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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.001
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 score0.272
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
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