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Record W2061209675 · doi:10.2217/14622416.8.10.1385

Genetic Variability in<i>CYP2A6</i>and the Pharmacokinetics of Nicotine

2007· review· en· W2061209675 on OpenAlexafffund
Jill Mwenifumbo, Rachel F. Tyndale

Bibliographic record

VenuePharmacogenomics · 2007
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsCanada Research Chairs
FundersNational Institute on Drug AbuseCanadian Institutes of Health ResearchCentre for Addiction and Mental Health
KeywordsCYP2A6NicotinePharmacokineticsPharmacologyBiologyGeneticsNeuroscience

Abstract

fetched live from OpenAlex

Nicotine is the psychoactive substance responsible for tobacco dependence. It is also a therapeutic used to aid smoking cessation. Cytochrome P450 (CYP)2A6 is the human hepatic enzyme that mediates most of nicotine's metabolic inactivation to cotinine. Genetic variation in the CYP2A6 gene can increase or decrease enzyme activity through altering the protein's expression level or its structure and function. This article reviews CYP2A6 genetic variation and its impact on in vivo nicotine kinetics, including a description of the individual variants, different phenotyping approaches for assessing in vivo CYP2A6 activity and other sources of variation in nicotine metabolism such as gender. In addition, the effect of CYP2A6 polymorphisms on smoking behavior and tobacco-related lung cancer risk are briefly described. Furthering knowledge in this area will improve interpretation of studies examining smoking behavior, as well as those using nicotine as a therapeutic agent.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.004

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 head0.182
GPT teacher head0.484
Teacher spread0.302 · 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 designNot applicable
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

Citations111
Published2007
Admission routes2
Has abstractyes

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