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Assay for the simultaneous detection of the *1C and *1F alleles of the CYP1A2 gene by real-time polymerase chain reaction and melting curve analysis

2006· article· en· W2087592754 on OpenAlexaff
William L. Casley, Carole A. LeBlanc-Westwood

Bibliographic record

VenuePsychiatric Genetics · 2006
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsStatistics CanadaGovernment of CanadaHealth Canada
Fundersnot available
KeywordsGenotypingCYP1A2AllelePolymerase chain reactionGenotypeMelting curve analysisBiologyPharmacogeneticsGeneticsGenePharmacologyCytochrome P450EnzymeBiochemistry

Abstract

fetched live from OpenAlex

Pharmacogenetic variation is an important factor in the therapeutic outcome of many drug treatments. The cytochrome P450 isoform CYP1A2 is involved in the metabolism of a number of antipsychotic drugs. Variable expression of this enzyme may result in idiosyncratic drug responses, including adverse reactions. A number of DNA sequence polymorphisms have been identified in the CYP1A2 gene. Of these, two alleles, CYP1A2*1C and CYP1A2*1F, have been linked to changes in gene expression among smokers. In addition, these polymorphisms have been linked to susceptibility to tardive dyskinesia in some patient populations receiving antipsychotic drug therapy. Here, we present a rapid and robust method for simultaneously genotyping the CYP1A2*1C and *1F alleles using fluorescent hybridization probes and a widely available real-time polymerase chain reaction platform. Such an assay would offer the opportunity to routinely establish the CYP1A2 genotype of a patient prior to commencing drug therapy.

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)0.006
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.002
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0050.005

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 head0.019
GPT teacher head0.329
Teacher spread0.310 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations3
Published2006
Admission routes1
Has abstractyes

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