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A putative β<sub>2</sub>‐adrenoceptor from the rainbow trout (<i>Oncorhynuchus mykiss</i>)

2001· article· en· W1575545036 on OpenAlexaff
James G. Nickerson, Stephen G. Dugan, Guy Drouin, Thomas W. Moon

Bibliographic record

VenueEuropean Journal of Biochemistry · 2001
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRainbow troutBiologyTroutVertebrateGillPhylogenetic treeGeneGeneticsFish <Actinopterygii>Fishery

Abstract

fetched live from OpenAlex

Extensive molecular characterization of mammalian beta-adrenoceptors has revealed complex modes of regulation and interaction. Relatively little attention, however, has focused on adrenoceptors from early branching vertebrates such as fish. Using an RT-PCR approach we have cloned a rainbow trout beta2-adrenoceptor gene that codes for a 409-amino-acid protein with the same seven transmembrane domain structure as its mammalian counterparts. This rainbow trout beta2-adrenoceptor shares a high degree of amino-acid sequence conservation with other vertebrate beta2-adrenoceptors. The conclusion that this sequence is a rainbow trout beta2-adrenoceptor is further supported by phylogenetic analysis of vertebrate beta-adrenoceptor sequences and competitive pharmacological binding data. RNase protection assays demonstrate that the rainbow trout beta2-adrenoceptor gene is highly expressed in the liver and red and white muscle, with lower levels of expression in the gills, heart, kidney and spleen of the rainbow trout. The lack of regulatory phosphorylation sites within the G-protein-binding domain of the rainbow trout beta2-adrenoceptor sequence suggests that the in vivo control of trout beta2-adrenoceptor signaling differs substantially from that of mammals.

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 score0.003
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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.236
Teacher spread0.224 · 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

Citations74
Published2001
Admission routes1
Has abstractyes

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Same venueEuropean Journal of BiochemistrySame topicAdipose Tissue and MetabolismFrench-language works237,207