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Record W2076985436 · doi:10.1073/pnas.130155097

St. John's wort induces hepatic drug metabolism through activation of the pregnane X receptor

2000· article· en· W2076985436 on OpenAlexaboutno aff
Linda B. Moore, Bryan Goodwin, Stacey A. Jones, G. Bruce Wisely, Cosette J. Serabjit‐Singh, Timothy M. Willson, Jon L. Collins, Steven A. Kliewer

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2000
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsHyperforinHypericum perforatumPregnane X receptorCYP3A4HypericumPharmacologyHypericinPregnaneDrug metabolismChemistryCytochrome P450IndinavirNuclear receptorAngelica sinensisDrugMetabolismBiochemistryMedicineTraditional medicineTranscription factorStereochemistryHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

St. John's wort (Hypericum perforatum) is an herbal remedy used widely for the treatment of depression. Recent clinical studies demonstrate that hypericum extracts increase the metabolism of various drugs, including combined oral contraceptives, cyclosporin, and indinavir. In this report, we show that hyperforin, a constituent of St. John's wort with antidepressant activity, is a potent ligand (K(i) = 27 nM) for the pregnane X receptor, an orphan nuclear receptor that regulates expression of the cytochrome P450 (CYP) 3A4 monooxygenase. Treatment of primary human hepatocytes with hypericum extracts or hyperforin results in a marked induction of CYP3A4 expression. Because CYP3A4 is involved in the oxidative metabolism of >50% of all drugs, our findings provide a molecular mechanism for the interaction of St. John's wort with drugs and suggest that hypericum extracts are likely to interact with many more drugs than previously had been realized.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.109
GPT teacher head0.407
Teacher spread0.298 · 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
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

Citations938
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicPharmacogenetics and Drug MetabolismFrench-language works237,207