596 research outputs found

    Finding the shortest path with PesCa: A tool for network reconstruction

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    The growing dimension and complexity of the available experimental data generating biological networks have increased the need for tools that help in categorizing nodes by their topological relevance. Here we present CentiScaPe, a Cytoscape app specifically designed to calculate centrality indexes used for the identification of the most important nodes in a network. CentiScaPe is a comprehensive suite of algorithms dedicated to network nodes centrality analysis, computing several centralities for undirected, directed and weighted networks. The results of the topological analysis can be integrated with data set from lab experiments, like expression or phosphorylation levels for each protein represented in the network. Our app opens new perspectives in the analysis of biological networks, since the integration of topological analysis with lab experimental data enhance the predictive power of the bioinformatics analysis

    Association between Resistin Levels and All-Cause and Cardiovascular Mortality: A New Study and a Systematic Review and Meta-Analysis.

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    CONTEXT: Studies concerning the association between circulating resistin and mortality risk have reported, so far, conflicting results. OBJECTIVE: To investigate the association between resistin and both all-cause and cardiovascular (CV) mortality risk by 1) analyzing data from the Gargano Heart Study (GHS) prospective design (n=359 patients; 81 and 58 all-cause and CV deaths, respectively); 2) performing meta-analyses of all published studies addressing the above mentioned associations. DATA SOURCE AND STUDY SELECTION: MEDLINE and Web of Science search of studies reporting hazard ratios (HR) of circulating resistin for all-cause or CV mortality. DATA EXTRACTION: Performed independently by two investigators, using a standardized data extraction sheet. DATA SYNTHESIS: In GHS, adjusted HRs per one standard deviation (SD) increment in resistin concentration were 1.28 (95% CI: 1.07-1.54) and 1.32 (95% CI: 1.06-1.64) for all-cause and CV mortality, respectively. The meta-analyses included 7 studies (n=4016; 961 events) for all-cause mortality and 6 studies (n=4,187: 412 events) for CV mortality. Pooled HRs per one SD increment in resistin levels were 1.21 (95% CI: 1.03-1.42, Q-test p for heterogeneity<0.001) and 1.05 (95% CI: 1.01-1.10, Q-test p for heterogeneity=0.199) for all-cause and CV mortality, respectively. At meta-regression analyses, study mean age explained 9.9% of all-cause mortality studies heterogeneity. After adjusting for age, HR for all-cause mortality was 1.24 (95% CI: 1.06-1.45). CONCLUSIONS: Our results provide evidence for an association between circulating resistin and mortality risk among high-risk patients as are those with diabetes and coronary artery disease

    Analysing omics data sets with weighted nodes networks (WNNets)

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    Current trends in biomedical research indicate data integration as a fundamental step towards precision medicine. In this context, network models allow representing and analysing complex biological processes. However, although effective in unveiling network properties, these models fail in considering the individual, biochemical variations occurring at molecular level. As a consequence, the analysis of these models partially loses its predictive power. To overcome these limitations, Weighted Nodes Networks (WNNets) were developed. WNNets allow to easily and effectively weigh nodes using experimental information from multiple conditions. In this study, the characteristics of WNNets were described and a proteomics data set was modelled and analysed. Results suggested that degree, an established centrality index, may offer a novel perspective about the functional role of nodes in WNNets. Indeed, degree allowed retrieving significant differences between experimental conditions, highlighting relevant proteins, and provided a novel interpretation for degree itself, opening new perspectives in experimental data modelling and analysis. Overall, WNNets may be used to model any high-throughput experimental data set requiring weighted nodes. Finally, improving the power of the analysis by using centralities such as betweenness may provide further biological insights and unveil novel, interesting characteristics of WNNets

    TWAM: A Certifying Abstract Machine for Logic Programs

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    Type-preserving (or typed) compilation uses typing derivations to certify correctness properties of compilation. We have designed and implemented a type-preserving compiler for a simply-typed dialect of Prolog we call T-Prolog. The crux of our approach is a new certifying abstract machine which we call the Typed Warren Abstract Machine (TWAM). The TWAM has a dependent type system strong enough to specify the semantics of a logic program in the logical framework LF. We present a soundness metatheorem which constitutes a partial correctness guarantee: well-typed programs implement the logic program specified by their type. This metatheorem justifies our design and implementation of a certifying compiler from T-Prolog to TWAM.Comment: 41 pages, under submission to ACM Transactions on Computational Logi

    Somatostatin: A Novel Substrate and a Modulator of Insulin-Degrading Enzyme Activity

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    Insulin-degrading enzyme (IDE) is an interesting pharmacological target for Alzheimer's disease (AD), since it hydrolyzes beta-amyloid, producing non-neurotoxic fragments. It has also been shown that the somatostatin level reduction is a pathological feature of AD and that it regulates the neprilysin activity toward beta-amyloid. In this work, we report for the first time that IDE is able to hydrolyze somatostatin [k(cat) (s(-1)) = 0.38 (+/-0.05); K-m (M) = 7.5 (+/-0.9) x 10(-6)] at the Phe6-Phe7 amino acid bond. On the other hand, somatostatin modulates IDE activity, enhancing the enzymatic cleavage of a novel fluorogenic beta-amyloid through a decrease of the K-m toward this substrate, which corresponds to the 10-25 amino acid sequence of the A beta(1-40). Circular dichroism spectroscopy and surface plasmon resonance imaging experiments show that somatostatin binding to IDE brings about a concentration-dependent structural change of the secondary and tertiary structure(s) of the enzyme, revealing two possible binding sites. The higher affinity binding site disappears upon inactivation of IDE by ethylenediaminetetra acetic acid, which chelates, the catalytic Zn2+ ion. As a whole, these features suggest that the modulatory effect is due to an allosteric mechanism: somatostatin binding to the active site of one IDE subunit (where somatostatin is cleaved) induces an enhancement of IDE proteolytic activity toward fluorogenic beta-amyloid by another subunit. Therefore, this investigation on IDE-somatostatin interaction contributes to a more exhaustive knowledge about the functional and structural aspects of IDE and its pathophysiological implications in the amyloid deposition and somatostatin homeostasis in the brain. (C) 2008 Elsevier Ltd. All rights reserved
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