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Record W4221116614 · doi:10.1038/s41467-022-29231-6

Adipocyte Gq signaling is a regulator of glucose and lipid homeostasis in mice

2022· article· en· W4221116614 on OpenAlexafffund
Takefumi Kimura, Sai P. Pydi, Lei Wang, Dhanush Haspula, Yinghong Cui, Huiyan Lü, Gabriele M. König, Evi Kostenis, Gregory R. Steinberg, Oksana Gavrilova, Jürgen Wess

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsMcMaster University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesJapan Society for the Promotion of ScienceCanadian Institutes of Health ResearchUniversity of North Carolina at Chapel HillDiabetes CanadaNational Institutes of HealthRheinische Friedrich-Wilhelms-Universität BonnCentral Michigan UniversityJoslin Diabetes Center
KeywordsAdipocyteGlucose homeostasisLipolysisInternal medicineEndocrinologyInsulin resistanceReceptorInsulin receptorGlucose uptakeInsulinAdipose tissueBiologyChemistryMedicine

Abstract

fetched live from OpenAlex

Abstract Obesity is the major driver of the global epidemic in type 2 diabetes (T2D). In individuals with obesity, impaired insulin action leads to increased lipolysis in adipocytes, resulting in elevated plasma free fatty acid (FFA) levels that promote peripheral insulin resistance, a hallmark of T2D. Here we show, by using a combined genetic/biochemical/pharmacologic approach, that increased adipocyte lipolysis can be prevented by selective activation of adipocyte G q signaling in vitro and in vivo (in mice). Activation of this pathway by a G q -coupled designer receptor or by an agonist acting on an endogenous adipocyte G q -coupled receptor (CysLT 2 receptor) greatly improved glucose and lipid homeostasis in obese mice or in mice with adipocyte insulin receptor deficiency. Our findings identify adipocyte G q signaling as an essential regulator of whole-body glucose and lipid homeostasis and should inform the development of novel classes of GPCR-based antidiabetic drugs.

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 score0.164
Threshold uncertainty score0.349

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 science0.0000.001
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 head0.012
GPT teacher head0.263
Teacher spread0.252 · 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

Citations33
Published2022
Admission routes2
Has abstractyes

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