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Record W2041138404 · doi:10.1074/jbc.m205767200

Quantitative Assessment of β1- and β2-Adrenergic Receptor Homo- and Heterodimerization by Bioluminescence Resonance Energy Transfer

2002· article· en· W2041138404 on OpenAlexafffund
Jean‐François Mercier, Ali Salahpour, Stéphane Angers, Andreas Breit, Michel Bouvier

Bibliographic record

VenueJournal of Biological Chemistry · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicbioluminescence and chemiluminescence research
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsBioluminescenceEnergy transferResonance (particle physics)Förster resonance energy transferAdrenergic receptorReceptorBiophysicsChemistryBiologyPhysicsBiochemistryAtomic physicsFluorescence

Abstract

fetched live from OpenAlex

Quantitative bioluminescence resonance energy transfer (BRET) analysis was applied to the study of beta(1)- and beta(2)-adrenergic receptor homo- and heterodimerization. To assess the relative affinity between each of the protomers, BRET saturation experiments were carried out in HEK-293T cells. beta(1)- and beta(2)-adrenergic receptors were found to have similar propensity to engage in homo- and heterotropic interactions suggesting that, at equivalent expression levels of the two receptor subtypes, an equal proportion of homo- and heterodimers would form. Analysis of the data also revealed that, at equimolar expression levels of energy donor and acceptor, more than 80% of the receptor molecules exist as dimers and that this high incidence of receptor dimerization is insensitive to receptor density for expression levels varying between 1.4 and 26.9 pmol of receptor/mg of membrane protein. Taken together, these results indicate that most of the receptors expressed in cells exist as constitutive dimers and that, at least in undifferentiated fibroblasts, the proportion of homo- and heterodimers between the closely related beta(1)- and beta(2)-adrenergic receptors is determined by their relative levels of expression.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.549

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 integrity0.0000.000
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 head0.023
GPT teacher head0.275
Teacher spread0.253 · 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

Citations470
Published2002
Admission routes2
Has abstractyes

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