The Interaction of Selected Phytochemicals, HIV Drugs, and Commercial-Source Herbal Teas and Capsules with Human Cytochrome P450 3A4 and P-glycoprotein
Bibliographic record
Abstract
As the popularity of natural health product (NHP) use increases, unfortunately, so does the frequency of cases reporting suspected adverse interactions. Adverse reactions associated with concomitant NHP-therapeutic use may result from competing interactions at the level of the key xenobiotic-biotransforming phase I enzyme cytochrome P450 3A4 (CYP3A4) or the membrane-bound ATP-dependent protein pump P-glycoprotein (P-gp). In this study, selected NHPs of interest to the HIV+ community were assessed for their ability to affect these two important mechanisms of drug disposition. Briefly, commercial-source teas and powdered extracts in capsule formulations were examined for their ability to inhibit CYP3A4-mediated metabolism of the coadministered reference substrate dibenzyl-fluorescein, and their ability to stimulate P-gp ATPase activity. Among the herbal capsules, it was found that aqueous extracts of two different goldenseal (Hydrastis canadensis. L.) products were the most inhibitory of CYP3A4-mediated metabolism among all NHPs tested (IC50: 3.03 and 3.23 mg/mL). Goldenseal and milk thistle [Silybum marianum. (L.) Gaertn.] teas were found to stimulate P-gp ATPase to a greater degree than the reference positive control verapamil (20 μ M). As well, 70% ethanol extracts of one goldenseal product (designated NRP 121) and aqueous extracts of another (designated NRP 17) had the highest relative P-gp ATPase activity overall. Milk thistle and goldenseal products were further analyzed for levels of their marker constituents by HPLC; silibinin and berberine in the experimental design were found to be at biologically relevant concentrations. High-throughput in vitro. studies such as the CYP3A4 inhibition and P-pg ATPase screening assays may help to determine which NHPs interact with drug disposition mechanisms, thus ensuring that the occurrence of adverse events due to competing interactions is minimized. They are useful for selecting specific NHPs, NHP formulations, phytochemicals, or drugs to be advanced to more detailed in vivo. experimental designs. Although the extrapolation of the current in vitro. findings to clinical effects may well be considered speculative, the overall in vitro. data should still be viewed as a signal of potential in vivo. interactions.
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 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 | 0.000 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".