Cinaciguat prevents neointima formation after arterial injury by decreasing vascular smooth muscle cell migration and proliferation.

AIMS: Vascular smooth muscle cell (VSMC) migration, proliferation and remodeling of the extracellular matrix contribute to lumen loss after arterial injury leading to restenosis. Several studies indicated the role of the cyclic guanosine monophosphate signaling in neointimal formation. Cinaciguat, the novel soluble guanylate cyclase activator, currently being in phase IIb clinical trial, has been shown to exert antiplatelet and anti-remodeling effects in animal models of vascular pathology. In this study we investigated the effects of cinaciguat on post-injury arterial stenosis. METHODS AND RESULTS: Male Sprague-Dawley rats (n=100) underwent endothelial denudation by wire injury of the right common carotid artery. Cinaciguat (10mg/kg/day orally) were administered to 50 rats (1-, 2-, 3-day and 1-, 3-week treatment time), while 50 rats received placebo. A 3-week treatment resulted in a significantly reduced vascular stenosis (17.53 ± 10.84% in the treatment group vs. 43.25 ± 30.83% in the control wire injury group) and neointima/media area ratio (0.45 ± 0.32 in the treatment group vs. 1.09 ± 0.69 in the control wire injury group). By using quantitative real-time PCR, Western blot and immunohistochemistry, matrix-metallopreoteinase-9 (MMP-9) was found to be upregulated in the control-injured carotids over the whole follow-up, and cinaciguat significantly decreased MMP-9 expression by 3 weeks. As assessed by protein immunoblot, injury-induced local decrease of soluble guanylate cyclase ß1 subunit could be recovered by cinaciguat. In vitro wound healing assay with VSMCs revealed dose-dependent antimigratory and antiproliferative effects of cinaciguat. Plasma level of cyclic guanosine monophosphate was significantly elevated after 3 weeks of treatment. CONCLUSION: Our results show that cinaciguat prevents injury-induced neointimal hyperplasia by decreasing VSMC migration and proliferation through the regulation of MMP-9.

Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data.

MOTIVATION: Metabolomics is a rapidly evolving field that holds promise to provide insights into genotype-phenotype relationships in cancers, diabetes and other complex diseases. One of the major informatics challenges is providing tools that link metabolite data with other types of high-throughput molecular data (e.g. transcriptomics, proteomics), and incorporate prior knowledge of pathways and molecular interactions. RESULTS: We describe a new, substantially redesigned version of our tool Metscape that allows users to enter experimental data for metabolites, genes and pathways and display them in the context of relevant metabolic networks. Metscape 2 uses an internal relational database that integrates data from KEGG and EHMN databases. The new version of the tool allows users to identify enriched pathways from expression profiling data, build and analyze the networks of genes and metabolites, and visualize changes in the gene/metabolite data. We demonstrate the applications of Metscape to annotate molecular pathways for human and mouse metabolites implicated in the pathogenesis of sepsis-induced acute lung injury, for the analysis of gene expression and metabolite data from pancreatic ductal adenocarcinoma, and for identification of the candidate metabolites involved in cancer and inflammation. AVAILABILITY: Metscape is part of the National Institutes of Health-supported National Center for Integrative Biomedical Informatics (NCIBI) suite of tools, freely available at http://metscape.ncibi.org. It can be downloaded from http://cytoscape.org or installed via Cytoscape plugin manager. CONTACT: metscape-help@umich.edu; akarnovs@umich.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Metscape: a Cytoscape plug-in for visualizing and interpreting metabolomic data in the context of human metabolic networks.

SUMMARY: Metscape is a plug-in for Cytoscape, used to visualize and interpret metabolomic data in the context of human metabolic networks. We have developed a metabolite database by extracting and integrating information from several public sources. By querying this database, Metscape allows users to trace the connections between metabolites and genes, visualize compound networks and display compound structures as well as information for reactions, enzymes, genes and pathways. Applying the pathway filter, users can create subnetworks that consist of compounds and reactions from a given pathway. Metscape allows users to upload experimental data, and visualize and explore compound networks over time, or experimental conditions. Color and size of the nodes are used to visualize these dynamic changes. Metscape can display the entire metabolic network or any of the pathway-specific networks that exist in the database. AVAILABILITY: Metscape can be installed from within Cytoscape 2.6.x under 'Network and Attribute I/O' category. For more information, please visit http://metscape.ncibi.org/tryplugin.html.

Integrating and annotating the interactome using the MiMI plugin for cytoscape.

UNLABELLED: The MiMI molecular interaction repository integrates data from multiple sources, resolves interactions to standard gene names and symbols, links to annotation data from GO, MeSH and PubMed and normalizes the descriptions of interaction type. Here, we describe a Cytoscape plugin that retrieves interaction and annotation data from MiMI and links out to multiple data sources and tools. Community annotation of the interactome is supported. AVAILABILITY: MiMI plugin v3.0.1 can be installed from within Cytoscape 2.6 using the Cytoscape plugin manager in 'Network and Attribute I/0' category. The plugin is also preloaded when Cytoscape is launched using Java WebStart at http://mimi.ncibi.org by querying a gene and clicking 'View in MiMI Plugin for Cytoscape' link.

Michigan molecular interactions r2: from interacting proteins to pathways.

Molecular interaction data exists in a number of repositories, each with its own data format, molecule identifier and information coverage. Michigan molecular interactions (MiMI) assists scientists searching through this profusion of molecular interaction data. The original release of MiMI gathered data from well-known protein interaction databases, and deep merged this information while keeping track of provenance. Based on the feedback received from users, MiMI has been completely redesigned. This article describes the resulting MiMI Release 2 (MiMIr2). New functionality includes extension from proteins to genes and to pathways; identification of highlighted sentences in source publications; seamless two-way linkage with Cytoscape; query facilities based on MeSH/GO terms and other concepts; approximate graph matching to find relevant pathways; support for querying in bulk; and a user focus-group driven interface design. MiMI is part of the NIH's; National Center for Integrative Biomedical Informatics (NCIBI) and is publicly available at: http://mimi.ncibi.org.

Michigan Molecular Interactions (MiMI): putting the jigsaw puzzle together.

Protein interaction data exists in a number of repositories. Each repository has its own data format, molecule identifier and supplementary information. Michigan Molecular Interactions (MiMI) assists scientists searching through this overwhelming amount of protein interaction data. MiMI gathers data from well-known protein interaction databases and deep-merges the information. Utilizing an identity function, molecules that may have different identifiers but represent the same real-world object are merged. Thus, MiMI allows the users to retrieve information from many different databases at once, highlighting complementary and contradictory information. To help scientists judge the usefulness of a piece of data, MiMI tracks the provenance of all data. Finally, a simple yet powerful user interface aids users in their queries, and frees them from the onerous task of knowing the data format or learning a query language. MiMI allows scientists to query all data, whether corroborative or contradictory, and specify which sources to utilize. MiMI is part of the National Center for Integrative Biomedical Informatics (NCIBI) and is publicly available at: http://mimi.ncibi.org.