Linear analysis near a steady-state of biochemical networks: control analysis, correlation metrics and circuit theory

Directory of Open Access Journals (Sweden)

Qian Hong

2008-05-01

Full Text Available Abstract Background: Several approaches, including metabolic control analysis (MCA, flux balance analysis (FBA, correlation metric construction (CMC, and biochemical circuit theory (BCT, have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. Results: In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RT BS and ST BS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. Conclusion: One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA.

Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space

Directory of Open Access Journals (Sweden)

St Laurent Georges

2010-03-01

Full Text Available Abstract Background Signal transduction networks represent the information processing systems that dictate which dynamical regimes of biochemical activity can be accessible to a cell under certain circumstances. One of the major concerns in molecular systems biology is centered on the elucidation of the robustness properties and information processing capabilities of signal transduction networks. Achieving this goal requires the establishment of causal relations between the design principle of biochemical reaction systems and their emergent dynamical behaviors. Methods In this study, efforts were focused in the construction of a relatively well informed, deterministic, non-linear dynamic model, accounting for reaction mechanisms grounded on standard mass action and Hill saturation kinetics, of the canonical reaction topology underlying Toll-like receptor 4 (TLR4-mediated signaling events. This signaling mechanism has been shown to be deployed in macrophages during a relatively short time window in response to lypopolysaccharyde (LPS stimulation, which leads to a rapidly mounted innate immune response. An extensive computational exploration of the biochemical reaction space inhabited by this signal transduction network was performed via local and global perturbation strategies. Importantly, a broad spectrum of biologically plausible dynamical regimes accessible to the network in widely scattered regions of parameter space was reconstructed computationally. Additionally, experimentally reported transcriptional readouts of target pro-inflammatory genes, which are actively modulated by the network in response to LPS stimulation, were also simulated. This was done with the main goal of carrying out an unbiased statistical assessment of the intrinsic robustness properties of this canonical reaction topology. Results Our simulation results provide convincing numerical evidence supporting the idea that a canonical reaction mechanism of the TLR4

The alterations in biochemical signaling of hippocampal network activity in the autism brain The alterations in biochemical signaling of hippocampal network activity in the autism brain The alterations in biochemical signaling of hippocampal network activity in the autism brain

Institute of Scientific and Technical Information of China (English)

田允; 黄继云; 王锐; 陶蓉蓉; 卢应梅; 廖美华; 陆楠楠; 李静; 芦博; 韩峰

2012-01-01

Autism is a highly heritable neurodevelopmental condition characterized by impaired social interaction and communication. However, the role of synaptic dysfunction during development of autism remains unclear. In the present study, we address the alterations of biochemical signaling in hippocampal network following induction of the autism in experimental animals. Here, the an- imal disease model and DNA array being used to investigate the differences in transcriptome or- ganization between autistic and normal brain by gene co--expression network analysis.

Scalable rule-based modelling of allosteric proteins and biochemical networks.

Directory of Open Access Journals (Sweden)

Julien F Ollivier

2010-11-01

Full Text Available Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

Efficient Parallel Statistical Model Checking of Biochemical Networks

Directory of Open Access Journals (Sweden)

Paolo Ballarini

2009-12-01

Full Text Available We consider the problem of verifying stochastic models of biochemical networks against behavioral properties expressed in temporal logic terms. Exact probabilistic verification approaches such as, for example, CSL/PCTL model checking, are undermined by a huge computational demand which rule them out for most real case studies. Less demanding approaches, such as statistical model checking, estimate the likelihood that a property is satisfied by sampling executions out of the stochastic model. We propose a methodology for efficiently estimating the likelihood that a LTL property P holds of a stochastic model of a biochemical network. As with other statistical verification techniques, the methodology we propose uses a stochastic simulation algorithm for generating execution samples, however there are three key aspects that improve the efficiency: first, the sample generation is driven by on-the-fly verification of P which results in optimal overall simulation time. Second, the confidence interval estimation for the probability of P to hold is based on an efficient variant of the Wilson method which ensures a faster convergence. Third, the whole methodology is designed according to a parallel fashion and a prototype software tool has been implemented that performs the sampling/verification process in parallel over an HPC architecture.

Emergence of switch-like behavior in a large family of simple biochemical networks.

Directory of Open Access Journals (Sweden)

Dan Siegal-Gaskins

2011-05-01

Full Text Available Bistability plays a central role in the gene regulatory networks (GRNs controlling many essential biological functions, including cellular differentiation and cell cycle control. However, establishing the network topologies that can exhibit bistability remains a challenge, in part due to the exceedingly large variety of GRNs that exist for even a small number of components. We begin to address this problem by employing chemical reaction network theory in a comprehensive in silico survey to determine the capacity for bistability of more than 40,000 simple networks that can be formed by two transcription factor-coding genes and their associated proteins (assuming only the most elementary biochemical processes. We find that there exist reaction rate constants leading to bistability in ∼90% of these GRN models, including several circuits that do not contain any of the TF cooperativity commonly associated with bistable systems, and the majority of which could only be identified as bistable through an original subnetwork-based analysis. A topological sorting of the two-gene family of networks based on the presence or absence of biochemical reactions reveals eleven minimal bistable networks (i.e., bistable networks that do not contain within them a smaller bistable subnetwork. The large number of previously unknown bistable network topologies suggests that the capacity for switch-like behavior in GRNs arises with relative ease and is not easily lost through network evolution. To highlight the relevance of the systematic application of CRNT to bistable network identification in real biological systems, we integrated publicly available protein-protein interaction, protein-DNA interaction, and gene expression data from Saccharomyces cerevisiae, and identified several GRNs predicted to behave in a bistable fashion.

Identification of alterations in the Jacobian of biochemical reaction networks from steady state covariance data at two conditions.

Science.gov (United States)

Kügler, Philipp; Yang, Wei

2014-06-01

Model building of biochemical reaction networks typically involves experiments in which changes in the behavior due to natural or experimental perturbations are observed. Computational models of reaction networks are also used in a systems biology approach to study how transitions from a healthy to a diseased state result from changes in genetic or environmental conditions. In this paper we consider the nonlinear inverse problem of inferring information about the Jacobian of a Langevin type network model from covariance data of steady state concentrations associated to two different experimental conditions. Under idealized assumptions on the Langevin fluctuation matrices we prove that relative alterations in the network Jacobian can be uniquely identified when comparing the two data sets. Based on this result and the premise that alteration is locally confined to separable parts due to network modularity we suggest a computational approach using hybrid stochastic-deterministic optimization for the detection of perturbations in the network Jacobian using the sparsity promoting effect of [Formula: see text]-penalization. Our approach is illustrated by means of published metabolomic and signaling reaction networks.

Coarse-graining stochastic biochemical networks: adiabaticity and fast simulations

Energy Technology Data Exchange (ETDEWEB)

Nemenman, Ilya [Los Alamos National Laboratory; Sinitsyn, Nikolai [Los Alamos National Laboratory; Hengartner, Nick [Los Alamos National Laboratory

2008-01-01

We propose a universal approach for analysis and fast simulations of stiff stochastic biochemical kinetics networks, which rests on elimination of fast chemical species without a loss of information about mesoscoplc, non-Poissonian fluctuations of the slow ones. Our approach, which is similar to the Born-Oppenhelmer approximation in quantum mechanics, follows from the stochastic path Integral representation of the cumulant generating function of reaction events. In applications with a small number of chemIcal reactions, It produces analytical expressions for cumulants of chemical fluxes between the slow variables. This allows for a low-dimensional, Interpretable representation and can be used for coarse-grained numerical simulation schemes with a small computational complexity and yet high accuracy. As an example, we derive the coarse-grained description for a chain of biochemical reactions, and show that the coarse-grained and the microscopic simulations are in an agreement, but the coarse-gralned simulations are three orders of magnitude faster.

Modularization of biochemical networks based on classification of Petri net t-invariants.

Science.gov (United States)

Grafahrend-Belau, Eva; Schreiber, Falk; Heiner, Monika; Sackmann, Andrea; Junker, Björn H; Grunwald, Stefanie; Speer, Astrid; Winder, Katja; Koch, Ina

2008-02-08

Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find

Modularization of biochemical networks based on classification of Petri net t-invariants

Directory of Open Access Journals (Sweden)

Grunwald Stefanie

2008-02-01

Full Text Available Abstract Background Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior. With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system. Methods Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t

Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

LENUS (Irish Health Repository)

Casey, Fergal

2011-08-22

Abstract Background Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks. Results We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter. Conclusion We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.

CADLIVE toolbox for MATLAB: automatic dynamic modeling of biochemical networks with comprehensive system analysis.

Science.gov (United States)

Inoue, Kentaro; Maeda, Kazuhiro; Miyabe, Takaaki; Matsuoka, Yu; Kurata, Hiroyuki

2014-09-01

Mathematical modeling has become a standard technique to understand the dynamics of complex biochemical systems. To promote the modeling, we had developed the CADLIVE dynamic simulator that automatically converted a biochemical map into its associated mathematical model, simulated its dynamic behaviors and analyzed its robustness. To enhance the feasibility by CADLIVE and extend its functions, we propose the CADLIVE toolbox available for MATLAB, which implements not only the existing functions of the CADLIVE dynamic simulator, but also the latest tools including global parameter search methods with robustness analysis. The seamless, bottom-up processes consisting of biochemical network construction, automatic construction of its dynamic model, simulation, optimization, and S-system analysis greatly facilitate dynamic modeling, contributing to the research of systems biology and synthetic biology. This application can be freely downloaded from http://www.cadlive.jp/CADLIVE_MATLAB/ together with an instruction.

A moment-convergence method for stochastic analysis of biochemical reaction networks.

Science.gov (United States)

Zhang, Jiajun; Nie, Qing; Zhou, Tianshou

2016-05-21

Traditional moment-closure methods need to assume that high-order cumulants of a probability distribution approximate to zero. However, this strong assumption is not satisfied for many biochemical reaction networks. Here, we introduce convergent moments (defined in mathematics as the coefficients in the Taylor expansion of the probability-generating function at some point) to overcome this drawback of the moment-closure methods. As such, we develop a new analysis method for stochastic chemical kinetics. This method provides an accurate approximation for the master probability equation (MPE). In particular, the connection between low-order convergent moments and rate constants can be more easily derived in terms of explicit and analytical forms, allowing insights that would be difficult to obtain through direct simulation or manipulation of the MPE. In addition, it provides an accurate and efficient way to compute steady-state or transient probability distribution, avoiding the algorithmic difficulty associated with stiffness of the MPE due to large differences in sizes of rate constants. Applications of the method to several systems reveal nontrivial stochastic mechanisms of gene expression dynamics, e.g., intrinsic fluctuations can induce transient bimodality and amplify transient signals, and slow switching between promoter states can increase fluctuations in spatially heterogeneous signals. The overall approach has broad applications in modeling, analysis, and computation of complex biochemical networks with intrinsic noise.

A moment-convergence method for stochastic analysis of biochemical reaction networks

Energy Technology Data Exchange (ETDEWEB)

Zhang, Jiajun [School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275 (China); Nie, Qing [Department of Mathematics, University of California at Irvine, Irvine, California 92697 (United States); Zhou, Tianshou, E-mail: mcszhtsh@mail.sysu.edu.cn [School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275 (China); Guangdong Province Key Laboratory of Computational Science and School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275 (China)

2016-05-21

Traditional moment-closure methods need to assume that high-order cumulants of a probability distribution approximate to zero. However, this strong assumption is not satisfied for many biochemical reaction networks. Here, we introduce convergent moments (defined in mathematics as the coefficients in the Taylor expansion of the probability-generating function at some point) to overcome this drawback of the moment-closure methods. As such, we develop a new analysis method for stochastic chemical kinetics. This method provides an accurate approximation for the master probability equation (MPE). In particular, the connection between low-order convergent moments and rate constants can be more easily derived in terms of explicit and analytical forms, allowing insights that would be difficult to obtain through direct simulation or manipulation of the MPE. In addition, it provides an accurate and efficient way to compute steady-state or transient probability distribution, avoiding the algorithmic difficulty associated with stiffness of the MPE due to large differences in sizes of rate constants. Applications of the method to several systems reveal nontrivial stochastic mechanisms of gene expression dynamics, e.g., intrinsic fluctuations can induce transient bimodality and amplify transient signals, and slow switching between promoter states can increase fluctuations in spatially heterogeneous signals. The overall approach has broad applications in modeling, analysis, and computation of complex biochemical networks with intrinsic noise.

Parametric sensitivity analysis for biochemical reaction networks based on pathwise information theory.

Science.gov (United States)

Pantazis, Yannis; Katsoulakis, Markos A; Vlachos, Dionisios G

2013-10-22

Stochastic modeling and simulation provide powerful predictive methods for the intrinsic understanding of fundamental mechanisms in complex biochemical networks. Typically, such mathematical models involve networks of coupled jump stochastic processes with a large number of parameters that need to be suitably calibrated against experimental data. In this direction, the parameter sensitivity analysis of reaction networks is an essential mathematical and computational tool, yielding information regarding the robustness and the identifiability of model parameters. However, existing sensitivity analysis approaches such as variants of the finite difference method can have an overwhelming computational cost in models with a high-dimensional parameter space. We develop a sensitivity analysis methodology suitable for complex stochastic reaction networks with a large number of parameters. The proposed approach is based on Information Theory methods and relies on the quantification of information loss due to parameter perturbations between time-series distributions. For this reason, we need to work on path-space, i.e., the set consisting of all stochastic trajectories, hence the proposed approach is referred to as "pathwise". The pathwise sensitivity analysis method is realized by employing the rigorously-derived Relative Entropy Rate, which is directly computable from the propensity functions. A key aspect of the method is that an associated pathwise Fisher Information Matrix (FIM) is defined, which in turn constitutes a gradient-free approach to quantifying parameter sensitivities. The structure of the FIM turns out to be block-diagonal, revealing hidden parameter dependencies and sensitivities in reaction networks. As a gradient-free method, the proposed sensitivity analysis provides a significant advantage when dealing with complex stochastic systems with a large number of parameters. In addition, the knowledge of the structure of the FIM can allow to efficiently address

Shape, size, and robustness: feasible regions in the parameter space of biochemical networks.

Directory of Open Access Journals (Sweden)

Adel Dayarian

2009-01-01

Full Text Available The concept of robustness of regulatory networks has received much attention in the last decade. One measure of robustness has been associated with the volume of the feasible region, namely, the region in the parameter space in which the system is functional. In this paper, we show that, in addition to volume, the geometry of this region has important consequences for the robustness and the fragility of a network. We develop an approximation within which we could algebraically specify the feasible region. We analyze the segment polarity gene network to illustrate our approach. The study of random walks in the parameter space and how they exit the feasible region provide us with a rich perspective on the different modes of failure of this network model. In particular, we found that, between two alternative ways of activating Wingless, one is more robust than the other. Our method provides a more complete measure of robustness to parameter variation. As a general modeling strategy, our approach is an interesting alternative to Boolean representation of biochemical networks.

Bistable responses in bacterial genetic networks: Designs and dynamical consequences

Science.gov (United States)

Tiwari, Abhinav; Ray, J. Christian J.; Narula, Jatin; Igoshin, Oleg A.

2011-01-01

A key property of living cells is their ability to react to stimuli with specific biochemical responses. These responses can be understood through the dynamics of underlying biochemical and genetic networks. Evolutionary design principles have been well studied in networks that display graded responses, with a continuous relationship between input signal and system output. Alternatively, biochemical networks can exhibit bistable responses so that over a range of signals the network possesses two stable steady states. In this review, we discuss several conceptual examples illustrating network designs that can result in a bistable response of the biochemical network. Next, we examine manifestations of these designs in bacterial master-regulatory genetic circuits. In particular, we discuss mechanisms and dynamic consequences of bistability in three circuits: two-component systems, sigma-factor networks, and a multistep phosphorelay. Analyzing these examples allows us to expand our knowledge of evolutionary design principles for networks with bistable responses. PMID:21385588

Simulations of biopolymer networks under shear

NARCIS (Netherlands)

Huisman, Elisabeth Margaretha

2011-01-01

In this thesis we present a new method to simulate realistic three-dimensional networks of biopolymers under shear. These biopolymer networks are important for the structural functions of cells and tissues. We use the method to analyze these networks under shear, and consider the elastic modulus,

Biochemical component identification by plasmonic improved whispering gallery mode optical resonance based sensor

Science.gov (United States)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Saetchnikov, Anton V.; Schweiger, Gustav; Ostendorf, Andreas

2014-05-01

Experimental data on detection and identification of variety of biochemical agents, such as proteins, microelements, antibiotic of different generation etc. in both single and multi component solutions under varied in wide range concentration analyzed on the light scattering parameters of whispering gallery mode optical resonance based sensor are represented. Multiplexing on parameters and components has been realized using developed fluidic sensor cell with fixed in adhesive layer dielectric microspheres and data processing. Biochemical component identification has been performed by developed network analysis techniques. Developed approach is demonstrated to be applicable both for single agent and for multi component biochemical analysis. Novel technique based on optical resonance on microring structures, plasmon resonance and identification tools has been developed. To improve a sensitivity of microring structures microspheres fixed by adhesive had been treated previously by gold nanoparticle solution. Another technique used thin film gold layers deposited on the substrate below adhesive. Both biomolecule and nanoparticle injections caused considerable changes of optical resonance spectra. Plasmonic gold layers under optimized thickness also improve parameters of optical resonance spectra. Biochemical component identification has been also performed by developed network analysis techniques both for single and for multi component solution. So advantages of plasmon enhancing optical microcavity resonance with multiparameter identification tools is used for development of a new platform for ultra sensitive label-free biomedical sensor.

Biochemical components and dry matter of lemon and mandarin hybrids under salt stress

Directory of Open Access Journals (Sweden)

Francisco V. da S. Sá

Full Text Available ABSTRACT The objective was to study the biochemical changes and dry matter content in lemon and mandarin hybrids under salt stress during rootstock formation. For this, a study was conducted in randomized complete block, using a 2 x 5 factorial scheme, with two salinity levels (0.3 and 4.0 dS m-1 applied in five citrus rootstock genotypes (1. TSKC x CTARG - 019; 2. LRF; 3. TSKC x (LCR x TR - 040; 4. LCRSTC and 5. LVK, with three replicates and four plants per plot. At 90 days after sowing, saline treatments started to be applied and continued until 120 days after sowing, the moment in which the plants were collected for evaluation of biochemical characteristics and phytomass accumulation. The increase in water salinity negatively affected the biochemical components and dry matter accumulation of citrus genotypes. The genotypes TSKC x (LCR x TR - 040, LCRSTC and LVK were the least affected by salt stress, standing out as the materials most tolerant to salinity.

HRSSA – Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks

International Nuclear Information System (INIS)

Marchetti, Luca; Priami, Corrado; Thanh, Vo Hong

2016-01-01

This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.

HRSSA – Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks

Energy Technology Data Exchange (ETDEWEB)

Marchetti, Luca, E-mail: marchetti@cosbi.eu [The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, 1, 38068 Rovereto (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, 1, 38068 Rovereto (Italy); University of Trento, Department of Mathematics (Italy); Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI), Piazza Manifattura, 1, 38068 Rovereto (Italy)

2016-07-15

This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.

Multidimensional biochemical information processing of dynamical patterns.

Science.gov (United States)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

Directory of Open Access Journals (Sweden)

Joseph A. Wayman

2015-03-01

Full Text Available Cell-free systems offer many advantages for the study, manipulation and modeling of metabolism compared to in vivo processes. Many of the challenges confronting genome-scale kinetic modeling can potentially be overcome in a cell-free system. For example, there is no complex transcriptional regulation to consider, transient metabolic measurements are easier to obtain, and we no longer have to consider cell growth. Thus, cell-free operation holds several significant advantages for model development, identification and validation. Theoretically, genome-scale cell-free kinetic models may be possible for industrially important organisms, such as E. coli, if a simple, tractable framework for integrating allosteric regulation with enzyme kinetics can be formulated. Toward this unmet need, we present an effective biochemical network modeling framework for building dynamic cell-free metabolic models. The key innovation of our approach is the integration of simple effective rules encoding complex allosteric regulation with traditional kinetic pathway modeling. We tested our approach by modeling the time evolution of several hypothetical cell-free metabolic networks. We found that simple effective rules, when integrated with traditional enzyme kinetic expressions, captured complex allosteric patterns such as ultrasensitivity or non-competitive inhibition in the absence of mechanistic information. Second, when integrated into network models, these rules captured classic regulatory patterns such as product-induced feedback inhibition. Lastly, we showed, at least for the network architectures considered here, that we could simultaneously estimate kinetic parameters and allosteric connectivity from synthetic data starting from an unbiased collection of possible allosteric structures using particle swarm optimization. However, when starting with an initial population that was heavily enriched with incorrect structures, our particle swarm approach could converge

Strategies for optical transport network recovery under epidemic network failures

DEFF Research Database (Denmark)

Ruepp, Sarah Renée; Fagertun, Anna Manolova; Kosteas, Vasileios

2015-01-01

The current trend in deploying automatic control plane solutions for increased flexibility in the optical transport layer leads to numerous advantages for both the operators and the customers, but also pose challenges related to the stability of the network and its ability to operate in a robust...... manner under different failure scenarios. This work evaluates two rerouting strategies and proposes four policies for failure handling in a connection-oriented optical transport network, under generalized multiprotocol label switching control plane. The performance of the strategies and the policies......, and that there exist a clear trade-off between policy performance and network resource consumption, which must be addressed by network operators for improved robustness of their transport infrastructures. Applying proactive methods for avoiding areas where epidemic failures spread results in 50% less connections...

SABIO-RK: A data warehouse for biochemical reactions and their kinetics

Directory of Open Access Journals (Sweden)

Krebs Olga

2007-03-01

Full Text Available Systems biology is an emerging field that aims at obtaining a system-level understanding of biological processes. The modelling and simulation of networks of biochemical reactions have great and promising application potential but require reliable kinetic data. In order to support the systems biology community with such data we have developed SABIO-RK (System for the Analysis of Biochemical Pathways - Reaction Kinetics, a curated database with information about biochemical reactions and their kinetic properties, which allows researchers to obtain and compare kinetic data and to integrate them into models of biochemical networks. SABIO-RK is freely available for academic use at http://sabio.villa-bosch.de/SABIORK/.

Interspecific Competition Underlying Mutualistic Networks

Science.gov (United States)

Maeng, Seong Eun; Lee, Jae Woo; Lee, Deok-Sun

2012-03-01

Multiple classes of interactions may exist affecting one another in a given system. For the mutualistic networks of plants and pollinating animals, it has been known that the degree distribution is broad but often deviates from power-law form more significantly for plants than animals. To illuminate the origin of such asymmetry, we study a model network in which links are assigned under generalized preferential-selection rules between two groups of nodes and find the sensitive dependence of the resulting connectivity pattern on the model parameters. The nonlinearity of preferential selection can come from interspecific interactions among animals and among plants. The model-based analysis of real-world mutualistic networks suggests that a new animal determines its partners not only by their abundance but also under the competition with existing animal species, which leads to the stretched-exponential degree distributions of plants.

Nonequilibrium steady state of biochemical cycle kinetics under non-isothermal conditions

Science.gov (United States)

Jin, Xiao; Ge, Hao

2018-04-01

The nonequilibrium steady state of isothermal biochemical cycle kinetics has been extensively studied, but that under non-isothermal conditions has been much less extensively investigated. When the heat exchange between subsystems is slow, the isothermal assumption of the whole system breaks down, as is true for many types of living organisms. Here, starting with a four-state model of molecular transporter across the cell membrane, we generalize the nonequilibrium steady-state theory of isothermal biochemical cycle kinetics to the circumstances with non-uniform temperatures of subsystems in terms of general master equation models. We obtain a new thermodynamic relationship between the chemical reaction rates and thermodynamic potentials in non-isothermal circumstances, based on the overdamped dynamics along the continuous reaction coordinate. We show that the entropy production can vary up to 3% in real cells, even when the temperature difference across the cell membrane is only approximately 1 K. We then decompose the total thermodynamic driving force into its thermal and chemical components and predict that the net flux of molecules transported by the molecular transporter can potentially go against the temperature gradient in the absence of a chemical driving force. Furthermore, we demonstrate that the simple application of the isothermal transition-state rate formula for each chemical reaction in terms of only the reactant’ temperature is not thermodynamically consistent. Therefore, we mathematically derive several revised reaction rate formulas that are not only consistent with the new thermodynamic relationship but also approximate the exact reaction rate better than Kramers’ rate formula under isothermal conditions.

Biochemical and secondary metabolites changes under moisture ...

African Journals Online (AJOL)

The study showed the importance of carbohydrate and nitrogen cycle related metabolites in mediating tolerance in cassava by affecting their phenotypic expression in the plant. Keywords: Hydrothermal stress, bio-chemicals, pigments, secondary metabolites, cassava. African Journal of Biotechnology, Vol 13(31) 3173-3186 ...

Synchronization analysis of coloured delayed networks under ...

Indian Academy of Sciences (India)

This paper investigates synchronization of coloured delayed networks under decentralized pinning intermittent control. To begin with, the time delays are taken into account in the coloured networks. In addition, we propose a decentralized pinning intermittent control for coloured delayed networks, which is different from that ...

Glycinebetaine-induced modulation in some biochemical and physiological attributes of okra under salt

International Nuclear Information System (INIS)

Saeed, H.M.; Mirza, J.I.

2016-01-01

Role of glycinebetaine (GB) in okra (Abelmoschus esculentus L. Moench) cv. Subz-pari plants grown under salinity stress was investigated under field conditions. The crop was planted under varying levels (0, 200 and 400 mg NaCl per kg of soil) of salinity stress. Foliar application of 75 mM GB was employed at two phases i.e. after 30 and 60 days of sowing. Imposition of salinity stress significantly increased leaf GB and proline contents but significantly reduced leaf chlorophyll content and physiological characteristics such as rate of photosynthesis (Pn), rate of transpiration (E), stomatal conductance (gs) and leaf relative water content (LRWC). Exogenous application of GB significantly increased GB content but decreased proline content of leaves and improved various gas exchange characteristics/physiological parameters. The present results thus indicated that foliar application of GB (75 mM) can modulate various biochemical and gas exchange parameters of okra, grown under salt stress. (author)

Robustness analysis of interdependent networks under multiple-attacking strategies

Science.gov (United States)

Gao, Yan-Li; Chen, Shi-Ming; Nie, Sen; Ma, Fei; Guan, Jun-Jie

2018-04-01

The robustness of complex networks under attacks largely depends on the structure of a network and the nature of the attacks. Previous research on interdependent networks has focused on two types of initial attack: random attack and degree-based targeted attack. In this paper, a deliberate attack function is proposed, where six kinds of deliberate attacking strategies can be derived by adjusting the tunable parameters. Moreover, the robustness of four types of interdependent networks (BA-BA, ER-ER, BA-ER and ER-BA) with different coupling modes (random, positive and negative correlation) is evaluated under different attacking strategies. Interesting conclusions could be obtained. It can be found that the positive coupling mode can make the vulnerability of the interdependent network to be absolutely dependent on the most vulnerable sub-network under deliberate attacks, whereas random and negative coupling modes make the vulnerability of interdependent network to be mainly dependent on the being attacked sub-network. The robustness of interdependent network will be enhanced with the degree-degree correlation coefficient varying from positive to negative. Therefore, The negative coupling mode is relatively more optimal than others, which can substantially improve the robustness of the ER-ER network and ER-BA network. In terms of the attacking strategies on interdependent networks, the degree information of node is more valuable than the betweenness. In addition, we found a more efficient attacking strategy for each coupled interdependent network and proposed the corresponding protection strategy for suppressing cascading failure. Our results can be very useful for safety design and protection of interdependent networks.

Analysis and Reduction of Complex Networks Under Uncertainty.

Energy Technology Data Exchange (ETDEWEB)

Ghanem, Roger G [University of Southern California

2014-07-31

This effort was a collaboration with Youssef Marzouk of MIT, Omar Knio of Duke University (at the time at Johns Hopkins University) and Habib Najm of Sandia National Laboratories. The objective of this effort was to develop the mathematical and algorithmic capacity to analyze complex networks under uncertainty. Of interest were chemical reaction networks and smart grid networks. The statements of work for USC focused on the development of stochastic reduced models for uncertain networks. The USC team was led by Professor Roger Ghanem and consisted of one graduate student and a postdoc. The contributions completed by the USC team consisted of 1) methodology and algorithms to address the eigenvalue problem, a problem of significance in the stability of networks under stochastic perturbations, 2) methodology and algorithms to characterize probability measures on graph structures with random flows. This is an important problem in characterizing random demand (encountered in smart grid) and random degradation (encountered in infrastructure systems), as well as modeling errors in Markov Chains (with ubiquitous relevance !). 3) methodology and algorithms for treating inequalities in uncertain systems. This is an important problem in the context of models for material failure and network flows under uncertainty where conditions of failure or flow are described in the form of inequalities between the state variables.

Some scale-free networks could be robust under selective node attacks

Science.gov (United States)

Zheng, Bojin; Huang, Dan; Li, Deyi; Chen, Guisheng; Lan, Wenfei

2011-04-01

It is a mainstream idea that scale-free network would be fragile under the selective attacks. Internet is a typical scale-free network in the real world, but it never collapses under the selective attacks of computer viruses and hackers. This phenomenon is different from the deduction of the idea above because this idea assumes the same cost to delete an arbitrary node. Hence this paper discusses the behaviors of the scale-free network under the selective node attack with different cost. Through the experiments on five complex networks, we show that the scale-free network is possibly robust under the selective node attacks; furthermore, the more compact the network is, and the larger the average degree is, then the more robust the network is; with the same average degrees, the more compact the network is, the more robust the network is. This result would enrich the theory of the invulnerability of the network, and can be used to build robust social, technological and biological networks, and also has the potential to find the target of drugs.

A dynamically coupled allosteric network underlies binding cooperativity in Src kinase.

Science.gov (United States)

Foda, Zachariah H; Shan, Yibing; Kim, Eric T; Shaw, David E; Seeliger, Markus A

2015-01-20

Protein tyrosine kinases are attractive drug targets because many human diseases are associated with the deregulation of kinase activity. However, how the catalytic kinase domain integrates different signals and switches from an active to an inactive conformation remains incompletely understood. Here we identify an allosteric network of dynamically coupled amino acids in Src kinase that connects regulatory sites to the ATP- and substrate-binding sites. Surprisingly, reactants (ATP and peptide substrates) bind with negative cooperativity to Src kinase while products (ADP and phosphopeptide) bind with positive cooperativity. We confirm the molecular details of the signal relay through the allosteric network by biochemical studies. Experiments on two additional protein tyrosine kinases indicate that the allosteric network may be largely conserved among these enzymes. Our work provides new insights into the regulation of protein tyrosine kinases and establishes a potential conduit by which resistance mutations to ATP-competitive kinase inhibitors can affect their activity.

Improved methods for the mathematically controlled comparison of biochemical systems

Directory of Open Access Journals (Sweden)

Schwacke John H

2004-06-01

Full Text Available Abstract The method of mathematically controlled comparison provides a structured approach for the comparison of alternative biochemical pathways with respect to selected functional effectiveness measures. Under this approach, alternative implementations of a biochemical pathway are modeled mathematically, forced to be equivalent through the application of selected constraints, and compared with respect to selected functional effectiveness measures. While the method has been applied successfully in a variety of studies, we offer recommendations for improvements to the method that (1 relax requirements for definition of constraints sufficient to remove all degrees of freedom in forming the equivalent alternative, (2 facilitate generalization of the results thus avoiding the need to condition those findings on the selected constraints, and (3 provide additional insights into the effect of selected constraints on the functional effectiveness measures. We present improvements to the method and related statistical models, apply the method to a previously conducted comparison of network regulation in the immune system, and compare our results to those previously reported.

Soil Biochemical Changes Induced by Poultry Litter Application and Conservation Tillage under Cotton Production Systems

Directory of Open Access Journals (Sweden)

Seshadri Sajjala

2012-07-01

Full Text Available Problems arising from conventional tillage (CT systems (such as soil erosion, decrease of organic matter, environmental damage etc. have led many farmers to the adoption of no-till (NT systems that are more effective in improving soil physical, chemical and microbial properties. Results from this study clearly indicated that NT, mulch tillage (MT, and winter rye cover cropping systems increased the activity of phosphatase, β-glucosidase and arylsulfatase at a 0–10 cm soil depth but decreased the activity of these enzymes at 10–20 cm. The increase in enzyme activity was a good indicator of intensive soil microbial activity in different soil management practices. Poultry litter (PL application under NT, MT, and rye cropping system could be considered as effective management practices due to the improvement in carbon (C content and the biochemical quality at the soil surface. The activities of the studied enzymes were highly correlated with soil total nitrogen (STN soil organic carbon (SOC at the 0–10 cm soil depth, except for acid phosphatase where no correlation was observed. This study revealed that agricultural practices such as tillage, PL, and cover crop cropping system have a noticeable positive effect on soil biochemical activities under cotton production.

Complex networks under dynamic repair model

Science.gov (United States)

Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

2018-01-01

Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

Patterns of Stochastic Behavior in Dynamically Unstable High-Dimensional Biochemical Networks

Directory of Open Access Journals (Sweden)

Simon Rosenfeld

2009-01-01

Full Text Available The question of dynamical stability and stochastic behavior of large biochemical networks is discussed. It is argued that stringent conditions of asymptotic stability have very little chance to materialize in a multidimensional system described by the differential equations of chemical kinetics. The reason is that the criteria of asymptotic stability (Routh- Hurwitz, Lyapunov criteria, Feinberg’s Deficiency Zero theorem would impose the limitations of very high algebraic order on the kinetic rates and stoichiometric coefficients, and there are no natural laws that would guarantee their unconditional validity. Highly nonlinear, dynamically unstable systems, however, are not necessarily doomed to collapse, as a simple Jacobian analysis would suggest. It is possible that their dynamics may assume the form of pseudo-random fluctuations quite similar to a shot noise, and, therefore, their behavior may be described in terms of Langevin and Fokker-Plank equations. We have shown by simulation that the resulting pseudo-stochastic processes obey the heavy-tailed Generalized Pareto Distribution with temporal sequence of pulses forming the set of constituent-specific Poisson processes. Being applied to intracellular dynamics, these properties are naturally associated with burstiness, a well documented phenomenon in the biology of gene expression.

Reliability of lifeline networks under seismic hazard

International Nuclear Information System (INIS)

Selcuk, A. Sevtap; Yuecemen, M. Semih

1999-01-01

Lifelines, such as pipelines, transportation, communication and power transmission systems, are networks which extend spatially over large geographical regions. The quantification of the reliability (survival probability) of a lifeline under seismic threat requires attention, as the proper functioning of these systems during or after a destructive earthquake is vital. In this study, a lifeline is idealized as an equivalent network with the capacity of its elements being random and spatially correlated and a comprehensive probabilistic model for the assessment of the reliability of lifelines under earthquake loads is developed. The seismic hazard that the network is exposed to is described by a probability distribution derived by using the past earthquake occurrence data. The seismic hazard analysis is based on the 'classical' seismic hazard analysis model with some modifications. An efficient algorithm developed by Yoo and Deo (Yoo YB, Deo N. A comparison of algorithms for terminal pair reliability. IEEE Transactions on Reliability 1988; 37: 210-215) is utilized for the evaluation of the network reliability. This algorithm eliminates the CPU time and memory capacity problems for large networks. A comprehensive computer program, called LIFEPACK is coded in Fortran language in order to carry out the numerical computations. Two detailed case studies are presented to show the implementation of the proposed model

Line and lattice networks under deterministic interference models

NARCIS (Netherlands)

Goseling, Jasper; Gastpar, Michael; Weber, Jos H.

Capacity bounds are compared for four different deterministic models of wireless networks, representing four different ways of handling broadcast and superposition in the physical layer. In particular, the transport capacity under a multiple unicast traffic pattern is studied for a 1-D network of

BIOCHEMICAL PROCESSES IN CHERNOZEM SOIL UNDER DIFFERENT FERTILIZATION SYSTEMS

Directory of Open Access Journals (Sweden)

Ecaterina Emnova

2012-06-01

Full Text Available The paper deals with the evaluation of the intensity of certain soil biochemical processes (e.g. soil organic C mineralization at Organic and mixed Mineral+Organic fertilization of typical chernozem in crop rotation dynamics (for 6 years by use of eco-physiological indicators of biological soil quality: microbial biomass carbon, basal soil respiration, as well as, microbial and metabolic quotients. Soil sampling was performed from a long-term field crop experiment, which has been established in 1971 at the Balti steppe (Northern Moldova. The crop types had a more considerable impact on the soil microbial biomass accumulation and community biochemical activity compared to long-term Organic or mixed Mineral + Organic fertilizers amendments. The Org fertilization system doesn’t make it possible to avoid the loss of organic C in arable typical chernozem. The organic fertilizer (cattle manure is able to mitigate the negative consequences of long-term mineral fertilization.

Flows in networks under fuzzy conditions

CERN Document Server

Bozhenyuk, Alexander Vitalievich; Kacprzyk, Janusz; Rozenberg, Igor Naymovich

2017-01-01

This book offers a comprehensive introduction to fuzzy methods for solving flow tasks in both transportation and networks. It analyzes the problems of minimum cost and maximum flow finding with fuzzy nonzero lower flow bounds, and describes solutions to minimum cost flow finding in a network with fuzzy arc capacities and transmission costs. After a concise introduction to flow theory and tasks, the book analyzes two important problems. The first is related to determining the maximum volume for cargo transportation in the presence of uncertain network parameters, such as environmental changes, measurement errors and repair work on the roads. These parameters are represented here as fuzzy triangular, trapezoidal numbers and intervals. The second problem concerns static and dynamic flow finding in networks under fuzzy conditions, and an effective method that takes into account the network’s transit parameters is presented here. All in all, the book provides readers with a practical reference guide to state-of-...

Connection Management and Recovery Strategies under Epidemic Network Failures in Optical Transport Networks

DEFF Research Database (Denmark)

Fagertun, Anna Manolova; Ruepp, Sarah Renée

2014-01-01

The current trend in deploying automatic control plane solutions for increased flexibility in the optical transport layer leads to numerous advantages for both the operators and the customers, but also pose challenges related to the stability of the network and its ability to operate in a robust...... manner under attacks. This work proposes four policies for failure handling in a connection-oriented optical transport network, under Generalized MultiProtocol Label Switching control plane, and evaluates their performance under multiple correlated large-scale failures. We employ the Susceptible...... of their transport infrastructures. Applying proactive methods for avoiding areas where epidemic failures spread results in 50% less connections requiring recovery, which translates in improved quality of service to customers....

Asymptotic stability of a genetic network under impulsive control

International Nuclear Information System (INIS)

Li Fangfei; Sun Jitao

2010-01-01

The study of the stability of genetic network is an important motif for the understanding of the living organism at both molecular and cellular levels. In this Letter, we provide a theoretical method for analyzing the asymptotic stability of a genetic network under impulsive control. And the sufficient conditions of its asymptotic stability under impulsive control are obtained. Finally, an example is given to illustrate the effectiveness of the obtained method.

Efficient simulation of intrinsic, extrinsic and external noise in biochemical systems

Science.gov (United States)

Pischel, Dennis; Sundmacher, Kai; Flassig, Robert J.

2017-01-01

Abstract Motivation: Biological cells operate in a noisy regime influenced by intrinsic, extrinsic and external noise, which leads to large differences of individual cell states. Stochastic effects must be taken into account to characterize biochemical kinetics accurately. Since the exact solution of the chemical master equation, which governs the underlying stochastic process, cannot be derived for most biochemical systems, approximate methods are used to obtain a solution. Results: In this study, a method to efficiently simulate the various sources of noise simultaneously is proposed and benchmarked on several examples. The method relies on the combination of the sigma point approach to describe extrinsic and external variability and the τ-leaping algorithm to account for the stochasticity due to probabilistic reactions. The comparison of our method to extensive Monte Carlo calculations demonstrates an immense computational advantage while losing an acceptable amount of accuracy. Additionally, the application to parameter optimization problems in stochastic biochemical reaction networks is shown, which is rarely applied due to its huge computational burden. To give further insight, a MATLAB script is provided including the proposed method applied to a simple toy example of gene expression. Availability and implementation: MATLAB code is available at Bioinformatics online. Contact: flassig@mpi-magdeburg.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28881987

Silicon mediated biochemical changes in wheat under salinized and ...

African Journals Online (AJOL)

Silicon (Si) can alleviate salinity damage, a major threat to agriculture that causes instability in wheat production. We report on the effects of silicon (150 mg L-1) on the morphological, physiological and biochemical traits in wheat (Triticum aestivum L.) cultivars (salt sensitive; Auqab-2000 and salt tolerant; SARC-5) differing ...

Simulation studies in biochemical signaling and enzyme reactions

Science.gov (United States)

Nelatury, Sudarshan R.; Vagula, Mary C.

2014-06-01

Biochemical pathways characterize various biochemical reaction schemes that involve a set of species and the manner in which they are connected. Determination of schematics that represent these pathways is an important task in understanding metabolism and signal transduction. Examples of these Pathways are: DNA and protein synthesis, and production of several macro-molecules essential for cell survival. A sustained feedback mechanism arises in gene expression and production of mRNA that lead to protein synthesis if the protein so synthesized serves as a transcription factor and becomes a repressor of the gene expression. The cellular regulations are carried out through biochemical networks consisting of reactions and regulatory proteins. Systems biology is a relatively new area that attempts to describe the biochemical pathways analytically and develop reliable mathematical models for the pathways. A complete understanding of chemical reaction kinetics is prohibitively hard thanks to the nonlinear and highly complex mechanisms that regulate protein formation, but attempting to numerically solve some of the governing differential equations seems to offer significant insight about their biochemical picture. To validate these models, one can perform simple experiments in the lab. This paper introduces fundamental ideas in biochemical signaling and attempts to take first steps into the understanding of biochemical oscillations. Initially, the two-pool model of calcium is used to describe the dynamics behind the oscillations. Later we present some elementary results showing biochemical oscillations arising from solving differential equations of Elowitz and Leibler using MATLAB software.

Robust Optimization of Fourth Party Logistics Network Design under Disruptions

Directory of Open Access Journals (Sweden)

Jia Li

2015-01-01

Full Text Available The Fourth Party Logistics (4PL network faces disruptions of various sorts under the dynamic and complex environment. In order to explore the robustness of the network, the 4PL network design with consideration of random disruptions is studied. The purpose of the research is to construct a 4PL network that can provide satisfactory service to customers at a lower cost when disruptions strike. Based on the definition of β-robustness, a robust optimization model of 4PL network design under disruptions is established. Based on the NP-hard characteristic of the problem, the artificial fish swarm algorithm (AFSA and the genetic algorithm (GA are developed. The effectiveness of the algorithms is tested and compared by simulation examples. By comparing the optimal solutions of the 4PL network for different robustness level, it is indicated that the robust optimization model can evade the market risks effectively and save the cost in the maximum limit when it is applied to 4PL network design.

Energy network dispatch optimization under emergency of local energy shortage

International Nuclear Information System (INIS)

Cai, Tianxing; Zhao, Chuanyu; Xu, Qiang

2012-01-01

The consequence of short-time energy shortage under extreme conditions, such as earthquake, tsunami, and hurricane, may cause local areas to suffer from delayed rescues, widespread power outages, tremendous economic losses, and even public safety threats. In such urgent events of local energy shortage, agile energy dispatching through an effective energy transportation network, targeting the minimum energy recovery time, should be a top priority. In this paper, a novel methodology is developed for energy network dispatch optimization under emergency of local energy shortage, which includes four stages of work. First, emergency-area-centered energy network needs to be characterized, where the capacity, quantity, and availability of various energy sources are determined. Second, the energy initial situation under emergency conditions needs to be identified. Then, the energy dispatch optimization is conducted based on a developed MILP (mixed-integer linear programming) model in the third stage. Finally, the sensitivity of the minimum dispatch time with respect to uncertainty parameters is characterized by partitioning the entire space of uncertainty parameters into multiple subspaces. The efficacy of the developed methodology is demonstrated via a case study with in-depth discussions. -- Highlights: ► Address the energy network dispatch problem under emergency of local energy shortage. ► Minimize the energy restoration time for the entire energy network under emergency events. ► Develop a new MILP model and a sensitivity analysis method with respect to uncertainties.

Effects of pulsed magnetic field treatment of soybean seeds on calli growth, cell damage, and biochemical changes under salt stress.

Science.gov (United States)

Radhakrishnan, Ramalingam; Leelapriya, Thasari; Kumari, Bollipo Diana Ranjitha

2012-12-01

The effects of magnetic field (MF) treatments of soybean seeds on calli growth, cell damage, and biochemical changes under salt stress were investigated under controlled conditions. Soybean seeds were exposed to a 1.0 Hz sinusoidal uniform pulsed magnetic field (PMF) of 1.5 µT for 5 h/day for 20 days. Non-treated seeds were considered as controls. For callus regeneration, the embryonic axis explants were taken from seeds and inoculated in a saline medium with a concentration of 10 mM NaCl for calli growth analysis and biochemical changes. The combined treatment of MF and salt stress was found to significantly increase calli fresh weight, total soluble sugar, total protein, and total phenol contents, but it decreased the ascorbic acid, lipid peroxidation, and catalase activity of calli from magnetically exposed seeds compared to the control calli. PMF treatment significantly improved calli tolerance to salt stress in terms of an increase in flavonoid, flavone, flavonole, alkaloid, saponin, total polyphenol, genistein, and daidzein contents under salt stress. The results suggest that PMF treatment of soybean seeds has the potential to counteract the adverse effects of salt stress on calli growth by improving primary and secondary metabolites under salt stress conditions. Copyright © 2012 Wiley Periodicals, Inc.

A Simple Approach to Study Designs in Complex Biochemical ...

Indian Academy of Sciences (India)

Somdatta Sinha

Protein sequences. • Biochemical & Genetic information. REVERSE ENGINEERING. LARGE NETWORKS. FORWARD ENGINEERING. All designs that are not physically forbidden are realizable, but not all realizable designs are functionally effective. (in relation to context and constraints of the system and environment).

Information Diffusion in Facebook-Like Social Networks Under Information Overload

Science.gov (United States)

Li, Pei; Xing, Kai; Wang, Dapeng; Zhang, Xin; Wang, Hui

2013-07-01

Research on social networks has received remarkable attention, since many people use social networks to broadcast information and stay connected with their friends. However, due to the information overload in social networks, it becomes increasingly difficult for users to find useful information. This paper takes Facebook-like social networks into account, and models the process of information diffusion under information overload. The term view scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated is proposed to characterize the information diffusion efficiency. Through theoretical analysis, we find that factors such as network structure and view scope number have no impact on the information diffusion efficiency, which is a surprising result. To verify the results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly.

Modeling of uncertainties in biochemical reactions.

Science.gov (United States)

Mišković, Ljubiša; Hatzimanikatis, Vassily

2011-02-01

Mathematical modeling is an indispensable tool for research and development in biotechnology and bioengineering. The formulation of kinetic models of biochemical networks depends on knowledge of the kinetic properties of the enzymes of the individual reactions. However, kinetic data acquired from experimental observations bring along uncertainties due to various experimental conditions and measurement methods. In this contribution, we propose a novel way to model the uncertainty in the enzyme kinetics and to predict quantitatively the responses of metabolic reactions to the changes in enzyme activities under uncertainty. The proposed methodology accounts explicitly for mechanistic properties of enzymes and physico-chemical and thermodynamic constraints, and is based on formalism from systems theory and metabolic control analysis. We achieve this by observing that kinetic responses of metabolic reactions depend: (i) on the distribution of the enzymes among their free form and all reactive states; (ii) on the equilibrium displacements of the overall reaction and that of the individual enzymatic steps; and (iii) on the net fluxes through the enzyme. Relying on this observation, we develop a novel, efficient Monte Carlo sampling procedure to generate all states within a metabolic reaction that satisfy imposed constrains. Thus, we derive the statistics of the expected responses of the metabolic reactions to changes in enzyme levels and activities, in the levels of metabolites, and in the values of the kinetic parameters. We present aspects of the proposed framework through an example of the fundamental three-step reversible enzymatic reaction mechanism. We demonstrate that the equilibrium displacements of the individual enzymatic steps have an important influence on kinetic responses of the enzyme. Furthermore, we derive the conditions that must be satisfied by a reversible three-step enzymatic reaction operating far away from the equilibrium in order to respond to

A study on the evolution of crack networks under thermal fatigue loading

International Nuclear Information System (INIS)

Kamaya, Masayuki; Taheri, Said

2008-01-01

The crack network is a typical cracking morphology caused by thermal fatigue loading. It was pointed out that the crack network appeared under relatively small temperature fluctuations and did not grow deeply. In this study, the mechanism of evolution of crack network and its influence on crack growth was examined by numerical calculation. First, the stress field near two interacting cracks was investigated. It was shown that there are stress-concentration and stress-shielding zones around interacting cracks, and that cracks can form a network under the bi-axial stress condition. Secondly, a Monte Carlo simulation was developed in order to simulate the initiation and growth of cracks under thermal fatigue loading and the evolution of the crack network. The local stress field formed by pre-existing cracks was evaluated by the body force method and its role in the initiation and growth of cracks was considered. The simulation could simulate the evolution of the crack network and change in number of cracks observed in the experiments. It was revealed that reduction in the stress intensity factor due to stress feature in the depth direction under high cycle thermal fatigue loading plays an important role in the evolution of the crack network and that mechanical interaction between cracks in the network affects initiation rather than growth of cracks. The crack network appears only when the crack growth in the depth direction is interrupted. It was concluded that the emergence of the crack network is preferable for the structural integrity of cracked components

Brain network response underlying decisions about abstract reinforcers.

Science.gov (United States)

Mills-Finnerty, Colleen; Hanson, Catherine; Hanson, Stephen Jose

2014-12-01

Decision making studies typically use tasks that involve concrete action-outcome contingencies, in which subjects do something and get something. No studies have addressed decision making involving abstract reinforcers, where there are no action-outcome contingencies and choices are entirely hypothetical. The present study examines these kinds of choices, as well as whether the same biases that exist for concrete reinforcer decisions, specifically framing effects, also apply during abstract reinforcer decisions. We use both General Linear Model as well as Bayes network connectivity analysis using the Independent Multi-sample Greedy Equivalence Search (IMaGES) algorithm to examine network response underlying choices for abstract reinforcers under positive and negative framing. We find for the first time that abstract reinforcer decisions activate the same network of brain regions as concrete reinforcer decisions, including the striatum, insula, anterior cingulate, and VMPFC, results that are further supported via comparison to a meta-analysis of decision making studies. Positive and negative framing activated different parts of this network, with stronger activation in VMPFC during negative framing and in DLPFC during positive, suggesting different decision making pathways depending on frame. These results were further clarified using connectivity analysis, which revealed stronger connections between anterior cingulate, insula, and accumbens during negative framing compared to positive. Taken together, these results suggest that not only do abstract reinforcer decisions rely on the same brain substrates as concrete reinforcers, but that the response underlying framing effects on abstract reinforcers also resemble those for concrete reinforcers, specifically increased limbic system connectivity during negative frames. Copyright © 2014 Elsevier Inc. All rights reserved.

Robustness Analysis of Real Network Topologies Under Multiple Failure Scenarios

DEFF Research Database (Denmark)

Manzano, M.; Marzo, J. L.; Calle, E.

2012-01-01

on topological characteristics. Recently approaches also consider the services supported by such networks. In this paper we carry out a robustness analysis of five real backbone telecommunication networks under defined multiple failure scenarios, taking into account the consequences of the loss of established......Nowadays the ubiquity of telecommunication networks, which underpin and fulfill key aspects of modern day living, is taken for granted. Significant large-scale failures have occurred in the last years affecting telecommunication networks. Traditionally, network robustness analysis has been focused...... connections. Results show which networks are more robust in response to a specific type of failure....

Markovian dynamics on complex reaction networks

Energy Technology Data Exchange (ETDEWEB)

Goutsias, J., E-mail: goutsias@jhu.edu; Jenkinson, G., E-mail: jenkinson@jhu.edu

2013-08-10

Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.

Markovian dynamics on complex reaction networks

International Nuclear Information System (INIS)

Goutsias, J.; Jenkinson, G.

2013-01-01

Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples

CDMA coverage under mobile heterogeneous network load

NARCIS (Netherlands)

Saban, D.; van den Berg, Hans Leo; Boucherie, Richardus J.; Endrayanto, A.I.

2002-01-01

We analytically investigate coverage (determined by the uplink) under non-homogeneous and moving traffic load of third generation UMTS mobile networks. In particular, for different call assignment policies, we investigate cell breathing and the movement of the coverage gap occurring between cells

Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics

Directory of Open Access Journals (Sweden)

Aaron M. Prescott

2016-08-01

underlying ethylene signaling. Analysis of each network topology results in predictions about changes that occur in network components that can be experimentally tested to give insights into which, if either, network underlies ethylene responses.

Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics.

Science.gov (United States)

Prescott, Aaron M; McCollough, Forest W; Eldreth, Bryan L; Binder, Brad M; Abel, Steven M

2016-01-01

Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. The dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i) whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii) what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB). In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB). Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations, and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms underlying ethylene

Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.

Science.gov (United States)

Inoue, Kentaro; Shimozono, Shinichi; Yoshida, Hideaki; Kurata, Hiroyuki

2012-01-01

For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor) algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.

Directory of Open Access Journals (Sweden)

Kentaro Inoue

Full Text Available BACKGROUND: For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. RESULTS: We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. CONCLUSIONS: Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

Effect of abscisic acid on biochemical constituents, enzymatic and non enzymatic antioxidant status of lettuce (Lactuca sativa L. under varied irrigation regimes

Directory of Open Access Journals (Sweden)

Mohamed A. Al Muhairi

2015-12-01

Full Text Available Economically important vegetable crop lettuce (Lactuca sativa L. of family Asteraceae was selected for the present investigation. It is being cultivated in UAE due to its commercial importance. In lettuce cultivation, the major problem is the requirement of large quantities of irrigation water. The present study was aimed to reduce the water consumption of lettuce cultivation; for that, a varied irrigation regime was used with the application of abscisic acid (ABA. The parameters studied were biochemical constituents, antioxidant potential and antioxidant enzymes’ activities in lettuce plants under drought stress and its response to ABA under stress. Drought stress caused an increase in the biochemical constituents like proline and amino acid contents when compared with control and also increased under individual ABA treatments and treatments under drought stress. The non-enzymatic antioxidant molecules like ascorbate and α-tocopherol showed significant increase under drought condition in lettuce. ABA slightly reduced these contents. The antioxidant enzymes like superoxide dismutase, catalase and peroxidase showed significant increase under drought condition and ABA caused significant enhancement in these antioxidant enzymes under drought stress and also in unstressed conditions, thereby protecting the plants from the deleterious effects of drought stress. From the results of this investigation, it can be concluded that ABA in 10 mg g−1 can be used as a potential tool to minimise the drought stress effects in lettuce cultivation.

Inferring the gene network underlying the branching of tomato inflorescence.

Directory of Open Access Journals (Sweden)

Laura Astola

Full Text Available The architecture of tomato inflorescence strongly affects flower production and subsequent crop yield. To understand the genetic activities involved, insight into the underlying network of genes that initiate and control the sympodial growth in the tomato is essential. In this paper, we show how the structure of this network can be derived from available data of the expressions of the involved genes. Our approach starts from employing biological expert knowledge to select the most probable gene candidates behind branching behavior. To find how these genes interact, we develop a stepwise procedure for computational inference of the network structure. Our data consists of expression levels from primary shoot meristems, measured at different developmental stages on three different genotypes of tomato. With the network inferred by our algorithm, we can explain the dynamics corresponding to all three genotypes simultaneously, despite their apparent dissimilarities. We also correctly predict the chronological order of expression peaks for the main hubs in the network. Based on the inferred network, using optimal experimental design criteria, we are able to suggest an informative set of experiments for further investigation of the mechanisms underlying branching behavior.

Dynamics of Clinical and Biochemical Parameters in Patients with Liver Cirrhosis Under the Influence of Complex Therapy with Ursodeoxycholic Acid

Directory of Open Access Journals (Sweden)

M.I. Shved

2013-11-01

Full Text Available It was studied dynamics of clinical and biochemical parameters in patients with liver cirrhosis under the influence of complex treatment using ursosan. It is found that the inclusion of ursosan in complex treatment improves clinical and laboratory parameters, significantly reduces the manifestations of general inflammatory liver syndrome, which prevents the progression of the disease.

A Nondominated Genetic Algorithm Procedure for Multiobjective Discrete Network Design under Demand Uncertainty

Directory of Open Access Journals (Sweden)

Bian Changzhi

2015-01-01

Full Text Available This paper addresses the multiobjective discrete network design problem under demand uncertainty. The OD travel demands are supposed to be random variables with the given probability distribution. The problem is formulated as a bilevel stochastic optimization model where the decision maker’s objective is to minimize the construction cost, the expectation, and the standard deviation of total travel time simultaneously and the user’s route choice is described using user equilibrium model on the improved network under all scenarios of uncertain demand. The proposed model generates globally near-optimal Pareto solutions for network configurations based on the Monte Carlo simulation and nondominated sorting genetic algorithms II. Numerical experiments implemented on Nguyen-Dupuis test network show trade-offs among construction cost, the expectation, and standard deviation of total travel time under uncertainty are obvious. Investment on transportation facilities is an efficient method to improve the network performance and reduce risk under demand uncertainty, but it has an obvious marginal decreasing effect.

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

Science.gov (United States)

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-01-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks.

Science.gov (United States)

Rumschinski, Philipp; Borchers, Steffen; Bosio, Sandro; Weismantel, Robert; Findeisen, Rolf

2010-05-25

Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand. In this work we present a set-based framework that allows to discriminate between competing model hypotheses and to provide guaranteed outer estimates on the model parameters that are consistent with the (possibly sparse and uncertain) experimental measurements. This is obtained by means of exact proofs of model invalidity that exploit the polynomial/rational structure of biochemical reaction networks, and by making use of an efficient strategy to balance solution accuracy and computational effort. The practicability of our approach is illustrated with two case studies. The first study shows that our approach allows to conclusively rule out wrong model hypotheses. The second study focuses on parameter estimation, and shows that the proposed method allows to evaluate the global influence of measurement sparsity, uncertainty, and prior knowledge on the parameter estimates. This can help in designing further experiments leading to improved parameter estimates.

Dynamics of the cell-cycle network under genome-rewiring perturbations

International Nuclear Information System (INIS)

Katzir, Yair; Elhanati, Yuval; Braun, Erez; Averbukh, Inna

2013-01-01

The cell-cycle progression is regulated by a specific network enabling its ordered dynamics. Recent experiments supported by computational models have shown that a core of genes ensures this robust cycle dynamics. However, much less is known about the direct interaction of the cell-cycle regulators with genes outside of the cell-cycle network, in particular those of the metabolic system. Following our recent experimental work, we present here a model focusing on the dynamics of the cell-cycle core network under rewiring perturbations. Rewiring is achieved by placing an essential metabolic gene exclusively under the regulation of a cell-cycle's promoter, forcing the cell-cycle network to function under a multitasking challenging condition; operating in parallel the cell-cycle progression and a metabolic essential gene. Our model relies on simple rate equations that capture the dynamics of the relevant protein–DNA and protein–protein interactions, while making a clear distinction between these two different types of processes. In particular, we treat the cell-cycle transcription factors as limited ‘resources’ and focus on the redistribution of resources in the network during its dynamics. This elucidates the sensitivity of its various nodes to rewiring interactions. The basic model produces the correct cycle dynamics for a wide range of parameters. The simplicity of the model enables us to study the interface between the cell-cycle regulation and other cellular processes. Rewiring a promoter of the network to regulate a foreign gene, forces a multitasking regulatory load. The higher the load on the promoter, the longer is the cell-cycle period. Moreover, in agreement with our experimental results, the model shows that different nodes of the network exhibit variable susceptibilities to the rewiring perturbations. Our model suggests that the topology of the cell-cycle core network ensures its plasticity and flexible interface with other cellular processes

Hidden long evolutionary memory in a model biochemical network

Science.gov (United States)

Ali, Md. Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-04-01

We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

Performance in wireless networks and industrial wireless networks on control processes in real time under industrial environments

Directory of Open Access Journals (Sweden)

Juan F. Monsalve-Posada

2015-01-01

Full Text Available The growing use of Ethernet networks on the industrial automation pyramid has led many companies to develop new devices to operate in requirements of this level, nowadays it is called Industrial Ethernet network, on the market there are various sensors and actuators to industrial scale equipped with this technology, many of these devices are very expensive. In this paper, the performance of two wireless networks is evaluated, the first network has conventional Ethernet devices, and the second network has Industrial Ethernet devices. For the process we vary four parameters such as distance, number of bytes, the signal to noise ratio, and the packet error rate, and then we measure delays and compare with metric statistics results, Box Plot graphs were used for the analysis. Finally, we conclude that under the parameters and conditions tested, wireless networks can serve as a communication system in control applications with allowable delays of up to 50 ms, in addition, the results show a better performance of Industrial Ethernet networks over conventional networks, with differences in the RTT of milliseconds. Therefore, it is recommended to establish what risk is for the process to control these delays to determine if the equipment conventional applies, since under certain features like humidity and temperature can operate properly for a considerable time and at lower cost than devices to Industrial Ethernet.

Effect of Salicylic acid on some Growth and Biochemical Parameters of Wheat and Maize Plants under Salt Stress in Vitro

Directory of Open Access Journals (Sweden)

Z. Dashagha

2014-04-01

Full Text Available In this study, the difference between the resistance of wheat plants (c3 and maize (c4 the salinity was investigated. Research on environmental stresses (Hakimi, 2008 show thatstresses are considered as Limiting factors in crop production.and some phenolic compounds such as salicylic acid are used to improve or alleviate the negative effects of stress. In this study, plants were grown in plastic pots and the plants treated with salicylic acid, after two weeks and seven days later salinity was exerted.The effect of salinity treatmenton both plants, for some morphological and biochemical characteristics were studied. In biochemical tests, lipid peroxidation under salinity and salicylic acid treatments has increased for weat which represents the effect of salinity on the plant and the activetion of the defense mechanism, Howweverthese factors have reduced formaize. Moreover, the increase in total chlorophyll and flavonoids in wheatchlorophyll in wheat and maize shows the role of these pigments in quenching hydrogen peroxide and other active Oxygen types. This increases has not been concideralle in maize. The effect of treatment on the weight of … and root of both plants differed under the investigated concentration.

Escherichia coli under Ionic Silver Stress: An Integrative Approach to Explore Transcriptional, Physiological and Biochemical Responses.

Directory of Open Access Journals (Sweden)

Claire Saulou-Bérion

Full Text Available For a better understanding of the systemic effect of sub-lethal micromolar concentrations of ionic silver on Escherichia coli, we performed a multi-level characterization of cells under Ag+-mediated stress using an integrative biology approach combining physiological, biochemical and transcriptomic data. Physiological parameters, namely bacterial growth and survival after Ag+ exposure, were first quantified and related to the accumulation of intracellular silver, probed for the first time by nano secondary ion mass spectroscopy at sub-micrometer lateral resolution. Modifications in E. coli biochemical composition were evaluated under Ag+-mediated stress by in situ synchrotron Fourier-transform infrared microspectroscopy and a comprehensive transcriptome response was also determined. Using multivariate statistics, correlations between the physiological parameters, the extracellular concentration of AgNO3 and the intracellular silver content, gene expression profiles and micro-spectroscopic data were investigated. We identified Ag+-dependent regulation of gene expression required for growth (e.g. transporter genes, transcriptional regulators, ribosomal proteins, for ionic silver transport and detoxification (e.g. copA, cueO, mgtA, nhaR and for coping with various types of stress (dnaK, pspA, metA,R, oxidoreductase genes. The silver-induced shortening of the acyl chain of fatty acids, mostly encountered in cell membrane, was highlighted by microspectroscopy and correlated with the down-regulated expression of genes involved in fatty acid transport (fadL and synthesis/modification of lipid A (lpxA and arnA. The increase in the disordered secondary structure of proteins in the presence of Ag+ was assessed through the conformational shift shown for amides I and II, and further correlated with the up-regulated expression of peptidase (hfq and chaperone (dnaJ, and regulation of transpeptidase expression (ycfS and ycbB. Interestingly, as these

The Network Structure Underlying the Earth Observation Assessment

Science.gov (United States)

Vitkin, S.; Doane, W. E. J.; Mary, J. C.

2017-12-01

The Earth Observations Assessment (EOA 2016) is a multiyear project designed to assess the effectiveness of civil earth observation data sources (instruments, sensors, models, etc.) on societal benefit areas (SBAs) for the United States. Subject matter experts (SMEs) provided input and scored how data sources inform products, product groups, key objectives, SBA sub-areas, and SBAs in an attempt to quantify the relationships between data sources and SBAs. The resulting data were processed by Integrated Applications Incorporated (IAI) using MITRE's PALMA software to create normalized relative impact scores for each of these relationships. However, PALMA processing obscures the natural network representation of the data. Any network analysis that might identify patterns of interaction among data sources, products, and SBAs is therefore impossible. Collaborating with IAI, we cleaned and recreated a network from the original dataset. Using R and Python we explore the underlying structure of the network and apply frequent itemset mining algorithms to identify groups of data sources and products that interact. We reveal interesting patterns and relationships in the EOA dataset that were not immediately observable from the EOA 2016 report and provide a basis for further exploration of the EOA network dataset.

Vulnerability of complex networks under intentional attack with incomplete information

International Nuclear Information System (INIS)

Wu, J; Deng, H Z; Tan, Y J; Zhu, D Z

2007-01-01

We study the vulnerability of complex networks under intentional attack with incomplete information, which means that one can only preferentially attack the most important nodes among a local region of a network. The known random failure and the intentional attack are two extreme cases of our study. Using the generating function method, we derive the exact value of the critical removal fraction f c of nodes for the disintegration of networks and the size of the giant component. To validate our model and method, we perform simulations of intentional attack with incomplete information in scale-free networks. We show that the attack information has an important effect on the vulnerability of scale-free networks. We also demonstrate that hiding a fraction of the nodes information is a cost-efficient strategy for enhancing the robustness of complex networks

A flood-based information flow analysis and network minimization method for gene regulatory networks.

Science.gov (United States)

Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias

2013-04-24

Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.

Physiological and biochemical principles underlying volume-targeted therapy--the "Lund concept".

Science.gov (United States)

Nordström, Carl-Henrik

2005-01-01

The optimal therapy of sustained increase in intracranial pressure (ICP) remains controversial. The volume-targeted therapy ("Lund concept") discussed in this article focuses on the physiological volume regulation of the intracranial compartments. The balance between effective transcapillary hydrostatic and osmotic pressures constitutes the driving force for transcapillary fluid exchange. The low permeability for sodium and chloride combined with the high crystalloid osmotic pressure (approximately 5700 mmHg) on both sides of the blood-brain barrier (BBB) counteracts fluid exchange across the intact BBB. Additionally, variations in systemic blood pressure generally are not transmitted to these capillaries because cerebral intracapillary hydrostatic pressure (and blood flow) is physio-logically tightly autoregulated. Under pathophysiological conditions, the BBB may be partially disrupted. Transcapillary water exchange is then determined by the differences in hydrostatic and colloid osmotic pressure between the intra- and extracapillary compartments. Pressure autoregulation of cerebral blood flow is likely to be impaired in these conditions. A high cerebral perfusion pressure accordingly increases intracapillary hydrostatic pressure and leads to increased intracerebral water content and an increase in ICP. The volume-targeted "Lund concept" has been evaluated in experimental and clinical studies to examine the physiological and biochemical (utilizing intracerebral microdialysis) effects, and the clinical experiences have been favorable.

Estimating Biochemical Parameters of Tea (camellia Sinensis (L.)) Using Hyperspectral Techniques

Science.gov (United States)

Bian, M.; Skidmore, A. K.; Schlerf, M.; Liu, Y.; Wang, T.

2012-07-01

Tea (Camellia Sinensis (L.)) is an important economic crop and the market price of tea depends largely on its quality. This research aims to explore the potential of hyperspectral remote sensing on predicting the concentration of biochemical components, namely total tea polyphenols, as indicators of tea quality at canopy scale. Experiments were carried out for tea plants growing in the field and greenhouse. Partial least squares regression (PLSR), which has proven to be the one of the most successful empirical approach, was performed to establish the relationship between reflectance and biochemical concentration across six tea varieties in the field. Moreover, a novel integrated approach involving successive projections algorithms as band selection method and neural networks was developed and applied to detect the concentration of total tea polyphenols for one tea variety, in order to explore and model complex nonlinearity relationships between independent (wavebands) and dependent (biochemicals) variables. The good prediction accuracies (r2 > 0.8 and relative RMSEP < 10 %) achieved for tea plants using both linear (partial lease squares regress) and nonlinear (artificial neural networks) modelling approaches in this study demonstrates the feasibility of using airborne and spaceborne sensors to cover wide areas of tea plantation for in situ monitoring of tea quality cheaply and rapidly.

Time course of physiological, biochemical, and gene expression changes under short-term salt stress in Brassica juncea L.

Directory of Open Access Journals (Sweden)

Manish Pandey

2017-06-01

Full Text Available Salinity-imposed limitations on plant growth are manifested through osmotic and ionic imbalances. However, because salinity-induced responses vary considerably among crop plants, monitoring of such responses at an early stage has relevance. In this study, physiological (seed germination, seed vigor index, root length, shoot length, fresh weight, dry weight and biochemical attributes (osmoprotectants, K+/Na+ ratio were analyzed for a time-course assessment of salt responses in Indian mustard (Brassica juncea L. with an emphasis on early monitoring. The results showed strong correlations for total soluble sugars at germination phase (24 h, proline content in the seedling establishment phase (48 h and various physiological parameters including seed vigor index (R2 = 0.901, shoot length (R2 = 0.982, and fresh weight (R2 = 0.980 at 72 h (adaptation under stress. In addition, transcriptional changes were observed under NaCl treatment for key genes belonging to the family of selective ion transporters (NHX, HKT and abscisic acid synthesis (AAO-3. The status of mitochondrial respiration was also examined as a probe for salinity tolerance at an early stage. The results suggested that although all the analyzed parameters showed correlations (negative or positive with salt stress magnitude, their critical response times differed, with most of the studied biochemical, physiological, or molecular markers providing valuable information only after radicle emergence, whereas mitochondrial respiration via alternative oxidase was useful for the early detection of salt responses.

Node vulnerability of water distribution networks under cascading failures

International Nuclear Information System (INIS)

Shuang, Qing; Zhang, Mingyuan; Yuan, Yongbo

2014-01-01

Water distribution networks (WDNs) are important in modern lifeline system. Its stability and reliability are critical for guaranteeing high living quality and continuous operation of urban functions. The aim of this paper is to evaluate the nodal vulnerability of WDNs under cascading failures. Vulnerability is defined to analyze the effects of the consequent failures. A cascading failure is a step-by-step process which is quantitatively investigated by numerical simulation with intentional attack. Monitored pressures in different nodes and flows in different pipes have been used to estimate the network topological structure and the consequences of nodal failure. Based on the connectivity loss of topological structure, the nodal vulnerability has been evaluated. A load variation function is established to record the nodal failure reason and describe the relative differences between the load and the capacity. The proposed method is validated by an illustrative example. The results revealed that the network vulnerability should be evaluated with the consideration of hydraulic analysis and network topology. In the case study, 70.59% of the node failures trigger the cascading failures with different failure processes. It is shown that the cascading failures result in severe consequences in WDNs. - Highlights: • The aim of this paper is to evaluate the nodal vulnerability of water distribution networks under cascading failures. • Monitored pressures and flows have been used to estimate the network topological structure and the consequences of nodal failure. • Based on the connectivity loss of topological structure, the nodal vulnerability has been evaluated. • A load variation function is established to record the failure reason and describe the relative differences between load and capacity. • The results show that 70.59% of the node failures trigger the cascading failures with different failure processes

Epidemic Survivability: Characterizing Networks Under Epidemic-like Failure Propagation Scenarios

DEFF Research Database (Denmark)

Manzano, Marc; Calle, Eusebi; Ripoll, Jordi

2013-01-01

Epidemics theory has been used in different contexts in order to describe the propagation of diseases, human interactions or natural phenomena. In computer science, virus spreading has been also characterized using epidemic models. Although in the past the use of epidemic models...... in telecommunication networks has not been extensively considered, nowadays, with the increasing computation capacity and complexity of operating systems of modern network devices (routers, switches, etc.), the study of possible epidemic-like failure scenarios must be taken into account. When epidemics occur......, such as in other multiple failure scenarios, identifying the level of vulnerability offered by a network is one of the main challenges. In this paper, we present epidemic survivability, a new network measure that describes the vulnerability of each node of a network under a specific epidemic intensity. Moreover...

Systems biology and the origins of life? part II. Are biochemical networks possible ancestors of living systems? networks of catalysed chemical reactions: non-equilibrium, self-organization and evolution.

Science.gov (United States)

Ricard, Jacques

2010-01-01

The present article discusses the possibility that catalysed chemical networks can evolve. Even simple enzyme-catalysed chemical reactions can display this property. The example studied is that of a two-substrate proteinoid, or enzyme, reaction displaying random binding of its substrates A and B. The fundamental property of such a system is to display either emergence or integration depending on the respective values of the probabilities that the enzyme has bound one of its substrate regardless it has bound the other substrate, or, specifically, after it has bound the other substrate. There is emergence of information if p(A)>p(AB) and p(B)>p(BA). Conversely, if p(A)equilibrium. Moreover, in such systems, emergence results in an increase of the energy level of the ternary EAB complex that becomes closer to the transition state of the reaction, thus leading to the enhancement of catalysis. Hence a drift from quasi-equilibrium is, to a large extent, responsible for the production of information and enhancement of catalysis. Non-equilibrium of these simple systems must be an important aspect that leads to both self-organization and evolutionary processes. These conclusions can be extended to networks of catalysed chemical reactions. Such networks are, in fact, networks of networks, viz. meta-networks. In this formal representation, nodes are chemical reactions catalysed by poorly specific proteinoids, and links can be identified to the transport of metabolites from proteinoid to proteinoid. The concepts of integration and emergence can be applied to such situations and can be used to define the identity of these networks and therefore their evolution. Defined as open non-equilibrium structures, such biochemical networks possess two remarkable properties: (1) the probability of occurrence of their nodes is dependant upon the input and output of matter in, and from, the system and (2) the probability of occurrence of the nodes is strictly linked to their degree of

Soil biochemical properties and microbial resilience in agroforestry systems: effects on wheat growth under controlled drought and flooding conditions.

Science.gov (United States)

Rivest, David; Lorente, Miren; Olivier, Alain; Messier, Christian

2013-10-01

Agroforestry is increasingly viewed as an effective means of maintaining or even increasing crop and tree productivity under climate change while promoting other ecosystem functions and services. This study focused on soil biochemical properties and resilience following disturbance within agroforestry and conventional agricultural systems and aimed to determine whether soil differences in terms of these biochemical properties and resilience would subsequently affect crop productivity under extreme soil water conditions. Two research sites that had been established on agricultural land were selected for this study. The first site included an 18-year-old windbreak, while the second site consisted in an 8-year-old tree-based intercropping system. In each site, soil samples were used for the determination of soil nutrient availability, microbial dynamics and microbial resilience to different wetting-drying perturbations and for a greenhouse pot experiment with wheat. Drying and flooding were selected as water stress treatments and compared to a control. These treatments were initiated at the beginning of the wheat anthesis period and maintained over 10 days. Trees contributed to increase soil nutrient pools, as evidenced by the higher extractable-P (both sites), and the higher total N and mineralizable N (tree-based intercropping site) found in the agroforestry compared to the conventional agricultural system. Metabolic quotient (qCO2) was lower in the agroforestry than in the conventional agricultural system, suggesting higher microbial substrate use efficiency in agroforestry systems. Microbial resilience was higher in the agroforestry soils compared to soils from the conventional agricultural system (windbreak site only). At the windbreak site, wheat growing in soils from agroforestry system exhibited higher aboveground biomass and number of grains per spike than in conventional agricultural system soils in the three water stress treatments. At the tree

Biochemical basis of drought tolerance in hybrid Populus grown under field production conditions. CRADA final report

Energy Technology Data Exchange (ETDEWEB)

Tschaplinski, T.J.; Tuskan, G.A. [Oak Ridge National Lab., TN (United States); Wierman, C. [Boise Cascade Corp., Wallula, WA (United States)

1997-04-01

The purpose of this cooperative effort was to assess the use of osmotically active compounds as molecular selection criteria for drought tolerance in Populus in a large-scale field trial. It is known that some plant species, and individuals within a plant species, can tolerate increasing stress associated with reduced moisture availability by accumulating solutes. The biochemical matrix of such metabolites varies among species and among individuals. The ability of Populus clones to tolerate drought has equal value to other fiber producers, i.e., the wood products industry, where irrigation is used in combination with other cultural treatments to obtain high dry weight yields. The research initially involved an assessment of drought stress under field conditions and characterization of changes in osmotic constitution among the seven clones across the six moisture levels. The near-term goal was to provide a mechanistic basis for clonal differences in productivity under various irrigation treatments over time.

Wireless Networks under a Backoff Attack: A Game Theoretical Perspective.

Science.gov (United States)

Parras, Juan; Zazo, Santiago

2018-01-30

We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi's network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality.

Supply chain network design under uncertainty

DEFF Research Database (Denmark)

Govindan, Kannan; Fattahi, Mohammad; Keyvanshokooh, Esmaeil

2017-01-01

Supply chain network design (SCND) is one of the most crucial planning problems in supply chain management (SCM). Nowadays, design decisions should be viable enough to function well under complex and uncertain business environments for many years or decades. Therefore, it is essential to make...... programming, risk-averse stochastic programming, robust optimization, and fuzzy mathematical programming are explored in terms of mathematical modeling and solution approaches. Finally, the drawbacks and missing aspects of the related literature are highlighted and a list of potential issues for future...

Capacity planning of link restorable optical networks under dynamic change of traffic

Science.gov (United States)

Ho, Kwok Shing; Cheung, Kwok Wai

2005-11-01

Future backbone networks shall require full-survivability and support dynamic changes of traffic demands. The Generalized Survivable Networks (GSN) was proposed to meet these challenges. GSN is fully-survivable under dynamic traffic demand changes, so it offers a practical and guaranteed characterization framework for ASTN / ASON survivable network planning and bandwidth-on-demand resource allocation 4. The basic idea of GSN is to incorporate the non-blocking network concept into the survivable network models. In GSN, each network node must specify its I/O capacity bound which is taken as constraints for any allowable traffic demand matrix. In this paper, we consider the following generic GSN network design problem: Given the I/O bounds of each network node, find a routing scheme (and the corresponding rerouting scheme under failure) and the link capacity assignment (both working and spare) which minimize the cost, such that any traffic matrix consistent with the given I/O bounds can be feasibly routed and it is single-fault tolerant under the link restoration scheme. We first show how the initial, infeasible formal mixed integer programming formulation can be transformed into a more feasible problem using the duality transformation of the linear program. Then we show how the problem can be simplified using the Lagrangian Relaxation approach. Previous work has outlined a two-phase approach for solving this problem where the first phase optimizes the working capacity assignment and the second phase optimizes the spare capacity assignment. In this paper, we present a jointly optimized framework for dimensioning the survivable optical network with the GSN model. Experiment results show that the jointly optimized GSN can bring about on average of 3.8% cost savings when compared with the separate, two-phase approach. Finally, we perform a cost comparison and show that GSN can be deployed with a reasonable cost.

Local biochemical and morphological differences in human Achilles tendinopathy

DEFF Research Database (Denmark)

Pingel, Jessica; Fredberg, U.; Qvortrup, Klaus

2012-01-01

The incidence of Achilles tendinopathy is high and underlying etiology as well as biochemical and morphological pathology associated with the disease is largely unknown. The aim of the present study was to describe biochemical and morphological differences in chronic Achilles tendinopathy....... The expressions of growth factors, inflammatory mediators and tendon morphology were determined in both chronically diseased and healthy tendon parts....

Complexity of generic biochemical circuits: topology versus strength of interactions

Science.gov (United States)

Tikhonov, Mikhail; Bialek, William

2016-12-01

The historical focus on network topology as a determinant of biological function is still largely maintained today, illustrated by the rise of structure-only approaches to network analysis. However, biochemical circuits and genetic regulatory networks are defined both by their topology and by a multitude of continuously adjustable parameters, such as the strength of interactions between nodes, also recognized as important. Here we present a class of simple perceptron-based Boolean models within which comparing the relative importance of topology versus interaction strengths becomes a quantitatively well-posed problem. We quantify the intuition that for generic networks, optimization of interaction strengths is a crucial ingredient of achieving high complexity, defined here as the number of fixed points the network can accommodate. We propose a new methodology for characterizing the relative role of parameter optimization for topologies of a given class.

Physiological and Biochemical Responses of Lavandula angustifolia to Salinity Under Mineral Foliar Application

Science.gov (United States)

Chrysargyris, Antonios; Michailidi, Evgenia; Tzortzakis, Nikos

2018-01-01

Saline water has been proposed as a solution to partially cover plant water demands due to scarcity of irrigation water in hot arid areas. Lavender (Lavandula angustifolia Mill.) plants were grown hydroponically under salinity (0–25–50–100 mM NaCl). The overcome of salinity stress was examined by K, Zn, and Si foliar application for the plant physiological and biochemical characteristics. The present study indicated that high (100 mM NaCl) salinity decreased plant growth, content of phenolics and antioxidant status and essential oil (EO) yield, while low-moderate salinity levels maintained the volatile oil profile in lavender. The integrated foliar application of K and Zn lighten the presumable detrimental effects of salinity in terms of fresh biomass, antioxidant capacity, and EO yield. Moderate salinity stress along with balanced concentration of K though foliar application changed the primary metabolites pathways in favor of major volatile oil constituents biosynthesis and therefore lavender plant has the potential for cultivation under prevalent semi-saline conditions. Zn and Si application, had lesser effects on the content of EO constituents, even though altered salinity induced changings. Our results have demonstrated that lavender growth/development and EO production may be affected by saline levels, whereas mechanisms for alteration of induced stress are of great significance considering the importance of the oil composition, as well. PMID:29731759

Influence of season and sex on hemato-biochemical traits in adult turkeys under arid tropical environment

Directory of Open Access Journals (Sweden)

Anil Gattani

2016-05-01

Full Text Available Aim: The objective of this study was to evaluate the effect of season and sex on hemato-biochemical parameters of turkey (Meleagris gallopavo in the arid tropical environment. Materials and Methods: The experiment was conducted on 20-week old turkeys consisting of 20 males and 20 females. Blood was collected from all turkeys during January and May. Hemoglobin (Hb, red blood cell (RBC, packed cell volume (PCV, mean corpuscular volume (MCV, mean corpuscular hemoglobin (MCH, and mean corpuscular hemoglobin concentration (MCHC were estimated in whole blood and glucose, protein, albumin, globulin, A/G ratio, calcium, phosphorus, alanine aminotransferase (ALT, and aspartate aminotransferase (AST in serum. Result: Season has significant (p<0.05 effect on Hb concentration, RBC, and PCV in both male and female. Male has significantly higher (p<0.05 Hb concentration, RBC, and PCV. There is no significant effect of sex, and season was observed on MCV, MCH, and MCHC. Glucose, protein, albumin, globulin, and A/G ratio were significantly (p<0.05 affected by season and sex. AST and ALT were significantly (p<0.05 affected by season in both sexes. There is no significant difference was recorded on calcium, phosphorus due to season and sex. Conclusion: Under arid tropical environment, turkey hemato-biochemical parameters are influenced by both sex and season.

Mean field interaction in biochemical reaction networks

KAUST Repository

Tembine, Hamidou; Tempone, Raul; Vilanova, Pedro

2011-01-01

In this paper we establish a relationship between chemical dynamics and mean field game dynamics. We show that chemical reaction networks can be studied using noisy mean field limits. We provide deterministic, noisy and switching mean field limits

Formal Models of the Network Co-occurrence Underlying Mental Operations.

Science.gov (United States)

Bzdok, Danilo; Varoquaux, Gaël; Grisel, Olivier; Eickenberg, Michael; Poupon, Cyril; Thirion, Bertrand

2016-06-01

Systems neuroscience has identified a set of canonical large-scale networks in humans. These have predominantly been characterized by resting-state analyses of the task-unconstrained, mind-wandering brain. Their explicit relationship to defined task performance is largely unknown and remains challenging. The present work contributes a multivariate statistical learning approach that can extract the major brain networks and quantify their configuration during various psychological tasks. The method is validated in two extensive datasets (n = 500 and n = 81) by model-based generation of synthetic activity maps from recombination of shared network topographies. To study a use case, we formally revisited the poorly understood difference between neural activity underlying idling versus goal-directed behavior. We demonstrate that task-specific neural activity patterns can be explained by plausible combinations of resting-state networks. The possibility of decomposing a mental task into the relative contributions of major brain networks, the "network co-occurrence architecture" of a given task, opens an alternative access to the neural substrates of human cognition.

Computing molecular fluctuations in biochemical reaction systems based on a mechanistic, statistical theory of irreversible processes.

Science.gov (United States)

Kulasiri, Don

2011-01-01

We discuss the quantification of molecular fluctuations in the biochemical reaction systems within the context of intracellular processes associated with gene expression. We take the molecular reactions pertaining to circadian rhythms to develop models of molecular fluctuations in this chapter. There are a significant number of studies on stochastic fluctuations in intracellular genetic regulatory networks based on single cell-level experiments. In order to understand the fluctuations associated with the gene expression in circadian rhythm networks, it is important to model the interactions of transcriptional factors with the E-boxes in the promoter regions of some of the genes. The pertinent aspects of a near-equilibrium theory that would integrate the thermodynamical and particle dynamic characteristics of intracellular molecular fluctuations would be discussed, and the theory is extended by using the theory of stochastic differential equations. We then model the fluctuations associated with the promoter regions using general mathematical settings. We implemented ubiquitous Gillespie's algorithms, which are used to simulate stochasticity in biochemical networks, for each of the motifs. Both the theory and the Gillespie's algorithms gave the same results in terms of the time evolution of means and variances of molecular numbers. As biochemical reactions occur far away from equilibrium-hence the use of the Gillespie algorithm-these results suggest that the near-equilibrium theory should be a good approximation for some of the biochemical reactions. © 2011 Elsevier Inc. All rights reserved.

Large-scale networks in engineering and life sciences

CERN Document Server

Findeisen, Rolf; Flockerzi, Dietrich; Reichl, Udo; Sundmacher, Kai

2014-01-01

This edited volume provides insights into and tools for the modeling, analysis, optimization, and control of large-scale networks in the life sciences and in engineering. Large-scale systems are often the result of networked interactions between a large number of subsystems, and their analysis and control are becoming increasingly important. The chapters of this book present the basic concepts and theoretical foundations of network theory and discuss its applications in different scientific areas such as biochemical reactions, chemical production processes, systems biology, electrical circuits, and mobile agents. The aim is to identify common concepts, to understand the underlying mathematical ideas, and to inspire discussions across the borders of the various disciplines.  The book originates from the interdisciplinary summer school “Large Scale Networks in Engineering and Life Sciences” hosted by the International Max Planck Research School Magdeburg, September 26-30, 2011, and will therefore be of int...

Wireless Networks under a Backoff Attack: A Game Theoretical Perspective

Directory of Open Access Journals (Sweden)

Juan Parras

2018-01-01

Full Text Available We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi’s network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality.

Bio-chemical remediation of under-ground water contaminated by uranium in-situ leaching

International Nuclear Information System (INIS)

Wang Qingliang; Li Qian; Zhang Hongcan; Hu Eming; Chen Yongbo

2014-01-01

In the process of uranium in-situ leaching, it was serious that strong acid, uranium and heavy metals, and SO_4"2"-, NO_3"- could contaminate underground water. To remedy these pollutants, conventional methods are high-cost and low-efficient, so a bio-chemical remediation method was proposed to cope with the under-ground water pollution in this study. The results showed, in the chemical treatment with Ca(OH)_2 neutralization, pH went up from 2.0 to 7.0, the removal rates of U, Mn"2"+, Zn"2"+, Pb"2"+, SO_4"2"-, NO_3"- were 91.5%, 78.3%, 85.1%, 100%, 71.4% and 2.6% respectively, SO_4"2"- and NO_3"- need to be treated again by bio-method. In the biological process, the Hydraulic Retention Time (HRT) of bioreactor was controlled at 42 h, and 100% NO_3"- and 70% SO_4"2"- in the contaminated water were removed; Acidithiobacillus ferrooxidans (A. f) liquid to H_2S showed better absorption effect, can fully meet the process requirements of H_2S removal. (authors)

Mean field interaction in biochemical reaction networks

KAUST Repository

Tembine, Hamidou

2011-09-01

In this paper we establish a relationship between chemical dynamics and mean field game dynamics. We show that chemical reaction networks can be studied using noisy mean field limits. We provide deterministic, noisy and switching mean field limits and illustrate them with numerical examples. © 2011 IEEE.

On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach

Science.gov (United States)

Chen, Bor-Sen; Lin, Ying-Po

2011-01-01

In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563

Analytic Treatment of Deep Neural Networks Under Additive Gaussian Noise

KAUST Repository

Alfadly, Modar

2018-01-01

Despite the impressive performance of deep neural networks (DNNs) on numerous vision tasks, they still exhibit yet-to-understand uncouth behaviours. One puzzling behaviour is the reaction of DNNs to various noise attacks, where it has been shown that there exist small adversarial noise that can result in a severe degradation in the performance of DNNs. To rigorously treat this, we derive exact analytic expressions for the first and second moments (mean and variance) of a small piecewise linear (PL) network with a single rectified linear unit (ReLU) layer subject to general Gaussian input. We experimentally show that these expressions are tight under simple linearizations of deeper PL-DNNs, especially popular architectures in the literature (e.g. LeNet and AlexNet). Extensive experiments on image classification show that these expressions can be used to study the behaviour of the output mean of the logits for each class, the inter-class confusion and the pixel-level spatial noise sensitivity of the network. Moreover, we show how these expressions can be used to systematically construct targeted and non-targeted adversarial attacks. Then, we proposed a special estimator DNN, named mixture of linearizations (MoL), and derived the analytic expressions for its output mean and variance, as well. We employed these expressions to train the model to be particularly robust against Gaussian attacks without the need for data augmentation. Upon training this network on a loss that is consolidated with the derived output probabilistic moments, the network is not only robust under very high variance Gaussian attacks but is also as robust as networks that are trained with 20 fold data augmentation.

Analytic Treatment of Deep Neural Networks Under Additive Gaussian Noise

KAUST Repository

Alfadly, Modar M.

2018-04-12

Despite the impressive performance of deep neural networks (DNNs) on numerous vision tasks, they still exhibit yet-to-understand uncouth behaviours. One puzzling behaviour is the reaction of DNNs to various noise attacks, where it has been shown that there exist small adversarial noise that can result in a severe degradation in the performance of DNNs. To rigorously treat this, we derive exact analytic expressions for the first and second moments (mean and variance) of a small piecewise linear (PL) network with a single rectified linear unit (ReLU) layer subject to general Gaussian input. We experimentally show that these expressions are tight under simple linearizations of deeper PL-DNNs, especially popular architectures in the literature (e.g. LeNet and AlexNet). Extensive experiments on image classification show that these expressions can be used to study the behaviour of the output mean of the logits for each class, the inter-class confusion and the pixel-level spatial noise sensitivity of the network. Moreover, we show how these expressions can be used to systematically construct targeted and non-targeted adversarial attacks. Then, we proposed a special estimator DNN, named mixture of linearizations (MoL), and derived the analytic expressions for its output mean and variance, as well. We employed these expressions to train the model to be particularly robust against Gaussian attacks without the need for data augmentation. Upon training this network on a loss that is consolidated with the derived output probabilistic moments, the network is not only robust under very high variance Gaussian attacks but is also as robust as networks that are trained with 20 fold data augmentation.

Mixed Transportation Network Design under a Sustainable Development Perspective

Directory of Open Access Journals (Sweden)

Jin Qin

2013-01-01

Full Text Available A mixed transportation network design problem considering sustainable development was studied in this paper. Based on the discretization of continuous link-grade decision variables, a bilevel programming model was proposed to describe the problem, in which sustainability factors, including vehicle exhaust emissions, land-use scale, link load, and financial budget, are considered. The objective of the model is to minimize the total amount of resources exploited under the premise of meeting all the construction goals. A heuristic algorithm, which combined the simulated annealing and path-based gradient projection algorithm, was developed to solve the model. The numerical example shows that the transportation network optimized with the method above not only significantly alleviates the congestion on the link, but also reduces vehicle exhaust emissions within the network by up to 41.56%.

Mixed Transportation Network Design under a Sustainable Development Perspective

Science.gov (United States)

Qin, Jin; Ni, Ling-lin; Shi, Feng

2013-01-01

A mixed transportation network design problem considering sustainable development was studied in this paper. Based on the discretization of continuous link-grade decision variables, a bilevel programming model was proposed to describe the problem, in which sustainability factors, including vehicle exhaust emissions, land-use scale, link load, and financial budget, are considered. The objective of the model is to minimize the total amount of resources exploited under the premise of meeting all the construction goals. A heuristic algorithm, which combined the simulated annealing and path-based gradient projection algorithm, was developed to solve the model. The numerical example shows that the transportation network optimized with the method above not only significantly alleviates the congestion on the link, but also reduces vehicle exhaust emissions within the network by up to 41.56%. PMID:23476142

Trade networks evolution under the conditions of stock market globalization

Directory of Open Access Journals (Sweden)

Kopylova Olga Volodymyrivna

2016-12-01

Full Text Available The modern perception of the stock market in terms of information technologies rapid development and under the institutionalists influence has been significantly modified and becomes multifaceted. It was detected that the main function of the market is activated, information asymmetry is minimized and more advanced financial architecture space is formed through trade networks. Formation of the modern trade networks has started on the basis of the old infrastructure, that had the highest tendency to self-organization and adaptation. The proposed architecture of trade networks of the stock market has a very clear vector of subordination – from top to bottom and has a number of positive points.

Formal Models of the Network Co-occurrence Underlying Mental Operations.

Directory of Open Access Journals (Sweden)

Danilo Bzdok

2016-06-01

Full Text Available Systems neuroscience has identified a set of canonical large-scale networks in humans. These have predominantly been characterized by resting-state analyses of the task-unconstrained, mind-wandering brain. Their explicit relationship to defined task performance is largely unknown and remains challenging. The present work contributes a multivariate statistical learning approach that can extract the major brain networks and quantify their configuration during various psychological tasks. The method is validated in two extensive datasets (n = 500 and n = 81 by model-based generation of synthetic activity maps from recombination of shared network topographies. To study a use case, we formally revisited the poorly understood difference between neural activity underlying idling versus goal-directed behavior. We demonstrate that task-specific neural activity patterns can be explained by plausible combinations of resting-state networks. The possibility of decomposing a mental task into the relative contributions of major brain networks, the "network co-occurrence architecture" of a given task, opens an alternative access to the neural substrates of human cognition.

Robustness of Dengue Complex Network under Targeted versus Random Attack

Directory of Open Access Journals (Sweden)

Hafiz Abid Mahmood Malik

2017-01-01

Full Text Available Dengue virus infection is one of those epidemic diseases that require much consideration in order to save the humankind from its unsafe impacts. According to the World Health Organization (WHO, 3.6 billion individuals are at risk because of the dengue virus sickness. Researchers are striving to comprehend the dengue threat. This study is a little commitment to those endeavors. To observe the robustness of the dengue network, we uprooted the links between nodes randomly and targeted by utilizing different centrality measures. The outcomes demonstrated that 5% targeted attack is equivalent to the result of 65% random assault, which showed the topology of this complex network validated a scale-free network instead of random network. Four centrality measures (Degree, Closeness, Betweenness, and Eigenvector have been ascertained to look for focal hubs. It has been observed through the results in this study that robustness of a node and links depends on topology of the network. The dengue epidemic network presented robust behaviour under random attack, and this network turned out to be more vulnerable when the hubs of higher degree have higher probability to fail. Moreover, representation of this network has been projected, and hub removal impact has been shown on the real map of Gombak (Malaysia.

Optimal Intermittent Operation of Water Distribution Networks under Water Shortage

Directory of Open Access Journals (Sweden)

mohamad Solgi

2017-07-01

Full Text Available Under water shortage conditions, it is necessary to exercise water consumption management practices in water distribution networks (WDN. Intermittent supply of water is one such practice that makes it possible to supply consumption nodal demands with the required pressure via water cutoff to some consumers during certain hours of the day. One of the most important issues that must be observed in this management practice is the equitable and uniform water distribution among the consumers. In the present study, uniformity in water distribution and minimum supply of water to all consumers are defined as justice and equity, respectively. Also, an optimization model has been developed to find an optimal intermittent supply schedule that ensures maximum number of demand nodes are supplied with water while the constraints on the operation of water distribution networks are also observed. To show the efficiency of the proposed model, it has been used in the Two-Loop distribution network under several different scenarios of water shortage. The optimization model has been solved using the honey bee mating optimization algorithm (HBMO linked to the hydraulic simulator EPANET. The results obtained confirm the efficiency of the proposed model in achieving an optimal intermittent supply schedule. Moreover, the model is found capable of distributing the available water in an equitable and just manner among all the consumers even under severe water shoratges.

Fruit development, pigmentation and biochemical properties of wax apple as affected by localized Application of GA3 under field conditions

OpenAIRE

Khandaker, Mohammad Moneruzzaman; Boyce, Amru Nasrulhaq; Osman, Normaniza; Golam, Faruq; Rahman, M. Motior; Sofian-Azirun, M.

2013-01-01

This study investigated the effects of gibberellin (GA3) on the fruit development, pigmentation and biochemical properties of wax apple. The wax apple trees were rubbing treated with 0, 20, 50 and 100 mgGA3/l under field conditions. The localized application (rubbing) of 50 mg GA3/l significantly increased the fruit set, fruit length and diameter, color development, weight and yieldcompared to the control. In addition, GA3 treatments significantly reduced the fruit drop. With regard to the fr...

Convergence and approximate calculation of average degree under different network sizes for decreasing random birth-and-death networks

Science.gov (United States)

Long, Yin; Zhang, Xiao-Jun; Wang, Kui

2018-05-01

In this paper, convergence and approximate calculation of average degree under different network sizes for decreasing random birth-and-death networks (RBDNs) are studied. First, we find and demonstrate that the average degree is convergent in the form of power law. Meanwhile, we discover that the ratios of the back items to front items of convergent reminder are independent of network link number for large network size, and we theoretically prove that the limit of the ratio is a constant. Moreover, since it is difficult to calculate the analytical solution of the average degree for large network sizes, we adopt numerical method to obtain approximate expression of the average degree to approximate its analytical solution. Finally, simulations are presented to verify our theoretical results.

Autonomous bio-chemical decontaminator (ABCD) against weapons of mass destruction

Science.gov (United States)

Hyacinthe, Berg P.

2006-05-01

The proliferation of weapons of mass destruction (WMD) and the use of such elements pose an eminent asymmetric threat with disastrous consequences to the national security of any nation. In particular, the use of biochemical warfare agents against civilians and unprotected troops in international conflicts or by terrorists against civilians is considered as a very peculiar threat. Accordingly, taking a quarantine-before-inhalation approach to biochemical warfare, the author introduces the notion of autonomous biochemical decontamination against WMD. In the unfortunate event of a biochemical attack, the apparatus proposed herein is intended to automatically detect, identify, and more importantly neutralize a biochemical threat. Along with warnings concerning a cyber-WMD nexus, various sections cover discussions on human senses and computer sensors, corroborating evidence related to detection and neutralization of chemical toxins, and cyber-assisted olfaction in stand alone, peer-to-peer, and network settings. In essence, the apparatus can be used in aviation and mass transit security to initiate mass decontamination by dispersing a decontaminant aerosol or to protect the public water supply against a potential bioterrorist attack. Future effort may involve a system-on-chip (SoC) embodiment of this apparatus that allows a safer environment for the emerging phenomenon of cyber-assisted olfaction and morph cell phones into ubiquitous sensors/decontaminators. Although this paper covers mechanisms and protocols to avail a neutralizing substance, further research will need to explore the substance's various pharmacological profiles and potential side effects.

Similarity between community structures of different online social networks and its impact on underlying community detection

Science.gov (United States)

Fan, W.; Yeung, K. H.

2015-03-01

As social networking services are popular, many people may register in more than one online social network. In this paper we study a set of users who have accounts of three online social networks: namely Foursquare, Facebook and Twitter. Community structure of this set of users may be reflected in these three online social networks. Therefore, high correlation between these reflections and the underlying community structure may be observed. In this work, community structures are detected in all three online social networks. Also, we investigate the similarity level of community structures across different networks. It is found that they show strong correlation with each other. The similarity between different networks may be helpful to find a community structure close to the underlying one. To verify this, we propose a method to increase the weights of some connections in networks. With this method, new networks are generated to assist community detection. By doing this, value of modularity can be improved and the new community structure match network's natural structure better. In this paper we also show that the detected community structures of online social networks are correlated with users' locations which are identified on Foursquare. This information may also be useful for underlying community detection.

Deterministic modelling and stochastic simulation of biochemical pathways using MATLAB.

Science.gov (United States)

Ullah, M; Schmidt, H; Cho, K H; Wolkenhauer, O

2006-03-01

The analysis of complex biochemical networks is conducted in two popular conceptual frameworks for modelling. The deterministic approach requires the solution of ordinary differential equations (ODEs, reaction rate equations) with concentrations as continuous state variables. The stochastic approach involves the simulation of differential-difference equations (chemical master equations, CMEs) with probabilities as variables. This is to generate counts of molecules for chemical species as realisations of random variables drawn from the probability distribution described by the CMEs. Although there are numerous tools available, many of them free, the modelling and simulation environment MATLAB is widely used in the physical and engineering sciences. We describe a collection of MATLAB functions to construct and solve ODEs for deterministic simulation and to implement realisations of CMEs for stochastic simulation using advanced MATLAB coding (Release 14). The program was successfully applied to pathway models from the literature for both cases. The results were compared to implementations using alternative tools for dynamic modelling and simulation of biochemical networks. The aim is to provide a concise set of MATLAB functions that encourage the experimentation with systems biology models. All the script files are available from www.sbi.uni-rostock.de/ publications_matlab-paper.html.

Will electrical cyber-physical interdependent networks undergo first-order transition under random attacks?

Science.gov (United States)

Ji, Xingpei; Wang, Bo; Liu, Dichen; Dong, Zhaoyang; Chen, Guo; Zhu, Zhenshan; Zhu, Xuedong; Wang, Xunting

2016-10-01

Whether the realistic electrical cyber-physical interdependent networks will undergo first-order transition under random failures still remains a question. To reflect the reality of Chinese electrical cyber-physical system, the "partial one-to-one correspondence" interdependent networks model is proposed and the connectivity vulnerabilities of three realistic electrical cyber-physical interdependent networks are analyzed. The simulation results show that due to the service demands of power system the topologies of power grid and its cyber network are highly inter-similar which can effectively avoid the first-order transition. By comparing the vulnerability curves between electrical cyber-physical interdependent networks and its single-layer network, we find that complex network theory is still useful in the vulnerability analysis of electrical cyber-physical interdependent networks.

Effect of Shading on Physiological, Biochemical and Behaviour Changes in Crossbred Calves Under Hot Climatic Conditions

International Nuclear Information System (INIS)

Teama, F.E.I.; Gad, A.E.; El-Tarabany, A.A.

2012-01-01

The purpose of this study was to investigate the importance and the effect of shading and non-shading house on physiological changes, body weight (BW), average daily gain (ADG), total antioxidant and thyroid hormones in crossbred calves under hot conditions. Thirty six growing crossbred calves (Friesian x Baladi) aged 8-10 months were divided into two groups (each 18 calves); the first group was maintained in shaded house and the second in house without shade (climatic house). The period of study was 79 days during hot conditions. Performance variables (BW, ADG) were measured and the blood samples were collected to assess some biochemical parameters including antioxidants such as total antioxidant (TA), catalase (CAT), total protein, thyroid hormones (T3, T4) and immunoglobulin factor (IgG). Respiration rates and behaviour parameters (feeding, drinking, standing, lying and agonistic) were also measured during the study. The data indicated that the shaded calves had higher ADG (P<0.05) and final BW than non-shaded ones. Also, a significant improvement in total protein levels and globulins were recorded in shaded house calves as compared to non-shaded ones. The same result was obtained for T3 level whereas non-significant changes were observed for T4 level as well as the level of IgG at different times. The present data indicated that using shaded house will decrease the effect of heat stress on calves which will increase the animal performance through improving BW and ADG as well as some biochemical parameters in addition to T3 hormonal level.

Network Performance Improvement under Epidemic Failures in Optical Transport Networks

DEFF Research Database (Denmark)

Fagertun, Anna Manolova; Ruepp, Sarah Renée

2013-01-01

In this paper we investigate epidemic failure spreading in large- scale GMPLS-controlled transport networks. By evaluating the effect of the epidemic failure spreading on the network, we design several strategies for cost-effective network performance improvement via differentiated repair times....... First we identify the most vulnerable and the most strategic nodes in the network. Then, via extensive simulations we show that strategic placement of resources for improved failure recovery has better performance than randomly assigning lower repair times among the network nodes. Our OPNET simulation...... model can be used during the network planning process for facilitating cost- effective network survivability design....

Switching performance of OBS network model under prefetched real traffic

Science.gov (United States)

Huang, Zhenhua; Xu, Du; Lei, Wen

2005-11-01

Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.

Biochemical indicators of root damage in rice (Oryza sativa) genotypes under zinc deficiency stress.

Science.gov (United States)

Lee, Jae-Sung; Wissuwa, Matthias; Zamora, Oscar B; Ismail, Abdelbagi M

2017-11-01

Zn deficiency is one of the major soil constraints currently limiting rice production. Although recent studies demonstrated that higher antioxidant activity in leaf tissue effectively protects against Zn deficiency stress, little is known about whether similar tolerance mechanisms operate in root tissue. In this study we explored root-specific responses of different rice genotypes to Zn deficiency. Root solute leakage and biomass reduction, antioxidant activity, and metabolic changes were measured using plants grown in Zn-deficient soil and hydroponics. Solute leakage from roots was higher in sensitive genotypes and linked to membrane damage caused by Zn deficiency-induced oxidative stress. However, total root antioxidant activity was four-fold lower than in leaves and did not differ between sensitive and tolerant genotypes. Root metabolite analysis using gas chromatography-mass spectrometry and high performance liquid chromatography indicated that Zn deficiency triggered the accumulation of glycerol-3-phosphate and acetate in sensitive genotypes, while less or no accumulation was seen in tolerant genotypes. We suggest that these metabolites may serve as biochemical indicators of root damage under Zn deficiency.

Evolution of cooperation under social pressure in multiplex networks.

Science.gov (United States)

Pereda, María

2016-09-01

In this work, we aim to contribute to the understanding of human prosocial behavior by studying the influence that a particular form of social pressure, "being watched," has on the evolution of cooperative behavior. We study how cooperation emerges in multiplex complex topologies by analyzing a particular bidirectionally coupled dynamics on top of a two-layer multiplex network (duplex). The coupled dynamics appears between the prisoner's dilemma game in a network and a threshold cascade model in the other. The threshold model is intended to abstract the behavior of a network of vigilant nodes that impose the pressure of being observed altering hence the temptation to defect of the dilemma. Cooperation or defection in the game also affects the state of a node of being vigilant. We analyze these processes on different duplex networks structures and assess the influence of the topology, average degree and correlated multiplexity, on the outcome of cooperation. Interestingly, we find that the social pressure of vigilance may impact cooperation positively or negatively, depending on the duplex structure, specifically the degree correlations between layers is determinant. Our results give further quantitative insights in the promotion of cooperation under social pressure.

Uranium mining and metallurgy library information service under the network environment

International Nuclear Information System (INIS)

Tang Lilei

2012-01-01

This paper analyzes the effect of the network environment on the uranium mining and metallurgy of the information service. Introduces some measures such as strengthening professional characteristic literature resources construction, changing the service mode, building up information navigation, deepening service, meet the individual needs of users, raising librarian's quality, promoting the co-construction and sharing of library information resources, and puts forward the development idea of uranium mining and metallurgy library information service under the network environment. (author)

Security Evaluation of the Cyber Networks under Advanced Persistent Threats

NARCIS (Netherlands)

Yang, L.; Li, Pengdeng; Yang, Xiaofan; Tang, Yuan Yan

2017-01-01

Advanced persistent threats (APTs) pose a grave threat to cyberspace, because they deactivate all the conventional cyber defense mechanisms. This paper addresses the issue of evaluating the security of the cyber networks under APTs. For this purpose, a dynamic model capturing the APT-based

Signaling mechanisms underlying the robustness and tunability of the plant immune network

Science.gov (United States)

Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

2014-01-01

Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

A case study of evolutionary computation of biochemical adaptation

International Nuclear Information System (INIS)

François, Paul; Siggia, Eric D

2008-01-01

Simulations of evolution have a long history, but their relation to biology is questioned because of the perceived contingency of evolution. Here we provide an example of a biological process, adaptation, where simulations are argued to approach closer to biology. Adaptation is a common feature of sensory systems, and a plausible component of other biochemical networks because it rescales upstream signals to facilitate downstream processing. We create random gene networks numerically, by linking genes with interactions that model transcription, phosphorylation and protein–protein association. We define a fitness function for adaptation in terms of two functional metrics, and show that any reasonable combination of them will yield the same adaptive networks after repeated rounds of mutation and selection. Convergence to these networks is driven by positive selection and thus fast. There is always a path in parameter space of continuously improving fitness that leads to perfect adaptation, implying that the actual mutation rates we use in the simulation do not bias the results. Our results imply a kinetic view of evolution, i.e., it favors gene networks that can be learned quickly from the random examples supplied by mutation. This formulation allows for deductive predictions of the networks realized in nature

Autocatalytic sets in a partitioned biochemical network.

Science.gov (United States)

Smith, Joshua I; Steel, Mike; Hordijk, Wim

2014-01-01

In previous work, RAF theory has been developed as a tool for making theoretical progress on the origin of life question, providing insight into the structure and occurrence of self-sustaining and collectively autocatalytic sets within catalytic polymer networks. We present here an extension in which there are two "independent" polymer sets, where catalysis occurs within and between the sets, but there are no reactions combining polymers from both sets. Such an extension reflects the interaction between nucleic acids and peptides observed in modern cells and proposed forms of early life. We present theoretical work and simulations which suggest that the occurrence of autocatalytic sets is robust to the partitioned structure of the network. We also show that autocatalytic sets remain likely even when the molecules in the system are not polymers, and a low level of inhibition is present. Finally, we present a kinetic extension which assigns a rate to each reaction in the system, and show that identifying autocatalytic sets within such a system is an NP-complete problem. Recent experimental work has challenged the necessity of an RNA world by suggesting that peptide-nucleic acid interactions occurred early in chemical evolution. The present work indicates that such a peptide-RNA world could support the spontaneous development of autocatalytic sets and is thus a feasible alternative worthy of investigation.

Effect of Dietary Supplementation of Curcuma Longa on the Biochemical Profile and Meat Characteristics of Broiler Rabbits under Summer Stress

Directory of Open Access Journals (Sweden)

Basavaraj

2011-02-01

Full Text Available Eighteen four week’s old weaned broiler rabbits of comparable body weights were allotted to three dietary treatment groups of six rabbits in each group namely T0 (basal control diet, T1 (basal diet added with turmeric rhizome powder, TRP, at the ratio of 150mgand T2 (basal diet added with TRP at the ratio of 300mg/100g diet. Different hematological and serum biochemical parameters such as packed cell volume, Hemoglobin, total erythrocyte count and total leukocyte count and serum total protein, albumin, cholesterol, alkaline phosphatase, alanine transaminase and aspartate transaminase due to the dietary inclusion of turmeric powder rhizome supplementation at 0, 0.15 and 0.30 percent did not show significant difference between the treatment groups. Carcass parameters and chemical composition of meat were closer to the standard values. The results of the study indicated no beneficial effect of dietary inclusion of turmeric (Curcuma longa rhizome powder at 0, 0.15 and 0.30 per cent on blood biochemical and meat characteristics of broiler rabbits reared under summer stress [Veterinary World 2011; 4(1.000: 15-18

Timing of product introduction in network economies under heterogeneous demand

DEFF Research Database (Denmark)

Winther, Christian Dahl

This paper studies the introduction of a new and incompatible technology in a spatial market with network externalities. In competition with an established network, the entrant chooses how long to do research and a level of product differentiation, which determine the adoption patterns of consumers...... level of product differentiation that should be chosen by the sponsor of the new technology in equilibrium. Third, the formal relationship between these variables are derived under compatibility.  Fourth, the entering firm's problem is solved by numerical methods to gain insight into the optimal linkage...... between research time and product design....

ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

KAUST Repository

Kuwahara, Hiroyuki; Umarov, Ramzan; Almasri, Islam; Gao, Xin

2017-01-01

To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

ACRE: Absolute concentration robustness exploration in module-based combinatorial networks

KAUST Repository

Kuwahara, Hiroyuki

2017-03-01

To engineer cells for industrial-scale application, a deep understanding of how to design molecular control mechanisms to tightly maintain functional stability under various fluctuations is crucial. Absolute concentration robustness (ACR) is a category of robustness in reaction network models in which the steady-state concentration of a molecular species is guaranteed to be invariant even with perturbations in the other molecular species in the network. Here, we introduce a software tool, absolute concentration robustness explorer (ACRE), which efficiently explores combinatorial biochemical networks for the ACR property. ACRE has a user-friendly interface, and it can facilitate efficient analysis of key structural features that guarantee the presence and the absence of the ACR property from combinatorial networks. Such analysis is expected to be useful in synthetic biology as it can increase our understanding of how to design molecular mechanisms to tightly control the concentration of molecular species. ACRE is freely available at https://github.com/ramzan1990/ACRE.

Computing with competition in biochemical networks.

Science.gov (United States)

Genot, Anthony J; Fujii, Teruo; Rondelez, Yannick

2012-11-16

Cells rely on limited resources such as enzymes or transcription factors to process signals and make decisions. However, independent cellular pathways often compete for a common molecular resource. Competition is difficult to analyze because of its nonlinear global nature, and its role remains unclear. Here we show how decision pathways such as transcription networks may exploit competition to process information. Competition for one resource leads to the recognition of convex sets of patterns, whereas competition for several resources (overlapping or cascaded regulons) allows even more general pattern recognition. Competition also generates surprising couplings, such as correlating species that share no resource but a common competitor. The mechanism we propose relies on three primitives that are ubiquitous in cells: multiinput motifs, competition for a resource, and positive feedback loops.

Stochastic Online Learning in Dynamic Networks under Unknown Models

Science.gov (United States)

2016-08-02

The key is to develop online learning strategies at each individual node. Specifically, through local information exchange with its neighbors, each...infinitely repeated game with incomplete information and developed a dynamic pricing strategy referred to as Competitive and Cooperative Demand Learning...Stochastic Online Learning in Dynamic Networks under Unknown Models This research aims to develop fundamental theories and practical algorithms for

Analysis and Reduction of Complex Networks Under Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Knio, Omar M

2014-04-09

This is a collaborative proposal that aims at developing new methods for the analysis and reduction of complex multiscale networks under uncertainty. The approach is based on combining methods of computational singular perturbation (CSP) and probabilistic uncertainty quantification. In deterministic settings, CSP yields asymptotic approximations of reduced-dimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty raises fundamentally new issues, particularly concerning its impact on the topology of slow manifolds, and means to represent and quantify associated variability. To address these challenges, this project uses polynomial chaos (PC) methods to reformulate uncertain network models, and to analyze them using CSP in probabilistic terms. Specific objectives include (1) developing effective algorithms that can be used to illuminate fundamental and unexplored connections among model reduction, multiscale behavior, and uncertainty, and (2) demonstrating the performance of these algorithms through applications to model problems.

Functional brain networks underlying detection and integration of disconfirmatory evidence.

Science.gov (United States)

Lavigne, Katie M; Metzak, Paul D; Woodward, Todd S

2015-05-15

.g., 17s after trial onset) the hemodynamic responses associated with all three networks were simultaneously active. These findings highlight distinct cognitive processes and corresponding functional brain networks underlying stages of disconfirmatory evidence integration, and demonstrate the power of multivariate and multi-experiment methodology in cognitive neuroscience. Copyright © 2015 Elsevier Inc. All rights reserved.

The effect of triazole induced photosynthetic pigments and biochemical constituents of Zea mays L. (Maize) under drought stress

Science.gov (United States)

Rajasekar, Mahalingam; Rabert, Gabriel Amalan; Manivannan, Paramasivam

2016-06-01

In this investigation, pot culture experiment was carried out to estimate the ameliorating effect of triazole compounds, namely Triadimefon (TDM), Tebuconazole (TBZ), and Propiconazole (PCZ) on drought stress, photosynthetic pigments, and biochemical constituents of Zea mays L. (Maize). From 30 days after sowing (DAS), the plants were subjected to 4 days interval drought (DID) stress and drought with TDM at 15 mg l-1, TBZ at 10 mg l-1, and PCZ at 15 mg l-1. Irrigation at 1-day interval was kept as control. Irrigation performed on alternative day. The plant samples were collected on 40, 50, and 60 DAS and separated into root, stem, and leaf for estimating the photosynthetic pigments and biochemical constituents. Drought and drought with triazole compounds treatment increased the biochemical glycine betaine content, whereas the protein and the pigments contents chlorophyll-a, chlorophyll-b, total chlorophyll, carotenoid, and anthocyanin decreased when compared to control. The triazole treatment mitigated the adverse effects of drought stress by increasing the biochemical potentials and paved the way to overcome drought stress in corn plant.

Feasibility of Optical Packet Switched WDM Networks without Packet Synchronisation Under Bursty Traffic Conditions

DEFF Research Database (Denmark)

Fjelde, Tina; Hansen, Peter Bukhave; Kloch, Allan

1999-01-01

We show that complex packet synchronisation may be avoided in optical packetswitched networks. Detailed traffic analysis demonstrates that packet lossratios of 1e-10 are feasible under bursty traffic conditions for a highcapacity network consisting of asynchronously operated add-drop switch...

Common and distinct brain networks underlying verbal and visual creativity.

Science.gov (United States)

Zhu, Wenfeng; Chen, Qunlin; Xia, Lingxiang; Beaty, Roger E; Yang, Wenjing; Tian, Fang; Sun, Jiangzhou; Cao, Guikang; Zhang, Qinglin; Chen, Xu; Qiu, Jiang

2017-04-01

Creativity is imperative to the progression of human civilization, prosperity, and well-being. Past creative researches tends to emphasize the default mode network (DMN) or the frontoparietal network (FPN) somewhat exclusively. However, little is known about how these networks interact to contribute to creativity and whether common or distinct brain networks are responsible for visual and verbal creativity. Here, we use functional connectivity analysis of resting-state functional magnetic resonance imaging data to investigate visual and verbal creativity-related regions and networks in 282 healthy subjects. We found that functional connectivity within the bilateral superior parietal cortex of the FPN was negatively associated with visual and verbal creativity. The strength of connectivity between the DMN and FPN was positively related to both creative domains. Visual creativity was negatively correlated with functional connectivity within the precuneus of the pDMN and right middle frontal gyrus of the FPN, and verbal creativity was negatively correlated with functional connectivity within the medial prefrontal cortex of the aDMN. Critically, the FPN mediated the relationship between the aDMN and verbal creativity, and it also mediated the relationship between the pDMN and visual creativity. Taken together, decreased within-network connectivity of the FPN and DMN may allow for flexible between-network coupling in the highly creative brain. These findings provide indirect evidence for the cooperative role of the default and executive control networks in creativity, extending past research by revealing common and distinct brain systems underlying verbal and visual creative cognition. Hum Brain Mapp 38:2094-2111, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Hybrid modeling of the crosstalk between signaling and transcriptional networks using ordinary differential equations and multi-valued logic.

Science.gov (United States)

Khan, Faiz M; Schmitz, Ulf; Nikolov, Svetoslav; Engelmann, David; Pützer, Brigitte M; Wolkenhauer, Olaf; Vera, Julio

2014-01-01

A decade of successful results indicates that systems biology is the appropriate approach to investigate the regulation of complex biochemical networks involving transcriptional and post-transcriptional regulations. It becomes mandatory when dealing with highly interconnected biochemical networks, composed of hundreds of compounds, or when networks are enriched in non-linear motifs like feedback and feedforward loops. An emerging dilemma is to conciliate models of massive networks and the adequate description of non-linear dynamics in a suitable modeling framework. Boolean networks are an ideal representation of massive networks that are humble in terms of computational complexity and data demand. However, they are inappropriate when dealing with nested feedback/feedforward loops, structural motifs common in biochemical networks. On the other hand, models of ordinary differential equations (ODEs) cope well with these loops, but they require enormous amounts of quantitative data for a full characterization of the model. Here we propose hybrid models, composed of ODE and logical sub-modules, as a strategy to handle large scale, non-linear biochemical networks that include transcriptional and post-transcriptional regulations. We illustrate the construction of this kind of models using as example a regulatory network centered on E2F1, a transcription factor involved in cancer. The hybrid modeling approach proposed is a good compromise between quantitative/qualitative accuracy and scalability when considering large biochemical networks with a small highly interconnected core, and module of transcriptionally regulated genes that are not part of critical regulatory loops. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology & Clinical Implications. Guest Editor: Yudong Cai. Copyright © 2013 Elsevier B.V. All rights reserved.

A method for under-sampled ecological network data analysis: plant-pollination as case study

Directory of Open Access Journals (Sweden)

Peter B. Sorensen

2012-01-01

Full Text Available In this paper, we develop a method, termed the Interaction Distribution (ID method, for analysis of quantitative ecological network data. In many cases, quantitative network data sets are under-sampled, i.e. many interactions are poorly sampled or remain unobserved. Hence, the output of statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks. The ID method can support assessment and inference of under-sampled ecological network data. In the current paper, we illustrate and discuss the ID method based on the properties of plant-animal pollination data sets of flower visitation frequencies. However, the ID method may be applied to other types of ecological networks. The method can supplement existing network analyses based on two definitions of the underlying probabilities for each combination of pollinator and plant species: (1, pi,j: the probability for a visit made by the i’th pollinator species to take place on the j’th plant species; (2, qi,j: the probability for a visit received by the j’th plant species to be made by the i’th pollinator. The method applies the Dirichlet distribution to estimate these two probabilities, based on a given empirical data set. The estimated mean values for pi,j and qi,j reflect the relative differences between recorded numbers of visits for different pollinator and plant species, and the estimated uncertainty of pi,j and qi,j decreases with higher numbers of recorded visits.

Biochemical parameters in the blood of grass snakes (Natrix natrix in ecosystems under varying degrees of anthropogenic influence

Directory of Open Access Journals (Sweden)

V. Y. Gasso

2016-09-01

Full Text Available The grass snake Natrix natrix (Linnaeus, 1758 is a partly hygrophilous species, distributed throughoutUkraine. This snake may be considered as a test object for environmental biomonitoring. Modern biochemical methods make it possible to obtain new scientific data on the effects of anthropogenic pressure on reptiles. Blood is a sensitive and informative indicator of the condition of an organism as it responds quickly to most changes in exogenous and endogenous factors, and reflects negative influences on both individual and, indirectly, populations. Changes in biochemical parameters may be used as biomarkers of the state of health of reptiles in ecosystems under varying degrees of anthropogenic pressure. Due the increase in anthropogenic influence the development and introduction of new methods of perceptual research, collection of up-to-date information and development of a database of reptile biochemical parameters have become an urgent priority. We collected mature individuals of the grass snake in floodplain ecosystems on the right bank of the Dnieper River in Dnipropetrovsk city. Grass snakes from floodplain habitats on the left bank of theSamaraRiver (O.L. Belgard Prysamarskii International Biosphere Station, Novomoskovsk district, Dnipropetrovsk province were studied as the control specimens. Our study demonstrated statistically significant differences between snakes from the study sites in the amount of albumin, urea and urea nitrogen, and inorganic phosphorus, as well as in alanine aminotransferase (ALT and alkaline phosphatise (AP activity. The amount of albumin in the blood serum of specimens from the anthropogenically transformed areas was significantly lower (by 25% than in that of the snakes caught in the control habitats. Decrease of the albumin concentration usually indicates abnormal processes in the kidneys and liver. According to the changes observed in the concentration of albumin, a corresponding increase in the albumin to

Physiological and biochemical response to Omega-3 plus as a dietary supplement to growing goats under hot summer conditions

Directory of Open Access Journals (Sweden)

Fatma Edrees Ibrahim Teama

2016-04-01

Full Text Available ABSTRACT The objective of the present study was to assess the effect of dietary supplementation of Omega-3 plus on some the physiological and biochemical traits in growing Baladi goats under hot summer conditions. Thirty-four growing male goats (4-5 months old were randomly divided into two equal groups. Animals in group 1 were fed a concentrate feed mixture (CFM, which was the control group. Goats in group 2 (the experimental group were offered Omega-3 plus (1,000 mg/animal day-1 (30% fish oil, containing 18% eicosapentaenoic acid and 12% docosahexaenoic acid + 100 mg wheat germ oil (0.22% tocopherols daily in addition to the basal diet for four months (the experimental period during the hot summer season. Body weight (BW changes of both groups were recorded monthly during the experiment. Blood samples were collected monthly, and total protein, immunoglobulin G (IgG, total cholesterol, triglycerides, liver enzymes (AST and ALT, blood urea nitrogen, serum creatinine, and thyroid hormones (T3 and T4 were estimated. A significant increase in the live BW of growing goats was recorded as a result of dietary supplementation of Omega-3 plus. Total protein, IgG, and T3 levels were higher than those obtained with control. In contrast, total cholesterol, triglycerides, urea, ALT, and AST levels were significantly reduced. The serum concentration of creatinine and T4 levels was indistinguishable from those of control. Addition of Omega-3 plus as a dietary supplement to growing goats under hot summer conditions increases their daily weight gain and improves their general physiological and biochemical status by decreasing total cholesterol, triglycerides, urea, ALT, and AST. It is thus suggested that Omega-3 plus should be used as a supplement in the growth period of goats.

Modeling stochasticity in biochemical reaction networks

International Nuclear Information System (INIS)

Constantino, P H; Vlysidis, M; Smadbeck, P; Kaznessis, Y N

2016-01-01

Small biomolecular systems are inherently stochastic. Indeed, fluctuations of molecular species are substantial in living organisms and may result in significant variation in cellular phenotypes. The chemical master equation (CME) is the most detailed mathematical model that can describe stochastic behaviors. However, because of its complexity the CME has been solved for only few, very small reaction networks. As a result, the contribution of CME-based approaches to biology has been very limited. In this review we discuss the approach of solving CME by a set of differential equations of probability moments, called moment equations. We present different approaches to produce and to solve these equations, emphasizing the use of factorial moments and the zero information entropy closure scheme. We also provide information on the stability analysis of stochastic systems. Finally, we speculate on the utility of CME-based modeling formalisms, especially in the context of synthetic biology efforts. (topical review)

Learning gene networks under SNP perturbations using eQTL datasets.

Directory of Open Access Journals (Sweden)

Lingxue Zhang

2014-02-01

Full Text Available The standard approach for identifying gene networks is based on experimental perturbations of gene regulatory systems such as gene knock-out experiments, followed by a genome-wide profiling of differential gene expressions. However, this approach is significantly limited in that it is not possible to perturb more than one or two genes simultaneously to discover complex gene interactions or to distinguish between direct and indirect downstream regulations of the differentially-expressed genes. As an alternative, genetical genomics study has been proposed to treat naturally-occurring genetic variants as potential perturbants of gene regulatory system and to recover gene networks via analysis of population gene-expression and genotype data. Despite many advantages of genetical genomics data analysis, the computational challenge that the effects of multifactorial genetic perturbations should be decoded simultaneously from data has prevented a widespread application of genetical genomics analysis. In this article, we propose a statistical framework for learning gene networks that overcomes the limitations of experimental perturbation methods and addresses the challenges of genetical genomics analysis. We introduce a new statistical model, called a sparse conditional Gaussian graphical model, and describe an efficient learning algorithm that simultaneously decodes the perturbations of gene regulatory system by a large number of SNPs to identify a gene network along with expression quantitative trait loci (eQTLs that perturb this network. While our statistical model captures direct genetic perturbations of gene network, by performing inference on the probabilistic graphical model, we obtain detailed characterizations of how the direct SNP perturbation effects propagate through the gene network to perturb other genes indirectly. We demonstrate our statistical method using HapMap-simulated and yeast eQTL datasets. In particular, the yeast gene network

Development of a new first-aid biochemical detector

Science.gov (United States)

Hu, Jingfei; Liao, Haiyang; Su, Shilin; Ding, Hao; Liu, Suquan

2016-10-01

The traditional biochemical detector exhibits poor adaptability, inconvenient carrying and slow detection, which can't meet the needs of first-aid under field condition like natural or man-made disasters etc. Therefore a scheme of first-aid biochemical detector based on MOMES Micro Spectrometer, UV LED and Photodiode was proposed. An optical detection structure combined continuous spectrum sweep with fixed wavelength measurement was designed, which adopted mobile detection optical path consisting of Micro Spectrometer and Halogen Lamp to detect Chloride (Cl-), Creatinine (Cre), Glucose (Glu), Hemoglobin (Hb). The UV LED and Photodiode were designed to detect Potassium (K-), Carbon dioxide (CO2), Sodium (Na+). According to the field diagnosis and treatment requirements, we designed the embedded control hardware circuit and software system, the prototype of first-aid biochemical detector was developed and the clinical trials were conducted. Experimental results show that the sample's absorbance repeatability is less than 2%, the max coefficient of variation (CV) in the batch repeatability test of all 7 biochemical parameters in blood samples is 4.68%, less than the clinical requirements 10%, the correlation coefficient (R2) in the clinical contrast test with AU5800 is almost greater than 0.97. To sum up, the prototype meets the requirements of clinical application.

A multi-period distribution network design model under demand uncertainty

Science.gov (United States)

Tabrizi, Babak H.; Razmi, Jafar

2013-05-01

Supply chain management is taken into account as an inseparable component in satisfying customers' requirements. This paper deals with the distribution network design (DND) problem which is a critical issue in achieving supply chain accomplishments. A capable DND can guarantee the success of the entire network performance. However, there are many factors that can cause fluctuations in input data determining market treatment, with respect to short-term planning, on the one hand. On the other hand, network performance may be threatened by the changes that take place within practicing periods, with respect to long-term planning. Thus, in order to bring both kinds of changes under control, we considered a new multi-period, multi-commodity, multi-source DND problem in circumstances where the network encounters uncertain demands. The fuzzy logic is applied here as an efficient tool for controlling the potential customers' demand risk. The defuzzifying framework leads the practitioners and decision-makers to interact with the solution procedure continuously. The fuzzy model is then validated by a sensitivity analysis test, and a typical problem is solved in order to illustrate the implementation steps. Finally, the formulation is tested by some different-sized problems to show its total performance.

An effective method to improve the robustness of small-world networks under attack

International Nuclear Information System (INIS)

Zhang Zheng-Zhen; Xu Wen-Jun; Lin Jia-Ru; Zeng Shang-You

2014-01-01

In this study, the robustness of small-world networks to three types of attack is investigated. Global efficiency is introduced as the network coefficient to measure the robustness of a small-world network. The simulation results prove that an increase in rewiring probability or average degree can enhance the robustness of the small-world network under all three types of attack. The effectiveness of simultaneously increasing both rewiring probability and average degree is also studied, and the combined increase is found to significantly improve the robustness of the small-world network. Furthermore, the combined effect of rewiring probability and average degree on network robustness is shown to be several times greater than that of rewiring probability or average degree individually. This means that small-world networks with a relatively high rewiring probability and average degree have advantages both in network communications and in good robustness to attacks. Therefore, simultaneously increasing rewiring probability and average degree is an effective method of constructing realistic networks. Consequently, the proposed method is useful to construct efficient and robust networks in a realistic scenario. (interdisciplinary physics and related areas of science and technology)

Effect of foliar application of α-tocopherol on vegetative growth and some biochemical constituents of two soybean genotypes under salt stress

Science.gov (United States)

Rahmawati, N.; Damanik, R. I. M.

2018-02-01

Foliar spray of plant growth regulating compounds including antioxidants is an effective strategy to overcome the adverse effects of environmental constraints on different plants. A field experiment was conducted on May - July 2017 at the experimental farm in Paluh Merbau Village Deli Serdang (EC 6 - 7 dS/m). The aim was to study the effects of foliar spray of α-tocopherol (0, 250, 500, 500 ppm) on vegetative growth and some chemical constituents of 2 soybean genotypes (Grobogan x Grobogan and Grobogan x Anjasmoro) under salt stress (EC 6 - 7 dS/m). Most of morphological and biochemical parameters were significantly affected by application of α-tocopherol. The α-tocopherol at 500 ppm recorded the best value of root fresh weight, shoot and root dry weight, number of leaves, chlorophyll b, and soluble protein content. There was significant difference found between plants treated with α-tocopherol in terms of number of branch, shoot fresh weight, and chlorophyll a. Soybean genotypes showed diverse morphology and physiological responses to salt stress. Grobogan x Anjasmoro genotype was salt-sensitive based on all variable, while Grobogan x Grobogan genotype was more tolerant based on morphological and biochemical characters.

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

Science.gov (United States)

Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

2017-04-27

Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By

Robustness of the Drinking Water Distribution Network under Changing Future Demand

NARCIS (Netherlands)

Agudelo-Vera, C.; Blokker, M.; Vreeburg, J.; Bongard, T.; Hillegers, S.; Van der Hoek, J.P.

2014-01-01

A methodology to determine the robustness of the drinking water distribution system is proposed. The performance of three networks under ten future demand scenarios was tested, using head loss and residence time as indicators. The scenarios consider technological and demographic changes. Daily

Biochemical Changes of the Organism of Apodemus flavicollis (Rodentia: Muridae Under Conditions of Environmental Anthropogenic Pollution by Heavy Metals in Northern Areas of Ukraine

Directory of Open Access Journals (Sweden)

Svitlana V. Zadyra

2014-04-01

Full Text Available The present research dedicates the integral assessment of biochemistry indexes of nature populations of rodents under conditions of environment pollution by heavy metals. The raised content in soils of mobile forms Pb, Cd, Cr, Ni and Co was revealed оn distance of 500 m to the South-West from Tripillya Thermal Power Plant (Kyiv region, Ukraine. That’s considerably (3–5 times exceeds levels for territory of Kaniv Nature Reserve (Cherkassy region, Ukraine. Territory of National Nature Park “Holosiivsky” (Kyiv, Ukraine characterized by rather increased content of active form of researched heavy metals especially Pb. Increase of the concentration of diene conjugates (3–7 times and malonic dialdehyde (2–4 times in yellow-necked mouse liver (Apodemus flavicollis of under pollution by heavy metals has been discovered. Insignificant increasing of content of Schiff basis in liver cells of rodents in region of impact of Tripillya TPP (in 2 times in spring and in summer, in autumn – in 2.5 times was detected. Seasonal dynamics of the maintenance of lipid peroxidation has been revealed. The registered changes of biochemical indicators testify about presence ecological-biochemical stress in an organism of the yellow-necked mouse in the district of influence of Tripillya TPP.

Network of vascular diseases, death and biochemical characteristics in a set of 4,197 patients with type 1 diabetes (The FinnDiane Study

Directory of Open Access Journals (Sweden)

Wadén Johan

2009-10-01

Full Text Available Background Cardiovascular disease is the main cause of premature death in patients with type 1 diabetes. Patients with diabetic kidney disease have an increased risk of heart attack or stroke. Accurate knowledge of the complex inter-dependencies between the risk factors is critical for pinpointing the best targets for research and treatment. Therefore, the aim of this study was to describe the association patterns between clinical and biochemical features of diabetic complications. Methods Medical records and serum and urine samples of 4,197 patients with type 1 diabetes were collected from health care centers in Finland. At baseline, the mean diabetes duration was 22 years, 52% were male, 23% had kidney disease (urine albumin excretion over 300 mg/24 h or end-stage renal disease and 8% had a history of macrovascular events. All-cause mortality was evaluated after an average of 6.5 years of follow-up (25,714 patient years. The dataset comprised 28 clinical and 25 biochemical variables that were regarded as the nodes of a network to assess their mutual relationships. Results The networks contained cliques that were densely inter-connected (r > 0.6, including cliques for high-density lipoprotein (HDL markers, for triglycerides and cholesterol, for urinary excretion and for indices of body mass. The links between the cliques showed biologically relevant interactions: an inverse relationship between HDL cholesterol and the triglyceride clique (r P -16, a connection between triglycerides and body mass via C-reactive protein (r > 0.3, P -16 and intermediate-density cholesterol as the connector between lipoprotein metabolism and albuminuria (r > 0.3, P -16. Aging and macrovascular disease were linked to death via working ability and retinopathy. Diabetic kidney disease, serum creatinine and potassium, retinopathy and blood pressure were inter-connected. Blood pressure correlations indicated accelerated vascular aging in individuals with kidney disease

Optimization of temporal networks under uncertainty

CERN Document Server

Wiesemann, Wolfram

2012-01-01

Many decision problems in Operations Research are defined on temporal networks, that is, workflows of time-consuming tasks whose processing order is constrained by precedence relations. For example, temporal networks are used to model projects, computer applications, digital circuits and production processes. Optimization problems arise in temporal networks when a decision maker wishes to determine a temporal arrangement of the tasks and/or a resource assignment that optimizes some network characteristic (e.g. the time required to complete all tasks). The parameters of these optimization probl

A MULTILAYER BIOCHEMICAL DRY DEPOSITION MODEL 2. MODEL EVALUATION

Science.gov (United States)

The multilayer biochemical dry deposition model (MLBC) described in the accompanying paper was tested against half-hourly eddy correlation data from six field sites under a wide range of climate conditions with various plant types. Modeled CO2, O3, SO2<...

Genetic and biochemical evidences reveal novel insights into the ...

Indian Academy of Sciences (India)

Home; Journals; Journal of Biosciences; Volume 41; Issue 4. Genetic and biochemical evidences reveal novel insights into the mechanism underlying Saccharomyces cerevisiae Sae2-mediated abrogation of DNA replication stress. INDRAJEET GHODKE K MUNIYAPPA. ARTICLE Volume 41 Issue 4 December 2016 pp ...

The influence of Metisevit on biochemical and morphological indicators of blood of piglets under nitrate loading

Directory of Open Access Journals (Sweden)

B. Gutyj

2017-07-01

Full Text Available The article presents the results of research on the influence of the developed complex preparation Metisevit on the dynamics of morphological and biochemical blood indicators of piglets under nitrate loading. The research established that sodium nitrate intoxication causes disbalance of the physiological level of hematological indicators of the tested animals’ organisms. This was indicated by the manifestations of subclinical chronic nitrate-nitrite toxicosis: the increase in the level of nitrates, nitrites and methemoglobin in the blood. After prolonged feeding of the piglets with sodium nitrate at a dose of 0.3 g nitrate ion/kg, the concentration of nitrates and nitrites in the blood serum reached its maximum on the 60th day of the experiment. Also, the number of leukocytes and erythrocytes in the blood increased, and the activity of aspartate- and alanineaminotransferase in the blood serum increased. We rank the extent of liver intoxication with nitrates according to intensity of aminotransferase in the blood serum of the tested piglets. The normalization of morphological and biochemical blood indicators of piglets under nitrate-nitrite intoxication requires usage of a preparation which contains vitamins, zeolites and antioxidants. If the fodder contains high doses of nitrates, 1.0 mg/kg dose of Metisevit is added to the fodder for preventing subclinical nitrate-nitrite toxicosis. Metisevit contains the following agents: phenozan acid, methionine, zeolite, selenium, vitamins E and C. The research conducted proved the feasibility of using Metisevit for preventing chronic nitrate-nitrite toxicosis in piglets. This preparation caused a decrease in the concentration of nitrates, nitrites and in the level of methemoglobin in the blood of piglets. Usage of Metisevit on piglets showed normalization of the number of erythrocytes and hemoglobin in the blood on the 10th day, and normalization of ASAT and ALAT on 30th and 90th days. The mechanism of

Network Formation under the Threat of Disruption

NARCIS (Netherlands)

Hoyer, B.

2013-01-01

The studies in this thesis are focused on the impact the presence of a network disruptor has on network formation models. In particular, we build two theoretical models to study the effect of network disruption on network formation and test the effect network disruption has on equilibrium selection

Biochemical and anatomical changes and yield reduction in rice (Oryza sativa L.) under varied salinity regimes.

Science.gov (United States)

Hakim, M A; Juraimi, Abdul Shukor; Hanafi, M M; Ismail, Mohd Razi; Selamat, Ahmad; Rafii, M Y; Latif, M A

2014-01-01

Five Malaysian rice (Oryza sativa L.) varieties, MR33, MR52, MR211, MR219, and MR232, were tested in pot culture under different salinity regimes for biochemical response, physiological activity, and grain yield. Three different levels of salt stresses, namely, 4, 8, and 12 dS m(-1), were used in a randomized complete block design with four replications under glass house conditions. The results revealed that the chlorophyll content, proline, sugar content, soluble protein, free amino acid, and yield per plant of all the genotypes were influenced by different salinity levels. The chlorophyll content was observed to decrease with salinity level but the proline increased with salinity levels in all varieties. Reducing sugar and total sugar increased up to 8 dS m(-1) and decreased up to 12 dS m(-1). Nonreducing sugar decreased with increasing the salinity levels in all varieties. Soluble protein and free amino acid also decreased with increasing salinity levels. Cortical cells of MR211 and MR232 did not show cell collapse up to 8 dS m(-1) salinity levels compared to susceptible checks (IR20 and BRRI dhan29). Therefore, considering all parameters, MR211 and MR232 showed better salinity tolerance among the tested varieties. Both cluster and principal component analyses depict the similar results.

Biochemical and Anatomical Changes and Yield Reduction in Rice (Oryza sativa L. under Varied Salinity Regimes

Directory of Open Access Journals (Sweden)

M. A. Hakim

2014-01-01

Full Text Available Five Malaysian rice (Oryza sativa L. varieties, MR33, MR52, MR211, MR219, and MR232, were tested in pot culture under different salinity regimes for biochemical response, physiological activity, and grain yield. Three different levels of salt stresses, namely, 4, 8, and 12 dS m−1, were used in a randomized complete block design with four replications under glass house conditions. The results revealed that the chlorophyll content, proline, sugar content, soluble protein, free amino acid, and yield per plant of all the genotypes were influenced by different salinity levels. The chlorophyll content was observed to decrease with salinity level but the proline increased with salinity levels in all varieties. Reducing sugar and total sugar increased up to 8 dS m−1 and decreased up to 12 dS m−1. Nonreducing sugar decreased with increasing the salinity levels in all varieties. Soluble protein and free amino acid also decreased with increasing salinity levels. Cortical cells of MR211 and MR232 did not show cell collapse up to 8 dS m−1 salinity levels compared to susceptible checks (IR20 and BRRI dhan29. Therefore, considering all parameters, MR211 and MR232 showed better salinity tolerance among the tested varieties. Both cluster and principal component analyses depict the similar results.

Multiple network alignment on quantum computers

Science.gov (United States)

Daskin, Anmer; Grama, Ananth; Kais, Sabre

2014-12-01

Comparative analyses of graph-structured datasets underly diverse problems. Examples of these problems include identification of conserved functional components (biochemical interactions) across species, structural similarity of large biomolecules, and recurring patterns of interactions in social networks. A large class of such analyses methods quantify the topological similarity of nodes across networks. The resulting correspondence of nodes across networks, also called node alignment, can be used to identify invariant subgraphs across the input graphs. Given graphs as input, alignment algorithms use topological information to assign a similarity score to each -tuple of nodes, with elements (nodes) drawn from each of the input graphs. Nodes are considered similar if their neighbors are also similar. An alternate, equivalent view of these network alignment algorithms is to consider the Kronecker product of the input graphs and to identify high-ranked nodes in the Kronecker product graph. Conventional methods such as PageRank and HITS (Hypertext-Induced Topic Selection) can be used for this purpose. These methods typically require computation of the principal eigenvector of a suitably modified Kronecker product matrix of the input graphs. We adopt this alternate view of the problem to address the problem of multiple network alignment. Using the phase estimation algorithm, we show that the multiple network alignment problem can be efficiently solved on quantum computers. We characterize the accuracy and performance of our method and show that it can deliver exponential speedups over conventional (non-quantum) methods.

Synchronisation of networked Kuramoto oscillators under stable Lévy noise

Science.gov (United States)

Kalloniatis, Alexander C.; Roberts, Dale O.

2017-01-01

We study the Kuramoto model on several classes of network topologies examining the dynamics under the influence of Lévy noise. Such noise exhibits heavier tails than Gaussian and allows us to understand how 'shocks' influence the individual oscillator and collective system behaviour. Skewed α-stable Lévy noise, equivalent to fractional diffusion perturbations, are considered. We perform numerical simulations for Erdős-Rényi (ER) and Barabási-Albert (BA) scale free networks of size N = 1000 while varying the Lévy index α for the noise. We find that synchrony now assumes a surprising variety of forms, not seen for Gaussian-type noise, and changing with α: a noise-generated drift, a smooth α dependence of the point of cross-over of ER and BA networks in the degree of synchronisation, and a severe loss of synchronisation at low values of α. We also show that this robustness of the BA network across most values of α can also be understood as a consequence of the Laplacian of the graph working within the fractional Fokker-Planck equation of the linearised system, close to synchrony, with both eigenvalues and eigenvectors alternately contributing in different regimes of α.

Estimation of parameter sensitivities for stochastic reaction networks

KAUST Repository

Gupta, Ankit

2016-01-07

Quantification of the effects of parameter uncertainty is an important and challenging problem in Systems Biology. We consider this problem in the context of stochastic models of biochemical reaction networks where the dynamics is described as a continuous-time Markov chain whose states represent the molecular counts of various species. For such models, effects of parameter uncertainty are often quantified by estimating the infinitesimal sensitivities of some observables with respect to model parameters. The aim of this talk is to present a holistic approach towards this problem of estimating parameter sensitivities for stochastic reaction networks. Our approach is based on a generic formula which allows us to construct efficient estimators for parameter sensitivity using simulations of the underlying model. We will discuss how novel simulation techniques, such as tau-leaping approximations, multi-level methods etc. can be easily integrated with our approach and how one can deal with stiff reaction networks where reactions span multiple time-scales. We will demonstrate the efficiency and applicability of our approach using many examples from the biological literature.

Suppression of anomalous synchronization and nonstationary behavior of neural network under small-world topology

Science.gov (United States)

Boaretto, B. R. R.; Budzinski, R. C.; Prado, T. L.; Kurths, J.; Lopes, S. R.

2018-05-01

It is known that neural networks under small-world topology can present anomalous synchronization and nonstationary behavior for weak coupling regimes. Here, we propose methods to suppress the anomalous synchronization and also to diminish the nonstationary behavior occurring in weakly coupled neural network under small-world topology. We consider a network of 2000 thermally sensitive identical neurons, based on the model of Hodgkin-Huxley in a small-world topology, with the probability of adding non local connection equal to p = 0 . 001. Based on experimental protocols to suppress anomalous synchronization, as well as nonstationary behavior of the neural network dynamics, we make use of (i) external stimulus (pulsed current); (ii) biologic parameters changing (neuron membrane conductance changes); and (iii) body temperature changes. Quantification analysis to evaluate phase synchronization makes use of the Kuramoto's order parameter, while recurrence quantification analysis, particularly the determinism, computed over the easily accessible mean field of network, the local field potential (LFP), is used to evaluate nonstationary states. We show that the methods proposed can control the anomalous synchronization and nonstationarity occurring for weak coupling parameter without any effect on the individual neuron dynamics, neither in the expected asymptotic synchronized states occurring for large values of the coupling parameter.

Modeling the Propagation of Mobile Phone Virus under Complex Network

Science.gov (United States)

Yang, Wei; Wei, Xi-liang; Guo, Hao; An, Gang; Guo, Lei

2014-01-01

Mobile phone virus is a rogue program written to propagate from one phone to another, which can take control of a mobile device by exploiting its vulnerabilities. In this paper the propagation model of mobile phone virus is tackled to understand how particular factors can affect its propagation and design effective containment strategies to suppress mobile phone virus. Two different propagation models of mobile phone viruses under the complex network are proposed in this paper. One is intended to describe the propagation of user-tricking virus, and the other is to describe the propagation of the vulnerability-exploiting virus. Based on the traditional epidemic models, the characteristics of mobile phone viruses and the network topology structure are incorporated into our models. A detailed analysis is conducted to analyze the propagation models. Through analysis, the stable infection-free equilibrium point and the stability condition are derived. Finally, considering the network topology, the numerical and simulation experiments are carried out. Results indicate that both models are correct and suitable for describing the spread of two different mobile phone viruses, respectively. PMID:25133209

Dynamics of biochemical processes and redox conditions in geochemically linked landscapes of oligotrophic bogs

Science.gov (United States)

Inisheva, L. I.; Szajdak, L.; Sergeeva, M. A.

2016-04-01

The biological activity in oligotrophic peatlands at the margins of the Vasyugan Mire has been studied. It is shown found that differently directed biochemical processes manifest themselves in the entire peat profile down to the underlying mineral substrate. Their activity is highly variable. It is argued that the notion about active and inert layers in peat soils is only applicable for the description of their water regime. The degree of the biochemical activity is specified by the physical soil properties. As a result of the biochemical processes, a micromosaic aerobic-anaerobic medium is developed under the surface waterlogged layer of peat deposits. This layer contains the gas phase, including oxygen. It is concluded that the organic and mineral parts of peat bogs represent a single functional system of a genetic peat profile with a clear record of the history of its development.

Biochemical and physiological characterization of three rice cultivars under different daytime temperature conditions

Directory of Open Access Journals (Sweden)

Alefsi David Sanchez-Reinoso

2014-12-01

Full Text Available Heat stress due to high daytime temperatures is one of the main limiting factors in rice (Oryza sativa L. yield in Colombia. Thus, the objective of the present research was to analyze the effect of three different daytime temperatures (25, 35, and 40 °C on the physiological responses of three Colombian rice cultivars (F60, F733, and F473, thereby contributing to the knowledge of rice acclimation mechanisms. For 10 d, eight plants of each of the three cultivars were subjected daily to 5 h periods of 35 and 40 °C. The control treatment corresponded to normal growth conditions (25 °C. Thermal stress was assessed based on a series of physiological and biochemical parameters. The 35 °C treatment produced photosynthetic and respiratory differences in all three cultivars. At 40 °C, 'F60' displayed the lowest photosynthetic rate and the highest respiratory rate. Although this cultivar experienced particularly strong electrolyte leakage and changes in proline when subjected to the high-temperature treatments, similar trends were observed in 'F733' and 'F473'. At 40 °C, the concentration of malondialdehyde (MDA was lower in 'F473' than in the other cultivars. These results may explain the poor agronomic performance of 'F60' in the field under daytime heat stress. The methodologies employed in the present work may be useful in Colombian rice breeding programs, particularly for the selection of heat-tolerant breeding stocks.

Using chemistry and microfluidics to understand the spatial dynamics of complex biological networks.

Science.gov (United States)

Kastrup, Christian J; Runyon, Matthew K; Lucchetta, Elena M; Price, Jessica M; Ismagilov, Rustem F

2008-04-01

Understanding the spatial dynamics of biochemical networks is both fundamentally important for understanding life at the systems level and also has practical implications for medicine, engineering, biology, and chemistry. Studies at the level of individual reactions provide essential information about the function, interactions, and localization of individual molecular species and reactions in a network. However, analyzing the spatial dynamics of complex biochemical networks at this level is difficult. Biochemical networks are nonequilibrium systems containing dozens to hundreds of reactions with nonlinear and time-dependent interactions, and these interactions are influenced by diffusion, flow, and the relative values of state-dependent kinetic parameters. To achieve an overall understanding of the spatial dynamics of a network and the global mechanisms that drive its function, networks must be analyzed as a whole, where all of the components and influential parameters of a network are simultaneously considered. Here, we describe chemical concepts and microfluidic tools developed for network-level investigations of the spatial dynamics of these networks. Modular approaches can be used to simplify these networks by separating them into modules, and simple experimental or computational models can be created by replacing each module with a single reaction. Microfluidics can be used to implement these models as well as to analyze and perturb the complex network itself with spatial control on the micrometer scale. We also describe the application of these network-level approaches to elucidate the mechanisms governing the spatial dynamics of two networkshemostasis (blood clotting) and early patterning of the Drosophila embryo. To investigate the dynamics of the complex network of hemostasis, we simplified the network by using a modular mechanism and created a chemical model based on this mechanism by using microfluidics. Then, we used the mechanism and the model to

Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

Science.gov (United States)

2015-03-03

based whole-cell models of E. coli [6]. Conversely , highly abstracted kinetic frameworks, such as the cybernetic framework, represented a paradigm shift...metabolic objective function has been the optimization of biomass formation [18], although other metabolic objectives have also been estimated [19...experimental data. Toward these questions, we explored five hypothetical cell-free networks. Each network shared the same enzymatic connectivity, but

Microbial and biochemical alterations due to storage of deep-sea sediments under ambient tropical conditions

Digital Repository Service at National Institute of Oceanography (India)

Das, A.; Fernandes, C.E.G.; Naik, S.S.; Mourya, B.S.; Sujith, P.P.; Sharma, R; LokaBharathi, P.A.

-tight polythene containers. Changes in microbial and biochemical parameters were monitored once in every two months for a year. Bacterial counts and ATP decreased from ~108 to ~107 g-1 and ~103 to ~101 ng g-1 dry sediment respectively, within 8-10 months before...

Enhancing network performance under single link failure with AS-disjoint BGP extension

DEFF Research Database (Denmark)

Manolova, Anna Vasileva; Romeral, S.; Ruepp, Sarah Renée

2009-01-01

In this paper we propose an enhancement of the BGP protocol for obtaining AS-disjoint paths in GMPLS multi-domain networks. We evaluate the benefits of having AS-disjoint paths under single inter-domain link failure for two main applications: routing of future connection requests during routing...... protocol re-convergence and applying multi-domain restoration as survivability mechanism in case of a single link failure. The proposed BGP modification is a simple and effective solution for disjoint path selection in connection-oriented multi-domain networks. Our results show that applying the proper...

Identification of neutral biochemical network models from time series data.

Science.gov (United States)

Vilela, Marco; Vinga, Susana; Maia, Marco A Grivet Mattoso; Voit, Eberhard O; Almeida, Jonas S

2009-05-05

The major difficulty in modeling biological systems from multivariate time series is the identification of parameter sets that endow a model with dynamical behaviors sufficiently similar to the experimental data. Directly related to this parameter estimation issue is the task of identifying the structure and regulation of ill-characterized systems. Both tasks are simplified if the mathematical model is canonical, i.e., if it is constructed according to strict guidelines. In this report, we propose a method for the identification of admissible parameter sets of canonical S-systems from biological time series. The method is based on a Monte Carlo process that is combined with an improved version of our previous parameter optimization algorithm. The method maps the parameter space into the network space, which characterizes the connectivity among components, by creating an ensemble of decoupled S-system models that imitate the dynamical behavior of the time series with sufficient accuracy. The concept of sloppiness is revisited in the context of these S-system models with an exploration not only of different parameter sets that produce similar dynamical behaviors but also different network topologies that yield dynamical similarity. The proposed parameter estimation methodology was applied to actual time series data from the glycolytic pathway of the bacterium Lactococcus lactis and led to ensembles of models with different network topologies. In parallel, the parameter optimization algorithm was applied to the same dynamical data upon imposing a pre-specified network topology derived from prior biological knowledge, and the results from both strategies were compared. The results suggest that the proposed method may serve as a powerful exploration tool for testing hypotheses and the design of new experiments.

Towards a predictive theory for genetic regulatory networks

Science.gov (United States)

Tkacik, Gasper

When cells respond to changes in the environment by regulating the expression levels of their genes, we often draw parallels between these biological processes and engineered information processing systems. One can go beyond this qualitative analogy, however, by analyzing information transmission in biochemical ``hardware'' using Shannon's information theory. Here, gene regulation is viewed as a transmission channel operating under restrictive constraints set by the resource costs and intracellular noise. We present a series of results demonstrating that a theory of information transmission in genetic regulatory circuits feasibly yields non-trivial, testable predictions. These predictions concern strategies by which individual gene regulatory elements, e.g., promoters or enhancers, read out their signals; as well as strategies by which small networks of genes, independently or in spatially coupled settings, respond to their inputs. These predictions can be quantitatively compared to the known regulatory networks and their function, and can elucidate how reproducible biological processes, such as embryonic development, can be orchestrated by networks built out of noisy components. Preliminary successes in the gap gene network of the fruit fly Drosophila indicate that a full ab initio theoretical prediction of a regulatory network is possible, a feat that has not yet been achieved for any real regulatory network. We end by describing open challenges on the path towards such a prediction.

Biochemical impacts of Hg in Mytilus galloprovincialis under present and predicted warming scenarios.

Science.gov (United States)

Coppola, Francesca; Almeida, Ângela; Henriques, Bruno; Soares, Amadeu M V M; Figueira, Etelvina; Pereira, Eduarda; Freitas, Rosa

2017-12-01

The interest in the consequences of climate change on the physiological and biochemical functioning of marine organisms is increasing, but the indirect and interactive effects resulting from warming on bioconcentration and responsiveness to pollutants are still poorly explored, particularly in terms of cellular responses. The present study investigated the impacts of Hg in Mytilus galloprovincialis under control (17°C) and warming (21°C) conditions, assessing mussels Hg bioconcentration capacity, metabolic and oxidative status after 14 and 28days of exposure. Results obtained showed greater impacts in mussels exposed for 28days in comparison to 14days of exposure. Furthermore, our findings revealed that the increase in temperature from 17 to 21°C reduced the bioconcentration of Hg by M. galloprovincialis, which may explain higher mortality rates at 17°C in comparison to 21°C. Lower Hg concentration at 21°C in mussels tissue may result from valves closure for longer periods, identified by reduced energy reserves consumption at higher temperature, which in turn might also contributed to higher oxidative stress in organisms exposed to this condition. The highest LPO levels observed in mussels exposed to higher temperatures alone indicate that warming conditions will greatly affect M. galloprovincialis. Furthermore, the present study showed that the impacts induced by the combination of Hg and warming were similar to the ones caused by increased temperature acting alone, mainly due to increased antioxidant defenses in organisms under combined effects of Hg and warming, suggesting that warming was the factor that mostly contributed to oxidative stress in mussels. Although higher mortality was observed in individuals exposed to 17°C and Hg compared to organisms exposed to Hg at 21°C, the oxidative stress induced at higher temperature may generate negative consequences on mussels reproductive and feeding capacity, growth and, consequently, on population

Biochemical Factors Modulating Cellular Neurotoxicity of Methylmercury

Directory of Open Access Journals (Sweden)

Parvinder Kaur

2011-01-01

Full Text Available Methylmercury (MeHg, an environmental toxicant primarily found in fish and seafood, poses a dilemma to both consumers and regulatory authorities, given the nutritional benefits of fish consumption versus the possible adverse neurological damage. Several studies have shown that MeHg toxicity is influenced by a number of biochemical factors, such as glutathione (GSH, fatty acids, vitamins, and essential elements, but the cellular mechanisms underlying these complex interactions have not yet been fully elucidated. The objective of this paper is to outline the cellular response to dietary nutrients, as well as to describe the neurotoxic exposures to MeHg. In order to determine the cellular mechanism(s of toxicity, the effect of pretreatment with biochemical factors (e.g., N-acetyl cysteine, (NAC; diethyl maleate, (DEM; docosahexaenoic acid, (DHA; selenomethionine, SeM; Trolox and MeHg treatment on intercellular antioxidant status, MeHg content, and other endpoints was evaluated. This paper emphasizes that the protection against oxidative stress offered by these biochemical factors is among one of the major mechanisms responsible for conferring neuroprotection. It is therefore critical to ascertain the cellular mechanisms associated with various dietary nutrients as well as to determine the potential effects of neurotoxic exposures for accurately assessing the risks and benefits associated with fish consumption.

A characterization of scale invariant responses in enzymatic networks.

Directory of Open Access Journals (Sweden)

Maja Skataric

Full Text Available An ubiquitous property of biological sensory systems is adaptation: a step increase in stimulus triggers an initial change in a biochemical or physiological response, followed by a more gradual relaxation toward a basal, pre-stimulus level. Adaptation helps maintain essential variables within acceptable bounds and allows organisms to readjust themselves to an optimum and non-saturating sensitivity range when faced with a prolonged change in their environment. Recently, it was shown theoretically and experimentally that many adapting systems, both at the organism and single-cell level, enjoy a remarkable additional feature: scale invariance, meaning that the initial, transient behavior remains (approximately the same even when the background signal level is scaled. In this work, we set out to investigate under what conditions a broadly used model of biochemical enzymatic networks will exhibit scale-invariant behavior. An exhaustive computational study led us to discover a new property of surprising simplicity and generality, uniform linearizations with fast output (ULFO, whose validity we show is both necessary and sufficient for scale invariance of three-node enzymatic networks (and sufficient for any number of nodes. Based on this study, we go on to develop a mathematical explanation of how ULFO results in scale invariance. Our work provides a surprisingly consistent, simple, and general framework for understanding this phenomenon, and results in concrete experimental predictions.

Sustainable and Resilient Supply Chain Network Design under Disruption Risks

Directory of Open Access Journals (Sweden)

Sonia Irshad Mari

2014-09-01

Full Text Available Sustainable supply chain network design is a rich area for academic research that is still in its infancy and has potential to affect supply chain performance. Increasing regulations for carbon and waste management are forcing firms to consider their supply chains from ecological and social objectives, but in reality, however, facilities and the links connecting them are disrupted from time to time, due to poor weather, natural or manmade disasters or a combination of any other factors. Supply chain systems drop their sustainability objectives while coping with these unexpected disruptions. Hence, the new challenges for supply chain managers are to design an efficient and effective supply chain network that will be resilient enough to bounce back from any disruption and that also should have sufficient vigilance to offer same sustainability under a disruption state. This paper focuses on ecological sustainability, because an environmental focus in a supply chain system is more important and also links with other pillars of sustainability, as the products need to be produced, packed and transported in an ethical way, which should not harm social balance and the environment. Owing to importance of the considered issue, this paper attempts to introduce a network optimization model for a sustainable and resilient supply chain network by incorporating (1 sustainability via carbon emissions and embodied carbon footprints and (2 resilience by incorporating location-specific risks. The proposed goal programming (GP model optimizes the total cost, while considering the resilience and sustainability of the supply chain network.

Geometric universality of currents in an open network of interacting particles

International Nuclear Information System (INIS)

Sinitsyn, Nikolai A.; Chernyak, Vladimir Y.; Chertkov, Michael

2010-01-01

We discuss a non-equilibrium statistical system on a graph or network. Identical particles are injected, interact with each other, traverse, and leave the graph in a stochastic manner described in terms of Poisson rates, possibly dependent on time and instantaneous occupation numbers at the nodes of the graph. We show that under the assumption of the relative rates constancy, the system demonstrates a profound statistical symmetry, resulting in geometric universality of the particle currents statistics. The phenomenon applies broadly to many man-made and natural open stochastic systems, such as queuing of packages over internet, transport of electrons and quasi-particles in mesoscopic systems, and chains of reactions in bio-chemical networks. We illustrate the utility of the general approach using two enabling examples from the two latter disciplines.

A performance study of unmanned aerial vehicle-based sensor networks under cyber attack

Science.gov (United States)

Puchaty, Ethan M.

In UAV-based sensor networks, an emerging area of interest is the performance of these networks under cyber attack. This study seeks to evaluate the performance trade-offs from a System-of-Systems (SoS) perspective between various UAV communications architecture options in the context two missions: tracking ballistic missiles and tracking insurgents. An agent-based discrete event simulation is used to model a sensor communication network consisting of UAVs, military communications satellites, ground relay stations, and a mission control center. Network susceptibility to cyber attack is modeled with probabilistic failures and induced data variability, with performance metrics focusing on information availability, latency, and trustworthiness. Results demonstrated that using UAVs as routers increased network availability with a minimal latency penalty and communications satellite networks were best for long distance operations. Redundancy in the number of links between communication nodes helped mitigate cyber-caused link failures and add robustness in cases of induced data variability by an adversary. However, when failures were not independent, redundancy and UAV routing were detrimental in some cases to network performance. Sensitivity studies indicated that long cyber-caused downtimes and increasing failure dependencies resulted in build-ups of failures and caused significant degradations in network performance.

Biochemical Control With Radiotherapy Improves Overall Survival in Intermediate and High-Risk Prostate Cancer Patients Who Have an Estimated 10-Year Overall Survival of >90%

International Nuclear Information System (INIS)

Herbert, Christopher; Liu, Mitchell; Tyldesley, Scott; Morris, W. James; Joffres, Michel; Khaira, Mandip; Kwan, Winkle; Moiseenko, Vitali; Pickles, Thomas

2012-01-01

Purpose: To identify subgroups of patients with carcinoma of the prostate treated with radical radiotherapy that have improved overall survival when disease is biochemically controlled. Methods and Materials: A cohort of 1,060 prostate cancer patients treated with radical radiotherapy was divided into nine subgroups based on National Comprehensive Cancer Network risk category and estimated 10-year overall survival (eOS 10y) derived from the age adjusted Charlson Comorbidity Index. Patients with and without biochemical control were compared with respect to overall survival. Actuarial estimates of overall survival were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards models were used for analysis of overall survival. Results: Median follow-up was 125 months (range, 51–176 months). Only the subgroups with high or intermediate risk disease and an eOS 10y of >90% had a statistically significantly improved overall survival when prostate cancer was biochemically controlled. In all other groups, biochemical control made no significant difference to overall survival. In the subgroup with high-risk disease and eOS 10y >90%, actuarial overall survival was 86.3% (95% confidence interval [CI] 78.5%–94.1%) and 62.1% (95% CI 52.9%–71.3%) for patients with biochemical control and biochemical relapse respectively (p = 0.002). In the intermediate risk group with eOS >90%, actuarial overall survival was 95.3% (95% CI 89.0%–100%) and 79.8% (95% CI 68.0%–91.6%) for biochemically controlled and biochemically relapsed patients (p = 0.033). On multivariate analysis, National Comprehensive Cancer Network risk group (p = 0.005), biochemical control (p = 0.033) and eOS 10y (p 90%.

Near-infrared Raman spectroscopy for estimating biochemical changes associated with different pathological conditions of cervix

Science.gov (United States)

Daniel, Amuthachelvi; Prakasarao, Aruna; Ganesan, Singaravelu

2018-02-01

The molecular level changes associated with oncogenesis precede the morphological changes in cells and tissues. Hence molecular level diagnosis would promote early diagnosis of the disease. Raman spectroscopy is capable of providing specific spectral signature of various biomolecules present in the cells and tissues under various pathological conditions. The aim of this work is to develop a non-linear multi-class statistical methodology for discrimination of normal, neoplastic and malignant cells/tissues. The tissues were classified as normal, pre-malignant and malignant by employing Principal Component Analysis followed by Artificial Neural Network (PC-ANN). The overall accuracy achieved was 99%. Further, to get an insight into the quantitative biochemical composition of the normal, neoplastic and malignant tissues, a linear combination of the major biochemicals by non-negative least squares technique was fit to the measured Raman spectra of the tissues. This technique confirms the changes in the major biomolecules such as lipids, nucleic acids, actin, glycogen and collagen associated with the different pathological conditions. To study the efficacy of this technique in comparison with histopathology, we have utilized Principal Component followed by Linear Discriminant Analysis (PC-LDA) to discriminate the well differentiated, moderately differentiated and poorly differentiated squamous cell carcinoma with an accuracy of 94.0%. And the results demonstrated that Raman spectroscopy has the potential to complement the good old technique of histopathology.

Thermodynamically consistent Bayesian analysis of closed biochemical reaction systems

Directory of Open Access Journals (Sweden)

Goutsias John

2010-11-01

Full Text Available Abstract Background Estimating the rate constants of a biochemical reaction system with known stoichiometry from noisy time series measurements of molecular concentrations is an important step for building predictive models of cellular function. Inference techniques currently available in the literature may produce rate constant values that defy necessary constraints imposed by the fundamental laws of thermodynamics. As a result, these techniques may lead to biochemical reaction systems whose concentration dynamics could not possibly occur in nature. Therefore, development of a thermodynamically consistent approach for estimating the rate constants of a biochemical reaction system is highly desirable. Results We introduce a Bayesian analysis approach for computing thermodynamically consistent estimates of the rate constants of a closed biochemical reaction system with known stoichiometry given experimental data. Our method employs an appropriately designed prior probability density function that effectively integrates fundamental biophysical and thermodynamic knowledge into the inference problem. Moreover, it takes into account experimental strategies for collecting informative observations of molecular concentrations through perturbations. The proposed method employs a maximization-expectation-maximization algorithm that provides thermodynamically feasible estimates of the rate constant values and computes appropriate measures of estimation accuracy. We demonstrate various aspects of the proposed method on synthetic data obtained by simulating a subset of a well-known model of the EGF/ERK signaling pathway, and examine its robustness under conditions that violate key assumptions. Software, coded in MATLAB®, which implements all Bayesian analysis techniques discussed in this paper, is available free of charge at http://www.cis.jhu.edu/~goutsias/CSS%20lab/software.html. Conclusions Our approach provides an attractive statistical methodology for

Mathematical treatment of isotopologue and isotopomer speciation and fractionation in biochemical kinetics

Science.gov (United States)

Maggi, Federico; Riley, William J.

2010-03-01

We present a mathematical treatment of the kinetic equations that describe isotopologue and isotopomer speciation and fractionation during enzyme-catalyzed biochemical reactions. These equations, presented here with the name GEBIK (general equations for biochemical isotope kinetics) and GEBIF (general equations for biochemical isotope fractionation), take into account microbial biomass and enzyme dynamics, reaction stoichiometry, isotope substitution number, and isotope location within each isotopologue and isotopomer. In addition to solving the complete GEBIK and GEBIF, we also present and discuss two approximations to the full solutions under the assumption of biomass-free and enzyme steady-state, and under the quasi-steady-state assumption as applied to the complexation rate. The complete and approximate approaches are applied to observations of biological denitrification in soils. Our analysis highlights that the full GEBIK and GEBIF provide a more accurate description of concentrations and isotopic compositions of substrates and products throughout the reaction than do the approximate forms. We demonstrate that the isotopic effects of a biochemical reaction depend, in the most general case, on substrate and complex concentrations and, therefore, the fractionation factor is a function of time. We also demonstrate that inverse isotopic effects can occur for values of the fractionation factor smaller than 1, and that reactions that do not discriminate isotopes do not necessarily imply a fractionation factor equal to 1.

Phenotypic stability and plasticity in GMP-derived cells as determined by their underlying regulatory network.

Science.gov (United States)

Ramírez, Carlos; Mendoza, Luis

2018-04-01

Blood cell formation has been recognized as a suitable system to study celular differentiation mainly because of its experimental accessibility, and because it shows characteristics such as hierarchical and gradual bifurcated patterns of commitment, which are present in several developmental processes. Although hematopoiesis has been extensively studied and there is a wealth of molecular and cellular data about it, it is not clear how the underlying molecular regulatory networks define or restrict cellular differentiation processes. Here, we infer the molecular regulatory network that controls the differentiation of a blood cell subpopulation derived from the granulocyte-monocyte precursor (GMP), comprising monocytes, neutrophils, eosinophils, basophils and mast cells. We integrate published qualitative experimental data into a model to describe temporal expression patterns observed in GMP-derived cells. The model is implemented as a Boolean network, and its dynamical behavior is studied. Steady states of the network can be clearly identified with the expression profiles of monocytes, mast cells, neutrophils, basophils, and eosinophils, under wild-type and mutant backgrounds. All scripts are publicly available at https://github.com/caramirezal/RegulatoryNetworkGMPModel. lmendoza@biomedicas.unam.mx. Supplementary data are available at Bioinformatics online.

A comparison of approximation techniques for variance-based sensitivity analysis of biochemical reaction systems

Directory of Open Access Journals (Sweden)

Goutsias John

2010-05-01

Full Text Available Abstract Background Sensitivity analysis is an indispensable tool for the analysis of complex systems. In a recent paper, we have introduced a thermodynamically consistent variance-based sensitivity analysis approach for studying the robustness and fragility properties of biochemical reaction systems under uncertainty in the standard chemical potentials of the activated complexes of the reactions and the standard chemical potentials of the molecular species. In that approach, key sensitivity indices were estimated by Monte Carlo sampling, which is computationally very demanding and impractical for large biochemical reaction systems. Computationally efficient algorithms are needed to make variance-based sensitivity analysis applicable to realistic cellular networks, modeled by biochemical reaction systems that consist of a large number of reactions and molecular species. Results We present four techniques, derivative approximation (DA, polynomial approximation (PA, Gauss-Hermite integration (GHI, and orthonormal Hermite approximation (OHA, for analytically approximating the variance-based sensitivity indices associated with a biochemical reaction system. By using a well-known model of the mitogen-activated protein kinase signaling cascade as a case study, we numerically compare the approximation quality of these techniques against traditional Monte Carlo sampling. Our results indicate that, although DA is computationally the most attractive technique, special care should be exercised when using it for sensitivity analysis, since it may only be accurate at low levels of uncertainty. On the other hand, PA, GHI, and OHA are computationally more demanding than DA but can work well at high levels of uncertainty. GHI results in a slightly better accuracy than PA, but it is more difficult to implement. OHA produces the most accurate approximation results and can be implemented in a straightforward manner. It turns out that the computational cost of the

Identifiability of tree-child phylogenetic networks under a probabilistic recombination-mutation model of evolution.

Science.gov (United States)

Francis, Andrew; Moulton, Vincent

2018-06-07

Phylogenetic networks are an extension of phylogenetic trees which are used to represent evolutionary histories in which reticulation events (such as recombination and hybridization) have occurred. A central question for such networks is that of identifiability, which essentially asks under what circumstances can we reliably identify the phylogenetic network that gave rise to the observed data? Recently, identifiability results have appeared for networks relative to a model of sequence evolution that generalizes the standard Markov models used for phylogenetic trees. However, these results are quite limited in terms of the complexity of the networks that are considered. In this paper, by introducing an alternative probabilistic model for evolution along a network that is based on some ground-breaking work by Thatte for pedigrees, we are able to obtain an identifiability result for a much larger class of phylogenetic networks (essentially the class of so-called tree-child networks). To prove our main theorem, we derive some new results for identifying tree-child networks combinatorially, and then adapt some techniques developed by Thatte for pedigrees to show that our combinatorial results imply identifiability in the probabilistic setting. We hope that the introduction of our new model for networks could lead to new approaches to reliably construct phylogenetic networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

BISEN: Biochemical simulation environment

NARCIS (Netherlands)

Vanlier, J.; Wu, F.; Qi, F.; Vinnakota, K.C.; Han, Y.; Dash, R.K.; Yang, F.; Beard, D.A.

2009-01-01

The Biochemical Simulation Environment (BISEN) is a suite of tools for generating equations and associated computer programs for simulating biochemical systems in the MATLAB® computing environment. This is the first package that can generate appropriate systems of differential equations for

Credal Networks under Maximum Entropy

OpenAIRE

Lukasiewicz, Thomas

2013-01-01

We apply the principle of maximum entropy to select a unique joint probability distribution from the set of all joint probability distributions specified by a credal network. In detail, we start by showing that the unique joint distribution of a Bayesian tree coincides with the maximum entropy model of its conditional distributions. This result, however, does not hold anymore for general Bayesian networks. We thus present a new kind of maximum entropy models, which are computed sequentially. ...

Identification of neutral biochemical network models from time series data

Directory of Open Access Journals (Sweden)

Maia Marco

2009-05-01

Full Text Available Abstract Background The major difficulty in modeling biological systems from multivariate time series is the identification of parameter sets that endow a model with dynamical behaviors sufficiently similar to the experimental data. Directly related to this parameter estimation issue is the task of identifying the structure and regulation of ill-characterized systems. Both tasks are simplified if the mathematical model is canonical, i.e., if it is constructed according to strict guidelines. Results In this report, we propose a method for the identification of admissible parameter sets of canonical S-systems from biological time series. The method is based on a Monte Carlo process that is combined with an improved version of our previous parameter optimization algorithm. The method maps the parameter space into the network space, which characterizes the connectivity among components, by creating an ensemble of decoupled S-system models that imitate the dynamical behavior of the time series with sufficient accuracy. The concept of sloppiness is revisited in the context of these S-system models with an exploration not only of different parameter sets that produce similar dynamical behaviors but also different network topologies that yield dynamical similarity. Conclusion The proposed parameter estimation methodology was applied to actual time series data from the glycolytic pathway of the bacterium Lactococcus lactis and led to ensembles of models with different network topologies. In parallel, the parameter optimization algorithm was applied to the same dynamical data upon imposing a pre-specified network topology derived from prior biological knowledge, and the results from both strategies were compared. The results suggest that the proposed method may serve as a powerful exploration tool for testing hypotheses and the design of new experiments.

Seasonal Patterns of Soil Respiration and Related Soil Biochemical Properties under Nitrogen Addition in Winter Wheat Field.

Science.gov (United States)

Liang, Guopeng; Houssou, Albert A; Wu, Huijun; Cai, Dianxiong; Wu, Xueping; Gao, Lili; Li, Jing; Wang, Bisheng; Li, Shengping

2015-01-01

Understanding the changes of soil respiration under increasing N fertilizer in cropland ecosystems is crucial to accurately predicting global warming. This study explored seasonal variations of soil respiration and its controlling biochemical properties under a gradient of Nitrogen addition during two consecutive winter wheat growing seasons (2013-2015). N was applied at four different levels: 0, 120, 180 and 240 kg N ha(-1) year(-1) (denoted as N0, N12, N18 and N24, respectively). Soil respiration exhibited significant seasonal variation and was significantly affected by soil temperature with Q10 ranging from 2.04 to 2.46 and from 1.49 to 1.53 during 2013-2014 and 2014-2015 winter wheat growing season, respectively. Soil moisture had no significant effect on soil respiration during 2013-2014 winter wheat growing season but showed a significant and negative correlation with soil respiration during 2014-2015 winter wheat growing season. Soil respiration under N24 treatment was significantly higher than N0 treatment. Averaged over the two growing seasons, N12, N18 and N24 significantly increased soil respiration by 13.4, 16.4 and 25.4% compared with N0, respectively. N addition also significantly increased easily extractable glomalin-related soil protein (EEG), soil organic carbon (SOC), total N, ammonium N and nitrate N contents. In addition, soil respiration was significantly and positively correlated with β-glucosidase activity, EEG, SOC, total N, ammonium N and nitrate N contents. The results indicated that high N fertilization improved soil chemical properties, but significantly increased soil respiration.

Criteria for the Evaluation and Selection of Radiation-Induced Metabolic Changes as Biochemical Indicators of Radiation Damage

Energy Technology Data Exchange (ETDEWEB)

Altman, K. I. [Departments of Experimental Radiology, Radiation Biology, Biophysics and Biochemistry, University of Rochester, School of Medicine and Dentistry, Rochester, NY (United States)

1971-03-15

There are several reasons which prompt a search for suitable biochemical indicators of radiation damage in man. Perhaps the most compelling of these reasons is the urgent need for estimates of exposure doses in cases of accidental exposures of human subjects to ionizing radiations under conditions which preclude a reliable assessment of the exposure dose by the usual physical means. At worst, a biochemical estimate of the dose would provide an independent means of obtaining information otherwise based solely on physical considerations and assumptions. In addition, a biochemical estimate of radiation injury may also, under ideal circumstances, serve as a guide to the attending physician in chosing the type of therapy most efficacious and least likely to lead to complications in the near as well as more distant future. The availability of biochemical indicators capable of revealing with some degree of accuracy the impairment of function of a particular organ would be a helpful adjunct in making decisions concerning the therapeutic approach to be adopted. The latter aspect would be of considerable interest in acute, accidental radiation exposures since under these circumstances radiation exposures are frequently of the partial-body type. An estimate of radiation injury by means of biochemical indicators should also prove useful in cases of protracted or chronic exposures to radiation, the source of which may be either external or internal. The use of biochemical indicators under these conditions of radiation exposure may, in general, aid 'case-finding' efforts and, in a more specific way, may help in pin-pointing discrete organ dysfunctions. In evaluating the suitability of radiation-induced metabolic changes for application as biochemical indicators of radiation damage, the following general criteria may be set forth: (1) the biochemical response to irradiation must be dose-dependent within a certain, sufficiently wide range in order to be useful; (2) the sensitivity

Sublethal microcystin exposure and biochemical outcomes among hemodialysis patients.

Directory of Open Access Journals (Sweden)

Elizabeth D Hilborn

Full Text Available Cyanobacteria are commonly-occurring contaminants of surface waters worldwide. Microcystins, potent hepatotoxins, are among the best characterized cyanotoxins. During November, 2001, a group of 44 hemodialysis patients were exposed to microcystins via contaminated dialysate. Serum microcystin concentrations were quantified with enzyme-linked immunosorbent assay which measures free serum microcystin LR equivalents (ME. We describe serum ME concentrations and biochemical outcomes among a subset of patients during 8 weeks following exposure. Thirteen patients were included; 6 were males, patients' median age was 45 years (range 16-80, one was seropositive for hepatitis B surface antigen. The median serum ME concentration was 0.33 ng/mL (range: <0.16-0.96. One hundred thirty nine blood samples were collected following exposure. Patients' biochemical outcomes varied, but overall indicated a mixed liver injury. Linear regression evaluated each patient's weekly mean biochemical outcome with their maximum serum ME concentration; a measure of the extrinsic pathway of clotting function, prothrombin time, was negatively and significantly associated with serum ME concentrations. This group of exposed patients' biochemical outcomes display evidence of a mixed liver injury temporally associated with microcystin exposure. Interpretation of biochemical outcomes are complicated by the study population's underlying chronic disease status. It is clear that dialysis patients are a distinct 'at risk' group for cyanotoxin exposures due to direct intravenous exposure to dialysate prepared from surface drinking water supplies. Careful monitoring and treatment of water supplies used to prepare dialysate is required to prevent future cyanotoxin exposure events.

Biochemical changes during aging of soybean seed

Directory of Open Access Journals (Sweden)

Balešević-Tubić Svetlana

2009-01-01

Full Text Available Biochemical changes that occur in the seed as a result of ageing are very significant for seed quality and longevity. Because of its characteristic composition, processes occurring in the seed of oil crops during storage will be typical as well. Six soybean varieties developed in Institute of field and vegetable crops Novi Sad, submitted to accelerated and natural aging, under controlled and conventional storage conditions were used in these trials. The content of malondialdehyde, superoxide dismutase and peroxidase activities were studied. The biochemical processes i.e. lipid peroxidation, as well as the decrease in supeoxide dismutase and peroxidase activities (especially pronounced by applied accelerated aging were caused by both type of aging. The degree of seed damage and the ability of seed to resist the negative consequences of aging were influenced, beside duration of aging period, by type of storage and characteristics of soybean varieties. .

Thermo-Mechanical Properties of Semi-Degradable Poly(β-amino ester)-co-Methyl Methacrylate Networks under Simulated Physiological Conditions

Science.gov (United States)

Safranski, David L.; Crabtree, Jacob C.; Huq, Yameen R.; Gall, Ken

2011-01-01

Poly(β-amino ester) networks are being explored for biomedical applications, but they may lack the mechanical properties necessary for long term implantation. The objective of this study is to evaluate the effect of adding methyl methacrylate on networks' mechanical properties under simulated physiological conditions. The networks were synthesized in two parts: (1) a biodegradable crosslinker was formed from a diacrylate and amine, (2) and then varying concentrations of methyl methacrylate were added prior to photopolymerizing the network. Degradation rate, mechanical properties, and glass transition temperature were studied as a function of methyl methacrylate composition. The crosslinking density played a limited role on mechanical properties for these networks, but increasing methyl methacrylate concentration improved the toughness by several orders of magnitude. Under simulated physiological conditions, networks showed increasing toughness or sustained toughness as degradation occurred. This work establishes a method of creating degradable networks with tailorable toughness while undergoing partial degradation. PMID:21966028

Optimal Retrofit Scheme for Highway Network under Seismic Hazards

Directory of Open Access Journals (Sweden)

Yongxi Huang

2014-06-01

Full Text Available Many older highway bridges in the United States (US are inadequate for seismic loads and could be severely damaged or collapsed in a relatively small earthquake. According to the most recent American Society of Civil Engineers’ infrastructure report card, one-third of the bridges in the US are rated as structurally deficient and many of these structurally deficient bridges are located in seismic zones. To improve this situation, at-risk bridges must be identified and evaluated and effective retrofitting programs should be in place to reduce their seismic vulnerabilities. In this study, a new retrofit strategy decision scheme for highway bridges under seismic hazards is developed and seamlessly integrate the scenario-based seismic analysis of bridges and the traffic network into the proposed optimization modeling framework. A full spectrum of bridge retrofit strategies is considered based on explicit structural assessment for each seismic damage state. As an empirical case study, the proposed retrofit strategy decision scheme is utilized to evaluate the bridge network in one of the active seismic zones in the US, Charleston, South Carolina. The developed modeling framework, on average, will help increase network throughput traffic capacity by 45% with a cost increase of only $15million for the Mw 5.5 event and increase the capacity fourfold with a cost of only $32m for the Mw 7.0 event.

PHYSIOLOGICAL AND BIOCHEMICAL MARKERS OF SALINITY TOLERANCE IN PLANTS

Directory of Open Access Journals (Sweden)

Mustafa YILDIZ

2011-02-01

Full Text Available Salt stress limits plant productivity in arid and semi arid regions. Salt stress causes decrease in plant growth by adversely affecting physiological processes, especially photosynthesis. Salinity tolerance is defined as the ability of plant to maintain normal rowth and development under salt conditions. Salt stress results in accumulation of low molecular weight compounds, termed compatible solutes, which do not interfere with the normal biochemical reactions. These compatible solutes such as carbohydrates, polyols, amino acids and amides, quaternary ammonium compounds, polyamines andsoluble proteins may play a crucial role in osmotic adjustment, protection of macromolecules, maintenance of cellular pH and detoxification of free radicals. On the other hand, plants subjected to environmental stresses such as salinity produce reactive oxygen species (ROS and these ROS are efficiently eliminated by antioxidant enzyme systems. In plant breeding studies, the use of some physiological and biochemical markers for improving the salt tolerance in plants is crucial. In this review, the possibility of using some physiological and biochemical markers as selection criteria for salt tolerance is discussed.

A statistical framework for differential network analysis from microarray data

Directory of Open Access Journals (Sweden)

Datta Somnath

2010-02-01

underlying biochemical pathways. Differential network analysis with appropriate connectivity scores is a useful tool in exploring changes in network structures under different biological conditions. An R package of our tests can be downloaded from the supplementary website http://www.somnathdatta.org/Supp/DNA.

Effects of Pineal Proteins on Biochemical, Enzyme Profile and Non ...

African Journals Online (AJOL)

Effects of Pineal Proteins on Biochemical, Enzyme Profile and Non-Specific Immune Response of Indian Goats under Thermal Stress. ... Total precipitated pineal proteins successfully and significantly relieved the animals from adverse effects of heat stress and metyrapone treatment. There is evidence that most of the ...

Strategies for a better performance of RPL under mobility in wireless sensor networks

Science.gov (United States)

Latib, Z. A.; Jamil, A.; Alduais, N. A. M.; Abdullah, J.; Audah, L. H. M.; Alias, R.

2017-09-01

A Wireless Sensor Network (WSN) is usually stationary, which the network comprises of static nodes. The increase demand for mobility in various applications such as environmental monitoring, medical, home automation, and military, raises the question how IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) would perform under these mobility applications. This paper aims to understand performance of RPL and come out with strategies for a better performance of RPL in mobility scenarios. Because of this, this paper evaluates the performance of the RPL protocol under three different scenarios: sink and sensor nodes are static, static sink and mobile sensor nodes, and sink and sensor nodes are mobile. The network scenarios are implemented in Cooja simulator. A WSN consists of 25 sensor nodes and one sink node is configured in the simulation environment. The simulation is varied over different packet rates and ContikiMAC's Clear Channel Assessment (CCA) rate. As the performance metric, RPL is evaluated in term of packet delivery ratio (PDR), power consumption and packet rates. The simulation results show RPL provides a poor PDR in the mobility scenarios when compared to the static scenario. In addition, RPL consumes more power and increases duty-cycle rate to support mobility when compared to the static scenario. Based on the findings, we suggest three strategies for a better performance of RPL in mobility scenarios. First, RPL should operates at a lower packet rates when implemented in the mobility scenarios. Second, RPL should be implemented with a higher duty-cycle rate. Lastly, the sink node should be positioned as much as possible in the center of the mobile network.

Near-optimal Downlink precoding of a MISO system for a secondary network under the SINR constraints of a primary network

KAUST Repository

Park, Kihong

2013-04-01

In this paper, we study a multiple-input single-output cognitive radio (CR) system where only the primary base station (BS) has multiple antennas. We consider a rate maximization problem of the secondary network under signal-to-interference-plus-noise-ratio constraints on the primary network in order to guarantee the quality-of-service for the latter network. While the interference due to the secondary transmission in the conventional underlay CR approach may severely degrade the performance of the primary network, we propose a primary BS-aided approach in which the primary BS helps relay the secondary users\\' signals instead of allowing them to communicate with each other via a direct path between them. In addition, an algorithm to find a near-optimal beamforming solution at the primary BS is proposed. Finally, based on some selected numerical results, we show that the proposed scheme outperforms the conventional underlay CR configuration over a wide transmit power range. © 2013 IEEE.

Multistate Model Builder (MSMB): a flexible editor for compact biochemical models.

Science.gov (United States)

Palmisano, Alida; Hoops, Stefan; Watson, Layne T; Jones, Thomas C; Tyson, John J; Shaffer, Clifford A

2014-04-04

Building models of molecular regulatory networks is challenging not just because of the intrinsic difficulty of describing complex biological processes. Writing a model is a creative effort that calls for more flexibility and interactive support than offered by many of today's biochemical model editors. Our model editor MSMB - Multistate Model Builder - supports multistate models created using different modeling styles. MSMB provides two separate advances on existing network model editors. (1) A simple but powerful syntax is used to describe multistate species. This reduces the number of reactions needed to represent certain molecular systems, thereby reducing the complexity of model creation. (2) Extensive feedback is given during all stages of the model creation process on the existing state of the model. Users may activate error notifications of varying stringency on the fly, and use these messages as a guide toward a consistent, syntactically correct model. MSMB default values and behavior during model manipulation (e.g., when renaming or deleting an element) can be adapted to suit the modeler, thus supporting creativity rather than interfering with it. MSMB's internal model representation allows saving a model with errors and inconsistencies (e.g., an undefined function argument; a syntactically malformed reaction). A consistent model can be exported to SBML or COPASI formats. We show the effectiveness of MSMB's multistate syntax through models of the cell cycle and mRNA transcription. Using multistate reactions reduces the number of reactions need to encode many biochemical network models. This reduces the cognitive load for a given model, thereby making it easier for modelers to build more complex models. The many interactive editing support features provided by MSMB make it easier for modelers to create syntactically valid models, thus speeding model creation. Complete information and the installation package can be found at http

Efficient Characterization of Parametric Uncertainty of Complex (Biochemical Networks.

Directory of Open Access Journals (Sweden)

Claudia Schillings

2015-08-01

Full Text Available Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

Physio-biochemical and morphological characters of halophyte legume shrub, Acacia ampliceps seedlings in response to salt stress under greenhouse

Directory of Open Access Journals (Sweden)

Cattarin eTheerawitaya

2015-08-01

Full Text Available Acacia ampliceps (salt wattle, a leguminous shrub, has been introduced in salt-affected areas in northeast of Thailand for remediation of saline soils. However, the defense mechanisms underlying salt tolerance A. ampliceps are unknown. We investigated various physio-biochemical and morphological attributes of A. ampliceps in response to varying levels of salt treatment (200 to 600 mM NaCl. Seedlings of A. ampliceps (252 cm in plant height raised from seeds were treated with 200 mM (mild stress, 400 and 600 mM (extreme stress of salt treatment (NaCl under greenhouse conditions. Na+ and Ca2+ contents in the leaf tissues increased significantly under salt treatment, whereas K+ content declined in salt-stressed plants. Free proline and soluble sugar contents in plant grown under extreme salt stress (600 mM NaCl for 9 days significantly increased by 28.7 (53.33 mol g1 FW and 3.2 (42.11 mg g1 DW folds, respectively over the control, thereby playing a major role as osmotic adjustment. Na+ enrichment in the phyllode tissues of salt-stressed seedlings positively related to total chlorophyll degradation (R2=0.72. Photosynthetic pigments and chlorophyll fluorescence in salt-stressed plants increased under mild salt stress (200 mM NaCl. However, these declined under high level of salinity (400-600 mM NaCl, consequently resulting in reduced net photosynthetic rate (R2=0.81 and plant dry weight (R2= 0.91. The study concludes that A. ampliceps has an osmotic adjustment and Na+ compartmentation as effective salt defense mechanisms, and thus it could be an excellent species to grow in salt-affected soils.

Seasonal Patterns of Soil Respiration and Related Soil Biochemical Properties under Nitrogen Addition in Winter Wheat Field

Science.gov (United States)

Liang, Guopeng; Houssou, Albert A.; Wu, Huijun; Cai, Dianxiong; Wu, Xueping; Gao, Lili; Li, Jing; Wang, Bisheng; Li, Shengping

2015-01-01

Understanding the changes of soil respiration under increasing N fertilizer in cropland ecosystems is crucial to accurately predicting global warming. This study explored seasonal variations of soil respiration and its controlling biochemical properties under a gradient of Nitrogen addition during two consecutive winter wheat growing seasons (2013–2015). N was applied at four different levels: 0, 120, 180 and 240 kg N ha-1 year-1 (denoted as N0, N12, N18 and N24, respectively). Soil respiration exhibited significant seasonal variation and was significantly affected by soil temperature with Q10 ranging from 2.04 to 2.46 and from 1.49 to 1.53 during 2013–2014 and 2014–2015 winter wheat growing season, respectively. Soil moisture had no significant effect on soil respiration during 2013–2014 winter wheat growing season but showed a significant and negative correlation with soil respiration during 2014–2015 winter wheat growing season. Soil respiration under N24 treatment was significantly higher than N0 treatment. Averaged over the two growing seasons, N12, N18 and N24 significantly increased soil respiration by 13.4, 16.4 and 25.4% compared with N0, respectively. N addition also significantly increased easily extractable glomalin-related soil protein (EEG), soil organic carbon (SOC), total N, ammonium N and nitrate N contents. In addition, soil respiration was significantly and positively correlated with β-glucosidase activity, EEG, SOC, total N, ammonium N and nitrate N contents. The results indicated that high N fertilization improved soil chemical properties, but significantly increased soil respiration. PMID:26629695

Development of Shale Gas Supply Chain Network under Market Uncertainties

Directory of Open Access Journals (Sweden)

Jorge Chebeir

2017-02-01

Full Text Available The increasing demand of energy has turned the shale gas and shale oil into one of the most promising sources of energy in the United States. In this article, a model is proposed to address the long-term planning problem of the shale gas supply chain under uncertain conditions. A two-stage stochastic programming model is proposed to describe and optimize the shale gas supply chain network. Inherent uncertainty in final products’ prices, such as natural gas and natural gas liquids (NGL, is treated through the utilization of a scenario-based method. A binomial option pricing model is utilized to approximate the stochastic process through the generation of scenario trees. The aim of the proposed model is to generate an appropriate and realistic supply chain network configuration as well as scheduling of different operations throughout the planning horizon of a shale gas development project.

Egg quality parameters and blood biochemical profile of six strains ...

African Journals Online (AJOL)

Six different poultry strains (Indigenous chicken, Broiler, Turkey, Geese, Duck and Guinea fowl) were studied under extensive system of management to investigate the effect of rearing system on their egg quality and the blood biochemical profile, respectively. Birds used for the study were obtained from four different ...

Propagating semantic information in biochemical network models

Directory of Open Access Journals (Sweden)

Schulz Marvin

2012-01-01

Full Text Available Abstract Background To enable automatic searches, alignments, and model combination, the elements of systems biology models need to be compared and matched across models. Elements can be identified by machine-readable biological annotations, but assigning such annotations and matching non-annotated elements is tedious work and calls for automation. Results A new method called "semantic propagation" allows the comparison of model elements based not only on their own annotations, but also on annotations of surrounding elements in the network. One may either propagate feature vectors, describing the annotations of individual elements, or quantitative similarities between elements from different models. Based on semantic propagation, we align partially annotated models and find annotations for non-annotated model elements. Conclusions Semantic propagation and model alignment are included in the open-source library semanticSBML, available on sourceforge. Online services for model alignment and for annotation prediction can be used at http://www.semanticsbml.org.

Serviceability Assessment for Cascading Failures in Water Distribution Network under Seismic Scenario

Directory of Open Access Journals (Sweden)

Qing Shuang

2016-01-01

Full Text Available The stability of water service is a hot point in industrial production, public safety, and academic research. The paper establishes a service evaluation model for the water distribution network (WDN. The serviceability is measured in three aspects: (1 the functionality of structural components under disaster environment; (2 the recognition of cascading failure process; and (3 the calculation of system reliability. The node and edge failures in WDN are interrelated under seismic excitations. The cascading failure process is provided with the balance of water supply and demand. The matrix-based system reliability (MSR method is used to represent the system events and calculate the nonfailure probability. An example is used to illustrate the proposed method. The cascading failure processes with different node failures are simulated. The serviceability is analyzed. The critical node can be identified. The result shows that the aged network has a greater influence on the system service under seismic scenario. The maintenance could improve the antidisaster ability of WDN. Priority should be given to controlling the time between the initial failure and the first secondary failure, for taking postdisaster emergency measures within this time period can largely cut down the spread of cascade effect in the whole WDN.

The research on optimization of auto supply chain network robust model under macroeconomic fluctuations

International Nuclear Information System (INIS)

Guo, Chunxiang; Liu, Xiaoli; Jin, Maozhu; Lv, Zhihan

2016-01-01

Considering the uncertainty of the macroeconomic environment, the robust optimization method is studied for constructing and designing the automotive supply chain network, and based on the definition of robust solution a robust optimization model is built for integrated supply chain network design that consists of supplier selection problem and facility location–distribution problem. The tabu search algorithm is proposed for supply chain node configuration, analyzing the influence of the level of uncertainty on robust results, and by comparing the performance of supply chain network design through the stochastic programming model and robustness optimize model, on this basis, determining the rational layout of supply chain network under macroeconomic fluctuations. At last the contrastive test result validates that the performance of tabu search algorithm is outstanding on convergence and computational time. Meanwhile it is indicated that the robust optimization model can reduce investment risks effectively when it is applied to supply chain network design.

Intermittency route to chaos in a biochemical system.

Science.gov (United States)

De la Fuente, I M; Martinez, L; Veguillas, J

1996-01-01

The numerical analysis of a glycolytic model performed through the construction of a system of three differential-delay equations reveals a phenomenon of intermittency route to chaos. In our biochemical system, the consideration of delay time variations under constant input flux as well as frequency variations of the periodic substrate input flux allows us, in both cases, to observe a type of transition to chaos different from the 'Feigenbaum route'.

Core regulatory network motif underlies the ocellar complex patterning in Drosophila melanogaster

Science.gov (United States)

Aguilar-Hidalgo, D.; Lemos, M. C.; Córdoba, A.

2015-03-01

During organogenesis, developmental programs governed by Gene Regulatory Networks (GRN) define the functionality, size and shape of the different constituents of living organisms. Robustness, thus, is an essential characteristic that GRNs need to fulfill in order to maintain viability and reproducibility in a species. In the present work we analyze the robustness of the patterning for the ocellar complex formation in Drosophila melanogaster fly. We have systematically pruned the GRN that drives the development of this visual system to obtain the minimum pathway able to satisfy this pattern. We found that the mechanism underlying the patterning obeys to the dynamics of a 3-nodes network motif with a double negative feedback loop fed by a morphogenetic gradient that triggers the inhibition in a French flag problem fashion. A Boolean modeling of the GRN confirms robustness in the patterning mechanism showing the same result for different network complexity levels. Interestingly, the network provides a steady state solution in the interocellar part of the patterning and an oscillatory regime in the ocelli. This theoretical result predicts that the ocellar pattern may underlie oscillatory dynamics in its genetic regulation.

Biomphalaria prona (Gastropoda: Planorbidae: a morphological and biochemical study

Directory of Open Access Journals (Sweden)

W. Lobato Paraense

1992-06-01

Full Text Available Two samples of Biomphalaria prona (Martens, 1873 from Lake Valencia (type locality and seven from other Venezuelan localities were studied morphologically (shell and reproductive system and biochemically (allozyme electrophoresis. In spite of marked differences in shell characters, all of them proved indistinguishable under the anatomic and biochemical criteria. So far B. prona has been considered an endemic species, restricted to Lake Valencia. It is now demonstrated that the extralacustrine populations refered to Biomphalaria havanensis (Pfeiffer, 1839 by several authors correspond in shell characters to an extreme variant of B. prona from the Lake and really belong to the last*mentioned species. They may be regarded as the result of a process of directional selection favoring a shell phenotype other than those making up the modal class in the Lake.

Designing container shipping network under changing demand and freight rates

Directory of Open Access Journals (Sweden)

C. Chen

2010-03-01

Full Text Available This paper focuses on the optimization of container shipping network and its operations under changing cargo demand and freight rates. The problem is formulated as a mixed integer non-linear programming problem (MINP with an objective of maximizing the average unit ship-slot profit at three stages using analytical methodology. The issues such as empty container repositioning, ship-slot allocating, ship sizing, and container configuration are simultaneously considered based on a series of the matrices of demand for a year. To solve the model, a bi-level genetic algorithm based method is proposed. Finally, numerical experiments are provided to illustrate the validity of the proposed model and algorithms. The obtained results show that the suggested model can provide a more realistic solution to the issues on the basis of changing demand and freight rates and arrange a more effective approach to the optimization of container shipping network structures and operations than does the model based on the average demand.

Converging models of schizophrenia - Network alterations of prefrontal cortex underlying cognitive impairments

Science.gov (United States)

Sakurai, Takeshi; Gamo, Nao J; Hikida, Takatoshi; Kim, Sun-Hong; Murai, Toshiya; Tomoda, Toshifumi; Sawa, Akira

2015-01-01

The prefrontal cortex (PFC) and its connections with other brain areas are crucial for cognitive function. Cognitive impairments are one of the core symptoms associated with schizophrenia, and manifest even before the onset of the disorder. Altered neural networks involving PFC contribute to cognitive impairments in schizophrenia. Both genetic and environmental risk factors affect the development of the local circuitry within PFC as well as development of broader brain networks, and make the system vulnerable to further insults during adolescence, leading to the onset of the disorder in young adulthood. Since spared cognitive functions correlate with functional outcome and prognosis, a better understanding of the mechanisms underlying cognitive impairments will have important implications for novel therapeutics for schizophrenia focusing on cognitive functions. Multidisciplinary approaches, from basic neuroscience to clinical studies, are required to link molecules, circuitry, networks, and behavioral phenotypes. Close interactions among such fields by sharing a common language on connectomes, behavioral readouts, and other concepts are crucial for this goal. PMID:26408506

Network interactions underlying mirror feedback in stroke: A dynamic causal modeling study

Directory of Open Access Journals (Sweden)

Soha Saleh

2017-01-01

Full Text Available Mirror visual feedback (MVF is potentially a powerful tool to facilitate recovery of disordered movement and stimulate activation of under-active brain areas due to stroke. The neural mechanisms underlying MVF have therefore been a focus of recent inquiry. Although it is known that sensorimotor areas can be activated via mirror feedback, the network interactions driving this effect remain unknown. The aim of the current study was to fill this gap by using dynamic causal modeling to test the interactions between regions in the frontal and parietal lobes that may be important for modulating the activation of the ipsilesional motor cortex during mirror visual feedback of unaffected hand movement in stroke patients. Our intent was to distinguish between two theoretical neural mechanisms that might mediate ipsilateral activation in response to mirror-feedback: transfer of information between bilateral motor cortices versus recruitment of regions comprising an action observation network which in turn modulate the motor cortex. In an event-related fMRI design, fourteen chronic stroke subjects performed goal-directed finger flexion movements with their unaffected hand while observing real-time visual feedback of the corresponding (veridical or opposite (mirror hand in virtual reality. Among 30 plausible network models that were tested, the winning model revealed significant mirror feedback-based modulation of the ipsilesional motor cortex arising from the contralesional parietal cortex, in a region along the rostral extent of the intraparietal sulcus. No winning model was identified for the veridical feedback condition. We discuss our findings in the context of supporting the latter hypothesis, that mirror feedback-based activation of motor cortex may be attributed to engagement of a contralateral (contralesional action observation network. These findings may have important implications for identifying putative cortical areas, which may be targeted with

Mercury Induced Biochemical Alterations As Oxidative Stress In Mugil Cephalus In Short Term Toxicity Test

OpenAIRE

J.S.I Rajkumar; Samuel Tennyson

2013-01-01

Mugil cephalus juveniles of size 2.5 ±0.6cm were exposed to mercury in short term chronic toxicity test through static renewal bioassay to detect the possible biochemical agent as biomarkers in aquatic pollution and in estuarine contamination as specific. Lipid peroxidation levels, glutathione S -transferase, catalase, reduced glutathione and acetylcholinesterase were studied as biochemical parameters. Increased thio-barbituric acid reactive substances levels were observed under exposur...

Biochemical analysis of force-sensitive responses using a large-scale cell stretch device.

Science.gov (United States)

Renner, Derrick J; Ewald, Makena L; Kim, Timothy; Yamada, Soichiro

2017-09-03

Physical force has emerged as a key regulator of tissue homeostasis, and plays an important role in embryogenesis, tissue regeneration, and disease progression. Currently, the details of protein interactions under elevated physical stress are largely missing, therefore, preventing the fundamental, molecular understanding of mechano-transduction. This is in part due to the difficulty isolating large quantities of cell lysates exposed to force-bearing conditions for biochemical analysis. We designed a simple, easy-to-fabricate, large-scale cell stretch device for the analysis of force-sensitive cell responses. Using proximal biotinylation (BioID) analysis or phospho-specific antibodies, we detected force-sensitive biochemical changes in cells exposed to prolonged cyclic substrate stretch. For example, using promiscuous biotin ligase BirA* tagged α-catenin, the biotinylation of myosin IIA increased with stretch, suggesting the close proximity of myosin IIA to α-catenin under a force bearing condition. Furthermore, using phospho-specific antibodies, Akt phosphorylation was reduced upon stretch while Src phosphorylation was unchanged. Interestingly, phosphorylation of GSK3β, a downstream effector of Akt pathway, was also reduced with stretch, while the phosphorylation of other Akt effectors was unchanged. These data suggest that the Akt-GSK3β pathway is force-sensitive. This simple cell stretch device enables biochemical analysis of force-sensitive responses and has potential to uncover molecules underlying mechano-transduction.

Thermodynamically based constraints for rate coefficients of large biochemical networks.

Science.gov (United States)

Vlad, Marcel O; Ross, John

2009-01-01

Wegscheider cyclicity conditions are relationships among the rate coefficients of a complex reaction network, which ensure the compatibility of kinetic equations with the conditions for thermodynamic equilibrium. The detailed balance at equilibrium, that is the equilibration of forward and backward rates for each elementary reaction, leads to compatibility between the conditions of kinetic and thermodynamic equilibrium. Therefore, Wegscheider cyclicity conditions can be derived by eliminating the equilibrium concentrations from the conditions of detailed balance. We develop matrix algebra tools needed to carry out this elimination, reexamine an old derivation of the general form of Wegscheider cyclicity condition, and develop new derivations which lead to more compact and easier-to-use formulas. We derive scaling laws for the nonequilibrium rates of a complex reaction network, which include Wegscheider conditions as a particular case. The scaling laws for the rates are used for clarifying the kinetic and thermodynamic meaning of Wegscheider cyclicity conditions. Finally, we discuss different ways of using Wegscheider cyclicity conditions for kinetic computations in systems biology.

Pheochromocytoma-paraganglioma: Biochemical and genetic diagnosis.

Science.gov (United States)

Cano Megías, Marta; Rodriguez Puyol, Diego; Fernández Rodríguez, Loreto; Sención Martinez, Gloria Lisette; Martínez Miguel, Patricia

Pheochromocytomas and paragangliomas are tumours derived from neural crest cells, which can be diagnosed by biochemical measurement of metanephrine and methoxytyramine. Advances in genetic research have identified many genes involved in the pathogenesis of these tumours, suggesting that up to 35-45% may have an underlying germline mutation. These genes have a singular transcriptional signature and can be grouped into 2 clusters (or groups): cluster 1 (VHL and SHDx), involved in angiogenesis and hypoxia pathways; and cluster 2 (MEN2 and NF1), linked to the kinase signalling pathway. In turn, these genes are associated with a characteristic biochemical phenotype (noradrenergic and adrenergic), and clinical features (location, biological behaviour, age of presentation, etc.) in a large number of cases. Early diagnosis of these tumours, accompanied by a correct genetic diagnosis, should eventually become a priority to enable better treatment, early detection of complications, proper screening of family members and related tumours, as well as an improvement in the overall prognosis of these patients. Copyright © 2016 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. All rights reserved.

Estimation of parameter sensitivities for stochastic reaction networks

KAUST Repository

Gupta, Ankit

2016-01-01

Quantification of the effects of parameter uncertainty is an important and challenging problem in Systems Biology. We consider this problem in the context of stochastic models of biochemical reaction networks where the dynamics is described as a

River water quality model no. 1 (RWQM1): II. Biochemical process equations

DEFF Research Database (Denmark)

Reichert, P.; Borchardt, D.; Henze, Mogens

2001-01-01

In this paper, biochemical process equations are presented as a basis for water quality modelling in rivers under aerobic and anoxic conditions. These equations are not new, but they summarise parts of the development over the past 75 years. The primary goals of the presentation are to stimulate...... transformation processes. This paper is part of a series of three papers. In the first paper, the general modelling approach is described; in the present paper, the biochemical process equations of a complex model are presented; and in the third paper, recommendations are given for the selection of a reasonable...

Biochemical and seminal parameters of lambs fed palm kernel cake under grazing system

Directory of Open Access Journals (Sweden)

Lopes César Mugabe

Full Text Available ABSTRACT This study aimed to assess the effects of palm kernel cake on semen quality and biochemical parameters of Santa Inês lambs. A total of 40 animals with 24.10±2.72 kg body weight and five months old were assigned in a completely randomized design into four groups and 10 replicates. The animals were subjected to four levels of palm kernel cake (0, 15, 30, and 45% based on dry matter. The trial lasted 90 days foregone by 15 days for adaptation. Blood samples were collected every 45 days from jugular vein using vacuum tubes without anticoagulant. Total serum cholesterol, triglycerides, high-density lipoprotein, low-density lipoprotein, and very-low-density lipoprotein were assessed. Once the animals reached puberty at a mean age of 225 days, the semen samples were collected by electroejaculator once a week for three sequence weeks and assessed for volume, color, aspect, wave motion, motility, sperm concentration, sperm vigor, total of spermatozoa per ejaculate, viable spermatozoa per mL, and sperm morphology. The data were subjected to analysis of variance and followed by regression analysis. Non-parametric data were analysed by Kruskal-Wallis test. Total cholesterol, high-density lipoprotein, triglycerides, and very-low-density lipoprotein were linearly increased. There was no difference for low-density lipoprotein. Diets did not affect mass motility, sperm motility, vigor, total spermatozoa per ejaculate, viability sperm per mL, and minor and total sperm defects. Sperm concentration increased linearly. Negative quadratic effects were observed for major sperm defects. Supplementation of diets with palm kernel cake up to 45% on dry matter enhance biochemical parameters and do not impair the qualitative variables of lamb sperm.

Securing ad hoc wireless sensor networks under Byzantine attacks by implementing non-cryptographic method

Directory of Open Access Journals (Sweden)

Shabir Ahmad Sofi

2017-05-01

Full Text Available Ad Hoc wireless sensor network (WSN is a collection of nodes that do not need to rely on predefined infrastructure to keep the network connected. The level of security and performance are always somehow related to each other, therefore due to limited resources in WSN, cryptographic methods for securing the network against attacks is not feasible. Byzantine attacks disrupt the communication between nodes in the network without regard to its own resource consumption. This paper discusses the performance of cluster based WSN comparing LEACH with Advanced node based clusters under byzantine attacks. This paper also proposes an algorithm for detection and isolation of the compromised nodes to mitigate the attacks by non-cryptographic means. The throughput increases after using the algorithm for isolation of the malicious nodes, 33% in case of Gray Hole attack and 62% in case of Black Hole attack.

Chemical networks with inflows and outflows: a positive linear differential inclusions approach.

Science.gov (United States)

Angeli, David; De Leenheer, Patrick; Sontag, Eduardo D

2009-01-01

Certain mass-action kinetics models of biochemical reaction networks, although described by nonlinear differential equations, may be partially viewed as state-dependent linear time-varying systems, which in turn may be modeled by convex compact valued positive linear differential inclusions. A result is provided on asymptotic stability of such inclusions, and applied to a ubiquitous biochemical reaction network with inflows and outflows, known as the futile cycle. We also provide a characterization of exponential stability of general homogeneous switched systems which is not only of interest in itself, but also plays a role in the analysis of the futile cycle. 2009 American Institute of Chemical Engineers

Emergence of amplitude death scenario in a network of oscillators under repulsive delay interaction

Energy Technology Data Exchange (ETDEWEB)

Bera, Bidesh K., E-mail: bideshbera18@gmail.com [Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata 700108 (India); Hens, Chittaranjan, E-mail: chittaranjanhens@gmail.com [Department of Mathematics, Bar-Ilan University, Ramat Gan 52900 (Israel); Ghosh, Dibakar, E-mail: dibakar@isical.ac.in [Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata 700108 (India)

2016-07-15

Highlights: • Amplitude death is observed using repulsive mean coupling. • Analytical conditions for amplitude death are derived. • Effect of asymmetry time delay coupling for death is discussed. - Abstract: We report the existence of amplitude death in a network of identical oscillators under repulsive mean coupling. Amplitude death appears in a globally coupled network of identical oscillators with instantaneous repulsive mean coupling only when the number of oscillators is more than two. We further investigate that, amplitude death may emerge even in two coupled oscillators as well as network of oscillators if we introduce delay time in the repulsive mean coupling. We have analytically derived the region of amplitude death island and find out how strength of delay controls the death regime in two coupled or a large network of coupled oscillators. We have verified our results on network of delayed Mackey–Glass systems where parameters are set in hyperchaotic regime. We have also tested our coupling approach in two paradigmatic limit cycle oscillators: Stuart–Landau and Van der Pol oscillators.

Emergence of amplitude death scenario in a network of oscillators under repulsive delay interaction

International Nuclear Information System (INIS)

Bera, Bidesh K.; Hens, Chittaranjan; Ghosh, Dibakar

2016-01-01

Highlights: • Amplitude death is observed using repulsive mean coupling. • Analytical conditions for amplitude death are derived. • Effect of asymmetry time delay coupling for death is discussed. - Abstract: We report the existence of amplitude death in a network of identical oscillators under repulsive mean coupling. Amplitude death appears in a globally coupled network of identical oscillators with instantaneous repulsive mean coupling only when the number of oscillators is more than two. We further investigate that, amplitude death may emerge even in two coupled oscillators as well as network of oscillators if we introduce delay time in the repulsive mean coupling. We have analytically derived the region of amplitude death island and find out how strength of delay controls the death regime in two coupled or a large network of coupled oscillators. We have verified our results on network of delayed Mackey–Glass systems where parameters are set in hyperchaotic regime. We have also tested our coupling approach in two paradigmatic limit cycle oscillators: Stuart–Landau and Van der Pol oscillators.

Evolving phenotypic networks in silico.

Science.gov (United States)

François, Paul

2014-11-01

Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

LeishCyc: a biochemical pathways database for Leishmania major

Directory of Open Access Journals (Sweden)

Doyle Maria A

2009-06-01

Full Text Available Abstract Background Leishmania spp. are sandfly transmitted protozoan parasites that cause a spectrum of diseases in more than 12 million people worldwide. Much research is now focusing on how these parasites adapt to the distinct nutrient environments they encounter in the digestive tract of the sandfly vector and the phagolysosome compartment of mammalian macrophages. While data mining and annotation of the genomes of three Leishmania species has provided an initial inventory of predicted metabolic components and associated pathways, resources for integrating this information into metabolic networks and incorporating data from transcript, protein, and metabolite profiling studies is currently lacking. The development of a reliable, expertly curated, and widely available model of Leishmania metabolic networks is required to facilitate systems analysis, as well as discovery and prioritization of new drug targets for this important human pathogen. Description The LeishCyc database was initially built from the genome sequence of Leishmania major (v5.2, based on the annotation published by the Wellcome Trust Sanger Institute. LeishCyc was manually curated to remove errors, correct automated predictions, and add information from the literature. The ongoing curation is based on public sources, literature searches, and our own experimental and bioinformatics studies. In a number of instances we have improved on the original genome annotation, and, in some ambiguous cases, collected relevant information from the literature in order to help clarify gene or protein annotation in the future. All genes in LeishCyc are linked to the corresponding entry in GeneDB (Wellcome Trust Sanger Institute. Conclusion The LeishCyc database describes Leishmania major genes, gene products, metabolites, their relationships and biochemical organization into metabolic pathways. LeishCyc provides a systematic approach to organizing the evolving information about Leishmania

Statistical physics approaches to subnetwork dynamics in biochemical systems

Science.gov (United States)

Bravi, B.; Sollich, P.

2017-08-01

We apply a Gaussian variational approximation to model reduction in large biochemical networks of unary and binary reactions. We focus on a small subset of variables (subnetwork) of interest, e.g. because they are accessible experimentally, embedded in a larger network (bulk). The key goal is to write dynamical equations reduced to the subnetwork but still retaining the effects of the bulk. As a result, the subnetwork-reduced dynamics contains a memory term and an extrinsic noise term with non-trivial temporal correlations. We first derive expressions for this memory and noise in the linearized (Gaussian) dynamics and then use a perturbative power expansion to obtain first order nonlinear corrections. For the case of vanishing intrinsic noise, our description is explicitly shown to be equivalent to projection methods up to quadratic terms, but it is applicable also in the presence of stochastic fluctuations in the original dynamics. An example from the epidermal growth factor receptor signalling pathway is provided to probe the increased prediction accuracy and computational efficiency of our method.

Network structure underlying resolution of conflicting non-verbal and verbal social information.

Science.gov (United States)

Watanabe, Takamitsu; Yahata, Noriaki; Kawakubo, Yuki; Inoue, Hideyuki; Takano, Yosuke; Iwashiro, Norichika; Natsubori, Tatsunobu; Takao, Hidemasa; Sasaki, Hiroki; Gonoi, Wataru; Murakami, Mizuho; Katsura, Masaki; Kunimatsu, Akira; Abe, Osamu; Kasai, Kiyoto; Yamasue, Hidenori

2014-06-01

Social judgments often require resolution of incongruity in communication contents. Although previous studies revealed that such conflict resolution recruits brain regions including the medial prefrontal cortex (mPFC) and posterior inferior frontal gyrus (pIFG), functional relationships and networks among these regions remain unclear. In this functional magnetic resonance imaging study, we investigated the functional dissociation and networks by measuring human brain activity during resolving incongruity between verbal and non-verbal emotional contents. First, we found that the conflict resolutions biased by the non-verbal contents activated the posterior dorsal mPFC (post-dmPFC), bilateral anterior insula (AI) and right dorsal pIFG, whereas the resolutions biased by the verbal contents activated the bilateral ventral pIFG. In contrast, the anterior dmPFC (ant-dmPFC), bilateral superior temporal sulcus and fusiform gyrus were commonly involved in both of the resolutions. Second, we found that the post-dmPFC and right ventral pIFG were hub regions in networks underlying the non-verbal- and verbal-content-biased resolutions, respectively. Finally, we revealed that these resolution-type-specific networks were bridged by the ant-dmPFC, which was recruited for the conflict resolutions earlier than the two hub regions. These findings suggest that, in social conflict resolutions, the ant-dmPFC selectively recruits one of the resolution-type-specific networks through its interaction with resolution-type-specific hub regions. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Deciding where to attend: Large-scale network mechanisms underlying attention and intention revealed by graph-theoretic analysis.

Science.gov (United States)

Liu, Yuelu; Hong, Xiangfei; Bengson, Jesse J; Kelley, Todd A; Ding, Mingzhou; Mangun, George R

2017-08-15

The neural mechanisms by which intentions are transformed into actions remain poorly understood. We investigated the network mechanisms underlying spontaneous voluntary decisions about where to focus visual-spatial attention (willed attention). Graph-theoretic analysis of two independent datasets revealed that regions activated during willed attention form a set of functionally-distinct networks corresponding to the frontoparietal network, the cingulo-opercular network, and the dorsal attention network. Contrasting willed attention with instructed attention (where attention is directed by external cues), we observed that the dorsal anterior cingulate cortex was allied with the dorsal attention network in instructed attention, but shifted connectivity during willed attention to interact with the cingulo-opercular network, which then mediated communications between the frontoparietal network and the dorsal attention network. Behaviorally, greater connectivity in network hubs, including the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the inferior parietal lobule, was associated with faster reaction times. These results, shown to be consistent across the two independent datasets, uncover the dynamic organization of functionally-distinct networks engaged to support intentional acts. Copyright © 2017 Elsevier Inc. All rights reserved.

Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

DEFF Research Database (Denmark)

Förster, Jochen; Famili, I.; Fu, P.

2003-01-01

The metabolic network in the yeast Saccharomyces cerevisiae was reconstructed using currently available genomic, biochemical, and physiological information. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, and transport steps between the compartments...

Analysis of Informationization Construction of Business Financial Management under the Network Economy

Science.gov (United States)

Dong, Yahui; Zhang, Pengwei; Li, Wei

To strengthen the informationization construction of the financial management has great significance to the achievement of business management informationization, and under the network economic environment, it is an important task of the financial management that how to conduct informationization construction of traditional financial management to provide true, reliable and complete financial information system for the business managers. This paper thoroughly researches the problem of financial information orientation management (FIOM) by taking the method of combining theory with practice. This paper puts forward the thinking method of financial information management, makes the new contents of E-finance. At last, this paper rebuilds the system of finance internal control from four aspects such as control of organization and management, system development control and safety control of network system.

Molecular codes in biological and chemical reaction networks.

Directory of Open Access Journals (Sweden)

Dennis Görlich

Full Text Available Shannon's theory of communication has been very successfully applied for the analysis of biological information. However, the theory neglects semantic and pragmatic aspects and thus cannot directly be applied to distinguish between (bio- chemical systems able to process "meaningful" information from those that do not. Here, we present a formal method to assess a system's semantic capacity by analyzing a reaction network's capability to implement molecular codes. We analyzed models of chemical systems (martian atmosphere chemistry and various combustion chemistries, biochemical systems (gene expression, gene translation, and phosphorylation signaling cascades, an artificial chemistry, and random reaction networks. Our study suggests that different chemical systems possess different semantic capacities. No semantic capacity was found in the model of the martian atmosphere chemistry, the studied combustion chemistries, and highly connected random networks, i.e. with these chemistries molecular codes cannot be implemented. High semantic capacity was found in the studied biochemical systems and in random reaction networks where the number of second order reactions is twice the number of species. We conclude that our approach can be applied to evaluate the information processing capabilities of a chemical system and may thus be a useful tool to understand the origin and evolution of meaningful information, e.g. in the context of the origin of life.

[Circulating miR-152 helps early prediction of postoperative biochemical recurrence of prostate cancer].

Science.gov (United States)

Chen, Jun-Feng; Liao, Yu-Feng; Ma, Jian-Bo; Mao, Qi-Feng; Jia, Guang-Cheng; Dong, Xue-Jun

2017-07-01

To investigate the value of circulating miR-152 in the early prediction of postoperative biochemical recurrence of prostate cancer. Sixty-six cases of prostate cancer were included in this study, 35 with and 31 without biochemical recurrence within two years postoperatively, and another 31 healthy individuals were enrolled as normal controls. The relative expression levels of circulating miR-152 in the serum of the subjects were detected by qRT-PCR, its value in the early diagnosis of postoperative biochemical recurrence of prostate cancer was assessed by ROC curve analysis, and the correlation of its expression level with the clinicopathological parameters of the patients were analyzed. The expression of circulating miR-152 was significantly lower in the serum of the prostate cancer patients than in the normal controls (t = －5.212, P = 0.001), and so was it in the patients with than in those without postoperative biochemical recurrence (t = －5.727, P = 0.001). The ROC curve for the value of miR-152 in the early prediction of postoperative biochemical recurrence of prostate cancer showed the area under the curve (AUC) to be 0.906 (95% CI: 0.809－0.964), with a sensitivity of 91.4% and a specificity of 80.6%. The expression level of miR-152 was correlated with the Gleason score, clinical stage of prostate cancer, biochemical recurrence, and bone metastasis (P 0.05). The expression level of circulating miR-152 is significantly reduced in prostate cancer patients with biochemical recurrence after prostatectomy and could be a biomarker in the early prediction of postoperative biochemical recurrence of the malignancy.

Modular verification of chemical reaction network encodings via serializability analysis

Science.gov (United States)

Lakin, Matthew R.; Stefanovic, Darko; Phillips, Andrew

2015-01-01

Chemical reaction networks are a powerful means of specifying the intended behaviour of synthetic biochemical systems. A high-level formal specification, expressed as a chemical reaction network, may be compiled into a lower-level encoding, which can be directly implemented in wet chemistry and may itself be expressed as a chemical reaction network. Here we present conditions under which a lower-level encoding correctly emulates the sequential dynamics of a high-level chemical reaction network. We require that encodings are transactional, such that their execution is divided by a “commit reaction” that irreversibly separates the reactant-consuming phase of the encoding from the product-generating phase. We also impose restrictions on the sharing of species between reaction encodings, based on a notion of “extra tolerance”, which defines species that may be shared between encodings without enabling unwanted reactions. Our notion of correctness is serializability of interleaved reaction encodings, and if all reaction encodings satisfy our correctness properties then we can infer that the global dynamics of the system are correct. This allows us to infer correctness of any system constructed using verified encodings. As an example, we show how this approach may be used to verify two- and four-domain DNA strand displacement encodings of chemical reaction networks, and we generalize our result to the limit where the populations of helper species are unlimited. PMID:27325906

A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

Science.gov (United States)

Tsumori, Kenji; Ozawa, Seiichi

When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

Soya bean Gα proteins with distinct biochemical properties exhibit differential ability to complement Saccharomyces cerevisiae gpa1 mutant.

Science.gov (United States)

Roy Choudhury, Swarup; Wang, Yuqi; Pandey, Sona

2014-07-01

Signalling pathways mediated by heterotrimeric G-proteins are common to all eukaryotes. Plants have a limited number of each of the G-protein subunits, with the most elaborate G-protein network discovered so far in soya bean (Glycine max, also known as soybean) which has four Gα, four Gβ and ten Gγ proteins. Biochemical characterization of Gα proteins from plants suggests significant variation in their properties compared with the well-characterized non-plant proteins. Furthermore, the four soya bean Gα (GmGα) proteins exhibit distinct biochemical activities among themselves, but the extent to which such biochemical differences contribute to their in vivo function is also not known. We used the yeast gpa1 mutant which displays constitutive signalling and growth arrest in the pheromone-response pathway as an in vivo model to evaluate the effect of distinct biochemical activities of GmGα proteins. We showed that specific GmGα proteins can be activated during pheromone-dependent receptor-mediated signalling in yeast and they display different strengths towards complementation of yeast gpa1 phenotypes. We also identified amino acids that are responsible for differential complementation abilities of specific Gα proteins. These data establish that specific plant Gα proteins are functional in the receptor-mediated pheromone-response pathway in yeast and that the subtle biochemical differences in their activity are physiologically relevant.

Schizophrenia alters intra-network functional connectivity in the caudate for detecting speech under informational speech masking conditions.

Science.gov (United States)

Zheng, Yingjun; Wu, Chao; Li, Juanhua; Li, Ruikeng; Peng, Hongjun; She, Shenglin; Ning, Yuping; Li, Liang

2018-04-04

Speech recognition under noisy "cocktail-party" environments involves multiple perceptual/cognitive processes, including target detection, selective attention, irrelevant signal inhibition, sensory/working memory, and speech production. Compared to health listeners, people with schizophrenia are more vulnerable to masking stimuli and perform worse in speech recognition under speech-on-speech masking conditions. Although the schizophrenia-related speech-recognition impairment under "cocktail-party" conditions is associated with deficits of various perceptual/cognitive processes, it is crucial to know whether the brain substrates critically underlying speech detection against informational speech masking are impaired in people with schizophrenia. Using functional magnetic resonance imaging (fMRI), this study investigated differences between people with schizophrenia (n = 19, mean age = 33 ± 10 years) and their matched healthy controls (n = 15, mean age = 30 ± 9 years) in intra-network functional connectivity (FC) specifically associated with target-speech detection under speech-on-speech-masking conditions. The target-speech detection performance under the speech-on-speech-masking condition in participants with schizophrenia was significantly worse than that in matched healthy participants (healthy controls). Moreover, in healthy controls, but not participants with schizophrenia, the strength of intra-network FC within the bilateral caudate was positively correlated with the speech-detection performance under the speech-masking conditions. Compared to controls, patients showed altered spatial activity pattern and decreased intra-network FC in the caudate. In people with schizophrenia, the declined speech-detection performance under speech-on-speech masking conditions is associated with reduced intra-caudate functional connectivity, which normally contributes to detecting target speech against speech masking via its functions of suppressing masking-speech signals.

Adaptive neural network motion control for aircraft under uncertainty conditions

Science.gov (United States)

Efremov, A. V.; Tiaglik, M. S.; Tiumentsev, Yu V.

2018-02-01

We need to provide motion control of modern and advanced aircraft under diverse uncertainty conditions. This problem can be solved by using adaptive control laws. We carry out an analysis of the capabilities of these laws for such adaptive systems as MRAC (Model Reference Adaptive Control) and MPC (Model Predictive Control). In the case of a nonlinear control object, the most efficient solution to the adaptive control problem is the use of neural network technologies. These technologies are suitable for the development of both a control object model and a control law for the object. The approximate nature of the ANN model was taken into account by introducing additional compensating feedback into the control system. The capabilities of adaptive control laws under uncertainty in the source data are considered. We also conduct simulations to assess the contribution of adaptivity to the behavior of the system.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks.

Science.gov (United States)

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-08-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

[Simulation of vegetation indices optimizing under retrieval of vegetation biochemical parameters based on PROSPECT + SAIL model].

Science.gov (United States)

Wu, Ling; Liu, Xiang-Nan; Zhou, Bo-Tian; Liu, Chuan-Hao; Li, Lu-Feng

2012-12-01

This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.

Experimental study and artificial neural network modeling of tartrazine removal by photocatalytic process under solar light.

Science.gov (United States)

Sebti, Aicha; Souahi, Fatiha; Mohellebi, Faroudja; Igoud, Sadek

2017-07-01

This research focuses on the application of an artificial neural network (ANN) to predict the removal efficiency of tartrazine from simulated wastewater using a photocatalytic process under solar illumination. A program is developed in Matlab software to optimize the neural network architecture and select the suitable combination of training algorithm, activation function and hidden neurons number. The experimental results of a batch reactor operated under different conditions of pH, TiO 2 concentration, initial organic pollutant concentration and solar radiation intensity are used to train, validate and test the networks. While negligible mineralization is demonstrated, the experimental results show that under sunlight irradiation, 85% of tartrazine is removed after 300 min using only 0.3 g/L of TiO 2 powder. Therefore, irradiation time is prolonged and almost 66% of total organic carbon is reduced after 15 hours. ANN 5-8-1 with Bayesian regulation back-propagation algorithm and hyperbolic tangent sigmoid transfer function is found to be able to predict the response with high accuracy. In addition, the connection weights approach is used to assess the importance contribution of each input variable on the ANN model response. Among the five experimental parameters, the irradiation time has the greatest effect on the removal efficiency of tartrazine.

Diversity in the dynamical behaviour of a compartmentalized programmable biochemical oscillator.

Science.gov (United States)

Weitz, Maximilian; Kim, Jongmin; Kapsner, Korbinian; Winfree, Erik; Franco, Elisa; Simmel, Friedrich C

2014-04-01

In vitro compartmentalization of biochemical reaction networks is a crucial step towards engineering artificial cell-scale devices and systems. At this scale the dynamics of molecular systems becomes stochastic, which introduces several engineering challenges and opportunities. Here we study a programmable transcriptional oscillator system that is compartmentalized into microemulsion droplets with volumes between 33 fl and 16 pl. Simultaneous measurement of large populations of droplets reveals major variations in the amplitude, frequency and damping of the oscillations. Variability increases for smaller droplets and depends on the operating point of the oscillator. Rather than reflecting the stochastic kinetics of the chemical reaction network itself, the variability can be attributed to the statistical variation of reactant concentrations created during their partitioning into droplets. We anticipate that robustness to partitioning variability will be a critical challenge for engineering cell-scale systems, and that highly parallel time-series acquisition from microemulsion droplets will become a key tool for characterization of stochastic circuit function.

Integrated analysis of genetic, behavioral, and biochemical data implicates neural stem cell-induced changes in immunity, neurotransmission and mitochondrial function in Dementia with Lewy Body mice.

Science.gov (United States)

Lakatos, Anita; Goldberg, Natalie R S; Blurton-Jones, Mathew

2017-03-10

We previously demonstrated that transplantation of murine neural stem cells (NSCs) can improve motor and cognitive function in a transgenic model of Dementia with Lewy Bodies (DLB). These benefits occurred without changes in human α-synuclein pathology and were mediated in part by stem cell-induced elevation of brain-derived neurotrophic factor (BDNF). However, instrastriatal NSC transplantation likely alters the brain microenvironment via multiple mechanisms that may synergize to promote cognitive and motor recovery. The underlying neurobiology that mediates such restoration no doubt involves numerous genes acting in concert to modulate signaling within and between host brain cells and transplanted NSCs. In order to identify functionally connected gene networks and additional mechanisms that may contribute to stem cell-induced benefits, we performed weighted gene co-expression network analysis (WGCNA) on striatal tissue isolated from NSC- and vehicle-injected wild-type and DLB mice. Combining continuous behavioral and biochemical data with genome wide expression via network analysis proved to be a powerful approach; revealing significant alterations in immune response, neurotransmission, and mitochondria function. Taken together, these data shed further light on the gene network and biological processes that underlie the therapeutic effects of NSC transplantation on α-synuclein induced cognitive and motor impairments, thereby highlighting additional therapeutic targets for synucleinopathies.

Temporal motifs in time-dependent networks

International Nuclear Information System (INIS)

Kovanen, Lauri; Karsai, Márton; Kaski, Kimmo; Kertész, János; Saramäki, Jari

2011-01-01

Temporal networks are commonly used to represent systems where connections between elements are active only for restricted periods of time, such as telecommunication, neural signal processing, biochemical reaction and human social interaction networks. We introduce the framework of temporal motifs to study the mesoscale topological–temporal structure of temporal networks in which the events of nodes do not overlap in time. Temporal motifs are classes of similar event sequences, where the similarity refers not only to topology but also to the temporal order of the events. We provide a mapping from event sequences to coloured directed graphs that enables an efficient algorithm for identifying temporal motifs. We discuss some aspects of temporal motifs, including causality and null models, and present basic statistics of temporal motifs in a large mobile call network

The Performance Evaluation of an IEEE 802.11 Network Containing Misbehavior Nodes under Different Backoff Algorithms

Directory of Open Access Journals (Sweden)

Trong-Minh Hoang

2017-01-01

Full Text Available Security of any wireless network is always an important issue due to its serious impacts on network performance. Practically, the IEEE 802.11 medium access control can be violated by several native or smart attacks that result in downgrading network performance. In recent years, there are several studies using analytical model to analyze medium access control (MAC layer misbehavior issue to explore this problem but they have focused on binary exponential backoff only. Moreover, a practical condition such as the freezing backoff issue is not included in the previous models. Hence, this paper presents a novel analytical model of the IEEE 802.11 MAC to thoroughly understand impacts of misbehaving node on network throughput and delay parameters. Particularly, the model can express detailed backoff algorithms so that the evaluation of the network performance under some typical attacks through numerical simulation results would be easy.

Biochemical and morphological changes in rat lung tissue under the influence of external ionizing radiation

International Nuclear Information System (INIS)

Uzlenkova, N.Je.; Mamotyuk, Je.M.; Gusakova, V.A.; Kononenko, O.K.

2006-01-01

Single external x-ray exposure at minimum and mean lethal doses was established to cause a long activation of biochemical processes in the connective tissue of the rat lungs. Morphological and ultrastructure changes in the tissue of the lungs at early terms after x-ray and gamma-radiation exposure were due to development of destructive and degenerative reactions. The long-term changes were characterized by growth of connective tissue and formation of areas of fibrous changes in the structure of the lungs

On the rejection-based algorithm for simulation and analysis of large-scale reaction networks

Energy Technology Data Exchange (ETDEWEB)

Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Zunino, Roberto, E-mail: roberto.zunino@unitn.it [Department of Mathematics, University of Trento, Trento (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research-University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Department of Mathematics, University of Trento, Trento (Italy)

2015-06-28

Stochastic simulation for in silico studies of large biochemical networks requires a great amount of computational time. We recently proposed a new exact simulation algorithm, called the rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)], to improve simulation performance by postponing and collapsing as much as possible the propensity updates. In this paper, we analyze the performance of this algorithm in detail, and improve it for simulating large-scale biochemical reaction networks. We also present a new algorithm, called simultaneous RSSA (SRSSA), which generates many independent trajectories simultaneously for the analysis of the biochemical behavior. SRSSA improves simulation performance by utilizing a single data structure across simulations to select reaction firings and forming trajectories. The memory requirement for building and storing the data structure is thus independent of the number of trajectories. The updating of the data structure when needed is performed collectively in a single operation across the simulations. The trajectories generated by SRSSA are exact and independent of each other by exploiting the rejection-based mechanism. We test our new improvement on real biological systems with a wide range of reaction networks to demonstrate its applicability and efficiency.

xHeinz: an algorithm for mining cross-species network modules under a flexible conservation model

NARCIS (Netherlands)

El-Kebir, Mohammed; Soueidan, Hayssam; Hume, Thomas; Beisser, Daniela; Dittrich, Marcus; Müller, Tobias; Blin, Guillaume; Heringa, Jaap; Nikolski, Macha; Wessels, Lodewyk F.A.; Klau, G.W.

2015-01-01

Motivation: Integrative network analysis methods provide robust interpretations of differential high-throughput molecular profile measurements. They are often used in a biomedical context - to generate novel hypotheses about the underlying cellular processes or to derive biomarkers for

Network conditioning under conflicting goals: Accident causation

International Nuclear Information System (INIS)

Jouse, W.C.

1992-01-01

Networks based on the Barto-Sutton architecture (BSA) of neural-like elements have an information-processing structure that is analogous to the cognitive structure of a human. Given a set of explicitly stated rules of conduct, such networks develop a set of skills that is capable of satisfying the rules. In this sense, the network acts as a translator of rules into skill-based behavior. The BSA acquires its skills through casual, correlation-based scheduling. Stated briefly, it first constructs an internal representation, or model, of the rules of conduct, and then uses the model to correct deficiencies in its skill. It learns in a manner that closely resembles classical conditioning, shifting the onset of signals associated with unconditioned stimuli forward in time to coincide with the onset of conditioning stimuli. The low-level positive reinforcement the network receives from enhancing its operational efficiency is immediate and direct. In the absence of countervailing influences, this continuous pressure is sufficient to discount the recollection of past failures and leads to accidents with a predictable regularity

Joint Secrecy for D2D Communications Underlying Cellular Networks

KAUST Repository

Hyadi, Amal

2018-01-15

In this work, we investigate the ergodic secrecy rate region of a block-fading spectrum-sharing system, where a D2D communication is underlying a cellular channel. We consider that both the primary and the secondary transmissions require their respective transmitted messages to be kept secret from a common eavesdropper under a joint secrecy constraint. The presented results are for three different scenarios, each corresponding to a particular requirement of the cellular system. First, we consider the case of a fair cellular system, and we show that the impact of jointly securing the transmissions can be balanced between the primary and the secondary systems. The second scenario examines the case when the primary network is demanding and requires the secondary transmission to be at a rate that is decodable by the primary receiver, while the last scenario assumes a joint transmission of artificial noise by the primary and the secondary transmitters. For each scenario, we present an achievable ergodic secrecy rate region that can be used as an indicator for the cellular and the D2D systems to agree under which terms the spectrum will be shared.

Gluconeogenesis: An ancient biochemical pathway with a new twist

OpenAIRE

Miyamoto, Tetsuya; Amrein, Hubert

2017-01-01

Synthesis of sugars from simple carbon sources is critical for survival of animals under limited nutrient availability. Thus, sugar-synthesizing enzymes should be present across the entire metazoan spectrum. Here, we explore the evolution of glucose and trehalose synthesis using a phylogenetic analysis of enzymes specific for the two pathways. Our analysis reveals that the production of trehalose is the more ancestral biochemical process, found in single cell organisms and primitive metazoans...

Structure versus time in the evolutionary diversification of avian carotenoid metabolic networks.

Science.gov (United States)

Morrison, Erin S; Badyaev, Alexander V

2018-05-01

Historical associations of genes and proteins are thought to delineate pathways available to subsequent evolution; however, the effects of past functional involvements on contemporary evolution are rarely quantified. Here, we examined the extent to which the structure of a carotenoid enzymatic network persists in avian evolution. Specifically, we tested whether the evolution of carotenoid networks was most concordant with phylogenetically structured expansion from core reactions of common ancestors or with subsampling of biochemical pathway modules from an ancestral network. We compared structural and historical associations in 467 carotenoid networks of extant and ancestral species and uncovered the overwhelming effect of pre-existing metabolic network structure on carotenoid diversification over the last 50 million years of avian evolution. Over evolutionary time, birds repeatedly subsampled and recombined conserved biochemical modules, which likely maintained the overall structure of the carotenoid metabolic network during avian evolution. These findings explain the recurrent convergence of evolutionary distant species in carotenoid metabolism and weak phylogenetic signal in avian carotenoid evolution. Remarkable retention of an ancient metabolic structure throughout extensive and prolonged ecological diversification in avian carotenoid metabolism illustrates a fundamental requirement of organismal evolution - historical continuity of a deterministic network that links past and present functional associations of its components. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

The stochastic network dynamics underlying perceptual discrimination

Directory of Open Access Journals (Sweden)

Genis Prat-Ortega

2015-04-01

Full Text Available The brain is able to interpret streams of high-dimensional ambiguous information and yield coherent percepts. The mechanisms governing sensory integration have been extensively characterized using time-varying visual stimuli (Britten et al. 1996; Roitman and Shadlen 2002, but some of the basic principles regarding the network dynamics underlying this process remain largely unknown. We captured the basic features of a neural integrator using three canonical one-dimensional models: (1 the Drift Diffusion Model (DDM, (2 the Perfect Integrator (PI which is a particular case of the DDM where the bounds are set to infinity and (3 the double-well potential (DW which captures the dynamics of the attractor networks (Wang 2002; Roxin and Ledberg 2008. Although these models has been widely studied (Bogacz et al. 2006; Roxin and Ledberg 2008; Gold and Shadlen 2002, it has been difficult to experimentally discriminate among them because most of the observables measured are only quantitatively different among these models (e.g. psychometric curves. Here we aim to find experimentally measurable quantities that can yield qualitatively different behaviors depending on the nature of the underlying network dynamics. We examined the categorization dynamics of these models in response to fluctuating stimuli of different duration (T. On each time step, stimuli are drawn from a Gaussian distribution N(μ, σ and the two stimulus categories are defined by μ > 0 and μ < 0. Psychometric curves can therefore be obtained by quantifying the probability of the integrator to yield one category versus μ . We find however that varying σ can reveal more clearly the differences among the different integrators. In the small σ regime, both the DW and the DDM perform transient integration and exhibit a decaying stimulus reverse correlation kernel revealing a primacy effect (Nienborg and Cumming 2009; Wimmer et al. 2015 . In the large σ regime, the integration in the DDM

Spatially Nonlinear Interdependence of Alpha-Oscillatory Neural Networks under Chan Meditation

Directory of Open Access Journals (Sweden)

Pei-Chen Lo

2013-01-01

Full Text Available This paper reports the results of our investigation of the effects of Chan meditation on brain electrophysiological behaviors from the viewpoint of spatially nonlinear interdependence among regional neural networks. Particular emphasis is laid on the alpha-dominated EEG (electroencephalograph. Continuous-time wavelet transform was adopted to detect the epochs containing substantial alpha activities. Nonlinear interdependence quantified by similarity index S(X∣Y, the influence of source signal Y on sink signal X, was applied to the nonlinear dynamical model in phase space reconstructed from multichannel EEG. Experimental group involved ten experienced Chan-Meditation practitioners, while control group included ten healthy subjects within the same age range, yet, without any meditation experience. Nonlinear interdependence among various cortical regions was explored for five local neural-network regions, frontal, posterior, right-temporal, left-temporal, and central regions. In the experimental group, the inter-regional interaction was evaluated for the brain dynamics under three different stages, at rest (stage R, pre-meditation background recording, in Chan meditation (stage M, and the unique Chakra-focusing practice (stage C. Experimental group exhibits stronger interactions among various local neural networks at stages M and C compared with those at stage R. The intergroup comparison demonstrates that Chan-meditation brain possesses better cortical inter-regional interactions than the resting brain of control group.

Exploring biological network structure with clustered random networks

Directory of Open Access Journals (Sweden)

Bansal Shweta

2009-12-01

Full Text Available Abstract Background Complex biological systems are often modeled as networks of interacting units. Networks of biochemical interactions among proteins, epidemiological contacts among hosts, and trophic interactions in ecosystems, to name a few, have provided useful insights into the dynamical processes that shape and traverse these systems. The degrees of nodes (numbers of interactions and the extent of clustering (the tendency for a set of three nodes to be interconnected are two of many well-studied network properties that can fundamentally shape a system. Disentangling the interdependent effects of the various network properties, however, can be difficult. Simple network models can help us quantify the structure of empirical networked systems and understand the impact of various topological properties on dynamics. Results Here we develop and implement a new Markov chain simulation algorithm to generate simple, connected random graphs that have a specified degree sequence and level of clustering, but are random in all other respects. The implementation of the algorithm (ClustRNet: Clustered Random Networks provides the generation of random graphs optimized according to a local or global, and relative or absolute measure of clustering. We compare our algorithm to other similar methods and show that ours more successfully produces desired network characteristics. Finding appropriate null models is crucial in bioinformatics research, and is often difficult, particularly for biological networks. As we demonstrate, the networks generated by ClustRNet can serve as random controls when investigating the impacts of complex network features beyond the byproduct of degree and clustering in empirical networks. Conclusion ClustRNet generates ensembles of graphs of specified edge structure and clustering. These graphs allow for systematic study of the impacts of connectivity and redundancies on network function and dynamics. This process is a key step in

Reverse engineering GTPase programming languages with reconstituted signaling networks.

Science.gov (United States)

Coyle, Scott M

2016-07-02

The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems.

Impact of seasonal thermal stress on physiological and blood biochemical parameters in pigs under different dietary energy levels.

Science.gov (United States)

Pathak, P K; Roychoudhury, R; Saharia, J; Borah, M C; Dutta, D J; Bhuyan, R; Kalita, D

2018-06-01

The present study was formulated to find out the status of important season related thermal stress biomarkers of pure-bred (Hampshire) and crossbred (50% Hampshire × 50% local) pigs under the agro-climatic condition of Assam State, India. The experiment was also aimed to study the role of different level of energy ration (110, 100, and 90% energy of NRC feeding standard for pig) in variation of physiological and biochemical parameters in two genetic groups of pigs in different seasons. The metabolizable energy value were 3260, 2936.5, and 3585.8 kcal/kg in grower ration and 3260.2, 2936.6, and 3587 kcal/kg in finisher ration for normal energy (NE), low energy (LE) and high energy (HE), respectively. Both the genetic group of animals were housed separately under intensive system of management. Each pen was measuring 10' × 12' along with an outer enclosure. Six weaned piglets (almost similar body weight of average 10.55 kg) of each group were kept in a separate pen. However, after attainment of 35 kg body weight, the animals of a group were divided in two pens of three animals each. The present experiment indicated that average ambient temperature during summer months (27.33-29.51 °C) was above the comfort zone for pigs (22 °C). The significantly (P energy (HE) ration during summer season. Serum triiodothyronine (T 3 ) and thyroxine (T 4 ) concentrations were significantly (P energy level of the ration might be helpful to minimize the effects of thermal stress during summer.

Connecting Biochemical Photosynthesis Models with Crop Models to Support Crop Improvement.

Science.gov (United States)

Wu, Alex; Song, Youhong; van Oosterom, Erik J; Hammer, Graeme L

2016-01-01

The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation.

Connecting Biochemical Photosynthesis Models with Crop Models to Support Crop Improvement

Science.gov (United States)

Wu, Alex; Song, Youhong; van Oosterom, Erik J.; Hammer, Graeme L.

2016-01-01

The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation. PMID:27790232

Improving Marine Ecosystem Models with Biochemical Tracers

Science.gov (United States)

Pethybridge, Heidi R.; Choy, C. Anela; Polovina, Jeffrey J.; Fulton, Elizabeth A.

2018-01-01

Empirical data on food web dynamics and predator-prey interactions underpin ecosystem models, which are increasingly used to support strategic management of marine resources. These data have traditionally derived from stomach content analysis, but new and complementary forms of ecological data are increasingly available from biochemical tracer techniques. Extensive opportunities exist to improve the empirical robustness of ecosystem models through the incorporation of biochemical tracer data and derived indices, an area that is rapidly expanding because of advances in analytical developments and sophisticated statistical techniques. Here, we explore the trophic information required by ecosystem model frameworks (species, individual, and size based) and match them to the most commonly used biochemical tracers (bulk tissue and compound-specific stable isotopes, fatty acids, and trace elements). Key quantitative parameters derived from biochemical tracers include estimates of diet composition, niche width, and trophic position. Biochemical tracers also provide powerful insight into the spatial and temporal variability of food web structure and the characterization of dominant basal and microbial food web groups. A major challenge in incorporating biochemical tracer data into ecosystem models is scale and data type mismatches, which can be overcome with greater knowledge exchange and numerical approaches that transform, integrate, and visualize data.

Study Under AC Stimulation on Excitement Properties of Weighted Small-World Biological Neural Networks with Side-Restrain Mechanism

International Nuclear Information System (INIS)

Yuan Wujie; Luo Xiaoshu; Jiang Pinqun

2007-01-01

In this paper, we propose a new model of weighted small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with side-restrain mechanism. Then we study excitement properties of the model under alternating current (AC) stimulation. The study shows that the excitement properties in the networks are preferably consistent with the behavior properties of a brain nervous system under different AC stimuli, such as refractory period and the brain neural excitement response induced by different intensities of noise and coupling. The results of the study have reference worthiness for the brain nerve electrophysiology and epistemological science.

Abscisic acid regulates root growth under osmotic stress conditions via an interacting hormonal network with cytokinin, ethylene and auxin.

Science.gov (United States)

Rowe, James H; Topping, Jennifer F; Liu, Junli; Lindsey, Keith

2016-07-01

Understanding the mechanisms regulating root development under drought conditions is an important question for plant biology and world agriculture. We examine the effect of osmotic stress on abscisic acid (ABA), cytokinin and ethylene responses and how they mediate auxin transport, distribution and root growth through effects on PIN proteins. We integrate experimental data to construct hormonal crosstalk networks to formulate a systems view of root growth regulation by multiple hormones. Experimental analysis shows: that ABA-dependent and ABA-independent stress responses increase under osmotic stress, but cytokinin responses are only slightly reduced; inhibition of root growth under osmotic stress does not require ethylene signalling, but auxin can rescue root growth and meristem size; osmotic stress modulates auxin transporter levels and localization, reducing root auxin concentrations; PIN1 levels are reduced under stress in an ABA-dependent manner, overriding ethylene effects; and the interplay among ABA, ethylene, cytokinin and auxin is tissue-specific, as evidenced by differential responses of PIN1 and PIN2 to osmotic stress. Combining experimental analysis with network construction reveals that ABA regulates root growth under osmotic stress conditions via an interacting hormonal network with cytokinin, ethylene and auxin. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Raman spectroscopic biochemical mapping of tissues

Science.gov (United States)

Stone, Nicholas; Hart Prieto, Maria C.; Kendall, Catherine A.; Shetty, Geeta; Barr, Hugh

2006-02-01

Advances in technologies have brought us closer to routine spectroscopic diagnosis of early malignant disease. However, there is still a poor understanding of the carcinogenesis process. For example it is not known whether many cancers follow a logical sequence from dysplasia, to carcinoma in situ, to invasion. Biochemical tissue changes, triggered by genetic mutations, precede morphological and structural changes. These can be probed using Raman or FTIR microspectroscopy and the spectra analysed for biochemical constituents. Local microscopic distribution of various constituents can then be visualised. Raman mapping has been performed on a number of tissues including oesophagus, breast, bladder and prostate. The biochemical constituents have been calculated at each point using basis spectra and least squares analysis. The residual of the least squares fit indicates any unfit spectral components. The biochemical distribution will be compared with the defined histopathological boundaries. The distribution of nucleic acids, glycogen, actin, collagen I, III, IV, lipids and others appear to follow expected patterns.

Cerebral energy metabolism and the brain's functional network architecture: an integrative review.

Science.gov (United States)

Lord, Louis-David; Expert, Paul; Huckins, Jeremy F; Turkheimer, Federico E

2013-09-01

Recent functional magnetic resonance imaging (fMRI) studies have emphasized the contributions of synchronized activity in distributed brain networks to cognitive processes in both health and disease. The brain's 'functional connectivity' is typically estimated from correlations in the activity time series of anatomically remote areas, and postulated to reflect information flow between neuronal populations. Although the topological properties of functional brain networks have been studied extensively, considerably less is known regarding the neurophysiological and biochemical factors underlying the temporal coordination of large neuronal ensembles. In this review, we highlight the critical contributions of high-frequency electrical oscillations in the γ-band (30 to 100 Hz) to the emergence of functional brain networks. After describing the neurobiological substrates of γ-band dynamics, we specifically discuss the elevated energy requirements of high-frequency neural oscillations, which represent a mechanistic link between the functional connectivity of brain regions and their respective metabolic demands. Experimental evidence is presented for the high oxygen and glucose consumption, and strong mitochondrial performance required to support rhythmic cortical activity in the γ-band. Finally, the implications of mitochondrial impairments and deficits in glucose metabolism for cognition and behavior are discussed in the context of neuropsychiatric and neurodegenerative syndromes characterized by large-scale changes in the organization of functional brain networks.

[Individual physical performance capacity with physiological and biochemical indicators of stress].

Science.gov (United States)

Bergert, K D; Nestler, K; Böttger, H; Schettler, R

1989-09-01

22 health male subjects were exposed by a combination of physical exercises and heat. Strain related physiological and biochemical parameters were measured. Different individual reactions were obtained under controlled conditions. In dependence on the individual performance an increased mobilisation of lactat, free fatty acids and catecholamines were found. The determination of aerob physical performance can be applied for the evaluation of working capacity.

Novel topological descriptors for analyzing biological networks

Directory of Open Access Journals (Sweden)

Varmuza Kurt K

2010-06-01

Full Text Available Abstract Background Topological descriptors, other graph measures, and in a broader sense, graph-theoretical methods, have been proven as powerful tools to perform biological network analysis. However, the majority of the developed descriptors and graph-theoretical methods does not have the ability to take vertex- and edge-labels into account, e.g., atom- and bond-types when considering molecular graphs. Indeed, this feature is important to characterize biological networks more meaningfully instead of only considering pure topological information. Results In this paper, we put the emphasis on analyzing a special type of biological networks, namely bio-chemical structures. First, we derive entropic measures to calculate the information content of vertex- and edge-labeled graphs and investigate some useful properties thereof. Second, we apply the mentioned measures combined with other well-known descriptors to supervised machine learning methods for predicting Ames mutagenicity. Moreover, we investigate the influence of our topological descriptors - measures for only unlabeled vs. measures for labeled graphs - on the prediction performance of the underlying graph classification problem. Conclusions Our study demonstrates that the application of entropic measures to molecules representing graphs is useful to characterize such structures meaningfully. For instance, we have found that if one extends the measures for determining the structural information content of unlabeled graphs to labeled graphs, the uniqueness of the resulting indices is higher. Because measures to structurally characterize labeled graphs are clearly underrepresented so far, the further development of such methods might be valuable and fruitful for solving problems within biological network analysis.

Work of scientific and technological information under network environment

International Nuclear Information System (INIS)

Chen Yingxi; Huang Daifu; Yang Lifeng

2010-01-01

With the development of internet and information technology, the work of scientific and technological information is faced with great challenge. This article expounds the new changes of scientific and technological information in enterprise under network environment by giving a minute description on the situation the work faced and characteristic of the work. Not only does it carry out enthusiastic discussion upon problems which are present in the work of scientific and technological information in the company, but puts forward proposals and specific measures as well. Service theory is also offered by adjusting and reforming the resources construction, service ways and the job of providing contents. We should take vigorous action to the research work of scientific and technological information, changing the information directional service into knowledge providing service. (authors)

Resting-state functional under-connectivity within and between large-scale cortical networks across three low-frequency bands in adolescents with autism.

Science.gov (United States)

Duan, Xujun; Chen, Heng; He, Changchun; Long, Zhiliang; Guo, Xiaonan; Zhou, Yuanyue; Uddin, Lucina Q; Chen, Huafu

2017-10-03

Although evidence is accumulating that autism spectrum disorder (ASD) is associated with disruption of functional connections between and within brain networks, it remains largely unknown whether these abnormalities are related to specific frequency bands. To address this question, network contingency analysis was performed on brain functional connectomes obtained from 213 adolescent participants across nine sites in the Autism Brain Imaging Data Exchange (ABIDE) multisite sample, to determine the disrupted connections between and within seven major cortical networks in adolescents with ASD at Slow-5, Slow-4 and Slow-3 frequency bands and further assess whether the aberrant intra- and inter-network connectivity varied as a function of ASD symptoms. Overall under-connectivity within and between large-scale intrinsic networks in ASD was revealed across the three frequency bands. Specifically, decreased connectivity strength within the default mode network (DMN), between DMN and visual network (VN), ventral attention network (VAN), and between dorsal attention network (DAN) and VAN was observed in the lower frequency band (slow-5, slow-4), while decreased connectivity between limbic network (LN) and frontal-parietal network (FPN) was observed in the higher frequency band (slow-3). Furthermore, weaker connectivity within and between specific networks correlated with poorer communication and social interaction skills in the slow-5 band, uniquely. These results demonstrate intrinsic under-connectivity within and between multiple brain networks within predefined frequency bands in ASD, suggesting that frequency-related properties underlie abnormal brain network organization in the disorder. Copyright © 2017 Elsevier Inc. All rights reserved.

Complex network analysis of phase dynamics underlying oil-water two-phase flows

Science.gov (United States)

Gao, Zhong-Ke; Zhang, Shan-Shan; Cai, Qing; Yang, Yu-Xuan; Jin, Ning-De

2016-01-01

Characterizing the complicated flow behaviors arising from high water cut and low velocity oil-water flows is an important problem of significant challenge. We design a high-speed cycle motivation conductance sensor and carry out experiments for measuring the local flow information from different oil-in-water flow patterns. We first use multivariate time-frequency analysis to probe the typical features of three flow patterns from the perspective of energy and frequency. Then we infer complex networks from multi-channel measurements in terms of phase lag index, aiming to uncovering the phase dynamics governing the transition and evolution of different oil-in-water flow patterns. In particular, we employ spectral radius and weighted clustering coefficient entropy to characterize the derived unweighted and weighted networks and the results indicate that our approach yields quantitative insights into the phase dynamics underlying the high water cut and low velocity oil-water flows. PMID:27306101

Tradeoff between robustness and elaboration in carotenoid networks produces cycles of avian color diversification.

Science.gov (United States)

Badyaev, Alexander V; Morrison, Erin S; Belloni, Virginia; Sanderson, Michael J

2015-08-20

Resolution of the link between micro- and macroevolution calls for comparing both processes on the same deterministic landscape, such as genomic, metabolic or fitness networks. We apply this perspective to the evolution of carotenoid pigmentation that produces spectacular diversity in avian colors and show that basic structural properties of the underlying carotenoid metabolic network are reflected in global patterns of elaboration and diversification in color displays. Birds color themselves by consuming and metabolizing several dietary carotenoids from the environment. Such fundamental dependency on the most upstream external compounds should intrinsically constrain sustained evolutionary elongation of multi-step metabolic pathways needed for color elaboration unless the metabolic network gains robustness - the ability to synthesize the same carotenoid from an additional dietary starting point. We found that gains and losses of metabolic robustness were associated with evolutionary cycles of elaboration and stasis in expressed carotenoids in birds. Lack of metabolic robustness constrained lineage's metabolic explorations to the immediate biochemical vicinity of their ecologically distinct dietary carotenoids, whereas gains of robustness repeatedly resulted in sustained elongation of metabolic pathways on evolutionary time scales and corresponding color elaboration. The structural link between length and robustness in metabolic pathways may explain periodic convergence of phylogenetically distant and ecologically distinct species in expressed carotenoid pigmentation; account for stasis in carotenoid colors in some ecological lineages; and show how the connectivity of the underlying metabolic network provides a mechanistic link between microevolutionary elaboration and macroevolutionary diversification.

Biofertilizing efficiency of Sargassum polycystum extract on growth and biochemical composition of Vigna radiata and Vigna mungo

Directory of Open Access Journals (Sweden)

B Bharath

2018-01-01

Full Text Available Objective: To evaluate the effect of marine brown alga Sargassum polycystum extract on growth and biochemical parameters of Vigna radiata and Vigna mungo.Methods: Different concentrations of algal extracts (0.5%, 1.0%, 2.0%, 3.0%, 4.0%, and 5.0% were prepared and applied to the crops at every 10-day intervals under natural conditions. After 30 d, the plants were harvested to evaluate the growth and biochemical parameters.Results: Seaweed liquid fertilizers treated seedlings showed maximum growth in 3.0% concentration when compared to the untreated seedlings. Similarly, biochemical parameters such as photosynthetic pigments, protein, reducing sugar, total sugar and amino acids exhibited increases in 3.0% concentration seaweed extract. Decreases in growth and biochemical parameters were noticed in concentrations higher than 3.0%.Conclusions: Presence of micronutrients and growth regulating substances in the liquid extract help healthier and faster productivity of the crop.

Physiological and biochemical relationship under drought stress in ...

African Journals Online (AJOL)

Yomi

2012-01-24

Jan 24, 2012 ... Some statistical procedures like correlation, stepwise regression, factor analysis and cluster analysis were used to study the relationship between wheat grain yield and some physiological parameters under drought conditions. Results reveal that the ratio fv/fm of chlorophyll fluorescence is the most.

Bayesian networks for clinical decision support: A rational approach to dynamic decision-making under uncertainty

NARCIS (Netherlands)

Gerven, M.A.J. van

2007-01-01

This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed

Creating and Using a Computer Networking and Systems Administration Laboratory Built under Relaxed Financial Constraints

Science.gov (United States)

Conlon, Michael P.; Mullins, Paul

2011-01-01

The Computer Science Department at Slippery Rock University created a laboratory for its Computer Networks and System Administration and Security courses under relaxed financial constraints. This paper describes the department's experience designing and using this laboratory, including lessons learned and descriptions of some student projects…

Physiological and biochemical relationship under drought stress in ...

African Journals Online (AJOL)

Some statistical procedures like correlation, stepwise regression, factor analysis and cluster analysis were used to study the relationship between wheat grain yield and some physiological parameters under drought conditions. Results reveal that the ratio fv/fm of chlorophyll fluorescence is the most effective parameter to ...

Artificial neural networks for control of a grid-connected rectifier/inverter under disturbance, dynamic and power converter switching conditions.

Science.gov (United States)

Li, Shuhui; Fairbank, Michael; Johnson, Cameron; Wunsch, Donald C; Alonso, Eduardo; Proaño, Julio L

2014-04-01

Three-phase grid-connected converters are widely used in renewable and electric power system applications. Traditionally, grid-connected converters are controlled with standard decoupled d-q vector control mechanisms. However, recent studies indicate that such mechanisms show limitations in their applicability to dynamic systems. This paper investigates how to mitigate such restrictions using a neural network to control a grid-connected rectifier/inverter. The neural network implements a dynamic programming algorithm and is trained by using back-propagation through time. To enhance performance and stability under disturbance, additional strategies are adopted, including the use of integrals of error signals to the network inputs and the introduction of grid disturbance voltage to the outputs of a well-trained network. The performance of the neural-network controller is studied under typical vector control conditions and compared against conventional vector control methods, which demonstrates that the neural vector control strategy proposed in this paper is effective. Even in dynamic and power converter switching environments, the neural vector controller shows strong ability to trace rapidly changing reference commands, tolerate system disturbances, and satisfy control requirements for a faulted power system.

Relative localization in wireless sensor networks for measurement of electric fields under HVDC transmission lines.

Science.gov (United States)

Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

2015-02-04

In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

Relative Localization in Wireless Sensor Networks for Measurement of Electric Fields under HVDC Transmission Lines

Directory of Open Access Journals (Sweden)

Yong Cui

2015-02-01

Full Text Available In the wireless sensor networks (WSNs for electric field measurement system under the High-Voltage Direct Current (HVDC transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes’ neighbor lists based on the Received Signal Strength Indicator (RSSI values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

Some biochemical and hematological changes in female rats under protein malnutrition

International Nuclear Information System (INIS)

EL-Sherbiny, E.M.; El-Mahdy, A.A.; Bayoumi, M.M.

2006-01-01

The aim of this study was to clarify the effect of low and high dietary protein on some biochemical and hematological parameters in blood of female albino rats. A total number of 75 albino female rats were equally divided into 3 groups, the first group was fed 20% protein diet and served as control and the second and third groups were fed 5% and 65% protein for 5 weeks and served as low and high protein dietary groups, respectively. The results showed high significant decreases in serum growth hormone, ferritin levels and iron concentration in group II and there was significant increase in unsaturated iron binding capacity (UIBC) in group III, compared to control group. Studies of total protein and its fractions revealed high significant decreases in total protein, albumin, alpha-1-globulin, beta-globulin as well as gamma globulin in group II and significant increases in total protein, alpha-1- globulin, beta-globulin and gamma-globulin in group III, compared to normal control group. The hematological investigations in group II revealed significant decreases in hemoglobin value, total leukocyte count, platelets, mean corpuscular hemoglobin concentration (MCHC), erythrocytic count and mean corpuscular volume (MCV). On the other hand, there was significant increase in total leukocyte count in group III if compared to control group

DMPD: Toll-like receptor (TLR)-based networks regulate neutrophilic inflammation inrespiratory disease. [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available 18031251 Toll-like receptor (TLR)-based networks regulate neutrophilic inflammation inrespiratory...l) (.csml) Show Toll-like receptor (TLR)-based networks regulate neutrophilic inflammation inrespiratory dis...utrophilic inflammation inrespiratory disease. Authors Sabroe I, Whyte MK. Publication Biochem Soc Trans. 20

Salience network dynamics underlying successful resistance of temptation

Science.gov (United States)

Nomi, Jason S; Calhoun, Vince D; Stelzel, Christine; Paschke, Lena M; Gaschler, Robert; Goschke, Thomas; Walter, Henrik; Uddin, Lucina Q

2017-01-01

Abstract Self-control and the ability to resist temptation are critical for successful completion of long-term goals. Contemporary models in cognitive neuroscience emphasize the primary role of prefrontal cognitive control networks in aligning behavior with such goals. Here, we use gaze pattern analysis and dynamic functional connectivity fMRI data to explore how individual differences in the ability to resist temptation are related to intrinsic brain dynamics of the cognitive control and salience networks. Behaviorally, individuals exhibit greater gaze distance from target location (e.g. higher distractibility) during presentation of tempting erotic images compared with neutral images. Individuals whose intrinsic dynamic functional connectivity patterns gravitate toward configurations in which salience detection systems are less strongly coupled with visual systems resist tempting distractors more effectively. The ability to resist tempting distractors was not significantly related to intrinsic dynamics of the cognitive control network. These results suggest that susceptibility to temptation is governed in part by individual differences in salience network dynamics and provide novel evidence for involvement of brain systems outside canonical cognitive control networks in contributing to individual differences in self-control. PMID:29048582

Biochemical Indicators of Radiation Injury in Man. Proceedings of a Scientific Meeting

International Nuclear Information System (INIS)

1971-01-01

After an organism has suffered a radiation insult, knowledge of the dose and localization of the exposure is of the greatest importance for the treatment of any radiation damage. Supplementary to the information obtained from physical dosimetry, data obtained by biochemical indicators can, on the basis of metabolic changes in the irradiated organism, help in making early diagnosis, in assessing the extent of the radiation injury, and making a prognosis. Biochemical tests under optimal conditions would not depend on the quality and distribution of the dose in the body and would also reflect the sensitivity of the individual organisms. The International Atomic Energy Agency and the World Health Organization convened a joint scientific meeting on Biochemical Indicators of Radiation Injury in Man in Paris-Le Vésinet, France, from 22 to 26 June 1970. The main purpose of the meeting was to discuss recent problems in determining which biochemical and metabolic changes occurring in irradiated organisms could be used as indicators of radiation injury and its extent, and could thus be of help in planning the proper treatment of the injured persons. During the meeting the results obtained with various biochemical indicators, and experimental techniques and laboratory methods used in this field, were evaluated and compared. Both research workers and clinicians were invited to participate at the meeting. They discussed the possible value of several tests, used successfully in experimental animals, for clinical application; ways of standardizing suitable tests; and mutual collaboration between laboratories and clinics. The outcome of their discussions is summarized in the conclusions and recommendations which are included in these Proceedings together with the papers presented

Friendly network robotics; Friendly network robotics

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

This paper summarizes the research results on the friendly network robotics in fiscal 1996. This research assumes an android robot as an ultimate robot and the future robot system utilizing computer network technology. The robot aiming at human daily work activities in factories or under extreme environments is required to work under usual human work environments. The human robot with similar size, shape and functions to human being is desirable. Such robot having a head with two eyes, two ears and mouth can hold a conversation with human being, can walk with two legs by autonomous adaptive control, and has a behavior intelligence. Remote operation of such robot is also possible through high-speed computer network. As a key technology to use this robot under coexistence with human being, establishment of human coexistent robotics was studied. As network based robotics, use of robots connected with computer networks was also studied. In addition, the R-cube (R{sup 3}) plan (realtime remote control robot technology) was proposed. 82 refs., 86 figs., 12 tabs.

Modelling the Cost Performance of a Given Logistics Network Operating Under Regular and Irregular Conditions

NARCIS (Netherlands)

Janic, M.

2009-01-01

This paper develops an analytical model for the assessment of the cost performance of a given logistics network operating under regular and irregular (disruptive) conditions. In addition, the paper aims to carry out a sensitivity analysis of this cost with respect to changes of the most influencing

Training signaling pathway maps to biochemical data with constrained fuzzy logic: quantitative analysis of liver cell responses to inflammatory stimuli.

Directory of Open Access Journals (Sweden)

Melody K Morris

2011-03-01

Full Text Available Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL, converts a prior knowledge network (obtained from literature or interactome databases into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a generating experimentally testable biological hypotheses concerning pathway crosstalk, (b establishing capability for quantitative prediction of protein activity, and (c prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone.

Analyzing Bullwhip Effect in Supply Networks under Exogenous Uncertainty

Directory of Open Access Journals (Sweden)

Mitra Darvish

2014-05-01

Full Text Available This paper explains a model for analyzing and measuring the propagation of order amplifications (i.e. bullwhip effect for a single-product supply network topology considering exogenous uncertainty and linear and time-invariant inventory management policies for network entities. The stream of orders placed by each entity of the network is characterized assuming customer demand is ergodic. In fact, we propose an exact formula in order to measure the bullwhip effect in the addressed supply network topology considering the system in Markovian chain framework and presenting a matrix of network member relationships and relevant order sequences. The formula turns out using a mathematical method called frequency domain analysis. The major contribution of this paper is analyzing the bullwhip effect considering exogenous uncertainty in supply networks and using the Fourier transform in order to simplify the relevant calculations. We present a number of numerical examples to assess the analytical results accuracy in quantifying the bullwhip effect.

Network-level architecture and the evolutionary potential of underground metabolism.

Science.gov (United States)

Notebaart, Richard A; Szappanos, Balázs; Kintses, Bálint; Pál, Ferenc; Györkei, Ádám; Bogos, Balázs; Lázár, Viktória; Spohn, Réka; Csörgő, Bálint; Wagner, Allon; Ruppin, Eytan; Pál, Csaba; Papp, Balázs

2014-08-12

A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ∼20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

The dtudy of physiological and biochemical responses of Agrostis stolonifera and Festuca arundinacea Schreb. under drought stress

Directory of Open Access Journals (Sweden)

Mohammad Hassan Alibiglouei

2014-12-01

Full Text Available Drought stress is a main limiting factor of turfgrass growth in arid and semi-arid regions. Therefore, in this study, the physiological and biochemical changes in two turfgrass species Agrostis stolonifera and Festuca arundinacea schreb during drought stress (70-75 centibar in a 40-day period and recovery were investigated. Control plants during drought stress were regularly irrigated at soil field capacity (20-25 centibar. The results showed that leaf relative water content and leaf chlorophyll content with long-term stress decreased. Electrolyte leakage and proline during drought stress significantly increased and in recovery stage, the level of electrolyte leakage and proline reached to the control. The activity of peroxidase and superoxide dismutase in two turfgrass significantly increased after 30 days and then significantly reduced. In F. arundinacea schreb the activity of ascorbat peroxidase after 20 days significantly increased and then significantly reduced. Also, in F. arundinacea schreb species the activity of catalase increased during drought stress and in recovery stage the activity of catalase reduced. In studied species during drought stress and recovery stage, the activity of ascorbat peroxidase and catalase significantly increased compared to the control. These results suggested that the resistant species F. arundinacea schreb, under drought stress had a low level of electrolyte leakage, higher level of relative water content and chlorophyll destruction was less than A. stolonifera.

Robustness of networks against propagating attacks under vaccination strategies

International Nuclear Information System (INIS)

Hasegawa, Takehisa; Masuda, Naoki

2011-01-01

We study the effect of vaccination on the robustness of networks against propagating attacks that obey the susceptible–infected–removed model. By extending the generating function formalism developed by Newman (2005 Phys. Rev. Lett. 95 108701), we analytically determine the robustness of networks that depends on the vaccination parameters. We consider the random defense where nodes are vaccinated randomly and the degree-based defense where hubs are preferentially vaccinated. We show that, when vaccines are inefficient, the random graph is more robust against propagating attacks than the scale-free network. When vaccines are relatively efficient, the scale-free network with the degree-based defense is more robust than the random graph with the random defense and the scale-free network with the random defense

QoS Parameters Evaluation in a VPN-MPLS Diffserv Network under a Complete Free Software Emulation Environment

Directory of Open Access Journals (Sweden)

Miroslava Aracely Zapata Rodríguez

2017-12-01

Full Text Available The use of Virtual Private Network – Multi Protocol Label Switching (VPN-MPLS networks has become very common inside enterprises thanks to their multiple advantages; such as, the private communication across a public network infrastructure between geographically diverse sites. This leads to a need for an efficient network in terms of Quality of Service (QoS to guarantee reliability and security of information. However, the implementation of a VPN-MPLS network is neither easy nor cheap for small and medium companies; hence, in most cases, it is required the use of emulators that are not free either. In this paper, we analyze a VPN-MPLS network in terms of QoS metrics: delay, jitter and packet loss. This evaluation was performed in a virtual environment using only free software tools under two test scenarios, with and without Differentiated Services (DiffServ. The results showed that a VPN-MPLS DiffServ network reduces the delay by approximately 96.78% in VoIP, 39.21% in Data and 66.83% in Streaming; furthermore, the jitter was reduced by approximately 27.88% in VoIP and 41.09% in Data.

Network formation under heterogeneous costs: The multiple group model

NARCIS (Netherlands)

Kamphorst, J.J.A.; van der Laan, G.

2007-01-01

It is widely recognized that the shape of networks influences both individual and aggregate behavior. This raises the question which types of networks are likely to arise. In this paper we investigate a model of network formation, where players are divided into groups and the costs of a link between

Signatures of arithmetic simplicity in metabolic network architecture.

Directory of Open Access Journals (Sweden)

William J Riehl

2010-04-01

Full Text Available 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 properties similar to those predicted for the artificial chemistry hold also for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity.

Rational design of functional and tunable oscillating enzymatic networks

Science.gov (United States)

Semenov, Sergey N.; Wong, Albert S. Y.; van der Made, R. Martijn; Postma, Sjoerd G. J.; Groen, Joost; van Roekel, Hendrik W. H.; de Greef, Tom F. A.; Huck, Wilhelm T. S.

2015-02-01

Life is sustained by complex systems operating far from equilibrium and consisting of a multitude of enzymatic reaction networks. The operating principles of biology's regulatory networks are known, but the in vitro assembly of out-of-equilibrium enzymatic reaction networks has proved challenging, limiting the development of synthetic systems showing autonomous behaviour. Here, we present a strategy for the rational design of programmable functional reaction networks that exhibit dynamic behaviour. We demonstrate that a network built around autoactivation and delayed negative feedback of the enzyme trypsin is capable of producing sustained oscillating concentrations of active trypsin for over 65 h. Other functions, such as amplification, analog-to-digital conversion and periodic control over equilibrium systems, are obtained by linking multiple network modules in microfluidic flow reactors. The methodology developed here provides a general framework to construct dissipative, tunable and robust (bio)chemical reaction networks.

GKIN: a tool for drawing genetic networks

Directory of Open Access Journals (Sweden)

Jonathan Arnold

2012-03-01

Full Text Available We present GKIN, a simulator and a comprehensive graphical interface where one can draw the model specification of reactions between hypothesized molecular participants in a gene regulatory and biochemical reaction network (or genetic network for short. The solver is written in C++ in a nearly platform independentmanner to simulate large ensembles of models, which can run on PCs, Macintoshes, and UNIX machines, and its graphical user interface is written in Java which can run as a standalone or WebStart application. The drawing capability for rendering a network significantly enhances the ease of use of other reaction network simulators, such as KINSOLVER (Aleman-Meza et al., 2009 and enforces a correct semantic specification of the network. In a usability study with novice users, drawing the network with GKIN was preferred and faster in comparison with entry with a dialog-box guided interface in COPASI (Hoops, et al., 2006 with no difference in error rates between GKIN and COPASI in specifying the network. GKIN is freely available at http://faculty.cs.wit.edu/~ldeligia/PROJECTS/GKIN/.

Biochemical Process Development and Integration | Bioenergy | NREL

Science.gov (United States)

Biochemical Process Development and Integration Biochemical Process Development and Integration Our conversion and separation processes to pilot-scale integrated process development and scale up. We also Publications Accounting for all sugar produced during integrated production of ethanol from lignocellulosic

Activating and inhibiting connections in biological network dynamics

Directory of Open Access Journals (Sweden)

Knight Rob

2008-12-01

Full Text Available Abstract Background Many studies of biochemical networks have analyzed network topology. Such work has suggested that specific types of network wiring may increase network robustness and therefore confer a selective advantage. However, knowledge of network topology does not allow one to predict network dynamical behavior – for example, whether deleting a protein from a signaling network would maintain the network's dynamical behavior, or induce oscillations or chaos. Results Here we report that the balance between activating and inhibiting connections is important in determining whether network dynamics reach steady state or oscillate. We use a simple dynamical model of a network of interacting genes or proteins. Using the model, we study random networks, networks selected for robust dynamics, and examples of biological network topologies. The fraction of activating connections influences whether the network dynamics reach steady state or oscillate. Conclusion The activating fraction may predispose a network to oscillate or reach steady state, and neutral evolution or selection of this parameter may affect the behavior of biological networks. This principle may unify the dynamics of a wide range of cellular networks. Reviewers Reviewed by Sergei Maslov, Eugene Koonin, and Yu (Brandon Xia (nominated by Mark Gerstein. For the full reviews, please go to the Reviewers' comments section.

A mathematical framework for modelling and evaluating natural gas pipeline networks under hydrogen injection

Energy Technology Data Exchange (ETDEWEB)

Tabkhi, F.; Azzaro-Pantel, C.; Pibouleau, L.; Domenech, S. [Laboratoire de Genie Chimique, UMR5503 CNRS/INP/UPS, 5 rue Paulin Talabot F-BP1301, 31106 Toulouse Cedex 1 (France)

2008-11-15

This article presents the framework of a mathematical formulation for modelling and evaluating natural gas pipeline networks under hydrogen injection. The model development is based on gas transport through pipelines and compressors which compensate for the pressure drops by implying mainly the mass and energy balances on the basic elements of the network. The model was initially implemented for natural gas transport and the principle of extension for hydrogen-natural gas mixtures is presented. The objective is the treatment of the classical fuel minimizing problem in compressor stations. The optimization procedure has been formulated by means of a nonlinear technique within the General Algebraic Modelling System (GAMS) environment. This work deals with the adaptation of the current transmission networks of natural gas to the transport of hydrogen-natural gas mixtures. More precisely, the quantitative amount of hydrogen that can be added to natural gas can be determined. The studied pipeline network, initially proposed in [1] is revisited here for the case of hydrogen-natural gas mixtures. Typical quantitative results are presented, showing that the addition of hydrogen to natural gas decreases significantly the transmitted power: the maximum fraction of hydrogen that can be added to natural gas is around 6 mass% for this example. (author)

Meta-stochastic simulation of biochemical models for systems and synthetic biology.

Science.gov (United States)

Sanassy, Daven; Widera, Paweł; Krasnogor, Natalio

2015-01-16

Stochastic simulation algorithms (SSAs) are used to trace realistic trajectories of biochemical systems at low species concentrations. As the complexity of modeled biosystems increases, it is important to select the best performing SSA. Numerous improvements to SSAs have been introduced but they each only tend to apply to a certain class of models. This makes it difficult for a systems or synthetic biologist to decide which algorithm to employ when confronted with a new model that requires simulation. In this paper, we demonstrate that it is possible to determine which algorithm is best suited to simulate a particular model and that this can be predicted a priori to algorithm execution. We present a Web based tool ssapredict that allows scientists to upload a biochemical model and obtain a prediction of the best performing SSA. Furthermore, ssapredict gives the user the option to download our high performance simulator ngss preconfigured to perform the simulation of the queried biochemical model with the predicted fastest algorithm as the simulation engine. The ssapredict Web application is available at http://ssapredict.ico2s.org. It is free software and its source code is distributed under the terms of the GNU Affero General Public License.

Scrutiny of the ASTRO consensus definition of biochemical failure in irradiated prostate cancer patients demonstrates its usefulness and robustness

International Nuclear Information System (INIS)

Hanlon, Alexandra L.; Hanks, Gerald E.

2000-01-01

Purpose: The goals of this study are: (1) to establish the robustness of the Fox Chase Cancer Center (FCCC) and the American Society for Therapeutic Radiology and Oncology (ASTRO) consensus definitions of failure by comparing biochemical estimates under various modifications of the censoring and failure time components to their respective unaltered definitions; (2) to isolate the source of variation between the two definitions of failure; and (3) to describe the hazard of failure over time for each definition. Methods: Between May 1989 and May 1997, 670 men were treated at Fox Chase Cancer Center for localized prostate cancer using three-dimensional conformal radiation therapy (3DCRT). These men were stratified into three groups for analysis: 111 men treated with adjuvant hormones; 204 men treated with radiation therapy alone and presenting with more favorable prognosis tumor characteristics; 255 men treated with radiation therapy alone and presenting with less favorable prognosis tumor characteristics. For each group, biochemical failure was estimated and compared using the FCCC and ASTRO definitions of failure. The robustness of each definition was evaluated by comparing estimates under the definition as stated to those under various modifications of the censoring and failure components. Analyses were also performed while excluding slow-progressing patients. To isolate the source of variation between the two failure definitions, estimates were compared for patients with agreement in failure status. Estimates of biochemical failure, and thus hazard rates, were made using Kaplan-Meier methodology. Results: ASTRO biochemical failure estimates were higher than the FCCC failure estimates in the first 5 years post-treatment. Beyond 5 years, ASTRO estimates level off, while the FCCC failure estimates continued to increase. These failure patterns were similar in all patient groups; however, patients treated with adjuvant hormones had a much higher risk of failure

A Nondominated Genetic Algorithm Procedure for Multiobjective Discrete Network Design under Demand Uncertainty

OpenAIRE

Changzhi, Bian

2015-01-01

This paper addresses the multiobjective discrete network design problem under demand uncertainty. The OD travel demands are supposed to be random variables with the given probability distribution. The problem is formulated as a bilevel stochastic optimization model where the decision maker’s objective is to minimize the construction cost, the expectation, and the standard deviation of total travel time simultaneously and the user’s route choice is described using user equilibrium model on the...

Prioritization of Candidate Genes in QTL Regions for Physiological and Biochemical Traits Underlying Drought Response in Barley (Hordeum vulgare L.

Directory of Open Access Journals (Sweden)

Kornelia Gudys

2018-06-01

Full Text Available Drought is one of the most adverse abiotic factors limiting growth and productivity of crops. Among them is barley, ranked fourth cereal worldwide in terms of harvested acreage and production. Plants have evolved various mechanisms to cope with water deficit at different biological levels, but there is an enormous challenge to decipher genes responsible for particular complex phenotypic traits, in order to develop drought tolerant crops. This work presents a comprehensive approach for elucidation of molecular mechanisms of drought tolerance in barley at the seedling stage of development. The study includes mapping of QTLs for physiological and biochemical traits associated with drought tolerance on a high-density function map, projection of QTL confidence intervals on barley physical map, and the retrievement of positional candidate genes (CGs, followed by their prioritization based on Gene Ontology (GO enrichment analysis. A total of 64 QTLs for 25 physiological and biochemical traits that describe plant water status, photosynthetic efficiency, osmoprotectant and hormone content, as well as antioxidant activity, were positioned on a consensus map, constructed using RIL populations developed from the crosses between European and Syrian genotypes. The map contained a total of 875 SNP, SSR and CGs, spanning 941.86 cM with resolution of 1.1 cM. For the first time, QTLs for ethylene, glucose, sucrose, maltose, raffinose, α-tocopherol, γ-tocotrienol content, and catalase activity, have been mapped in barley. Based on overlapping confidence intervals of QTLs, 11 hotspots were identified that enclosed more than 60% of mapped QTLs. Genetic and physical map integration allowed the identification of 1,101 positional CGs within the confidence intervals of drought response-specific QTLs. Prioritization resulted in the designation of 143 CGs, among them were genes encoding antioxidants, carboxylic acid biosynthesis enzymes, heat shock proteins, small auxin

Network optimization including gas lift and network parameters under subsurface uncertainty

Energy Technology Data Exchange (ETDEWEB)

Schulze-Riegert, R.; Baffoe, J.; Pajonk, O. [SPT Group GmbH, Hamburg (Germany); Badalov, H.; Huseynov, S. [Technische Univ. Clausthal, Clausthal-Zellerfeld (Germany). ITE; Trick, M. [SPT Group, Calgary, AB (Canada)

2013-08-01

Optimization of oil and gas field production systems poses a great challenge to field development due to complex and multiple interactions between various operational design parameters and subsurface uncertainties. Conventional analytical methods are capable of finding local optima based on single deterministic models. They are less applicable for efficiently generating alternative design scenarios in a multi-objective context. Practical implementations of robust optimization workflows integrate the evaluation of alternative design scenarios and multiple realizations of subsurface uncertainty descriptions. Production or economic performance indicators such as NPV (Net Present Value) are linked to a risk-weighted objective function definition to guide the optimization processes. This work focuses on an integrated workflow using a reservoir-network simulator coupled to an optimization framework. The work will investigate the impact of design parameters while considering the physics of the reservoir, wells, and surface facilities. Subsurface uncertainties are described by well parameters such as inflow performance. Experimental design methods are used to investigate parameter sensitivities and interactions. Optimization methods are used to find optimal design parameter combinations which improve key performance indicators of the production network system. The proposed workflow will be applied to a representative oil reservoir coupled to a network which is modelled by an integrated reservoir-network simulator. Gas-lift will be included as an explicit measure to improve production. An objective function will be formulated for the net present value of the integrated system including production revenue and facility costs. Facility and gas lift design parameters are tuned to maximize NPV. Well inflow performance uncertainties are introduced with an impact on gas lift performance. Resulting variances on NPV are identified as a risk measure for the optimized system design. A

Biochemical and Haematological Blood Parameters at Different Stages of Lactation in Cows

Directory of Open Access Journals (Sweden)

Cristian Ovidiu COROIAN

2017-05-01

Full Text Available The health status of cows is evaluated and depending on haematological and biochemical profile of blood. Nutrition is the main technological factor that can produce profound changes in the metabolic profile in animals (Dhiman et al., 1991; Khaled et al., 1999; Ingvartsen, 2006. Blood parameters analyze can lead to identify if there are errors in nutrition of lactating cows (Payne et al., 1970. The aim of this study was the evaluation of metabolic and biochemical changes that occur during colostrum period and in terms of number of lactations in cows. The biological material was represented by a total of 60 heads of dairy cows from a family farm from Sălaj County, Romania. The cows are all from Holstein breed and presented no clinical signs of any specific pathology. Blood samples were collected from the jugular vein of each cow and analyzed. 10 individuals from each of the six lactations have been randomly selected. Haematological and biochemical parameters showed variations depending on factors analyzed here. In lactation 1 Hb was 7.55±3.05 (g/dl, while in lactation 6 the value was 12.5±2.10 (g/dl. RBC ranged as follows: in lactation 1 - 28.50±2.05 and in lactation 6 - 30.02±2.05. Lymphocytes varied within very wide limits under the influence of lactation: in lactation 1 - 2.8±1.56 and in lactation 6 - 7.55±1.80. The number of lactations and lactation rank have influenced blood biochemical and hematological parameters in dairy cows. Biochemical parameters are influenced by post-partum day, showing the lowest values in the early days of colostral period and the highest in the last few days of the same period.

Information transmission in genetic regulatory networks: a review

International Nuclear Information System (INIS)

Tkacik, Gasper; Walczak, Aleksandra M

2011-01-01

Genetic regulatory networks enable cells to respond to changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits has deepened our understanding of what kinds of computations genetic regulatory networks can perform, and with what reliability. These advances have motivated researchers to look for connections between the architecture and function of genetic regulatory networks. Transmitting information between a network's inputs and outputs has been proposed as one such possible measure of function, relevant in certain biological contexts. Here we summarize recent developments in the application of information theory to gene regulatory networks. We first review basic concepts in information theory necessary for understanding recent work. We then discuss the functional complexity of gene regulation, which arises from the molecular nature of the regulatory interactions. We end by reviewing some experiments that support the view that genetic networks responsible for early development of multicellular organisms might be maximizing transmitted 'positional information'. (topical review)

Dopamine D1 signaling organizes network dynamics underlying working memory.

Science.gov (United States)

Roffman, Joshua L; Tanner, Alexandra S; Eryilmaz, Hamdi; Rodriguez-Thompson, Anais; Silverstein, Noah J; Ho, New Fei; Nitenson, Adam Z; Chonde, Daniel B; Greve, Douglas N; Abi-Dargham, Anissa; Buckner, Randy L; Manoach, Dara S; Rosen, Bruce R; Hooker, Jacob M; Catana, Ciprian

2016-06-01

Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography-magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory-emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits.

Biochemical Disincentives to Fertilizing Cellulosic Ethanol Crops

Science.gov (United States)

Gallagher, M. E.; Hockaday, W. C.; Snapp, S.; McSwiney, C.; Baldock, J.

2010-12-01

Corn grain biofuel crops produce the highest yields when the cropping ecosystem is not nitrogen (N)-limited, achieved by application of fertilizer. There are environmental consequences for excessive fertilizer application to crops, including greenhouse gas emissions, hypoxic “dead zones,” and health problems from N runoff into groundwater. The increase in corn acreage in response to demand for alternative fuels (i.e. ethanol) could exacerbate these problems, and divert food supplies to fuel production. A potential substitute for grain ethanol that could reduce some of these impacts is cellulosic ethanol. Cellulosic ethanol feedstocks include grasses (switchgrass), hardwoods, and crop residues (e.g. corn stover, wheat straw). It has been assumed that these feedstocks will require similar N fertilization rates to grain biofuel crops to maximize yields, but carbohydrate yield versus N application has not previously been monitored. We report the biochemical stocks (carbohydrate, protein, and lignin in Mg ha-1) of a corn ecosystem grown under varying N levels. We measured biochemical yield in Mg ha-1 within the grain, leaf and stem, and reproductive parts of corn plants grown at seven N fertilization rates (0-202 kg N ha-1), to evaluate the quantity and quality of these feedstocks across a N fertilization gradient. The N fertilization rate study was performed at the Kellogg Biological Station-Long Term Ecological Research Site (KBS-LTER) in Michigan. Biochemical stocks were measured using 13C nuclear magnetic resonance spectroscopy (NMR), combined with a molecular mixing model (Baldock et al. 2004). Carbohydrate and lignin are the main biochemicals of interest in ethanol production since carbohydrate is the ethanol feedstock, and lignin hinders the carbohydrate to ethanol conversion process. We show that corn residue carbohydrate yields respond only weakly to N fertilization compared to grain. Grain carbohydrate yields plateau in response to fertilization at

Biochemical basis for the action of radioprotective drugs

International Nuclear Information System (INIS)

Romantsev, E.F.; Blokhina, V.D.; Zhulanova, Z.I.; Koshcheenko, N.N.; Filippovich, I.V.

1977-01-01

The hypothesis of complex biochemical mechanism of action of radioprotective drugs is described. Shortly after injection of radioprotective aminothiols into animals the inhibition of radiosensitive biochemical processes: DNA and RNA synthesis, protein synthesis and oxidative phosphorylation has been observed. The molecular mechanism of these phenomena consists of radioprotectors ability to form adsorption, thioester, amide, and disulphide bonds with appropriate enzymes. The curve reflecting the formation and breakdown of mixed disulphides between radioprotectors and proteins coincides well with that reflecting the radioprotective effect dependence on time. The radiobiological significance of molecular interactions observed may be interpreted as the diminution in ''spoiled'' molecules formation (inhibition of replication) and elevation in repartion rate. The inhibition of biochemical processes has the reversible nature and last for short time. The drugs acting according to so-called oxygen effect protect also by means of biochemical mechanisms. The molecular mechanism is mediated through their ability to bind to receptors, and biologically important molecules and macromolecules. As a result the inhibition of radiosensitive processes occurs, the ''spoiled'' molecules number is diminished and reparation takes place more easily. The idea on the complex biochemical mechanism of action of radioprotectors correlates with the proposal on complex biochemical mechanism responsible for interphase death occured after irradiation

Video interpretability rating scale under network impairments

Science.gov (United States)

Kreitmair, Thomas; Coman, Cristian

2014-01-01

This paper presents the results of a study of the impact of network transmission channel parameters on the quality of streaming video data. A common practice for estimating the interpretability of video information is to use the Motion Imagery Quality Equation (MIQE). MIQE combines a few technical features of video images (such as: ground sampling distance, relative edge response, modulation transfer function, gain and signal-to-noise ratio) to estimate the interpretability level. One observation of this study is that the MIQE does not fully account for video-specific parameters such as spatial and temporal encoding, which are relevant to appreciating degradations caused by the streaming process. In streaming applications the main artifacts impacting the interpretability level are related to distortions in the image caused by lossy decompression of video data (due to loss of information and in some cases lossy re-encoding by the streaming server). One parameter in MIQE that is influenced by network transmission errors is the Relative Edge Response (RER). The automated calculation of RER includes the selection of the best edge in the frame, which in case of network errors may be incorrectly associated with a blocked region (e.g. low resolution areas caused by loss of information). A solution is discussed in this document to address this inconsistency by removing corrupted regions from the image analysis process. Furthermore, a recommendation is made on how to account for network impairments in the MIQE, such that a more realistic interpretability level is estimated in case of streaming applications.

Biochemical reactions of the organism

International Nuclear Information System (INIS)

Fedorova, A.V.

1984-01-01

Effects of mercury, strontium chloride, GMDA, trichlorfon as well as some radionuclides ( 89 Sr, 137 Cs, 203 Hg) were studied on rats. Changes in biochemical parameters (histamine content, activity of cholinesterase and histaminase) are noted. Most noticeable changes were observed in enzymatic activity. Distortion of enzymatic systems and accumulation of intermediate exchange and decay products of tissues in excess quantities affecting other systems can be the reason for changes in the organism. The observed changes in biochemical parameters should be necessarily taken into account at hygienic regulations of harmful effects of enviroment

Physiological, Biochemical, Epigenetic and Molecular Analyses of Wheat (Triticum aestivum Genotypes with Contrasting Salt Tolerance

Directory of Open Access Journals (Sweden)

Suresh Kumar

2017-06-01

Full Text Available Abiotic stress exerts significant impact on plant’s growth, development, and productivity. Productivity of crop plants under salt stress is lagging behind because of our limited knowledge about physiological, biochemical, epigenetic, and molecular mechanisms of salt tolerance in plants. This study aimed to investigate physio-biochemical, molecular indices and defense responses of selected wheat cultivars to identify the most contrasting salt-responsive genotypes and the mechanisms associated with their differential responses. Physio-biochemical traits specifically membrane stability index, antioxidant potential, osmoprotectants and chlorophyll contents, measured at vegetative stage, were used for multivariate analysis to identify the most contrasting genotypes. Genetic and epigenetic analyses indicated the possible mechanisms associated with differential response of the wheat genotypes under salt stress. Better antioxidant potential, membrane stability, increased accumulation of osmolytes/phytophenolics, and higher K+/Na+ ratio under 200 mM NaCl stress identified Kharchia-65 to be the most salt-tolerant cultivar. By contrast, increased MDA level, reduced soluble sugar, proline, total chlorophyll, total phenolics contents, and lower antioxidant potential in HD-2329 marked it to be sensitive to the stress. Genetic and bioinformatics analyses of HKT1;4 of contrasting genotypes (Kharchia-65 and HD-2329 revealed deletions, transitions, and transversions resulting into altered structure, loss of conserved motifs (Ser-Gly-Gly-Gly and Gly-Arg and function in salt-sensitive (HD-2329 genotype. Expression analysis of HKTs rationalized the observed responses. Epigenetic variations in cytosine methylation explained tissue- and genotype-specific differential expression of HKT2;1 and HKT2;3.

Biochemically enhanced methane production from coal

Science.gov (United States)

Opara, Aleksandra

For many years, biogas was connected mostly with the organic matter decomposition in shallow sediments (e.g., wetlands, landfill gas, etc.). Recently, it has been realized that biogenic methane production is ongoing in many hydrocarbon reservoirs. This research examined microbial methane and carbon dioxide generation from coal. As original contributions methane production from various coal materials was examined in classical and electro-biochemical bench-scale reactors using unique, developed facultative microbial consortia that generate methane under anaerobic conditions. Facultative methanogenic populations are important as all known methanogens are strict anaerobes and their application outside laboratory would be problematic. Additional testing examined the influence of environmental conditions, such as pH, salinity, and nutrient amendments on methane and carbon dioxide generation. In 44-day ex-situ bench-scale batch bioreactor tests, up to 300,000 and 250,000 ppm methane was generated from bituminous coal and bituminous coal waste respectively, a significant improvement over 20-40 ppm methane generated from control samples. Chemical degradation of complex hydrocarbons using environmentally benign reagents, prior to microbial biodegradation and methanogenesis, resulted in dissolution of up to 5% bituminous coal and bituminous coal waste and up to 25% lignite in samples tested. Research results confirm that coal waste may be a significant underutilized resource that could be converted to useful fuel. Rapid acidification of lignite samples resulted in low pH (below 4.0), regardless of chemical pretreatment applied, and did not generate significant methane amounts. These results confirmed the importance of monitoring and adjusting in situ and ex situ environmental conditions during methane production. A patented Electro-Biochemical Reactor technology was used to supply electrons and electron acceptor environments, but appeared to influence methane generation in a

An agent-based signal processing in-node environment for real-time human activity monitoring based on wireless body sensor networks

NARCIS (Netherlands)

Aiello, F.; Bellifemine, F.L.; Fortino, G.; Galzarano, S.; Gravina, R.

2011-01-01

Nowadays wireless body sensor networks (WBSNs) have great potential to enable a broad variety of assisted living applications such as human biophysical/biochemical control and activity monitoring for health care, e-fitness, emergency detection, emotional recognition for social networking, security,

Diamond network: template-free fabrication and properties.

Science.gov (United States)

Zhuang, Hao; Yang, Nianjun; Fu, Haiyuan; Zhang, Lei; Wang, Chun; Huang, Nan; Jiang, Xin

2015-03-11

A porous diamond network with three-dimensionally interconnected pores is of technical importance but difficult to be produced. In this contribution, we demonstrate a simple, controllable, and "template-free" approach to fabricate diamond networks. It combines the deposition of diamond/β-SiC nanocomposite film with a wet-chemical selective etching of the β-SiC phase. The porosity of these networks was tuned from 15 to 68%, determined by the ratio of the β-SiC phase in the composite films. The electrochemical working potential and the reactivity of redox probes on the diamond networks are similar to those of a flat nanocrystalline diamond film, while their surface areas are hundreds of times larger than that of a flat diamond film (e.g., 490-fold enhancement for a 3 μm thick diamond network). The marriage of the unprecedented physical/chemical features of diamond with inherent advantages of the porous structure makes the diamond network a potential candidate for various applications such as water treatment, energy conversion (batteries or fuel cells), and storage (capacitors), as well as electrochemical and biochemical sensing.

Memory networks supporting retrieval effort and retrieval success under conditions of full and divided attention.

Science.gov (United States)

Skinner, Erin I; Fernandes, Myra A; Grady, Cheryl L

2009-01-01

We used a multivariate analysis technique, partial least squares (PLS), to identify distributed patterns of brain activity associated with retrieval effort and retrieval success. Participants performed a recognition memory task under full attention (FA) or two different divided attention (DA) conditions during retrieval. Behaviorally, recognition was disrupted when a word, but not digit-based distracting task, was performed concurrently with retrieval. PLS was used to identify patterns of brain activation that together covaried with the three memory conditions and which were functionally connected with activity in the right hippocampus to produce successful memory performance. Results indicate that activity in the right dorsolateral frontal cortex increases during conditions of DA at retrieval, and that successful memory performance in the DA-digit condition is associated with activation of the same network of brain regions functionally connected to the right hippocampus, as under FA, which increases with increasing memory performance. Finally, DA conditions that disrupt successful memory performance (DA-word) interfere with recruitment of both retrieval-effort and retrieval-success networks.

Prevalence of biochemical and immunological abnormalities in ...

African Journals Online (AJOL)

Tile prevalence of biochemical and immunological abnormalities was studied in a group of 256 patients with rheumatoid arthritis (104 coloureds, 100 whites and 52 blacks). The most common biochemical abnormalities detected were a reduction in the serum creatinine value (43,4%), raised globulins (39,7%), raised serum ...

[Biochemical diagnostics of fatal opium intoxication].

Science.gov (United States)

Papyshev, I P; Astashkina, O G; Tuchik, E S; Nikolaev, B S; Cherniaev, A L

2013-01-01

Biochemical diagnostics of fatal opium intoxication remains a topical problem in forensic medical science and practice. We investigated materials obtained in the course of forensic medical expertise of the cases of fatal opium intoxication. The study revealed significant differences between myoglobin levels in blood, urine, myocardium, and skeletal muscles. The proposed approach to biochemical diagnostics of fatal opium intoxication enhances the accuracy and the level of evidence of expert conclusions.

Hypothalamus-Related Resting Brain Network Underlying Short-Term Acupuncture Treatment in Primary Hypertension

Directory of Open Access Journals (Sweden)

Hongyan Chen

2013-01-01

Full Text Available The present study attempted to explore modulated hypothalamus-seeded resting brain network underlying the cardiovascular system in primary hypertensive patients after short-term acupuncture treatment. Thirty right-handed patients (14 male were divided randomly into acupuncture and control groups. The acupuncture group received a continuous five-day acupuncture treatment and undertook three resting-state fMRI scans and 24-hour ambulatory blood pressure monitoring (ABPM as well as SF-36 questionnaires before, after, and one month after acupuncture treatment. The control group undertook fMRI scans and 24-hour ABPM. For verum acupuncture, average blood pressure (BP and heart rate (HR decreased after treatment but showed no statistical differences. There were no significant differences in BP and HR between the acupuncture and control groups. Notably, SF-36 indicated that bodily pain (P = 0.005 decreased and vitality (P = 0.036 increased after acupuncture compared to the baseline. The hypothalamus-related brain network showed increased functional connectivity with the medulla, brainstem, cerebellum, limbic system, thalamus, and frontal lobes. In conclusion, short-term acupuncture did not decrease BP significantly but appeared to improve body pain and vitality. Acupuncture may regulate the cardiovascular system through a complicated brain network from the cortical level, the hypothalamus, and the brainstem.

Determinants of investment under incentive regulation: The case of the Norwegian electricity distribution networks

International Nuclear Information System (INIS)

Poudineh, Rahmatallah; Jamasb, Tooraj

2016-01-01

Investment in electricity networks, as regulated natural monopolies, is among the highest regulatory and energy policy priorities. The electricity sector regulators adopt different incentive mechanisms to ensure that the firms undertake sufficient investment to maintain and modernise the grid. Thus, an effective regulatory treatment of investment requires understanding the response of companies to the regulatory incentives. This study analyses the determinants of investment in electricity distribution networks using a panel dataset of 129 Norwegian companies observed from 2004 to 2010. A Bayesian Model Averaging approach is used to provide a robust statistical inference by taking into account the uncertainties around model selection and estimation. The results show that three factors drive nearly all network investments: investment rate in previous period, socio-economic costs of energy not supplied and finally useful life of assets. The results indicate that Norwegian companies have, to some degree, responded to the investment incentives provided by the regulatory framework. However, some of the incentives do not appear to be effective in driving the investments. - Highlights: • This paper investigates determinants of investment under incentive regulation. • We apply a Bayesian model averaging technique to deal with model uncertainty. • Dataset comprises 129 Norwegian electricity network companies from 2004 to 2010. • The results show that firms have generally responded to investment incentives. • However, some of the incentives do not appear to have been effective.

Simulation and Statistical Inference of Stochastic Reaction Networks with Applications to Epidemic Models

KAUST Repository

Moraes, Alvaro

2015-01-01

Networks (SRNs), that are intended to describe the time evolution of interacting particle systems where one particle interacts with the others through a finite set of reaction channels. SRNs have been mainly developed to model biochemical reactions

Wireless Powered Relaying Networks Under Imperfect Channel State Information: System Performance and Optimal Policy for Instantaneous Rate

Directory of Open Access Journals (Sweden)

D. T. Do

2017-09-01

Full Text Available In this investigation, we consider wireless powered relaying systems, where energy is scavenged by a relay via radio frequency (RF signals. We explore hybrid time switching-based and power splitting-based relaying protocol (HTPSR and compare performance of Amplify-and-Forward (AF with Decode-and-Forward (DF scheme under imperfect channel state information (CSI. Most importantly, the instantaneous rate, achievable bit error rate (BER are determined in the closed-form expressions under the impact of imperfect CSI. Through numerical analysis, we evaluate system insights via different parameters such as power splitting (PS and time switching (TS ratio of the considered HTPSR which affect outage performance and BER. It is noted that DF relaying networks outperform AF relaying networks. Besides that, the numerical results are given to prove the optimization problems of PS and TS ratio to obtain optimal instantaneous rate.

Modulation of attention network activation under antidepressant agents in healthy subjects.

Science.gov (United States)

Graf, Heiko; Abler, Birgit; Hartmann, Antonie; Metzger, Coraline D; Walter, Martin

2013-07-01

While antidepressants are supposed to exert similar effects on mood and drive via various mechanisms of action, diverging effects are observed regarding side-effects and accordingly on neural correlates of motivation, emotion, reward and salient stimuli processing as a function of the drugs impact on neurotransmission. In the context of erotic stimulation, a unidirectional modulation of attentional functioning despite opposite effects on sexual arousal has been suggested for the selective serotonin reuptake-inhibitor (SSRI) paroxetine and the selective dopamine and noradrenaline reuptake-inhibitor (SDNRI) bupropion. To further elucidate the effects of antidepressant-related alterations of neural attention networks, we investigated 18 healthy males under subchronic administration (7 d) of paroxetine (20 mg), bupropion (150 mg) and placebo within a randomized placebo-controlled cross-over double-blind functional magnetic resonance imaging (fMRI) design during an established preceding attention task. Neuropsychological effects beyond the fMRI-paradigm were assessed by measuring alertness and divided attention. Comparing preceding attention periods of salient vs. neutral pictures, we revealed congruent effects of both drugs vs. placebo within the anterior midcingulate cortex, dorsolateral prefrontal cortex, anterior prefrontal cortex, superior temporal gyrus, anterior insula and the thalamus. Relatively decreased activation in this network was paralleled by slower reaction times in the divided attention task in both verum conditions compared to placebo. Our results suggest similar effects of antidepressant treatments on behavioural and neural attentional functioning by diverging neurochemical pathways. Concurrent alterations of brain regions within a fronto-parietal and cingulo-opercular attention network for top-down control could point to basic neural mechanisms of antidepressant action irrespective of receptor profiles.

Gaussian process regression for sensor networks under localization uncertainty

Science.gov (United States)

Jadaliha, M.; Xu, Yunfei; Choi, Jongeun; Johnson, N.S.; Li, Weiming

2013-01-01

In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.

Under-Frequency Load Shedding Technique Considering Event-Based for an Islanded Distribution Network

Directory of Open Access Journals (Sweden)

Hasmaini Mohamad

2016-06-01

Full Text Available One of the biggest challenge for an islanding operation is to sustain the frequency stability. A large power imbalance following islanding would cause under-frequency, hence an appropriate control is required to shed certain amount of load. The main objective of this research is to develop an adaptive under-frequency load shedding (UFLS technique for an islanding system. The technique is designed considering an event-based which includes the moment system is islanded and a tripping of any DG unit during islanding operation. A disturbance magnitude is calculated to determine the amount of load to be shed. The technique is modeled by using PSCAD simulation tool. A simulation studies on a distribution network with mini hydro generation is carried out to evaluate the UFLS model. It is performed under different load condition: peak and base load. Results show that the load shedding technique have successfully shed certain amount of load and stabilized the system frequency.

Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

Science.gov (United States)

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

Biochemical Responses of Peach Leaves Infected with Taphrina Deformans Berk/Tul.

Directory of Open Access Journals (Sweden)

Lyubka Koleva-Valkova

2017-01-01

Full Text Available The phytopathogenic fungus Taphrina deformans causing the so called “leaf curl disease” in peach trees leads to severe yield losses due to the development of leaf hypertrophy and subsequent necrosis and scission. Because of its economic importance, the molecular mechanisms underlying the onset and progression of the disease are of considerable interest to the agricultural science. In this study various biochemical parameters, including the activities of the antioxidant enzymes guaiacol peroxidase, syringaldazine peroxidase and catalase, total polyphenols and anthocyanin content, concentration of free proline, antiradical activity and quantity of plastid pigments, were characterized. All these were measured in both leaves with clear symptoms and distally situated leaves from the same plant that show no signs of the infection. The results demonstrate that the pathogen induces considerable biochemical changes concerning enzymatic and non‑enzymatic elements of the plant defense and antioxidant systems. Moreover, it seems that the fungus provokes a systemic response detectable even in the tissues without observable symptoms.

COMPONENT SUPPLY MODEL FOR REPAIR ACTIVITIES NETWORK UNDER CONDITIONS OF PROBABILISTIC INDEFINITENESS.

Directory of Open Access Journals (Sweden)

Victor Yurievich Stroganov

2017-02-01

Full Text Available This article contains the systematization of the major production functions of repair activities network and the list of planning and control functions, which are described in the form of business processes (BP. Simulation model for analysis of the delivery effectiveness of components under conditions of probabilistic uncertainty was proposed. It has been shown that a significant portion of the total number of business processes is represented by the management and planning of the parts and components movement. Questions of construction of experimental design techniques on the simulation model in the conditions of non-stationarity were considered.

Two-terminal reliability of a mobile ad hoc network under the asymptotic spatial distribution of the random waypoint model

International Nuclear Information System (INIS)

Chen, Binchao; Phillips, Aaron; Matis, Timothy I.

2012-01-01

The random waypoint (RWP) mobility model is frequently used in describing the movement pattern of mobile users in a mobile ad hoc network (MANET). As the asymptotic spatial distribution of nodes under a RWP model exhibits central tendency, the two-terminal reliability of the MANET is investigated as a function of the source node location. In particular, analytical expressions for one and two hop connectivities are developed as well as an efficient simulation methodology for two-terminal reliability. A study is then performed to assess the effect of nodal density and network topology on network reliability.

Biochemical and toxicological studies of aqueous extract of ...

African Journals Online (AJOL)

Biochemical and toxicological studies of aqueous extract of Syzigium ... tract diseases and also used as food spices), on some biochemical indices, such as ... liver functions and blood parameters were studied in adult albino rats of both sexes.

Dynamical Response of Networks Under External Perturbations: Exact Results

Science.gov (United States)

Chinellato, David D.; Epstein, Irving R.; Braha, Dan; Bar-Yam, Yaneer; de Aguiar, Marcus A. M.

2015-04-01

We give exact statistical distributions for the dynamic response of influence networks subjected to external perturbations. We consider networks whose nodes have two internal states labeled 0 and 1. We let nodes be frozen in state 0, in state 1, and the remaining nodes change by adopting the state of a connected node with a fixed probability per time step. The frozen nodes can be interpreted as external perturbations to the subnetwork of free nodes. Analytically extending and to be smaller than 1 enables modeling the case of weak coupling. We solve the dynamical equations exactly for fully connected networks, obtaining the equilibrium distribution, transition probabilities between any two states and the characteristic time to equilibration. Our exact results are excellent approximations for other topologies, including random, regular lattice, scale-free and small world networks, when the numbers of fixed nodes are adjusted to take account of the effect of topology on coupling to the environment. This model can describe a variety of complex systems, from magnetic spins to social networks to population genetics, and was recently applied as a framework for early warning signals for real-world self-organized economic market crises.

eQuilibrator--the biochemical thermodynamics calculator.

Science.gov (United States)

Flamholz, Avi; Noor, Elad; Bar-Even, Arren; Milo, Ron

2012-01-01

The laws of thermodynamics constrain the action of biochemical systems. However, thermodynamic data on biochemical compounds can be difficult to find and is cumbersome to perform calculations with manually. Even simple thermodynamic questions like 'how much Gibbs energy is released by ATP hydrolysis at pH 5?' are complicated excessively by the search for accurate data. To address this problem, eQuilibrator couples a comprehensive and accurate database of thermodynamic properties of biochemical compounds and reactions with a simple and powerful online search and calculation interface. The web interface to eQuilibrator (http://equilibrator.weizmann.ac.il) enables easy calculation of Gibbs energies of compounds and reactions given arbitrary pH, ionic strength and metabolite concentrations. The eQuilibrator code is open-source and all thermodynamic source data are freely downloadable in standard formats. Here we describe the database characteristics and implementation and demonstrate its use.

eQuilibrator—the biochemical thermodynamics calculator

Science.gov (United States)

Flamholz, Avi; Noor, Elad; Bar-Even, Arren; Milo, Ron

2012-01-01

The laws of thermodynamics constrain the action of biochemical systems. However, thermodynamic data on biochemical compounds can be difficult to find and is cumbersome to perform calculations with manually. Even simple thermodynamic questions like ‘how much Gibbs energy is released by ATP hydrolysis at pH 5?’ are complicated excessively by the search for accurate data. To address this problem, eQuilibrator couples a comprehensive and accurate database of thermodynamic properties of biochemical compounds and reactions with a simple and powerful online search and calculation interface. The web interface to eQuilibrator (http://equilibrator.weizmann.ac.il) enables easy calculation of Gibbs energies of compounds and reactions given arbitrary pH, ionic strength and metabolite concentrations. The eQuilibrator code is open-source and all thermodynamic source data are freely downloadable in standard formats. Here we describe the database characteristics and implementation and demonstrate its use. PMID:22064852

The Glymphatic Hypothesis of Glaucoma : A Unifying Concept Incorporating Vascular, Biomechanical, and Biochemical Aspects of the Disease

NARCIS (Netherlands)

Wostyn, Peter; De Groot, Veva; Van Dam, Debby; Audenaert, Kurt; Killer, Hanspeter Esriel; De Deyn, Peter Paul

2017-01-01

The pathophysiology of primary open-angle glaucoma is still largely unknown, although a joint contribution of vascular, biomechanical, and biochemical factors is widely acknowledged. Since glaucoma is a leading cause of irreversible blindness worldwide, exploring its underlying pathophysiological

Intrinsic noise analyzer: a software package for the exploration of stochastic biochemical kinetics using the system size expansion.

Science.gov (United States)

Thomas, Philipp; Matuschek, Hannes; Grima, Ramon

2012-01-01

The accepted stochastic descriptions of biochemical dynamics under well-mixed conditions are given by the Chemical Master Equation and the Stochastic Simulation Algorithm, which are equivalent. The latter is a Monte-Carlo method, which, despite enjoying broad availability in a large number of existing software packages, is computationally expensive due to the huge amounts of ensemble averaging required for obtaining accurate statistical information. The former is a set of coupled differential-difference equations for the probability of the system being in any one of the possible mesoscopic states; these equations are typically computationally intractable because of the inherently large state space. Here we introduce the software package intrinsic Noise Analyzer (iNA), which allows for systematic analysis of stochastic biochemical kinetics by means of van Kampen's system size expansion of the Chemical Master Equation. iNA is platform independent and supports the popular SBML format natively. The present implementation is the first to adopt a complementary approach that combines state-of-the-art analysis tools using the computer algebra system Ginac with traditional methods of stochastic simulation. iNA integrates two approximation methods based on the system size expansion, the Linear Noise Approximation and effective mesoscopic rate equations, which to-date have not been available to non-expert users, into an easy-to-use graphical user interface. In particular, the present methods allow for quick approximate analysis of time-dependent mean concentrations, variances, covariances and correlations coefficients, which typically outperforms stochastic simulations. These analytical tools are complemented by automated multi-core stochastic simulations with direct statistical evaluation and visualization. We showcase iNA's performance by using it to explore the stochastic properties of cooperative and non-cooperative enzyme kinetics and a gene network associated with

Intrinsic noise analyzer: a software package for the exploration of stochastic biochemical kinetics using the system size expansion.

Directory of Open Access Journals (Sweden)

Philipp Thomas

Full Text Available The accepted stochastic descriptions of biochemical dynamics under well-mixed conditions are given by the Chemical Master Equation and the Stochastic Simulation Algorithm, which are equivalent. The latter is a Monte-Carlo method, which, despite enjoying broad availability in a large number of existing software packages, is computationally expensive due to the huge amounts of ensemble averaging required for obtaining accurate statistical information. The former is a set of coupled differential-difference equations for the probability of the system being in any one of the possible mesoscopic states; these equations are typically computationally intractable because of the inherently large state space. Here we introduce the software package intrinsic Noise Analyzer (iNA, which allows for systematic analysis of stochastic biochemical kinetics by means of van Kampen's system size expansion of the Chemical Master Equation. iNA is platform independent and supports the popular SBML format natively. The present implementation is the first to adopt a complementary approach that combines state-of-the-art analysis tools using the computer algebra system Ginac with traditional methods of stochastic simulation. iNA integrates two approximation methods based on the system size expansion, the Linear Noise Approximation and effective mesoscopic rate equations, which to-date have not been available to non-expert users, into an easy-to-use graphical user interface. In particular, the present methods allow for quick approximate analysis of time-dependent mean concentrations, variances, covariances and correlations coefficients, which typically outperforms stochastic simulations. These analytical tools are complemented by automated multi-core stochastic simulations with direct statistical evaluation and visualization. We showcase iNA's performance by using it to explore the stochastic properties of cooperative and non-cooperative enzyme kinetics and a gene network

Intrinsic Noise Analyzer: A Software Package for the Exploration of Stochastic Biochemical Kinetics Using the System Size Expansion

Science.gov (United States)

Grima, Ramon

2012-01-01

The accepted stochastic descriptions of biochemical dynamics under well-mixed conditions are given by the Chemical Master Equation and the Stochastic Simulation Algorithm, which are equivalent. The latter is a Monte-Carlo method, which, despite enjoying broad availability in a large number of existing software packages, is computationally expensive due to the huge amounts of ensemble averaging required for obtaining accurate statistical information. The former is a set of coupled differential-difference equations for the probability of the system being in any one of the possible mesoscopic states; these equations are typically computationally intractable because of the inherently large state space. Here we introduce the software package intrinsic Noise Analyzer (iNA), which allows for systematic analysis of stochastic biochemical kinetics by means of van Kampen’s system size expansion of the Chemical Master Equation. iNA is platform independent and supports the popular SBML format natively. The present implementation is the first to adopt a complementary approach that combines state-of-the-art analysis tools using the computer algebra system Ginac with traditional methods of stochastic simulation. iNA integrates two approximation methods based on the system size expansion, the Linear Noise Approximation and effective mesoscopic rate equations, which to-date have not been available to non-expert users, into an easy-to-use graphical user interface. In particular, the present methods allow for quick approximate analysis of time-dependent mean concentrations, variances, covariances and correlations coefficients, which typically outperforms stochastic simulations. These analytical tools are complemented by automated multi-core stochastic simulations with direct statistical evaluation and visualization. We showcase iNA’s performance by using it to explore the stochastic properties of cooperative and non-cooperative enzyme kinetics and a gene network associated with

Dynamics in steady state in vitro acto-myosin networks

International Nuclear Information System (INIS)

Sonn-Segev, Adar; Roichman, Yael; Bernheim-Groswasser, Anne

2017-01-01

It is well known that many biochemical processes in the cell such as gene regulation, growth signals and activation of ion channels, rely on mechanical stimuli. However, the mechanism by which mechanical signals propagate through cells is not as well understood. In this review we focus on stress propagation in a minimal model for cell elasticity, actomyosin networks, which are comprised of a sub-family of cytoskeleton proteins. After giving an overview of th actomyosin network components, structure and evolution we review stress propagation in these materials as measured through the correlated motion of tracer beads. We also discuss the possibility to extract structural features of these networks from the same experiments. We show that stress transmission through these networks has two pathways, a quickly dissipative one through the bulk, and a long ranged weakly dissipative one through the pre-stressed actin network. (topical review)

[Food status peculiarities, anthropometric, clinica and biochemical indices at professional sportsmen].

Science.gov (United States)

Gapparova, K M; Nikitiuk, D B; Zaĭnudinov, Z M; Tserekh, A A; Chekhonina, Iu G; Golubeva, A A; Sil'vestrova, G A; Rusakova, D S; Grigor'ian, O N

2011-01-01

Under steady state conditions in 66 athletes involved in weightlifting, bodybuilding, judo and taekwondo have studied features of the metabolic status. Data on matter-of-fact nutrition, body weight content within the inter-competition period, energy exchange, clinical and biochemical indices and physical acceptability indices were analyzed. As a result, the decrease indexes of metabolism at all the sportsmen and high-level caloric value at sportsmen who are engaged in weightlifting, which corresponds their energy expenditures, was revealed.

Possible Biochemical Markers in Protein-Energy Malnutrition and ...

African Journals Online (AJOL)

This study was carried out to determine possible biochemical markers in children suffering from Plasmodium falciparum malaria and Protein-Energy Malnutrition in a Hospital setting in Western Kenya. Spectrophotometric assays of selected biochemical parameters namely, albumin, total proteins, glucose, glutamate ...

Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation

International Nuclear Information System (INIS)

Schachter, Jonathan A.; Mancarella, Pierluigi; Moriarty, John; Shaw, Rita

2016-01-01

Classical deterministic models applied to investment valuation in distribution networks may not be adequate for a range of real-world decision-making scenarios as they effectively ignore the uncertainty found in the most important variables driving network planning (e.g., load growth). As greater uncertainty is expected from growing distributed energy resources in distribution networks, there is an increasing risk of investing in too much or too little network capacity and hence causing the stranding and inefficient use of network assets; these costs are then passed on to the end-user. An alternative emerging solution in the context of smart grid development is to release untapped network capacity through Demand-Side Response (DSR). However, to date there is no approach able to quantify the value of ‘smart’ DSR solutions against ‘conventional’ asset-heavy investments. On these premises, this paper presents a general real options framework and a novel probabilistic tool for the economic assessment of DSR for smart distribution network planning under uncertainty, which allows the modeling and comparison of multiple investment strategies, including DSR and capacity reinforcements, based on different cost and risk metrics. In particular the model provides an explicit quantification of the economic value of DSR against alternative investment strategies. Through sensitivity analysis it is able to indicate the maximum price payable for DSR service such that DSR remains economically optimal against these alternatives. The proposed model thus provides Regulators with clear insights for overseeing DSR contractual arrangements. Further it highlights that differences exist in the economic perspective of the regulated DNO business and of customers. Our proposed model is therefore capable of highlighting instances where a particular investment strategy is favorable to the DNO but not to its customers, or vice-versa, and thus aspects of the regulatory framework which may

Possibilities and methods for biochemical assessment of radiation injury

Energy Technology Data Exchange (ETDEWEB)

Minkova, M [Meditsinska Akademiya, Sofia (Bulgaria). Nauchen Inst. po Rentgenologiya i Radiobiologiya

1986-01-01

An extensitive review (77 references) is made of the application of biochemical diagnostic methods for assessment of radiation diseases. A brief characteristics of several biochemical indicators is given: deoxycytidine, thymidine, rho-aminoisocarboxylic acid, DNA-ase, nucleic acids. Influence of such factors as age, sex, season etc. is studied by means of functional biochemical indicators as: creatine, triptophanic metabolites, 5-hydroxy-indolacetic acid, biogenic amines, serum proteins, enzymes, etc.

Brain networks underlying mental imagery of auditory and visual information.

Science.gov (United States)

Zvyagintsev, Mikhail; Clemens, Benjamin; Chechko, Natalya; Mathiak, Krystyna A; Sack, Alexander T; Mathiak, Klaus

2013-05-01

Mental imagery is a complex cognitive process that resembles the experience of perceiving an object when this object is not physically present to the senses. It has been shown that, depending on the sensory nature of the object, mental imagery also involves correspondent sensory neural mechanisms. However, it remains unclear which areas of the brain subserve supramodal imagery processes that are independent of the object modality, and which brain areas are involved in modality-specific imagery processes. Here, we conducted a functional magnetic resonance imaging study to reveal supramodal and modality-specific networks of mental imagery for auditory and visual information. A common supramodal brain network independent of imagery modality, two separate modality-specific networks for imagery of auditory and visual information, and a common deactivation network were identified. The supramodal network included brain areas related to attention, memory retrieval, motor preparation and semantic processing, as well as areas considered to be part of the default-mode network and multisensory integration areas. The modality-specific networks comprised brain areas involved in processing of respective modality-specific sensory information. Interestingly, we found that imagery of auditory information led to a relative deactivation within the modality-specific areas for visual imagery, and vice versa. In addition, mental imagery of both auditory and visual information widely suppressed the activity of primary sensory and motor areas, for example deactivation network. These findings have important implications for understanding the mechanisms that are involved in generation of mental imagery. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Haematological and blood biochemical indices of West African ...

African Journals Online (AJOL)

Haematological and blood biochemical indices of West African dwarf goats vaccinated against Pestes des petit ruminants (PPR) ... blood biochemical indices of forty randomly selected West African dwarf (WAD) goats were studied. Packed cell volume ... neutrophil/lymphocyte ratio and white blood cells (WBC) than females.

Robust synchronization analysis in nonlinear stochastic cellular networks with time-varying delays, intracellular perturbations and intercellular noise.

Science.gov (United States)

Chen, Po-Wei; Chen, Bor-Sen

2011-08-01

Naturally, a cellular network consisted of a large amount of interacting cells is complex. These cells have to be synchronized in order to emerge their phenomena for some biological purposes. However, the inherently stochastic intra and intercellular interactions are noisy and delayed from biochemical processes. In this study, a robust synchronization scheme is proposed for a nonlinear stochastic time-delay coupled cellular network (TdCCN) in spite of the time-varying process delay and intracellular parameter perturbations. Furthermore, a nonlinear stochastic noise filtering ability is also investigated for this synchronized TdCCN against stochastic intercellular and environmental disturbances. Since it is very difficult to solve a robust synchronization problem with the Hamilton-Jacobi inequality (HJI) matrix, a linear matrix inequality (LMI) is employed to solve this problem via the help of a global linearization method. Through this robust synchronization analysis, we can gain a more systemic insight into not only the robust synchronizability but also the noise filtering ability of TdCCN under time-varying process delays, intracellular perturbations and intercellular disturbances. The measures of robustness and noise filtering ability of a synchronized TdCCN have potential application to the designs of neuron transmitters, on-time mass production of biochemical molecules, and synthetic biology. Finally, a benchmark of robust synchronization design in Escherichia coli repressilators is given to confirm the effectiveness of the proposed methods. Copyright © 2011 Elsevier Inc. All rights reserved.

Definitions of biochemical failure in prostate cancer following radiation therapy

International Nuclear Information System (INIS)

Taylor, Jeremy M.G.; Griffith, Kent A.; Sandler, Howard M.

2001-01-01

Purpose: The American Society for Therapeutic Radiology and Oncology (ASTRO) published a consensus panel definition of biochemical failure following radiation therapy for prostate cancer. In this paper, we develop a series of alternative definitions of biochemical failure. Using data from 688 patients, we evaluated the sensitivity and specificity of the various definitions, with respect to a defined 'clinically meaningful' outcome. Methods and Materials: The ASTRO definition of biochemical failure requires 3 consecutive rises in prostate-specific antigen (PSA). We considered several modifications to the standard definition: to require PSA rises of a certain magnitude, to consider 2 instead of 3 rises, to require the final PSA value to be greater than a fixed cutoff level, and to define biochemical failure based on the slope of PSA over 1, 1.5, or 2 years. A clinically meaningful failure is defined as local recurrence, distant metastases, initiation of unplanned hormonal therapy, unplanned radical prostatectomy, or a PSA>25 later than 6 months after radiation. Results: Requiring the final PSA in a series of consecutive rises to be larger than 1.5 ng/mL increased the specificity of biochemical failure. For a fixed specificity, defining biochemical failure based on 2 consecutive rises, or the slope over the last year, could increase the sensitivity by up to approximately 20%, compared to the ASTRO definition. Using a rule based on the slope over the previous year or 2 rises leads to a slightly earlier detection of biochemical failure than does the ASTRO definition. Even with the best rule, only approximately 20% of true failures are biochemically detected more than 1 year before the clinically meaningful event time. Conclusion: There is potential for improvement in the ASTRO consensus definition of biochemical failure. Further research is needed, in studies with long follow-up times, to evaluate the relationship between various definitions of biochemical failure and

INTEGRATING GENETIC AND STRUCTURAL DATA ON HUMAN PROTEIN KINOME IN NETWORK-BASED MODELING OF KINASE SENSITIVITIES AND RESISTANCE TO TARGETED AND PERSONALIZED ANTICANCER DRUGS.

Science.gov (United States)

Verkhivker, Gennady M

2016-01-01

The human protein kinome presents one of the largest protein families that orchestrate functional processes in complex cellular networks, and when perturbed, can cause various cancers. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Coupled with the evolution of system biology approaches, genomic and proteomic technologies are rapidly identifying and charactering novel resistance mechanisms with the goal to inform rationale design of personalized kinase drugs. Integration of experimental and computational approaches can help to bring these data into a unified conceptual framework and develop robust models for predicting the clinical drug resistance. In the current study, we employ a battery of synergistic computational approaches that integrate genetic, evolutionary, biochemical, and structural data to characterize the effect of cancer mutations in protein kinases. We provide a detailed structural classification and analysis of genetic signatures associated with oncogenic mutations. By integrating genetic and structural data, we employ network modeling to dissect mechanisms of kinase drug sensitivities to oncogenic EGFR mutations. Using biophysical simulations and analysis of protein structure networks, we show that conformational-specific drug binding of Lapatinib may elicit resistant mutations in the EGFR kinase that are linked with the ligand-mediated changes in the residue interaction networks and global network properties of key residues that are responsible for structural stability of specific functional states. A strong network dependency on high centrality residues in the conformation-specific Lapatinib-EGFR complex may explain vulnerability of drug binding to a broad spectrum of mutations and the emergence of drug resistance. Our study offers a systems-based perspective on drug design by unravelling

Coverage-maximization in networks under resource constraints.

Science.gov (United States)

Nandi, Subrata; Brusch, Lutz; Deutsch, Andreas; Ganguly, Niloy

2010-06-01

Efficient coverage algorithms are essential for information search or dispersal in all kinds of networks. We define an extended coverage problem which accounts for constrained resources of consumed bandwidth B and time T . Our solution to the network challenge is here studied for regular grids only. Using methods from statistical mechanics, we develop a coverage algorithm with proliferating message packets and temporally modulated proliferation rate. The algorithm performs as efficiently as a single random walker but O(B(d-2)/d) times faster, resulting in significant service speed-up on a regular grid of dimension d . The algorithm is numerically compared to a class of generalized proliferating random walk strategies and on regular grids shown to perform best in terms of the product metric of speed and efficiency.

Biochemical systems identification by a random drift particle swarm optimization approach

Science.gov (United States)

2014-01-01

Background Finding an efficient method to solve the parameter estimation problem (inverse problem) for nonlinear biochemical dynamical systems could help promote the functional understanding at the system level for signalling pathways. The problem is stated as a data-driven nonlinear regression problem, which is converted into a nonlinear programming problem with many nonlinear differential and algebraic constraints. Due to the typical ill conditioning and multimodality nature of the problem, it is in general difficult for gradient-based local optimization methods to obtain satisfactory solutions. To surmount this limitation, many stochastic optimization methods have been employed to find the global solution of the problem. Results This paper presents an effective search strategy for a particle swarm optimization (PSO) algorithm that enhances the ability of the algorithm for estimating the parameters of complex dynamic biochemical pathways. The proposed algorithm is a new variant of random drift particle swarm optimization (RDPSO), which is used to solve the above mentioned inverse problem and compared with other well known stochastic optimization methods. Two case studies on estimating the parameters of two nonlinear biochemical dynamic models have been taken as benchmarks, under both the noise-free and noisy simulation data scenarios. Conclusions The experimental results show that the novel variant of RDPSO algorithm is able to successfully solve the problem and obtain solutions of better quality than other global optimization methods used for finding the solution to the inverse problems in this study. PMID:25078435

On library information resources construction under network environment

International Nuclear Information System (INIS)

Guo Huifang; Wang Jingjing

2014-01-01

Information resources construction is the primary task and critical measures for libraries. In the 2lst century, the knowledge economy era, with the continuous development of computer network technology, information resources have become an important part of libraries which have been a significant indicator of its capacity construction. The development of socialized Information, digitalization and internalization has put forward new requirements for library information resources construction. This paper describes the impact of network environment on construction of library information resources and proposes the measures of library information resources. (authors)

Advances in citric acid fermentation by Aspergillus niger: biochemical aspects, membrane transport and modeling.

Science.gov (United States)

Papagianni, Maria

2007-01-01

Citric acid is regarded as a metabolite of energy metabolism, of which the concentration will rise to appreciable amounts only under conditions of substantive metabolic imbalances. Citric acid fermentation conditions were established during the 1930s and 1940s, when the effects of various medium components were evaluated. The biochemical mechanism by which Aspergillus niger accumulates citric acid has continued to attract interest even though its commercial production by fermentation has been established for decades. Although extensive basic biochemical research has been carried out with A. niger, the understanding of the events relevant for citric acid accumulation is not completely understood. This review is focused on citric acid fermentation by A. niger. Emphasis is given to aspects of fermentation biochemistry, membrane transport in A. niger and modeling of the production process.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

Directory of Open Access Journals (Sweden)

Kim Hyun

2011-12-01

Full Text Available Abstract Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

Science.gov (United States)

Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

2011-01-01

Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

40 CFR 158.2080 - Experimental use permit data requirements-biochemical pesticides.

Science.gov (United States)

2010-07-01

... requirements-biochemical pesticides. 158.2080 Section 158.2080 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) PESTICIDE PROGRAMS DATA REQUIREMENTS FOR PESTICIDES Biochemical Pesticides § 158.2080 Experimental use permit data requirements—biochemical pesticides. (a) Sections 158.2081...

Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model

Science.gov (United States)

Vahdani, Behnam; Tavakkoli-Moghaddam, Reza; Jolai, Fariborz; Baboli, Arman

2013-06-01

This article seeks to offer a systematic approach to establishing a reliable network of facilities in closed loop supply chains (CLSCs) under uncertainties. Facilities that are located in this article concurrently satisfy both traditional objective functions and reliability considerations in CLSC network designs. To attack this problem, a novel mathematical model is developed that integrates the network design decisions in both forward and reverse supply chain networks. The model also utilizes an effective reliability approach to find a robust network design. In order to make the results of this article more realistic, a CLSC for a case study in the iron and steel industry has been explored. The considered CLSC is multi-echelon, multi-facility, multi-product and multi-supplier. Furthermore, multiple facilities exist in the reverse logistics network leading to high complexities. Since the collection centres play an important role in this network, the reliability concept of these facilities is taken into consideration. To solve the proposed model, a novel interactive hybrid solution methodology is developed by combining a number of efficient solution approaches from the recent literature. The proposed solution methodology is a bi-objective interval fuzzy possibilistic chance-constraint mixed integer linear programming (BOIFPCCMILP). Finally, computational experiments are provided to demonstrate the applicability and suitability of the proposed model in a supply chain environment and to help decision makers facilitate their analyses.

A bilateral frontoparietal network underlies visuospatial analogical reasoning.

Science.gov (United States)

Watson, Christine E; Chatterjee, Anjan

2012-02-01

Our ability to reason by analogy facilitates problem solving and allows us to communicate ideas efficiently. In this study, we examined the neural correlates of analogical reasoning and, more specifically, the contribution of rostrolateral prefrontal cortex (RLPFC) to reasoning. This area of the brain has been hypothesized to integrate relational information, as in analogy, or the outcomes of subgoals, as in multi-tasking and complex problem solving. Using fMRI, we compared visuospatial analogical reasoning to a control task that was as complex and difficult as the analogies and required the coordination of subgoals but not the integration of relations. We found that analogical reasoning more strongly activated bilateral RLPFC, suggesting that anterior prefrontal cortex is preferentially recruited by the integration of relational knowledge. Consistent with the need for inhibition during analogy, bilateral, and particularly right, inferior frontal gyri were also more active during analogy. Finally, greater activity in bilateral inferior parietal cortex during the analogy task is consistent with recent evidence for the neural basis of spatial relation knowledge. Together, these findings indicate that a network of frontoparietal areas underlies analogical reasoning; we also suggest that hemispheric differences may emerge depending on the visuospatial or verbal/semantic nature of the analogies. Copyright © 2011 Elsevier Inc. All rights reserved.

Antagonistic Neural Networks Underlying Differentiated Leadership Roles

Directory of Open Access Journals (Sweden)

Richard Eleftherios Boyatzis

2014-03-01

Full Text Available The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950’s. Recent research in neuroscience suggests that the division between task oriented and socio-emotional oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks -- the Task Positive Network (TPN and the Default Mode Network (DMN. Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success.

Antagonistic neural networks underlying differentiated leadership roles

Science.gov (United States)

Boyatzis, Richard E.; Rochford, Kylie; Jack, Anthony I.

2014-01-01

The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950s. Recent research in neuroscience suggests that the division between task-oriented and socio-emotional-oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks – the task-positive network (TPN) and the default mode network (DMN). Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task-oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions, and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success. PMID:24624074

Antagonistic neural networks underlying differentiated leadership roles.

Science.gov (United States)

Boyatzis, Richard E; Rochford, Kylie; Jack, Anthony I

2014-01-01

The emergence of two distinct leadership roles, the task leader and the socio-emotional leader, has been documented in the leadership literature since the 1950s. Recent research in neuroscience suggests that the division between task-oriented and socio-emotional-oriented roles derives from a fundamental feature of our neurobiology: an antagonistic relationship between two large-scale cortical networks - the task-positive network (TPN) and the default mode network (DMN). Neural activity in TPN tends to inhibit activity in the DMN, and vice versa. The TPN is important for problem solving, focusing of attention, making decisions, and control of action. The DMN plays a central role in emotional self-awareness, social cognition, and ethical decision making. It is also strongly linked to creativity and openness to new ideas. Because activation of the TPN tends to suppress activity in the DMN, an over-emphasis on task-oriented leadership may prove deleterious to social and emotional aspects of leadership. Similarly, an overemphasis on the DMN would result in difficulty focusing attention, making decisions, and solving known problems. In this paper, we will review major streams of theory and research on leadership roles in the context of recent findings from neuroscience and psychology. We conclude by suggesting that emerging research challenges the assumption that role differentiation is both natural and necessary, in particular when openness to new ideas, people, emotions, and ethical concerns are important to success.

Event timing in associative learning: from biochemical reaction dynamics to behavioural observations.

Directory of Open Access Journals (Sweden)

Ayse Yarali

Full Text Available Associative learning relies on event timing. Fruit flies for example, once trained with an odour that precedes electric shock, subsequently avoid this odour (punishment learning; if, on the other hand the odour follows the shock during training, it is approached later on (relief learning. During training, an odour-induced Ca(++ signal and a shock-induced dopaminergic signal converge in the Kenyon cells, synergistically activating a Ca(++-calmodulin-sensitive adenylate cyclase, which likely leads to the synaptic plasticity underlying the conditioned avoidance of the odour. In Aplysia, the effect of serotonin on the corresponding adenylate cyclase is bi-directionally modulated by Ca(++, depending on the relative timing of the two inputs. Using a computational approach, we quantitatively explore this biochemical property of the adenylate cyclase and show that it can generate the effect of event timing on associative learning. We overcome the shortage of behavioural data in Aplysia and biochemical data in Drosophila by combining findings from both systems.

Noise transmission and delay-induced stochasticoscillations in biochemical network motifs

Institute of Scientific and Technical Information of China (English)

Liu Sheng-Jun; Wang Qi; Liu Bo; Yan Shi-Wei; Fumihiko Sakata

2011-01-01

With the aid of stochastic delayed-feedback differential equations,we derive an analytic expression for the power spectra of reacting molecules included in a generic biological network motif that is incorporated with a feedback mechanism and time delays in gene regulation.We systematically analyse the effects of time delays,the feedback mechanism,and biological stochasticity on the power spectra.It has been clarified that the time delays together with the feedback mechanism can induce stochastic oscillations at the molecular level and invalidate the noise addition rule for a modular description of the noise propagator.Delay-induced stochastic resonance can be expected,which is related to the stability loss of the reaction systems and Hopf bifurcation occurring for solutions of the corresponding deterministic reaction equations.Through the analysis of the power spectrum,a new approach is proposed to estimate the oscillation period.

Quantifying the dynamics of coupled networks of switches and oscillators.

Directory of Open Access Journals (Sweden)

Matthew R Francis

Full Text Available Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's evolution. We, therefore, introduce a new modeling framework that describes the dynamics of networks composed of both oscillators and switches. Both oscillator synchronization and switch stability are preserved in these heterogeneous, coupled networks. Furthermore, this model recapitulates the qualitative dynamics for the yeast cell cycle consistent with the hypothesized dynamics resulting from decomposition of the regulatory network into dynamic motifs. Introducing feedback into the cell-cycle network induces qualitative dynamics analogous to limitless replicative potential that is a hallmark of cancer. As a result, the proposed model of switch and oscillator coupling provides the ability to incorporate mechanisms that underlie the synchronized stimulus response ubiquitous in biochemical systems.

Effect of plant-derived smoke solutions on physiological and biochemical attributes of maize (Zea mays L.) under salt stress

International Nuclear Information System (INIS)

Waheed, M.A.; Shakir, S.K.; Rehman, S.U.; Khan, M.D.

2016-01-01

Among abiotic stresses, salinity is an important factor reducing crop yield. Plant-derived smoke solutions have been used as growth promoters since last two decades. The present study was conducted to investigate the effect of Cymbopogon jwaracusa smoke extracts (1:100 and 1:400) on physiological and biochemical aspects of maize (Zea mays L.) under salt stress (100, 150, 200 and 250 mM). Results showed that seed germination percentage was improved up to 93% with smoke as compared to control (70%), while seedling vigor in term of root and shoot fresh weights and dry weights were also significantly increased in seeds primed with smoke extracts. Similarly, in case of alleviating solutions, there occurred a significant alleviation in the adverse effects of salt solutions when mixed smoke in all studied end points. Application of smoke solution has also increased the level of K+ and Ca+2 while reduced the level of Na+ content in maize. In addition, the levels of photosynthetic pigments, total nitrogen and protein contents were also alleviated with the application of smoke as compared to salt. There occurred an increase in the activities of Anti-oxidant in response of salt stress but overcome with the smoke application. It can be concluded that plant-derived smoke solution has the potential to alleviate the phytotoxic effects of saline condition and can increased the productivity in plants. (author)

Soil restoration under pasture after lignite mining - management effects on soil biochemical properties and their relationships with herbage yields

Energy Technology Data Exchange (ETDEWEB)

Ross, D.J.; Speir, T.W.; Cowling, J.C.; Feltham, C.W. (DSIR, Lower Hutt (New Zealand))

1992-01-01

The recovery of soil biochemical properties under grazed, grass-clover pasture after simulated lignite mining was studied over a 5-year period in a mesic Typic Dystrochrept soil at Waimumu, Southland, New Zealand. Restoration procedures involved four replacement treatments, after A,B and C horizon materials had been separately removed, from all except the control, and stockpiled for 2-3 weeks. Replacement treatment markedly influenced the recovery of herbage production and soil organic C and total N contents, N mineralization, microbial biomass (as indicated by mineral-N flush) and invertase and sulphatase activities. The effectiveness of replacement treatments decreased in the order: 1. control (no stripping or replacement). 2. A,B and C horizon materials replaced in the same order. 3. A,B and C horizon materials each mixed with an equal amount of siltstone overburden and replaced in order, 4. A and B horizon materials mixed before replacing over C horizon materials. Ripping increased herbage production, net N mineralization and microbial biomass. Fertilizer N also stimulated herbage production but depressed clover growth. Increases in soil invertase and, to a lesser extent, sulphatase activity were closely related to changes in herbage production. Microbial biomass increased more rapidly than soil organic C in early stages in the trial. Rates of net N mineralization suggest that N availability would have limited pasture growth.

Modeling delay in genetic networks: from delay birth-death processes to delay stochastic differential equations.

Science.gov (United States)

Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Bennett, Matthew R; Josić, Krešimir; Ott, William

2014-05-28

Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.

Modeling delay in genetic networks: From delay birth-death processes to delay stochastic differential equations

Energy Technology Data Exchange (ETDEWEB)

Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Ott, William [Department of Mathematics, University of Houston, Houston, Texas 77004 (United States); Bennett, Matthew R. [Department of Biochemistry and Cell Biology, Rice University, Houston, Texas 77204, USA and Institute of Biosciences and Bioengineering, Rice University, Houston, Texas 77005 (United States); Josić, Krešimir [Department of Mathematics, University of Houston, Houston, Texas 77004 (United States); Department of Biology and Biochemistry, University of Houston, Houston, Texas 77204 (United States)

2014-05-28

Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay.

Modeling delay in genetic networks: From delay birth-death processes to delay stochastic differential equations

International Nuclear Information System (INIS)

Gupta, Chinmaya; López, José Manuel; Azencott, Robert; Ott, William; Bennett, Matthew R.; Josić, Krešimir

2014-01-01

Delay is an important and ubiquitous aspect of many biochemical processes. For example, delay plays a central role in the dynamics of genetic regulatory networks as it stems from the sequential assembly of first mRNA and then protein. Genetic regulatory networks are therefore frequently modeled as stochastic birth-death processes with delay. Here, we examine the relationship between delay birth-death processes and their appropriate approximating delay chemical Langevin equations. We prove a quantitative bound on the error between the pathwise realizations of these two processes. Our results hold for both fixed delay and distributed delay. Simulations demonstrate that the delay chemical Langevin approximation is accurate even at moderate system sizes. It captures dynamical features such as the oscillatory behavior in negative feedback circuits, cross-correlations between nodes in a network, and spatial and temporal information in two commonly studied motifs of metastability in biochemical systems. Overall, these results provide a foundation for using delay stochastic differential equations to approximate the dynamics of birth-death processes with delay

Functional neural networks underlying response inhibition in adolescents and adults.

Science.gov (United States)

Stevens, Michael C; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

2007-07-19

This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by fronto-striatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development.

Fruit development, pigmentation and biochemical properties of wax apple as affected by localized Application of GA3 under field conditions

Directory of Open Access Journals (Sweden)

Mohammad Moneruzzaman Khandaker

2013-02-01

Full Text Available This study investigated the effects of gibberellin (GA3 on the fruit development, pigmentation and biochemical properties of wax apple. The wax apple trees were rubbing treated with 0, 20, 50 and 100 mgGA3/l under field conditions. The localized application (rubbing of 50 mg GA3/l significantly increased the fruit set, fruit length and diameter, color development, weight and yieldcompared to the control. In addition, GA3 treatments significantly reduced the fruit drop. With regard to the fruit quality, 50 mg/l GA3 treatment increased the juice content, K+, TSS, total sugar and sugar acid ratio of wax apple fruits. In addition, higher vitamin C, phenol, flavonoid, anthocyanin, carotene content, PAL and antioxidant activities were recorded in the treated fruits. There was a positive correlation between the peel colour and TSS content and between the PAL activity and anthocyanin formation in the GA3-treated fruit. It was concluded that rubbing with 50 mg/L GA3 at inflorescence developing point of phloem once a week from the tiny inflorescence bud until the flower opening resulted in better yield and quality of wax apple fruits and could be an effective technique to safe the environment from excessive spray.

Epigenetic Modulation of Brain Gene Networks for Cocaine and Alcohol Abuse

Directory of Open Access Journals (Sweden)

Sean P Farris

2015-05-01

Full Text Available Cocaine and alcohol are two substances of abuse that prominently affect the central nervous system (CNS. Repeated exposure to cocaine and alcohol leads to longstanding changes in gene expression, and subsequent functional CNS plasticity, throughout multiple brain regions. Epigenetic modifications of histones are one proposed mechanism guiding these enduring changes to the transcriptome. Characterizing the large number of available biological relationships as network models can reveal unexpected biochemical relationships. Clustering analysis of variation from whole-genome sequencing of gene expression (RNA-Seq and histone H3 lysine 4 trimethylation (H3K4me3 events (ChIP-Seq revealed the underlying structure of the transcriptional and epigenomic landscape within hippocampal postmortem brain tissue of drug abusers and control cases. Distinct sets of interrelated networks for cocaine and alcohol abuse were determined for each abusive substance. The network approach identified subsets of functionally related genes that are regulated in agreement with H3K4me3 changes, suggesting cause and effect relationships between this epigenetic mark and gene expression. Gene expression networks consisted of recognized substrates for addiction, such as the dopamine- and cAMP-regulated neuronal phosphoprotein PPP1R1B / DARPP-32 and the vesicular glutamate transporter SLC17A7 / VGLUT1 as well as potentially novel molecular targets for substance abuse. Through a systems biology based approach our results illustrate the utility of integrating epigenetic and transcript expression to establish relevant biological networks in the human brain for addiction. Future work with laboratory models may clarify the functional relevance of these gene networks for cocaine and alcohol, and provide a framework for the development of medications for the treatment of addiction.

Biophysical and biochemical constraints imposed by salt stress:Learning from halophyte

Directory of Open Access Journals (Sweden)

Bernardo eDuarte

2014-12-01

Full Text Available Soil salinization is one of the most important factors impacting plant productivity. About 3.6 billion of the world’s 5.2 billion ha of agricultural dryland have already suffered erosion, degradation and salinization. Halophytes typically are considered as plants able to complete their life cycle in environments where the salt concentration is 200 mM NaCl or higher. Different strategies are known to overcome salt stress, as adaptation mechanisms from this type of plants. Salinity adjustment is a complex phenomenon characterized by both biochemical and biophysical adaptations. As photosynthesis is a prerequisite for biomass production, halophytes adapted their electronic transduction pathways and the entire energetic metabolism to overcome the salt excess. The maintenance of ionic homeostasis is in the basis of all cellular stress in particular in terms of redox potential and energy transduction. In the present work the biophysical mechanisms underlying energy capture and transduction in halophytes are discussed alongside with their relation to biochemical mechanisms, integrating data from photosystem light harvesting complexes, electronic transport chains to the quinone pools, carbon harvesting and energy dissipation metabolism.

Accurate atom-mapping computation for biochemical reactions.

Science.gov (United States)

Latendresse, Mario; Malerich, Jeremiah P; Travers, Mike; Karp, Peter D

2012-11-26

The complete atom mapping of a chemical reaction is a bijection of the reactant atoms to the product atoms that specifies the terminus of each reactant atom. Atom mapping of biochemical reactions is useful for many applications of systems biology, in particular for metabolic engineering where synthesizing new biochemical pathways has to take into account for the number of carbon atoms from a source compound that are conserved in the synthesis of a target compound. Rapid, accurate computation of the atom mapping(s) of a biochemical reaction remains elusive despite significant work on this topic. In particular, past researchers did not validate the accuracy of mapping algorithms. We introduce a new method for computing atom mappings called the minimum weighted edit-distance (MWED) metric. The metric is based on bond propensity to react and computes biochemically valid atom mappings for a large percentage of biochemical reactions. MWED models can be formulated efficiently as Mixed-Integer Linear Programs (MILPs). We have demonstrated this approach on 7501 reactions of the MetaCyc database for which 87% of the models could be solved in less than 10 s. For 2.1% of the reactions, we found multiple optimal atom mappings. We show that the error rate is 0.9% (22 reactions) by comparing these atom mappings to 2446 atom mappings of the manually curated Kyoto Encyclopedia of Genes and Genomes (KEGG) RPAIR database. To our knowledge, our computational atom-mapping approach is the most accurate and among the fastest published to date. The atom-mapping data will be available in the MetaCyc database later in 2012; the atom-mapping software will be available within the Pathway Tools software later in 2012.

Computer-aided biochemical programming of synthetic microreactors as diagnostic devices.

Science.gov (United States)

Courbet, Alexis; Amar, Patrick; Fages, François; Renard, Eric; Molina, Franck

2018-04-26

Biological systems have evolved efficient sensing and decision-making mechanisms to maximize fitness in changing molecular environments. Synthetic biologists have exploited these capabilities to engineer control on information and energy processing in living cells. While engineered organisms pose important technological and ethical challenges, de novo assembly of non-living biomolecular devices could offer promising avenues toward various real-world applications. However, assembling biochemical parts into functional information processing systems has remained challenging due to extensive multidimensional parameter spaces that must be sampled comprehensively in order to identify robust, specification compliant molecular implementations. We introduce a systematic methodology based on automated computational design and microfluidics enabling the programming of synthetic cell-like microreactors embedding biochemical logic circuits, or protosensors , to perform accurate biosensing and biocomputing operations in vitro according to temporal logic specifications. We show that proof-of-concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. Protosensors may enable novel approaches to medicine and represent a step toward autonomous micromachines capable of precise interfacing of human physiology or other complex biological environments, ecosystems, or industrial bioprocesses. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Biochemical Removal of HAP Precursors From Coal

Energy Technology Data Exchange (ETDEWEB)

Olson, G.; Tucker, L.; Richards, J.

1997-07-01

This project addresses DOE`s interest in advanced concepts for controlling emissions of air toxics from coal-fired utility boilers. We are determining the feasibility of developing a biochemical process for the precombustion removal of substantial percentages of 13 inorganic hazardous air pollutant (HAP) precursors from coal. These HAP precursors are Sb, As, Be, Cd, Cr, Cl, Co, F, Pb, Hg, Mn, Ni, and Se. Although rapid physical coal cleaning is done routinely in preparation plants, biochemical processes for removal of HAP precursors from coal potentially offer advantages of deeper cleaning, more specificity, and less coal loss. Compared to chemical processes for coal cleaning, biochemical processes potentially offer lower costs and milder process conditions. Pyrite oxidizing bacteria, most notably Thiobacillusferrooxidans, are being evaluated in this project for their ability to remove HAP precursors from U.S. coals.

Biochemical Removal of HAP Precursors From Coal

International Nuclear Information System (INIS)

Olson, G.; Tucker, L.; Richards, J.

1997-07-01

This project addresses DOE's interest in advanced concepts for controlling emissions of air toxics from coal-fired utility boilers. We are determining the feasibility of developing a biochemical process for the precombustion removal of substantial percentages of 13 inorganic hazardous air pollutant (HAP) precursors from coal. These HAP precursors are Sb, As, Be, Cd, Cr, Cl, Co, F, Pb, Hg, Mn, Ni, and Se. Although rapid physical coal cleaning is done routinely in preparation plants, biochemical processes for removal of HAP precursors from coal potentially offer advantages of deeper cleaning, more specificity, and less coal loss. Compared to chemical processes for coal cleaning, biochemical processes potentially offer lower costs and milder process conditions. Pyrite oxidizing bacteria, most notably Thiobacillusferrooxidans, are being evaluated in this project for their ability to remove HAP precursors from U.S. coals

Virtualized cognitive network architecture for 5G cellular networks

KAUST Repository

Elsawy, Hesham

2015-07-17

Cellular networks have preserved an application agnostic and base station (BS) centric architecture1 for decades. Network functionalities (e.g. user association) are decided and performed regardless of the underlying application (e.g. automation, tactile Internet, online gaming, multimedia). Such an ossified architecture imposes several hurdles against achieving the ambitious metrics of next generation cellular systems. This article first highlights the features and drawbacks of such architectural ossification. Then the article proposes a virtualized and cognitive network architecture, wherein network functionalities are implemented via software instances in the cloud, and the underlying architecture can adapt to the application of interest as well as to changes in channels and traffic conditions. The adaptation is done in terms of the network topology by manipulating connectivities and steering traffic via different paths, so as to attain the applications\\' requirements and network design objectives. The article presents cognitive strategies to implement some of the classical network functionalities, along with their related implementation challenges. The article further presents a case study illustrating the performance improvement of the proposed architecture as compared to conventional cellular networks, both in terms of outage probability and handover rate.

When Is Network Lasso Accurate?

Directory of Open Access Journals (Sweden)

Alexander Jung

2018-01-01

Full Text Available The “least absolute shrinkage and selection operator” (Lasso method has been adapted recently for network-structured datasets. In particular, this network Lasso method allows to learn graph signals from a small number of noisy signal samples by using the total variation of a graph signal for regularization. While efficient and scalable implementations of the network Lasso are available, only little is known about the conditions on the underlying network structure which ensure network Lasso to be accurate. By leveraging concepts of compressed sensing, we address this gap and derive precise conditions on the underlying network topology and sampling set which guarantee the network Lasso for a particular loss function to deliver an accurate estimate of the entire underlying graph signal. We also quantify the error incurred by network Lasso in terms of two constants which reflect the connectivity of the sampled nodes.

Complex network inference from P300 signals: Decoding brain state under visual stimulus for able-bodied and disabled subjects

Science.gov (United States)

Gao, Zhong-Ke; Cai, Qing; Dong, Na; Zhang, Shan-Shan; Bo, Yun; Zhang, Jie

2016-10-01

Distinguishing brain cognitive behavior underlying disabled and able-bodied subjects constitutes a challenging problem of significant importance. Complex network has established itself as a powerful tool for exploring functional brain networks, which sheds light on the inner workings of the human brain. Most existing works in constructing brain network focus on phase-synchronization measures between regional neural activities. In contrast, we propose a novel approach for inferring functional networks from P300 event-related potentials by integrating time and frequency domain information extracted from each channel signal, which we show to be efficient in subsequent pattern recognition. In particular, we construct brain network by regarding each channel signal as a node and determining the edges in terms of correlation of the extracted feature vectors. A six-choice P300 paradigm with six different images is used in testing our new approach, involving one able-bodied subject and three disabled subjects suffering from multiple sclerosis, cerebral palsy, traumatic brain and spinal-cord injury, respectively. We then exploit global efficiency, local efficiency and small-world indices from the derived brain networks to assess the network topological structure associated with different target images. The findings suggest that our method allows identifying brain cognitive behaviors related to visual stimulus between able-bodied and disabled subjects.

Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks.

Science.gov (United States)

Zhang, Guomei; Sun, Hao

2016-12-16

We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE) is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor's reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured.

A scalable computational framework for establishing long-term behavior of stochastic reaction networks.

Directory of Open Access Journals (Sweden)

Ankit Gupta

2014-06-01

Full Text Available Reaction networks are systems in which the populations of a finite number of species evolve through predefined interactions. Such networks are found as modeling tools in many biological disciplines such as biochemistry, ecology, epidemiology, immunology, systems biology and synthetic biology. It is now well-established that, for small population sizes, stochastic models for biochemical reaction networks are necessary to capture randomness in the interactions. The tools for analyzing such models, however, still lag far behind their deterministic counterparts. In this paper, we bridge this gap by developing a constructive framework for examining the long-term behavior and stability properties of the reaction dynamics in a stochastic setting. In particular, we address the problems of determining ergodicity of the reaction dynamics, which is analogous to having a globally attracting fixed point for deterministic dynamics. We also examine when the statistical moments of the underlying process remain bounded with time and when they converge to their steady state values. The framework we develop relies on a blend of ideas from probability theory, linear algebra and optimization theory. We demonstrate that the stability properties of a wide class of biological networks can be assessed from our sufficient theoretical conditions that can be recast as efficient and scalable linear programs, well-known for their tractability. It is notably shown that the computational complexity is often linear in the number of species. We illustrate the validity, the efficiency and the wide applicability of our results on several reaction networks arising in biochemistry, systems biology, epidemiology and ecology. The biological implications of the results as well as an example of a non-ergodic biological network are also discussed.

Spike Pattern Structure Influences Synaptic Efficacy Variability Under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

Directory of Open Access Journals (Sweden)

Zedong Bi

2016-08-01

Full Text Available Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded, by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy.

Simulating carbon dioxide exchange rates of deciduous tree species: evidence for a general pattern in biochemical changes and water stress response.

Science.gov (United States)

Reynolds, Robert F; Bauerle, William L; Wang, Ying

2009-09-01

Deciduous trees have a seasonal carbon dioxide exchange pattern that is attributed to changes in leaf biochemical properties. However, it is not known if the pattern in leaf biochemical properties - maximum Rubisco carboxylation (V(cmax)) and electron transport (J(max)) - differ between species. This study explored whether a general pattern of changes in V(cmax), J(max), and a standardized soil moisture response accounted for carbon dioxide exchange of deciduous trees throughout the growing season. The model MAESTRA was used to examine V(cmax) and J(max) of leaves of five deciduous trees, Acer rubrum 'Summer Red', Betula nigra, Quercus nuttallii, Quercus phellos and Paulownia elongata, and their response to soil moisture. MAESTRA was parameterized using data from in situ measurements on organs. Linking the changes in biochemical properties of leaves to the whole tree, MAESTRA integrated the general pattern in V(cmax) and J(max) from gas exchange parameters of leaves with a standardized soil moisture response to describe carbon dioxide exchange throughout the growing season. The model estimates were tested against measurements made on the five species under both irrigated and water-stressed conditions. Measurements and modelling demonstrate that the seasonal pattern of biochemical activity in leaves and soil moisture response can be parameterized with straightforward general relationships. Over the course of the season, differences in carbon exchange between measured and modelled values were within 6-12 % under well-watered conditions and 2-25 % under water stress conditions. Hence, a generalized seasonal pattern in the leaf-level physiological change of V(cmax) and J(max), and a standardized response to soil moisture was sufficient to parameterize carbon dioxide exchange for large-scale evaluations. Simplification in parameterization of the seasonal pattern of leaf biochemical activity and soil moisture response of deciduous forest species is demonstrated. This

Spectral Analysis of Rich Network Topology in Social Networks

Science.gov (United States)

Wu, Leting

2013-01-01

Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

Inferring general relations between network characteristics from specific network ensembles.

Science.gov (United States)

Cardanobile, Stefano; Pernice, Volker; Deger, Moritz; Rotter, Stefan

2012-01-01

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their ability to generate networks with large structural variability. In particular, we consider the statistical constraints which the respective construction scheme imposes on the generated networks. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This makes it possible to infer global features from local ones using regression models trained on networks with high generalization power. Our results confirm and extend previous findings regarding the synchronization properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks in good approximation. Finally, we demonstrate on three different data sets (C. elegans neuronal network, R. prowazekii metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models.

Soil biochemical properties of grassland ecosystems under anthropogenic emission of nitrogen compounds

Science.gov (United States)

Kudrevatykh, Irina; Ivashchenko, Kristina; Ananyeva, Nadezhda

2016-04-01

Inflow of pollutants in terrestrial ecosystems nowadays increases dramatically, that might be led to disturbance of natural biogeochemical cycles and landscapes structure. Production of nitrogen fertilizers is one of the air pollution sources, namely by nitrogen compounds (NH4+, NO3-, NO2-). Air pollution by nitrogen compounds of terrestrial ecosystems might be affected on soil biochemical properties, which results increasing mineral nitrogen content in soil, changing soil P/N and Al/Ca ratios, and, finally, the deterioration of soil microbial community functioning. The research is focused on the assessment of anthropogenic emission of nitrogen compounds on soil properties of grassland ecosystems in European Russia. Soil samples (Voronic Chernozem Pachic, upper 10 cm mineral layer, totally 10) were taken from grassland ecosystem: near (5-10 m) nitrogen fertilizer factory (NFF), and far from it (20-30 km, served as a control) in Tula region. In soil samples the NH4+ and NO3- (Kudeyarov's photocolorimetric method), P, Ca, Al (X-ray fluorescence method) contents were measured. Soil microbial biomass carbon (Cmic) was analyzed by substrate-induced respiration method. Soil microbial respiration (MR) was assessed by CO2 rate production. Soil microbial metabolic quotient (qCO2) was calculated as MR/Cmic ratio. Near NFF the soil ammonium and nitrate nitrogen contents were a strongly varied, variation coefficient (CV) was 42 and 86This study was supported by Russian Foundation of Basic Research Grant No. 14-04-00098, 15-44-03220, 15-04-00915.

Take it of leave it : Mechanisms underlying bacterial bistable regulatory networks

NARCIS (Netherlands)

Siebring, Jeroen; Sorg, Robin; Herber, Martijn; Kuipers, Oscar; Filloux, Alain A.M.

2012-01-01

Bistable switches occur in regulatory networks that can exist in two distinct stable states. Such networks allow distinct switching of individual cells. In bacteria these switches coexist with regulatory networks that respond gradually to environmental input. Bistable switches play key roles in high

Craniometaphyseal dysplasia with obvious biochemical abnormality and rickets-like features.

Science.gov (United States)

Wu, Bo; Jiang, Yan; Wang, Ou; Li, Mei; Xing, Xiao-Ping; Xia, Wei-Bo

2016-05-01

Craniometaphyseal dysplasia (CMD) is a rare genetic disorder that is characterized by progressive sclerosis of the craniofacial bones and metaphyseal widening of long bones, and biochemical indexes were mostly normal. To further the understanding of the disease from a biochemical perspective, we reported a CMD case with obviously abnormal biochemical indexes. A 1-year-old boy was referred to our clinic. Biochemical test showed obviously increased alkaline phosphatase (ALP) and parathyroid hormone (PTH), mild hypocalcemia and hypophosphatemia. Moreover, significant elevated receptor activator of nuclear factor kappa-B ligand (RANKL) level, but normal β-C-terminal telopeptide of type I collagen (β-CTX) concentration were revealed. He was initially suspected of rickets, because the radiological examination also showed broadened epiphysis in his long bones. Supplementation with calcium and calcitriol alleviated biochemical abnormality. However, the patient gradually developed osteosclerosis which was inconformity with rickets. Considering that he was also presented with facial paralysis and nasal obstruction symptom, the diagnosis of craniometaphyseal dysplasia was suspected, and then was confirmed by the mutation analysis of ANKH of the proband and his family, which showed a de novo heterozygous mutation (C1124-1126delCCT) on exon 9. Our study revealed that obvious biochemical abnormality and rickets-like features might present as uncommon characteristics in CMD patients, and the calcium and calcitriol supplementation could alleviate biochemical abnormalities. Furthermore, although early osteoclast differentiation factor was excited in CMD patient, activity of osteoclast was still inert. Copyright © 2016. Published by Elsevier B.V.

Lignin plays a negative role in the biochemical process for producing lignocellulosic biofuels.

Science.gov (United States)

Zeng, Yining; Zhao, Shuai; Yang, Shihui; Ding, Shi-You

2014-06-01

A biochemical platform holds the most promising route toward lignocellulosic biofuels, in which polysaccharides are hydrolyzed by cellulase enzymes into simple sugars and fermented to ethanol by microbes. However, these polysaccharides are cross-linked in the plant cell walls with the hydrophobic network of lignin that physically impedes enzymatic deconstruction. A thermochemical pretreatment process is often required to remove or delocalize lignin, which may also generate inhibitors that hamper enzymatic hydrolysis and fermentation. Here we review recent advances in understanding lignin structure in the plant cell walls and the negative roles of lignin in the processes of converting biomass to biofuels. Perspectives and future directions to improve the biomass conversion process are also discussed. Copyright © 2013. Published by Elsevier Ltd.

Hierarchical analysis of dependency in metabolic networks.

Science.gov (United States)

Gagneur, Julien; Jackson, David B; Casari, Georg

2003-05-22

Elucidation of metabolic networks for an increasing number of organisms reveals that even small networks can contain thousands of reactions and chemical species. The intimate connectivity between components complicates their decomposition into biologically meaningful sub-networks. Moreover, traditional higher-order representations of metabolic networks as metabolic pathways, suffers from the lack of rigorous definition, yielding pathways of disparate content and size. We introduce a hierarchical representation that emphasizes the gross organization of metabolic networks in largely independent pathways and sub-systems at several levels of independence. The approach highlights the coupling of different pathways and the shared compounds responsible for those couplings. By assessing our results on Escherichia coli (E.coli metabolic reactions, Genetic Circuits Research Group, University of California, San Diego, http://gcrg.ucsd.edu/organisms/ecoli.html, 'model v 1.01. reactions') against accepted biochemical annotations, we provide the first systematic synopsis of an organism's metabolism. Comparison with operons of E.coli shows that low-level clusters are reflected in genome organization and gene regulation. Source code, data sets and supplementary information are available at http://www.mas.ecp.fr/labo/equipe/gagneur/hierarchy/hierarchy.html

Developments in commercially produced microbials at Biochem Products

Science.gov (United States)

John Lublinkhof; Douglas H. Ross

1985-01-01

Biochem Products is part of a large industrial and scientific family - the Solvay Group. Solvay, headquartered in Brussels, Belgium is a multinational company with 46,000 employees worldwide. In the U.S., our working partners include a large polymer manufacturer, a peroxygen producer and a leading poultry and animal health products company. Biochem Products is a...

Kombucha tea fermentation: Microbial and biochemical dynamics.

Science.gov (United States)

Chakravorty, Somnath; Bhattacharya, Semantee; Chatzinotas, Antonis; Chakraborty, Writachit; Bhattacharya, Debanjana; Gachhui, Ratan

2016-03-02

Kombucha tea, a non-alcoholic beverage, is acquiring significant interest due to its claimed beneficial properties. The microbial community of Kombucha tea consists of bacteria and yeast which thrive in two mutually non-exclusive compartments: the soup or the beverage and the biofilm floating on it. The microbial community and the biochemical properties of the beverage have so far mostly been described in separate studies. This, however, may prevent understanding the causal links between the microbial communities and the beneficial properties of Kombucha tea. Moreover, an extensive study into the microbial and biochemical dynamics has also been missing. In this study, we thus explored the structure and dynamics of the microbial community along with the biochemical properties of Kombucha tea at different time points up to 21 days of fermentation. We hypothesized that several biochemical properties will change during the course of fermentation along with the shifts in the yeast and bacterial communities. The yeast community of the biofilm did not show much variation over time and was dominated by Candida sp. (73.5-83%). The soup however, showed a significant shift in dominance from Candida sp. to Lachancea sp. on the 7th day of fermentation. This is the first report showing Candida as the most dominating yeast genus during Kombucha fermentation. Komagateibacter was identified as the single largest bacterial genus present in both the biofilm and the soup (~50%). The bacterial diversity was higher in the soup than in the biofilm with a peak on the seventh day of fermentation. The biochemical properties changed with the progression of the fermentation, i.e., beneficial properties of the beverage such as the radical scavenging ability increased significantly with a maximum increase at day 7. We further observed a significantly higher D-saccharic acid-1,4-lactone content and caffeine degradation property compared to previously described Kombucha tea fermentations. Our

Biochemical markers of bone turnover

International Nuclear Information System (INIS)

Kim, Deog Yoon

1999-01-01

Biochemical markers of bone turnover has received increasing attention over the past few years, because of the need for sensitivity and specific tool in the clinical investigation of osteoporosis. Bone markers should be unique to bone, reflect changes of bone less, and should be correlated with radiocalcium kinetics, histomorphometry, or changes in bone mass. The markers also should be useful in monitoring treatment efficacy. Although no bone marker has been established to meet all these criteria, currently osteocalcin and pyridinium crosslinks are the most efficient markers to assess the level of bone turnover in the menopausal and senile osteoporosis. Recently, N-terminal telopeptide (NTX), C-terminal telopeptide (CTX) and bone specific alkaline phosphatase are considered as new valid markers of bone turnover. Recent data suggest that CTX and free deoxypyridinoline could predict the subsequent risk of hip fracture of elderly women. Treatment of postmenopausal women with estrogen, calcitonin and bisphosphonates demonstrated rapid decrease of the levels of bone markers that correlated with the long-term increase of bone mass. Factors such as circadian rhythms, diet, age, sex, bone mass and renal function affect the results of biochemical markers and should be appropriately adjusted whenever possible. Each biochemical markers of bone turnover may have its own specific advantages and limitations. Recent advances in research will provide more sensitive and specific assays

Network Traffic Features for Anomaly Detection in Specific Industrial Control System Network

Directory of Open Access Journals (Sweden)

Matti Mantere

2013-09-01

Full Text Available The deterministic and restricted nature of industrial control system networks sets them apart from more open networks, such as local area networks in office environments. This improves the usability of network security, monitoring approaches that would be less feasible in more open environments. One of such approaches is machine learning based anomaly detection. Without proper customization for the special requirements of the industrial control system network environment, many existing anomaly or misuse detection systems will perform sub-optimally. A machine learning based approach could reduce the amount of manual customization required for different industrial control system networks. In this paper we analyze a possible set of features to be used in a machine learning based anomaly detection system in the real world industrial control system network environment under investigation. The network under investigation is represented by architectural drawing and results derived from network trace analysis. The network trace is captured from a live running industrial process control network and includes both control data and the data flowing between the control network and the office network. We limit the investigation to the IP traffic in the traces.

Modeling the relationships between quality and biochemical composition of fatty liver in mule ducks.

Science.gov (United States)

Theron, L; Cullere, M; Bouillier-Oudot, M; Manse, H; Dalle Zotte, A; Molette, C; Fernandez, X; Vitezica, Z G

2012-09-01

The fatty liver of mule ducks (i.e., French "foie gras") is the most valuable product in duck production systems. Its quality is measured by the technological yield, which is the opposite of the fat loss during cooking. The purpose of this study was to determine whether biochemical measures of fatty liver could be used to accurately predict the technological yield (TY). Ninety-one male mule ducks were bred, overfed, and slaughtered under commercial conditions. Fatty liver weight (FLW) and biochemical variables, such as DM, lipid (LIP), and protein content (PROT), were collected. To evaluate evidence for nonlinear fat loss during cooking, we compared regression models describing linear and nonlinear relations between biochemical measures and TY. We detected significantly greater (P = 0.02) linear relation between DM and TY. Our results indicate that LIP and PROT follow a different pattern (linear) than DM and showed that LIP and PROT are nonexclusive contributing factors to TY. Other components, such as carbohydrates, other than those measured in this study, could contribute to DM. Stepwise regression for TY was performed. The traditional model with FLW was tested. The results showed that the weight of the liver is of limited value in the determination of fat loss during cooking (R(2) = 0.14). The most accurate TY prediction equation included DM (in linear and quadratic terms), FLW, and PROT (R(2) = 0.43). Biochemical measures in the fatty liver were more accurate predictors of TY than FLW. The model is useful in commercial conditions because DM, PROT, and FLW are noninvasive measures.

Body Composition and Ectopic Lipid Changes With Biochemical Control of Acromegaly.

Science.gov (United States)

Bredella, Miriam A; Schorr, Melanie; Dichtel, Laura E; Gerweck, Anu V; Young, Brian J; Woodmansee, Whitney W; Swearingen, Brooke; Miller, Karen K

2017-11-01

Acromegaly is characterized by growth hormone (GH) and insulinlike growth factor-1 (IGF-1) hypersecretion, and GH and IGF-1 play important roles in regulating body composition and glucose homeostasis. The purpose of our study was to investigate body composition including ectopic lipids, measures of glucose homeostasis, and gonadal steroids in patients with active acromegaly compared with age-, body mass index (BMI)-, and sex-matched controls and to determine changes in these parameters after biochemical control of acromegaly. Cross-sectional study of 20 patients with active acromegaly and 20 healthy matched controls. Prospective study of 16 patients before and after biochemical control of acromegaly. Body composition including ectopic lipids by magnetic resonance imaging/proton magnetic resonance spectroscopy; measures of glucose homeostasis by an oral glucose tolerance test; gonadal steroids. Patients with active acromegaly had lower mean intrahepatic lipid (IHL) and higher mean fasting insulin and insulin area under the curve (AUC) values than controls. Men with acromegaly had lower mean total testosterone, sex hormone-binding globulin, and estradiol values than male controls. After therapy, homeostasis model assessment of insulin resistance, fasting insulin level, and insulin AUC decreased despite an increase in IHL and abdominal and thigh adipose tissues and a decrease in muscle mass. Patients with acromegaly were characterized by insulin resistance and hyperinsulinemia but lower IHL compared with age-, BMI-, and sex-matched healthy controls. Biochemical control of acromegaly improved insulin resistance but led to a less favorable anthropometric phenotype with increased IHL and abdominal adiposity and decreased muscle mass. Copyright © 2017 Endocrine Society

Chemical, biochemical and microbiological indicators to assess soil quality in temperate agro-ecosystems

OpenAIRE

Giacometti, Caterina

2013-01-01

Soil is a critically important component of the earth’s biosphere. Developing agricultural production systems able to conserve soil quality is essential to guarantee the current and future capacity of soil to provide goods and services. This study investigates the potential of microbial and biochemical parameters to be used as early and sensitive soil quality indicators. Their ability to differentiate plots under contrasting fertilization regimes is evaluated based also on their sensitivi...

Measures of Biochemical Sociology

Science.gov (United States)

Snell, Joel; Marsh, Mitchell

2008-01-01

In a previous article, the authors introduced a new sub field in sociology that we labeled "biochemical sociology." We introduced the definition of a sociology that encompasses sociological measures, psychological measures, and biological indicators Snell & Marsh (2003). In this article, we want to demonstrate a research strategy that would assess…

Design of real-time voice over internet protocol system under bandwidth network

Science.gov (United States)

Zhang, Li; Gong, Lina

2017-04-01

With the increasing bandwidth of the network and network convergence accelerating, VoIP means of communication across the network is becoming increasingly popular phenomenon. The real-time identification and analysis for VOIP flow over backbone network become the urgent needs and research hotspot of network operations management. Based on this, the paper proposes a VoIP business management system over backbone network. The system first filters VoIP data stream over backbone network and further resolves the call signaling information and media voice. The system can also be able to design appropriate rules to complete real-time reduction and presentation of specific categories of calls. Experimental results show that the system can parse and process real-time backbone of the VoIP call, and the results are presented accurately in the management interface, VoIP-based network traffic management and maintenance provide the necessary technical support.

Discovering Reliable Sources of Biochemical Thermodynamic Data to Aid Students' Understanding

Science.gov (United States)

Me´ndez, Eduardo; Cerda´, María F.

2016-01-01

Students of physical chemistry in biochemical disciplines need biochemical examples to capture the need, not always understood, of a difficult area in their studies. The use of thermodynamic data in the chemical reference state may lead to incorrect interpretations in the analysis of biochemical examples when the analysis does not include relevant…

Pretreatment Endorectal Coil Magnetic Resonance Imaging Findings Predict Biochemical Tumor Control in Prostate Cancer Patients Treated With Combination Brachytherapy and External-Beam Radiotherapy

International Nuclear Information System (INIS)

Riaz, Nadeem; Afaq, Asim; Akin, Oguz; Pei Xin; Kollmeier, Marisa A.; Cox, Brett; Hricak, Hedvig; Zelefsky, Michael J.

2012-01-01

Purpose: To investigate the utility of endorectal coil magenetic resonance imaging (eMRI) in predicting biochemical relapse in prostate cancer patients treated with combination brachytherapy and external-beam radiotherapy. Methods and Materials: Between 2000 and 2008, 279 men with intermediate- or high-risk prostate cancer underwent eMRI of their prostate before receiving brachytherapy and supplemental intensity-modulated radiotherapy. Endorectal coil MRI was performed before treatment and retrospectively reviewed by two radiologists experienced in genitourinary MRI. Image-based variables, including tumor diameter, location, number of sextants involved, and the presence of extracapsular extension (ECE), were incorporated with other established clinical variables to predict biochemical control outcomes. The median follow-up was 49 months (range, 1–13 years). Results: The 5-year biochemical relapse-free survival for the cohort was 92%. Clinical findings predicting recurrence on univariate analysis included Gleason score (hazard ratio [HR] 3.6, p = 0.001), PSA (HR 1.04, p = 0.005), and National Comprehensive Cancer Network risk group (HR 4.1, p = 0.002). Clinical T stage and the use of androgen deprivation therapy were not correlated with biochemical failure. Imaging findings on univariate analysis associated with relapse included ECE on MRI (HR 3.79, p = 0.003), tumor size (HR 2.58, p = 0.04), and T stage (HR 1.71, p = 0.004). On multivariate analysis incorporating both clinical and imaging findings, only ECE on MRI and Gleason score were independent predictors of recurrence. Conclusions: Pretreatment eMRI findings predict for biochemical recurrence in intermediate- and high-risk prostate cancer patients treated with combination brachytherapy and external-beam radiotherapy. Gleason score and the presence of ECE on MRI were the only significant predictors of biochemical relapse in this group of patients.

Immunobiological, biochemical, and physico-chemical characteristics of Brucella lipopolysaccharide subjected to various doses of gamma radiation

Energy Technology Data Exchange (ETDEWEB)

Dranovskaya, E A; Shibaeva, I V [Akademiya Meditsinskikh Nauk SSSR, Moscow. Inst. Ehpidemiologii i Mikrobiologii; Khabakpasheva, N A; Rostovtseva, N A [Institut Vaktsin i Syvorotok, Moscow (USSR)

1975-01-01

A comparative study is presented of toxicity, serological activity, some biochemical and physico-chemical properties of the highly toxic Brucella lipopolysaccharide (LPS) and of preparations obtained as a result of gamma irradiation in doses of 1, 3, and 10 mrad on the antigen. The toxicity of LPS was found to decrease with increasing radiation dose. Irradiation with a dose of 3 mrad produced a marked decrease in the toxicity of the antigen without essentially changing its serological properties. The process of LPS detoxication under the effect of irradiation was accompanied by changes in certain biochemical and physico-chemical indices suggestive of a modification of the primary structure of the LPS molecule and of an impairment especially of its polysaccharide side chains.

Immunobiological, biochemical and physico-chemical characteristics of Brucella lipopolysaccharide subjected to various doses of gamma radiation

International Nuclear Information System (INIS)

Dranovskaya, E.A.; Shibaeva, I.V.

1975-01-01

A comparative study is presented of toxicity, serological activity, some biochemical and physico-chemical properties of the highly toxic Brucella lipopolysaccharide (LPS) and of preparations obtained as a result of gamma irradiation in doses of 1, 3, and 10 mrad on the antigen. The toxicity of LPS was found to decrease with increasing radiation dose. Irradiation with a dose of 3 mrad produced a marked decrease in the toxicity of the antigen without essentially changing its serological properties. The process of LPS detoxication under the effect of irradiation was accompanied by changes in certain biochemical and physico-chemical indices suggestive of a modification of the primary structure of the LPS molecule and of an impairment especially of its polysaccharide side chains. (author)

Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean.

Science.gov (United States)

Fang, Chao; Ma, Yanming; Wu, Shiwen; Liu, Zhi; Wang, Zheng; Yang, Rui; Hu, Guanghui; Zhou, Zhengkui; Yu, Hong; Zhang, Min; Pan, Yi; Zhou, Guoan; Ren, Haixiang; Du, Weiguang; Yan, Hongrui; Wang, Yanping; Han, Dezhi; Shen, Yanting; Liu, Shulin; Liu, Tengfei; Zhang, Jixiang; Qin, Hao; Yuan, Jia; Yuan, Xiaohui; Kong, Fanjiang; Liu, Baohui; Li, Jiayang; Zhang, Zhiwu; Wang, Guodong; Zhu, Baoge; Tian, Zhixi

2017-08-24

Soybean (Glycine max [L.] Merr.) is one of the most important oil and protein crops. Ever-increasing soybean consumption necessitates the improvement of varieties for more efficient production. However, both correlations among different traits and genetic interactions among genes that affect a single trait pose a challenge to soybean breeding. To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits. This study provides insights into the genetic correlation among complex traits and will facilitate future soybean functional studies and breeding through molecular design.

Exploring basic biochemical constituents in the body tissues of ...

African Journals Online (AJOL)

Feeding regime did not influence susceptibility to mass loss during export. Animal age influenced the biochemical composition and export performance of abalone. Keywords: abalone; aquaculture; feeds; Haliotis midae; live export; mass loss; tissue biochemical constituents. African Journal of Marine Science 2010, 32(1): ...

Biochemical principles underlying the stable maintenance of LTP by the CaMKII/NMDAR complex.

Science.gov (United States)

Lisman, John; Raghavachari, Sridhar

2015-09-24

Memory involves the storage of information at synapses by an LTP-like process. This information storage is synapse specific and can endure for years despite the turnover of all synaptic proteins. There must, therefore, be special principles that underlie the stability of LTP. Recent experimental results suggest that LTP is maintained by the complex of CaMKII with the NMDAR. Here we consider the specifics of the CaMKII/NMDAR molecular switch, with the goal of understanding the biochemical principles that underlie stable information storage by synapses. Consideration of a variety of experimental results suggests that multiple principles are involved. One switch requirement is to prevent spontaneous transitions from the off to the on state. The highly cooperative nature of CaMKII autophosphorylation by Ca(2+) (Hill coefficient of 8) and the fact that formation of the CaMKII/NMDAR complex requires release of CaMKII from actin are mechanisms that stabilize the off state. The stability of the on state depends critically on intersubunit autophosphorylation, a process that restores any loss of pT286 due to phosphatase activity. Intersubunit autophosphorylation is also important in explaining why on state stability is not compromised by protein turnover. Recent evidence suggests that turnover occurs by subunit exchange. Thus, stability could be achieved if a newly inserted unphosphorylated subunit was autophosphorylated by a neighboring subunit. Based on other recent work, we posit a novel mechanism that enhances the stability of the on state by protection of pT286 from phosphatases. We posit that the binding of the NMNDAR to CaMKII forces pT286 into the catalytic site of a neighboring subunit, thereby protecting pT286 from phosphatases. A final principle concerns the role of structural changes. The binding of CaMKII to the NMDAR may act as a tag to organize the binding of further proteins that produce the synapse enlargement that underlies late LTP. We argue that these

The role of networks and artificial intelligence in nanotechnology design and analysis.

Science.gov (United States)

Hudson, D L; Cohen, M E

2004-05-01

Techniques with their origins in artificial intelligence have had a great impact on many areas of biomedicine. Expert-based systems have been used to develop computer-assisted decision aids. Neural networks have been used extensively in disease classification and more recently in many bioinformatics applications including genomics and drug design. Network theory in general has proved useful in modeling all aspects of biomedicine from healthcare organizational structure to biochemical pathways. These methods show promise in applications involving nanotechnology both in the design phase and in interpretation of system functioning.

Secure Distributed Detection under Energy Constraint in IoT-Oriented Sensor Networks

Directory of Open Access Journals (Sweden)

Guomei Zhang

2016-12-01

Full Text Available We study the secure distributed detection problems under energy constraint for IoT-oriented sensor networks. The conventional channel-aware encryption (CAE is an efficient physical-layer secure distributed detection scheme in light of its energy efficiency, good scalability and robustness over diverse eavesdropping scenarios. However, in the CAE scheme, it remains an open problem of how to optimize the key thresholds for the estimated channel gain, which are used to determine the sensor’s reporting action. Moreover, the CAE scheme does not jointly consider the accuracy of local detection results in determining whether to stay dormant for a sensor. To solve these problems, we first analyze the error probability and derive the optimal thresholds in the CAE scheme under a specified energy constraint. These results build a convenient mathematic framework for our further innovative design. Under this framework, we propose a hybrid secure distributed detection scheme. Our proposal can satisfy the energy constraint by keeping some sensors inactive according to the local detection confidence level, which is characterized by likelihood ratio. In the meanwhile, the security is guaranteed through randomly flipping the local decisions forwarded to the fusion center based on the channel amplitude. We further optimize the key parameters of our hybrid scheme, including two local decision thresholds and one channel comparison threshold. Performance evaluation results demonstrate that our hybrid scheme outperforms the CAE under stringent energy constraints, especially in the high signal-to-noise ratio scenario, while the security is still assured.

Efficient network disintegration under incomplete information: the comic effect of link prediction

Science.gov (United States)

Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

2016-01-01

The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the “comic effect” of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized. PMID:26960247

Efficient network disintegration under incomplete information: the comic effect of link prediction

Science.gov (United States)

Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

2016-03-01

The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the “comic effect” of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized.

Accessible methods for the dynamic time-scale decomposition of biochemical systems.

Science.gov (United States)

Surovtsova, Irina; Simus, Natalia; Lorenz, Thomas; König, Artjom; Sahle, Sven; Kummer, Ursula

2009-11-01

The growing complexity of biochemical models asks for means to rationally dissect the networks into meaningful and rather independent subnetworks. Such foregoing should ensure an understanding of the system without any heuristics employed. Important for the success of such an approach is its accessibility and the clarity of the presentation of the results. In order to achieve this goal, we developed a method which is a modification of the classical approach of time-scale separation. This modified method as well as the more classical approach have been implemented for time-dependent application within the widely used software COPASI. The implementation includes different possibilities for the representation of the results including 3D-visualization. The methods are included in COPASI which is free for academic use and available at www.copasi.org. irina.surovtsova@bioquant.uni-heidelberg.de Supplementary data are available at Bioinformatics online.

Contracting for Competitive Supply Chains under Network Externalities and Demand Uncertainty

Directory of Open Access Journals (Sweden)

Xiaojing Liu

2016-01-01

Full Text Available Based on network externalities and demand uncertainty environment, supply chain competition model is built; we identify the valid mechanism for the alternative range of profit-sharing contracts and also analyze the effect of product substitutability coefficient and network externalities on the alliance and profit-sharing contract. The results show that the vertical alliance contributes profit improvement to both the manufacturer and the retailer when the impact of network externalities on the product substitutability is not strong. However, vertical alliance will be out of operation when the effect of network externalities on the product substitutability is strong.

GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework.

Science.gov (United States)

Deng, Lei; Jiao, Peng; Pei, Jing; Wu, Zhenzhi; Li, Guoqi

2018-04-01

Although deep neural networks (DNNs) are being a revolutionary power to open up the AI era, the notoriously huge hardware overhead has challenged their applications. Recently, several binary and ternary networks, in which the costly multiply-accumulate operations can be replaced by accumulations or even binary logic operations, make the on-chip training of DNNs quite promising. Therefore there is a pressing need to build an architecture that could subsume these networks under a unified framework that achieves both higher performance and less overhead. To this end, two fundamental issues are yet to be addressed. The first one is how to implement the back propagation when neuronal activations are discrete. The second one is how to remove the full-precision hidden weights in the training phase to break the bottlenecks of memory/computation consumption. To address the first issue, we present a multi-step neuronal activation discretization method and a derivative approximation technique that enable the implementing the back propagation algorithm on discrete DNNs. While for the second issue, we propose a discrete state transition (DST) methodology to constrain the weights in a discrete space without saving the hidden weights. Through this way, we build a unified framework that subsumes the binary or ternary networks as its special cases, and under which a heuristic algorithm is provided at the website https://github.com/AcrossV/Gated-XNOR. More particularly, we find that when both the weights and activations become ternary values, the DNNs can be reduced to sparse binary networks, termed as gated XNOR networks (GXNOR-Nets) since only the event of non-zero weight and non-zero activation enables the control gate to start the XNOR logic operations in the original binary networks. This promises the event-driven hardware design for efficient mobile intelligence. We achieve advanced performance compared with state-of-the-art algorithms. Furthermore, the computational sparsity

Estimating plant root water uptake using a neural network approach

DEFF Research Database (Denmark)

Qiao, D M; Shi, H B; Pang, H B

2010-01-01

but has not yet been addressed. This paper presents and tests such an approach. The method is based on a neural network model, estimating the water uptake using different types of data that are easy to measure in the field. Sunflower grown in a sandy loam subjected to water stress and salinity was taken......Water uptake by plant roots is an important process in the hydrological cycle, not only for plant growth but also for the role it plays in shaping microbial community and bringing in physical and biochemical changes to soils. The ability of roots to extract water is determined by combined soil...... and plant characteristics, and how to model it has been of interest for many years. Most macroscopic models for water uptake operate at soil profile scale under the assumption that the uptake rate depends on root density and soil moisture. Whilst proved appropriate, these models need spatio-temporal root...

Temporal entrainment of cognitive functions: musical mnemonics induce brain plasticity and oscillatory synchrony in neural networks underlying memory.

Science.gov (United States)

Thaut, Michael H; Peterson, David A; McIntosh, Gerald C

2005-12-01

In a series of experiments, we have begun to investigate the effect of music as a mnemonic device on learning and memory and the underlying plasticity of oscillatory neural networks. We used verbal learning and memory tests (standardized word lists, AVLT) in conjunction with electroencephalographic analysis to determine differences between verbal learning in either a spoken or musical (verbal materials as song lyrics) modality. In healthy adults, learning in both the spoken and music condition was associated with significant increases in oscillatory synchrony across all frequency bands. A significant difference between the spoken and music condition emerged in the cortical topography of the learning-related synchronization. When using EEG measures as predictors during learning for subsequent successful memory recall, significantly increased coherence (phase-locked synchronization) within and between oscillatory brain networks emerged for music in alpha and gamma bands. In a similar study with multiple sclerosis patients, superior learning and memory was shown in the music condition when controlled for word order recall, and subjects were instructed to sing back the word lists. Also, the music condition was associated with a significant power increase in the low-alpha band in bilateral frontal networks, indicating increased neuronal synchronization. Musical learning may access compensatory pathways for memory functions during compromised PFC functions associated with learning and recall. Music learning may also confer a neurophysiological advantage through the stronger synchronization of the neuronal cell assemblies underlying verbal learning and memory. Collectively our data provide evidence that melodic-rhythmic templates as temporal structures in music may drive internal rhythm formation in recurrent cortical networks involved in learning and memory.

Biochemical Stimulus-Based Strategies for Meniscus Tissue Engineering and Regeneration

Science.gov (United States)

Chen, Mingxue; Guo, Weimin; Gao, Shunag; Hao, Chunxiang; Shen, Shi; Zhang, Zengzeng; Wang, Zhenyong; Wang, Zehao; Li, Xu; Jing, Xiaoguang; Zhang, Xueliang; Yuan, Zhiguo; Wang, Mingjie; Zhang, Yu; Peng, Jiang; Wang, Aiyuan; Wang, Yu; Sui, Xiang

2018-01-01

Meniscus injuries are very common and still pose a challenge for the orthopedic surgeon. Meniscus injuries in the inner two-thirds of the meniscus remain incurable. Tissue-engineered meniscus strategies seem to offer a new approach for treating meniscus injuries with a combination of seed cells, scaffolds, and biochemical or biomechanical stimulation. Cell- or scaffold-based strategies play a pivotal role in meniscus regeneration. Similarly, biochemical and biomechanical stimulation are also important. Seed cells and scaffolds can be used to construct a tissue-engineered tissue; however, stimulation to enhance tissue maturation and remodeling is still needed. Such stimulation can be biomechanical or biochemical, but this review focuses only on biochemical stimulation. Growth factors (GFs) are one of the most important forms of biochemical stimulation. Frequently used GFs always play a critical role in normal limb development and growth. Further understanding of the functional mechanism of GFs will help scientists to design the best therapy strategies. In this review, we summarize some of the most important GFs in tissue-engineered menisci, as well as other types of biological stimulation. PMID:29581987

Analysis of Network Vulnerability Under Joint Node and Link Attacks

Science.gov (United States)

Li, Yongcheng; Liu, Shumei; Yu, Yao; Cao, Ting

2018-03-01

The security problem of computer network system is becoming more and more serious. The fundamental reason is that there are security vulnerabilities in the network system. Therefore, it’s very important to identify and reduce or eliminate these vulnerabilities before they are attacked. In this paper, we are interested in joint node and link attacks and propose a vulnerability evaluation method based on the overall connectivity of the network to defense this attack. Especially, we analyze the attack cost problem from the attackers’ perspective. The purpose is to find the set of least costs for joint links and nodes, and their deletion will lead to serious network connection damage. The simulation results show that the vulnerable elements obtained from the proposed method are more suitable for the attacking idea of the malicious persons in joint node and link attack. It is easy to find that the proposed method has more realistic protection significance.

Synthesis and Design of Biorefinery Processing Networks with Uncertainty and Sustainability analysis

DEFF Research Database (Denmark)

Cheali, Peam; Gernaey, Krist; Sin, Gürkan

combinations of processing networks. The optimization of the network is formulated as a mixed integer nonlinear programming type of problem and solved in GAMS. The methodology was applied for designing optimal biorefinery networks considering biochemical routes. Furthermore, the methodology has also been...... for processing renewable feedstocks, with the aim of bridging the gap for fuel, chemical and material production. This project is focusing on biorefinery network design, in particular for early stage design and development studies. Optimal biorefinery design is a challenging problem. It is a multi......-objective decision-making problem not only with respect to technical and economic feasibility but also with respect to environmental impacts, sustainability constraints and limited availability & uncertainties of input data at the early design stage. It is therefore useful to develop a systematic methodology...

Biochemical toxicology of environmental agents

International Nuclear Information System (INIS)

Bruin, A. de

1976-01-01

A thorough and up-to-date account of the molecular-biological aspects of harmful agents - both chemical and physical - is given. This current treatise is principally intended to serve as an informative reference work for researchers in various areas of the field. In the pursuit of this aim, a devision of the entire field into 42 chapters has been made. Each chapter starts with a short introductory account dealing with the biochemical essentials of the particular subject. Radiation effects are discussed briefly at the end of each treatise. In order to make the treatise useful as a source book, a substantial collection of pertinent literature references is provided which are numbered in order of citation in the text. Initial chapters are devoted to the metabolic fate of the major classes of xenobiotic compounds. Peripheral topics, closely related to metabolism and dealing with modification of xenobiotic-metabolizing ability, as well as interaction phenomena follow (chs. 5-8). Subjects that draw heavily on the practical field of occupational hygiene are dealt with in chapters 9 and 10. The systematic treatment of how chemical and physical agents interact with the various biochemical and enzymatic systems they encounter during their passage through the organism occupies quantitatively the main part of the book (chs. 11-36). Finally, radiation biochemistry is discussed from the viewpoint of its high degree of scientific advancement, and secondly because the type of biochemical changes produced in vivo by X-rays closely parallel those evoked by chemical agents

Enzyme and biochemical producing fungi

DEFF Research Database (Denmark)

Lübeck, Peter Stephensen; Lübeck, Mette; Nilsson, Lena

2010-01-01

factories for sustainable production of important molecules. For developing fungi into efficient cell factories, the project includes identification of important factors that control the flux through the pathways using metabolic flux analysis and metabolic engineering of biochemical pathways....

One-dimensional model of cable-in-conduit superconductors under cyclic loading using artificial neural networks

International Nuclear Information System (INIS)

Lefik, M.; Schrefler, B.A.

2002-01-01

An artificial neural network with two hidden layers is trained to define a mechanical constitutive relation for superconducting cable under transverse cyclic loading. The training is performed using a set of experimental data. The behaviour of the cable is strongly non-linear. Irreversible phenomena result with complicated loops of hysteresis. The performance of the ANN, which is applied as a tool for storage, interpolation and interpretation of experimental data is investigated, both from numerical, as well as from physical viewpoints

Molecular cloning and biochemical characterization of an α-amylase family from Aspergillus niger

Directory of Open Access Journals (Sweden)

Junying Wang

2018-03-01

Full Text Available Background: α-Amylase is widely used in the starch processing, food and paper industries, hydrolyzing starch, glycogen and other polysaccharides into glucose, maltose and oligosaccharides. An α-amylase gene family from Aspergillus niger CBS513.88 encode eight putative α-amylases. The differences and similarities, biochemical properties and functional diversity among these eight α-amylases remain unknown. Results: The eight genes were cloned and expressed in Pichia pastoris GS115 by shaking-flask fermentation under the induction of methanol. The sequence alignment, biochemical characterizations and product analysis of starch hydrolysis by these α-amylases were investigated. It is found that the eight α-amylases belonged to three different groups with the typical structure of fungal α-amylase. They exhibited maximal activities at 30–40°C except AmyG and were all stable at acidic pH. Ca2+ and EDTA had no effects on the activities of α-amylases except AmyF and AmyH, indicating that the six amylases were Ca2+ independent. Two novel α-amylases of AmyE and AmyF were found. AmyE hydrolyzed starch into maltose, maltotriose and a small amount of glucose, while AmyF hydrolyzed starch into mainly glucose. The excellent physical and chemical properties including high acidic stability, Ca2+-independent and high maltotriose-forming capacity make AmyE suitable in food and sugar syrup industries. Conclusions: This study illustrates that a gene family can encode multiple enzymes members having remarkable differences in biochemical properties. It provides not only new insights into evolution and functional divergence among different members of an α-amylase family, but the development of new enzymes for industrial application. Keywords: Biochemical properties, Food industry, Fungal α-amylase, Glycosyl hydrolase family, Glycosyl hydrolase family, Industrial application, Paper industry, Recombinant Pichia pastoris, Starch processing, α-amylase cloning

Probabilistic sensitivity analysis of biochemical reaction systems.

Science.gov (United States)

Zhang, Hong-Xuan; Dempsey, William P; Goutsias, John

2009-09-07

Sensitivity analysis is an indispensable tool for studying the robustness and fragility properties of biochemical reaction systems as well as for designing optimal approaches for selective perturbation and intervention. Deterministic sensitivity analysis techniques, using derivatives of the system response, have been extensively used in the literature. However, these techniques suffer from several drawbacks, which must be carefully considered before using them in problems of systems biology. We develop here a probabilistic approach to sensitivity analysis of biochemical reaction systems. The proposed technique employs a biophysically derived model for parameter fluctuations and, by using a recently suggested variance-based approach to sensitivity analysis [Saltelli et al., Chem. Rev. (Washington, D.C.) 105, 2811 (2005)], it leads to a powerful sensitivity analysis methodology for biochemical reaction systems. The approach presented in this paper addresses many problems associated with derivative-based sensitivity analysis techniques. Most importantly, it produces thermodynamically consistent sensitivity analysis results, can easily accommodate appreciable parameter variations, and allows for systematic investigation of high-order interaction effects. By employing a computational model of the mitogen-activated protein kinase signaling cascade, we demonstrate that our approach is well suited for sensitivity analysis of biochemical reaction systems and can produce a wealth of information about the sensitivity properties of such systems. The price to be paid, however, is a substantial increase in computational complexity over derivative-based techniques, which must be effectively addressed in order to make the proposed approach to sensitivity analysis more practical.

Defense strategies for asymmetric networked systems under composite utilities

Energy Technology Data Exchange (ETDEWEB)

Rao, Nageswara S. [ORNL; Ma, Chris Y. T. [Hang Seng Management College, Hon Kong; Hausken, Kjell [University of Stavanger, Norway; He, Fei [Texas A& M University, Kingsville, TX, USA; Yau, David K. Y. [Singapore University of Technology and Design; Zhuang, Jun [University at Buffalo (SUNY)

2017-11-01

We consider an infrastructure of networked systems with discrete components that can be reinforced at certain costs to guard against attacks. The communications network plays a critical, asymmetric role of providing the vital connectivity between the systems. We characterize the correlations within this infrastructure at two levels using (a) aggregate failure correlation function that specifies the infrastructure failure probability giventhe failure of an individual system or network, and (b) first order differential conditions on system survival probabilities that characterize component-level correlations. We formulate an infrastructure survival game between an attacker and a provider, who attacks and reinforces individual components, respectively. They use the composite utility functions composed of a survival probability term and a cost term, and the previously studiedsum-form and product-form utility functions are their special cases. At Nash Equilibrium, we derive expressions for individual system survival probabilities and the expected total number of operational components. We apply and discuss these estimates for a simplified model of distributed cloud computing infrastructure

Alterations in reducing sugar in Triticum aestivum under irrigated ...

African Journals Online (AJOL)

DELL

2012-03-13

47 ... unstable with respect to yield and yield components. ... Wheat (Triticum aestivum), one of the important staple ... stress affects many physiological and biochemical ... regulation as the osmolyte under adverse environmental.

A Non-Targeted Approach Unravels the Volatile Network in Peach Fruit

Science.gov (United States)

Sánchez, Gerardo; Besada, Cristina; Badenes, María Luisa; Monforte, Antonio José; Granell, Antonio

2012-01-01

Volatile compounds represent an important part of the plant metabolome and are of particular agronomic and biological interest due to their contribution to fruit aroma and flavor and therefore to fruit quality. By using a non-targeted approach based on HS-SPME-GC-MS, the volatile-compound complement of peach fruit was described. A total of 110 volatile compounds (including alcohols, ketones, aldehydes, esters, lactones, carboxylic acids, phenolics and terpenoids) were identified and quantified in peach fruit samples from different genetic backgrounds, locations, maturity stages and physiological responses. By using a combination of hierarchical cluster analysis and metabolomic correlation network analysis we found that previously known peach fruit volatiles are clustered according to their chemical nature or known biosynthetic pathways. Moreover, novel volatiles that had not yet been described in peach were identified and assigned to co-regulated groups. In addition, our analyses showed that most of the co-regulated groups showed good intergroup correlations that are therefore consistent with the existence of a higher level of regulation orchestrating volatile production under different conditions and/or developmental stages. In addition, this volatile network of interactions provides the ground information for future biochemical studies as well as a useful route map for breeding or biotechnological purposes. PMID:22761719

Dysfunctional default mode network and executive control network in people with Internet gaming disorder: Independent component analysis under a probability discounting task.

Science.gov (United States)

Wang, L; Wu, L; Lin, X; Zhang, Y; Zhou, H; Du, X; Dong, G

2016-04-01

The present study identified the neural mechanism of risky decision-making in Internet gaming disorder (IGD) under a probability discounting task. Independent component analysis was used on the functional magnetic resonance imaging data from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years). For the behavioral results, IGD subjects prefer the risky to the fixed options and showed shorter reaction time compared to HC. For the imaging results, the IGD subjects showed higher task-related activity in default mode network (DMN) and less engagement in the executive control network (ECN) than HC when making the risky decisions. Also, we found the activities of DMN correlate negatively with the reaction time and the ECN correlate positively with the probability discounting rates. The results suggest that people with IGD show altered modulation in DMN and deficit in executive control function, which might be the reason for why the IGD subjects continue to play online games despite the potential negative consequences. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Simulation of biochemical reactions with time-dependent rates by the rejection-based algorithm

Energy Technology Data Exchange (ETDEWEB)

Thanh, Vo Hong, E-mail: vo@cosbi.eu [The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Priami, Corrado, E-mail: priami@cosbi.eu [The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068 (Italy); Department of Mathematics, University of Trento, Trento (Italy)

2015-08-07

We address the problem of simulating biochemical reaction networks with time-dependent rates and propose a new algorithm based on our rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)]. The computation for selecting next reaction firings by our time-dependent RSSA (tRSSA) is computationally efficient. Furthermore, the generated trajectory is exact by exploiting the rejection-based mechanism. We benchmark tRSSA on different biological systems with varying forms of reaction rates to demonstrate its applicability and efficiency. We reveal that for nontrivial cases, the selection of reaction firings in existing algorithms introduces approximations because the integration of reaction rates is very computationally demanding and simplifying assumptions are introduced. The selection of the next reaction firing by our approach is easier while preserving the exactness.

Biochemical effects of gamma irradiation on banana fruits

International Nuclear Information System (INIS)

El-Motaium, R.A.

1980-01-01

It is of important to study the extension of shelf-life at ambient temperature. This study would be of significant in the case of non- refrigerated transport, practices within the country and transhipment to distant countries. studies have therefore extended to assess the shelf-life of irradiated banana stored under-room temperature. Extension of shelf -life have been achieved by many methods, the most modern one is using gamma irradiation as a promising technology for developing nations. the aim of this investigation is to study the biochemical effects of gamma irradiation on G ros Michel m ature green banana fruits and also to determine the optimum dose level and the optimum storage conditions which resulted in, keeping the organoleptic qualities as it is and maximum extension in shelf-life

Optimization of waste to energy routes through biochemical and thermochemical treatment options of municipal solid waste in Hyderabad, Pakistan

International Nuclear Information System (INIS)

Korai, Muhammad Safar; Mahar, Rasool Bux; Uqaili, Muhammad Aslam

2016-01-01

Highlights: • Existing practice of municipal solid waste management of Hyderabad city, Pakistan have been analyzed. • Development of scenarios on basis of nature of waste components for optimizing waste to energy route. • Analyzing the biochemical and thermochemical potential of MSW through various scenarios. • Evaluation of various treatment technologies under scenarios to optimize waste to energy route. - Abstract: Improper disposal of municipal solid waste (MSW) has created many environmental problems in Pakistan and the country is facing energy shortages as well. The present study evaluates the biochemical and thermochemical treatment options of MSW in order to address both the endemic environmental challenges and in part the energy shortage. According to the nature of waste components, a number of scenarios were developed to optimize the waste to energy (WTE) routes. The evaluation of treatment options has been performed by mathematical equations using the special characteristics of MSW. The power generation potential (PGP) of biochemical (anaerobic digestion) has been observed in the range of 5.9–11.3 kW/ton day under various scenarios. The PGP of Refuse Derived Fuel (RDF), Mass Burn Incinerator (MBI), Gasification/Pyrolysis (Gasi./Pyro.) and Plasma Arc Gasification (PAG) have been found to be in the range of 2.7–118.6 kW/ton day, 3.8–164.7 kW/ton day, 4.2–184.5 kW/ton day and 5.2–224 kW/ton day, respectively. The highest values of biochemical and all thermochemical technologies have been obtained through the use of scenarios including the putrescible components (PCs) of MSW such as food and yard wastes, and the non-biodegradable components (NBCs) of MSW such as plastic, rubber, leather, textile and wood respectively. Therefore, routes which include these components are the optimized WTE routes for maximum PGP by biochemical and thermochemical treatments of MSW. The findings of study lead to recommend that socio-economic and environmental

Effect of maltose and trehalose on growth, yield and some biochemical components of wheat plant under water stress

Directory of Open Access Journals (Sweden)