The structure and evolution of trade relations between countries along the Belt and Road

Trade facilitation is one of the five main agendas of the Belt and Road Initiative (BRI). Social network analysis has helped understand the complexity of trade networks, but existing studies tend to overlook the fact that not all bilateral trade relations are equally important to a country. To fill this gap in the literature, this paper focuses on the top 2 trade relations networks to illuminate the structure and evolution of B&R trade relations, the relative positions of different countries, and changes in the composition of trade communities (e.g., the community leaders) and the changing patterns of trade between them. We find rich dynamics over time both inter- and intra-communities. The overall international trade networks of B&R countries experienced a leadership change from Russia to China on one hand, some temporary communities experienced emergence, disappearance (e.g. the Kuwait- and Thailand-led communities) or reemergence (e.g. Poland-led community), and a community membership was generally consistent on the other hand. Since the future impacts of China’s BRI will depend on the degree of integration of the connected regions, some countries with stable and high centrality indices (e.g. Russia, Singapore, Serbia, Greece, Turkey, Iran, Poland, Hungary and Romania) could be selected by China as strategic regional partners, and countries with a strategically important geographical position but weak trade links (e.g. Myanmar, Pakistan, and Belarus) should be prioritized

Network Analysis of World Trade using the BACI-CEPII dataset

In this paper we explore the BACI-CEPII database using Network Analysis. Starting from the visualization of the World Trade Network, we then define and describe the topology of the network, both in its binary version and in its weighted version, calculating and discussing some of the commonly used network's statistics. We finally discuss some specic topics that can be studied using Network Analysis and International Trade data, both at the aggregated and sectoral level. The analysis is done using multiple software (Stata, R, and Pajek). The scripts to replicate part of the analysis are included in the appendix, and can be used as an handson tutorial. Moreover,the World Trade Network local and global centrality measures, for the unweighted and the weighted version of the Network, calculated using the bilateral aggregate trade data for each country (178 in total) and each year (from 1995 to 2010,) can be downloaded from the CEPII webpage

POINeT: protein interactome with sub-network analysis and hub prioritization

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions (PPIs) are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools.</p> <p>Results</p> <p>We have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3) to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles.</p> <p>Conclusion</p> <p>The functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to selected tissues can be revealed. The straightforward interface of POINeT makes PPI search and analysis just a few clicks away. The modular design permits further functional enhancement without hampering the simplicity. POINeT is available at <url>http://poinet.bioinformatics.tw/</url>.</p

Intragraft transcriptional profiling of renal transplant patients with tubular dysfunction reveals mechanisms underlying graft injury and recovery

Background: Proximal tubular dysfunction (PTD) is associated with a decreased long-term graft survival in renal transplant patients and can be detected by the elevation of urinary tubular proteins. This study investigated transcriptional changes in biopsies from renal transplant patients with PTD to disclose molecular mechanisms underlying graft injury and functional recovery. Methods: Thirty-three renal transplant patients with high urinary levels of retinol-binding protein, a biomarker of PTD, were enrolled in the study. The initial immunosuppressive scheme included azathioprine, cyclosporine, and steroids. After randomization, 18 patients (group 2) had their treatment modified by reducing cyclosporine dosage and substituting azathioprine for mycophenolate mofetil, while the other 15 patients (group 1) remained under the initial scheme. Patients were biopsied at enrollment and after 12 months of follow-up, and paired comparisons were performed between their intragraft gene expression profiles. The differential transcriptome profiles were analyzed by constructing gene co-expression networks and identifying enriched functions and central nodes in each network. Results: Only the alternative immunosuppressive scheme used in group 2 ameliorated renal function and tubular proteinuria after 12 months of follow-up. Intragraft molecular changes observed in group 2 were linked to autophagy, extracellular matrix, and adaptive immunity. Conversely, gene expression changes in group 1 were related to fibrosis, endocytosis, ubiquitination, and endoplasmic reticulum stress. Conclusion: These results suggest that molecular networks associated with the control of endocytosis, autophagy, protein overload, fibrosis, and adaptive immunity may be involved in improvement of graft function.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo-FAPESP [2009/53443-1, 2011/50761-2, 2012/02270-2]Conselho Nacional de Desenvolvimento Cientifico e Tecnologico-CNPq [307626/2014-8]Conselho Nacional de Desenvolvimento Cientifico e Tecnologico-CNPq (INCT Complex Fluids)NAP e-Science USPDepartment of Pediatrics, Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, BrazilLaboratory of Transplantation Immunobiology, Department of Immunology, Institute of Biomedical Sciences, Universidade de São Paulo (USP), São Paulo, BrazilLaboratory of Clinical and Experimental Immunology, Nephrology Division, Universidade Federal de São Paulo (UNIFESP), São Paulo, BrazilInstituto Israelita de Ensino e Pesquisa Albert Einstein, Hospital Albert Einstein, São Paulo, BrazilLaboratory of Clinical and Experimental Immunology, Nephrology Division, Universidade Federal de São Paulo (UNIFESP), São Paulo, BrazilFAPESP: 2009/53443-1FAPESP: 2011/50761-2FAPESP: 2012/02270-2CNPq: 307626/2014-8Web of Scienc

Assortativity Effects on Diffusion-like Processes in Scale-free Networks

We study the variation in epidemic thresholds in complex networks with different assortativity properties. We determine the thresholds by applying spectral analysis to the matrices associated to the graphs. In order to produce graphs with a specific assortativity we introduce a procedure to sample the space of all the possible networks with a given degree sequence. Our analysis shows that while disassortative networks have an higher epidemiological threshold, assortative networks have a slower diffusion time for diseases. We also used these networks for evaluating the effects of assortativity in a specific dynamic model of sandpile. We show that immunization procedures give different results according to the assortativity of the network considered