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Objective To study the effect of marein on the damage of rat myocardial cell line (H9c2) induced by high glucose. Methods H9c2 cells were divided into Ctrl group, high glucose (30 mmol/L) injury model group and marein (25, 50, 100 μmol/L) intervention group. The viability of H9c2 cells was detected by MTT method. Western blot was used to detect the protein expression level of LC-3Ⅱ/Ⅰ,p62 and mTOR. Results Compared with the Ctrl group, the viability of H9c2 cells in the model group was decreased (P＜ 0.01) and the viability of H9c2 cells in the marein group was significantly increased (P＜ 0.01). The protein expression of LC-3Ⅱ/Ⅰ in model group was decreased (P＜ 0.05) and the level of p62 and mTOR was increased (P＜ 0.01). The level of LC-3Ⅱ/Ⅰ in the marein group was increased, while the level of p62 and mTOR was decreased (P＜ 0.01). The protein expression was more obvious with the increase of concentration. Conclusions Marein can affect the expression of autophagy associated proteins in cardiomyocyte injury induced by high glucose.

aimin Zhang, Zhenzong Tan, Hezhao Zhao, Hao Sun Chongqing University Cancer Hospital Gastrointestinal Department, Chongqing, 400000, People's Republic of ChinaCorrespondence: Hao Sun; Hezhao ZhaoChongqing University Cancer Hospital, Gastrointestinal Department, Chongqing, 400000, People's Republic of ChinaEmail [email protected] ; [email protected] Background: Growing evidence indicated that circRNAs played major roles in the progression of human cancer. Nevertheless, the molecular mechanism and effects of circTMCO3 in GC are still unclear. Methods: First, qRT-PCR was used to evaluate the levels of circTMCO3 from GC tissues, GC cells, normal tissues and gastric epithelial cells. Then, the GC cells were transfected to analyze the proliferation, migration and invasion of GC cells by MTT, colony formation and transwell assays. Next, the expressions of miR-577 and RAB14 in GC tissues and cells were examined by qRT-PCR following transfection. The target interaction of circTMCO3-miR-577 and miR-577-RAB14 was explored by the dual-luciferase reporter and RNA pull-down assays. In the end, the growth and viability of GC cells were detected by MTT, colony formation and transwell assays, respectively, following the transfection of GC cells. Results: In this research, we found circTMCO3 expressions are significantly up-regulated in GC tissues and cells compared with the normal tissues and gastric epithelial cells. We discovered that the knockdown of circTMCO3 remarkably inhibits the proliferation, migration and invasion of GC cells. Besides, through the prediction of binding sites between circTMCO3, miR-577 and RAB14, we discovered miR-577 is a target of circTMCO3 while RAB14 is a target gene of miR-577. Finally, the results demonstrate the overexpression of miR-577 and the silence of RAB14 could inhibit the effects of circTMCO3 on proliferation, migration and invasion in GC cells. Conclusion: circTMCO3 accelerated the growth and migration of GC cells by regulating miR-577/RAB14 axis. [ABSTRACT FROM AUTHOR]

As the core component of the smart grid, advanced metering infrastructure (AMI) is responsible for automated billing, demand response, load forecasting, management, etc. The jamming attack poses a serious threat to the AMI communication networks, especially the neighborhood area network where wireless technologies are widely adopted to connect a tremendous amount of smart meters. An attacker can easily build a jammer using a software-defined radio and jam the wireless communications between smart meters and local controllers, causing failures of on-line monitoring and state estimation. Accurate jammer localization is the first step for defending AMIs against jamming attacks. In this paper, we propose JamCatcher, a mobile jammer localization scheme for defending the AMI. Unlike existing jammer localization schemes, which only consider stationary jammers and usually require a high density of anchor nodes, the proposed scheme utilizes a tracker and can localize a mobile jammer with sparse anchor nodes. The time delay of data transmission is also considered, and the jammer localization process is divided into two stages, i.e., far-field chasing stage and near-field capturing stage. Different localization algorithms are developed for each stage. The proposed method has been tested with data from both simulation and real-world experiment. The results demonstrate that JamCatcher outperforms existing jammer localization algorithms with a limited number of anchor nodes in the AMI scenario. [ABSTRACT FROM AUTHOR]