Molecular genetics of type 2 diabetes

Type 2 diabetes is a common and chronic disease caused by interactions between genetic and environmental factors. The Goto-Kakizaki (GK) rat is a well-established genetic model of type 2 diabetes. Since several aspects of the pathophysiology of diabetes are shared between human and GK rats, we used this model to perform the first genome-wide scan for quantitative trait locus (QTL) of type 2 diabetes. A genetic linkage map with 530 microsatellite markers was constructed in a (GK x F344)F2 intercross. The map covers the whole rat genome evenly, and has a total length of 1827 centimorgans (cM), an average interval of 3 cM between markers and the maximum interval less than 20 cM. Subsequently, this map was used as a framework for the integration of 6 linkage maps and 2 radiation hybrid maps of the rat. The unified map comprises the majority of available rat markers (a total of 8627 markers) in a single map, allowing us to assemble a comparative genetic map for type 2 diabetes between human and rat. LOD scores > 2.9 for diabetes were identified in the 23 rat orthologous fragments, previously reported to be linked to diabetes in human. A total of 51 human candidate orthologous genes for type 2 diabetes were also suggested from the glucose QTLs on rat chromosomes 1, 5, and 10. Seven gender-influenced QTLs significantly affecting diabetes were assigned to chromosomes 1, 2, 5, 7, 10, and 18 with LOD scores > 4.0. These findings indicate that hyperglycemia, body weight, and insulin resistance can be genetically controlled in a sex-specific manner. A genome-wide scan for gene-gene interactions between loci indicated eleven epistatic interactions (P < 0.0001) responsible for diabetic susceptibility in the F2 rats. We longitudinally examined fasting blood glucose and insulin values, glucose tolerance, insulin secretion, body weight, metabolic responses to high-fat-diet, and glucose response to insulin injections in 230 (GK x F344)F72 intercross progeny with a 3 1 -week follow-up. We found that the incidence of diabetes in the F2 progeny significantly increased from day 31 to day 50. Four QTLs were mapped for the early development of diabetes on chromosomes 1, 2, 10, and 14 with LOD scores of 12.4, 5.1, 4.9, and 5.8. Additionally, we found that the incidence of diabetes in the F2 progeny increased after a treatment with a high fat diet (HFD). Four loci responsible for the increased incidence of diabetes after the HFD were located on chromosomes 1, 2, 11, and 14 with LOD scores of 4.8, 5.1, 4.5, and 4.7. A locus on chromosome 10 was also found to contribute to lowering scrum cholesterol levels with LOD score of 5.4. The GK alleles at this locus also resulted in decreased body weight and better glucose response to insulin injections, as well as a decreased rate of disease progression. A locus on chromosome 5 with LOD score of 4.5 was responsible for increased fasting glucose in response to pentobarbital injections as well. These findings suggest that the susceptibility genes contributing to the early-onset diabetes may also accelerate the disease progression during HFD. To our knowledge, this is the first genome- wide scan for the QTLs associated with early-onset and HFD-induced diabetes. The mitochondrial FAD-dependent glycerol-3-phosphate dehydrogenase (mtGPD) plays an important role in the regulation of insulin secretion. In the present study, the rat mtGPD gene (Gpd2) was cloned and mapped to the region of rat chromosome 3 that contains a region linked to diabetes in the GK rat. The insulin receptor gene is expressed as two alternative splice forms with or without exon 11. The encoded protein has two isoforms with discrete functional differences. In HepG2 cells, we demonstrated that dexamethasone treatment dose-dependently increased the expression of the splice form with exon 11, while low concentrations of glucose decreased the expression of this splice form. In conclusion, these results strongly indicate that the genome-wide linkage analysis combined with the follow-up study would outline the most significant loci influencing the onset and progression of diabetes. The present study suggests that the genetics of diabetes/metabolic syndrome in the GK-rat is a moving target that changes according to biological factors like age, gender, parent-of-origin, gene-gene interactions, and environmental factors like diet. Moreover, the effects of drugs in this model appear to be genetically regulated

Determination of shear strength parameters and stability analysis of waste disposal area using laboratory large-scale shear testing and engineering geologic analogy method

The engineering geological classification method has been widely used for determining the shear strength parameters of waste disposal areas in engineering practice; however the calculation error is large.It is necessary to use various methods to comprehensively estiamte the shear strength parameters of the spoil field. Taking a road waste slag yard as an example, the particle size distribution of the slag in the waste disposal area is determined by laboratory particle grading testing, and on this basis, the shear strength of the waste slag is comprehensively determined by indoor large-scale shear testing and engineering geological analogy method parameters.The shear strength is used to perform the stability analysis of the slag body. The results show that the factor of safety of the slag body is 1.369 under natural working conditions and 1.083 under heavy rain conditions, respectively. Additionally, the monitoring results are consistent with the stability analysis, proving that the determination of the shear strength parameter of the slag is reasonable and accurate, and it can provide a reference for the parameter value of the highway waste disposal engineering

Oxidative Stress: Implications for the Development of Diabetic Retinopathy and Antioxidant Therapeutic Perspectives

In recent decades, localized tissue oxidative stress has been implicated as a key component in the development of diabetic retinopathy (DR). Increasing evidence shows that oxidative stress caused by diabetes-induced metabolic abnormalities is the most common mechanism associated with the pathogenesis of DR for both type 1 and type 2 diabetes. Increase in intracellular reactive oxygen species (ROS) concentrations results in the activation of several mechanisms involved in the pathogenesis of DR. In particular, damage or dysfunction caused by oxidative stress still persists even after glycemia has been normalized. Despite considerable evidence showing the beneficial effects of antioxidants in preventing the development of retinopathy, results from large-scale clinical trials on classic antioxidants are somewhat ambiguous. Scavenging reactive radicals may not be the most ideal antioxidant strategy in DR. Advances in understanding the function of ROS in the development of DR can lead to the development of new therapeutic strategies based on the mechanisms of ROS generation and scavenging. Increasing amounts of data have demonstrated the promising prospect of antioxidant therapy and its beneficial effects in vision protection. Therefore, new strategies that utilize antioxidants as additive therapy should be implemented in the treatment of DR

A cross-layers service discovery protocol for MANET

With the rapid development of Internet, MANET is becoming a popular network organization. Automatic service discovery plays an important role in the appliance of auto-finding and using the resource in the dynamic network environment, and it also can reduce the complexity of system configuration and maintenance. This paper proposes a new service discovery protocol called SCAODV which integrates route protocol and the process of service discovery. SCAODV protocol is based on CAODV protocol. The NS2 Simulation experiments prove that SCAODV protocol not only achieve route discovery and service discovery, but also decrease control packets efficiently and keep lower delay of service discovery. SCAODV protocol also achieve security certificate based on the symmetric encryption technology between service requester and service replier in the process of service

A novel feature selection method based on probability latent semantic analysis for chinese text classification

In this paper, a novel Chinese text feature selection algorithm based on Probability latent semantic analysis (PLSA) was presented for text classification. The algorithm first employs the Expectation-maximization method (EM) to calculate the correlations between words and the latent topics for every category documents. It then selects feature words for each latent topics and merge those words to describe the corresponding category documents. At last, it merges all feature words of every category into classification feature words. An empirical comparison with other four effective feature selection methods on a benchmark data is presented in this paper. The results show that this method could get the best classification performance