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β‐cell preservation: a potential role for thiazolidinediones to improve clinical care in Type 2 diabetes

2005· review· en· W2100485391 on OpenAlexaff
LA Leiter

Bibliographic record

VenueDiabetic Medicine · 2005
Typereview
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineType 2 diabetesInsulin resistanceBeta cellDiabetes mellitusBETA (programming language)InsulinDiseaseBioinformaticsCellType 2 Diabetes MellitusEndocrinologyInternal medicineIsletGeneticsBiology

Abstract

fetched live from OpenAlex

Type 2 diabetes is caused by progressively increasing insulin resistance coupled with deteriorating beta-cell function, and there is a growing body of evidence to suggest that both of these defects precede hyperglycaemia by many years. Several studies have demonstrated the importance of maintaining beta-cell function in patients with Type 2 diabetes. This review explores parameters used to indicate beta-cell dysfunction, in Type 2 diabetes and in individuals with a predisposition to the disease. A genetic element undoubtedly underlies beta-cell dysfunction; however, a number of modifiable components are also associated with beta-cell deterioration, such as chronic hyperglycaemia and elevated free fatty acids. There is also evidence for a link between pro-inflammatory cytokines and impairment of insulin-signalling pathways in the beta-cell, and the potential role of islet amyloid deposition in beta-cell deterioration continues to be a subject for debate. The thiazolidinediones are a class of agents that have demonstrated clinical improvements in indices of beta-cell dysfunction and have the potential to improve beta-cell function. Data are accumulating to show that this therapeutic group offers a number of advantages over traditionally employed oral agents, and these data demonstrate the growing importance of thiazolidinediones in Type 2 diabetes management.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.050
GPT teacher head0.369
Teacher spread0.319 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations44
Published2005
Admission routes1
Has abstractyes

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