The Influence of St. John's Wort on CYP2C19 Activity with Respect to Genotype
Bibliographic record
Abstract
Induction of cytochrome p450 isozymes is the major cause for clinical drug interactions of St. John's wort. The relationships of St. John's wort to cytochrome p450 isoforms have been fully investigated, but its effect on CYP2C19 is lacking. Thus, the aim of the present study was to observe the effect of St. John's wort on CYP2C19 activity using CYP1A2 as a control. Twelve healthy adult men-6 extensive metabolizers of CYP2C19 (2C19(*)1/2C19(*)1) and 6 poor metabolizers (4 2C19(*)2/2C19(*)2 and 2 2C19(*)2/2C19(*)3)-were enrolled in a two-phase, randomized, crossover manner. All subjects took a 300-mg St. John's wort tablet or placebo three times daily for 14 days, and then the activities of CYP2C19 and CYP1A2 were measured using mephenytoin and caffeine. It was found that St. John's wort treatment significantly increased CYP2C19 activity in CYP2C19 wild-genotype subjects, with urinary 4'-hydroxymephenytoin excretion raised by 151.5% +/- 91.9% (p = 0.0156), whereas no significant alteration was observed for CYP2C19 poor metabolizers. Repeated St. John's wort administration did not affect the CYP1A2 phenotypic ratio for both CYP2C19 genotype subjects. In conclusion, St. John's wort is an inducer to the human CYP2C19, and clinicians should pay great attention when St. John's wort is added to or withdrawn from an existing drug regimen containing substrates for such enzymes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".