To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR,MAPK14, BCL2L1, KRT18,PTPN6, CASP3, TGFBR2,AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.

A simple Trefftz-type finite element method (TFEM) is proposed for solving certain potential problems in orthotropic media. The "body force", which is induced by internal sources or sinks, may produce domain integrals in the standard Trefftz finite element formulation. This will make the advantage "only-boundary integration" of TFEM lose entirely. To overcome this difficulty, the dual reciprocity method (DRM) is employed to transfer the original problem into a homogeneous one. Then, a particular solution (PS) Trefftz-type finite element model is established based on the modified functional. Three benchmark examples are investigated by the proposed approach and compared with the analytical solutions.

The evolutionary game of co-opetition relationship between regional logistics nodes is studied in this paper. A replicator dynamic model is built to obtain the Evolutionary Stable Strategy (ESS) of the game. Then, according to the status and level of logistics nodes, the symmetric and asymmetric game models based on evolutionary game theory are proposed, respectively. The former is used to analyze the changing trends of co-opetition relationship between logistics nodes from a same layer of a logistics network. While the latter can be used to deal with the relationship forecasting problems between logistics nodes from different layers. The result of the case study reveals that the proposed models have good practicability and accuracy in dealing with the relationship forecasting problems within a regional logistics network.

The objective of the present study was to explore the factors related to the prognosis of colorectal cancer (CRC) and to establish a prognostic model for the selection of patients who might benefit from hepatic resection for metastatic CRC. A total of 293 patients undergoing liver resection for metastatic CRC (172 males and 80 females ranging in age from 26 to 80 years) were selected and clinical, pathological and outcome data were examined in this retrospective study. The prognostic index (PI) of the patients was calculated on the basis of results of multivariate analysis. Patients were stratified into different groups, with survival curves projected according to PI. The 1-, 3-, and 5-year overall survival rates were 58.3, 26.4, and 11.3%, respectively. Univariate analysis indicated that degree of primary tumor differentiation, resection margin, preoperative carcinoembryonic antigen (CEA) level, number of liver metastases, and resection of liver metastases were associated with prognosis (P < 0.05). In multivariate analysis, the last three factors were found to be independent prognostic factors. The resection of liver metastases was a favorable factor. Patients were classified into three groups according to PI, which differed significantly in survival rate (P < 0.05). The individual survival rate was evaluated based on PI. Resection of hepatic colorectal metastases may produce long-term survival and cure. The proposed PI was easy to use, was highly predictive of patient outcome, and permitted categorization of patients into treatment groups.