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Timing of the Functional Diversification of α‐ and β‐Adrenoceptors in Fish and Other Vertebrates

2009· article· en· W2165022068 on OpenAlexaff
Stéphane Aris‐Brosou, XIAO-FANG CHEN, Steven F. Perry, Thomas W. Moon

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsOntario GenomicsUniversity of Ottawa
Fundersnot available
KeywordsGene duplicationBiologyVertebratePhylogenetic treeEvolutionary biologyDiversification (marketing strategy)Fish <Actinopterygii>Functional divergenceGenomePhylogeneticsGeneGeneticsGene familyFishery

Abstract

fetched live from OpenAlex

Adrenoceptors (ARs) are G protein-coupled receptors found throughout the vertebrates. Their pharmacology and preliminary phylogenetic analyses suggest that ARs are classified as alpha(1), alpha(2) (and their subtypes), and beta(1), beta(2), and beta(3). However, the relationships among subtypes of this superfamily, as well as both the pattern and the timing of their diversification, are poorly understood. In addition, fish AR subtypes possess pharmacologies and tissue distributions that only partially overlap with those of their mammalian counterparts, in spite of their apparent orthologous relationships within subtypes. Here we analyze 136 sequences in a range of vertebrates, including fish, to resolve these issues. We show that diversification of ARs occurred during duplication events that occurred within distinct time periods. Each period maps to whole-genome duplication events, two in vertebrates and one in fish. We also show that ARs underwent multiple duplications within these broad windows and that fish ARs underwent extensive gene loss after duplications that promoted their functional divergence with respect to other vertebrates.

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 score0.048
Threshold uncertainty score0.098

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 head0.074
GPT teacher head0.298
Teacher spread0.223 · 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

Citations40
Published2009
Admission routes1
Has abstractyes

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