NLRC5, the largest member of nucleotide-binding and oligomerization domain (NOD)-like receptor (NLR) family, has been reported to regulate immune responses and is associated with chronic inflammatory diseases. However, the biological function of NLRC5 in hepatocellular carcinoma (HCC) has not yet been well demonstrated. In this study, the role of NLRC5 in hepatocellular carcinoma cell proliferation, migration and invasion capacities was evaluated by using MTT, flow cytometry, wound healing, transwell assay, and tumor formation assay in nude mice. Western blot analysis and qPCR assay were performed to assess NLRC5 interacting with the activation of Wnt/β-catenin signaling pathway. Here, we demonstrate that NLRC5 was highly expressed in HCC. Knockdown of NLRC5 significantly inhibited cell proliferation, migration, invasion and the tumor formation in nude mice, and arrested the cell cycle at G0/G1 phase. Furthermore, overexpression of NLRC5 promoted the proliferation, migration and invasion of HCC cells in vitro. Interestingly, we found that up-regulation of NLRC5 not only positively correlates with the increase of β-catenin but also coordinates the activation of downstream Wnt/β-catenin signaling pathway. Thus, our findings suggest that NLRC5 may play an important role in progression of HCC and provide a potential therapeutic value in this tumor.

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Linear sensor networks (LSNs) have recently attracted increasing attention due to the vast requirements on the monitoring and surveillance of a structure or area with a linear topology. However, there is little work on the network modeling and analysis based on a duty-cycling MAC protocol for LSNs. In this paper, we model a duty-cycling MAC with a pipelinedscheduling feature for an LSN, where each node is responsible for monitoring a certain area and can generate packets according to its sensed results. Based on the model, we analyze the network performance in terms of the system throughput, active time ratio per cycle of each node, and packet delivery latency. Through the extensive OPNET-based simulations, we validate the model and reveal the dependency of the network performance on various system parameters. Besides enabling the effective estimation of the protocol performance by using our model, we believe that our model and analysis could provide an insightful understanding on the behavior of a duty-cycling MAC protocol and aid its design and optimization for a multi-hop LSN.

Background: Valproic acid (VPA) as a widely used primary medication in the treatment of epilepsy is associated with reversible or irreversible hepatotoxicity. Long-term VPA therapy is also related to increased risk for the development of non-alcoholic fatty liver disease (NAFLD). In this review, metabolic elimination pathways of VPA in the liver and underlying mechanisms of VPA-induced hepatotoxicity are discussed. Methods: We searched in PubMed for manuscripts published in English, combining terms such as “Valproic acid”, “hepatotoxicity”, “liver injury”, and “mechanisms”. The data of screened papers were analyzed and summarized. Results: The formation of VPA reactive metabolites, inhibition of fatty acid β-oxidation, excessive oxidative stress and genetic variants of some enzymes, such as CPS1, POLG, GSTs, SOD2, UGTs and CYPs genes, have been reported to be associated with VPA hepatotoxicity. Furthermore, carnitine supplementation and antioxidants administration proved to be positive treatment strategies for VPA-induced hepatotoxicity. Conclusion: Therapeutic drug monitoring (TDM) and routine liver biochemistry monitoring during VPA-therapy, as well as genotype screening for certain patients before VPA administration, could improve the safety profile of this antiepileptic drug.

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