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Record W2990798938 · doi:10.1097/cxa.0000000000000069

Association Study of OPRM1 Gene in a Sample of Schizophrenia Patients With Alcohol Dependence or Abuse

2019· article· en· W2990798938 on OpenAlexaffvenue
Marie Gendy, Clement C. Zai, Bernard Le Foll, James L. Kennedy

Bibliographic record

VenueThe Canadian Journal of Addiction · 2019
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsMental Health Research CanadaCanada Research ChairsUniversity of TorontoOntario Brain InstituteCentre for Addiction and Mental Health
FundersNational Institute on Alcohol Abuse and Alcoholism
KeywordsSingle-nucleotide polymorphismAlcohol dependenceSNPPolymorphism (computer science)MedicineAlleleGeneticsGenotypeAlcoholGeneBiology

Abstract

fetched live from OpenAlex

Alcohol use disorder is a complex disorder that is influenced by genetic factors. The non-synonymous single-nucleotide polymorphism rs1799971 in exon 1 in opioid receptor OPRM1 was extensively studied in patients with alcohol dependence with mixed findings. Moreover, studies showed that opioid receptor polymorphism might play a role in the pathophysiology of schizophrenia. Our results suggest that rs1799971 single-nucleotide polymorphism is not significantly associated with alcohol dependence in our sample of Schizophrenia patients of European ancestry. Le trouble lié à l’alcool est un trouble complexe qui est influencé par des facteurs génétiques. Le polymorphisme mononucléotidique non synonyme (SNP) rs1799971 dans l’exon 1 du récepteur opioïde OPRM1 a fait l’objet d’une étude approfondie chez des patients présentant une dépendance à l’alcool avec des résultats mitigés. De plus, des études ont montré que le polymorphisme des récepteurs opioïdes pourrait jouer un rôle dans la physiopathologie de la schizophrénie. Nos résultats suggèrent que le rs1799971 SNP n’est pas associé de manière significative à la dépendance à l’alcool dans notre échantillon de patients schizophrènes d’ascendance européenne.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.999

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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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 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

Citations1
Published2019
Admission routes2
Has abstractyes

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Same venueThe Canadian Journal of AddictionSame topicSubstance Abuse Treatment and OutcomesFrench-language works237,207