As a chronic inflammatory disease of the liver, the pathogenic mechanisms of autoimmune hepatitis (AIH) have not yet been elucidated, with prognosis and diagnosis remaining unsatisfied. Currently the only viable treatments of AIH are immunosuppressant application and liver transplantation. It is considered that lack of good animal AIH models is the main reason for the shortage of a simple and efficient cure. The Concanavalin A (Con A) model is a typical and well established model for investigating T-cell and macrophage dependent liver injury in mice, which closely mimics the pathogenesis mechanisms and pathological changes of patients, and is regarded as the best experimental model for AIH research so far. In this paper we elucidated the pathogenic mechanisms of AIH and the evolution of relative animal models. We go on to further focus on Con A-induced liver injury from the point of immunological mechanisms and the change of cytokine levels. Finally, we manifested the clinical significance of the AIH animal models and the challenges they would meet during their future development.

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Intrinsically disordered proteins or protein regions are involved in key biological processes including regulation of transcription, signal transduction, and alternative splicing. Accurately predicting order/disorder regions ab initio from the protein sequence is a prerequisite step for further analysis of functions and mechanisms for these disordered regions. This work presents a learning method, weighted DeepCNF (Deep Convolutional Neural Fields), to improve the accuracy of order/disorder prediction by exploiting the long-range sequential information and the interdependency between adjacent order/disorder labels and by assigning different weights for each label during training and prediction to solve the label imbalance issue. Evaluated by the CASP9 and CASP10 targets, our method obtains 0.855 and 0.898 AUC values, which are higher than the state-of-the-art single ab initio predictors.

BackgroundHepatocellular carcinoma (HCC) is one of most common and aggressive human malignancies in the world, especially, in eastern Asia, and its mortality is very high at any phase. We want to investigate mechanism of niclosamide inducing cell apoptosis in HCC.MethodsTwo hepatoma cell lines were used to evaluate activity of niclosamide inducing cell apoptosis and study its mechanism. Quantitative real-time PCR and western blotting were used in analysis of genes expression or protein active regulated by niclosamide.ResultsNiclosamide remarkably induced cell apoptosis in hepatoma cells. Furthermore, our study revealed that RNA-dependent protein kinase-like kinase (PERK) is activated and its expression is up-regulated in HCC cells which are exposed to niclosamide. niclosamide also significantly increase activating transcription factor 3 (ATF3), activating transcription factor 4 (ATF4) and CCAAT/enhancer-binding protein-homologous protein (CHOP) expression in HCC cells. It’s suggested that the function of niclosamide was abrogated by PERK inhibitor or absent ATF3. Expression of PERK and CHOP is correlated with ATF3 level in the cells.ConclusionTaken together, our results indicate that ATF3 plays an integral role in ER stress activated and cell apoptosis induced by niclosamide in HCC cells. In this study, the new mechanism of niclosamide as anti-cancer we investigated, too.

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