111 research outputs found

    2D and 3D cubic monocrystalline and polycrystalline materials: their stability and mechanical properties

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    We consider 2- and 3-dimensional cubic monocrystalline and polycrystalline materials. Expressions for Young's and shear moduli and Poisson's ratio are expressed in terms of eigenvalues of the stiffness tensor. Such a form is well suited for studying properties of these mechanical characteristics on sides of the stability triangles. For crystalline high-symmetry directions lines of vanishing Poisson's ratio are found. These lines demarcate regions of the stability triangle into areas of various auxeticity properties. The simplest model of polycrystalline 2D and 3D cubic materials is considered. In polycrystalline phases the region of complete auxetics is larger than for monocrystalline materials.Comment: 9 pages, 3 figures, in proceedings of the Tenth International School on Theoretical Physics, Symmetry and Structural Properties of Condensed Matter, Myczkowce 200

    Increase in bacteraemia cases in the East Midlands region of the UK due to MDREscherichia coliST73: high levels of genomic and plasmid diversity in causative isolates

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    Objectives: To determine the population structure of E. coli ST73 isolated from human bacteraemia and urinary tract infections. Methods: The genomes of 22 E.coli ST73 isolates were sequenced using the Illumina HiSeq platform. High resolution SNP typing was used to create a phylogenetic tree. Comparative genomics were also performed using a pangenome approach. In silico and S1-PFGE plasmid profiling was conducted, and isolates were checked for their ability to survive exposure to human serum. Results: E.coli ST73 isolates circulating in clinically unrelated episodes show a high degree of diversity at a whole genome level, though exhibit conservation in gene content, particularly in virulence associated gene carriage. The isolates also contain a highly diverse plasmid pool that confers multi-drug resistance via carriage of CTX-M genes. All strains are highly serum resistant and uniformly carry genes shown to be essential for serum resistance. Conclusions: Our data shows that a rise in incidence of multi-drug resistant E.coli ST73 clinical isolates is not due to a circulating outbreak strain as in E.coli ST131. Rather the ST73 circulating strains are distantly related and carry a diverse set of resistance plasmids. This suggests that the evolutionary events behind emergence of drug resistant E.coli differ between lineages

    Electrically conductive PTT-block-PTMO/SWCNTs+Graphene Nanoplatelets hybrid nanocomposites prepared by in situ polymerization

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    Hybrid Materials 2015; Sitges, Barcelona, Spain, 9 - 13 March 2015The studies were financed by the National Science Centre within project PRELUDE no 2013/11/N/ST8/00404.Peer Reviewe

    The Composition of the Cuticular and Internal Free Fatty Acids and Alcohols from Lucilia sericata Males and Females

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    GC, GC–MS, and HPLC–LLSD analyses were used to identify and quantify cuticular and internal lipids in males and females of the blow-fly (Lucilia sericata). Sixteen free fatty acids, seven alcohols and cholesterol were identified and quantitatively determined in the cuticular lipids of L. sericata. Cuticular fatty acids ranged from C6 to C20 and included unsaturated entities such as 16:1n-9, 18:1n-9, 20:4n-3 and 20:5n-3. Cuticular alcohols (only saturated and even-numbered) ranged from C12 to C20 in males and C10 to C22 in females. Only one sterol was found in the cuticular lipids of both males and females. 23 free fatty acids, five alcohols and cholesterol were identified in the internal lipids. Internal fatty acids were present in large amounts—7.4 mg/g (female) and 10.1 mg/g (male). Only traces of internal alcohols (from C14 to C26 in males, from C14 to C22 in females) were found in L. sericata. Large amounts of internal cholesterol were identified in L. sericata males and females (0.49 and 0.97 mg/g of the insect body, respectively)

    Genome-wide transcriptional profiling of appressorium development by the rice blast fungus Magnaporthe oryzae.

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    addresses: College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom.notes: PMCID: PMC3276559The rice blast fungus Magnaporthe oryzae is one of the most significant pathogens affecting global food security. To cause rice blast disease the fungus elaborates a specialised infection structure called an appressorium. Here, we report genome wide transcriptional profile analysis of appressorium development using next generation sequencing (NGS). We performed both RNA-Seq and High-Throughput SuperSAGE analysis to compare the utility of these procedures for identifying differential gene expression in M. oryzae. We then analysed global patterns of gene expression during appressorium development. We show evidence for large-scale gene expression changes, highlighting the role of autophagy, lipid metabolism and melanin biosynthesis in appressorium differentiation. We reveal the role of the Pmk1 MAP kinase as a key global regulator of appressorium-associated gene expression. We also provide evidence for differential expression of transporter-encoding gene families and specific high level expression of genes involved in quinate uptake and utilization, consistent with pathogen-mediated perturbation of host metabolism during plant infection. When considered together, these data provide a comprehensive high-resolution analysis of gene expression changes associated with cellular differentiation that will provide a key resource for understanding the biology of rice blast disease

    Molecular mechanisms of toxicity of silver nanoparticles in zebrafish embryos.

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    addresses: Biosciences, College of Life and Environmental Sciences, Geoffrey Pope Building, University of Exeter, Stocker Road, Exeter, EX4 4QD, UK. [email protected]: Journal Article; Research Support, Non-U.S. Gov'tThis is an open access article that is freely available in ORE or from the publisher's web site. http://pubs.acs.org/doi/abs/10.1021/es401758d. Please cite the published version© 2013 American Chemical SocietySupporting Information: Further details on the methodology and results for the characterization of the silver particles used for the exposures, mortality curves, sequencing analysis, and a number of supporting figures and tables. This material is available free of charge via the Internet at http://pubs.acs.org.Silver nanoparticles cause toxicity in exposed organisms and are an environmental health concern. The mechanisms of silver nanoparticle toxicity, however, remain unclear. We examined the effects of exposure to silver in nano-, bulk-, and ionic forms on zebrafish embryos (Danio rerio) using a Next Generation Sequencing approach in an Illumina platform (High-Throughput SuperSAGE). Significant alterations in gene expression were found for all treatments and many of the gene pathways affected, most notably those associated with oxidative phosphorylation and protein synthesis, overlapped strongly between the three treatments indicating similar mechanisms of toxicity for the three forms of silver studied. Changes in oxidative phosphorylation indicated a down-regulation of this pathway at 24 h of exposure, but with a recovery at 48 h. This finding was consistent with a dose-dependent decrease in oxygen consumption at 24 h, but not at 48 h, following exposure to silver ions. Overall, our data provide support for the hypothesis that the toxicity caused by silver nanoparticles is principally associated with bioavailable silver ions in exposed zebrafish embryos. These findings are important in the evaluation of the risk that silver particles may pose to exposed vertebrate organisms.Natural Environment Research Council (NERC)NERC Biomolecular Analysis FacilityUK Environment AgencySystems Biology Seed fund, University of Exete

    Tumour-associated carbohydrate antigens in breast cancer

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    Glycosylation changes that occur in cancer often lead to the expression of tumour-associated carbohydrate antigens. In breast cancer, these antigens are usually associated with a poor prognosis and a reduced overall survival. Cellular models have shown the implication of these antigens in cell adhesion, migration, proliferation and tumour growth. The present review summarizes our current knowledge of glycosylation changes (structures, biosynthesis and occurrence) in breast cancer cell lines and primary tumours, and the consequences on disease progression and aggressiveness. The therapeutic strategies attempted to target tumour-associated carbohydrate antigens in breast cancer are also discussed

    Deciphering the Preference and Predicting the Viability of Circular Permutations in Proteins

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    Circular permutation (CP) refers to situations in which the termini of a protein are relocated to other positions in the structure. CP occurs naturally and has been artificially created to study protein function, stability and folding. Recently CP is increasingly applied to engineer enzyme structure and function, and to create bifunctional fusion proteins unachievable by tandem fusion. CP is a complicated and expensive technique. An intrinsic difficulty in its application lies in the fact that not every position in a protein is amenable for creating a viable permutant. To examine the preferences of CP and develop CP viability prediction methods, we carried out comprehensive analyses of the sequence, structural, and dynamical properties of known CP sites using a variety of statistics and simulation methods, such as the bootstrap aggregating, permutation test and molecular dynamics simulations. CP particularly favors Gly, Pro, Asp and Asn. Positions preferred by CP lie within coils, loops, turns, and at residues that are exposed to solvent, weakly hydrogen-bonded, environmentally unpacked, or flexible. Disfavored positions include Cys, bulky hydrophobic residues, and residues located within helices or near the protein's core. These results fostered the development of an effective viable CP site prediction system, which combined four machine learning methods, e.g., artificial neural networks, the support vector machine, a random forest, and a hierarchical feature integration procedure developed in this work. As assessed by using the hydrofolate reductase dataset as the independent evaluation dataset, this prediction system achieved an AUC of 0.9. Large-scale predictions have been performed for nine thousand representative protein structures; several new potential applications of CP were thus identified. Many unreported preferences of CP are revealed in this study. The developed system is the best CP viability prediction method currently available. This work will facilitate the application of CP in research and biotechnology
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