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Record W2341648636 · doi:10.1097/fpc.0000000000000222

Disposition kinetics and metabolism of nicotine and cotinine in African American smokers

2016· article· en· W2341648636 on OpenAlexaff
Neal L. Benowitz, Gideon St. Helen, Delia Dempsey, Peyton Jacob, Rachel F. Tyndale

Bibliographic record

VenuePharmacogenetics and Genomics · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
FundersNational Center for Research ResourcesNational Institute on Drug Abuse
KeywordsCotinineCYP2A6NicotineMetabolitePharmacokineticsUrineChemistryPharmacologyMetabolismGenotypeExcretionInternal medicineMedicineBiochemistryGene

Abstract

fetched live from OpenAlex

OBJECTIVE: The rate of nicotine metabolism, determined primarily by CYP2A6 activity, influences tobacco dependence and smoking-induced disease risk. The prevalence of CYP2A6 gene variants differs by race, with greater numbers in African Americans compared with Caucasians. We studied nicotine disposition kinetics and metabolism by the CYP2A6 genotype and enzymatic activity, as measured by the nicotine metabolite ratio (NMR), in African American smokers. METHODS: Participants were administered intravenous infusions of deuterium-labeled nicotine and cotinine. Plasma and urine concentrations of nicotine and metabolites were measured and pharmacokinetic parameters were estimated. RESULTS: Pharmacokinetic parameters and urine metabolite excretion data were analyzed by CYP2A6 genotype and by NMR. A number of gene variants were associated with markedly reduced nicotine and cotinine clearances. NMR was strongly correlated with nicotine (r=0.72) and cotinine (r=0.80) clearances. Participants with higher NMR excreted significantly greater nicotine C-oxidation and lower non-C-oxidation products compared with lower NMR participants. CONCLUSION: CYP2A6 genotype, NMR, and nicotine pharmacokinetic data may inform studies of individual differences in smoking behavior and biomarkers of nicotine exposure.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.585

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 head0.007
GPT teacher head0.255
Teacher spread0.249 · 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 designBench or experimental
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

Citations40
Published2016
Admission routes1
Has abstractyes

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