Cree antidiabetic plant extracts display mechanism-based inactivation of CYP3A4
Bibliographic record
Abstract
Seventeen Cree antidiabetic medicinal plants were studied to determine their potential to inhibit cytochrome P450 3A4 (CYP3A4) through mechanism-based inactivation (MBI). The ethanolic extracts of the medicinal plants were studied for their inhibition of CYP3A4 using the substrates testosterone and dibenzylfluorescein (DBF) in high pressure liquid chromatography (HPLC) and microtiter fluorometric assays, respectively. Using testosterone as a substrate, extracts of Alnus incana, Sarracenia purpurea, and Lycopodium clavatum were identified as potent CYP3A4 MBIs, while those from Abies balsamea, Picea mariana, Pinus banksiana, Rhododendron tomentosum, Kalmia angustifolia, and Picea glauca were identified as less potent inactivators. Not unexpectedly, the other substrate, DBF, showed a different profile of inhibition. Only A. balsamea was identified as a CYP3A4 MBI using DBF. Abies balsamea displayed both NADPH- and time-dependence of CYP3A4 inhibition using both substrates. Overall, several of the medicinal plants may markedly deplete CYP3A4 through MBI and, consequently, decrease the metabolism of CYP3A4 substrates including numerous medications used by diabetics.
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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 | 0.000 |
| 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 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".