Diabetes, which has shown an explosive increase in terms of its incidence, is regarded as a serious disease that must be overcome for the sake of human life. Among animal models used for testing of drug efficacy, the mini-pig model has shown a rapid upload due to its many similarities with human, particularly concerning the pharmacokinetics of compounds after subcutaneous administration, the structure and function of the gastrointestinal tract, the morphology of the pancreas, and overall metabolic status. Based on these various advantages, we sought to develop an animal model of type II diabetic mellitus using the Micro-pig, which differs from other miniature pigs. We used six male Micro-pigs for induction of a moderate insulin deficient model with nicotinamide (NIA)/streptozotocin (STZ) treatment and three animals for control. For evaluation of incidence of type II diabetes, we measured blood glucose level, and performed oral glucose tolerance test and immunohistochemistry on pancreatic tissue using insulin antibody. Compared to control animals, all animals treated with NIA/STZ showed high levels of glucose and low levels of insulin. In addition, we observed the partially destroyed beta cell population from tissue of the pancreas in treated animals. Based on these results, we report that the Micro-pig model developed in this study can be used for testing of the efficacy of therapeutic agents for treatment of Type 2 diabetic mellitus.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3469849PMC
http://dx.doi.org/10.5625/lar.2012.28.3.205DOI Listing

Publication Analysis

Top Keywords

type diabetic
12
diabetic mellitus
12
animal model
8
model
5
development type
4
mellitus animal
4
model micropig®
4
micropig® diabetes
4
diabetes explosive
4
explosive increase
4

Similar Publications

For patients considering bariatric surgery, it is essential to have clear answers to common questions to ensure the success of the procedure. Patients should understand that surgery is not a quick fix but a tool that must be complemented by lifestyle changes, including dietary adjustments and regular physical activity. The procedure carries potential risks that should be weighed against the potential benefits.

View Article and Find Full Text PDF

Background: The triglyceride‒glucose index (TyG index) is a reliable surrogate for insulin resistance (IR) in individuals with type 2 diabetes mellitus and is associated with cardiovascular disease. Recent studies have reported that H-type hypertension is likewise a predictor of adverse events in patients with coronary heart disease (CHD). However, the relationship between the TyG index and prognosis in patients with H-type hypertension combined with CHD has not yet been reported.

View Article and Find Full Text PDF

Background: Lysinuric protein intolerance is a rare autosomal disorder caused by mutations in the Slc7a7 gene that lead to impaired transport of neutral and basic amino acids. The gold standard treatment for lysinuric protein intolerance involves a low-protein diet and citrulline supplementation. While this approach partially improves cationic amino acid plasma levels and alleviates some symptoms, long-term treatment is suggested to be detrimental and may lead to life-threatening complications characterized by a wide range of hematological and immunological abnormalities.

View Article and Find Full Text PDF

Background: The aim of this study was to analyze the influence of good metabolic control, based on glycosylated hemoglobin (HbA1c) levels, on oral health status and the need for orthodontic treatment in children.

Methods: This cross-sectional study was carried out at the Dental Clinic of the University of Salamanca (Spain) during the years 2020 and 2024. A total of 260 children with type 1 diabetes (aged between 6 and 12 years) participated.

View Article and Find Full Text PDF

Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.

Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!