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Record W2133487229 · doi:10.1210/me.2013-1085

Minireview: The Effects of Species Ortholog and SNP Variation on Receptors for Free Fatty Acids

2013· review· en· W2133487229 on OpenAlexfundno aff
Brian D. Hudson, Hannah Murdoch, Graeme Milligan

Bibliographic record

VenueMolecular Endocrinology · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsnot available
FundersUniversity of GlasgowWellcome TrustCanadian Institutes of Health ResearchStrategiske Forskningsråd
KeywordsBiologyReceptorSNPPhenotypeGPR120Single-nucleotide polymorphismHormoneG protein-coupled receptorGeneComputational biologyLigand (biochemistry)Hormone receptorGeneticsBiochemistryGenotype

Abstract

fetched live from OpenAlex

Although it is widely assumed that species orthologs of hormone-responsive G protein-coupled receptors will be activated by the same endogenously produced ligand(s), variation in potency, particularly in cases in which more than 1 receptor responds to the same hormone, can result in challenges in defining the contribution of individual receptors in different species. This can create considerably greater issues when using synthetic chemical ligands and, in some cases, may result in a complete lack of efficacy of such a ligand when used in animal models of pathophysiology. In man, the concept that distinct responses of individuals to medicines may reflect differences in the ability of such drugs to bind to or activate single nucleotide polymorphism variants of receptors is more established as a concept but, in many cases, clear links between such variants that are associated with disease phenotypes and substantial differences in receptor ligand pharmacology have been more difficult to obtain. Herein we consider each of these issues for the group of free fatty acid receptors, FFA1-FFA4, defined to be activated by free fatty acids of varying chain length, which, based on their production by 1 tissue or location and action in distinct locations, have been suggested to possess characteristics of hormones.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.029
GPT teacher head0.295
Teacher spread0.266 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations37
Published2013
Admission routes1
Has abstractyes

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