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Differential role of ginkgolide A and bilobalide in CYP3A and CYP2B6 induction by Ginkgo biloba extract in primary cultures of human hepatocytes

2010· article· en· W2290781649 on OpenAlexafffund
Aik Jiang Lau, Ganesh Rajaraman, Christie C. Baucom, Guixiang Yang, Thomas K. H. Chang

Bibliographic record

VenueThe FASEB Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicGinkgo biloba and Cashew Applications
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsGinkgo bilobaCYP3ACYP2B6ChemistryPharmacologyCYP3A4Cytochrome P450BiochemistryEnzymeBiology

Abstract

fetched live from OpenAlex

Ginkgo biloba extract and ginkgolide A induce CYP3A and CYP2B6 in human hepatocytes, but conflicting data exist for the effect of bilobalide on CYP3A expression. Also, it is unknown which chemicals contribute to these effects by the extract. We assessed in human hepatocytes the role of ginkgolide A and bilobalide in the modulation of CYP3A and CYP2B6 expression by G. biloba extract, and compared the effect of the extract and chemicals on these enzymes. As analyzed by HPLC, LC‐MS, and real‐time PCR, control analysis indicated that rifampicin increased CYP3A‐mediated testosterone 6β‐hydroxylation and CYP3A4 mRNA levels, and CITCO increased CYP2B6‐mediated bupropion hydroxylation and CYP2B6 mRNA levels. G. biloba extract (25–200 μg/ml) induced CYP3A to a greater extent than CYP2B6. At a level present in 100 μg/ml of extract, ginkgolide A (1.1 μg/ml) increased CYP3A but not CYP2B6 expression, whereas bilobalide (2.8 μg/ml) had no effect. Ginkgolide A (1.1–10 μg/ml) induced CYP3A to a greater extent than CYP2B6, but bilobalide (5–20 μg/ml) induced both enzymes to a similar extent. CYP3A induction by bilobalide was less than that by ginkgolide A. In summary, G. biloba extract, ginkgolide A, and bilobalide differentially induced CYP3A and CYP2B6. Among the two chemicals, only ginkgolide A contributed to CYP3A induction by the extract, whereas neither of them accounted for CYP2B6 induction. [Supported by CIHR and MSFHR]

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.264
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes2
Has abstractyes

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