Major gene mutations associated with obesity and diabetes mellitus

Obesity and diabetes mellitus are associated with low or elevated serum leptin and insulin levels (U-like relation). Mutations in LEP and INS are linked to decreases in leptin and insulin while mutations in LEPR and INSR are linked to their increase. Homozygous LEP mutations are associated with the early onset of severe obesity and the diverse impairment of physiological functions. The recessive LEPR mutations are associated with similar pathology in homozygous state. Missense mutations of INS are dominant and induce the synthesis of chimeric proinsulin, which may interfere with the folding and processing of active insulin molecules. In the heterozygous state, they cause insulin deficiency and PND. Recessive INS mutations do not induce the synthesis of anomalous proinsulin, and they are only associated with PND in the homozygous state. Mutations of INSR induce insulin resistance, lipodystrophy, other pathologies, and suggest the important role of insulin in glucose level regulation and in the stimulation of fat accumulation.     

A coalescent model of recombination hotspots

Recent experimental findings suggest that the assumption of a homogeneous recombination rate along the human genome is too naive. These findings point to block-structured recombination rates; certain regions (called hotspots) are more prone than other regions to recombination. In this report a coalescent model incorporating hotspot or block-structured recombination is developed and investigated analytically as well as by simulation. Our main results can be summarized as follows: (1) The expected number of recombination events is much lower in a model with pure hotspot recombination than in a model with pure homogeneous recombination, (2) hotspots give rise to large variation in recombination rates along the genome as well as in the number of historical recombination events, and (3) the size of a (nonrecombining) block in the hotspot model is likely to be overestimated grossly when estimated from SNP data. The results are discussed with reference to the current debate about block-structured recombination and, in addition, the results are compared to genome-wide variation in recombination rates. A number of new analytical results about the model are derived.     

A novel model mouse for type 2 diabetes mellitus with early onset and persistent hyperglycemia

Various mouse models of type 2 diabetes have been established, but few of these show early onset and persistent hyperglycemia. We have established a congenic mouse strain (NSY.B6-Tyr⁺,A^y) in which a spontaneous mutation of the agouti yellow (A^y) gene, which causes obesity by hyperphagia, was introduced into the NSY strain, which shows increased glucose intolerance with age. This strain has been maintained as a segregating inbred strain by mating obese yellow (A^y/a) males with normal black (a/a) females. All yellow males showed marked obesity and hyperglycemia (mean blood glucose level >400 mg/dl) from 10 to 24 weeks of age. The yellow males also showed glucose intolerance and insulin resistance. They provide a potentially valuable model mouse for research into type 2 diabetes, hyperlipidemia, fatty liver, and renal glomerular complications. Yellow female mice also showed marked obesity, but the incidence of diabetes and the severity of various pathological conditions were milder than in yellow males. None of the black mice showed hyperglycemia in either sex. NSY.B6-Tyr⁺,A^y strain has good fertility and does not display inter-male aggression, making them useful as a new model for type 2 diabetes with early onset and persistent hyperglycemia.     

An optimal control model of diabetes mellitus

Engineering optimal control theory is applied to equations describing insulin and glucose interactions. The nature of the optimal controller is established. It is shown how the results can be utilized in a closed loop feedback control system.     

In vivo model for dyslipidemia with diabetes mellitus in hamster

Due to similarities in lipid metabolism to those in humans, hamster is considered as a good model for the study of regulatory mechanisms of plasma lipoproteins in response to cholesterol or fatty acid-enriched diet. This model of hyperlipidemia has been modified to produce dyslipidedmia with diabetes complexities by feeding with high fat diet added with 9% (w/w) fructose. Feeding this diet to hamster for 10 days markedly increases plasma levels of triglyceride, cholesterol, fatty acids followed by a significant increase in glycerol, beta lipoproteins, high density lipoprotein, glucose and glycosylated proteins. This model is being used for research and development of lipid lowering drugs with hypoglycemic activity in collaboration with Novo Nordisk, Denmark. The modified high fat diet formulation has now been prepared (Research diet D.99122211) and supplied by Research Diets Inc, Burnswick USA.     

Cost and policy implications from the increasing prevalence of obesity and diabetes mellitus

Background: The increasing prevalence of obesity and type 2 diabetes mellitus (DM), among children and adults, has posed important policy and budgetary considerations to government, health insurance companies, employers, physicians, and health care delivery systems.Objective: This article examines issues that are common to obesity and DM, including cost, clinical research, and treatment barriers, and proposes health policies to address these issues.Method: A manual review was performed of authoritative literature from peer-reviewed medical publications and recently published medical textbooks.Results: Obesity has been disproportionately prevalent among women and minorities, accompanied by an increased risk for DM. Women have experienced an increased risk for the metabolic syndrome, DM, and cardiovascular disease after onset of menopause. Obesity has been related to an increased risk for breast cancer among women, and may be a barrier that prevents women from being screened for colon and breast cancers. Maternal obesity has been a risk factor for gestational DM.Conclusions: Obesity and DM represent crises for the health care system and the health of the public, incurring costs and disease burden for adults and children, with increasing costs and prevalence expected unless more coordinated efforts to address the causes of these conditions at the national level are implemented. An investment in infrastructure to promote increased physical activity and reward weight management may be budget neutral in the long term by reducing the costs of morbidity and mortality. About two thirds of the costs from DM complications could be averted with appropriate primary care.     

Multivariate classification analysis of metabolomic data for candidate biomarker discovery in type 2 diabetes mellitus

Recent advances in genomics, metabolomics and proteomics have made it possible to interrogate disease pathophysiology and drug response on a systems level. The analysis and interpretation of the complex data obtained using these techniques is potentially fertile but equally challenging. We conducted a small clinical trial to explore the application of metabolomics data in candidate biomarker discovery. Specifically, serum and urine samples from patients with type 2 diabetes mellitus (T2DM) were profiled on metabolomics platforms before and after 8 weeks of treatment with one of three commonly used oral antidiabetic agents, the sulfonyurea glyburide, the biguanide metformin, or the thiazolidinedione rosiglitazone. Multivariate classification techniques were used to detect serum or urine analytes, obtained at baseline (pre-treatment) that could predict a significant treatment response after 8 weeks. Using this approach, we identified three analytes, measured at baseline, that were associated with response to a thiazolidinedione after 8 weeks of treatment. Although larger and longer-term studies are required to validate any of the candidate biomarkers, pharmacometabolomic profiling, in combination with multivariate classification, is worthy of further exploration as an adjunct to clinical decision making regarding treatment selection and for patient stratification within clinical trials. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A proposed model of the treatment of diabetes mellitus in pregnancy

A model of management of pregnant diabetic patients is proposed. Such a model has been implemented at the Voivodeship Out-patient Clinic for Diabetics. Proposed model includes recent data on diabetes mellitus complications and the effect of coexisting diseases on the mother and fetus health. Management was adapted to the real and potential possibilities of health service in Poland. A decrease in the rate of mortality of fetuses under 7% was achieved. It is worth emphasizing despite higher value than those reported in the literature.     

A novel screening model for the molecular drug for diabetes and obesity based on tyrosine phosphatase Shp2

Tyrosine phosphatase Src-homology phosphotyrosyl phosphatase 2 (Shp2) was identified as a potential molecular target for therapeutic treatment of diabetes and obesity. However, there is still no systematic research on the enhancers for the Shp2 enzyme. The present study established a novel powerful model for the high-throughput screening of Shp2 enhancers and successfully identified a new specific Shp2 enhancer, oleanolic acid, from Chinese herbs.     

A Cox regression model for the relative mortality and its application to diabetes mellitus survival data

A Cox-type regression model for the ratio between the mortality in a cohort and that in a reference population is introduced. By means of the model it is possible to include in the survival analysis both individual (possibly time-dependent) characteristics for the study cohort and changing trends in the mortality in the reference population. This is particularly relevant in long-term follow-up studies where there may be considerable changes in the mortality in the reference population. Estimation procedures in the model are discussed and large-sample properties of the estimators are outlined. The model is applied to the analysis of two sets of data concerning the survival among insulin-dependent diabetics in Denmark.     

DNA binding sites: representation and discovery

The purpose of this article is to provide a brief history of the development and application of computer algorithms for the analysis and prediction of DNA binding sites. This problem can be conveniently divided into two subproblems. The first is, given a collection of known binding sites, develop a representation of those sites that can be used to search new sequences and reliably predict where additional binding sites occur. The second is, given a set of sequences known to contain binding sites for a common factor, but not knowing where the sites are, discover the location of the sites in each sequence and a representation for the specificity of the protein.     

Blood glucose level neural model for type 1 diabetes mellitus patients

This paper deals with the blood glucose level modeling for Type 1 Diabetes Mellitus (T1DM) patients. The model is developed using a recurrent neural network trained with an extended Kalman filter based algorithm in order to develop an affine model, which captures the nonlinear behavior of the blood glucose metabolism. The goal is to derive a dynamical mathematical model for the T1DM as the response of a patient to meal and subcutaneous insulin infusion. Experimental data given by continuous glucose monitoring system is utilized for identification and for testing the applicability of the proposed scheme to T1DM subjects.     

Insulin replacement therapy for the rat model of streptozotocin-induced diabetes mellitus

OBJECTIVE: This study was conducted to compare various strategies for insulin replacement therapy in the streptozotocin-induced diabetic rat model. METHODS: Control and diabetic Sprague Dawley rats were fed ad libitum, blood glucose concentration was measured twice daily, and outcome was assessed over the final 5 days of a 10-day treatment period, with adjustment of insulin dosage toward the goal of normal glucose values. RESULTS: All insulin regimens induced weight gain at least comparable to that of controls, but glucose regulation differed. It was not possible to normalize glucose values by use of protamine zinc insulin (PZI) or Ultralente insulin given once daily. In contrast, PZI and neutral protamine Hagedorn (NPH) insulin given twice daily provided glucose values comparable to those in controls, whereas glucose values were modestly higher in response to a 70% human insulin isophane suspension and 30% soluble human insulin solution (70/ 30 insulin) given twice daily. Attempted normalization of glucose values was limited by hypoglycemia, which was most common after administration of PZI once daily, and least common after 70/30 insulin given twice daily. Dosage requirements for Ultralente insulin were four- to fivefold higher than those for all other insulins. CONCLUSION: In streptozotocin-diabetic rats, normal weight gain can be achieved by treatment with PZI insulin once daily, but attainment of near-normal glucose values requires administration of PZI, NPH, or 70/ 30 insulin twice daily. Ultralente insulin may have reduced bioeffectiveness in this animal model.     

A model for neural representation of temporal duration

To address how temporal duration is encoded in neural systems, we put forward a simple model for recurrent neural networks. Particular assumptions are only the following two: (1) neuronal bistability and; (2) environmental effects described by a heat bath. The results of Monte Carlo simulation show that population activity triggered at an initial time continues for a prolonged duration, followed by an abrupt self-termination. This time course seems highly suitable for neural representation of temporal duration. The time scale of this prolonged duration is much longer than the time scale of neuronal firing which is of the order of ms. The former time scale implies that of interval timing in cognition and behaviour. Thus, the model provides a possible explanation for a link between these two separated time scales. The Weber law, a hallmark of humans and animals' interval timing, can also be reproduced in our model.     

A knowledge discovery object model API for Java

Background  

Biological data resources have become heterogeneous and derive from multiple sources. This introduces challenges in the management and utilization of this data in software development. Although efforts are underway to create a standard format for the transmission and storage of biological data, this objective has yet to be fully realized.     

Pancreatectomized swine as a model of diabetes mellitus

The development of a model of diabetes mellitus using swine offers the potential for new investigations in the study of human diabetic complications. In particular, animal models for the study of accelerated atherosclerosis associated with diabetes are important and presently lacking. Swine were selected because they have a natural susceptibility to atherosclerosis and have plasma lipoprotein patterns which are close to those of humans. Diabetes mellitus was induced in nine miniature swine by total pancreatectomy. Following surgery, they were maintained on porcine derived insulin at doses predicated on blood glucose levels. Pancreatic enzymes were replaced by dietary supplementation. Eight of the nine pigs were pancreatectomized successfully and stabilized with insulin. After initial weight loss, the pancreatectomized pigs maintained growth rates comparable to controls. Hypoglycemia and bacterial infections were the major problems experienced. Post-operative survival ranged from 50 days to 455 days. Our study shows that swine can be pancreatectomized successfully and maintained as insulin dependent animals, presenting a realistic model for research on the complications of diabetes.     

A mouse model repository for cancer biomarker discovery

Early detection of cancer using biomarkers obtained from blood or other easily accessible tissues would have a significant impact on reducing cancer mortality. However, identifying new blood-based biomarkers has been hindered by the dynamic complexity of the human plasma proteome, confounded by genetic and environmental variability, and the scarcity of high quality controlled samples. In this report, we discuss a new paradigm for biomarker discovery through the use of mouse models. Inbred mouse models of cancer recapitulate many critical features of human cancer, while eliminating sources of environmental and genetic variability. The ability to collect samples from highly matched cases and controls under identical conditions further reduces variability which is critical for successful biomarker discovery. We describe the establishment of a repository containing tumor, plasma, urine, and other tissues from 10 different mouse models of human cancer, including two breast, two lung, two prostate, two gastrointestinal, one ovarian, and one skin tumor model. We present the overall design of this resource and its potential use by the research community for biomarker discovery.