Representing and describing nanomaterials in predictive nanoinformatics

This Review discusses how a comprehensive system for defining nanomaterial descriptors can enable a safe-and-sustainable-by-design concept for engineered nanomaterials. Engineered nanomaterials (ENMs) enable new and enhanced products and devices in which matter can be controlled at a near-atomic scale (in the range of 1 to 100 nm). However, the unique nanoscale properties that make ENMs attractive may result in as yet poorly known risks to human health and the environment. Thus, new ENMs should be designed in line with the idea of safe-and-sustainable-by-design (SSbD). The biological activity of ENMs is closely related to their physicochemical characteristics, changes in these characteristics may therefore cause changes in the ENMs activity. In this sense, a set of physicochemical characteristics (for example, chemical composition, crystal structure, size, shape, surface structure) creates a unique 'representation' of a given ENM. The usability of these characteristics or nanomaterial descriptors (nanodescriptors) in nanoinformatics methods such as quantitative structure-activity/property relationship (QSAR/QSPR) models, provides exciting opportunities to optimize ENMs at the design stage by improving their functionality and minimizing unforeseen health/environmental hazards. A computational screening of possible versions of novel ENMs would return optimal nanostructures and manage ('design out') hazardous features at the earliest possible manufacturing step. Safe adoption of ENMs on a vast scale will depend on the successful integration of the entire bulk of nanodescriptors extracted experimentally with data from theoretical and computational models. This Review discusses directions for developing appropriate nanomaterial representations and related nanodescriptors to enhance the reliability of computational modelling utilized in designing safer and more sustainable ENMs.Peer reviewe

DNA methylation profile of genes involved in iflammation and autoimmunity in inflammatory boewl disease

Objective This thesis aimed to investigate the methylation profile of 22 genes associated with thepathogenesis of IBD in patients with ulcerative colitis (UC) or Crohn’s Disease (CD) andcompare them with the methylation profile of the same genes in healthy controls. Anadditional purpose of the study was to investigate whether methylation profile of these genesbetween inflamed intestinal tissue and peripheral blood are in concordance, hoping to indicatea possible future use of methylation as biomarker.Materials & MethodsIsolated peripheral blood samples and inflamed intestinal tissue samples were collectedfrom 24 patients with IBD, 12 of them suffering from UC and 12 from CD. The control groupconsisted of 12 healthy subjects without any personal and family history of digestive diseases.The promoter methylation status of genes involved in inflammation and autoimmunity wasprofiled using the Human Inflammatory Response and Autoimmunity EpiTect Methyl IISignature PCR Array profiles. Methylation was considered to be hyper-methylated if >20%according to the instructions of the manufacturer. The microarrays were validated with Quantitative Real-time PCR.The statistical analysis was performed using non-parametricstatistical tests (non-parametric statistical tests).ResultsRegarding CD, the methylation status of IL10RA, IL13, IL13RA1 and IL17C inperipheral blood samples did not differ significantly from the methylation status of healthycontrols. Only three genes – ATF2, CXCL5 and IL12B showed higher methylation in CDcompared to controls, but they did not exceed the threshold of 20% for hypermethylation. Allother genes tested appear lower methylation than controls.Regarding UC, methylation status of CXCL6 and IL13RA1 in peripheral blood samplesdid not differ significantly from the methylation status of healthy individuals. Five genes(CXCL14, CXCL5, GATA3, IL17C and IL4R,) were found to be significantly hypermethylatedin UC patients compared to healthy individuals. Some genes show higher methylation thancontrols, but they do not exceed 20% methylation threshold for hypermethylation. All other genes show lower methylation in UC compared to controls.Active cases of both CD and UC could be promptly distinguished from healthycontrols based on the signatures provided by the methylation profiles in peripheral bloodsamples. Based on these results - despite the relatively limited number of patients - it waspossible to define distinct signatures for active CD vs. active UC. Specifically, CXCL14,CXCL5, GATA3, IL17C and IL4R genes were hyper-methylated in UC compared to CD. Inaddition, CXCL6 which did not differ significantly between UC and controls appeared hypermethylatedcompared to CD; in contrast, IL13 which did not differ significantly between CDand controls appeared hypermethylated in CD compared to UC. Moreover the real-timequantitative PCR conducted for seven genes (CCL25, IL13, IL17RA, IL17A, IL12B, CXCL5,and IL4R) confirmed the causal relationship between hyper-methylation and lower expressionof genes. Finally, it was confirmed that methylation profile in intestinal tissue and peripheralblood are in concordance. ConclusionsIn this study we have identified panels of genes that show evidence of differentialmethylation between UC and controls, as well as CD and UC. Moreover there is strongevidence that methylation level in intestinal tissue samples is well related to methylation levelin whole blood samples. Our findings suggest that these genes play an important role in IBDpathogenesis, as differential methylation status observed affects gene expression at the mRNAlevel. In conclusion, the different methylation levels between CD and UC could play a role inconfirming the diagnosis of IBD, determining the exact type of IBD (UC or CD) and possiblyestimating the activity of diseas

Viscoelasticity of wood and the influence of moisture at the mechanical properties

84 σ.Στο πρώτο κεφάλαιο γίνεται εισαγωγή στην θεωρεία της ιξωδοελστικότητας και διαμόρφωση των βασικών ιξωδοελαστικών μοντέλων αυτής. Στην συνέχεια στο δεύτερο κεφάλαιο παρουσιάζεται το υλικό που είναι υπό μελέτη, στην συγκεκριμένη εργασία, το ξύλο και δύο διαφορετικά ρεολογικά μοντέλα με τα οποία θα επιχειρηθεί η μοντελοποίηση της ιξωδοελαστικής συμπεριφοράς του ξύλου με πειράματα από βιβλιογραφία.Στο τρίτο κεφάλαιο γίνεται η σύγκριση των πειραματικών δεδομένων με τα μοντέλα που επιλέχθηκαν για την περιγραφή της ιξωδοελαστικής συμπεριφοράς και της επίδρασης της υγρασίας σε αυτή. Τέλος στο τέταρτο κεφάλαιο γίνεται η συζήτηση και τα συμπεράσματα που προκύπτουν.The first chapter is introduction to the theory of viscoelasticity and basic configuration of viscoelastic models. Then the second chapter presents the material being studied , in this work , wood and two different rheological models which will attempt to model the viscoelastic behavior of wood with experiments from references.Third chapter is the comparison of experimental data to the models chosen for the description of the viscoelastic behavior and the effect of moisture in it. Finally, in the fourth chapter is the discussion and the conclusions drawn .Καρατζάς Ε. Παντελή

VICTOR: A visual analytics web application for comparing cluster sets

Clustering is the process of grouping different data objects based on similar properties. Clustering has applications in various case studies from several fields such as graph theory, image analysis, pattern recognition, statistics and others. Nowadays, there are numerous algorithms and tools able to generate clustering results. However, different algorithms or parameterizations may produce quite dissimilar cluster sets. In this way, the user is often forced to manually filter and compare these results in order to decide which of them generate the ideal clusters. To automate this process, in this study, we present VICTOR, the first fully interactive and dependency-free visual analytics web application which allows the visual comparison of the results of various clustering algorithms. VICTOR can handle multiple cluster set results simultaneously and compare them using ten different metrics. Clustering results can be filtered and compared to each other with the use of data tables or interactive heatmaps, bar plots, correlation networks, sankey and circos plots. We demonstrate VICTOR's functionality using three examples. In the first case, we compare five different network clustering algorithms on a Yeast protein-protein interaction dataset whereas in the second example, we test four different parameters of the MCL clustering algorithm on the same dataset. Finally, as a third example, we compare four different metaanalyses with hierarchically clustered differentially expressed genes found to be involved in myocardial infarction. VICTOR is available at http://victor.pavlopouloslab.info or http://bib.fleming.gr:3838/VICTOR

Biomolecule and Bioentity Interaction Databases in Systems Biology:A Comprehensive Review

Technological advances in high-throughput techniques have resulted in tremendous growth of complex biological datasets providing evidence regarding various biomolecular interactions. To cope with this data flood, computational approaches, web services, and databases have been implemented to deal with issues such as data integration, visualization, exploration, organization, scalability, and complexity. Nevertheless, as the number of such sets increases, it is becoming more and more difficult for an end user to know what the scope and focus of each repository is and how redundant the information between them is. Several repositories have a more general scope, while others focus on specialized aspects, such as specific organisms or biological systems. Unfortunately, many of these databases are self-contained or poorly documented and maintained. For a clearer view, in this article we provide a comprehensive categorization, comparison and evaluation of such repositories for different bioentity interaction types. We discuss most of the publicly available services based on their content, sources of information, data representation methods, user-friendliness, scope and interconnectivity, and we comment on their strengths and weaknesses. We aim for this review to reach a broad readership varying from biomedical beginners to experts and serve as a reference article in the field of Network Biology