2,236 research outputs found

    Parallel fast fourier transform in SPMD style of cilk

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    Copyright © 2019 Inderscience Enterprises Ltd. In this paper, we propose a parallel one-dimensional non-recursive fast Fourier transform (FFT) program based on conventional Cooley-Tukey’s algorithm written in C using Cilk in single program multiple data (SPMD) style. As a highly compact designed code, this code is compared with a highly tuned parallel recursive fast Fourier transform (FFT) using Cilk, which is included in Cilk package of version 5.4.6. Both algorithms are executed on multicore servers, and experimental results show that the performance of the SPMD style of Cilk fast Fourier transform (FFT) parallel code is highly competitive and promising

    Detection of putative new mutacins by bioinformatic analysis using available web tools

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    In order to characterise new bacteriocins produced by Streptococcus mutans we perform a complete bioinformatic analyses by scanning the genome sequence of strains UA159 and NN2025. By searching in the adjacent genomic context of the two-component signal transduction system we predicted the existence of many putative new bacteriocins' maturation pathways and some of them were only exclusive to a group of Streptococcus. Computational genomic and proteomic analysis combined to predictive functionnal analysis represent an alternative way for rapid identification of new putative bacteriocins as well as new potential antimicrobial drugs compared to the more traditional methods of drugs discovery using antagonism tests

    EasyModeller: A graphical interface to MODELLER

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    <p>Abstract</p> <p>Background</p> <p>MODELLER is a program for automated protein Homology Modeling. It is one of the most widely used tool for homology or comparative modeling of protein three-dimensional structures, but most users find it a bit difficult to start with MODELLER as it is command line based and requires knowledge of basic Python scripting to use it efficiently.</p> <p>Findings</p> <p>The study was designed with an aim to develop of "EasyModeller" tool as a frontend graphical interface to MODELLER using Perl/Tk, which can be used as a standalone tool in windows platform with MODELLER and Python preinstalled. It helps inexperienced users to perform modeling, assessment, visualization, and optimization of protein models in a simple and straightforward way.</p> <p>Conclusion</p> <p>EasyModeller provides a graphical straight forward interface and functions as a stand-alone tool which can be used in a standard personal computer with Microsoft Windows as the operating system.</p

    Hybrid Si nanocones/PEDOT:PSS solar cell

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    Periodic silicon nanocones (SiNCs) with different periodicities are fabricated by dry etching of a Si substrate patterned using monolayer polystyrene (PS) nanospheres as a mask. Hybrid Si/PEDOT:PSS solar cells based on the SiNCs are then fabricated and characterized in terms of their optical, electrical, and photovoltaic properties. The optical properties of the SiNCs are also investigated using theoretical simulation based on the finite element method. The SiNCs reveal excellent light trapping ability as compared to a planar Si substrate. It is found that the power conversion efficiency (PCE) of the hybrid cells decreases with increasing periodicity of the SiNCs. The highest PCE of 7.1% is achieved for the SiNC hybrid cell with a 400-nm periodicity, due to the strong light trapping near the peak of the solar spectrum and better current collection efficiency. PACS: 81.07.-b; 81.16.-c; 88.40.h

    Common and Distant Structural Characteristics of Feruloyl Esterase Families from Aspergillus oryzae

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    Background: Feruloyl esterases (FAEs) are important biomass degrading accessory enzymes due to their capability of cleaving the ester links between hemicellulose and pectin to aromatic compounds of lignin, thus enhancing the accessibility of plant tissues to cellulolytic and hemicellulolytic enzymes. FAEs have gained increased attention in the area of biocatalytic transformations for the synthesis of value added compounds with medicinal and nutritional applications. Following the increasing attention on these enzymes, a novel descriptor based classification system has been proposed for FAEs resulting into 12 distinct families and pharmacophore models for three FAE sub-families have been developed. Methodology/Principal Findings: The feruloylome of Aspergillus oryzae contains 13 predicted FAEs belonging to six sub-families based on our recently developed descriptor-based classification system. The three-dimensional structures of the 13 FAEs were modeled for structural analysis of the feruloylome. The three genes coding for three enzymes, viz., A.O.2, A.O.8 and A.O.10 from the feruloylome of A. oryzae, representing sub-families with unknown functional features, were heterologously expressed in Pichia pastoris, characterized for substrate specificity and structural characterization through CD spectroscopy. Common feature-based pharamacophore models were developed according to substrate specificity characteristics of the three enzymes. The active site residues were identified for the three expressed FAEs by determining the titration curves of amino acid residues as a function of the pH by applying molecular simulations. Conclusions/Significance: Our findings on the structure-function relationships and substrate specificity of the FAEs of A. oryzae will be instrumental for further understanding of the FAE families in the novel classification system. The developed pharmacophore models could be applied for virtual screening of compound databases for short listing the putative substrates prior to docking studies or for post-processing docking results to remove false positives. Our study exemplifies how computational predictions can complement to the information obtained through experimental methods. © 2012 Udatha et al.published_or_final_versio

    Glycoprotein Ib activation by thrombin stimulates the energy metabolism in human platelets

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    <div><p>Thrombin-induced platelet activation requires substantial amounts of ATP. However, the specific contribution of each ATP-generating pathway <i>i</i>.<i>e</i>., oxidative phosphorylation (OxPhos) versus glycolysis and the biochemical mechanisms involved in the thrombin-induced activation of energy metabolism remain unclear. Here we report an integral analysis on the role of both energy pathways in human platelets activated by several agonists, and the signal transducing mechanisms associated with such activation. We found that thrombin, Trap-6, arachidonic acid, collagen, A23187, epinephrine and ADP significantly increased glycolytic flux (3–38 times <i>vs</i>. non-activated platelets) whereas ristocetin was ineffective. OxPhos (33 times) and mitochondrial transmembrane potential (88%) were increased only by thrombin. OxPhos was the main source of ATP in thrombin-activated platelets, whereas in platelets activated by any of the other agonists, glycolysis was the principal ATP supplier. In order to establish the biochemical mechanisms involved in the thrombin-induced OxPhos activation in platelets, several signaling pathways associated with mitochondrial activation were analyzed. Wortmannin and LY294002 (PI3K/Akt pathway inhibitors), ristocetin and heparin (GPIb inhibitors) as well as resveratrol, ATP (calcium-release inhibitors) and PP1 (Tyr-phosphorylation inhibitor) prevented the thrombin-induced platelet activation. These results suggest that thrombin activates OxPhos and glycolysis through GPIb-dependent signaling involving PI3K and Akt activation, calcium mobilization and protein phosphorylation.</p></div

    Signatures of arithmetic simplicity in metabolic network architecture

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    Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

    Intracerebroventricular Leptin Infusion Improves Glucose Homeostasis in Lean Type 2 Diabetic MKR Mice via Hepatic Vagal and Non-Vagal Mechanisms

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    MKR mice, lacking insulin-like growth factor 1 receptor (IGF-1R) signaling in skeletal muscle, are lean yet hyperlipidemic, hyperinsulinemic, and hyperglycemic, with severe insulin resistance and elevated hepatic and skeletal muscle levels of triglycerides. We have previously shown that chronic peripheral administration of the adipokine leptin improves hepatic insulin sensitivity in these mice independently of its effects on food intake. As central leptin signaling has been implicated in the control of peripheral glucose homeostasis, here we examined the ability of central intracerebroventricular leptin administration to affect energy balance and peripheral glucose homeostasis in non-obese diabetic male MKR mice. Central leptin significantly reduced food intake, body weight gain and adiposity, as well as serum glucose, insulin, leptin, free fatty acid and triglyceride levels relative to ACSF treated controls. These reductions were accompanied by increased fat oxidation as measured by indirect calorimetry, as well as increased oxygen consumption. Central leptin also improved glucose tolerance and hepatic insulin sensitivity determined using the euglycemic-hyperinsulinemic clamps relative to pair fed vehicle treated controls, as well as increasing the rate of glucose disappearance. Hepatic vagotomy only partially reversed the ability of central leptin to improve glucose tolerance. These results demonstrate that central leptin dramatically improves insulin sensitivity independently of its effects on food intake, in a lean mouse model of type 2 diabetes. The findings also suggest that: 1) both hepatic vagal and non-vagal pathways contribute to this improvement, and 2) central leptin alters glucose disposal in skeletal muscle in this model
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