BACKGROUND:Bone marrow mesenchymal stem cel transplantation has not been thoroughly reported on its effects on apoptosis in hepatoma carcinoma cel s and inflammatory factor level.
OBJECTIVE:To investigate the effect of rat bone marrow mesenchymal stem cel s on dynamic change of inflammatory factors and cel apoptosis during hepatocarcinogenesis.
METHODS:Sixty healthy Sprague-Dawley rats were divided randomly into healthy group (n=30), control group (n=30) and transplantation group (n=30). Healthy group was given ordinary feed and normal water, while other groups were given diethylnitrosamine solution in drinking water to induce liver cancer models. Then, rats in the transplantation group were subjected to bone marrow mesenchymal stem cel transplantation via the tail vein. Two weeks after cel transplantation, CXCL5, interleukin-8 and interleukin-6 levels were tested by ELISA, mRNA level of hepatocyte nuclear factor 1αdetected by RT-PCR, expression of Bcl-2 and Bax in liver tissue measured by immunohistochemical method, and liver cancer cel apoptosis index detected by TUNEL technique.
RESULTS AND CONCLUSION:After modeling, the expressions of CXCL5, interleukin-8 and interleukin-6 in the control group were significantly higher than those in the healthy group (P<0.05), while these indexes were reduced significantly after bone marrow mesenchymal stem cel transplantation (P<0.05) and close to the normal levels (P>0.05). Bone marrow mesenchymal stem cel transplantation significantly up-regulated the mRNA level of hepatocyte nuclear factor 1αin the liver tissue that was decreased obviously after modeling (P<0.05). In addition, the expression of Bcl-2 was reduced, while the expression of Bax and the apoptosis index increased significantly in the transplantation group compared with the control group (P<0.05). These findings indicate that bone marrow mesenchymal stem cel transplantation contributes to hepatocyte differentiation and regeneration in liver cancer rats by reducing serum inflammatory factor levels and promoting apoptosis in hepatoma carcinoma cel s.

In this paper, we present a brief review of the existing computational methods for predicting proteome-wide protein-protein interaction networks from high-throughput data. The availability of various types of omics data provides great opportunity and also unprecedented challenge to infer the interactome in cells. Reconstructing the interactome or interaction network is a crucial step for studying the functional relationship among proteins and the involved biological processes. The protein interaction network will provide valuable resources and alternatives to decipher the mechanisms of these functionally interacting elements as well as the running system of cellular operations. In this paper, we describe the main steps of predicting protein-protein interaction networks and categorize the available approaches to couple the physical and functional linkages. The future topics and the analyses beyond prediction are also discussed and concluded.
Algorithms ; Artificial Intelligence ; Humans ; Models, Biological ; Protein Interaction Domains and Motifs ; Protein Interaction Mapping ; Protein Interaction Maps ; Proteome ; genetics ; metabolism ; Proteomics ; Systems Biology