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Record W4367043185 · doi:10.1016/j.isci.2023.106748

Pancreas-derived DPP4 is not essential for glucose homeostasis under metabolic stress

2023· article· en· W4367043185 on OpenAlexaff
Evgenia Fadzeyeva, Cassandra A.A. Locatelli, Natasha A. Trzaskalski, My-Anh Nguyen, Megan E. Capozzi, Branka Vulesevic, Nadya M. Morrow, Peyman Ghorbani, Antonio A. Hanson, Ilka Lorenzen‐Schmidt, Mary-Anne Doyle, Richard J. Seymour, Elodie M. Varin, Morgan D. Fullerton, Jonathan E. Campbell, Erin E. Mulvihill

Bibliographic record

VenueiScience · 2023
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsLunenfeld-Tanenbaum Research InstituteInstitute of Infection and ImmunityUniversity of Ottawa
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsGlucose homeostasisHomeostasisPancreasChemistryBiochemistryCell biologyBiologyEndocrinologyDiabetes mellitusInsulin resistance

Abstract

fetched live from OpenAlex

Mice systemically lacking dipeptidyl peptidase-4 (DPP4) have improved islet health, glucoregulation, and reduced obesity with high-fat diet (HFD) feeding compared to wild-type mice. Some, but not all, of this improvement can be linked to the loss of DPP4 in endothelial cells (ECs), pointing to the contribution of non-EC types. The importance of intra-islet signaling mediated by α to β cell communication is becoming increasingly clear; thus, our objective was to determine if β cell DPP4 regulates insulin secretion and glucose tolerance in HFD-fed mice by regulating the local concentrations of insulinotropic peptides. Using β cell double incretin receptor knockout mice, β cell- and pancreas-specific Dpp4 −/− mice, we reveal that β cell incretin receptors are necessary for DPP4 inhibitor effects. However, although β cell DPP4 modestly contributes to high glucose (16.7 mM)-stimulated insulin secretion in isolated islets, it does not regulate whole-body glucose homeostasis.

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 score0.085
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.036
GPT teacher head0.306
Teacher spread0.270 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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