Differential activation of rat and human pregnane X receptor by terpene trilactones
Bibliographic record
Abstract
Pregnane X receptor regulates the expression of genes (e.g. CYP3A ) involved in various biological functions. Among the terpene trilactones, ginkgolide A induces CYP3A in rat and human hepatocytes, but conflicting data exist for bilobalide. We compared the effect of five individual terpene trilactones on rat PXR (rPXR) and human PXR (hPXR) activity. As assessed by a luciferase reporter gene assay in rPXR‐ or hPXR‐transfected human hepatoma cells (HepG2), control analysis showed that pregnenolone 16α‐carbonitrile activated rPXR with an EC 50 of 1.0 ± 0.2 μM (mean ± S.E.M., n = 4) and E max of 17 ± 2 fold, whereas rifampicin activated hPXR with an EC 50 of 0.4 ± 0.1 μM and E max of 12 ± 2 fold. Ginkgolide A (30–100 μM) activated rPXR (7–8 fold; E max = 9 ± 1 fold) to a lesser extent than hPXR (9–11 fold; E max = 12 ± 1 fold), and the EC 50 values were 12 ± 1 and 16 ± 1 μM for rPXR and hPXR activation, respectively. The increase in rPXR activity (2–8 fold) by ginkgolide B (3–100 μM) was less than that of hPXR (3–15 fold). Ginkgolide C (60–100 μM) activated rPXR to a somewhat lesser extent than hPXR, but ginkgolide J and bilobalide had no effect. In summary, several of the ginkgolides activated rPXR and hPXR differentially. Ginkgolide A and ginkgolide B were stronger activators than ginkgolide C, ginkgolide J, and bilobalide, suggesting a relationship between the structure of terpene trilactones and activation of rPXR and hPXR. [Supported by CIHR and MSFHR]
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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) | 0.003 | 0.001 |
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".