Protein kinase C (Pkc)-δ mediates arginine-induced glucagon secretion in pancreatic α-cells

The pathophysiology of type 2 diabetes involves insulin and glucagon. Protein kinase C (Pkc)-δ, a serine-threonine kinase, is ubiquitously expressed and involved in regulating cell death and proliferation. However, the role of Pkcδ in regulating glucagon secretion in pancreatic α-cells remains unclear. Therefore, this study aimed to elucidate the physiological role of Pkcδ in glucagon secretion from pancreatic α-cells. Glucagon secretions were investigated in Pkcδ-knockdown InR1G9 cells and pancreatic α-cell-specific Pkcδ-knockout (αPkcδKO) mice. Knockdown of Pkcδ in the glucagon-secreting cell line InR1G9 cells reduced glucagon secretion. The basic amino acid arginine enhances glucagon secretion via voltage-dependent calcium channels (VDCC). Furthermore, we showed that arginine increased Pkcδ phosphorylation at Th

芸術科学会論文 誌 Vol.6 No.1 pp.21-36 Point Splatting Based on Translucent Shadow Mapping and Hierarchical Bucket Sorting

clouds (building, basin) in an outdoor scene, (b) mixing the surface model (skull) and volume data (head) in medical imaging, (c) visualizing the volume data (retina), the translucent surface (iris) and the opaque surface (lens) in an artificial eye. In this paper we present our solution for shadow generation, visibility sorting and GPU based shading of translucent point data for point based rendering. Our Translucent Shadow Mapping Algorithm uses a spherical coordinate system and solves the distancebased sorting, transparency calculation, shadow mapping, omni-directional mapping and light intensity attenuation problems in one step. We also propose a novel algorithm for visibility sorting of unstructured point data using the Hierarchical Bucket Sorting approach. This algorithm uses less memory and produces precise back-to-front ordered slices compared to previous methods. Finally, the shading calculations are performed in the GPU, using the rendering-oriented attributes of the point splats. Furthermore, we demonstrate the efficiency and flexibility of our novel approach of point splatting by showing several rendering results for visualizing mixed 3D data sets