014906270 · doi:10.1097/ypg.0b013e3283351221

Association of the orphan nuclear receptor NR4A1 with tardive dyskinesia

2009· article· en· W2014906270 on OpenAlexaff
Gabriela Novak, Alexandra Gallo, Clement C. Zai, Herbert Y. Meltzer, Jeffrey A. Lieberman, Steven G. Potkin, Aristotle N. Voineskos, Gary Remington, James L. Kennedy, Daniel Lévesque, Bernard Le Foll

Bibliographic record

VenuePsychiatric Genetics · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNuclear Receptors and Signaling
Canadian institutionsMuscular Dystrophy CanadaUniversité de MontréalHôpital Louis-H LafontaineCentre for Addiction and Mental Health
Fundersnot available
KeywordsTardive dyskinesiaSingle-nucleotide polymorphismHaplotypeSNPAssociation (psychology)Candidate geneGeneticsMedicineGenetic associationSchizophrenia (object-oriented programming)OncologyGeneBiologyAllelePsychiatryGenotypePsychology

Abstract

fetched live from OpenAlex

Recent evidence has identified the NR4A1 (NUR77, NGFI-B) gene as a strong candidate for involvement in tardive dyskinesia (TD). We have investigated the association of six single nucleotide polymorphisms within the NR4A family of genes with TD in a sample of 171 patients with schizophrenia of Caucasian descent. The NR4A1 single nucleotide polymorphism (SNP) marker rs2603751 showed a nominal association with the risk of TD, as well as with the extent of TD based on the Abnormal Involuntary Movements Scale (AIMS) scores. The haplotype generated by the markers rs2603751 and rs2701124 also showed association with TD and, after adjustment for multiple testing, both the NR4A1 marker rs2603751 and the haplotype continued to show a trend toward association with TD. Although the results of this study are limited by a small sample size, it presents important pilot data and warrants further investigation of the involvement of NR4A1 variants in TD.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0020.000

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 head0.008
GPT teacher head0.207
Teacher spread0.200 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

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