Inhibition of Human Liver Cytochrome P450 by Star Fruit Juice
Bibliographic record
Abstract
PURPOSE: To examine the inhibitory effects of star fruit (Averrhoa carambola) juice towards seven major cytochrome P450 (CYP) isoforms and NADPH-cytochrome P450 reductase (CPR). METHODS: The inhibitory effects of star fruit juice (0.5 to 5%, v/v) against the activities of seven CYP isoforms including CYP1A2, CYP2A6, CYP2C8, CYP2C9, CYP2D6, CYP2E1, CYP3A4 and CPR were examined in human liver microsomes. To identify time-dependent inhibition, star fruit juice (2.5%, v/v) was preincubated with microsomes and a NADPH-generating system for 0-15 min, and then the extent of inhibition towards seven CYP isoforms were examined. RESULTS: Star fruit juice (5.0%, v/v) was found to inhibit all the activities of CYP isoforms tested by more than 70%. Based on the half inhibition values (%, v/v), the inhibitory effects towards different CYP isoforms were in the following order: CYP2A6 (0.9) > CYP1A2 (1.4) > CYP2D6 (1.6) > CYP2E1 (2.0) > CYP2C8 (2.2) > CYP2C9 (3.0) > CYP3A4 (3.2). Time-dependent inhibition was not observed towards any of the tested CYP isoforms. In addition, star fruit juice was found not to inhibit the activity of CPR. CONCLUSIONS: Star fruit juice inhibited the seven CYP isoforms tested, with the strongest inhibitory effect against CYP2A6 and the least towards CYP3A4.
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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) | 0.000 | 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 | 0.000 |
| 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".