Network embedding, as an approach to learn low-dimensional representations of vertices, has been proved extremely useful in many applications. Lots of state-of-the-art network embedding methods based on Skip-gram framework are efficient and effective. However, these methods mainly focus on the static network embedding and cannot naturally generalize to the dynamic environment. In this paper, we propose a stable dynamic embedding framework with high efficiency. It is an extension for the Skip-gram based network embedding methods, which can keep the optimality of the objective in the Skip-gram based methods in theory. Our model can not only generalize to the new vertex representation, but also update the most affected original vertex representations during the evolvement of the network. Multi-class classification on three real-world networks demonstrates that, our model can update the vertex representations efficiently and achieve the performance of retraining simultaneously. Besides, the visualization experimental result illustrates that, our model is capable of avoiding the embedding space drifting.

The etiopathology of inflammatory bowel disease (IBD) remains elusive. Accumulating evidence suggests that the abnormality of innate and adaptive immunity responses plays an important role in intestinal inflammation. IBD including Crohn's disease (CD) and ulcerative colitis (UC) is a chronic inflammatory disease of the gastrointestinal tract, which is implicated in an inappropriate and overactive mucosal immune response to luminal flora. Traditionally, CD is regarded as a Th1-mediated inflammatory disorder while UC is regarded as a Th2-like disease. Recently, Th17 cells were identified as a new subset of T helper cells unrelated to Th1 or Th2 cells, and several cytokines [e.g. interleukin (IL)-21, IL-23] are involved in regulating their activation and differentiation. They not only play an important role in host defense against extracellular pathogens, but are also associated with the development of autoimmunity and inflammatory response such as IBD. The identification of Th17 cells helps us to explain some of the anomalies seen in the Th1/Th2 axis and has broadened our understanding of the immunopathological effects of Th17 cells in the development of IBD.

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BackgroundHepatic ischemia–reperfusion injury (HIRI) remains a pivotal clinical problem after hemorrhagic shock, transplantation, and some types of toxic hepatic injury. Apoptosis and autophagy play important roles in cell death during HIRI. It is also known that N-acetylcysteine (NAC) has significant pharmacologic effects on HIRI including elimination of reactive oxygen species (ROS) and attenuation of hepatic apoptosis. However, the effects of NAC on HIRI-induced autophagy have not been reported. In this study, we evaluated the effects of NAC on autophagy and apoptosis in HIRI, and explored the possible mechanism involved.MethodsA mouse model of segmental (70%) hepatic warm ischemia was adopted to determine hepatic injury. NAC (150 mg/kg), a hepatoprotection agent, was administered before surgery. We hypothesized that the mechanism of NAC may involve the ROS/JNK/Bcl-2 pathway. We evaluated the expression of JNK, P-JNK, Bcl-2, Beclin 1 and LC3 by western blotting and immunohistochemical staining. Autophagosomes were evaluated by transmission electron microscopy (TEM).ResultsWe found that ALT, AST and pathological changes were significantly improved in the NAC group. Western blotting analysis showed that the expression levels of Beclin 1 and LC3 were significantly decreased in NAC-treated mice. In addition, JNK, p-JNK, Bax, TNF-α, NF-κB, IL2, IL6 and levels were also decreased in NAC-treated mice.ConclusionNAC can prevent HIRI-induced autophagy and apoptosis by influencing the JNK signal pathway. The mechanism is likely to involve attenuation of JNK and p-JNK via scavenged ROS, an indirect increase in Bcl-2 level, and finally an alteration in the balance of Beclin 1 and Bcl-2.