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      A network pharmacology approach to investigate the mechanisms of Si-Jun-Zi decoction in the treatment of gastric precancerous lesions

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Highlights

          The Si-Jun-Zi decoction may exert a therapeutic effect on gastric precancerous lesions by intervening in the mucosal inflammation, cell apoptosis process, and cell proliferation.

          Editor’s Summary

          Gastric mucosal inflammation has the potential to promote the proliferation of gastric mucosal epithelial cells and inhibit their apoptosis. However, Si-Jun-Zi decoction may exert a therapeutic effect on these process via the multi-target network level.

          Abstract

          Objective: To find out the potential mechanisms of Si-Jun-Zi (SJZ) decoction in the treatment of gastric precancerous lesions (GPL). Methods: A network pharmacology approach was used to analyze the active compounds, drug targets and interacting pathways of SJZ decoction in treating GPL. The compounds and predicted targets of SJZ decoction were screened from TCMSP, and the disease targets were obtained from GeneCards. The therapeutic mechanisms of action of the SJZ decoction were analyzed by gene ontology (GO) enrichment, Kyoto encyclopedia of genes and genomes pathway enrichment analyses. Results: The results show that 111 compounds and 90 targets were obtained in this work. These targets were further mapped to 654 GO biological process terms and 21 remarkably pathways. Active compounds, targets, and pathways were used to construct a compound-target network, a target-pathways network, and an integrated GPL pathway. These results indicated that SJZ decoction may treat the dysfunctions of GPL mainly from intervening in the mucosal inflammation, cell apoptosis process, and cell proliferation. Conclusion: This work provided a novel approach to understand the pathogenesis of GPL and revealed the therapeutic mechanisms of SJZ decoction, which facilitate the modernization of herbal medicine for complex diseases in the future.

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          Most cited references 88

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            KEGG: kyoto encyclopedia of genes and genomes.

             M Kanehisa (2000)
            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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              Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool

              Background System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Results Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Conclusions Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr.
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                Author and article information

                Contributors
                Journal
                TMR Editorial Board
                Traditional Medicine Research
                TMR Editorial Board (Jintang road, 99, Hedong district Tianjin,China, 300170 )
                2413-3973
                5 November 2018
                5 November 2018
                : 3
                : 6
                : 273-285
                Affiliations
                1Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
                2The First People's Hospital of Xiangtan City, Xiangtan, Hunan, China.
                3Lin’an Hospital of Traditional Chinese Medicine, Lin’an, Zhejiang, China.
                4Chengdu University of Traditional Chinese Medicine, Chengdu, China.
                5Sichuan Second Hospital of Traditional Chinese Medicine, Chengdu, Sichuan China.
                Author notes
                *Correspondence to: Yong Zhang, Sichuan Second Hospital of Traditional Chinese Medicine, Chengdu, Sichuan China. E-mail: 568958305@ 123456qq.com .
                Article
                2413-3973-3-6-273
                10.12032/TMR201814087

                This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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                Modernization of Traditional Medicine

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