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Record W2805241084 · doi:10.1016/j.molmet.2018.06.006

GLP-2 receptor signaling controls circulating bile acid levels but not glucose homeostasis in Gcgr mice and is dispensable for the metabolic benefits ensuing after vertical sleeve gastrectomy

2018· article· en· W2805241084 on OpenAlexafffund
Anita Patel, Bernardo Yusta, Dianne Matthews, Maureen Charron, Randy J. Seeley, Daniel J. Drucker

Bibliographic record

VenueMolecular Metabolism · 2018
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
FundersDaiichi Sankyo EuropePfizerEthicon Endo-SurgeryNational Institute of Diabetes and Digestive and Kidney DiseasesBanting and Best Diabetes Centre, University of TorontoCanadian Institutes of Health ResearchCanada Research ChairsNational Institutes of HealthShireNovo NordiskUniversity of MichiganUniversity of Toronto
KeywordsGlucose homeostasisSleeve gastrectomyHomeostasisEndocrinologyBile acidReceptorInternal medicineMedicineDiabetes mellitusObesityInsulin resistanceGastric bypass

Abstract

fetched live from OpenAlex

Therapeutic interventions that improve glucose homeostasis such as attenuation of glucagon receptor (Gcgr) signaling and bariatric surgery share common metabolic features conserved in mice and humans. These include increased circulating levels of bile acids (BA) and the proglucagon-derived peptides (PGDPs), GLP-1 and GLP-2. Whether BA acting through TGR5 (Gpbar1) increases PGDP levels in these scenarios has not been examined. Furthermore, although the importance of GLP-1 action has been interrogated in Gcgr−/− mice and after bariatric surgery, whether GLP-2 contributes to the metabolic benefits of these interventions is not known. To assess whether BA acting through Gpbar1 mediates improved glucose homeostasis in Gcgr−/− mice we generated and characterized Gcgr−/−:Gpbar1−/− mice. The contribution of GLP-2 receptor (GLP-2R) signaling to intestinal and metabolic adaptation arising following loss of the Gcgr was studied in Gcgr−/−:Glp2r−/− mice. The role of the GLP-2R in the metabolic improvements evident after bariatric surgery was studied in high fat-fed Glp2r−/− mice subjected to vertical sleeve gastrectomy (VSG). Circulating levels of BA were markedly elevated yet similar in Gcgr−/−:Gpbar1+/+ vs. Gcgr−/−:Gpbar1−/− mice. Loss of GLP-2R lowered levels of BA in Gcgr−/− mice. Gcgr−/−:Glp2r−/− mice also exhibited shifts in the proportion of circulating BA species. Loss of Gpbar1 did not impact body weight, intestinal mass, or glucose homeostasis in Gcgr−/− mice. In contrast, small bowel growth was attenuated in Gcgr−/−:Glp2r−/− mice. The improvement in glucose tolerance, elevated circulating levels of GLP-1, and glucose-stimulated insulin levels were not different in Gcgr−/−:Glp2r+/+ vs. Gcgr−/−:Glp2r−/− mice. Similarly, loss of the GLP-2R did not attenuate the extent of weight loss and improvement in glucose control after VSG. These findings reveal that GLP-2R controls BA levels and relative proportions of BA species in Gcgr−/− mice. Nevertheless, the GLP-2R is not essential for i) control of body weight or glucose homeostasis in Gcgr−/− mice or ii) metabolic improvements arising after VSG in high fat-fed mice. Furthermore, despite elevations of circulating levels of BA, Gpbar1 does not mediate elevated levels of PGDPs or major metabolic phenotypes in Gcgr−/− mice. Collectively these findings refine our understanding of the relationship between Gpbar1, elevated levels of BA, PGDPs, and the GLP-2R in amelioration of metabolic derangements arising following loss of Gcgr signaling or after vertical sleeve gastrectomy.

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 score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.019
GPT teacher head0.256
Teacher spread0.237 · 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".

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Citations26
Published2018
Admission routes2
Has abstractyes

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