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Record W2008423993 · doi:10.1177/0091270003261078

Effects of St. John's Wort (<i>Hypericum perforatum</i>) on Tacrolimus Pharmacokinetics in Healthy Volunteers

2003· article· en· W2008423993 on OpenAlexaboutno aff
Mary F. Hébert, Jeong Mi Park, Yu‐Luan Chen, Shahzad Akhtar, Anne M. Larson

Bibliographic record

VenueThe Journal of Clinical Pharmacology · 2003
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsnot available
FundersNational Center for Research Resources
KeywordsPharmacokineticsHypericum perforatumTacrolimusPharmacologyCYP3AVolume of distributionMedicinePharmacokinetic interactionOral administrationDosingDrug interactionChemistryTransplantationMetabolismInternal medicineCytochrome P450

Abstract

fetched live from OpenAlex

Tacrolimus is an immunosuppressant approved for the prevention of rejection following transplantation and is a substrate for CYP3A and P-glycoprotein. A pharmacokinetic interaction between St. John's wort (antidepressant herbal product and inducer of CYP3A and P-glycoprotein) and tacrolimus was evaluated in 10 healthy volunteers. The pharmacokinetics of tacrolimus were obtained from serial blood samples collected following single oral doses (0.1 mg/kg) prior to and during an 18-day concomitant St. John's wort dosing phase (300 mg orally three times daily). Coadministration of St. John's wort significantly decreased tacrolimus AUC (306.9 microg.h/L +/- 175.8 microg.h/L vs. 198.7 microg.h/L +/- 139.6 microg.h/L; p=0.004) and increased apparent oral clearance (349.0 mL/h/kg +/- 126.0 mL/h/kg vs. 586.4 mL/h/kg +/- 274.9 mL/h/kg; p=0.01) and apparent oral volume of distribution at steady state (11.5 L/kg +/- 4.3 L/kg vs. 17.6 L/kg +/- 9.6 L/kg; p=0.04). St. John's wort appears to induce tacrolimus metabolism, most likely through induction of CYP3A and P-glycoprotein.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.100
GPT teacher head0.486
Teacher spread0.386 · 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 designNon-randomized trial
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

Citations113
Published2003
Admission routes1
Has abstractyes

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