MétaCan
Menu
Back to cohort
Record W2113206514 · doi:10.1111/dom.12529

Islet amyloid inhibitors improve glucose homeostasis in a transgenic mouse model of type 2 diabetes

2015· letter· en· W2113206514 on OpenAlexafffund
Nadeeja Wijesekara, Rosemary Ahrens, Ling Wu, Katherine Ha, Ying Liu, Michael B. Wheeler, Paul E. Fraser

Bibliographic record

VenueDiabetes Obesity and Metabolism · 2015
Typeletter
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsOccupational Cancer Research CentreUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsIsletAmyloid (mycology)Genetically modified mouseGlucose homeostasisEndocrinologyInternal medicineIn vivoType 2 diabetesTransgeneDiabetes mellitusApoptosisInsulinSecretionBiologyChemistryMedicineBiochemistryInsulin resistance

Abstract

fetched live from OpenAlex

Increasing evidence points to the cytotoxicity of islet amyloid polypeptide (IAPP) aggregates as a major contributor to the loss of β-cell mass in type 2 diabetes. Prevention of IAPP formation represents a potential treatment to increase β-cell survival and function. The IAPP inhibitory peptide, D-ANFLVH, has been previously shown to prevent islet amyloid accumulation in cultured human islets. To assess its activity in vivo, D-ANFLVH was administered by intraperitoneal injection into a human IAPP transgenic mouse model, which replicates type 2 diabetes islet amyloid pathology. The peptide was a potent inhibitor of islet amyloid deposition, resulting in reduced islet cell apoptosis and preservation of β-cell area leading to improved glucose tolerance. These findings provide support for a key role of islet amyloid in β-cell survival and validate the application of anti-amyloid compounds as therapeutic strategies to maintain normal insulin secretion in patients with type 2 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 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.228
Teacher spread0.210 · 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

Citations25
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueDiabetes Obesity and MetabolismSame topicPancreatic function and diabetesFrench-language works237,207