Effect of Oregon grape root extracts on P-glycoprotein mediated transport in in vitro cell lines
Bibliographic record
Abstract
Purpose: This study aims to investigate the potential of Oregon grape root extracts to modulate the activity of P-glycoprotein. Methods: We performed 3H-CsA or 3H-digoxin transport experiments in the absence or presence of two sources of Oregon grape root extracts (E1 and E2), berberine or berbamine in Caco-2 and MDCKII-MDR1 cells. In addition, real time quantitative polymerase chain reaction (RT-PCR) was performed in Caco-2 and LS-180 cells to investigate the mechanism of modulating P-glycoprotein. Results: Our results showed that in Caco-2 cells, Oregon grape root extracts (E1 and E2) (0.1–1 mg/mL) inhibited the efflux of CsA and digoxin in a dose-dependent manner. However, 0.05 mg/mL E1 significantly increased the absorption of digoxin. Ten µM berberine and 30 µM berbamine significantly reduced the efflux of CsA, while no measurable effect of berberine was observed with digoxin. In the MDCKII-MDR1 cells, 10 µM berberine and 30 µM berbamine inhibited the efflux of CsA and digoxin. Lastly, in real time RT-PCR study, Oregon grape root extract (0.1 mg/mL) up-regulated mRNA levels of human MDR1 in Caco-2 and LS-180 cells at 24 h. Conclusion: Our study showed that Oregon grape root extracts modulated P-glycoprotein, thereby may affect the bioavailability of drugs that are substrates of P-glycoprotein.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".