790 research outputs found
Finding the shortest path with PesCa: A tool for network reconstruction
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
Analysing omics data sets with weighted nodes networks (WNNets)
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
A DRIVING SIMULATION STUDY ON THE EFFECTS OF DIFFERENT WINE TYPES ON THE PERFORMANCE OF YOUNG DRIVERS
Background. Alcohol consumption is responsible for a significant number of road fatalities. To contrast this phenomenon, a more responsible attitude to the wine consumption, especially among young, inexperienced drivers prone to risky behaviour on the road must be promoted. Method. This is a simplified single-blind, placebo-controlled experiment aimed at evaluating 44 young drivers monitored during a driving simulation following the consumption of natural and conventional wines, with a reference blood alcohol concentration (BAC) of 0.5 g/l. Two hypotheses are tested: (1) the legal consumption of wine has no significant impact on young drivers’ performance in both ordinary and unusual road events; (2) natural and conventional wines are expected to produce negligible and acceptable impairments in young drivers the same BAC. Two reference groups (BAC = 0 g/l), one a placebo controlled group with drivers treated with a dealcoholized wine, were included. Results and Conclusions. Significant differences between the groups in terms of perception and reaction times (PRT) to visual and auditory stimuli, and to speeding were observed, with young drivers treated with conventional wine displaying more aggressive behaviours. In contrast, participants treated with natural wine showed PRT which were not significantly different from those belonging to control groups. The gaze attention levels of wine treated drivers were found to be dose dependant, with young drivers of the two control groups and those of the treated ones with BAC < 0.3 g/l able to focus on wider area ahead and, thereby, collect more information from the road environment
Moral reasoning behind the veil of ignorance: An investigation into perspective-taking accessibility in the context of autonomous vehicles
Perspective-taking (PT) accessibility has been recognized as an important factor in affecting moral reasoning, also playing a non-trivial role in moral investigation towards autonomous vehicles (AVs). A new proposal to deepen this effect leverages the principles of the veil of ignorance (VOI), as a moral reasoning device aimed to control self-interested decisions by limiting the access to specific perspectives and to potentially biased information. Throughout two studies, we deepen the role of VOI reasoning in the moral perception of AVs, disclosing personal and contingent information progressively throughout the experiment. With the use of the moral trilemma paradigm, two different VOI conditions were operationalized, inspired by the Original Position theory by John Rawls and the Equiprobability Model by John Harsanyi. Evidence suggests a significant role of VOI reasoning in affecting moral reasoning, which seems not independent from the order in which information is revealed. Coherently, a detrimental effect of self-involvement on utilitarian behaviours was detected. These results highlight the importance of considering PT accessibility and self-involvement when investigating moral attitudes towards AVs, since it can help the intelligibility of general concerns and hesitations towards this new technology
Somatostatin: A Novel Substrate and a Modulator of Insulin-Degrading Enzyme Activity
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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