We recently showed that activation of G protein-coupled receptor 119 (GPR119) (also termed glucose dependent insulinotropic receptor) improves glucose homeostasis via direct cAMP-mediated enhancement of glucose-dependent insulin release in pancreatic beta-cells. Here we show that GPR119 also stimulates incretin hormone release and thus may regulate glucose homeostasis by this additional mechanism. GPR119 mRNA was found to be expressed at significant levels in intestinal subregions that produce glucose-dependent insulinotropic peptide and glucagon-like peptide (GLP)-1. Furthermore, in situ hybridization studies indicated that most GLP-1-producing cells coexpress GPR119 mRNA. In GLUTag cells, a well-established model of intestinal L-cell function, the potent GPR119 agonist AR231453 stimulated cAMP accumulation and GLP-1 release. When administered in mice, AR231453 increased active GLP-1 levels within 2 min after oral glucose delivery and substantially enhanced total glucose-dependent insulinotropic peptide levels. Blockade of GLP-1 receptor signaling with exendin(9-39) reduced the ability of AR231453 to improve glucose tolerance in mice. Conversely, combined administration of AR231453 and the DPP-4 inhibitor sitagliptin to wild-type mice significantly amplified both plasma GLP-1 levels and oral glucose tolerance, relative to either agent alone. In mice lacking GPR119, no such enhancement was seen. Thus, GPR119 regulates glucose tolerance by acting on intestinal endocrine cells as well as pancreatic beta-cells. These data also suggest that combined stimulation of incretin hormone release and protection against incretin hormone degradation may be an effective antidiabetic strategy.

Pancreatic ␤-cell dysfunction is a hallmark event in the pathogenesis of type 2 diabetes. Injectable peptide agonists of the glucagon-like peptide 1 (GLP-1) receptor have shown significant promise as antidiabetic agents by virtue of their ability to amplify glucose-dependent insulin release and preserve pancreatic ␤-cell mass. These effects are mediated via stimulation of cAMP through ␤-cell GLP-1 receptors. We report that the G␣ s -coupled receptor GPR119 is largely restricted to insulin-producing ␤-cells of pancreatic islets. Additionally, we show here that GPR119 functions as a glucose-dependent insulinotropic receptor. Unlike receptors for GLP-1 and other peptides that mediate enhanced glucose-dependent insulin release, GPR119 was suitable for the development of potent, orally active, small-molecule agonists. The GPR119-specific agonist AR231453 significantly increased cAMP accumulation and insulin release in both HIT-T15 cells and rodent islets. In both cases, loss of GPR119 rendered AR231453 inactive. AR231453 also enhanced glucose-dependent insulin release in vivo and improved oral glucose tolerance in wild-type mice but not in GPR119-deficient mice. Diabetic KK/A y mice were also highly responsive to AR231453. Orally active GPR119 agonists may offer significant promise as novel antihyperglycemic agents acting in a glucose-dependent fashion. (Endocrinology

Financial credit scoring is one of the most crucial processes in the finance industry sector to be able to assess the credit-worthiness of individuals and enterprises. Various statistics-based machine learning techniques have been employed for this task. "Curse of Dimensionality" is still a significant challenge in machine learning techniques. Some research has been carried out on Feature Selection (FS) using genetic algorithm as wrapper to improve the performance of credit scoring models. However, the challenge lies in finding an overall best method in credit scoring problems and improving the time-consuming process of feature selection. In this study, the credit scoring problem is investigated through feature selection to improve classification performance. This work proposes a novel approach to feature selection in credit scoring applications, called as Information Gain Directed Feature Selection algorithm (IGDFS), which performs the ranking of features based on information gain, propagates the top m features through the GA wrapper (GAW) algorithm using

G protein-coupled receptor 119 (GPR119) is largely restricted to pancreatic insulin-producing beta-cells and intestinal glucagon-like peptide-1-producing L-cells. Synthetic agonists of this receptor elicit glucose-dependent release of these endocrine factors, thereby enhancing glycemic control. Oleoylethanolamide also activates GPR119, but it remains unclear whether endogenous production of this lipid modulates GPR119 activity under normal or dysglycemic conditions. We show here that a relatively diverse set of lipid amides activate GPR119. Among these, the endovallinoid N-oleoyldopamine (OLDA) stimulated cAMP accumulation in GPR119-transfected cells as effectively as oleoylethanolamide and the previously described synthetic agonist AR231453. None of these lipid amides increased cAMP in control-transfected cells or in cells transfected with a number of other G protein-coupled receptors. OLDA stimulated both cAMP accumulation and insulin release in HIT-T15 cells, which express GPR119 endogenously, and in GPR119-transfected RIN-5F cells. Oral administration of OLDA to C57bl/6 mice elicited significant improvement in glucose tolerance, whereas GPR119-deficient mice were essentially unresponsive. OLDA also acutely elevated plasma gastric inhibitory peptide levels, a known hallmark of GPR119 activation. OLDA represents a possible paracrine modulator of GPR119 in pancreatic islets, where markers of dopamine synthesis correlated well with GPR119 expression. However, no such correlation was seen in the colon. Collectively, these studies indicate that multiple, distinct classes of lipid amides, acting via GPR119, may be important modulators of glucose homeostasis.

Abstract-Internet of Things (IoT) has given rise to the fourth industrial revolution (Industrie 4.0), and it brings great benefits by connecting people, processes and data. However, cybersecurity has become a critical challenge in the IoT enabled cyber physical systems, from connected supply chain, Big Data produced by huge amount of IoT devices, to industry control systems. Evolutionary computation combining with other computational intelligence will play an important role for cybersecurity, such as artificial immune mechanism for IoT security architecture, data mining/fusion in IoT enabled cyber physical systems, and data driven cybersecurity. This paper provides an overview of security challenges in IoT enabled cyber-physical systems and what evolutionary computation and other computational intelligence technology could contribute for the challenges. The overview could provide clues and guidance for research in IoT security with computational intelligence.