Objective Biliary epithelial cell (BEC) proliferated actively induced by ischemia-type biliary lesion (ITBL), which played an important role in the development of biliary complication after orthortopic liver transplantation (OLT). The aims of this study is to provide novel method to protect the liver endured cold preservation and reperfusion injury (CPRI) and reduce posttransplant biliary complication, and explore its possible mechanism.Methods Based on constructed OLT models for studying ITBL, the hepatic oval cell (HOC) or the IL-13 genemodified HOC to the portal vein of the recipient 〔OLT+HOC group and OLT+IL-13· HOC group〕 were-transfused, then the pathology change, the liver function and the expressions of the α-smooth muscle actin (αSMA) and Heme oxygenase-1 (HO-1) mRNA of the transplanted liver of CPRI were observed, the proliferation of BEC and survival rate of the recipients were also observed. Results The BEC injury was showed in grafts with prolonged ischemia time, characterized by induction of BEC proliferation, liver function injury and cholestasis sign reflecting the increase of serum ALT, AST and TBIL. The OLT+IL-13·HOC group had better results than OLT and OLT+HOC group, which indicated the OLT+IL-13·HOC group had low level of expression α-SMA (after operation 7 d, Plt;0.05) and proliferation of BEC (after operation 3 d, Plt;0.05). The expressions of HO-1 mRNA were higher in OLT+IL-13·HOC group than in other groups. The survival rate of OLT group was lower than that of the OLT+IL-13·HOC group and sham operation group (Plt;0.05).Conclusion High expression level of IL-13 in recipient rats could promote the expression of HO-1 mRNA in transplant liver, and profit to protection donor liver, and recover of the liver function after liver transplantation. It perhaps is the mechanism of protective effect of IL-13 on graft that stimulate the expression of HO-1 mRNA significantly.
It is of great clinical significance in the differential diagnosis of primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) because there are enormous differences between them in terms of therapeutic regimens. In this paper, we propose a system based on sparse representation for automatic classification of PCNSL and GBM. The proposed system distinguishes the two tumors by using of the different texture detail information of the two tumors on T1 contrast magnetic resonance imaging (MRI) images. First, inspired by the process of radiomics, we designed a dictionary learning and sparse representation-based method to extract texture information, and with this approach, the tumors with different volume and shape were transformed into 968 quantitative texture features. Next, aiming at the problem of the redundancy in the extracted features, feature selection based on iterative sparse representation was set up to select some key texture features with high stability and discrimination. Finally, the selected key features are used for differentiation based on sparse representation classification (SRC) method. By using ten-fold cross-validation method, the differentiation based on the proposed approach presents accuracy of 96.36%, sensitivity 96.30%, and specificity 96.43%. Experimental results show that our approach not only effectively distinguish the two tumors but also has strong robustness in practical application since it avoids the process of parameter extraction on advanced MRI images.
Objective To develop hepatic surgical planning software for hepatic operation on deciding the rational operational scheme and simulating procedures before the operation to accomplish the precise liver resection and decrease the operational risk. Methods3D-econstruction of liver was restored from spiral computed tomography (CT) data by using LiVirtue software. The liver and its anatomic structures were reconstructed to illuminate the location of the tumor and its related vessels to design a rational operational scheme. The virtul results, such as liver volume, hepatic sections, anatomy of portal vein and hepatic veins or possible operation plans, were compared with the actual situations during the operations. Results3D models of liver, tumor and their relative vessels were reconstructed successfully. Preoperative planning and intra-perative navigation based on the models ensured the safety of liver resection in our 32 cases of right lobe tumors. This preoperative simulation allowed surgeons to dissect the liver with reduced complications. These models could be also viewed and manipulated on personal computers.ConclusionThe LiVirtue is very helpful in the hepatic surgery, for clearly disclosing hepatic structures, rationally deciding operation schemes, virtually simulating the operations. This preoperative estimation from 3D model of liver benefits a lot to complicated liver resection.