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Record W4411294436 · doi:10.2337/db25-1843-p

1843-P: Regulator of G Protein Signaling 9 (RGS9) Is a Positive Regulator of Insulin Secretion in Mouse Islets

2025· article· en· W4411294436 on OpenAlexaboutno aff
SARAH FERRAGNE, S. Campbell, LAURA REININGER, Caroline Tremblay, Julien Ghislain, Vincent Poitout

Bibliographic record

VenueDiabetes · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsnot available
Fundersnot available
KeywordsRegulatorIsletInternal medicineSecretionEndocrinologyRegulator of G protein signalingInsulinCell biologyBiologyChemistryMedicineSignal transductionG proteinGTPase-activating proteinGeneBiochemistry

Abstract

fetched live from OpenAlex

Introduction and Objective: Beta-cell function and mass are under control of G protein-coupled receptors (GPCRs) which are themselves subject to intracellular regulation by regulator of G protein signaling (RGS) proteins. Although the importance of GPCRs to beta-cell biology is well documented, the role of RGS proteins is largely unknown. Recent evidence suggests that RGS9 may have a role in the control of beta-cell function. The aim of this study was to better understand how RGS9 regulates insulin secretion. Methods: Quantitative (q) PCR and RNA in situ hybridization were performed on isolated male mouse islets and pancreatic sections, respectively. Male mouse pseudoislets were infected with adenoviruses encoding short-hairpin (sh) RNAs against RGS9 or control viruses. Glucose-stimulated insulin secretion (GSIS) was assessed in 1h-static incubations and is expressed as mean of the percent of insulin content ± SEM. Significance was tested using a two-way ANOVA with post hoc adjustment for multiple comparisons. Results: RGS9 transcripts were detected in beta, alpha and delta cells in mouse pancreatic sections and both RGS9-1 and -2 isoforms were detected in whole islet extracts. RGS9 knockdown with two distinct shRNAs decreased KCl-stimulated insulin secretion (Control: 4.9±1.0 versus shRNA1: 1.3±0.3 p<0.0001 and shRNA2: 2.8±0.4 p<0.05, n=5-6). Surprisingly, in RGS9 knockout (RGS9Δexon2-4) islets GSIS was not affected (wild-type: 0.8±0.1 versus mutant: 0.7±0.06, n=6, ns). However, expression of alternative, truncated RGS9 transcripts were detected in RGS9Δexon2-4 islets, and GSIS was reduced upon RGS9 knockdown in RGS9Δexon2-4 islets (Control: 1.1±0.4 versus shRNA1: 0.3±0.1 p<0.01, n=4). Conclusion: RGS9 positively controls insulin secretion. Preserved GSIS in RGS9Δexon2-4 islets may be due to compensation from truncated RGS9. Disclosure S. Ferragne: None. S.A. Campbell: Employee; Applied Pharmaceutical Innovation, Hepion Pharmaceuticals. L. Reininger: None. C. Tremblay: None. J. Ghislain: None. V. Poitout: Research Support; Biodexa. Funding Natural Sciences and Engineering Research Council of CanadaFonds de recherche du Québec - Nature et technologie

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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.005
GPT teacher head0.224
Teacher spread0.220 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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