The Effects of Commercial Preparations of Herbal Supplements Commonly Used by Women on the Biotransformation of Fluorogenic Substrates by Human Cytochromes P450
Bibliographic record
Abstract
The study set out to determine the potential for commercially available preparations of black cohosh (Actaea racemosa), chaste tree berry (Vitex agnus-castus), crampbark (Viburnum opulus) and false unicorn (Chamaelirium luteum) to inhibit the major human drug metabolizing enzymes CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4 as well as CYP1A1 which activates some carcinogens. In vitro microplate-based assays using cDNA-expressed CYP450 isoforms and fluorogenic substrates were used. Components of the commercial herbal preparations interfered with the assays and limited the concentration ranges that could be tested. Nevertheless, the fluorogenic assays were robust, reproducible and easy to perform and thus are still useful for initial screening for potential herb-drug interactions. None of the preparations affected CYPs 1A1 or 2C9 at the concentrations tested but all preparations inhibited some of the enzymes with potencies around 1 μg/mL. The three most potent interactions were: chaste tree berry and CYP2C19 (IC₅₀) 0.22 μg/mL); chaste tree berry and CYP3A4 (IC₅₀) 0.3 μg/mL); black cohosh and CYP2C19 (IC₅₀) 0.37 μg/mL,). Thus, the study successfully identified the potential for the commercial herbal preparations to inhibit human drug metabolizing enzymes. Whether this potential translates into clinically significant herb-drug interactions can only be confirmed by appropriate in vivo studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".