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Record W4390706523 · doi:10.1530/joe-23-0317

In vivo models of gestational and type 2 diabetes mellitus characterized by endocrine pancreas cell impairments

2024· article· en· W4390706523 on OpenAlexaff
Sandra Szlapinski, David J. Hill

Bibliographic record

VenueJournal of Endocrinology · 2024
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsGestational diabetesDiabetes mellitusType 2 diabetesInsulin resistancePancreasEndocrine systemMedicineEndocrinologyBeta cellEnteroendocrine cellInternal medicineInsulinType 1 diabetesIsletBioinformaticsHormonePregnancyBiologyGestation

Abstract

fetched live from OpenAlex

Insulin resistance contributes to the development of various diseases, including type 2 diabetes and gestational diabetes. Even though gestational diabetes is specific to pregnancy, it can result in long-term glucose intolerance and type 2 diabetes after delivery. Given the substantial health and economic burdens associated with diabetes, it is imperative to better understand the mechanisms leading to insulin resistance and type 2 diabetes so that treatments targeted at reversing symptoms can be developed. Considering that the endocrine cells of the pancreas (islets of Langerhans) largely contribute to the pathogenesis of diabetes (beta-cell insufficiency and dysfunction), the elucidation of the various mechanisms of endocrine cell plasticity is important to understand. By better defining these mechanisms, targeted therapeutics can be developed to reverse symptoms of beta-cell deficiency and insulin resistance in diabetes. Animal models play an important role in better understanding these mechanisms, as techniques for in vivo imaging of endocrine cells in the pancreas are limited. Therefore, this review article will discuss the available rodent models of gestational and type 2 diabetes that are characterized by endocrine cell impairments in the pancreas, discuss the models with a comparison to human diabetes, and explore the potential mechanisms of endocrine cell plasticity that contribute to these phenotypes, as these mechanisms could ultimately be used to reverse blood glucose dysregulation in diabetes.

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 score0.220
Threshold uncertainty score0.441

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 science0.0000.000
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 head0.013
GPT teacher head0.264
Teacher spread0.251 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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