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Record W2396419952 · doi:10.1007/978-1-60761-700-6_7

Fluorescence Studies of Drug Binding and Translocation by Membrane Transporters

2010· article· en· W2396419952 on OpenAlexaff
Frances J. Sharom, Ronghua Liu, Balpreet Vinepal

Bibliographic record

VenueMethods in molecular biology · 2010
Typearticle
Languageen
FieldMedicine
TopicDrug Transport and Resistance Mechanisms
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsP-glycoproteinATP-binding cassette transporterEffluxTransporterABCC1DrugMultiple drug resistanceChemistryFluorescenceGlycoproteinPharmacologyBiochemistryAbcg2Chromosomal translocationBiologyGene

Abstract

fetched live from OpenAlex

Resistance to multiple drugs is a serious limitation to chemotherapy treatment of human cancers. In addition, many clinically useful drugs show limited uptake in the intestine and cannot gain access to the brain. Three multidrug efflux pumps of the ABC superfamily (P-glycoprotein/ABCB1, MRP1/ABCC1, and BCRP/ABGG2) are responsible for most drug transport out of mammalian cells. P-glycoprotein is the best characterized of the ABC drug transporters. However, the lipophilic nature of its substrates has made it difficult to directly quantitate drug binding to the protein by classical biochemical methods, and the measurement of drug transport rates has also proved challenging. In recent years, fluorescence spectroscopic approaches have proved very useful in overcoming these problems. This chapter focuses on the use of fluorescence tools to quantitate the affinity of binding of various drugs to purified P-glycoprotein and to measure its drug transport activity in reconstituted proteoliposomes in real time. The ability of various drugs to inhibit P-glycoprotein mediated transport can also be assessed using this approach.

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 score0.002
Threshold uncertainty score0.006

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.377
Teacher spread0.358 · 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".

Quick stats

Citations7
Published2010
Admission routes1
Has abstractyes

Explore more

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