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Record W1973349045 · doi:10.3810/pgm.2009.01.1954

Impact of Incretin Therapy on Islet Dysfunction: An Underlying Defect in the Pathophysiology of Type 2 Diabetes

2009· article· en· W1973349045 on OpenAlexfundno aff
Janet B. McGill

Bibliographic record

VenuePostgraduate Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsnot available
FundersNovo NordiskBiodelMcGill UniversityMerck
KeywordsIncretinMedicineInternal medicineEndocrinologyVildagliptinGlucose homeostasisLiraglutideAmylinExenatideType 2 diabetesInsulinGlucagonSitagliptinDipeptidyl peptidase-4Diabetes mellitusHomeostasisHormoneIsletInsulin resistance

Abstract

fetched live from OpenAlex

Glucose homeostasis is governed by a complex interplay of hormonal signaling and modulation. Insulin, glucagon, amylin, the incretin hormones glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), and other hormones and enzymes interact to maintain glucose homeostasis and normal cellular metabolism. Derangements in these hormonal interactions, particularly insulin deficits and impaired insulin action, result in the development of type 2 diabetes-but only in individuals who have experienced significant dysfunction or loss of beta-cells, located in the pancreatic islets of Langerhans. Much less is known about the impact of alpha-cell dysregulation on glucose homeostasis, although it has been demonstrated that glucagon-secreting alpha-cells, also located in the pancreatic islets, play an important role in glucose metabolism. Because beta-cell dysfunction occurs early in the course of type 2 diabetes and is progressive, early intervention with therapies that improve beta-cell function is desirable. In addition to reducing HbA1c and fasting plasma glucose, the recently developed diabetes therapies GLP-1 receptor agonists (eg, exenatide, liraglutide) and dipeptidyl peptidase-4 (DPP-4) inhibitors (eg, sitagliptin, vildagliptin) appear to have beneficial effects on beta-cell dysfunction and, possibly, on alpha-cell dysregulation.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.058
GPT teacher head0.346
Teacher spread0.287 · 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 designObservational
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

Citations16
Published2009
Admission routes1
Has abstractyes

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