An improved method for scoring protein-protein interactions using semantic similarity within the gene ontology

<p>Abstract</p> <p>Background</p> <p>Semantic similarity measures are useful to assess the physiological relevance of protein-protein interactions (PPIs). They quantify similarity between proteins based on their function using annotation systems like the Gene Ontology (GO). Proteins that interact in the cell are likely to be in similar locations or involved in similar biological processes compared to proteins that do not interact. Thus the more semantically similar the gene function annotations are among the interacting proteins, more likely the interaction is physiologically relevant. However, most semantic similarity measures used for PPI confidence assessment do not consider the unequal depth of term hierarchies in different classes of cellular location, molecular function, and biological process ontologies of GO and thus may over-or under-estimate similarity.</p> <p>Results</p> <p>We describe an improved algorithm, Topological Clustering Semantic Similarity (TCSS), to compute semantic similarity between GO terms annotated to proteins in interaction datasets. Our algorithm, considers unequal depth of biological knowledge representation in different branches of the GO graph. The central idea is to divide the GO graph into sub-graphs and score PPIs higher if participating proteins belong to the same sub-graph as compared to if they belong to different sub-graphs.</p> <p>Conclusions</p> <p>The TCSS algorithm performs better than other semantic similarity measurement techniques that we evaluated in terms of their performance on distinguishing true from false protein interactions, and correlation with gene expression and protein families. We show an average improvement of 4.6 times the <it>F</it>₁score over Resnik, the next best method, on our <it>Saccharomyces cerevisiae </it>PPI dataset and 2 times on our <it>Homo sapiens </it>PPI dataset using cellular component, biological process and molecular function GO annotations.</p

Regulatory Effects of IFN-β on the Development of Experimental Autoimmune Uveoretinitis in B10RIII Mice

BACKGROUND: Experimental autoimmune uveoretinitis (EAU) serves as a model for human intraocular inflammation. IFN-β has been used in the treatment of certain autoimmune diseases. Earlier studies showed that it ameliorated EAU; however, the mechanisms involved in this inhibition are still largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: B10RIII mice were immunized with interphotoreceptor retinoid-binding protein (IRBP) peptide 161-180 in Complete Freund's adjuvant. Splenocytes from different time points after immunization were used to evaluate the expression of IFN-β. An increased expression of IFN-β was observed during EAU and its highest expression was observed on day 16, 3 days after the peak of intraocular inflammation. Splenocytes and draining lymph node cells from mice immunized with IRBP(161-180) on day 13 and control mice were activated with anti-CD3/anti-CD28 antibodies or IRBP(161-180) to evaluate the production of IFN-γ and IL-17. The results showed that IFN-γ and IL-17 were significantly higher in immunized mice as compared to the control mice when exposed to anti-CD3/anti-CD28 antibodies. However, the production of IFN-γ and IL-17 was detected only in immunized mice, but not in the control mice when stimulated with IRBP(161-180). Multiple subcutaneous injections of IFN-β significantly inhibited EAU activity in association with a down-regulated expression of IFN-γ, IL-17 and an enhanced IL-10 production. In an in vitro system using cells from mice, IFN-β suppressed IFN-γ production by CD4(+)CD62L(-) T cells, IL-17 production by CD4(+)CD62L(+/-) T cells and proliferation of CD4(+)CD62L(+/-) T cells. IFN-β inhibited the secretion of IL-6, but promoted the secretion of IL-10 by monocytes. IFN-β-treated monocytes inhibited IL-17 secretion by CD4(+)CD62L(+/-) T cells, but did not influence IFN-γ expression and T cell proliferation. CONCLUSIONS/SIGNIFICANCE: IFN-β may exert its inhibitory effect on EAU by inhibiting Th1, Th17 cells and modulating relevant cytokines. IFN-β may provide a potential treatment for diseases mediated by Th1 and Th17 cells

Proposal, project, practice, pause: developing a framework for evaluating smart domestic product engagement

Smart homes are fast becoming a reality, with smart TVs, smart meters and other such “smart” devices/systems already representing a substantial household presence. These, which we collectively term “smart domestic products” (SDPs), will need to be promoted, adopted, and normalized into daily routines. Despite this, the marketing canon lacks a substantive discourse on pertinent research. We look to help correct this by melding ideas from organizational sociology, innovation diffusion and appropriation studies, and service dominant logic. Consequently, we suggest a framework for research that responds directly to the specific characteristics of SDPs. Using the SDP eco-system as a context, our framework emphasizes the interplay of embeddedness, practice, value and engagement. It comprises a four-stage horizontal/ longitudinal axis we describe as proposal, project, practice and pause. Cross-sectionally we focus on value, and combine aspects of existing thought to suggest how this impacts each stage of our engagement continuum. We subsequently identify perceived personal advantage as the resultant of these two axes and propose this as the key for understanding consumer and SDP sociomaterial engagement. This article also advances a definition of SDPs and ends with an agenda for further research

An agenda for integrated system-wide interdisciplinary agri-food research

© 2017 The Author(s)This paper outlines the development of an integrated interdisciplinary approach to agri-food research, designed to address the ‘grand challenge’ of global food security. Rather than meeting this challenge by working in separate domains or via single-disciplinary perspectives, we chart the development of a system-wide approach to the food supply chain. In this approach, social and environmental questions are simultaneously addressed. Firstly, we provide a holistic model of the agri-food system, which depicts the processes involved, the principal inputs and outputs, the actors and the external influences, emphasising the system’s interactions, feedbacks and complexities. Secondly, we show how this model necessitates a research programme that includes the study of land-use, crop production and protection, food processing, storage and distribution, retailing and consumption, nutrition and public health. Acknowledging the methodological and epistemological challenges involved in developing this approach, we propose two specific ways forward. Firstly, we propose a method for analysing and modelling agri-food systems in their totality, which enables the complexity to be reduced to essential components of the whole system to allow tractable quantitative analysis using LCA and related methods. This initial analysis allows for more detailed quantification of total system resource efficiency, environmental impact and waste. Secondly, we propose a method to analyse the ethical, legal and political tensions that characterise such systems via the use of deliberative fora. We conclude by proposing an agenda for agri-food research which combines these two approaches into a rational programme for identifying, testing and implementing the new agri-technologies and agri-food policies, advocating the critical application of nexus thinking to meet the global food security challenge

Treatment options for small cell lung cancer – do we have more choice?

Small cell lung cancer (SCLC) is a significant health problem worldwide because of its high propensity for relapse. This review discusses existing and future therapies for the treatment of SCLC