Competing endogenous RNA network analysis identifies critical genes among the different breast cancer subtypes.

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Chen, Juan; Xu, Juan; Li, Yongsheng; Zhang, Jinwen; Chen, Hong; Lu, Jianping; Wang, Zishan; Zhao, Xueying; Xu, Kang; Li, Yixue; Li, Xia; Zhang, Yan

2017-02-07

Although competing endogenous RNAs (ceRNAs) have been implicated in many solid tumors, their roles in breast cancer subtypes are not well understood. We therefore generated a ceRNA network for each subtype based on the significance of both, positive co-expression and the shared miRNAs, in the corresponding subtype miRNA dys-regulatory network, which was constructed based on negative regulations between differentially expressed miRNAs and targets. All four subtype ceRNA networks exhibited scale-free architecture and showed that the common ceRNAs were at the core of the networks. Furthermore, the common ceRNA hubs had greater connectivity than the subtype-specific hubs. Functional analysis of the common subtype ceRNA hubs highlighted factors involved in proliferation, MAPK signaling pathways and tube morphogenesis. Subtype-specific ceRNA hubs highlighted unique subtype-specific pathways, like the estrogen response and inflammatory pathways in the luminal subtypes or the factors involved in the coagulation process that participates in the basal-like subtype. Ultimately, we identified 29 critical subtype-specific ceRNA hubs that characterized the different breast cancer subtypes. Our study thus provides new insight into the common and specific subtype ceRNA interactions that define the different categories of breast cancer and enhances our understanding of the pathology underlying the different breast cancer subtypes, which can have prognostic and therapeutic implications in the future.

Network features and pathway analyses of a signal transduction cascade

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Ryoji Yanashima

2009-05-01

Full Text Available The scale-free and small-world network models reflect the functional units of networks. However, when we investigated the network properties of a signaling pathway using these models, no significant differences were found between the original undirected graphs and the graphs in which inactive proteins were eliminated from the gene expression data. We analyzed signaling networks by focusing on those pathways that best reflected cellular function. Therefore, our analysis of pathways started from the ligands and progressed to transcription factors and cytoskeletal proteins. We employed the Python module to assess the target network. This involved comparing the original and restricted signaling cascades as a directed graph using microarray gene expression profiles of late onset Alzheimer's disease. The most commonly used method of shortest-path analysis neglects to consider the influences of alternative pathways that can affect the activation of transcription factors or cytoskeletal proteins. We therefore introduced included k-shortest paths and k-cycles in our network analysis using the Python modules, which allowed us to attain a reasonable computational time and identify k-shortest paths. This technique reflected results found in vivo and identified pathways not found when shortest path or degree analysis was applied. Our module enabled us to comprehensively analyse the characteristics of biomolecular networks and also enabled analysis of the effects of diseases considering the feedback loop and feedforward loop control structures as an alternative path.

KeyPathwayMiner - De-novo network enrichment by combining multiple OMICS data and biological networks

DEFF Research Database (Denmark)

Baumbach, Jan; Alcaraz, Nicolas; Pauling, Josch K.

We tackle the problem of de-novo pathway extraction. Given a biological network and a set of case-control studies, KeyPathwayMiner efficiently extracts and visualizes all maximal connected sub-networks that contain mainly genes that are dysregulated, e.g., differentially expressed, in most cases ...

Pathways, Networks and Systems Medicine Conferences

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Nadeau, Joseph H. [Pacific Northwest Research Institute

2013-11-25

The 6th Pathways, Networks and Systems Medicine Conference was held at the Minoa Palace Conference Center, Chania, Crete, Greece (16-21 June 2008). The Organizing Committee was composed of Joe Nadeau (CWRU, Cleveland), Rudi Balling (German Research Centre, Brauschweig), David Galas (Institute for Systems Biology, Seattle), Lee Hood (Institute for Systems Biology, Seattle), Diane Isonaka (Seattle), Fotis Kafatos (Imperial College, London), John Lambris (Univ. Pennsylvania, Philadelphia),Harris Lewin (Univ. of Indiana, Urbana-Champaign), Edison Liu (Genome Institute of Singapore, Singapore), and Shankar Subramaniam (Univ. California, San Diego). A total of 101 individuals from 21 countries participated in the conference: USA (48), Canada (5), France (5), Austria (4), Germany (3), Italy (3), UK (3), Greece (2), New Zealand (2), Singapore (2), Argentina (1), Australia (1), Cuba (1), Denmark (1), Japan (1), Mexico (1), Netherlands (1), Spain (1), Sweden (1), Switzerland (1). With respect to speakers, 29 were established faculty members and 13 were graduate students or postdoctoral fellows. With respect to gender representation, among speakers, 13 were female and 28 were male, and among all participants 43 were female and 58 were male. Program these included the following topics: Cancer Pathways and Networks (Day 1), Metabolic Disease Networks (Day 2), Day 3 ? Organs, Pathways and Stem Cells (Day 3), and Day 4 ? Inflammation, Immunity, Microbes and the Environment (Day 4). Proceedings of the Conference were not published.

Adverse Outcome Pathway Networks II: Network Analytics.

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Villeneuve, Daniel L; Angrish, Michelle M; Fortin, Marie C; Katsiadaki, Ioanna; Leonard, Marc; Margiotta-Casaluci, Luigi; Munn, Sharon; O'Brien, Jason M; Pollesch, Nathan L; Smith, L Cody; Zhang, Xiaowei; Knapen, Dries

2018-02-28

Toxicological responses to stressors are more complex than the simple one biological perturbation to one adverse outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present paper introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory-based approaches for identifying important topological features are illustrated using two example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses, or previously undefined emergent patterns of response, are introduced. Along with a companion article (Knapen et al. part I), these concepts set the stage for development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. Collectively, this work addresses one of the major themes identified through a SETAC Horizon Scanning effort focused on advancing the AOP framework. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Benchmarking pathway interaction network for colorectal cancer to identify dysregulated pathways

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Q. Wang

Full Text Available Different pathways act synergistically to participate in many biological processes. Thus, the purpose of our study was to extract dysregulated pathways to investigate the pathogenesis of colorectal cancer (CRC based on the functional dependency among pathways. Protein-protein interaction (PPI information and pathway data were retrieved from STRING and Reactome databases, respectively. After genes were aligned to the pathways, each pathway activity was calculated using the principal component analysis (PCA method, and the seed pathway was discovered. Subsequently, we constructed the pathway interaction network (PIN, where each node represented a biological pathway based on gene expression profile, PPI data, as well as pathways. Dysregulated pathways were then selected from the PIN according to classification performance and seed pathway. A PIN including 11,960 interactions was constructed to identify dysregulated pathways. Interestingly, the interaction of mRNA splicing and mRNA splicing-major pathway had the highest score of 719.8167. Maximum change of the activity score between CRC and normal samples appeared in the pathway of DNA replication, which was selected as the seed pathway. Starting with this seed pathway, a pathway set containing 30 dysregulated pathways was obtained with an area under the curve score of 0.8598. The pathway of mRNA splicing, mRNA splicing-major pathway, and RNA polymerase I had the maximum genes of 107. Moreover, we found that these 30 pathways had crosstalks with each other. The results suggest that these dysregulated pathways might be used as biomarkers to diagnose CRC.

Self-organized criticality in developing neuronal networks.

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Christian Tetzlaff

Full Text Available Recently evidence has accumulated that many neural networks exhibit self-organized criticality. In this state, activity is similar across temporal scales and this is beneficial with respect to information flow. If subcritical, activity can die out, if supercritical epileptiform patterns may occur. Little is known about how developing networks will reach and stabilize criticality. Here we monitor the development between 13 and 95 days in vitro (DIV of cortical cell cultures (n = 20 and find four different phases, related to their morphological maturation: An initial low-activity state (≈19 DIV is followed by a supercritical (≈20 DIV and then a subcritical one (≈36 DIV until the network finally reaches stable criticality (≈58 DIV. Using network modeling and mathematical analysis we describe the dynamics of the emergent connectivity in such developing systems. Based on physiological observations, the synaptic development in the model is determined by the drive of the neurons to adjust their connectivity for reaching on average firing rate homeostasis. We predict a specific time course for the maturation of inhibition, with strong onset and delayed pruning, and that total synaptic connectivity should be strongly linked to the relative levels of excitation and inhibition. These results demonstrate that the interplay between activity and connectivity guides developing networks into criticality suggesting that this may be a generic and stable state of many networks in vivo and in vitro.

Critical behavior of the contact process on small-world networks

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Ferreira, Ronan S.; Ferreira, Silvio C.

2013-11-01

We investigate the role of clustering on the critical behavior of the contact process (CP) on small-world networks using the Watts-Strogatz (WS) network model with an edge rewiring probability p. The critical point is well predicted by a homogeneous cluster-approximation for the limit of vanishing clustering ( p → 1). The critical exponents and dimensionless moment ratios of the CP are in agreement with those predicted by the mean-field theory for any p > 0. This independence on the network clustering shows that the small-world property is a sufficient condition for the mean-field theory to correctly predict the universality of the model. Moreover, we compare the CP dynamics on WS networks with rewiring probability p = 1 and random regular networks and show that the weak heterogeneity of the WS network slightly changes the critical point but does not alter other critical quantities of the model.

Critical pathways of change in fruit export regions at desert margin (Chile)

DEFF Research Database (Denmark)

Frederiksen, Peter

The purpose is to elucidate how critical pathways function in a fruit export region at the desert margin in Chile. The region was investigated at the system level as an open land system with managed fruit plantations in a geographically complex valley. Data collection procedures included total...... change changed pathways. Pathways resulted from a combination of global value chains, the adoption of innovations, past climate change, and regional conditions at different scales. Main pathways of change were upgrade and downgrade of the fruit export region and irrigation systems, whereas the breaking...... areas and not in others. The probable future is expected to be increased separation of intraregional pathways and a more imbalanced region. The conclusion is that openness is the main property responsible for critical pathways of change in the region....

Investigating multiple dysregulated pathways in rheumatoid arthritis based on pathway interaction network.

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Song, Xian-Dong; Song, Xian-Xu; Liu, Gui-Bo; Ren, Chun-Hui; Sun, Yuan-Bo; Liu, Ke-Xin; Liu, Bo; Liang, Shuang; Zhu, Zhu

2018-03-01

The traditional methods of identifying biomarkers in rheumatoid arthritis (RA) have focussed on the differentially expressed pathways or individual pathways, which however, neglect the interactions between pathways. To better understand the pathogenesis of RA, we aimed to identify dysregulated pathway sets using a pathway interaction network (PIN), which considered interactions among pathways. Firstly, RA-related gene expression profile data, protein-protein interactions (PPI) data and pathway data were taken up from the corresponding databases. Secondly, principal component analysis method was used to calculate the pathway activity of each of the pathway, and then a seed pathway was identified using data gleaned from the pathway activity. A PIN was then constructed based on the gene expression profile, pathway data, and PPI information. Finally, the dysregulated pathways were extracted from the PIN based on the seed pathway using the method of support vector machines and an area under the curve (AUC) index. The PIN comprised of a total of 854 pathways and 1064 pathway interactions. The greatest change in the activity score between RA and control samples was observed in the pathway of epigenetic regulation of gene expression, which was extracted and regarded as the seed pathway. Starting with this seed pathway, one maximum pathway set containing 10 dysregulated pathways was extracted from the PIN, having an AUC of 0.8249, and the result indicated that this pathway set could distinguish RA from the controls. These 10 dysregulated pathways might be potential biomarkers for RA diagnosis and treatment in the future.

Network dynamics in nociceptive pathways assessed by the neuronal avalanche model

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Wu José

2012-04-01

Full Text Available Abstract Background Traditional electroencephalography provides a critical assessment of pain responses. The perception of pain, however, may involve a series of signal transmission pathways in higher cortical function. Recent studies have shown that a mathematical method, the neuronal avalanche model, may be applied to evaluate higher-order network dynamics. The neuronal avalanche is a cascade of neuronal activity, the size distribution of which can be approximated by a power law relationship manifested by the slope of a straight line (i.e., the α value. We investigated whether the neuronal avalanche could be a useful index for nociceptive assessment. Findings Neuronal activity was recorded with a 4 × 8 multichannel electrode array in the primary somatosensory cortex (S1 and anterior cingulate cortex (ACC. Under light anesthesia, peripheral pinch stimulation increased the slope of the α value in both the ACC and S1, whereas brush stimulation increased the α value only in the S1. The increase in α values was blocked in both regions under deep anesthesia. The increase in α values in the ACC induced by peripheral pinch stimulation was blocked by medial thalamic lesion, but the increase in α values in the S1 induced by brush and pinch stimulation was not affected. Conclusions The neuronal avalanche model shows a critical state in the cortical network for noxious-related signal processing. The α value may provide an index of brain network activity that distinguishes the responses to somatic stimuli from the control state. These network dynamics may be valuable for the evaluation of acute nociceptive processes and may be applied to chronic pathological pain conditions.

Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle

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Ram Prahlad T

2008-08-01

Full Text Available Abstract Background In systems biology the experimentalist is presented with a selection of software for analyzing dynamic properties of signaling networks. These tools either assume that the network is in steady-state or require highly parameterized models of the network of interest. For biologists interested in assessing how signal propagates through a network under specific conditions, the first class of methods does not provide sufficiently detailed results and the second class requires models which may not be easily and accurately constructed. A tool that is able to characterize the dynamics of a signaling network using an unparameterized model of the network would allow biologists to quickly obtain insights into a signaling network's behavior. Results We introduce PathwayOracle, an integrated suite of software tools for computationally inferring and analyzing structural and dynamic properties of a signaling network. The feature which differentiates PathwayOracle from other tools is a method that can predict the response of a signaling network to various experimental conditions and stimuli using only the connectivity of the signaling network. Thus signaling models are relatively easy to build. The method allows for tracking signal flow in a network and comparison of signal flows under different experimental conditions. In addition, PathwayOracle includes tools for the enumeration and visualization of coherent and incoherent signaling paths between proteins, and for experimental analysis – loading and superimposing experimental data, such as microarray intensities, on the network model. Conclusion PathwayOracle provides an integrated environment in which both structural and dynamic analysis of a signaling network can be quickly conducted and visualized along side experimental results. By using the signaling network connectivity, analyses and predictions can be performed quickly using relatively easily constructed signaling network models

Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

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Kirouac Daniel C

2012-05-01

Full Text Available Abstract Background Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID, PANTHER, Reactome, I2D, and STRING. We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data. Results We have assembled an ensemble network from multiple on-line sources representing a significant portion of all machine-readable and reconcilable human knowledge on proteins and protein interactions involved in inflammation. This ensemble network has many features expected of complex signalling networks assembled from high-throughput data: a power law distribution of both node degree and edge annotations, and topological features of a “bow tie” architecture in which diverse pathways converge on a highly conserved set of enzymatic cascades focused around PI3K/AKT, MAPK/ERK, JAK/STAT, NFκB, and apoptotic signaling. Individual pathways exhibit “fuzzy” modularity that is statistically significant but still involving a majority of “cross-talk” interactions. However, we find that the most widely used pathway databases are highly inconsistent with respect to the actual constituents and interactions in this network. Using a set of growth factor signalling networks as examples (epidermal growth factor, transforming growth factor-beta, tumor necrosis factor, and wingless, we find a multiplicity of network topologies in which receptors couple to downstream

Exploring Practice-Research Networks for Critical Professional Learning

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Appleby, Yvon; Hillier, Yvonne

2012-01-01

This paper discusses the contribution that practice-research networks can make to support critical professional development in the Learning and Skills sector in England. By practice-research networks we mean groups or networks which maintain a connection between research and professional practice. These networks stem from the philosophy of…

Criticality is an emergent property of genetic networks that exhibit evolvability.

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Christian Torres-Sosa

Full Text Available Accumulating experimental evidence suggests that the gene regulatory networks of living organisms operate in the critical phase, namely, at the transition between ordered and chaotic dynamics. Such critical dynamics of the network permits the coexistence of robustness and flexibility which are necessary to ensure homeostatic stability (of a given phenotype while allowing for switching between multiple phenotypes (network states as occurs in development and in response to environmental change. However, the mechanisms through which genetic networks evolve such critical behavior have remained elusive. Here we present an evolutionary model in which criticality naturally emerges from the need to balance between the two essential components of evolvability: phenotype conservation and phenotype innovation under mutations. We simulated the Darwinian evolution of random Boolean networks that mutate gene regulatory interactions and grow by gene duplication. The mutating networks were subjected to selection for networks that both (i preserve all the already acquired phenotypes (dynamical attractor states and (ii generate new ones. Our results show that this interplay between extending the phenotypic landscape (innovation while conserving the existing phenotypes (conservation suffices to cause the evolution of all the networks in a population towards criticality. Furthermore, the networks produced by this evolutionary process exhibit structures with hubs (global regulators similar to the observed topology of real gene regulatory networks. Thus, dynamical criticality and certain elementary topological properties of gene regulatory networks can emerge as a byproduct of the evolvability of the phenotypic landscape.

Critical cooperation range to improve spatial network robustness.

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Vitor H P Louzada

Full Text Available A robust worldwide air-transportation network (WAN is one that minimizes the number of stranded passengers under a sequence of airport closures. Building on top of this realistic example, here we address how spatial network robustness can profit from cooperation between local actors. We swap a series of links within a certain distance, a cooperation range, while following typical constraints of spatially embedded networks. We find that the network robustness is only improved above a critical cooperation range. Such improvement can be described in the framework of a continuum transition, where the critical exponents depend on the spatial correlation of connected nodes. For the WAN we show that, except for Australia, all continental networks fall into the same universality class. Practical implications of this result are also discussed.

Enabling software defined networking experiments in networked critical infrastructures

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Béla Genge

2014-05-01

Full Text Available Nowadays, the fact that Networked Critical Infrastructures (NCI, e.g., power plants, water plants, oil and gas distribution infrastructures, and electricity grids, are targeted by significant cyber threats is well known. Nevertheless, recent research has shown that specific characteristics of NCI can be exploited in the enabling of more efficient mitigation techniques, while novel techniques from the field of IP networks can bring significant advantages. In this paper we explore the interconnection of NCI communication infrastructures with Software Defined Networking (SDN-enabled network topologies. SDN provides the means to create virtual networking services and to implement global networking decisions. It relies on OpenFlow to enable communication with remote devices and has been recently categorized as the “Next Big Technology”, which will revolutionize the way decisions are implemented in switches and routers. Therefore, the paper documents the first steps towards enabling an SDN-NCI and presents the impact of a Denial of Service experiment over traffic resulting from an XBee sensor network which is routed across an emulated SDN network.

Adverse Outcome Pathway Network Analyses: Techniques and benchmarking the AOPwiki

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Abstract: As the community of toxicological researchers, risk assessors, and risk managers adopt the adverse outcome pathway (AOP) paradigm for organizing toxicological knowledge, the number and diversity of adverse outcome pathways and AOP networks are continuing to grow. This ...

Using consensus bayesian network to model the reactive oxygen species regulatory pathway.

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Liangdong Hu

Full Text Available Bayesian network is one of the most successful graph models for representing the reactive oxygen species regulatory pathway. With the increasing number of microarray measurements, it is possible to construct the bayesian network from microarray data directly. Although large numbers of bayesian network learning algorithms have been developed, when applying them to learn bayesian networks from microarray data, the accuracies are low due to that the databases they used to learn bayesian networks contain too few microarray data. In this paper, we propose a consensus bayesian network which is constructed by combining bayesian networks from relevant literatures and bayesian networks learned from microarray data. It would have a higher accuracy than the bayesian networks learned from one database. In the experiment, we validated the bayesian network combination algorithm on several classic machine learning databases and used the consensus bayesian network to model the Escherichia coli's ROS pathway.

Pathway Relevance Ranking for Tumor Samples through Network-Based Data Integration.

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Lieven P C Verbeke

Full Text Available The study of cancer, a highly heterogeneous disease with different causes and clinical outcomes, requires a multi-angle approach and the collection of large multi-omics datasets that, ideally, should be analyzed simultaneously. We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single comprehensive network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. We demonstrate the performance of the new method by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method's potential to identify key pathways involved in breast cancer development shared by different molecular subtypes is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi-genetic disturbances were diverse. Next to prioritizing universally high-scoring pathways, the pathway ranking method was able to identify subtype-specific pathways. Often the score of a pathway could not be motivated by a single mutation, copy number or methylation alteration, but rather by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method's ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad

Critical success factors in implementing clinical pathways/case management.

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Choo, J

2001-07-01

With the advent of casemix reimbursement implementation, rapid technological changes, an ageing population and changing consumer behaviour, the Singapore health care industry is faced with the impetus to provide a cost-effective and efficient care delivery system. One ubiquitous tool used is the establishment of a clinical pathway/case management programme within the hospital. As the concept of clinical pathway for patient care is a relatively new concept in Singapore, several critical factors must be considered to ensure successful implementation of clinical pathway/case management programme. One key success factor lies in continued clinician support and acceptance. Other factors include top management leadership and support and a dedicated team of case managers, nurses and paramedical professionals.

CRITICAL RADIONUCLIDE AND PATHWAY ANALYSIS FOR THE SAVANNAH RIVER SITE

Energy Technology Data Exchange (ETDEWEB)

Jannik, T.

2011-08-30

This report is an update to the analysis, Assessment of SRS Radiological Liquid and Airborne Contaminants and Pathways, that was performed in 1997. An electronic version of this large original report is included in the attached CD to this report. During the operational history (1954 to the present) of the Savannah River Site (SRS), many different radionuclides have been released to the environment from the various production facilities. However, as will be shown by this updated radiological critical contaminant/critical pathway analysis, only a small number of the released radionuclides have been significant contributors to potential doses and risks to offsite people. The analysis covers radiological releases to the atmosphere and to surface waters, the principal media that carry contaminants offsite. These releases potentially result in exposure to offsite people. The groundwater monitoring performed at the site shows that an estimated 5 to 10% of SRS has been contaminated by radionuclides, no evidence exists from the extensive monitoring performed that groundwater contaminated with these constituents has migrated off the site (SRS 2011). Therefore, with the notable exception of radiological source terms originating from shallow surface water migration into site streams, onsite groundwater was not considered as a potential exposure pathway to offsite people. In addition, in response to the Department of Energy's (DOE) Order 435.1, several Performance Assessments (WSRC 2008; LWO 2009; SRR 2010; SRR 2011) and a Comprehensive SRS Composite Analysis (SRNO 2010) have recently been completed at SRS. The critical radionuclides and pathways identified in these extensive reports are discussed and, where applicable, included in this analysis.

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

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Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

2016-09-09

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators

Network Expansion and Pathway Enrichment Analysis towards Biologically Significant Findings from Microarrays

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Wu Xiaogang

2012-06-01

Full Text Available In many cases, crucial genes show relatively slight changes between groups of samples (e.g. normal vs. disease, and many genes selected from microarray differential analysis by measuring the expression level statistically are also poorly annotated and lack of biological significance. In this paper, we present an innovative approach - network expansion and pathway enrichment analysis (NEPEA for integrative microarray analysis. We assume that organized knowledge will help microarray data analysis in significant ways, and the organized knowledge could be represented as molecular interaction networks or biological pathways. Based on this hypothesis, we develop the NEPEA framework based on network expansion from the human annotated and predicted protein interaction (HAPPI database, and pathway enrichment from the human pathway database (HPD. We use a recently-published microarray dataset (GSE24215 related to insulin resistance and type 2 diabetes (T2D as case study, since this study provided a thorough experimental validation for both genes and pathways identified computationally from classical microarray analysis and pathway analysis. We perform our NEPEA analysis for this dataset based on the results from the classical microarray analysis to identify biologically significant genes and pathways. Our findings are not only consistent with the original findings mostly, but also obtained more supports from other literatures.

Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network.

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Del Papa, Bruno; Priesemann, Viola; Triesch, Jochen

2017-01-01

Many experiments have suggested that the brain operates close to a critical state, based on signatures of criticality such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes information processing capacities, e.g. sensitivity to input, dynamical range and storage capacity, which makes it a favorable candidate state for brain function. Although models that self-organize towards a critical state have been proposed, the relation between criticality signatures and learning is still unclear. Here, we investigate signatures of criticality in a self-organizing recurrent neural network (SORN). Investigating criticality in the SORN is of particular interest because it has not been developed to show criticality. Instead, the SORN has been shown to exhibit spatio-temporal pattern learning through a combination of neural plasticity mechanisms and it reproduces a number of biological findings on neural variability and the statistics and fluctuations of synaptic efficacies. We show that, after a transient, the SORN spontaneously self-organizes into a dynamical state that shows criticality signatures comparable to those found in experiments. The plasticity mechanisms are necessary to attain that dynamical state, but not to maintain it. Furthermore, onset of external input transiently changes the slope of the avalanche distributions - matching recent experimental findings. Interestingly, the membrane noise level necessary for the occurrence of the criticality signatures reduces the model's performance in simple learning tasks. Overall, our work shows that the biologically inspired plasticity and homeostasis mechanisms responsible for the SORN's spatio-temporal learning abilities can give rise to criticality signatures in its activity when driven by random input, but these break down under the structured input of short repeating sequences.

Network-based identification of biomarkers coexpressed with multiple pathways.

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Guo, Nancy Lan; Wan, Ying-Wooi

2014-01-01

Unraveling complex molecular interactions and networks and incorporating clinical information in modeling will present a paradigm shift in molecular medicine. Embedding biological relevance via modeling molecular networks and pathways has become increasingly important for biomarker identification in cancer susceptibility and metastasis studies. Here, we give a comprehensive overview of computational methods used for biomarker identification, and provide a performance comparison of several network models used in studies of cancer susceptibility, disease progression, and prognostication. Specifically, we evaluated implication networks, Boolean networks, Bayesian networks, and Pearson's correlation networks in constructing gene coexpression networks for identifying lung cancer diagnostic and prognostic biomarkers. The results show that implication networks, implemented in Genet package, identified sets of biomarkers that generated an accurate prediction of lung cancer risk and metastases; meanwhile, implication networks revealed more biologically relevant molecular interactions than Boolean networks, Bayesian networks, and Pearson's correlation networks when evaluated with MSigDB database.

Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

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Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

2017-09-21

Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

Criticality predicts maximum irregularity in recurrent networks of excitatory nodes.

Directory of Open Access Journals (Sweden)

Yahya Karimipanah

Full Text Available A rigorous understanding of brain dynamics and function requires a conceptual bridge between multiple levels of organization, including neural spiking and network-level population activity. Mounting evidence suggests that neural networks of cerebral cortex operate at a critical regime, which is defined as a transition point between two phases of short lasting and chaotic activity. However, despite the fact that criticality brings about certain functional advantages for information processing, its supporting evidence is still far from conclusive, as it has been mostly based on power law scaling of size and durations of cascades of activity. Moreover, to what degree such hypothesis could explain some fundamental features of neural activity is still largely unknown. One of the most prevalent features of cortical activity in vivo is known to be spike irregularity of spike trains, which is measured in terms of the coefficient of variation (CV larger than one. Here, using a minimal computational model of excitatory nodes, we show that irregular spiking (CV > 1 naturally emerges in a recurrent network operating at criticality. More importantly, we show that even at the presence of other sources of spike irregularity, being at criticality maximizes the mean coefficient of variation of neurons, thereby maximizing their spike irregularity. Furthermore, we also show that such a maximized irregularity results in maximum correlation between neuronal firing rates and their corresponding spike irregularity (measured in terms of CV. On the one hand, using a model in the universality class of directed percolation, we propose new hallmarks of criticality at single-unit level, which could be applicable to any network of excitable nodes. On the other hand, given the controversy of the neural criticality hypothesis, we discuss the limitation of this approach to neural systems and to what degree they support the criticality hypothesis in real neural networks. Finally

Neural Network Based Intrusion Detection System for Critical Infrastructures

Energy Technology Data Exchange (ETDEWEB)

Todd Vollmer; Ondrej Linda; Milos Manic

2009-07-01

Resiliency and security in control systems such as SCADA and Nuclear plant’s in today’s world of hackers and malware are a relevant concern. Computer systems used within critical infrastructures to control physical functions are not immune to the threat of cyber attacks and may be potentially vulnerable. Tailoring an intrusion detection system to the specifics of critical infrastructures can significantly improve the security of such systems. The IDS-NNM – Intrusion Detection System using Neural Network based Modeling, is presented in this paper. The main contributions of this work are: 1) the use and analyses of real network data (data recorded from an existing critical infrastructure); 2) the development of a specific window based feature extraction technique; 3) the construction of training dataset using randomly generated intrusion vectors; 4) the use of a combination of two neural network learning algorithms – the Error-Back Propagation and Levenberg-Marquardt, for normal behavior modeling. The presented algorithm was evaluated on previously unseen network data. The IDS-NNM algorithm proved to be capable of capturing all intrusion attempts presented in the network communication while not generating any false alerts.

Design and validation of a critical pathway for hospital management of patients with severe traumatic brain injury.

Science.gov (United States)

Espinosa-Aguilar, Amilcar; Reyes-Morales, Hortensia; Huerta-Posada, Carlos E; de León, Itzcoatl Limón-Pérez; López-López, Fernando; Mejía-Hernández, Margarita; Mondragón-Martínez, María A; Calderón-Téllez, Ligia M; Amezcua-Cuevas, Rosa L; Rebollar-González, Jorge A

2008-05-01

Critical pathways for the management of patients with severe traumatic brain injury (STBI) may contribute to reducing the incidence of hospital complications, length of hospitalization stay, and cost of care. Such pathways have previously been developed for departments with significant resource availability. In Mexico, STBI is the most important cause of complications and length of stay in neurotrauma services at public hospitals. Although current treatment is designed basically in accordance with the Brain Trauma Foundation guidelines, shortfalls in the availability of local resources make it difficult to comply with these standards, and no critical pathway is available that accords with the resources of public hospitals. The purpose of the present study was to design and to validate a critical pathway for managing STBI patients that would be suitable for implementation in neurotrauma departments of middle-income level countries. The study comprised two phases: design (through literature review and design plan) and validation (content, construct, and appearance) of the critical pathway. The validated critical pathway for managing STBI patients entails four sequential subprocesses summarizing the hospital's care procedures, and includes three components: (1) nodes and criteria (in some cases, indicators are also included); (2) health team members in charge of the patient; (3) maximum estimated time for compliance with recommendations. This validated critical pathway is based on the current scientific evidence and accords with the availability of resources of middle-income countries.

An Analysis for the Use of Research and Education Networks and Commercial Network Vendors in Support of Space Based Mission Critical and Non-Critical Networking

Science.gov (United States)

Bradford, Robert N.

2002-01-01

Currently, and in the past, dedicated communication circuits and "network services" with very stringent performance requirements are being used to support manned and unmanned mission critical ground operations at GSFC, JSC, MSFC, KSC and other NASA facilities. Because of the evolution of network technology, it is time to investigate using other approaches to providing mission services for space ground operations. The current NASA approach is not in keeping with the evolution of network technologies. In the past decade various research and education networks dedicated to scientific and educational endeavors have emerged, as well as commercial networking providers, that employ advanced networking technologies. These technologies have significantly changed networking in recent years. Significant advances in network routing techniques, various topologies and equipment have made commercial networks very stable and virtually error free. Advances in Dense Wave Division Multiplexing will provide tremendous amounts of bandwidth for the future. The question is: Do these networks, which are controlled and managed centrally, provide a level of service that equals the stringent NASA performance requirements. If they do, what are the implication(s) of using them for critical space based ground operations as they are, without adding high cost contractual performance requirements? A second question is the feasibility of applying the emerging grid technology in space operations. Is it feasible to develop a Space Operations Grid and/or a Space Science Grid? Since these network's connectivity is substantial, both nationally and internationally, development of these sorts of grids may be feasible. The concept of research and education networks has evolved to the international community as well. Currently there are international RENs connecting the US in Chicago to and from Europe, South America, Asia and the Pacific rim, Russia and Canada. And most countries in these areas have their

Critical Transitions in Social Network Activity

DEFF Research Database (Denmark)

Kuehn, Christian; Martens, Erik Andreas; Romero, Daniel M

2014-01-01

A large variety of complex systems in ecology, climate science, biomedicine and engineering have been observed to exhibit tipping points, where the dynamical state of the system abruptly changes. For example, such critical transitions may result in the sudden change of ecological environments...... a priori known events are preceded by variance and autocorrelation growth. Our findings thus clearly establish the necessary starting point to further investigate the relationship between abstract mathematical theory and various classes of critical transitions in social networks....

Decentralized control of transmission rates in energy-critical wireless networks

KAUST Repository

Xia, Li

2013-06-01

In this paper, we discuss the decentralized optimization of delay and energy consumption in a multi-hop wireless network. The goal is to minimize the energy consumption of energy-critical nodes and the overall packet transmission delay of the network. The transmission rates of energy-critical nodes are adjustable according to the local information of nodes, i.e., the length of packets queued. The multi-hop network is modeled as a queueing network.We prove that the system performance is monotone w.r.t. (with respect to) the transmission rate, thus the “bang-bang” control is an optimal control. We also prove that there exists a threshold type control policy which is optimal. We propose a decentralized algorithm to control transmission rates of these energy-critical nodes. Some simulation experiments are conducted to demonstrate the effectiveness of our approach.

Decentralized control of transmission rates in energy-critical wireless networks

KAUST Repository

Xia, Li; Shihada, Basem

2013-01-01

In this paper, we discuss the decentralized optimization of delay and energy consumption in a multi-hop wireless network. The goal is to minimize the energy consumption of energy-critical nodes and the overall packet transmission delay of the network. The transmission rates of energy-critical nodes are adjustable according to the local information of nodes, i.e., the length of packets queued. The multi-hop network is modeled as a queueing network.We prove that the system performance is monotone w.r.t. (with respect to) the transmission rate, thus the “bang-bang” control is an optimal control. We also prove that there exists a threshold type control policy which is optimal. We propose a decentralized algorithm to control transmission rates of these energy-critical nodes. Some simulation experiments are conducted to demonstrate the effectiveness of our approach.

Critical Radionuclide and Pathway Analysis for the Savannah River Site, 2016 Update

Energy Technology Data Exchange (ETDEWEB)

Jannik, Tim [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Hartman, Larry [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2016-09-08

During the operational history of Savannah River Site, many different radionuclides have been released from site facilities. However, as shown in this analysis, only a relatively small number of the released radionuclides have been significant contributors to doses to the offsite public. This report is an update to the 2011 analysis, Critical Radionuclide and Pathway Analysis for the Savannah River Site. SRS-based Performance Assessments for E-Area, Saltstone, F-Tank Farm, H-Tank Farm, and a Comprehensive SRS Composite Analysis have been completed. The critical radionuclides and pathways identified in those extensive reports are also detailed and included in this analysis.

Critical exponents for diluted resistor networks.

Science.gov (United States)

Stenull, O; Janssen, H K; Oerding, K

1999-05-01

An approach by Stephen [Phys. Rev. B 17, 4444 (1978)] is used to investigate the critical properties of randomly diluted resistor networks near the percolation threshold by means of renormalized field theory. We reformulate an existing field theory by Harris and Lubensky [Phys. Rev. B 35, 6964 (1987)]. By a decomposition of the principal Feynman diagrams, we obtain diagrams which again can be interpreted as resistor networks. This interpretation provides for an alternative way of evaluating the Feynman diagrams for random resistor networks. We calculate the resistance crossover exponent phi up to second order in epsilon=6-d, where d is the spatial dimension. Our result phi=1+epsilon/42+4epsilon(2)/3087 verifies a previous calculation by Lubensky and Wang, which itself was based on the Potts-model formulation of the random resistor network.

Estimating the per-capita contribution of habitats and pathways in a migratory network: A modelling approach

Science.gov (United States)

Wiederholt, Ruscena; Mattsson, Brady J.; Thogmartin, Wayne E.; Runge, Michael C.; Diffendorfer, Jay E.; Erickson, Richard A.; Federico, Paula; Lopez-Hoffman, Laura; Fryxell, John; Norris, D. Ryan; Sample, Christine

2018-01-01

Every year, migratory species undertake seasonal movements along different pathways between discrete regions and habitats. The ability to assess the relative demographic contributions of these different habitats and pathways to the species’ overall population dynamics is critical for understanding the ecology of migratory species, and also has practical applications for management and conservation. Metrics for assessing habitat contributions have been well-developed for metapopulations, but an equivalent metric is not currently available for migratory populations. Here, we develop a framework for estimating the demographic contributions of the discrete habitats and pathways used by migratory species throughout the annual cycle by estimating the per capita contribution of cohorts using these locations. Our framework accounts for seasonal movements between multiple breeding and non-breeding habitats and for both resident and migratory cohorts. We illustrate our framework using a hypothetical migratory network of four habitats, which allows us to better understand how variations in habitat quality affect per capita contributions. Results indicate that per capita contributions for any habitat or pathway are dependent on habitat-specific survival probabilities in all other areas used as part of the migratory circuit, and that contribution metrics are spatially linked (e.g. reduced survival in one habitat also decreases the contribution metric for other habitats). Our framework expands existing theory on the dynamics of spatiotemporally structured populations by developing a generalized approach to estimate the habitat- and pathway-specific contributions of species migrating between multiple breeding and multiple non-breeding habitats for a range of life histories or migratory strategies. Most importantly, it provides a means of prioritizing conservation efforts towards those migratory pathways and habitats that are most critical for the population viability of

Impact of network topology on self-organized criticality

Science.gov (United States)

Hoffmann, Heiko

2018-02-01

The general mechanisms behind self-organized criticality (SOC) are still unknown. Several microscopic and mean-field theory approaches have been suggested, but they do not explain the dependence of the exponents on the underlying network topology of the SOC system. Here, we first report the phenomena that in the Bak-Tang-Wiesenfeld (BTW) model, sites inside an avalanche area largely return to their original state after the passing of an avalanche, forming, effectively, critically arranged clusters of sites. Then, we hypothesize that SOC relies on the formation process of these clusters, and present a model of such formation. For low-dimensional networks, we show theoretically and in simulation that the exponent of the cluster-size distribution is proportional to the ratio of the fractal dimension of the cluster boundary and the dimensionality of the network. For the BTW model, in our simulations, the exponent of the avalanche-area distribution matched approximately our prediction based on this ratio for two-dimensional networks, but deviated for higher dimensions. We hypothesize a transition from cluster formation to the mean-field theory process with increasing dimensionality. This work sheds light onto the mechanisms behind SOC, particularly, the impact of the network topology.

Hierarchical modular structure enhances the robustness of self-organized criticality in neural networks

International Nuclear Information System (INIS)

Wang Shengjun; Zhou Changsong

2012-01-01

One of the most prominent architecture properties of neural networks in the brain is the hierarchical modular structure. How does the structure property constrain or improve brain function? It is thought that operating near criticality can be beneficial for brain function. Here, we find that networks with modular structure can extend the parameter region of coupling strength over which critical states are reached compared to non-modular networks. Moreover, we find that one aspect of network function—dynamical range—is highest for the same parameter region. Thus, hierarchical modularity enhances robustness of criticality as well as function. However, too much modularity constrains function by preventing the neural networks from reaching critical states, because the modular structure limits the spreading of avalanches. Our results suggest that the brain may take advantage of the hierarchical modular structure to attain criticality and enhanced function. (paper)

Discriminating response groups in metabolic and regulatory pathway networks.

Science.gov (United States)

Van Hemert, John L; Dickerson, Julie A

2012-04-01

Analysis of omics experiments generates lists of entities (genes, metabolites, etc.) selected based on specific behavior, such as changes in response to stress or other signals. Functional interpretation of these lists often uses category enrichment tests using functional annotations like Gene Ontology terms and pathway membership. This approach does not consider the connected structure of biochemical pathways or the causal directionality of events. The Omics Response Group (ORG) method, described in this work, interprets omics lists in the context of metabolic pathway and regulatory networks using a statistical model for flow within the networks. Statistical results for all response groups are visualized in a novel Pathway Flow plot. The statistical tests are based on the Erlang distribution model under the assumption of independent and identically Exponential-distributed random walk flows through pathways. As a proof of concept, we applied our method to an Escherichia coli transcriptomics dataset where we confirmed common knowledge of the E.coli transcriptional response to Lipid A deprivation. The main response is related to osmotic stress, and we were also able to detect novel responses that are supported by the literature. We also applied our method to an Arabidopsis thaliana expression dataset from an abscisic acid study. In both cases, conventional pathway enrichment tests detected nothing, while our approach discovered biological processes beyond the original studies. We created a prototype for an interactive ORG web tool at http://ecoserver.vrac.iastate.edu/pathwayflow (source code is available from https://subversion.vrac.iastate.edu/Subversion/jlv/public/jlv/pathwayflow). The prototype is described along with additional figures and tables in Supplementary Material. julied@iastate.edu Supplementary data are available at Bioinformatics online.

Criticality and avalanches in neural networks

International Nuclear Information System (INIS)

Zare, Marzieh; Grigolini, Paolo

2013-01-01

Highlights: • Temporal criticality is used as criticality indicator. • The Mittag–Leffler function is proposed as a proper form of temporal complexity. • The distribution of avalanche size becomes scale free in the supercritical state. • The scale-free distribution of avalanche sizes is an epileptic manifestation. -- Abstract: Experimental work, both in vitro and in vivo, reveals the occurrence of neural avalanches with an inverse power law distribution in size and time duration. These properties are interpreted as an evident manifestation of criticality, thereby suggesting that the brain is an operating near criticality complex system: an attractive theoretical perspective that according to Gerhard Werner may help to shed light on the origin of consciousness. However, a recent experimental observation shows no clear evidence for power-law scaling in awake and sleeping brain of mammals, casting doubts on the assumption that the brain works at criticality. This article rests on a model proposed by our group in earlier publications to generate neural avalanches with the time duration and size distribution matching the experimental results on neural networks. We now refine the analysis of the time distance between consecutive firing bursts and observe the deviation of the corresponding distribution from the Poisson statistics, as the system moves from the non-cooperative to the cooperative regime. In other words, we make the assumption that the genuine signature of criticality may emerge from temporal complexity rather than from the size and time duration of avalanches. We argue that the Mittag–Leffler (ML) exponential function is a satisfactory indicator of temporal complexity, namely of the occurrence of non-Poisson and renewal events. The assumption that the onset of criticality corresponds to the birth of renewal non-Poisson events establishes a neat distinction between the ML function and the power law avalanches generating regime. We find that

A Critical Agency Network Model for Building an Integrated Outreach Program

Science.gov (United States)

Kiyama, Judy Marquez; Lee, Jenny J.; Rhoades, Gary

2012-01-01

This study considers a distinct case of a college outreach program that integrates student affairs staff, academic administrators, and faculty across campus. The authors find that social networks and critical agency help to understand the integration of these various professionals and offer a critical agency network model of enacting change.…

Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

Directory of Open Access Journals (Sweden)

Sheng-Jun Wang

2011-06-01

Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

Genome-wide analysis of a Wnt1-regulated transcriptional network implicates neurodegenerative pathways.

Science.gov (United States)

Wexler, Eric M; Rosen, Ezra; Lu, Daning; Osborn, Gregory E; Martin, Elizabeth; Raybould, Helen; Geschwind, Daniel H

2011-10-04

Wnt proteins are critical to mammalian brain development and function. The canonical Wnt signaling pathway involves the stabilization and nuclear translocation of β-catenin; however, Wnt also signals through alternative, noncanonical pathways. To gain a systems-level, genome-wide view of Wnt signaling, we analyzed Wnt1-stimulated changes in gene expression by transcriptional microarray analysis in cultured human neural progenitor (hNP) cells at multiple time points over a 72-hour time course. We observed a widespread oscillatory-like pattern of changes in gene expression, involving components of both the canonical and the noncanonical Wnt signaling pathways. A higher-order, systems-level analysis that combined independent component analysis, waveform analysis, and mutual information-based network construction revealed effects on pathways related to cell death and neurodegenerative disease. Wnt effectors were tightly clustered with presenilin1 (PSEN1) and granulin (GRN), which cause dominantly inherited forms of Alzheimer's disease and frontotemporal dementia (FTD), respectively. We further explored a potential link between Wnt1 and GRN and found that Wnt1 decreased GRN expression by hNPs. Conversely, GRN knockdown increased WNT1 expression, demonstrating that Wnt and GRN reciprocally regulate each other. Finally, we provided in vivo validation of the in vitro findings by analyzing gene expression data from individuals with FTD. These unbiased and genome-wide analyses provide evidence for a connection between Wnt signaling and the transcriptional regulation of neurodegenerative disease genes.

Migrant networks and pathways to child obesity in Mexico.

Science.gov (United States)

Creighton, Mathew J; Goldman, Noreen; Teruel, Graciela; Rubalcava, Luis

2011-03-01

The purpose of this paper is twofold: 1) to assess the link between migrant networks and becoming overweight or obese and 2) to explore the pathways by which migrant networks may contribute to the increasing overweight and obese population of children in Mexico. Using two waves of the Mexican Family Life Survey (MxFLS), we find that children and adolescents (ages 3 to 15) living in households with migrant networks are at an increased risk of becoming overweight or obese over the period of observation, relative to their peers with no migrant networks. Sedentary behavior and household-level measures of economic wellbeing explain some of the association between networks and changes in weight status, but the role of extended networks remains significant. Community-level characteristics related to migration do not account for any of the observed relationship between household-level networks and becoming overweight or obese. Copyright © 2010 Elsevier Ltd. All rights reserved.

Bruno Latour, actor-networks, and the critique of critical sociology

Directory of Open Access Journals (Sweden)

Spasić Ivana

2007-01-01

Full Text Available The paper analyzes the theoretical opus of Bruno Latour and his treatment of the concept of critique. In the first section "actor-network theory" is presented through its key notions (actant, network, translation, associations together with Latour’s theory of modernity. In the second section various aspects of the relation between Latour and critique are discussed - first his own criticism of others (standard sociology and especially "critical", i.e. Bourdieu’s sociology, then the criticisms aimed at his work, to conclude with the political ambivalences of Latour’s attempt to develop an "acritical" social theory. .

Critical behavior and correlations on scale-free small-world networks: Application to network design

Science.gov (United States)

Ostilli, M.; Ferreira, A. L.; Mendes, J. F. F.

2011-06-01

We analyze critical phenomena on networks generated as the union of hidden variable models (networks with any desired degree sequence) with arbitrary graphs. The resulting networks are general small worlds similar to those à la Watts and Strogatz, but with a heterogeneous degree distribution. We prove that the critical behavior (thermal or percolative) remains completely unchanged by the presence of finite loops (or finite clustering). Then, we show that, in large but finite networks, correlations of two given spins may be strong, i.e., approximately power-law-like, at any temperature. Quite interestingly, if γ is the exponent for the power-law distribution of the vertex degree, for γ⩽3 and with or without short-range couplings, such strong correlations persist even in the thermodynamic limit, contradicting the common opinion that, in mean-field models, correlations always disappear in this limit. Finally, we provide the optimal choice of rewiring under which percolation phenomena in the rewired network are best performed, a natural criterion to reach best communication features, at least in noncongested regimes.

Social Network Analysis and Critical Realism

DEFF Research Database (Denmark)

Buch-Hansen, Hubert

2014-01-01

in relation to established philosophies of science. This article argues that there is a tension between applied and methods-oriented SNA studies, on the one hand, and those addressing the social-theoretical nature and implications of networks, on the other. The former, in many cases, exhibits positivist...... tendencies, whereas the latter incorporate a number of assumptions that are directly compatible with core critical realist views on the nature of social reality and knowledge. This article suggests that SNA may be detached from positivist social science and come to constitute a valuable instrument...... in the critical realist toolbox....

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

A universal indicator of critical state transitions in noisy complex networked systems.

Science.gov (United States)

Liang, Junhao; Hu, Yanqing; Chen, Guanrong; Zhou, Tianshou

2017-02-23

Critical transition, a phenomenon that a system shifts suddenly from one state to another, occurs in many real-world complex networks. We propose an analytical framework for exactly predicting the critical transition in a complex networked system subjected to noise effects. Our prediction is based on the characteristic return time of a simple one-dimensional system derived from the original higher-dimensional system. This characteristic time, which can be easily calculated using network data, allows us to systematically separate the respective roles of dynamics, noise and topology of the underlying networked system. We find that the noise can either prevent or enhance critical transitions, playing a key role in compensating the network structural defect which suffers from either internal failures or environmental changes, or both. Our analysis of realistic or artificial examples reveals that the characteristic return time is an effective indicator for forecasting the sudden deterioration of complex networks.

Fault tolerance in protein interaction networks: stable bipartite subgraphs and redundant pathways.

Science.gov (United States)

Brady, Arthur; Maxwell, Kyle; Daniels, Noah; Cowen, Lenore J

2009-01-01

As increasing amounts of high-throughput data for the yeast interactome become available, more system-wide properties are uncovered. One interesting question concerns the fault tolerance of protein interaction networks: whether there exist alternative pathways that can perform some required function if a gene essential to the main mechanism is defective, absent or suppressed. A signature pattern for redundant pathways is the BPM (between-pathway model) motif, introduced by Kelley and Ideker. Past methods proposed to search the yeast interactome for BPM motifs have had several important limitations. First, they have been driven heuristically by local greedy searches, which can lead to the inclusion of extra genes that may not belong in the motif; second, they have been validated solely by functional coherence of the putative pathways using GO enrichment, making it difficult to evaluate putative BPMs in the absence of already known biological annotation. We introduce stable bipartite subgraphs, and show they form a clean and efficient way of generating meaningful BPMs which naturally discard extra genes included by local greedy methods. We show by GO enrichment measures that our BPM set outperforms previous work, covering more known complexes and functional pathways. Perhaps most importantly, since our BPMs are initially generated by examining the genetic-interaction network only, the location of edges in the protein-protein physical interaction network can then be used to statistically validate each candidate BPM, even with sparse GO annotation (or none at all). We uncover some interesting biological examples of previously unknown putative redundant pathways in such areas as vesicle-mediated transport and DNA repair.

Critical features of coupling parameter in synchronization of small world neural networks

International Nuclear Information System (INIS)

Li Yanlong; Ma Jun; Xu Wenke; Li Hongbo; Wu Min

2008-01-01

The critical features of a coupling parameter in the synchronization of small world neural networks are investigated. A power law decay form is observed in this spatially extended system, the larger linked degree becomes, the larger critical coupling intensity. There exists maximal and minimal critical coupling intensity for synchronization in the extended system. An approximate synchronization diagram has been constructed. In the case of partial coupling, a primary result is presented about the critical coupling fraction for various linked degree of networks

A study on methodologies for assessing safety critical network's risk impact on Nuclear Power Plant

International Nuclear Information System (INIS)

Lim, T. J.; Lee, H. J.; Park, S. K.; Seo, S. J.

2006-08-01

The objectives of this project is to investigate and study existing reliability analysis techniques for communication networks in order to develop reliability analysis models for Nuclear Power Plant's safety-critical networks. It is necessary to make a comprehensive survey of current methodologies for communication network reliability. Major outputs of the first year study are design characteristics of safety-critical communication networks, efficient algorithms for quantifying reliability of communication networks, and preliminary models for assessing reliability of safety-critical communication networks

Making Wireless Networks Secure for NASA Mission Critical Applications Using Virtual Private Network (VPN) Technology

Science.gov (United States)

Nichols, Kelvin F.; Best, Susan; Schneider, Larry

2004-01-01

With so many security issues involved with wireless networks, the technology has not been fully utilized in the area of mission critical applications. These applications would include the areas of telemetry, commanding, voice and video. Wireless networking would allow payload operators the mobility to take computers outside of the control room to their off ices and anywhere else in the facility that the wireless network was extended. But the risk is too great of having someone sit just inside of your wireless network coverage and intercept enough of your network traffic to steal proprietary data from a payload experiment or worse yet hack back into your system and do even greater harm by issuing harmful commands. Wired Equivalent Privacy (WEP) is improving but has a ways to go before it can be trusted to protect mission critical data. Today s hackers are becoming more aggressive and innovative, and in order to take advantage of the benefits that wireless networking offer, appropriate security measures need to be in place that will thwart hackers. The Virtual Private Network (VPN) offers a solution to the security problems that have kept wireless networks from being used for mission critical applications. VPN provides a level of encryption that will ensure that data is protected while it is being transmitted over a wireless local area network (LAN). The VPN allows a user to authenticate to the site that the user needs to access. Once this authentication has taken place the network traffic between that site and the user is encapsulated in VPN packets with the Triple Data Encryption Standard (3DES). 3DES is an encryption standard that uses a single secret key to encrypt and decrypt data. The length of the encryption key is 168 bits as opposed to its predecessor DES that has a 56-bit encryption key. Even though 3DES is the common encryption standard for today, the Advance Encryption Standard (AES), which provides even better encryption at a lower cycle cost is growing

Conformational Network and Residence Time Estimation of Trypsin-Benzamidine Unbinding Pathways

OpenAIRE

Dickson, Alex; Lotz, Samuel D.

2016-01-01

In this poster we present results from molecular dynamics sampling of benzamidine unbinding from trypsin. We give background on the weighted ensemble technique used (WExplore) and the Markovian state model construction. Our network shows three unique unbinding pathways including a never before observed unbinding pathway. We also estimate residence time to within one order of magnitude to the experimental value.

Social Network Culture Needs the Lens of Critical Trust Research

OpenAIRE

Dwyer , Natasha; Marsh , Stephen

2015-01-01

Part 2: Full Papers; International audience; Trust is essential to the success of the social networks that are aggregating and applying masses of information about us. In this position paper, we argue that a critical approach to exploring trust and social networks is required; this entails genuinely working in the interests of users and acknowledging the power relations and wider social context of this form of technology that is impacting more and more of our everyday life. Without a critical...

Fault tolerance in protein interaction networks: stable bipartite subgraphs and redundant pathways.

Directory of Open Access Journals (Sweden)

Arthur Brady

Full Text Available As increasing amounts of high-throughput data for the yeast interactome become available, more system-wide properties are uncovered. One interesting question concerns the fault tolerance of protein interaction networks: whether there exist alternative pathways that can perform some required function if a gene essential to the main mechanism is defective, absent or suppressed. A signature pattern for redundant pathways is the BPM (between-pathway model motif, introduced by Kelley and Ideker. Past methods proposed to search the yeast interactome for BPM motifs have had several important limitations. First, they have been driven heuristically by local greedy searches, which can lead to the inclusion of extra genes that may not belong in the motif; second, they have been validated solely by functional coherence of the putative pathways using GO enrichment, making it difficult to evaluate putative BPMs in the absence of already known biological annotation. We introduce stable bipartite subgraphs, and show they form a clean and efficient way of generating meaningful BPMs which naturally discard extra genes included by local greedy methods. We show by GO enrichment measures that our BPM set outperforms previous work, covering more known complexes and functional pathways. Perhaps most importantly, since our BPMs are initially generated by examining the genetic-interaction network only, the location of edges in the protein-protein physical interaction network can then be used to statistically validate each candidate BPM, even with sparse GO annotation (or none at all. We uncover some interesting biological examples of previously unknown putative redundant pathways in such areas as vesicle-mediated transport and DNA repair.

Non-criticality of interaction network over system's crises: A percolation analysis.

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Shirazi, Amir Hossein; Saberi, Abbas Ali; Hosseiny, Ali; Amirzadeh, Ehsan; Toranj Simin, Pourya

2017-11-20

Extraction of interaction networks from multi-variate time-series is one of the topics of broad interest in complex systems. Although this method has a wide range of applications, most of the previous analyses have focused on the pairwise relations. Here we establish the potential of such a method to elicit aggregated behavior of the system by making a connection with the concepts from percolation theory. We study the dynamical interaction networks of a financial market extracted from the correlation network of indices, and build a weighted network. In correspondence with the percolation model, we find that away from financial crises the interaction network behaves like a critical random network of Erdős-Rényi, while close to a financial crisis, our model deviates from the critical random network and behaves differently at different size scales. We perform further analysis to clarify that our observation is not a simple consequence of the growth in correlations over the crises.

A networked pathway to the PhD: The African-Norwegian case of ...

African Journals Online (AJOL)

How do PhD students become socialised into the professional world of academic work? This article pays attention to a 'networked' support pathway towards a PhD. The network constitutes an international research collaboration through a programme called Productive Learning Cultures (PLC) (2002-2011) between Norway ...

Insensitivity of proportional fairness in critically loaded bandwidth sharing networks

NARCIS (Netherlands)

Vlasiou, M.; Zhang, J.; Zwart, B.

2014-01-01

Proportional fairness is a popular service allocation mechanism to describe and analyze the performance of data networks at flow level. Recently, several authors have shown that the invariant distribution of such networks admits a product form distribution under critical loading. Assuming

Upper critical field of complex superconducting networks in the continuum limit

International Nuclear Information System (INIS)

Santhanam, P.; Chi, C.C.

1988-01-01

We propose a simple method for calculating the superconducting upper critical field of complex periodic two-dimensional networks in the continuum limit. Two specific lattices with space groups P4gm and C2mm are used to demonstrate this approach. We obtain the result that the ratio of the critical field of these networks to that of a uniform film is close to but larger than 2

Self-organized criticality occurs in non-conservative neuronal networks during `up' states

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Millman, Daniel; Mihalas, Stefan; Kirkwood, Alfredo; Niebur, Ernst

2010-10-01

During sleep, under anaesthesia and in vitro, cortical neurons in sensory, motor, association and executive areas fluctuate between so-called up and down states, which are characterized by distinct membrane potentials and spike rates. Another phenomenon observed in preparations similar to those that exhibit up and down states-such as anaesthetized rats, brain slices and cultures devoid of sensory input, as well as awake monkey cortex-is self-organized criticality (SOC). SOC is characterized by activity `avalanches' with a branching parameter near unity and size distribution that obeys a power law with a critical exponent of about -3/2. Recent work has demonstrated SOC in conservative neuronal network models, but critical behaviour breaks down when biologically realistic `leaky' neurons are introduced. Here, we report robust SOC behaviour in networks of non-conservative leaky integrate-and-fire neurons with short-term synaptic depression. We show analytically and numerically that these networks typically have two stable activity levels, corresponding to up and down states, that the networks switch spontaneously between these states and that up states are critical and down states are subcritical.

Transnational issue-specific expert networking: A pathway to local policy change.

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O'Brien, Cheryl

2015-12-01

This article reports on key findings from a study of subnational governments in Mexico and Nigeria (O'Brien, 2013). With empirical richness of the case study method and small-n statistical analysis across the subnational units for each country, this study asks: How can we push the needle toward more progressive policy change on violence against women in developing and democratizing contexts? This study finds that issue-specific expert networking is a civic pathway to subnational policy responsiveness in Mexico and Nigeria. The dynamics of this pathway illuminate local-global political connections, and this study shows how issue-specific expert networking is important for the diffusion of an international norm and policies on violence against women. Copyright © 2015 Elsevier Ltd. All rights reserved.

CRITICAL INFORMATION INFRASTRUCTURE SECURITY - NETWORK INTRUSION DETECTION SYSTEMS

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Cristea DUMITRU

2011-12-01

Full Text Available Critical Information Infrastructure security will always be difficult to ensure, just because of the features that make it irreplaceable tor other critical infrastructures normal operation. It is decentralized, interconnected interdependent, controlled by multiple actors (mainly private and incorporating diverse types of technologies. It is almost axiomatic that the disruption of the Critical Information Infrastructure affects systems located much farther away, and the cyber problems have direct consequences on the real world. Indeed the Internet can be used as a multiplier in order to amplify the effects of an attack on some critical infrastructures. Security challenges increase with the technological progress. One of the last lines of defense which comes to complete the overall security scheme of the Critical Information Infrastructure is represented by the Network Intrusion Detection Systems.

Prediction Approach of Critical Node Based on Multiple Attribute Decision Making for Opportunistic Sensor Networks

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Qifan Chen

2016-01-01

Full Text Available Predicting critical nodes of Opportunistic Sensor Network (OSN can help us not only to improve network performance but also to decrease the cost in network maintenance. However, existing ways of predicting critical nodes in static network are not suitable for OSN. In this paper, the conceptions of critical nodes, region contribution, and cut-vertex in multiregion OSN are defined. We propose an approach to predict critical node for OSN, which is based on multiple attribute decision making (MADM. It takes RC to present the dependence of regions on Ferry nodes. TOPSIS algorithm is employed to find out Ferry node with maximum comprehensive contribution, which is a critical node. The experimental results show that, in different scenarios, this approach can predict the critical nodes of OSN better.

HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

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Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

2015-04-01

The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.

Interdependency control : compensation strategies for the inherent vulnerability of critical infrastructure networks

International Nuclear Information System (INIS)

Mao, D.; Sotoodeh, M.; Monu, K.; Marti, J.R.; Srivastava, K.D.

2009-01-01

Today's increasingly interacting national critical infrastructures (NCIs) can tolerate most stochastic local disturbances. However, they are extremely fragile under global disturbances, as the latter may either push the whole system into a critical state or reveal many unexpected hidden interdependencies, inducing or triggering cascading failures among all possible layers. This robust yet fragile duality is an inherent vulnerability of modern infrastructures. It is therefore expected that weather-related disasters will be more frequent under a changing climate. This paper proposed an interdependency control strategy (ICS) that would maintain the survival of the most critical services, and compensate for this inherent vulnerability during emergency states. The paper also proposed a generalized adjacency matrix (GAM) to represent the physical interdependencies intra/inter of various infrastructure networks. The vulnerable section in the network can be identified, based on computed results of GAM, number of islands in the network, and influence domain(s) of each component. These features render ICS more effective and convincing. Last, the paper proposed a survivability index for isolated sub-networks and described relevant measures for improving this index during the four phases of emergency management. It was concluded that the proposed strategy is an effective means to reduce the inherent vulnerability and increase the resiliency of these critical infrastructures networks. 20 refs., 5 figs

Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

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Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

2016-06-01

Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying the Critical Links in Road Transportation Networks: Centrality-based approach utilizing structural properties

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Chinthavali, Supriya [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2016-04-01

Surface transportation road networks share structural properties similar to other complex networks (e.g., social networks, information networks, biological networks, and so on). This research investigates the structural properties of road networks for any possible correlation with the traffic characteristics such as link flows those determined independently. Additionally, we define a criticality index for the links of the road network that identifies the relative importance in the network. We tested our hypotheses with two sample road networks. Results show that, correlation exists between the link flows and centrality measures of a link of the road (dual graph approach is followed) and the criticality index is found to be effective for one test network to identify the vulnerable nodes.

Sleep Scheduling in Critical Event Monitoring with Wireless Sensor Networks

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Guo, Peng; Jiang, Tao; Zhang, Qian; Zhang, Kui

In this paper, we focus on the applications of wireless sensor networks (WSNs) for critical event monitoring, where normally there are only small number of packets need to be transmitted, while when urgent event occurs, the alarm should be broadcast to the entire network as soon as possible. During

Youth at ultra high risk for psychosis: using the Revised Network Episode Model to examine pathways to mental health care.

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Boydell, Katherine M; Volpe, Tiziana; Gladstone, Brenda M; Stasiulis, Elaine; Addington, Jean

2013-05-01

This paper aims to identify the ways in which youth at ultra high risk for psychosis access mental health services and the factors that advance or delay help seeking, using the Revised Network Episode Model (REV NEM) of mental health care. A case study approach documents help-seeking pathways, encompassing two qualitative interviews with 10 young people and 29 significant others. Theoretical propositions derived from the REV NEM are explored, consisting of the content, structure and function of the: (i) family; (ii) community and school; and (iii) treatment system. Although the aspects of the REV NEM are supported and shape pathways to care, we consider rethinking the model for help seeking with youth at ultra high risk for psychosis. The pathway concept is important to our understanding of how services and supports are received and experienced over time. Understanding this process and the strategies that support positive early intervention on the part of youth and significant others is critical. © 2012 Wiley Publishing Asia Pty Ltd.

Climate Change Literacy across the Critical Zone Observatory Network

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Moore, A.; Derry, L. A.; Zabel, I.; Duggan-Haas, D.; Ross, R. M.

2017-12-01

Earth's Critical Zone extends from the top of the tree canopy to the base of the groundwater lens. Thus the Critical Zone is examined as a suite of interconnected systems and study of the CZ is inherently interdisciplinary. Climate change is an important driver of CZ processes. The US Critical Zone Observatory Network comprises nine observatories and a coordinating National Office. Educational programs and materials developed at each CZO and the National Office have been collected, reviewed, and presented on-line at the CZONO (criticalzone.org/national/education-outreach/resources). Because the CZOs are designed to observe and measure a suite of common parameters on varying geological substrates and within different ecological contexts, educational resources reflect the diversity of processes represented across the network. As climate change has a network-wide impact, the fundamental building blocks of climate change literacy are key elements in many activities within the CZONO resource collection. Carbon-cycle and hydrologic cycle processes are well-represented, with emphasis on human interactions with these resources, as well as the impact of extreme events and the changing climate. Current work on the resource collection focuses on connecting individual resources to "Teach Climate Science" project and the Teacher-Friendly Guide to Climate Change (teachclimatescience.wordpress.com). The Teacher-Friendly Guide is a manual for K-12 teachers that presents both the fundamentals of climate science alongside resources for effective teaching of this controversial topic. Using the reach of the CZO network we hope to disseminate effective climate literacy resources and support to the K-12 community.

Fault tolerance of artificial neural networks with applications in critical systems

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Protzel, Peter W.; Palumbo, Daniel L.; Arras, Michael K.

1992-01-01

This paper investigates the fault tolerance characteristics of time continuous recurrent artificial neural networks (ANN) that can be used to solve optimization problems. The principle of operations and performance of these networks are first illustrated by using well-known model problems like the traveling salesman problem and the assignment problem. The ANNs are then subjected to 13 simultaneous 'stuck at 1' or 'stuck at 0' faults for network sizes of up to 900 'neurons'. The effects of these faults is demonstrated and the cause for the observed fault tolerance is discussed. An application is presented in which a network performs a critical task for a real-time distributed processing system by generating new task allocations during the reconfiguration of the system. The performance degradation of the ANN under the presence of faults is investigated by large-scale simulations, and the potential benefits of delegating a critical task to a fault tolerant network are discussed.

Mixed Criticality Scheduling for Industrial Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Xi Jin

2016-08-01

Full Text Available Wireless sensor networks (WSNs have been widely used in industrial systems. Their real-time performance and reliability are fundamental to industrial production. Many works have studied the two aspects, but only focus on single criticality WSNs. Mixed criticality requirements exist in many advanced applications in which different data flows have different levels of importance (or criticality. In this paper, first, we propose a scheduling algorithm, which guarantees the real-time performance and reliability requirements of data flows with different levels of criticality. The algorithm supports centralized optimization and adaptive adjustment. It is able to improve both the scheduling performance and flexibility. Then, we provide the schedulability test through rigorous theoretical analysis. We conduct extensive simulations, and the results demonstrate that the proposed scheduling algorithm and analysis significantly outperform existing ones.

Boolean network model for cancer pathways: predicting carcinogenesis and targeted therapy outcomes.

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Herman F Fumiã

Full Text Available A Boolean dynamical system integrating the main signaling pathways involved in cancer is constructed based on the currently known protein-protein interaction network. This system exhibits stationary protein activation patterns--attractors--dependent on the cell's microenvironment. These dynamical attractors were determined through simulations and their stabilities against mutations were tested. In a higher hierarchical level, it was possible to group the network attractors into distinct cell phenotypes and determine driver mutations that promote phenotypic transitions. We find that driver nodes are not necessarily central in the network topology, but at least they are direct regulators of central components towards which converge or through which crosstalk distinct cancer signaling pathways. The predicted drivers are in agreement with those pointed out by diverse census of cancer genes recently performed for several human cancers. Furthermore, our results demonstrate that cell phenotypes can evolve towards full malignancy through distinct sequences of accumulated mutations. In particular, the network model supports routes of carcinogenesis known for some tumor types. Finally, the Boolean network model is employed to evaluate the outcome of molecularly targeted cancer therapies. The major find is that monotherapies were additive in their effects and that the association of targeted drugs is necessary for cancer eradication.

White matter pathways critical for language are also critical for resolving proactive interference in working memory

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Stephanie Kathleen Ries

2014-04-01

Full Text Available Background White matter pathways connecting brain regions involved in language processing in the left prefrontal (PFC and temporal cortices have been found to play a critical role in language comprehension (Turken and Dronkers, 2011. Among the frontal brain regions associated with language processing, the left inferior frontal gyrus (lIFG has also been strongly associated with resolving proactive interference in working memory (Jonides and Nee, 2006. Here we investigated whether the white matter pathways connecting the lIFG to the left temporal lobe found to be important in language comprehension were also critical for resolving proactive interference in working memory. Methods We tested 4 patients with left PFC damage involving the lIFG, 5 with left temporal damage and 6 age-matched controls. Critically, 2 left PFC patients and 1 left temporal patient had lesions involving a complete disconnection between the lIFG and the left temporal cortex and the remaining patients had partial disconnection only. Performance was assessed using the Recent Probes test (Monsell, 1978: 4 visually-presented letters are followed by a probe: one central letter. The task was to decide whether or not the probe was part of the immediately preceding set of letters. Whether or not the probe was also part of the previous trial and elicited a positive or negative response was then manipulated and created recent negative (RN and recent positive trials, respectively. RN trials generated interference in trial n compared to non-recent negative (NN trials. Behavioral results were reported using error rates as the dependent variable. Results When the groups were separated based on which cortical lobe was damaged, there was a significant main interference effect (F(1,12=24.94, p <.001, where RN trials were associated with worse performance than NN trials, and a main effect of group (F(2,12=4.65, p <.05, where performance was worse for patients than for controls, but there was

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

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Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

2018-01-06

Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

The node-weighted Steiner tree approach to identify elements of cancer-related signaling pathways.

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Sun, Yahui; Ma, Chenkai; Halgamuge, Saman

2017-12-28

Cancer constitutes a momentous health burden in our society. Critical information on cancer may be hidden in its signaling pathways. However, even though a large amount of money has been spent on cancer research, some critical information on cancer-related signaling pathways still remains elusive. Hence, new works towards a complete understanding of cancer-related signaling pathways will greatly benefit the prevention, diagnosis, and treatment of cancer. We propose the node-weighted Steiner tree approach to identify important elements of cancer-related signaling pathways at the level of proteins. This new approach has advantages over previous approaches since it is fast in processing large protein-protein interaction networks. We apply this new approach to identify important elements of two well-known cancer-related signaling pathways: PI3K/Akt and MAPK. First, we generate a node-weighted protein-protein interaction network using protein and signaling pathway data. Second, we modify and use two preprocessing techniques and a state-of-the-art Steiner tree algorithm to identify a subnetwork in the generated network. Third, we propose two new metrics to select important elements from this subnetwork. On a commonly used personal computer, this new approach takes less than 2 s to identify the important elements of PI3K/Akt and MAPK signaling pathways in a large node-weighted protein-protein interaction network with 16,843 vertices and 1,736,922 edges. We further analyze and demonstrate the significance of these identified elements to cancer signal transduction by exploring previously reported experimental evidences. Our node-weighted Steiner tree approach is shown to be both fast and effective to identify important elements of cancer-related signaling pathways. Furthermore, it may provide new perspectives into the identification of signaling pathways for other human diseases.

Pathways for Emotions: Specializations in the Amygdalar, Mediodorsal Thalamic, and Posterior Orbitofrontal Network.

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Timbie, Clare; Barbas, Helen

2015-08-26

The primate amygdala projects to posterior orbitofrontal cortex (pOFC) directly and possibly indirectly through a pathway to the magnocellular mediodorsal thalamic nucleus (MDmc), which may convey signals about the significance of stimuli. However, because MDmc receives input from structures in addition to the amygdala and MDmc projects to areas in addition to pOFC, it is unknown whether amygdalar pathways in MDmc innervate pOFC-bound neurons. We addressed this issue using double- or triple-labeling approaches to identify pathways and key cellular and molecular features in rhesus monkeys. We found that amygdalar terminations innervated labeled neurons in MDmc that project to pOFC. Projection neurons in MDmc directed to pOFC included comparatively fewer "core" parvalbumin neurons that project focally to the middle cortical layers and more "matrix" calbindin neurons that project expansively to the upper cortical layers. In addition, a small and hitherto unknown pathway originated from MDmc calretinin neurons and projected to pOFC. Further, whereas projection neurons directed to MDmc and to pOFC were intermingled in the amygdala, none projected to both structures. Larger amygdalar neurons projected to MDmc and expressed the vesicular glutamate transporter 2 (VGLUT2), which is found in highly efficient "driver" pathways. In contrast, smaller amygdalar neurons directed to pOFC expressed VGLUT1 found in modulatory pathways. The indirect pathway from the amygdala to pOFC via MDmc may provide information about the emotional significance of events and, along with a parallel direct pathway, ensures transfer of signals to all layers of pOFC. The amygdala-the brain's center for emotions-is strongly linked with the orbital cortex, a region associated with social interactions. This study provides evidence that a robust pathway from the amygdala reaches neurons in the thalamus that link directly with the orbital cortex, forming a tight tripartite network. The dual pathways from

Self-organized Criticality in a Modified Evolution Model on Generalized Barabasi-Albert Scale-Free Networks

International Nuclear Information System (INIS)

Lin Min; Wang Gang; Chen Tianlun

2007-01-01

A modified evolution model of self-organized criticality on generalized Barabasi-Albert (GBA) scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behaviors. More importantly, these critical behaviors change with the parameter b, which weights the distance in comparison with the degree in the GBA network evolution.

Critical Role of the Sphingolipid Pathway in Stroke: a Review of Current Utility and Potential Therapeutic Targets.

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Sun, Na; Keep, Richard F; Hua, Ya; Xi, Guohua

2016-10-01

Sphingolipids are a series of cell membrane-derived lipids which act as signaling molecules and play a critical role in cell death and survival, proliferation, recognition, and migration. Sphingosine-1-phosphate acts as a key signaling molecule and regulates lymphocyte trafficking, glial cell activation, vasoconstriction, endothelial barrier function, and neuronal death pathways which plays a critical role in numerous neurological conditions. Stroke is a second leading cause of death all over the world and effective therapies are still in great demand, including ischemic stroke and hemorrhagic stroke as well as poststroke repair. Significantly, sphingolipid activities change after stroke and correlate with stroke outcome, which has promoted efforts to testify whether the sphingolipid pathway could be a novel therapeutic target in stroke. The sphingolipid metabolic pathway, the connection between the pathway and stroke, as well as therapeutic interventions to manipulate the pathway to reduce stroke-induced brain injury are discussed in this review.

msiDBN: A Method of Identifying Critical Proteins in Dynamic PPI Networks

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Yuan Zhang

2014-01-01

Full Text Available Dynamics of protein-protein interactions (PPIs reveals the recondite principles of biological processes inside a cell. Shown in a wealth of study, just a small group of proteins, rather than the majority, play more essential roles at crucial points of biological processes. This present work focuses on identifying these critical proteins exhibiting dramatic structural changes in dynamic PPI networks. First, a comprehensive way of modeling the dynamic PPIs is presented which simultaneously analyzes the activity of proteins and assembles the dynamic coregulation correlation between proteins at each time point. Second, a novel method is proposed, named msiDBN, which models a common representation of multiple PPI networks using a deep belief network framework and analyzes the reconstruction errors and the variabilities across the time courses in the biological process. Experiments were implemented on data of yeast cell cycles. We evaluated our network construction method by comparing the functional representations of the derived networks with two other traditional construction methods. The ranking results of critical proteins in msiDBN were compared with the results from the baseline methods. The results of comparison showed that msiDBN had better reconstruction rate and identified more proteins of critical value to yeast cell cycle process.

Bioinformatic Integration of Molecular Networks and Major Pathways Involved in Mice Cochlear and Vestibular Supporting Cells.

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Requena, Teresa; Gallego-Martinez, Alvaro; Lopez-Escamez, Jose A

2018-01-01

Background : Cochlear and vestibular epithelial non-hair cells (ENHCs) are the supporting elements of the cellular architecture in the organ of Corti and the vestibular neuroepithelium in the inner ear. Intercellular and cell-extracellular matrix interactions are essential to prevent an abnormal ion redistribution leading to hearing and vestibular loss. The aim of this study is to define the main pathways and molecular networks in the mouse ENHCs. Methods : We retrieved microarray and RNA-seq datasets from mouse epithelial sensory and non-sensory cells from gEAR portal (http://umgear.org/index.html) and obtained gene expression fold-change between ENHCs and non-epithelial cells (NECs) against HCs for each gene. Differentially expressed genes (DEG) with a log2 fold change between 1 and -1 were discarded. The remaining genes were selected to search for interactions using Ingenuity Pathway Analysis and STRING platform. Specific molecular networks for ENHCs in the cochlea and the vestibular organs were generated and significant pathways were identified. Results : Between 1723 and 1559 DEG were found in the mouse cochlear and vestibular tissues, respectively. Six main pathways showed enrichment in the supporting cells in both tissues: (1) "Inhibition of Matrix Metalloproteases"; (2) "Calcium Transport I"; (3) "Calcium Signaling"; (4) "Leukocyte Extravasation Signaling"; (5) "Signaling by Rho Family GTPases"; and (6) "Axonal Guidance Si". In the mouse cochlea, ENHCs showed a significant enrichment in 18 pathways highlighting "axonal guidance signaling (AGS)" ( p = 4.37 × 10 -8 ) and "RhoGDI Signaling" ( p = 3.31 × 10 -8 ). In the vestibular dataset, there were 20 enriched pathways in ENHCs, the most significant being "Leukocyte Extravasation Signaling" ( p = 8.71 × 10 -6 ), "Signaling by Rho Family GTPases" ( p = 1.20 × 10 -5 ) and "Calcium Signaling" ( p = 1.20 × 10 -5 ). Among the top ranked networks, the most biologically significant network contained the

Association between mutations of critical pathway genes and survival outcomes according to the tumor location in colorectal cancer.

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Lee, Dae-Won; Han, Sae-Won; Cha, Yongjun; Bae, Jeong Mo; Kim, Hwang-Phill; Lyu, Jaemyun; Han, Hyojun; Kim, Hyoki; Jang, Hoon; Bang, Duhee; Huh, Iksoo; Park, Taesung; Won, Jae-Kyung; Jeong, Seung-Yong; Park, Kyu Joo; Kang, Gyeong Hoon; Kim, Tae-You

2017-09-15

Colorectal cancer (CRC) develops through the alteration of several critical pathways. This study was aimed at evaluating the influence of critical pathways on survival outcomes for patients with CRC. Targeted next-generation sequencing of 40 genes included in the 5 critical pathways of CRC (WNT, P53, RTK-RAS, phosphatidylinositol-4,5-bisphosphate 3-kinase [PI3K], and transforming growth factor β [TGF-β]) was performed for 516 patients with stage III or high-risk stage II CRC treated with surgery followed by adjuvant fluoropyrimidine and oxaliplatin chemotherapy. The associations between critical pathway mutations and relapse-free survival (RFS) and overall survival were analyzed. The associations were further analyzed according to the tumor location. The mutation rates for the WNT, P53, RTK-RAS, PI3K, and TGF-β pathways were 84.5%, 69.0%, 60.7%, 30.0%, and 28.9%, respectively. A mutation in the PI3K pathway was associated with longer RFS (adjusted hazard ratio [HR], 0.59; 95% confidence interval [CI], 0.36-0.99), whereas a mutation in the RTK-RAS pathway was associated with shorter RFS (adjusted HR, 1.60; 95% CI, 1.01-2.52). Proximal tumors showed a higher mutation rate than distal tumors, and the mutation profile was different according to the tumor location. The mutation rates of Kirsten rat sarcoma viral oncogene homolog (KRAS), phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit α (PIK3CA), and B-Raf proto-oncogene serine/threonine kinase (BRAF) were higher in proximal tumors, and the mutation rates of adenomatous polyposis coli (APC), tumor protein 53 (TP53), and neuroblastoma RAS viral oncogene homolog (NRAS) were higher in distal tumors. The better RFS with the PI3K pathway mutation was significant only for proximal tumors, and the worse RFS with the RTK-RAS pathway mutation was significant only for distal tumors. A PI3K pathway mutation was associated with better RFS for CRC patients treated with adjuvant chemotherapy, and an RTK

LncRNAs in Secondary Hair Follicle of Cashmere Goat: Identification, Expression, and Their Regulatory Network in Wnt Signaling Pathway.

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Bai, Wen L; Zhao, Su J; Wang, Ze Y; Zhu, Yu B; Dang, Yun L; Cong, Yu Y; Xue, Hui L; Wang, Wei; Deng, Liang; Guo, Dan; Wang, Shi Q; Zhu, Yan X; Yin, Rong H

2018-07-03

Long noncoding RNAs (lncRNAs) are a novel class of eukaryotic transcripts. They are thought to act as a critical regulator of protein-coding gene expression. Herein, we identified and characterized 13 putative lncRNAs from the expressed sequence tags from secondary hair follicle of Cashmere goat. Furthermore, we investigated their transcriptional pattern in secondary hair follicle of Liaoning Cashmere goat during telogen and anagen phases. Also, we generated intracellular regulatory networks of upregulated lncRNAs at anagen in Wnt signaling pathway based on bioinformatics analysis. The relative expression of six putative lncRNAs (lncRNA-599618, -599556, -599554, -599547, -599531, and -599509) at the anagen phase is significantly higher than that at telogen. Compared with anagen, the relative expression of four putative lncRNAs (lncRNA-599528, -599518, -599511, and -599497) was found to be significantly upregulated at telogen phase. The network generated showed that a rich and complex regulatory relationship of the putative lncRNAs and related miRNAs with their target genes in Wnt signaling pathway. Our results from the present study provided a foundation for further elucidating the functional and regulatory mechanisms of these putative lncRNAs in the development of secondary hair follicle and cashmere fiber growth of Cashmere goat.

Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

Science.gov (United States)

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

Find_tfSBP: find thermodynamics-feasible and smallest balanced pathways with high yield from large-scale metabolic networks.

Science.gov (United States)

Xu, Zixiang; Sun, Jibin; Wu, Qiaqing; Zhu, Dunming

2017-12-11

Biologically meaningful metabolic pathways are important references in the design of industrial bacterium. At present, constraint-based method is the only way to model and simulate a genome-scale metabolic network under steady-state criteria. Due to the inadequate assumption of the relationship in gene-enzyme-reaction as one-to-one unique association, computational difficulty or ignoring the yield from substrate to product, previous pathway finding approaches can't be effectively applied to find out the high yield pathways that are mass balanced in stoichiometry. In addition, the shortest pathways may not be the pathways with high yield. At the same time, a pathway, which exists in stoichiometry, may not be feasible in thermodynamics. By using mixed integer programming strategy, we put forward an algorithm to identify all the smallest balanced pathways which convert the source compound to the target compound in large-scale metabolic networks. The resulting pathways by our method can finely satisfy the stoichiometric constraints and non-decomposability condition. Especially, the functions of high yield and thermodynamics feasibility have been considered in our approach. This tool is tailored to direct the metabolic engineering practice to enlarge the metabolic potentials of industrial strains by integrating the extensive metabolic network information built from systems biology dataset.

Designing a Care Pathway Model - A Case Study of the Outpatient Total Hip Arthroplasty Care Pathway.

Science.gov (United States)

Oosterholt, Robin I; Simonse, Lianne Wl; Boess, Stella U; Vehmeijer, Stephan Bw

2017-03-09

Although the clinical attributes of total hip arthroplasty (THA) care pathways have been thoroughly researched, a detailed understanding of the equally important organisational attributes is still lacking. The aim of this article is to contribute with a model of the outpatient THA care pathway that depicts how the care team should be organised to enable patient discharge on the day of surgery. The outpatient THA care pathway enables patients to be discharged on the day of surgery, shortening the length of stay and intensifying the provision and organisation of care. We utilise visual care modelling to construct a visual design of the organisation of the care pathway. An embedded case study was conducted of the outpatient THA care pathway at a teaching hospital in the Netherlands. The data were collected using a visual care modelling toolkit in 16 semi-structured interviews. Problems and inefficiencies in the care pathway were identified and addressed in the iterative design process. The results are two visual models of the most critical phases of the outpatient THA care pathway: diagnosis & preparation (1) and mobilisation & discharge (4). The results show the care team composition, critical value exchanges, and sequence that enable patient discharge on the day of surgery. The design addressed existing problems and is an optimisation of the case hospital's pathway. The network of actors consists of the patient (1), radiologist (1), anaesthetist (1), nurse specialist (1), pharmacist (1), orthopaedic surgeon (1,4), physiotherapist (1,4), nurse (4), doctor (4) and patient application (1,4). The critical value exchanges include patient preparation (mental and practical), patient education, aligned care team, efficient sequence of value exchanges, early patient mobilisation, flexible availability of the physiotherapist, functional discharge criteria, joint decision making and availability of the care team.

Implementing critical pathways and a multidisciplinary team approach to cardiovascular disease management.

Science.gov (United States)

Peterson, Eric D; Albert, Nancy M; Amin, Alpesh; Patterson, J Herbert; Fonarow, Gregg C

2008-09-08

According to several medical registries, there is a need to improve the care of post-myocardial infarction (MI) patients, especially those with left ventricular dysfunction (LVD) and heart failure. This can potentially be achieved by implementing disease management programs, which include critical pathways, patient education, and multidisciplinary hospital teams. Currently, algorithms for critical pathways, including discharge processes, are lacking for post-MI LVD patients. Such schemes can increase the use of evidence-based medicines proved to reduce mortality. Educational programs are aimed at increasing patients' awareness of their condition, promoting medication compliance, and encouraging the adoption of healthy behaviors; such programs have been shown to be effective in improving outcomes of post-MI LVD patients. Reductions in all-cause hospitalizations and medical costs as well as improved survival rates have been observed when a multidisciplinary team (a nurse, a pharmacist, and a hospitalist) is engaged in patient care. In addition, the use of the "pay for performance" method, which can be advantageous for patients, physicians, and hospitals, may potentially improve the care of post-MI patients with LVD.

A pathway-based network analysis of hypertension-related genes

Science.gov (United States)

Wang, Huan; Hu, Jing-Bo; Xu, Chuan-Yun; Zhang, De-Hai; Yan, Qian; Xu, Ming; Cao, Ke-Fei; Zhang, Xu-Sheng

2016-02-01

Complex network approach has become an effective way to describe interrelationships among large amounts of biological data, which is especially useful in finding core functions and global behavior of biological systems. Hypertension is a complex disease caused by many reasons including genetic, physiological, psychological and even social factors. In this paper, based on the information of biological pathways, we construct a network model of hypertension-related genes of the salt-sensitive rat to explore the interrelationship between genes. Statistical and topological characteristics show that the network has the small-world but not scale-free property, and exhibits a modular structure, revealing compact and complex connections among these genes. By the threshold of integrated centrality larger than 0.71, seven key hub genes are found: Jun, Rps6kb1, Cycs, Creb312, Cdk4, Actg1 and RT1-Da. These genes should play an important role in hypertension, suggesting that the treatment of hypertension should focus on the combination of drugs on multiple genes.

Integrative Network Analysis Unveils Convergent Molecular Pathways in Parkinson's Disease and Diabetes

OpenAIRE

Santiago, Jose A.; Potashkin, Judith A.

2013-01-01

Background Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. ...

Social network as a determinant of pathway to mental health service ...

African Journals Online (AJOL)

Objective: The main objectives of the study were to determine the relationship between social network and pathway to service utilization among psychotic patients. Materials and Methods: This descriptive study was carried out in a psychiatric unit in a general hospital in South West Nigeria. Using structured questionnaires ...

Analysis of critical operating conditions for LV distribution networks with microgrids

Science.gov (United States)

Zehir, M. A.; Batman, A.; Sonmez, M. A.; Font, A.; Tsiamitros, D.; Stimoniaris, D.; Kollatou, T.; Bagriyanik, M.; Ozdemir, A.; Dialynas, E.

2016-11-01

Increase in the penetration of Distributed Generation (DG) in distribution networks, raises the risk of voltage limit violations while contributing to line losses. Especially in low voltage (LV) distribution networks (secondary distribution networks), impacts of active power flows on the bus voltages and on the network losses are more dominant. As network operators must meet regulatory limitations, they have to take into account the most critical operating conditions in their systems. In this study, it is aimed to present the impact of the worst operation cases of LV distribution networks comprising microgrids. Simulation studies are performed on a field data-based virtual test-bed. The simulations are repeated for several cases consisting different microgrid points of connection with different network loading and microgrid supply/demand conditions.

Interaction, Critical Thinking, and Social Network Analysis (SNA in Online Courses

Directory of Open Access Journals (Sweden)

Joan Thormann

2013-07-01

Full Text Available This study tried to ascertain a possible relationship between the number of student moderators (1, 2, and 3, online interactions, and critical thinking of K-12 educators enrolled in an online course that was taught from a constructivist approach. The course topic was use of technology in special education. Social network analysis (SNA and measures of critical thinking (Newman, Webb, & Cochrane, 1995 were used to research and assess if there was a difference in interaction and critical thinking between 1, 2, or 3 student moderators who facilitated a forum discussion of an assignment in an online course. The same course was repeated over three years. Each year either 1, 2, or 3 students moderated. The analysis indicated more discussion per non-moderating student with the three student moderated group. Using SNA we found that there was only one noticeable difference among the three groups which was in the value of network centralization. Using critical thinking measures the three student moderator group scored higher in five of the eight critical thinking categories. Variations in instructor presence in the online courses may have influenced these findings.

Critical assessment of human metabolic pathway databases: a stepping stone for future integration

Directory of Open Access Journals (Sweden)

Stobbe Miranda D

2011-10-01

Full Text Available Abstract Background Multiple pathway databases are available that describe the human metabolic network and have proven their usefulness in many applications, ranging from the analysis and interpretation of high-throughput data to their use as a reference repository. However, so far the various human metabolic networks described by these databases have not been systematically compared and contrasted, nor has the extent to which they differ been quantified. For a researcher using these databases for particular analyses of human metabolism, it is crucial to know the extent of the differences in content and their underlying causes. Moreover, the outcomes of such a comparison are important for ongoing integration efforts. Results We compared the genes, EC numbers and reactions of five frequently used human metabolic pathway databases. The overlap is surprisingly low, especially on reaction level, where the databases agree on 3% of the 6968 reactions they have combined. Even for the well-established tricarboxylic acid cycle the databases agree on only 5 out of the 30 reactions in total. We identified the main causes for the lack of overlap. Importantly, the databases are partly complementary. Other explanations include the number of steps a conversion is described in and the number of possible alternative substrates listed. Missing metabolite identifiers and ambiguous names for metabolites also affect the comparison. Conclusions Our results show that each of the five networks compared provides us with a valuable piece of the puzzle of the complete reconstruction of the human metabolic network. To enable integration of the networks, next to a need for standardizing the metabolite names and identifiers, the conceptual differences between the databases should be resolved. Considerable manual intervention is required to reach the ultimate goal of a unified and biologically accurate model for studying the systems biology of human metabolism. Our comparison

Proteomic Assessment of Biochemical Pathways That Are Critical to Nickel-Induced Toxicity Responses in Human Epithelial Cells

Science.gov (United States)

Ge, Yue; Bruno, Maribel; Haykal-Coates, Najwa; Wallace, Kathleen; Andrews, Debora; Swank, Adam; Winnik, Witold; Ross, Jeffrey A.

2016-01-01

Understanding the mechanisms underlying toxicity initiated by nickel, a ubiquitous environmental contaminant and known human carcinogen is necessary for proper assessment of its risks to human and environment. Among a variety of toxic mechanisms, disruption of protein responses and protein response-based biochemical pathways represents a key mechanism through which nickel induces cytotoxicity and carcinogenesis. To identify protein responses and biochemical pathways that are critical to nickel-induced toxicity responses, we measured cytotoxicity and changes in expression and phosphorylation status of 14 critical biochemical pathway regulators in human BEAS-2B cells exposed to four concentrations of nickel using an integrated proteomic approach. A subset of the pathway regulators, including interleukin-6, and JNK, were found to be linearly correlated with cell viability, and may function as molecular determinants of cytotoxic responses of BEAS-2B cells to nickel exposures. In addition, 128 differentially expressed proteins were identified by two dimensional electrophoresis (2-DE) and mass spectrometry. Principal component analysis, hierarchical cluster analyses, and ingenuity signaling pathway analysis (IPA) identified putative nickel toxicity pathways. Some of the proteins and pathways identified have not previously been linked to nickel toxicity. Based on the consistent results obtained from both ELISA and 2-DE proteomic analysis, we propose a core signaling pathway regulating cytotoxic responses of human BEAS-2B cells to nickel exposures, which integrates a small set of proteins involved in glycolysis and gluconeogenesis pathways, apoptosis, protein degradation, and stress responses including inflammation and oxidative stress. PMID:27626938

Unravelling Protein-Protein Interaction Networks Linked to Aliphatic and Indole Glucosinolate Biosynthetic Pathways in Arabidopsis

Directory of Open Access Journals (Sweden)

Sebastian J. Nintemann

2017-11-01

Full Text Available Within the cell, biosynthetic pathways are embedded in protein-protein interaction networks. In Arabidopsis, the biosynthetic pathways of aliphatic and indole glucosinolate defense compounds are well-characterized. However, little is known about the spatial orchestration of these enzymes and their interplay with the cellular environment. To address these aspects, we applied two complementary, untargeted approaches—split-ubiquitin yeast 2-hybrid and co-immunoprecipitation screens—to identify proteins interacting with CYP83A1 and CYP83B1, two homologous enzymes specific for aliphatic and indole glucosinolate biosynthesis, respectively. Our analyses reveal distinct functional networks with substantial interconnection among the identified interactors for both pathway-specific markers, and add to our knowledge about how biochemical pathways are connected to cellular processes. Specifically, a group of protein interactors involved in cell death and the hypersensitive response provides a potential link between the glucosinolate defense compounds and defense against biotrophic pathogens, mediated by protein-protein interactions.

Designing a Care Pathway Model – A Case Study of the Outpatient Total Hip Arthroplasty Care Pathway

Directory of Open Access Journals (Sweden)

Robin I. Oosterholt

2017-03-01

Full Text Available Introduction: Although the clinical attributes of total hip arthroplasty (THA care pathways have been thoroughly researched, a detailed understanding of the equally important organisational attributes is still lacking. The aim of this article is to contribute with a model of the outpatient THA care pathway that depicts how the care team should be organised to enable patient discharge on the day of surgery. Theory: The outpatient THA care pathway enables patients to be discharged on the day of surgery, short- ening the length of stay and intensifying the provision and organisation of care. We utilise visual care modelling to construct a visual design of the organisation of the care pathway. Methods: An embedded case study was conducted of the outpatient THA care pathway at a teaching hospital in the Netherlands. The data were collected using a visual care modelling toolkit in 16 semi- structured interviews. Problems and inefficiencies in the care pathway were identified and addressed in the iterative design process. Results: The results are two visual models of the most critical phases of the outpatient THA care pathway: diagnosis & preparation (1 and mobilisation & discharge (4. The results show the care team composition, critical value exchanges, and sequence that enable patient discharge on the day of surgery. Conclusion: The design addressed existing problems and is an optimisation of the case hospital’s pathway. The network of actors consists of the patient (1, radiologist (1, anaesthetist (1, nurse specialist (1, pharmacist (1, orthopaedic surgeon (1,4, physiotherapist (1,4, nurse (4, doctor (4 and patient applica- tion (1,4. The critical value exchanges include patient preparation (mental and practical, patient education, aligned care team, efficient sequence of value exchanges, early patient mobilisation, flexible availability of the physiotherapist, functional discharge criteria, joint decision making and availability of the care team.

Critical Vulnerability: Defending the Decisive Point of United States Computer Networked Information Systems

National Research Council Canada - National Science Library

Virden, Roy

2003-01-01

.... The military's use of computer networked information systems is thus a critical strength. These systems are then critical vulnerabilities because they may lack adequate protection and are open to enemy attack...

FREQUENT SUBGRAPH MINING OF PERSONALIZED SIGNALING PATHWAY NETWORKS GROUPS PATIENTS WITH FREQUENTLY DYSREGULATED DISEASE PATHWAYS AND PREDICTS PROGNOSIS.

Science.gov (United States)

Durmaz, Arda; Henderson, Tim A D; Brubaker, Douglas; Bebek, Gurkan

2017-01-01

Large scale genomics studies have generated comprehensive molecular characterization of numerous cancer types. Subtypes for many tumor types have been established; however, these classifications are based on molecular characteristics of a small gene sets with limited power to detect dysregulation at the patient level. We hypothesize that frequent graph mining of pathways to gather pathways functionally relevant to tumors can characterize tumor types and provide opportunities for personalized therapies. In this study we present an integrative omics approach to group patients based on their altered pathway characteristics and show prognostic differences within breast cancer (p network-based classifier algorithms and showed that our unsupervised approach generates more robust and biologically relevant clustering whereas previous approaches failed to report specific functions for similar patient groups or classify patients into prognostic groups. These results could serve as a means to improve prognosis for future cancer patients, and to provide opportunities for improved treatment options and personalized interventions. The proposed novel graph mining approach is able to integrate PPI networks with gene expression in a biologically sound approach and cluster patients in to clinically distinct groups. We have utilized breast cancer and glioblastoma multiforme datasets from microarray and RNA-Seq platforms and identified disease mechanisms differentiating samples. Supplementary methods, figures, tables and code are available at https://github.com/bebeklab/dysprog.

Pathway and network-based analysis of genome-wide association studies and RT-PCR validation in polycystic ovary syndrome.

Science.gov (United States)

Shen, Haoran; Liang, Zhou; Zheng, Saihua; Li, Xuelian

2017-11-01

The purpose of this study was to identify promising candidate genes and pathways in polycystic ovary syndrome (PCOS). Microarray dataset GSE345269 obtained from the Gene Expression Omnibus database includes 7 granulosa cell samples from PCOS patients, and 3 normal granulosa cell samples. Differentially expressed genes (DEGs) were screened between PCOS and normal samples. Pathway enrichment analysis was conducted for DEGs using ClueGO and CluePedia plugin of Cytoscape. A Reactome functional interaction (FI) network of the DEGs was built using ReactomeFIViz, and then network modules were extracted, followed by pathway enrichment analysis for the modules. Expression of DEGs in granulosa cell samples was measured using quantitative RT-PCR. A total of 674 DEGs were retained, which were significantly enriched with inflammation and immune-related pathways. Eight modules were extracted from the Reactome FI network. Pathway enrichment analysis revealed significant pathways of each module: module 0, Regulation of RhoA activity and Signaling by Rho GTPases pathways shared ARHGAP4 and ARHGAP9; module 2, GlycoProtein VI-mediated activation cascade pathway was enriched with RHOG; module 3, Thromboxane A2 receptor signaling, Chemokine signaling pathway, CXCR4-mediated signaling events pathways were enriched with LYN, the hub gene of module 3. Results of RT-PCR confirmed the finding of the bioinformatic analysis that ARHGAP4, ARHGAP9, RHOG and LYN were significantly upregulated in PCOS. RhoA-related pathways, GlycoProtein VI-mediated activation cascade pathway, ARHGAP4, ARHGAP9, RHOG and LYN may be involved in the pathogenesis of PCOS.

Optimizing mission critical data dissemination in massive IoT networks

KAUST Repository

Farooq, Muhammad Junaid

2017-06-29

Mission critical data dissemination in massive Internet of things (IoT) networks imposes constraints on the message transfer delay between devices. Due to low power and communication range of IoT devices, data is foreseen to be relayed over multiple device-to-device (D2D) links before reaching the destination. The coexistence of a massive number of IoT devices poses a challenge in maximizing the successful transmission capacity of the overall network alongside reducing the multi-hop transmission delay in order to support mission critical applications. There is a delicate interplay between the carrier sensing threshold of the contention based medium access protocol and the choice of packet forwarding strategy selected at each hop by the devices. The fundamental problem in optimizing the performance of such networks is to balance the tradeoff between conflicting performance objectives such as the spatial frequency reuse, transmission quality, and packet progress towards the destination. In this paper, we use a stochastic geometry approach to quantify the performance of multi-hop massive IoT networks in terms of the spatial frequency reuse and the transmission quality under different packet forwarding schemes. We also develop a comprehensive performance metric that can be used to optimize the system to achieve the best performance. The results can be used to select the best forwarding scheme and tune the carrier sensing threshold to optimize the performance of the network according to the delay constraints and transmission quality requirements.

Network modularity reveals critical scales for connectivity in ecology and evolution

Science.gov (United States)

Fletcher, Robert J.; Revell, Andre; Reichert, Brian E.; Kitchens, Wiley M.; Dixon, J.; Austin, James D.

2013-01-01

For nearly a century, biologists have emphasized the profound importance of spatial scale for ecology, evolution and conservation. Nonetheless, objectively identifying critical scales has proven incredibly challenging. Here we extend new techniques from physics and social sciences that estimate modularity on networks to identify critical scales for movement and gene flow in animals. Using four species that vary widely in dispersal ability and include both mark-recapture and population genetic data, we identify significant modularity in three species, two of which cannot be explained by geographic distance alone. Importantly, the inclusion of modularity in connectivity and population viability assessments alters conclusions regarding patch importance to connectivity and suggests higher metapopulation viability than when ignoring this hidden spatial scale. We argue that network modularity reveals critical meso-scales that are probably common in populations, providing a powerful means of identifying fundamental scales for biology and for conservation strategies aimed at recovering imperilled species.

Critical behavior of the XY-rotor model on regular and small-world networks

Science.gov (United States)

De Nigris, Sarah; Leoncini, Xavier

2013-07-01

We study the XY rotors model on small networks whose number of links scales with the system size Nlinks˜Nγ, where 1≤γ≤2. We first focus on regular one-dimensional rings in the microcanonical ensemble. For γ1.5, the system equilibrium properties are found to be identical to the mean field, which displays a second-order phase transition at a critical energy density ɛ=E/N,ɛc=0.75. Moreover, for γc≃1.5 we find that a nontrivial state emerges, characterized by an infinite susceptibility. We then consider small-world networks, using the Watts-Strogatz mechanism on the regular networks parametrized by γ. We first analyze the topology and find that the small-world regime appears for rewiring probabilities which scale as pSW∝1/Nγ. Then considering the XY-rotors model on these networks, we find that a second-order phase transition occurs at a critical energy ɛc which logarithmically depends on the topological parameters p and γ. We also define a critical probability pMF, corresponding to the probability beyond which the mean field is quantitatively recovered, and we analyze its dependence on γ.

Protein design for pathway engineering.

Science.gov (United States)

Eriksen, Dawn T; Lian, Jiazhang; Zhao, Huimin

2014-02-01

Design and construction of biochemical pathways has increased the complexity of biosynthetically-produced compounds when compared to single enzyme biocatalysis. However, the coordination of multiple enzymes can introduce a complicated set of obstacles to overcome in order to achieve a high titer and yield of the desired compound. Metabolic engineering has made great strides in developing tools to optimize the flux through a target pathway, but the inherent characteristics of a particular enzyme within the pathway can still limit the productivity. Thus, judicious protein design is critical for metabolic and pathway engineering. This review will describe various strategies and examples of applying protein design to pathway engineering to optimize the flux through the pathway. The proteins can be engineered for altered substrate specificity/selectivity, increased catalytic activity, reduced mass transfer limitations through specific protein localization, and reduced substrate/product inhibition. Protein engineering can also be expanded to design biosensors to enable high through-put screening and to customize cell signaling networks. These strategies have successfully engineered pathways for significantly increased productivity of the desired product or in the production of novel compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

Inducing self-organized criticality in a network toy model by neighborhood assortativity.

Science.gov (United States)

Allen-Perkins, Alfonso; Galeano, Javier; Pastor, Juan Manuel

2016-11-01

Complex networks are a recent type of framework used to study complex systems with many interacting elements, such as self-organized criticality (SOC). The network nodes' tendency to link to other nodes of similar type is characterized by assortative mixing. Real networks exhibit assortative mixing by vertex degree, however, typical random network models, such as the Erdős-Rényi or the Barabási-Albert model, show no assortative arrangements. In this paper we introduce the notion of neighborhood assortativity as the tendency of a node to belong to a community (its neighborhood) showing an average property similar to its own. Imposing neighborhood assortative mixing by degree in a network toy model, SOC dynamics can be found. These dynamics are driven only by the network topology. The long-range correlations resulting from criticality have been characterized by means of fluctuation analysis and show an anticorrelation in the node's activity. The model contains only one parameter and its statistics plots for different values of the parameter can be collapsed into a single curve. The simplicity of the model allows us to perform numerical simulations and also to study analytically the statistics for a specific value of the parameter, making use of the Markov chains.

Safety culture and subcontractor network governance in a complex safety critical project

International Nuclear Information System (INIS)

Oedewald, Pia; Gotcheva, Nadezhda

2015-01-01

In safety critical industries many activities are currently carried out by subcontractor networks. Nevertheless, there are few studies where the core dimensions of resilience would have been studied in safety critical network activities. This paper claims that engineering resilience into a system is largely about steering the development of culture of the system towards better ability to anticipate, monitor, respond and learn. Thus, safety culture literature has relevance in resilience engineering field. This paper analyzes practical and theoretical challenges in applying the concept of safety culture in a complex, dynamic network of subcontractors involved in the construction of a new nuclear power plant in Finland, Olkiluoto 3. The concept of safety culture is in focus since it is widely used in nuclear industry and bridges the scientific and practical interests. This paper approaches subcontractor networks as complex systems. However, the management model of the Olkiluoto 3 project is to a large degree a traditional top-down hierarchy, which creates a mismatch between the management approach and the characteristics of the system to be managed. New insights were drawn from network governance studies. - Highlights: • We studied a relevant topical subject safety culture in nuclear new build project. • We integrated safety science challenges and network governance studies. • We produced practicable insights in managing safety of subcontractor networks

Efficient identification of critical residues based only on protein structure by network analysis.

Directory of Open Access Journals (Sweden)

Michael P Cusack

2007-05-01

Full Text Available Despite the increasing number of published protein structures, and the fact that each protein's function relies on its three-dimensional structure, there is limited access to automatic programs used for the identification of critical residues from the protein structure, compared with those based on protein sequence. Here we present a new algorithm based on network analysis applied exclusively on protein structures to identify critical residues. Our results show that this method identifies critical residues for protein function with high reliability and improves automatic sequence-based approaches and previous network-based approaches. The reliability of the method depends on the conformational diversity screened for the protein of interest. We have designed a web site to give access to this software at http://bis.ifc.unam.mx/jamming/. In summary, a new method is presented that relates critical residues for protein function with the most traversed residues in networks derived from protein structures. A unique feature of the method is the inclusion of the conformational diversity of proteins in the prediction, thus reproducing a basic feature of the structure/function relationship of proteins.

Optimizing mission critical data dissemination in massive IoT networks

KAUST Repository

Farooq, Muhammad Junaid; Elsawy, Hesham; Zhu, Quanyan; Alouini, Mohamed-Slim

2017-01-01

Mission critical data dissemination in massive Internet of things (IoT) networks imposes constraints on the message transfer delay between devices. Due to low power and communication range of IoT devices, data is foreseen to be relayed over multiple

Nano hydroxyapatite-blasted titanium surface affects pre-osteoblast morphology by modulating critical intracellular pathways.

Science.gov (United States)

Bezerra, Fábio; Ferreira, Marcel R; Fontes, Giselle N; da Costa Fernandes, Célio Jr; Andia, Denise C; Cruz, Nilson C; da Silva, Rodrigo A; Zambuzzi, Willian F

2017-08-01

Although, intracellular signaling pathways are proposed to predict the quality of cell-surface relationship, this study addressed pre-osteoblast behavior in response to nano hydroxyapatite (HA)-blasted titanium (Ti) surface by exploring critical intracellular pathways and pre-osteoblast morphological change. Physicochemical properties were evaluated by atomic force microscopy (AFM) and wettability considering water contact angle of three differently texturized Ti surfaces: Machined (Mac), Dual acid-etching (DAE), and nano hydroxyapatite-blasted (nHA). The results revealed critical differences in surface topography, impacting the water contact angle and later the osteoblast performance. In order to evaluate the effect of those topographical characteristics on biological responses, we have seeded pre-osteoblast cells on the Ti discs for up to 4 h and subjected the cultures to biological analysis. First, we have observed pre-osteoblasts morphological changes resulting from the interaction with the Ti texturized surfaces whereas the cells cultured on nHA presented a more advanced spreading process when compared with the cells cultured on the other surfaces. These results argued us for analyzing the molecular machinery and thus, we have shown that nHA promoted a lower Bax/Bcl2 ratio, suggesting an interesting anti-apoptotic effect, maybe explained by the fact that HA is a natural element present in bone composition. Thereafter, we investigated the potential effect of those surfaces on promoting pre-osteoblast adhesion and survival signaling by performing crystal violet and immunoblotting approaches, respectively. Our results showed that nHA promoted a higher pre-osteoblast adhesion supported by up-modulating FAK and Src activations, both signaling transducers involved during eukaryotic cell adhesion. Also, we have shown Ras-Erk stimulation by the all evaluated surfaces. Finally, we showed that all Ti-texturing surfaces were able to promote osteoblast differentiation

Neuronal network disintegration: common pathways linking neurodegenerative diseases.

Science.gov (United States)

Ahmed, Rebekah M; Devenney, Emma M; Irish, Muireann; Ittner, Arne; Naismith, Sharon; Ittner, Lars M; Rohrer, Jonathan D; Halliday, Glenda M; Eisen, Andrew; Hodges, John R; Kiernan, Matthew C

2016-11-01

Neurodegeneration refers to a heterogeneous group of brain disorders that progressively evolve. It has been increasingly appreciated that many neurodegenerative conditions overlap at multiple levels and therefore traditional clinicopathological correlation approaches to better classify a disease have met with limited success. Neuronal network disintegration is fundamental to neurodegeneration, and concepts based around such a concept may better explain the overlap between their clinical and pathological phenotypes. In this Review, promoters of overlap in neurodegeneration incorporating behavioural, cognitive, metabolic, motor, and extrapyramidal presentations will be critically appraised. In addition, evidence that may support the existence of large-scale networks that might be contributing to phenotypic differentiation will be considered across a neurodegenerative spectrum. Disintegration of neuronal networks through different pathological processes, such as prion-like spread, may provide a better paradigm of disease and thereby facilitate the identification of novel therapies for neurodegeneration. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

The origin of the criticality in meme popularity distribution on complex networks.

Science.gov (United States)

Kim, Yup; Park, Seokjong; Yook, Soon-Hyung

2016-03-24

Previous studies showed that the meme popularity distribution is described by a heavy-tailed distribution or a power-law, which is a characteristic feature of the criticality. Here, we study the origin of the criticality on non-growing and growing networks based on the competition induced criticality model. From the direct Mote Carlo simulations and the exact mapping into the position dependent biased random walk (PDBRW), we find that the meme popularity distribution satisfies a very robust power- law with exponent α = 3/2 if there is an innovation process. On the other hand, if there is no innovation, then we find that the meme popularity distribution is bounded and highly skewed for early transient time periods, while it satisfies a power-law with exponent α ≠ 3/2 for intermediate time periods. The exact mapping into PDBRW clearly shows that the balance between the creation of new memes by the innovation process and the extinction of old memes is the key factor for the criticality. We confirm that the balance for the criticality sustains for relatively small innovation rate. Therefore, the innovation processes with significantly influential memes should be the simple and fundamental processes which cause the critical distribution of the meme popularity in real social networks.

The origin of the criticality in meme popularity distribution on complex networks

Science.gov (United States)

Kim, Yup; Park, Seokjong; Yook, Soon-Hyung

2016-03-01

Previous studies showed that the meme popularity distribution is described by a heavy-tailed distribution or a power-law, which is a characteristic feature of the criticality. Here, we study the origin of the criticality on non-growing and growing networks based on the competition induced criticality model. From the direct Mote Carlo simulations and the exact mapping into the position dependent biased random walk (PDBRW), we find that the meme popularity distribution satisfies a very robust power- law with exponent α = 3/2 if there is an innovation process. On the other hand, if there is no innovation, then we find that the meme popularity distribution is bounded and highly skewed for early transient time periods, while it satisfies a power-law with exponent α ≠ 3/2 for intermediate time periods. The exact mapping into PDBRW clearly shows that the balance between the creation of new memes by the innovation process and the extinction of old memes is the key factor for the criticality. We confirm that the balance for the criticality sustains for relatively small innovation rate. Therefore, the innovation processes with significantly influential memes should be the simple and fundamental processes which cause the critical distribution of the meme popularity in real social networks.

Phase transitions and self-organized criticality in networks of stochastic spiking neurons.

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Brochini, Ludmila; de Andrade Costa, Ariadne; Abadi, Miguel; Roque, Antônio C; Stolfi, Jorge; Kinouchi, Osame

2016-11-07

Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Φ(V) of the membrane potential V, rather than a sharp firing threshold. We find that such networks can operate in several dynamic regimes (phases) depending on the average synaptic weight and the shape of the firing function Φ. In particular, we encounter both continuous and discontinuous phase transitions to absorbing states. At the continuous transition critical boundary, neuronal avalanches occur whose distributions of size and duration are given by power laws, as observed in biological neural networks. We also propose and test a new mechanism to produce SOC: the use of dynamic neuronal gains - a form of short-term plasticity probably located at the axon initial segment (AIS) - instead of depressing synapses at the dendrites (as previously studied in the literature). The new self-organization mechanism produces a slightly supercritical state, that we called SOSC, in accord to some intuitions of Alan Turing.

Automated implementation of rule-based expert systems with neural networks for time-critical applications

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Ramamoorthy, P. A.; Huang, Song; Govind, Girish

1991-01-01

In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

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Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

2010-01-01

Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

Critical properties of the SIS model dynamics on the Apollonian network

International Nuclear Information System (INIS)

Da Silva, L F; Costa Filho, R N; Cunha, A R; Macedo-Filho, A; Serva, M; Fulco, U L; Albuquerque, E L

2013-01-01

We present an analysis of the classical SIS (susceptible–infected–susceptible) model on the Apollonian network which is scale free and displays the small word effect. Numerical simulations show a continuous absorbing-state phase transition at a finite critical value λ c of the control parameter λ. Since the coordination number k of the vertices of the Apollonian network is cumulatively distributed according to a power-law P(k) ∝ 1/k η−1 , with exponent η ≃ 2.585, finite size effects are large and the infinite network limit cannot be reached in practice. Consequently, our study requires the application of finite size scaling theory, allowing us to characterize the transition by a set of critical exponents β/ν ⊥ , γ/ν ⊥ , ν ⊥ , β. We found that the phase transition belongs to the mean-field directed percolation universality class in regular lattices but, very peculiarly, is associated with a short-range distribution whose power-law distribution of k is defined by an exponent η larger than 3. (paper)

Thermodynamic analysis of computed pathways integrated into the metabolic networks of E. coli and Synechocystis reveals contrasting expansion potential.

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Asplund-Samuelsson, Johannes; Janasch, Markus; Hudson, Elton P

2018-01-01

Introducing biosynthetic pathways into an organism is both reliant on and challenged by endogenous biochemistry. Here we compared the expansion potential of the metabolic network in the photoautotroph Synechocystis with that of the heterotroph E. coli using the novel workflow POPPY (Prospecting Optimal Pathways with PYthon). First, E. coli and Synechocystis metabolomic and fluxomic data were combined with metabolic models to identify thermodynamic constraints on metabolite concentrations (NET analysis). Then, thousands of automatically constructed pathways were placed within each network and subjected to a network-embedded variant of the max-min driving force analysis (NEM). We found that the networks had different capabilities for imparting thermodynamic driving forces toward certain compounds. Key metabolites were constrained differently in Synechocystis due to opposing flux directions in glycolysis and carbon fixation, the forked tri-carboxylic acid cycle, and photorespiration. Furthermore, the lysine biosynthesis pathway in Synechocystis was identified as thermodynamically constrained, impacting both endogenous and heterologous reactions through low 2-oxoglutarate levels. Our study also identified important yet poorly covered areas in existing metabolomics data and provides a reference for future thermodynamics-based engineering in Synechocystis and beyond. The POPPY methodology represents a step in making optimal pathway-host matches, which is likely to become important as the practical range of host organisms is diversified. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Construction of an miRNA-Regulated Pathway Network Reveals Candidate Biomarkers for Postmenopausal Osteoporosis

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Min Shao

2017-01-01

Full Text Available We aimed to identify risk pathways for postmenopausal osteoporosis (PMOP via establishing an microRNAs- (miRNA- regulated pathway network (MRPN. Firstly, we identified differential pathways through calculating gene- and pathway-level statistics based on the accumulated normal samples using the individual pathway aberrance score (iPAS. Significant pathways based on differentially expressed genes (DEGs using DAVID were extracted, followed by identifying the common pathways between iPAS and DAVID methods. Next, miRNAs prediction was implemented via calculating TargetScore values with precomputed input (log fold change (FC, TargetScan context score (TSCS, and probabilities of conserved targeting (PCT. An MRPN construction was constructed using the common genes in the common pathways and the predicted miRNAs. Using false discovery rate (FDR < 0.05, 279 differential pathways were identified. Using the criteria of FDR < 0.05 and log⁡FC≥2, 39 DEGs were retrieved, and these DEGs were enriched in 64 significant pathways identified by DAVID. Overall, 27 pathways were the common ones between two methods. Importantly, MAPK signaling pathway and PI3K-Akt signaling pathway were the first and second significantly enriched ones, respectively. These 27 common pathways separated PMOP from controls with the accuracy of 0.912. MAPK signaling pathway and PI3K/Akt signaling pathway might play crucial roles in PMOP.

A Systems Biology Analysis Unfolds the Molecular Pathways and Networks of Two Proteobacteria in Spaceflight and Simulated Microgravity Conditions.

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Roy, Raktim; Shilpa, P Phani; Bagh, Sangram

2016-09-01

Bacteria are important organisms for space missions due to their increased pathogenesis in microgravity that poses risks to the health of astronauts and for projected synthetic biology applications at the space station. We understand little about the effect, at the molecular systems level, of microgravity on bacteria, despite their significant incidence. In this study, we proposed a systems biology pipeline and performed an analysis on published gene expression data sets from multiple seminal studies on Pseudomonas aeruginosa and Salmonella enterica serovar Typhimurium under spaceflight and simulated microgravity conditions. By applying gene set enrichment analysis on the global gene expression data, we directly identified a large number of new, statistically significant cellular and metabolic pathways involved in response to microgravity. Alteration of metabolic pathways in microgravity has rarely been reported before, whereas in this analysis metabolic pathways are prevalent. Several of those pathways were found to be common across studies and species, indicating a common cellular response in microgravity. We clustered genes based on their expression patterns using consensus non-negative matrix factorization. The genes from different mathematically stable clusters showed protein-protein association networks with distinct biological functions, suggesting the plausible functional or regulatory network motifs in response to microgravity. The newly identified pathways and networks showed connection with increased survival of pathogens within macrophages, virulence, and antibiotic resistance in microgravity. Our work establishes a systems biology pipeline and provides an integrated insight into the effect of microgravity at the molecular systems level. Systems biology-Microgravity-Pathways and networks-Bacteria. Astrobiology 16, 677-689.

Reliability modeling of safety-critical network communication in a digitalized nuclear power plant

International Nuclear Information System (INIS)

Lee, Sang Hun; Kim, Hee Eun; Son, Kwang Seop; Shin, Sung Min; Lee, Seung Jun; Kang, Hyun Gook

2015-01-01

The Engineered Safety Feature-Component Control System (ESF-CCS), which uses a network communication system for the transmission of safety-critical information from group controllers (GCs) to loop controllers (LCs), was recently developed. However, the ESF-CCS has not been applied to nuclear power plants (NPPs) because the network communication failure risk in the ESF-CCS has yet to be fully quantified. Therefore, this study was performed to identify the potential hazardous states for network communication between GCs and LCs and to develop quantification schemes for various network failure causes. To estimate the risk effects of network communication failures in the ESF-CCS, a fault-tree model of an ESF-CCS signal failure in the containment spray actuation signal condition was developed for the case study. Based on a specified range of periodic inspection periods for network modules and the baseline probability of software failure, a sensitivity study was conducted to analyze the risk effect of network failure between GCs and LCs on ESF-CCS signal failure. This study is expected to provide insight into the development of a fault-tree model for network failures in digital I&C systems and the quantification of the risk effects of network failures for safety-critical information transmission in NPPs. - Highlights: • Network reliability modeling framework for digital I&C system in NPP is proposed. • Hazardous states of network protocol between GC and LC in ESF-CCS are identified. • Fault-tree model of ESF-CCS signal failure in ESF actuation condition is developed. • Risk effect of network failure on ESF-CCS signal failure is analyzed.

Critical behavior of the contact process in a multiscale network

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Ferreira, Silvio C.; Martins, Marcelo L.

2007-09-01

Inspired by dengue and yellow fever epidemics, we investigated the contact process (CP) in a multiscale network constituted by one-dimensional chains connected through a Barabási-Albert scale-free network. In addition to the CP dynamics inside the chains, the exchange of individuals between connected chains (travels) occurs at a constant rate. A finite epidemic threshold and an epidemic mean lifetime diverging exponentially in the subcritical phase, concomitantly with a power law divergence of the outbreak’s duration, were found. A generalized scaling function involving both regular and SF components was proposed for the quasistationary analysis and the associated critical exponents determined, demonstrating that the CP on this hybrid network and nonvanishing travel rates establishes a new universality class.

Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).

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Huan, Jinliang; Wang, Lishan; Xing, Li; Qin, Xianju; Feng, Lingbin; Pan, Xiaofeng; Zhu, Ling

2014-01-01

Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with KEGG pathway enrichment, PPI network construction, module analysis and text mining methods to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the genes queried on the Affymetrix Human Genome U133 plus 2.0 microarray, we identified 628 (12h), 852 (24h) and 880 (48 h) differentially expressed genes (DEGs) that showed a robust pattern of regulation by E2. From pathway enrichment analysis, we found out the changes of metabolic pathways of E2 treated samples at each time point. At 12h time point, the changes of metabolic pathways were mainly focused on pathways in cancer, focal adhesion, and chemokine signaling pathway. At 24h time point, the changes were mainly enriched in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction and calcium signaling pathway. At 48 h time point, the significant pathways were pathways in cancer, regulation of actin cytoskeleton, cell adhesion molecules (CAMs), axon guidance and ErbB signaling pathway. Of interest, our PPI network analysis and module analysis found that E2 treatment induced enhancement of PRSS23 at the three time points and PRSS23 was in the central position of each module. Text mining results showed that the important genes of DEGs have relationship with signal pathways, such as ERbB pathway (AREG), Wnt pathway (NDP), MAPK pathway (NTRK3, TH), IP3 pathway (TRA@) and some transcript factors (TCF4, MAF). Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to achieve its

Group B streptococcal infection of the choriodecidua induces dysfunction of the cytokeratin network in amniotic epithelium: a pathway to membrane weakening.

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Jeroen P Vanderhoeven

2014-03-01

Full Text Available Early events leading to intrauterine infection remain poorly defined, but may hold the key to preventing preterm delivery. To determine molecular pathways within fetal membranes (chorioamnion associated with early choriodecidual infection that may progress to preterm premature rupture of membranes (PPROM, we examined the effects of a Group B Streptococcus (GBS choriodecidual infection on chorioamnion in a nonhuman primate model. Ten chronically catheterized pregnant monkeys (Macaca nemestrina at 118-125 days gestation (term = 172 days received choriodecidual inoculation of either GBS (n = 5 or saline (n = 5. Cesarean section was performed in the first week after GBS or saline inoculation. RNA extracted from chorioamnion (inoculation site was profiled by microarray. Single gene, Gene Set, and Ingenuity Pathway Analysis results were validated using qRT-PCR (chorioamnion, Luminex (amniotic fluid, AF, immunohistochemistry, and transmission electron microscopy (TEM. Despite uterine quiescence in most cases, significant elevations of AF cytokines (TNF-α, IL-8, IL-1β, IL-6 were detected in GBS versus controls (p2-fold change, p<0.05. Remarkably, GBS exposure was associated with significantly downregulated expression of multiple cytokeratin (CK and other cytoskeletal genes critical for maintenance of tissue tensile strength. Immunofluorescence revealed highly significant changes in the CK network within amniocytes with dense CK aggregates and retraction from the cell periphery (all p = 0.006. In human pregnancies affected by PPROM, there was further evidence of CK network retraction with significantly shorter amniocyte foot processes (p = 0.002. These results suggest early choriodecidual infection results in decreased cellular membrane integrity and tensile strength via dysfunction of CK networks. Downregulation of CK expression and perturbations in the amniotic epithelial cell intermediate filament network occur after GBS

Effects of Network Treatments on Perceptions of a Political Campaign Film: Can Rhetorical Criticism Make a Difference?

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Simons, Herbert W.; And Others

1989-01-01

Compares three television networks' treatments of "A New Beginning" (a Reagan campaign film shown at the 1984 Republican National Convention) and examines the effects on viewers of one network's critical preview of the film. Assesses the uses and limitations of rhetorical criticism in television coverage of political campaigns. (SR)

Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks.

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Matteo Smerlak

Full Text Available The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the "critical degree" (the number of creditors per bank below which an individual shock can propagate throughout the network, and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology.

Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks.

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Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S

2015-01-01

The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the "critical degree" (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology.

Social Network Assessments and Interventions for Health Behavior Change: A Critical Review.

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Latkin, Carl A; Knowlton, Amy R

2015-01-01

Social networks provide a powerful approach for health behavior change. This article documents how social network interventions have been successfully used for a range of health behaviors, including HIV risk practices, smoking, exercise, dieting, family planning, bullying, and mental health. We review the literature that suggests the relationship between health behaviors and social network attributes demonstrates a high degree of specificity. The article then examines hypothesized social influence mechanisms including social norms, modeling, and social rewards and the factors of social identity and social rewards that can be employed to sustain social network interventions. Areas of future research avenues are highlighted, including the need to examine and to adjust analytically for contamination and social diffusion, social influence versus differential affiliation, and network change. Use and integration of mhealth and face-to-face networks for promoting health behavior change are also critical research areas.

Estimation of the number of extreme pathways for metabolic networks

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Thiele Ines

2007-09-01

Full Text Available Abstract Background The set of extreme pathways (ExPa, {pi}, defines the convex basis vectors used for the mathematical characterization of the null space of the stoichiometric matrix for biochemical reaction networks. ExPa analysis has been used for a number of studies to determine properties of metabolic networks as well as to obtain insight into their physiological and functional states in silico. However, the number of ExPas, p = |{pi}|, grows with the size and complexity of the network being studied, and this poses a computational challenge. For this study, we investigated the relationship between the number of extreme pathways and simple network properties. Results We established an estimating function for the number of ExPas using these easily obtainable network measurements. In particular, it was found that log [p] had an exponential relationship with log⁡[∑i=1Rd−id+ici] MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacyGGSbaBcqGGVbWBcqGGNbWzdaWadaqaamaaqadabaGaemizaq2aaSbaaSqaaiabgkHiTmaaBaaameaacqWGPbqAaeqaaaWcbeaakiabdsgaKnaaBaaaleaacqGHRaWkdaWgaaadbaGaemyAaKgabeaaaSqabaGccqWGJbWydaWgaaWcbaGaemyAaKgabeaaaeaacqWGPbqAcqGH9aqpcqaIXaqmaeaacqWGsbGua0GaeyyeIuoaaOGaay5waiaaw2faaaaa@4414@, where R = |Reff| is the number of active reactions in a network, d−i MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaacqWGKbazdaWgaaWcbaGaeyOeI0YaaSbaaWqaaiabdMgaPbqabaaaleqaaaaa@30A9@ and d+i MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb

Shared molecular pathways and gene networks for cardiovascular disease and type 2 diabetes mellitus in women across diverse ethnicities.

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Chan, Kei Hang K; Huang, Yen-Tsung; Meng, Qingying; Wu, Chunyuan; Reiner, Alexander; Sobel, Eric M; Tinker, Lesley; Lusis, Aldons J; Yang, Xia; Liu, Simin

2014-12-01

Although cardiovascular disease (CVD) and type 2 diabetes mellitus (T2D) share many common risk factors, potential molecular mechanisms that may also be shared for these 2 disorders remain unknown. Using an integrative pathway and network analysis, we performed genome-wide association studies in 8155 blacks, 3494 Hispanic American, and 3697 Caucasian American women who participated in the national Women's Health Initiative single-nucleotide polymorphism (SNP) Health Association Resource and the Genomics and Randomized Trials Network. Eight top pathways and gene networks related to cardiomyopathy, calcium signaling, axon guidance, cell adhesion, and extracellular matrix seemed to be commonly shared between CVD and T2D across all 3 ethnic groups. We also identified ethnicity-specific pathways, such as cell cycle (specific for Hispanic American and Caucasian American) and tight junction (CVD and combined CVD and T2D in Hispanic American). In network analysis of gene-gene or protein-protein interactions, we identified key drivers that included COL1A1, COL3A1, and ELN in the shared pathways for both CVD and T2D. These key driver genes were cross-validated in multiple mouse models of diabetes mellitus and atherosclerosis. Our integrative analysis of American women of 3 ethnicities identified multiple shared biological pathways and key regulatory genes for the development of CVD and T2D. These prospective findings also support the notion that ethnicity-specific susceptibility genes and process are involved in the pathogenesis of CVD and T2D. © 2014 American Heart Association, Inc.

Identifying groups of critical edges in a realistic electrical network by multi-objective genetic algorithms

International Nuclear Information System (INIS)

Zio, E.; Golea, L.R.; Rocco S, C.M.

2012-01-01

In this paper, an analysis of the vulnerability of the Italian high-voltage (380 kV) electrical transmission network (HVIET) is carried out for the identification of the groups of links (or edges, or arcs) most critical considering the network structure and flow. Betweenness centrality and network connection efficiency variations are considered as measures of the importance of the network links. The search of the most critical ones is carried out within a multi-objective optimization problem aimed at the maximization of the importance of the groups and minimization of their dimension. The problem is solved using a genetic algorithm. The analysis is based only on information on the topology of the network and leads to the identification of the most important single component, couples of components, triplets and so forth. The comparison of the results obtained with those reported by previous analyses indicates that the proposed approach provides useful complementary information.

The Integration of Epistasis Network and Functional Interactions in a GWAS Implicates RXR Pathway Genes in the Immune Response to Smallpox Vaccine.

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Brett A McKinney

Full Text Available Although many diseases and traits show large heritability, few genetic variants have been found to strongly separate phenotype groups by genotype. Complex regulatory networks of variants and expression of multiple genes lead to small individual-variant effects and difficulty replicating the effect of any single variant in an affected pathway. Interaction network modeling of GWAS identifies effects ignored by univariate models, but population differences may still cause specific genes to not replicate. Integrative network models may help detect indirect effects of variants in the underlying biological pathway. In this study, we used gene-level functional interaction information from the Integrative Multi-species Prediction (IMP tool to reveal important genes associated with a complex phenotype through evidence from epistasis networks and pathway enrichment. We test this method for augmenting variant-based network analyses with functional interactions by applying it to a smallpox vaccine immune response GWAS. The integrative analysis spotlights the role of genes related to retinoid X receptor alpha (RXRA, which has been implicated in a previous epistasis network analysis of smallpox vaccine.

Network pharmacology-based identification of key pharmacological pathways of Yin-Huang-Qing-Fei capsule acting on chronic bronchitis.

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Yu, Guohua; Zhang, Yanqiong; Ren, Weiqiong; Dong, Ling; Li, Junfang; Geng, Ya; Zhang, Yi; Li, Defeng; Xu, Haiyu; Yang, Hongjun

2017-01-01

For decades in China, the Yin-Huang-Qing-Fei capsule (YHQFC) has been widely used in the treatment of chronic bronchitis, with good curative effects. Owing to the complexity of traditional Chinese herbal formulas, the pharmacological mechanism of YHQFC remains unclear. To address this problem, a network pharmacology-based strategy was proposed in this study. At first, the putative target profile of YHQFC was predicted using MedChem Studio, based on structural and functional similarities of all available YHQFC components to the known drugs obtained from the DrugBank database. Then, an interaction network was constructed using links between putative YHQFC targets and known therapeutic targets of chronic bronchitis. Following the calculation of four topological features (degree, betweenness, closeness, and coreness) of each node in the network, 475 major putative targets of YHQFC and their topological importance were identified. In addition, a pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes pathway database indicated that the major putative targets of YHQFC are significantly associated with various pathways involved in anti-inflammation processes, immune responses, and pathological changes caused by asthma. More interestingly, eight major putative targets of YHQFC (interleukin [IL]-3, IL-4, IL-5, IL-10, IL-13, FCER1G, CCL11, and EPX) were demonstrated to be associated with the inflammatory process that occurs during the progression of asthma. Finally, a molecular docking simulation was performed and the results exhibited that 17 pairs of chemical components and candidate YHQFC targets involved in asthma pathway had strong binding efficiencies. In conclusion, this network pharmacology-based investigation revealed that YHQFC may attenuate the inflammatory reaction of chronic bronchitis by regulating its candidate targets, which may be implicated in the major pathological processes of the asthma pathway.

Historical emissions critical for mapping decarbonization pathways

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Majkut, J.; Kopp, R. E.; Sarmiento, J. L.; Oppenheimer, M.

2016-12-01

Policymakers have set a goal of limiting temperature increase from human influence on the climate. This motivates the identification of decarbonization pathways to stabilize atmospheric concentrations of CO2. In this context, the future behavior of CO2 sources and sinks define the CO2 emissions necessary to meet warming thresholds with specified probabilities. We adopt a simple model of the atmosphere-land-ocean carbon balance to reflect uncertainty in how natural CO2 sinks will respond to increasing atmospheric CO2 and temperature. Bayesian inversion is used to estimate the probability distributions of selected parameters of the carbon model. Prior probability distributions are chosen to reflect the behavior of CMIP5 models. We then update these prior distributions by running historical simulations of the global carbon cycle and inverting with observationally-based inventories and fluxes of anthropogenic carbon in the ocean and atmosphere. The result is a best-estimate of historical CO2 sources and sinks and a model of how CO2 sources and sinks will vary in the future under various emissions scenarios, with uncertainty. By linking the carbon model to a simple climate model, we calculate emissions pathways and carbon budgets consistent with meeting specific temperature thresholds and identify key factors that contribute to remaining uncertainty. In particular, we show how the assumed history of CO2 emissions from land use change (LUC) critically impacts estimates of the strength of the land CO2 sink via CO2 fertilization. Different estimates of historical LUC emissions taken from the literature lead to significantly different parameterizations of the carbon system. High historical CO2 emissions from LUC lead to a more robust CO2 fertilization effect, significantly lower future atmospheric CO2 concentrations, and an increased amount of CO2 that can be emitted to satisfy temperature stabilization targets. Thus, in our model, historical LUC emissions have a

Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes.

Directory of Open Access Journals (Sweden)

Jose A Santiago

Full Text Available Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level.Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP, previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS and the Prognostic Biomarker Study (PROBE, revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients.These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first

Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes.

Science.gov (United States)

Santiago, Jose A; Potashkin, Judith A

2013-01-01

Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP), previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Prognostic Biomarker Study (PROBE), revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients. These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first time that

Proteomics and pathway analysis identifies JNK signaling as critical for high linear energy transfer radiation-induced apoptosis in non-small lung cancer cells.

Science.gov (United States)

Ståhl, Sara; Fung, Eva; Adams, Christopher; Lengqvist, Johan; Mörk, Birgitta; Stenerlöw, Bo; Lewensohn, Rolf; Lehtiö, Janne; Zubarev, Roman; Viktorsson, Kristina

2009-05-01

During the past decade, we have witnessed an explosive increase in generation of large proteomics data sets, not least in cancer research. There is a growing need to extract and correctly interpret information from such data sets to generate biologically relevant hypotheses. A pathway search engine (PSE) has recently been developed as a novel tool intended to meet these requirements. Ionizing radiation (IR) is an anticancer treatment modality that triggers multiple signal transduction networks. In this work, we show that high linear energy transfer (LET) IR induces apoptosis in a non-small cell lung cancer cell line, U-1810, whereas low LET IR does not. PSE was applied to study changes in pathway status between high and low LET IR to find pathway candidates of importance for high LET-induced apoptosis. Such pathways are potential clinical targets, and they were further validated in vitro. We used an unsupervised shotgun proteomics approach where high resolution mass spectrometry coupled to nanoflow liquid chromatography determined the identity and relative abundance of expressed proteins. Based on the proteomics data, PSE suggested the JNK pathway (p = 6.10(-6)) as a key event in response to high LET IR. In addition, the Fas pathway was found to be activated (p = 3.10(-5)) and the p38 pathway was found to be deactivated (p = 0.001) compared with untreated cells. Antibody-based analyses confirmed that high LET IR caused an increase in phosphorylation of JNK. Moreover pharmacological inhibition of JNK blocked high LET-induced apoptotic signaling. In contrast, neither an activation of p38 nor a role for p38 in high LET IR-induced apoptotic signaling was found. We conclude that, in contrast to conventional low LET IR, high LET IR can trigger activation of the JNK pathway, which in turn is critical for induction of apoptosis in these cells. Thus PSE predictions were largely confirmed, and PSE was proven to be a useful hypothesis-generating tool.

KeyPathwayMinerWeb

DEFF Research Database (Denmark)

List, Markus; Alcaraz, Nicolas; Dissing-Hansen, Martin

2016-01-01

, for instance), KeyPathwayMiner extracts connected sub-networks containing a high number of active or differentially regulated genes (proteins, metabolites) in the molecular profiles. The web interface at (http://keypathwayminer.compbio.sdu.dk) implements all core functionalities of the KeyPathwayMiner tool set......We present KeyPathwayMinerWeb, the first online platform for de novo pathway enrichment analysis directly in the browser. Given a biological interaction network (e.g. protein-protein interactions) and a series of molecular profiles derived from one or multiple OMICS studies (gene expression...... such as data integration, input of background knowledge, batch runs for parameter optimization and visualization of extracted pathways. In addition to an intuitive web interface, we also implemented a RESTful API that now enables other online developers to integrate network enrichment as a web service...

Robust de novo pathway enrichment with KeyPathwayMiner 5 [version 1; referees: 2 approved

Directory of Open Access Journals (Sweden)

Nicolas Alcaraz

2016-06-01

Full Text Available Identifying functional modules or novel active pathways, recently termed de novo pathway enrichment, is a computational systems biology challenge that has gained much attention during the last decade. Given a large biological interaction network, KeyPathwayMiner extracts connected subnetworks that are enriched for differentially active entities from a series of molecular profiles encoded as binary indicator matrices. Since interaction networks constantly evolve, an important question is how robust the extracted results are when the network is modified. We enable users to study this effect through several network perturbation techniques and over a range of perturbation degrees. In addition, users may now provide a gold-standard set to determine how enriched extracted pathways are with relevant genes compared to randomized versions of the original network.

Signal Transduction Pathways of TNAP: Molecular Network Analyses.

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Négyessy, László; Györffy, Balázs; Hanics, János; Bányai, Mihály; Fonta, Caroline; Bazsó, Fülöp

2015-01-01

Despite the growing body of evidence pointing on the involvement of tissue non-specific alkaline phosphatase (TNAP) in brain function and diseases like epilepsy and Alzheimer's disease, our understanding about the role of TNAP in the regulation of neurotransmission is severely limited. The aim of our study was to integrate the fragmented knowledge into a comprehensive view regarding neuronal functions of TNAP using objective tools. As a model we used the signal transduction molecular network of a pyramidal neuron after complementing with TNAP related data and performed the analysis using graph theoretic tools. The analyses show that TNAP is in the crossroad of numerous pathways and therefore is one of the key players of the neuronal signal transduction network. Through many of its connections, most notably with molecules of the purinergic system, TNAP serves as a controller by funnelling signal flow towards a subset of molecules. TNAP also appears as the source of signal to be spread via interactions with molecules involved among others in neurodegeneration. Cluster analyses identified TNAP as part of the second messenger signalling cascade. However, TNAP also forms connections with other functional groups involved in neuronal signal transduction. The results indicate the distinct ways of involvement of TNAP in multiple neuronal functions and diseases.

Critical node lifetimes in random networks via the Chen-Stein method

NARCIS (Netherlands)

Franceschetti, M.; Meester, R.W.J.

2006-01-01

This correspondence considers networks where nodes are connected randomly and can fail at random times. It provides scaling laws that allow to find the critical time at which isolated nodes begin to appear in the system as its size tends to infinity. Applications are in the areas of sensor and

Critical phenomena in communication/computation networks with various topologies and suboptimal to optimal resource allocation

Science.gov (United States)

Cogoni, Marco; Busonera, Giovanni; Anedda, Paolo; Zanetti, Gianluigi

2015-01-01

We generalize previous studies on critical phenomena in communication networks [1,2] by adding computational capabilities to the nodes. In our model, a set of tasks with random origin, destination and computational structure is distributed on a computational network, modeled as a graph. By varying the temperature of a Metropolis Montecarlo, we explore the global latency for an optimal to suboptimal resource assignment at a given time instant. By computing the two-point correlation function for the local overload, we study the behavior of the correlation distance (both for links and nodes) while approaching the congested phase: a transition from peaked to spread g(r) is seen above a critical (Montecarlo) temperature Tc. The average latency trend of the system is predicted by averaging over several network traffic realizations while maintaining a spatially detailed information for each node: a sharp decrease of performance is found over Tc independently of the workload. The globally optimized computational resource allocation and network routing defines a baseline for a future comparison of the transition behavior with respect to existing routing strategies [3,4] for different network topologies.

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways

OpenAIRE

Musungu, Bryan M.; Bhatnagar, Deepak; Brown, Robert L.; Payne, Gary A.; OBrian, Greg; Fakhoury, Ahmad M.; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flav...

[Development of a clinical pathway for the attention of patients with amyotrophic lateral sclerosis in a regional network. ALS Assistance Network-Comunidad de Madrid].

Science.gov (United States)

Rodríguez de Rivera, F J; Grande, M; García-Caballero, J; Muñoz-Blanco, J; Mora, J; Esteban, J; Guerrero, A; Matias-Guiu, J; de Andrés-Colsa, R; Buey, C; Díez-Tejedor, E

2007-01-01

Amyotrophic lateral sclerosis (ALS) requires complex multidisciplinary attention. Clinical pathways are assistance plans for certain diseases with a predictable course. These plans are established in isolated centers, not in multicenter regions. The aim is to develop a clinical pathway capable of organizing and homogenizing assistance given in ALS Assistance Network-Comunidad de Madrid which is made up of five hospitals, from the beginning until the end of the disease. In successive meetings, neurologists of these hospitals and members of the Madrid Health Service evaluated published therapeutic guidelines and other documents used in ALS assistance. A clinical pathway was developed adapting this information to social-health care conditions in the Comunidad de Madrid following the FOCUS-PDCA model. A clinical pathway was created consisting of a scientist-technical framework which arranges the attention in relationship to the diagnosis and treatment, according to the degree of disease progression and a chronogram. This is accompanied by several patient information documents on the disease and the tests that are required, and a patient assistance evaluation form. The standards are established to reach and to promote 354 constant improvement in patient care. Clinical pathway for the ALS assistance in a regional network organizes the attention and cares that the patients must receive from the beginning to the end of the disease. This arrangement and homogenization of the attention improves the quality of patient care, diminishes variability and rationalizes the use of the health care resources.

Heading in the right direction: thermodynamics-based network analysis and pathway engineering.

Science.gov (United States)

Ataman, Meric; Hatzimanikatis, Vassily

2015-12-01

Thermodynamics-based network analysis through the introduction of thermodynamic constraints in metabolic models allows a deeper analysis of metabolism and guides pathway engineering. The number and the areas of applications of thermodynamics-based network analysis methods have been increasing in the last ten years. We review recent applications of these methods and we identify the areas that such analysis can contribute significantly, and the needs for future developments. We find that organisms with multiple compartments and extremophiles present challenges for modeling and thermodynamics-based flux analysis. The evolution of current and new methods must also address the issues of the multiple alternatives in flux directionalities and the uncertainties and partial information from analytical methods. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Proteomics and Pathway Analysis Identifies JNK Signaling as Critical for High Linear Energy Transfer Radiation-induced Apoptosis in Non-small Lung Cancer Cells*S⃞

Science.gov (United States)

Ståhl, Sara; Fung, Eva; Adams, Christopher; Lengqvist, Johan; Mörk, Birgitta; Stenerlöw, Bo; Lewensohn, Rolf; Lehtiö, Janne; Zubarev, Roman; Viktorsson, Kristina

2009-01-01

During the past decade, we have witnessed an explosive increase in generation of large proteomics data sets, not least in cancer research. There is a growing need to extract and correctly interpret information from such data sets to generate biologically relevant hypotheses. A pathway search engine (PSE) has recently been developed as a novel tool intended to meet these requirements. Ionizing radiation (IR) is an anticancer treatment modality that triggers multiple signal transduction networks. In this work, we show that high linear energy transfer (LET) IR induces apoptosis in a non-small cell lung cancer cell line, U-1810, whereas low LET IR does not. PSE was applied to study changes in pathway status between high and low LET IR to find pathway candidates of importance for high LET-induced apoptosis. Such pathways are potential clinical targets, and they were further validated in vitro. We used an unsupervised shotgun proteomics approach where high resolution mass spectrometry coupled to nanoflow liquid chromatography determined the identity and relative abundance of expressed proteins. Based on the proteomics data, PSE suggested the JNK pathway (p = 6·10−6) as a key event in response to high LET IR. In addition, the Fas pathway was found to be activated (p = 3·10−5) and the p38 pathway was found to be deactivated (p = 0.001) compared with untreated cells. Antibody-based analyses confirmed that high LET IR caused an increase in phosphorylation of JNK. Moreover pharmacological inhibition of JNK blocked high LET-induced apoptotic signaling. In contrast, neither an activation of p38 nor a role for p38 in high LET IR-induced apoptotic signaling was found. We conclude that, in contrast to conventional low LET IR, high LET IR can trigger activation of the JNK pathway, which in turn is critical for induction of apoptosis in these cells. Thus PSE predictions were largely confirmed, and PSE was proven to be a useful hypothesis-generating tool. PMID:19168796

Modeling most likely pathways for smuggling radioactive and special nuclear materials on a worldwide multimodal transportation network

Energy Technology Data Exchange (ETDEWEB)

Saeger, Kevin J [Los Alamos National Laboratory; Cuellar, Leticia [Los Alamos National Laboratory

2010-01-01

Nuclear weapons proliferation is an existing and growing worldwide problem. To help with devising strategies and supporting decisions to interdict the transport of nuclear material, we developed the Pathway Analysis, Threat Response and Interdiction Options Tool (PATRIOT) that provides an analytical approach for evaluating the probability that an adversary smuggling radioactive or special nuclear material will be detected during transit. We incorporate a global, multi-modal transportation network, explicit representation of designed and serendipitous detection opportunities, and multiple threat devices, material types, and shielding levels. This paper presents the general structure of PATRIOT, and focuses on the theoretical framework used to model the reliabilities of all network components that are used to predict the most likely pathways to the target.

Effects of Vertex Activity and Self-organized Criticality Behavior on a Weighted Evolving Network

International Nuclear Information System (INIS)

Zhang Guiqing; Yang Qiuying; Chen Tianlun

2008-01-01

Effects of vertex activity have been analyzed on a weighted evolving network. The network is characterized by the probability distribution of vertex strength, each edge weight and evolution of the strength of vertices with different vertex activities. The model exhibits self-organized criticality behavior. The probability distribution of avalanche size for different network sizes is also shown. In addition, there is a power law relation between the size and the duration of an avalanche and the average of avalanche size has been studied for different vertex activities

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways

Science.gov (United States)

Musungu, Bryan M.; Bhatnagar, Deepak; Brown, Robert L.; Payne, Gary A.; OBrian, Greg; Fakhoury, Ahmad M.; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus, a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays, and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays, there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus. Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus. PMID:27917194

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways.

Science.gov (United States)

Musungu, Bryan M; Bhatnagar, Deepak; Brown, Robert L; Payne, Gary A; OBrian, Greg; Fakhoury, Ahmad M; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus , a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays , and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays , there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus . Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus .

Unstable dynamics, nonequilibrium phases, and criticality in networked excitable media

International Nuclear Information System (INIS)

Franciscis, S. de; Torres, J. J.; Marro, J.

2010-01-01

Excitable systems are of great theoretical and practical interest in mathematics, physics, chemistry, and biology. Here, we numerically study models of excitable media, namely, networks whose nodes may occasionally be dormant and the connection weights are allowed to vary with the system activity on a short-time scale, which is a convenient and realistic representation. The resulting global activity is quite sensitive to stimuli and eventually becomes unstable also in the absence of any stimuli. Outstanding consequences of such unstable dynamics are the spontaneous occurrence of various nonequilibrium phases--including associative-memory phases and one in which the global activity wanders irregularly, e.g., chaotically among all or part of the dynamic attractors--and 1/f noise as the system is driven into the phase region corresponding to the most irregular behavior. A net result is resilience which results in an efficient search in the model attractor space that can explain the origin of some observed behavior in neural, genetic, and ill-condensed matter systems. By extensive computer simulation we also address a previously conjectured relation between observed power-law distributions and the possible occurrence of a ''critical state'' during functionality of, e.g., cortical networks, and describe the precise nature of such criticality in the model which may serve to guide future experiments.

Cancer-related marketing centrality motifs acting as pivot units in the human signaling network and mediating cross-talk between biological pathways.

Science.gov (United States)

Li, Wan; Chen, Lina; Li, Xia; Jia, Xu; Feng, Chenchen; Zhang, Liangcai; He, Weiming; Lv, Junjie; He, Yuehan; Li, Weiguo; Qu, Xiaoli; Zhou, Yanyan; Shi, Yuchen

2013-12-01

Network motifs in central positions are considered to not only have more in-coming and out-going connections but are also localized in an area where more paths reach the networks. These central motifs have been extensively investigated to determine their consistent functions or associations with specific function categories. However, their functional potentials in the maintenance of cross-talk between different functional communities are unclear. In this paper, we constructed an integrated human signaling network from the Pathway Interaction Database. We identified 39 essential cancer-related motifs in central roles, which we called cancer-related marketing centrality motifs, using combined centrality indices on the system level. Our results demonstrated that these cancer-related marketing centrality motifs were pivotal units in the signaling network, and could mediate cross-talk between 61 biological pathways (25 could be mediated by one motif on average), most of which were cancer-related pathways. Further analysis showed that molecules of most marketing centrality motifs were in the same or adjacent subcellular localizations, such as the motif containing PI3K, PDK1 and AKT1 in the plasma membrane, to mediate signal transduction between 32 cancer-related pathways. Finally, we analyzed the pivotal roles of cancer genes in these marketing centrality motifs in the pathogenesis of cancers, and found that non-cancer genes were potential cancer-related genes.

Network pharmacology-based identification of key pharmacological pathways of Yin–Huang–Qing–Fei capsule acting on chronic bronchitis

Directory of Open Access Journals (Sweden)

Yu GH

2016-12-01

Full Text Available Guohua Yu,1,2,* Yanqiong Zhang,2,* Weiqiong Ren,3 Ling Dong,1 Junfang Li,2,4 Ya Geng,2,5 Yi Zhang,2 Defeng Li,2 Haiyu Xu,2 Hongjun Yang2 1School of Chinese Materia Medica, Beijing University of Chinese Medicine, 2Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 3The First Affiliated Hospital of Hunan University of Traditional Chinese Medicine, Changsha, 4School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin, 5School of Basic Medicine, Shandong University of Chinese Medicine, Jinan, China *These authors contributed equally to this work Abstract: For decades in China, the Yin–Huang–Qing–Fei capsule (YHQFC has been widely used in the treatment of chronic bronchitis, with good curative effects. Owing to the complexity of traditional Chinese herbal formulas, the pharmacological mechanism of YHQFC remains unclear. To address this problem, a network pharmacology-based strategy was proposed in this study. At first, the putative target profile of YHQFC was predicted using MedChem Studio, based on structural and functional similarities of all available YHQFC components to the known drugs obtained from the DrugBank database. Then, an interaction network was constructed using links between putative YHQFC targets and known therapeutic targets of chronic bronchitis. Following the calculation of four topological features (degree, betweenness, closeness, and coreness of each node in the network, 475 major putative targets of YHQFC and their topological importance were identified. In addition, a pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes pathway database indicated that the major putative targets of YHQFC are significantly associated with various pathways involved in anti-inflammation processes, immune responses, and pathological changes caused by asthma. More interestingly, eight major putative targets of YHQFC (interleukin [IL]-3, IL-4, IL

A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer

NARCIS (Netherlands)

C. Staiger (Christine); S. Cadot; R Kooter; M. Dittrich (Marcus); T. Müller (Tobias); G.W. Klau (Gunnar); L.F.A. Wessels (Lodewyk)

2012-01-01

htmlabstractRecently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically

A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways

Science.gov (United States)

Han, Junwei; Li, Chunquan; Yang, Haixiu; Xu, Yanjun; Zhang, Chunlong; Ma, Jiquan; Shi, Xinrui; Liu, Wei; Shang, Desi; Yao, Qianlan; Zhang, Yunpeng; Su, Fei; Feng, Li; Li, Xia

2015-01-01

Identifying dysregulated pathways from high-throughput experimental data in order to infer underlying biological insights is an important task. Current pathway-identification methods focus on single pathways in isolation; however, consideration of crosstalk between pathways could improve our understanding of alterations in biological states. We propose a novel method of pathway analysis based on global influence (PAGI) to identify dysregulated pathways, by considering both within-pathway effects and crosstalk between pathways. We constructed a global gene–gene network based on the relationships among genes extracted from a pathway database. We then evaluated the extent of differential expression for each gene, and mapped them to the global network. The random walk with restart algorithm was used to calculate the extent of genes affected by global influence. Finally, we used cumulative distribution functions to determine the significance values of the dysregulated pathways. We applied the PAGI method to five cancer microarray datasets, and compared our results with gene set enrichment analysis and five other methods. Based on these analyses, we demonstrated that PAGI can effectively identify dysregulated pathways associated with cancer, with strong reproducibility and robustness. We implemented PAGI using the freely available R-based and Web-based tools (http://bioinfo.hrbmu.edu.cn/PAGI). PMID:25551156

Modelling the structure of a ceRNA-theoretical, bipartite microRNA-mRNA interaction network regulating intestinal epithelial cellular pathways using R programming.

Science.gov (United States)

Robinson, J M; Henderson, W A

2018-01-12

We report a method using functional-molecular databases and network modelling to identify hypothetical mRNA-miRNA interaction networks regulating intestinal epithelial barrier function. The model forms a data-analysis component of our cell culture experiments, which produce RNA expression data from Nanostring Technologies nCounter ® system. The epithelial tight-junction (TJ) and actin cytoskeleton interact as molecular components of the intestinal epithelial barrier. Upstream regulation of TJ-cytoskeleton interaction is effected by the Rac/Rock/Rho signaling pathway and other associated pathways which may be activated or suppressed by extracellular signaling from growth factors, hormones, and immune receptors. Pathway activations affect epithelial homeostasis, contributing to degradation of the epithelial barrier associated with osmotic dysregulation, inflammation, and tumor development. The complexity underlying miRNA-mRNA interaction networks represents a roadblock for prediction and validation of competing-endogenous RNA network function. We developed a network model to identify hypothetical co-regulatory motifs in a miRNA-mRNA interaction network related to epithelial function. A mRNA-miRNA interaction list was generated using KEGG and miRWalk2.0 databases. R-code was developed to quantify and visualize inherent network structures. We identified a sub-network with a high number of shared, targeting miRNAs, of genes associated with cellular proliferation and cancer, including c-MYC and Cyclin D.

Self-organized critical neural networks

International Nuclear Information System (INIS)

Bornholdt, Stefan; Roehl, Torsten

2003-01-01

A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics, which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters

Pathway Detection from Protein Interaction Networks and Gene Expression Data Using Color-Coding Methods and A* Search Algorithms

Directory of Open Access Journals (Sweden)

Cheng-Yu Yeh

2012-01-01

Full Text Available With the large availability of protein interaction networks and microarray data supported, to identify the linear paths that have biological significance in search of a potential pathway is a challenge issue. We proposed a color-coding method based on the characteristics of biological network topology and applied heuristic search to speed up color-coding method. In the experiments, we tested our methods by applying to two datasets: yeast and human prostate cancer networks and gene expression data set. The comparisons of our method with other existing methods on known yeast MAPK pathways in terms of precision and recall show that we can find maximum number of the proteins and perform comparably well. On the other hand, our method is more efficient than previous ones and detects the paths of length 10 within 40 seconds using CPU Intel 1.73GHz and 1GB main memory running under windows operating system.

Hydrologic Synthesis Across the Critical Zone Observatory Network: A Step Towards Understanding the Coevolution of Critical Zone Function and Structure

Science.gov (United States)

Wlostowski, A. N.; Harman, C. J.; Molotch, N. P.

2017-12-01

The physical and biological architecture of the Earth's Critical Zone controls hydrologic partitioning, storage, and chemical evolution of precipitated water. The Critical Zone Observatory (CZO) Network provides an ideal platform to explore linkages between catchment structure and hydrologic function across a gradient of geologic and climatic settings. A legacy of hypothesis-motivated research at each site has generated a wealth of data characterizing the architecture and hydrologic function of the critical zone. We will present a synthesis of this data that aims to elucidate and explain (in the sense of making mutually intelligible) variations in hydrologic function across the CZO network. Top-down quantitative signatures of the storage and partitioning of water at catchment scales extracted from precipitation, streamflow, and meteorological data will be compared with each other, and provide quantitative benchmarks to assess differences in perceptual models of hydrologic function at each CZO site. Annual water balance analyses show that CZO sites span a wide gradient of aridity and evaporative partitioning. The aridity index (PET/P) ranges from 0.3 at Luquillo to 4.3 at Reynolds Creek, while the evaporative index (E/P) ranges from 0.3 at Luquillo (Rio Mamayes) to 0.9 at Reynolds Creek (Reynolds Creek Outlet). Snow depth and SWE observations reveal that snowpack is an important seasonal storage reservoir at three sites: Boulder, Jemez, Reynolds Creek and Southern Sierra. Simple dynamical models are also used to infer seasonal patterns of subsurface catchment storage. A root-zone water balance model reveals unique seasonal variations in plant-available water storage. Seasonal patterns of plant-available storage are driven by the asynchronicity of seasonal precipitation and evaporation cycles. Catchment sensitivity functions are derived at each site to infer relative changes in hydraulic storage (the apparent storage reservoir responsible for modulating streamflow

Critical Social Network Analysis in Community Colleges: Peer Effects and Credit Attainment

Science.gov (United States)

González Canché, Manuel S.; Rios-Aguilar, Cecilia

2014-01-01

This chapter discusses the importance of conducting critical social network analysis (CSNA) in higher education. To illustrate the benefits of CSNA, the authors use existing institutional data to examine peer effects in community colleges. The chapter ends with a discussion of the implications of using a CSNA approach to measure inequities in…

Network Randomization and Dynamic Defense for Critical Infrastructure Systems

Energy Technology Data Exchange (ETDEWEB)

Chavez, Adrian R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Martin, Mitchell Tyler [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hamlet, Jason [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stout, William M.S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lee, Erik [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-04-01

Critical Infrastructure control systems continue to foster predictable communication paths, static configurations, and unpatched systems that allow easy access to our nation's most critical assets. This makes them attractive targets for cyber intrusion. We seek to address these attack vectors by automatically randomizing network settings, randomizing applications on the end devices themselves, and dynamically defending these systems against active attacks. Applying these protective measures will convert control systems into moving targets that proactively defend themselves against attack. Sandia National Laboratories has led this effort by gathering operational and technical requirements from Tennessee Valley Authority (TVA) and performing research and development to create a proof-of-concept solution. Our proof-of-concept has been tested in a laboratory environment with over 300 nodes. The vision of this project is to enhance control system security by converting existing control systems into moving targets and building these security measures into future systems while meeting the unique constraints that control systems face.

Critical neural networks with short- and long-term plasticity

Science.gov (United States)

Michiels van Kessenich, L.; Luković, M.; de Arcangelis, L.; Herrmann, H. J.

2018-03-01

In recent years self organized critical neuronal models have provided insights regarding the origin of the experimentally observed avalanching behavior of neuronal systems. It has been shown that dynamical synapses, as a form of short-term plasticity, can cause critical neuronal dynamics. Whereas long-term plasticity, such as Hebbian or activity dependent plasticity, have a crucial role in shaping the network structure and endowing neural systems with learning abilities. In this work we provide a model which combines both plasticity mechanisms, acting on two different time scales. The measured avalanche statistics are compatible with experimental results for both the avalanche size and duration distribution with biologically observed percentages of inhibitory neurons. The time series of neuronal activity exhibits temporal bursts leading to 1 /f decay in the power spectrum. The presence of long-term plasticity gives the system the ability to learn binary rules such as xor, providing the foundation of future research on more complicated tasks such as pattern recognition.

Modeling most likely pathways for smuggling radioactive and special nuclear materials on a worldwide multi-modal transportation network

Energy Technology Data Exchange (ETDEWEB)

Saeger, Kevin J [Los Alamos National Laboratory; Cuellar, Leticia [Los Alamos National Laboratory

2010-10-28

Nuclear weapons proliferation is an existing and growing worldwide problem. To help with devising strategies and supporting decisions to interdict the transport of nuclear material, we developed the Pathway Analysis, Threat Response and Interdiction Options Tool (PATRIOT) that provides an analytical approach for evaluating the probability that an adversary smuggling radioactive or special nuclear material will be detected during transit. We incorporate a global, multi-modal transportation network, explicit representation of designed and serendipitous detection opportunities, and multiple threat devices, material types, and shielding levels. This paper presents the general structure of PATRIOT, all focuses on the theoretical framework used to model the reliabilities of all network components that are used to predict the most likely pathways to the target.

A novel critical infrastructure resilience assessment approach using dynamic Bayesian networks

Science.gov (United States)

Cai, Baoping; Xie, Min; Liu, Yonghong; Liu, Yiliu; Ji, Renjie; Feng, Qiang

2017-10-01

The word resilience originally originates from the Latin word "resiliere", which means to "bounce back". The concept has been used in various fields, such as ecology, economics, psychology, and society, with different definitions. In the field of critical infrastructure, although some resilience metrics are proposed, they are totally different from each other, which are determined by the performances of the objects of evaluation. Here we bridge the gap by developing a universal critical infrastructure resilience metric from the perspective of reliability engineering. A dynamic Bayesian networks-based assessment approach is proposed to calculate the resilience value. A series, parallel and voting system is used to demonstrate the application of the developed resilience metric and assessment approach.

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.

Transcriptional plant responses critical for resistance towards necrotrophic pathogens

Directory of Open Access Journals (Sweden)

Rainer P. Birkenbihl

2011-11-01

Full Text Available Plant defenses aimed at necrotrophic pathogens appear to be genetically complex. Despite the apparent lack of a specific recognition of such necrotrophs by products of major R genes, biochemical, molecular, and genetic studies, in particular using the model plant Arabidopsis, have uncovered numerous host components critical for the outcome of such interactions. Although the JA signaling pathway plays a central role in plant defense towards necrotrophs additional signaling pathways contribute to the plant response network. Transcriptional reprogramming is a vital part of the host defense machinery and several key regulators have recently been identified. Some of these transcription factors positively affect plant resistance whereas others play a role in enhancing host susceptibility towards these phytopathogens.

Functional water flow pathways and hydraulic regulation in the xylem network of Arabidopsis.

Science.gov (United States)

Park, Joonghyuk; Kim, Hae Koo; Ryu, Jeongeun; Ahn, Sungsook; Lee, Sang Joon; Hwang, Ildoo

2015-03-01

In vascular plants, the xylem network constitutes a complex microfluidic system. The relationship between vascular network architecture and functional hydraulic regulation during actual water flow remains unexplored. Here, we developed a method to visualize individual xylem vessels of the 3D xylem network of Arabidopsis thaliana, and to analyze the functional activities of these vessels using synchrotron X-ray computed tomography with hydrophilic gold nanoparticles as flow tracers. We show how the organization of the xylem network changes dynamically throughout the plant, and reveal how the elementary units of this transport system are organized to ensure both long-distance axial water transport and local lateral water transport. Xylem vessels form distinct clusters that operate as functional units, and the activity of these units, which determines water flow pathways, is modulated not only by varying the number and size of xylem vessels, but also by altering their interconnectivity and spatial arrangement. Based on these findings, we propose a regulatory model of water transport that ensures hydraulic efficiency and safety. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Cytogenomic Integrative Network Analysis of the Critical Region Associated with Wolf-Hirschhorn Syndrome

Directory of Open Access Journals (Sweden)

Thiago Corrêa

2018-01-01

Full Text Available Deletions in the 4p16.3 region are associated with Wolf-Hirschhorn syndrome (WHS, a contiguous gene deletion syndrome involving variable size deletions. In this study, we perform a cytogenomic integrative analysis combining classical cytogenetic methods, fluorescence in situ hybridization (FISH, chromosomal microarray analysis (CMA, and systems biology strategies, to establish the cytogenomic profile involving the 4p16.3 critical region and suggest WHS-related intracellular cell signaling cascades. The cytogenetic and clinical patient profiles were evaluated. We characterized 12 terminal deletions, one interstitial deletion, two ring chromosomes, and one classical translocation 4;8. CMA allowed delineation of the deletions, which ranged from 3.7 to 25.6 Mb with breakpoints from 4p16.3 to 4p15.33. Furthermore, the smallest region of overlapping (SRO encompassed seven genes in a terminal region of 330 kb in the 4p16.3 region, suggesting a region of susceptibility to convulsions and microcephaly. Therefore, molecular interaction networks and topological analysis were performed to understand these WHS-related symptoms. Our results suggest that specific cell signaling pathways including dopamine receptor, NAD+ nucleosidase activity, and fibroblast growth factor-activated receptor activity are associated with the diverse pathological WHS phenotypes and their symptoms. Additionally, we identified 29 hub-bottlenecks (H-B nodes with a major role in WHS.

Integration of Pathway Knowledge and Dynamic Bayesian Networks for the Prediction of Oral Cancer Recurrence.

Science.gov (United States)

Kourou, Konstantina; Papaloukas, Costas; Fotiadis, Dimitrios I

2017-03-01

Oral squamous cell carcinoma has been characterized as a complex disease which involves dynamic genomic changes at the molecular level. These changes indicate the worth to explore the interactions of the molecules and especially of differentially expressed genes that contribute to cancer progression. Moreover, based on this knowledge the identification of differentially expressed genes and related molecular pathways is of great importance. In the present study, we exploit differentially expressed genes in order to further perform pathway enrichment analysis. According to our results we found significant pathways in which the disease associated genes have been identified as strongly enriched. Furthermore, based on the results of the pathway enrichment analysis we propose a methodology for predicting oral cancer recurrence using dynamic Bayesian networks. The methodology takes into consideration time series gene expression data in order to predict a disease recurrence. Subsequently, we are able to conjecture about the causal interactions between genes in consecutive time intervals. Concerning the performance of the predictive models, the overall accuracy of the algorithm is 81.8% and the area under the ROC curve 89.2% regarding the knowledge from the overrepresented pre-NOTCH Expression and processing pathway.

Critical regimes driven by recurrent mobility patterns of reaction-diffusion processes in networks

Science.gov (United States)

Gómez-Gardeñes, J.; Soriano-Paños, D.; Arenas, A.

2018-04-01

Reaction-diffusion processes1 have been widely used to study dynamical processes in epidemics2-4 and ecology5 in networked metapopulations. In the context of epidemics6, reaction processes are understood as contagions within each subpopulation (patch), while diffusion represents the mobility of individuals between patches. Recently, the characteristics of human mobility7, such as its recurrent nature, have been proven crucial to understand the phase transition to endemic epidemic states8,9. Here, by developing a framework able to cope with the elementary epidemic processes, the spatial distribution of populations and the commuting mobility patterns, we discover three different critical regimes of the epidemic incidence as a function of these parameters. Interestingly, we reveal a regime of the reaction-diffussion process in which, counter-intuitively, mobility is detrimental to the spread of disease. We analytically determine the precise conditions for the emergence of any of the three possible critical regimes in real and synthetic networks.

Proceedings of the International Symposium on Topological Aspects of Critical Systems and Networks

Science.gov (United States)

Yakubo, Kousuke; Amitsuka, Hiroshi; Ishikawa, Goo; Machino, Kazuo; Nakagaki, Toshiyuki; Tanda, Satoshi; Yamada, Hideto; Kichiji, Nozomi

2007-07-01

I. General properties of networks. Physics of network security / Y.-C. Lai, X. Wand and C. H. Lai. Multi-state interacting particle systems on scale-free networks / N. Masuda and N. Konno. Homotopy Reduction of Complex Networks 18 / Y. Hiraoka and T. Ichinomiya. Analysis of the Susceptible-Infected-Susceptible Model on Complex Network / T. Ichinomiya -- II. Complexity in social science. Innovation and Development in a Random Lattice / J. Lahtinen. Long-tailed distributions in biological systems: revisit to Lognormals / N. Kobayashi ... [et al.]. Two-class structure of income distribution in the USA:exponential bulk and power-law tail / V. M. Yakovenko and A. Christian Silva. Power Law distributions in two community currencies / N. Kichiji and M. Nishibe -- III. Patterns in biological objects. Stoichiometric network analysis of nonlinear phenomena in rection mechanism for TWC converters / M. Marek ... [et al.]. Collective movement and morphogenesis of epithelial cells / H. Haga and K. Kawabata. Indecisive behavior of amoeba crossing an environmental barrier / S. Takagi ... [et al.]. Effects of amount of food on path selection in the transport network of an amoeboid organism / T. Nakagaki ... [et al.]. Light scattering study in double network gels / M. Fukunaya ... [et al.].Blood flow velocity in the choroid in punctate inner choroidopathy and Vogt-Koyanagi-Harada disease; amd multifractal analysis of choroidal blood flow in age-related macular degeneration / K. Yoshida ... [et al.]. Topological analysis of placental arteries: correlation with neonatal growth / H. Yamada and K. Yakubo -- IV. Criticality in pure and applied physics. Droplets in Disordered Metallic Quantum Critical Systems / A. H. Castro Neto and B. A. Jones. Importance of static disorder and inhomogeneous cooperative dynamics in heavy-fermion metals / O. O. Bernal. Competition between spin glass and Antiferromagnetic phases in heavy fermion materials / S. Sullow. Emergent Phases via Fermi surface

Network Analysis Tools: from biological networks to clusters and pathways.

Science.gov (United States)

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma.

Science.gov (United States)

Li, Chaoxing; Liu, Li; Dinu, Valentin

2018-01-01

Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes

In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

DEFF Research Database (Denmark)

Kjeldsen, Kjeld Raunkjær; Nielsen, J.

2009-01-01

A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... was extensively validated against published flux data, and flux distribution values were found to correlate well between simulations and experiments. The split pathway of the lysine synthesis pathway of C. glutamicum was investigated, and it was found that the direct dehydrogenase variant gave a higher lysine...... yield than the alternative succinyl pathway at high lysine production rates. The NADPH demand of the network was not found to be critical for lysine production until lysine yields exceeded 55% (mmol lysine (mmol glucose)(-1)). The model was validated during growth on the organic acids acetate...

Critical groups - basic concepts

International Nuclear Information System (INIS)

Carter, M.W.

1992-01-01

The potential exposure pathways from the land application site to man are presented. It is emphasised that the critical group is not necessary the population group closest to the source. It could be the group impact by the most significant pathways(s). Only by assessing the importance of each of these pathways and then combining them can a proper choice of critical group be made. It would be wrong to select a critical group on the basis that it seems the most probable one, before the pathways have been properly assessed. A calculation in Carter (1983) suggested that for the operating mine site, the annual doses to an Aboriginal person, a service worker and a local housewife, were all about the same and were in the range 0.1 to 0.2 mSv per year. Thus it may be that for the land application area, the critical group turns out to be non-Aboriginal rather than the expected Aboriginal group. 6 refs., 3 figs

METHODS OF MANAGING TRAFFIC DISTRIBUTION IN INFORMATION AND COMMUNICATION NETWORKS OF CRITICAL INFRASTRUCTURE SYSTEMS

OpenAIRE

Kosenko, Viktor; Persiyanova, Elena; Belotskyy, Oleksiy; Malyeyeva, Olga

2017-01-01

The subject matter of the article is information and communication networks (ICN) of critical infrastructure systems (CIS). The goal of the work is to create methods for managing the data flows and resources of the ICN of CIS to improve the efficiency of information processing. The following tasks were solved in the article: the data flow model of multi-level ICN structure was developed, the method of adaptive distribution of data flows was developed, the method of network resource assignment...

Critical Factors to Achieve Dockless Bike-Sharing Sustainability in China: A Stakeholder-Oriented Network Perspective

Directory of Open Access Journals (Sweden)

Jian-gang Shi

2018-06-01

Full Text Available In China, dockless bike-sharing programs (DBSPs play a significant role in promoting the goals of sustainable urban travel and carbon emissions reduction. However, the sustainability of DBSPs is increasingly being challenged as various issues associated with different stakeholders emerge. While numerous studies have focused on the barriers to traditional bike-sharing programs, the sustainability performance of new-generation DBSPs is largely overlooked. It is accordingly imperative to understand the primary challenges that impede the sustainability of DBSPs and to consider what stimulative measures can be taken. In this study, we investigate the factors that are critical to DBSPs’ sustainability from a network perspective. Stakeholder-associated factors and their interrelations were identified via literature analysis and interviews, and the social network analysis (SNA method was employed to recognize the critical factors and links in DBSPs. As a result, 10 critical factors and 10 major interactions were identified and further classified into six challenges. Sharing transport schemes, legislative perfection, public private partnership (PPP, and product lifecycle management (PLM were proposed to govern these challenges. This paper contributes to the existing body of knowledge of bike-sharing programs via a network approach that integrates the key influencing factors with those factors’ associated stakeholders. Furthermore, these findings provide the government and operators with implications for mitigating the tough challenges and facilitating the sustainability of DBSPs.

NEURAL NETWORKS CONTROL OF THE HYBRID POWER UNIT BASED ON THE METHOD OF ADAPTIVE CRITICS

Directory of Open Access Journals (Sweden)

S. Serikov

2012-01-01

Full Text Available The formal statement of the optimization problem of hybrid vehicle power unit control is given. Its solving by neural networks method application on the basis of adaptive critic is considered.

Ventral aspect of the visual form pathway is not critical for the perception of biological motion

Science.gov (United States)

Gilaie-Dotan, Sharon; Saygin, Ayse Pinar; Lorenzi, Lauren J.; Rees, Geraint; Behrmann, Marlene

2015-01-01

Identifying the movements of those around us is fundamental for many daily activities, such as recognizing actions, detecting predators, and interacting with others socially. A key question concerns the neurobiological substrates underlying biological motion perception. Although the ventral “form” visual cortex is standardly activated by biologically moving stimuli, whether these activations are functionally critical for biological motion perception or are epiphenomenal remains unknown. To address this question, we examined whether focal damage to regions of the ventral visual cortex, resulting in significant deficits in form perception, adversely affects biological motion perception. Six patients with damage to the ventral cortex were tested with sensitive point-light display paradigms. All patients were able to recognize unmasked point-light displays and their perceptual thresholds were not significantly different from those of three different control groups, one of which comprised brain-damaged patients with spared ventral cortex (n > 50). Importantly, these six patients performed significantly better than patients with damage to regions critical for biological motion perception. To assess the necessary contribution of different regions in the ventral pathway to biological motion perception, we complement the behavioral findings with a fine-grained comparison between the lesion location and extent, and the cortical regions standardly implicated in biological motion processing. This analysis revealed that the ventral aspects of the form pathway (e.g., fusiform regions, ventral extrastriate body area) are not critical for biological motion perception. We hypothesize that the role of these ventral regions is to provide enhanced multiview/posture representations of the moving person rather than to represent biological motion perception per se. PMID:25583504

Robust de novo pathway enrichment with KeyPathwayMiner 5

DEFF Research Database (Denmark)

Alcaraz, Nicolas; List, Markus; Dissing-Hansen, Martin

2016-01-01

Identifying functional modules or novel active pathways, recently termed de novo pathway enrichment, is a computational systems biology challenge that has gained much attention during the last decade. Given a large biological interaction network, KeyPathwayMiner extracts connected subnetworks tha...

PeerShield: determining control and resilience criticality of collaborative cyber assets in networks

Science.gov (United States)

Cam, Hasan

2012-06-01

As attackers get more coordinated and advanced in cyber attacks, cyber assets are required to have much more resilience, control effectiveness, and collaboration in networks. Such a requirement makes it essential to take a comprehensive and objective approach for measuring the individual and relative performances of cyber security assets in network nodes. To this end, this paper presents four techniques as to how the relative importance of cyber assets can be measured more comprehensively and objectively by considering together the main variables of risk assessment (e.g., threats, vulnerabilities), multiple attributes (e.g., resilience, control, and influence), network connectivity and controllability among collaborative cyber assets in networks. In the first technique, a Bayesian network is used to include the random variables for control, recovery, and resilience attributes of nodes, in addition to the random variables of threats, vulnerabilities, and risk. The second technique shows how graph matching and coloring can be utilized to form collaborative pairs of nodes to shield together against threats and vulnerabilities. The third technique ranks the security assets of nodes by incorporating multiple weights and thresholds of attributes into a decision-making algorithm. In the fourth technique, the hierarchically well-separated tree is enhanced to first identify critical nodes of a network with respect to their attributes and network connectivity, and then selecting some nodes as driver nodes for network controllability.

Applicability of the Critical pathway analysis usually used for nuclear installations, to the control marine environment pollution by heavy metals

International Nuclear Information System (INIS)

Franca, E.P.; Pfeiffer, W.C.; Fiszman, M.; Lacerda, L.D. de

1984-01-01

The methodology of the controlling radionuclide releases from nuclear facilities by the critical pathway criteria, is given. The use of this methodology for the environmental impact studies for an industry that causes pollution is discussed. (M.A.) [pt

How Effective Are Clinical Pathways With and Without Online Peer-Review? An Analysis of Bone Metastases Pathway in a Large, Integrated National Cancer Institute-Designated Comprehensive Cancer Center Network

Energy Technology Data Exchange (ETDEWEB)

Beriwal, Sushil, E-mail: beriwals@upmc.edu [Department of Radiation Oncology, University of Pittsburgh Cancer Institute, Pittsburgh, PA (United States); Rajagopalan, Malolan S.; Flickinger, John C.; Rakfal, Susan M. [Department of Radiation Oncology, University of Pittsburgh Cancer Institute, Pittsburgh, PA (United States); Rodgers, Edwin [Via Oncology, Pittsburgh, PA (United States); Heron, Dwight E. [Department of Radiation Oncology, University of Pittsburgh Cancer Institute, Pittsburgh, PA (United States)

2012-07-15

Purpose: Clinical pathways are an important tool used to manage the quality in health care by standardizing processes. This study evaluated the impact of the implementation of a peer-reviewed clinical pathway in a large, integrated National Cancer Institute-Designated Comprehensive Cancer Center Network. Methods: In 2003, we implemented a clinical pathway for the management of bone metastases with palliative radiation therapy. In 2009, we required the entry of management decisions into an online tool that records pathway choices. The pathway specified 1 or 5 fractions for symptomatic bone metastases with the option of 10-14 fractions for certain clinical situations. The data were obtained from 13 integrated sites (3 central academic, 10 community locations) from 2003 through 2010. Results: In this study, 7905 sites were treated with 64% of courses delivered in community practice and 36% in academic locations. Academic practices were more likely than community practices to treat with 1-5 fractions (63% vs. 23%; p < 0.0001). The number of delivered fractions decreased gradually from 2003 to 2010 for both academic and community practices (p < 0.0001); however, greater numbers of fractions were selected more often in community practices (p < 0.0001). Using multivariate logistic regression, we found that a significantly greater selection of 1-5 fractions developed after implementation online pathway monitoring (2009) with an odds ratio of 1.2 (confidence interval, 1.1-1.4) for community and 1.3 (confidence interval, 1.1-1.6) for academic practices. The mean number of fractions also decreased after online peer review from 6.3 to 6.0 for academic (p = 0.07) and 9.4 to 9.0 for community practices (p < 0.0001). Conclusion: This is one of the first studies to examine the efficacy of a clinical pathway for radiation oncology in an integrated cancer network. Clinical pathway implementation appears to be effective in changing patterns of care, particularly with online clinical

How Effective Are Clinical Pathways With and Without Online Peer-Review? An Analysis of Bone Metastases Pathway in a Large, Integrated National Cancer Institute–Designated Comprehensive Cancer Center Network

International Nuclear Information System (INIS)

Beriwal, Sushil; Rajagopalan, Malolan S.; Flickinger, John C.; Rakfal, Susan M.; Rodgers, Edwin; Heron, Dwight E.

2012-01-01

Purpose: Clinical pathways are an important tool used to manage the quality in health care by standardizing processes. This study evaluated the impact of the implementation of a peer-reviewed clinical pathway in a large, integrated National Cancer Institute–Designated Comprehensive Cancer Center Network. Methods: In 2003, we implemented a clinical pathway for the management of bone metastases with palliative radiation therapy. In 2009, we required the entry of management decisions into an online tool that records pathway choices. The pathway specified 1 or 5 fractions for symptomatic bone metastases with the option of 10–14 fractions for certain clinical situations. The data were obtained from 13 integrated sites (3 central academic, 10 community locations) from 2003 through 2010. Results: In this study, 7905 sites were treated with 64% of courses delivered in community practice and 36% in academic locations. Academic practices were more likely than community practices to treat with 1–5 fractions (63% vs. 23%; p < 0.0001). The number of delivered fractions decreased gradually from 2003 to 2010 for both academic and community practices (p < 0.0001); however, greater numbers of fractions were selected more often in community practices (p < 0.0001). Using multivariate logistic regression, we found that a significantly greater selection of 1–5 fractions developed after implementation online pathway monitoring (2009) with an odds ratio of 1.2 (confidence interval, 1.1–1.4) for community and 1.3 (confidence interval, 1.1–1.6) for academic practices. The mean number of fractions also decreased after online peer review from 6.3 to 6.0 for academic (p = 0.07) and 9.4 to 9.0 for community practices (p < 0.0001). Conclusion: This is one of the first studies to examine the efficacy of a clinical pathway for radiation oncology in an integrated cancer network. Clinical pathway implementation appears to be effective in changing patterns of care, particularly with

Unavailability of critical SCADA communication links interconnecting a power grid and a Telco network

International Nuclear Information System (INIS)

Bobbio, A.; Bonanni, G.; Ciancamerla, E.; Clemente, R.; Iacomini, A.; Minichino, M.; Scarlatti, A.; Terruggia, R.; Zendri, E.

2010-01-01

The availability of power supply to power grid customers depends upon the availability of services of supervision, control and data acquisition (SCADA) system, which constitutes the nervous system of a power grid. In turn, SCADA services depend on the availability of the interconnected networks supporting such services. We propose a service oriented stochastic modelling methodology to investigate the availability of large interconnected networks, based on the hierarchical application of different modelling formalisms to different parts of the networks. Interconnected networks are decomposed according to the specific services delivered until the failure and repair mechanisms of the decomposed elementary blocks can be identified. We represent each network by a convenient stochastic modelling formalism, able to capture the main technological issues and to cope with realistic assumptions about failure and recovery mechanisms. This procedure confines the application of the more intensive computational techniques to those subsystems that actually require it. The paper concentrates on an actual failure scenario, occurred in Rome in January 2004 that involved the outage of critical SCADA communication links, interconnecting a power grid and a Telco network.

Unavailability of critical SCADA communication links interconnecting a power grid and a Telco network

Energy Technology Data Exchange (ETDEWEB)

Bobbio, A. [Dipartimento di Informatica, Universita del Piemonte Orientale, Viale Michel 11, 15121 Alessandria (Italy); Bonanni, G.; Ciancamerla, E. [ENEA - CRE Casaccia, Via Anguillarese 301, 00060 Roma (Italy); Clemente, R. [Telecom Italia Mobile, Via Isonzo112, 10141 Torino (Italy); Iacomini, A. [ACEA, Pl. Ostiense 2, 00154 Roma (Italy); Minichino, M., E-mail: minichino@casaccia.enea.i [ENEA - CRE Casaccia, Via Anguillarese 301, 00060 Roma (Italy); Scarlatti, A. [ACEA, Pl. Ostiense 2, 00154 Roma (Italy); Terruggia, R. [Dipartimento di Informatica, Universita del Piemonte Orientale, Viale Michel 11, 15121 Alessandria (Italy); Zendri, E. [ACEA, Pl. Ostiense 2, 00154 Roma (Italy)

2010-12-15

The availability of power supply to power grid customers depends upon the availability of services of supervision, control and data acquisition (SCADA) system, which constitutes the nervous system of a power grid. In turn, SCADA services depend on the availability of the interconnected networks supporting such services. We propose a service oriented stochastic modelling methodology to investigate the availability of large interconnected networks, based on the hierarchical application of different modelling formalisms to different parts of the networks. Interconnected networks are decomposed according to the specific services delivered until the failure and repair mechanisms of the decomposed elementary blocks can be identified. We represent each network by a convenient stochastic modelling formalism, able to capture the main technological issues and to cope with realistic assumptions about failure and recovery mechanisms. This procedure confines the application of the more intensive computational techniques to those subsystems that actually require it. The paper concentrates on an actual failure scenario, occurred in Rome in January 2004 that involved the outage of critical SCADA communication links, interconnecting a power grid and a Telco network.

Inwardly Rectifying Potassium (Kir) Channels Represent a Critical Ion Conductance Pathway in the Nervous Systems of Insects.

Science.gov (United States)

Chen, Rui; Swale, Daniel R

2018-01-25

A complete understanding of the physiological pathways critical for proper function of the insect nervous system is still lacking. The recent development of potent and selective small-molecule modulators of insect inward rectifier potassium (Kir) channels has enabled the interrogation of the physiological role and toxicological potential of Kir channels within various insect tissue systems. Therefore, we aimed to highlight the physiological and functional role of neural Kir channels the central nervous system, muscular system, and neuromuscular system through pharmacological and genetic manipulations. Our data provide significant evidence that Drosophila neural systems rely on the inward conductance of K + ions for proper function since pharmacological inhibition and genetic ablation of neural Kir channels yielded dramatic alterations of the CNS spike discharge frequency and broadening and reduced amplitude of the evoked EPSP at the neuromuscular junction. Based on these data, we conclude that neural Kir channels in insects (1) are critical for proper function of the insect nervous system, (2) represents an unexplored physiological pathway that is likely to shape the understanding of neuronal signaling, maintenance of membrane potentials, and maintenance of the ionic balance of insects, and (3) are capable of inducing acute toxicity to insects through neurological poisoning.

Finding Solvable Units of Variables in Nonlinear ODEs of ECM Degradation Pathway Network

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Shuji Kawasaki

2017-01-01

Full Text Available We consider ordinary differential equation (ODE model for a pathway network that arises in extracellular matrix (ECM degradation. For solving the ODEs, we propose applying the mass conservation law (MCL, together with a stoichiometry called doubling rule, to them. Then it leads to extracting new units of variables in the ODEs that can be solved explicitly, at least in principle. The simulation results for the ODE solutions show that the numerical solutions are indeed in good accord with theoretical solutions and satisfy the MALs.

Finding Solvable Units of Variables in Nonlinear ODEs of ECM Degradation Pathway Network.

Science.gov (United States)

Kawasaki, Shuji; Minerva, Dhisa; Itano, Keiko; Suzuki, Takashi

2017-01-01

We consider ordinary differential equation (ODE) model for a pathway network that arises in extracellular matrix (ECM) degradation. For solving the ODEs, we propose applying the mass conservation law (MCL), together with a stoichiometry called doubling rule , to them. Then it leads to extracting new units of variables in the ODEs that can be solved explicitly, at least in principle. The simulation results for the ODE solutions show that the numerical solutions are indeed in good accord with theoretical solutions and satisfy the MALs.

Effects of Some Neurobiological Factors in a Self-organized Critical Model Based on Neural Networks

International Nuclear Information System (INIS)

Zhou Liming; Zhang Yingyue; Chen Tianlun

2005-01-01

Based on an integrate-and-fire mechanism, we investigate the effect of changing the efficacy of the synapse, the transmitting time-delayed, and the relative refractoryperiod on the self-organized criticality in our neural network model.

VitisNet: "Omics" integration through grapevine molecular networks.

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Jérôme Grimplet

Full Text Available BACKGROUND: Genomic data release for the grapevine has increased exponentially in the last five years. The Vitis vinifera genome has been sequenced and Vitis EST, transcriptomic, proteomic, and metabolomic tools and data sets continue to be developed. The next critical challenge is to provide biological meaning to this tremendous amount of data by annotating genes and integrating them within their biological context. We have developed and validated a system of Grapevine Molecular Networks (VitisNet. METHODOLOGY/PRINCIPAL FINDINGS: The sequences from the Vitis vinifera (cv. Pinot Noir PN40024 genome sequencing project and ESTs from the Vitis genus have been paired and the 39,424 resulting unique sequences have been manually annotated. Among these, 13,145 genes have been assigned to 219 networks. The pathway sets include 88 "Metabolic", 15 "Genetic Information Processing", 12 "Environmental Information Processing", 3 "Cellular Processes", 21 "Transport", and 80 "Transcription Factors". The quantitative data is loaded onto molecular networks, allowing the simultaneous visualization of changes in the transcriptome, proteome, and metabolome for a given experiment. CONCLUSIONS/SIGNIFICANCE: VitisNet uses manually annotated networks in SBML or XML format, enabling the integration of large datasets, streamlining biological functional processing, and improving the understanding of dynamic processes in systems biology experiments. VitisNet is grounded in the Vitis vinifera genome (currently at 8x coverage and can be readily updated with subsequent updates of the genome or biochemical discoveries. The molecular network files can be dynamically searched by pathway name or individual genes, proteins, or metabolites through the MetNet Pathway database and web-portal at http://metnet3.vrac.iastate.edu/. All VitisNet files including the manual annotation of the grape genome encompassing pathway names, individual genes, their genome identifier, and chromosome

Pathways of topological rank analysis (PoTRA: a novel method to detect pathways involved in hepatocellular carcinoma

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Chaoxing Li

2018-04-01

Full Text Available Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway’s topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher’s exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov–Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several

Tracing Pathways to Higher Education for Refugees: The Role of Virtual Support Networks and Mobile Phones for Women in Refugee Camps

Science.gov (United States)

Dahya, Negin; Dryden-Peterson, Sarah

2017-01-01

In this paper, we explore the role of online social networks in the cultivation of pathways to higher education for refugees, particularly for women. We compare supports garnered in local and offline settings to those accrued through online social networks and examine the differences between women and men. The paper draws on complementary original…

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems.

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Padhi, Radhakant; Unnikrishnan, Nishant; Wang, Xiaohua; Balakrishnan, S N

2006-12-01

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the "Single Network Adaptive Critic (SNAC)" is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Reliability estimation of safety-critical software-based systems using Bayesian networks

International Nuclear Information System (INIS)

Helminen, A.

2001-06-01

Due to the nature of software faults and the way they cause system failures new methods are needed for the safety and reliability evaluation of software-based safety-critical automation systems in nuclear power plants. In the research project 'Programmable automation system safety integrity assessment (PASSI)', belonging to the Finnish Nuclear Safety Research Programme (FINNUS, 1999-2002), various safety assessment methods and tools for software based systems are developed and evaluated. The project is financed together by the Radiation and Nuclear Safety Authority (STUK), the Ministry of Trade and Industry (KTM) and the Technical Research Centre of Finland (VTT). In this report the applicability of Bayesian networks to the reliability estimation of software-based systems is studied. The applicability is evaluated by building Bayesian network models for the systems of interest and performing simulations for these models. In the simulations hypothetical evidence is used for defining the parameter relations and for determining the ability to compensate disparate evidence in the models. Based on the experiences from modelling and simulations we are able to conclude that Bayesian networks provide a good method for the reliability estimation of software-based systems. (orig.)

Gene Network Construction from Microarray Data Identifies a Key Network Module and Several Candidate Hub Genes in Age-Associated Spatial Learning Impairment.

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Uddin, Raihan; Singh, Shiva M

2017-01-01

As humans age many suffer from a decrease in normal brain functions including spatial learning impairments. This study aimed to better understand the molecular mechanisms in age-associated spatial learning impairment (ASLI). We used a mathematical modeling approach implemented in Weighted Gene Co-expression Network Analysis (WGCNA) to create and compare gene network models of young (learning unimpaired) and aged (predominantly learning impaired) brains from a set of exploratory datasets in rats in the context of ASLI. The major goal was to overcome some of the limitations previously observed in the traditional meta- and pathway analysis using these data, and identify novel ASLI related genes and their networks based on co-expression relationship of genes. This analysis identified a set of network modules in the young, each of which is highly enriched with genes functioning in broad but distinct GO functional categories or biological pathways. Interestingly, the analysis pointed to a single module that was highly enriched with genes functioning in "learning and memory" related functions and pathways. Subsequent differential network analysis of this "learning and memory" module in the aged (predominantly learning impaired) rats compared to the young learning unimpaired rats allowed us to identify a set of novel ASLI candidate hub genes. Some of these genes show significant repeatability in networks generated from independent young and aged validation datasets. These hub genes are highly co-expressed with other genes in the network, which not only show differential expression but also differential co-expression and differential connectivity across age and learning impairment. The known function of these hub genes indicate that they play key roles in critical pathways, including kinase and phosphatase signaling, in functions related to various ion channels, and in maintaining neuronal integrity relating to synaptic plasticity and memory formation. Taken together, they

Screening key candidate genes and pathways involved in insulinoma by microarray analysis.

Science.gov (United States)

Zhou, Wuhua; Gong, Li; Li, Xuefeng; Wan, Yunyan; Wang, Xiangfei; Li, Huili; Jiang, Bin

2018-06-01

Insulinoma is a rare type tumor and its genetic features remain largely unknown. This study aimed to search for potential key genes and relevant enriched pathways of insulinoma.The gene expression data from GSE73338 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified between insulinoma tissues and normal pancreas tissues, followed by pathway enrichment analysis, protein-protein interaction (PPI) network construction, and module analysis. The expressions of candidate key genes were validated by quantitative real-time polymerase chain reaction (RT-PCR) in insulinoma tissues.A total of 1632 DEGs were obtained, including 1117 upregulated genes and 514 downregulated genes. Pathway enrichment results showed that upregulated DEGs were significantly implicated in insulin secretion, and downregulated DEGs were mainly enriched in pancreatic secretion. PPI network analysis revealed 7 hub genes with degrees more than 10, including GCG (glucagon), GCGR (glucagon receptor), PLCB1 (phospholipase C, beta 1), CASR (calcium sensing receptor), F2R (coagulation factor II thrombin receptor), GRM1 (glutamate metabotropic receptor 1), and GRM5 (glutamate metabotropic receptor 5). DEGs involved in the significant modules were enriched in calcium signaling pathway, protein ubiquitination, and platelet degranulation. Quantitative RT-PCR data confirmed that the expression trends of these hub genes were similar to the results of bioinformatic analysis.The present study demonstrated that candidate DEGs and enriched pathways were the potential critical molecule events involved in the development of insulinoma, and these findings were useful for better understanding of insulinoma genesis.

Optimal system size for complex dynamics in random neural networks near criticality

Energy Technology Data Exchange (ETDEWEB)

Wainrib, Gilles, E-mail: wainrib@math.univ-paris13.fr [Laboratoire Analyse Géométrie et Applications, Université Paris XIII, Villetaneuse (France); García del Molino, Luis Carlos, E-mail: garciadelmolino@ijm.univ-paris-diderot.fr [Institute Jacques Monod, Université Paris VII, Paris (France)

2013-12-15

In this article, we consider a model of dynamical agents coupled through a random connectivity matrix, as introduced by Sompolinsky et al. [Phys. Rev. Lett. 61(3), 259–262 (1988)] in the context of random neural networks. When system size is infinite, it is known that increasing the disorder parameter induces a phase transition leading to chaotic dynamics. We observe and investigate here a novel phenomenon in the sub-critical regime for finite size systems: the probability of observing complex dynamics is maximal for an intermediate system size when the disorder is close enough to criticality. We give a more general explanation of this type of system size resonance in the framework of extreme values theory for eigenvalues of random matrices.

Optimal system size for complex dynamics in random neural networks near criticality

International Nuclear Information System (INIS)

Wainrib, Gilles; García del Molino, Luis Carlos

2013-01-01

In this article, we consider a model of dynamical agents coupled through a random connectivity matrix, as introduced by Sompolinsky et al. [Phys. Rev. Lett. 61(3), 259–262 (1988)] in the context of random neural networks. When system size is infinite, it is known that increasing the disorder parameter induces a phase transition leading to chaotic dynamics. We observe and investigate here a novel phenomenon in the sub-critical regime for finite size systems: the probability of observing complex dynamics is maximal for an intermediate system size when the disorder is close enough to criticality. We give a more general explanation of this type of system size resonance in the framework of extreme values theory for eigenvalues of random matrices

Use of critical pathway models and log-normal frequency distributions for siting nuclear facilities

International Nuclear Information System (INIS)

Waite, D.A.; Denham, D.H.

1975-01-01

The advantages and disadvantages of potential sites for nuclear facilities are evaluated through the use of environmental pathway and log-normal distribution analysis. Environmental considerations of nuclear facility siting are necessarily geared to the identification of media believed to be sifnificant in terms of dose to man or to be potential centres for long-term accumulation of contaminants. To aid in meeting the scope and purpose of this identification, an exposure pathway diagram must be developed. This type of diagram helps to locate pertinent environmental media, points of expected long-term contaminant accumulation, and points of population/contaminant interface for both radioactive and non-radioactive contaminants. Confirmation of facility siting conclusions drawn from pathway considerations must usually be derived from an investigatory environmental surveillance programme. Battelle's experience with environmental surveillance data interpretation using log-normal techniques indicates that this distribution has much to offer in the planning, execution and analysis phases of such a programme. How these basic principles apply to the actual siting of a nuclear facility is demonstrated for a centrifuge-type uranium enrichment facility as an example. A model facility is examined to the extent of available data in terms of potential contaminants and facility general environmental needs. A critical exposure pathway diagram is developed to the point of prescribing the characteristics of an optimum site for such a facility. Possible necessary deviations from climatic constraints are reviewed and reconciled with conclusions drawn from the exposure pathway analysis. Details of log-normal distribution analysis techniques are presented, with examples of environmental surveillance data to illustrate data manipulation techniques and interpretation procedures as they affect the investigatory environmental surveillance programme. Appropriate consideration is given these

Integrated network for structural integrity monitoring of critical components in nuclear facilities, RIMIS

International Nuclear Information System (INIS)

Roth, Maria; Constantinescu, Dan Mihai; Brad, Sebastian; Ducu, Catalin; Malinovschi, Viorel

2008-01-01

The round table aims to join specialists working in the research area of the Romanian R and D Institutes and Universities involved in structural integrity assessment of materials, especially those working in the nuclear field, together with the representatives of the end user, the Cernavoda NPP. This scientific event will offer the opportunity to disseminate the theoretical, experimental and modelling activities, carried out to date, in the framework of the National Program 'Research of Excellence', Module I 2006-2008, managed by the National Authority for Scientific Research. Entitled 'Integrated Network for Structural Integrity Monitoring of Critical Components in Nuclear Facilities, RIMIS, the project has two main objectives: 1. - to elaborate a procedure applicable to the structural integrity assessment of critical components used in Romanian nuclear facilities (CANDU type Reactor, Hydrogen Isotopes Separation installations); 2. - to integrate the national networking into a similar one of European level, and to enhance the scientific significance of Romanian R and D organisations as well as to increase the contribution in solving major issues of the nuclear field. The topics of the round table will be focused on: 1. Development of a Structural Integrity Assessment Methodology applicable to the nuclear facilities components; 2. Experimental investigation methods and procedures; 3. Numeric simulation of nuclear components behaviour; 4. Further activities to finalize the assessment procedure. Also participations and contributions to sustain the activity in the European Network NULIFE, FP6 will be discussed. (authors)

Critical pathway studies for selected radionuclides. Part of a coordinated programme on environmental monitoring for radiological protection in Asia and the Far East

International Nuclear Information System (INIS)

Bhat, I.S.

1980-04-01

The programme carried out critical pathway studies for selected radionuclides ( 60 Co, 63 Ni, 59 Fe, 54 Mn, sup(110m)Ag, 106 Ru and 144 Ce) and assessed population exposure in the vicinity of Tarapur Atomic Power Station. The following topics are covered under the programme. (i) Demographic study of dietary habits and consumption data for Tarapur population. (ii) Concentration and accumulation of radionuclides in food products. (iii) Determination of radionuclides in sea water, silt, marine algae and marine organisms at Tarapur Atomic Power Station (TAPS) Site. (iv) Behaviour of radionuclides released to marine environment. (v) Evaluation of critical exposure pathway. (vi) Population exposure in the vicinity of Tarapur Atomic Power Station

Definition of critical periods for Hedgehog pathway antagonist-induced holoprosencephaly, cleft lip, and cleft palate.

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Galen W Heyne

Full Text Available The Hedgehog (Hh signaling pathway mediates multiple spatiotemporally-specific aspects of brain and face development. Genetic and chemical disruptions of the pathway are known to result in an array of structural malformations, including holoprosencephaly (HPE, clefts of the lip with or without cleft palate (CL/P, and clefts of the secondary palate only (CPO. Here, we examined patterns of dysmorphology caused by acute, stage-specific Hh signaling inhibition. Timed-pregnant wildtype C57BL/6J mice were administered a single dose of the potent pathway antagonist vismodegib at discrete time points between gestational day (GD 7.0 and 10.0, an interval approximately corresponding to the 15th to 24th days of human gestation. The resultant pattern of facial and brain dysmorphology was dependent upon stage of exposure. Insult between GD7.0 and GD8.25 resulted in HPE, with peak incidence following exposure at GD7.5. Unilateral clefts of the lip extending into the primary palate were also observed, with peak incidence following exposure at GD8.875. Insult between GD9.0 and GD10.0 resulted in CPO and forelimb abnormalities. We have previously demonstrated that Hh antagonist-induced cleft lip results from deficiency of the medial nasal process and show here that CPO is associated with reduced growth of the maxillary-derived palatal shelves. By defining the critical periods for the induction of HPE, CL/P, and CPO with fine temporal resolution, these results provide a mechanism by which Hh pathway disruption can result in "non-syndromic" orofacial clefting, or HPE with or without co-occurring clefts. This study also establishes a novel and tractable mouse model of human craniofacial malformations using a single dose of a commercially available and pathway-specific drug.

Fast grid layout algorithm for biological networks with sweep calculation.

Science.gov (United States)

Kojima, Kaname; Nagasaki, Masao; Miyano, Satoru

2008-06-15

Properly drawn biological networks are of great help in the comprehension of their characteristics. The quality of the layouts for retrieved biological networks is critical for pathway databases. However, since it is unrealistic to manually draw biological networks for every retrieval, automatic drawing algorithms are essential. Grid layout algorithms handle various biological properties such as aligning vertices having the same attributes and complicated positional constraints according to their subcellular localizations; thus, they succeed in providing biologically comprehensible layouts. However, existing grid layout algorithms are not suitable for real-time drawing, which is one of requisites for applications to pathway databases, due to their high-computational cost. In addition, they do not consider edge directions and their resulting layouts lack traceability for biochemical reactions and gene regulations, which are the most important features in biological networks. We devise a new calculation method termed sweep calculation and reduce the time complexity of the current grid layout algorithms through its encoding and decoding processes. We conduct practical experiments by using 95 pathway models of various sizes from TRANSPATH and show that our new grid layout algorithm is much faster than existing grid layout algorithms. For the cost function, we introduce a new component that penalizes undesirable edge directions to avoid the lack of traceability in pathways due to the differences in direction between in-edges and out-edges of each vertex. Java implementations of our layout algorithms are available in Cell Illustrator. masao@ims.u-tokyo.ac.jp Supplementary data are available at Bioinformatics online.

Ties that bind: the integration of plastid signalling pathways in plant cell metabolism.

Science.gov (United States)

Brunkard, Jacob O; Burch-Smith, Tessa M

2018-04-13

Plastids are critical organelles in plant cells that perform diverse functions and are central to many metabolic pathways. Beyond their major roles in primary metabolism, of which their role in photosynthesis is perhaps best known, plastids contribute to the biosynthesis of phytohormones and other secondary metabolites, store critical biomolecules, and sense a range of environmental stresses. Accordingly, plastid-derived signals coordinate a host of physiological and developmental processes, often by emitting signalling molecules that regulate the expression of nuclear genes. Several excellent recent reviews have provided broad perspectives on plastid signalling pathways. In this review, we will highlight recent advances in our understanding of chloroplast signalling pathways. Our discussion focuses on new discoveries illuminating how chloroplasts determine life and death decisions in cells and on studies elucidating tetrapyrrole biosynthesis signal transduction networks. We will also examine the role of a plastid RNA helicase, ISE2, in chloroplast signalling, and scrutinize intriguing results investigating the potential role of stromules in conducting signals from the chloroplast to other cellular locations. © 2018 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Network Attack Detection and Defense: Securing Industrial Control Systems for Critical Infrastructures (Dagstuhl Seminar 14292)

NARCIS (Netherlands)

Dacer, Marc; Kargl, Frank; König, Hartmut; Valdes, Alfonso

2014-01-01

This report documents the program and the outcomes of Dagstuhl Seminar 14292 “Network Attack Detection and Defense: Securing Industrial Control Systems for Critical Infrastructures”. The main objective of the seminar was to discuss new approaches and ideas for securing industrial control systems. It

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

Science.gov (United States)

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

Pathways from Poverty.

Science.gov (United States)

Baldwin, Barbara, Ed.

1995-01-01

Articles in this theme issue are based on presentations at the Pathways from Poverty Workshop held in Albuquerque, New Mexico, on May 18-25, 1995. The event aimed to foster development of a network to address rural poverty issues in the Western Rural Development Center (WRDC) region. Articles report on outcomes from the Pathways from Poverty…

Modeling the effects of a Staphylococcal Enterotoxin B (SEB on the apoptosis pathway

Directory of Open Access Journals (Sweden)

Hammamieh Rasha

2006-05-01

Full Text Available Abstract Background The lack of detailed understanding of the mechanism of action of many biowarfare agents poses an immediate challenge to biodefense efforts. Many potential bioweapons have been shown to affect the cellular pathways controlling apoptosis 1234. For example, pathogen-produced exotoxins such as Staphylococcal Enterotoxin B (SEB and Anthrax Lethal Factor (LF have been shown to disrupt the Fas-mediated apoptotic pathway 24. To evaluate how these agents affect these pathways it is first necessary to understand the dynamics of a normally functioning apoptosis network. This can then serve as a baseline against which a pathogen perturbed system can be compared. Such comparisons can expose both the proteins most susceptible to alteration by the agent as well as the most critical reaction rates to better instill control on a biological network. Results We explore this through the modeling and simulation of the Fas-mediated apoptotic pathway under normal and SEB influenced conditions. We stimulated human Jurkat cells with an anti-Fas antibody in the presence and absence of SEB and determined the relative levels of seven proteins involved in the core pathway at five time points following exposure. These levels were used to impute relative rate constants and build a quantitative model consisting of a series of ordinary differential equations (ODEs that simulate the network under both normal and pathogen-influenced conditions. Experimental results show that cells exposed to SEB exhibit an increase in the rate of executioner caspase expression (and subsequently apoptosis of 1 hour 43 minutes (± 14 minutes, as compared to cells undergoing normal cell death. Conclusion Our model accurately reflects these results and reveals intervention points that can be altered to restore SEB-influenced system dynamics back to levels within the range of normal conditions.

Pathway Distiller - multisource biological pathway consolidation.

Science.gov (United States)

Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong

2012-01-01

One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow

A study on the critical factors which influence habitual entrepreneurs' success in networking from the perspective of social captial theory

OpenAIRE

Li, SiQi

2012-01-01

The aim of the research is to provide an insight on the critical factors which influence habitual entrepreneurs’ success in networking through which effective networking strategies may lead to increased business performance. The perspective of explaining the factors adopts social capital theory and social dimensions of entrepreneurs’ network. The key findings suggest that social capital is in a form of non-linear pattern that the interactions are complex. Network configuration influences effe...

Pathway reconstruction of airway remodeling in chronic lung diseases: a systems biology approach.

Directory of Open Access Journals (Sweden)

Ali Najafi

Full Text Available Airway remodeling is a pathophysiologic process at the clinical, cellular, and molecular level relating to chronic obstructive airway diseases such as chronic obstructive pulmonary disease (COPD, asthma and mustard lung. These diseases are associated with the dysregulation of multiple molecular pathways in the airway cells. Little progress has so far been made in discovering the molecular causes of complex disease in a holistic systems manner. Therefore, pathway and network reconstruction is an essential part of a systems biology approach to solve this challenging problem. In this paper, multiple data sources were used to construct the molecular process of airway remodeling pathway in mustard lung as a model of airway disease. We first compiled a master list of genes that change with airway remodeling in the mustard lung disease and then reconstructed the pathway by generating and merging the protein-protein interaction and the gene regulatory networks. Experimental observations and literature mining were used to identify and validate the master list. The outcome of this paper can provide valuable information about closely related chronic obstructive airway diseases which are of great importance for biologists and their future research. Reconstructing the airway remodeling interactome provides a starting point and reference for the future experimental study of mustard lung, and further analysis and development of these maps will be critical to understanding airway diseases in patients.

Cellular Neural Network Method for Critical Slab with Albedo Boundary Condition

International Nuclear Information System (INIS)

Pirouzmanda, A.; Hadada, K.; Suh, K. Y.

2010-01-01

The neutron transport problems have been studied theoretically and numerically for years. A number of researchers have studied the criticality problems of one-speed neutrons in homogeneous slabs and spheres using various methods. The Chebyshev polynomial approximation method (T N method) has lately been developed and improved for the neutron transport equation in slab geometry. The one-speed time-dependent neutron transport equation using the Cellular Neural Network (CNN) for the vacuum boundary condition has previously been solved. In this paper, we demonstrate the capacity of CNN in calculating the critical slab thickness for different boundary conditions and its variation with moments N. The architecture of the CNN has already been dealt with thoroughly. Essentially, the CNN is used to model a first-order system of the partial differential equations (PDEs). The original equations in the T N approximation are also a set of PDEs. The CNN approach lends itself to analog VLSI implementation. In this study, the CNN model is implemented using the HSpice software package

Classification and prediction of the critical heat flux using fuzzy theory and artificial neural networks

International Nuclear Information System (INIS)

Moon, Sang Ki; Chang, Soon Heung

1994-01-01

A new method to predict the critical heat flux (CHF) is proposed, based on the fuzzy clustering and artificial neural network. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulting clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanism. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods. ((orig.))

Optimal and robust control of a class of nonlinear systems using dynamically re-optimised single network adaptive critic design

Science.gov (United States)

Tiwari, Shivendra N.; Padhi, Radhakant

2018-01-01

Following the philosophy of adaptive optimal control, a neural network-based state feedback optimal control synthesis approach is presented in this paper. First, accounting for a nominal system model, a single network adaptive critic (SNAC) based multi-layered neural network (called as NN1) is synthesised offline. However, another linear-in-weight neural network (called as NN2) is trained online and augmented to NN1 in such a manner that their combined output represent the desired optimal costate for the actual plant. To do this, the nominal model needs to be updated online to adapt to the actual plant, which is done by synthesising yet another linear-in-weight neural network (called as NN3) online. Training of NN3 is done by utilising the error information between the nominal and actual states and carrying out the necessary Lyapunov stability analysis using a Sobolev norm based Lyapunov function. This helps in training NN2 successfully to capture the required optimal relationship. The overall architecture is named as 'Dynamically Re-optimised single network adaptive critic (DR-SNAC)'. Numerical results for two motivating illustrative problems are presented, including comparison studies with closed form solution for one problem, which clearly demonstrate the effectiveness and benefit of the proposed approach.

Identification of cell proliferation, immune response and cell migration as critical pathways in a prognostic signature for HER2+:ERα- breast cancer.

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Jeffrey C Liu

Full Text Available Multi-gene prognostic signatures derived from primary tumor biopsies can guide clinicians in designing an appropriate course of treatment. Identifying genes and pathways most essential to a signature performance may facilitate clinical application, provide insights into cancer progression, and uncover potentially new therapeutic targets. We previously developed a 17-gene prognostic signature (HTICS for HER2+:ERα- breast cancer patients, using genes that are differentially expressed in tumor initiating cells (TICs versus non-TICs from MMTV-Her2/neu mammary tumors. Here we probed the pathways and genes that underlie the prognostic power of HTICS.We used Leave-One Out, Data Combination Test, Gene Set Enrichment Analysis (GSEA, Correlation and Substitution analyses together with Receiver Operating Characteristic (ROC and Kaplan-Meier survival analysis to identify critical biological pathways within HTICS. Publically available cohorts with gene expression and clinical outcome were used to assess prognosis. NanoString technology was used to detect gene expression in formalin-fixed paraffin embedded (FFPE tissues.We show that three major biological pathways: cell proliferation, immune response, and cell migration, drive the prognostic power of HTICS, which is further tuned by Homeostatic and Glycan metabolic signalling. A 6-gene minimal Core that retained a significant prognostic power, albeit less than HTICS, also comprised the proliferation/immune/migration pathways. Finally, we developed NanoString probes that could detect expression of HTICS genes and their substitutions in FFPE samples.Our results demonstrate that the prognostic power of a signature is driven by the biological processes it monitors, identify cell proliferation, immune response and cell migration as critical pathways for HER2+:ERα- cancer progression, and defines substitutes and Core genes that should facilitate clinical application of HTICS.

Study on tube critical heat flux data treatment with artificial neural networks

International Nuclear Information System (INIS)

Han Lang; Shan Jianqiang

2005-01-01

Prediction of the Critical Heat Flux (CHF) are analyzed by Artificial Neural Networks (ANN) to a CHF database for upward flow of water in uniformly heated vertical round tubes. The analysis is performed with three viewpoints hypothesis, i.e. for fixed inlet condition, fixed exit condition and local condition. Half of 6941 from CHF database data is trained through ANN, the trained ANN predicts the total CHF data better than any other conventional correlations, showing RMS error of 6.6%, 10.39% and 21.39%, respectively. (author)

Thyroid hormone-dependent development of early cortical networks: Temporal specificity and the contribution of trkB and mTOR pathways

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Sören eWesterholz

2013-08-01

Full Text Available Early in neocortical network development, triiodothyronine (T3 promotes GABAergic neurons’ population increase, their somatic growth and the formation of GABAergic synapses. In the presence of T3, GABAergic interneurons form longer axons and conspicuous axonal arborizations, with an increased number of putative synaptic boutons. Here we show that the increased GABAergic axonal growth is positively correlated with the proximity to non-GABAergic neurons. A differential innervation emerges from a T3-dependent decrease of axonal length in fields with low density of neuronal cell bodies, combined with an increased bouton formation in fields with high density of neuronal somata. T3 addition to deprived networks after the first two weeks of development did not rescue deficits in the GABAergic synaptic bouton distribution, or in the frequency and duration of spontaneous bursts. During the critical two-week-period, GABAergic signaling is depolarizing as revealed by calcium imaging experiments. Interestingly, T3 enhanced the expression of the potassium-chloride cotransporter 2 (KCC2, and accelerated the developmental shift from depolarizing to hyperpolarizing GABAergic signaling in non-GABAergic neurons.The T3-related increase of spontaneous network activity was remarkably reduced after blockade of either tropomyosin-receptor kinase B (trkB or mammalian target of rapamycin (mTOR pathways. T3-dependent increase in GABAergic neurons’ soma size was mediated mainly by mTOR signaling. Conversely, the T3-dependent selective increase of GABAergic boutons near non-GABAergic cell bodies is mediated by trkB signaling only. Both trkB and mTOR signaling mediate T3-dependent reduction of the GABAergic axon extension. The circuitry context is relevant for the interaction between T3 and trkB signaling, but not for the interactions between T3 and mTOR signaling.

Identification of Key Pathways and Genes in Advanced Coronary Atherosclerosis Using Bioinformatics Analysis

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Xiaowen Tan

2017-01-01

Full Text Available Background. Coronary artery atherosclerosis is a chronic inflammatory disease. This study aimed to identify the key changes of gene expression between early and advanced carotid atherosclerotic plaque in human. Methods. Gene expression dataset GSE28829 was downloaded from Gene Expression Omnibus (GEO, including 16 advanced and 13 early stage atherosclerotic plaque samples from human carotid. Differentially expressed genes (DEGs were analyzed. Results. 42,450 genes were obtained from the dataset. Top 100 up- and downregulated DEGs were listed. Functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG identification were performed. The result of functional and pathway enrichment analysis indicted that the immune system process played a critical role in the progression of carotid atherosclerotic plaque. Protein-protein interaction (PPI networks were performed either. Top 10 hub genes were identified from PPI network and top 6 modules were inferred. These genes were mainly involved in chemokine signaling pathway, cell cycle, B cell receptor signaling pathway, focal adhesion, and regulation of actin cytoskeleton. Conclusion. The present study indicated that analysis of DEGs would make a deeper understanding of the molecular mechanisms of atherosclerosis development and they might be used as molecular targets and diagnostic biomarkers for the treatment of atherosclerosis.

Criticality in Neuronal Networks

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Friedman, Nir; Ito, Shinya; Brinkman, Braden A. W.; Shimono, Masanori; Deville, R. E. Lee; Beggs, John M.; Dahmen, Karin A.; Butler, Tom C.

2012-02-01

In recent years, experiments detecting the electrical firing patterns in slices of in vitro brain tissue have been analyzed to suggest the presence of scale invariance and possibly criticality in the brain. Much of the work done however has been limited in two ways: 1) the data collected is from local field potentials that do not represent the firing of individual neurons; 2) the analysis has been primarily limited to histograms. In our work we examine data based on the firing of individual neurons (spike data), and greatly extend the analysis by considering shape collapse and exponents. Our results strongly suggest that the brain operates near a tuned critical point of a highly distinctive universality class.

Critical behavior of the ideal-gas Bose-Einstein condensation in the Apollonian network.

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de Oliveira, I N; dos Santos, T B; de Moura, F A B F; Lyra, M L; Serva, M

2013-08-01

We show that the ideal Boson gas displays a finite-temperature Bose-Einstein condensation transition in the complex Apollonian network exhibiting scale-free, small-world, and hierarchical properties. The single-particle tight-binding Hamiltonian with properly rescaled hopping amplitudes has a fractal-like energy spectrum. The energy spectrum is analytically demonstrated to be generated by a nonlinear mapping transformation. A finite-size scaling analysis over several orders of magnitudes of network sizes is shown to provide precise estimates for the exponents characterizing the condensed fraction, correlation size, and specific heat. The critical exponents, as well as the power-law behavior of the density of states at the bottom of the band, are similar to those of the ideal Boson gas in lattices with spectral dimension d(s)=2ln(3)/ln(9/5)~/=3.74.

Proteomics-based network analysis characterizes biological processes and pathways activated by preconditioned mesenchymal stem cells in cardiac repair mechanisms.

Science.gov (United States)

Di Silvestre, Dario; Brambilla, Francesca; Scardoni, Giovanni; Brunetti, Pietro; Motta, Sara; Matteucci, Marco; Laudanna, Carlo; Recchia, Fabio A; Lionetti, Vincenzo; Mauri, Pierluigi

2017-05-01

We have demonstrated that intramyocardial delivery of human mesenchymal stem cells preconditioned with a hyaluronan mixed ester of butyric and retinoic acid (MSCp + ) is more effective in preventing the decay of regional myocardial contractility in a swine model of myocardial infarction (MI). However, the understanding of the role of MSCp + in proteomic remodeling of cardiac infarcted tissue is not complete. We therefore sought to perform a comprehensive analysis of the proteome of infarct remote (RZ) and border zone (BZ) of pigs treated with MSCp + or unconditioned stem cells. Heart tissues were analyzed by MudPIT and differentially expressed proteins were selected by a label-free approach based on spectral counting. Protein profiles were evaluated by using PPI networks and their topological analysis. The proteomic remodeling was largely prevented in MSCp + group. Extracellular proteins involved in fibrosis were down-regulated, while energetic pathways were globally up-regulated. Cardioprotectant pathways involved in the production of keto acid metabolites were also activated. Additionally, we found that new hub proteins support the cardioprotective phenotype characterizing the left ventricular BZ treated with MSCp + . In fact, the up-regulation of angiogenic proteins NCL and RAC1 can be explained by the increase of capillary density induced by MSCp + . Our results show that angiogenic pathways appear to be uniquely positioned to integrate signaling with energetic pathways involving cardiac repair. Our findings prompt the use of proteomics-based network analysis to optimize new approaches preventing the post-ischemic proteomic remodeling that may underlie the limited self-repair ability of adult heart. Copyright © 2017 Elsevier B.V. All rights reserved.

The role of network theory and object-oriented modeling within a framework for the vulnerability analysis of critical infrastructures

International Nuclear Information System (INIS)

Eusgeld, Irene; Kroeger, Wolfgang; Sansavini, Giovanni; Schlaepfer, Markus; Zio, Enrico

2009-01-01

A framework for the analysis of the vulnerability of critical infrastructures has been proposed by some of the authors. The framework basically consists of two successive stages: (i) a screening analysis for identifying the parts of the critical infrastructure most relevant with respect to its vulnerability and (ii) a detailed modeling of the operational dynamics of the identified parts for gaining insights on the causes and mechanisms responsible for the vulnerability. In this paper, a critical presentation is offered of the results of a set of investigations aimed at evaluating the potentials of (i) using network analysis based on measures of topological interconnection and reliability efficiency, for the screening task; (ii) using object-oriented modeling as the simulation framework to capture the detailed dynamics of the operational scenarios involving the most vulnerable parts of the critical infrastructure as identified by the preceding network analysis. A case study based on the Swiss high-voltage transmission system is considered. The results are cross-compared and evaluated; the needs of further research are defined

Regulatory network of secondary metabolism in Brassica rapa: insight into the glucosinolate pathway.

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Dunia Pino Del Carpio

Full Text Available Brassica rapa studies towards metabolic variation have largely been focused on the profiling of the diversity of metabolic compounds in specific crop types or regional varieties, but none aimed to identify genes with regulatory function in metabolite composition. Here we followed a genetical genomics approach to identify regulatory genes for six biosynthetic pathways of health-related phytochemicals, i.e carotenoids, tocopherols, folates, glucosinolates, flavonoids and phenylpropanoids. Leaves from six weeks-old plants of a Brassica rapa doubled haploid population, consisting of 92 genotypes, were profiled for their secondary metabolite composition, using both targeted and LC-MS-based untargeted metabolomics approaches. Furthermore, the same population was profiled for transcript variation using a microarray containing EST sequences mainly derived from three Brassica species: B. napus, B. rapa and B. oleracea. The biochemical pathway analysis was based on the network analyses of both metabolite QTLs (mQTLs and transcript QTLs (eQTLs. Co-localization of mQTLs and eQTLs lead to the identification of candidate regulatory genes involved in the biosynthesis of carotenoids, tocopherols and glucosinolates. We subsequently focused on the well-characterized glucosinolate pathway and revealed two hotspots of co-localization of eQTLs with mQTLs in linkage groups A03 and A09. Our results indicate that such a large-scale genetical genomics approach combining transcriptomics and metabolomics data can provide new insights into the genetic regulation of metabolite composition of Brassica vegetables.

The TCA Pathway is an Important Player in the Regulatory Network Governing Vibrio alginolyticus Adhesion Under Adversity.

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Huang, Lixing; Huang, Li; Yan, Qingpi; Qin, Yingxue; Ma, Ying; Lin, Mao; Xu, Xiaojin; Zheng, Jiang

2016-01-01

Adhesion is a critical step in the initial stage of Vibrio alginolyticus infection; therefore, it is important to understand the underlying mechanisms governing the adhesion of V. alginolyticus and determine if environmental factors have any effect. A greater understanding of this process may assist in developing preventive measures for reducing infection. In our previous research, we presented the first RNA-seq data from V. alginolyticus cultured under stress conditions that resulted in reduced adhesion. Based on the RNA-seq data, we found that the Tricarboxylic acid cycle (TCA pathway) might be closely related to adhesion. Environmental interactions with the TCA pathway might alter adhesion. To validate this, bioinformatics analysis, quantitative Real-Time PCR (qPCR), RNAi, and in vitro adhesion assays were performed, while V. alginolyticus was treated with various stresses including temperature, pH, salinity, and starvation. The expression of genes involved in the TCA pathway was confirmed by qPCR, which reinforced the reliability of the sequencing data. Silencing of these genes was capable of reducing the adhesion ability of V. alginolyticus. Adhesion of V. alginolyticus is influenced substantially by environmental factors and the TCA pathway is sensitive to some environmental stresses, especially changes in pH and starvation. Our results indicated that (1) the TCA pathway plays a key role in V. alginolyticus adhesion: (2) the TCA pathway is sensitive to environmental stresses.

The TCA pathway is an important player in the regulatory network governing Vibrio alginolyticus adhesion under adversity

Directory of Open Access Journals (Sweden)

Lixing eHuang

2016-02-01

Full Text Available Adhesion is a critical step in the initial stage of Vibrio alginolyticus infection; therefore, it is important to understand the underlying mechanisms governing the adhesion of V. alginolyticus and determine if environmental factors have any effect. A greater understanding of this process may assist in developing preventive measures for reducing infection. In our previous research, we presented the first RNA-seq data from V. alginolyticus cultured under stress conditions that resulted in reduced adhesion. Based on the RNA-seq data, we found that the Tricarboxylic acid cycle (TCA pathway might be closely related to adhesion. Environmental interactions with the TCA pathway might alter adhesion. To validate this, bioinformatics analysis, qPCR, RNAi and in vitro adhesion assays were performed, while V. alginolyticus was treated with various stresses including temperature, pH, salinity and starvation. The expression of genes involved in the TCA pathway was confirmed by qPCR, which reinforced the reliability of the sequencing data. Silencing of these genes was capable of reducing the adhesion ability of V. alginolyticus. Adhesion of V. alginolyticus is influenced substantially by environmental factors and the TCA pathway is sensitive to some environmental stresses, especially changes in pH and starvation. Our results indicated that 1 the TCA pathway plays a key role in V. alginolyticus adhesion: 2 the TCA pathway is sensitive to environmental stresses.

Critical Node Location in De Bruijn Networks

Science.gov (United States)

2016-10-01

algorithms that are normally time- consuming perform exceptionally well on de Bruijn networks. This class of networks has yet to be considered from an...tolerant networks, peer-to-peer networks, amongst others. Because of their unique properties, many algorithms that are normally time- consuming perform...a quadratic binary equation, each higher order term must be replaced with several new variables. While this is possible, it is a time- consuming and

Atomic switch networks as complex adaptive systems

Science.gov (United States)

Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

2018-03-01

Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

A Network Approach to Psychosis: Pathways Between Childhood Trauma and Psychotic Symptoms.

Science.gov (United States)

Isvoranu, Adela-Maria; van Borkulo, Claudia D; Boyette, Lindy-Lou; Wigman, Johanna T W; Vinkers, Christiaan H; Borsboom, Denny

2017-01-01

Childhood trauma (CT) has been identified as a potential risk factor for the onset of psychotic disorders. However, to date, there is limited consensus with respect to which symptoms may ensue after exposure to trauma in early life, and whether specific pathways may account for these associations. The aim of the present study was to use the novel network approach to investigate how different types of traumatic childhood experiences relate to specific symptoms of psychotic disorders and to identify pathways that may be involved in the relationship between CT and psychosis. We used data of patients diagnosed with a psychotic disorder (n = 552) from the longitudinal observational study Genetic Risk and Outcome of Psychosis Project and included the 5 scales of the Childhood Trauma Questionnaire-Short Form and all original symptom dimensions of the Positive and Negative Syndrome Scale. Our results show that all 5 types of CT and positive and negative symptoms of psychosis are connected through symptoms of general psychopathology. These findings are in line with the theory of an affective pathway to psychosis after exposure to CT, with anxiety as a main connective component, but they also point to several additional connective paths between trauma and psychosis: eg, through poor impulse control (connecting abuse to grandiosity, excitement, and hostility) and motor retardation (connecting neglect to most negative symptoms). The results of the current study suggest that multiple paths may exist between trauma and psychosis and may also be useful in mapping potential transdiagnostic processes. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Linking metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways.

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Adam M Wentzell

2007-09-01

Full Text Available Phenotypic variation between individuals of a species is often under quantitative genetic control. Genomic analysis of gene expression polymorphisms between individuals is rapidly gaining popularity as a way to query the underlying mechanistic causes of variation between individuals. However, there is little direct evidence of a linkage between global gene expression polymorphisms and phenotypic consequences. In this report, we have mapped quantitative trait loci (QTLs-controlling glucosinolate content in a population of 403 Arabidopsis Bay x Sha recombinant inbred lines, 211 of which were previously used to identify expression QTLs controlling the transcript levels of biosynthetic genes. In a comparative study, we have directly tested two plant biosynthetic pathways for association between polymorphisms controlling biosynthetic gene transcripts and the resulting metabolites within the Arabidopsis Bay x Sha recombinant inbred line population. In this analysis, all loci controlling expression variation also affected the accumulation of the resulting metabolites. In addition, epistasis was detected more frequently for metabolic traits compared to transcript traits, even when both traits showed similar distributions. An analysis of candidate genes for QTL-controlling networks of transcripts and metabolites suggested that the controlling factors are a mix of enzymes and regulatory factors. This analysis showed that regulatory connections can feedback from metabolism to transcripts. Surprisingly, the most likely major regulator of both transcript level for nearly the entire pathway and aliphatic glucosinolate accumulation is variation in the last enzyme in the biosynthetic pathway, AOP2. This suggests that natural variation in transcripts may significantly impact phenotypic variation, but that natural variation in metabolites or their enzymatic loci can feed back to affect the transcripts.

Deep-ocean disposal of high-activity nuclear wastes: a conservative assessment of the seafood critical pathway

International Nuclear Information System (INIS)

Baxter, M.S.; Economides, B.

1984-01-01

This paper applies conventional 'worst-case' assumptions to modelling the effects of possible future disposal of high-activity wastes in the oceans. It otherwise uses previously published and generally accepted data to assess the possible intakes of the waste nuclides via consumption of seaweeds, molluscs, crustaceans, plankton and fish. Model-predicted intakes for critical groups generally exceed ICRP-recommended limits, with 244 Cm, 241 Am and 137 Cs being the most potentially hazardous nuclides. The various seafood consumption pathways are found to rank, in decreasing order of potential hazard, as seaweeds > molluscs > plankton > fish > crustaceans. (Auth.)

Minimal-Intrusion Traffic Monitoring And Analysis In Mission-Critical Communication Networks

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Alberto Domingo Ajenjo

2003-10-01

Full Text Available A good knowledge of expected and actual traffic patterns is an essential tool for network planning, design and operation in deployed, mission-critical applications. This paper describes those needs, and explains the Traffic Monitoring and Analysis Platform (TMAP concept, as developed in support of NATO deployed military headquarters Communications and Information Systems. It shows how a TMAP was deployed to a real NATO exercise, to prove the concept and baseline the traffic needs per application, per user community and per time of day. Then, it analyses the obtained results and derives conclusions on how to integrate traffic monitoring and analysis platforms in future deployments.

Satisfying needs through Social Networking Sites: A pathway towards problematic Internet use for socially anxious people?

OpenAIRE

Silvia Casale, Silvia Casale; Giulia Fioravanti, Giulia Fioravanti

2017-01-01

Introduction: Following the theoretical frameworks of the dual-factor model of Facebook use and the Self Determination Theory, the present study hypothesizes that the satisfaction of unmet needs through Social Networking Sites (SNSs) may represent a pathway towards problematic use of Internet communicative services (GPIU) for socially anxious people. Methods: Four hundred undergraduate students (females = 51.8%; mean age = 22.45 + 2.09) completed three brief scales measuring the satisfacti...

Mathematical Teaching Strategies: Pathways to Critical Thinking and Metacognition

OpenAIRE

Su, Hui Fang Huang " Ricci, Frederick A; Mnatsakanian, Mamikon

2015-01-01

A teacher that emphasizes reasoning, logic and validity gives their students access to mathematics as an effective way of practicing critical thinking. All students have the ability to enhance and expand their critical thinking when learning mathematics. Students can develop this ability when confronting mathematical problems, identifying possible solutions and evaluating and justifying their reasons for the results, thereby allowing students to become confident critical thinkers. Critical th...

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

Science.gov (United States)

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

A cross-study gene set enrichment analysis identifies critical pathways in endometriosis

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Bai Chunyan

2009-09-01

Full Text Available Abstract Background Endometriosis is an enigmatic disease. Gene expression profiling of endometriosis has been used in several studies, but few studies went further to classify subtypes of endometriosis based on expression patterns and to identify possible pathways involved in endometriosis. Some of the observed pathways are more inconsistent between the studies, and these candidate pathways presumably only represent a fraction of the pathways involved in endometriosis. Methods We applied a standardised microarray preprocessing and gene set enrichment analysis to six independent studies, and demonstrated increased concordance between these gene datasets. Results We find 16 up-regulated and 19 down-regulated pathways common in ovarian endometriosis data sets, 22 up-regulated and one down-regulated pathway common in peritoneal endometriosis data sets. Among them, 12 up-regulated and 1 down-regulated were found consistent between ovarian and peritoneal endometriosis. The main canonical pathways identified are related to immunological and inflammatory disease. Early secretory phase has the most over-represented pathways in the three uterine cycle phases. There are no overlapping significant pathways between the dataset from human endometrial endothelial cells and the datasets from ovarian endometriosis which used whole tissues. Conclusion The study of complex diseases through pathway analysis is able to highlight genes weakly connected to the phenotype which may be difficult to detect by using classical univariate statistics. By standardised microarray preprocessing and GSEA, we have increased the concordance in identifying many biological mechanisms involved in endometriosis. The identified gene pathways will shed light on the understanding of endometriosis and promote the development of novel therapies.

Critical Branching Neural Networks

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Kello, Christopher T.

2013-01-01

It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…

KeyPathwayMiner 4.0

DEFF Research Database (Denmark)

Alcaraz, Nicolas; Pauling, Josch; Batra, Richa

2014-01-01

release of KeyPathwayMiner (version 4.0) that is not limited to analyses of single omics data sets, e.g. gene expression, but is able to directly combine several different omics data types. Version 4.0 can further integrate existing knowledge by adding a search bias towards sub-networks that contain...... (avoid) genes provided in a positive (negative) list. Finally the new release now also provides a set of novel visualization features and has been implemented as an app for the standard bioinformatics network analysis tool: Cytoscape. CONCLUSION: With KeyPathwayMiner 4.0, we publish a Cytoscape app...

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

Science.gov (United States)

Caspi, Ron; Altman, Tomer; Dale, Joseph M.; Dreher, Kate; Fulcher, Carol A.; Gilham, Fred; Kaipa, Pallavi; Karthikeyan, Athikkattuvalasu S.; Kothari, Anamika; Krummenacker, Markus; Latendresse, Mario; Mueller, Lukas A.; Paley, Suzanne; Popescu, Liviu; Pujar, Anuradha; Shearer, Alexander G.; Zhang, Peifen; Karp, Peter D.

2010-01-01

The MetaCyc database (MetaCyc.org) is a comprehensive and freely accessible resource for metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are experimentally determined, small-molecule metabolic pathways and are curated from the primary scientific literature. With more than 1400 pathways, MetaCyc is the largest collection of metabolic pathways currently available. Pathways reactions are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes, and literature citations. BioCyc (BioCyc.org) is a collection of more than 500 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the full genome and predicted metabolic network of one organism. The network, which is predicted by the Pathway Tools software using MetaCyc as a reference, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs also contain additional features, such as predicted operons, transport systems, and pathway hole-fillers. The BioCyc Web site offers several tools for the analysis of the PGDBs, including Omics Viewers that enable visualization of omics datasets on two different genome-scale diagrams and tools for comparative analysis. The BioCyc PGDBs generated by SRI are offered for adoption by any party interested in curation of metabolic, regulatory, and genome-related information about an organism. PMID:19850718

Exact critical properties of two-dimensional polymer networks from conformal invariance

International Nuclear Information System (INIS)

Duplantier, B.

1988-03-01

An infinity of exact critical exponents for two-dimensional self-avoiding walks can be derived from conformal invariance and Coulomb gas techniques applied to the O(n) model and to the Potts model. They apply to polymer networks of any topology, for which a general scaling theory is given, valid in any dimension d. The infinite set of exponents has also been calculated to O(ε 2 ), for d=4-ε. The 2D study also includes other universality classes like the dense polymers, the Hamiltonian walks, the polymers at their θ-point. Exact correlation functions can be further given for Hamiltonian walks, and exact winding angle probability distributions for the self-avoiding walks

Understanding pathways of exposure using site-specific habits surveys, particularly new pathways and methodologies

International Nuclear Information System (INIS)

Grzechnik, M.; McTaggart, K.; Clyne, F.

2006-01-01

Full text of publication follows: UK policy on the control of radiation exposure via routine discharges from nuclear licensed sites has long been based on ICRP recommendations that embody the principles of justification of practices, optimisation of protection, and dose limitation. Radiological protection of the public is based on the concept of a critical group of individuals. This group is defined as those people who, as a result of the area they reside and their habits, receive the highest radiation dose due to the operations of a site. Therefore, if the dose to this critical group is acceptable in relation to relevant dose limits and constraints, then other members of the public will receive lower doses. Thus, the principle of critical groups provides overall protection for the public. Surveys to determine local habits involve an integrated methodology, whereby the potential radioactive exposure pathways from liquid and gaseous discharges and direct radiation from the site are investigated. Surveys to identify these habits must be undertaken rigorously for consistency, and have been known to reveal unexpected pathways of radiation exposure. Pathways typically include consumption of local foodstuffs and external exposure. Furthermore, a number of critical groups ma y be identified within a single survey area if the habits of one group do not adequately describe those of the other inhabitants of the area. Survey preparation involves the initial identification of high producers and consumers of local foods in a geographically defined area surrounding the nuclear facility. Pathways can be broken down into three general groups, which include exposure arising from; 1) Terrestrial (gaseous) discharges surveyed within 5 km of the site 2) Direct radiation surveyed within 1 km of the site 3) Aquatic (liquid) discharges surveyed within local areas affected by the discharges, including seas, rivers and sewage works. The survey fieldwork involves interviewing members of the

Drug use Discrimination Predicts Formation of High-Risk Social Networks: Examining Social Pathways of Discrimination.

Science.gov (United States)

Crawford, Natalie D; Ford, Chandra; Rudolph, Abby; Kim, BoRin; Lewis, Crystal M

2017-09-01

Experiences of discrimination, or social marginalization and ostracism, may lead to the formation of social networks characterized by inequality. For example, those who experience discrimination may be more likely to develop drug use and sexual partnerships with others who are at increased risk for HIV compared to those without experiences of discrimination. This is critical as engaging in risk behaviors with others who are more likely to be HIV positive can increase one's risk of HIV. We used log-binomial regression models to examine the relationship between drug use, racial and incarceration discrimination with changes in the composition of one's risk network among 502 persons who use drugs. We examined both absolute and proportional changes with respect to sex partners, drug use partners, and injecting partners, after accounting for individual risk behaviors. At baseline, participants were predominately male (70%), black or Latino (91%), un-married (85%), and used crack (64%). Among those followed-up (67%), having experienced discrimination due to drug use was significantly related to increases in the absolute number of sex networks and drug networks over time. No types of discrimination were related to changes in the proportion of high-risk network members. Discrimination may increase one's risk of HIV acquisition by leading them to preferentially form risk relationships with higher-risk individuals, thereby perpetuating racial and ethnic inequities in HIV. Future social network studies and behavioral interventions should consider whether social discrimination plays a role in HIV transmission.

Pathways towards instability in financial networks

Science.gov (United States)

Bardoscia, Marco; Battiston, Stefano; Caccioli, Fabio; Caldarelli, Guido

2017-02-01

Following the financial crisis of 2007-2008, a deep analogy between the origins of instability in financial systems and complex ecosystems has been pointed out: in both cases, topological features of network structures influence how easily distress can spread within the system. However, in financial network models, the details of how financial institutions interact typically play a decisive role, and a general understanding of precisely how network topology creates instability remains lacking. Here we show how processes that are widely believed to stabilize the financial system, that is, market integration and diversification, can actually drive it towards instability, as they contribute to create cyclical structures which tend to amplify financial distress, thereby undermining systemic stability and making large crises more likely. This result holds irrespective of the details of how institutions interact, showing that policy-relevant analysis of the factors affecting financial stability can be carried out while abstracting away from such details.

Strength of Temporal White Matter Pathways Predicts Semantic Learning.

Science.gov (United States)

Ripollés, Pablo; Biel, Davina; Peñaloza, Claudia; Kaufmann, Jörn; Marco-Pallarés, Josep; Noesselt, Toemme; Rodríguez-Fornells, Antoni

2017-11-15

Learning the associations between words and meanings is a fundamental human ability. Although the language network is cortically well defined, the role of the white matter pathways supporting novel word-to-meaning mappings remains unclear. Here, by using contextual and cross-situational word learning, we tested whether learning the meaning of a new word is related to the integrity of the language-related white matter pathways in 40 adults (18 women). The arcuate, uncinate, inferior-fronto-occipital and inferior-longitudinal fasciculi were virtually dissected using manual and automatic deterministic fiber tracking. Critically, the automatic method allowed assessing the white matter microstructure along the tract. Results demonstrate that the microstructural properties of the left inferior-longitudinal fasciculus predict contextual learning, whereas the left uncinate was associated with cross-situational learning. In addition, we identified regions of special importance within these pathways: the posterior middle temporal gyrus, thought to serve as a lexical interface and specifically related to contextual learning; the anterior temporal lobe, known to be an amodal hub for semantic processing and related to cross-situational learning; and the white matter near the hippocampus, a structure fundamental for the initial stages of new-word learning and, remarkably, related to both types of word learning. No significant associations were found for the inferior-fronto-occipital fasciculus or the arcuate. While previous results suggest that learning new phonological word forms is mediated by the arcuate fasciculus, these findings show that the temporal pathways are the crucial neural substrate supporting one of the most striking human abilities: our capacity to identify correct associations between words and meanings under referential indeterminacy. SIGNIFICANCE STATEMENT The language-processing network is cortically (i.e., gray matter) well defined. However, the role of the

Mobile Ad Hoc Networks in Bandwidth-Demanding Mission-Critical Applications: Practical Implementation Insights

KAUST Repository

Bader, Ahmed

2016-09-28

There has been recently a growing trend of using live video feeds in mission-critical applications. Real-time video streaming from front-end personnel or mobile agents is believed to substantially improve situational awareness in mission-critical operations such as disaster relief, law enforcement, and emergency response. Mobile Ad Hoc Networks (MANET) is a natural contender in such contexts. However, classical MANET routing schemes fall short in terms of scalability, bandwidth and latency; all three metrics being quite essential for mission-critical applications. As such, autonomous cooperative routing (ACR) has gained traction as the most viable MANET proposition. Nonetheless, ACR is also associated with a few implementation challenges. If they go unaddressed, will deem ACR practically useless. In this paper, efficient and low-complexity remedies to those issues are presented, analyzed, and validated. The validation is based on field experiments carried out using software-defined radio (SDR) platforms. Compared to classical MANET routing schemes, ACR was shown to offer up to 2X better throughput, more than 4X reduction in end-to-end latency, while observing a given target of transport rate normalized to energy consumption.

The relationship between social networks and pathways to kidney transplant parity: evidence from black Americans in Chicago.

Science.gov (United States)

Browne, Teri

2011-09-01

Research has shown that black dialysis patients in the United States are significantly less likely than their white peers to be evaluated and listed for a kidney transplant. Extrapolating from social-network theory, I hypothesize that a lack of access to social contacts with information about kidney transplantation may hinder information transaction regarding the benefits of, and pathway to, transplantation. In 2007-2008, the following research questions were addressed in an investigation in Chicago, USA: (1) What is the role of social networks in providing information about kidney transplantation to black hemodialysis patients? (2) What is the relationship between social networks and a patient's likelihood of being seen at a kidney transplant center? From a stratified sample of dialysis units in the area, a purposive sample of 228 black patients was surveyed while they received treatment about their social networks and kidney transplant status. It was found that the odds of black hemodialysis patients being seen at a kidney transplant center increase with income, and patients who have people in their social network with information about kidney transplant were significantly more likely to be seen at a kidney transplant center. Specifically, black dialysis patients who get informational social support from their dialysis team and social networks were significantly more likely to be seen at kidney transplant centers. I conclude that considering black dialysis patients' social milieu can be complementary to the existing research regarding this public health crisis. Copyright © 2011 Elsevier Ltd. All rights reserved.

COST action TD1407: network on technology-critical elements (NOTICE)--from environmental processes to human health threats.

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Cobelo-García, A; Filella, M; Croot, P; Frazzoli, C; Du Laing, G; Ospina-Alvarez, N; Rauch, S; Salaun, P; Schäfer, J; Zimmermann, S

2015-10-01

The current socio-economic, environmental and public health challenges that countries are facing clearly need common-defined strategies to inform and support our transition to a sustainable economy. Here, the technology-critical elements (which includes Ga, Ge, In, Te, Nb, Ta, Tl, the Platinum Group Elements and most of the rare-earth elements) are of great relevance in the development of emerging key technologies-including renewable energy, energy efficiency, electronics or the aerospace industry. In this context, the increasing use of technology-critical elements (TCEs) and associated environmental impacts (from mining to end-of-life waste products) is not restricted to a national level but covers most likely a global scale. Accordingly, the European COST Action TD1407: Network on Technology-Critical Elements (NOTICE)-from environmental processes to human health threats, has an overall objective for creating a network of scientists and practitioners interested in TCEs, from the evaluation of their environmental processes to understanding potential human health threats, with the aim of defining the current state of knowledge and gaps, proposing priority research lines/activities and acting as a platform for new collaborations and joint research projects. The Action is focused on three major scientific areas: (i) analytical chemistry, (ii) environmental biogeochemistry and (iii) human exposure and (eco)-toxicology.

.Network analytics for adverse outcome pathways

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Adverse Outcome Pathways (AOPs) organize toxicological knowledge from the molecular level up to the population level, providing evidence-based causal linkages at each step. The AOPWiki serves as a repository of AOPs. With the international adoption of the AOP framework, the AOPw...

Critical importance of the de novo pyrimidine biosynthesis pathway for Trypanosoma cruzi growth in the mammalian host cell cytoplasm

International Nuclear Information System (INIS)

Hashimoto, Muneaki; Morales, Jorge; Fukai, Yoshihisa; Suzuki, Shigeo; Takamiya, Shinzaburo; Tsubouchi, Akiko; Inoue, Syou; Inoue, Masayuki; Kita, Kiyoshi; Harada, Shigeharu; Tanaka, Akiko; Aoki, Takashi; Nara, Takeshi

2012-01-01

Highlights: ► We established Trypanosoma cruzi lacking the gene for carbamoyl phosphate synthetase II. ► Disruption of the cpsII gene significantly reduced the growth of epimastigotes. ► In particular, the CPSII-null mutant severely retarded intracellular growth. ► The de novo pyrimidine pathway is critical for the parasite growth in the host cell. -- Abstract: The intracellular parasitic protist Trypanosoma cruzi is the causative agent of Chagas disease in Latin America. In general, pyrimidine nucleotides are supplied by both de novo biosynthesis and salvage pathways. While epimastigotes—an insect form—possess both activities, amastigotes—an intracellular replicating form of T. cruzi—are unable to mediate the uptake of pyrimidine. However, the requirement of de novo pyrimidine biosynthesis for parasite growth and survival has not yet been elucidated. Carbamoyl-phosphate synthetase II (CPSII) is the first and rate-limiting enzyme of the de novo biosynthetic pathway, and increased CPSII activity is associated with the rapid proliferation of tumor cells. In the present study, we showed that disruption of the T. cruzicpsII gene significantly reduced parasite growth. In particular, the growth of amastigotes lacking the cpsII gene was severely suppressed. Thus, the de novo pyrimidine pathway is important for proliferation of T. cruzi in the host cell cytoplasm and represents a promising target for chemotherapy against Chagas disease.

Applying a Space-Based Security Recovery Scheme for Critical Homeland Security Cyberinfrastructure Utilizing the NASA Tracking and Data Relay (TDRS) Based Space Network

Science.gov (United States)

Shaw, Harry C.; McLaughlin, Brian; Stocklin, Frank; Fortin, Andre; Israel, David; Dissanayake, Asoka; Gilliand, Denise; LaFontaine, Richard; Broomandan, Richard; Hyunh, Nancy

2015-01-01

Protection of the national infrastructure is a high priority for cybersecurity of the homeland. Critical infrastructure such as the national power grid, commercial financial networks, and communications networks have been successfully invaded and re-invaded from foreign and domestic attackers. The ability to re-establish authentication and confidentiality of the network participants via secure channels that have not been compromised would be an important countermeasure to compromise of our critical network infrastructure. This paper describes a concept of operations by which the NASA Tracking and Data Relay (TDRS) constellation of spacecraft in conjunction with the White Sands Complex (WSC) Ground Station host a security recovery system for re-establishing secure network communications in the event of a national or regional cyberattack. Users would perform security and network restoral functions via a Broadcast Satellite Service (BSS) from the TDRS constellation. The BSS enrollment only requires that each network location have a receive antenna and satellite receiver. This would be no more complex than setting up a DIRECTTV-like receiver at each network location with separate network connectivity. A GEO BSS would allow a mass re-enrollment of network nodes (up to nationwide) simultaneously depending upon downlink characteristics. This paper details the spectrum requirements, link budget, notional assets and communications requirements for the scheme. It describes the architecture of such a system and the manner in which it leverages off of the existing secure infrastructure which is already in place and managed by the NASAGSFC Space Network Project.

Designing a network of critical zone observatories to explore the living skin of the terrestrial Earth

Directory of Open Access Journals (Sweden)

S. L. Brantley

2017-12-01

Full Text Available The critical zone (CZ, the dynamic living skin of the Earth, extends from the top of the vegetative canopy through the soil and down to fresh bedrock and the bottom of the groundwater. All humans live in and depend on the CZ. This zone has three co-evolving surfaces: the top of the vegetative canopy, the ground surface, and a deep subsurface below which Earth's materials are unweathered. The network of nine CZ observatories supported by the US National Science Foundation has made advances in three broad areas of CZ research relating to the co-evolving surfaces. First, monitoring has revealed how natural and anthropogenic inputs at the vegetation canopy and ground surface cause subsurface responses in water, regolith structure, minerals, and biotic activity to considerable depths. This response, in turn, impacts aboveground biota and climate. Second, drilling and geophysical imaging now reveal how the deep subsurface of the CZ varies across landscapes, which in turn influences aboveground ecosystems. Third, several new mechanistic models now provide quantitative predictions of the spatial structure of the subsurface of the CZ.Many countries fund critical zone observatories (CZOs to measure the fluxes of solutes, water, energy, gases, and sediments in the CZ and some relate these observations to the histories of those fluxes recorded in landforms, biota, soils, sediments, and rocks. Each US observatory has succeeded in (i synthesizing research across disciplines into convergent approaches; (ii providing long-term measurements to compare across sites; (iii testing and developing models; (iv collecting and measuring baseline data for comparison to catastrophic events; (v stimulating new process-based hypotheses; (vi catalyzing development of new techniques and instrumentation; (vii informing the public about the CZ; (viii mentoring students and teaching about emerging multidisciplinary CZ science; and (ix discovering new insights about the CZ. Many

Designing a network of critical zone observatories to explore the living skin of the terrestrial Earth

Science.gov (United States)

Brantley, Susan L.; McDowell, William H.; Dietrich, William E.; White, Timothy S.; Kumar, Praveen; Anderson, Suzanne P.; Chorover, Jon; Lohse, Kathleen Ann; Bales, Roger C.; Richter, Daniel D.; Grant, Gordon; Gaillardet, Jérôme

2017-12-01

The critical zone (CZ), the dynamic living skin of the Earth, extends from the top of the vegetative canopy through the soil and down to fresh bedrock and the bottom of the groundwater. All humans live in and depend on the CZ. This zone has three co-evolving surfaces: the top of the vegetative canopy, the ground surface, and a deep subsurface below which Earth's materials are unweathered. The network of nine CZ observatories supported by the US National Science Foundation has made advances in three broad areas of CZ research relating to the co-evolving surfaces. First, monitoring has revealed how natural and anthropogenic inputs at the vegetation canopy and ground surface cause subsurface responses in water, regolith structure, minerals, and biotic activity to considerable depths. This response, in turn, impacts aboveground biota and climate. Second, drilling and geophysical imaging now reveal how the deep subsurface of the CZ varies across landscapes, which in turn influences aboveground ecosystems. Third, several new mechanistic models now provide quantitative predictions of the spatial structure of the subsurface of the CZ.Many countries fund critical zone observatories (CZOs) to measure the fluxes of solutes, water, energy, gases, and sediments in the CZ and some relate these observations to the histories of those fluxes recorded in landforms, biota, soils, sediments, and rocks. Each US observatory has succeeded in (i) synthesizing research across disciplines into convergent approaches; (ii) providing long-term measurements to compare across sites; (iii) testing and developing models; (iv) collecting and measuring baseline data for comparison to catastrophic events; (v) stimulating new process-based hypotheses; (vi) catalyzing development of new techniques and instrumentation; (vii) informing the public about the CZ; (viii) mentoring students and teaching about emerging multidisciplinary CZ science; and (ix) discovering new insights about the CZ. Many of these

The Glymphatic Pathway.

Science.gov (United States)

Benveniste, Helene; Lee, Hedok; Volkow, Nora D

2017-01-01

The overall premise of this review is that cerebrospinal fluid (CSF) is transported within a dedicated peri-vascular network facilitating metabolic waste clearance from the central nervous system while we sleep. The anatomical profile of the network is complex and has been defined as a peri-arterial CSF influx pathway and peri-venous clearance routes, which are functionally coupled by interstitial bulk flow supported by astrocytic aquaporin 4 water channels. The role of the newly discovered system in the brain is equivalent to the lymphatic system present in other body organs and has been termed the "glymphatic pathway" or "(g)lymphatics" because of its dependence on glial cells. We will discuss and review the general anatomy and physiology of CSF from the perspective of the glymphatic pathway, a discovery which has greatly improved our understanding of key factors that control removal of metabolic waste products from the central nervous system in health and disease and identifies an additional purpose for sleep. A brief historical and factual description of CSF production and transport will precede the ensuing discussion of the glymphatic system along with a discussion of its clinical implications.

Extracting reaction networks from databases-opening Pandora's box.

Science.gov (United States)

Fearnley, Liam G; Davis, Melissa J; Ragan, Mark A; Nielsen, Lars K

2014-11-01

Large quantities of information describing the mechanisms of biological pathways continue to be collected in publicly available databases. At the same time, experiments have increased in scale, and biologists increasingly use pathways defined in online databases to interpret the results of experiments and generate hypotheses. Emerging computational techniques that exploit the rich biological information captured in reaction systems require formal standardized descriptions of pathways to extract these reaction networks and avoid the alternative: time-consuming and largely manual literature-based network reconstruction. Here, we systematically evaluate the effects of commonly used knowledge representations on the seemingly simple task of extracting a reaction network describing signal transduction from a pathway database. We show that this process is in fact surprisingly difficult, and the pathway representations adopted by various knowledge bases have dramatic consequences for reaction network extraction, connectivity, capture of pathway crosstalk and in the modelling of cell-cell interactions. Researchers constructing computational models built from automatically extracted reaction networks must therefore consider the issues we outline in this review to maximize the value of existing pathway knowledge. © The Author 2013. Published by Oxford University Press.

Identifying the Gene Signatures from Gene-Pathway Bipartite Network Guarantees the Robust Model Performance on Predicting the Cancer Prognosis

Directory of Open Access Journals (Sweden)

Li He

2014-01-01

Full Text Available For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.

Logarithmic corrections to scaling in critical percolation and random resistor networks.

Science.gov (United States)

Stenull, Olaf; Janssen, Hans-Karl

2003-09-01

We study the critical behavior of various geometrical and transport properties of percolation in six dimensions. By employing field theory and renormalization group methods we analyze fluctuation induced logarithmic corrections to scaling up to and including the next-to-leading order correction. Our study comprehends the percolation correlation function, i.e., the probability that two given points are connected, and some of the fractal masses describing percolation clusters. To be specific, we calculate the mass of the backbone, the red bonds, and the shortest path. Moreover, we study key transport properties of percolation as represented by the random resistor network. We investigate the average two-point resistance as well as the entire family of multifractal moments of the current distribution.

Development of Tool Representations in the Dorsal and Ventral Visual Object Processing Pathways

Science.gov (United States)

Kersey, Alyssa J.; Clark, Tyia S.; Lussier, Courtney A.; Mahon, Bradford Z.; Cantlon, Jessica F.

2016-01-01

Tools represent a special class of objects, because they are processed across both the dorsal and ventral visual object processing pathways. Three core regions are known to be involved in tool processing: the left posterior middle temporal gyrus, the medial fusiform gyrus (bilaterally), and the left inferior parietal lobule. A critical and relatively unexplored issue concerns whether, in development, tool preferences emerge at the same time and to a similar degree across all regions of the tool-processing network. To test this issue, we used functional magnetic resonance imaging to measure the neural amplitude, peak location, and the dispersion of tool-related neural responses in the youngest sample of children tested to date in this domain (ages 4–8 years). We show that children recruit overlapping regions of the adult tool-processing network and also exhibit similar patterns of co-activation across the network to adults. The amplitude and co-activation data show that the core components of the tool-processing network are established by age 4. Our findings on the distributions of peak location and dispersion of activation indicate that the tool network undergoes refinement between ages 4 and 8 years. PMID:26108614

Application of R to investigate common gene regulatory network pathway among bipolar disorder and associate diseases

Directory of Open Access Journals (Sweden)

Nahida Habib

2016-12-01

Full Text Available Depression, Major Depression or mental disorder creates severe diseases. Mental illness such as Unipolar Major Depression, Bipolar Disorder, Dysthymia, Schizophrenia, Cardiovascular Diseases (Hypertension, Coronary Heart Disease, Stroke etc., are known as Major Depression. Several studies have revealed the possibilities about the association among Bipolar Disorder, Schizophrenia, Coronary Heart Diseases and Stroke with each other. The current study aimed to investigate the relationships between genetic variants in the above four diseases and to create a common pathway or PPI network. The associated genes of each disease are collected from different gene database with verification using R. After performing some preprocessing, mining and operations using R on collected genes, seven (7 common associated genes are discovered on selected four diseases (SZ, BD, CHD and Stroke. In each of the iteration, the numbers of collected genes are reduced up to 51%, 36%, 10%, 2% and finally less than 1% respectively. Moreover, common pathway on selected diseases has been investigated in this research.

Failure Diagnosis and Prognosis of Rolling - Element Bearings using Artificial Neural Networks: A Critical Overview

Science.gov (United States)

Rao, B. K. N.; Srinivasa Pai, P.; Nagabhushana, T. N.

2012-05-01

Rolling - Element Bearings are extensively used in almost all global industries. Any critical failures in these vitally important components would not only affect the overall systems performance but also its reliability, safety, availability and cost-effectiveness. Proactive strategies do exist to minimise impending failures in real time and at a minimum cost. Continuous innovative developments are taking place in the field of Artificial Neural Networks (ANNs) technology. Significant research and development are taking place in many universities, private and public organizations and a wealth of published literature is available highlighting the potential benefits of employing ANNs in intelligently monitoring, diagnosing, prognosing and managing rolling-element bearing failures. This paper attempts to critically review the recent trends in this topical area of interest.

Failure Diagnosis and Prognosis of Rolling - Element Bearings using Artificial Neural Networks: A Critical Overview

International Nuclear Information System (INIS)

Rao, B K N; Pai, P Srinivasa; Nagabhushana, T N

2012-01-01

Rolling - Element Bearings are extensively used in almost all global industries. Any critical failures in these vitally important components would not only affect the overall systems performance but also its reliability, safety, availability and cost-effectiveness. Proactive strategies do exist to minimise impending failures in real time and at a minimum cost. Continuous innovative developments are taking place in the field of Artificial Neural Networks (ANNs) technology. Significant research and development are taking place in many universities, private and public organizations and a wealth of published literature is available highlighting the potential benefits of employing ANNs in intelligently monitoring, diagnosing, prognosing and managing rolling-element bearing failures. This paper attempts to critically review the recent trends in this topical area of interest.

Evaluating between-pathway models with expression data.

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Hescott, B J; Leiserson, M D M; Cowen, L J; Slonim, D K

2010-03-01

Between-pathway models (BPMs) are network motifs consisting of pairs of putative redundant pathways. In this article, we show how adding another source of high-throughput data--microarray gene expression data from knockout experiments--allows us to identify a compensatory functional relationship between genes from the two BPM pathways. We evaluate the quality of the BPMs from four different studies, and we describe how our methods might be extended to refine pathways.

Bioinformatics analysis of RNA-seq data revealed critical genes in colon adenocarcinoma.

Science.gov (United States)

Xi, W-D; Liu, Y-J; Sun, X-B; Shan, J; Yi, L; Zhang, T-T

2017-07-01

RNA-seq data of colon adenocarcinoma (COAD) were analyzed with bioinformatics tools to discover critical genes in the disease. Relevant small molecule drugs, transcription factors (TFs) and microRNAs (miRNAs) were also investigated. RNA-seq data of COAD were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis was performed with package edgeR. False positive discovery (FDR) 1 were set as the cut-offs to screen out differentially expressed genes (DEGs). Gene coexpression network was constructed with package Ebcoexpress. GO enrichment analysis was performed for the DEGs in the gene coexpression network with DAVID. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was also performed for the genes with KOBASS 2.0. Modules were identified with MCODE of Cytoscape. Relevant small molecules drugs were predicted by Connectivity map. Relevant miRNAs and TFs were searched by WebGestalt. A total of 457 DEGs, including 255 up-regulated and 202 down-regulated genes, were identified from 437 COAD and 39 control samples. A gene coexpression network was constructed containing 40 DEGs and 101 edges. The genes were mainly associated with collagen fibril organization, extracellular matrix organization and translation. Two modules were identified from the gene coexpression network, which were implicated in muscle contraction and extracellular matrix organization, respectively. Several critical genes were disclosed, such as MYH11, COL5A2 and ribosomal proteins. Nine relevant small molecule drugs were identified, such as scriptaid and STOCK1N-35874. Accordingly, a total of 17 TFs and 10 miRNAs related to COAD were acquired, such as ETS2, NFAT, AP4, miR-124A, MiR-9, miR-96 and let-7. Several critical genes and relevant drugs, TFs and miRNAs were revealed in COAD. These findings could advance the understanding of the disease and benefit therapy development.

IL-1β, But Not Programed Death-1 and Programed Death Ligand Pathway, Is Critical for the Human Th17 Response to Mycobacterium tuberculosis

Science.gov (United States)

Stephen-Victor, Emmanuel; Sharma, Varun Kumar; Das, Mrinmoy; Karnam, Anupama; Saha, Chaitrali; Lecerf, Maxime; Galeotti, Caroline; Kaveri, Srinivas V.; Bayry, Jagadeesh

2016-01-01

The programed death-1 (PD-1)–programed death ligand-1 (PD-L1) and PD-L2 co-inhibitory pathway has been implicated in the evasion strategies of Mycobacterium tuberculosis. Specifically, M. tuberculosis-induced PD-L1 orchestrates expansion of regulatory T cells and suppression of Th1 response. However, the role of PD pathway in regulating Th17 response to M. tuberculosis has not been investigated. In the present report, we demonstrate that M. tuberculosis and M. tuberculosis-derived antigen fractions have differential abilities to mediate human monocyte- and dendritic cell (DC)-mediated Th17 response and were independent of expression of PD-L1 or PD-L2 on aforementioned antigen-presenting cells. Importantly, we observed that blockade of PD-L1 or PD-1 did not significantly modify either the frequencies of Th17 cells or the production of IL-17 from CD4+ T cells though IFN-γ response was significantly enhanced. On the contrary, IL-1β from monocytes and DCs were critical for the Th17 response to M. tuberculosis. Together, our results indicate that IL-1β, but not members of the programed death pathway, is critical for human Th17 response to M. tuberculosis. PMID:27867382

IL-1β but not programmed death-1 and programmed death-ligand pathway is critical for the human Th17 response to M. tuberculosis

Directory of Open Access Journals (Sweden)

Emmanuel Stephen-Victor

2016-11-01

Full Text Available The programmed death-1 (PD-1- programmed death ligand-1 (PD-L1 and PD-L2 co-inhibitory pathway has been implicated in the evasion strategies of Mycobacterium tuberculosis. Specifically, M. tuberculosis-induced PD-L1 orchestrates expansion of regulatory T cells (Tregs and suppression of Th1 response. However, the role of PD pathway in regulating Th17 response to M. tuberculosis has not been investigated. In the present report, we demonstrate that M. tuberculosis and M. tuberculosis-derived antigen fractions have differential abilities to mediate human monocyte and dendritic cell (DC-mediated Th17 response and were independent of expression of PD-L1 or PD-L2 on aforementioned antigen-presenting cells. Importantly, we observed that blockade of PD-L1 or PD-1 did not significantly modify either the frequencies of Th17 cells or the production of IL-17 from CD4+ T cells though IFN-γ response was significantly enhanced. On the contrary, IL-1β from monocytes and DCs were critical for the Th17 response to M. tuberculosis. Together, our results indicate that IL-1β but not members of the programmed death pathway is critical for human Th17 response to M. tuberculosis

Significant Deregulated Pathways in Diabetes Type II Complications Identified through Expression Based Network Biology

Science.gov (United States)

Ukil, Sanchaita; Sinha, Meenakshee; Varshney, Lavneesh; Agrawal, Shipra

Type 2 Diabetes is a complex multifactorial disease, which alters several signaling cascades giving rise to serious complications. It is one of the major risk factors for cardiovascular diseases. The present research work describes an integrated functional network biology approach to identify pathways that get transcriptionally altered and lead to complex complications thereby amplifying the phenotypic effect of the impaired disease state. We have identified two sub-network modules, which could be activated under abnormal circumstances in diabetes. Present work describes key proteins such as P85A and SRC serving as important nodes to mediate alternate signaling routes during diseased condition. P85A has been shown to be an important link between stress responsive MAPK and CVD markers involved in fibrosis. MAPK8 has been shown to interact with P85A and further activate CTGF through VEGF signaling. We have traced a novel and unique route correlating inflammation and fibrosis by considering P85A as a key mediator of signals. The next sub-network module shows SRC as a junction for various signaling processes, which results in interaction between NF-kB and beta catenin to cause cell death. The powerful interaction between these important genes in response to transcriptionally altered lipid metabolism and impaired inflammatory response via SRC causes apoptosis of cells. The crosstalk between inflammation, lipid homeostasis and stress, and their serious effects downstream have been explained in the present analyses.

Using Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways

Directory of Open Access Journals (Sweden)

Sébastien De Landtsheer

2018-05-01

Full Text Available Understanding the functional properties of cells of different origins is a long-standing challenge of personalized medicine. Especially in cancer, the high heterogeneity observed in patients slows down the development of effective cures. The molecular differences between cell types or between healthy and diseased cellular states are usually determined by the wiring of regulatory networks. Understanding these molecular and cellular differences at the systems level would improve patient stratification and facilitate the design of rational intervention strategies. Models of cellular regulatory networks frequently make weak assumptions about the distribution of model parameters across cell types or patients. These assumptions are usually expressed in the form of regularization of the objective function of the optimization problem. We propose a new method of regularization for network models of signaling pathways based on the local density of the inferred parameter values within the parameter space. Our method reduces the complexity of models by creating groups of cell line-specific parameters which can then be optimized together. We demonstrate the use of our method by recovering the correct topology and inferring accurate values of the parameters of a small synthetic model. To show the value of our method in a realistic setting, we re-analyze a recently published phosphoproteomic dataset from a panel of 14 colon cancer cell lines. We conclude that our method efficiently reduces model complexity and helps recovering context-specific regulatory information.

Maintaining relationships is critical in network's success.

Science.gov (United States)

Huerta, Timothy

2006-01-01

As the authors of the lead paper recognize, networks have become an increasingly popular form of organizing, both in the delivery of public services and within political arenas. A network is an arrangement of individuals and/or organizations that are linked through connections that range from informal relationships to formally agreed protocols. Networks have proved useful in addressing complex and intractable problems that require a holistic approach to identifying and implementing long-term solutions. They succeed in situations where hierarchies and "silo-based" systems have failed, and are particularly valuable in facilitating the transfer of resources and knowledge across sectoral and organizational boundaries.

Info-Gap robustness pathway method for transitioning of urban drainage systems under deep uncertainties.

Science.gov (United States)

Zischg, Jonatan; Goncalves, Mariana L R; Bacchin, Taneha Kuzniecow; Leonhardt, Günther; Viklander, Maria; van Timmeren, Arjan; Rauch, Wolfgang; Sitzenfrei, Robert

2017-09-01

In the urban water cycle, there are different ways of handling stormwater runoff. Traditional systems mainly rely on underground piped, sometimes named 'gray' infrastructure. New and so-called 'green/blue' ambitions aim for treating and conveying the runoff at the surface. Such concepts are mainly based on ground infiltration and temporal storage. In this work a methodology to create and compare different planning alternatives for stormwater handling on their pathways to a desired system state is presented. Investigations are made to assess the system performance and robustness when facing the deeply uncertain spatial and temporal developments in the future urban fabric, including impacts caused by climate change, urbanization and other disruptive events, like shifts in the network layout and interactions of 'gray' and 'green/blue' structures. With the Info-Gap robustness pathway method, three planning alternatives are evaluated to identify critical performance levels at different stages over time. This novel methodology is applied to a real case study problem where a city relocation process takes place during the upcoming decades. In this case study it is shown that hybrid systems including green infrastructures are more robust with respect to future uncertainties, compared to traditional network design.

The Influence of Social Networks and Supports on Depression Symptoms: Differential Pathways for Older Korean Immigrants and Non-Hispanic White Americans.

Science.gov (United States)

Jeon, Haesang; Lubben, James

The current cross-cultural study examines the pathways underlying different formations of social networks and social support systems, which affect depression symptoms among older Korean immigrants and non-Hispanic Whites in the United States. Data for this study came from a panel survey of 223 older Korean American immigrants and 201 non-Hispanic White older adults 65 years of age and older living in Los Angeles. Structural equation modeling (SEM) is used to test the proposed conceptual model designed to explain the direct and indirect relationships between social networks and social support on depression symptoms. Empirical evidence from this study indicated different effect of one's social networks and social support on depression by race/ethnicity. The work discussed in this article pointed to the need to recognize the role of culture in assessing the relationships between social networks, social support, and health among older adults.

Rising utilization of inpatient pediatric asthma pathways.

Science.gov (United States)

Kaiser, Sunitha V; Rodean, Jonathan; Bekmezian, Arpi; Hall, Matt; Shah, Samir S; Mahant, Sanjay; Parikh, Kavita; Morse, Rustin; Puls, Henry; Cabana, Michael D

2018-02-01

Clinical pathways are detailed care plans that operationalize evidence-based guidelines into an accessible format for health providers. Their goal is to link evidence to practice to optimize patient outcomes and delivery efficiency. It is unknown to what extent inpatient pediatric asthma pathways are being utilized nationally. (1) Describe inpatient pediatric asthma pathway design and implementation across a large hospital network. (2) Compare characteristics of hospitals with and without pathways. We conducted a descriptive, cross-sectional, survey study of hospitals in the Pediatric Research in Inpatient Settings Network (75% children's hospitals, 25% community hospitals). Our survey determined if each hospital used a pathway and pathway characteristics (e.g. pathway elements, implementation methods). Hospitals with and without pathways were compared using Chi-square tests (categorical variables) and Student's t-tests (continuous variables). Surveys were distributed to 3-5 potential participants from each hospital and 302 (74%) participants responded, representing 86% (106/123) of surveyed hospitals. From 2005-2015, the proportion of hospitals utilizing inpatient asthma pathways increased from 27% to 86%. We found variation in pathway elements, implementation strategies, electronic medical record integration, and compliance monitoring across hospitals. Hospitals with pathways had larger inpatient pediatric programs [mean 12.1 versus 6.1 full-time equivalents, p = 0.04] and were more commonly free-standing children's hospitals (52% versus 23%, p = 0.05). From 2005-2015, there was a dramatic rise in implementation of inpatient pediatric asthma pathways. We found variation in many aspects of pathway design and implementation. Future studies should determine optimal implementation strategies to better support hospital-level efforts in improving pediatric asthma care and outcomes.

Modeling evolution of crosstalk in noisy signal transduction networks

Science.gov (United States)

Tareen, Ammar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

2018-02-01

Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

The c-Jun N-terminal kinase pathway is critical for cell transformation by the latent membrane protein 1 of Epstein-Barr virus

International Nuclear Information System (INIS)

Kutz, Helmut; Reisbach, Gilbert; Schultheiss, Ute; Kieser, Arnd

2008-01-01

The latent membrane protein 1 (LMP1) of Epstein-Barr virus (EBV) transforms cells activating signal transduction pathways such as NF-κB, PI3-kinase, or c-Jun N-terminal kinase (JNK). Here, we investigated the functional role of the LMP1-induced JNK pathway in cell transformation. Expression of a novel dominant-negative JNK1 allele caused a block of proliferation in LMP1-transformed Rat1 fibroblasts. The JNK-specific inhibitor SP600125 reproduced this effect in Rat1-LMP1 cells and efficiently interfered with proliferation of EBV-transformed lymphoblastoid cells (LCLs). Inhibition of the LMP1-induced JNK pathway in LCLs caused the downregulation of c-Jun and Cdc2, the essential G2/M cell cycle kinase, which was accompanied by a cell cycle arrest of LCLs at G2/M phase transition. Moreover, SP600125 retarded tumor growth of LCLs in a xenograft model in SCID mice. Our data support a critical role of the LMP1-induced JNK pathway for proliferation of LMP1-transformed cells and characterize JNK as a potential target for intervention against EBV-induced malignancies

Mathematical Teaching Strategies: Pathways to Critical Thinking and Metacognition

Science.gov (United States)

Su, Hui Fang Huang; Ricci, Frederick A.; Mnatsakanian, Mamikon

2016-01-01

A teacher that emphasizes reasoning, logic and validity gives their students access to mathematics as an effective way of practicing critical thinking. All students have the ability to enhance and expand their critical thinking when learning mathematics. Students can develop this ability when confronting mathematical problems, identifying possible…

Effect of curcumin on aged Drosophila melanogaster: a pathway prediction analysis.

Science.gov (United States)

Zhang, Zhi-guo; Niu, Xu-yan; Lu, Ai-ping; Xiao, Gary Guishan

2015-02-01

To re-analyze the data published in order to explore plausible biological pathways that can be used to explain the anti-aging effect of curcumin. Microarray data generated from other study aiming to investigate effect of curcumin on extending lifespan of Drosophila melanogaster were further used for pathway prediction analysis. The differentially expressed genes were identified by using GeneSpring GX with a criterion of 3.0-fold change. Two Cytoscape plugins including BisoGenet and molecular complex detection (MCODE) were used to establish the protein-protein interaction (PPI) network based upon differential genes in order to detect highly connected regions. The function annotation clustering tool of Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for pathway analysis. A total of 87 genes expressed differentially in D. melanogaster melanogaster treated with curcumin were identified, among which 50 were up-regulated significantly and 37 were remarkably down-regulated in D. melanogaster melanogaster treated with curcumin. Based upon these differential genes, PPI network was constructed with 1,082 nodes and 2,412 edges. Five highly connected regions in PPI networks were detected by MCODE algorithm, suggesting anti-aging effect of curcumin may be underlined through five different pathways including Notch signaling pathway, basal transcription factors, cell cycle regulation, ribosome, Wnt signaling pathway, and p53 pathway. Genes and their associated pathways in D. melanogaster melanogaster treated with anti-aging agent curcumin were identified using PPI network and MCODE algorithm, suggesting that curcumin may be developed as an alternative therapeutic medicine for treating aging-associated diseases.

OZCAR: the French network of Critical Zone Observatories: principles and scientific objectives

Science.gov (United States)

Braud, Isabelle; Gaillardet, Jérôme; Hankard, Fatim; Le Borgne, Tanguy; Nord, Guillaume; Six, Delphine; Galy, Catherine; Laggoun-Défarge, Fatima; Tallec, Tiphaine; Pauwels, Hélène

2017-04-01

This contribution aims at presenting the principles that underlined the creation of the OZCAR research infrastructure, gathering various Critical Zone Observatories in France, and the scientific questions that drives the observation settings. The Critical Zone includes the fine zone between the lower atmosphere at the top of the canopy down to the bedrock-soil interface. This lithosphere-atmosphere boundary is critical for the availability of life-sustaining resources and critical for humanity because this is the zone where we live, where we build our cities, from which we extract our food and our water and where we release most of our wastes. This is the fragile zone on which the natural ecosystem relies because this is where nutrients are being released from the rocks. OZCAR is a distributed research infrastructure gathering instrumented sites and catchments on continental surfaces all dedicated to the observation and monitoring of the different compartments of the Critical Zone at the national scale. All these observatories (more that 40) were all built up on specific questions (acid deposition, flood prediction, urban hydrology…), some of them more than 50 years ago, but they have all in common to be highly instrumented, permanently funded as infrastructures. They all share the same overarching goal of understanding and predicting the Critical Zone in a changing world. OZCAR gathers instrumented catchments, hydrogeological sites, peatlands, glacier and permafrost regions and a spatial observatory under the common umbrella of understanding water and biogeochemical cycles and the associated fluxes of energy by using natural gradients and experimentation. Based on the collaboration with Southern Countries, OZCAR's sites have a global coverage including tropical areas and high mountainous regions in the Andes and the Himalaya. OZCAR benefits from a French investments project called CRITEX (Innovative equipment for the critical zone, https://www.critex.fr/critex-3

Magnocellular pathway for rotation invariant Neocognitron.

Science.gov (United States)

Ting, C H

1993-03-01

In the mammalian visual system, magnocellular pathway and parvocellular pathway cooperatively process visual information in parallel. The magnocellular pathway is more global and less particular about the details while the parvocellular pathway recognizes objects based on the local features. In many aspects, Neocognitron may be regarded as the artificial analogue of the parvocellular pathway. It is interesting then to model the magnocellular pathway. In order to achieve "rotation invariance" for Neocognitron, we propose a neural network model after the magnocellular pathway and expand its roles to include surmising the orientation of the input pattern prior to recognition. With the incorporation of the magnocellular pathway, a basic shift in the original paradigm has taken place. A pattern is now said to be recognized when and only when one of the winners of the magnocellular pathway is validified by the parvocellular pathway. We have implemented the magnocellular pathway coupled with Neocognitron parallel on transputers; our simulation programme is now able to recognize numerals in arbitrary orientation.

Microbial Disruption of Autophagy Alters Expression of the RISC Component AGO2, a Critical Regulator of the miRNA Silencing Pathway.

Science.gov (United States)

Sibony, Michal; Abdullah, Majd; Greenfield, Laura; Raju, Deepa; Wu, Ted; Rodrigues, David M; Galindo-Mata, Esther; Mascarenhas, Heidi; Philpott, Dana J; Silverberg, Mark S; Jones, Nicola L

2015-12-01

Autophagy is implicated in Crohn's disease (CD) pathogenesis. Recent evidence suggests autophagy regulates the microRNA (miRNA)-induced silencing complex (miRISC). Therefore, autophagy may play a novel role in CD by regulating expression of miRISC, thereby altering miRNA silencing. As microbes associated with CD can alter autophagy, we hypothesized that microbial disruption of autophagy affects the critical miRISC component AGO2. AGO2 expression was assessed in epithelial and immune cells, and intestinal organoids with disrupted autophagy. Microarray technology was used to determine the expression of downstream miRNAs in cells with defective autophagy. Increased AGO2 was detected in autophagy-deficient ATG5-/- and ATG16-/- mouse embryonic fibroblast cells (MEFs) in comparison with wild-type MEFs. Chemical agents and VacA toxin, which disrupt autophagy, increased AGO2 expression in MEFs, epithelial cells lines, and human monocytes, respectively. Increased AGO2 was also detected in ATG7-/- intestinal organoids, in comparison with wild-type organoids. Five miRNAs were differentially expressed in autophagy-deficient MEFs. Pathway enrichment analysis of the differentially expressed miRNAs implicated signaling pathways previously associated with CD. Taken together, our results suggest that autophagy is involved in the regulation of the critical miRISC component AGO2 in epithelial and immune cells and primary intestinal epithelial cells. We propose a mechanism by which autophagy alters miRNA expression, which likely impacts the regulation of CD-associated pathways. Furthermore, as enteric microbial products can manipulate autophagy and AGO2, our findings suggest a novel mechanism by which enteric microbes could influence miRNA to promote disease.

Critical heat flux prediction by using radial basis function and multilayer perceptron neural networks: A comparison study

International Nuclear Information System (INIS)

Vaziri, Nima; Hojabri, Alireza; Erfani, Ali; Monsefi, Mehrdad; Nilforooshan, Behnam

2007-01-01

Critical heat flux (CHF) is an important parameter for the design of nuclear reactors. Although many experimental and theoretical researches have been performed, there is not a single correlation to predict CHF because it is influenced by many parameters. These parameters are based on fixed inlet, local and fixed outlet conditions. Artificial neural networks (ANNs) have been applied to a wide variety of different areas such as prediction, approximation, modeling and classification. In this study, two types of neural networks, radial basis function (RBF) and multilayer perceptron (MLP), are trained with the experimental CHF data and their performances are compared. RBF predicts CHF with root mean square (RMS) errors of 0.24%, 7.9%, 0.16% and MLP predicts CHF with RMS errors of 1.29%, 8.31% and 2.71%, in fixed inlet conditions, local conditions and fixed outlet conditions, respectively. The results show that neural networks with RBF structure have superior performance in CHF data prediction over MLP neural networks. The parametric trends of CHF obtained by the trained ANNs are also evaluated and results reported

Temporal network based analysis of cell specific vein graft transcriptome defines key pathways and hub genes in implantation injury.

Directory of Open Access Journals (Sweden)

Manoj Bhasin

Full Text Available Vein graft failure occurs between 1 and 6 months after implantation due to obstructive intimal hyperplasia, related in part to implantation injury. The cell-specific and temporal response of the transcriptome to vein graft implantation injury was determined by transcriptional profiling of laser capture microdissected endothelial cells (EC and medial smooth muscle cells (SMC from canine vein grafts, 2 hours (H to 30 days (D following surgery. Our results demonstrate a robust genomic response beginning at 2 H, peaking at 12-24 H, declining by 7 D, and resolving by 30 D. Gene ontology and pathway analyses of differentially expressed genes indicated that implantation injury affects inflammatory and immune responses, apoptosis, mitosis, and extracellular matrix reorganization in both cell types. Through backpropagation an integrated network was built, starting with genes differentially expressed at 30 D, followed by adding upstream interactive genes from each prior time-point. This identified significant enrichment of IL-6, IL-8, NF-κB, dendritic cell maturation, glucocorticoid receptor, and Triggering Receptor Expressed on Myeloid Cells (TREM-1 signaling, as well as PPARα activation pathways in graft EC and SMC. Interactive network-based analyses identified IL-6, IL-8, IL-1α, and Insulin Receptor (INSR as focus hub genes within these pathways. Real-time PCR was used for the validation of two of these genes: IL-6 and IL-8, in addition to Collagen 11A1 (COL11A1, a cornerstone of the backpropagation. In conclusion, these results establish causality relationships clarifying the pathogenesis of vein graft implantation injury, and identifying novel targets for its prevention.

Updating the Wnt pathways

Science.gov (United States)

Yu, Jia; Virshup, David M.

2014-01-01

In the three decades since the discovery of the Wnt1 proto-oncogene in virus-induced mouse mammary tumours, our understanding of the signalling pathways that are regulated by the Wnt proteins has progressively expanded. Wnts are involved in an complex signalling network that governs multiple biological processes and cross-talk with multiple additional signalling cascades, including the Notch, FGF (fibroblast growth factor), SHH (Sonic hedgehog), EGF (epidermal growth factor) and Hippo pathways. The Wnt signalling pathway also illustrates the link between abnormal regulation of the developmental processes and disease manifestation. Here we provide an overview of Wnt-regulated signalling cascades and highlight recent advances. We focus on new findings regarding the dedicated Wnt production and secretion pathway with potential therapeutic targets that might be beneficial for patients with Wnt-related diseases. PMID:25208913

HIF-VEGF pathways are critical for chronic otitis media in Junbo and Jeff mouse mutants.

Directory of Open Access Journals (Sweden)

Michael T Cheeseman

2011-10-01

Full Text Available Otitis media with effusion (OME is the commonest cause of hearing loss in children, yet the underlying genetic pathways and mechanisms involved are incompletely understood. Ventilation of the middle ear with tympanostomy tubes is the commonest surgical procedure in children and the best treatment for chronic OME, but the mechanism by which they work remains uncertain. As hypoxia is a common feature of inflamed microenvironments, moderation of hypoxia may be a significant contributory mechanism. We have investigated the occurrence of hypoxia and hypoxia-inducible factor (HIF mediated responses in Junbo and Jeff mouse mutant models, which develop spontaneous chronic otitis media. We found that Jeff and Junbo mice labeled in vivo with pimonidazole showed cellular hypoxia in inflammatory cells in the bulla lumen, and in Junbo the middle ear mucosa was also hypoxic. The bulla fluid inflammatory cell numbers were greater and the upregulation of inflammatory gene networks were more pronounced in Junbo than Jeff. Hif-1α gene expression was elevated in bulla fluid inflammatory cells, and there was upregulation of its target genes including Vegfa in Junbo and Jeff. We therefore investigated the effects in Junbo of small-molecule inhibitors of VEGFR signaling (PTK787, SU-11248, and BAY 43-9006 and destabilizing HIF by inhibiting its chaperone HSP90 with 17-DMAG. We found that both classes of inhibitor significantly reduced hearing loss and the occurrence of bulla fluid and that VEGFR inhibitors moderated angiogenesis and lymphangiogenesis in the inflamed middle ear mucosa. The effectiveness of HSP90 and VEGFR signaling inhibitors in suppressing OM in the Junbo model implicates HIF-mediated VEGF as playing a pivotal role in OM pathogenesis. Our analysis of the Junbo and Jeff mutants highlights the role of hypoxia and HIF-mediated pathways, and we conclude that targeting molecules in HIF-VEGF signaling pathways has therapeutic potential in the treatment of

Domination criticality in product graphs

Directory of Open Access Journals (Sweden)

M.R. Chithra

2015-07-01

Full Text Available A connected dominating set is an important notion and has many applications in routing and management of networks. Graph products have turned out to be a good model of interconnection networks. This motivated us to study the Cartesian product of graphs G with connected domination number, γc(G=2,3 and characterize such graphs. Also, we characterize the k−γ-vertex (edge critical graphs and k−γc-vertex (edge critical graphs for k=2,3 where γ denotes the domination number of G. We also discuss the vertex criticality in grids.

Pathways to deep decarbonization - Interim 2014 Report

International Nuclear Information System (INIS)

2014-01-01

The interim 2014 report by the Deep Decarbonization Pathways Project (DDPP), coordinated and published by IDDRI and the Sustainable Development Solutions Network (SDSN), presents preliminary findings of the pathways developed by the DDPP Country Research Teams with the objective of achieving emission reductions consistent with limiting global warming to less than 2 deg. C. The DDPP is a knowledge network comprising 15 Country Research Teams and several Partner Organizations who develop and share methods, assumptions, and findings related to deep decarbonization. Each DDPP Country Research Team has developed an illustrative road-map for the transition to a low-carbon economy, with the intent of taking into account national socio-economic conditions, development aspirations, infrastructure stocks, resource endowments, and other relevant factors. The interim 2014 report focuses on technically feasible pathways to deep decarbonization

On the performance of de novo pathway enrichment

DEFF Research Database (Denmark)

Batra, Richa; Alcaraz, Nicolas; Gitzhofer, Kevin

2017-01-01

De novo pathway enrichment is a powerful approach to discover previously uncharacterized molecular mechanisms in addition to already known pathways. To achieve this, condition-specific functional modules are extracted from large interaction networks. Here, we give an overview of the state...

Pathway enrichment analysis approach based on topological structure and updated annotation of pathway.

Science.gov (United States)

Yang, Qian; Wang, Shuyuan; Dai, Enyu; Zhou, Shunheng; Liu, Dianming; Liu, Haizhou; Meng, Qianqian; Jiang, Bin; Jiang, Wei

2017-08-16

Pathway enrichment analysis has been widely used to identify cancer risk pathways, and contributes to elucidating the mechanism of tumorigenesis. However, most of the existing approaches use the outdated pathway information and neglect the complex gene interactions in pathway. Here, we first reviewed the existing widely used pathway enrichment analysis approaches briefly, and then, we proposed a novel topology-based pathway enrichment analysis (TPEA) method, which integrated topological properties and global upstream/downstream positions of genes in pathways. We compared TPEA with four widely used pathway enrichment analysis tools, including database for annotation, visualization and integrated discovery (DAVID), gene set enrichment analysis (GSEA), centrality-based pathway enrichment (CePa) and signaling pathway impact analysis (SPIA), through analyzing six gene expression profiles of three tumor types (colorectal cancer, thyroid cancer and endometrial cancer). As a result, we identified several well-known cancer risk pathways that could not be obtained by the existing tools, and the results of TPEA were more stable than that of the other tools in analyzing different data sets of the same cancer. Ultimately, we developed an R package to implement TPEA, which could online update KEGG pathway information and is available at the Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/TPEA/. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Fault-Tree Modeling of Safety-Critical Network Communication in a Digitalized Nuclear Power Plant

Energy Technology Data Exchange (ETDEWEB)

Lee, Sang Hun; Kang, Hyun Gook [KAIST, Daejeon (Korea, Republic of)

2015-10-15

To achieve technical self-reliance for nuclear I and C systems in Korea, the Advanced Power Reactor 1400 (APR-1400) man-machine interface system (MMIS) architecture was developed by the Korea Atomic Energy Research Institute (KAERI). As one of the systems in the developed MMIS architecture, the Engineered Safety Feature-Component Control System (ESF-CCS) employs a network communication system for the transmission of safety-critical information from group controllers (GCs) to loop controllers (LCs) to effectively accommodate the vast number of field controllers. The developed fault-tree model was then applied to several case studies. As an example of the development of a fault-tree model for ESF-CCS signal failure, the fault-tree model of ESF-CCS signal failure for CS pump PP01A in the CSAS condition was designed by considering the identified hazardous states of network failure that would result in a failure to provide input signals to the corresponding LC. The quantitative results for four case studies demonstrated that the probability of overall network communication failure, which was calculated as the sum of the failure probability associated with each failure cause, contributes up to 1.88% of the probability of ESF-CCS signal failure for the CS pump considered in the case studies.

A Microsoft-Excel-based tool for running and critically appraising network meta-analyses--an overview and application of NetMetaXL.

Science.gov (United States)

Brown, Stephen; Hutton, Brian; Clifford, Tammy; Coyle, Doug; Grima, Daniel; Wells, George; Cameron, Chris

2014-09-29

The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL's interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows for more efficient and transparent

A Microsoft-Excel-based tool for running and critically appraising network meta-analyses—an overview and application of NetMetaXL

Science.gov (United States)

2014-01-01

Background The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. Methods We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL’s interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. Results We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. Conclusions Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows

Prediction is difficult, preparation is critical and possible

DEFF Research Database (Denmark)

Zilli, Romano; Dalton, Luke; Ooms, Wim

at the level of the source of infection, transmission pathways, and the outcomes. Changes to such challenges and uncertainties are inevitable and foresight in identifying strategies is required for us to prepare for a sustainable future. The EU-funded Global Network on Infectious Diseases of Animals...... and technological needs, including research capacity and support structures to prevent, control or mitigate animal health and zoonotic challenges for 2030 and beyond. While our ability to predict the future is often limited, being prepared to engage with whatever may happen is critical. Methods: Foresight workshops...... to give an overall list in which transnational data sharing, knowledge transfer, public-private partnerships, vaccinology/immunology, vector control, antimicrobial resistance, socioeconomics, genetics/bioinformatics and utilisation of big data rated highly. Conclusion: The outputs of the STAR...

Telecommunication Networks

DEFF Research Database (Denmark)

Olsen, Rasmus Løvenstein; Balachandran, Kartheepan; Hald, Sara Ligaard

2014-01-01

In this chapter, we look into the role of telecommunication networks and their capability of supporting critical infrastructure systems and applications. The focus is on smart grids as the key driving example, bearing in mind that other such systems do exist, e.g., water management, traffic control......, etc. First, the role of basic communication is examined with a focus on critical infrastructures. We look at heterogenic networks and standards for smart grids, to give some insight into what has been done to ensure inter-operability in this direction. We then go to the physical network, and look...... threats to the critical infrastructure. Finally, before our conclusions and outlook, we give a brief overview of some key activities in the field and what research directions are currently investigated....

Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort.

Science.gov (United States)

Cong, Wang; Meng, Xianglian; Li, Jin; Zhang, Qiushi; Chen, Feng; Liu, Wenjie; Wang, Ying; Cheng, Sipu; Yao, Xiaohui; Yan, Jingwen; Kim, Sungeun; Saykin, Andrew J; Liang, Hong; Shen, Li

2017-05-30

The cerebrospinal fluid (CSF) levels of total tau (t-tau) and Aβ 1-42 are potential early diagnostic markers for probable Alzheimer's disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this study is to gain further biological insights via the integration of statistical gene associations in AD with physical protein interaction networks. The CSF and genotyping data of 843 study subjects (199 CN, 85 SMC, 239 EMCI, 207 LMCI, 113 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were analyzed. PLINK was used to perform GWAS on the t-tau/Aβ 1-42 ratio using quality controlled genotype data, including 563,980 single nucleotide polymorphisms (SNPs), with age, sex and diagnosis as covariates. Gene-level p-values were obtained by VEGAS2. Genes with p-value ≤ 0.05 were mapped on to a protein-protein interaction (PPI) network (9,617 nodes, 39,240 edges, from the HPRD Database). We integrated a consensus model strategy into the iPINBPA network analysis framework, and named it as CM-iPINBPA. Four consensus modules (CMs) were discovered by CM-iPINBPA, and were functionally annotated using the pathway analysis tool Enrichr. The intersection of four CMs forms a common subnetwork of 29 genes, including those related to tau phosphorylation (GSK3B, SUMO1, AKAP5, CALM1 and DLG4), amyloid beta production (CASP8, PIK3R1, PPA1, PARP1, CSNK2A1, NGFR, and RHOA), and AD (BCL3, CFLAR, SMAD1, and HIF1A). This study coupled a consensus module (CM) strategy with the iPINBPA network analysis framework, and applied it to the GWAS of CSF t-tau/Aβ1-42 ratio in an AD study. The genome-wide network analysis yielded 4 enriched CMs that share not only genes related to tau phosphorylation or amyloid beta

Topology-induced critical current enhancement in Josephson networks

International Nuclear Information System (INIS)

Silvestrini, P.; Russo, R.; Corato, V.; Ruggiero, B.; Granata, C.; Rombetto, S.; Russo, M.; Cirillo, M.; Trombettoni, A.; Sodano, P.

2007-01-01

We investigate the properties of Josephson junction networks with inhomogeneous architecture. The networks are shaped as 'square comb' planar lattices on which Josephson junctions link superconducting islands arranged in the plane to generate the pertinent topology. Compared to the behavior of reference linear arrays, the temperature dependencies of the Josephson currents of the branches of the network exhibit relevant differences. The observed phenomena evidence new and surprising behavior of superconducting Josephson arrays

Topology-induced critical current enhancement in Josephson networks

Energy Technology Data Exchange (ETDEWEB)

Silvestrini, P. [Dipartimento d' Ingegneria dell' Informazione, Seconda Universita di Napoli, Aversa (Italy); Istituto di Cibernetica ' E. Caianiello' del CNR, Pozzuoli (Italy)], E-mail: p.silvestrini@cib.na.cnr.it; Russo, R. [Istituto di Cibernetica ' E. Caianiello' del CNR, Pozzuoli (Italy); Corato, V. [Dipartimento d' Ingegneria dell' Informazione, Seconda Universita di Napoli, Aversa (Italy); Ruggiero, B.; Granata, C.; Rombetto, S.; Russo, M. [Istituto di Cibernetica ' E. Caianiello' del CNR, Pozzuoli (Italy); Cirillo, M. [Dipartimento di Fisica and INFM, Universita di Roma ' Tor Vergata' , 00173 Roma (Italy); Trombettoni, A. [International School for Advanced Studies and Sezione INFN, Via Beirut 2/4, 34104 Trieste (Italy); Sodano, P. [International School for Advanced Studies and Sezione INFN, Via Beirut 2/4, 34104 Trieste (Italy); Dipartimento di Fisica, Universita di Perugia, 06123 Perugia, and Sezione INFN, Perugia (Italy); Progetto Lagrange, Fondazione C.R.T. e Fondazione I.S.I., Dipartimento di Fisica, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10124 Torino (Italy)

2007-10-29

We investigate the properties of Josephson junction networks with inhomogeneous architecture. The networks are shaped as 'square comb' planar lattices on which Josephson junctions link superconducting islands arranged in the plane to generate the pertinent topology. Compared to the behavior of reference linear arrays, the temperature dependencies of the Josephson currents of the branches of the network exhibit relevant differences. The observed phenomena evidence new and surprising behavior of superconducting Josephson arrays.

The endocytic pathways of a secretory granule membrane protein in HEK293 cells: PAM and EGF traverse a dynamic multivesicular body network together.

Science.gov (United States)

Bäck, Nils; Kanerva, Kristiina; Kurutihalli, Vishwanatha; Yanik, Andrew; Ikonen, Elina; Mains, Richard E; Eipper, Betty A

2017-08-01

Peptidylglycine α-amidating monooxygenase (PAM) is highly expressed in neurons and endocrine cells, where it catalyzes one of the final steps in the biosynthesis of bioactive peptides. PAM is also expressed in unicellular organisms such as Chlamydomonas reinhardtii, which do not store peptides in secretory granules. As for other granule membrane proteins, PAM is retrieved from the cell surface and returned to the trans-Golgi network. This pathway involves regulated entry of PAM into multivesicular body intralumenal vesicles (ILVs). The aim of this study was defining the endocytic pathways utilized by PAM in cells that do not store secretory products in granules. Using stably transfected HEK293 cells, endocytic trafficking of PAM was compared to that of the mannose 6-phosphate (MPR) and EGF (EGFR) receptors, established markers for the endosome to trans-Golgi network and degradative pathways, respectively. As in neuroendocrine cells, PAM internalized by HEK293 cells accumulated in the trans-Golgi network. Based on surface biotinylation, >70% of the PAM on the cell surface was recovered intact after a 4h chase and soluble, bifunctional PAM was produced. Endosomes containing PAM generally contained both EGFR and MPR and ultrastructural analysis confirmed that all three cargos accumulated in ILVs. PAM containing multivesicular bodies made frequent dynamic tubular contacts with younger and older multivesicular bodies. Frequent dynamic contacts were observed between lysosomes and PAM containing early endosomes and multivesicular bodies. The ancient ability of PAM to localize to ciliary membranes, which release bioactive ectosomes, may be related to its ability to accumulate in ILVs and exosomes. Copyright © 2017 Elsevier GmbH. All rights reserved.

Inferring regulatory networks from experimental morphological phenotypes: a computational method reverse-engineers planarian regeneration.

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Daniel Lobo

2015-06-01

Full Text Available Transformative applications in biomedicine require the discovery of complex regulatory networks that explain the development and regeneration of anatomical structures, and reveal what external signals will trigger desired changes of large-scale pattern. Despite recent advances in bioinformatics, extracting mechanistic pathway models from experimental morphological data is a key open challenge that has resisted automation. The fundamental difficulty of manually predicting emergent behavior of even simple networks has limited the models invented by human scientists to pathway diagrams that show necessary subunit interactions but do not reveal the dynamics that are sufficient for complex, self-regulating pattern to emerge. To finally bridge the gap between high-resolution genetic data and the ability to understand and control patterning, it is critical to develop computational tools to efficiently extract regulatory pathways from the resultant experimental shape phenotypes. For example, planarian regeneration has been studied for over a century, but despite increasing insight into the pathways that control its stem cells, no constructive, mechanistic model has yet been found by human scientists that explains more than one or two key features of its remarkable ability to regenerate its correct anatomical pattern after drastic perturbations. We present a method to infer the molecular products, topology, and spatial and temporal non-linear dynamics of regulatory networks recapitulating in silico the rich dataset of morphological phenotypes resulting from genetic, surgical, and pharmacological experiments. We demonstrated our approach by inferring complete regulatory networks explaining the outcomes of the main functional regeneration experiments in the planarian literature; By analyzing all the datasets together, our system inferred the first systems-biology comprehensive dynamical model explaining patterning in planarian regeneration. This method

Incorporation of Spatial Interactions in Location Networks to Identify Critical Geo-Referenced Routes for Assessing Disease Control Measures on a Large-Scale Campus

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Tzai-Hung Wen

2015-04-01

Full Text Available Respiratory diseases mainly spread through interpersonal contact. Class suspension is the most direct strategy to prevent the spread of disease through elementary or secondary schools by blocking the contact network. However, as university students usually attend courses in different buildings, the daily contact patterns on a university campus are complicated, and once disease clusters have occurred, suspending classes is far from an efficient strategy to control disease spread. The purpose of this study is to propose a methodological framework for generating campus location networks from a routine administration database, analyzing the community structure of the network, and identifying the critical links and nodes for blocking respiratory disease transmission. The data comes from the student enrollment records of a major comprehensive university in Taiwan. We combined the social network analysis and spatial interaction model to establish a geo-referenced community structure among the classroom buildings. We also identified the critical links among the communities that were acting as contact bridges and explored the changes in the location network after the sequential removal of the high-risk buildings. Instead of conducting a questionnaire survey, the study established a standard procedure for constructing a location network on a large-scale campus from a routine curriculum database. We also present how a location network structure at a campus could function to target the high-risk buildings as the bridges connecting communities for blocking disease transmission.

Challenges of the information age: the impact of false discovery on pathway identification.

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Rog, Colin J; Chekuri, Srinivasa C; Edgerton, Mary E

2012-11-21

Pathways with members that have known relevance to a disease are used to support hypotheses generated from analyses of gene expression and proteomic studies. Using cancer as an example, the pitfalls of searching pathways databases as support for genes and proteins that could represent false discoveries are explored. The frequency with which networks could be generated from 100 instances each of randomly selected five and ten genes sets as input to MetaCore, a commercial pathways database, was measured. A PubMed search enumerated cancer-related literature published for any gene in the networks. Using three, two, and one maximum intervening step between input genes to populate the network, networks were generated with frequencies of 97%, 77%, and 7% using ten gene sets and 73%, 27%, and 1% using five gene sets. PubMed reported an average of 4225 cancer-related articles per network gene. This can be attributed to the richly populated pathways databases and the interest in the molecular basis of cancer. As information sources become enriched, they are more likely to generate plausible mechanisms for false discoveries.

Pivotal role of the muscle-contraction pathway in cryptorchidism and evidence for genomic connections with cardiomyopathy pathways in RASopathies

KAUST Repository

Cannistraci, Carlo

2013-02-14

Background: Cryptorchidism is the most frequent congenital disorder in male children; however the genetic causes of cryptorchidism remain poorly investigated. Comparative integratomics combined with systems biology approach was employed to elucidate genetic factors and molecular pathways underlying testis descent. Methods. Literature mining was performed to collect genomic loci associated with cryptorchidism in seven mammalian species. Information regarding the collected candidate genes was stored in MySQL relational database. Genomic view of the loci was presented using Flash GViewer web tool (http://gmod.org/wiki/Flashgviewer/). DAVID Bioinformatics Resources 6.7 was used for pathway enrichment analysis. Cytoscape plug-in PiNGO 1.11 was employed for protein-network-based prediction of novel candidate genes. Relevant protein-protein interactions were confirmed and visualized using the STRING database (version 9.0). Results. The developed cryptorchidism gene atlas includes 217 candidate loci (genes, regions involved in chromosomal mutations, and copy number variations) identified at the genomic, transcriptomic, and proteomic level. Human orthologs of the collected candidate loci were presented using a genomic map viewer. The cryptorchidism gene atlas is freely available online: http://www.integratomics-time.com/cryptorchidism/. Pathway analysis suggested the presence of twelve enriched pathways associated with the list of 179 literature-derived candidate genes. Additionally, a list of 43 network-predicted novel candidate genes was significantly associated with four enriched pathways. Joint pathway analysis of the collected and predicted candidate genes revealed the pivotal importance of the muscle-contraction pathway in cryptorchidism and evidence for genomic associations with cardiomyopathy pathways in RASopathies. Conclusions: The developed gene atlas represents an important resource for the scientific community researching genetics of cryptorchidism. The

The networks scale and coupling parameter in synchronization of neural networks with diluted synapses

International Nuclear Information System (INIS)

Li Yanlong; Ma Jun; Chen Yuhong; Xu Wenke; Wang Yinghai

2008-01-01

In this paper the influence of the networks scale on the coupling parameter in the synchronization of neural networks with diluted synapses is investigated. Using numerical simulations, an exponential decay form is observed in the extreme case of global coupling among networks and full connection in each network; the larger linked degree becomes, the larger critical coupling intensity becomes; and the oscillation phenomena in the relationship of critical coupling intensity and the number of neural networks layers in the case of small-scale networks are found

Alternative Cell Death Pathways and Cell Metabolism

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Simone Fulda

2013-01-01

Full Text Available While necroptosis has for long been viewed as an accidental mode of cell death triggered by physical or chemical damage, it has become clear over the last years that necroptosis can also represent a programmed form of cell death in mammalian cells. Key discoveries in the field of cell death research, including the identification of critical components of the necroptotic machinery, led to a revised concept of cell death signaling programs. Several regulatory check and balances are in place in order to ensure that necroptosis is tightly controlled according to environmental cues and cellular needs. This network of regulatory mechanisms includes metabolic pathways, especially those linked to mitochondrial signaling events. A better understanding of these signal transduction mechanisms will likely contribute to open new avenues to exploit our knowledge on the regulation of necroptosis signaling for therapeutic application in the treatment of human diseases.

An algorithm for modularization of MAPK and calcium signaling pathways: comparative analysis among different species.

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Nayak, Losiana; De, Rajat K

2007-12-01

Signaling pathways are large complex biochemical networks. It is difficult to analyze the underlying mechanism of such networks as a whole. In the present article, we have proposed an algorithm for modularization of signal transduction pathways. Unlike studying a signaling pathway as a whole, this enables one to study the individual modules (less complex smaller units) easily and hence to study the entire pathway better. A comparative study of modules belonging to different species (for the same signaling pathway) has been made, which gives an overall idea about development of the signaling pathways over the taken set of species of calcium and MAPK signaling pathways. The superior performance, in terms of biological significance, of the proposed algorithm over an existing community finding algorithm of Newman [Newman MEJ. Modularity and community structure in networks. Proc Natl Acad Sci USA 2006;103(23):8577-82] has been demonstrated using the aforesaid pathways of H. sapiens.

Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

DEFF Research Database (Denmark)

Huang, Sijia; Chong, Nicole; Lewis, Nathan

2016-01-01

diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...... metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease...

Stochasticity in the yeast mating pathway

International Nuclear Information System (INIS)

Hong-Li, Wang; Zheng-Ping, Fu; Xin-Hang, Xu; Qi, Ouyang

2009-01-01

We report stochastic simulations of the yeast mating signal transduction pathway. The effects of intrinsic and external noise, the influence of cell-to-cell difference in the pathway capacity, and noise propagation in the pathway have been examined. The stochastic temporal behaviour of the pathway is found to be robust to the influence of inherent fluctuations, and intrinsic noise propagates in the pathway in a uniform pattern when the yeasts are treated with pheromones of different stimulus strengths and of varied fluctuations. In agreement with recent experimental findings, extrinsic noise is found to play a more prominent role than intrinsic noise in the variability of proteins. The occurrence frequency for the reactions in the pathway are also examined and a more compact network is obtained by dropping most of the reactions of least occurrence

Comparative study of ion conducting pathways in borate glasses

International Nuclear Information System (INIS)

Hall, Andreas; Swenson, Jan; Adams, Stefan

2006-01-01

The conduction pathways in metal-halide doped silver, lithium, and sodium diborate glasses have been examined by bond valence analysis of reverse Monte Carlo (RMC) produced structural models of the glasses. Although all glass compositions have basically the same short-range structure of the boron-oxygen network, it is evident that the intermediate-range structure is strongly dependent on the type of mobile ion. The topography of the pathways and the coordination of the pathway sites differ distinctly between the three glass systems. The mobile silver ions in the AgI-doped glass tend to be mainly iodine-coordinated and travel in homogeneously distributed pathways located in salt-rich channels of the borate network. In the NaCl-doped glass, there is an inhomogeneous spatial distribution of pathways that reflects the inhomogeneous introduction of salt ions into the glass. However, since the salt clusters are not connected, no long-range conduction pathways are formed without including also oxygen-rich regions. The pathways in the LiCl-doped glass are slightly more evenly distributed compared to the NaCl-doped glass (but not as ordered as in the AgI-doped glass), and the regions of mainly oxygen-coordinated pathway sites are of higher importance for the long-range migration. In order to more accurately investigate how these differences in the intermediate-range order of the glasses affect the ionic conductivity, we have compared the realistic structure models to more or less randomized structures. An important conclusion from this comparison is that we find no evidence that a pronounced intermediate-range order in the atomic structure or in the network of conduction pathways, as in the AgI-doped glass, is beneficial for the dc conductivity

Toward a standardized soil carbon database platform in the US Critical Zone Observatory Network

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Filley, T. R.; Marini, L.; Todd-Brown, K. E.; Malhotra, A.; Harden, J. W.; Kumar, P.

2017-12-01

Within the soil carbon community of the US Critical Zone Observatory (CZO) Network, efforts are underway to promote network-level data syntheses and modeling projects and to identify barriers to data intercomparability. This represents a challenging goal given the diversity of soil carbon sampling methodologies, spatial and vertical resolution, carbon pool isolation protocols, subsequent measurement techniques, and matrix terminology. During the last annual meeting of the CZO SOC Working Group, Dec 11, 2016, it was decided that integration with, and potentially adoption of, a widely used, active, and mature data aggregation, archival, and visualization platform was the easiest route to achieve this ultimate goal. Additionally, to assess the state of deep and shallow soil C data among the CZO sites it was recommended that a comprehensive survey must be undertaken to identify data gaps and catalog the various soil sampling and analysis methodologies. The International Soil Carbon Network (ISCN) has a long history of leadership in the development of soil C data aggregation, archiving, and visualization tools and currently houses data for over 70,000 soil cores contributed from international soil carbon community. Over the past year, members of the CZO network and the ISCN have met to discuss logistics of adopting the ISCN template within the CZO. Collaborative efforts among all of the CZO site data managers, led by the Intensively Managed Landscapes CZO, will evaluate feasibility of adoption of the ISCN template, or some modification thereof, and distribution to the appropriate soil scientists for data upload and aggregation. Partnering with ISCN also ensures that soil characteristics from the US CZO are placed in a developing global soil context and paves the way for future integration of data from other international CZO networks. This poster will provide an update of this overall effort along with a summary of data products, partnering networks, and recommendations

Evolution of metabolic network organization

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Bonchev Danail

2010-05-01

Full Text Available Abstract Background Comparison of metabolic networks across species is a key to understanding how evolutionary pressures shape these networks. By selecting taxa representative of different lineages or lifestyles and using a comprehensive set of descriptors of the structure and complexity of their metabolic networks, one can highlight both qualitative and quantitative differences in the metabolic organization of species subject to distinct evolutionary paths or environmental constraints. Results We used a novel representation of metabolic networks, termed network of interacting pathways or NIP, to focus on the modular, high-level organization of the metabolic capabilities of the cell. Using machine learning techniques we identified the most relevant aspects of cellular organization that change under evolutionary pressures. We considered the transitions from prokarya to eukarya (with a focus on the transitions among the archaea, bacteria and eukarya, from unicellular to multicellular eukarya, from free living to host-associated bacteria, from anaerobic to aerobic, as well as the acquisition of cell motility or growth in an environment of various levels of salinity or temperature. Intuitively, we expect organisms with more complex lifestyles to have more complex and robust metabolic networks. Here we demonstrate for the first time that such organisms are not only characterized by larger, denser networks of metabolic pathways but also have more efficiently organized cross communications, as revealed by subtle changes in network topology. These changes are unevenly distributed among metabolic pathways, with specific categories of pathways being promoted to more central locations as an answer to environmental constraints. Conclusions Combining methods from graph theory and machine learning, we have shown here that evolutionary pressures not only affects gene and protein sequences, but also specific details of the complex wiring of functional modules

Optimal structural inference of signaling pathways from unordered and overlapping gene sets.

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Acharya, Lipi R; Judeh, Thair; Wang, Guangdi; Zhu, Dongxiao

2012-02-15

A plethora of bioinformatics analysis has led to the discovery of numerous gene sets, which can be interpreted as discrete measurements emitted from latent signaling pathways. Their potential to infer signaling pathway structures, however, has not been sufficiently exploited. Existing methods accommodating discrete data do not explicitly consider signal cascading mechanisms that characterize a signaling pathway. Novel computational methods are thus needed to fully utilize gene sets and broaden the scope from focusing only on pairwise interactions to the more general cascading events in the inference of signaling pathway structures. We propose a gene set based simulated annealing (SA) algorithm for the reconstruction of signaling pathway structures. A signaling pathway structure is a directed graph containing up to a few hundred nodes and many overlapping signal cascades, where each cascade represents a chain of molecular interactions from the cell surface to the nucleus. Gene sets in our context refer to discrete sets of genes participating in signal cascades, the basic building blocks of a signaling pathway, with no prior information about gene orderings in the cascades. From a compendium of gene sets related to a pathway, SA aims to search for signal cascades that characterize the optimal signaling pathway structure. In the search process, the extent of overlap among signal cascades is used to measure the optimality of a structure. Throughout, we treat gene sets as random samples from a first-order Markov chain model. We evaluated the performance of SA in three case studies. In the first study conducted on 83 KEGG pathways, SA demonstrated a significantly better performance than Bayesian network methods. Since both SA and Bayesian network methods accommodate discrete data, use a 'search and score' network learning strategy and output a directed network, they can be compared in terms of performance and computational time. In the second study, we compared SA and

Science education as a pathway to teaching language literacy: a critical book review

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Tolbert, Sara

2011-03-01

In this paper, I present a critical review of the recent book, Science Education as a Pathway to Teaching Language Literacy, edited by Alberto J. Rodriguez. This volume is a timely collection of essays in which the authors bring to attention both the successes and challenges of integrating science instruction with literacy instruction (and vice versa). Although several themes in the book merit further attention, a central unifying issue throughout all of the chapters is the task of designing instruction which (1) gives students access to the dominant Discourses in science and literacy, (2) builds on students' lived experiences, and (3) connects new material to socially and culturally relevant contexts in both science and literacy instruction— all within the high stakes testing realities of teachers and students in public schools. In this review, I illustrate how the authors of these essays effectively address this formidable challenge through research that `ascends to the concrete'. I also discuss where we could build on the work of the authors to integrate literacy and science instruction with the purpose of `humanizing and democratizing' science education in K-12 classrooms.

A Networks Approach to Modeling Enzymatic Reactions.

Science.gov (United States)

Imhof, P

2016-01-01

Modeling enzymatic reactions is a demanding task due to the complexity of the system, the many degrees of freedom involved and the complex, chemical, and conformational transitions associated with the reaction. Consequently, enzymatic reactions are not determined by precisely one reaction pathway. Hence, it is beneficial to obtain a comprehensive picture of possible reaction paths and competing mechanisms. By combining individually generated intermediate states and chemical transition steps a network of such pathways can be constructed. Transition networks are a discretized representation of a potential energy landscape consisting of a multitude of reaction pathways connecting the end states of the reaction. The graph structure of the network allows an easy identification of the energetically most favorable pathways as well as a number of alternative routes. © 2016 Elsevier Inc. All rights reserved.

Use of a simplified pathways model to improve the environmental surveillance program at the radioactive waste management complex of the Idaho National Engineering Laboratory (INEL)

International Nuclear Information System (INIS)

Case, M.J.; Rope, S.K.

1985-01-01

Systems analysis, including a simple pathways model based on first-order kinetics, is a useful way to design or improve environmental monitoring networks. This method allows investigators and administrators to consider interactions that may be occurring in the system and provides guidance in determining the need to collect data on various system components and processes. A simplified pathways model of radionuclide movement from low-level waste and transuranic waste buried at the Radioactive Waste Management Complex was developed (1) to identify critical pathways that should be monitored and (2) to identify key input parameters that need investigation by special studies. The model was modified from the Savannah River Laboratory DOSTOMAN code. Site-specific data were used in the model, if available. Physical and biological pathways include airborne and waterborne transport of surface soil, subsurface migration to the aquifer, waste container degradation, plant uptake, small mammal burrowing, and a few simplified food chain pathways. The model was run using a set of radionuclides determined to be significant in terms of relative hazard. Critical transport pathways which should be monitored were selected based on relative influence on model results. Key input parameters were identified for possible special studies by evaluating the sensitivity of model response to the parameters used to define transport pathways. A description of the approaches used and the guidance recommended to improve the environmental surveillance program are presented in this paper. 5 references, 1 figure, 2 tables

The PD1:PD-L1/2 Pathway from Discovery to Clinical Implementation.

Science.gov (United States)

Bardhan, Kankana; Anagnostou, Theodora; Boussiotis, Vassiliki A

2016-01-01

The immune system maintains a critically organized network to defend against foreign particles, while evading self-reactivity simultaneously. T lymphocytes function as effectors and play an important regulatory role to orchestrate the immune signals. Although central tolerance mechanism results in the removal of the most of the autoreactive T cells during thymic selection, a fraction of self-reactive lymphocytes escapes to the periphery and pose a threat to cause autoimmunity. The immune system evolved various mechanisms to constrain such autoreactive T cells and maintain peripheral tolerance, including T cell anergy, deletion, and suppression by regulatory T cells (T Regs ). These effects are regulated by a complex network of stimulatory and inhibitory receptors expressed on T cells and their ligands, which deliver cell-to-cell signals that dictate the outcome of T cell encountering with cognate antigens. Among the inhibitory immune mediators, the pathway consisting of the programed cell death 1 (PD-1) receptor (CD279) and its ligands PD-L1 (B7-H1, CD274) and PD-L2 (B7-DC, CD273) plays an important role in the induction and maintenance of peripheral tolerance and for the maintenance of the stability and the integrity of T cells. However, the PD-1:PD-L1/L2 pathway also mediates potent inhibitory signals to hinder the proliferation and function of T effector cells and have inimical effects on antiviral and antitumor immunity. Therapeutic targeting of this pathway has resulted in successful enhancement of T cell immunity against viral pathogens and tumors. Here, we will provide a brief overview on the properties of the components of the PD-1 pathway, the signaling events regulated by PD-1 engagement, and their consequences on the function of T effector cells.

Gene networks and toxicity pathways induced by acute cadmium exposure in adult largemouth bass (Micropterus salmoides).

Science.gov (United States)

Mehinto, Alvine C; Prucha, Melinda S; Colli-Dula, Reyna C; Kroll, Kevin J; Lavelle, Candice M; Barber, David S; Vulpe, Christopher D; Denslow, Nancy D

2014-07-01

Cadmium is a heavy metal that can accumulate to toxic levels in the environment leading to detrimental effects in animals and humans including kidney, liver and lung injuries. Using a transcriptomics approach, genes and cellular pathways affected by a low dose of cadmium were investigated. Adult largemouth bass were intraperitoneally injected with 20μg/kg of cadmium chloride (mean exposure level - 2.6μg of cadmium per fish) and microarray analyses were conducted in the liver and testis 48h after injection. Transcriptomic profiles identified in response to cadmium exposure were tissue-specific with the most differential expression changes found in the liver tissues, which also contained much higher levels of cadmium than the testis. Acute exposure to a low dose of cadmium induced oxidative stress response and oxidative damage pathways in the liver. The mRNA levels of antioxidants such as catalase increased and numerous transcripts related to DNA damage and DNA repair were significantly altered. Hepatic mRNA levels of metallothionein, a molecular marker of metal exposure, did not increase significantly after 48h exposure. Carbohydrate metabolic pathways were also disrupted with hepatic transcripts such as UDP-glucose, pyrophosphorylase 2, and sorbitol dehydrogenase highly induced. Both tissues exhibited a disruption of steroid signaling pathways. In the testis, estrogen receptor beta and transcripts linked to cholesterol metabolism were suppressed. On the contrary, genes involved in cholesterol metabolism were highly increased in the liver including genes encoding for the rate limiting steroidogenic acute regulatory protein and the catalytic enzyme 7-dehydrocholesterol reductase. Integration of the transcriptomic data using functional enrichment analyses revealed a number of enriched gene networks associated with previously reported adverse outcomes of cadmium exposure such as liver toxicity and impaired reproduction. Copyright © 2014 Elsevier B.V. All rights

Life after critical illness: an overview.

Science.gov (United States)

Rattray, Janice

2014-03-01

To illustrate the potential physical and psychological problems faced by patients after an episode of critical illness, highlight some of the interventions that have been tested and identify areas for future research. Recovery from critical illness is an international problem and as an issue is likely to increase. For some, recovery from critical illness is prolonged, subject to physical and psychological problems that may negatively impact upon health-related quality of life. The literature accessed for this review includes the work of a number of key researchers in the field of critical care research. These were identified from a number of sources include (1) personal knowledge of the research field accumulated over the last decade and (2) using the search engine 'The Knowledge Network Scotland'. Fatigue and weakness are significant problems for critical care survivors and are common in patients who have been in ICU for more than one week. Psychological problems include anxiety, depression, post-traumatic stress, delirium and cognitive impairment. Prevalence of these problems is difficult to establish for a number of methodological reasons that include the use of self-report questionnaires, the number of different questionnaires used and the variation in administration and timing. Certain subgroups of ICU survivors especially those at the more severe end of the illness severity spectrum are more at risk and this has been demonstrated for both physical and psychological problems. Findings from international studies of a range of potential interventions are presented. However, establishing effectiveness for most of these still has to be empirically demonstrated. What seems clear is the need for a co-ordinated, multidisciplinary, designated recovery and rehabilitation pathway that begins as soon as the patient is admitted into an intensive care unit. © 2013 John Wiley & Sons Ltd.

A molecular systems approach to modelling human skin pigmentation: identifying underlying pathways and critical components.

Science.gov (United States)

Raghunath, Arathi; Sambarey, Awanti; Sharma, Neha; Mahadevan, Usha; Chandra, Nagasuma

2015-04-29

Ultraviolet radiations (UV) serve as an environmental stress for human skin, and result in melanogenesis, with the pigment melanin having protective effects against UV induced damage. This involves a dynamic and complex regulation of various biological processes that results in the expression of melanin in the outer most layers of the epidermis, where it can exert its protective effect. A comprehensive understanding of the underlying cross talk among different signalling molecules and cell types is only possible through a systems perspective. Increasing incidences of both melanoma and non-melanoma skin cancers necessitate the need to better comprehend UV mediated effects on skin pigmentation at a systems level, so as to ultimately evolve knowledge-based strategies for efficient protection and prevention of skin diseases. A network model for UV-mediated skin pigmentation in the epidermis was constructed and subjected to shortest path analysis. Virtual knock-outs were carried out to identify essential signalling components. We describe a network model for UV-mediated skin pigmentation in the epidermis. The model consists of 265 components (nodes) and 429 directed interactions among them, capturing the manner in which one component influences the other and channels information. Through shortest path analysis, we identify novel signalling pathways relevant to pigmentation. Virtual knock-outs or perturbations of specific nodes in the network have led to the identification of alternate modes of signalling as well as enabled determining essential nodes in the process. The model presented provides a comprehensive picture of UV mediated signalling manifesting in human skin pigmentation. A systems perspective helps provide a holistic purview of interconnections and complexity in the processes leading to pigmentation. The model described here is extensive yet amenable to expansion as new data is gathered. Through this study, we provide a list of important proteins essential

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

Chemical Transformation Motifs --- Modelling Pathways as Integer Hyperflows

DEFF Research Database (Denmark)

Andersen, Jakob L.; Flamm, Christoph; Merkle, Daniel

2018-01-01

analysis are discussed in detail. To demonstrate the applicability of the mathematical framework to real-life problems we first explore the design space of possible non-oxidative glycolysis pathways and show that recent manually designed pathways can be further optimised. We then use a model of sugar...... chemistry to investigate pathways in the autocatalytic formose process. A graph transformation-based approach is used to automatically generate the reaction networks of interest....

Critical Roles of the Direct GABAergic Pallido-cortical Pathway in Controlling Absence Seizures

Science.gov (United States)

Li, Min; Ma, Tao; Wu, Shengdun; Ma, Jingling; Cui, Yan; Xia, Yang; Xu, Peng; Yao, Dezhong

2015-01-01

The basal ganglia (BG), serving as an intermediate bridge between the cerebral cortex and thalamus, are believed to play crucial roles in controlling absence seizure activities generated by the pathological corticothalamic system. Inspired by recent experiments, here we systematically investigate the contribution of a novel identified GABAergic pallido-cortical pathway, projecting from the globus pallidus externa (GPe) in the BG to the cerebral cortex, to the control of absence seizures. By computational modelling, we find that both increasing the activation of GPe neurons and enhancing the coupling strength of the inhibitory pallido-cortical pathway can suppress the bilaterally synchronous 2–4 Hz spike and wave discharges (SWDs) during absence seizures. Appropriate tuning of several GPe-related pathways may also trigger the SWD suppression, through modulating the activation level of GPe neurons. Furthermore, we show that the previously discovered bidirectional control of absence seizures due to the competition between other two BG output pathways also exists in our established model. Importantly, such bidirectional control is shaped by the coupling strength of this direct GABAergic pallido-cortical pathway. Our work suggests that the novel identified pallido-cortical pathway has a functional role in controlling absence seizures and the presented results might provide testable hypotheses for future experimental studies. PMID:26496656

Social pathways to health: On the mediating role of the social network in the relation between socio-economic position and health.

Science.gov (United States)

Aartsen, Marja; Veenstra, Marijke; Hansen, Thomas

2017-12-01

Good health is one of the key qualities of life, but opportunities to be and remain healthy are unequally distributed across socio-economic groups. The beneficial health effects of the social network are well known. However, research on the social network as potential mediator in the pathway from socio-economic position (SEP) to health is scarce, while there are good reasons to expect a socio-economical patterning of networks. We aim to contribute to our understanding of socio-economic inequalities in health by examining the mediating role of structural and functional characteristics of the social network in the SEP-health relationship. Data were from the second wave of the Norwegian study on the life course, aging and generation study (NorLAG) and comprised 4534 men and 4690 women aged between 40 and 81. We applied multiple mediation models to evaluate the relative importance of each network characteristic, and multiple group analysis to examine differences between middle-aged and older men and women. Our results indicated a clear socio-economical patterning of the social network for men and women. People with higher SEP had social networks that better protect against loneliness, which in turn lead to better health outcomes. The explained variance in health in older people by the social network and SEP was only half of the explained variance observed in middle-aged people, suggesting that other factors than SEP were more important for health when people age. We conclude that it is the function of the network, rather than the structure, that counts for health.

Social pathways to health: On the mediating role of the social network in the relation between socio-economic position and health

Directory of Open Access Journals (Sweden)

Marja Aartsen

2017-12-01

Full Text Available Good health is one of the key qualities of life, but opportunities to be and remain healthy are unequally distributed across socio-economic groups. The beneficial health effects of the social network are well known. However, research on the social network as potential mediator in the pathway from socio-economic position (SEP to health is scarce, while there are good reasons to expect a socio-economical patterning of networks. We aim to contribute to our understanding of socio-economic inequalities in health by examining the mediating role of structural and functional characteristics of the social network in the SEP-health relationship. Data were from the second wave of the Norwegian study on the life course, aging and generation study (NorLAG and comprised 4534 men and 4690 women aged between 40 and 81. We applied multiple mediation models to evaluate the relative importance of each network characteristic, and multiple group analysis to examine differences between middle-aged and older men and women. Our results indicated a clear socio-economical patterning of the social network for men and women. People with higher SEP had social networks that better protect against loneliness, which in turn lead to better health outcomes. The explained variance in health in older people by the social network and SEP was only half of the explained variance observed in middle-aged people, suggesting that other factors than SEP were more important for health when people age. We conclude that it is the function of the network, rather than the structure, that counts for health.

Molecular pathways involved in neuronal cell adhesion and membrane scaffolding contribute to schizophrenia and bipolar disorder susceptibility.

LENUS (Irish Health Repository)

O'Dushlaine, C

2011-03-01

Susceptibility to schizophrenia and bipolar disorder may involve a substantial, shared contribution from thousands of common genetic variants, each of small effect. Identifying whether risk variants map to specific molecular pathways is potentially biologically informative. We report a molecular pathway analysis using the single-nucleotide polymorphism (SNP) ratio test, which compares the ratio of nominally significant (P<0.05) to nonsignificant SNPs in a given pathway to identify the \\'enrichment\\' for association signals. We applied this approach to the discovery (the International Schizophrenia Consortium (n=6909)) and validation (Genetic Association Information Network (n=2729)) of schizophrenia genome-wide association study (GWAS) data sets. We investigated each of the 212 experimentally validated pathways described in the Kyoto Encyclopaedia of Genes and Genomes in the discovery sample. Nominally significant pathways were tested in the validation sample, and five pathways were found to be significant (P=0.03-0.001); only the cell adhesion molecule (CAM) pathway withstood conservative correction for multiple testing. Interestingly, this pathway was also significantly associated with bipolar disorder (Wellcome Trust Case Control Consortium (n=4847)) (P=0.01). At a gene level, CAM genes associated in all three samples (NRXN1 and CNTNAP2), which were previously implicated in specific language disorder, autism and schizophrenia. The CAM pathway functions in neuronal cell adhesion, which is critical for synaptic formation and normal cell signaling. Similar pathways have also emerged from a pathway analysis of autism, suggesting that mechanisms involved in neuronal cell adhesion may contribute broadly to neurodevelopmental psychiatric phenotypes.

Simulating an Infection Growth Model in Certain Healthy Metabolic Pathways of Homo sapiens for Highlighting Their Role in Type I Diabetes mellitus Using Fire-Spread Strategy, Feedbacks and Sensitivities

Science.gov (United States)

Tagore, Somnath; De, Rajat K.

2013-01-01

Disease Systems Biology is an area of life sciences, which is not very well understood to date. Analyzing infections and their spread in healthy metabolite networks can be one of the focussed areas in this regard. We have proposed a theory based on the classical forest fire model for analyzing the path of infection spread in healthy metabolic pathways. The theory suggests that when fire erupts in a forest, it spreads, and the surrounding trees also catch fire. Similarly, when we consider a metabolic network, the infection caused in the metabolites of the network spreads like a fire. We have constructed a simulation model which is used to study the infection caused in the metabolic networks from the start of infection, to spread and ultimately combating it. For implementation, we have used two approaches, first, based on quantitative strategies using ordinary differential equations and second, using graph-theory based properties. Furthermore, we are using certain probabilistic scores to complete this task and for interpreting the harm caused in the network, given by a ‘critical value’ to check whether the infection can be cured or not. We have tested our simulation model on metabolic pathways involved in Type I Diabetes mellitus in Homo sapiens. For validating our results biologically, we have used sensitivity analysis, both local and global, as well as for identifying the role of feedbacks in spreading infection in metabolic pathways. Moreover, information in literature has also been used to validate the results. The metabolic network datasets have been collected from the Kyoto Encyclopedia of Genes and Genomes (KEGG). PMID:24039701

Simulating an infection growth model in certain healthy metabolic pathways of Homo sapiens for highlighting their role in Type I Diabetes mellitus using fire-spread strategy, feedbacks and sensitivities.

Directory of Open Access Journals (Sweden)

Somnath Tagore

Full Text Available Disease Systems Biology is an area of life sciences, which is not very well understood to date. Analyzing infections and their spread in healthy metabolite networks can be one of the focussed areas in this regard. We have proposed a theory based on the classical forest fire model for analyzing the path of infection spread in healthy metabolic pathways. The theory suggests that when fire erupts in a forest, it spreads, and the surrounding trees also catch fire. Similarly, when we consider a metabolic network, the infection caused in the metabolites of the network spreads like a fire. We have constructed a simulation model which is used to study the infection caused in the metabolic networks from the start of infection, to spread and ultimately combating it. For implementation, we have used two approaches, first, based on quantitative strategies using ordinary differential equations and second, using graph-theory based properties. Furthermore, we are using certain probabilistic scores to complete this task and for interpreting the harm caused in the network, given by a 'critical value' to check whether the infection can be cured or not. We have tested our simulation model on metabolic pathways involved in Type I Diabetes mellitus in Homo sapiens. For validating our results biologically, we have used sensitivity analysis, both local and global, as well as for identifying the role of feedbacks in spreading infection in metabolic pathways. Moreover, information in literature has also been used to validate the results. The metabolic network datasets have been collected from the Kyoto Encyclopedia of Genes and Genomes (KEGG.

Modularized TGFbeta-Smad Signaling Pathway

Science.gov (United States)

Li, Yongfeng; Wang, M.; Carra, C.; Cucinotta, F. A.

2011-01-01

The Transforming Growth Factor beta (TGFbeta) signaling pathway is a prominent regulatory signaling pathway controlling various important cellular processes. It can be induced by several factors, including ionizing radiation. It is regulated by Smads in a negative feedback loop through promoting increases in the regulatory Smads in the cell nucleus, and subsequent expression of inhibitory Smad, Smad7 to form a ubiquitin ligase with Smurf targeting active TGF receptors for degradation. In this work, we proposed a mathematical model to study the radiation-induced Smad-regulated TGF signaling pathway. By modularization, we are able to analyze each module (subsystem) and recover the nonlinear dynamics of the entire network system. Meanwhile the excitability, a common feature observed in the biological systems, along the TGF signaling pathway is discussed by mathematical analysis and numerical simulation.

Businesses Partner with Schools, Community to Create Alternative Career Pathways

Science.gov (United States)

Overman, Stephenie

2012-01-01

Business, education and community leaders are working together to create alternative career pathways for young people who are not profiting from the four-year college track. The new Pathways to Prosperity Network brings together the Pathways to Prosperity Project at Harvard Graduate School of Education (HGSE), Jobs for the Future (JFF) and six…

Academic provenance: Investigation of pathways that lead students into the geosciences

Science.gov (United States)

Houlton, Heather R.

Pathways that lead students into the geosciences as a college major have not been fully explored in the current literature, despite the recent studies on the "geoscience pipeline model." Anecdotal evidence suggests low quality geoscience curriculum in K-12 education, lack of visibility of the discipline and lack of knowledge about geoscience careers contribute to low geoscience enrollments at universities. This study investigated the reasons why college students decided to major in the geosciences. Students' interests, experiences, motivations and desired future careers were examined to develop a pathway model. In addition, self-efficacy was used to inform pathway analyses, as it is an influential factor in academic major and career choice. These results and interpretations have strong implications for recruitment and retention in academia and industry. A semi-structured interview protocol was developed, which was informed by John Flanagan's critical incident theory. The responses to this interview were used to identify common experiences that diverse students shared for reasons they became geoscience majors. Researchers used self-efficacy theory by Alfred Bandura to assess students' pathways. Seventeen undergraduate geoscience majors from two U.S. Midwest research universities were sampled for cross-comparison and analysis. Qualitative analyses led to the development of six categorical steps for the geoscience pathway. The six pathway steps are: innate attributes/interest sources, pre-college critical incidents, college critical incidents, current/near future goals, expected career attributes and desired future careers. Although, how students traversed through each step was unique for individuals, similar patterns were identified between different populations in our participants: Natives, Immigrants and Refugees. In addition, critical incidents were found to act on behavior in two different ways: to support and confirm decision-making behavior (supportive critical

State Strategies for Sustaining and Scaling Grades 9-14 Career Pathways: Toward a Policy Set for Pathways to Prosperity

Science.gov (United States)

Cahill, Charlotte; Hoffman, Nancy; Loyd, Amy; Vargas, Joel

2014-01-01

This brief begins with a discussion of the composition of state leadership teams and organizing structures for supporting a Pathways to Prosperity Network initiative, and then describes effective strategies currently at play in the network states for jumpstarting work in the regions. It goes on to review state policies that support 9-14…

A Network Inference Workflow Applied to Virulence-Related Processes in Salmonella typhimurium

Energy Technology Data Exchange (ETDEWEB)

Taylor, Ronald C.; Singhal, Mudita; Weller, Jennifer B.; Khoshnevis, Saeed; Shi, Liang; McDermott, Jason E.

2009-04-20

Inference of the structure of mRNA transcriptional regulatory networks, protein regulatory or interaction networks, and protein activation/inactivation-based signal transduction networks are critical tasks in systems biology. In this article we discuss a workflow for the reconstruction of parts of the transcriptional regulatory network of the pathogenic bacterium Salmonella typhimurium based on the information contained in sets of microarray gene expression data now available for that organism, and describe our results obtained by following this workflow. The primary tool is one of the network inference algorithms deployed in the Software Environment for BIological Network Inference (SEBINI). Specifically, we selected the algorithm called Context Likelihood of Relatedness (CLR), which uses the mutual information contained in the gene expression data to infer regulatory connections. The associated analysis pipeline automatically stores the inferred edges from the CLR runs within SEBINI and, upon request, transfers the inferred edges into either Cytoscape or the plug-in Collective Analysis of Biological of Biological Interaction Networks (CABIN) tool for further post-analysis of the inferred regulatory edges. The following article presents the outcome of this workflow, as well as the protocols followed for microarray data collection, data cleansing, and network inference. Our analysis revealed several interesting interactions, functional groups, metabolic pathways, and regulons in S. typhimurium.

Dominating biological networks.

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Tijana Milenković

Full Text Available Proteins are essential macromolecules of life that carry out most cellular processes. Since proteins aggregate to perform function, and since protein-protein interaction (PPI networks model these aggregations, one would expect to uncover new biology from PPI network topology. Hence, using PPI networks to predict protein function and role of protein pathways in disease has received attention. A debate remains open about whether network properties of "biologically central (BC" genes (i.e., their protein products, such as those involved in aging, cancer, infectious diseases, or signaling and drug-targeted pathways, exhibit some topological centrality compared to the rest of the proteins in the human PPI network.To help resolve this debate, we design new network-based approaches and apply them to get new insight into biological function and disease. We hypothesize that BC genes have a topologically central (TC role in the human PPI network. We propose two different concepts of topological centrality. We design a new centrality measure to capture complex wirings of proteins in the network that identifies as TC those proteins that reside in dense extended network neighborhoods. Also, we use the notion of domination and find dominating sets (DSs in the PPI network, i.e., sets of proteins such that every protein is either in the DS or is a neighbor of the DS. Clearly, a DS has a TC role, as it enables efficient communication between different network parts. We find statistically significant enrichment in BC genes of TC nodes and outperform the existing methods indicating that genes involved in key biological processes occupy topologically complex and dense regions of the network and correspond to its "spine" that connects all other network parts and can thus pass cellular signals efficiently throughout the network. To our knowledge, this is the first study that explores domination in the context of PPI networks.

Salicylic acid-independent plant defence pathways

OpenAIRE

Pieterse, C.M.J.; Loon, L.C. van

1999-01-01

Salicylic acid is an important signalling molecule involved in both locally and systemically induced disease resistance responses. Recent advances in our understanding of plant defence signalling have revealed that plants employ a network of signal transduction pathways, some of which are independent of salicylic acid. Evidence is emerging that jasmonic acid and ethylene play key roles in these salicylic acid-independent pathways. Cross-talk between the salicylic acid-dependent and the salicy...

Consolidated Deep Actor Critic Networks (DRAFT)

NARCIS (Netherlands)

Van der Laan, T.A.

2015-01-01

The works [Volodymyr et al. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602, 2013.] and [Volodymyr et al. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 2015.] have demonstrated the power of combining deep neural networks with

PathwaySplice: An R package for unbiased pathway analysis of alternative splicing in RNA-Seq data.

Science.gov (United States)

Yan, Aimin; Ban, Yuguang; Gao, Zhen; Chen, Xi; Wang, Lily

2018-04-24

Pathway analysis of alternative splicing would be biased without accounting for the different number of exons or junctions associated with each gene, because genes with higher number of exons or junctions are more likely to be included in the "significant" gene list in alternative splicing. We present PathwaySplice, an R package that (1) Performs pathway analysis that explicitly adjusts for the number of exons or junctions associated with each gene; (2) Visualizes selection bias due to different number of exons or junctions for each gene and formally tests for presence of bias using logistic regression; (3) Supports gene sets based on the Gene Ontology terms, as well as more broadly defined gene sets (e.g. MSigDB) or user defined gene sets; (4) Identifies the significant genes driving pathway significance and (5) Organizes significant pathways with an enrichment map, where pathways with large number of overlapping genes are grouped together in a network graph. https://bioconductor.org/packages/release/bioc/html/PathwaySplice.html. lily.wangg@gmail.com, xi.steven.chen@gmail.com.

Discrete event simulations for glycolysis pathway and energy balance

NARCIS (Netherlands)

Zwieten, van D.A.J.; Rooda, J.E.; Armbruster, H.D.; Nagy, J.D.

2010-01-01

In this report, the biological network of the glycolysis pathway has been modeled using discrete event models (DEMs). The most important feature of this pathway is that energy is released. To create a stable steady-state system an energy molecule equilibrating enzyme and metabolic reactions have

Decoding network dynamics in cancer

DEFF Research Database (Denmark)

Linding, Rune

2014-01-01

Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language and with an accur......Biological systems are composed of highly dynamic and interconnected molecular networks that drive biological decision processes. The goal of network biology is to describe, quantify and predict the information flow and functional behaviour of living systems in a formal language...... and with an accuracy that parallels our characterisation of other physical systems such as Jumbo-jets. Decades of targeted molecular and biological studies have led to numerous pathway models of developmental and disease related processes. However, so far no global models have been derived from pathways, capable...

A critical analysis of the implementation of social networking as an e-recruitment tool within a security enterprise

Directory of Open Access Journals (Sweden)

Anthony Lewis

2015-12-01

Full Text Available Many enterprises are operating in complex and competitive environments, and changes in the internal and external environment have prompted them to engage in better ways of doing business. In order to respond to these changes, and survive in today’s volatile business environment, enterprises need to change their strategies. Human Resource departments are under pressure to keep operating costs low whilst also ensuring they are attracting, recruiting, and retaining talent within the enterprise. To achieve this, an increasing number of enterprises have adopted social networking into their recruitment strategy. This research aims to critically analyze the implementation of social networking as an e-recruitment tool within a Security Enterprise. The research key objective is to examine the importance of attracting Generation Y through the use of social networking sites and also to develop an understanding of the advantages and disadvantages of using social networking as an e-recruitment tool. The research also looks at contemporary examples of enterprises that have implemented social networking into their recruitment strategy. A further objective of the research is to gain an understanding of the attitudes and perceptions of the use of social networking as an e-recruitment tool. To achieve this, the research has taken a mixed-methods approach whilst focusing on an interpretivist stance. Data was gathered through an interview with the HR Manager at the Security Enterprise and a questionnaire was distributed to 22 employees within the enterprise and 84 respondents on social networking sites. The overall attitudes and perceptions of respondents showed that social networking can be effectively used as an e-recruitment tool as long as a traditional recruitment method is also used.

Modularized Smad-regulated TGFβ signaling pathway.

Science.gov (United States)

Li, Yongfeng; Wang, Minli; Carra, Claudio; Cucinotta, Francis A

2012-12-01

The transforming Growth Factor β (TGFβ) signaling pathway is a prominent regulatory signaling pathway controlling various important cellular processes. TGFβ signaling can be induced by several factors including ionizing radiation. The pathway is regulated in a negative feedback loop through promoting the nuclear import of the regulatory Smads and a subsequent expression of inhibitory Smad7, that forms ubiquitin ligase with Smurf2, targeting active TGFβ receptors for degradation. In this work, we proposed a mathematical model to study the Smad-regulated TGFβ signaling pathway. By modularization, we are able to analyze mathematically each component subsystem and recover the nonlinear dynamics of the entire network system. Meanwhile the excitability, a common feature observed in the biological systems, in the TGFβ signaling pathway is discussed and supported as well by numerical simulation, indicating the robustness of the model. Published by Elsevier Inc.

Evaluation of gene association methods for coexpression network construction and biological knowledge discovery.

Directory of Open Access Journals (Sweden)

Sapna Kumari

Full Text Available BACKGROUND: Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. METHODS AND RESULTS: In this study, we compared eight gene association methods - Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. CONCLUSIONS: We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction.

Quantitative inference of dynamic regulatory pathways via microarray data

Directory of Open Access Journals (Sweden)

Chen Bor-Sen

2005-03-01

Full Text Available Abstract Background The cellular signaling pathway (network is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway are considered as the foundation of functional genomics. Thus, what genes and how much they influence each other through transcriptional binding or physical interactions are essential problems. Under the synchronous measures of gene expression via a microarray chip, an amount of dynamic information is embedded and remains to be discovered. Using a systematically dynamic modeling approach, we explore the causal relationship among genes in cellular signaling pathways from the system biology approach. Results In this study, a second-order dynamic model is developed to describe the regulatory mechanism of a target gene from the upstream causality point of view. From the expression profile and dynamic model of a target gene, we can estimate its upstream regulatory function. According to this upstream regulatory function, we would deduce the upstream regulatory genes with their regulatory abilities and activation delays, and then link up a regulatory pathway. Iteratively, these regulatory genes are considered as target genes to trace back their upstream regulatory genes. Then we could construct the regulatory pathway (or network to the genome wide. In short, we can infer the genetic regulatory pathways from gene-expression profiles quantitatively, which can confirm some doubted paths or seek some unknown paths in a regulatory pathway (network. Finally, the proposed approach is validated by randomly reshuffling the time order of microarray data. Conclusion We focus our algorithm on the inference of regulatory abilities of the identified causal genes, and how much delay before they regulate the downstream genes. With this information, a regulatory pathway would be built up using microarray data. In the present study, two signaling pathways, i.e. circadian regulatory

Universal Critical Dynamics in High Resolution Neuronal Avalanche Data

Science.gov (United States)

Friedman, Nir; Ito, Shinya; Brinkman, Braden A. W.; Shimono, Masanori; DeVille, R. E. Lee; Dahmen, Karin A.; Beggs, John M.; Butler, Thomas C.

2012-05-01

The tasks of neural computation are remarkably diverse. To function optimally, neuronal networks have been hypothesized to operate near a nonequilibrium critical point. However, experimental evidence for critical dynamics has been inconclusive. Here, we show that the dynamics of cultured cortical networks are critical. We analyze neuronal network data collected at the individual neuron level using the framework of nonequilibrium phase transitions. Among the most striking predictions confirmed is that the mean temporal profiles of avalanches of widely varying durations are quantitatively described by a single universal scaling function. We also show that the data have three additional features predicted by critical phenomena: approximate power law distributions of avalanche sizes and durations, samples in subcritical and supercritical phases, and scaling laws between anomalous exponents.

Progress Report on the US Critical Zone Observatory Program

Science.gov (United States)

Barrera, E. C.

2014-12-01

The Critical Zone Observatory (CZO) program supported by the National Science Foundation originated from the recommendation of the Earth Science community published in the National Research Council report "Basic Research Opportunities in Earth Sciences" (2001) to establish natural laboratories to study processes and systems of the Critical Zone - the surface and near-surface environment sustaining nearly all terrestrial life. After a number of critical zone community workshops to develop a science plan, the CZO program was initiated in 2007 with three sites and has now grown to 10 sites and a National Office, which coordinates research, education and outreach activities of the network. Several of the CZO sites are collocated with sites supported by the US Long Term Ecological Research (LTER) and the Long Term Agricultural Research (LTAR) programs, and the National Ecological Observatory Network (NEON). Future collaboration with additional sites of these networks will add to the potential to answer questions in a more comprehensive manner and in a larger regional scale about the critical zone form and function. At the international level, CZOs have been established in many countries and strong collaborations with the US program have been in place for many years. The next step is the development of a coordinated international program of critical zone research. The success of the CZO network of sites can be measured in transformative results that elucidate properties and processes controlling the critical zone and how the critical zone structure, stores and fluxes respond to climate and land use change. This understanding of the critical zone can be used to enhance resilience and sustainability, and restore ecosystem function. Thus, CZO science can address major societal challenges. The US CZO network is a facility open to research of the critical zone community at large. Scientific data and information about the US program are available at www.criticalzone.org.

Seeded Bayesian Networks: Constructing genetic networks from microarray data

Directory of Open Access Journals (Sweden)

Quackenbush John

2008-07-01

Full Text Available Abstract Background DNA microarrays and other genomics-inspired technologies provide large datasets that often include hidden patterns of correlation between genes reflecting the complex processes that underlie cellular metabolism and physiology. The challenge in analyzing large-scale expression data has been to extract biologically meaningful inferences regarding these processes – often represented as networks – in an environment where the datasets are often imperfect and biological noise can obscure the actual signal. Although many techniques have been developed in an attempt to address these issues, to date their ability to extract meaningful and predictive network relationships has been limited. Here we describe a method that draws on prior information about gene-gene interactions to infer biologically relevant pathways from microarray data. Our approach consists of using preliminary networks derived from the literature and/or protein-protein interaction data as seeds for a Bayesian network analysis of microarray results. Results Through a bootstrap analysis of gene expression data derived from a number of leukemia studies, we demonstrate that seeded Bayesian Networks have the ability to identify high-confidence gene-gene interactions which can then be validated by comparison to other sources of pathway data. Conclusion The use of network seeds greatly improves the ability of Bayesian Network analysis to learn gene interaction networks from gene expression data. We demonstrate that the use of seeds derived from the biomedical literature or high-throughput protein-protein interaction data, or the combination, provides improvement over a standard Bayesian Network analysis, allowing networks involving dynamic processes to be deduced from the static snapshots of biological systems that represent the most common source of microarray data. Software implementing these methods has been included in the widely used TM4 microarray analysis package.

The effect of alcohol on the differential expression of cluster of differentiation 14 gene, associated pathways, and genetic network.

Directory of Open Access Journals (Sweden)

Diana X Zhou

Full Text Available Alcohol consumption affects human health in part by compromising the immune system. In this study, we examined the expression of the Cd14 (cluster of differentiation 14 gene, which is involved in the immune system through a proinflammatory cascade. Expression was evaluated in BXD mice treated with saline or acute 1.8 g/kg i.p. ethanol (12.5% v/v. Hippocampal gene expression data were generated to examine differential expression and to perform systems genetics analyses. The Cd14 gene expression showed significant changes among the BXD strains after ethanol treatment, and eQTL mapping revealed that Cd14 is a cis-regulated gene. We also identified eighteen ethanol-related phenotypes correlated with Cd14 expression related to either ethanol responses or ethanol consumption. Pathway analysis was performed to identify possible biological pathways involved in the response to ethanol and Cd14. We also constructed a genetic network for Cd14 using the top 20 correlated genes and present several genes possibly involved in Cd14 and ethanol responses based on differential gene expression. In conclusion, we found Cd14, along with several other genes and pathways, to be involved in ethanol responses in the hippocampus, such as increased susceptibility to lipopolysaccharides and neuroinflammation.

[Exploration of common biological pathways for attention deficit hyperactivity disorder and low birth weight].

Science.gov (United States)

Xiang, Bo; Yu, Minglan; Liang, Xuemei; Lei, Wei; Huang, Chaohua; Chen, Jing; He, Wenying; Zhang, Tao; Li, Tao; Liu, Kezhi

2017-12-10

To explore common biological pathways for attention deficit hyperactivity disorder (ADHD) and low birth weight (LBW). Thei-Gsea4GwasV2 software was used to analyze the result of genome-wide association analysis (GWAS) for LBW (pathways were derived from Reactome), and nominally significant (Ppathways were tested for replication in ADHD.Significant pathways were analyzed with DAPPLE and Reatome FI software to identify genes involved in such pathways, with each cluster enriched with the gene ontology (GO). The Centiscape2.0 software was used to calculate the degree of genetic networks and the betweenness value to explore the core node (gene). Weighed gene co-expression network analysis (WGCNA) was then used to explore the co-expression of genes in these pathways.With gene expression data derived from BrainSpan, GO enrichment was carried out for each gene module. Eleven significant biological pathways was identified in association with LBW, among which two (Selenoamino acid metabolism and Diseases associated with glycosaminoglycan metabolism) were replicated during subsequent ADHD analysis. Network analysis of 130 genes in these pathways revealed that some of the sub-networksare related with morphology of cerebellum, development of hippocampus, and plasticity of synaptic structure. Upon co-expression network analysis, 120 genes passed the quality control and were found to express in 3 gene modules. These modules are mainly related to the regulation of synaptic structure and activity regulation. ADHD and LBW share some biological regulation processes. Anomalies of such proces sesmay predispose to ADHD.

Quality of Service Model on Data Link Layer for Mission Critical Traffic on IEEE 802.11g Networks in Infrastructure Mode

Directory of Open Access Journals (Sweden)

Gerald B. Fuenmayor-Rivadeneira

2013-11-01

Full Text Available This article presents a synthesized review as state of the art of the study of QoS for mission-critical traffic in wireless local area networks that use the IEEE 802.11g protocol. This is to highlight previous research for their contribution will constitute a reference to guide a proposed new approach to ensuring the quality of service for this type of traffic using the above protocol. The review is based on academic and business items made during the current five years. As a result of this review it is evident that there have been many efforts to address the issue but there are still gaps in the characterization of mission-critical traffic and ensuring quality of service for the same, due the new applications and the large host of WiFi networks in business and government, which has led to increased demand for access channels and, therefore, a challenge to the progress already known, such as IEEE 802.1q.

Early brain response to low-dose radiation exposure involves molecular networks and pathways associated with cognitive functions, advanced aging and Alzheimer's disease.

Science.gov (United States)

Lowe, Xiu R; Bhattacharya, Sanchita; Marchetti, Francesco; Wyrobek, Andrew J

2009-01-01

Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy and environmental nuclear contamination as well as for Earth-orbit and space missions. Analyses of transcriptome profiles of mouse brain tissue after whole-body irradiation showed that low-dose exposures (10 cGy) induced genes not affected by high-dose radiation (2 Gy) and that low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues and pathways that were specific for brain tissue. Low-dose genes clustered into a saturated network (P < 10(-53)) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified nine neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose irradiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down-regulated in normal human aging and Alzheimer's disease.

Early Brain Response to Low-Dose Radiation Exposure Involves Molecular Networks and Pathways Associated with Cognitive Functions, Advanced Aging and Alzheimer's Disease

International Nuclear Information System (INIS)

Lowe, Xiu R.; Bhattacharya, Sanchita; Marchetti, Francesco; Wyrobek, Andrew J.

2008-01-01

Understanding the cognitive and behavioral consequences of brain exposures to low-dose ionizing radiation has broad relevance for health risks from medical radiation diagnostic procedures, radiotherapy, environmental nuclear contamination, as well as earth orbit and space missions. Analyses of transcriptome profiles of murine brain tissue after whole-body radiation showed that low-dose exposures (10 cGy) induced genes not affected by high dose (2 Gy), and low-dose genes were associated with unique pathways and functions. The low-dose response had two major components: pathways that are consistently seen across tissues, and pathways that were brain tissue specific. Low-dose genes clustered into a saturated network (p -53 ) containing mostly down-regulated genes involving ion channels, long-term potentiation and depression, vascular damage, etc. We identified 9 neural signaling pathways that showed a high degree of concordance in their transcriptional response in mouse brain tissue after low-dose radiation, in the aging human brain (unirradiated), and in brain tissue from patients with Alzheimer's disease. Mice exposed to high-dose radiation did not show these effects and associations. Our findings indicate that the molecular response of the mouse brain within a few hours after low-dose irradiation involves the down-regulation of neural pathways associated with cognitive dysfunctions that are also down regulated in normal human aging and Alzheimer's disease

Stormwater management network effectiveness and implications for urban watershed function: A critical review

Science.gov (United States)

Jefferson, Anne J.; Bhaskar, Aditi S.; Hopkins, Kristina G.; Fanelli, Rosemary; Avellaneda, Pedro M.; McMillan, Sara K.

2017-01-01

Deleterious effects of urban stormwater are widely recognized. In several countries, regulations have been put into place to improve the conditions of receiving water bodies, but planning and engineering of stormwater control is typically carried out at smaller scales. Quantifying cumulative effectiveness of many stormwater control measures on a watershed scale is critical to understanding how small-scale practices translate to urban river health. We review 100 empirical and modelling studies of stormwater management effectiveness at the watershed scale in diverse physiographic settings. Effects of networks with stormwater control measures (SCMs) that promote infiltration and harvest have been more intensively studied than have detention-based SCM networks. Studies of peak flows and flow volumes are common, whereas baseflow, groundwater recharge, and evapotranspiration have received comparatively little attention. Export of nutrients and suspended sediments have been the primary water quality focus in the United States, whereas metals, particularly those associated with sediments, have received greater attention in Europe and Australia. Often, quantifying cumulative effects of stormwater management is complicated by needing to separate its signal from the signal of urbanization itself, innate watershed characteristics that lead to a range of hydrologic and water quality responses, and the varying functions of multiple types of SCMs. Biases in geographic distribution of study areas, and size and impervious surface cover of watersheds studied also limit our understanding of responses. We propose hysteretic trajectories for how watershed function responds to increasing imperviousness and stormwater management. Even where impervious area is treated with SCMs, watershed function may not be restored to its predevelopment condition because of the lack of treatment of all stormwater generated from impervious surfaces; non-additive effects of individual SCMs; and

A Method to Evaluate Critical Factors for Successful Implementation of Clinical Pathways.

Science.gov (United States)

Dong, W; Huang, Z

2015-01-01

Clinical pathways (CPs) have been viewed as a multidisciplinary tool to improve the quality and efficiency of evidence-based care. Despite widespread enthusiasm for CPs, research has shown that many CP initiatives are unsuccessful. To this end, this study provides a methodology to evaluate critical success factors (CSFs) that can aid healthcare organizations to achieve successful CP implementation. This study presents a new approach to evaluate CP implementation CSFs, with the aims being: (1) to identify CSFs for implementation of CPs through a comprehensive literature review and interviews with collaborative experts; (2) to use a filed study data with a robust fuzzy DEMATEL (the decision making trial and evaluation laboratory) approach to visualize the structure of complicated causal relationships between CSFs and obtain the influence level of these factors. The filed study data is provided by ten clinical experts of a Chinese hospital. 23 identified CSF factors which are initially identified through a review of the literature and interviews with collaborative experts. Then, a number of direct and indirect relationships are derived from the data such that different perceptions can be integrated into a compromised cause and effect model of CP implementation. The results indicate that the proposed approach can systematically evaluate CSFs and realize the importance of each factor such that the most common causes of failure of CP implementation could be eliminated or avoided. Therefore, the tool proposed would help healthcare organizations to manage CP implementation in a more effective and proactive way.

An in silico assessment of gene function and organization of the phenylpropanoid pathway metabolic networks in Arabidopsis thaliana and limitations thereof

Science.gov (United States)

Costa, Michael A.; Collins, R. Eric; Anterola, Aldwin M.; Cochrane, Fiona C.; Davin, Laurence B.; Lewis, Norman G.

2003-01-01

The Arabidopsis genome sequencing in 2000 gave to science the first blueprint of a vascular plant. Its successful completion also prompted the US National Science Foundation to launch the Arabidopsis 2010 initiative, the goal of which is to identify the function of each gene by 2010. In this study, an exhaustive analysis of The Institute for Genomic Research (TIGR) and The Arabidopsis Information Resource (TAIR) databases, together with all currently compiled EST sequence data, was carried out in order to determine to what extent the various metabolic networks from phenylalanine ammonia lyase (PAL) to the monolignols were organized and/or could be predicted. In these databases, there are some 65 genes which have been annotated as encoding putative enzymatic steps in monolignol biosynthesis, although many of them have only very low homology to monolignol pathway genes of known function in other plant systems. Our detailed analysis revealed that presently only 13 genes (two PALs, a cinnamate-4-hydroxylase, a p-coumarate-3-hydroxylase, a ferulate-5-hydroxylase, three 4-coumarate-CoA ligases, a cinnamic acid O-methyl transferase, two cinnamoyl-CoA reductases) and two cinnamyl alcohol dehydrogenases can be classified as having a bona fide (definitive) function; the remaining 52 genes currently have undetermined physiological roles. The EST database entries for this particular set of genes also provided little new insight into how the monolignol pathway was organized in the different tissues and organs, this being perhaps a consequence of both limitations in how tissue samples were collected and in the incomplete nature of the EST collections. This analysis thus underscores the fact that even with genomic sequencing, presumed to provide the entire suite of putative genes in the monolignol-forming pathway, a very large effort needs to be conducted to establish actual catalytic roles (including enzyme versatility), as well as the physiological function(s) for each member

VSNL1 Co-expression networks in aging include calcium signaling, synaptic plasticity, and Alzheimer’s disease pathways

Directory of Open Access Journals (Sweden)

C W Lin

2015-03-01

Full Text Available The Visinin-like 1 (VSNL1 gene encodes Visinin-like protein 1, a peripheral biomarker for Alzheimer disease (AD. Little is known, however, about normal VSNL1 expression in brain and the biologic networks in which it participates. Frontal cortex gray matter from 209 subjects without neurodegenerative or psychiatric illness, ranging in age from 16–91, were processed on Affymetrix GeneChip 1.1 ST and Human SNP Array 6.0. VSNL1 expression was unaffected by age and sex, and not significantly associated with SNPs in cis or trans. VSNL1 was significantly co-expressed with genes in pathways for Calcium Signaling, AD, Long Term Potentiation, Long Term Depression, and Trafficking of AMPA Receptors. The association with AD was driven, in part, by correlation with amyloid precursor protein (APP expression. These findings provide an unbiased link between VSNL1 and molecular mechanisms of AD, including pathways implicated in synaptic pathology in AD. Whether APP may drive increased VSNL1 expression, VSNL1 drives increased APP expression, or both are downstream of common pathogenic regulators will need to be evaluated in model systems.

SUPERCOMPUTER SIMULATION OF CRITICAL PHENOMENA IN COMPLEX SOCIAL SYSTEMS

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Petrus M.A. Sloot

2014-09-01

Full Text Available The paper describes a problem of computer simulation of critical phenomena in complex social systems on a petascale computing systems in frames of complex networks approach. The three-layer system of nested models of complex networks is proposed including aggregated analytical model to identify critical phenomena, detailed model of individualized network dynamics and model to adjust a topological structure of a complex network. The scalable parallel algorithm covering all layers of complex networks simulation is proposed. Performance of the algorithm is studied on different supercomputing systems. The issues of software and information infrastructure of complex networks simulation are discussed including organization of distributed calculations, crawling the data in social networks and results visualization. The applications of developed methods and technologies are considered including simulation of criminal networks disruption, fast rumors spreading in social networks, evolution of financial networks and epidemics spreading.

Network Analysis of Human Genes Influencing Susceptibility to Mycobacterial Infections

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Lipner, Ettie M.; Garcia, Benjamin J.; Strong, Michael

2016-01-01

Tuberculosis and nontuberculous mycobacterial infections constitute a high burden of pulmonary disease in humans, resulting in over 1.5 million deaths per year. Building on the premise that genetic factors influence the instance, progression, and defense of infectious disease, we undertook a systems biology approach to investigate relationships among genetic factors that may play a role in increased susceptibility or control of mycobacterial infections. We combined literature and database mining with network analysis and pathway enrichment analysis to examine genes, pathways, and networks, involved in the human response to Mycobacterium tuberculosis and nontuberculous mycobacterial infections. This approach allowed us to examine functional relationships among reported genes, and to identify novel genes and enriched pathways that may play a role in mycobacterial susceptibility or control. Our findings suggest that the primary pathways and genes influencing mycobacterial infection control involve an interplay between innate and adaptive immune proteins and pathways. Signaling pathways involved in autoimmune disease were significantly enriched as revealed in our networks. Mycobacterial disease susceptibility networks were also examined within the context of gene-chemical relationships, in order to identify putative drugs and nutrients with potential beneficial immunomodulatory or anti-mycobacterial effects. PMID:26751573

Critical Complexities, (from marginal paradigms to learning networks)

NARCIS (Netherlands)

S.J. Magala (Slawomir)

2000-01-01

textabstractThe concepts of critical theory require critical changes. Strategies of a Frankfurt school had been transformed in the new academic and institutional environment. The development of scientific research programs resulted in a flexible restructuring of research communities. The new

Revealing complex function, process and pathway interactions with high-throughput expression and biological annotation data.

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Singh, Nitesh Kumar; Ernst, Mathias; Liebscher, Volkmar; Fuellen, Georg; Taher, Leila

2016-10-20

The biological relationships both between and within the functions, processes and pathways that operate within complex biological systems are only poorly characterized, making the interpretation of large scale gene expression datasets extremely challenging. Here, we present an approach that integrates gene expression and biological annotation data to identify and describe the interactions between biological functions, processes and pathways that govern a phenotype of interest. The product is a global, interconnected network, not of genes but of functions, processes and pathways, that represents the biological relationships within the system. We validated our approach on two high-throughput expression datasets describing organismal and organ development. Our findings are well supported by the available literature, confirming that developmental processes and apoptosis play key roles in cell differentiation. Furthermore, our results suggest that processes related to pluripotency and lineage commitment, which are known to be critical for development, interact mainly indirectly, through genes implicated in more general biological processes. Moreover, we provide evidence that supports the relevance of cell spatial organization in the developing liver for proper liver function. Our strategy can be viewed as an abstraction that is useful to interpret high-throughput data and devise further experiments.

Semantic Mining based on graph theory and ontologies. Case Study: Cell Signaling Pathways

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Carlos R. Rangel

2016-08-01

Full Text Available In this paper we use concepts from graph theory and cellular biology represented as ontologies, to carry out semantic mining tasks on signaling pathway networks. Specifically, the paper describes the semantic enrichment of signaling pathway networks. A cell signaling network describes the basic cellular activities and their interactions. The main contribution of this paper is in the signaling pathway research area, it proposes a new technique to analyze and understand how changes in these networks may affect the transmission and flow of information, which produce diseases such as cancer and diabetes. Our approach is based on three concepts from graph theory (modularity, clustering and centrality frequently used on social networks analysis. Our approach consists into two phases: the first uses the graph theory concepts to determine the cellular groups in the network, which we will call them communities; the second uses ontologies for the semantic enrichment of the cellular communities. The measures used from the graph theory allow us to determine the set of cells that are close (for example, in a disease, and the main cells in each community. We analyze our approach in two cases: TGF-ß and the Alzheimer Disease.

Exploring Social Networking: Developing Critical Literacies

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Watson, Pauline

2012-01-01

While schools have been using computers within their classrooms for years now, there has been a purposeful ignoring of the growing power of social networks such as Facebook and Twitter. Many schools ban students from accessing and using sites such as Facebook at school and many English and literacy teachers ignore or deny their value as a teaching…

Dual pathways to prospective remembering

Science.gov (United States)

McDaniel, Mark A.; Umanath, Sharda; Einstein, Gilles O.; Waldum, Emily R.

2015-01-01

According to the multiprocess framework (McDaniel and Einstein, 2000), the cognitive system can support prospective memory (PM) retrieval through two general pathways. One pathway depends on top–down attentional control processes that maintain activation of the intention and/or monitor the environment for the triggering or target cues that indicate that the intention should be executed. A second pathway depends on (bottom–up) spontaneous retrieval processes, processes that are often triggered by a PM target cue; critically, spontaneous retrieval is assumed not to require monitoring or active maintenance of the intention. Given demand characteristics associated with experimental settings, however, participants are often inclined to monitor, thereby potentially masking discovery of bottom–up spontaneous retrieval processes. In this article, we discuss parameters of laboratory PM paradigms to discourage monitoring and review recent behavioral evidence from such paradigms that implicate spontaneous retrieval in PM. We then re-examine the neuro-imaging evidence from the lens of the multiprocess framework and suggest some critical modifications to existing neuro-cognitive interpretations of the neuro-imaging results. These modifications illuminate possible directions and refinements for further neuro-imaging investigations of PM. PMID:26236213

Dual Pathways to Prospective Remembering

Directory of Open Access Journals (Sweden)

Mark A Mcdaniel

2015-07-01

Full Text Available According to the multiprocess framework (McDaniel & Einstein, 2000, the cognitive system can support prospective memory (PM retrieval through two general pathways. One pathway depends on top-down attentional control processes that maintain activation of the intention and/or monitor the environment for the triggering or target cues that indicate that the intention should be executed. A second pathway depends on (bottom-up spontaneous retrieval processes, processes that are often triggered by a PM target cue; critically spontaneous retrieval is assumed to not require monitoring or active maintenance of the intention. Given demand characteristics associated with experimental settings, however, participants are often inclined to monitor, thereby potentially masking discovery of bottom-up spontaneous retrieval processes. In this article, we discuss parameters of laboratory PM paradigms to discourage monitoring and review recent behavioral evidence from such paradigms that implicate spontaneous retrieval in PM. We then re-examine the neuro-imaging evidence from the lens of the multiprocess framework and suggest some critical modifications to existing neuro-cognitive interpretations of the neuro-imaging results. These modifications illuminate possible directions and refinements for further neuro-imaging investigations of PM.

Beyond Critical Exponents in Neuronal Avalanches

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Friedman, Nir; Butler, Tom; Deville, Robert; Beggs, John; Dahmen, Karin

2011-03-01

Neurons form a complex network in the brain, where they interact with one another by firing electrical signals. Neurons firing can trigger other neurons to fire, potentially causing avalanches of activity in the network. In many cases these avalanches have been found to be scale independent, similar to critical phenomena in diverse systems such as magnets and earthquakes. We discuss models for neuronal activity that allow for the extraction of testable, statistical predictions. We compare these models to experimental results, and go beyond critical exponents.

The Hippo Pathway: Immunity and Cancer.

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Taha, Zaid; J Janse van Rensburg, Helena; Yang, Xiaolong

2018-03-28

Since its discovery, the Hippo pathway has emerged as a central signaling network in mammalian cells. Canonical signaling through the Hippo pathway core components (MST1/2, LATS1/2, YAP and TAZ) is important for development and tissue homeostasis while aberrant signaling through the Hippo pathway has been implicated in multiple pathologies, including cancer. Recent studies have uncovered new roles for the Hippo pathway in immunology. In this review, we summarize the mechanisms by which Hippo signaling in pathogen-infected or neoplastic cells affects the activities of immune cells that respond to these threats. We further discuss how Hippo signaling functions as part of an immune response. Finally, we review how immune cell-intrinsic Hippo signaling modulates the development/function of leukocytes and propose directions for future work.

Reliability Analysis Techniques for Communication Networks in Nuclear Power Plant

International Nuclear Information System (INIS)

Lim, T. J.; Jang, S. C.; Kang, H. G.; Kim, M. C.; Eom, H. S.; Lee, H. J.

2006-09-01

The objectives of this project is to investigate and study existing reliability analysis techniques for communication networks in order to develop reliability analysis models for nuclear power plant's safety-critical networks. It is necessary to make a comprehensive survey of current methodologies for communication network reliability. Major outputs of this study are design characteristics of safety-critical communication networks, efficient algorithms for quantifying reliability of communication networks, and preliminary models for assessing reliability of safety-critical communication networks

Metabolic pathway alignment between species using a comprehensive and flexible similarity measure

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de Ridder Dick

2008-12-01

Full Text Available Abstract Background Comparative analysis of metabolic networks in multiple species yields important information on their evolution, and has great practical value in metabolic engineering, human disease analysis, drug design etc. In this work, we aim to systematically search for conserved pathways in two species, quantify their similarities, and focus on the variations between them. Results We present an efficient framework, Metabolic Pathway Alignment and Scoring (M-PAS, for identifying and ranking conserved metabolic pathways. M-PAS aligns all reactions in entire metabolic networks of two species and assembles them into pathways, taking mismatches, gaps and crossovers into account. It uses a comprehensive scoring function, which quantifies pathway similarity such that we can focus on different pathways given different biological motivations. Using M-PAS, we detected 1198 length-four pathways fully conserved between Saccharomyces cerevisiae and Escherichia coli, and also revealed 1399 cases of a species using a unique route in otherwise highly conserved pathways. Conclusion Our method efficiently automates the process of exploring reaction arrangement possibilities, both between species and within species, to find conserved pathways. We not only reconstruct conventional pathways such as those found in KEGG, but also discover new pathway possibilities. Our results can help to generate hypotheses on missing reactions and manifest differences in highly conserved pathways, which is useful for biology and life science applications.

Gradient networks on uncorrelated random scale-free networks

International Nuclear Information System (INIS)

Pan Guijun; Yan Xiaoqing; Huang Zhongbing; Ma Weichuan

2011-01-01

Uncorrelated random scale-free (URSF) networks are useful null models for checking the effects of scale-free topology on network-based dynamical processes. Here, we present a comparative study of the jamming level of gradient networks based on URSF networks and Erdos-Renyi (ER) random networks. We find that the URSF networks are less congested than ER random networks for the average degree (k)>k c (k c ∼ 2 denotes a critical connectivity). In addition, by investigating the topological properties of the two kinds of gradient networks, we discuss the relations between the topological structure and the transport efficiency of the gradient networks. These findings show that the uncorrelated scale-free structure might allow more efficient transport than the random structure.

Salicylic acid-independent plant defence pathways

NARCIS (Netherlands)

Pieterse, C.M.J.; Loon, L.C. van

1999-01-01

Salicylic acid is an important signalling molecule involved in both locally and systemically induced disease resistance responses. Recent advances in our understanding of plant defence signalling have revealed that plants employ a network of signal transduction pathways, some of which are

A Space Operations Network Alternative: Using Globally Connected Research and Education Networks for Space-Based Science Operations

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Bradford, Robert N.

2006-01-01

Earth based networking in support of various space agency projects has been based on leased service/circuits which has a high associated cost. This cost is almost always taken from the science side resulting in less science. This is a proposal to use Research and Education Networks (RENs) worldwide to support space flight operations in general and space-based science operations in particular. The RENs were developed to support scientific and educational endeavors. They do not provide support for general Internet traffic. The connectivity and performance of the research and education networks is superb. The connectivity at Layer 3 (IP) virtually encompasses the globe. Most third world countries and all developed countries have their own research and education networks, which are connected globally. Performance of the RENs especially in the developed countries is exceptional. Bandwidth capacity currently exists and future expansion promises that this capacity will continue. REN performance statistics has always exceeded minimum requirements for spaceflight support. Research and Education networks are more loosely managed than a corporate network but are highly managed when compared to the commodity Internet. Management of RENs on an international level is accomplished by the International Network Operations Center at Indiana University at Indianapolis. With few exceptions, each regional and national REN has its own network ops center. The acceptable use policies (AUP), although differing by country, allows any scientific program or project the use of their networks. Once in compliance with the first RENs AUP, all others will accept that specific traffic including regional and transoceanic networks. RENs can support spaceflight related scientific programs and projects. Getting the science to the researcher is obviously key to any scientific project. RENs provide a pathway to virtually any college or university in the world, as well as many governmental institutes and

Application of the critical pathway and integrated case teaching method to nursing orientation.

Science.gov (United States)

Goodman, D

1997-01-01

Nursing staff development programs must be responsive to current changes in healthcare. New nursing staff must be prepared to manage continuous change and to function competently in clinical practice. The orientation pathway, based on a case management model, is used as a structure for the orientation phase of staff development. The integrated case is incorporated as a teaching strategy in orientation. The integrated case method is based on discussion and analysis of patient situations with emphasis on role modeling and integration of theory and skill. The orientation pathway and integrated case teaching method provide a useful framework for orientation of new staff. Educators, preceptors and orientees find the structure provided by the orientation pathway very useful. Orientation that is developed, implemented and evaluated based on a case management model with the use of an orientation pathway and incorporation of an integrated case teaching method provides a standardized structure for orientation of new staff. This approach is designed for the adult learner, promotes conceptual reasoning, and encourages the social and contextual basis for continued learning.

Grappling with the HOX network in hematopoiesis and leukemia.

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McGonigle, Glenda J; Lappin, Terence R J; Thompson, Alexander

2008-05-01

The mammalian HOX gene network encodes a family of proteins which act as master regulators of developmental processes such as embryogenesis and hematopoiesis. The complex arrangement, regulation and co-factor association of HOX has been an area of intense research, particularly in cancer biology, for over a decade. The concept of redeployment of embryonic regulators in the neoplastic arena has received support from many quarters. Observations of altered HOX gene expression in various solid tumours and leukemia appear to support the thesis that 'oncology recapitulates ontogeny' but the identification of critical HOX subsets and their functional role in cancer onset and maintenance requires further investigation. The application of novel techniques and model systems will continue to enhance our understanding of the HOX network in the years to come. Better understanding of the intricacy of the complex as well as identification of functional pathways and direct targets of the encoded proteins will permit harnessing of this family of genes for clinical application.

The identification of critical groups

International Nuclear Information System (INIS)

Hunt, G.J.; Shepherd, J.G.

1980-01-01

The criteria for critical group identification are summarized and the extent to which they are satisfied by possible numerical methods are examined, drawing on UK experience in dose estimation within a system for setting controls on liquid radioactive waste discharges from major nuclear installations. The nature of the exposure pathway is an important factor in identifying an appropriate method. It is held that there is a greater uncertainty in estimating individual exposure from internal exposure than that from external exposure due to the greater relevance of metabolic variations. Accordingly different methods are proposed for numerical treatment of data associated with internal exposure pathways compared with external exposure pathways. (H.K.)

The return of metabolism: biochemistry and physiology of the pentose phosphate pathway

Science.gov (United States)

Stincone, Anna; Prigione, Alessandro; Cramer, Thorsten; Wamelink, Mirjam M. C.; Campbell, Kate; Cheung, Eric; Olin-Sandoval, Viridiana; Grüning, Nana-Maria; Krüger, Antje; Alam, Mohammad Tauqeer; Keller, Markus A.; Breitenbach, Michael; Brindle, Kevin M.; Rabinowitz, Joshua D.; Ralser, Markus

2015-01-01

The pentose phosphate pathway (PPP) is a fundamental component of cellular metabolism. The PPP is important to maintain carbon homoeostasis, to provide precursors for nucleotide and amino acid biosynthesis, to provide reducing molecules for anabolism, and to defeat oxidative stress. The PPP shares reactions with the Entner–Doudoroff pathway and Calvin cycle and divides into an oxidative and non-oxidative branch. The oxidative branch is highly active in most eukaryotes and converts glucose 6-phosphate into carbon dioxide, ribulose 5-phosphate and NADPH. The latter function is critical to maintain redox balance under stress situations, when cells proliferate rapidly, in ageing, and for the ‘Warburg effect’ of cancer cells. The non-oxidative branch instead is virtually ubiquitous, and metabolizes the glycolytic intermediates fructose 6-phosphate and glyceraldehyde 3-phosphate as well as sedoheptulose sugars, yielding ribose 5-phosphate for the synthesis of nucleic acids and sugar phosphate precursors for the synthesis of amino acids. Whereas the oxidative PPP is considered unidirectional, the non-oxidative branch can supply glycolysis with intermediates derived from ribose 5-phosphate and vice versa, depending on the biochemical demand. These functions require dynamic regulation of the PPP pathway that is achieved through hierarchical interactions between transcriptome, proteome and metabolome. Consequently, the biochemistry and regulation of this pathway, while still unresolved in many cases, are archetypal for the dynamics of the metabolic network of the cell. In this comprehensive article we review seminal work that led to the discovery and description of the pathway that date back now for 80 years, and address recent results about genetic and metabolic mechanisms that regulate its activity. These biochemical principles are discussed in the context of PPP deficiencies causing metabolic disease and the role of this pathway in biotechnology, bacterial and

Transcriptomics, NF-κB Pathway, and Their Potential Spaceflight-Related Health Consequences.

Science.gov (United States)

Zhang, Ye; Moreno-Villanueva, Maria; Krieger, Stephanie; Ramesh, Govindarajan T; Neelam, Srujana; Wu, Honglu

2017-05-31

In space, living organisms are exposed to multiple stress factors including microgravity and space radiation. For humans, these harmful environmental factors have been known to cause negative health impacts such as bone loss and immune dysfunction. Understanding the mechanisms by which spaceflight impacts human health at the molecular level is critical not only for accurately assessing the risks associated with spaceflight, but also for developing effective countermeasures. Over the years, a number of studies have been conducted under real or simulated space conditions. RNA and protein levels in cellular and animal models have been targeted in order to identify pathways affected by spaceflight. Of the many pathways responsive to the space environment, the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) network appears to commonly be affected across many different cell types under the true or simulated spaceflight conditions. NF-κB is of particular interest, as it is associated with many of the spaceflight-related health consequences. This review intends to summarize the transcriptomics studies that identified NF-κB as a responsive pathway to ground-based simulated microgravity or the true spaceflight condition. These studies were carried out using either human cell or animal models. In addition, the review summarizes the studies that focused specifically on NF-κB pathway in specific cell types or organ tissues as related to the known spaceflight-related health risks including immune dysfunction, bone loss, muscle atrophy, central nerve system (CNS) dysfunction, and risks associated with space radiation. Whether the NF-κB pathway is activated or inhibited in space is dependent on the cell type, but the potential health impact appeared to be always negative. It is argued that more studies on NF-κB should be conducted to fully understand this particular pathway for the benefit of crew health in space.

Transcriptomics, NF-κB Pathway, and Their Potential Spaceflight-Related Health Consequences

Directory of Open Access Journals (Sweden)

Ye Zhang

2017-05-01

Full Text Available In space, living organisms are exposed to multiple stress factors including microgravity and space radiation. For humans, these harmful environmental factors have been known to cause negative health impacts such as bone loss and immune dysfunction. Understanding the mechanisms by which spaceflight impacts human health at the molecular level is critical not only for accurately assessing the risks associated with spaceflight, but also for developing effective countermeasures. Over the years, a number of studies have been conducted under real or simulated space conditions. RNA and protein levels in cellular and animal models have been targeted in order to identify pathways affected by spaceflight. Of the many pathways responsive to the space environment, the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB network appears to commonly be affected across many different cell types under the true or simulated spaceflight conditions. NF-κB is of particular interest, as it is associated with many of the spaceflight-related health consequences. This review intends to summarize the transcriptomics studies that identified NF-κB as a responsive pathway to ground-based simulated microgravity or the true spaceflight condition. These studies were carried out using either human cell or animal models. In addition, the review summarizes the studies that focused specifically on NF-κB pathway in specific cell types or organ tissues as related to the known spaceflight-related health risks including immune dysfunction, bone loss, muscle atrophy, central nerve system (CNS dysfunction, and risks associated with space radiation. Whether the NF-κB pathway is activated or inhibited in space is dependent on the cell type, but the potential health impact appeared to be always negative. It is argued that more studies on NF-κB should be conducted to fully understand this particular pathway for the benefit of crew health in space.

RIP2 Is a Critical Regulator for NLRs Signaling and MHC Antigen Presentation but Not for MAPK and PI3K/Akt Pathways.

Science.gov (United States)

Wu, Xiao Man; Chen, Wen Qin; Hu, Yi Wei; Cao, Lu; Nie, Pin; Chang, Ming Xian

2018-01-01

RIP2 is an adaptor protein which is essential for the activation of NF-κB and NOD1- and NOD2-dependent signaling. Although NOD-RIP2 axis conservatively existed in the teleost, the function of RIP2 was only reported in zebrafish, goldfish, and rainbow trout in vitro . Very little is known about the role and mechanisms of piscine NOD-RIP2 axis in vivo . Our previous study showed the protective role of zebrafish NOD1 in larval survival through CD44a-mediated activation of PI3K-Akt signaling. In this study, we examined whether RIP2 was required for larval survival with or without pathogen infection, and determined the signaling pathways modulated by RIP2. Based on our previous report and the present study, our data demonstrated that NOD1-RIP2 axis was important for larval survival in the early ontogenesis. Similar to NOD1, RIP2 deficiency significantly affected immune system processes. The significantly enriched pathways were mainly involved in immune system, such as "Antigen processing and presentation" and "NOD-like receptor signaling pathway" and so on. Furthermore, both transcriptome analysis and qRT-PCR revealed that RIP2 was a critical regulator for expression of NLRs (NOD-like receptors) and those genes involved in MHC antigen presentation. Different from NOD1, the present study showed that NOD1, but not RIP2 deficiency significantly impaired protein levels of MAPK pathways. Although RIP2 deficiency also significantly impaired the expression of CD44a, the downstream signaling of CD44a-Lck-PI3K-Akt pathway remained unchanged. Collectively, our works highlight the similarity and discrepancy of NOD1 and RIP2 in the regulation of immune signaling pathways in the zebrafish early ontogenesis, and confirm the crucial role of RIP2 in NLRs signaling and MHC antigen presentation, but not for MAPK and PI3K/Akt pathways.

Prediction of critical heat flux in narrow rectangular channels using an artificial neural network

International Nuclear Information System (INIS)

Zhou Lei; Yan Xiao; Huang Yanping; Xiao Zejun; Yu Jiyang

2011-01-01

The concept of Critical heat flux (CHF) and its importance are introduced and the meaning to research CHF in narrow rectangular channels independently is emphasized. This paper is the first effort to predict CHF in NRCs using aritificial neural network. The mathematical structure of the artificial neural network and the error back-propagation algorithm are introduced. To predict CHF, the four dimensionless groups are inputted to the neural network and the output is the dimensionless CHF. As the hidden nodes increased, the training error decreases while the testing error decreases firstly and then transition occurs. Based on this, the hidden nodes are set as 5 and the trained network predicts all of the training and testing data points with RMS=0.0016 and μ=1.0003, which is better than several well-known existing correlations. Based on the trained network, the effect of several parameters on CHF are simulated and discussed. CHF increases almost linearly as the inlet subcooling increases. And larger mass flux enhances the effect of the inlet subcooling. CHF increases with the mass flux increasing. And the effect seems to be a little stronger for relatively low system pressure. CHF decreases almost linearly as the system pressure increases for the fixed inlet condition. The slope of the curve also increases with higher mass flux. This observation is limited to the ranges of the experimental database. CHF decreases as the heated length is increased and the gradients of the curves become very sharp for relatively short channel. CHF increases slightly with the diameter increasing with the variance of the gap limited within 1 to 3 mm. For relatively low mass flux, the effect of the equivalent diameter on CHF is insignificant. As the width of the channel is large enough, the effect of the gap is quite the same as that of the equivalent diameter. A BPNN is successfully trained based on near 500 CHF data points in NRCs, which has much better performances than the

CyLineUp: A Cytoscape app for visualizing data in network small multiples.

Science.gov (United States)

Costa, Maria Cecília D; Slijkhuis, Thijs; Ligterink, Wilco; Hilhorst, Henk W M; de Ridder, Dick; Nijveen, Harm

2016-01-01

CyLineUp is a Cytoscape 3 app for the projection of high-throughput measurement data from multiple experiments/samples on a network or pathway map using "small multiples". This visualization method allows for easy comparison of different experiments in the context of the network or pathway. The user can import various kinds of measurement data and select any appropriate Cytoscape network or WikiPathways pathway map. CyLineUp creates small multiples by replicating the loaded network as many times as there are experiments/samples (e.g. time points, stress conditions, tissues, etc.). The measurement data for each experiment are then mapped onto the nodes (genes, proteins etc.) of the corresponding network using a color gradient. Each step of creating the visualization can be customized to the user's needs. The results can be exported as a high quality vector image.

Network reconfiguration and neuronal plasticity in rhythm-generating networks.

Science.gov (United States)

Koch, Henner; Garcia, Alfredo J; Ramirez, Jan-Marino

2011-12-01

Neuronal networks are highly plastic and reconfigure in a state-dependent manner. The plasticity at the network level emerges through multiple intrinsic and synaptic membrane properties that imbue neurons and their interactions with numerous nonlinear properties. These properties are continuously regulated by neuromodulators and homeostatic mechanisms that are critical to maintain not only network stability and also adapt networks in a short- and long-term manner to changes in behavioral, developmental, metabolic, and environmental conditions. This review provides concrete examples from neuronal networks in invertebrates and vertebrates, and illustrates that the concepts and rules that govern neuronal networks and behaviors are universal.

Critical Action as a Pathway to Social Mobility among Marginalized Youth

Science.gov (United States)

Rapa, Luke J.; Diemer, Matthew A.; Bañales, Josefina

2018-01-01

Marginalized youth's development occurs in contexts rife with racialized, gendered, and socioeconomic social identity threats and barriers to social mobility. An emergent line of inquiry suggests critical action--a component of critical consciousness, defined as engaging in individual or collective social action to produce social change--may…

Fostering Collaboration Across the U.S. Critical Zone Observatories Network

Science.gov (United States)

Sharkey, S.; White, T. S.

2017-12-01

The Critical Zone (CZ) is defined as the permeable layer from the top of the vegetation canopy to the bottom of freely circulating groundwater where rock, soil, water, air and life meet. The study of the CZ is motivated by an overall lack of understanding of the coupled physical, chemical, and biological processes in this zone at differing spatial and temporal scales. Critical Zone Observatories (CZOs), supported by the U.S. National Science Foundation's Geosciences Directorate, are natural laboratories that aim to provide infrastructure, data and models to gain understanding of the evolution and function of the CZ from grain-to-watershed scales. The nine U.S. observatories span a range of climatic, ecologic, geologic, and physiographic environments from California to Puerto Rico, working on site-specific hypotheses and network-scale goals. CZO research infrastructure allows for teams of cross-disciplinary scientists at each site to further CZ science using field and theoretical approaches, education and outreach, and cross-CZO science. Cross-CZO science emerges from a set of common CZ science questions and hypotheses focused on CZ structure and evolution, event-based and continuous fluxes across CZ interfaces, and changes in storage of major CZ reservoirs at the catchment scale. CZO research seeks to understand coupled processes across all timescales using quantitative models parameterized from observations of meteorological variables, streams, and groundwater, and sampling and analyzing landforms, bedrock, soils, and ecosystems. Each observatory strives to apply common infrastructure, protocols and measurements that help quantify the composition and fluxes of energy, water, solutes, sediments, energy, and mass across boundaries of the CZ system through both space and time. This type of approach enables researchers to access and integrate data in a way that allows for the isolation of environmental variables and comparison of processes and responses across

The EH network

DEFF Research Database (Denmark)

Santolini, E; Salcini, A E; Kay, B K

1999-01-01

. Moreover, a number of cellular ligands of the domain have been identified and demonstrated to define a complex network of protein-protein interactions in the eukaryotic cell. Interestingly, many of the EH-containing and EH-binding proteins display characteristics of endocytic "accessory" proteins......, suggesting that the principal function of the EH network is to regulate various steps in endocytosis. In addition, recent evidence suggests that the EH network might work as an "integrator" of signals controlling cellular pathways as diverse as endocytosis, nucleocytosolic export, and ultimately cell...

Age-related physical and psychological vulnerability as pathways to problem gambling in older adults.

Science.gov (United States)

Parke, Adrian; Griffiths, Mark; Pattinson, Julie; Keatley, David

2018-03-01

Background To inform clinical treatment and preventative efforts, there is an important need to understand the pathways to late-life gambling disorder. Aims This study assesses the association between age-related physical health, social networks, and problem gambling in adults aged over 65 years and assesses the mediating role of affective disorders in this association. Methods The sample comprised 595 older adults (mean age: 74.4 years, range: 65-94 years; 77.1% female) who were interviewed using a structured questionnaire to assess physical frailty, geriatric pain, loneliness, geriatric depression, geriatric anxiety, and problem gambling. Results Pathway analysis demonstrated associations between these variables and gambling problems, providing a good fit for the data, but that critically these relationships were mediated by both anxiety and depression symptoms. Conclusions This study indicates that late-life problem gambling may develop as vulnerable individuals gamble to escape anxiety and depression consequent to deteriorating physical well-being and social support. When individuals develop late-life problem gambling, it is recommended that the treatment primarily focuses upon targeting and replacing avoidant coping approaches.

Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

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Nitta, Tohru

2017-10-01

We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

Spike-timing computation properties of a feed-forward neural network model

Directory of Open Access Journals (Sweden)

Drew Benjamin Sinha

2014-01-01

Full Text Available Brain function is characterized by dynamical interactions among networks of neurons. These interactions are mediated by network topology at many scales ranging from microcircuits to brain areas. Understanding how networks operate can be aided by understanding how the transformation of inputs depends upon network connectivity patterns, e.g. serial and parallel pathways. To tractably determine how single synapses or groups of synapses in such pathways shape transformations, we modeled feed-forward networks of 7-22 neurons in which synaptic strength changed according to a spike-timing dependent plasticity rule. We investigated how activity varied when dynamics were perturbed by an activity-dependent electrical stimulation protocol (spike-triggered stimulation; STS in networks of different topologies and background input correlations. STS can successfully reorganize functional brain networks in vivo, but with a variability in effectiveness that may derive partially from the underlying network topology. In a simulated network with a single disynaptic pathway driven by uncorrelated background activity, structured spike-timing relationships between polysynaptically connected neurons were not observed. When background activity was correlated or parallel disynaptic pathways were added, however, robust polysynaptic spike timing relationships were observed, and application of STS yielded predictable changes in synaptic strengths and spike-timing relationships. These observations suggest that precise input-related or topologically induced temporal relationships in network activity are necessary for polysynaptic signal propagation. Such constraints for polysynaptic computation suggest potential roles for higher-order topological structure in network organization, such as maintaining polysynaptic correlation in the face of relatively weak synapses.