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Record W2416329088 · doi:10.1007/978-1-62703-251-3_8

BRET Approaches to Characterize Dopamine and TAAR1 Receptor Pharmacology and Signaling

2012· article· en· W2416329088 on OpenAlexafffund
Stefano Espinoza, Bernard Masri, Ali Salahpour, Raul R. Gainetdinov

Bibliographic record

VenueMethods in molecular biology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsG protein-coupled receptorDopamineDopamine receptor D2Dopamine receptorReceptorSignal transductionDopamine receptor D3ChemistryNeurosciencePharmacologyBiologyCell biologyBiochemistry

Abstract

fetched live from OpenAlex

It is evident that G protein-coupled receptors (GPCRs) such as D2 dopamine receptor and functionally related Trace Amine Associated Receptor 1 (TAAR1) can engage both in G protein-dependent (e.g., cAMP-mediated) and -independent β-arrestin-mediated signaling modalities. Both of these signaling events can be monitored in real-time and in live cells by using new biosensors based on a Bioluminescence Resonance Energy Transfer (BRET) approach. Here we discuss the practical applications of BRET to analyze dynamics of cAMP modulation via an EPAC biosensor as well as recruitment of β-arrestin2 to the D2 dopamine receptor. Combination of these approaches allows for a comparison of activity of pharmacological compounds on these signaling modalities as demonstrated for various antipsychotics as regard to D2 dopamine receptor. Furthermore, analysis of cAMP concentrations in cells expressing TAAR1 provides a simple high-throughput screening method to identify new ligands for this receptor. These BRET approaches could be applied for the characterization of pharmacology and signaling of variety of other GPCRs.

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)0.002
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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.183
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.065
GPT teacher head0.351
Teacher spread0.287 · 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
GenreMethods

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

Citations25
Published2012
Admission routes2
Has abstractyes

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