Effects of Kava Alkaloid, Pipermethystine, and Kavalactones on Oxidative Stress and Cytochrome P450 in F-344 Rats
Bibliographic record
Abstract
Kava-containing products remain popular in the United States and continue to be sold in health food stores and ethnic markets regardless of the fact that it was banned in Western countries such as Germany, France, Switzerland, Australia, and Canada, following reports of alleged hepatotoxicity. It is therefore critical to establish efficacy and verify adverse effects and/or herb-drug interactions for kava-kava (Piper methysticum). We have previously demonstrated that kava alkaloid, pipermethystine (PM), abundant in leaves and stem peelings, induces mitochondrial toxicity in human hepatoma cells, HepG2, as compared with the bioactive components, kavalactones (KL), abundant in the rhizome. The current study compared short-term toxic effects of PM in Fischer-344 (F-344) rats to acetone-water extracts of kava rhizome (KRE). Treatment of F-344 rats with PM (10 mg/kg) and KRE (100 mg/kg) for 2 weeks failed to elicit any significant changes in liver function tests or cause severe hepatic toxicity as measured by lipid peroxidation and apoptosis markers such as malondialdehyde, Bax, and Bcl-2. However, PM-treated rats demonstrated a significant increase in hepatic glutathione, cytosolic superoxide dismutase (Cu/ZnSOD), tumor necrosis factor alpha mRNA expression, and cytochrome P450 (CYP) 2E1 and 1A2, suggesting adaptation to oxidative stress and possible drug-drug interactions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".