GENERATION OF TRANSGENIC MICE FOR IN VIVO DETECTION OF INSULIN-CONTAINING GRANULE EXOCYTOSIS AND QUANTIFICATION OF INSULIN SECRETION

Insulin secretion is a complex and highly regulated process.Although much progress has been made in understanding the cellular mechanisms of insulin secretion and regulation,it remains unclear how conclusions from these studies apply to living animals.That few studies have been done to address these issues is largely due to the lack of suitable tools in detecting secretory events at high spatial and temporal resolution in vivo.When combined with genetically encoded biosensor,optical imaging is a powerful tool for visualization of molecular events in vivo.In this study,we generated a DNA construct encoding a secretory granule resident protein that is linked with two spectrally separate fluorescent proteins,a highly pH-sensitive green pHluorin on the intra-granular side and a red mCherry in the cytosol.Upon exocytosis of secretory granules,the dim pHluorin inside the acidic secretory granules became highly fluorescent outside the cells at neutral pH,while mCherry fluorescence remained constant in the process,thus allowing ratiometric quantification of insulin secretory events.Furthermore,mCherry fluorescence enabled tracking the movement of secretory granules in living cells.We validated this approach in insulin-secreting cells,and generated a transgenic mouse line expressing the optical sensor specifically in pancreaticβ-cells.The transgenic mice will be a useful tool for future investigations of molecular mechanism of insulin secretion in vitro and in vivo.

g-Good-neighbor conditional diagnosability of star graph networks under PMC model and MM＊ model

Diagnosability of a multiprocessor system is an important study topic. S. L. Peng, C. K. Lin, J. J. M. Tan, and L. H. Hsu [Appl. Math. Comput., 2012, 218（21）： 10406-10412] proposed a new measure for fault diagnosis of the system, which is called the 9-good-neighbor conditional diagnosability that restrains every fault-free node containing at least 9 fault-free neighbors. As a famous topological structure of intereonnection networks, the n-dimensional star graph Sn has many good properties. In this paper, we establish the 9_good-neighbor conditional diagnosability of Sn under the PMC model and MM＊ model.

The synergy of Helicobacter pylori and lipid metabolic disorders in induction of Th17-related cytokines in human gastric cancer

Aim:To study the impact of Helicobacter pylori(H.pylori)and lipid metabolic disorder on the expression of Th17-related cytokines in gastric cancer(GC).Methods:GC specimens were randomly collected from 42 patients,of whom 15 had H.pylori infection and 27 were without.Tumor RNA was extracted for reverse transcription quantitative polymerase chain reaction quantification of gene expression.Results:The mRNA levels of interleukin(IL)-6 and leptin,which are known to regulate Th17 differentiation,were upregulated by 20 and 6 folds,respectively,in H.pylori-infected compared to uninfected patients.IL-17A and granulocyte-macrophage colony-stimulating factor,two cytokines produced by Th17 cells,were 5-and 6-fold higher in tumors with H.pylori infection,respectively.Consistently,RORγt,a transcription factor regulating Th17 differentiation,was increased 6-fold in H.pylori-positive vs.negative tumors.Further elevation of RORγt was seen in advanced H.pylori-associated tumors.In addition,H.pylori infection was also associated with enhanced expression of CXCL1(5 folds),chemotactic factor capable of driving bone marrow-derived immature myeloid cells.Interestingly,we observed that H.pylori-associated increase of IL-17A was enhanced in the group with higher plasma triglycerides.Conclusion:The findings demonstrate a cross-talk and synergistic role of H.pylori infection and abnormal lipid metabolism in GC development,at least partly via cooperative induction of Th17 differentiation and activation.