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Record W1570616401 · doi:10.18433/j3bw2s

Karanjin interferes with ABCB1, ABCC1, and ABCG2

2014· article· en· W1570616401 on OpenAlexvenueno aff
Martin Michaelis, Florian Rothweiler, Thomas Nerreter, Mohsen Sharifi, Taravat Ghafourian, Jindřich Činátl

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2014
Typearticle
Languageen
FieldMedicine
TopicDrug Transport and Resistance Mechanisms
Canadian institutionsnot available
FundersUniversitätsklinikum Hamburg-EppendorfHilfe für krebskranke Kinder FrankfurtFrankfurter Stiftung für krebskranke Kinder
KeywordsTraditional medicineAbcg2MedicineChemistryATP-binding cassette transporterBiochemistry

Abstract

fetched live from OpenAlex

PURPOSE: The prominent ATP-binding cassette (ABC) transporters ABCB1, ABCC1, and ABCG2 are involved in substance transport across physiological barriers and therefore in drug absorption, distribution, and elimination. They also mediate multi-drug resistance in cancer cells. Different flavonoids are known to interfere with different ABC transporters. Here, the effect of the furanoflavonol karanjin, a potential drug with antiglycaemic, gastroprotective, antifungal, and antibacterial effects, was investigated on ABCB1, ABCC1, and ABCG2-mediated drug transport in comparison to the flavonoids apigenin, genistein, and naringenin. METHODS: Cells expressing the relevant transporters (ABCB1: UKF-NB-3ABCB1, UKF-NB-3rVCR10; ABCC1: G62, PC-3rVCR20; ABCG2: UKF-NB-3ABCG2) were used in combination with specific fluorescent and cytotoxic ABC transporter substrates and ABC transporter inhibitors to study ABC transporter function. Moreover, the effects of the investigated flavonoids were determined on the ABC transporter ATPase activities. RESULTS: Karanjin interfered with drug efflux mediated by ABCB1, ABCC1, and ABCG2 and enhanced the ATPase activity of all three transporters. Moreover, karanjin exerted more pronounced effects than the control flavonoids apigenin, genistein, and naringenin on all three transporters. Most notably, karanjin interfered with ABCB1 at low concentrations being about 1µM. CONCLUSIONS: Taken together, these findings should be taken into account during further consideration of karanjin as a potential drug for different therapeutic indications. The effects on ABCB1, ABCC1, and ABCG2 may affect the pharmacokinetics of co-administered drugs. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.METHODS: Cells expressing the relevant transporters (ABCB1: UKF-NB-3ABCB1, UKF-NB-3rVCR10; ABCC1: G62, PC-3rVCR20; ABCG2: UKF-NB-3ABCG2) were used in combination with specific fluorescent and cytotoxic ABC transporter substrates and ABC transporter inhibitors to study ABC transporter function. Moreover, the effects of the investigated flavonoids were determined on the ABC transporter ATPase activities.RESULTS: Karanjin interfered with drug efflux mediated by ABCB1, ABCC1, and ABCG2 and enhanced the ATPase activity of all three transporters. Moreover, karanjin exerted more pronounced effects than the control flavonoids apigenin, genistein, and naringenin on all three transporters. Most notably, karanjin interfered with ABCB1 at low concentrations being about 1µM.CONCLUSIONS: Taken together, these findings should be taken into account during further consideration of karanjin as a potential drug for different therapeutic indications. The effects on ABCB1, ABCC1, and ABCG2 may affect the pharmacokinetics of co-administered drugs.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.367
Teacher spread0.325 · 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 source (direct Gemma or distilled Codex), 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".

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Citations31
Published2014
Admission routes1
Has abstractyes

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