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Record W4212797158 · doi:10.1113/ep089947

Zucker Diabetic‐Sprague Dawley (ZDSD) rat: Type 2 diabetes translational research model

2022· article· en· W4212797158 on OpenAlexafffund

Bibliographic record

VenueExperimental Physiology · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsMemorial University of NewfoundlandWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsDiabetes mellitusLeptinType 2 diabetesDiseasePopulationPreclinical researchTranslational researchInsulinPhenotype

Abstract

fetched live from OpenAlex

NEW FINDINGS: What is the topic of this review? The Zucker Diabetic-Sprague Dawley (ZDSD) rat is in the early adoption phase of use by researchers in the fields of diabetes, including prediabetes, obesity and metabolic syndrome. It is essential that physiology researchers choose preclinical models that model human type 2 diabetes appropriately and are aware of the limitations on experimental design. What advances does it highlight? Our review of the scientific literature finds that although sex, age and diets contribute to variability, the ZDSD phenotype and disease progression model the characteristics of humans who have prediabetes and diabetes, including co-morbidities. ABSTRACT: Type 2 diabetes (T2D) is a prevalent disease and a significant concern for global population health. For persons with T2D, clinical treatments target not only the characteristics of hyperglycaemia and insulin resistance, but also co-morbidities, such as obesity, cardiovascular and renal disease, neuropathies and skeletal bone conditions. The Zucker Diabetic-Sprague Dawley (ZDSD) rat is a rodent model developed for experimental studies of T2D. We reviewed the scientific literature to highlight the characteristics of T2D development and the associated phenotypes, such as metabolic syndrome, cardiovascular complications and bone and skeletal pathologies in ZDSD rats. We found that ZDSD phenotype characteristics are independent of leptin receptor signalling. The ZDSD rat develops prediabetes, then progresses to overt diabetes that is accelerated by introduction of a timed high-fat diet. In male ZDSD rats, glycated haemoglobin (HbA1c) increases at a constant rate from 7 to >30 weeks of age. Diabetic ZDSD rats are moderately hypertensive compared with other rat strains. Diabetes in ZDSD rats leads to endothelial dysfunction in specific vasculatures, impaired wound healing, decreased systolic and diastolic cardiac function, neuropathy and nephropathy. Changes to bone composition and the skeleton increase the risk of bone fractures. Zucker Diabetic-Sprague Dawley rats have not yet achieved widespread use by researchers. We highlight sex-related differences in the ZDSD phenotype and gaps in knowledge for future studies. Overall, scientific data support the premise that the phenotype and disease progression in ZDSD rats models the characteristics in humans. We conclude that ZDSD rats are an advantageous model to advance understanding and discovery of treatments for T2D through preclinical research.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.054
GPT teacher head0.344
Teacher spread0.290 · 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 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

Citations28
Published2022
Admission routes2
Has abstractyes

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