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Sample records for links signaling network

  1. Novel links in the plant TOR kinase signaling network.

    PubMed

    Xiong, Yan; Sheen, Jen

    2015-12-01

    Nutrient and energy sensing and signaling mechanisms constitute the most ancient and fundamental regulatory networks to control growth and development in all life forms. The target of rapamycin (TOR) protein kinase is modulated by diverse nutrient, energy, hormone and stress inputs and plays a central role in regulating cell proliferation, growth, metabolism and stress responses from yeasts to plants and animals. Recent chemical, genetic, genomic and metabolomic analyses have enabled significant progress toward molecular understanding of the TOR signaling network in multicellular plants. This review discusses the applications of new chemical tools to probe plant TOR functions and highlights recent findings and predictions on TOR-mediate biological processes. Special focus is placed on novel and evolutionarily conserved TOR kinase effectors as positive and negative signaling regulators that control transcription, translation and metabolism to support cell proliferation, growth and maintenance from embryogenesis to senescence in the plant system.

  2. Full-Duplex Link Providing Alternative Wired and Wireless Broadband Access for the Wavelength-Division Multiplexing Passive Optical Network with a Uniform Converged Signal Format

    NASA Astrophysics Data System (ADS)

    Ma, Jianxin

    2014-05-01

    A full-duplex link implementing alternative wired and wireless access for wavelength-division multiplexing passive optical network is proposed with the uniformed three-tone converged optical signal, which provides a wired or wireless downlink access signal alternatively and an uplink optical carrier. The uplink optical carrier reversed by the converged optical signal makes the hybrid optical node unit free from the optical source. The simulation results show that the full-duplex link with a 10-Gb/s 16-quadrature amplitude modulation (16-QAM) downstream and 5 Gb/s binary upstream can provide both wired access with a bit-error rate below 10-9 and radio-over-fiber-based wireless access with a bit-error rate below 10-7 over 40 km of fiber without an optical source and optical amplifier in the hybrid optical node unit.

  3. "Conjectural" links in complex networks

    NASA Astrophysics Data System (ADS)

    Snarskii, A. A.; Zorinets, D. I.; Lande, D. V.

    2016-11-01

    This paper introduces the concept of Conjectural Link for Complex Networks, in particular, social networks. Conjectural Link we understand as an implicit link, not available in the network, but supposed to be present, based on the characteristics of its topology. It is possible, for example, when in the formal description of the network some connections are skipped due to errors, deliberately hidden or withdrawn (e.g. in the case of partial destruction of the network). Introduced a parameter that allows ranking the Conjectural Link. The more this parameter - the more likely that this connection should be present in the network. This paper presents a method of recovery of partially destroyed Complex Networks using Conjectural Links finding. Presented two methods of finding the node pairs that are not linked directly to one another, but have a great possibility of Conjectural Link communication among themselves: a method based on the determination of the resistance between two nodes, and method based on the computation of the lengths of routes between two nodes. Several examples of real networks are reviewed and performed a comparison to know network links prediction methods, not intended to find the missing links in already formed networks.

  4. PIPELINES AS COMMUNICATION NETWORK LINKS

    SciTech Connect

    Kelvin T. Erickson; Ann Miller; E. Keith Stanek; C.H. Wu; Shari Dunn-Norman

    2005-03-14

    This report presents the results of an investigation into two methods of using the natural gas pipeline as a communication medium. The work addressed the need to develop secure system monitoring and control techniques between the field and control centers and to robotic devices in the pipeline. In the first method, the pipeline was treated as a microwave waveguide. In the second method, the pipe was treated as a leaky feeder or a multi-ground neutral and the signal was directly injected onto the metal pipe. These methods were tested on existing pipeline loops at UMR and Batelle. The results reported in this report indicate the feasibility of both methods. In addition, a few suitable communication link protocols for this network were analyzed.

  5. Link weight evolution in a network of coupled chemical oscillators.

    PubMed

    Ke, Hua; Tinsley, Mark R; Steele, Aaron; Wang, Fang; Showalter, Kenneth

    2014-05-01

    Link weight evolution is studied in a network of coupled chemical oscillators. Oscillators are perturbed by adjustments in imposed light intensity based on excitatory or inhibitory links to other oscillators undergoing excitation. Experimental and modeling studies demonstrate that the network is capable of producing sustained coordinated activity. The individual nodes of the network exhibit incoherent firing events; however, a dominant frequency can be discerned within the collective signal by Fourier analysis. The introduction of spike-timing-dependent plasticity yields a network that evolves to a stable unimodal link weight distribution.

  6. LinkMind: link optimization in swarming mobile sensor networks.

    PubMed

    Ngo, Trung Dung

    2011-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation. PMID:22164070

  7. LinkMind: Link Optimization in Swarming Mobile Sensor Networks

    PubMed Central

    Ngo, Trung Dung

    2011-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation. PMID:22164070

  8. LinkMind: link optimization in swarming mobile sensor networks.

    PubMed

    Ngo, Trung Dung

    2011-01-01

    A swarming mobile sensor network is comprised of a swarm of wirelessly connected mobile robots equipped with various sensors. Such a network can be applied in an uncertain environment for services such as cooperative navigation and exploration, object identification and information gathering. One of the most advantageous properties of the swarming wireless sensor network is that mobile nodes can work cooperatively to organize an ad-hoc network and optimize the network link capacity to maximize the transmission of gathered data from a source to a target. This paper describes a new method of link optimization of swarming mobile sensor networks. The new method is based on combination of the artificial potential force guaranteeing connectivities of the mobile sensor nodes and the max-flow min-cut theorem of graph theory ensuring optimization of the network link capacity. The developed algorithm is demonstrated and evaluated in simulation.

  9. Growing Networks with Positive and Negative Links

    NASA Astrophysics Data System (ADS)

    Dech, Corynne; Antwi, Shadrack; Shaw, Leah

    Scale-free networks grown via preferential attachment have been used to model real-world networks such as the Internet, citation networks, and social networks. Here we investigate signed scale-free networks where an edge represents a positive or negative connection. We present analytic results and simulation for a growing signed network model. We compare the signed network to an unsigned scale-free network. We discuss several options for preferential attachment in a signed network that could be further adapted to model the accumulation of links over time in real-world signed networks.

  10. Link prediction in complex networks: A survey

    NASA Astrophysics Data System (ADS)

    Lü, Linyuan; Zhou, Tao

    2011-03-01

    Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labeled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.

  11. SIGNALING NETWORKS IN PALATE DEVELOPMENT

    PubMed Central

    Lane, Jamie; Kaartinen, Vesa

    2014-01-01

    Palatogenesis, the formation of the palate, is a dynamic process that is regulated by a complex series of context-dependent morphogenetic signaling events. Many genes involved in palatogenesis have been discovered through the use of genetically-manipulated mouse models as well as from human genetic studies, but the roles of these genes and their products in signaling networks regulating palatogenesis are still poorly known. In this review, we give a brief overview on palatogenesis and introduce key signaling cascades leading to formation of the intact palate. Moreover, we review conceptual differences between pathway biology and network biology and discuss how some of the recent technological advances in conjunction with mouse genetic models have contributed to our understanding of signaling networks regulating palate growth and fusion. PMID:24644145

  12. The Hedgehog Signal Transduction Network

    PubMed Central

    Robbins, David J.; Fei, Dennis Liang; Riobo, Natalia A.

    2013-01-01

    Hedgehog (Hh) proteins regulate the development of a wide range of metazoan embryonic and adult structures, and disruption of Hh signaling pathways results in various human diseases. Here, we provide a comprehensive review of the signaling pathways regulated by Hh, consolidating data from a diverse array of organisms in a variety of scientific disciplines. Similar to the elucidation of many other signaling pathways, our knowledge of Hh signaling developed in a sequential manner centered on its earliest discoveries. Thus, our knowledge of Hh signaling has for the most part focused on elucidating the mechanism by which Hh regulates the Gli family of transcription factors, the so-called “canonical” Hh signaling pathway. However, in the past few years, numerous studies have shown that Hh proteins can also signal through Gli-independent mechanisms collectively referred to as “noncanonical” signaling pathways. Noncanonical Hh signaling is itself subdivided into two distinct signaling modules: (i) those not requiring Smoothened (Smo) and (ii) those downstream of Smo that do not require Gli transcription factors. Thus, Hh signaling is now proposed to occur through a variety of distinct context-dependent signaling modules that have the ability to crosstalk with one another to form an interacting, dynamic Hh signaling network. PMID:23074268

  13. Cross-linked structure of network evolution

    SciTech Connect

    Bassett, Danielle S.; Wymbs, Nicholas F.; Grafton, Scott T.; Porter, Mason A.; Mucha, Peter J.

    2014-03-15

    We study the temporal co-variation of network co-evolution via the cross-link structure of networks, for which we take advantage of the formalism of hypergraphs to map cross-link structures back to network nodes. We investigate two sets of temporal network data in detail. In a network of coupled nonlinear oscillators, hyperedges that consist of network edges with temporally co-varying weights uncover the driving co-evolution patterns of edge weight dynamics both within and between oscillator communities. In the human brain, networks that represent temporal changes in brain activity during learning exhibit early co-evolution that then settles down with practice. Subsequent decreases in hyperedge size are consistent with emergence of an autonomous subgraph whose dynamics no longer depends on other parts of the network. Our results on real and synthetic networks give a poignant demonstration of the ability of cross-link structure to uncover unexpected co-evolution attributes in both real and synthetic dynamical systems. This, in turn, illustrates the utility of analyzing cross-links for investigating the structure of temporal networks.

  14. Toward link predictability of complex networks

    PubMed Central

    Lü, Linyuan; Pan, Liming; Zhou, Tao; Zhang, Yi-Cheng; Stanley, H. Eugene

    2015-01-01

    The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners. PMID:25659742

  15. Toward link predictability of complex networks.

    PubMed

    Lü, Linyuan; Pan, Liming; Zhou, Tao; Zhang, Yi-Cheng; Stanley, H Eugene

    2015-02-24

    The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability and (ii) a derivative algorithm outperforms state-of-the-art link prediction methods in both accuracy and robustness. This analysis has further applications in evaluating link prediction algorithms and monitoring sudden changes in evolving network mechanisms. It will provide unique fundamental insights into the above-mentioned academic research fields, and will foster the development of advanced information filtering technologies of interest to information technology practitioners.

  16. Hypothesis generation in signaling networks.

    PubMed

    Ruths, Derek A; Nakhleh, Luay; Iyengar, M Sriram; Reddy, Shrikanth A G; Ram, Prahlad T

    2006-11-01

    Biological signaling networks comprise the chemical processes by which cells detect and respond to changes in their environment. Such networks have been implicated in the regulation of important cellular activities, including cellular reproduction, mobility, and death. Though technological and scientific advances have facilitated the rapid accumulation of information about signaling networks, utilizing these massive information resources has become infeasible except through computational methods and computer-based tools. To date, visualization and simulation tools have received significant emphasis. In this paper, we present a graph-theoretic formalization of biological signaling network models that are in wide but informal use, and formulate two problems on the graph: the Constrained Downstream and Minimum Knockout Problems. Solutions to these problems yield qualitative tools for generating hypotheses about the networks, which can then be experimentally tested in a laboratory setting. Using established graph algorithms, we provide a solution to the Constrained Downstream Problem. We also show that the Minimum Knockout Problem is NP-Hard, propose a heuristic, and assess its performance. In tests on the Epidermal Growth Factor Receptor (EGFR) network, we find that our heuristic reports the correct solution to the problem in seconds. Source code for the implementations of both solutions is available from the authors upon request.

  17. Linking brain imaging signals to visual perception.

    PubMed

    Welchman, Andrew E; Kourtzi, Zoe

    2013-11-01

    The rapid advances in brain imaging technology over the past 20 years are affording new insights into cortical processing hierarchies in the human brain. These new data provide a complementary front in seeking to understand the links between perceptual and physiological states. Here we review some of the challenges associated with incorporating brain imaging data into such "linking hypotheses," highlighting some of the considerations needed in brain imaging data acquisition and analysis. We discuss work that has sought to link human brain imaging signals to existing electrophysiological data and opened up new opportunities in studying the neural basis of complex perceptual judgments. We consider a range of approaches when using human functional magnetic resonance imaging to identify brain circuits whose activity changes in a similar manner to perceptual judgments and illustrate these approaches by discussing work that has studied the neural basis of 3D perception and perceptual learning. Finally, we describe approaches that have sought to understand the information content of brain imaging data using machine learning and work that has integrated multimodal data to overcome the limitations associated with individual brain imaging approaches. Together these approaches provide an important route in seeking to understand the links between physiological and psychological states.

  18. Bounded link prediction in very large networks

    NASA Astrophysics Data System (ADS)

    Cui, Wei; Pu, Cunlai; Xu, Zhongqi; Cai, Shimin; Yang, Jian; Michaelson, Andrew

    2016-09-01

    Evaluating link prediction methods is a hard task in very large complex networks due to the prohibitive computational cost. However, if we consider the lower bound of node pairs' similarity scores, this task can be greatly optimized. In this paper, we study CN index in the bounded link prediction framework, which is applicable to enormous heterogeneous networks. Specifically, we propose a fast algorithm based on the parallel computing scheme to obtain all node pairs with CN values larger than the lower bound. Furthermore, we propose a general measurement, called self-predictability, to quantify the performance of similarity indices in link prediction, which can also indicate the link predictability of networks with respect to given similarity indices.

  19. Porous Cross-Linked Polyimide Networks

    NASA Technical Reports Server (NTRS)

    Meador, Mary Ann B. (Inventor); Guo, Haiquan (Inventor)

    2015-01-01

    Porous cross-linked polyimide networks are provided. The networks comprise an anhydride end-capped polyamic acid oligomer. The oligomer (i) comprises a repeating unit of a dianhydride and a diamine and terminal anhydride groups, (ii) has an average degree of polymerization of 10 to 50, (iii) has been cross-linked via a cross-linking agent, comprising three or more amine groups, at a balanced stoichiometry of the amine groups to the terminal anhydride groups, and (iv) has been chemically imidized to yield the porous cross-linked polyimide network. Also provided are porous cross-linked polyimide aerogels comprising a cross-linked and imidized anhydride end-capped polyamic acid oligomer, wherein the oligomer comprises a repeating unit of a dianhydride and a diamine, and the aerogel has a density of 0.10 to 0.333 g/cm.sup.3 and a Young's modulus of 1.7 to 102 MPa. Also provided are thin films comprising aerogels, and methods of making porous cross-linked polyimide networks.

  20. Missing and forbidden links in mutualistic networks.

    PubMed

    Olesen, Jens M; Bascompte, Jordi; Dupont, Yoko L; Elberling, Heidi; Rasmussen, Claus; Jordano, Pedro

    2011-03-01

    Ecological networks are complexes of interacting species, but not all potential links among species are realized. Unobserved links are either missing or forbidden. Missing links exist, but require more sampling or alternative ways of detection to be verified. Forbidden links remain unobservable, irrespective of sampling effort. They are caused by linkage constraints. We studied one Arctic pollination network and two Mediterranean seed-dispersal networks. In the first, for example, we recorded flower-visit links for one full season, arranged data in an interaction matrix and got a connectance C of 15 per cent. Interaction accumulation curves documented our sampling of interactions through observation of visits to be robust. Then, we included data on pollen from the body surface of flower visitors as an additional link 'currency'. This resulted in 98 new links, missing from the visitation data. Thus, the combined visit-pollen matrix got an increased C of 20 per cent. For the three networks, C ranged from 20 to 52 per cent, and thus the percentage of unobserved links (100 - C) was 48 to 80 per cent; these were assumed forbidden because of linkage constraints and not missing because of under-sampling. Phenological uncoupling (i.e. non-overlapping phenophases between interacting mutualists) is one kind of constraint, and it explained 22 to 28 per cent of all possible, but unobserved links. Increasing phenophase overlap between species increased link probability, but extensive overlaps were required to achieve a high probability. Other kinds of constraint, such as size mismatch and accessibility limitations, are briefly addressed.

  1. Retrograde signaling: Organelles go networking.

    PubMed

    Kleine, Tatjana; Leister, Dario

    2016-08-01

    The term retrograde signaling refers to the fact that chloroplasts and mitochondria utilize specific signaling molecules to convey information on their developmental and physiological states to the nucleus and modulate the expression of nuclear genes accordingly. Signals emanating from plastids have been associated with two main networks: 'Biogenic control' is active during early stages of chloroplast development, while 'operational' control functions in response to environmental fluctuations. Early work focused on the former and its major players, the GUN proteins. However, our view of retrograde signaling has since been extended and revised. Elements of several 'operational' signaling circuits have come to light, including metabolites, signaling cascades in the cytosol and transcription factors. Here, we review recent advances in the identification and characterization of retrograde signaling components. We place particular emphasis on the strategies employed to define signaling components, spanning the entire spectrum of genetic screens, metabolite profiling and bioinformatics. This article is part of a Special Issue entitled 'EBEC 2016: 19th European Bioenergetics Conference, Riva del Garda, Italy, July 2-6, 2016', edited by Prof. Paolo Bernardi. PMID:26997501

  2. Met1-linked ubiquitination in immune signalling

    PubMed Central

    Fiil, Berthe K; Gyrd-Hansen, Mads

    2014-01-01

    N-terminal methionine-linked ubiquitin (Met1-Ub), or linear ubiquitin, has emerged as a central post-translational modification in innate immune signalling. The molecular machinery that assembles, senses and, more recently, disassembles Met1-Ub has been identified, and technical advances have enabled the identification of physiological substrates for Met1-Ub in response to activation of innate immune receptors. These discoveries have significantly advanced our understanding of how nondegradative ubiquitin modifications control proinflammatory responses mediated by nuclear factor-κB and mitogen-activated protein kinases. In this review, we discuss the current data on Met1-Ub function and regulation, and point to some of the questions that still remain unanswered. PMID:25060092

  3. Visualizing Transmedia Networks: Links, Paths and Peripheries

    ERIC Educational Resources Information Center

    Ruppel, Marc Nathaniel

    2012-01-01

    'Visualizing Transmedia Networks: Links, Paths and Peripheries' examines the increasingly complex rhetorical intersections between narrative and media ("old" and "new") in the creation of transmedia fictions, loosely defined as multisensory and multimodal stories told extensively across a diverse media set. In order…

  4. Dopamine D1 signaling organizes network dynamics underlying working memory

    PubMed Central

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

    2016-01-01

    Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography–magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory–emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits. PMID:27386561

  5. Feedback to distal dendrites links fMRI signals to neural receptive fields in a spiking network model of the visual cortex.

    PubMed

    Heikkinen, Hanna; Sharifian, Fariba; Vigario, Ricardo; Vanni, Simo

    2015-07-01

    The blood oxygenation level-dependent (BOLD) response has been strongly associated with neuronal activity in the brain. However, some neuronal tuning properties are consistently different from the BOLD response. We studied the spatial extent of neural and hemodynamic responses in the primary visual cortex, where the BOLD responses spread and interact over much longer distances than the small receptive fields of individual neurons would predict. Our model shows that a feedforward-feedback loop between V1 and a higher visual area can account for the observed spread of the BOLD response. In particular, anisotropic landing of inputs to compartmental neurons were necessary to account for the BOLD signal spread, while retaining realistic spiking responses. Our work shows that simple dendrites can separate tuning at the synapses and at the action potential output, thus bridging the BOLD signal to the neural receptive fields with high fidelity.

  6. Simulated evolution of signal transduction networks.

    PubMed

    Mobashir, Mohammad; Schraven, Burkhart; Beyer, Tilo

    2012-01-01

    Signal transduction is the process of routing information inside cells when receiving stimuli from their environment that modulate the behavior and function. In such biological processes, the receptors, after receiving the corresponding signals, activate a number of biomolecules which eventually transduce the signal to the nucleus. The main objective of our work is to develop a theoretical approach which will help to better understand the behavior of signal transduction networks due to changes in kinetic parameters and network topology. By using an evolutionary algorithm, we designed a mathematical model which performs basic signaling tasks similar to the signaling process of living cells. We use a simple dynamical model of signaling networks of interacting proteins and their complexes. We study the evolution of signaling networks described by mass-action kinetics. The fitness of the networks is determined by the number of signals detected out of a series of signals with varying strength. The mutations include changes in the reaction rate and network topology. We found that stronger interactions and addition of new nodes lead to improved evolved responses. The strength of the signal does not play any role in determining the response type. This model will help to understand the dynamic behavior of the proteins involved in signaling pathways. It will also help to understand the robustness of the kinetics of the output response upon changes in the rate of reactions and the topology of the network.

  7. Node link stability in wireless mobile networks

    NASA Astrophysics Data System (ADS)

    Hökelek, İbrahim; Uyar, M. Ümit; Fecko, Mariusz A.

    2006-05-01

    This paper presents an improvement of a novel analytic model for ad hoc networks based on Markov chains whose states represent node degree and the number of link failures. The model divides a geographic area into logical hexagonal cells, where random walk with probabilistic state-transition matrix determines link creation/failure. We can thus compute two important metrics characterizing the dynamics of a node's random movement: the expected times for the number of link changes to drop below and for the node degree to exceed a threshold. We obtained the two-dimensional Markov chain that allows us to apply these two metrics as the selection rules for the virtual backbone formation algorithm. Hence, our model is used to analyze the performance of service discovery architectures based on virtual backbone in mobile ad-hoc networks. We also plan to extend the created modeling framework to derive a number of additional metrics that characterize network connectivity, capacity, and survivability. Because the model is capable of computing the dynamics and the expected value of the number of a node's neighbors, it can also be used to estimate the level of interference as well as achievable and sustainable routing path diversity, degree of network connectivity, and the stability of routing tables. We expect to apply our modeling framework to analytic assessment of the stability of routing domains. The rate and expected values at which the nodes move in and out of domains characterize the rate of degradation of optimally built routing domains, and hence the resulting routing scalability and overhead.

  8. A Network of Mitogen-Activated Protein Kinases Links G Protein-Coupled Receptors to the c-jun Promoter: a Role for c-Jun NH2-Terminal Kinase, p38s, and Extracellular Signal-Regulated Kinase 5

    PubMed Central

    Marinissen, Maria Julia; Chiariello, Mario; Pallante, Michael; Gutkind, J. Silvio

    1999-01-01

    The expression of the c-jun proto-oncogene is rapidly induced in response to mitogens acting on a large variety of cell surface receptors. The resulting functional activity of c-Jun proteins appears to be critical for cell proliferation. Recently, we have shown that a large family of G protein-coupled receptors (GPCRs), represented by the m1 muscarinic receptor, can initiate intracellular signaling cascades that result in the activation of mitogen-activated protein kinases (MAPK) and c-Jun NH2-terminal kinases (JNK) and that the activation of JNK but not of MAPK correlated with a remarkable increase in the expression of c-jun mRNA. Subsequently, however, we obtained evidence that GPCRs can potently stimulate the activity of the c-jun promoter through MEF2 transcription factors, which do not act downstream from JNK. In view of these observations, we set out to investigate further the nature of the signaling pathway linking GPCRs to the c-jun promoter. Utilizing NIH 3T3 cells, we found that GPCRs can activate the c-jun promoter in a JNK-independent manner. Additionally, we demonstrated that these GPCRs can elevate the activity of novel members of the MAPK family, including ERK5, p38α, p38γ, and p38δ, and that the activation of certain kinases acting downstream from MEK5 (ERK5) and MKK6 (p38α and p38γ) is necessary to fully activate the c-jun promoter. Moreover, in addition to JNK, ERK5, p38α, and p38γ were found to stimulate the c-jun promoter by acting on distinct responsive elements. Taken together, these results suggest that the pathway linking GPCRs to the c-jun promoter involves the integration of numerous signals transduced by a highly complex network of MAPK, rather than resulting from the stimulation of a single linear protein kinase cascade. Furthermore, our findings suggest that each signaling pathway affects one or more regulatory elements on the c-jun promoter and that the transcriptional response most likely results from the temporal integration

  9. A comparative analysis of network robustness against different link attacks

    NASA Astrophysics Data System (ADS)

    Duan, Boping; Liu, Jing; Zhou, Mingxing; Ma, Liangliang

    2016-04-01

    Recently, the study of optimizing network robustness has attracted increasing attentions, and the constraint that every node's degree cannot be changed is considered. Although this constraint maintains the node degree distribution consistently in order to reserve the structure of networks, it makes the network structure be lack of flexibility since many network structure always transform in the modern society. Given this consideration, in this paper, we analyze the robustness of networks through setting a new constraint; that is, only the number of edges should be unchanged. Then, we use the link-robustness index (Rl) as the measure of the network robustness against either random failures or intentional attacks, and make a comparative analysis of network robustness against different types of link attacks. Moreover, we use four types of networks as initial networks, namely scale-free networks, random networks, regular networks, and small-world networks. The experimental results show that the values of robustness measures for the optimized networks starting from different initial networks are similar under different link attacks, but the network topologies may be different. That is to say, networks with different topologies may have similar robustness in terms of the robustness measures. We also find that the optimized networks obtained by one link attack may not robust against other link attacks, sometimes, even weaker than the original networks. Therefore, before building networks, it is better to study which type of link attacks may happen.

  10. Signal transduction in the activation of spermatozoa compared to other signalling pathways: a biological networks study.

    PubMed

    Bernabò, Nicola; Mattioli, Mauro; Barboni, Barbara

    2015-01-01

    In this paper we represented Spermatozoa Activation (SA) the process that leads male gametes to reach their fertilising ability of sea urchin, Caenorhabditis elegans and human as biological networks, i.e. as networks of nodes (molecules) linked by edges (their interactions). Then, we compared them with networks representing ten pathways of relevant physio-pathological importance and with a computer-generated network. We have found that the number of nodes and edges composing each network is not related with the amount of published papers on each specific topic and that all the topological parameters examined are similar in all the networks, thus conferring them a scale free topology and small world behaviour. In conclusion, SA topology, independently from the reproductive biology of considered organism, as others signalling networks is characterised by robustness against random failure, controllability and efficiency in signal transmission. PMID:26489142

  11. Improving interdependent networks robustness by adding connectivity links

    NASA Astrophysics Data System (ADS)

    Ji, Xingpei; Wang, Bo; Liu, Dichen; Chen, Guo; Tang, Fei; Wei, Daqian; Tu, Lian

    2016-02-01

    Compared with a single and isolated network, interdependent networks have two types of links: connectivity link and dependency link. This paper aims to improve the robustness of interdependent networks by adding connectivity links. Firstly, interdependent networks failure model and four frequently used link addition strategies are briefly reviewed. Furthermore, by defining inter degree-degree difference, two novel link addition strategies are proposed. Finally, we verify the effectiveness of our proposed link addition strategies by comparing with the current link addition strategies in three different network models. The simulation results show that, given the number of added links, link allocation strategies have great effects on the robustness of interdependent networks, i.e., the double-network link allocation strategy is superior to single-network link allocation strategy. Link addition strategies proposed in this paper excel the current strategies, especially for BA interdependent networks. Moreover, our work can provide guidance on how to allocate limited resources to an existing interdependent networks system and optimize its topology to avoid the potential cascade failures.

  12. Optimal Prediction by Cellular Signaling Networks

    NASA Astrophysics Data System (ADS)

    Becker, Nils B.; Mugler, Andrew; ten Wolde, Pieter Rein

    2015-12-01

    Living cells can enhance their fitness by anticipating environmental change. We study how accurately linear signaling networks in cells can predict future signals. We find that maximal predictive power results from a combination of input-noise suppression, linear extrapolation, and selective readout of correlated past signal values. Single-layer networks generate exponential response kernels, which suffice to predict Markovian signals optimally. Multilayer networks allow oscillatory kernels that can optimally predict non-Markovian signals. At low noise, these kernels exploit the signal derivative for extrapolation, while at high noise, they capitalize on signal values in the past that are strongly correlated with the future signal. We show how the common motifs of negative feedback and incoherent feed-forward can implement these optimal response functions. Simulations reveal that E. coli can reliably predict concentration changes for chemotaxis, and that the integration time of its response kernel arises from a trade-off between rapid response and noise suppression.

  13. Analysis and logical modeling of biological signaling transduction networks

    NASA Astrophysics Data System (ADS)

    Sun, Zhongyao

    The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

  14. Cascaded multiplexed optical link on a telecommunication network for frequency dissemination.

    PubMed

    Lopez, Olivier; Haboucha, Adil; Kéfélian, Fabien; Jiang, Haifeng; Chanteau, Bruno; Roncin, Vincent; Chardonnet, Christian; Amy-Klein, Anne; Santarelli, Giorgio

    2010-08-01

    We demonstrate a cascaded optical link for ultrastable frequency dissemination comprised of two compensated links of 150 km and a repeater station. Each link includes 114 km of Internet fiber simultaneously carrying data traffic through a dense wavelength division multiplexing technology, and passes through two routing centers of the telecommunication network. The optical reference signal is inserted in and extracted from the communication network using bidirectional optical add-drop multiplexers. The repeater station operates autonomously ensuring noise compensation on the two links and the ultra-stable signal optical regeneration. The compensated link shows a fractional frequency instability of 3 x 10(-15) at one second measurement time and 5 x 10(-20) at 20 hours. This work paves the way to a wide dissemination of ultra-stable optical clock signals between distant laboratories via the Internet network.

  15. Accelerating coordination in temporal networks by engineering the link order

    NASA Astrophysics Data System (ADS)

    Masuda, Naoki

    2016-02-01

    Social dynamics on a network may be accelerated or decelerated depending on which pairs of individuals in the network communicate early and which pairs do later. The order with which the links in a given network are sequentially used, which we call the link order, may be a strong determinant of dynamical behaviour on networks, potentially adding a new dimension to effects of temporal networks relative to static networks. Here we study the effect of the link order on linear coordination (i.e., synchronisation) dynamics. We show that the coordination speed considerably depends on specific orders of links. In addition, applying each single link for a long time to ensure strong pairwise coordination before moving to a next pair of individuals does not often enhance coordination of the entire network. We also implement a simple greedy algorithm to optimise the link order in favour of fast coordination.

  16. Identification of hybrid node and link communities in complex networks

    NASA Astrophysics Data System (ADS)

    He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

    2015-03-01

    Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

  17. Community detection by signaling on complex networks

    NASA Astrophysics Data System (ADS)

    Hu, Yanqing; Li, Menghui; Zhang, Peng; Fan, Ying; di, Zengru

    2008-07-01

    Based on a signaling process of complex networks, a method for identification of community structure is proposed. For a network with n nodes, every node is assumed to be a system which can send, receive, and record signals. Each node is taken as the initial signal source to excite the whole network one time. Then the source node is associated with an n -dimensional vector which records the effects of the signaling process. By this process, the topological relationship of nodes on the network could be transferred into a geometrical structure of vectors in n -dimensional Euclidean space. Then the best partition of groups is determined by F statistics and the final community structure is given by the K -means clustering method. This method can detect community structure both in unweighted and weighted networks. It has been applied to ad hoc networks and some real networks such as the Zachary karate club network and football team network. The results indicate that the algorithm based on the signaling process works well.

  18. Utility-Based Link Recommendation in Social Networks

    ERIC Educational Resources Information Center

    Li, Zhepeng

    2013-01-01

    Link recommendation, which suggests links to connect currently unlinked users, is a key functionality offered by major online social networking platforms. Salient examples of link recommendation include "people you may know"' on Facebook and "who to follow" on Twitter. A social networking platform has two types of stakeholder:…

  19. Optimum waiting time for acquisition of return link PN signals

    NASA Technical Reports Server (NTRS)

    Kolata, W.

    1982-01-01

    The subject of this paper is a model that takes into account the effect that acquisition of a PN signal on the forward link has on the acquisition of a PN signal on the return link. The model is used to determine how long the start of the PN search on the return link should be delayed in order to minimize the combined acquisition time (delay + acquisition time) as a function of desired acquisition probability. It is assumed that the return link a-priori epoch uncertainty information is available. Software has been developed that models the return link PN receiver and incorporates in it the effect of forward link PN acquisition statistics in assessing performance.

  20. Robust bidirectional links for photonic quantum networks

    PubMed Central

    Xu, Jin-Shi; Yung, Man-Hong; Xu, Xiao-Ye; Tang, Jian-Shun; Li, Chuan-Feng; Guo, Guang-Can

    2016-01-01

    Optical fibers are widely used as one of the main tools for transmitting not only classical but also quantum information. We propose and report an experimental realization of a promising method for creating robust bidirectional quantum communication links through paired optical polarization-maintaining fibers. Many limitations of existing protocols can be avoided with the proposed method. In particular, the path and polarization degrees of freedom are combined to deterministically create a photonic decoherence-free subspace without the need for any ancillary photon. This method is input state–independent, robust against dephasing noise, postselection-free, and applicable bidirectionally. To rigorously quantify the amount of quantum information transferred, the optical fibers are analyzed with the tools developed in quantum communication theory. These results not only suggest a practical means for protecting quantum information sent through optical quantum networks but also potentially provide a new physical platform for enriching the structure of the quantum communication theory. PMID:26824069

  1. Robust bidirectional links for photonic quantum networks.

    PubMed

    Xu, Jin-Shi; Yung, Man-Hong; Xu, Xiao-Ye; Tang, Jian-Shun; Li, Chuan-Feng; Guo, Guang-Can

    2016-01-01

    Optical fibers are widely used as one of the main tools for transmitting not only classical but also quantum information. We propose and report an experimental realization of a promising method for creating robust bidirectional quantum communication links through paired optical polarization-maintaining fibers. Many limitations of existing protocols can be avoided with the proposed method. In particular, the path and polarization degrees of freedom are combined to deterministically create a photonic decoherence-free subspace without the need for any ancillary photon. This method is input state-independent, robust against dephasing noise, postselection-free, and applicable bidirectionally. To rigorously quantify the amount of quantum information transferred, the optical fibers are analyzed with the tools developed in quantum communication theory. These results not only suggest a practical means for protecting quantum information sent through optical quantum networks but also potentially provide a new physical platform for enriching the structure of the quantum communication theory.

  2. Design and Analysis of Underwater Acoustic Networks with Reflected Links

    NASA Astrophysics Data System (ADS)

    Emokpae, Lloyd

    Underwater acoustic networks (UWANs) have applications in environmental state monitoring, oceanic profile measurements, leak detection in oil fields, distributed surveillance, and navigation. For these applications, sets of nodes are employed to collaboratively monitor an area of interest and track certain events or phenomena. In addition, it is common to find autonomous underwater vehicles (AUVs) acting as mobile sensor nodes that perform search-and-rescue missions, reconnaissance in combat zones, and coastal patrol. These AUVs are to work cooperatively to achieve a desired goal and thus need to be able to, in an ad-hoc manner, establish and sustain communication links in order to ensure some desired level of quality of service. Therefore, each node is required to adapt to environmental changes and be able to overcome broken communication links caused by external noise affecting the communication channel due to node mobility. In addition, since radio waves are quickly absorbed in the water medium, it is common for most underwater applications to rely on acoustic (or sound) rather than radio channels for mid-to-long range communications. However, acoustic channels pose multiple challenging issues, most notably the high transmission delay due to slow signal propagation and the limited channel bandwidth due to high frequency attenuation. Moreover, the inhomogeneous property of the water medium affects the sound speed profile while the signal surface and bottom reflections leads to multipath effects. In this dissertation, we address these networking challenges by developing protocols that take into consideration the underwater physical layer dynamics. We begin by introducing a novel surface-based reflection scheme (SBR), which takes advantage of the multipath effects of the acoustic channel. SBR works by using reflections from the water surface, and bottom, to establish non-line-of-sight (NLOS) communication links. SBR makes it possible to incorporate both line

  3. Lewis Information Network (LINK): Background and overview

    NASA Technical Reports Server (NTRS)

    Schulte, Roger R.

    1987-01-01

    The NASA Lewis Research Center supports many research facilities with many isolated buildings, including wind tunnels, test cells, and research laboratories. These facilities are all located on a 350 acre campus adjacent to the Cleveland Hopkins Airport. The function of NASA-Lewis is to do basic and applied research in all areas of aeronautics, fluid mechanics, materials and structures, space propulsion, and energy systems. These functions require a great variety of remote high speed, high volume data communications for computing and interactive graphic capabilities. In addition, new requirements for local distribution of intercenter video teleconferencing and data communications via satellite have developed. To address these and future communications requirements for the next 15 yrs, a project team was organized to design and implement a new high speed communication system that would handle both data and video information in a common lab-wide Local Area Network. The project team selected cable television broadband coaxial cable technology as the communications medium and first installation of in-ground cable began in the summer of 1980. The Lewis Information Network (LINK) became operational in August 1982 and has become the backbone of all data communications and video.

  4. Critical Links and Nonlocal Rerouting in Complex Supply Networks

    NASA Astrophysics Data System (ADS)

    Witthaut, Dirk; Rohden, Martin; Zhang, Xiaozhu; Hallerberg, Sarah; Timme, Marc

    2016-04-01

    Link failures repeatedly induce large-scale outages in power grids and other supply networks. Yet, it is still not well understood which links are particularly prone to inducing such outages. Here we analyze how the nature and location of each link impact the network's capability to maintain a stable supply. We propose two criteria to identify critical links on the basis of the topology and the load distribution of the network prior to link failure. They are determined via a link's redundant capacity and a renormalized linear response theory we derive. These criteria outperform the critical link prediction based on local measures such as loads. The results not only further our understanding of the physics of supply networks in general. As both criteria are available before any outage from the state of normal operation, they may also help real-time monitoring of grid operation, employing countermeasures and support network planning and design.

  5. Critical Links and Nonlocal Rerouting in Complex Supply Networks.

    PubMed

    Witthaut, Dirk; Rohden, Martin; Zhang, Xiaozhu; Hallerberg, Sarah; Timme, Marc

    2016-04-01

    Link failures repeatedly induce large-scale outages in power grids and other supply networks. Yet, it is still not well understood which links are particularly prone to inducing such outages. Here we analyze how the nature and location of each link impact the network's capability to maintain a stable supply. We propose two criteria to identify critical links on the basis of the topology and the load distribution of the network prior to link failure. They are determined via a link's redundant capacity and a renormalized linear response theory we derive. These criteria outperform the critical link prediction based on local measures such as loads. The results not only further our understanding of the physics of supply networks in general. As both criteria are available before any outage from the state of normal operation, they may also help real-time monitoring of grid operation, employing countermeasures and support network planning and design. PMID:27082006

  6. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NASA Astrophysics Data System (ADS)

    Overeem, Aart; Uijlenhoet, Remko; Leijnse, Hidde

    2016-04-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. We present a rainfall retrieval algorithm, which is employed to obtain rainfall maps from microwave links in a cellular communication network. We compare these rainfall maps to gauge-adjusted radar rainfall maps. The microwave link data set, as well as the developed code, a package in the open source scripting language "R", are freely available at GitHub (https://github.com/overeem11/RAINLINK). The purpose of this presentation is to promote rainfall mapping utilizing microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  7. Linked in: immunologic membrane nanotube networks.

    PubMed

    Zaccard, C R; Rinaldo, C R; Mailliard, R B

    2016-07-01

    Membrane nanotubes, also termed tunneling nanotubes, are F-actin-based structures that can form direct cytoplasmic connections and support rapid communication between distant cells. These nanoscale conduits have been observed in diverse cell types, including immune, neuronal, stromal, cancer, and stem cells. Until recently, little was known about the mechanisms involved in membrane nanotube development in myeloid origin APCs or how membrane nanotube networks support their ability to bridge innate and adaptive immunity. New research has provided insight into the modes of induction and regulation of the immune process of "reticulation" or the development of multicellular membrane nanotube networks in dendritic cells. Preprogramming by acute type 1 inflammatory mediators at their immature stage licenses mature type 1-polarized dendritic cells to reticulate upon subsequent interaction with CD40 ligand-expressing CD4(+) Th cells. Dendritic cell reticulation can support direct antigen transfer for amplification of specific T cell responses and can be positively or negatively regulated by signals from distinct Th cell subsets. Membrane nanotubes not only enhance the ability of immature dendritic cells to sense pathogens and rapidly mobilize nearby antigen-presenting cells in the peripheral tissues but also likely support communication of pathogen-related information from mature migratory dendritic cells to resident dendritic cells in lymph nodes. Therefore, the reticulation process facilitates a coordinated multicellular response for the efficient initiation of cell-mediated adaptive immune responses. Herein, we discuss studies focused on the molecular mechanisms of membrane nanotube formation, structure, and function in the context of immunity and how pathogens, such as HIV-1, may use dendritic cell reticulation to circumvent host defenses. PMID:26931578

  8. Mixed-method Exploration of Social Network Links to Participation

    PubMed Central

    Kreider, Consuelo M.; Bendixen, Roxanna M.; Mann, William C.; Young, Mary Ellen; McCarty, Christopher

    2015-01-01

    The people who regularly interact with an adolescent form that youth's social network, which may impact participation. We investigated the relationship of social networks to participation using personal network analysis and individual interviews. The sample included 36 youth, age 11 – 16 years. Nineteen had diagnoses of learning disability, attention disorder, or high-functioning autism and 17 were typically developing. Network analysis yielded 10 network variables, of which 8 measured network composition and 2 measured network structure, with significant links to at least one measure of participation using the Children's Assessment of Participation and Enjoyment (CAPE). Interviews from youth in the clinical group yielded description of strategies used to negotiate social interactions, as well as processes and reasoning used to remain engaged within social networks. Findings contribute to understanding the ways social networks are linked to youth participation and suggest the potential of social network factors for predicting rehabilitation outcomes. PMID:26594737

  9. Enhancing complex network controllability by minimum link direction reversal

    NASA Astrophysics Data System (ADS)

    Hou, Lvlin; Lao, Songyang; Small, Michael; Xiao, Yandong

    2015-07-01

    Controllability of complex networks has recently become one of the most popular research fields, but the importance of link direction for controllability has not been systematically considered. We propose a method to enhance controllability of a directed network by changing the direction of a small fraction of links while keeping the total number of links unchanged. The main idea of the method is to find candidate links based on the matching path. Extensive numerical simulation on many modeled networks demonstrates that this method is effective. Furthermore, we find that the nodes linked to candidate links have a distinct character, which provide us with a strategy to improve the controllability based on the local structure. Since the whole topology of many real networks is not visible and we only get some local structure information, this strategy is potentially more practical compared to those that demand complete topology information.

  10. Adenylate Kinase and AMP Signaling Networks: Metabolic Monitoring, Signal Communication and Body Energy Sensing

    PubMed Central

    Dzeja, Petras; Terzic, Andre

    2009-01-01

    Adenylate kinase and downstream AMP signaling is an integrated metabolic monitoring system which reads the cellular energy state in order to tune and report signals to metabolic sensors. A network of adenylate kinase isoforms (AK1-AK7) are distributed throughout intracellular compartments, interstitial space and body fluids to regulate energetic and metabolic signaling circuits, securing efficient cell energy economy, signal communication and stress response. The dynamics of adenylate kinase-catalyzed phosphotransfer regulates multiple intracellular and extracellular energy-dependent and nucleotide signaling processes, including excitation-contraction coupling, hormone secretion, cell and ciliary motility, nuclear transport, energetics of cell cycle, DNA synthesis and repair, and developmental programming. Metabolomic analyses indicate that cellular, interstitial and blood AMP levels are potential metabolic signals associated with vital functions including body energy sensing, sleep, hibernation and food intake. Either low or excess AMP signaling has been linked to human disease such as diabetes, obesity and hypertrophic cardiomyopathy. Recent studies indicate that derangements in adenylate kinase-mediated energetic signaling due to mutations in AK1, AK2 or AK7 isoforms are associated with hemolytic anemia, reticular dysgenesis and ciliary dyskinesia. Moreover, hormonal, food and antidiabetic drug actions are frequently coupled to alterations of cellular AMP levels and associated signaling. Thus, by monitoring energy state and generating and distributing AMP metabolic signals adenylate kinase represents a unique hub within the cellular homeostatic network. PMID:19468337

  11. Design and implementation of a fiber optic link for a token ring local area network

    NASA Astrophysics Data System (ADS)

    Doran, Thomas J.

    1992-09-01

    This thesis describes the design and implementation of a fiber optic link for a token ring local area network (LAN). It features the use of fiber optic channels as the transmission medium between a computer system and a wiring concentrator to convert a physical ring design into a starwired configuration. The LAN was controlled by the TMS380 LAN Adapter chipset, which provided all diagnostic and network management features to include the 4 Mb/s electrical signal for operation. Since this adapter was developed for systems using twisted wire pair adapter cables, design modifications required that the fiber link be able to simulate impedance and current characteristics of copper wire link. This allows the use of adapter diagnostic checks for ring continuity and proper ring operation. Design evaluations using test signals and adapter signals from within the computer-concentrator link showed mixed results. All transmission objectives were met but the circuit loaded down the LAN adapter causing hardware error messages.

  12. Artificial neural networks for classifying olfactory signals.

    PubMed

    Linder, R; Pöppl, S J

    2000-01-01

    For practical applications, artificial neural networks have to meet several requirements: Mainly they should learn quick, classify accurate and behave robust. Programs should be user-friendly and should not need the presence of an expert for fine tuning diverse learning parameters. The present paper demonstrates an approach using an oversized network topology, adaptive propagation (APROP), a modified error function, and averaging outputs of four networks described for the first time. As an example, signals from different semiconductor gas sensors of an electronic nose were classified. The electronic nose smelt different types of edible oil with extremely different a-priori-probabilities. The fully-specified neural network classifier fulfilled the above mentioned demands. The new approach will be helpful not only for classifying olfactory signals automatically but also in many other fields in medicine, e.g. in data mining from medical databases.

  13. Linking cortical network synchrony and excitability

    PubMed Central

    Meisel, Christian

    2016-01-01

    ABSTRACT Theoretical approaches based on dynamical systems theory can provide useful frameworks to guide experiments and analysis techniques when investigating cortical network activity. The notion of phase transitions between qualitatively different kinds of network dynamics has been such a framework inspiring novel approaches to neurophysiological data analysis over the recent years. One particular intriguing hypothesis has been that cortical networks reside in the vicinity of a phase transition. Although the final verdict on this hypothesis is still out, trying to understand cortex dynamics from this viewpoint has recently led to interesting insights on cortical network function with relevance for clinical practice. PMID:27065159

  14. Percolation in networks composed of connectivity and dependency links

    NASA Astrophysics Data System (ADS)

    Bashan, Amir; Parshani, Roni; Havlin, Shlomo

    2011-05-01

    Networks composed from both connectivity and dependency links were found to be more vulnerable compared to classical networks with only connectivity links. Their percolation transition is usually of a first order compared to the second-order transition found in classical networks. We analytically analyze the effect of different distributions of dependencies links on the robustness of networks. For a random Erdös-Rényi (ER) network with average degree k that is divided into dependency clusters of size s, the fraction of nodes that belong to the giant component P∞ is given by P∞=ps-1[1-exp(-kpP∞)]s, where 1-p is the initial fraction of removed nodes. Our general result coincides with the known Erdös-Rényi equation for random networks for s=1. For networks with Poissonian distribution of dependency links we find that P∞ is given by P∞=fk,p(P∞)e(-1)[pfk,p(P∞)-1], where fk,p(P∞)≡1-exp(-kpP∞) and is the mean value of the size of dependency clusters. For networks with Gaussian distribution of dependency links we show how the average and width of the distribution affect the robustness of the networks.

  15. Satellite links in the integrated services digital network

    NASA Astrophysics Data System (ADS)

    Gatfield, A. G.

    The Integrated Services Digital Network (ISDN) is intended to be a worldwide, digitally implemented transmission network which will carry voice and all forms of data in a common format. The CCITT has recommended that the ISDN use plesiochronous interconnections between national digital networks. Satellite links are the key to this configuration since they presently provide the only world-wide network capable of realizing the necessary high-bit-rate paths.

  16. Link Prediction in Complex Networks: A Mutual Information Perspective

    PubMed Central

    Tan, Fei; Xia, Yongxiang; Zhu, Boyao

    2014-01-01

    Topological properties of networks are widely applied to study the link-prediction problem recently. Common Neighbors, for example, is a natural yet efficient framework. Many variants of Common Neighbors have been thus proposed to further boost the discriminative resolution of candidate links. In this paper, we reexamine the role of network topology in predicting missing links from the perspective of information theory, and present a practical approach based on the mutual information of network structures. It not only can improve the prediction accuracy substantially, but also experiences reasonable computing complexity. PMID:25207920

  17. PACRG, a protein linked to ciliary motility, mediates cellular signaling

    PubMed Central

    Loucks, Catrina M.; Bialas, Nathan J.; Dekkers, Martijn P. J.; Walker, Denise S.; Grundy, Laura J.; Li, Chunmei; Inglis, P. Nick; Kida, Katarzyna; Schafer, William R.; Blacque, Oliver E.; Jansen, Gert; Leroux, Michel R.

    2016-01-01

    Cilia are microtubule-based organelles that project from nearly all mammalian cell types. Motile cilia generate fluid flow, whereas nonmotile (primary) cilia are required for sensory physiology and modulate various signal transduction pathways. Here we investigate the nonmotile ciliary signaling roles of parkin coregulated gene (PACRG), a protein linked to ciliary motility. PACRG is associated with the protofilament ribbon, a structure believed to dictate the regular arrangement of motility-associated ciliary components. Roles for protofilament ribbon–associated proteins in nonmotile cilia and cellular signaling have not been investigated. We show that PACRG localizes to a small subset of nonmotile cilia in Caenorhabditis elegans, suggesting an evolutionary adaptation for mediating specific sensory/signaling functions. We find that it influences a learning behavior known as gustatory plasticity, in which it is functionally coupled to heterotrimeric G-protein signaling. We also demonstrate that PACRG promotes longevity in C. elegans by acting upstream of the lifespan-promoting FOXO transcription factor DAF-16 and likely upstream of insulin/IGF signaling. Our findings establish previously unrecognized sensory/signaling functions for PACRG and point to a role for this protein in promoting longevity. Furthermore, our work suggests additional ciliary motility-signaling connections, since EFHC1 (EF-hand containing 1), a potential PACRG interaction partner similarly associated with the protofilament ribbon and ciliary motility, also positively regulates lifespan. PMID:27193298

  18. PACRG, a protein linked to ciliary motility, mediates cellular signaling.

    PubMed

    Loucks, Catrina M; Bialas, Nathan J; Dekkers, Martijn P J; Walker, Denise S; Grundy, Laura J; Li, Chunmei; Inglis, P Nick; Kida, Katarzyna; Schafer, William R; Blacque, Oliver E; Jansen, Gert; Leroux, Michel R

    2016-07-01

    Cilia are microtubule-based organelles that project from nearly all mammalian cell types. Motile cilia generate fluid flow, whereas nonmotile (primary) cilia are required for sensory physiology and modulate various signal transduction pathways. Here we investigate the nonmotile ciliary signaling roles of parkin coregulated gene (PACRG), a protein linked to ciliary motility. PACRG is associated with the protofilament ribbon, a structure believed to dictate the regular arrangement of motility-associated ciliary components. Roles for protofilament ribbon-associated proteins in nonmotile cilia and cellular signaling have not been investigated. We show that PACRG localizes to a small subset of nonmotile cilia in Caenorhabditis elegans, suggesting an evolutionary adaptation for mediating specific sensory/signaling functions. We find that it influences a learning behavior known as gustatory plasticity, in which it is functionally coupled to heterotrimeric G-protein signaling. We also demonstrate that PACRG promotes longevity in C. elegans by acting upstream of the lifespan-promoting FOXO transcription factor DAF-16 and likely upstream of insulin/IGF signaling. Our findings establish previously unrecognized sensory/signaling functions for PACRG and point to a role for this protein in promoting longevity. Furthermore, our work suggests additional ciliary motility-signaling connections, since EFHC1 (EF-hand containing 1), a potential PACRG interaction partner similarly associated with the protofilament ribbon and ciliary motility, also positively regulates lifespan. PMID:27193298

  19. A new mutually reinforcing network node and link ranking algorithm

    PubMed Central

    Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.

    2015-01-01

    This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity. PMID:26492958

  20. Prediction of missing links and reconstruction of complex networks

    NASA Astrophysics Data System (ADS)

    Zhang, Cheng-Jun; Zeng, An

    2016-04-01

    Predicting missing links in complex networks is of great significance from both theoretical and practical point of view, which not only helps us understand the evolution of real systems but also relates to many applications in social, biological and online systems. In this paper, we study the features of different simple link prediction methods, revealing that they may lead to the distortion of networks’ structural and dynamical properties. Moreover, we find that high prediction accuracy is not definitely corresponding to a high performance in preserving the network properties when using link prediction methods to reconstruct networks. Our work highlights the importance of considering the feedback effect of the link prediction methods on network properties when designing the algorithms.

  1. Master Regulators in Plant Glucose Signaling Networks

    PubMed Central

    Sheen, Jen

    2014-01-01

    The daily life of photosynthetic plants revolves around sugar production, transport, storage and utilization, and the complex sugar metabolic and signaling networks integrate internal regulators and environmental cues to govern and sustain plant growth and survival. Although diverse sugar signals have emerged as pivotal regulators from embryogenesis to senescence, glucose is the most ancient and conserved regulatory signal that controls gene and protein expression, cell-cycle progression, central and secondary metabolism, as well as growth and developmental programs. Glucose signals are perceived and transduced by two principal mechanisms: direct sensing through glucose sensors and indirect sensing via a variety of energy and metabolite sensors. This review focuses on the comparative and functional analyses of three glucose-modulated master regulators in Arabidopsis thaliana, the hexokinase1 (HXK1) glucose sensor, the energy sensor kinases KIN10/KIN11 inactivated by glucose, and the glucose-activated target of rapamycin (TOR) kinase. These regulators are evolutionarily conserved, but have evolved universal and unique regulatory wiring and functions in plants and animals. They form protein complexes with multiple partners as regulators or effectors to serve distinct functions in different subcellular locales and organs, and play integrative and complementary roles from cellular signaling and metabolism to development in the plant glucose signaling networks. PMID:25530701

  2. Targeted attack on networks coupled by connectivity and dependency links

    NASA Astrophysics Data System (ADS)

    Du, Ruijin; Dong, Gaogao; Tian, Lixin; Liu, Runran

    2016-05-01

    Coupled systems used to increase capacity were shown beneficial as long as it does not open pathways to cascades. Previous studies on the robustness of coupled networks except for interdependent networks are almost the cases of random attack. Many challenges remain exist in targeted-attack problem of coupled networks. Since nodes within coupled networks show different functions for each network, this paper both analytically and numerically analyzed the robustness of coupled networks under three types of targeted attacking strategies, including attacking on nodes by considering internal and external degree, internal degree only, and external degree only. For coupled network with both interdependent and interconnected links, all degree distributions of intra- and inter-connectivity links are Poissonian, we find the system undergoes from second to first order phase transition as coupling strength q increases. The fraction of nodes in the giant component P∞ at stable state, the critical phase transition threshold pc (first order threshold pcI and second order threshold pcII), and the critical point (pc ,qc) separating the first and second order phase transitions are analytically obtained for three types of attacking strategies with attacking probability parameter α = 0 , 1. We also find the system becomes more vulnerable as the average degree of intra-links k ¯ or inter-links K ¯ decreases. Therefore, the minimum average degrees k¯min and K¯min to maintain the system stable are obtained for the case of α = 0 , 1. Moreover, we discussed three typical cases of coupled networks, interdependent networks (K ¯ = 0), interacting networks (q = 0) and bipartite network (k = 0, q = 0), the analytical expressions of P∞, pc and (pc ,qc) (only for interdependent) are given respectively. Besides, we study the equivalence relations between interdependent networks and coupled networks with connectivity and dependency links for the same pc. The results imply that we can

  3. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NASA Astrophysics Data System (ADS)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2016-06-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide (≈ 35 500 km2) 15 min rainfall maps can be derived from the signal attenuations of approximately 2400 microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm. Moreover, the documented, modular, and user-friendly code (a package in the scripting language "R") is made available, including a 2-day data set of approximately 2600 commercial microwave links from the Netherlands. The purpose of this paper is to promote rainfall mapping utilising microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  4. Link Prediction in Weighted Networks: A Weighted Mutual Information Model

    PubMed Central

    Zhu, Boyao; Xia, Yongxiang

    2016-01-01

    The link-prediction problem is an open issue in data mining and knowledge discovery, which attracts researchers from disparate scientific communities. A wealth of methods have been proposed to deal with this problem. Among these approaches, most are applied in unweighted networks, with only a few taking the weights of links into consideration. In this paper, we present a weighted model for undirected and weighted networks based on the mutual information of local network structures, where link weights are applied to further enhance the distinguishable extent of candidate links. Empirical experiments are conducted on four weighted networks, and results show that the proposed method can provide more accurate predictions than not only traditional unweighted indices but also typical weighted indices. Furthermore, some in-depth discussions on the effects of weak ties in link prediction as well as the potential to predict link weights are also given. This work may shed light on the design of algorithms for link prediction in weighted networks. PMID:26849659

  5. Link Prediction in Weighted Networks: A Weighted Mutual Information Model.

    PubMed

    Zhu, Boyao; Xia, Yongxiang

    2016-01-01

    The link-prediction problem is an open issue in data mining and knowledge discovery, which attracts researchers from disparate scientific communities. A wealth of methods have been proposed to deal with this problem. Among these approaches, most are applied in unweighted networks, with only a few taking the weights of links into consideration. In this paper, we present a weighted model for undirected and weighted networks based on the mutual information of local network structures, where link weights are applied to further enhance the distinguishable extent of candidate links. Empirical experiments are conducted on four weighted networks, and results show that the proposed method can provide more accurate predictions than not only traditional unweighted indices but also typical weighted indices. Furthermore, some in-depth discussions on the effects of weak ties in link prediction as well as the potential to predict link weights are also given. This work may shed light on the design of algorithms for link prediction in weighted networks.

  6. Link prediction in the network of global virtual water trade

    NASA Astrophysics Data System (ADS)

    Tuninetti, Marta; Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

    2016-04-01

    Through the international food-trade, water resources are 'virtually' transferred from the country of production to the country of consumption. The international food-trade, thus, implies a network of virtual water flows from exporting to importing countries (i.e., nodes). Given the dynamical behavior of the network, where food-trade relations (i.e., links) are created and dismissed every year, link prediction becomes a challenge. In this study, we propose a novel methodology for link prediction in the virtual water network. The model aims at identifying the main factors (among 17 different variables) driving the creation of a food-trade relation between any two countries, along the period between 1986 and 2011. Furthermore, the model can be exploited to investigate the network configuration in the future, under different possible (climatic and demographic) scenarios. The model grounds the existence of a link between any two nodes on the link weight (i.e., the virtual water flow): a link exists when the nodes exchange a minimum (fixed) volume of virtual water. Starting from a set of potential links between any two nodes, we fit the associated virtual water flows (both the real and the null ones) by means of multivariate linear regressions. Then, links with estimated flows higher than a minimum value (i.e., threshold) are considered active-links, while the others are non-active ones. The discrimination between active and non-active links through the threshold introduces an error (called link-prediction error) because some real links are lost (i.e., missed links) and some non-existing links (i.e., spurious links) are inevitably introduced in the network. The major drivers are those significantly minimizing the link-prediction error. Once the structure of the unweighted virtual water network is known, we apply, again, linear regressions to assess the major factors driving the fluxes traded along (modelled) active-links. Results indicate that, on the one hand

  7. Link-based formalism for time evolution of adaptive networks

    NASA Astrophysics Data System (ADS)

    Zhou, Jie; Xiao, Gaoxi; Chen, Guanrong

    2013-09-01

    Network topology and nodal dynamics are two fundamental stones of adaptive networks. Detailed and accurate knowledge of these two ingredients is crucial for understanding the evolution and mechanism of adaptive networks. In this paper, by adopting the framework of the adaptive SIS model proposed by Gross [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.96.208701 96, 208701 (2006)] and carefully utilizing the information of degree correlation of the network, we propose a link-based formalism for describing the system dynamics with high accuracy and subtle details. Several specific degree correlation measures are introduced to reveal the coevolution of network topology and system dynamics.

  8. Linking Classrooms of the Future through Interactive Telecommunications Network.

    ERIC Educational Resources Information Center

    Cisco, Ponney G.

    This document describes an interactive television (ITV) distance education network designed to service rural schools. Phase one of the network involved the installation of over 14 miles of fiber optic cable linking two high schools, a career center, and the University of Rio Grande; phase two will bring seven high schools in economically depressed…

  9. CrossRef: A Collaborative Linking Network.

    ERIC Educational Resources Information Center

    Pentz, Ed

    2001-01-01

    CrossRef was created to make broad-based linking efficient and scalable across a wide range of primary publishers, secondary publishers, abstracting and indexing services, and libraries. CrossRef runs a system that enables publishers to assign Digital Object Identifiers (DOIs) to articles and collects standardized metadata so the identifiers can…

  10. Mixed-Method Exploration of Social Network Links to Participation.

    PubMed

    Kreider, Consuelo M; Bendixen, Roxanna M; Mann, William C; Young, Mary Ellen; McCarty, Christopher

    2015-07-01

    The people who regularly interact with an adolescent form that youth's social network (SN), which may impact participation. We investigated the relationship of SNs to participation using personal network analysis and individual interviews. The sample included 36 youth, aged 11 to 16 years. Nineteen had diagnoses of learning disability, attention disorder, or high-functioning autism, and 17 were typically developing. Network analysis yielded 10 network variables, of which 8 measured network composition and 2 measured network structure, with significant links to at least I measure of participation using the Children's Assessment of Participation and Enjoyment (CAPE). Interviews from youth in the clinical group yielded description of strategies used to negotiate social interactions, as well as processes and reasoning used to remain engaged within SNs. Findings contribute to understanding the ways SNs are linked to youth participation and suggest the potential of SN factors for predicting rehabilitation outcomes.

  11. Network worlds : from link analysis to virtual places.

    SciTech Connect

    Joslyn, C.

    2002-01-01

    Significant progress is being made in knowledge systems through recent advances in the science of very large networks. Attention is now turning in many quarters to the potential impact on counter-terrorism methods. After reviewing some of these advances, we will discuss the difference between such 'network analytic' approaches, which focus on large, homogeneous graph strucures, and what we are calling 'link analytic' approaches, which focus on somewhat smaller graphs with heterogeneous link types. We use this venue to begin the process of rigorously defining link analysis methods, especially the concept of chaining of views of multidimensional databases. We conclude with some speculation on potential connections to virtual world architectures.

  12. Link Investigation of IEEE 802.15.4 Wireless Sensor Networks in Forests.

    PubMed

    Ding, Xingjian; Sun, Guodong; Yang, Gaoxiang; Shang, Xinna

    2016-06-27

    Wireless sensor networks are expected to automatically monitor the ecological evolution and wildlife habits in forests. Low-power links (transceivers) are often adopted in wireless sensor network applications, in order to save the precious sensor energy and then achieve long-term, unattended monitoring. Recent research has presented some performance characteristics of such low-power wireless links under laboratory or outdoor scenarios with less obstacles, and they have found that low-power wireless links are unreliable and prone to be affected by the target environment. However, there is still less understanding about how well the low-power wireless link performs in real-world forests and to what extent the complex in-forest surrounding environments affect the link performances. In this paper, we empirically evaluate the low-power links of wireless sensors in three typical different forest environments. Our experiment investigates the performance of the link layer compatible with the IEEE 802.15.4 standard and analyzes the variation patterns of the packet reception ratio (PRR), the received signal strength indicator (RSSI) and the link quality indicator (LQI) under diverse experimental settings. Some observations of this study are inconsistent with or even contradict prior results that are achieved in open fields or relatively clean environments and thus, provide new insights both into effectively evaluating the low-power wireless links and into efficiently deploying wireless sensor network systems in forest environments.

  13. Link Investigation of IEEE 802.15.4 Wireless Sensor Networks in Forests.

    PubMed

    Ding, Xingjian; Sun, Guodong; Yang, Gaoxiang; Shang, Xinna

    2016-01-01

    Wireless sensor networks are expected to automatically monitor the ecological evolution and wildlife habits in forests. Low-power links (transceivers) are often adopted in wireless sensor network applications, in order to save the precious sensor energy and then achieve long-term, unattended monitoring. Recent research has presented some performance characteristics of such low-power wireless links under laboratory or outdoor scenarios with less obstacles, and they have found that low-power wireless links are unreliable and prone to be affected by the target environment. However, there is still less understanding about how well the low-power wireless link performs in real-world forests and to what extent the complex in-forest surrounding environments affect the link performances. In this paper, we empirically evaluate the low-power links of wireless sensors in three typical different forest environments. Our experiment investigates the performance of the link layer compatible with the IEEE 802.15.4 standard and analyzes the variation patterns of the packet reception ratio (PRR), the received signal strength indicator (RSSI) and the link quality indicator (LQI) under diverse experimental settings. Some observations of this study are inconsistent with or even contradict prior results that are achieved in open fields or relatively clean environments and thus, provide new insights both into effectively evaluating the low-power wireless links and into efficiently deploying wireless sensor network systems in forest environments. PMID:27355957

  14. Link Investigation of IEEE 802.15.4 Wireless Sensor Networks in Forests

    PubMed Central

    Ding, Xingjian; Sun, Guodong; Yang, Gaoxiang; Shang, Xinna

    2016-01-01

    Wireless sensor networks are expected to automatically monitor the ecological evolution and wildlife habits in forests. Low-power links (transceivers) are often adopted in wireless sensor network applications, in order to save the precious sensor energy and then achieve long-term, unattended monitoring. Recent research has presented some performance characteristics of such low-power wireless links under laboratory or outdoor scenarios with less obstacles, and they have found that low-power wireless links are unreliable and prone to be affected by the target environment. However, there is still less understanding about how well the low-power wireless link performs in real-world forests and to what extent the complex in-forest surrounding environments affect the link performances. In this paper, we empirically evaluate the low-power links of wireless sensors in three typical different forest environments. Our experiment investigates the performance of the link layer compatible with the IEEE 802.15.4 standard and analyzes the variation patterns of the packet reception ratio (PRR), the received signal strength indicator (RSSI) and the link quality indicator (LQI) under diverse experimental settings. Some observations of this study are inconsistent with or even contradict prior results that are achieved in open fields or relatively clean environments and thus, provide new insights both into effectively evaluating the low-power wireless links and into efficiently deploying wireless sensor network systems in forest environments. PMID:27355957

  15. Community detection in networks with positive and negative links

    NASA Astrophysics Data System (ADS)

    Traag, V. A.; Bruggeman, Jeroen

    2009-09-01

    Detecting communities in complex networks accurately is a prime challenge, preceding further analyses of network characteristics and dynamics. Until now, community detection took into account only positively valued links, while many actual networks also feature negative links. We extend an existing Potts model to incorporate negative links as well, resulting in a method similar to the clustering of signed graphs, as dealt with in social balance theory, but more general. To illustrate our method, we applied it to a network of international alliances and disputes. Using data from 1993-2001, it turns out that the world can be divided into six power blocs similar to Huntington’s civilizations, with some notable exceptions.

  16. ATR promotes cilia signalling: links to developmental impacts.

    PubMed

    Stiff, Tom; Casar Tena, Teresa; O'Driscoll, Mark; Jeggo, Penny A; Philipp, Melanie

    2016-04-15

    Mutations in ATR(ataxia telangiectasia and RAD3-related) cause Seckel syndrome (ATR-SS), a microcephalic primordial dwarfism disorder. Hitherto, the clinical manifestation of ATR deficiency has been attributed to its canonical role in DNA damage response signalling following replication fork stalling/collapse. Here, we show that ATR regulates cilia-dependent signalling in a manner that can be uncoupled from its function during replication. ATR-depleted or patient-derived ATR-SS cells form cilia of slightly reduced length but are dramatically impaired in cilia-dependent signalling functions, including growth factor and Sonic hedgehog signalling. To better understand the developmental impact of ATR loss of function, we also used zebrafish as a model. Zebrafish embryos depleted of Atr resembled ATR-SS morphology, showed a modest but statistically significant reduction in cilia length and other morphological features indicative of cilia dysfunction. Additionally, they displayed defects in left-right asymmetry including ambiguous expression of southpaw, incorrectly looped hearts and randomized localization of internal organs including the pancreas, features typically conferred by cilia dysfunction. Our findings reveal a novel role for ATR in cilia signalling distinct from its canonical function during replication and strengthen emerging links between cilia function and development. PMID:26908596

  17. ATR promotes cilia signalling: links to developmental impacts

    PubMed Central

    Stiff, Tom; Casar Tena, Teresa; O'Driscoll, Mark; Jeggo, Penny A.; Philipp, Melanie

    2016-01-01

    Mutations in ATR (ataxia telangiectasia and RAD3-related) cause Seckel syndrome (ATR-SS), a microcephalic primordial dwarfism disorder. Hitherto, the clinical manifestation of ATR deficiency has been attributed to its canonical role in DNA damage response signalling following replication fork stalling/collapse. Here, we show that ATR regulates cilia-dependent signalling in a manner that can be uncoupled from its function during replication. ATR-depleted or patient-derived ATR-SS cells form cilia of slightly reduced length but are dramatically impaired in cilia-dependent signalling functions, including growth factor and Sonic hedgehog signalling. To better understand the developmental impact of ATR loss of function, we also used zebrafish as a model. Zebrafish embryos depleted of Atr resembled ATR-SS morphology, showed a modest but statistically significant reduction in cilia length and other morphological features indicative of cilia dysfunction. Additionally, they displayed defects in left-right asymmetry including ambiguous expression of southpaw, incorrectly looped hearts and randomized localization of internal organs including the pancreas, features typically conferred by cilia dysfunction. Our findings reveal a novel role for ATR in cilia signalling distinct from its canonical function during replication and strengthen emerging links between cilia function and development. PMID:26908596

  18. Numeric simulation of plant signaling networks.

    PubMed

    Genoud, T; Trevino Santa Cruz, M B; Métraux, J P

    2001-08-01

    Plants have evolved an intricate signaling apparatus that integrates relevant information and allows an optimal response to environmental conditions. For instance, the coordination of defense responses against pathogens involves sophisticated molecular detection and communication systems. Multiple protection strategies may be deployed differentially by the plant according to the nature of the invading organism. These responses are also influenced by the environment, metabolism, and developmental stage of the plant. Though the cellular signaling processes traditionally have been described as linear sequences of events, it is now evident that they may be represented more accurately as network-like structures. The emerging paradigm can be represented readily with the use of Boolean language. This digital (numeric) formalism allows an accurate qualitative description of the signal transduction processes, and a dynamic representation through computer simulation. Moreover, it provides the required power to process the increasing amount of information emerging from the fields of genomics and proteomics, and from the use of new technologies such as microarray analysis. In this review, we have used the Boolean language to represent and analyze part of the signaling network of disease resistance in Arabidopsis. PMID:11500542

  19. The effect of cross-link distributions in axially-ordered, cross-linked networks

    PubMed Central

    Bennett, C. Brad; Kruczek, James; Rabson, D. A.; Matthews, W. Garrett; Pandit, Sagar A.

    2013-01-01

    Cross-linking between the constituent chains of biopolymers has a marked effect on their materials properties. In certain of these materials, such as fibrillar collagen, increases in cross-linking lead to an increase in the melting temperature. Fibrillar collagen is an axially-ordered network of cross-linked polymer chains exhibiting a broadened denaturation transition, which has been explained in terms of the successive denaturation with temperature of multiple species. We model axially-ordered cross-linked materials as stiff chains with distinct arrangements of cross-link-forming sites. Simulations suggest that systems composed of chains with identical arrangements of cross-link-forming sites exhibit critical behavior. In contrast, systems composed of non-identical chains undergo a crossover. This model suggests that the arrangement of cross-link-forming sites may contribute to the broadening of the denaturation transition in fibrillar collagen. PMID:23751928

  20. Model selection for athermal cross-linked fiber networks.

    PubMed

    Shahsavari, A; Picu, R C

    2012-07-01

    Athermal random fiber networks are usually modeled by representing each fiber as a truss, a Euler-Bernoulli or a Timoshenko beam, and, in the case of cross-linked networks, each cross-link as a pinned, rotating, or welded joint. In this work we study the effect of these various modeling options on the dependence of the overall network stiffness on system parameters. We conclude that Timoshenko beams can be used for the entire range of density and beam stiffness parameters, while the Euler-Bernoulli model can be used only at relatively low network densities. In the high density-high bending stiffness range, strain energy is stored predominantly in the axial and shear deformation modes, while in the other extreme range of parameters, the energy is stored in the bending mode. The effect of the model size on the network stiffness is also discussed. PMID:23005468

  1. Link-Prediction Enhanced Consensus Clustering for Complex Networks

    PubMed Central

    Burgess, Matthew; Adar, Eytan; Cafarella, Michael

    2016-01-01

    Many real networks that are collected or inferred from data are incomplete due to missing edges. Missing edges can be inherent to the dataset (Facebook friend links will never be complete) or the result of sampling (one may only have access to a portion of the data). The consequence is that downstream analyses that “consume” the network will often yield less accurate results than if the edges were complete. Community detection algorithms, in particular, often suffer when critical intra-community edges are missing. We propose a novel consensus clustering algorithm to enhance community detection on incomplete networks. Our framework utilizes existing community detection algorithms that process networks imputed by our link prediction based sampling algorithm and merges their multiple partitions into a final consensus output. On average our method boosts performance of existing algorithms by 7% on artificial data and 17% on ego networks collected from Facebook. PMID:27203750

  2. The organization of strong links in complex networks

    NASA Astrophysics Data System (ADS)

    Pajevic, Sinisa; Plenz, Dietmar

    2012-05-01

    Many complex systems reveal a small-world topology, which allows simultaneously local and global efficiency in the interaction between system constituents. Here, we report the results of a comprehensive study that investigates the relation between the clustering properties in such small-world systems and the strength of interactions between its constituents, quantified by the link weight. For brain, gene, social and language networks, we find a local integrative weight organization in which strong links preferentially occur between nodes with overlapping neighbourhoods; we relate this to global robustness of the clustering to removal of the weakest links. Furthermore, we identify local learning rules that establish integrative networks and improve network traffic in response to past traffic failures. Our findings identify a general organization for complex systems that strikes a balance between efficient local and global communication in their strong interactions, while allowing for robust, exploratory development of weak interactions.

  3. Cascaded optical fiber link using the internet network for remote clocks comparison

    NASA Astrophysics Data System (ADS)

    Chiodo, Nicola; Quintin, Nicolas; Stefani, Fabio; Wiotte, Fabrice; Camisard, Emilie; Chardonnet, Christian; Santarelli, Giorgio; Amy-Klein, Anne; Pottie, Paul-Eric; Lopez, Olivier

    2015-12-01

    We report a cascaded optical link of 1100 km for ultra-stable frequency distribution over an Internet fiber network. The link is composed of four spans for which the propagation noise is actively compensated. The robustness and the performance of the link are ensured by five fully automated optoelectronic stations, two of them at the link ends, and three deployed on the field and connecting the spans. This device coherently regenerates the optical signal with the heterodyne optical phase locking of a low-noise laser diode. Optical detection of the beat-note signals for the laser lock and the link noise compensation are obtained with stable and low-noise fibered optical interferometer. We show 3.5 days of continuous operation of the noise-compensated 4-span cascaded link leading to fractional frequency instability of 4x10-16 at 1-s measurement time and 1x10-19 at 2000 s. This cascaded link was extended to 1480-km with the same performance. This work is a significant step towards a sustainable wide area ultra-stable optical frequency distribution and comparison network at a very high level of performance.

  4. Porous Cross-Linked Polyimide-Urea Networks

    NASA Technical Reports Server (NTRS)

    Meador, Mary Ann B. (Inventor); Nguyen, Baochau N. (Inventor)

    2015-01-01

    Porous cross-linked polyimide-urea networks are provided. The networks comprise a subunit comprising two anhydride end-capped polyamic acid oligomers in direct connection via a urea linkage. The oligomers (a) each comprise a repeating unit of a dianhydride and a diamine and a terminal anhydride group and (b) are formulated with 2 to 15 of the repeating units. The subunit was formed by reaction of the diamine and a diisocyanate to form a diamine-urea linkage-diamine group, followed by reaction of the diamine-urea linkage-diamine group with the dianhydride and the diamine to form the subunit. The subunit has been cross-linked via a cross-linking agent, comprising three or more amine groups, at a balanced stoichiometry of the amine groups to the terminal anhydride groups. The subunit has been chemically imidized to yield the porous cross-linked polyimide-urea network. Also provided are wet gels, aerogels, and thin films comprising the networks, and methods of making the networks.

  5. Prediction of Links and Weights in Networks by Reliable Routes

    PubMed Central

    Zhao, Jing; Miao, Lili; Yang, Jian; Fang, Haiyang; Zhang, Qian-Ming; Nie, Min; Holme, Petter; Zhou, Tao

    2015-01-01

    Link prediction aims to uncover missing links or predict the emergence of future relationships from the current network structure. Plenty of algorithms have been developed for link prediction in unweighted networks, but only a few have been extended to weighted networks. In this paper, we present what we call a “reliable-route method” to extend unweighted local similarity indices to weighted ones. Using these indices, we can predict both the existence of links and their weights. Experiments on various real-world networks suggest that our reliable-route weighted resource-allocation index performs noticeably better than others with respect to weight prediction. For existence prediction it is either the highest or very close to the highest. Further analysis shows a strong positive correlation between the clustering coefficient and prediction accuracy. Finally, we apply our method to the prediction of missing protein-protein interactions and their confidence scores from known PPI networks. Once again, our reliable-route method shows the highest accuracy. PMID:26198206

  6. Early-warning signals of topological collapse in interbank networks

    NASA Astrophysics Data System (ADS)

    Squartini, Tiziano; van Lelyveld, Iman; Garlaschelli, Diego

    2013-11-01

    The financial crisis clearly illustrated the importance of characterizing the level of `systemic' risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze the quarterly interbank exposures among Dutch banks over the period 1998-2008, ending with the crisis. After controlling for the link density, many topological properties display an abrupt change in 2008, providing a clear - but unpredictable - signature of the crisis. By contrast, if the heterogeneity of banks' connectivity is controlled for, the same properties show a gradual transition to the crisis, starting in 2005 and preceded by an even earlier period during which anomalous debt loops could have led to the underestimation of counter-party risk. These early-warning signals are undetectable if the network is reconstructed from partial bank-specific data, as routinely done. We discuss important implications for bank regulatory policies.

  7. Text mining for metabolic pathways, signaling cascades, and protein networks.

    PubMed

    Hoffmann, Robert; Krallinger, Martin; Andres, Eduardo; Tamames, Javier; Blaschke, Christian; Valencia, Alfonso

    2005-05-10

    The complexity of the information stored in databases and publications on metabolic and signaling pathways, the high throughput of experimental data, and the growing number of publications make it imperative to provide systems to help the researcher navigate through these interrelated information resources. Text-mining methods have started to play a key role in the creation and maintenance of links between the information stored in biological databases and its original sources in the literature. These links will be extremely useful for database updating and curation, especially if a number of technical problems can be solved satisfactorily, including the identification of protein and gene names (entities in general) and the characterization of their types of interactions. The first generation of openly accessible text-mining systems, such as iHOP (Information Hyperlinked over Proteins), provides additional functions to facilitate the reconstruction of protein interaction networks, combine database and text information, and support the scientist in the formulation of novel hypotheses. The next challenge is the generation of comprehensive information regarding the general function of signaling pathways and protein interaction networks. PMID:15886388

  8. Cascaded optical link on a telecommunication fiber network for ultra-stable frequency dissemination

    NASA Astrophysics Data System (ADS)

    Lopez, Olivier; Chiodo, Nicola; Stefani, Fabio; Wiotte, Fabrice; Quintin, Nicolas; Bercy, Anthony; Chardonnet, Christian; Santarelli, Giorgio; Pottie, Paul-Eric; Amy-Klein, Anne

    2015-03-01

    The transfer of ultra-stable frequencies between distant laboratories is required by many applications in time and frequency metrology, fundamental physics, particle accelerators and astrophysics. Optical fiber links have been intensively studied for a decade and brought the potential to transfer frequency with a very high accuracy and stability thanks to an active compensation of the propagation noise. We are currently developing an optical metrological network using the fibers of the French National Research and Education Network. Using the so-called dark-channel approach, the ultrastable signal is copropagating with data traffic using wavelength division multiplexing. Due to significant reflections and losses along the fibers, which cannot be compensated with amplifiers, we have developed some repeater stations for the metrological signal. These remotely-operated stations amplify the ultrastable signal and compensate the propagation noise. The link is thus composed of a few cascaded spans. It gives the possibility to increase the noise correction bandwidth, which is proportional to the inverse of the fiber length for each span. These stations are a key element for the deployment of a reliable and large scale metrological network. We report here on the implementation of a two-spans cascaded link of 740 km reaching a relative stability of a few 10-20 after 103 s averaging time. Extension to longer links and alternative transfer methods will be discussed.

  9. Collective Calcium Signaling of Defective Multicellular Networks

    NASA Astrophysics Data System (ADS)

    Potter, Garrett; Sun, Bo

    2015-03-01

    A communicating multicellular network processes environmental cues into collective cellular dynamics. We have previously demonstrated that, when excited by extracellular ATP, fibroblast monolayers generate correlated calcium dynamics modulated by both the stimuli and gap junction communication between the cells. However, just as a well-connected neural network may be compromised by abnormal neurons, a tissue monolayer can also be defective with cancer cells, which typically have down regulated gap junctions. To understand the collective cellular dynamics in a defective multicellular network we have studied the calcium signaling of co-cultured breast cancer cells and fibroblast cells in various concentrations of ATP delivered through microfluidic devices. Our results demonstrate that cancer cells respond faster, generate singular spikes, and are more synchronous across all stimuli concentrations. Additionally, fibroblast cells exhibit persistent calcium oscillations that increase in regularity with greater stimuli. To interpret these results we quantitatively analyzed the immunostaining of purigenic receptors and gap junction channels. The results confirm our hypothesis that collective dynamics are mainly determined by the availability of gap junction communications.

  10. MSAT signalling and network management architectures

    NASA Technical Reports Server (NTRS)

    Garland, Peter; Keelty, J. Malcolm

    1989-01-01

    Spar Aerospace has been active in the design and definition of Mobile Satellite Systems since the mid 1970's. In work sponsored by the Canadian Department of Communications, various payload configurations have evolved. In addressing the payload configuration, the requirements of the mobile user, the service provider and the satellite operator have always been the most important consideration. The current Spar 11 beam satellite design is reviewed, and its capabilities to provide flexibility and potential for network growth within the WARC87 allocations are explored. To enable the full capabilities of the payload to be realized, a large amount of ground based Switching and Network Management infrastructure will be required, when space segment becomes available. Early indications were that a single custom designed Demand Assignment Multiple Access (DAMA) switch should be implemented to provide efficient use of the space segment. As MSAT has evolved into a multiple service concept, supporting many service providers, this architecture should be reviewed. Some possible signalling and Network Management solutions are explored.

  11. Neural Networks for Signal Processing and Control

    NASA Astrophysics Data System (ADS)

    Hesselroth, Ted Daniel

    cortex by the application of lateral interactions during the learning phase. The organization of the mature network is compared to that found in the macaque monkey by several analytical tests. The capacity of the network to process images is investigated. By a method of reconstructing the input images in terms of V1 activities, the simulations show that images can be faithfully represented in V1 by the proposed network. The signal-to-noise ratio of the image is improved by the representation, and compression ratios of well over two-hundred are possible. Lateral interactions between V1 neurons sharpen their orientational tuning. We further study the dynamics of the processing, showing that the rate of decrease of the error of the reconstruction is maximized for the receptive fields used. Lastly, we employ a Fokker-Planck equation for a more detailed prediction of the error value vs. time. The Fokker-Planck equation for an underdamped system with a driving force is derived, yielding an energy-dependent diffusion coefficient which is the integral of the spectral densities of the force and the velocity of the system. The theory is applied to correlated noise activation and resonant activation. Simulation results for the error of the network vs time are compared to the solution of the Fokker-Planck equation.

  12. Locating inefficient links in a large-scale transportation network

    NASA Astrophysics Data System (ADS)

    Sun, Li; Liu, Like; Xu, Zhongzhi; Jie, Yang; Wei, Dong; Wang, Pu

    2015-02-01

    Based on data from geographical information system (GIS) and daily commuting origin destination (OD) matrices, we estimated the distribution of traffic flow in the San Francisco road network and studied Braess's paradox in a large-scale transportation network with realistic travel demand. We measured the variation of total travel time Δ T when a road segment is closed, and found that | Δ T | follows a power-law distribution if Δ T < 0 or Δ T > 0. This implies that most roads have a negligible effect on the efficiency of the road network, while the failure of a few crucial links would result in severe travel delays, and closure of a few inefficient links would counter-intuitively reduce travel costs considerably. Generating three theoretical networks, we discovered that the heterogeneously distributed travel demand may be the origin of the observed power-law distributions of | Δ T | . Finally, a genetic algorithm was used to pinpoint inefficient link clusters in the road network. We found that closing specific road clusters would further improve the transportation efficiency.

  13. TCP flow control using link layer information in mobile networks

    NASA Astrophysics Data System (ADS)

    Koga, Hiroyuki; Kawahara, Kenji; Oie, Yuji

    2002-07-01

    Mobile Networks have been expanding and IMT-2000 further increases their available bandwidth over wireless links. However, TCP, which is a reliable end-to-end transport protocol, is tuned to perform well in wired networks where bit error rates are very low and packet loss occurs mostly because of congestion. Although a TCP sender can execute flow control to utilize as much available bandwidth as possible in wired networks, it cannot work well in wireless networks characterized by high bit error rates. In the next generation mobile systems, sophisticated error recovery technologies of FEC and ARQ are indeed employed over wireless links, i.e., over Layer 2, to avoid performance degradation of upper layers. However, multiple retransmissions by Layer 2 ARQ can adversely increase transmission delay of TCP segments, which will further make TCP unnecessarily increase RTO (Retransmission TimeOut). Furthermore, a link bandwidth assigned to TCP flows can change in response to changing air conditions to use wireless links efficiently. TCP thus has to adapt its transmission rate according to the changing available bandwidth. The major goal of this study is to develop a receiver-based effective TCP flow control without any modification on TCP senders, which are probably connected with wired networks. For this end, we propose a TCP flow control employing some Layer 2 information on a wireless link at the mobile station. Our performance evaluation of the proposed TCP shows that the receiver-based TCP flow control can moderate the performance degradation very well even if FER on Layer 2 is high.

  14. Rainfall retrieval in urban areas using commercial microwave links from mobile networks: A modelling feasibility study

    NASA Astrophysics Data System (ADS)

    Zohidov, Bahtiyor; Andrieu, Hervé; Servières, Myriam; Normand, Nicolas

    2014-05-01

    Rainfall is usually measured by networks of rain gauges and weather radars. Many cities worldwide are not supplied with these devices; however, they are generally equipped with mobile telecommunication networks. Mobile networks use atmospheric Hyper-Frequency (HF) links whose transmitted signal power is attenuated by rainfall. Measuring that signal attenuation along each link could allow the measurement of path-averaged rainfall [Leijnse et al 2007, Overeem et al 2013, Messer et al 2006, Guili et al 1991, Zinevich et al 2008, Cuccoli et al 2011]. As HF links are concentrated in cities, these networks could constitute a self-sufficient approach to monitoring rainfall in urban areas. We adopt a simulation approach in order to study the feasibility of mapping rainfall fields at the city scale by means of existing HF links. Our domain of study is the central part of the city of Nantes, France, where the density of cellular networks is greatest. As a basis, we use a data set consisting of hundreds of weather radar images recorded by the Météo-France C band weather radar at high spatial (250m x 250m) and temporal (5 minute) resolutions located about 10 km north of the center of Nantes. We convert these images into rainfall maps using the Z-R relation and consider them as reference rainfall fields. The simulation is performed as follows. First, we simulate the measurement of total attenuation along each HF link using a rain-attenuation model based on Mie theory and a known drop size distribution in a continental temperate climate. This procedure is applied for 256 real radio links operating at different frequencies (18, 23, 38 GHz) with lengths ranging from 0.4 to 16 km. This helps us to substitute the attenuation data for the signal power received from microwave links. Error sources affecting measurement accuracy are introduced as a zero-mean Gaussian distributed random variable with variance of 10% of total attenuation. The retrieval of the rainfield is performed by a

  15. Architecture and design of optical path networks utilizing waveband virtual links

    NASA Astrophysics Data System (ADS)

    Ito, Yusaku; Mori, Yojiro; Hasegawa, Hiroshi; Sato, Ken-ichi

    2016-02-01

    We propose a novel optical network architecture that uses waveband virtual links, each of which can carry several optical paths, to directly bridge distant node pairs. Future photonic networks should not only transparently cover extended areas but also expand fiber capacity. However, the traversal of many ROADM nodes impairs the optical signal due to spectrum narrowing. To suppress the degradation, the bandwidth of guard bands needs to be increased, which degrades fiber frequency utilization. Waveband granular switching allows us to apply broader pass-band filtering at ROADMs and to insert sufficient guard bands between wavebands with minimum frequency utilization offset. The scheme resolves the severe spectrum narrowing effect. Moreover, the guard band between optical channels in a waveband can be minimized, which increases the number of paths that can be accommodated per fiber. In the network, wavelength path granular routing is done without utilizing waveband virtual links, and it still suffers from spectrum narrowing. A novel network design algorithm that can bound the spectrum narrowing effect by limiting the number of hops (traversed nodes that need wavelength path level routing) is proposed in this paper. This algorithm dynamically changes the waveband virtual link configuration according to the traffic distribution variation, where optical paths that need many node hops are effectively carried by virtual links. Numerical experiments demonstrate that the number of necessary fibers is reduced by 23% compared with conventional optical path networks.

  16. Adaptive Reliable Routing Protocol Using Combined Link Stability Estimation for Mobile Ad hoc Networks

    NASA Astrophysics Data System (ADS)

    Vadivel, R.; Bhaskaran, V. Murali

    2010-10-01

    The main reason for packet loss in ad hoc networks is the link failure or node failure. In order to increase the path stability, it is essential to distinguish and moderate the failures. By knowing individual link stability along a path, path stability can be identified. In this paper, we develop an adaptive reliable routing protocol using combined link stability estimation for mobile ad hoc networks. The main objective of this protocol is to determine a Quality of Service (QoS) path along with prolonging the network life time and to reduce the packet loss. We calculate a combined metric for a path based on the parameters Link Expiration Time, Node Remaining Energy and Node Velocity and received signal strength to predict the link stability or lifetime. Then, a bypass route is established to retransmit the lost data, when a link failure occurs. By simulation results, we show that the proposed reliable routing protocol achieves high delivery ratio with reduced delay and packet drop.

  17. Linking Individual and Collective Behavior in Adaptive Social Networks.

    PubMed

    Pinheiro, Flávio L; Santos, Francisco C; Pacheco, Jorge M

    2016-03-25

    Adaptive social structures are known to promote the evolution of cooperation. However, up to now the characterization of the collective, population-wide dynamics resulting from the self-organization of individual strategies on a coevolving, adaptive network has remained unfeasible. Here we establish a (reversible) link between individual (micro)behavior and collective (macro)behavior for coevolutionary processes. We demonstrate that an adaptive network transforms a two-person social dilemma locally faced by individuals into a collective dynamics that resembles that associated with an N-person coordination game, whose characterization depends sensitively on the relative time scales between the entangled behavioral and network evolutions. In particular, we show that the faster the relative rate of adaptation of the network, the smaller the critical fraction of cooperators required for cooperation to prevail, thus establishing a direct link between network adaptation and the evolution of cooperation. The framework developed here is general and may be readily applied to other dynamical processes occurring on adaptive networks, notably, the spreading of contagious diseases or the diffusion of innovations.

  18. Linking Individual and Collective Behavior in Adaptive Social Networks

    NASA Astrophysics Data System (ADS)

    Pinheiro, Flávio L.; Santos, Francisco C.; Pacheco, Jorge M.

    2016-03-01

    Adaptive social structures are known to promote the evolution of cooperation. However, up to now the characterization of the collective, population-wide dynamics resulting from the self-organization of individual strategies on a coevolving, adaptive network has remained unfeasible. Here we establish a (reversible) link between individual (micro)behavior and collective (macro)behavior for coevolutionary processes. We demonstrate that an adaptive network transforms a two-person social dilemma locally faced by individuals into a collective dynamics that resembles that associated with an N -person coordination game, whose characterization depends sensitively on the relative time scales between the entangled behavioral and network evolutions. In particular, we show that the faster the relative rate of adaptation of the network, the smaller the critical fraction of cooperators required for cooperation to prevail, thus establishing a direct link between network adaptation and the evolution of cooperation. The framework developed here is general and may be readily applied to other dynamical processes occurring on adaptive networks, notably, the spreading of contagious diseases or the diffusion of innovations.

  19. Predicting top-L missing links with node and link clustering information in large-scale networks

    NASA Astrophysics Data System (ADS)

    Wu, Zhihao; Lin, Youfang; Wan, Huaiyu; Jamil, Waleed

    2016-08-01

    Networks are mathematical structures that are universally used to describe a large variety of complex systems, such as social, biological, and technological systems. The prediction of missing links in incomplete complex networks aims to estimate the likelihood of the existence of a link between a pair of nodes. Various topological features of networks have been applied to develop link prediction methods. However, the exploration of features of links is still limited. In this paper, we demonstrate the power of node and link clustering information in predicting top -L missing links. In the existing literature, link prediction algorithms have only been tested on small-scale and middle-scale networks. The network scale factor has not attracted the same level of attention. In our experiments, we test the proposed method on three groups of networks. For small-scale networks, since the structures are not very complex, advanced methods cannot perform significantly better than classical methods. For middle-scale networks, the proposed index, combining both node and link clustering information, starts to demonstrate its advantages. In many networks, combining both node and link clustering information can improve the link prediction accuracy a great deal. Large-scale networks with more than 100 000 links have rarely been tested previously. Our experiments on three large-scale networks show that local clustering information based methods outperform other methods, and link clustering information can further improve the accuracy of node clustering information based methods, in particular for networks with a broad distribution of the link clustering coefficient.

  20. Logic integer programming models for signaling networks.

    PubMed

    Haus, Utz-Uwe; Niermann, Kathrin; Truemper, Klaus; Weismantel, Robert

    2009-05-01

    We propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this, we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in molecular biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.

  1. Uncovering the essential links in online commercial networks

    PubMed Central

    Zeng, Wei; Fang, Meiling; Shao, Junming; Shang, Mingsheng

    2016-01-01

    Recommender systems are designed to effectively support individuals' decision-making process on various web sites. It can be naturally represented by a user-object bipartite network, where a link indicates that a user has collected an object. Recently, research on the information backbone has attracted researchers' interests, which is a sub-network with fewer nodes and links but carrying most of the relevant information. With the backbone, a system can generate satisfactory recommenda- tions while saving much computing resource. In this paper, we propose an enhanced topology-aware method to extract the information backbone in the bipartite network mainly based on the information of neighboring users and objects. Our backbone extraction method enables the recommender systems achieve more than 90% of the accuracy of the top-L recommendation, however, consuming only 20% links. The experimental results show that our method outperforms the alternative backbone extraction methods. Moreover, the structure of the information backbone is studied in detail. Finally, we highlight that the information backbone is one of the most important properties of the bipartite network, with which one can significantly improve the efficiency of the recommender system. PMID:27682464

  2. Uncovering the essential links in online commercial networks

    NASA Astrophysics Data System (ADS)

    Zeng, Wei; Fang, Meiling; Shao, Junming; Shang, Mingsheng

    2016-09-01

    Recommender systems are designed to effectively support individuals' decision-making process on various web sites. It can be naturally represented by a user-object bipartite network, where a link indicates that a user has collected an object. Recently, research on the information backbone has attracted researchers' interests, which is a sub-network with fewer nodes and links but carrying most of the relevant information. With the backbone, a system can generate satisfactory recommenda- tions while saving much computing resource. In this paper, we propose an enhanced topology-aware method to extract the information backbone in the bipartite network mainly based on the information of neighboring users and objects. Our backbone extraction method enables the recommender systems achieve more than 90% of the accuracy of the top-L recommendation, however, consuming only 20% links. The experimental results show that our method outperforms the alternative backbone extraction methods. Moreover, the structure of the information backbone is studied in detail. Finally, we highlight that the information backbone is one of the most important properties of the bipartite network, with which one can significantly improve the efficiency of the recommender system.

  3. Linking the levels: network and relational perspectives for community psychology.

    PubMed

    Neal, Jennifer Watling; Christens, Brian D

    2014-06-01

    In this article, we assert that relationships and networks are of paramount importance for understanding and improving settings, neighborhoods, communities, and larger social systems. Despite previous acknowledgements of their relevance, relational and social network perspectives and analyses remain underrepresented in community psychological research and action. Here, we claim that network and relational perspectives can provide conceptual and empirical 'links' between levels of analysis, more fully reflecting a transactional view. We also describe some of the sophisticated methodologies that can be employed in empirical studies drawing on these perspectives. Additionally, we contend that core concepts in community psychology such as health promotion, empowerment, coalition building, and dissemination and implementation can be better understood when employing relational and network perspectives. As an introduction to this special issue of American Journal of Community Psychology, we draw out themes and key points from the articles in the issue, and offer recommendations for future advancement of these perspectives in the field.

  4. Asynchronous transfer mode link performance over ground networks

    NASA Technical Reports Server (NTRS)

    Chow, E. T.; Markley, R. W.

    1993-01-01

    The results of an experiment to determine the feasibility of using asynchronous transfer mode (ATM) technology to support advanced spacecraft missions that require high-rate ground communications and, in particular, full-motion video are reported. Potential nodes in such a ground network include Deep Space Network (DSN) antenna stations, the Jet Propulsion Laboratory, and a set of national and international end users. The experiment simulated a lunar microrover, lunar lander, the DSN ground communications system, and distributed science users. The users were equipped with video-capable workstations. A key feature was an optical fiber link between two high-performance workstations equipped with ATM interfaces. Video was also transmitted through JPL's institutional network to a user 8 km from the experiment. Variations in video depending on the networks and computers were observed, the results are reported.

  5. Spatial Modeling of Cell Signaling Networks

    PubMed Central

    Cowan, Ann E.; Moraru, Ion I.; Schaff, James C.; Slepchenko, Boris M.; Loew, Leslie M.

    2012-01-01

    The shape of a cell, the sizes of subcellular compartments and the spatial distribution of molecules within the cytoplasm can all control how molecules interact to produce a cellular behavior. This chapter describes how these spatial features can be included in mechanistic mathematical models of cell signaling. The Virtual Cell computational modeling and simulation software is used to illustrate the considerations required to build a spatial model. An explanation of how to appropriately choose between physical formulations that implicitly or explicitly account for cell geometry and between deterministic vs, stochastic formulations for molecular dynamics is provided, along with a discussion of their respective strengths and weaknesses. As a first step toward constructing a spatial model, the geometry needs to be specified and associated with the molecules, reactions and membrane flux processes of the network. Initial conditions, diffusion coefficients, velocities and boundary conditions complete the specifications required to define the mathematics of the model. The numerical methods used to solve reaction-diffusion problems both deterministically and stochastically are then described and some guidance is provided in how to set up and run simulations. A study of cAMP signaling in neurons ends the chapter, providing an example of the insights that can be gained in interpreting experimental results through the application of spatial modeling. PMID:22482950

  6. Orthogonal least squares based complex-valued functional link network.

    PubMed

    Amin, Md Faijul; Savitha, Ramasamy; Amin, Muhammad Ilias; Murase, Kazuyuki

    2012-08-01

    Functional link networks are single-layered neural networks that impose nonlinearity in the input layer using nonlinear functions of the original input variables. In this paper, we present a fully complex-valued functional link network (CFLN) with multivariate polynomials as the nonlinear functions. Unlike multilayer neural networks, the CFLN is free from local minima problem, and it offers very fast learning of parameters because of its linear structure. Polynomial based CFLN does not require an activation function which is a major concern in the complex-valued neural networks. However, it is important to select a smaller subset of polynomial terms (monomials) for faster and better performance since the number of all possible monomials may be quite large. Here, we use the orthogonal least squares (OLS) method in a constructive fashion (starting from lower degree to higher) for the selection of a parsimonious subset of monomials. It is argued here that computing CFLN in purely complex domain is advantageous than in double-dimensional real domain, in terms of number of connection parameters, faster design, and possibly generalization performance. Simulation results on a function approximation, wind prediction with real-world data, and a nonlinear channel equalization problem exhibit that the OLS based CFLN yields very simple structure having favorable performance.

  7. Orthogonal least squares based complex-valued functional link network.

    PubMed

    Amin, Md Faijul; Savitha, Ramasamy; Amin, Muhammad Ilias; Murase, Kazuyuki

    2012-08-01

    Functional link networks are single-layered neural networks that impose nonlinearity in the input layer using nonlinear functions of the original input variables. In this paper, we present a fully complex-valued functional link network (CFLN) with multivariate polynomials as the nonlinear functions. Unlike multilayer neural networks, the CFLN is free from local minima problem, and it offers very fast learning of parameters because of its linear structure. Polynomial based CFLN does not require an activation function which is a major concern in the complex-valued neural networks. However, it is important to select a smaller subset of polynomial terms (monomials) for faster and better performance since the number of all possible monomials may be quite large. Here, we use the orthogonal least squares (OLS) method in a constructive fashion (starting from lower degree to higher) for the selection of a parsimonious subset of monomials. It is argued here that computing CFLN in purely complex domain is advantageous than in double-dimensional real domain, in terms of number of connection parameters, faster design, and possibly generalization performance. Simulation results on a function approximation, wind prediction with real-world data, and a nonlinear channel equalization problem exhibit that the OLS based CFLN yields very simple structure having favorable performance. PMID:22386786

  8. Epidemics with temporary link deactivation in scale-free networks.

    PubMed

    Shkarayev, Maxim S; Tunc, Ilker; Shaw, Leah B

    2014-11-14

    During an epidemic, people may adapt or alter their social contacts to avoid infection. Various adaptation mechanisms have been studied previously. Recently, a new adaptation mechanism was presented in [1], where susceptible nodes temporarily deactivate their links to infected neighbors and reactivate when their neighbors recover. Considering the same adaptation mechanism on a scale-free network, we find that the topology of the subnetwork consisting of active links is fundamentally different from the original network topology. We predict the scaling exponent of the active degree distribution and derive mean-field equations by using improved moment closure approximations based on the conditional distribution of active degree given the total degree. These mean field equations show better agreement with numerical simulation results than the standard mean field equations based on a homogeneity assumption.

  9. Epidemics with temporary link deactivation in scale-free networks

    NASA Astrophysics Data System (ADS)

    Shkarayev, Maxim S.; Tunc, Ilker; Shaw, Leah B.

    2014-11-01

    During an epidemic, people may adapt or alter their social contacts to avoid infection. Various adaptation mechanisms have been studied previously. Recently, a new adaptation mechanism was presented in (Tunc et al 2013 J. Stat. Phys. 151 355), where susceptible nodes temporarily deactivate their links to infected neighbors and reactivate when their neighbors recover. Considering the same adaptation mechanism on a scale-free network, we find that the topology of the subnetwork consisting of active links is fundamentally different from the original network topology. We predict the scaling exponent of the active degree distribution and derive mean field equations by using improved moment closure approximations based on the conditional distribution of active degree given the total degree. These mean field equations show better agreement with numerical simulation results than the standard mean field equations based on a homogeneity assumption.

  10. Epidemics with temporary link deactivation in scale-free networks

    PubMed Central

    Shkarayev, Maxim S.; Tunc, Ilker; Shaw, Leah B.

    2014-01-01

    During an epidemic, people may adapt or alter their social contacts to avoid infection. Various adaptation mechanisms have been studied previously. Recently, a new adaptation mechanism was presented in [1], where susceptible nodes temporarily deactivate their links to infected neighbors and reactivate when their neighbors recover. Considering the same adaptation mechanism on a scale-free network, we find that the topology of the subnetwork consisting of active links is fundamentally different from the original network topology. We predict the scaling exponent of the active degree distribution and derive mean-field equations by using improved moment closure approximations based on the conditional distribution of active degree given the total degree. These mean field equations show better agreement with numerical simulation results than the standard mean field equations based on a homogeneity assumption. PMID:25419231

  11. MiRTargetLink--miRNAs, Genes and Interaction Networks.

    PubMed

    Hamberg, Maarten; Backes, Christina; Fehlmann, Tobias; Hart, Martin; Meder, Benjamin; Meese, Eckart; Keller, Andreas

    2016-04-14

    Information on miRNA targeting genes is growing rapidly. For high-throughput experiments, but also for targeted analyses of few genes or miRNAs, easy analysis with concise representation of results facilitates the work of life scientists. We developed miRTargetLink, a tool for automating respective analysis procedures that are frequently applied. Input of the web-based solution is either a single gene or single miRNA, but also sets of genes or miRNAs, can be entered. Validated and predicted targets are extracted from databases and an interaction network is presented. Users can select whether predicted targets, experimentally validated targets with strong or weak evidence, or combinations of those are considered. Central genes or miRNAs are highlighted and users can navigate through the network interactively. To discover the most relevant biochemical processes influenced by the target network, gene set analysis and miRNA set analysis are integrated. As a showcase for miRTargetLink, we analyze targets of five cardiac miRNAs. miRTargetLink is freely available without restrictions at www.ccb.uni-saarland.de/mirtargetlink.

  12. Effects of adaptive dynamical linking in networked games

    NASA Astrophysics Data System (ADS)

    Yang, Zhihu; Li, Zhi; Wu, Te; Wang, Long

    2013-10-01

    The role of dynamical topologies in the evolution of cooperation has received considerable attention, as some studies have demonstrated that dynamical networks are much better than static networks in terms of boosting cooperation. Here we study a dynamical model of evolution of cooperation on stochastic dynamical networks in which there are no permanent partners to each agent. Whenever a new link is created, its duration is randomly assigned without any bias or preference. We allow the agent to adaptively adjust the duration of each link during the evolution in accordance with the feedback from game interactions. By Monte Carlo simulations, we find that cooperation can be remarkably promoted by this adaptive dynamical linking mechanism both for the game of pairwise interactions, such as the Prisoner's Dilemma game (PDG), and for the game of group interactions, illustrated by the public goods game (PGG). And the faster the adjusting rate, the more successful the evolution of cooperation. We also show that in this context weak selection favors cooperation much more than strong selection does. What is particularly meaningful is that the prosperity of cooperation in this study indicates that the rationality and selfishness of a single agent in adjusting social ties can lead to the progress of altruism of the whole population.

  13. Photoreceptor signaling networks in plant responses to shade.

    PubMed

    Casal, Jorge J

    2013-01-01

    The dynamic light environment of vegetation canopies is perceived by phytochromes, cryptochromes, phototropins, and UV RESISTANCE LOCUS 8 (UVR8). These receptors control avoidance responses to preclude exposure to limiting or excessive light and acclimation responses to cope with conditions that cannot be avoided. The low red/far-red ratios of shade light reduce phytochrome B activity, which allows PHYTOCHROME INTERACTING FACTORS (PIFs) to directly activate the transcription of auxin-synthesis genes, leading to shade-avoidance responses. Direct PIF interaction with DELLA proteins links gibberellin and brassinosteroid signaling to shade avoidance. Shade avoidance also requires CONSTITUTIVE PHOTOMORPHOGENESIS 1 (COP1), a target of cryptochromes, phytochromes, and UVR8. Multiple regulatory loops and the input of the circadian clock create a complex network able to respond even to subtle threats of competition with neighbors while still compensating for major environmental fluctuations such as the day-night cycles.

  14. CD-Based Indices for Link Prediction in Complex Network

    PubMed Central

    Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

    2016-01-01

    Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks. PMID:26752405

  15. CD-Based Indices for Link Prediction in Complex Network.

    PubMed

    Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

    2016-01-01

    Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks.

  16. CD-Based Indices for Link Prediction in Complex Network.

    PubMed

    Wang, Tao; Wang, Hongjue; Wang, Xiaoxia

    2016-01-01

    Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks. PMID:26752405

  17. Spatial signals link exit from mitosis to spindle position

    PubMed Central

    Falk, Jill Elaine; Tsuchiya, Dai; Verdaasdonk, Jolien; Lacefield, Soni; Bloom, Kerry; Amon, Angelika

    2016-01-01

    In budding yeast, if the spindle becomes mispositioned, cells prevent exit from mitosis by inhibiting the mitotic exit network (MEN). The MEN is a signaling cascade that localizes to spindle pole bodies (SPBs) and activates the phosphatase Cdc14. There are two competing models that explain MEN regulation by spindle position. In the 'zone model', exit from mitosis occurs when a MEN-bearing SPB enters the bud. The 'cMT-bud neck model' posits that cytoplasmic microtubule (cMT)-bud neck interactions prevent MEN activity. Here we find that 1) eliminating cMT– bud neck interactions does not trigger exit from mitosis and 2) loss of these interactions does not precede Cdc14 activation. Furthermore, using binucleate cells, we show that exit from mitosis occurs when one SPB enters the bud despite the presence of a mispositioned spindle. We conclude that exit from mitosis is triggered by a correctly positioned spindle rather than inhibited by improper spindle position. DOI: http://dx.doi.org/10.7554/eLife.14036.001 PMID:27166637

  18. Forgetting in Reinforcement Learning Links Sustained Dopamine Signals to Motivation

    PubMed Central

    Morita, Kenji

    2016-01-01

    It has been suggested that dopamine (DA) represents reward-prediction-error (RPE) defined in reinforcement learning and therefore DA responds to unpredicted but not predicted reward. However, recent studies have found DA response sustained towards predictable reward in tasks involving self-paced behavior, and suggested that this response represents a motivational signal. We have previously shown that RPE can sustain if there is decay/forgetting of learned-values, which can be implemented as decay of synaptic strengths storing learned-values. This account, however, did not explain the suggested link between tonic/sustained DA and motivation. In the present work, we explored the motivational effects of the value-decay in self-paced approach behavior, modeled as a series of ‘Go’ or ‘No-Go’ selections towards a goal. Through simulations, we found that the value-decay can enhance motivation, specifically, facilitate fast goal-reaching, albeit counterintuitively. Mathematical analyses revealed that underlying potential mechanisms are twofold: (1) decay-induced sustained RPE creates a gradient of ‘Go’ values towards a goal, and (2) value-contrasts between ‘Go’ and ‘No-Go’ are generated because while chosen values are continually updated, unchosen values simply decay. Our model provides potential explanations for the key experimental findings that suggest DA's roles in motivation: (i) slowdown of behavior by post-training blockade of DA signaling, (ii) observations that DA blockade severely impairs effortful actions to obtain rewards while largely sparing seeking of easily obtainable rewards, and (iii) relationships between the reward amount, the level of motivation reflected in the speed of behavior, and the average level of DA. These results indicate that reinforcement learning with value-decay, or forgetting, provides a parsimonious mechanistic account for the DA's roles in value-learning and motivation. Our results also suggest that when biological

  19. NOD1/NOD2 signaling links ER stress with inflammation

    PubMed Central

    Keestra-Gounder, A. Marijke; Byndloss, Mariana X.; Seyffert, Núbia; Young, Briana M.; Chávez-Arroyo, Alfredo; Tsai, April Y.; Cevallos, Stephanie A.; Winter, Maria G.; Pham, Oanh H.; Tiffany, Connor R.; de Jong, Maarten F.; Kerrinnes, Tobias; Ravindran, Resmi; Luciw, Paul A.; McSorley, Stephen J.; Bäumler, Andreas J.; Tsolis, Renée M.

    2016-01-01

    Endoplasmic reticulum (ER) stress is a major contributor to inflammatory diseases, such as Crohn’s disease and type 2 diabetes1,2. ER stress induces the unfolded protein response (UPR), which involves activation of three transmembrane receptors, ATF6 (activating transcription factor 6), PERK (protein kinase RNA-like endoplasmic reticulum kinase) and IRE1α (inositol-requiring enzyme 1α)3 (Extended Data figure 1a). Once activated, IRE1α recruits TRAF2 (TNF receptor-associated factor 2) to the ER membrane to initiate inflammatory responses via the nuclear factor kappa B (NF-κB) pathway4. Inflammation is commonly triggered when pattern recognition receptors (PRRs), such as Toll-like receptors (TLRs) or nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs), detect tissue damage or microbial infection. However, it is not clear which PRRs play a major role in inducing inflammation during ER stress. Here we show that NOD1 and NOD2, two members of the NLR family of PRRs, are important mediators of ER stress-induced inflammation. The ER stress inducers thapsigargin and dithiothreitol (DTT) triggered production of the pro-inflammatory cytokine interleukin (IL)-6 in a NOD1/2-dependent fashion. Inflammation and IL-6 production triggered by infection with Brucella abortus, which induces ER stress by injecting the type IV secretion system (T4SS) effector protein VceC into host cells5, was TRAF2, NOD1/2 and RIP2-dependent and could be blunted by treatment with the ER-stress inhibitor tauroursodeoxycholate (TUDCA) or an IRE1α kinase inhibitor. The association of NOD1 and NOD2 with pro-inflammatory responses induced by the IRE1α/TRAF2 signaling pathway provides a novel link between innate immunity and ER stress-induced inflammation. PMID:27007849

  20. Autoclavable highly cross-linked polyurethane networks in ophthalmology.

    PubMed

    Bruin, P; Meeuwsen, E A; van Andel, M V; Worst, J G; Pennings, A J

    1993-11-01

    Highly cross-linked aliphatic polyurethane networks have been prepared by the bulk step reaction of low molecular weight polyols and hexamethylenediisocyanate (HDI). These polyurethane networks are optically transparent, colourless and autoclavable amorphous glassy thermosets, which are suited for use in ophthalmic applications such as intraocular lenses and keratoprostheses. The properties of these glassy polyurethanes, obtained from the reaction of the low molecular weight polyols triisopropanolamine (TIPA) or tetrakis (2-hydroxypropyl)ethylenediamine (Quadrol) and HDI in stoichiometric proportions, have been investigated in more detail. The glassy Quadrol/HDI-based polyurethane exhibits a reduction in ultimate glass transition temperature from 85 to 48 degrees C by uptake of 1% of water, and good ultimate mechanical properties (tensile strength 80-85 MPa, elongation at break ca 15%, modulus ca 1.5 GPa). IR spectra of these hydrophobic polyurethane networks revealed the absence of an isocyanate absorption, indicating that all isocyanates, apparently, had reacted during the cross-linking reaction. The biocompatibility could be increased by grafting tethered polyacrylamide chains onto the surface during network formation. These transparent cross-linked polyurethanes did not transmit UV light up to 400 nm, by incorporation of a small amount of the UV absorbing chromophore Coumarin 102, and could be sterilized simply by autoclaving. They were implanted in rabbit eyes, either in the form of small circular disks or in the form of a keratoprosthesis (artificial cornea). It was shown that the material was well tolerated by the rabbit eyes. Serious opacification of the cornea, a direct result of an adverse reaction to the implant, was never seen. Even 1 yr after implantation of a polyurethane keratoprosthesis the eye was still 'quiet'. PMID:7508760

  1. Directed networks' different link formation mechanisms causing degree distribution distinction

    NASA Astrophysics Data System (ADS)

    Behfar, Stefan Kambiz; Turkina, Ekaterina; Cohendet, Patrick; Burger-Helmchen, Thierry

    2016-11-01

    Within undirected networks, scientists have shown much interest in presenting power-law features. For instance, Barabási and Albert (1999) claimed that a common property of many large networks is that vertex connectivity follows scale-free power-law distribution, and in another study Barabási et al. (2002) showed power law evolution in the social network of scientific collaboration. At the same time, Jiang et al. (2011) discussed deviation from power-law distribution; others indicated that size effect (Bagrow et al., 2008), information filtering mechanism (Mossa et al., 2002), and birth and death process (Shi et al., 2005) could account for this deviation. Within directed networks, many authors have considered that outlinks follow a similar mechanism of creation as inlinks' (Faloutsos et al., 1999; Krapivsky et al., 2001; Tanimoto, 2009) with link creation rate being the linear function of node degree, resulting in a power-law shape for both indegree and outdegree distribution. Some other authors have made an assumption that directed networks, such as scientific collaboration or citation, behave as undirected, resulting in a power-law degree distribution accordingly (Barabási et al., 2002). At the same time, we claim (1) Outlinks feature different degree distributions than inlinks; where different link formation mechanisms cause the distribution distinctions, (2) in/outdegree distribution distinction holds for different levels of system decomposition; therefore this distribution distinction is a property of directed networks. First, we emphasize in/outlink formation mechanisms as causal factors for distinction between indegree and outdegree distributions (where this distinction has already been noticed in Barker et al. (2010) and Baxter et al. (2006)) within a sample network of OSS projects as well as Java software corpus as a network. Second, we analyze whether this distribution distinction holds for different levels of system decomposition: open

  2. Protein Interaction Networks Link Schizophrenia Risk Loci to Synaptic Function

    PubMed Central

    Schwarz, Emanuel; Izmailov, Rauf; Liò, Pietro; Meyer-Lindenberg, Andreas

    2016-01-01

    Schizophrenia is a severe and highly heritable psychiatric disorder affecting approximately 1% of the population. Genome-wide association studies have identified 108 independent genetic loci with genome-wide significance but their functional importance has yet to be elucidated. Here, we develop a novel strategy based on network analysis of protein–protein interactions (PPI) to infer biological function associated with variants most strongly linked to illness risk. We show that the schizophrenia loci are strongly linked to synaptic transmission (P FWE < .001) and ion transmembrane transport (P FWE = .03), but not to ontological categories previously found to be shared across psychiatric illnesses. We demonstrate that brain expression of risk-linked genes within the identified processes is strongly modulated during birth and identify a set of synaptic genes consistently changed across multiple brain regions of adult schizophrenia patients. These results suggest synaptic function as a developmentally determined schizophrenia process supported by the illness’s most associated genetic variants and their PPI networks. The implicated genes may be valuable targets for mechanistic experiments and future drug development approaches. PMID:27056717

  3. Early-warning signals of topological collapse in interbank networks

    PubMed Central

    Squartini, Tiziano; van Lelyveld, Iman; Garlaschelli, Diego

    2013-01-01

    The financial crisis clearly illustrated the importance of characterizing the level of ‘systemic’ risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze the quarterly interbank exposures among Dutch banks over the period 1998–2008, ending with the crisis. After controlling for the link density, many topological properties display an abrupt change in 2008, providing a clear – but unpredictable – signature of the crisis. By contrast, if the heterogeneity of banks' connectivity is controlled for, the same properties show a gradual transition to the crisis, starting in 2005 and preceded by an even earlier period during which anomalous debt loops could have led to the underestimation of counter-party risk. These early-warning signals are undetectable if the network is reconstructed from partial bank-specific data, as routinely done. We discuss important implications for bank regulatory policies. PMID:24285089

  4. Establishing a Statistical Link between Network Oscillations and Neural Synchrony.

    PubMed

    Zhou, Pengcheng; Burton, Shawn D; Snyder, Adam C; Smith, Matthew A; Urban, Nathaniel N; Kass, Robert E

    2015-10-01

    Pairs of active neurons frequently fire action potentials or "spikes" nearly synchronously (i.e., within 5 ms of each other). This spike synchrony may occur by chance, based solely on the neurons' fluctuating firing patterns, or it may occur too frequently to be explicable by chance alone. When spike synchrony above chances levels is present, it may subserve computation for a specific cognitive process, or it could be an irrelevant byproduct of such computation. Either way, spike synchrony is a feature of neural data that should be explained. A point process regression framework has been developed previously for this purpose, using generalized linear models (GLMs). In this framework, the observed number of synchronous spikes is compared to the number predicted by chance under varying assumptions about the factors that affect each of the individual neuron's firing-rate functions. An important possible source of spike synchrony is network-wide oscillations, which may provide an essential mechanism of network information flow. To establish the statistical link between spike synchrony and network-wide oscillations, we have integrated oscillatory field potentials into our point process regression framework. We first extended a previously-published model of spike-field association and showed that we could recover phase relationships between oscillatory field potentials and firing rates. We then used this new framework to demonstrate the statistical relationship between oscillatory field potentials and spike synchrony in: 1) simulated neurons, 2) in vitro recordings of hippocampal CA1 pyramidal cells, and 3) in vivo recordings of neocortical V4 neurons. Our results provide a rigorous method for establishing a statistical link between network oscillations and neural synchrony. PMID:26465621

  5. Establishing a Statistical Link between Network Oscillations and Neural Synchrony

    PubMed Central

    Zhou, Pengcheng; Burton, Shawn D.; Snyder, Adam C.; Smith, Matthew A.; Urban, Nathaniel N.; Kass, Robert E.

    2015-01-01

    Pairs of active neurons frequently fire action potentials or “spikes” nearly synchronously (i.e., within 5 ms of each other). This spike synchrony may occur by chance, based solely on the neurons’ fluctuating firing patterns, or it may occur too frequently to be explicable by chance alone. When spike synchrony above chances levels is present, it may subserve computation for a specific cognitive process, or it could be an irrelevant byproduct of such computation. Either way, spike synchrony is a feature of neural data that should be explained. A point process regression framework has been developed previously for this purpose, using generalized linear models (GLMs). In this framework, the observed number of synchronous spikes is compared to the number predicted by chance under varying assumptions about the factors that affect each of the individual neuron’s firing-rate functions. An important possible source of spike synchrony is network-wide oscillations, which may provide an essential mechanism of network information flow. To establish the statistical link between spike synchrony and network-wide oscillations, we have integrated oscillatory field potentials into our point process regression framework. We first extended a previously-published model of spike-field association and showed that we could recover phase relationships between oscillatory field potentials and firing rates. We then used this new framework to demonstrate the statistical relationship between oscillatory field potentials and spike synchrony in: 1) simulated neurons, 2) in vitro recordings of hippocampal CA1 pyramidal cells, and 3) in vivo recordings of neocortical V4 neurons. Our results provide a rigorous method for establishing a statistical link between network oscillations and neural synchrony. PMID:26465621

  6. Assessing the weather monitoring capabilities of cellular microwave link networks

    NASA Astrophysics Data System (ADS)

    Fencl, Martin; Vrzba, Miroslav; Rieckermann, Jörg; Bareš, Vojtěch

    2016-04-01

    Using of microwave links for rainfall monitoring was suggested already by (Atlas and Ulbrich, 1977). However, this technique attracted broader attention of scientific community only in the recent decade, with the extensive growth of cellular microwave link (CML) networks, which form the backbone of today's cellular telecommunication infrastructure. Several studies have already shown that CMLs can be conveniently used as weather sensors and have potential to provide near-ground path-integrated observations of rainfall but also humidity or fog. However, although research is still focusing on algorithms to improve the weather sensing capabilities (Fencl et al., 2015), it is not clear how to convince cellular operators to provide the power levels of their network. One step in this direction is to show in which regions or municipalities the networks are sufficiently dense to provide/develop good services. In this contribution we suggest a standardized approach to evaluate CML networks in terms of rainfall observation and to identify suitable regions for CML rainfall monitoring. We estimate precision of single CML based on its sensitivity to rainfall, i.e. as a function of frequency, polarization and path length. Capability of a network to capture rainfall spatial patterns is estimated from the CML coverage and path lengths considering that single CML provides path-integrated rain rates. We also search for suitable predictors for regions where no network topologies are available. We test our approach on several European networks and discuss the results. Our results show that CMLs are very dense in urban areas (> 1 CML/km2), but less in rural areas (< 0.02 CML/km2). We found a strong correlation between a population and CML network density (e.g. R2 = 0.97 in Czech Republic), thus population could be a simple proxy to identify suitable regions for CML weather monitoring. To enable a simple and efficient assessment of the CML monitoring potential for any region worldwide

  7. Radar signal categorization using a neural network

    NASA Technical Reports Server (NTRS)

    Anderson, James A.; Gately, Michael T.; Penz, P. Andrew; Collins, Dean R.

    1991-01-01

    Neural networks were used to analyze a complex simulated radar environment which contains noisy radar pulses generated by many different emitters. The neural network used is an energy minimizing network (the BSB model) which forms energy minima - attractors in the network dynamical system - based on learned input data. The system first determines how many emitters are present (the deinterleaving problem). Pulses from individual simulated emitters give rise to separate stable attractors in the network. Once individual emitters are characterized, it is possible to make tentative identifications of them based on their observed parameters. As a test of this idea, a neural network was used to form a small data base that potentially could make emitter identifications.

  8. Bio-inspired signal transduction with heterogeneous networks of nanoscillators

    NASA Astrophysics Data System (ADS)

    Cervera, Javier; Manzanares, José A.; Mafé, Salvador

    2012-02-01

    Networks of single-electron transistors mimic some of the essential properties of neuron populations, because weak electrical signals trigger network oscillations with a frequency proportional to the input signal. Input potentials representing the pixel gray level of a grayscale image can then be converted into rhythms and the image can be recovered from these rhythms. Networks of non-identical nanoscillators complete the noisy transduction more reliably than identical ones. These results are important for signal processing schemes and could support recent studies suggesting that neuronal variability enhances the processing of biological information.

  9. SP-NET: A draft signal processor network protocol

    NASA Astrophysics Data System (ADS)

    Burns, David M.

    SP-net, a synchronous high-speed switched network that has been designed for signal processor backplanes, is discussed. The network uses bit-slicing to improve fault tolerance and to allow growth in the width of the data path. In addition, single-bit error detection has been included in the protocol. Although no company at present is building a network to the draft SP-net specifications, SP-net has several similarities to signal processor network designs by major defense contractors.

  10. An extended signal control strategy for urban network traffic flow

    NASA Astrophysics Data System (ADS)

    Yan, Fei; Tian, Fuli; Shi, Zhongke

    2016-03-01

    Traffic flow patterns are in general repeated on a daily or weekly basis. To improve the traffic conditions by using the inherent repeatability of traffic flow, a novel signal control strategy for urban networks was developed via iterative learning control (ILC) approach. Rigorous analysis shows that the proposed learning control method can guarantee the asymptotic convergence. The impacts of the ILC-based signal control strategy on the macroscopic fundamental diagram (MFD) were analyzed by simulations on a test road network. The results show that the proposed ILC strategy can evenly distribute the accumulation in the network and improve the network mobility.

  11. Signaled and Unsignaled Terminal Links in Concurrent Chains I: Effects of Reinforcer Probability and Immediacy

    ERIC Educational Resources Information Center

    Mattson, Karla M.; Hucks, Andrew; Grace, Randolph C.; McLean, Anthony P.

    2010-01-01

    Eight pigeons responded in a three-component concurrent-chains procedure, with either independent or dependent initial links. Relative probability and immediacy of reinforcement in the terminal links were both varied, and outcomes on individual trials (reinforcement or nonreinforcement) were either signaled or unsignaled. Terminal-link fixed-time…

  12. P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

    PubMed

    Young-Rae Cho; Yanan Xin; Speegle, Greg

    2015-01-01

    Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.

  13. Predictors of the peak width for networks with exponential links

    USGS Publications Warehouse

    Troutman, B.M.; Karlinger, M.R.

    1989-01-01

    We investigate optimal predictors of the peak (S) and distance to peak (T) of the width function of drainage networks under the assumption that the networks are topologically random with independent and exponentially distributed link lengths. Analytical results are derived using the fact that, under these assumptions, the width function is a homogeneous Markov birth-death process. In particular, exact expressions are derived for the asymptotic conditional expectations of S and T given network magnitude N and given mainstream length H. In addition, a simulation study is performed to examine various predictors of S and T, including N, H, and basin morphometric properties; non-asymptotic conditional expectations and variances are estimated. The best single predictor of S is N, of T is H, and of the scaled peak (S divided by the area under the width function) is H. Finally, expressions tested on a set of drainage basins from the state of Wyoming perform reasonably well in predicting S and T despite probable violations of the original assumptions. ?? 1989 Springer-Verlag.

  14. Cell cycle networks link gene expression dysregulation, mutation, and brain maldevelopment in autistic toddlers.

    PubMed

    Pramparo, Tiziano; Lombardo, Michael V; Campbell, Kathleen; Barnes, Cynthia Carter; Marinero, Steven; Solso, Stephanie; Young, Julia; Mayo, Maisi; Dale, Anders; Ahrens-Barbeau, Clelia; Murray, Sarah S; Lopez, Linda; Lewis, Nathan; Pierce, Karen; Courchesne, Eric

    2015-12-14

    Genetic mechanisms underlying abnormal early neural development in toddlers with Autism Spectrum Disorder (ASD) remain uncertain due to the impossibility of direct brain gene expression measurement during critical periods of early development. Recent findings from a multi-tissue study demonstrated high expression of many of the same gene networks between blood and brain tissues, in particular with cell cycle functions. We explored relationships between blood gene expression and total brain volume (TBV) in 142 ASD and control male toddlers. In control toddlers, TBV variation significantly correlated with cell cycle and protein folding gene networks, potentially impacting neuron number and synapse development. In ASD toddlers, their correlations with brain size were lost as a result of considerable changes in network organization, while cell adhesion gene networks significantly correlated with TBV variation. Cell cycle networks detected in blood are highly preserved in the human brain and are upregulated during prenatal states of development. Overall, alterations were more pronounced in bigger brains. We identified 23 candidate genes for brain maldevelopment linked to 32 genes frequently mutated in ASD. The integrated network includes genes that are dysregulated in leukocyte and/or postmortem brain tissue of ASD subjects and belong to signaling pathways regulating cell cycle G1/S and G2/M phase transition. Finally, analyses of the CHD8 subnetwork and altered transcript levels from an independent study of CHD8 suppression further confirmed the central role of genes regulating neurogenesis and cell adhesion processes in ASD brain maldevelopment.

  15. Time Score: A New Feature for Link Prediction in Social Networks

    NASA Astrophysics Data System (ADS)

    Munasinghe, Lankeshwara; Ichise, Ryutaro

    Link prediction in social networks, such as friendship networks and coauthorship networks, has recently attracted a great deal of attention. There have been numerous attempts to address the problem of link prediction through diverse approaches. In the present paper, we focus on the temporal behavior of the link strength, particularly the relationship between the time stamps of interactions or links and the temporal behavior of link strength and how link strength affects future link evolution. Most previous studies have not sufficiently discussed either the impact of time stamps of the interactions or time stamps of the links on link evolution. The gap between the current time and the time stamps of the interactions or links is also important to link evolution. In the present paper, we introduce a new time-aware feature, referred to as time score, that captures the important aspects of time stamps of interactions and the temporality of the link strengths. We also analyze the effectiveness of time score with different parameter settings for different network data sets. The results of the analysis revealed that the time score was sensitive to different networks and different time measures. We applied time score to two social network data sets, namely, Facebook friendship network data set and a coauthorship network data set. The results revealed a significant improvement in predicting future links.

  16. Hybrid digital signal processing and neural networks applications in PWRs

    SciTech Connect

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-12-31

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  17. Hybrid digital signal processing and neural networks applications in PWRs

    SciTech Connect

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-01-01

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications.

  18. Linking experimental results, biological networks and sequence analysis methods using Ontologies and Generalised Data Structures.

    PubMed

    Koehler, Jacob; Rawlings, Chris; Verrier, Paul; Mitchell, Rowan; Skusa, Andre; Ruegg, Alexander; Philippi, Stephan

    2005-01-01

    The structure of a closely integrated data warehouse is described that is designed to link different types and varying numbers of biological networks, sequence analysis methods and experimental results such as those coming from microarrays. The data schema is inspired by a combination of graph based methods and generalised data structures and makes use of ontologies and meta-data. The core idea is to consider and store biological networks as graphs, and to use generalised data structures (GDS) for the storage of further relevant information. This is possible because many biological networks can be stored as graphs: protein interactions, signal transduction networks, metabolic pathways, gene regulatory networks etc. Nodes in biological graphs represent entities such as promoters, proteins, genes and transcripts whereas the edges of such graphs specify how the nodes are related. The semantics of the nodes and edges are defined using ontologies of node and relation types. Besides generic attributes that most biological entities possess (name, attribute description), further information is stored using generalised data structures. By directly linking to underlying sequences (exons, introns, promoters, amino acid sequences) in a systematic way, close interoperability to sequence analysis methods can be achieved. This approach allows us to store, query and update a wide variety of biological information in a way that is semantically compact without requiring changes at the database schema level when new kinds of biological information is added. We describe how this datawarehouse is being implemented by extending the text-mining framework ONDEX to link, support and complement different bioinformatics applications and research activities such as microarray analysis, sequence analysis and modelling/simulation of biological systems. The system is developed under the GPL license and can be downloaded from http://sourceforge.net/projects/ondex/

  19. Hermite Functional Link Neural Network for Solving the Van der Pol-Duffing Oscillator Equation.

    PubMed

    Mall, Susmita; Chakraverty, S

    2016-08-01

    Hermite polynomial-based functional link artificial neural network (FLANN) is proposed here to solve the Van der Pol-Duffing oscillator equation. A single-layer hermite neural network (HeNN) model is used, where a hidden layer is replaced by expansion block of input pattern using Hermite orthogonal polynomials. A feedforward neural network model with the unsupervised error backpropagation principle is used for modifying the network parameters and minimizing the computed error function. The Van der Pol-Duffing and Duffing oscillator equations may not be solved exactly. Here, approximate solutions of these types of equations have been obtained by applying the HeNN model for the first time. Three mathematical example problems and two real-life application problems of Van der Pol-Duffing oscillator equation, extracting the features of early mechanical failure signal and weak signal detection problems, are solved using the proposed HeNN method. HeNN approximate solutions have been compared with results obtained by the well known Runge-Kutta method. Computed results are depicted in term of graphs. After training the HeNN model, we may use it as a black box to get numerical results at any arbitrary point in the domain. Thus, the proposed HeNN method is efficient. The results reveal that this method is reliable and can be applied to other nonlinear problems too. PMID:27348738

  20. Hermite Functional Link Neural Network for Solving the Van der Pol-Duffing Oscillator Equation.

    PubMed

    Mall, Susmita; Chakraverty, S

    2016-08-01

    Hermite polynomial-based functional link artificial neural network (FLANN) is proposed here to solve the Van der Pol-Duffing oscillator equation. A single-layer hermite neural network (HeNN) model is used, where a hidden layer is replaced by expansion block of input pattern using Hermite orthogonal polynomials. A feedforward neural network model with the unsupervised error backpropagation principle is used for modifying the network parameters and minimizing the computed error function. The Van der Pol-Duffing and Duffing oscillator equations may not be solved exactly. Here, approximate solutions of these types of equations have been obtained by applying the HeNN model for the first time. Three mathematical example problems and two real-life application problems of Van der Pol-Duffing oscillator equation, extracting the features of early mechanical failure signal and weak signal detection problems, are solved using the proposed HeNN method. HeNN approximate solutions have been compared with results obtained by the well known Runge-Kutta method. Computed results are depicted in term of graphs. After training the HeNN model, we may use it as a black box to get numerical results at any arbitrary point in the domain. Thus, the proposed HeNN method is efficient. The results reveal that this method is reliable and can be applied to other nonlinear problems too.

  1. Capacity Limit, Link Scheduling and Power Control in Wireless Networks

    ERIC Educational Resources Information Center

    Zhou, Shan

    2013-01-01

    The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different…

  2. ATP-Releasing Nucleotides: Linking DNA Synthesis to Luciferase Signaling.

    PubMed

    Ji, Debin; Mohsen, Michael G; Harcourt, Emily M; Kool, Eric T

    2016-02-01

    A new strategy is reported for the production of luminescence signals from DNA synthesis through the use of chimeric nucleoside tetraphosphate dimers in which ATP, rather than pyrophosphate, is the leaving group. ATP-releasing nucleotides (ARNs) were synthesized as derivatives of the four canonical nucleotides. All four derivatives are good substrates for DNA polymerase, with Km values averaging 13-fold higher than those of natural dNTPs, and kcat values within 1.5-fold of those of native nucleotides. Importantly, ARNs were found to yield very little background signal with luciferase. DNA synthesis experiments show that the ATP byproduct can be harnessed to elicit a chemiluminescence signal in the presence of luciferase. When using a polymerase together with the chimeric nucleotides, target DNAs/RNAs trigger the release of stoichiometrically large quantities of ATP, thereby allowing sensitive isothermal luminescence detection of nucleic acids as diverse as phage DNAs and short miRNAs.

  3. Teleconnection Paths via Climate Network Direct Link Detection.

    PubMed

    Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

    2015-12-31

    Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales. PMID:26765033

  4. Human Identification with Electrocardiogram Signals: a Neural Network Approach

    NASA Astrophysics Data System (ADS)

    Wan, Yongbo; Yao, Jianchu

    2009-05-01

    This paper presents a neural network developed to identify human subjects using electrocardiogram (ECG) signals collected from an "in-house" wearable electrocardiogram (ECG) sensor. In this project, noises were first removed from the raw signals with wavelet filters. ECG cycles were then extracted from the filtered signals and decomposed into wavelet coefficient structures. These coefficient structures were used as input vectors to a 3-layer feedforward neural network that generates the identification results. In the current study, 61 datasets collected from 23 subjects were utilized to train the neural network, which thereafter was tested with 15 new datasets from 15 different subjects. All the 15 subjects in the experiment were successfully identified. The testing results demonstrate that the neural network is effective.

  5. SIMULATING BIOCHEMICAL SIGNALING NETWORKS IN COMPLEX MOVING GEOMETRIES.

    PubMed

    Strychalski, Wanda; Adalsteinsson, David; Elston, Timothy C

    2010-01-01

    Signaling networks regulate cellular responses to environmental stimuli through cascades of protein interactions. External signals can trigger cells to polarize and move in a specific direction. During migration, spatially localized activity of proteins is maintained. To investigate the effects of morphological changes on intracellular signaling, we developed a numerical scheme consisting of a cut cell finite volume spatial discretization coupled with level set methods to simulate the resulting advection-reaction-diffusion system. We then apply the method to several biochemical reaction networks in changing geometries. We found that a Turing instability can develop exclusively by cell deformations that maintain constant area. For a Turing system with a geometry-dependent single or double peak solution, simulations in a dynamically changing geometry suggest that a single peak solution is the only stable one, independent of the oscillation frequency. The method is also applied to a model of a signaling network in a migrating fibroblast. PMID:24086102

  6. Timing and time signal distribution in digital communications networks

    NASA Astrophysics Data System (ADS)

    Kihara, Masami; Imaoka, Atushi

    1992-06-01

    The timing signal distribution characteristics of a digital communications network are evaluated to determine the Maximum Time Interval Error (MTIE) of the network; reference is made to the performance of network components such as transmission systems, slave clocks and timing distribution systems in intraoffices. The MTIE of each component is measured and used to determine the allowable MTIE of that component. The maximum number of slave node chains is shown to be 20. Time signal distribution performance is detailed. It is shown that time synchronization accuracy is of the order of submicroseconds between nodes separated by 2400 km over a two year period. For intra-office time signal distribution, the relative time accuracy is less than 3 nanoseconds using an 8 Mb/s round trip digital interface to connect a time signal supply in an office to dispersed equipment.

  7. Structural permeability of complex networks to control signals

    NASA Astrophysics Data System (ADS)

    Lo Iudice, Francesco; Garofalo, Franco; Sorrentino, Francesco

    2015-09-01

    Many biological, social and technological systems can be described as complex networks. The goal of affecting their behaviour has motivated recent work focusing on the relationship between the network structure and its propensity to be controlled. While this work has provided insight into several relevant problems, a comprehensive approach to address partial and complete controllability of networks is still lacking. Here, we bridge this gap by developing a framework to maximize the diffusion of the control signals through a network, while taking into account physical and economic constraints that inevitably arise in applications. This approach allows us to introduce the network permeability, a unified metric of the propensity of a network to be controllable. The analysis of the permeability of several synthetic and real networks enables us to extract some structural features that deepen our quantitative understanding of the ease with which specific controllability requirements can be met.

  8. Ultrahigh-capacity access network architecture for mobile data backhaul using integrated W-band wireless and free-space optical links with OAM multiplexing.

    PubMed

    Fang, Yuan; Yu, Jianjun; Zhang, Junwen; Chi, Nan; Xiao, Jiangnan; Chang, Gee-Kung

    2014-07-15

    In this Letter, we propose and experimentally demonstrate a novel access network architecture using hybrid integrated W-band wireless and free-space optical (FSO) links with orbital angular momentum (OAM) multiplexing. The transmission of a 20 GBd quadrature phase-shift keying signal modulated over 10 OAM modes has been demonstrated over a 0.6 m FSO link and a 0.4 m W-band wireless link at 100 GHz. The experimental results show that the architecture can support future ultrahigh-capacity, converged optical-wireless access networks that require extra bandwidth and system flexibility in mobile data networks.

  9. Comorbidities of Psoriasis - Exploring the Links by Network Approach

    PubMed Central

    Sundarrajan, Sudharsana; Arumugam, Mohanapriya

    2016-01-01

    Increasing epidemiological studies in patients with psoriasis report the frequent occurrence of one or more associated disorders. Psoriasis is associated with multiple comorbidities including autoimmune disease, neurological disorders, cardiometabolic diseases and inflammatory-bowel disease. An integrated system biology approach is utilized to decipher the molecular alliance of psoriasis with its comorbidities. An unbiased integrative network medicine methodology is adopted for the investigation of diseasome, biological process and pathways of five most common psoriasis associated comorbidities. A significant overlap was observed between genes acting in similar direction in psoriasis and its comorbidities proving the mandatory occurrence of either one of its comorbidities. The biological processes involved in inflammatory response and cell signaling formed a common basis between psoriasis and its associated comorbidities. The pathway analysis revealed the presence of few common pathways such as angiogenesis and few uncommon pathways which includes CCKR signaling map and gonadotrophin-realising hormone receptor pathway overlapping in all the comorbidities. The work shed light on few common genes and pathways that were previously overlooked. These fruitful targets may serve as a starting point for diagnosis and/or treatment of psoriasis comorbidities. The current research provides an evidence for the existence of shared component hypothesis between psoriasis and its comorbidities. PMID:26966903

  10. Protein S-glutathionlyation links energy metabolism to redox signaling in mitochondria

    PubMed Central

    Mailloux, Ryan J.; Treberg, Jason R.

    2015-01-01

    At its core mitochondrial function relies on redox reactions. Electrons stripped from nutrients are used to form NADH and NADPH, electron carriers that are similar in structure but support different functions. NADH supports ATP production but also generates reactive oxygen species (ROS), superoxide (O2·-) and hydrogen peroxide (H2O2). NADH-driven ROS production is counterbalanced by NADPH which maintains antioxidants in an active state. Mitochondria rely on a redox buffering network composed of reduced glutathione (GSH) and peroxiredoxins (Prx) to quench ROS generated by nutrient metabolism. As H2O2 is quenched, NADPH is expended to reactivate antioxidant networks and reset the redox environment. Thus, the mitochondrial redox environment is in a constant state of flux reflecting changes in nutrient and ROS metabolism. Changes in redox environment can modulate protein function through oxidation of protein cysteine thiols. Typically cysteine oxidation is considered to be mediated by H2O2 which oxidizes protein thiols (SH) forming sulfenic acid (SOH). However, problems begin to emerge when one critically evaluates the regulatory function of SOH. Indeed SOH formation is slow, non-specific, and once formed SOH reacts rapidly with a variety of molecules. By contrast, protein S-glutathionylation (PGlu) reactions involve the conjugation and removal of glutathione moieties from modifiable cysteine residues. PGlu reactions are driven by fluctuations in the availability of GSH and oxidized glutathione (GSSG) and thus should be exquisitely sensitive to changes ROS flux due to shifts in the glutathione pool in response to varying H2O2 availability. Here, we propose that energy metabolism-linked redox signals originating from mitochondria are mediated indirectly by H2O2 through the GSH redox buffering network in and outside mitochondria. This proposal is based on several observations that have shown that unlike other redox modifications PGlu reactions fulfill the requisite

  11. Protein S-glutathionlyation links energy metabolism to redox signaling in mitochondria.

    PubMed

    Mailloux, Ryan J; Treberg, Jason R

    2016-08-01

    At its core mitochondrial function relies on redox reactions. Electrons stripped from nutrients are used to form NADH and NADPH, electron carriers that are similar in structure but support different functions. NADH supports ATP production but also generates reactive oxygen species (ROS), superoxide (O2(·-)) and hydrogen peroxide (H2O2). NADH-driven ROS production is counterbalanced by NADPH which maintains antioxidants in an active state. Mitochondria rely on a redox buffering network composed of reduced glutathione (GSH) and peroxiredoxins (Prx) to quench ROS generated by nutrient metabolism. As H2O2 is quenched, NADPH is expended to reactivate antioxidant networks and reset the redox environment. Thus, the mitochondrial redox environment is in a constant state of flux reflecting changes in nutrient and ROS metabolism. Changes in redox environment can modulate protein function through oxidation of protein cysteine thiols. Typically cysteine oxidation is considered to be mediated by H2O2 which oxidizes protein thiols (SH) forming sulfenic acid (SOH). However, problems begin to emerge when one critically evaluates the regulatory function of SOH. Indeed SOH formation is slow, non-specific, and once formed SOH reacts rapidly with a variety of molecules. By contrast, protein S-glutathionylation (PGlu) reactions involve the conjugation and removal of glutathione moieties from modifiable cysteine residues. PGlu reactions are driven by fluctuations in the availability of GSH and oxidized glutathione (GSSG) and thus should be exquisitely sensitive to changes ROS flux due to shifts in the glutathione pool in response to varying H2O2 availability. Here, we propose that energy metabolism-linked redox signals originating from mitochondria are mediated indirectly by H2O2 through the GSH redox buffering network in and outside mitochondria. This proposal is based on several observations that have shown that unlike other redox modifications PGlu reactions fulfill the requisite

  12. Evolution of SH2 domains and phosphotyrosine signalling networks

    PubMed Central

    Liu, Bernard A.; Nash, Piers D.

    2012-01-01

    Src homology 2 (SH2) domains mediate selective protein–protein interactions with tyrosine phosphorylated proteins, and in doing so define specificity of phosphotyrosine (pTyr) signalling networks. SH2 domains and protein-tyrosine phosphatases expand alongside protein-tyrosine kinases (PTKs) to coordinate cellular and organismal complexity in the evolution of the unikont branch of the eukaryotes. Examination of conserved families of PTKs and SH2 domain proteins provides fiduciary marks that trace the evolutionary landscape for the development of complex cellular systems in the proto-metazoan and metazoan lineages. The evolutionary provenance of conserved SH2 and PTK families reveals the mechanisms by which diversity is achieved through adaptations in tissue-specific gene transcription, altered ligand binding, insertions of linear motifs and the gain or loss of domains following gene duplication. We discuss mechanisms by which pTyr-mediated signalling networks evolve through the development of novel and expanded families of SH2 domain proteins and the elaboration of connections between pTyr-signalling proteins. These changes underlie the variety of general and specific signalling networks that give rise to tissue-specific functions and increasingly complex developmental programmes. Examination of SH2 domains from an evolutionary perspective provides insight into the process by which evolutionary expansion and modification of molecular protein interaction domain proteins permits the development of novel protein-interaction networks and accommodates adaptation of signalling networks. PMID:22889907

  13. Noise decomposition of intracellular biochemical signaling networks using nonequivalent reporters.

    PubMed

    Rhee, Alex; Cheong, Raymond; Levchenko, Andre

    2014-12-01

    Experimental measurements of biochemical noise have primarily focused on sources of noise at the gene expression level due to limitations of existing noise decomposition techniques. Here, we introduce a mathematical framework that extends classical extrinsic-intrinsic noise analysis and enables mapping of noise within upstream signaling networks free of such restrictions. The framework applies to systems for which the responses of interest are linearly correlated on average, although the framework can be easily generalized to the nonlinear case. Interestingly, despite the high degree of complexity and nonlinearity of most mammalian signaling networks, three distinct tumor necrosis factor (TNF) signaling network branches displayed linearly correlated responses, in both wild-type and perturbed versions of the network, across multiple orders of magnitude of ligand concentration. Using the noise mapping analysis, we find that the c-Jun N-terminal kinase (JNK) pathway generates higher noise than the NF-κB pathway, whereas the activation of c-Jun adds a greater amount of noise than the activation of ATF-2. In addition, we find that the A20 protein can suppress noise in the activation of ATF-2 by separately inhibiting the TNF receptor complex and JNK pathway through a negative feedback mechanism. These results, easily scalable to larger and more complex networks, pave the way toward assessing how noise propagates through cellular signaling pathways and create a foundation on which we can further investigate the relationship between signaling system architecture and biological noise.

  14. Noise decomposition of intracellular biochemical signaling networks using nonequivalent reporters

    PubMed Central

    Rhee, Alex; Cheong, Raymond; Levchenko, Andre

    2014-01-01

    Experimental measurements of biochemical noise have primarily focused on sources of noise at the gene expression level due to limitations of existing noise decomposition techniques. Here, we introduce a mathematical framework that extends classical extrinsic–intrinsic noise analysis and enables mapping of noise within upstream signaling networks free of such restrictions. The framework applies to systems for which the responses of interest are linearly correlated on average, although the framework can be easily generalized to the nonlinear case. Interestingly, despite the high degree of complexity and nonlinearity of most mammalian signaling networks, three distinct tumor necrosis factor (TNF) signaling network branches displayed linearly correlated responses, in both wild-type and perturbed versions of the network, across multiple orders of magnitude of ligand concentration. Using the noise mapping analysis, we find that the c-Jun N-terminal kinase (JNK) pathway generates higher noise than the NF-κB pathway, whereas the activation of c-Jun adds a greater amount of noise than the activation of ATF-2. In addition, we find that the A20 protein can suppress noise in the activation of ATF-2 by separately inhibiting the TNF receptor complex and JNK pathway through a negative feedback mechanism. These results, easily scalable to larger and more complex networks, pave the way toward assessing how noise propagates through cellular signaling pathways and create a foundation on which we can further investigate the relationship between signaling system architecture and biological noise. PMID:25404303

  15. The protist, Monosiga brevicollis, has a tyrosine kinase signaling network more elaborate and diverse than found in any known metazoan

    PubMed Central

    Manning, Gerard; Young, Susan L.; Miller, W. Todd; Zhai, Yufeng

    2008-01-01

    Tyrosine kinase signaling has long been considered a hallmark of intercellular communication, unique to multicellular animals. Our genomic analysis of the unicellular choanoflagellate Monosiga brevicollis discovers a remarkable count of 128 tyrosine kinases, 38 tyrosine phosphatases, and 123 phosphotyrosine (pTyr)-binding SH2 proteins, all higher counts than seen in any metazoan. This elaborate signaling network shows little orthology to metazoan counterparts yet displays many innovations reminiscent of metazoans. These include extracellular domains structurally related to those of metazoan receptor kinases, alternative methods for membrane anchoring and phosphotyrosine interaction in cytoplasmic kinases, and domain combinations that link kinases to small GTPase signaling and transcription. These proteins also display a wealth of combinations of known signaling domains. This uniquely divergent and elaborate signaling network illuminates the early evolution of pTyr signaling, explores innovative ways to traverse the cellular signaling circuitry, and shows extensive convergent evolution, highlighting pervasive constraints on pTyr signaling. PMID:18621719

  16. Dictyostelium uses ether-linked inositol phospholipids for intracellular signalling

    PubMed Central

    Clark, Jonathan; Kay, Robert R; Kielkowska, Anna; Niewczas, Izabella; Fets, Louise; Oxley, David; Stephens, Len R; Hawkins, Phillip T

    2014-01-01

    Inositol phospholipids are critical regulators of membrane biology throughout eukaryotes. The general principle by which they perform these roles is conserved across species and involves binding of differentially phosphorylated inositol head groups to specific protein domains. This interaction serves to both recruit and regulate the activity of several different classes of protein which act on membrane surfaces. In mammalian cells, these phosphorylated inositol head groups are predominantly borne by a C38:4 diacylglycerol backbone. We show here that the inositol phospholipids of Dictyostelium are different, being highly enriched in an unusual C34:1e lipid backbone, 1-hexadecyl-2-(11Z-octadecenoyl)-sn-glycero-3-phospho-(1'-myo-inositol), in which the sn-1 position contains an ether-linked C16:0 chain; they are thus plasmanylinositols. These plasmanylinositols respond acutely to stimulation of cells with chemoattractants, and their levels are regulated by PIPKs, PI3Ks and PTEN. In mammals and now in Dictyostelium, the hydrocarbon chains of inositol phospholipids are a highly selected subset of those available to other phospholipids, suggesting that different molecular selectors are at play in these organisms but serve a common, evolutionarily conserved purpose. PMID:25180230

  17. Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6

    PubMed Central

    Jebaseeli Samuelraj, Ananthi; Jayapal, Sundararajan

    2015-01-01

    Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point. PMID:26366431

  18. Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6.

    PubMed

    Samuelraj, Ananthi Jebaseeli; Jayapal, Sundararajan

    2015-01-01

    Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

  19. Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6.

    PubMed

    Samuelraj, Ananthi Jebaseeli; Jayapal, Sundararajan

    2015-01-01

    Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point. PMID:26366431

  20. Signaling for fast restoration in heterogeneous optical mesh networks

    NASA Astrophysics Data System (ADS)

    Rajagopalan, Bala; Saha, Debanjan; Bernstein, Greg; Sharma, Vishal

    2001-10-01

    With the advent of optical mesh networks, certain new protection schemes have been defined. This encompasses both local span and end-to-end path protection. But the implementations of these protection schemes have so far been based on proprietary mechanisms developed by each vendor. This has made it virtually impractical to construct a heterogeneous network with interoperable mesh protection schemes. Also, while the notion of a standard IP-centric control plane for optical networks based on Generalized Multi-Protocol Label Switching (GMPLS) has gained wide acceptance, the work in this area has so far focused exclusively on connection provisioning rather than restoration. This paper defines standard, IP-based signaling protocols for restoration in optical mesh networks. These protocols focus on a new local span protection mode and end-to-end shared protection. The main requirements on these protocols are simplicity and speed. The signaling mechanisms described in this paper are complimentary to the GMPLS provisioning mechanisms.

  1. Stable transmission of radio frequency signals on fiber links using interferomectric delay sensing

    SciTech Connect

    Wilcox, Russell B.; Byrd, J.M.; Doolittle, Lawrence; Huang, Gang; Staples, J.W.

    2009-07-29

    The authors demonstrate distribution of a 2850 MHz rf signal over stabilized optical fiber links. For a 2.2 km link they measure an rms drift of 19.4 fs over 60 h, and for a 200 m link an rms drift of 8.4 fs over 20 h. The rf signals are transmitted as amplitude modulation on a continuous optical carrier. Variations in the delay length are sensed using heterodyne interferometry and used to correct the rf phase. The system uses standard fiber telecommunications components.

  2. On the propagation of diel signals in river networks using analytic solutions of flow equations

    NASA Astrophysics Data System (ADS)

    Fonley, Morgan; Mantilla, Ricardo; Small, Scott J.; Curtu, Rodica

    2016-07-01

    Several authors have reported diel oscillations in streamflow records and have hypothesized that these oscillations are linked to evapotranspiration cycles in the watershed. The timing of oscillations in rivers, however, lags behind those of temperature and evapotranspiration in hillslopes. Two hypotheses have been put forth to explain the magnitude and timing of diel streamflow oscillations during low-flow conditions. The first suggests that delays between the peaks and troughs of streamflow and daily evapotranspiration are due to processes occurring in the soil as water moves toward the channels in the river network. The second posits that they are due to the propagation of the signal through the channels as water makes its way to the outlet of the basin. In this paper, we design and implement a theoretical model to test these hypotheses. We impose a baseflow signal entering the river network and use a linear transport equation to represent flow along the network. We develop analytic streamflow solutions for the case of uniform velocities in space over all river links. We then use our analytic solution to simulate streamflows along a self-similar river network for different flow velocities. Our results show that the amplitude and time delay of the streamflow solution are heavily influenced by transport in the river network. Moreover, our equations show that the geomorphology and topology of the river network play important roles in determining how amplitude and signal delay are reflected in streamflow signals. Finally, we have tested our theoretical formulation in the Dry Creek Experimental Watershed, where oscillations are clearly observed in streamflow records. We find that our solution produces streamflow values and fluctuations that are similar to those observed in the summer of 2011.

  3. Neuroplasticity Signaling Pathways Linked to the Pathophysiology of Schizophrenia

    PubMed Central

    Balu, Darrick T.; Coyle, Joseph T.

    2010-01-01

    Schizophrenia is a severe mental illness that afflicts nearly 1% of the world's population. One of the cardinal pathological features of schizophrenia is perturbation in synaptic connectivity. Although the etiology of schizophrenia is unknown, it appears to be a developmental disorder involving the interaction of a potentially large number of risk genes, with no one gene producing a strong effect except rare, highly penetrant copy number variants. The purpose of this review is to detail how putative schizophrenia risk genes (DISC-1, neuregulin/ErbB4, dysbindin, Akt1, BDNF, and NMDA receptor) are involved in regulating neuroplasticity and how alterations in their expression may contribute to the disconnectivity observed in schizophrenia. Moreover, this review highlights how many of these risk genes converge to regulate common neurotransmitter systems and signaling pathways. Future studies aimed at elucidating the functions of these risk genes will provide new insights into the pathophysiology of schizophrenia and will likely lead to the nomination of novel therapeutic targets for restoring proper synaptic connectivity in the brain in schizophrenia and related disorders. PMID:20951727

  4. CREB pathway links PGE2 signaling with macrophage polarization.

    PubMed

    Luan, Bing; Yoon, Young-Sil; Le Lay, John; Kaestner, Klaus H; Hedrick, Susan; Montminy, Marc

    2015-12-22

    Obesity is thought to promote insulin resistance in part via activation of the innate immune system. Increases in proinflammatory cytokine production by M1 macrophages inhibit insulin signaling in white adipose tissue. In contrast, M2 macrophages have been found to enhance insulin sensitivity in part by reducing adipose tissue inflammation. The paracrine hormone prostaglandin E2 (PGE2) enhances M2 polarization in part through activation of the cAMP pathway, although the underlying mechanism is unclear. Here we show that PGE2 stimulates M2 polarization via the cyclic AMP-responsive element binding (CREB)-mediated induction of Krupple-like factor 4 (KLF4). Targeted disruption of CREB or the cAMP-regulated transcriptional coactivators 2 and 3 (CRTC2/3) in macrophages down-regulated M2 marker gene expression and promoted insulin resistance in the context of high-fat diet feeding. As re-expression of KLF4 rescued M2 marker gene expression in CREB-depleted cells, our results demonstrate the importance of the CREB/CRTC pathway in maintaining insulin sensitivity in white adipose tissue via its effects on the innate immune system.

  5. CREB pathway links PGE2 signaling with macrophage polarization

    PubMed Central

    Luan, Bing; Yoon, Young-Sil; Le Lay, John; Kaestner, Klaus H.; Hedrick, Susan; Montminy, Marc

    2015-01-01

    Obesity is thought to promote insulin resistance in part via activation of the innate immune system. Increases in proinflammatory cytokine production by M1 macrophages inhibit insulin signaling in white adipose tissue. In contrast, M2 macrophages have been found to enhance insulin sensitivity in part by reducing adipose tissue inflammation. The paracrine hormone prostaglandin E2 (PGE2) enhances M2 polarization in part through activation of the cAMP pathway, although the underlying mechanism is unclear. Here we show that PGE2 stimulates M2 polarization via the cyclic AMP-responsive element binding (CREB)-mediated induction of Krupple-like factor 4 (KLF4). Targeted disruption of CREB or the cAMP-regulated transcriptional coactivators 2 and 3 (CRTC2/3) in macrophages down-regulated M2 marker gene expression and promoted insulin resistance in the context of high-fat diet feeding. As re-expression of KLF4 rescued M2 marker gene expression in CREB-depleted cells, our results demonstrate the importance of the CREB/CRTC pathway in maintaining insulin sensitivity in white adipose tissue via its effects on the innate immune system. PMID:26644581

  6. Structural link prediction based on ant colony approach in social networks

    NASA Astrophysics Data System (ADS)

    Sherkat, Ehsan; Rahgozar, Maseud; Asadpour, Masoud

    2015-02-01

    As the size and number of online social networks are increasing day by day, social network analysis has become a popular issue in many branches of science. The link prediction is one of the key rolling issues in the analysis of social network's evolution. As the size of social networks is increasing, the necessity for scalable link prediction algorithms is being felt more. The aim of this paper is to introduce a new unsupervised structural link prediction algorithm based on the ant colony approach. Recently, ant colony approach has been used for solving some graph problems. Different kinds of networks are used for testing the proposed approach. In some networks, the proposed scalable algorithm has the best result in comparison to other structural unsupervised link prediction algorithms. In order to evaluate the algorithm results, methods like the top- n precision, area under the Receiver Operating Characteristic (ROC) and Precision-Recall curves are carried out on real-world networks.

  7. Cellular Signaling Networks Function as Generalized Wiener-Kolmogorov Filters to Suppress Noise

    NASA Astrophysics Data System (ADS)

    Hinczewski, Michael; Thirumalai, D.

    2014-10-01

    Cellular signaling involves the transmission of environmental information through cascades of stochastic biochemical reactions, inevitably introducing noise that compromises signal fidelity. Each stage of the cascade often takes the form of a kinase-phosphatase push-pull network, a basic unit of signaling pathways whose malfunction is linked with a host of cancers. We show that this ubiquitous enzymatic network motif effectively behaves as a Wiener-Kolmogorov optimal noise filter. Using concepts from umbral calculus, we generalize the linear Wiener-Kolmogorov theory, originally introduced in the context of communication and control engineering, to take nonlinear signal transduction and discrete molecule populations into account. This allows us to derive rigorous constraints for efficient noise reduction in this biochemical system. Our mathematical formalism yields bounds on filter performance in cases important to cellular function—such as ultrasensitive response to stimuli. We highlight features of the system relevant for optimizing filter efficiency, encoded in a single, measurable, dimensionless parameter. Our theory, which describes noise control in a large class of signal transduction networks, is also useful both for the design of synthetic biochemical signaling pathways and the manipulation of pathways through experimental probes such as oscillatory input.

  8. The dynamic control of signal transduction networks in cancer cells.

    PubMed

    Kolch, Walter; Halasz, Melinda; Granovskaya, Marina; Kholodenko, Boris N

    2015-09-01

    Cancer is often considered a genetic disease. However, much of the enormous plasticity of cancer cells to evolve different phenotypes, to adapt to challenging microenvironments and to withstand therapeutic assaults is encoded by the structure and spatiotemporal dynamics of signal transduction networks. In this Review, we discuss recent concepts concerning how the rich signalling dynamics afforded by these networks are regulated and how they impinge on cancer cell proliferation, survival, invasiveness and drug resistance. Understanding this dynamic circuitry by mathematical modelling could pave the way to new therapeutic approaches and personalized treatments.

  9. Signal processing techniques for synchronization of wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Lee, Jaehan; Wu, Yik-Chung; Chaudhari, Qasim; Qaraqe, Khalid; Serpedin, Erchin

    2010-11-01

    Clock synchronization is a critical component in wireless sensor networks, as it provides a common time frame to different nodes. It supports functions such as fusing voice and video data from different sensor nodes, time-based channel sharing, and sleep wake-up scheduling, etc. Early studies on clock synchronization for wireless sensor networks mainly focus on protocol design. However, clock synchronization problem is inherently related to parameter estimation, and recently, studies of clock synchronization from the signal processing viewpoint started to emerge. In this article, a survey of latest advances on clock synchronization is provided by adopting a signal processing viewpoint. We demonstrate that many existing and intuitive clock synchronization protocols can be interpreted by common statistical signal processing methods. Furthermore, the use of advanced signal processing techniques for deriving optimal clock synchronization algorithms under challenging scenarios will be illustrated.

  10. Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

    PubMed Central

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

  11. Functional Divergence in the Role of N-Linked Glycosylation in Smoothened Signaling

    PubMed Central

    Marada, Suresh; Navarro, Gemma; Truong, Ashley; Stewart, Daniel P.; Arensdorf, Angela M.; Nachtergaele, Sigrid; Angelats, Edgar; Opferman, Joseph T.; Rohatgi, Rajat; McCormick, Peter J.; Ogden, Stacey K.

    2015-01-01

    The G protein-coupled receptor (GPCR) Smoothened (Smo) is the requisite signal transducer of the evolutionarily conserved Hedgehog (Hh) pathway. Although aspects of Smo signaling are conserved from Drosophila to vertebrates, significant differences have evolved. These include changes in its active sub-cellular localization, and the ability of vertebrate Smo to induce distinct G protein-dependent and independent signals in response to ligand. Whereas the canonical Smo signal to Gli transcriptional effectors occurs in a G protein-independent manner, its non-canonical signal employs Gαi. Whether vertebrate Smo can selectively bias its signal between these routes is not yet known. N-linked glycosylation is a post-translational modification that can influence GPCR trafficking, ligand responsiveness and signal output. Smo proteins in Drosophila and vertebrate systems harbor N-linked glycans, but their role in Smo signaling has not been established. Herein, we present a comprehensive analysis of Drosophila and murine Smo glycosylation that supports a functional divergence in the contribution of N-linked glycans to signaling. Of the seven predicted glycan acceptor sites in Drosophila Smo, one is essential. Loss of N-glycosylation at this site disrupted Smo trafficking and attenuated its signaling capability. In stark contrast, we found that all four predicted N-glycosylation sites on murine Smo were dispensable for proper trafficking, agonist binding and canonical signal induction. However, the under-glycosylated protein was compromised in its ability to induce a non-canonical signal through Gαi, providing for the first time evidence that Smo can bias its signal and that a post-translational modification can impact this process. As such, we postulate a profound shift in N-glycan function from affecting Smo ER exit in flies to influencing its signal output in mice. PMID:26291458

  12. VLSI Neural Networks Help To Compress Video Signals

    NASA Technical Reports Server (NTRS)

    Fang, Wai-Chi; Sheu, Bing J.

    1996-01-01

    Advanced analog/digital electronic system for compression of video signals incorporates artificial neural networks. Performs motion-estimation and image-data-compression processing. Effectively eliminates temporal and spatial redundancies of sequences of video images; processes video image data, retaining only nonredundant parts to be transmitted, then transmits resulting data stream in form of efficient code. Reduces bandwidth and storage requirements for transmission and recording of video signal.

  13. An artificial network model for estimating the network structure underlying partially observed neuronal signals.

    PubMed

    Komatsu, Misako; Namikawa, Jun; Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka; Nakamura, Kiyohiko; Tani, Jun

    2014-01-01

    Many previous studies have proposed methods for quantifying neuronal interactions. However, these methods evaluated the interactions between recorded signals in an isolated network. In this study, we present a novel approach for estimating interactions between observed neuronal signals by theorizing that those signals are observed from only a part of the network that also includes unobserved structures. We propose a variant of the recurrent network model that consists of both observable and unobservable units. The observable units represent recorded neuronal activity, and the unobservable units are introduced to represent activity from unobserved structures in the network. The network structures are characterized by connective weights, i.e., the interaction intensities between individual units, which are estimated from recorded signals. We applied this model to multi-channel brain signals recorded from monkeys, and obtained robust network structures with physiological relevance. Furthermore, the network exhibited common features that portrayed cortical dynamics as inversely correlated interactions between excitatory and inhibitory populations of neurons, which are consistent with the previous view of cortical local circuits. Our results suggest that the novel concept of incorporating an unobserved structure into network estimations has theoretical advantages and could provide insights into brain dynamics beyond what can be directly observed.

  14. Plant gravitropic signal transduction: A network analysis leads to gene discovery

    NASA Astrophysics Data System (ADS)

    Wyatt, Sarah

    Gravity plays a fundamental role in plant growth and development. Although a significant body of research has helped define the events of gravity perception, the role of the plant growth regulator auxin, and the mechanisms resulting in the gravity response, the events of signal transduction, those that link the biophysical action of perception to a biochemical signal that results in auxin redistribution, those that regulate the gravitropic effects on plant growth, remain, for the most part, a “black box.” Using a cold affect, dubbed the gravity persistent signal (GPS) response, we developed a mutant screen to specifically identify components of the signal transduction pathway. Cloning of the GPS genes have identified new proteins involved in gravitropic signaling. We have further exploited the GPS response using a multi-faceted approach including gene expression microarrays, proteomics analysis, and bioinformatics analysis and continued mutant analysis to identified additional genes, physiological and biochemical processes. Gene expression data provided the foundation of a regulatory network for gravitropic signaling. Based on these gene expression data and related data sets/information from the literature/repositories, we constructed a gravitropic signaling network for Arabidopsis inflorescence stems. To generate the network, both a dynamic Bayesian network approach and a time-lagged correlation coefficient approach were used. The dynamic Bayesian network added existing information of protein-protein interaction while the time-lagged correlation coefficient allowed incorporation of temporal regulation and thus could incorporate the time-course metric from the data set. Thus the methods complemented each other and provided us with a more comprehensive evaluation of connections. Each method generated a list of possible interactions associated with a statistical significance value. The two networks were then overlaid to generate a more rigorous, intersected

  15. Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model

    PubMed Central

    Minoarivelo, H. O.; Hui, C.; Terblanche, J. S.; Pond, S. L. Kosakovsky; Scheffler, K.

    2014-01-01

    Ecological interaction networks, such as those describing the mutualistic interactions between plants and their pollinators or between plants and their frugivores, exhibit non-random structural properties that cannot be explained by simple models of network formation. One factor affecting the formation and eventual structure of such a network is its evolutionary history. We argue that this, in many cases, is closely linked to the evolutionary histories of the species involved in the interactions. Indeed, empirical studies of interaction networks along with the phylogenies of the interacting species have demonstrated significant associations between phylogeny and network structure. To date, however, no generative model explaining the way in which the evolution of individual species affects the evolution of interaction networks has been proposed. We present a model describing the evolution of pairwise interactions as a branching Markov process, drawing on phylogenetic models of molecular evolution. Using knowledge of the phylogenies of the interacting species, our model yielded a significantly better fit to 21% of a set of plant – pollinator and plant – frugivore mutualistic networks. This highlights the importance, in a substantial minority of cases, of inheritance of interaction patterns without excluding the potential role of ecological novelties in forming the current network architecture. We suggest that our model can be used as a null model for controlling evolutionary signals when evaluating the role of other factors in shaping the emergence of ecological networks. PMID:25294947

  16. Ultrasensitive response motifs: basic amplifiers in molecular signalling networks

    PubMed Central

    Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E.

    2013-01-01

    Multi-component signal transduction pathways and gene regulatory circuits underpin integrated cellular responses to perturbations. A recurring set of network motifs serve as the basic building blocks of these molecular signalling networks. This review focuses on ultrasensitive response motifs (URMs) that amplify small percentage changes in the input signal into larger percentage changes in the output response. URMs generally possess a sigmoid input–output relationship that is steeper than the Michaelis–Menten type of response and is often approximated by the Hill function. Six types of URMs can be commonly found in intracellular molecular networks and each has a distinct kinetic mechanism for signal amplification. These URMs are: (i) positive cooperative binding, (ii) homo-multimerization, (iii) multistep signalling, (iv) molecular titration, (v) zero-order covalent modification cycle and (vi) positive feedback. Multiple URMs can be combined to generate highly switch-like responses. Serving as basic signal amplifiers, these URMs are essential for molecular circuits to produce complex nonlinear dynamics, including multistability, robust adaptation and oscillation. These dynamic properties are in turn responsible for higher-level cellular behaviours, such as cell fate determination, homeostasis and biological rhythm. PMID:23615029

  17. Full-duplex radio over fiber link with colorless source-free base station based on single sideband optical mm-wave signal with polarization rotated optical carrier

    NASA Astrophysics Data System (ADS)

    Ma, Jianxin

    2016-07-01

    A full-duplex radio-over fiber (RoF) link scheme based on single sideband (SSB) optical millimeter (mm)-wave signal with polarization-rotated optical carrier is proposed to realize the source-free colorless base station (BS), in which a polarization beam splitter (PBS) is used to abstract part of the optical carrier for conveying the uplink data. Since the optical carrier for the uplink does not bear the downlink signal, no cross-talk from the downlink contaminates the uplink signal. The simulation results demonstrate that both down- and up-links maintain good performance. The mm-wave signal distribution network based on the proposed full duplex fiber link scheme can use the uniform source-free colorless BSs, which makes the access system very simpler.

  18. Efficient network disintegration under incomplete information: the comic effect of link prediction

    NASA Astrophysics Data System (ADS)

    Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

    2016-03-01

    The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the “comic effect” of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized.

  19. Efficient network disintegration under incomplete information: the comic effect of link prediction

    PubMed Central

    Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

    2016-01-01

    The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the “comic effect” of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized. PMID:26960247

  20. Efficient network disintegration under incomplete information: the comic effect of link prediction.

    PubMed

    Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

    2016-03-10

    The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the "comic effect" of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized.

  1. Efficient network disintegration under incomplete information: the comic effect of link prediction.

    PubMed

    Tan, Suo-Yi; Wu, Jun; Lü, Linyuan; Li, Meng-Jun; Lu, Xin

    2016-01-01

    The study of network disintegration has attracted much attention due to its wide applications, including suppressing the epidemic spreading, destabilizing terrorist network, preventing financial contagion, controlling the rumor diffusion and perturbing cancer networks. The crux of this matter is to find the critical nodes whose removal will lead to network collapse. This paper studies the disintegration of networks with incomplete link information. An effective method is proposed to find the critical nodes by the assistance of link prediction techniques. Extensive experiments in both synthetic and real networks suggest that, by using link prediction method to recover partial missing links in advance, the method can largely improve the network disintegration performance. Besides, to our surprise, we find that when the size of missing information is relatively small, our method even outperforms than the results based on complete information. We refer to this phenomenon as the "comic effect" of link prediction, which means that the network is reshaped through the addition of some links that identified by link prediction algorithms, and the reshaped network is like an exaggerated but characteristic comic of the original one, where the important parts are emphasized. PMID:26960247

  2. A Noise-Filtering Method for Link Prediction in Complex Networks

    PubMed Central

    Ouyang, Bo

    2016-01-01

    Link prediction plays an important role in both finding missing links in networked systems and complementing our understanding of the evolution of networks. Much attention from the network science community are paid to figure out how to efficiently predict the missing/future links based on the observed topology. Real-world information always contain noise, which is also the case in an observed network. This problem is rarely considered in existing methods. In this paper, we treat the existence of observed links as known information. By filtering out noises in this information, the underlying regularity of the connection information is retrieved and then used to predict missing or future links. Experiments on various empirical networks show that our method performs noticeably better than baseline algorithms. PMID:26788737

  3. Subsurface Event Detection and Classification Using Wireless Signal Networks

    PubMed Central

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T.

    2012-01-01

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

  4. Subsurface event detection and classification using Wireless Signal Networks.

    PubMed

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

    2012-01-01

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events. PMID:23202191

  5. Neural network approach to classification of infrasound signals

    NASA Astrophysics Data System (ADS)

    Lee, Dong-Chang

    As part of the International Monitoring Systems of the Preparatory Commissions for the Comprehensive Nuclear Test-Ban Treaty Organization, the Infrasound Group at the University of Alaska Fairbanks maintains and operates two infrasound stations to monitor global nuclear activity. In addition, the group specializes in detecting and classifying the man-made and naturally produced signals recorded at both stations by computing various characterization parameters (e.g. mean of the cross correlation maxima, trace velocity, direction of arrival, and planarity values) using the in-house developed weighted least-squares algorithm. Classifying commonly observed low-frequency (0.015--0.1 Hz) signals at out stations, namely mountain associated waves and high trace-velocity signals, using traditional approach (e.g. analysis of power spectral density) presents a problem. Such signals can be separated statistically by setting a window to the trace-velocity estimate for each signal types, and the feasibility of such technique is demonstrated by displaying and comparing various summary plots (e.g. universal, seasonal and azimuthal variations) produced by analyzing infrasound data (2004--2007) from the Fairbanks and Antarctic arrays. Such plots with the availability of magnetic activity information (from the College International Geophysical Observatory located at Fairbanks, Alaska) leads to possible physical sources of the two signal types. Throughout this thesis a newly developed robust algorithm (sum of squares of variance ratios) with improved detection quality (under low signal to noise ratios) over two well-known detection algorithms (mean of the cross correlation maxima and Fisher Statistics) are investigated for its efficacy as a new detector. A neural network is examined for its ability to automatically classify the two signals described above against clutter (spurious signals with common characteristics). Four identical perceptron networks are trained and validated (with

  6. Robust allocation of weighted dependency links in cyber-physical networks

    NASA Astrophysics Data System (ADS)

    Li, Xin; Wu, Haotian; Scoglio, Caterina; Gruenbacher, Don

    2015-09-01

    Interdependent network models are often used to show how one network has an effect on another network through dependencies. In this paper, we propose a novel interdependent network model which consists of two individual networks with unequal numbers of nodes and one-to-multiple weighted dependency links between the two networks. Based on realistic assumptions, this model differs from previous works that considered equal numbers of nodes in the two networks and identical dependency links. We formulate an optimization problem to allocate dependency links using least resources. This novel model enhances the practicability of traditional cyber-physical system structures, but it makes the dependency link deployment problem more complex and the optimization problem cannot be solved in large networks. To overcome this problem, we propose a new algorithm based on a revised network flow method. Extensive simulations on random networks and real networks show that our deployment method produces topologies that are more robust than the ones obtained by other deployment techniques. Results indicate that our algorithm is efficient and cost-effective in designing robust interdependent networks, and our deployment method is suitable for networks of any size.

  7. Disentangling biological signaling networks by dynamic coupling of signaling lipids to modifying enzymes.

    PubMed

    Blind, Raymond D

    2014-01-01

    An unresolved problem in biological signal transduction is how particular branches of highly interconnected signaling networks can be decoupled, allowing activation of specific circuits within complex signaling architectures. Although signaling dynamics and spatiotemporal mechanisms serve critical roles, it remains unclear if these are the only ways cells achieve specificity within networks. The transcription factor Steroidogenic Factor-1 (SF-1) is an excellent model to address this question, as it forms dynamic complexes with several chemically distinct lipid species (phosphatidylinositols, phosphatidylcholines and sphingolipids). This property is important since lipids bound to SF-1 are modified by lipid signaling enzymes (IPMK & PTEN), regulating SF-1 biological activity in gene expression. Thus, a particular SF-1/lipid complex can interface with a lipid signaling enzyme only if SF-1 has been loaded with a chemically compatible lipid substrate. This mechanism permits dynamic downstream responsiveness to constant upstream input, disentangling specific pathways from the full network. The potential of this paradigm to apply generally to nuclear lipid signaling is discussed, with particular attention given to the nuclear receptor superfamily of transcription factors and their phospholipid ligands.

  8. SSL: Signal Similarity-Based Localization for Ocean Sensor Networks

    PubMed Central

    Chen, Pengpeng; Ma, Honglu; Gao, Shouwan; Huang, Yan

    2015-01-01

    Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes’ positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes’ positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes’ relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks. PMID:26610520

  9. Effects of link-orientation methods on robustness against cascading failures in complex networks

    NASA Astrophysics Data System (ADS)

    Jiang, Zhong-Yuan; Ma, Jian-Feng; Shen, Yu-Long; Zeng, Yong

    2016-09-01

    Unidirectional and bidirectional links may coexist in many realistic networked complex systems such as the city transportation networks. Even more, for some considerations, several bidirectional links are shifted to unidirectional ones. Many link-orientation strategies might be employed, including High-to-Low, Low-to-High and Random direction-determining methods, abbreviated as HTLDD, LTHDD and RDD respectively. Traffic passing through a unidirectional link is restricted to one-side direction. In real complex systems, nodes are correlated with each other. The failure from an initial node may be propagated iteratively, resulting in a large scale of failures of other nodes, called cascade phenomenon which may damage the safety or security of the networked system. Assuming that traffic load on any failed node can be redistributed to its non-failed neighbors, in this work, we try to reveal the effects of unidirectional links on network robustness against cascades. Extensive simulations have been implemented on kinds of networks including Scale-Free networks, Small-World networks, and Erdös-Rényi random networks. The results showed that all of the above three direction-determining methods decrease the robustness of the original networks against cascading failure. This work can help network designers and managers understand the robustness of network well and efficiently prevent the safety events.

  10. Planarian Hh signaling regulates regeneration polarity and links Hh pathway evolution to cilia

    PubMed Central

    Rink, Jochen C.; Gurley, Kyle A.; Elliott, Sarah A.; Alvarado, Alejandro Sánchez

    2010-01-01

    The Hedgehog (Hh) signaling pathway plays multiple essential roles during metazoan development, homeostasis, and disease. Although core protein components are highly conserved, the variations in Hh signal transduction mechanisms exhibited by existing model systems (Drosophila, fish, and mammals) are difficult to understand. We characterize the Hh pathway in planarians. Hh signaling is essential for establishing the Anterior/Posterior axis during regeneration by modulating wnt expression. Moreover, RNAi methods to reduce signal transduction proteins Cos2/Kif27/Kif7, Fused, or Iguana do not result in detectable Hh signaling defects; however, these proteins are essential for planarian ciliogenesis. Our study expands the understanding of Hh signaling in the animal kingdom and suggests an ancestral mechanistic link between Hh signaling and the function of cilia. PMID:19933103

  11. Multiplexed Signal Distribution Using Fiber Network For Radar Applications

    NASA Astrophysics Data System (ADS)

    Meena, D.; Prakasam, L. G. M.; Pandey, D. C.; Shivaleela, E. S.; Srinivas, T.

    2011-10-01

    Most of the modern Active phased Array Radars consist of multiple receive modules in an Antenna array. This demands the distribution of various Local Oscillator Signals (LOs) for the down conversion of received signals to the Intermediate Frequency (IF) band signals. This is normally achieved through Radio Frequency (RF) cables with Complex distribution networks which adds additional weight to the Arrays. Similarly these kinds of receivers require Control/Clock signals which are digital in nature, for the synchronization of all receive modules of the radar system which are also distributed through electrical cables. In addition some of the control messages (Digital in nature) are distributed through Optical interfaces. During Transmit operation, the RF transmit Signal is also distributed through the same receiver modules which will in turn distribute to all the elements of the Array which require RF cables which are bulky in nature. So it is very essential to have a multiplexed Signal distribution scheme through the existing Optical Interface for distribution of these signals which are RF and Digital in nature. This paper discusses about various distribution schemes for the realization in detail. We propose a distribution network architecture where existing fibers can be further extended for the distribution of other types of signals also. In addition, it also briefs about a comparative analysis done on these schemes by considering the complexity and space constraint factors. Thus we bring out an optimum scheme which will lead to the reduction in both hardware complexity and weight of the array systems. In addition, being an Optical network it is free from Electromagnetic interference which is a crucial requirement in an array environment.

  12. Reverse engineering GTPase programming languages with reconstituted signaling networks.

    PubMed

    Coyle, Scott M

    2016-07-01

    The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems. PMID:27128855

  13. Reverse engineering GTPase programming languages with reconstituted signaling networks.

    PubMed

    Coyle, Scott M

    2016-07-01

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

  14. Fragmentation transition in a coevolving network with link-state dynamics.

    PubMed

    Carro, A; Vazquez, F; Toral, R; San Miguel, M

    2014-06-01

    We study a network model that couples the dynamics of link states with the evolution of the network topology. The state of each link, either A or B, is updated according to the majority rule or zero-temperature Glauber dynamics, in which links adopt the state of the majority of their neighboring links in the network. Additionally, a link that is in a local minority is rewired to a randomly chosen node. While large systems evolving under the majority rule alone always fall into disordered topological traps composed by frustrated links, any amount of rewiring is able to drive the network to complete order, by relinking frustrated links and so releasing the system from traps. However, depending on the relative rate of the majority rule and the rewiring processes, the system evolves towards different ordered absorbing configurations: either a one-component network with all links in the same state or a network fragmented in two components with opposite states. For low rewiring rates and finite-size networks there is a domain of bistability between fragmented and nonfragmented final states. Finite-size scaling indicates that fragmentation is the only possible scenario for large systems and any nonzero rate of rewiring.

  15. Topic Models for Link Prediction in Document Networks

    ERIC Educational Resources Information Center

    Kataria, Saurabh

    2012-01-01

    Recent explosive growth of interconnected document collections such as citation networks, network of web pages, content generated by crowd-sourcing in collaborative environments, etc., has posed several challenging problems for data mining and machine learning community. One central problem in the domain of document networks is that of "link…

  16. Teaming Up: Linking Collaboration Networks, Collective Efficacy, and Student Achievement

    ERIC Educational Resources Information Center

    Moolenaar, Nienke M.; Sleegers, Peter J. C.; Daly, Alan J.

    2012-01-01

    Improving student achievement through teacher collaboration networks is a current focus of schools in many countries. Yet, empirical evidence on the relationship between teacher networks and student achievement and mechanisms that may explain this relationship is limited. This study examined the relationship between teacher networks and student…

  17. The statistical mechanics of complex signaling networks: nerve growth factor signaling

    NASA Astrophysics Data System (ADS)

    Brown, K. S.; Hill, C. C.; Calero, G. A.; Myers, C. R.; Lee, K. H.; Sethna, J. P.; Cerione, R. A.

    2004-10-01

    The inherent complexity of cellular signaling networks and their importance to a wide range of cellular functions necessitates the development of modeling methods that can be applied toward making predictions and highlighting the appropriate experiments to test our understanding of how these systems are designed and function. We use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. A key difficulty with signaling models is that, while significant effort is being made to experimentally measure the rate constants for individual steps in these networks, many of the parameters required to describe their behavior remain unknown or at best represent estimates. To establish the usefulness of our approach, we have applied our methods toward modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. In particular, we study the actions of NGF and mitogenic epidermal growth factor (EGF) in rat pheochromocytoma (PC12) cells. Through a network of intermediate signaling proteins, each of these growth factors stimulates extracellular regulated kinase (Erk) phosphorylation with distinct dynamical profiles. Using our modeling approach, we are able to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems that we call 'sloppiness.'

  18. Reducing the Spectral Radius of a Torus Network by Link Removal

    PubMed Central

    Yang, Xiaofan; Li, Pengdeng; Yang, Lu-Xing; Wu, Yingbo

    2016-01-01

    The optimal link removal (OLR) problem aims at removing a given number of links of a network so that the spectral radius of the residue network obtained by removing the links from the network attains the minimum. Torus networks are a class of regular networks that have witnessed widespread applications. This paper addresses three subproblems of the OLR problem for torus networks, where two or three or four edges are removed. For either of the three subproblems, a link-removing scheme is described. Exhaustive searches show that, for small-sized tori, each of the proposed schemes produces an optimal solution to the corresponding subproblem. Monte-Carlo simulations demonstrate that, for medium-sized tori, each of the three schemes produces a solution to the corresponding subproblem, which is optimal when compared to a large set of randomly produced link-removing schemes. Consequently, it is speculated that each of the three schemes produces an optimal solution to the corresponding subproblem for all torus networks. The set of links produced by each of our schemes is evenly distributed over a network, which may be a common feature of an optimal solution to the OLR problem for regular networks. PMID:27171372

  19. NASA 60 GHz intersatellite communication link definition study. Addendum A: Mixed baseband and IF signals

    NASA Technical Reports Server (NTRS)

    1986-01-01

    As part of a definition study for a 60 GHz intersatellite communications link system (ICLS), baseline design concepts for a channelized crosslink were identified. The crosslink would allow communications between geostationary satellites of the planned Tracking and Data Acquisition System (TDAS) and would accommodate a mixture of frequency translation coherent links (bent pipe links) and baseband-in/baseband-out links (mod/demod links). A 60 GHz communication system was developed for sizing and analyzing the crosslink. For the coherent links this system translates incoming signals directly up to the 60 GHz band; trunks the signals across from one satellite to a second satellite at 60 GHz then down converts to the proper frequency for re-transmission from the second satellite without converting to any intermediate frequencies. For the baseband-in/baseband-out links the baseband data is modulated on to the 60 GHz carrier at the transmitting satellite and demodulated at the receiving satellite. The frequency plan, equipment diagrams, and link calculations are presented along with results from sizing and reliability analyses.

  20. Signaling pathway networks mined from human pituitary adenoma proteomics data

    PubMed Central

    2010-01-01

    Background We obtained a series of pituitary adenoma proteomic expression data, including protein-mapping data (111 proteins), comparative proteomic data (56 differentially expressed proteins), and nitroproteomic data (17 nitroproteins). There is a pressing need to clarify the significant signaling pathway networks that derive from those proteins in order to clarify and to better understand the molecular basis of pituitary adenoma pathogenesis and to discover biomarkers. Here, we describe the significant signaling pathway networks that were mined from human pituitary adenoma proteomic data with the Ingenuity pathway analysis system. Methods The Ingenuity pathway analysis system was used to analyze signal pathway networks and canonical pathways from protein-mapping data, comparative proteomic data, adenoma nitroproteomic data, and control nitroproteomic data. A Fisher's exact test was used to test the statistical significance with a significance level of 0.05. Statistical significant results were rationalized within the pituitary adenoma biological system with literature-based bioinformatics analyses. Results For the protein-mapping data, the top pathway networks were related to cancer, cell death, and lipid metabolism; the top canonical toxicity pathways included acute-phase response, oxidative-stress response, oxidative stress, and cell-cycle G2/M transition regulation. For the comparative proteomic data, top pathway networks were related to cancer, endocrine system development and function, and lipid metabolism; the top canonical toxicity pathways included mitochondrial dysfunction, oxidative phosphorylation, oxidative-stress response, and ERK/MAPK signaling. The nitroproteomic data from a pituitary adenoma were related to cancer, cell death, lipid metabolism, and reproductive system disease, and the top canonical toxicity pathways mainly related to p38 MAPK signaling and cell-cycle G2/M transition regulation. Nitroproteins from a pituitary control related to

  1. EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT

    PubMed Central

    Choudhary, Kumari Sonal; Rohatgi, Neha; Briem, Eirikur; Gudjonsson, Thorarinn; Gudmundsson, Steinn; Rolfsson, Ottar

    2016-01-01

    Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend. PMID:27253373

  2. Collective signaling behavior in a networked-oscillator model

    NASA Astrophysics Data System (ADS)

    Liu, Z.-H.; Hui, P. M.

    2007-09-01

    We propose and study the collective behavior of a model of networked signaling objects that incorporates several ingredients of real-life systems. These ingredients include spatial inhomogeneity with grouping of signaling objects, signal attenuation with distance, and delayed and impulsive coupling between non-identical signaling objects. Depending on the coupling strength and/or time-delay effect, the model exhibits completely, partially, and locally collective signaling behavior. In particular, a correlated signaling (CS) behavior is observed in which there exist time durations when nearly a constant fraction of oscillators in the system are in the signaling state. These time durations are much longer than the duration of a spike when a single oscillator signals, and they are separated by regular intervals in which nearly all oscillators are silent. Such CS behavior is similar to that observed in biological systems such as fireflies, cicadas, crickets, and frogs. The robustness of the CS behavior against noise is also studied. It is found that properly adjusting the coupling strength and noise level could enhance the correlated behavior.

  3. Efficient Sparse Signal Transmission over a Lossy Link Using Compressive Sensing

    PubMed Central

    Wu, Liantao; Yu, Kai; Cao, Dongyu; Hu, Yuhen; Wang, Zhi

    2015-01-01

    Reliable data transmission over lossy communication link is expensive due to overheads for error protection. For signals that have inherent sparse structures, compressive sensing (CS) is applied to facilitate efficient sparse signal transmissions over lossy communication links without data compression or error protection. The natural packet loss in the lossy link is modeled as a random sampling process of the transmitted data, and the original signal will be reconstructed from the lossy transmission results using the CS-based reconstruction method at the receiving end. The impacts of packet lengths on transmission efficiency under different channel conditions have been discussed, and interleaving is incorporated to mitigate the impact of burst data loss. Extensive simulations and experiments have been conducted and compared to the traditional automatic repeat request (ARQ) interpolation technique, and very favorable results have been observed in terms of both accuracy of the reconstructed signals and the transmission energy consumption. Furthermore, the packet length effect provides useful insights for using compressed sensing for efficient sparse signal transmission via lossy links. PMID:26287195

  4. Efficient Sparse Signal Transmission over a Lossy Link Using Compressive Sensing.

    PubMed

    Wu, Liantao; Yu, Kai; Cao, Dongyu; Hu, Yuhen; Wang, Zhi

    2015-08-13

    Reliable data transmission over lossy communication link is expensive due to overheads for error protection. For signals that have inherent sparse structures, compressive sensing (CS) is applied to facilitate efficient sparse signal transmissions over lossy communication links without data compression or error protection. The natural packet loss in the lossy link is modeled as a random sampling process of the transmitted data, and the original signal will be reconstructed from the lossy transmission results using the CS-based reconstruction method at the receiving end. The impacts of packet lengths on transmission efficiency under different channel conditions have been discussed, and interleaving is incorporated to mitigate the impact of burst data loss. Extensive simulations and experiments have been conducted and compared to the traditional automatic repeat request (ARQ) interpolation technique, and very favorable results have been observed in terms of both accuracy of the reconstructed signals and the transmission energy consumption. Furthermore, the packet length effect provides useful insights for using compressed sensing for efficient sparse signal transmission via lossy links.

  5. Studies on characterizing the transmission of RF signals over a turbulent FSO link.

    PubMed

    Dat, Pham Tien; Bekkali, Abdemoula; Kazaura, Kamugisha; Wakamori, Kazuhiko; Suzuki, Toshiji; Matsumoto, Mitsuji; Higashino, Takeshi; Tsukamoto, Katsutoshi; Komaki, Shozo

    2009-05-11

    In this paper, we present an experimental study on transmission of RF signals over turbulent free-space optics (FSO) channel by using off-the-shelf Radio Frequency - FSO (RF-FSO) antennas. The results demonstrate potential of utilizing FSO links for transmission of RF signals and are used as a guideline in the design, prediction and evaluation of an advanced Dense Wavelength Division Multiplexing (DWDM) RoFSO system we are developing capable of transmitting multiple RF signals. An analytical modeling of the system is also conducted to identify key parameters in evaluating the performance of RF signal transmission using FSO links. The results confirm that the effect of scintillation on RF-FSO system performance can be estimated by using a simple estimation equation and satisfactory result are obtained from comparing the experimental and theoretical derived data under weak to strong turbulence condition.

  6. Signal Processing in Periodically Forced Gradient Frequency Neural Networks

    PubMed Central

    Kim, Ji Chul; Large, Edward W.

    2015-01-01

    Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

  7. Nonlinear signal processing using neural networks: Prediction and system modelling

    SciTech Connect

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  8. Signal Processing in Periodically Forced Gradient Frequency Neural Networks.

    PubMed

    Kim, Ji Chul; Large, Edward W

    2015-01-01

    Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing.

  9. Link prediction based on hyperbolic mapping with community structure for complex networks

    NASA Astrophysics Data System (ADS)

    Wang, Zuxi; Wu, Yao; Li, Qingguang; Jin, Fengdong; Xiong, Wei

    2016-05-01

    Link prediction is becoming a concerned topic in the complex network field in recent years. However, the existing link prediction methods are unsatisfactory for processing topological information and have high time complexity. This paper presents a novel method of Link Prediction with Community Structure (LPCS) based on hyperbolic mapping. Different from the existing link prediction methods, to utilize global structure information of the network, LPCS deals with the network from an overall perspective. LPCS takes full advantage of the community structure and its hierarchical organization to map networks into hyperbolic space, and obtains the hyperbolic coordinates which depict the global structure information of the network, then uses hyperbolic distance to describe the similarity between the nodes, finally predicts missing links according to the degree of the similarity between unconnected node pairs. The combination of the hyperbolic geometry framework and the community structure makes LPCS perform well in predicting missing links, and the time complexity of LPCS is linear, which makes LPCS can be applied to handle large scale networks in acceptable time. LPCS outperforms many state-of-the-art link prediction methods in the networks obeying power-law degree distribution.

  10. On-Board Fiber-Optic Network Architectures for Radar and Avionics Signal Distribution

    NASA Technical Reports Server (NTRS)

    Alam, Mohammad F.; Atiquzzaman, Mohammed; Duncan, Bradley B.; Nguyen, Hung; Kunath, Richard

    2000-01-01

    Continued progress in both civil and military avionics applications is overstressing the capabilities of existing radio-frequency (RF) communication networks based on coaxial cables on board modem aircrafts. Future avionics systems will require high-bandwidth on- board communication links that are lightweight, immune to electromagnetic interference, and highly reliable. Fiber optic communication technology can meet all these challenges in a cost-effective manner. Recently, digital fiber-optic communication systems, where a fiber-optic network acts like a local area network (LAN) for digital data communications, have become a topic of extensive research and development. Although a fiber-optic system can be designed to transport radio-frequency (RF) signals, the digital fiber-optic systems under development today are not capable of transporting microwave and millimeter-wave RF signals used in radar and avionics systems on board an aircraft. Recent advances in fiber optic technology, especially wavelength division multiplexing (WDM), has opened a number of possibilities for designing on-board fiber optic networks, including all-optical networks for radar and avionics RF signal distribution. In this paper, we investigate a number of different novel approaches for fiber-optic transmission of on-board VHF and UHF RF signals using commercial off-the-shelf (COTS) components. The relative merits and demerits of each architecture are discussed, and the suitability of each architecture for particular applications is pointed out. All-optical approaches show better performance than other traditional approaches in terms of signal-to-noise ratio, power consumption, and weight requirements.

  11. Oma1 Links Mitochondrial Protein Quality Control and TOR Signaling To Modulate Physiological Plasticity and Cellular Stress Responses.

    PubMed

    Bohovych, Iryna; Kastora, Stavroula; Christianson, Sara; Topil, Danelle; Kim, Heejeong; Fangman, Teresa; Zhou, You J; Barrientos, Antoni; Lee, Jaekwon; Brown, Alistair J P; Khalimonchuk, Oleh

    2016-09-01

    A network of conserved proteases known as the intramitochondrial quality control (IMQC) system is central to mitochondrial protein homeostasis and cellular health. IMQC proteases also appear to participate in establishment of signaling cues for mitochondrion-to-nucleus communication. However, little is known about this process. Here, we show that in Saccharomyces cerevisiae, inactivation of the membrane-bound IMQC protease Oma1 interferes with oxidative-stress responses through enhanced production of reactive oxygen species (ROS) during logarithmic growth and reduced stress signaling via the TORC1-Rim15-Msn2/Msn4 axis. Pharmacological or genetic prevention of ROS accumulation in Oma1-deficient cells restores this defective TOR signaling. Additionally, inactivation of the Oma1 ortholog in the human fungal pathogen Candida albicans also alters TOR signaling and, unexpectedly, leads to increased resistance to neutrophil killing and virulence in the invertebrate animal model Galleria mellonella Our findings reveal a novel and evolutionarily conserved link between IMQC and TOR-mediated signaling that regulates physiological plasticity and pancellular oxidative-stress responses. PMID:27325672

  12. Oma1 Links Mitochondrial Protein Quality Control and TOR Signaling To Modulate Physiological Plasticity and Cellular Stress Responses.

    PubMed

    Bohovych, Iryna; Kastora, Stavroula; Christianson, Sara; Topil, Danelle; Kim, Heejeong; Fangman, Teresa; Zhou, You J; Barrientos, Antoni; Lee, Jaekwon; Brown, Alistair J P; Khalimonchuk, Oleh

    2016-09-01

    A network of conserved proteases known as the intramitochondrial quality control (IMQC) system is central to mitochondrial protein homeostasis and cellular health. IMQC proteases also appear to participate in establishment of signaling cues for mitochondrion-to-nucleus communication. However, little is known about this process. Here, we show that in Saccharomyces cerevisiae, inactivation of the membrane-bound IMQC protease Oma1 interferes with oxidative-stress responses through enhanced production of reactive oxygen species (ROS) during logarithmic growth and reduced stress signaling via the TORC1-Rim15-Msn2/Msn4 axis. Pharmacological or genetic prevention of ROS accumulation in Oma1-deficient cells restores this defective TOR signaling. Additionally, inactivation of the Oma1 ortholog in the human fungal pathogen Candida albicans also alters TOR signaling and, unexpectedly, leads to increased resistance to neutrophil killing and virulence in the invertebrate animal model Galleria mellonella Our findings reveal a novel and evolutionarily conserved link between IMQC and TOR-mediated signaling that regulates physiological plasticity and pancellular oxidative-stress responses.

  13. The vulnerability of the global container shipping network to targeted link disruption

    NASA Astrophysics Data System (ADS)

    Viljoen, Nadia M.; Joubert, Johan W.

    2016-11-01

    Using complex network theory to describe the relational geography of maritime networks has provided great insights regarding their hierarchy and evolution over the past two decades. Unlike applications in other transport fields, notably air transport, complex network theory has had limited application in studying the vulnerability of maritime networks. This study uses targeted link disruption to investigate the strategy specific vulnerability of the network. Although nodal infrastructure such as ports can render a network vulnerable as a result of labour strikes, trade embargoes or natural disasters, it is the shipping lines connecting the ports that are more probably disrupted, either from within the industry, or outside. In this paper, we apply and evaluate two link-based disruption strategies on the global container shipping network, one based on link betweenness, and the other on link salience, to emulate the impact of large-scale service reconfiguration affecting priority links. The results show that the network is by and large robust to such reconfiguration. Meanwhile the flexibility of the network is reduced by both strategies, but to a greater degree by betweenness, resulting in a reduction of transshipment and dynamic rerouting potential amongst the busiest port regions. The results further show that the salience strategy is highly effective in reducing the commonality of shortest path sets, thereby diminishing opportunities for freight consolidation and scale economies.

  14. Effects of iterative learning based signal control strategies on macroscopic fundamental diagrams of urban road networks

    NASA Astrophysics Data System (ADS)

    Yan, Fei; Tian, Fuli; Shi, Zhongke

    2016-10-01

    Urban traffic flows are inherently repeated on a daily or weekly basis. This repeatability can help improve the traffic conditions if it is used properly by the control system. In this paper, we propose a novel iterative learning control (ILC) strategy for traffic signals of urban road networks using the repeatability feature of traffic flow. To improve the control robustness, the ILC strategy is further integrated with an error feedback control law in a complementary manner. Theoretical analysis indicates that the ILC-based traffic signal control methods can guarantee the asymptotic learning convergence, despite the presence of modeling uncertainties and exogenous disturbances. Finally, the impacts of the ILC-based signal control strategies on the network macroscopic fundamental diagram (MFD) are examined. The results show that the proposed ILC-based control strategies can homogenously distribute the network accumulation by controlling the vehicle numbers in each link to the desired levels under different traffic demands, which can result in the network with high capacity and mobility.

  15. From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

    NASA Astrophysics Data System (ADS)

    Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

    2016-03-01

    The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

  16. From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

    PubMed Central

    Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

    2016-01-01

    The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

  17. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

    Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks (WESNs), with an emphasis on distributed signal processing aspects. A WESN is conceived as a modular neuromonitoring platform for high-density EEG recordings, in which each node is equipped with an electrode array, a signal processing unit, and facilities for wireless communication. We first address the advantages of such a modular approach, and we explain how distributed signal processing algorithms make WESNs more power-efficient, in particular by avoiding data centralization. We provide an overview of distributed signal processing algorithms that are potentially applicable in WESNs, and for illustration purposes, we also provide a more detailed case study of a distributed eye blink artifact removal algorithm. Finally, we study the power efficiency of these distributed algorithms in comparison to their centralized counterparts in which all the raw sensor signals are centralized in a near-end or far-end fusion center.

  18. Full duplex fiber link for alternative wired and wireless access based on SSB optical millimeter-wave with 4-PAM signal

    NASA Astrophysics Data System (ADS)

    Ma, Jianxin; Zhang, Junjie

    2015-03-01

    A novel full-duplex fiber-wireless link based on single sideband (SSB) optical millimeter (mm)-wave with 10 Gbit/s 4-pulse amplitude modulation (PAM) signal is proposed to provide alternative wired and 40 GHz wireless accesses for the user terminals. The SSB optical mm-wave with 4-PAM signal consists of two tones: one bears the 4-PAM signal and the other is unmodulated with high power. After transmission over the fiber to the hybrid optical network unit (HONU), the SSB optical mm-wave signal can be decomposed by fiber Bragg gratings (FBGs) as the SSB optical mm-wave signal with reduced carrier-to-sideband ratio (the baseband 4-PAM optical signal) and the uplink optical carrier for the wireless (wired) access. This makes the HONU free from the laser source. For the uplink, since the wireless access signal is converted to the baseband by power detection, both the transmitter in the HONU and the receiver in optical line terminal (OLT) are co-shared for both wireless and wired accesses, which makes the full duplex link much simpler. In our scheme, the optical electrical field of the square-root increment level 4-PAM signal assures an equal level spacing receiving for both the downlink wired and wireless accesses. Since the downlink wireless signal is down-converted to the baseband by power detection, RF local oscillator is unnecessary. To confirm the feasibility of our proposed scheme, a simulation full duplex link with 40 GHz SSB optical mm-wave with 10 Gbit/s 4-PAM signal is built. The simulation results show that both down- and up-links for either wired or wireless access can keep good performance even if the link length of the SSMF is extended to 40 km.

  19. Traffic Management in ATM Networks Over Satellite Links

    NASA Technical Reports Server (NTRS)

    Goyal, Rohit; Jain, Raj; Goyal, Mukul; Fahmy, Sonia; Vandalore, Bobby; vonDeak, Thomas

    1999-01-01

    This report presents a survey of the traffic management Issues in the design and implementation of satellite Asynchronous Transfer Mode (ATM) networks. The report focuses on the efficient transport of Transmission Control Protocol (TCP) traffic over satellite ATM. First, a reference satellite ATM network architecture is presented along with an overview of the service categories available in ATM networks. A delay model for satellite networks and the major components of delay and delay variation are described. A survey of design options for TCP over Unspecified Bit Rate (UBR), Guaranteed Frame Rate (GFR) and Available Bit Rate (ABR) services in ATM is presented. The main focus is on traffic management issues. Several recommendations on the design options for efficiently carrying data services over satellite ATM networks are presented. Most of the results are based on experiments performed on Geosynchronous (GEO) latencies. Some results for Low Earth Orbits (LEO) and Medium Earth Orbit (MEO) latencies are also provided.

  20. Visualizing weighted networks: a performance comparison of adjacency matrices versus node-link diagrams

    NASA Astrophysics Data System (ADS)

    McIntire, John P.; Osesina, O. Isaac; Bartley, Cecilia; Tudoreanu, M. Eduard; Havig, Paul R.; Geiselman, Eric E.

    2012-06-01

    Ensuring the proper and effective ways to visualize network data is important for many areas of academia, applied sciences, the military, and the public. Fields such as social network analysis, genetics, biochemistry, intelligence, cybersecurity, neural network modeling, transit systems, communications, etc. often deal with large, complex network datasets that can be difficult to interact with, study, and use. There have been surprisingly few human factors performance studies on the relative effectiveness of different graph drawings or network diagram techniques to convey information to a viewer. This is particularly true for weighted networks which include the strength of connections between nodes, not just information about which nodes are linked to other nodes. We describe a human factors study in which participants performed four separate network analysis tasks (finding a direct link between given nodes, finding an interconnected node between given nodes, estimating link strengths, and estimating the most densely interconnected nodes) on two different network visualizations: an adjacency matrix with a heat-map versus a node-link diagram. The results should help shed light on effective methods of visualizing network data for some representative analysis tasks, with the ultimate goal of improving usability and performance for viewers of network data displays.

  1. Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

    PubMed Central

    Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

    2014-01-01

    Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications. PMID:24678277

  2. Negative feedback regulation of Wnt signaling via N-linked fucosylation in zebrafish.

    PubMed

    Feng, Lei; Jiang, Hao; Wu, Peng; Marlow, Florence L

    2014-11-15

    L-fucose, a monosaccharide widely distributed in eukaryotes and certain bacteria, is a determinant of many functional glycans that play central roles in numerous biological processes. The molecular mechanism, however, by which fucosylation mediates these processes remains largely elusive. To study how changes in fucosylation impact embryonic development, we up-regulated N-linked fucosylation via over-expression of a key GDP-Fucose transporter, Slc35c1, in zebrafish. We show that Slc35c1 overexpression causes elevated N-linked fucosylation and disrupts embryonic patterning in a transporter activity dependent manner. We demonstrate that patterning defects associated with enhanced N-linked fucosylation are due to diminished canonical Wnt signaling. Chimeric analyses demonstrate that elevated Slc35c1 expression in receiving cells decreases the signaling range of Wnt8a during zebrafish embryogenesis. Moreover, we provide biochemical evidence that this decrease is associated with reduced Wnt8 ligand and elevated Lrp6 coreceptor, which we show are both substrates for N-linked fucosylation in zebrafish embryos. Strikingly, slc35c1 expression is regulated by canonical Wnt signaling. These results suggest that Wnt limits its own signaling activity in part via up-regulation of a transporter, slc35c1 that promotes terminal fucosylation and thereby limits Wnt activity.

  3. β-Spectrin regulates the hippo signaling pathway and modulates the basal actin network.

    PubMed

    Wong, Kenneth Kin Lam; Li, Wenyang; An, Yanru; Duan, Yangyang; Li, Zhuoheng; Kang, Yibin; Yan, Yan

    2015-03-01

    Emerging evidence suggests functional regulation of the Hippo pathway by the actin cytoskeleton, although the detailed molecular mechanism remains incomplete. In a genetic screen, we identified a requirement for β-Spectrin in the posterior follicle cells for the oocyte repolarization process during Drosophila mid-oogenesis. β-spectrin mutations lead to loss of Hippo signaling activity in the follicle cells. A similar reduction of Hippo signaling activity was observed after β-Spectrin knockdown in mammalian cells. We further demonstrated that β-spectrin mutations disrupt the basal actin network in follicle cells. The abnormal stress fiber-like actin structure on the basal side of follicle cells provides a likely link between the β-spectrin mutations and the loss of the Hippo signaling activity phenotype.

  4. Wireless sensor networks for monitoring physiological signals of multiple patients.

    PubMed

    Dilmaghani, R S; Bobarshad, H; Ghavami, M; Choobkar, S; Wolfe, C

    2011-08-01

    This paper presents the design of a novel wireless sensor network structure to monitor patients with chronic diseases in their own homes through a remote monitoring system of physiological signals. Currently, most of the monitoring systems send patients' data to a hospital with the aid of personal computers (PC) located in the patients' home. Here, we present a new design which eliminates the need for a PC. The proposed remote monitoring system is a wireless sensor network with the nodes of the network installed in the patients' homes. These nodes are then connected to a central node located at a hospital through an Internet connection. The nodes of the proposed wireless sensor network are created by using a combination of ECG sensors, MSP430 microcontrollers, a CC2500 low-power wireless radio, and a network protocol called the SimpliciTI protocol. ECG signals are first sampled by a small portable device which each patient carries. The captured signals are then wirelessly transmitted to an access point located within the patients' home. This connectivity is based on wireless data transmission at 2.4-GHz frequency. The access point is also a small box attached to the Internet through a home asynchronous digital subscriber line router. Afterwards, the data are sent to the hospital via the Internet in real time for analysis and/or storage. The benefits of this remote monitoring are wide ranging: the patients can continue their normal lives, they do not need a PC all of the time, their risk of infection is reduced, costs significantly decrease for the hospital, and clinicians can check data in a short time. PMID:23851949

  5. Wireless sensor networks for monitoring physiological signals of multiple patients.

    PubMed

    Dilmaghani, R S; Bobarshad, H; Ghavami, M; Choobkar, S; Wolfe, C

    2011-08-01

    This paper presents the design of a novel wireless sensor network structure to monitor patients with chronic diseases in their own homes through a remote monitoring system of physiological signals. Currently, most of the monitoring systems send patients' data to a hospital with the aid of personal computers (PC) located in the patients' home. Here, we present a new design which eliminates the need for a PC. The proposed remote monitoring system is a wireless sensor network with the nodes of the network installed in the patients' homes. These nodes are then connected to a central node located at a hospital through an Internet connection. The nodes of the proposed wireless sensor network are created by using a combination of ECG sensors, MSP430 microcontrollers, a CC2500 low-power wireless radio, and a network protocol called the SimpliciTI protocol. ECG signals are first sampled by a small portable device which each patient carries. The captured signals are then wirelessly transmitted to an access point located within the patients' home. This connectivity is based on wireless data transmission at 2.4-GHz frequency. The access point is also a small box attached to the Internet through a home asynchronous digital subscriber line router. Afterwards, the data are sent to the hospital via the Internet in real time for analysis and/or storage. The benefits of this remote monitoring are wide ranging: the patients can continue their normal lives, they do not need a PC all of the time, their risk of infection is reduced, costs significantly decrease for the hospital, and clinicians can check data in a short time.

  6. Robustness and Evolvability of the Human Signaling Network

    PubMed Central

    Kim, Jeong-Rae; Munoz, Amaya Garcia; Kolch, Walter; Cho, Kwang-Hyun

    2014-01-01

    Biological systems are known to be both robust and evolvable to internal and external perturbations, but what causes these apparently contradictory properties? We used Boolean network modeling and attractor landscape analysis to investigate the evolvability and robustness of the human signaling network. Our results show that the human signaling network can be divided into an evolvable core where perturbations change the attractor landscape in state space, and a robust neighbor where perturbations have no effect on the attractor landscape. Using chemical inhibition and overexpression of nodes, we validated that perturbations affect the evolvable core more strongly than the robust neighbor. We also found that the evolvable core has a distinct network structure, which is enriched in feedback loops, and features a higher degree of scale-freeness and longer path lengths connecting the nodes. In addition, the genes with high evolvability scores are associated with evolvability-related properties such as rapid evolvability, low species broadness, and immunity whereas the genes with high robustness scores are associated with robustness-related properties such as slow evolvability, high species broadness, and oncogenes. Intriguingly, US Food and Drug Administration-approved drug targets have high evolvability scores whereas experimental drug targets have high robustness scores. PMID:25077791

  7. Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

    NASA Astrophysics Data System (ADS)

    Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

    2015-11-01

    Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively

  8. An information-theoretic model for link prediction in complex networks

    PubMed Central

    Zhu, Boyao; Xia, Yongxiang

    2015-01-01

    Various structural features of networks have been applied to develop link prediction methods. However, because different features highlight different aspects of network structural properties, it is very difficult to benefit from all of the features that might be available. In this paper, we investigate the role of network topology in predicting missing links from the perspective of information theory. In this way, the contributions of different structural features to link prediction are measured in terms of their values of information. Then, an information-theoretic model is proposed that is applicable to multiple structural features. Furthermore, we design a novel link prediction index, called Neighbor Set Information (NSI), based on the information-theoretic model. According to our experimental results, the NSI index performs well in real-world networks, compared with other typical proximity indices. PMID:26335758

  9. Signal-BNF: a Bayesian network fusing approach to predict signal peptides.

    PubMed

    Zheng, Zhi; Chen, Youying; Chen, Liping; Guo, Gongde; Fan, Yongxian; Kong, Xiangzeng

    2012-01-01

    A signal peptide is a short peptide chain that directs the transport of a protein and has become the crucial vehicle in finding new drugs or reprogramming cells for gene therapy. As the avalanche of new protein sequences generated in the postgenomic era, the challenge of identifying new signal sequences has become even more urgent and critical in biomedical engineering. In this paper, we propose a novel predictor called Signal-BNF to predict the N-terminal signal peptide as well as its cleavage site based on Bayesian reasoning network. Signal-BNF is formed by fusing the results of different Bayesian classifiers which used different feature datasets as its input through weighted voting system. Experiment results show that Signal-BNF is superior to the popular online predictors such as Signal-3L and PrediSi. Signal-BNF is featured by high prediction accuracy that may serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the zip code protein-sorting system in cells.

  10. Signal-BNF: A Bayesian Network Fusing Approach to Predict Signal Peptides

    PubMed Central

    Zheng, Zhi; Chen, Youying; Chen, Liping; Guo, Gongde; Fan, Yongxian; Kong, Xiangzeng

    2012-01-01

    A signal peptide is a short peptide chain that directs the transport of a protein and has become the crucial vehicle in finding new drugs or reprogramming cells for gene therapy. As the avalanche of new protein sequences generated in the postgenomic era, the challenge of identifying new signal sequences has become even more urgent and critical in biomedical engineering. In this paper, we propose a novel predictor called Signal-BNF to predict the N-terminal signal peptide as well as its cleavage site based on Bayesian reasoning network. Signal-BNF is formed by fusing the results of different Bayesian classifiers which used different feature datasets as its input through weighted voting system. Experiment results show that Signal-BNF is superior to the popular online predictors such as Signal-3L and PrediSi. Signal-BNF is featured by high prediction accuracy that may serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the zip code protein-sorting system in cells. PMID:23118510

  11. Reverse engineering of linking preferences from network restructuring

    NASA Astrophysics Data System (ADS)

    Palla, Gergely; Farkas, Illés; Derényi, Imre; Barabási, Albert-László; Vicsek, Tamás

    2004-10-01

    We provide a method to deduce the preferences governing the restructuring dynamics of a network from the observed rewiring of the edges. Our approach is applicable for systems in which the preferences can be formulated in terms of a single-vertex energy function with f(k) being the contribution of a node of degree k to the total energy, and the dynamics obeys the detailed balance. The method is first tested by Monte Carlo simulations of restructuring graphs with known energies; then it is used to study variations of real network systems ranging from the coauthorship network of scientific publications to the asset graphs of the New York Stock Exchange. The empirical energies obtained from the restructuring can be described by a universal function f(k)˜-klnk , which is consistent with and justifies the validity of the preferential attachment rule proposed for growing networks.

  12. FORUM: Ecological networks: the missing links in biomonitoring science

    PubMed Central

    Gray, Clare; Baird, Donald J; Baumgartner, Simone; Jacob, Ute; Jenkins, Gareth B; O'Gorman, Eoin J; Lu, Xueke; Ma, Athen; Pocock, Michael J O; Schuwirth, Nele; Thompson, Murray; Woodward, Guy

    2014-01-01

    Monitoring anthropogenic impacts is essential for managing and conserving ecosystems, yet current biomonitoring approaches lack the tools required to deal with the effects of stressors on species and their interactions in complex natural systems. Ecological networks (trophic or mutualistic) can offer new insights into ecosystem degradation, adding value to current taxonomically constrained schemes. We highlight some examples to show how new network approaches can be used to interpret ecological responses. Synthesis and applications. Augmenting routine biomonitoring data with interaction data derived from the literature, complemented with ground-truthed data from direct observations where feasible, allows us to begin to characterise large numbers of ecological networks across environmental gradients. This process can be accelerated by adopting emerging technologies and novel analytical approaches, enabling biomonitoring to move beyond simple pass/fail schemes and to address the many ecological responses that can only be understood from a network-based perspective. PMID:25558087

  13. Pathway connectivity and signaling coordination in the yeast stress-activated signaling network

    PubMed Central

    Chasman, Deborah; Ho, Yi-Hsuan; Berry, David B; Nemec, Corey M; MacGilvray, Matthew E; Hose, James; Merrill, Anna E; Lee, M Violet; Will, Jessica L; Coon, Joshua J; Ansari, Aseem Z; Craven, Mark; Gasch, Audrey P

    2014-01-01

    Stressed cells coordinate a multi-faceted response spanning many levels of physiology. Yet knowledge of the complete stress-activated regulatory network as well as design principles for signal integration remains incomplete. We developed an experimental and computational approach to integrate available protein interaction data with gene fitness contributions, mutant transcriptome profiles, and phospho-proteome changes in cells responding to salt stress, to infer the salt-responsive signaling network in yeast. The inferred subnetwork presented many novel predictions by implicating new regulators, uncovering unrecognized crosstalk between known pathways, and pointing to previously unknown ‘hubs’ of signal integration. We exploited these predictions to show that Cdc14 phosphatase is a central hub in the network and that modification of RNA polymerase II coordinates induction of stress-defense genes with reduction of growth-related transcripts. We find that the orthologous human network is enriched for cancer-causing genes, underscoring the importance of the subnetwork's predictions in understanding stress biology. PMID:25411400

  14. Linking social and pathogen transmission networks using microbial genetics in giraffe (Giraffa camelopardalis).

    PubMed

    VanderWaal, Kimberly L; Atwill, Edward R; Isbell, Lynne A; McCowan, Brenda

    2014-03-01

    Although network analysis has drawn considerable attention as a promising tool for disease ecology, empirical research has been hindered by limitations in detecting the occurrence of pathogen transmission (who transmitted to whom) within social networks. Using a novel approach, we utilize the genetics of a diverse microbe, Escherichia coli, to infer where direct or indirect transmission has occurred and use these data to construct transmission networks for a wild giraffe population (Giraffe camelopardalis). Individuals were considered to be a part of the same transmission chain and were interlinked in the transmission network if they shared genetic subtypes of E. coli. By using microbial genetics to quantify who transmits to whom independently from the behavioural data on who is in contact with whom, we were able to directly investigate how the structure of contact networks influences the structure of the transmission network. To distinguish between the effects of social and environmental contact on transmission dynamics, the transmission network was compared with two separate contact networks defined from the behavioural data: a social network based on association patterns, and a spatial network based on patterns of home-range overlap among individuals. We found that links in the transmission network were more likely to occur between individuals that were strongly linked in the social network. Furthermore, individuals that had more numerous connections or that occupied 'bottleneck' positions in the social network tended to occupy similar positions in the transmission network. No similar correlations were observed between the spatial and transmission networks. This indicates that an individual's social network position is predictive of transmission network position, which has implications for identifying individuals that function as super-spreaders or transmission bottlenecks in the population. These results emphasize the importance of association patterns in

  15. Signaling Network Map of Endothelial TEK Tyrosine Kinase.

    PubMed

    Khan, Aafaque Ahmad; Sandhya, Varot K; Singh, Priyata; Parthasarathy, Deepak; Kumar, Awinav; Advani, Jayshree; Gattu, Rudrappa; Ranjit, Dhanya V; Vaidyanathan, Rama; Mathur, Premendu Prakash; Prasad, T S Keshava; Mac Gabhann, F; Pandey, Akhilesh; Raju, Rajesh; Gowda, Harsha

    2014-01-01

    TEK tyrosine kinase is primarily expressed on endothelial cells and is most commonly referred to as TIE2. TIE2 is a receptor tyrosine kinase modulated by its ligands, angiopoietins, to regulate the development and remodeling of vascular system. It is also one of the critical pathways associated with tumor angiogenesis and familial venous malformations. Apart from the vascular system, TIE2 signaling is also associated with postnatal hematopoiesis. Despite the involvement of TIE2-angiopoietin system in several diseases, the downstream molecular events of TIE2-angiopoietin signaling are not reported in any pathway repository. Therefore, carrying out a detailed review of published literature, we have documented molecular signaling events mediated by TIE2 in response to angiopoietins and developed a network map of TIE2 signaling. The pathway information is freely available to the scientific community through NetPath, a manually curated resource of signaling pathways. We hope that this pathway resource will provide an in-depth view of TIE2-angiopoietin signaling and will lead to identification of potential therapeutic targets for TIE2-angiopoietin associated disorders.

  16. Energy Efficient Link Aware Routing with Power Control in Wireless Ad Hoc Networks.

    PubMed

    Katiravan, Jeevaa; Sylvia, D; Rao, D Srinivasa

    2015-01-01

    In wireless ad hoc networks, the traditional routing protocols make the route selection based on minimum distance between the nodes and the minimum number of hop counts. Most of the routing decisions do not consider the condition of the network such as link quality and residual energy of the nodes. Also, when a link failure occurs, a route discovery mechanism is initiated which incurs high routing overhead. If the broadcast nature and the spatial diversity of the wireless communication are utilized efficiently it becomes possible to achieve improvement in the performance of the wireless networks. In contrast to the traditional routing scheme which makes use of a predetermined route for packet transmission, such an opportunistic routing scheme defines a predefined forwarding candidate list formed by using single network metrics. In this paper, a protocol is proposed which uses multiple metrics such as residual energy and link quality for route selection and also includes a monitoring mechanism which initiates a route discovery for a poor link, thereby reducing the overhead involved and improving the throughput of the network while maintaining network connectivity. Power control is also implemented not only to save energy but also to improve the network performance. Using simulations, we show the performance improvement attained in the network in terms of packet delivery ratio, routing overhead, and residual energy of the network.

  17. Similarity index based on local paths for link prediction of complex networks.

    PubMed

    Lü, Linyuan; Jin, Ci-Hang; Zhou, Tao

    2009-10-01

    Predictions of missing links of incomplete networks, such as protein-protein interaction networks or very likely but not yet existent links in evolutionary networks like friendship networks in web society, can be considered as a guideline for further experiments or valuable information for web users. In this paper, we present a local path index to estimate the likelihood of the existence of a link between two nodes. We propose a network model with controllable density and noise strength in generating links, as well as collect data of six real networks. Extensive numerical simulations on both modeled networks and real networks demonstrated the high effectiveness and efficiency of the local path index compared with two well-known and widely used indices: the common neighbors and the Katz index. Indeed, the local path index provides competitively accurate predictions as the Katz index while requires much less CPU time and memory space than the Katz index, which is therefore a strong candidate for potential practical applications in data mining of huge-size networks.

  18. Wnt-signalling pathways and microRNAs network in carcinogenesis: experimental and bioinformatics approaches.

    PubMed

    Onyido, Emenike K; Sweeney, Eloise; Nateri, Abdolrahman Shams

    2016-01-01

    Over the past few years, microRNAs (miRNAs) have not only emerged as integral regulators of gene expression at the post-transcriptional level but also respond to signalling molecules to affect cell function(s). miRNAs crosstalk with a variety of the key cellular signalling networks such as Wnt, transforming growth factor-β and Notch, control stem cell activity in maintaining tissue homeostasis, while if dysregulated contributes to the initiation and progression of cancer. Herein, we overview the molecular mechanism(s) underlying the crosstalk between Wnt-signalling components (canonical and non-canonical) and miRNAs, as well as changes in the miRNA/Wnt-signalling components observed in the different forms of cancer. Furthermore, the fundamental understanding of miRNA-mediated regulation of Wnt-signalling pathway and vice versa has been significantly improved by high-throughput genomics and bioinformatics technologies. Whilst, these approaches have identified a number of specific miRNA(s) that function as oncogenes or tumour suppressors, additional analyses will be necessary to fully unravel the links among conserved cellular signalling pathways and miRNAs and their potential associated components in cancer, thereby creating therapeutic avenues against tumours. Hence, we also discuss the current challenges associated with Wnt-signalling/miRNAs complex and the analysis using the biomedical experimental and bioinformatics approaches. PMID:27590724

  19. Linking topological structure and dynamics in ecological networks.

    PubMed

    Alcántara, Julio M; Rey, Pedro J

    2012-08-01

    Interaction networks are basic descriptions of ecological communities and are at the core of community dynamics models. Knowledge of their structure should enable us to understand dynamical properties of ecological communities. However, the relationships between dynamical properties of communities and qualitative descriptors of network structure remain unclear. To improve our understanding of such relationships, we develop a framework based on the concept of strongly connected components, which are key structural components of networks necessary to explain stability properties such as persistence and robustness. We illustrate this framework for the analysis of qualitative empirical food webs and plant-plant interaction networks. Both types of networks exhibit high persistence (on average, 99% and 80% of species, respectively, are expected to persist) and robustness (only 0.2% and 2% of species are expected to disappear following the extinction of a species). Each of the networks is structured as a large group of interconnected species accompanied by much smaller groups that most often consist of a single species. This low-modularity configuration can be explained by a negative modularity-stability relationship. Our results suggest that ecological communities are not typically structured in multispecies compartments and that compartmentalization decreases robustness.

  20. Calcium/calmodulin-mediated signal network in plants

    NASA Technical Reports Server (NTRS)

    Yang, Tianbao; Poovaiah, B. W.

    2003-01-01

    Various extracellular stimuli elicit specific calcium signatures that can be recognized by different calcium sensors. Calmodulin, the predominant calcium receptor, is one of the best-characterized calcium sensors in eukaryotes. In recent years, completion of the Arabidopsis genome project and advances in functional genomics have helped to identify and characterize numerous calmodulin-binding proteins in plants. There are some similarities in Ca(2+)/calmodulin-mediated signaling in plants and animals. However, plants possess multiple calmodulin genes and many calmodulin target proteins, including unique protein kinases and transcription factors. Some of these proteins are likely to act as "hubs" during calcium signal transduction. Hence, a better understanding of the function of these calmodulin target proteins should help in deciphering the Ca(2+)/calmodulin-mediated signal network and its role in plant growth, development and response to environmental stimuli.

  1. Computational models of signalling networks for non-linear control.

    PubMed

    Fuente, Luis A; Lones, Michael A; Turner, Alexander P; Stepney, Susan; Caves, Leo S; Tyrrell, Andy M

    2013-05-01

    Artificial signalling networks (ASNs) are a computational approach inspired by the signalling processes inside cells that decode outside environmental information. Using evolutionary algorithms to induce complex behaviours, we show how chaotic dynamics in a conservative dynamical system can be controlled. Such dynamics are of particular interest as they mimic the inherent complexity of non-linear physical systems in the real world. Considering the main biological interpretations of cellular signalling, in which complex behaviours and robust cellular responses emerge from the interaction of multiple pathways, we introduce two ASN representations: a stand-alone ASN and a coupled ASN. In particular we note how sophisticated cellular communication mechanisms can lead to effective controllers, where complicated problems can be divided into smaller and independent tasks.

  2. Real-time data acquisition of commercial microwave link networks for hydrometeorological applications

    NASA Astrophysics Data System (ADS)

    Chwala, Christian; Keis, Felix; Kunstmann, Harald

    2016-03-01

    The usage of data from commercial microwave link (CML) networks for scientific purposes is becoming increasingly popular, in particular for rain rate estimation. However, data acquisition and availability is still a crucial problem and limits research possibilities. To overcome this issue, we have developed an open-source data acquisition system based on the Simple Network Management Protocol (SNMP). It is able to record transmitted and received signal levels of a large number of CMLs simultaneously with a temporal resolution of up to 1 s. We operate this system at Ericsson Germany, acquiring data from 450 CMLs with minutely real-time transfer to our database. Our data acquisition system is not limited to a particular CML hardware model or manufacturer, though. We demonstrate this by running the same system for CMLs of a different manufacturer, operated by an alpine ski resort in Germany. There, the data acquisition is running simultaneously for four CMLs with a temporal resolution of 1 s. We present an overview of our system, describe the details of the necessary SNMP requests and show results from its operational application.

  3. Real time data acquisition of commercial microwave link networks for hydrometeorological applications

    NASA Astrophysics Data System (ADS)

    Chwala, C.; Keis, F.; Kunstmann, H.

    2015-11-01

    The usage of data from commercial microwave link (CML) networks for scientific purposes is becoming increasingly popular, in particular for rain rate estimation. However, data acquisition and availability is still a crucial problem and limits research possibilities. To overcome this issue, we have developed an open source data acquisition system based on the Simple Network Management Protocol (SNMP). It is able to record transmitted- and received signal levels of a large number of CMLs simultaneously with a temporal resolution of up to one second. We operate this system at Ericsson Germany, acquiring data from 450 CMLs with minutely real time transfer to our data base. Our data acquisition system is not limited to a particular CML hardware model or manufacturer, though. We demonstrate this by running the same system for CMLs of a different manufacturer, operated by an alpine skiing resort in Germany. There, the data acquisition is running simultaneously for four CMLs with a temporal resolution of one second. We present an overview of our system, describe the details of the necessary SNMP requests and show results from its operational application.

  4. Brassinosteroid signalling

    PubMed Central

    Zhu, Jia-Ying; Sae-Seaw, Juthamas; Wang, Zhi-Yong

    2013-01-01

    The brassinosteroid (BR) class of steroid hormones regulates plant development and physiology. The BR signal is transduced by a receptor kinase-mediated signal transduction pathway, which is distinct from animal steroid signalling systems. Recent studies have fully connected the BR signal transduction chain and have identified thousands of BR target genes, linking BR signalling to numerous cellular processes. Molecular links between BR and several other signalling pathways have also been identified. Here, we provide an overview of the highly integrated BR signalling network and explain how this steroid hormone functions as a master regulator of plant growth, development and metabolism. PMID:23533170

  5. Dexras1 links glucocorticoids to insulin-like growth factor-1 signaling in adipogenesis

    PubMed Central

    Kim, Hyo Jung; Cha, Jiyoung Y.; Seok, Jo Woon; Choi, Yoonjeong; Yoon, Bo Kyung; Choi, Hyeonjin; Yu, Jung Hwan; Song, Su Jin; Kim, Ara; Lee, Hyemin; Kim, Daeun; Han, Ji Yoon; Kim, Jae-woo

    2016-01-01

    Glucocorticoids are associated with obesity, but the underlying mechanism by which they function remains poorly understood. Previously, we showed that small G protein Dexras1 is expressed by glucocorticoids and leads to adipocyte differentiation. In this study, we explored the mechanism by which Dexras1 mediates adipogenesis and show a link to the insulin-like growth factor-1 (IGF-1) signaling pathway. Without Dexras1, the activation of MAPK and subsequent phosphorylation of CCAAT/enhancer binding protein β (C/EBPβ) is abolished, thereby inhibiting mitotic clonal expansion and further adipocyte differentiation. Dexras1 translocates to the plasma membrane upon insulin or IGF-1 treatment, for which the unique C-terminal domain (amino acids 223–276) is essential. Dexras1-dependent MAPK activation is selectively involved in the IGF-1 signaling, because another Ras protein, H-ras localized to the plasma membrane independently of insulin treatment. Moreover, neither epidermal growth factor nor other cell types shows Dexras1-dependent MAPK activation, indicating the importance of Dexras1 in IGF-1 signaling in adipogenesis. Dexras1 interacts with Shc and Raf, indicating that Dexras1-induced activation of MAPK is largely dependent on the Shc-Grb2-Raf complex. These results suggest that Dexras1 is a critical mediator of the IGF-1 signal to activate MAPK, linking glucocorticoid signaling to IGF-1 signaling in adipogenesis. PMID:27345868

  6. Network Analysis of Neurodegenerative Disease Highlights a Role of Toll-Like Receptor Signaling

    PubMed Central

    Nguyen, Thanh-Phuong; Morine, Melissa J.

    2014-01-01

    Despite significant advances in the study of the molecular mechanisms altered in the development and progression of neurodegenerative diseases (NDs), the etiology is still enigmatic and the distinctions between diseases are not always entirely clear. We present an efficient computational method based on protein-protein interaction network (PPI) to model the functional network of NDs. The aim of this work is fourfold: (i) reconstruction of a PPI network relating to the NDs, (ii) construction of an association network between diseases based on proximity in the disease PPI network, (iii) quantification of disease associations, and (iv) inference of potential molecular mechanism involved in the diseases. The functional links of diseases not only showed overlap with the traditional classification in clinical settings, but also offered new insight into connections between diseases with limited clinical overlap. To gain an expanded view of the molecular mechanisms involved in NDs, both direct and indirect connector proteins were investigated. The method uncovered molecular relationships that are in common apparently distinct diseases and provided important insight into the molecular networks implicated in disease pathogenesis. In particular, the current analysis highlighted the Toll-like receptor signaling pathway as a potential candidate pathway to be targeted by therapy in neurodegeneration. PMID:24551850

  7. SPATA2 links CYLD to the TNF-α receptor signaling complex and modulates the receptor signaling outcomes.

    PubMed

    Wagner, Sebastian A; Satpathy, Shankha; Beli, Petra; Choudhary, Chunaram

    2016-09-01

    TNF-α is a key regulator of innate immune and proinflammatory responses. However, the composition of the TNF-α receptor-associated signaling complexes (TNF-RSC) and the architecture of the downstream signaling networks are incompletely understood. We employed quantitative mass spectrometry to demonstrate that TNF-α stimulation induces widespread protein phosphorylation and that the scope of phosphorylation expands in a temporal manner. TNF-α stimulation also induces rapid ubiquitylation of components of the TNF-RSC Temporal analysis of the TNF-RSC composition identified SPATA2 as a novel component of the TNF-RSC The predicted PUB domain in the N-terminus of SPATA2 interacts with the USP domain of CYLD, whereas the C-terminus of SPATA2 interacts with HOIP SPATA2 is required for recruitment of CYLD to the TNF-RSC Downregulation of SPATA2 augments transcriptional activation of NF-κB and inhibits TNF-α-induced necroptosis, pointing to an important function of SPATA2 in modulating the outcomes of TNF-α signaling. Taken together, our study draws a detailed map of TNF-α signaling, identifies SPATA2 as a novel component of TNF-α signaling, and provides a rich resource for further functional investigations.

  8. Phosphatase specificity and pathway insulation in signaling networks.

    PubMed

    Rowland, Michael A; Harrison, Brian; Deeds, Eric J

    2015-02-17

    Phosphatases play an important role in cellular signaling networks by regulating the phosphorylation state of proteins. Phosphatases are classically considered to be promiscuous, acting on tens to hundreds of different substrates. We recently demonstrated that a shared phosphatase can couple the responses of two proteins to incoming signals, even if those two substrates are from otherwise isolated areas of the network. This finding raises a potential paradox: if phosphatases are indeed highly promiscuous, how do cells insulate themselves against unwanted crosstalk? Here, we use mathematical models to explore three possible insulation mechanisms. One approach involves evolving phosphatase KM values that are large enough to prevent saturation by the phosphatase's substrates. Although this is an effective method for generating isolation, the phosphatase becomes a highly inefficient enzyme, which prevents the system from achieving switch-like responses and can result in slow response kinetics. We also explore the idea that substrate degradation can serve as an effective phosphatase. Assuming that degradation is unsaturatable, this mechanism could insulate substrates from crosstalk, but it would also preclude ultrasensitive responses and would require very high substrate turnover to achieve rapid dephosphorylation kinetics. Finally, we show that adaptor subunits, such as those found on phosphatases like PP2A, can provide effective insulation against phosphatase crosstalk, but only if their binding to substrates is uncoupled from their binding to the catalytic core. Analysis of the interaction network of PP2A's adaptor domains reveals that although its adaptors may isolate subsets of targets from one another, there is still a strong potential for phosphatase crosstalk within those subsets. Understanding how phosphatase crosstalk and the insulation mechanisms described here impact the function and evolution of signaling networks represents a major challenge for

  9. Phosphatase Specificity and Pathway Insulation in Signaling Networks

    PubMed Central

    Rowland, Michael A.; Harrison, Brian; Deeds, Eric J.

    2015-01-01

    Phosphatases play an important role in cellular signaling networks by regulating the phosphorylation state of proteins. Phosphatases are classically considered to be promiscuous, acting on tens to hundreds of different substrates. We recently demonstrated that a shared phosphatase can couple the responses of two proteins to incoming signals, even if those two substrates are from otherwise isolated areas of the network. This finding raises a potential paradox: if phosphatases are indeed highly promiscuous, how do cells insulate themselves against unwanted crosstalk? Here, we use mathematical models to explore three possible insulation mechanisms. One approach involves evolving phosphatase KM values that are large enough to prevent saturation by the phosphatase’s substrates. Although this is an effective method for generating isolation, the phosphatase becomes a highly inefficient enzyme, which prevents the system from achieving switch-like responses and can result in slow response kinetics. We also explore the idea that substrate degradation can serve as an effective phosphatase. Assuming that degradation is unsaturatable, this mechanism could insulate substrates from crosstalk, but it would also preclude ultrasensitive responses and would require very high substrate turnover to achieve rapid dephosphorylation kinetics. Finally, we show that adaptor subunits, such as those found on phosphatases like PP2A, can provide effective insulation against phosphatase crosstalk, but only if their binding to substrates is uncoupled from their binding to the catalytic core. Analysis of the interaction network of PP2A’s adaptor domains reveals that although its adaptors may isolate subsets of targets from one another, there is still a strong potential for phosphatase crosstalk within those subsets. Understanding how phosphatase crosstalk and the insulation mechanisms described here impact the function and evolution of signaling networks represents a major challenge for

  10. Discovering link communities in complex networks by an integer programming model and a genetic algorithm.

    PubMed

    Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua

    2013-01-01

    Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks.

  11. Phytochrome and retrograde signalling pathways coverage to antogonistically regulate a light-induced transcription network

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Plastid-to-nucleus retrograde signals emitted by dysfunctional chloroplasts impact photomorphogenic development, but the molecular link between retrograde and photosensory-receptor signaling has remained undefined. Here, we show that the phytochrome (phy) and retrograde signaling pathways converge a...

  12. Optoelectronic signal processing using finite impulse response neural networks

    NASA Astrophysics Data System (ADS)

    H. B. Xavier da Silveira, Paulo Eduardo

    2001-08-01

    This thesis investigates the use of finite impulse response neural network as the computational algorithm for efficient optoelectronic signal processing. The study begins with the analysis and development of different suitable algorithms, followed by the optoelectronic design of single-layer and multi-layer architectures, and it is concluded with the presentation of the results of a successful experimental implementation. First, finite impulse response adaptive filters and neural networks-the algorithmic building blocks-are introduced, followed by a description of finite impulse response neural networks. This introduction is followed by a historical background, describing early optoelectronic implementations of these algorithms. Next, different algorithms capable of temporal back-propagation are derived in detail, including a novel modification to the conventional algorithm, called delayed-feedback back- propagation. Based on these algorithms, different optoelectronic processors making use of adaptive volume holograms and three-dimensional optical processing are developed. Two single-layer architectures are presented: the input delay plane architecture and the output delay plane architecture. By combining them it is possible to implement both forward and backward propagation in two complementary multi-layer architectures: the first making use of the conventional temporal back-propagation and the second making use of delayed feedback back-propagation. Next, emphasis is given to a specific application: the processing of signals from adaptive antenna arrays. This research is initiated by computer simulations of different scenarios with multiple broadband signals and jammers, in planar and circular arrays, studying issues such as the effect of modulator non-linearities to the performance of the array, and the relation between the number of jammers and the final nulling depth. Two sets of simulations are presented: the first set applied to RF antenna arrays and the

  13. Leveraging Social Links for Trust and Privacy in Networks

    NASA Astrophysics Data System (ADS)

    Cutillo, Leucio Antonio; Molva, Refik; Strufe, Thorsten

    Existing on-line social networks (OSN) such as Facebook suffer from several weaknesses regarding privacy and security due to their inherent handling of personal data. As pointed out in [4], a preliminary analysis of existing OSNs shows that they are subject to a number of vulnerabilities, ranging from cloning legitimate users to sybil attacks through privacy violations. Starting from these OSN vulnerabilities as the first step of a broader research activity, we came up with a new approach that is very promising in re-visiting security and privacy problems in distributed systems and networks. We suggest a solution that both aims at avoiding any centralized control and leverages on the real life trust between users, that is part of the social network application itself. An anonymization technique based on multi-hop routing among trusted nodes guarantees privacy in data access and, generally speaking, in all the OSN operations.

  14. LINKEDIN TRILOGY: Part 1. Top 10 Reasons You Should NOT Join LinkedIn Professional Network!

    ERIC Educational Resources Information Center

    Berk, Ronald A.

    2013-01-01

    Disclaimer: I have been an active "free" user of LinkedIn for 5.463 years with more than 3000 (1st degree) connections from all over the world. I have no vested interest in LinkedIn other than as a user of the services it provides. Despite the fact that LinkedIn was originally designed as a network for business professionals, not…

  15. Building Student Networks with LinkedIn: The Potential for Connections, Internships, and Jobs

    ERIC Educational Resources Information Center

    Peterson, Robert M.; Dover, Howard F.

    2014-01-01

    Networking is a chance to interact with people, build friendships or business partners, identify opportunities, and create value. Technology has made this process easier, since individuals can readily contact others who were previously unknown. In the professional world, LinkedIn has become the standard way to build virtual and personal networks.…

  16. Enhancing traffic capacity of scale-free networks by link-directed strategy

    NASA Astrophysics Data System (ADS)

    Ma, Jinlong; Han, Weizhan; Guo, Qing; Zhang, Shuai

    2016-08-01

    The transport efficiency of a network is strongly related to the underlying structure. In this paper, we propose an efficient strategy named high-betweenness-first (HBF) for the purpose of improving the traffic handling capacity of scale-free networks by limiting a fraction of undirected links to be unidirectional ones based on the links’ betweenness. Compared with the high-degree-first (HDF) strategy, the traffic capacity can be more significantly enhanced under the proposed link-directed strategy with the shortest path (SP) routing protocol. Simulation results in the Barabási-Albert (BA) model for scale-free networks show that the critical generating rate Rc which can evaluate the overall traffic capacity of a network system is larger after applying the HBF strategy, especially with nonrandom direction-determining rules. Because of the strongly improved traffic capacity, this work is helpful to design and optimize modern communication networks such as the software defined network.

  17. Biasing vector network analyzers using variable frequency and amplitude signals.

    PubMed

    Nobles, J E; Zagorodnii, V; Hutchison, A; Celinski, Z

    2016-08-01

    We report the development of a test setup designed to provide a variable frequency biasing signal to a vector network analyzer (VNA). The test setup is currently used for the testing of liquid crystal (LC) based devices in the microwave region. The use of an AC bias for LC based devices minimizes the negative effects associated with ionic impurities in the media encountered with DC biasing. The test setup utilizes bias tees on the VNA test station to inject the bias signal. The square wave biasing signal is variable from 0.5 to 36.0 V peak-to-peak (VPP) with a frequency range of DC to 10 kHz. The test setup protects the VNA from transient processes, voltage spikes, and high-frequency leakage. Additionally, the signals to the VNA are fused to ½ amp and clipped to a maximum of 36 VPP based on bias tee limitations. This setup allows us to measure S-parameters as a function of both the voltage and the frequency of the applied bias signal. PMID:27587141

  18. Biasing vector network analyzers using variable frequency and amplitude signals

    NASA Astrophysics Data System (ADS)

    Nobles, J. E.; Zagorodnii, V.; Hutchison, A.; Celinski, Z.

    2016-08-01

    We report the development of a test setup designed to provide a variable frequency biasing signal to a vector network analyzer (VNA). The test setup is currently used for the testing of liquid crystal (LC) based devices in the microwave region. The use of an AC bias for LC based devices minimizes the negative effects associated with ionic impurities in the media encountered with DC biasing. The test setup utilizes bias tees on the VNA test station to inject the bias signal. The square wave biasing signal is variable from 0.5 to 36.0 V peak-to-peak (VPP) with a frequency range of DC to 10 kHz. The test setup protects the VNA from transient processes, voltage spikes, and high-frequency leakage. Additionally, the signals to the VNA are fused to ½ amp and clipped to a maximum of 36 VPP based on bias tee limitations. This setup allows us to measure S-parameters as a function of both the voltage and the frequency of the applied bias signal.

  19. Query and Visualization of extremely large network datasets over the web using Quadtree based KML Regional Network Links

    SciTech Connect

    Dadi, Upendra; Liu, Cheng; Vatsavai, Raju

    2009-01-01

    Geographic data sets are often very large in size. Interactive visualization of such data at all scales is not easy because of the limited resolution of the monitors and inability of visualization applications to handle the volume of data. This is especially true for large vector datasets. The end user s experience is frequently unsatisfactory when exploring such data over the web using a naive application. Network bandwidth is another contributing factor to the low performance. In this paper, a Quadtree based technique to visualize extremely large spatial network datasets over the web is described. It involves using custom developed algorithms leveraging a PostGIS database as the data source and Google Earth as the visualization client. This methodology supports both point and range queries along with non-spatial queries. This methodology is demonstrated using a network dataset consisting of several million links. The methodology is based on using some of the powerful features of KML (Keyhole Markup Language). Keyhole Markup Language (KML) is an Open Geospatial Consortium (OGC) standard for displaying geospatial data on Earth browsers. One of the features of KML is the notion of Network Links. Using network links, a wide range of geospatial data sources such as geodatabases, static files and geospatial data services can be simultaneously accessed and visualized seamlessly. Using the network links combined with Level of Detail principle, view based rendering and intelligent server and client-side caching, scalability in visualizing extremely large spatial datasets can be achieved.

  20. Linking Data and Learning - The Grow Network Study: Summary Report

    ERIC Educational Resources Information Center

    Light, Daniel; Honey, Margaret; Heinze, Juliet; Brunner, Cornelia; Wexler, Dara; Mandinach, Ellen; Fasca, Chad

    2005-01-01

    With funding from the Carnegie Corporation, in the spring of 2002, EDC's Center for Children and Technology began a two-year exploratory study that examined how educators and administrators within the New York City public school system are using data?made available to them through the print and web-based reporting system of the Grow Network to…

  1. A model integration approach linking signalling and gene-regulatory logic with kinetic metabolic models.

    PubMed

    Ryll, A; Bucher, J; Bonin, A; Bongard, S; Gonçalves, E; Saez-Rodriguez, J; Niklas, J; Klamt, S

    2014-10-01

    Systems biology has to increasingly cope with large- and multi-scale biological systems. Many successful in silico representations and simulations of various cellular modules proved mathematical modelling to be an important tool in gaining a solid understanding of biological phenomena. However, models spanning different functional layers (e.g. metabolism, signalling and gene regulation) are still scarce. Consequently, model integration methods capable of fusing different types of biological networks and various model formalisms become a key methodology to increase the scope of cellular processes covered by mathematical models. Here we propose a new integration approach to couple logical models of signalling or/and gene-regulatory networks with kinetic models of metabolic processes. The procedure ends up with an integrated dynamic model of both layers relying on differential equations. The feasibility of the approach is shown in an illustrative case study integrating a kinetic model of central metabolic pathways in hepatocytes with a Boolean logical network depicting the hormonally induced signal transduction and gene regulation events involved. In silico simulations demonstrate the integrated model to qualitatively describe the physiological switch-like behaviour of hepatocytes in response to nutritionally regulated changes in extracellular glucagon and insulin levels. A simulated failure mode scenario addressing insulin resistance furthermore illustrates the pharmacological potential of a model covering interactions between signalling, gene regulation and metabolism. PMID:25063553

  2. Simulation study of communication link for Pioneer Saturn/Uranus atmospheric entry probe. [signal acquisition by candidate modem for radio link

    NASA Technical Reports Server (NTRS)

    Hinrichs, C. A.

    1974-01-01

    A digital simulation is presented for a candidate modem in a modeled atmospheric scintillation environment with Doppler, Doppler rate, and signal attenuation typical of the radio link conditions for an outer planets atmospheric entry probe. The results indicate that the signal acquisition characteristics and the channel error rate are acceptable for the system requirements of the radio link. The simulation also outputs data for calculating other error statistics and a quantized symbol stream from which error correction decoding can be analyzed.

  3. Synchronization transmission of target signal within the coupling network with quantum chaos effect

    NASA Astrophysics Data System (ADS)

    Li, Wenlin; Li, Chong; Song, Heshan

    2016-11-01

    In this work, we propose a novel technology to investigate the synchronization transmission of target signal within the coupling network. In this new technology, the network synchronization transmission is realized through the coupling between the network nodes, and the controller is not required to add in the network. Especially, as long as the target signal can be input to an arbitrary node in the network, so all the network nodes are synchronized to the target signal, that is, the target signal has got synchronization transmission.

  4. Real time data acquisition of a countrywide commercial microwave link network

    NASA Astrophysics Data System (ADS)

    Chwala, Christian; Keis, Felix; Kunstmann, Harald

    2015-04-01

    Research in recent years has shown that data from commercial microwave link networks can provide very valuable precipitation information. Since these networks comprise the backbone of the cell phone network, they provide countrywide coverage. However acquiring the necessary data from the network operators is still difficult. Data is usually made available for researchers with a large time delay and often at irregular basis. This of course hinders the exploitation of commercial microwave link data in operational applications like QPE forecasts running at national meteorological services. To overcome this, we have developed a custom software in joint cooperation with our industry partner Ericsson. The software is installed on a dedicated server at Ericsson and is capable of acquiring data from the countrywide microwave link network in Germany. In its current first operational testing phase, data from several hundred microwave links in southern Germany is recorded. All data is instantaneously sent to our server where it is stored and organized in an emerging database. Time resolution for the Ericsson data is one minute. The custom acquisition software, however, is capable of processing higher sampling rates. Additionally we acquire and manage 1 Hz data from four microwave links operated by the skiing resort in Garmisch-Partenkirchen. We will present the concept of the data acquisition and show details of the custom-built software. Additionally we will showcase the accessibility and basic processing of real time microwave link data via our database web frontend.

  5. Cascading failures in coupled networks with both inner-dependency and inter-dependency links

    PubMed Central

    Liu, Run-Ran; Li, Ming; Jia, Chun-Xiao; Wang, Bing-Hong

    2016-01-01

    We study the percolation in coupled networks with both inner-dependency and inter-dependency links, where the inner- and inter-dependency links represent the dependencies between nodes in the same or different networks, respectively. We find that when most of dependency links are inner- or inter-ones, the coupled networks system is fragile and makes a discontinuous percolation transition. However, when the numbers of two types of dependency links are close to each other, the system is robust and makes a continuous percolation transition. This indicates that the high density of dependency links could not always lead to a discontinuous percolation transition as the previous studies. More interestingly, although the robustness of the system can be optimized by adjusting the ratio of the two types of dependency links, there exists a critical average degree of the networks for coupled random networks, below which the crossover of the two types of percolation transitions disappears, and the system will always demonstrate a discontinuous percolation transition. We also develop an approach to analyze this model, which is agreement with the simulation results well. PMID:27142883

  6. Cascading failures in coupled networks with both inner-dependency and inter-dependency links.

    PubMed

    Liu, Run-Ran; Li, Ming; Jia, Chun-Xiao; Wang, Bing-Hong

    2016-05-04

    We study the percolation in coupled networks with both inner-dependency and inter-dependency links, where the inner- and inter-dependency links represent the dependencies between nodes in the same or different networks, respectively. We find that when most of dependency links are inner- or inter-ones, the coupled networks system is fragile and makes a discontinuous percolation transition. However, when the numbers of two types of dependency links are close to each other, the system is robust and makes a continuous percolation transition. This indicates that the high density of dependency links could not always lead to a discontinuous percolation transition as the previous studies. More interestingly, although the robustness of the system can be optimized by adjusting the ratio of the two types of dependency links, there exists a critical average degree of the networks for coupled random networks, below which the crossover of the two types of percolation transitions disappears, and the system will always demonstrate a discontinuous percolation transition. We also develop an approach to analyze this model, which is agreement with the simulation results well.

  7. Controlling self-sustained spiking activity by adding or removing one network link

    NASA Astrophysics Data System (ADS)

    Xu, Kesheng; Huang, Wenwen; Li, Baowen; Dhamala, Mukesh; Liu, Zonghua

    2013-06-01

    Being able to control the neuronal spiking activity in specific brain regions is central to a treatment scheme in several brain disorders such as epileptic seizures, mental depression, and Parkinson's diseases. Here, we present an approach for controlling self-sustained oscillations by adding or removing one directed network link in coupled neuronal oscillators, in contrast to previous approaches of adding stimuli or noise. We find that such networks can exhibit a variety of activity patterns such as on-off switch, sustained spikes, and short-term spikes. We derive the condition for a specific link to be the controller of the on-off effect. A qualitative analysis is provided to facilitate the understanding of the mechanism for spiking activity by adding one link. Our findings represent the first report on generating spike activity with the addition of only one directed link to a network and provide a deeper understanding of the microscopic roots of self-sustained spiking.

  8. Transmembrane Signaling Characterized in Bacterial Chemoreceptors by Using Sulfhydryl Cross-Linking in vivo

    NASA Astrophysics Data System (ADS)

    Lee, Geoffrey F.; Lebert, Michael R.; Lilly, Angela A.; Hazelbauer, Gerald L.

    1995-04-01

    Transmembrane signaling by bacterial chemoreceptors is thought to involve conformational changes within a stable homodimer. We investigated the functional consequences of constraining movement between pairs of helices in the four-helix structure of the transmembrane domain of chemoreceptor Trg. Using a family of cysteine-containing receptors, we identified oxidation treatments for intact cells that catalyzed essentially complete sulfhydryl cross-linking at selected positions and yet left flagellar and sensory functions largely unperturbed. Constraining movement by cross-links between subunits had little effect on tactic response, but constraining movement between transmembrane segments of the monomer drastically reduced function. We deduce that transmembrane signaling requires substantial movement between transmembrane helices of a monomer but not between interacting helices across the interface between subunits.

  9. Lys63-linked polyubiquitination of BRAF at lysine 578 is required for BRAF-mediated signaling

    PubMed Central

    An, Lei; Jia, Wei; Yu, Yang; Zou, Ning; Liang, Li; Zhao, Yanling; Fan, Yihui; Cheng, Jin; Shi, Zhongcheng; Xu, Gufeng; Li, Grace; Yang, Jianhua; Zhang, Hong

    2013-01-01

    The RAF kinase family is essential in mediating signal transduction from RAS to ERK. BRAF constitutively active mutations correlate with human cancer development. However, the precise molecular regulation of BRAF activation is not fully understood. Here we report that BRAF is modified by Lys63-linked polyubiquitination at lysine 578 within its kinase domain once it is activated by gain of constitutively active mutation or epidermal growth factor (EGF) stimulation. Substitution of BRAF lysine 578 with arginine (K578R) inhibited BRAF-mediated ERK activation. Furthermore, ectopic expression of BRAF K578R mutant inhibited anchorage-independent colony formation of MCF7 breast cancer cell line. Our studies have identified a previously unrecognized regulatory role of Lys63-linked polyubiquitination in BRAF-mediated normal and oncogenic signalings. PMID:23907581

  10. The structural role of weak and strong links in a financial market network

    NASA Astrophysics Data System (ADS)

    Garas, A.; Argyrakis, P.; Havlin, S.

    2008-05-01

    We investigate the properties of correlation based networks originating from economic complex systems, such as the network of stocks traded at the New York Stock Exchange (NYSE). The weaker links (low correlation) of the system are found to contribute to the overall connectivity of the network significantly more than the strong links (high correlation). We find that nodes connected through strong links form well defined communities. These communities are clustered together in more complex ways compared to the widely used classification according to the economic activity. We find that some companies, such as General Electric (GE), Coca Cola (KO), and others, can be involved in different communities. The communities are found to be quite stable over time. Similar results were obtained by investigating markets completely different in size and properties, such as the Athens Stock Exchange (ASE). The present method may be also useful for other networks generated through correlations.

  11. Space Network Time Distribution and Synchronization Protocol Development for Mars Proximity Link

    NASA Technical Reports Server (NTRS)

    Woo, Simon S.; Gao, Jay L.; Mills, David

    2010-01-01

    Time distribution and synchronization in deep space network are challenging due to long propagation delays, spacecraft movements, and relativistic effects. Further, the Network Time Protocol (NTP) designed for terrestrial networks may not work properly in space. In this work, we consider the time distribution protocol based on time message exchanges similar to Network Time Protocol (NTP). We present the Proximity-1 Space Link Interleaved Time Synchronization (PITS) algorithm that can work with the CCSDS Proximity-1 Space Data Link Protocol. The PITS algorithm provides faster time synchronization via two-way time transfer over proximity links, improves scalability as the number of spacecraft increase, lowers storage space requirement for collecting time samples, and is robust against packet loss and duplication which underlying protocol mechanisms provide.

  12. Perturbation Biology: Inferring Signaling Networks in Cellular Systems

    PubMed Central

    Miller, Martin L.; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

    2013-01-01

    We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. PMID:24367245

  13. Mesoscopic simulations of hydrophilic cross-linked polycarbonate polyurethane networks: structure and morphology.

    PubMed

    Iype, E; Esteves, A C C; de With, G

    2016-06-14

    Polyurethane (PU) cross-linked networks are frequently used in biomedical and marine applications, e.g., as hydrophilic polymer coatings with antifouling or low-friction properties and have been reported to exhibit characteristic phase separation between soft and hard segments. Understanding this phase-separation behavior is critical to design novel hydrophilic polymer coatings. However, most of the studies on the structure and morphology of cross-linked coatings are experimental, which only assess the phase separation via indirect methods. Herein we present a mesoscopic simulation study of the network characteristics of model hydrophilic polymer networks, consisting of PU with and without methyl-polyethylene glycol (mPEG) dangling chains. The systems are analyzed using a number of tools, such as the radial distribution function, the cross-link point density distribution and the Voronoi volume distribution (of the cross-linking points). The combined results show that the cross-linked networks without dangling chains are rather homogeneous but contain a small amount of clustering of cross-linker molecules. A clear phase separation is observed when introducing the dangling chains. In spite of that, the amount of cross-linker molecules connected to dangling chains only, i.e., not connected to the main network, is relatively small, leading to about 3 wt% extractables. Thus, these cross-linked polymers consist of a phase-separated, yet highly connected network. This study provides valuable guidelines towards new self-healing hydrophilic coatings based on the molecular design of cross-linked networks in direct contact with water or aqueous fluids, e.g., as anti-fouling self-repairing coatings for marine applications. PMID:27174657

  14. Mesoscopic simulations of hydrophilic cross-linked polycarbonate polyurethane networks: structure and morphology.

    PubMed

    Iype, E; Esteves, A C C; de With, G

    2016-06-14

    Polyurethane (PU) cross-linked networks are frequently used in biomedical and marine applications, e.g., as hydrophilic polymer coatings with antifouling or low-friction properties and have been reported to exhibit characteristic phase separation between soft and hard segments. Understanding this phase-separation behavior is critical to design novel hydrophilic polymer coatings. However, most of the studies on the structure and morphology of cross-linked coatings are experimental, which only assess the phase separation via indirect methods. Herein we present a mesoscopic simulation study of the network characteristics of model hydrophilic polymer networks, consisting of PU with and without methyl-polyethylene glycol (mPEG) dangling chains. The systems are analyzed using a number of tools, such as the radial distribution function, the cross-link point density distribution and the Voronoi volume distribution (of the cross-linking points). The combined results show that the cross-linked networks without dangling chains are rather homogeneous but contain a small amount of clustering of cross-linker molecules. A clear phase separation is observed when introducing the dangling chains. In spite of that, the amount of cross-linker molecules connected to dangling chains only, i.e., not connected to the main network, is relatively small, leading to about 3 wt% extractables. Thus, these cross-linked polymers consist of a phase-separated, yet highly connected network. This study provides valuable guidelines towards new self-healing hydrophilic coatings based on the molecular design of cross-linked networks in direct contact with water or aqueous fluids, e.g., as anti-fouling self-repairing coatings for marine applications.

  15. Matching-centrality decomposition and the forecasting of new links in networks.

    PubMed

    Rohr, Rudolf P; Naisbit, Russell E; Mazza, Christian; Bersier, Louis-Félix

    2016-02-10

    Networks play a prominent role in the study of complex systems of interacting entities in biology, sociology, and economics. Despite this diversity, we demonstrate here that a statistical model decomposing networks into matching and centrality components provides a comprehensive and unifying quantification of their architecture. The matching term quantifies the assortative structure in which node makes links with which other node, whereas the centrality term quantifies the number of links that nodes make. We show, for a diverse set of networks, that this decomposition can provide a tight fit to observed networks. Then we provide three applications. First, we show that the model allows very accurate prediction of missing links in partially known networks. Second, when node characteristics are known, we show how the matching-centrality decomposition can be related to this external information. Consequently, it offers us a simple and versatile tool to explore how node characteristics explain network architecture. Finally, we demonstrate the efficiency and flexibility of the model to forecast the links that a novel node would create if it were to join an existing network.

  16. Deep Space Network Capabilities for Receiving Weak Probe Signals

    NASA Technical Reports Server (NTRS)

    Asmar, Sami; Johnston, Doug; Preston, Robert

    2005-01-01

    Planetary probes can encounter mission scenarios where communication is not favorable during critical maneuvers or emergencies. Launch, initial acquisition, landing, trajectory corrections, safing. Communication challenges due to sub-optimum antenna pointing or transmitted power, amplitude/frequency dynamics, etc. Prevent lock-up on signal and extraction of telemetry. Examples: loss of Mars Observer, nutation of Ulysses, Galileo antenna, Mars Pathfinder and Mars Exploration Rovers Entry, Descent, and Landing, and the Cassini Saturn Orbit Insertion. A Deep Space Network capability to handle such cases has been used successfully to receive signals to characterize the scenario. This paper will describe the capability and highlight the cases of the critical communications for the Mars rovers and Saturn Orbit Insertion and preparation radio tracking of the Huygens probe at (non-DSN) radio telescopes.

  17. A modular analysis of the auxin signalling network.

    PubMed

    Farcot, Etienne; Lavedrine, Cyril; Vernoux, Teva

    2015-01-01

    Auxin is essential for plant development from embryogenesis onwards. Auxin acts in large part through regulation of transcription. The proteins acting in the signalling pathway regulating transcription downstream of auxin have been identified as well as the interactions between these proteins, thus identifying the topology of this network implicating 54 Auxin Response Factor (ARF) and Aux/IAA (IAA) transcriptional regulators. Here, we study the auxin signalling pathway by means of mathematical modeling at the single cell level. We proceed analytically, by considering the role played by five functional modules into which the auxin pathway can be decomposed: the sequestration of ARF by IAA, the transcriptional repression by IAA, the dimer formation amongst ARFs and IAAs, the feedback loop on IAA and the auxin induced degradation of IAA proteins. Focusing on these modules allows assessing their function within the dynamics of auxin signalling. One key outcome of this analysis is that there are both specific and overlapping functions between all the major modules of the signaling pathway. This suggests a combinatorial function of the modules in optimizing the speed and amplitude of auxin-induced transcription. Our work allows identifying potential functions for homo- and hetero-dimerization of transcriptional regulators, with ARF:IAA, IAA:IAA and ARF:ARF dimerization respectively controlling the amplitude, speed and sensitivity of the response and a synergistic effect of the interaction of IAA with transcriptional repressors on these characteristics of the signaling pathway. Finally, we also suggest experiments which might allow disentangling the structure of the auxin signaling pathway and analysing further its function in plants.

  18. Signaling Pathways and Gene Regulatory Networks in Cardiomyocyte Differentiation

    PubMed Central

    Parikh, Abhirath; Wu, Jincheng; Blanton, Robert M.

    2015-01-01

    Strategies for harnessing stem cells as a source to treat cell loss in heart disease are the subject of intense research. Human pluripotent stem cells (hPSCs) can be expanded extensively in vitro and therefore can potentially provide sufficient quantities of patient-specific differentiated cardiomyocytes. Although multiple stimuli direct heart development, the differentiation process is driven in large part by signaling activity. The engineering of hPSCs to heart cell progeny has extensively relied on establishing proper combinations of soluble signals, which target genetic programs thereby inducing cardiomyocyte specification. Pertinent differentiation strategies have relied as a template on the development of embryonic heart in multiple model organisms. Here, information on the regulation of cardiomyocyte development from in vivo genetic and embryological studies is critically reviewed. A fresh interpretation is provided of in vivo and in vitro data on signaling pathways and gene regulatory networks (GRNs) underlying cardiopoiesis. The state-of-the-art understanding of signaling pathways and GRNs presented here can inform the design and optimization of methods for the engineering of tissues for heart therapies. PMID:25813860

  19. Criteria for Evaluating Alternative Network and Link Layer Protocols for the NASA Constellation Program Communication Architecture

    NASA Technical Reports Server (NTRS)

    Benbenek, Daniel; Soloff, Jason; Lieb, Erica

    2010-01-01

    Selecting a communications and network architecture for future manned space flight requires an evaluation of the varying goals and objectives of the program, development of communications and network architecture evaluation criteria, and assessment of critical architecture trades. This paper uses Cx Program proposed exploration activities as a guideline; lunar sortie, outpost, Mars, and flexible path options are described. A set of proposed communications network architecture criteria are proposed and described. They include: interoperability, security, reliability, and ease of automating topology changes. Finally a key set of architecture options are traded including (1) multiplexing data at a common network layer vs. at the data link layer, (2) implementing multiple network layers vs. a single network layer, and (3) the use of a particular network layer protocol, primarily IPv6 vs. Delay Tolerant Networking (DTN). In summary, the protocol options are evaluated against the proposed exploration activities and their relative performance with respect to the criteria are assessed. An architectural approach which includes (a) the capability of multiplexing at both the network layer and the data link layer and (b) a single network layer for operations at each program phase, as these solutions are best suited to respond to the widest array of program needs and meet each of the evaluation criteria.

  20. Link removal for the control of stochastically evolving epidemics over networks: a comparison of approaches.

    PubMed

    Enns, Eva A; Brandeau, Margaret L

    2015-04-21

    For many communicable diseases, knowledge of the underlying contact network through which the disease spreads is essential to determining appropriate control measures. When behavior change is the primary intervention for disease prevention, it is important to understand how to best modify network connectivity using the limited resources available to control disease spread. We describe and compare four algorithms for selecting a limited number of links to remove from a network: two "preventive" approaches (edge centrality, R0 minimization), where the decision of which links to remove is made prior to any disease outbreak and depends only on the network structure; and two "reactive" approaches (S-I edge centrality, optimal quarantining), where information about the initial disease states of the nodes is incorporated into the decision of which links to remove. We evaluate the performance of these algorithms in minimizing the total number of infections that occur over the course of an acute outbreak of disease. We consider different network structures, including both static and dynamic Erdös-Rényi random networks with varying levels of connectivity, a real-world network of residential hotels connected through injection drug use, and a network exhibiting community structure. We show that reactive approaches outperform preventive approaches in averting infections. Among reactive approaches, removing links in order of S-I edge centrality is favored when the link removal budget is small, while optimal quarantining performs best when the link removal budget is sufficiently large. The budget threshold above which optimal quarantining outperforms the S-I edge centrality algorithm is a function of both network structure (higher for unstructured Erdös-Rényi random networks compared to networks with community structure or the real-world network) and disease infectiousness (lower for highly infectious diseases). We conduct a value-of-information analysis of knowing which

  1. Value Co-creation and Co-innovation: Linking Networked Organisations and Customer Communities

    NASA Astrophysics Data System (ADS)

    Romero, David; Molina, Arturo

    Strategic networks such as Collaborative Networked Organisations (CNOs) and Virtual Customer Communities (VCCs) show a high potential as drivers of value co-creation and collaborative innovation in today’s Networking Era. Both look at the network structures as a source of jointly value creation and open innovation through access to new skills, knowledge, markets and technologies by sharing risk and integrating complementary competencies. This collaborative endeavour has proven to be able to enhance the adaptability and flexibility of CNOs and VCCs value creating systems in order to react in response to external drivers such as collaborative (business) opportunities. This paper presents a reference framework for creating interface networks, also known as ‘experience-centric networks’, as enablers for linking networked organisations and customer communities in order to support the establishment of user-driven and collaborative innovation networks.

  2. Time Development in the Early History of Social Networks: Link Stabilization, Group Dynamics, and Segregation

    PubMed Central

    Bruun, Jesper; Bearden, Ian G.

    2014-01-01

    Studies of the time development of empirical networks usually investigate late stages where lasting connections have already stabilized. Empirical data on early network history are rare but needed for a better understanding of how social network topology develops in real life. Studying students who are beginning their studies at a university with no or few prior connections to each other offers a unique opportunity to investigate the formation and early development of link patterns and community structure in social networks. During a nine week introductory physics course, first year physics students were asked to identify those with whom they communicated about problem solving in physics during the preceding week. We use these students' self reports to produce time dependent student interaction networks. We investigate these networks to elucidate possible effects of different student attributes in early network formation. Changes in the weekly number of links show that while roughly half of all links change from week to week, students also reestablish a growing number of links as they progress through their first weeks of study. Using the Infomap community detection algorithm, we show that the networks exhibit community structure, and we use non-network student attributes, such as gender and end-of-course grade to characterize communities during their formation. Specifically, we develop a segregation measure and show that students structure themselves according to gender and pre-organized sections (in which students engage in problem solving and laboratory work), but not according to end-of-coure grade. Alluvial diagrams of consecutive weeks' communities show that while student movement between groups are erratic in the beginnning of their studies, they stabilize somewhat towards the end of the course. Taken together, the analyses imply that student interaction networks stabilize quickly and that students establish collaborations based on who is immediately

  3. Disrupted Intrinsic Networks Link Amyloid-β Pathology and Impaired Cognition in Prodromal Alzheimer's Disease.

    PubMed

    Koch, Kathrin; Myers, Nicholas E; Göttler, Jens; Pasquini, Lorenzo; Grimmer, Timo; Förster, Stefan; Manoliu, Andrei; Neitzel, Julia; Kurz, Alexander; Förstl, Hans; Riedl, Valentin; Wohlschläger, Afra M; Drzezga, Alexander; Sorg, Christian

    2015-12-01

    Amyloid-β pathology (Aβ) and impaired cognition characterize Alzheimer's disease (AD); however, neural mechanisms that link Aβ-pathology with impaired cognition are incompletely understood. Large-scale intrinsic connectivity networks (ICNs) are potential candidates for this link: Aβ-pathology affects specific networks in early AD, these networks show disrupted connectivity, and they process specific cognitive functions impaired in AD, like memory or attention. We hypothesized that, in AD, regional changes of ICNs, which persist across rest- and cognitive task-states, might link Aβ-pathology with impaired cognition via impaired intrinsic connectivity. Pittsburgh compound B (PiB)-positron emission tomography reflecting in vivo Aβ-pathology, resting-state fMRI, task-fMRI, and cognitive testing were used in patients with prodromal AD and healthy controls. In patients, default mode network's (DMN) functional connectivity (FC) was reduced in the medial parietal cortex during rest relative to healthy controls, relatively increased in the same region during an attention-demanding task, and associated with patients' cognitive impairment. Local PiB-uptake correlated negatively with DMN connectivity. Importantly, corresponding results were found for the right lateral parietal region of an attentional network. Finally, structural equation modeling confirmed a direct influence of DMN resting-state FC on the association between Aβ-pathology and cognitive impairment. Data provide evidence that disrupted intrinsic network connectivity links Aβ-pathology with cognitive impairment in early AD.

  4. Control of cancer-related signal transduction networks

    NASA Astrophysics Data System (ADS)

    Albert, Reka

    2013-03-01

    Intra-cellular signaling networks are crucial to the maintenance of cellular homeostasis and for cell behavior (growth, survival, apoptosis, movement). Mutations or alterations in the expression of elements of cellular signaling networks can lead to incorrect behavioral decisions that could result in tumor development and/or the promotion of cell migration and metastasis. Thus, mitigation of the cascading effects of such dysregulations is an important control objective. My group at Penn State is collaborating with wet-bench biologists to develop and validate predictive models of various biological systems. Over the years we found that discrete dynamic modeling is very useful in molding qualitative interaction information into a predictive model. We recently demonstrated the effectiveness of network-based targeted manipulations on mitigating the disease T cell large granular lymphocyte (T-LGL) leukemia. The root of this disease is the abnormal survival of T cells which, after successfully fighting an infection, should undergo programmed cell death. We synthesized the relevant network of within-T-cell interactions from the literature, integrated it with qualitative knowledge of the dysregulated (abnormal) states of several network components, and formulated a Boolean dynamic model. The model indicated that the system possesses a steady state corresponding to the normal cell death state and a T-LGL steady state corresponding to the abnormal survival state. For each node, we evaluated the restorative manipulation consisting of maintaining the node in the state that is the opposite of its T-LGL state, e.g. knocking it out if it is overexpressed in the T-LGL state. We found that such control of any of 15 nodes led to the disappearance of the T-LGL steady state, leaving cell death as the only potential outcome from any initial condition. In four additional cases the probability of reaching the T-LGL state decreased dramatically, thus these nodes are also possible control

  5. Automated Measurement and Signaling Systems for the Transactional Network

    SciTech Connect

    Piette, Mary Ann; Brown, Richard; Price, Phillip; Page, Janie; Granderson, Jessica; Riess, David; Czarnecki, Stephen; Ghatikar, Girish; Lanzisera, Steven

    2013-12-31

    The Transactional Network Project is a multi-lab activity funded by the US Department of Energy?s Building Technologies Office. The project team included staff from Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory and Oak Ridge National Laboratory. The team designed, prototyped and tested a transactional network (TN) platform to support energy, operational and financial transactions between any networked entities (equipment, organizations, buildings, grid, etc.). PNNL was responsible for the development of the TN platform, with agents for this platform developed by each of the three labs. LBNL contributed applications to measure the whole-building electric load response to various changes in building operations, particularly energy efficiency improvements and demand response events. We also provide a demand response signaling agent and an agent for cost savings analysis. LBNL and PNNL demonstrated actual transactions between packaged rooftop units and the electric grid using the platform and selected agents. This document describes the agents and applications developed by the LBNL team, and associated tests of the applications.

  6. A new link between diabetes and cancer: enhanced WNT/β-catenin signaling by high glucose.

    PubMed

    García-Jiménez, Custodia; García-Martínez, Jose Manuel; Chocarro-Calvo, Ana; De la Vieja, Antonio

    2014-02-01

    Extensive epidemiological studies suggest that the diabetic population is at higher risk of site-specific cancers. The diabetes-cancer link has been hypothesized to rely on various hormonal (insulin, IGF1, adipokines), immunological (inflammation), or metabolic (hyperglycemia) characteristics of the disease and even on certain treatments. Inflammation may have an important but incompletely understood role. As a growth factor, insulin directly, or indirectly through IGF1, has been considered the major link between diabetes and cancer, while high glucose has been considered as a subordinate cause. Here we discuss the evidence that supports a role for insulin/IGF1 in general in cancer, and the mechanism by which hyperglycemia may enhance the appearance, growth and survival of diabetes-associated cancers. High glucose triggers several direct and indirect mechanisms that cooperate to promote cancer cell proliferation, migration, invasion and immunological escape. In particular, high glucose enhancement of WNT/β-catenin signaling in cancer cells promotes proliferation, survival and senescence bypass, and represents a previously unrecognized direct mechanism linking diabetes-associated hyperglycemia to cancer. Increased glucose uptake is a hallmark of tumor cells and may ensure enhanced WNT signaling for continuous proliferation. Mechanistically, high glucose unbalances acetylation through increased p300 acetyl transferase and decreased sirtuin 1 deacetylase activity, leading to β-catenin acetylation at lysine K354, a requirement for nuclear accumulation and transcriptional activation of WNT-target genes. The impact of high glucose on β-catenin illustrates the remodeling of cancer-associated signaling pathways by metabolites. Metabolic remodeling of cancer-associated signaling will receive much research attention in the coming years. Future epidemiological studies may be guided and complemented by the identification of these metabolic interplays. Together, these

  7. Joint transfer of time and frequency signals and multi-point synchronization via fiber network

    NASA Astrophysics Data System (ADS)

    Nan, Cheng; Wei, Chen; Qin, Liu; Dan, Xu; Fei, Yang; You-Zhen, Gui; Hai-Wen, Cai

    2016-01-01

    A system of jointly transferring time signals with a rate of 1 pulse per second (PPS) and frequency signals of 10 MHz via a dense wavelength division multiplex-based (DWDM) fiber is demonstrated in this paper. The noises of the fiber links are suppressed and compensated for by a controlled fiber delay line. A method of calibrating and characterizing time is described. The 1PPS is synchronized by feed-forward calibrating the fiber delays precisely. The system is experimentally examined via a 110 km spooled fiber in laboratory. The frequency stabilities of the user end with compensation are 1.8×10-14 at 1 s and 2.0×10-17 at 104 s average time. The calculated uncertainty of time synchronization is 13.1 ps, whereas the direct measurement of the uncertainty is 12 ps. Next, the frequency and 1PPS are transferred via a metropolitan area optical fiber network from one central site to two remote sites with distances of 14 km and 110 km. The frequency stabilities of 14 km link reach 3.0×10-14 averaged in 1 s and 1.4×10-17 in 104 s respectively; and the stabilities of 110 km link are 8.3×10-14 and 1.7×10-17, respectively. The accuracies of synchronization are estimated to be 12.3 ps for the 14 km link and 13.1 ps for the 110 km link, respectively. Project supported by the National Natural Science Foundation of China (Grant No. 61405227).

  8. Message passing theory for percolation models on multiplex networks with link overlap

    NASA Astrophysics Data System (ADS)

    Cellai, Davide; Dorogovtsev, Sergey N.; Bianconi, Ginestra

    2016-09-01

    Multiplex networks describe a large variety of complex systems, including infrastructures, transportation networks, and biological systems. Most of these networks feature a significant link overlap. It is therefore of particular importance to characterize the mutually connected giant component in these networks. Here we provide a message passing theory for characterizing the percolation transition in multiplex networks with link overlap and an arbitrary number of layers M . Specifically we propose and compare two message passing algorithms that generalize the algorithm widely used to study the percolation transition in multiplex networks without link overlap. The first algorithm describes a directed percolation transition and admits an epidemic spreading interpretation. The second algorithm describes the emergence of the mutually connected giant component, that is the percolation transition, but does not preserve the epidemic spreading interpretation. We obtain the phase diagrams for the percolation and directed percolation transition in simple representative cases. We demonstrate that for the same multiplex network structure, in which the directed percolation transition has nontrivial tricritical points, the percolation transition has a discontinuous phase transition, with the exception of the trivial case in which all the layers completely overlap.

  9. Space Link Extension Protocol Emulation for High-Throughput, High-Latency Network Connections

    NASA Technical Reports Server (NTRS)

    Tchorowski, Nicole; Murawski, Robert

    2014-01-01

    New space missions require higher data rates and new protocols to meet these requirements. These high data rate space communication links push the limitations of not only the space communication links, but of the ground communication networks and protocols which forward user data to remote ground stations (GS) for transmission. The Consultative Committee for Space Data Systems, (CCSDS) Space Link Extension (SLE) standard protocol is one protocol that has been proposed for use by the NASA Space Network (SN) Ground Segment Sustainment (SGSS) program. New protocol implementations must be carefully tested to ensure that they provide the required functionality, especially because of the remote nature of spacecraft. The SLE protocol standard has been tested in the NASA Glenn Research Center's SCENIC Emulation Lab in order to observe its operation under realistic network delay conditions. More specifically, the delay between then NASA Integrated Services Network (NISN) and spacecraft has been emulated. The round trip time (RTT) delay for the continental NISN network has been shown to be up to 120ms; as such the SLE protocol was tested with network delays ranging from 0ms to 200ms. Both a base network condition and an SLE connection were tested with these RTT delays, and the reaction of both network tests to the delay conditions were recorded. Throughput for both of these links was set at 1.2Gbps. The results will show that, in the presence of realistic network delay, the SLE link throughput is significantly reduced while the base network throughput however remained at the 1.2Gbps specification. The decrease in SLE throughput has been attributed to the implementation's use of blocking calls. The decrease in throughput is not acceptable for high data rate links, as the link requires constant data a flow in order for spacecraft and ground radios to stay synchronized, unless significant data is queued a the ground station. In cases where queuing the data is not an option

  10. Pattern recognition for electroencephalographic signals based on continuous neural networks.

    PubMed

    Alfaro-Ponce, M; Argüelles, A; Chairez, I

    2016-07-01

    This study reports the design and implementation of a pattern recognition algorithm to classify electroencephalographic (EEG) signals based on artificial neural networks (NN) described by ordinary differential equations (ODEs). The training method for this kind of continuous NN (CNN) was developed according to the Lyapunov theory stability analysis. A parallel structure with fixed weights was proposed to perform the classification stage. The pattern recognition efficiency was validated by two methods, a generalization-regularization and a k-fold cross validation (k=5). The classifier was applied on two different databases. The first one was made up by signals collected from patients suffering of epilepsy and it is divided in five different classes. The second database was made up by 90 single EEG trials, divided in three classes. Each class corresponds to a different visual evoked potential. The pattern recognition algorithm achieved a maximum correct classification percentage of 97.2% using the information of the entire database. This value was similar to some results previously reported when this database was used for testing pattern classification. However, these results were obtained when only two classes were considered for the testing. The result reported in this study used the whole set of signals (five different classes). In comparison with similar pattern recognition methods that even considered less number of classes, the proposed CNN proved to achieve the same or even better correct classification results.

  11. Pattern recognition for electroencephalographic signals based on continuous neural networks.

    PubMed

    Alfaro-Ponce, M; Argüelles, A; Chairez, I

    2016-07-01

    This study reports the design and implementation of a pattern recognition algorithm to classify electroencephalographic (EEG) signals based on artificial neural networks (NN) described by ordinary differential equations (ODEs). The training method for this kind of continuous NN (CNN) was developed according to the Lyapunov theory stability analysis. A parallel structure with fixed weights was proposed to perform the classification stage. The pattern recognition efficiency was validated by two methods, a generalization-regularization and a k-fold cross validation (k=5). The classifier was applied on two different databases. The first one was made up by signals collected from patients suffering of epilepsy and it is divided in five different classes. The second database was made up by 90 single EEG trials, divided in three classes. Each class corresponds to a different visual evoked potential. The pattern recognition algorithm achieved a maximum correct classification percentage of 97.2% using the information of the entire database. This value was similar to some results previously reported when this database was used for testing pattern classification. However, these results were obtained when only two classes were considered for the testing. The result reported in this study used the whole set of signals (five different classes). In comparison with similar pattern recognition methods that even considered less number of classes, the proposed CNN proved to achieve the same or even better correct classification results. PMID:27131469

  12. Remote facility sharing with ATM networks [PC based ATM Link Delay Simulator (LDS)]. Final report

    SciTech Connect

    Kung, H. T.

    2001-06-01

    The ATM Link Delay Simulator (LDS) adds propagation delay to the ATM link on which it is installed, to allow control of link propagation delay in network protocol experiments simulating an adjustable piece of optical fiber. Our LDS simulates a delay of between 1.5 and 500 milliseconds and is built with commodity PC hardware, only the ATM network interface card is not generally available. Our implementation is special in that it preserves the exact spacing of ATM data cells a feature that requires sustained high performance. Our implementation shows that applications demanding sustained high performance are possible on commodity PC hardware. This illustrates the promise that PC hardware has for adaptability to demanding specialized testing of high speed network.

  13. A New Signaling Architecture THREP with Autonomous Radio-Link Control for Wireless Communications Systems

    NASA Astrophysics Data System (ADS)

    Hirono, Masahiko; Nojima, Toshio

    This paper presents a new signaling architecture for radio-access control in wireless communications systems. Called THREP (for THREe-phase link set-up Process), it enables systems with low-cost configurations to provide tetherless access and wide-ranging mobility by using autonomous radio-link controls for fast cell searching and distributed call management. A signaling architecture generally consists of a radio-access part and a service-entity-access part. In THREP, the latter part is divided into two steps: preparing a communication channel, and sustaining it. Access control in THREP is thus composed of three separated parts, or protocol phases. The specifications of each phase are determined independently according to system requirements. In the proposed architecture, the first phase uses autonomous radio-link control because we want to construct low-power indoor wireless communications systems. Evaluation of channel usage efficiency and hand-over loss probability in the personal handy-phone system (PHS) shows that THREP makes the radio-access sub-system operations in a practical application model highly efficient, and the results of a field experiment show that THREP provides sufficient protection against severe fast CNR degradation in practical indoor propagation environments.

  14. LQER: A Link Quality Estimation based Routing for Wireless Sensor Networks

    PubMed Central

    Chen, Jiming; Lin, Ruizhong; Li, Yanjun; Sun, Youxian

    2008-01-01

    Routing protocols are crucial to self-organize wireless sensor networks (WSNs), which have been widely studied in recent years. For some specific applications, both energy aware and reliable data transmission need to be considered together. Historical link status should be captured and taken into account in making data forwarding decisions to achieve the data reliability and energy efficiency tradeoff. In this paper, a dynamic window concept (m, k) is presented to record the link historical information and a link quality estimation based routing protocol (LQER) are proposed, which integrates the approach of minimum hop field and (m, k). The performance of LQER is evaluated by extensive simulation experiments to be more energy-aware, with lower loss rate and better scalability than MHFR [1] and MCR [2]. Thus the WSNs with LQER get longer lifetime of networks and better link quality.

  15. Linking social and pathogen transmission networks using microbial genetics in giraffe (Giraffa camelopardalis).

    PubMed

    VanderWaal, Kimberly L; Atwill, Edward R; Isbell, Lynne A; McCowan, Brenda

    2014-03-01

    Although network analysis has drawn considerable attention as a promising tool for disease ecology, empirical research has been hindered by limitations in detecting the occurrence of pathogen transmission (who transmitted to whom) within social networks. Using a novel approach, we utilize the genetics of a diverse microbe, Escherichia coli, to infer where direct or indirect transmission has occurred and use these data to construct transmission networks for a wild giraffe population (Giraffe camelopardalis). Individuals were considered to be a part of the same transmission chain and were interlinked in the transmission network if they shared genetic subtypes of E. coli. By using microbial genetics to quantify who transmits to whom independently from the behavioural data on who is in contact with whom, we were able to directly investigate how the structure of contact networks influences the structure of the transmission network. To distinguish between the effects of social and environmental contact on transmission dynamics, the transmission network was compared with two separate contact networks defined from the behavioural data: a social network based on association patterns, and a spatial network based on patterns of home-range overlap among individuals. We found that links in the transmission network were more likely to occur between individuals that were strongly linked in the social network. Furthermore, individuals that had more numerous connections or that occupied 'bottleneck' positions in the social network tended to occupy similar positions in the transmission network. No similar correlations were observed between the spatial and transmission networks. This indicates that an individual's social network position is predictive of transmission network position, which has implications for identifying individuals that function as super-spreaders or transmission bottlenecks in the population. These results emphasize the importance of association patterns in

  16. Is the kinetoplast DNA a percolating network of linked rings at its critical point?

    NASA Astrophysics Data System (ADS)

    Michieletto, Davide; Marenduzzo, Davide; Orlandini, Enzo

    2015-05-01

    In this work we present a computational study of the kinetoplast genome, modelled as a large number of semiflexible unknotted loops, which are allowed to link with each other. As the DNA density increases, the systems shows a percolation transition between a gas of unlinked rings and a network of linked loops which spans the whole system. Close to the percolation transition, we find that the mean valency of the network, i.e. the average number of loops which are linked to any one loop, is around three, as found experimentally for the kinetoplast DNA (kDNA). Even more importantly, by simulating the digestion of the network by a restriction enzyme, we show that the distribution of oligomers, i.e. structures formed by a few loops which remain linked after digestion, quantitatively matches experimental data obtained from gel electrophoresis, provided that the density is, once again, close to the percolation transition. With respect to previous work, our analysis builds on a reduced number of assumptions, yet can still fully explain the experimental data. Our findings suggest that the kDNA can be viewed as a network of linked loops positioned very close to the percolation transition, and we discuss the possible biological implications of this remarkable fact.

  17. Space Link Extension (SLE) Emulation for High-Throughput Network Communication

    NASA Technical Reports Server (NTRS)

    Murawski, Robert W.; Tchorowski, Nicole; Golden, Bert

    2014-01-01

    As the data rate requirements for space communications increases, significant stress is placed not only on the wireless satellite communication links, but also on the ground networks which forward data from end-users to remote ground stations. These wide area network (WAN) connections add delay and jitter to the end-to-end satellite communication link, effects which can have significant impacts on the wireless communication link. It is imperative that any ground communication protocol can react to these effects such that the ground network does not become a bottleneck in the communication path to the satellite. In this paper, we present our SCENIC Emulation Lab testbed which was developed to test the CCSDS SLE protocol implementations proposed for use on future NASA communication networks. Our results show that in the presence of realistic levels of network delay, high-throughput SLE communication links can experience significant data rate throttling. Based on our observations, we present some insight into why this data throttling happens, and trace the probable issue back to non-optimal blocking communication which is sup-ported by the CCSDS SLE API recommended practices. These issues were presented as well to the SLE implementation developers which, based on our reports, developed a new release for SLE which we show fixes the SLE blocking issue and greatly improves the protocol throughput. In this paper, we also discuss future developments for our end-to-end emulation lab and how these improvements can be used to develop and test future space communication technologies.

  18. Effect of link oriented self-healing on resilience of networks

    NASA Astrophysics Data System (ADS)

    Shang, Yilun

    2016-08-01

    Many real, complex systems, such as the human brain and skin with their biological networks or intelligent material systems consisting of composite functional liquids, exhibit a noticeable capability of self-healing. Here, we study a network model with arbitrary degree distributions possessing natural link oriented recovery mechanisms, whereby a failed link can be recovered if its two end nodes maintain a sufficient proportion of functional links. These mechanisms are pertinent for many spontaneous healing and manual repair phenomena, interpolating smoothly between complete healing and no healing scenarios. We show that the self-healing strategies have profound impact on resilience of homogeneous and heterogeneous networks employing a percolation threshold, fraction of giant cluster, and link robustness index. The self-healing effect induces distinct resilience characteristics for scale-free networks under random failures and intentional attacks, and a resilience crossover has been observed at certain level of self-healing. Our work highlights the significance of understanding the competition between healing and collapsing in the resilience of complex networks.

  19. The expanding regulatory network of STING-mediated signaling.

    PubMed

    Surpris, Guy; Poltorak, Alexander

    2016-08-01

    The identification and characterization of DNA-sensing pathways has been a subject of intensive investigation for the last decade. This interest, in part, is supported by the fact that the main outcome of DNA-responses is production of type I interferon (IFN-I), which, if produced in excessive amounts, leads to various pathologies. STING (stimulator of interferon genes) is positioned in the center of these responses and is activated either via direct sensing of second messengers or via interaction with upstream sensors of dsDNA. STING mediates responses to pathogens as well as host-derived DNA and is, therefore, linked to various autoimmune diseases, cancer predisposition and ageing. Recent mouse models of DNA damage showed the adaptor STING to be crucial for heightened resting levels of IFN-I. In this review, we will focus on recent advances in understanding the regulation of STING-signaling and identification of its novel components. PMID:27414485

  20. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis.

    PubMed

    Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

    2016-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities.

  1. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis

    PubMed Central

    Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

    2016-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities. PMID:27104948

  2. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis.

    PubMed

    Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

    2016-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities. PMID:27104948

  3. Interacting inflammatory and growth factor signals underlie the obesity-cancer link.

    PubMed

    Lashinger, Laura M; Ford, Nikki A; Hursting, Stephen D

    2014-02-01

    The prevalence of obesity, an established risk factor for many chronic diseases (including diabetes, cardiovascular disease, stroke, and several types of cancer), has risen steadily for the past several decades in the United States and many parts of the world. Today, ∼70% of U.S. adults and 30% of children are at an unhealthy weight. The evidence on key biologic mechanisms underlying the obesity-cancer link, with an emphasis on local and systemic inflammatory processes and their crosstalk with energy-sensing growth factor signaling pathways, will be discussed. Understanding the influence and underlying mechanisms of obesity on chronic inflammation and cancer will identify promising mechanistic targets and strategies for disrupting the obesity-cancer link and provide important lessons regarding the associations between obesity, inflammation, and other chronic diseases.

  4. Growth signals, inflammation, and vascular perturbations: mechanistic links between obesity, metabolic syndrome, and cancer.

    PubMed

    Hursting, Stephen D; Hursting, Marcie J

    2012-08-01

    Nearly 35% of adults and 20% of children in the United States are obese, defined as a body mass index ≥ 30 kg/m(2). Obesity, which is accompanied by metabolic dysregulation often manifesting in the metabolic syndrome, is an established risk factor for many cancers. Within the growth-promoting, proinflammatory environment of the obese state, cross talk between macrophages, adipocytes, and epithelial cells occurs via obesity-associated hormones, cytokines, and other mediators that may enhance cancer risk and progression. This review synthesizes the evidence on key biological mechanisms underlying the obesity-cancer link, with particular emphasis on obesity-associated enhancements in growth factor signaling, inflammation, and vascular integrity processes. These interrelated pathways represent possible mechanistic targets for disrupting the obesity-cancer link.

  5. Signal Transduction at the Single-Cell Level: Approaches to Study the Dynamic Nature of Signaling Networks.

    PubMed

    Handly, L Naomi; Yao, Jason; Wollman, Roy

    2016-09-25

    Signal transduction, or how cells interpret and react to external events, is a fundamental aspect of cellular function. Traditional study of signal transduction pathways involves mapping cellular signaling pathways at the population level. However, population-averaged readouts do not adequately illuminate the complex dynamics and heterogeneous responses found at the single-cell level. Recent technological advances that observe cellular response, computationally model signaling pathways, and experimentally manipulate cells now enable studying signal transduction at the single-cell level. These studies will enable deeper insights into the dynamic nature of signaling networks.

  6. The Yeast Sks1p Kinase Signaling Network Regulates Pseudohyphal Growth and Glucose Response

    PubMed Central

    Johnson, Cole; Kweon, Hye Kyong; Sheidy, Daniel; Shively, Christian A.; Mellacheruvu, Dattatreya; Nesvizhskii, Alexey I.; Andrews, Philip C.; Kumar, Anuj

    2014-01-01

    The yeast Saccharomyces cerevisiae undergoes a dramatic growth transition from its unicellular form to a filamentous state, marked by the formation of pseudohyphal filaments of elongated and connected cells. Yeast pseudohyphal growth is regulated by signaling pathways responsive to reductions in the availability of nitrogen and glucose, but the molecular link between pseudohyphal filamentation and glucose signaling is not fully understood. Here, we identify the glucose-responsive Sks1p kinase as a signaling protein required for pseudohyphal growth induced by nitrogen limitation and coupled nitrogen/glucose limitation. To identify the Sks1p signaling network, we applied mass spectrometry-based quantitative phosphoproteomics, profiling over 900 phosphosites for phosphorylation changes dependent upon Sks1p kinase activity. From this analysis, we report a set of novel phosphorylation sites and highlight Sks1p-dependent phosphorylation in Bud6p, Itr1p, Lrg1p, Npr3p, and Pda1p. In particular, we analyzed the Y309 and S313 phosphosites in the pyruvate dehydrogenase subunit Pda1p; these residues are required for pseudohyphal growth, and Y309A mutants exhibit phenotypes indicative of impaired aerobic respiration and decreased mitochondrial number. Epistasis studies place SKS1 downstream of the G-protein coupled receptor GPR1 and the G-protein RAS2 but upstream of or at the level of cAMP-dependent PKA. The pseudohyphal growth and glucose signaling transcription factors Flo8p, Mss11p, and Rgt1p are required to achieve wild-type SKS1 transcript levels. SKS1 is conserved, and deletion of the SKS1 ortholog SHA3 in the pathogenic fungus Candida albicans results in abnormal colony morphology. Collectively, these results identify Sks1p as an important regulator of filamentation and glucose signaling, with additional relevance towards understanding stress-responsive signaling in C. albicans. PMID:24603354

  7. Autophagy signal transduction by ATG proteins: from hierarchies to networks.

    PubMed

    Wesselborg, Sebastian; Stork, Björn

    2015-12-01

    Autophagy represents an intracellular degradation process which is involved in both cellular homeostasis and disease settings. In the last two decades, the molecular machinery governing this process has been characterized in detail. To date, several key factors regulating this intracellular degradation process have been identified. The so-called autophagy-related (ATG) genes and proteins are central to this process. However, several additional molecules contribute to the outcome of an autophagic response. Several review articles describing the molecular process of autophagy have been published in the recent past. In this review article we would like to add the most recent findings to this knowledge, and to give an overview of the network character of the autophagy signaling machinery. PMID:26390974

  8. Signal integration by chloroplast phosphorylation networks: an update

    PubMed Central

    Schönberg, Anna; Baginsky, Sacha

    2012-01-01

    Forty years after the initial discovery of light-dependent protein phosphorylation at the thylakoid membrane system, we are now beginning to understand the roles of chloroplast phosphorylation networks in their function to decode and mediate information on the metabolic status of the organelle to long-term adaptations in plastid and nuclear gene expression. With the help of genetics and functional genomics tools, chloroplast kinases and several hundred phosphoproteins were identified that now await detailed functional characterization. The regulation and the target protein spectrum of some kinases are understood, but this information is fragmentary with respect to kinase and target protein crosstalk in a changing environment. In this review, we will highlight the most recent advances in the field and discuss approaches that might lead to a comprehensive understanding of plastid signal integration by protein phosphorylation. PMID:23181067

  9. An intimate link: two-component signal transduction systems and metal transport systems in bacteria

    PubMed Central

    Singh, Kamna; Senadheera, Dilani B; Cvitkovitch, Dennis G

    2014-01-01

    Bacteria have evolved various strategies to contend with high concentrations of environmental heavy metal ions for rapid, adaptive responses to maintain cell viability. Evidence gathered in the past two decades suggests that bacterial two-component signal transduction systems (TCSTSs) are intimately involved in monitoring cation accumulation, and can regulate the expression of related metabolic and virulence genes to elicit adaptive responses to changes in the concentration of these ions. Using examples garnered from recent studies, we summarize the cross-regulatory relationships between metal ions and TCSTSs. We present evidence of how bacterial TCSTSs modulate metal ion homeostasis and also how metal ions, in turn, function to control the activities of these signaling systems linked with bacterial survival and virulence. PMID:25437189

  10. Ku-band signal design study. [for space shuttle orbiter communication links

    NASA Technical Reports Server (NTRS)

    Lindsey, W. L.; Woo, K. T.

    1977-01-01

    The acquisition/tracking performance of a practical squaring loop in which the times two multiplier is mechanized as a limiter/multiplier combination is evaluated. This squaring approach serves to produce the absolute value of the arriving signal as opposed to the perfect square law action which is required in order to render acquisition and tracking performance equivalent to that of a Costas loop. The Ku-Band orbiter signal design for the forward link is assessed. Acquisition time results and acquisition and tracking thresholds are summarized. A tradeoff study which pertains to bit synchronization techniques for the high rate Ku-Band channel is included and an optimum selection is made based upon the appropriate design constraints.

  11. Network coding based joint signaling and dynamic bandwidth allocation scheme for inter optical network unit communication in passive optical networks

    NASA Astrophysics Data System (ADS)

    Wei, Pei; Gu, Rentao; Ji, Yuefeng

    2014-06-01

    As an innovative and promising technology, network coding has been introduced to passive optical networks (PON) in recent years to support inter optical network unit (ONU) communication, yet the signaling process and dynamic bandwidth allocation (DBA) in PON with network coding (NC-PON) still need further study. Thus, we propose a joint signaling and DBA scheme for efficiently supporting differentiated services of inter ONU communication in NC-PON. In the proposed joint scheme, the signaling process lays the foundation to fulfill network coding in PON, and it can not only avoid the potential threat to downstream security in previous schemes but also be suitable for the proposed hybrid dynamic bandwidth allocation (HDBA) scheme. In HDBA, a DBA cycle is divided into two sub-cycles for applying different coding, scheduling and bandwidth allocation strategies to differentiated classes of services. Besides, as network traffic load varies, the entire upstream transmission window for all REPORT messages slides accordingly, leaving the transmission time of one or two sub-cycles to overlap with the bandwidth allocation calculation time at the optical line terminal (the OLT), so that the upstream idle time can be efficiently eliminated. Performance evaluation results validate that compared with the existing two DBA algorithms deployed in NC-PON, HDBA demonstrates the best quality of service (QoS) support in terms of delay for all classes of services, especially guarantees the end-to-end delay bound of high class services. Specifically, HDBA can eliminate queuing delay and scheduling delay of high class services, reduce those of lower class services by at least 20%, and reduce the average end-to-end delay of all services over 50%. Moreover, HDBA also achieves the maximum delay fairness between coded and uncoded lower class services, and medium delay fairness for high class services.

  12. BioNetLink - an architecture for working with network data.

    PubMed

    Klapperstück, Matthias; Schreiber, Falk

    2014-01-01

    The visualization of biological data gained increasing importance in the last years. There is a large number of methods and software tools available that visualize biological data including the combination of measured experimental data and biological networks. With growing size of networks their handling and exploration becomes a challenging task for the user. In addition, scientists also have an interest in not just investigating a single kind of network, but on the combination of different types of networks, such as metabolic, gene regulatory and protein interaction networks. Therefore, fast access, abstract and dynamic views, and intuitive exploratory methods should be provided to search and extract information from the networks. This paper will introduce a conceptual framework for handling and combining multiple network sources that enables abstract viewing and exploration of large data sets including additional experimental data. It will introduce a three-tier structure that links network data to multiple network views, discuss a proof of concept implementation, and shows a specific visualization method for combining metabolic and gene regulatory networks in an example. PMID:24980619

  13. Disentangling information flow in the Ras-cAMP signaling network.

    PubMed

    Carter, Gregory W; Rupp, Steffen; Fink, Gerald R; Galitski, Timothy

    2006-04-01

    The perturbation of signal-transduction molecules elicits genomic-expression effects that are typically neither restricted to a small set of genes nor uniform. Instead there are broad, varied, and complex changes in expression across the genome. These observations suggest that signal transduction is not mediated by isolated pathways of information flow to distinct groups of genes in the genome. Rather, multiple entangled paths of information flow influence overlapping sets of genes. Using the Ras-cAMP pathway in Saccharomyces cerevisiae as a model system, we perturbed key pathway elements and collected genomic-expression data. Singular value decomposition was applied to separate the genome-wide transcriptional response into weighted expression components exhibited by overlapping groups of genes. Molecular interaction data were integrated to connect gene groups to perturbed signaling elements. The resulting series of linked subnetworks maps multiple putative pathways of information flow through a dense signaling network, and provides a set of testable hypotheses for complex gene-expression effects across the genome.

  14. Phytochrome and retrograde signalling pathways converge to antagonistically regulate a light-induced transcriptional network

    PubMed Central

    Martín, Guiomar; Leivar, Pablo; Ludevid, Dolores; Tepperman, James M.; Quail, Peter H.; Monte, Elena

    2016-01-01

    Plastid-to-nucleus retrograde signals emitted by dysfunctional chloroplasts impact photomorphogenic development, but the molecular link between retrograde- and photosensory-receptor signalling has remained unclear. Here, we show that the phytochrome and retrograde signalling (RS) pathways converge antagonistically to regulate the expression of the nuclear-encoded transcription factor GLK1, a key regulator of a light-induced transcriptional network central to photomorphogenesis. GLK1 gene transcription is directly repressed by PHYTOCHROME-INTERACTING FACTOR (PIF)-class bHLH transcription factors in darkness, but light-activated phytochrome reverses this activity, thereby inducing expression. Conversely, we show that retrograde signals repress this induction by a mechanism independent of PIF mediation. Collectively, our data indicate that light at moderate levels acts through the plant's nuclear-localized sensory-photoreceptor system to induce appropriate photomorphogenic development, but at excessive levels, sensed through the separate plastid-localized RS system, acts to suppress such development, thus providing a mechanism for protection against photo-oxidative damage by minimizing the tissue exposure to deleterious radiation. PMID:27150909

  15. NMR analysis of a stress response metabolic signaling network.

    PubMed

    Zhang, Bo; Halouska, Steven; Schiaffo, Charles E; Sadykov, Marat R; Somerville, Greg A; Powers, Robert

    2011-08-01

    We previously hypothesized that Staphylococcus epidermidis senses a diverse set of environmental and nutritional factors associated with biofilm formation through a modulation in the activity of the tricarboxylic acid (TCA) cycle. Herein, we report our further investigation of the impact of additional environmental stress factors on TCA cycle activity and provide a detailed description of our NMR methodology. S. epidermidis wild-type strain 1457 was treated with stressors that are associated with biofilm formation, a sublethal dose of tetracycline, 5% NaCl, 2% glucose, and autoinducer-2 (AI-2). As controls and to integrate our current data with our previous study, 4% ethanol stress and iron-limitation were also used. Consistent with our prior observations, the effect of many environmental stress factors on the S. epidermidis metabolome was essentially identical to the effect of TCA cycle inactivation in the aconitase mutant strain 1457-acnA::tetM. A detailed quantitative analysis of metabolite concentration changes using 2D (1)H-(13)C HSQC and (1)H-(1)H TOCSY spectra identified a network of 37 metabolites uniformly affected by the stressors and TCA cycle inactivation. We postulate that the TCA cycle acts as the central pathway in a metabolic signaling network.

  16. NMR analysis of a stress response metabolic signaling network.

    PubMed

    Zhang, Bo; Halouska, Steven; Schiaffo, Charles E; Sadykov, Marat R; Somerville, Greg A; Powers, Robert

    2011-08-01

    We previously hypothesized that Staphylococcus epidermidis senses a diverse set of environmental and nutritional factors associated with biofilm formation through a modulation in the activity of the tricarboxylic acid (TCA) cycle. Herein, we report our further investigation of the impact of additional environmental stress factors on TCA cycle activity and provide a detailed description of our NMR methodology. S. epidermidis wild-type strain 1457 was treated with stressors that are associated with biofilm formation, a sublethal dose of tetracycline, 5% NaCl, 2% glucose, and autoinducer-2 (AI-2). As controls and to integrate our current data with our previous study, 4% ethanol stress and iron-limitation were also used. Consistent with our prior observations, the effect of many environmental stress factors on the S. epidermidis metabolome was essentially identical to the effect of TCA cycle inactivation in the aconitase mutant strain 1457-acnA::tetM. A detailed quantitative analysis of metabolite concentration changes using 2D (1)H-(13)C HSQC and (1)H-(1)H TOCSY spectra identified a network of 37 metabolites uniformly affected by the stressors and TCA cycle inactivation. We postulate that the TCA cycle acts as the central pathway in a metabolic signaling network. PMID:21692534

  17. xiNET: Cross-link Network Maps With Residue Resolution*

    PubMed Central

    Combe, Colin W.; Fischer, Lutz; Rappsilber, Juri

    2015-01-01

    xiNET is a visualization tool for exploring cross-linking/mass spectrometry results. The interactive maps of the cross-link network that it generates are a type of node-link diagram. In these maps xiNET displays: (1) residue resolution positional information including linkage sites and linked peptides; (2) all types of cross-linking reaction product; (3) ambiguous results; and, (4) additional sequence information such as domains. xiNET runs in a browser and exports vector graphics which can be edited in common drawing packages to create publication quality figures. Availability: xiNET is open source, released under the Apache version 2 license. Results can be viewed by uploading data to http://crosslinkviewer.org/ or by downloading the software from http://github.com/colin-combe/crosslink-viewer and running it locally. PMID:25648531

  18. Suppression of optical beat interference-noise in orthogonal frequency division multiple access-passive optical network link using self-homodyne balanced detection

    NASA Astrophysics Data System (ADS)

    Won, Yong-Yuk; Jung, Sang-Min; Han, Sang-Kook

    2014-08-01

    A new technique, which reduces optical beat interference (OBI) noise in orthogonal frequency division multiple access-passive optical network (OFDMA-PON) links, is proposed. A self-homodyne balanced detection, which uses a single laser for the optical line terminal (OLT) as well as for the optical network unit (ONU), reduces OBI noise and also improves the signal to noise ratio (SNR) of the discrete multi-tone (DMT) signal. The proposed scheme is verified by transmitting quadrature phase shift keying (QPSK)-modulated DMT signal over a 20-km single mode fiber. The optical signal to noise ratio (OSNR), that is required for BER of 10-5, is reduced by 2 dB in the balanced detection compared with a single channel due to the cancellation of OBI noise in conjunction with the local laser.

  19. Dominant Enhancers of Egfr in Drosophila Melanogaster: Genetic Links between the Notch and Egfr Signaling Pathways

    PubMed Central

    Price, J. V.; Savenye, E. D.; Lum, D.; Breitkreutz, A.

    1997-01-01

    The Drosophila epidermal growth factor receptor (EGFR) is a key component of a complex signaling pathway that participates in multiple developmental processes. We have performed an F(1) screen for mutations that cause dominant enhancement of wing vein phenotypes associated with mutations in Egfr. With this screen, we have recovered mutations in Hairless (H), vein, groucho (gro), and three apparently novel loci. All of the E(Egfr)s we have identified show dominant interactions in transheterozygous combinations with each other and with alleles of N or Su(H), suggesting that they are involved in cross-talk between the N and EGFR signaling pathways. Further examination of the phenotypic interactions between Egfr, H, and gro revealed that reductions in Egfr activity enhanced both the bristle loss associated with H mutations, and the bristle hyperplasia and ocellar hypertrophy associated with gro mutations. Double mutant combinations of Egfr and gro hypomorphic alleles led to the formation of ectopic compound eyes in a dosage sensitive manner. Our findings suggest that these E(Egfr)s represent links between the Egfr and Notch signaling pathways, and that Egfr activity can either promote or suppress Notch signaling, depending on its developmental context. PMID:9383058

  20. The PAK system links Rho GTPase signaling to thrombin-mediated platelet activation

    PubMed Central

    Baker, Sandra M.; Loren, Cassandra P.; Haley, Kristina M.; Itakura, Asako; Pang, Jiaqing; Greenberg, Daniel L.; David, Larry L.; Manser, Ed; Chernoff, Jonathan; McCarty, Owen J. T.

    2013-01-01

    Regulation of the platelet actin cytoskeleton by the Rho family of small GTPases is essential for the proper maintenance of hemostasis. However, little is known about how intracellular platelet activation from Rho GTPase family members, including Rac, Cdc42, and Rho, translate into changes in platelet actin structures. To better understand how Rho family GTPases coordinate platelet activation, we identified platelet proteins associated with Rac1, a Rho GTPase family member, and actin regulatory protein essential for platelet hemostatic function. Mass spectrometry analysis revealed that upon platelet activation with thrombin, Rac1 associates with a set of effectors of the p21-activated kinases (PAKs), including GIT1, βPIX, and guanine nucleotide exchange factor GEFH1. Platelet activation by thrombin triggered the PAK-dependent phosphorylation of GIT1, GEFH1, and other PAK effectors, including LIMK1 and Merlin. PAK was also required for the thrombin-mediated activation of the MEK/ERK pathway, Akt, calcium signaling, and phosphatidylserine (PS) exposure. Inhibition of PAK signaling prevented thrombin-induced platelet aggregation and blocked platelet focal adhesion and lamellipodia formation in response to thrombin. Together, these results demonstrate that the PAK signaling system is a key orchestrator of platelet actin dynamics, linking Rho GTPase activation downstream of thrombin stimulation to PAK effector function, MAP kinase activation, calcium signaling, and PS exposure in platelets. PMID:23784547

  1. The distribution of highly stable millimeter-wave signals over different optical fiber links with accurate phase-correction

    NASA Astrophysics Data System (ADS)

    Liu, Zhangweiyi; Wang, Xiaocheng; Sun, Dongning; Dong, Yi; Hu, Weisheng

    2015-08-01

    We have demonstrated an optical generation of highly stable millimeter-wave signal distribution system, which transfers a 300GHz signal to two remote ends over different optical fiber links for signal stability comparison. The transmission delay variations of each fiber link caused by temperature and mechanical perturbations are compensated by high-precise phase-correction system. The residual phase noise between two remote end signals is detected by dual-heterodyne phase error transfer and reaches -46dBc/Hz at 1 Hz frequency offset from the carrier. The relative instability is 8×10-17 at 1000s averaging time.

  2. Effect of link margin and frequency granularity on the performance of a flexgrid optical network.

    PubMed

    Mitra, Abhijit; Lord, Andrew; Kar, Subrat; Wright, Paul

    2014-01-13

    We show how dynamically adjustable modulation formats can be used to reduce link margins in flexgrid networks, reverting to lower order QAM due to reduced OSNR, if ageing occurs. Spectral savings amount to as much as 63% gain in capacity across a network using 64QAM with a fine frequency granularity of 6.25 GHz, with variable baud rate transponder. Further, a fixed baud rate, demand multiplexed transponder with adaptive modulation has been suggested. These transponders provide twice as much network capacity as compared to widely used fixed baud rate transponders operating at fixed grid of 50 GHz. PMID:24514963

  3. Effect of link margin and frequency granularity on the performance of a flexgrid optical network.

    PubMed

    Mitra, Abhijit; Lord, Andrew; Kar, Subrat; Wright, Paul

    2014-01-13

    We show how dynamically adjustable modulation formats can be used to reduce link margins in flexgrid networks, reverting to lower order QAM due to reduced OSNR, if ageing occurs. Spectral savings amount to as much as 63% gain in capacity across a network using 64QAM with a fine frequency granularity of 6.25 GHz, with variable baud rate transponder. Further, a fixed baud rate, demand multiplexed transponder with adaptive modulation has been suggested. These transponders provide twice as much network capacity as compared to widely used fixed baud rate transponders operating at fixed grid of 50 GHz.

  4. Integrative Signaling Networks of Membrane Guanylate Cyclases: Biochemistry and Physiology

    PubMed Central

    Sharma, Rameshwar K.; Duda, Teresa; Makino, Clint L.

    2016-01-01

    This monograph presents a historical perspective of cornerstone developments on the biochemistry and physiology of mammalian membrane guanylate cyclases (MGCs), highlighting contributions made by the authors and their collaborators. Upon resolution of early contentious studies, cyclic GMP emerged alongside cyclic AMP, as an important intracellular second messenger for hormonal signaling. However, the two signaling pathways differ in significant ways. In the cyclic AMP pathway, hormone binding to a G protein coupled receptor leads to stimulation or inhibition of an adenylate cyclase, whereas the cyclic GMP pathway dispenses with intermediaries; hormone binds to an MGC to affect its activity. Although the cyclic GMP pathway is direct, it is by no means simple. The modular design of the molecule incorporates regulation by ATP binding and phosphorylation. MGCs can form complexes with Ca2+-sensing subunits that either increase or decrease cyclic GMP synthesis, depending on subunit identity. In some systems, co-expression of two Ca2+ sensors, GCAP1 and S100B with ROS-GC1 confers bimodal signaling marked by increases in cyclic GMP synthesis when intracellular Ca2+ concentration rises or falls. Some MGCs monitor or are modulated by carbon dioxide via its conversion to bicarbonate. One MGC even functions as a thermosensor as well as a chemosensor; activity reaches a maximum with a mild drop in temperature. The complexity afforded by these multiple limbs of operation enables MGC networks to perform transductions traditionally reserved for G protein coupled receptors and Transient Receptor Potential (TRP) ion channels and to serve a diverse array of functions, including control over cardiac vasculature, smooth muscle relaxation, blood pressure regulation, cellular growth, sensory transductions, neural plasticity and memory. PMID:27695398

  5. Integrative Signaling Networks of Membrane Guanylate Cyclases: Biochemistry and Physiology

    PubMed Central

    Sharma, Rameshwar K.; Duda, Teresa; Makino, Clint L.

    2016-01-01

    This monograph presents a historical perspective of cornerstone developments on the biochemistry and physiology of mammalian membrane guanylate cyclases (MGCs), highlighting contributions made by the authors and their collaborators. Upon resolution of early contentious studies, cyclic GMP emerged alongside cyclic AMP, as an important intracellular second messenger for hormonal signaling. However, the two signaling pathways differ in significant ways. In the cyclic AMP pathway, hormone binding to a G protein coupled receptor leads to stimulation or inhibition of an adenylate cyclase, whereas the cyclic GMP pathway dispenses with intermediaries; hormone binds to an MGC to affect its activity. Although the cyclic GMP pathway is direct, it is by no means simple. The modular design of the molecule incorporates regulation by ATP binding and phosphorylation. MGCs can form complexes with Ca2+-sensing subunits that either increase or decrease cyclic GMP synthesis, depending on subunit identity. In some systems, co-expression of two Ca2+ sensors, GCAP1 and S100B with ROS-GC1 confers bimodal signaling marked by increases in cyclic GMP synthesis when intracellular Ca2+ concentration rises or falls. Some MGCs monitor or are modulated by carbon dioxide via its conversion to bicarbonate. One MGC even functions as a thermosensor as well as a chemosensor; activity reaches a maximum with a mild drop in temperature. The complexity afforded by these multiple limbs of operation enables MGC networks to perform transductions traditionally reserved for G protein coupled receptors and Transient Receptor Potential (TRP) ion channels and to serve a diverse array of functions, including control over cardiac vasculature, smooth muscle relaxation, blood pressure regulation, cellular growth, sensory transductions, neural plasticity and memory.

  6. Linking Transnational Logics: A Feminist Rhetorical Analysis of Public Policy Networks

    ERIC Educational Resources Information Center

    Dingo, Rebecca

    2008-01-01

    In this article, the author investigates the circulation and appropriation of representations of women in public policy. The author effectively mobilizes the metaphor of the network to examine the discursive intersections and transnational links between U.S. welfare programs and the World Bank gender mainstreaming policies. Her analysis reveals…

  7. NetLinkS: A National Professional Development Project for Networked Learner Support.

    ERIC Educational Resources Information Center

    Levy, Philippa; And Others

    1996-01-01

    Provides an overview of NetLinkS, a professional development project for networked learner support in United Kingdom higher education institutions. Topics include objectives; results of focus groups; current trends; library-based services, including user education and support for distance learners; and future plans. (Author/LRW)

  8. A Study of an Optical Lunar Surface Communications Network with High Bandwidth Direct to Earth Link

    NASA Technical Reports Server (NTRS)

    Wilson, K.; Biswas, A.; Schoolcraft, J.

    2011-01-01

    Analyzed optical DTE (direct to earth) and lunar relay satellite link analyses, greater than 200 Mbps downlink to 1-m Earth receiver and greater than 1 Mbps uplink achieved with mobile 5-cm lunar transceiver, greater than 1Gbps downlink and greater than 10 Mpbs uplink achieved with 10-cm stationary lunar transceiver, MITLL (MIT Lincoln Laboratory) 2013 LLCD (Lunar Laser Communications Demonstration) plans to demonstrate 622 Mbps downlink with 20 Mbps uplink between lunar orbiter and ground station; Identified top five technology challenges to deploying lunar optical network, Performed preliminary experiments on two of challenges: (i) lunar dust removal and (ii)DTN over optical carrier, Exploring opportunities to evaluate DTN (delay-tolerant networking) over optical link in a multi-node network e.g. Desert RATS.

  9. Link and subgraph likelihoods in random undirected networks with fixed and partially fixed degree sequences.

    PubMed

    Foster, Jacob G; Foster, David V; Grassberger, Peter; Paczuski, Maya

    2007-10-01

    The simplest null models for networks, used to distinguish significant features of a particular network from a priori expected features, are random ensembles with the degree sequence fixed by the specific network of interest. These "fixed degree sequence" (FDS) ensembles are, however, famously resistant to analytic attack. In this paper we introduce ensembles with partially-fixed degree sequences (PFDS) and compare analytic results obtained for them with Monte Carlo results for the FDS ensemble. These results include link likelihoods, subgraph likelihoods, and degree correlations. We find that local structural features in the FDS ensemble can be reasonably well estimated by simultaneously fixing only the degrees of a few nodes, in addition to the total number of nodes and links. As test cases we use two protein interaction networks (Escherichia coli, Saccharomyces cerevisiae), the internet on the autonomous system (AS) level, and the World Wide Web. Fixing just the degrees of two nodes gives the mean neighbor degree as a function of node degree, k;{'}_{k} , in agreement with results explicitly obtained from rewiring. For power law degree distributions, we derive the disassortativity analytically. In the PFDS ensemble the partition function can be expanded diagrammatically. We obtain an explicit expression for the link likelihood to lowest order, which reduces in the limit of large, sparse undirected networks with L links and with k_{max}L to the simple formula P(k,k;{'})=kk;{'}(2L+kk;{'}) . In a similar limit, the probability for three nodes to be linked into a triangle reduces to the factorized expression P_{Delta}(k_{1},k_{2},k_{3})=P(k_{1},k_{2})P(k_{1},k_{3})P(k_{2},k_{3}) .

  10. The Obesity-Linked Gene Nudt3 Drosophila Homolog Aps Is Associated With Insulin Signaling.

    PubMed

    Williams, Michael J; Eriksson, Anders; Shaik, Muksheed; Voisin, Sarah; Yamskova, Olga; Paulsson, Johan; Thombare, Ketan; Fredriksson, Robert; Schiöth, Helgi B

    2015-09-01

    Several genome-wide association studies have linked the Nudix hydrolase family member nucleoside diphosphate-linked moiety X motif 3 (NUDT3) to obesity. However, the manner of NUDT3 involvement in obesity is unknown, and NUDT3 expression, regulation, and signaling in the central nervous system has not been studied. We performed an extensive expression analysis in mice, as well as knocked down the Drosophila NUDT3 homolog Aps in the nervous system, to determine its effect on metabolism. Detailed in situ hybridization studies in the mouse brain revealed abundant Nudt3 mRNA and protein expression throughout the brain, including reward- and feeding-related regions of the hypothalamus and amygdala, whereas Nudt3 mRNA expression was significantly up-regulated in the hypothalamus and brainstem of food-deprived mice. Knocking down Aps in the Drosophila central nervous system, or a subset of median neurosecretory cells, known as the insulin-producing cells (IPCs), induces hyperinsulinemia-like phenotypes, including a decrease in circulating trehalose levels as well as significantly decreasing all carbohydrate levels under starvation conditions. Moreover, lowering Aps IPC expression leads to a decreased ability to recruit these lipids during starvation. Also, loss of neuronal Aps expression caused a starvation susceptibility phenotype while inducing hyperphagia. Finally, the loss of IPC Aps lowered the expression of Akh, Ilp6, and Ilp3, genes known to be inhibited by insulin signaling. These results point toward a role for this gene in the regulation of insulin signaling, which could explain the robust association with obesity in humans.

  11. Linking EEG signals, brain functions and mental operations: Advantages of the Laplacian transformation.

    PubMed

    Vidal, Franck; Burle, Boris; Spieser, Laure; Carbonnell, Laurence; Meckler, Cédric; Casini, Laurence; Hasbroucq, Thierry

    2015-09-01

    Electroencephalography (EEG) is a very popular technique for investigating brain functions and/or mental processes. To this aim, EEG activities must be interpreted in terms of brain and/or mental processes. EEG signals being a direct manifestation of neuronal activity it is often assumed that such interpretations are quite obvious or, at least, straightforward. However, they often rely on (explicit or even implicit) assumptions regarding the structures supposed to generate the EEG activities of interest. For these assumptions to be used appropriately, reliable links between EEG activities and the underlying brain structures must be established. Because of volume conduction effects and the mixture of activities they induce, these links are difficult to establish with scalp potential recordings. We present different examples showing how the Laplacian transformation, acting as an efficient source separation method, allowed to establish more reliable links between EEG activities and brain generators and, ultimately, with mental operations. The nature of those links depends on the depth of inferences that can vary from weak to strong. Along this continuum, we show that 1) while the effects of experimental manipulation can appear widely distributed with scalp potentials, Laplacian transformation allows to reveal several generators contributing (in different manners) to these modulations, 2) amplitude variations within the same set of generators can generate spurious differences in scalp potential topographies, often interpreted as reflecting different source configurations. In such a case, Laplacian transformation provides much more similar topographies, evidencing the same generator(s) set, and 3) using the LRP as an index of response activation most often produces ambiguous results, Laplacian-transformed response-locked ERPs obtained over motor areas allow resolving these ambiguities. PMID:25958789

  12. Linking EEG signals, brain functions and mental operations: Advantages of the Laplacian transformation.

    PubMed

    Vidal, Franck; Burle, Boris; Spieser, Laure; Carbonnell, Laurence; Meckler, Cédric; Casini, Laurence; Hasbroucq, Thierry

    2015-09-01

    Electroencephalography (EEG) is a very popular technique for investigating brain functions and/or mental processes. To this aim, EEG activities must be interpreted in terms of brain and/or mental processes. EEG signals being a direct manifestation of neuronal activity it is often assumed that such interpretations are quite obvious or, at least, straightforward. However, they often rely on (explicit or even implicit) assumptions regarding the structures supposed to generate the EEG activities of interest. For these assumptions to be used appropriately, reliable links between EEG activities and the underlying brain structures must be established. Because of volume conduction effects and the mixture of activities they induce, these links are difficult to establish with scalp potential recordings. We present different examples showing how the Laplacian transformation, acting as an efficient source separation method, allowed to establish more reliable links between EEG activities and brain generators and, ultimately, with mental operations. The nature of those links depends on the depth of inferences that can vary from weak to strong. Along this continuum, we show that 1) while the effects of experimental manipulation can appear widely distributed with scalp potentials, Laplacian transformation allows to reveal several generators contributing (in different manners) to these modulations, 2) amplitude variations within the same set of generators can generate spurious differences in scalp potential topographies, often interpreted as reflecting different source configurations. In such a case, Laplacian transformation provides much more similar topographies, evidencing the same generator(s) set, and 3) using the LRP as an index of response activation most often produces ambiguous results, Laplacian-transformed response-locked ERPs obtained over motor areas allow resolving these ambiguities.

  13. Creating highly amplified enzyme-linked immunosorbent assay signals from genetically engineered bacteriophage.

    PubMed

    Brasino, Michael; Lee, Ju Hun; Cha, Jennifer N

    2015-02-01

    For early detection of many diseases, it is critical to be able to diagnose small amounts of biomarkers in blood or serum. One of the most widely used sensing assays is the enzyme-linked immunosorbent assay (ELISA), which typically uses detection monoclonal antibodies conjugated to enzymes to produce colorimetric signals. To increase the overall sensitivities of these sensors, we demonstrate the use of a dually modified version of filamentous bacteriophage Fd that produces significantly higher colorimetric signals in ELISAs than what can be achieved using antibodies alone. Because only a few proteins at the tip of the micron-long bacteriophage are involved in antigen binding, the approximately 4000 other coat proteins can be augmented-by either chemical functionalization or genetic engineering-with hundreds to thousands of functional groups. In this article, we demonstrate the use of bacteriophage that bear a large genomic fusion that allows them to bind specific antibodies on coat protein 3 (p3) and multiple biotin groups on coat protein 8 (p8) to bind to avidin-conjugated enzymes. In direct ELISAs, the anti-rTNFα (recombinant human tumor necrosis factor alpha)-conjugated bacteriophage show approximately 3- to 4-fold gains in signal over that of anti-rTNFα, demonstrating their use as a platform for highly sensitive protein detection.

  14. OTULIN Antagonizes LUBAC Signaling by Specifically Hydrolyzing Met1-Linked Polyubiquitin

    PubMed Central

    Keusekotten, Kirstin; Elliott, Paul Ronald; Glockner, Laura; Fiil, Berthe Katrine; Damgaard, Rune Busk; Kulathu, Yogesh; Wauer, Tobias; Hospenthal, Manuela Kathrin; Gyrd-Hansen, Mads; Krappmann, Daniel; Hofmann, Kay; Komander, David

    2013-01-01

    Summary The linear ubiquitin (Ub) chain assembly complex (LUBAC) is an E3 ligase that specifically assembles Met1-linked (also known as linear) Ub chains that regulate nuclear factor κB (NF-κB) signaling. Deubiquitinases (DUBs) are key regulators of Ub signaling, but a dedicated DUB for Met1 linkages has not been identified. Here, we reveal a previously unannotated human DUB, OTULIN (also known as FAM105B), which is exquisitely specific for Met1 linkages. Crystal structures of the OTULIN catalytic domain in complex with diubiquitin reveal Met1-specific Ub-binding sites and a mechanism of substrate-assisted catalysis in which the proximal Ub activates the catalytic triad of the protease. Mutation of Ub Glu16 inhibits OTULIN activity by reducing kcat 240-fold. OTULIN overexpression or knockdown affects NF-κB responses to LUBAC, TNFα, and poly(I:C) and sensitizes cells to TNFα-induced cell death. We show that OTULIN binds LUBAC and that overexpression of OTULIN prevents TNFα-induced NEMO association with ubiquitinated RIPK1. Our data suggest that OTULIN regulates Met1-polyUb signaling. PMID:23746843

  15. Wideband Analog Fiber Optic Signal Link For Use In The Space/Radiation Simulator Environment

    NASA Astrophysics Data System (ADS)

    Blackburn, J.; Vanderwall, J.; Gilbert, R.; Holliday, V.

    1982-01-01

    The report describes a wideband linear response fiber optic transmission link designed to telemeter signals from a system being irradiated in a space/radiation simulator. The environment is severe: the transmitter must withstand an x-ray pulse delivering 109 rad(Si)/sec (surface dose rate), beams of 300 - 1000 KeV electrons, hard vacuum, and liquid nitrogen temperatures without degradation or even momentary upset. Radiation hardness is achieved by a combination of circuit design and high-Z shielding, including an optical fiber shield made of non-conducting lead-loaded. polyethylene. Special heat. conducting and insulating measures are employed to maintain temperature. The transmitter measures 15 x 8.5 x 9.5 am and operates on self-contained batteries. Signal bandwidth is greater than 10 KHz to 400 MHz with approximately 35 dB, of dynamic range. Signal inputs ranging from one millivolt to several volts are accommodated; four single-or double-ended inputs are provided, with remote selection. The single-fiber coupled remote control also allows adjusting input. attenuation, power and calibrator control, and verification of transmitter function. The single-mode laser used as the high frequency optical source is microwave dither-blased1 to reduce modal noise.

  16. Probing Rubber Cross-Linking Generation of Industrial Polymer Networks at Nanometer Scale.

    PubMed

    Gabrielle, Brice; Gomez, Emmanuel; Korb, Jean-Pierre

    2016-06-23

    We present improved analyses of rheometric torque measurements as well as (1)H double-quantum (DQ) nuclear magnetic resonance (NMR) buildup data on polymer networks of industrial compounds. This latter DQ NMR analysis allows finding the distribution of an orientation order parameter (Dres) resulting from the noncomplete averaging of proton dipole-dipole couplings within the cross-linked polymer chains. We investigate the influence of the formulation (filler and vulcanization systems) as well as the process (curing temperature) ending to the final polymer network. We show that DQ NMR follows the generation of the polymer network during the vulcanization process from a heterogeneous network to a very homogeneous one. The time variations of microscopic Dres and macroscopic rheometric torques present power-law behaviors above a threshold time scale with characteristic exponents of the percolation theory. We observe also a very good linear correlation between the kinetics of Dres and rheometric data routinely performed in industry. All these observations confirm the description of the polymer network generation as a critical phenomenon. On the basis of all these results, we believe that DQ NMR could become a valuable tool for investigating in situ the cross-linking of industrial polymer networks at the nanometer scale. PMID:27254797

  17. Probing Rubber Cross-Linking Generation of Industrial Polymer Networks at Nanometer Scale.

    PubMed

    Gabrielle, Brice; Gomez, Emmanuel; Korb, Jean-Pierre

    2016-06-23

    We present improved analyses of rheometric torque measurements as well as (1)H double-quantum (DQ) nuclear magnetic resonance (NMR) buildup data on polymer networks of industrial compounds. This latter DQ NMR analysis allows finding the distribution of an orientation order parameter (Dres) resulting from the noncomplete averaging of proton dipole-dipole couplings within the cross-linked polymer chains. We investigate the influence of the formulation (filler and vulcanization systems) as well as the process (curing temperature) ending to the final polymer network. We show that DQ NMR follows the generation of the polymer network during the vulcanization process from a heterogeneous network to a very homogeneous one. The time variations of microscopic Dres and macroscopic rheometric torques present power-law behaviors above a threshold time scale with characteristic exponents of the percolation theory. We observe also a very good linear correlation between the kinetics of Dres and rheometric data routinely performed in industry. All these observations confirm the description of the polymer network generation as a critical phenomenon. On the basis of all these results, we believe that DQ NMR could become a valuable tool for investigating in situ the cross-linking of industrial polymer networks at the nanometer scale.

  18. The involvement of the interleukin-1 Receptor-Associated Kinases (IRAKs) in cellular signaling networks controlling inflammation

    PubMed Central

    Ringwood, Lorna; Li, Liwu

    2008-01-01

    Innate immunity and inflammation plays a key role in host defense and wound healing. However, Excessive or altered inflammatory processes can contribute to severe and diverse human diseases including cardiovascular disease, diabetes and cancer. The interleukin-1 receptor associated kinases (IRAKs) are critically involved in the regulation of intra-cellular signaling networks controlling inflammation. Collective studies indicate that IRAKs are present in many cell types, and can mediate signals from various cell receptors including Toll-Like-Receptors (TLRs). Consequently, diverse downstream signaling processes can be elicited following the activation of various IRAKs. Given the critical and complex roles IRAK proteins play, it is not surprising that genetic variations in human IRAK genes have been found to be linked with various human inflammatory diseases. This review intends to summarize the recent advances regarding the regulations of various IRAK proteins and their cellular functions in mediating inflammatory signaling processes. PMID:18249132

  19. Integrative Phosphoproteomics Links IL-23R Signaling with Metabolic Adaptation in Lymphocytes

    PubMed Central

    Lochmatter, Corinne; Fischer, Roman; Charles, Philip D.; Yu, Zhanru; Powrie, Fiona; Kessler, Benedikt M.

    2016-01-01

    Interleukin (IL)-23 mediated signal transduction represents a major molecular mechanism underlying the pathology of inflammatory bowel disease, Crohn’s disease and ulcerative colitis. In addition, emerging evidence supports the role of IL-23-driven Th17 cells in inflammation. Components of the IL-23 signaling pathway, such as IL-23R, JAK2 and STAT3, have been characterized, but elements unique to this network as compared to other interleukins have not been readily explored. In this study, we have undertaken an integrative phosphoproteomics approach to better characterise downstream signaling events. To this end, we performed and compared phosphopeptide and phosphoprotein enrichment methodologies after activation of T lymphocytes by IL-23. We demonstrate the complementary nature of the two phosphoenrichment approaches by maximizing the capture of phosphorylation events. A total of 8202 unique phosphopeptides, and 4317 unique proteins were identified, amongst which STAT3, PKM2, CDK6 and LASP-1 showed induction of specific phosphorylation not readily observed after IL-2 stimulation. Interestingly, quantitative analysis revealed predominant phosphorylation of pre-existing STAT3 nuclear subsets in addition to translocation of phosphorylated STAT3 within 30 min after IL-23 stimulation. After IL-23R activation, a small subset of PKM2 also translocates to the nucleus and may contribute to STAT3 phosphorylation, suggesting multiple cellular responses including metabolic adaptation. PMID:27080861

  20. Age-dependent homeostatic plasticity of GABAergic signaling in developing retinal networks.

    PubMed

    Hennig, Matthias H; Grady, John; van Coppenhagen, James; Sernagor, Evelyne

    2011-08-24

    Developing retinal ganglion cells fire in correlated spontaneous bursts, resulting in propagating waves with robust spatiotemporal features preserved across development and species. Here we investigate the effects of homeostatic adaptation on the circuits controlling retinal waves. Mouse retinal waves were recorded in vitro for up to 35 h with a multielectrode array in presence of the GABA(A) antagonist bicuculline, allowing us to obtain a precise, time-resolved characterization of homeostatic effects in this preparation. Experiments were performed at P4-P6, when GABA(A) signaling is depolarizing in ganglion cells, and at P7-P10, when GABA(A) signaling is hyperpolarizing. At all ages, bicuculline initially increased the wave sizes and other activity metrics. At P5-P6, wave sizes decreased toward control levels within a few hours while firing remained strong, but this ability to compensate disappeared entirely from P7 onwards. This demonstrates that homeostatic control of spontaneous retinal activity maintains specific network dynamic properties in an age-dependent manner, and suggests that the underlying mechanism is linked to GABA(A) signaling. PMID:21865458

  1. Hijacking common mycorrhizal networks for herbivore-induced defence signal transfer between tomato plants

    PubMed Central

    Song, Yuan Yuan; Ye, Mao; Li, Chuanyou; He, Xinhua; Zhu-Salzman, Keyan; Wang, Rui Long; Su, Yi Juan; Luo, Shi Ming; Zeng, Ren Sen

    2014-01-01

    Common mycorrhizal networks (CMNs) link multiple plants together. We hypothesized that CMNs can serve as an underground conduit for transferring herbivore-induced defence signals. We established CMN between two tomato plants in pots with mycorrhizal fungus Funneliformis mosseae, challenged a ‘donor' plant with caterpillar Spodoptera litura, and investigated defence responses and insect resistance in neighbouring CMN-connected ‘receiver' plants. After CMN establishment caterpillar infestation on ‘donor' plant led to increased insect resistance and activities of putative defensive enzymes, induction of defence-related genes and activation of jasmonate (JA) pathway in the ‘receiver' plant. However, use of a JA biosynthesis defective mutant spr2 as ‘donor' plants resulted in no induction of defence responses and no change in insect resistance in ‘receiver' plants, suggesting that JA signalling is required for CMN-mediated interplant communication. These results indicate that plants are able to hijack CMNs for herbivore-induced defence signal transfer and interplant defence communication. PMID:24468912

  2. Microwave analog fiber-optic link for use in the deep space network

    NASA Technical Reports Server (NTRS)

    Logan, R. T., Jr.; Lutes, G. F.; Maleki, L.

    1990-01-01

    A novel fiber-optic system with dynamic range of up to 150 dB-Hz for transmission of microwave analog signals is described. The design, analysis, and laboratory evaluations of this system are reported, and potential applications in the NASA/JPL Deep Space Network are discussed.

  3. 47 CFR 73.4157 - Network signals which adversely affect affiliate broadcast service.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 4 2011-10-01 2011-10-01 false Network signals which adversely affect affiliate broadcast service. 73.4157 Section 73.4157 Telecommunication FEDERAL COMMUNICATIONS COMMISSION....4157 Network signals which adversely affect affiliate broadcast service. See Public Notice, FCC...

  4. 47 CFR 73.4157 - Network signals which adversely affect affiliate broadcast service.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 4 2010-10-01 2010-10-01 false Network signals which adversely affect affiliate broadcast service. 73.4157 Section 73.4157 Telecommunication FEDERAL COMMUNICATIONS COMMISSION....4157 Network signals which adversely affect affiliate broadcast service. See Public Notice, FCC...

  5. G-Protein/β-Arrestin-Linked Fluctuating Network of G-Protein-Coupled Receptors for Predicting Drug Efficacy and Bias Using Short-Term Molecular Dynamics Simulation

    PubMed Central

    Ichikawa, Osamu; Fujimoto, Kazushi; Yamada, Atsushi; Okazaki, Susumu; Yamazaki, Kazuto

    2016-01-01

    The efficacy and bias of signal transduction induced by a drug at a target protein are closely associated with the benefits and side effects of the drug. In particular, partial agonist activity and G-protein/β-arrestin-biased agonist activity for the G-protein-coupled receptor (GPCR) family, the family with the most target proteins of launched drugs, are key issues in drug discovery. However, designing GPCR drugs with appropriate efficacy and bias is challenging because the dynamic mechanism of signal transduction induced by ligand—receptor interactions is complicated. Here, we identified the G-protein/β-arrestin-linked fluctuating network, which initiates large-scale conformational changes, using sub-microsecond molecular dynamics (MD) simulations of the β2-adrenergic receptor (β2AR) with a diverse collection of ligands and correlation analysis of their G protein/β-arrestin efficacy. The G-protein-linked fluctuating network extends from the ligand-binding site to the G-protein-binding site through the connector region, and the β-arrestin-linked fluctuating network consists of the NPxxY motif and adjacent regions. We confirmed that the averaged values of fluctuation in the fluctuating network detected are good quantitative indexes for explaining G protein/β-arrestin efficacy. These results indicate that short-term MD simulation is a practical method to predict the efficacy and bias of any compound for GPCRs. PMID:27187591

  6. Accelerated growth in outgoing links in evolving networks: deterministic versus stochastic picture.

    PubMed

    Sen, Parongama

    2004-04-01

    In several real-world networks such as the Internet, World Wide Web, etc., the number of links grow in time in a nonlinear fashion. We consider growing networks in which the number of outgoing links is a nonlinear function of time but new links between older nodes are forbidden. The attachments are made using a preferential attachment scheme. In the deterministic picture, the number of outgoing links m (t) at any time t is taken as N (t)(theta) where N (t) is the number of nodes present at that time. The continuum theory predicts a power-law decay of the degree distribution: P (k) proportional to k-(1-2/ (1-theta ) ), while the degree of the node introduced at time t(i) is given by k(t(i),t)=t(theta)(i) [t/t(i) ]((1+theta)/2) when the network is evolved till time t. Numerical results show a growth in the degree distribution for small k values at any nonzero theta. In the stochastic picture, m (t) is a random variable. As long as is independent of time, the network shows a behavior similar to the Barabási-Albert (BA) model. Different results are obtained when is time dependent, e.g., when m (t) follows a distribution P (m) proportional to m(-lambda). The behavior of P (k) changes significantly as lambda is varied: for lambda>3, the network has a scale-free distribution belonging to the BA class as predicted by the mean field theory; for smaller values of lambda it shows different behavior. Characteristic features of the clustering coefficients in both models have also been discussed.

  7. Accelerated growth in outgoing links in evolving networks:Deterministic versus stochastic picture

    NASA Astrophysics Data System (ADS)

    Sen, Parongama

    2004-04-01

    In several real-world networks such as the Internet, World Wide Web, etc., the number of links grow in time in a nonlinear fashion. We consider growing networks in which the number of outgoing links is a nonlinear function of time but new links between older nodes are forbidden. The attachments are made using a preferential attachment scheme. In the deterministic picture, the number of outgoing links m (t) at any time t is taken as N (t)θ where N (t) is the number of nodes present at that time. The continuum theory predicts a power-law decay of the degree distribution: P (k) ∝ k-1-2/ ( 1-θ ) , while the degree of the node introduced at time ti is given by k(ti,t)=tθi [t/ ti ](1+θ)/2 when the network is evolved till time t . Numerical results show a growth in the degree distribution for small k values at any nonzero θ . In the stochastic picture, m (t) is a random variable. As long as < m (t) > is independent of time, the network shows a behavior similar to the Barabási-Albert (BA) model. Different results are obtained when < m (t) > is time dependent, e.g., when m (t) follows a distribution P (m) ∝ m-λ . The behavior of P (k) changes significantly as λ is varied: for λ>3 , the network has a scale-free distribution belonging to the BA class as predicted by the mean field theory; for smaller values of λ it shows different behavior. Characteristic features of the clustering coefficients in both models have also been discussed.

  8. Network Signal Processor No. 2 after removal from Columbia

    NASA Technical Reports Server (NTRS)

    1998-01-01

    Two USA employees, Tim Seymour (at left) and Danny Brown (at right), look at the network signal processor (NSP) that was responsible for postponement of the launch of STS-90 on Apr. 16. The Space Shuttle Columbia's liftoff from Launch Pad 39B was postponed 24 hours due to difficulty with NSP No. 2 on the orbiter. This device formats data and voice communications between the ground and the Space Shuttle. The unit, which is located in the orbiter's mid-deck, was removed and replaced on Apr. 16. Mission managers first noticed the problem at about 3 a.m. during normal communications systems activation prior to tanking operations. As a result, work to load the external tank with the cryogenic propellants did not begin and launch postponement was made official at about 8:15 a.m. STS-90 is slated to be the launch of Neurolab, a nearly 17-day mission to examine the effects of spaceflight on the brain, spinal cord, peripheral nerves and sensory organs in the human body.

  9. Signal processing using artificial neural network for BOTDA sensor system.

    PubMed

    Azad, Abul Kalam; Wang, Liang; Guo, Nan; Tam, Hwa-Yaw; Lu, Chao

    2016-03-21

    We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy. PMID:27136863

  10. Signal processing using artificial neural network for BOTDA sensor system.

    PubMed

    Azad, Abul Kalam; Wang, Liang; Guo, Nan; Tam, Hwa-Yaw; Lu, Chao

    2016-03-21

    We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy.

  11. Identifying causal networks linking cancer processes and anti-tumor immunity using Bayesian network inference and metagene constructs.

    PubMed

    Kaiser, Jacob L; Bland, Cassidy L; Klinke, David J

    2016-03-01

    Cancer arises from a deregulation of both intracellular and intercellular networks that maintain system homeostasis. Identifying the architecture of these networks and how they are changed in cancer is a pre-requisite for designing drugs to restore homeostasis. Since intercellular networks only appear in intact systems, it is difficult to identify how these networks become altered in human cancer using many of the common experimental models. To overcome this, we used the diversity in normal and malignant human tissue samples from the Cancer Genome Atlas (TCGA) database of human breast cancer to identify the topology associated with intercellular networks in vivo. To improve the underlying biological signals, we constructed Bayesian networks using metagene constructs, which represented groups of genes that are concomitantly associated with different immune and cancer states. We also used bootstrap resampling to establish the significance associated with the inferred networks. In short, we found opposing relationships between cell proliferation and epithelial-to-mesenchymal transformation (EMT) with regards to macrophage polarization. These results were consistent across multiple carcinomas in that proliferation was associated with a type 1 cell-mediated anti-tumor immune response and EMT was associated with a pro-tumor anti-inflammatory response. To address the identifiability of these networks from other datasets, we could identify the relationship between EMT and macrophage polarization with fewer samples when the Bayesian network was generated from malignant samples alone. However, the relationship between proliferation and macrophage polarization was identified with fewer samples when the samples were taken from a combination of the normal and malignant samples. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:470-479, 2016.

  12. INPP5E interacts with AURKA, linking phosphoinositide signaling to primary cilium stability

    PubMed Central

    Plotnikova, Olga V.; Seo, Seongjin; Cottle, Denny L.; Conduit, Sarah; Hakim, Sandra; Dyson, Jennifer M.; Mitchell, Christina A.; Smyth, Ian M.

    2015-01-01

    ABSTRACT Mutations in inositol polyphosphate 5-phosphatase E (INPP5E) cause the ciliopathies known as Joubert and MORM syndromes; however, the role of INPP5E in ciliary biology is not well understood. Here, we describe an interaction between INPP5E and AURKA, a centrosomal kinase that regulates mitosis and ciliary disassembly, and we show that this interaction is important for the stability of primary cilia. Furthermore, AURKA phosphorylates INPP5E and thereby increases its 5-phosphatase activity, which in turn promotes transcriptional downregulation of AURKA, partly through an AKT-dependent mechanism. These findings establish the first direct link between AURKA and phosphoinositide signaling and suggest that the function of INPP5E in cilia is at least partly mediated by its interactions with AURKA. PMID:25395580

  13. Echo state property linked to an input: exploring a fundamental characteristic of recurrent neural networks.

    PubMed

    Manjunath, G; Jaeger, H

    2013-03-01

    The echo state property is a key for the design and training of recurrent neural networks within the paradigm of reservoir computing. In intuitive terms, this is a passivity condition: a network having this property, when driven by an input signal, will become entrained by the input and develop an internal response signal. This excited internal dynamics can be seen as a high-dimensional, nonlinear, unique transform of the input with a rich memory content. This view has implications for understanding neural dynamics beyond the field of reservoir computing. Available definitions and theorems concerning the echo state property, however, are of little practical use because they do not relate the network response to temporal or statistical properties of the driving input. Here we present a new definition of the echo state property that directly connects it to such properties. We derive a fundamental 0-1 law: if the input comes from an ergodic source, the network response has the echo state property with probability one or zero, independent of the given network. Furthermore, we give a sufficient condition for the echo state property that connects statistical characteristics of the input to algebraic properties of the network connection matrix. The mathematical methods that we employ are freshly imported from the young field of nonautonomous dynamical systems theory. Since these methods are not yet well known in neural computation research, we introduce them in some detail. As a side story, we hope to demonstrate the eminent usefulness of these methods.

  14. Near-Perfect Adaptation in the E. coli Chemotaxis Signal Transduction Network

    NASA Astrophysics Data System (ADS)

    Yang, Yang; Setayeshgar, Sima

    2007-03-01

    Biochemical reaction networks constitute the computing language of the cell, from converting external stimuli into appropriate intracellular signals to regulating gene expression. Precise adaptation is an important property of many signaling networks, allowing compensation for continued stimulation without saturation. Furthermore, a common feature of intracellular reaction networks is the ability to operate in a noisy environment where concentrations of key components, such as signaling molecules and enzymes controlling reaction rates are typically small and therefore fluctuations in their numbers are significant. In the context of the well- characterized E. coli chemotaxis signal transduction network, we present a new computational scheme that explores surfaces in the space of total protein concentrations and reaction rates on which (near-)perfect adaptation holds. The resulting dependencies between parameters provide conditions for (near-)perfect adaptation as well as ranges of numerical values for parameters not reliably known from experiments. We generalize the applicability of this scheme to other signaling networks.

  15. Structural properties of end-linked polymer networks: Monte Carlo simulation and neutron scattering studies

    NASA Astrophysics Data System (ADS)

    Gilra, Nisha

    2000-12-01

    In this work, computational and experimental approaches were taken to elucidate the structural behavior of end- linked polymer networks. Monte Carlo simulations with the bond fluctuation model were used to study the formation and structure of 10-, 20-, and 50-mer networks cured with various ratios of cross-link sites to chain ends, r. The simulations confirmed experimental results that optimum r values for structural properties are found at non- stoichiometric ratios, increase with increasing precursor polymer chain length, and increase with side reaction. The same structural properties were determined for 50-mer networks formed in the presence of a series of concentrations of 50-mer unreactive linear chain diluent. A slight maximum in the fraction of elastic material was observed at a small degree of dilution and was explained in terms of entanglement effects. The conformational behavior of a small fraction of 50-mer linear probe chains was studied in various polymer network mesh sizes, where mesh size is the number of monomers between cross- links. The radius of gyration, R g, of the probe chains decreased by less than 6% for all mesh sizes studied. Uniaxial network deformation was studied using constant pressure simulations. A new methodology to perform volume change moves was developed. The equation of state of 10- mer athermal network system was determined and found to be similar to the corresponding athermal linear polymer equation of state at high volume fractions, but approached a region of negative pressures at low volume fractions. The chain segment orientational correlation was determined for probe free chains trapped in isotropic and deformed networks. Increased correlation was observed at small distances, whereas no orientational preference was evident at larger distances. The study of probe free chains trapped in polymer networks was also performed using small-angle neutron scattering. The conformational behavior of 70K poly(dimethylsiloxane) (PDMS

  16. Impaired generation of 12-hydroxylated bile acids links hepatic insulin signaling with dyslipidemia.

    PubMed

    Haeusler, Rebecca A; Pratt-Hyatt, Matthew; Welch, Carrie L; Klaassen, Curtis D; Accili, Domenico

    2012-01-01

    The association of type 2 diabetes with elevated plasma triglyceride (TG) and very low-density lipoproteins (VLDL), and intrahepatic lipid accumulation represents a pathophysiological enigma and an unmet therapeutic challenge. Here, we uncover a link between insulin action through FoxO1, bile acid (BA) composition, and altered lipid homeostasis that brings new insight to this longstanding conundrum. FoxO1 ablation brings about two signature lipid abnormalities of diabetes and the metabolic syndrome, elevated liver and plasma TG. These changes are associated with deficiency of 12α-hydroxylated BAs and their synthetic enzyme, Cyp8b1, that hinders the TG-lowering effects of the BA receptor, Fxr. Accordingly, pharmacological activation of Fxr with GW4064 overcomes the BA imbalance, restoring hepatic and plasma TG levels of FoxO1-deficient mice to normal levels. We propose that generation of 12α-hydroxylated products of BA metabolism represents a signaling mechanism linking hepatic lipid abnormalities with type 2 diabetes, and a treatment target for this condition.

  17. Multiaxial deformations of end-linked poly(dimethylsiloxane) networks. 4. Further assessment of the slip-link model for chain-entanglement effect on rubber elasticity

    NASA Astrophysics Data System (ADS)

    Urayama, Kenji; Kawamura, Takanobu; Kohjiya, Shinzo

    2003-03-01

    The Edwards-Vilgis slip-link model for the chain-entanglement effect on rubber elasticity is critically assessed on the basis of quasiequilibrium biaxial stress—strain data of end-linked polydimethylsiloxane (PDMS) networks with different entanglement densities. The PDMS networks with different entanglement densities were prepared by end-linking end-reactive long precursor PDMS in solutions with different solvent contents. The slip-link model, in which trapped entanglement is modeled by fictitious mobile slip-link attaching two entangled chains, satisfactorily describes the biaxial data over the entire range of deformation for all the networks examined. The model-specific parameters, i.e., slippage of slip-link (η) and inextensibility of network (α), were employed as adjustable parameters in data-fitting. The fitted values of η and α vary reasonably with the degree of dilution at network preparation, i.e., entanglement density. With an increase in dilution, i.e., decrease in entanglement density, η increases, whereas α decreases. In addition, the fitted values of η and α are in good agreement with the estimates from another molecular approach independent of mechanical testings: η=Me/Mc, where Me and Mc are the molecular masses between neighboring entanglements and between adjacent cross-links, respectively; α=nj-1/2, where nj is the number of Kuhn segments between adjacent elastically effective junctions including cross-links and trapped entanglements. The satisfactory data-fit with the model parameters of physically reasonable magnitudes supports the validity of the slip-link model for entanglement effects on rubber elasticity.

  18. Broadband nanophotonic wireless links and networks using on-chip integrated plasmonic antennas.

    PubMed

    Yang, Yuanqing; Li, Qiang; Qiu, Min

    2016-01-01

    Owing to their high capacity and flexibility, broadband wireless communications have been widely employed in radio and microwave regimes, playing indispensable roles in our daily life. Their optical analogs, however, have not been demonstrated at the nanoscale. In this paper, by exploiting plasmonic nanoantennas, we demonstrate the complete design of broadband wireless links and networks in the realm of nanophotonics. With a 100-fold enhancement in power transfer superior to previous designs as well as an ultrawide bandwidth that covers the entire telecommunication wavelength range, such broadband nanolinks and networks are expected to pave the way for future optical integrated nanocircuits. PMID:26783033

  19. Broadband nanophotonic wireless links and networks using on-chip integrated plasmonic antennas

    NASA Astrophysics Data System (ADS)

    Yang, Yuanqing; Li, Qiang; Qiu, Min

    2016-01-01

    Owing to their high capacity and flexibility, broadband wireless communications have been widely employed in radio and microwave regimes, playing indispensable roles in our daily life. Their optical analogs, however, have not been demonstrated at the nanoscale. In this paper, by exploiting plasmonic nanoantennas, we demonstrate the complete design of broadband wireless links and networks in the realm of nanophotonics. With a 100-fold enhancement in power transfer superior to previous designs as well as an ultrawide bandwidth that covers the entire telecommunication wavelength range, such broadband nanolinks and networks are expected to pave the way for future optical integrated nanocircuits.

  20. The role of detachment of in-links in scale-free networks

    NASA Astrophysics Data System (ADS)

    Lansky, P.; Polito, F.; Sacerdote, L.

    2014-08-01

    Real-world networks may exhibit a detachment phenomenon determined by the canceling of previously existing connections. We discuss a tractable extension of the Yule model to account for this feature. Analytical results are derived and discussed both asymptotically and for a finite number of links. Comparison with the original model is performed in the supercritical case. The first-order asymptotic tail behavior of the two models is similar but differences arise in the second-order term. We explicitly refer to world wide web modeling and we show the agreement of the proposed model on very recent data. However, other possible network applications are also mentioned.

  1. Broadband nanophotonic wireless links and networks using on-chip integrated plasmonic antennas.

    PubMed

    Yang, Yuanqing; Li, Qiang; Qiu, Min

    2016-01-19

    Owing to their high capacity and flexibility, broadband wireless communications have been widely employed in radio and microwave regimes, playing indispensable roles in our daily life. Their optical analogs, however, have not been demonstrated at the nanoscale. In this paper, by exploiting plasmonic nanoantennas, we demonstrate the complete design of broadband wireless links and networks in the realm of nanophotonics. With a 100-fold enhancement in power transfer superior to previous designs as well as an ultrawide bandwidth that covers the entire telecommunication wavelength range, such broadband nanolinks and networks are expected to pave the way for future optical integrated nanocircuits.

  2. Molecular origin of strain softening in cross-linked F-actin networks

    NASA Astrophysics Data System (ADS)

    Lee, Hyungsuk; Ferrer, Jorge M.; Lang, Matthew J.; Kamm, Roger D.

    2010-07-01

    Two types of measurement are presented that relate molecular events to macroscopic behavior of F-actin networks. First, shear modulus is measured by oscillating an embedded microbead. Second, a microbead is translated at constant rate and transitions in the resisting force are observed. The loading rate dependence of the force at the transitions is similar to that of the molecular unbinding force, suggesting that they share a common origin. Reversibility tests of shear modulus provide further evidence that strain softening of F-actin networks is caused by force-induced rupture of cross-links.

  3. Broadband nanophotonic wireless links and networks using on-chip integrated plasmonic antennas

    PubMed Central

    Yang, Yuanqing; Li, Qiang; Qiu, Min

    2016-01-01

    Owing to their high capacity and flexibility, broadband wireless communications have been widely employed in radio and microwave regimes, playing indispensable roles in our daily life. Their optical analogs, however, have not been demonstrated at the nanoscale. In this paper, by exploiting plasmonic nanoantennas, we demonstrate the complete design of broadband wireless links and networks in the realm of nanophotonics. With a 100-fold enhancement in power transfer superior to previous designs as well as an ultrawide bandwidth that covers the entire telecommunication wavelength range, such broadband nanolinks and networks are expected to pave the way for future optical integrated nanocircuits. PMID:26783033

  4. Network dynamics for optimal compressive-sensing input-signal recovery.

    PubMed

    Barranca, Victor J; Kovačič, Gregor; Zhou, Douglas; Cai, David

    2014-10-01

    By using compressive sensing (CS) theory, a broad class of static signals can be reconstructed through a sequence of very few measurements in the framework of a linear system. For networks with nonlinear and time-evolving dynamics, is it similarly possible to recover an unknown input signal from only a small number of network output measurements? We address this question for pulse-coupled networks and investigate the network dynamics necessary for successful input signal recovery. Determining the specific network characteristics that correspond to a minimal input reconstruction error, we are able to achieve high-quality signal reconstructions with few measurements of network output. Using various measures to characterize dynamical properties of network output, we determine that networks with highly variable and aperiodic output can successfully encode network input information with high fidelity and achieve the most accurate CS input reconstructions. For time-varying inputs, we also find that high-quality reconstructions are achievable by measuring network output over a relatively short time window. Even when network inputs change with time, the same optimal choice of network characteristics and corresponding dynamics apply as in the case of static inputs.

  5. Droplet-Free Digital Enzyme-Linked Immunosorbent Assay Based on a Tyramide Signal Amplification System.

    PubMed

    Akama, Kenji; Shirai, Kentaro; Suzuki, Seigo

    2016-07-19

    Digital enzyme-linked immunosorbent assay (ELISA) is a single molecule counting technology and is one of the most sensitive immunoassay methods. The key aspect of this technology is to concentrate enzyme reaction products from a single target molecule in femtoliter droplets. This study presents a novel Digital ELISA that does not require droplets; instead, enzyme reaction products are concentrated using a tyramide signal amplification system. In our method, tyramide substrate reacts with horseradish peroxidase (HRP) labeled with an immunocomplex on beads, and the substrate is converted into short-lived radical intermediates. By adjusting the bead concentration in the HRP-tyramide reaction and conducting the reaction using freely moving beads, tyramide radicals are deposited only on beads labeled with HRP and there is no diffusion to other beads. Consequently, the fluorescence signal is localized on a portion of the beads, making it possible to count the number of labeled beads digitally. The performance of our method was demonstrated by detecting hepatitis B surface antigen with a limit of detection of 0.09 mIU/mL (139 aM) and a dynamic range of over 4 orders of magnitude. The obtained limit of detection represents a >20-fold higher sensitivity than conventional ELISA. Our method has potential applications in simple in vitro diagnostic systems for detecting ultralow concentrations of protein biomarkers.

  6. PINCH proteins regulate cardiac contractility by modulating integrin-linked kinase-protein kinase B signaling.

    PubMed

    Meder, Benjamin; Huttner, Inken G; Sedaghat-Hamedani, Farbod; Just, Steffen; Dahme, Tillman; Frese, Karen S; Vogel, Britta; Köhler, Doreen; Kloos, Wanda; Rudloff, Jessica; Marquart, Sabine; Katus, Hugo A; Rottbauer, Wolfgang

    2011-08-01

    Integrin-linked kinase (ILK) is an essential component of the cardiac mechanical stretch sensor and is bound in a protein complex with parvin and PINCH proteins, the so-called ILK-PINCH-parvin (IPP) complex. We have recently shown that inactivation of ILK or β-parvin activity leads to heart failure in zebrafish via reduced protein kinase B (PKB/Akt) activation. Here, we show that PINCH proteins localize at sarcomeric Z disks and costameres in the zebrafish heart and skeletal muscle. To investigate the in vivo role of PINCH proteins for IPP complex stability and PKB signaling within the vertebrate heart, we inactivated PINCH1 and PINCH2 in zebrafish. Inactivation of either PINCH isoform independently leads to instability of ILK, loss of stretch-responsive anf and vegf expression, and progressive heart failure. The predominant cause of heart failure in PINCH morphants seems to be loss of PKB activity, since PKB phosphorylation at serine 473 is significantly reduced in PINCH-deficient hearts and overexpression of constitutively active PKB reconstitutes cardiac function in PINCH morphants. These findings highlight the essential function of PINCH proteins in controlling cardiac contractility by granting IPP/PKB-mediated signaling.

  7. R4 regulators of G protein signaling (RGS) identify an ancient MHC-linked synteny group

    PubMed Central

    Suurväli, Jaanus; Robert, Jacques; Boudinot, Pierre; Boudinot, Sirje Rüütel

    2012-01-01

    Regulators of G Protein Signaling (RGS) are key regulators of G protein signaling. RGS proteins of the R4 RGS group are composed of a mere RGS domain and are mainly involved in immune response modulation. In both human and mouse, most genes encoding the R4 RGS proteins are located in the same region of chromosome 1. We show here that the RGS1/RGS16 neighborhood constitutes a synteny group well conserved across tetrapods, and closely linked to the MHC paralogon of chromosome 1. Genes located in the RGS1/RGS16 region have paralogs close to the MHC on chromosome 6 or close to the other MHC paralogons. In amphioxus, a cephalochordate, these genes possess orthologs that are located in the same scaffolds as a number of markers defining the proto-MHC in this species (Abi-Rached et al. 2002). We therefore propose that the RGS1/RGS16 region provides useful markers to investigate the origins and the evolution of the MHC. In addition, we show that some genes of the region appear to have immune functions not only in human, but also in Xenopus. PMID:23129146

  8. Using LinkedIn in the Marketing Classroom: Exploratory Insights and Recommendations for Teaching Social Media/Networking

    ERIC Educational Resources Information Center

    McCorkle, Denny E.; McCorkle, Yuhua Li

    2012-01-01

    With the rapid growth of social networking and media comes their consideration for use in the marketing classroom. Social networking skills are becoming essential for personal branding (e.g., networking, self-marketing) and corporate/product branding (e.g., marketing communication). This paper addresses the use of LinkedIn (i.e., an online…

  9. Domain-general signals in the cingulo-opercular network for visuospatial attention and episodic memory

    PubMed Central

    Sestieri, Carlo; Corbetta, Maurizio; Spadone, Sara; Romani, Gian Luca; Shulman, Gordon L.

    2014-01-01

    We investigated the functional properties of a previously described cingulo-opercular network (CON) putatively involved in cognitive control. Analyses of common fMRI task-evoked activity during perceptual and episodic memory search tasks that differently recruited the dorsal attention (DAN) and default mode network (DMN) established the generality of this network. Regions within the CON (anterior insula/frontal operculum and anterior cingulate/presupplementary cortex) displayed sustained signals during extended periods in which participants searched for behaviourally relevant information in a dynamically changing environment or from episodic memory in the absence of sensory stimulation. The CON was activated during all phases of both tasks, which involved trial initiation, target detection, decision and response, indicating its consistent involvement in a broad range of cognitive processes. Functional connectivity analyses showed that the CON flexibly linked with the DAN or DMN regions during perceptual or memory search, respectively. Aside from the CON, only a limited number of regions, including the lateral prefrontal cortex, showed evidence of domain-general, sustained activity, although in some cases the common activations may have reflected the functional-anatomical variability of domain-specific regions rather than a true domain-generality. These additional regions also showed task-dependent functional connectivity with the DMN and DAN, suggesting that this feature is not a specific marker of cognitive control. Finally, multivariate clustering analyses separated the CON from other fronto-parietal regions previously associated with cognitive control, indicating a unique fingerprint. We conclude that the CON’s functional properties and interactions with other brain regions support a broad role in cognition, consistent with its characterization as a task-control network. PMID:24144246

  10. Simultaneous multichannel signal transfers via chaos in a recurrent neural network.

    PubMed

    Soma, Ken-ichiro; Mori, Ryota; Sato, Ryuichi; Furumai, Noriyuki; Nara, Shigetoshi

    2015-05-01

    We propose neural network model that demonstrates the phenomenon of signal transfer between separated neuron groups via other chaotic neurons that show no apparent correlations with the input signal. The model is a recurrent neural network in which it is supposed that synchronous behavior between small groups of input and output neurons has been learned as fragments of high-dimensional memory patterns, and depletion of neural connections results in chaotic wandering dynamics. Computer experiments show that when a strong oscillatory signal is applied to an input group in the chaotic regime, the signal is successfully transferred to the corresponding output group, although no correlation is observed between the input signal and the intermediary neurons. Signal transfer is also observed when multiple signals are applied simultaneously to separate input groups belonging to different memory attractors. In this sense simultaneous multichannel communications are realized, and the chaotic neural dynamics acts as a signal transfer medium in which the signal appears to be hidden.

  11. Space Link Extension (SLE) Emulation for High-Throughput Network Communication

    NASA Technical Reports Server (NTRS)

    Murawski, Robert; Tchorowski, Nicole; Golden, Bert

    2014-01-01

    As the data rate requirements for space communications increases, signicant stressis placed not only on the wireless satellite communication links, but also on the groundnetworks which forward data from end-users to remote ground stations. These wide areanetwork (WAN) connections add delay and jitter to the end-to-end satellite communicationlink, eects which can have signicant impacts on the wireless communication link. It isimperative that any ground communication protocol can react to these eects such that theground network does not become a bottleneck in the communication path to the satellite.In this paper, we present our SCENIC Emulation Lab testbed which was developed to testthe CCSDS SLE protocol implementations proposed for use on future NASA communica-tion networks. Our results show that in the presence of realistic levels of network delay,high-throughput SLE communication links can experience signicant data rate throttling.Based on our observations, we present some insight into why this data throttling happens,and trace the probable issue back to non-optimal blocking communication which is sup-ported by the CCSDS SLE API recommended practices. These issues were presented aswell to the SLE implementation developers which, based on our reports, developed a newrelease for SLE which we show xes the SLE blocking issue and greatly improves the pro-tocol throughput. In this paper, we also discuss future developments for our end-to-endemulation lab and how these improvements can be used to develop and test future spacecommunication technologies.

  12. Mechanism of Shear Thickening in Reversibly Cross-linked Supramolecular Polymer Networks

    PubMed Central

    Xu, Donghua; Hawk, Jennifer L.; Loveless, David M.; Jeon, Sung Lan; Craig, Stephen L.

    2010-01-01

    We report here the nonlinear rheological properties of metallo-supramolecular networks formed by the reversible cross-linking of semi-dilute unentangled solutions of poly(4-vinylpyridine) (PVP) in dimethyl sulfoxide (DMSO). The reversible cross-linkers are bis-Pd(II) or bis-Pt(II) complexes that coordinate to the pyridine functional groups on the PVP. Under steady shear, shear thickening is observed above a critical shear rate, and that critical shear rate is experimentally correlated with the lifetime of the metal-ligand bond. The onset and magnitude of the shear thickening depend on the amount of cross-linkers added. In contrast to the behavior observed in most transient networks, the time scale of network relaxation is found to increase during shear thickening. The primary mechanism of shear thickening is ascribed to the shear-induced transformation of intrachain cross-linking to interchain cross-linking, rather than nonlinear high tension along polymer chains that are stretched beyond the Gaussian range. PMID:20479956

  13. Structural Analysis and Mechanical Characterization of Hyaluronic Acid-Based Doubly Cross-Linked Networks

    PubMed Central

    Jha, Amit K.; Hule, Rohan A.; Jiao, Tong; Teller, Sean S.; Clifton, Rodney J.; Duncan, Randall L.; Pochan, Darrin J.; Jia, Xinqiao

    2009-01-01

    We have created a new class of hyaluronic acid (HA)-based hydrogel materials with HA hydrogel particles (HGPs) embedded in and covalently cross-linked to a secondary network. HA HGPs with an average diameter of ∼900 nm and narrow particle size distribution were synthesized using a refined reverse micelle polymerization technique. The average mesh size of the HGPs was estimated to be approximately 5.5 to 7.0 nm by a protein uptake experiment. Sodium periodate oxidation not only introduced aldehyde groups to the particles but also reduced the average particle size. The aldehyde groups generated were used as reactive handles for subsequent cross-linking with an HA derivative containing hydrazide groups. The resulting macroscopic gels contain two distinct hierarchical networks (doubly cross-linked networks, DXNs): one within individual particles and another among different particles. Bulk gels (BGs) formed by direct mixing of HA derivatives with mutually reactive groups were included for comparison. The hydrogel microstructures were collectively characterized by microscopy and neutron scattering techniques. Their viscoelasticity was quantified at low frequencies (0.1−10 Hz) using a controlled stress rheometer and at high frequencies (up to 200 Hz) with a home-built torsional wave apparatus. Both BGs and DXNs are stable elastic gels that become stiffer at higher frequencies. The HA-based DXN offers unique structural hierarchy and mechanical properties that are suitable for soft tissue regeneration. PMID:20046226

  14. Adaptive Path Selection for Link Loss Inference in Network Tomography Applications

    PubMed Central

    Qiao, Yan; Jiao, Jun; Rao, Yuan; Ma, Huimin

    2016-01-01

    In this study, we address the problem of selecting the optimal end-to-end paths for link loss inference in order to improve the performance of network tomography applications, which infer the link loss rates from the path loss rates. Measuring the path loss rates using end-to-end probing packets may incur additional traffic overheads for networks, so it is important to select the minimum path set carefully while maximizing their performance. The usual approach is to select the maximum independent paths from the candidates simultaneously, while the other paths can be replaced by linear combinations of them. However, this approach ignores the fact that many paths always exist that do not lose any packets, and thus it is easy to determine that all of the links of these paths also have 0 loss rates. Not considering these good paths will inevitably lead to inefficiency and high probing costs. Thus, we propose an adaptive path selection method that selects paths sequentially based on the loss rates of previously selected paths. We also propose a theorem as well as a graph construction and decomposition approach to efficiently find the most valuable path during each round of selection. Our new method significantly outperforms the classical path selection method based on simulations in terms of the probing cost, number of accurate links determined, and the running speed. PMID:27701447

  15. Layered Signaling Regulatory Networks Analysis of Gene Expression Involved in Malignant Tumorigenesis of Non-Resolving Ulcerative Colitis via Integration of Cross-Study Microarray Profiles

    PubMed Central

    Fan, Shengjun; Pan, Zhenyu; Geng, Qiang; Li, Xin; Wang, Yefan; An, Yu; Xu, Yan; Tie, Lu; Pan, Yan; Li, Xuejun

    2013-01-01

    Background Ulcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups. Methodology/Principal Findings In this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks. Results Overall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one. Conclusions The present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis

  16. Transport link scanner: simulating geographic transport network expansion through individual investments

    NASA Astrophysics Data System (ADS)

    Jacobs-Crisioni, C.; Koopmans, C. C.

    2016-07-01

    This paper introduces a GIS-based model that simulates the geographic expansion of transport networks by several decision-makers with varying objectives. The model progressively adds extensions to a growing network by choosing the most attractive investments from a limited choice set. Attractiveness is defined as a function of variables in which revenue and broader societal benefits may play a role and can be based on empirically underpinned parameters that may differ according to private or public interests. The choice set is selected from an exhaustive set of links and presumably contains those investment options that best meet private operator's objectives by balancing the revenues of additional fare against construction costs. The investment options consist of geographically plausible routes with potential detours. These routes are generated using a fine-meshed regularly latticed network and shortest path finding methods. Additionally, two indicators of the geographic accuracy of the simulated networks are introduced. A historical case study is presented to demonstrate the model's first results. These results show that the modelled networks reproduce relevant results of the historically built network with reasonable accuracy.

  17. Two fundamental mechanisms govern the stiffening of cross-linked networks.

    PubMed

    Žagar, Goran; Onck, Patrick R; van der Giessen, Erik

    2015-03-24

    Biopolymer networks, such as those constituting the cytoskeleton of a cell or biological tissue, exhibit a nonlinear strain-stiffening behavior when subjected to large deformations. Interestingly, rheological experiments on various in vitro biopolymer networks have shown similar strain-stiffening trends regardless of the differences in their microstructure or constituents, suggesting a universal stiffening mechanism. In this article, we use computer simulations of a random network comprised of cross-linked biopolymer-like fibers to substantiate the notion that this universality lies in the existence of two fundamental stiffening mechanisms. After showing that the large strain response is accompanied by the development of a stress path, i.e., a percolating path of axially stressed fibers and cross-links, we demonstrate that the strain stiffening can be caused by two distinctly different mechanisms: 1) the pulling out of stress-path undulations; and 2) reorientation of the stress path. The former mechanism is bending-dominated and can be recognized by a power-law dependence with exponent 3/2 of the shear modulus on stress, whereas the latter mechanism is stretching-dominated and characterized by a power-law exponent 1/2. We demonstrate how material properties of the constituents, as well as the network microstructure, can affect the transition between the two stiffening mechanisms and, as such, control the dominant power-law scaling behavior.

  18. Linking Climate Risk, Policy Networks and Adaptation Planning in Public Lands

    NASA Astrophysics Data System (ADS)

    Lubell, M.; Schwartz, M.; Peters, C.

    2014-12-01

    Federal public land management agencies in the United States have engaged a variety of planning efforts to address climate adaptation. A major goal of these efforts is to build policy networks that enable land managers to access information and expertise needed for responding to local climate risks. This paper investigates whether the perceived and modeled climate risk faced by different land managers is leading to larger networks or more participating in climate adaptation. In theory, the benefits of climate planning networks are larger when land managers are facing more potential changes. The basic hypothesis is tested with a survey of public land managers from hundreds of local and regional public lands management units in the Southwestern United States, as well as other stakeholders involved with climate adaptation planning. All survey respondents report their perceptions of climate risk along a variety of dimensions, as well as their participation in climate adaptation planning and information sharing networks. For a subset of respondents, we have spatially explicity GIS data about their location, which will be linked with downscaled climate model data. With the focus on climate change, the analysis is a subset of the overall idea of linking social and ecological systems.

  19. Prestressed F-actin networks cross-linked by hinged filamins replicate mechanical properties of cells

    NASA Astrophysics Data System (ADS)

    Gardel, M. L.; Nakamura, F.; Hartwig, J. H.; Crocker, J. C.; Stossel, T. P.; Weitz, D. A.

    2006-02-01

    We show that actin filaments, shortened to physiological lengths by gelsolin and cross-linked with recombinant human filamins (FLNs), exhibit dynamic elastic properties similar to those reported for live cells. To achieve elasticity values of comparable magnitude to those of cells, the in vitro network must be subjected to external prestress, which directly controls network elasticity. A molecular requirement for the strain-related behavior at physiological conditionsis a flexible hinge found in FLNa and some FLNb molecules. Basic physical properties of the in vitro filamin-F-actin network replicate the essential mechanical properties of living cells. This physical behavior could accommodate passive deformation and internal organelle trafficking at low strains yet resist externally or internally generated high shear forces. cytoskeleton | cell mechanics | nonlinear rheology

  20. Impulse-induced optimum signal amplification in scale-free networks.

    PubMed

    Martínez, Pedro J; Chacón, Ricardo

    2016-04-01

    Optimizing information transmission across a network is an essential task for controlling and manipulating generic information-processing systems. Here, we show how topological amplification effects in scale-free networks of signaling devices are optimally enhanced when the impulse transmitted by periodic external signals (time integral over two consecutive zeros) is maximum. This is demonstrated theoretically by means of a star-like network of overdamped bistable systems subjected to generic zero-mean periodic signals and confirmed numerically by simulations of scale-free networks of such systems. Our results show that the enhancer effect of increasing values of the signal's impulse is due to a correlative increase of the energy transmitted by the periodic signals, while it is found to be resonant-like with respect to the topology-induced amplification mechanism.

  1. Impulse-induced optimum signal amplification in scale-free networks

    NASA Astrophysics Data System (ADS)

    Martínez, Pedro J.; Chacón, Ricardo

    2016-04-01

    Optimizing information transmission across a network is an essential task for controlling and manipulating generic information-processing systems. Here, we show how topological amplification effects in scale-free networks of signaling devices are optimally enhanced when the impulse transmitted by periodic external signals (time integral over two consecutive zeros) is maximum. This is demonstrated theoretically by means of a star-like network of overdamped bistable systems subjected to generic zero-mean periodic signals and confirmed numerically by simulations of scale-free networks of such systems. Our results show that the enhancer effect of increasing values of the signal's impulse is due to a correlative increase of the energy transmitted by the periodic signals, while it is found to be resonant-like with respect to the topology-induced amplification mechanism.

  2. Impulse-induced optimum signal amplification in scale-free networks.

    PubMed

    Martínez, Pedro J; Chacón, Ricardo

    2016-04-01

    Optimizing information transmission across a network is an essential task for controlling and manipulating generic information-processing systems. Here, we show how topological amplification effects in scale-free networks of signaling devices are optimally enhanced when the impulse transmitted by periodic external signals (time integral over two consecutive zeros) is maximum. This is demonstrated theoretically by means of a star-like network of overdamped bistable systems subjected to generic zero-mean periodic signals and confirmed numerically by simulations of scale-free networks of such systems. Our results show that the enhancer effect of increasing values of the signal's impulse is due to a correlative increase of the energy transmitted by the periodic signals, while it is found to be resonant-like with respect to the topology-induced amplification mechanism. PMID:27176316

  3. Ionically Cross-Linked Polymer Networks for the Multiple-Month Release of Small Molecules.

    PubMed

    Lawrence, Patrick G; Patil, Pritam S; Leipzig, Nic D; Lapitsky, Yakov

    2016-02-01

    Long-term (multiple-week or -month) release of small, water-soluble molecules from hydrogels remains a significant pharmaceutical challenge, which is typically overcome at the expense of more-complicated drug carrier designs. Such approaches are payload-specific and include covalent conjugation of drugs to base materials or incorporation of micro- and nanoparticles. As a simpler alternative, here we report a mild and simple method for achieving multiple-month release of small molecules from gel-like polymer networks. Densely cross-linked matrices were prepared through ionotropic gelation of poly(allylamine hydrochloride) (PAH) with either pyrophosphate (PPi) or tripolyphosphate (TPP), all of which are commonly available commercial molecules. The loading of model small molecules (Fast Green FCF and Rhodamine B dyes) within these polymer networks increases with the payload/network binding strength and with the PAH and payload concentrations used during encapsulation. Once loaded into the PAH/PPi and PAH/TPP ionic networks, only a few percent of the payload is released over multiple months. This extended release is achieved regardless of the payload/network binding strength and likely reflects the small hydrodynamic mesh size within the gel-like matrices. Furthermore, the PAH/TPP networks show promising in vitro cytocompatibility with model cells (human dermal fibroblasts), though slight cytotoxic effects were exhibited by the PAH/PPi networks. Taken together, the above findings suggest that PAH/PPi and (especially) PAH/TPP networks might be attractive materials for the multiple-month delivery of drugs and other active molecules (e.g., fragrances or disinfectants).

  4. Ionically Cross-Linked Polymer Networks for the Multiple-Month Release of Small Molecules.

    PubMed

    Lawrence, Patrick G; Patil, Pritam S; Leipzig, Nic D; Lapitsky, Yakov

    2016-02-01

    Long-term (multiple-week or -month) release of small, water-soluble molecules from hydrogels remains a significant pharmaceutical challenge, which is typically overcome at the expense of more-complicated drug carrier designs. Such approaches are payload-specific and include covalent conjugation of drugs to base materials or incorporation of micro- and nanoparticles. As a simpler alternative, here we report a mild and simple method for achieving multiple-month release of small molecules from gel-like polymer networks. Densely cross-linked matrices were prepared through ionotropic gelation of poly(allylamine hydrochloride) (PAH) with either pyrophosphate (PPi) or tripolyphosphate (TPP), all of which are commonly available commercial molecules. The loading of model small molecules (Fast Green FCF and Rhodamine B dyes) within these polymer networks increases with the payload/network binding strength and with the PAH and payload concentrations used during encapsulation. Once loaded into the PAH/PPi and PAH/TPP ionic networks, only a few percent of the payload is released over multiple months. This extended release is achieved regardless of the payload/network binding strength and likely reflects the small hydrodynamic mesh size within the gel-like matrices. Furthermore, the PAH/TPP networks show promising in vitro cytocompatibility with model cells (human dermal fibroblasts), though slight cytotoxic effects were exhibited by the PAH/PPi networks. Taken together, the above findings suggest that PAH/PPi and (especially) PAH/TPP networks might be attractive materials for the multiple-month delivery of drugs and other active molecules (e.g., fragrances or disinfectants). PMID:26811936

  5. Digital Signal Processing and Control for the Study of Gene Networks.

    PubMed

    Shin, Yong-Jun

    2016-04-22

    Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

  6. Digital Signal Processing and Control for the Study of Gene Networks

    PubMed Central

    Shin, Yong-Jun

    2016-01-01

    Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks. PMID:27102828

  7. A gel network constituted by rigid schizophyllan chains and nonpermanent cross-links.

    PubMed

    Fang, Yapeng; Takahashi, Rheo; Nishinari, Katsuyoshi

    2004-01-01

    This work reports a gel network formed by rigid schizophyllan (SPG) chains with Borax as a cross-linking agent. The formed cross-links are non-permanent and somewhat dynamic in nature because the cross-linking reaction is governed by a complexation equilibrium. Gelation processes are traced by dynamic viscoelastic measurements to examine the effects of Borax content, SPG concentration, temperature, salt concentration, salt type, and strain. The first-order kinetic model containing three parameters, t(0) (induction time), 1/tau(c) (gelation rate), and (saturated storage modulus), is successfully applied to describe the gelation of the SPG-Borax system. Gelation occurs faster at higher Borax content, higher SPG concentration, higher salt concentration, or lower temperature. Moreover the gelation is cation-type-specific. Storage modulus is a linear function of both Borax content and SPG concentration. The linear relationship between storage modulus and Borax content can be explained by a modified ideal rubber elasticity theory with a front factor alpha to take into account the presence of ineffective cross-links and the effect of SPG chain rigidity. On the other hand, the linear dependence of storage modulus on SPG concentration could be explained on the basis of chain-chain contacting behavior of extended SPG chains. Apparent activation energy and cross-linking enthalpy are calculated to be -74.5 and -32.4 kJ/mol for the present system. Strain sweep measurements manifest that the elasticity behavior of this gel starts to deviate from Gaussian-chain network at a small strain of 10%.

  8. Promoting Wired Links in Wireless Mesh Networks: An Efficient Engineering Solution

    PubMed Central

    Barekatain, Behrang; Raahemifar, Kaamran; Ariza Quintana, Alfonso; Triviño Cabrera, Alicia

    2015-01-01

    Wireless Mesh Networks (WMNs) cannot completely guarantee good performance of traffic sources such as video streaming. To improve the network performance, this study proposes an efficient engineering solution named Wireless-to-Ethernet-Mesh-Portal-Passageway (WEMPP) that allows effective use of wired communication in WMNs. WEMPP permits transmitting data through wired and stable paths even when the destination is in the same network as the source (Intra-traffic). Tested with four popular routing protocols (Optimized Link State Routing or OLSR as a proactive protocol, Dynamic MANET On-demand or DYMO as a reactive protocol, DYMO with spanning tree ability and HWMP), WEMPP considerably decreases the end-to-end delay, jitter, contentions and interferences on nodes, even when the network size or density varies. WEMPP is also cost-effective and increases the network throughput. Moreover, in contrast to solutions proposed by previous studies, WEMPP is easily implemented by modifying the firmware of the actual Ethernet hardware without altering the routing protocols and/or the functionality of the IP/MAC/Upper layers. In fact, there is no need for modifying the functionalities of other mesh components in order to work with WEMPPs. The results of this study show that WEMPP significantly increases the performance of all routing protocols, thus leading to better video quality on nodes. PMID:25793516

  9. A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders.

    PubMed

    Jiang, Peng; Scarpa, Joseph R; Fitzpatrick, Karrie; Losic, Bojan; Gao, Vance D; Hao, Ke; Summa, Keith C; Yang, He S; Zhang, Bin; Allada, Ravi; Vitaterna, Martha H; Turek, Fred W; Kasarskis, Andrew

    2015-05-01

    Sleep dysfunction and stress susceptibility are comorbid complex traits that often precede and predispose patients to a variety of neuropsychiatric diseases. Here, we demonstrate multilevel organizations of genetic landscape, candidate genes, and molecular networks associated with 328 stress and sleep traits in a chronically stressed population of 338 (C57BL/6J × A/J) F2 mice. We constructed striatal gene co-expression networks, revealing functionally and cell-type-specific gene co-regulations important for stress and sleep. Using a composite ranking system, we identified network modules most relevant for 15 independent phenotypic categories, highlighting a mitochondria/synaptic module that links sleep and stress. The key network regulators of this module are overrepresented with genes implicated in neuropsychiatric diseases. Our work suggests that the interplay among sleep, stress, and neuropathology emerges from genetic influences on gene expression and their collective organization through complex molecular networks, providing a framework for interrogating the mechanisms underlying sleep, stress susceptibility, and related neuropsychiatric disorders.

  10. Promoting wired links in wireless mesh networks: an efficient engineering solution.

    PubMed

    Barekatain, Behrang; Raahemifar, Kaamran; Ariza Quintana, Alfonso; Triviño Cabrera, Alicia

    2015-01-01

    Wireless Mesh Networks (WMNs) cannot completely guarantee good performance of traffic sources such as video streaming. To improve the network performance, this study proposes an efficient engineering solution named Wireless-to-Ethernet-Mesh-Portal-Passageway (WEMPP) that allows effective use of wired communication in WMNs. WEMPP permits transmitting data through wired and stable paths even when the destination is in the same network as the source (Intra-traffic). Tested with four popular routing protocols (Optimized Link State Routing or OLSR as a proactive protocol, Dynamic MANET On-demand or DYMO as a reactive protocol, DYMO with spanning tree ability and HWMP), WEMPP considerably decreases the end-to-end delay, jitter, contentions and interferences on nodes, even when the network size or density varies. WEMPP is also cost-effective and increases the network throughput. Moreover, in contrast to solutions proposed by previous studies, WEMPP is easily implemented by modifying the firmware of the actual Ethernet hardware without altering the routing protocols and/or the functionality of the IP/MAC/Upper layers. In fact, there is no need for modifying the functionalities of other mesh components in order to work with WEMPPs. The results of this study show that WEMPP significantly increases the performance of all routing protocols, thus leading to better video quality on nodes. PMID:25793516

  11. Synaptic signal streams generated by ex vivo neuronal networks contain non-random, complex patterns.

    PubMed

    Lee, Sangmook; Zemianek, Jill M; Shultz, Abraham; Vo, Anh; Maron, Ben Y; Therrien, Mikaela; Courtright, Christina; Guaraldi, Mary; Yanco, Holly A; Shea, Thomas B

    2014-11-01

    Cultured embryonic neurons develop functional networks that transmit synaptic signals over multiple sequentially connected neurons as revealed by multi-electrode arrays (MEAs) embedded within the culture dish. Signal streams of ex vivo networks contain spikes and bursts of varying amplitude and duration. Despite the random interactions inherent in dissociated cultures, neurons are capable of establishing functional ex vivo networks that transmit signals among synaptically connected neurons, undergo developmental maturation, and respond to exogenous stimulation by alterations in signal patterns. These characteristics indicate that a considerable degree of organization is an inherent property of neurons. We demonstrate herein that (1) certain signal types occur more frequently than others, (2) the predominant signal types change during and following maturation, (3) signal predominance is dependent upon inhibitory activity, and (4) certain signals preferentially follow others in a non-reciprocal manner. These findings indicate that the elaboration of complex signal streams comprised of a non-random distribution of signal patterns is an emergent property of ex vivo neuronal networks.

  12. Involvement of epidermal growth factor receptor-linked signaling responses in Pseudomonas fluorescens-infected alveolar epithelial cells.

    PubMed

    Choi, Hye Jin; Seo, Chan Hee; Park, Seong Hwan; Yang, Hyun; Do, Kee Hun; Kim, Juil; Kim, Hyung-Kab; Chung, Duk-Hwa; Ahn, Jung Hoon; Moon, Yuseok

    2011-05-01

    Pseudomonas fluorescens is an opportunistic indoor pathogen that can cause severe airway proinflammatory responses. Pulmonary epithelium, like other mucosal epithelial linings of the body, constitutes the first line of defense against airway microbial pathogens. Mucosal epithelial cells can be a sentinel of pathogenic bacteria via stimulation of specific cell surface receptors, including the epidermal growth factor receptor (EGFR) and Toll-like receptor (TLR). This study addressed the involvement of EGFR in airway epithelial pathogenesis by P. fluorescens. Human A549 pneumocytes showed prolonged production of proinflammatory interleukin-8 (IL-8) in response to infection with P. fluorescens, which was via the nuclear factor-kappa B (NF-κB) signaling pathway. Production of proinflammatory cytokine IL-8 was not mediated by P. fluorescens lipopolysaccharide, a representative TLR4 agonist, but was mediated through EGFR-linked signals activated by the opportunistic bacteria. Moreover, EGFR signals were involved in NF-κB signal-mediated production of proinflammatory cytokines. Along with persistent NF-κB activation, P. fluorescens enhanced the EGFR phosphorylation and subsequent activation of downstream mediators, including protein kinase B or extracellular-signal-regulated kinases 1/2. Blocking of EGFR-linked signals increased epithelial susceptibility to pathogen-induced epithelial cell death, suggesting protective roles of EGFR signals. Thus, airway epithelial exposure to P. fluorescens can trigger antiapoptotic responses via EGFR and proinflammatory responses via TLR4-independent NF-κB signaling pathway in human pneumocytes.

  13. Linking Alzheimer's disease and type 2 diabetes mellitus via aberrant insulin signaling and inflammation.

    PubMed

    Kamal, Mohammad A; Priyamvada, Shubha; Anbazhagan, Arivarasu N; Jabir, Nasimudeen R; Tabrez, Shams; Greig, Nigel H

    2014-03-01

    Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are two progressive and devastating health disorders afflicting millions of people worldwide. The probability and incidence of both have increased considerably in recent years consequent to increased longevity and population growth. Progressively more links are being continuously found between inflammation and central nervous system disorders like AD, Parkinson's disease, Huntington's disease, motor neuron disease, multiple sclerosis, stroke, traumatic brain injury and even cancers of the nervous tissue. The depth of the relationship depends on the timing and extent of anti- or pro-inflammatory gene expression. Inflammation has also been implicated in T2DM. Misfolding and fibrillization (of tissue specific and/or non-specific proteins) are features common to both AD and T2DM and are induced by as well as contribute to inflammation and stress (oxidative/ glycation). This review appraises the roles of inflammation and abnormalities in the insulin signaling system as important shared features of T2DM and AD. The capacity of anti-cholinesterases in reducing the level of certain common inflammatory markers in particular if they may provide therapeutic potential to mitigate awry mechanisms leading to AD.

  14. Hippo signaling regulates microprocessor and links cell-density-dependent miRNA biogenesis to cancer.

    PubMed

    Mori, Masaki; Triboulet, Robinson; Mohseni, Morvarid; Schlegelmilch, Karin; Shrestha, Kriti; Camargo, Fernando D; Gregory, Richard I

    2014-02-27

    Global downregulation of microRNAs (miRNAs) is commonly observed in human cancers and can have a causative role in tumorigenesis. The mechanisms responsible for this phenomenon remain poorly understood. Here, we show that YAP, the downstream target of the tumor-suppressive Hippo-signaling pathway regulates miRNA biogenesis in a cell-density-dependent manner. At low cell density, nuclear YAP binds and sequesters p72 (DDX17), a regulatory component of the miRNA-processing machinery. At high cell density, Hippo-mediated cytoplasmic retention of YAP facilitates p72 association with Microprocessor and binding to a specific sequence motif in pri-miRNAs. Inactivation of the Hippo pathway or expression of constitutively active YAP causes widespread miRNA suppression in cells and tumors and a corresponding posttranscriptional induction of MYC expression. Thus, the Hippo pathway links contact-inhibition regulation to miRNA biogenesis and may be responsible for the widespread miRNA repression observed in cancer.

  15. Stress-responsive sestrins link p53 with redox regulation and mammalian target of rapamycin signaling.

    PubMed

    Budanov, Andrei V

    2011-09-15

    The tumor suppressor p53 protects organisms from most types of cancer through multiple mechanisms. The p53 gene encodes a stress-activated transcriptional factor that transcriptionally regulates a large set of genes with versatile functions. These p53-activated genes mitigate consequences of stress regulating cell viability, growth, proliferation, repair, and metabolism. Recently, we described a novel antioxidant function of p53, which is important for its tumor suppressor activity. Among the many antioxidant genes activated by p53, Sestrins (Sesns) are critical for suppression of reactive oxygen species (ROS) and protection from oxidative stress, transformation, and genomic instability. Sestrins can regulate ROS through their direct effect on antioxidant peroxiredoxin proteins and through the AMP-activated protein kinase-target of rapamycin signaling pathway. The AMP-activated protein kinase-target of rapamycin axis is critical for regulation of metabolism and autophagy, two processes associated with ROS production, and deregulation of this pathway increases vulnerability of the organism to stress, aging, and age-related diseases, including cancer. Recently, we have shown that inactivation of Sestrin in fly causes accumulation of age-associated damage. Hence, Sestrins can link p53 with aging and age-related diseases. PMID:20712410

  16. Fascin links Btl/FGFR signalling to the actin cytoskeleton during Drosophila tracheal morphogenesis.

    PubMed

    Okenve-Ramos, Pilar; Llimargas, Marta

    2014-02-01

    A key challenge in normal development and in disease is to elucidate the mechanisms of cell migration. Here we approach this question using the tracheal system of Drosophila as a model. Tracheal cell migration requires the Breathless/FGFR pathway; however, how the pathway induces migration remains poorly understood. We find that the Breathless pathway upregulates singed at the tip of tracheal branches, and that this regulation is functionally relevant. singed encodes Drosophila Fascin, which belongs to a conserved family of actin-bundling proteins involved in cancer progression and metastasis upon misregulation. We show that singed is required for filopodia stiffness and proper morphology of tracheal tip cells, defects that correlate with an abnormal actin organisation. We propose that singed-regulated filopodia and cell fronts are required for timely and guided branch migration and for terminal branching and branch fusion. We find that singed requirements rely on its actin-bundling activity controlled by phosphorylation, and that active Singed can promote tip cell features. Furthermore, we find that singed acts in concert with forked, another actin cross-linker. The absence of both cross-linkers further stresses the relevance of tip cell morphology and filopodia for tracheal development. In summary, our results on the one hand reveal a previously undescribed role for forked in the organisation of transient actin structures such as filopodia, and on the other hand identify singed as a new target of Breathless signal, establishing a link between guidance cues, the actin cytoskeleton and tracheal morphogenesis.

  17. p70S6 kinase is a critical node that integrates HER-family and PI3 kinase signaling networks

    PubMed Central

    Axelrod, Mark J.; Gordon, Vicki; Mendez, Rolando E.; Leimgruber, Stephanie S.; Conaway, Mark R.; Sharlow, Elizabeth R.; Jameson, MarkJ.; Gioeli, Daniel G.; Weber, Michael J.

    2014-01-01

    Therapies targeting oncogenic drivers rapidly induce compensatory adaptive responses that blunt drug effectiveness, contributing to therapeutic resistance. Adaptive responses are characteristic of robust cell signaling networks, and thus there is increasing interest in drug combinations that co-target the driver and the adaptive response. An alternative approach to co-inhibiting oncogenic and adaptive targets is to identify a critical node where the activities of these targets converge. Nodes of convergence between signaling modules represent potential therapeutic vulnerabilities because their inhibition could result in collapse of the network, leading to enhanced cytotoxicity. In this report we demonstrate that p70S6 kinase (p70S6K) can function as a critical node linking HER-family and phosphoinositide-3-kinase (PI3K) pathway signaling. We used high-throughput combinatorial drug screening to identify adaptive survival responses to targeted therapies, and found that HER-family and PI3K represented compensatory signaling pathways. Co-targeting these pathways with drug combinations caused synergistic cytotoxicity in cases where inhibition of neither target was effective as a monotherapy. We utilized Reverse Phase Protein Arrays and determined that phosphorylation of ribosomal protein S6 was synergistically down-regulated upon HER-family and PI3K/mammalian target of rapamycin (mTOR) co-inhibition. Expression of constitutively active p70S6K protected against apoptosis induced by combined HER-family and PI3K/mTOR inhibition. Direct inhibition of p70S6K with small molecule inhibitors phenocopied HER-family and PI3K/mTOR co-inhibition. These data implicate p70S6K as a critical node in the HER-family/PI3K signaling network. The ability of direct inhibitors of p70S6K to phenocopy co-inhibition of two upstream signaling targets indicates that identification and targeting of critical nodes can overcome adaptive resistance to targeted therapies. PMID:24662264

  18. Impact of link deletions on public cooperation in scale-free networks

    NASA Astrophysics Data System (ADS)

    Jiang, Luo-Luo; Perc, Matjaž; Wang, Wen-Xu; Lai, Ying-Cheng; Wang, Bing-Hong

    2011-02-01

    Working together in groups may be beneficial if compared to isolated efforts. Yet this is true only if all group members contribute to the success. If not, group efforts may act detrimentally on the fitness of their members. Here we study the evolution of cooperation in public-goods games on scale-free networks that are subject to deletion of links connected to the highest-degree individuals, i.e., on network that are under attack. We focus on the case where all groups a player belongs to are considered for the determination of payoffs; the so-called multi-group public-goods games. We find that the effect of link deletions on the evolution of cooperation is predominantly detrimental, although there exist regions of the multiplication factor where the existence of an "optimal" number of removed links for the deterioration of cooperation can also be demonstrated. The findings are explained by means of wealth distributions and analytical approximations, confirming that socially diverse states are crucial for the successful evolution of cooperation.

  19. An integrated signal transduction network of macrophage migration inhibitory factor.

    PubMed

    Subbannayya, Tejaswini; Variar, Prathyaksha; Advani, Jayshree; Nair, Bipin; Shankar, Subramanian; Gowda, Harsha; Saussez, Sven; Chatterjee, Aditi; Prasad, T S Keshava

    2016-06-01

    Macrophage migration inhibitory factor (MIF) is a glycosylated multi-functional protein that acts as an enzyme as well as a cytokine. MIF mediates its actions through a cell surface class II major histocompatibility chaperone, CD74 and co-receptors such as CD44, CXCR2, CXCR4 or CXCR7. MIF has been implicated in the pathogenesis of several acute and chronic inflammatory diseases. Although MIF is a molecule of biomedical importance, a public resource of MIF signaling pathway is currently lacking. In view of this, we carried out detailed data mining and documentation of the signaling events pertaining to MIF from published literature and developed an integrated reaction map of MIF signaling. This resulted in the cataloguing of 68 molecules belonging to MIF signaling pathway, which includes 24 protein-protein interactions, 44 post-translational modifications, 11 protein translocation events and 8 activation/inhibition events. In addition, 65 gene regulation events at the mRNA levels induced by MIF signaling have also been catalogued. This signaling pathway has been integrated into NetPath ( http://www.netpath.org ), a freely available human signaling pathway resource developed previously by our group. The MIF pathway data is freely available online in various community standard data exchange formats. We expect that data on signaling events and a detailed signaling map of MIF will provide the scientific community with an improved platform to facilitate further molecular as well as biomedical investigations on MIF. PMID:27139435

  20. Bioorthogonally cross-linked hydrogel network with precisely controlled disintegration time over a broad range.

    PubMed

    Xu, Jianwen; Feng, Ellva; Song, Jie

    2014-03-19

    Hydrogels with predictable degradation are highly desired for biomedical applications where timely disintegration of the hydrogel (e.g., drug delivery, guided tissue regeneration) is required. However, precisely controlling hydrogel degradation over a broad range in a predictable manner is challenging due to limited intrinsic variability in the degradation rate of liable bonds and difficulties in modeling degradation kinetics for complex polymer networks. More often than not, empirical tuning of the degradation profile results in undesired changes in other properties. Here we report a simple but versatile hydrogel platform that allows us to formulate hydrogels with predictable disintegration time from 2 to >250 days yet comparable macroscopic physical properties. This platform is based on a well-defined network formed by two pairs of four-armed polyethylene glycol macromers terminated with azide and dibenzocyclooctyl groups, respectively, via labile or stable linkages. The high-fidelity bioorthogonal reaction between the symmetric hydrophilic macromers enables robust cross-linking in water, phosphate-buffered saline, and cell culture medium to afford tough hydrogels capable of withstanding >90% compressive strain. Strategic placement of labile ester linkages near the cross-linking site within this superhydrophilic network, accomplished by adjustments of the ratio of the macromers used, enables broad tuning of the disintegration rates precisely matching with the theoretical predictions based on first-order linkage cleavage kinetics. This platform can be exploited for applications where a precise degradation rate is targeted.

  1. Concentric Archimedean polyhedra: Mn(III)12Mn(II)9 aggregates linked into a cubic network.

    PubMed

    Nayak, Sanjit; Lan, Yanhua; Clérac, Rodolphe; Anson, Christopher E; Powell, Annie K

    2008-11-30

    A Mn(III)(12)Mn(II)(9) aggregate has a structure built up of concentric polyhedra with these units linked into a cubic network to give a remarkably pleasing structure isotypic with iron pyrites. PMID:19009052

  2. Research on the Wire Network Signal Prediction Based on the Improved NNARX Model

    NASA Astrophysics Data System (ADS)

    Zhang, Zipeng; Fan, Tao; Wang, Shuqing

    It is difficult to obtain accurately the wire net signal of power system's high voltage power transmission lines in the process of monitoring and repairing. In order to solve this problem, the signal measured in remote substation or laboratory is employed to make multipoint prediction to gain the needed data. But, the obtained power grid frequency signal is delay. In order to solve the problem, an improved NNARX network which can predict frequency signal based on multi-point data collected by remote substation PMU is describes in this paper. As the error curved surface of the NNARX network is more complicated, this paper uses L-M algorithm to train the network. The result of the simulation shows that the NNARX network has preferable predication performance which provides accurate real time data for field testing and maintenance.

  3. Signaling Networks Converge on TORC1-SREBP Activity to Promote Endoplasmic Reticulum Homeostasis

    PubMed Central

    Sanchez-Alvarez, Miguel; Finger, Fabian; Arias-Garcia, Maria del Mar; Bousgouni, Vicky; Pascual-Vargas, Patricia; Bakal, Chris

    2014-01-01

    The function and capacity of the endoplasmic reticulum (ER) is determined by multiple processes ranging from the local regulation of peptide translation, translocation, and folding, to global changes in lipid composition. ER homeostasis thus requires complex interactions amongst numerous cellular components. However, describing the networks that maintain ER function during changes in cell behavior and environmental fluctuations has, to date, proven difficult. Here we perform a systems-level analysis of ER homeostasis, and find that although signaling networks that regulate ER function have a largely modular architecture, the TORC1-SREBP signaling axis is a central node that integrates signals emanating from different sub-networks. TORC1-SREBP promotes ER homeostasis by regulating phospholipid biosynthesis and driving changes in ER morphology. In particular, our network model shows TORC1-SREBP serves to integrate signals promoting growth and G1-S progression in order to maintain ER function during cell proliferation. PMID:25007267

  4. Construction of cell type-specific logic models of signaling networks using CellNOpt.

    PubMed

    Morris, Melody K; Melas, Ioannis; Saez-Rodriguez, Julio

    2013-01-01

    Mathematical models are useful tools for understanding protein signaling networks because they provide an integrated view of pharmacological and toxicological processes at the molecular level. Here we describe an approach previously introduced based on logic modeling to generate cell-specific, mechanistic and predictive models of signal transduction. Models are derived from a network encoding prior knowledge that is trained to signaling data, and can be either binary (based on Boolean logic) or quantitative (using a recently developed formalism, constrained fuzzy logic). The approach is implemented in the freely available tool CellNetOptimizer (CellNOpt). We explain the process CellNOpt uses to train a prior knowledge network to data and illustrate its application with a toy example as well as a realistic case describing signaling networks in the HepG2 liver cancer cell line.

  5. Classification of eddy current signals using fuzzy logic and neural networks

    NASA Astrophysics Data System (ADS)

    Ewald, Hartmut; Stieper, Michael

    1996-11-01

    The nondestructive eddy current methods are commonly used for automated defect inspection to detect cracks in materials which are used in cars, power and aircraft industries. The eddy current signal from a infinitely long crack can be classified with the help of the fuzzy logic and the neural network techniques. A rule based fuzzy logic classification guarantees better results than fuzzy-cluster- means algorithm, because the classification results can be increased in this case step by step. By using the neural network for the classification of the crack signals it is very important to have a good 'learning pattern.' The advantage of time-delay networks in this application is the fact that the network can 'learn' the eddy-current time signal; a signal preprocessing is not necessary.

  6. Generalization characteristics of complex-valued feedforward neural networks in relation to signal coherence.

    PubMed

    Hirose, Akira; Yoshida, Shotaro

    2012-04-01

    Applications of complex-valued neural networks (CVNNs) have expanded widely in recent years-in particular in radar and coherent imaging systems. In general, the most important merit of neural networks lies in their generalization ability. This paper compares the generalization characteristics of complex-valued and real-valued feedforward neural networks in terms of the coherence of the signals to be dealt with. We assume a task of function approximation such as interpolation of temporal signals. Simulation and real-world experiments demonstrate that CVNNs with amplitude-phase-type activation function show smaller generalization error than real-valued networks, such as bivariate and dual-univariate real-valued neural networks. Based on the results, we discuss how the generalization characteristics are influenced by the coherence of the signals depending on the degree of freedom in the learning and on the circularity in neural dynamics.

  7. A methodology for the structural and functional analysis of signaling and regulatory networks

    PubMed Central

    Klamt, Steffen; Saez-Rodriguez, Julio; Lindquist, Jonathan A; Simeoni, Luca; Gilles, Ernst D

    2006-01-01

    Background Structural analysis of cellular interaction networks contributes to a deeper understanding of network-wide interdependencies, causal relationships, and basic functional capabilities. While the structural analysis of metabolic networks is a well-established field, similar methodologies have been scarcely developed and applied to signaling and regulatory networks. Results We propose formalisms and methods, relying on adapted and partially newly introduced approaches, which facilitate a structural analysis of signaling and regulatory networks with focus on functional aspects. We use two different formalisms to represent and analyze interaction networks: interaction graphs and (logical) interaction hypergraphs. We show that, in interaction graphs, the determination of feedback cycles and of all the signaling paths between any pair of species is equivalent to the computation of elementary modes known from metabolic networks. Knowledge on the set of signaling paths and feedback loops facilitates the computation of intervention strategies and the classification of compounds into activators, inhibitors, ambivalent factors, and non-affecting factors with respect to a certain species. In some cases, qualitative effects induced by perturbations can be unambiguously predicted from the network scheme. Interaction graphs however, are not able to capture AND relationships which do frequently occur in interaction networks. The consequent logical concatenation of all the arcs pointing into a species leads to Boolean networks. For a Boolean representation of cellular interaction networks we propose a formalism based on logical (or signed) interaction hypergraphs, which facilitates in particular a logical steady state analysis (LSSA). LSSA enables studies on the logical processing of signals and the identification of optimal intervention points (targets) in cellular networks. LSSA also reveals network regions whose parametrization and initial states are crucial for the

  8. A Novel Clustering Algorithm for Mobile Ad Hoc Networks Based on Determination of Virtual Links' Weight to Increase Network Stability

    PubMed Central

    Karimi, Abbas; Afsharfarnia, Abbas; Zarafshan, Faraneh; Al-Haddad, S. A. R.

    2014-01-01

    The stability of clusters is a serious issue in mobile ad hoc networks. Low stability of clusters may lead to rapid failure of clusters, high energy consumption for reclustering, and decrease in the overall network stability in mobile ad hoc network. In order to improve the stability of clusters, weight-based clustering algorithms are utilized. However, these algorithms only use limited features of the nodes. Thus, they decrease the weight accuracy in determining node's competency and lead to incorrect selection of cluster heads. A new weight-based algorithm presented in this paper not only determines node's weight using its own features, but also considers the direct effect of feature of adjacent nodes. It determines the weight of virtual links between nodes and the effect of the weights on determining node's final weight. By using this strategy, the highest weight is assigned to the best choices for being the cluster heads and the accuracy of nodes selection increases. The performance of new algorithm is analyzed by using computer simulation. The results show that produced clusters have longer lifetime and higher stability. Mathematical simulation shows that this algorithm has high availability in case of failure. PMID:25114965

  9. A novel clustering algorithm for mobile ad hoc networks based on determination of virtual links' weight to increase network stability.

    PubMed

    Karimi, Abbas; Afsharfarnia, Abbas; Zarafshan, Faraneh; Al-Haddad, S A R

    2014-01-01

    The stability of clusters is a serious issue in mobile ad hoc networks. Low stability of clusters may lead to rapid failure of clusters, high energy consumption for reclustering, and decrease in the overall network stability in mobile ad hoc network. In order to improve the stability of clusters, weight-based clustering algorithms are utilized. However, these algorithms only use limited features of the nodes. Thus, they decrease the weight accuracy in determining node's competency and lead to incorrect selection of cluster heads. A new weight-based algorithm presented in this paper not only determines node's weight using its own features, but also considers the direct effect of feature of adjacent nodes. It determines the weight of virtual links between nodes and the effect of the weights on determining node's final weight. By using this strategy, the highest weight is assigned to the best choices for being the cluster heads and the accuracy of nodes selection increases. The performance of new algorithm is analyzed by using computer simulation. The results show that produced clusters have longer lifetime and higher stability. Mathematical simulation shows that this algorithm has high availability in case of failure.

  10. Knowledge representation model for systems-level analysis of signal transduction networks.

    PubMed

    Lee, Dong-Yup; Zimmer, Ralf; Lee, Sang-Yup; Hanisch, Daniel; Park, Sunwon

    2004-01-01

    A Petri-net based model for knowledge representation has been developed to describe as explicitly and formally as possible the molecular mechanisms of cell signaling and their pathological implications. A conceptual framework has been established for reconstructing and analyzing signal transduction networks on the basis of the formal representation. Such a conceptual framework renders it possible to qualitatively understand the cell signaling behavior at systems-level. The mechanisms of the complex signaling network are explored by applying the established framework to the signal transduction induced by potent proinflammatory cytokines, IL-1beta and TNF-alpha The corresponding expert-knowledge network is constructed to evaluate its mechanisms in detail. This strategy should be useful in drug target discovery and its validation.

  11. Beyond the wiring diagram: signalling through complex neuromodulator networks

    PubMed Central

    Brezina, Vladimir

    2010-01-01

    During the computations performed by the nervous system, its ‘wiring diagram’—the map of its neurons and synaptic connections—is dynamically modified and supplemented by multiple actions of neuromodulators that can be so complex that they can be thought of as constituting a biochemical network that combines with the neuronal network to perform the computation. Thus, the neuronal wiring diagram alone is not sufficient to specify, and permit us to understand, the computation that underlies behaviour. Here I review how such modulatory networks operate, the problems that their existence poses for the experimental study and conceptual understanding of the computations performed by the nervous system, and how these problems may perhaps be solved and the computations understood by considering the structural and functional ‘logic’ of the modulatory networks. PMID:20603357

  12. A Study of an Optical Lunar Surface Communications Network with High Bandwidth Direct to Earth Link

    NASA Technical Reports Server (NTRS)

    Wilson, K.; Biswas, A.; Schoolcraft, J.

    2011-01-01

    A lunar surface systems study explores the application of optical communications to support a high bandwidth data link from a lunar relay satellite and from fixed lunar assets. The results show that existing 1-m ground stations could provide more than 99% coverage of the lunar terminal at 100Mb/s data rates from a lunar relay satellite and in excess of 200Mb/s from a fixed terminal on the lunar surface. We have looked at the effects of the lunar regolith and its removal on optical samples. Our results indicate that under repeated dust removal episodes sapphire rather than fused silica would be a more durable material for optical surfaces. Disruption tolerant network protocols can minimize the data loss due to link dropouts. We report on the preliminary results of the DTN protocol implemented over the optical carrier.

  13. A maintenance scheme of communication link in mobile robot ad hoc networks based on potential field

    NASA Astrophysics Data System (ADS)

    Jiang, Hong; Jin, WenPing; Yang, GyoYing; Li, LeiMin

    2007-12-01

    Maintaining communication link in mobile robot networks between task robots and a control center is very important in some urgent application occasions such as remote danger detections. To offer a reliable multi-hop communication link, a link maintaining scheme based on artificial potential field is presented. The scheme is achieved by a task robot and communication relay ones. The task robot performs predefined tasks, and relay ones are simple robots which form a communication relay chain. When robots move towards destination in formation, a kind of attractive force created by communication quality is added to traditional potential field, and relay robots follow the task robot and automatically stop at adequate locations to form a relay chain from the control station to the task robot. In order to increase relay usage efficiency, when some relays are replaced by other short cut relays, the redundant relays can be reused by initiating another moving toward specified location. Simulation results show that the scheme can provide a reliable multi-hop communication link, and that the communication connection can be obtained through minimal number of relays.

  14. Gelatin hydrogels cross-linked with bis(vinylsulfonyl)methane (BVSM): 1. The chemical networks.

    PubMed

    Hellio-Serughetti, Dominique; Djabourov, Madeleine

    2006-09-26

    This paper deals with chemical gelation of gelatin in the presence of a cross-linker, bis(vinylsulfonyl)methane (BVSM), which is able to create covalent C-N bonds with amine groups. The investigation is performed at 40 degrees C, where no triple helices are present. Gelatin is in random coil conformation. The influence of various parameters (gelatin concentration, cross-linker concentration, and pH (number of reacting sites along the gelatin chain)) was examined. Gel formation was followed by rheological and thermodynamic measurements (microcalorimetry) versus time (kinetic measurements). Furthermore, the storage moduli were compared to the number of links formed in the course of gelation. The experiments show that, within the experimental range investigated, a fully homogeneous network is not reached; the chemical gels, even upon completion of the reactions, are still in the critical domain, near the threshold. A power law behavior was put in evidence for the shear modulus versus the distance to the gel point, expressed as the concentration of links per gelatin chain. The exponent (f = 3.4 +/- 0.3) is close to that expected for the vulcanization of long chains. The storage moduli can be superposed on a single curve where the abscissa is the product of the number of C-N links per unit volume and the gelatin concentration at an exponent equal to -0.76 +/- 0.03. This exponent suggests the role of entanglements for interchain cross-linking. PMID:16981770

  15. Reduction of resting state network segregation is linked to disorders of consciousness

    NASA Astrophysics Data System (ADS)

    Rudas, Jorge; Martínez, Darwin; Guaje, Javier; Demertzi, Athena; Heine, Lizette; Tshibanda, Luaba; Soddu, Andrea; Laureys, Steven; Gómez, Francisco

    2015-12-01

    Recent evidence suggests that healthy brain is organized on large-scale in regions spatially distant and partially temporally synchronized. These regions commonly are called Resting State Networks (RSNs). Many RSNs has been identified in multiples spatial scales in healthy subjects and their interactions has been used to define the functional network connectivity (FNC). The main idea in FNC is that the dynamic shown in the interactions among RSNs in control subjects, can change in pathological and pharmacological conditions. However, this hypothesis assumes that functional structure of healthy brain, remains in other brain states or conditions. In this work, we proposed a novel methodology in order to find the new brain functional structure for disorders of consciousness conditions, based on multi-objective optimization approach. Particularly, we find the best partition of RSNs set, that maximize two modularity measures (Kapur and Otsu measures). Our results suggest that the brain segregation level, may be linked to consciousness level.

  16. Ophthalmology on social networking sites: an observational study of Facebook, Twitter, and LinkedIn

    PubMed Central

    Micieli, Jonathan A; Tsui, Edmund

    2015-01-01

    Background The use of social media in ophthalmology remains largely unknown. Our aim was to evaluate the extent and involvement of ophthalmology journals, professional associations, trade publications, and patient advocacy and fundraising groups on social networking sites. Methods An archived list of 107 ophthalmology journals from SCImago, trade publications, professional ophthalmology associations, and patient advocacy organizations were searched for their presence on Facebook, Twitter, and LinkedIn. Activity and popularity of each account was quantified by using the number of “likes” on Facebook, the number of followers on Twitter, and members on LinkedIn. Results Of the 107 journals ranked by SCImago, 21.5% were present on Facebook and 18.7% were present on Twitter. Journal of Community Eye Health was the most popular on Facebook and JAMA Ophthalmology was most popular on Twitter. Among the 133 members of the International Council of Ophthalmology, 17.3% were present on Facebook, 12.8% were present on Twitter, and 7.5% were present on LinkedIn. The most popular on Facebook was the International Council of Ophthalmology, and the American Academy of Ophthalmology was most popular on Twitter and LinkedIn. Patient advocacy organizations were more popular on all sites compared with journals, professional association, and trade publications. Among the top ten most popular pages in each category, patient advocacy groups were most active followed by trade publications, professional associations, and journals. Conclusion Patient advocacy groups lead the way in social networking followed by professional organizations and journals. Although some journals use social media, most have yet to engage its full potential and maximize the number of potential interested individuals. PMID:25709390

  17. The calcineurin signaling network evolves via conserved kinase-phosphatase modules that transcend substrate identity.

    PubMed

    Goldman, Aaron; Roy, Jagoree; Bodenmiller, Bernd; Wanka, Stefanie; Landry, Christian R; Aebersold, Ruedi; Cyert, Martha S

    2014-08-01

    To define a functional network for calcineurin, the conserved Ca(2+)/calmodulin-regulated phosphatase, we systematically identified its substrates in S. cerevisiae using phosphoproteomics and bioinformatics, followed by copurification and dephosphorylation assays. This study establishes new calcineurin functions and reveals mechanisms that shape calcineurin network evolution. Analyses of closely related yeasts show that many proteins were recently recruited to the network by acquiring a calcineurin-recognition motif. Calcineurin substrates in yeast and mammals are distinct due to network rewiring but, surprisingly, are phosphorylated by similar kinases. We postulate that corecognition of conserved substrate features, including phosphorylation and docking motifs, preserves calcineurin-kinase opposition during evolution. One example we document is a composite docking site that confers substrate recognition by both calcineurin and MAPK. We propose that conserved kinase-phosphatase pairs define the architecture of signaling networks and allow other connections between kinases and phosphatases to develop that establish common regulatory motifs in signaling networks.

  18. Stress Enhanced Gelation in α-Actinin-4 Cross-linked Actin Networks

    NASA Astrophysics Data System (ADS)

    Yao, Norman; Broedersz, Chase; Depken, Martin; Becker, Daniel; Pollak, Martin; Mackintosh, Frederick; Weitz, David

    2012-02-01

    A hallmark of biopolymer networks is their exquisite sensitivity to stress, demonstrated for example, by pronounced nonlinear elastic stiffening. Typically, they also yield under increased static load, providing a mechanism to achieve fluid-like behavior. In this talk, I will demonstrate an unexpected dynamical behavior in biopolymer networks consisting of F-actin cross-linked by a physiological actin binding protein, α-Actinin-4. Applied stress actually enhances gelation of these networks by delaying the onset of structural relaxation and network flow, thereby extending the regime of solid-like behavior to much lower frequencies. By using human kidney disease-associated mutant cross-linkers with varying binding affinities, we propose a molecular origin for this stress-enhanced gelation: It arises from the increased binding affinity of the cross-linker under load, characteristic of catch-bond-like behavior. This property may have important biological implications for intracellular mechanics, representing as it does a qualitatively new class of material behavior.

  19. TALON - The Telescope Alert Operation Network System : intelligent linking of distributed autonomous robotic telescopes

    SciTech Connect

    White, R. R.; Wren, J.; Davis, H. R.; Galassi, M. C.; Starr, D. L.; Vestrand, W. T.; Wozniak, P. R.

    2004-01-01

    The internet has brought about great change in the astronomical community, but this interconnectivity is just starting to be exploited for use in instrumentation. Utilizing the internet for communicating between distributed astronomical systems is still in its infancy, but it already shows great potential. Here we present an example of a distributed network of telescopes that performs more efficienfiy in synchronous operation than as individual instruments. RAPid Telescopes for Optical Response (RAPTOR) is a system of telescopes at LANL that has intelligent intercommunication, combined with wide-field optics, temporal monitoring software, and deep-field follow-up capability all working in closed-loop real-time operation. The Telescope ALert Operations Network (TALON) is a network server that allows intercommunication of alert triggers from external and internal resources and controls the distribution of these to each of the telescopes on the network. TALON is designed to grow, allowing any number of telescopes to be linked together and communicate. Coupled with an intelligent alert client at each telescope, it can analyze and respond to each distributed TALON alert based on the telescopes needs and schedule.

  20. Response of biopolymer networks governed by the physical properties of cross-linking molecules.

    PubMed

    Wei, Xi; Zhu, Qian; Qian, Jin; Lin, Yuan; Shenoy, V B

    2016-03-01

    In this study, we examine how the physical properties of cross-linking molecules affect the bulk response of bio-filament networks, an outstanding question in the study of biological gels and the cytoskeleton. We show that the stress-strain relationship of such networks typically undergoes linear increase - strain hardening - stress serration - total fracture transitions due to the interplay between the bending and stretching of individual filaments and the deformation and breakage of cross-linkers. Interestingly, the apparent network modulus is found to scale with the linear and rotational stiffness of the crosslinks to a power exponent of 0.78 and 0.13, respectively. In addition, the network fracture energy will reach its minimum at intermediate rotational compliance values, reflecting the fact that most of the strain energy will be stored in the distorted filaments with rigid cross-linkers while the imposed deformation will be "evenly" distributed among significantly more crosslinking molecules with high rotational compliance. PMID:26760315

  1. Dynamical patterns of calcium signaling in a functional model of neuron–astrocyte networks

    PubMed Central

    Koreshkov, R. N.; Brazhe, N. A.; Brazhe, A. R.; Sosnovtseva, O. V.

    2009-01-01

    We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission in astrocytic–neuronal networks. We reproduce local and global dynamical patterns observed experimentally. PMID:19669421

  2. Neuronal activity in primate dorsal anterior cingulate cortex signals task conflict and predicts adjustments in pupil-linked arousal

    PubMed Central

    Ebitz, R. Becket; Platt, Michael L.

    2014-01-01

    Summary Whether driving a car, shopping for food, or paying attention in a classroom of boisterous teenagers, it’s often hard to maintain focus on goals in the face of distraction. Brain imaging studies in humans implicate the dorsal anterior cingulate cortex (dACC) in regulating the conflict between goals and distractors. Here we show for the first time that single dACC neurons signal conflict between task goals and distractors in the rhesus macaque, particularly for biologically-relevant social stimuli. For some neurons, task conflict signals predicted subsequent changes in pupil size—a peripheral index of arousal linked to noradrenergic tone—associated with reduced distractor interference. dACC neurons also responded to errors and these signals predicted adjustments in pupil size. These findings provide the first neurophysiological endorsement of the hypothesis that dACC regulates conflict, in part, via modulation of pupil-linked processes such as arousal. PMID:25654259

  3. NOD1 and NOD2 signalling links ER stress with inflammation.

    PubMed

    Keestra-Gounder, A Marijke; Byndloss, Mariana X; Seyffert, Núbia; Young, Briana M; Chávez-Arroyo, Alfredo; Tsai, April Y; Cevallos, Stephanie A; Winter, Maria G; Pham, Oanh H; Tiffany, Connor R; de Jong, Maarten F; Kerrinnes, Tobias; Ravindran, Resmi; Luciw, Paul A; McSorley, Stephen J; Bäumler, Andreas J; Tsolis, Renée M

    2016-04-21

    Endoplasmic reticulum (ER) stress is a major contributor to inflammatory diseases, such as Crohn disease and type 2 diabetes. ER stress induces the unfolded protein response, which involves activation of three transmembrane receptors, ATF6, PERK and IRE1α. Once activated, IRE1α recruits TRAF2 to the ER membrane to initiate inflammatory responses via the NF-κB pathway. Inflammation is commonly triggered when pattern recognition receptors (PRRs), such as Toll-like receptors or nucleotide-binding oligomerization domain (NOD)-like receptors, detect tissue damage or microbial infection. However, it is not clear which PRRs have a major role in inducing inflammation during ER stress. Here we show that NOD1 and NOD2, two members of the NOD-like receptor family of PRRs, are important mediators of ER-stress-induced inflammation in mouse and human cells. The ER stress inducers thapsigargin and dithiothreitol trigger production of the pro-inflammatory cytokine IL-6 in a NOD1/2-dependent fashion. Inflammation and IL-6 production triggered by infection with Brucella abortus, which induces ER stress by injecting the type IV secretion system effector protein VceC into host cells, is TRAF2, NOD1/2 and RIP2-dependent and can be reduced by treatment with the ER stress inhibitor tauroursodeoxycholate or an IRE1α kinase inhibitor. The association of NOD1 and NOD2 with pro-inflammatory responses induced by the IRE1α/TRAF2 signalling pathway provides a novel link between innate immunity and ER-stress-induced inflammation.

  4. NOD1 and NOD2 signalling links ER stress with inflammation.

    PubMed

    Keestra-Gounder, A Marijke; Byndloss, Mariana X; Seyffert, Núbia; Young, Briana M; Chávez-Arroyo, Alfredo; Tsai, April Y; Cevallos, Stephanie A; Winter, Maria G; Pham, Oanh H; Tiffany, Connor R; de Jong, Maarten F; Kerrinnes, Tobias; Ravindran, Resmi; Luciw, Paul A; McSorley, Stephen J; Bäumler, Andreas J; Tsolis, Renée M

    2016-04-21

    Endoplasmic reticulum (ER) stress is a major contributor to inflammatory diseases, such as Crohn disease and type 2 diabetes. ER stress induces the unfolded protein response, which involves activation of three transmembrane receptors, ATF6, PERK and IRE1α. Once activated, IRE1α recruits TRAF2 to the ER membrane to initiate inflammatory responses via the NF-κB pathway. Inflammation is commonly triggered when pattern recognition receptors (PRRs), such as Toll-like receptors or nucleotide-binding oligomerization domain (NOD)-like receptors, detect tissue damage or microbial infection. However, it is not clear which PRRs have a major role in inducing inflammation during ER stress. Here we show that NOD1 and NOD2, two members of the NOD-like receptor family of PRRs, are important mediators of ER-stress-induced inflammation in mouse and human cells. The ER stress inducers thapsigargin and dithiothreitol trigger production of the pro-inflammatory cytokine IL-6 in a NOD1/2-dependent fashion. Inflammation and IL-6 production triggered by infection with Brucella abortus, which induces ER stress by injecting the type IV secretion system effector protein VceC into host cells, is TRAF2, NOD1/2 and RIP2-dependent and can be reduced by treatment with the ER stress inhibitor tauroursodeoxycholate or an IRE1α kinase inhibitor. The association of NOD1 and NOD2 with pro-inflammatory responses induced by the IRE1α/TRAF2 signalling pathway provides a novel link between innate immunity and ER-stress-induced inflammation. PMID:27007849

  5. cAMP-dependent proteolysis of GATA-6 is linked to JNK-signaling pathway

    SciTech Connect

    Ushijima, Hironori; Maeda, Masatomo

    2012-07-13

    Highlights: Black-Right-Pointing-Pointer A JNK inhibitor SP600125 inhibited cAMP-dependent proteolysis of GATA-6. Black-Right-Pointing-Pointer Effect of a JNK activator anisomycin on the proteolysis was examined. Black-Right-Pointing-Pointer Anisomycin stimulated the export of nuclear GATA-6 into the cytoplasm. Black-Right-Pointing-Pointer JNK activated the CRM1 mediated nuclear export of GATA-6. Black-Right-Pointing-Pointer JNK further stimulated slowly the degradation of GATA-6 by cytoplasmic proteasomes. -- Abstract: A JNK inhibitor SP600125 inhibited cAMP-dependent proteolysis of GATA-6 by proteasomes around its IC50. We further examined the effects of SP600125 on the degradation of GATA-6 in detail, since an activator of JNK (anisomycin) is available. Interestingly, anisomycin immediately stimulated the export of nuclear GATA-6 into the cytoplasm, and then the cytoplasmic content of GATA-6 decreased slowly through degradation by proteasomes. Such an effect of anisomycin was inhibited by SP600125, indicating that the observed phenomenon might be linked to the JNK signaling pathway. The inhibitory effect of SP600125 could not be ascribed to the inhibition of PKA, since phosphorylation of CREB occurred in the presence of dbcAMP and SP600125. The nuclear export of GATA-6 was inhibited by leptomycin B, suggesting that CRM1-mediated export could be activated by anisomycin. Furthermore, it seems likely that the JNK activated by anisomycin may stimulate not only the nuclear export of GATA-6 through CRM1 but also the degradation of GATA-6 by cytoplasmic proteasomes. In contrast, A-kinase might activate only the latter process through JNK.

  6. Array signal processing in the NASA Deep Space Network

    NASA Technical Reports Server (NTRS)

    Pham, Timothy T.; Jongeling, Andre P.

    2004-01-01

    In this paper, we will describe the benefits of arraying and past as well as expected future use of this application. The signal processing aspects of array system are described. Field measurements via actual tracking spacecraft are also presented.

  7. Transmission and pass-drop operations of mixed baudrate Nyquist OTDM-WDM signals for all-optical elastic network.

    PubMed

    Tan, Hung Nguyen; Inoue, Takashi; Kurosu, Takayuki; Namiki, Shu

    2013-08-26

    We propose the use of Nyquist OTDM-WDM signal for highly efficient, fully elastic all-optical networks. With the possibility of generation of ultra-coarse yet flexible granular channels, Nyquist OTDM-WDM can eliminate guard-bands in conventional WDM systems, and hence improves the spectral efficiency in network perspective. In this paper, transmission and pass-drop operations of mixed baudrate Nyquist OTDM-WDM channels from 43 Gbaud to dual-polarization 344 Gbaud are successfully demonstrated over 320 km fiber link with four FlexGrid-compatible WSS nodes. A stable clock recovery is also carried out for different baudrate Nyquist OTDMs by optical null-header insertion technique.

  8. Network Evolution: Rewiring and Signatures of Conservation in Signaling

    PubMed Central

    Costanzo, Michael; Boone, Charles; Kim, Philip M.

    2012-01-01

    The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3) domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree) and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules. PMID:22438796

  9. Probabilistic neural networks employing Lyapunov exponents for analysis of Doppler ultrasound signals.

    PubMed

    Ubeyli, Elif Derya

    2008-01-01

    The implementation of probabilistic neural networks (PNNs) with the Lyapunov exponents for Doppler ultrasound signals classification is presented. This study is directly based on the consideration that Doppler ultrasound signals are chaotic signals. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. Decision making was performed in two stages: computation of Lyapunov exponents as representative features of the Doppler ultrasound signals and classification using the PNNs trained on the extracted features. The present research demonstrated that the Lyapunov exponents are the features which well represent the Doppler ultrasound signals and the PNNs trained on these features achieved high classification accuracies. PMID:17709103

  10. Modeling approaches for qualitative and semi-quantitative analysis of cellular signaling networks

    PubMed Central

    2013-01-01

    A central goal of systems biology is the construction of predictive models of bio-molecular networks. Cellular networks of moderate size have been modeled successfully in a quantitative way based on differential equations. However, in large-scale networks, knowledge of mechanistic details and kinetic parameters is often too limited to allow for the set-up of predictive quantitative models. Here, we review methodologies for qualitative and semi-quantitative modeling of cellular signal transduction networks. In particular, we focus on three different but related formalisms facilitating modeling of signaling processes with different levels of detail: interaction graphs, logical/Boolean networks, and logic-based ordinary differential equations (ODEs). Albeit the simplest models possible, interaction graphs allow the identification of important network properties such as signaling paths, feedback loops, or global interdependencies. Logical or Boolean models can be derived from interaction graphs by constraining the logical combination of edges. Logical models can be used to study the basic input–output behavior of the system under investigation and to analyze its qualitative dynamic properties by discrete simulations. They also provide a suitable framework to identify proper intervention strategies enforcing or repressing certain behaviors. Finally, as a third formalism, Boolean networks can be transformed into logic-based ODEs enabling studies on essential quantitative and dynamic features of a signaling network, where time and states are continuous. We describe and illustrate key methods and applications of the different modeling formalisms and discuss their relationships. In particular, as one important aspect for model reuse, we will show how these three modeling approaches can be combined to a modeling pipeline (or model hierarchy) allowing one to start with the simplest representation of a signaling network (interaction graph), which can later be refined to

  11. Modeling approaches for qualitative and semi-quantitative analysis of cellular signaling networks.

    PubMed

    Samaga, Regina; Klamt, Steffen

    2013-01-01

    A central goal of systems biology is the construction of predictive models of bio-molecular networks. Cellular networks of moderate size have been modeled successfully in a quantitative way based on differential equations. However, in large-scale networks, knowledge of mechanistic details and kinetic parameters is often too limited to allow for the set-up of predictive quantitative models.Here, we review methodologies for qualitative and semi-quantitative modeling of cellular signal transduction networks. In particular, we focus on three different but related formalisms facilitating modeling of signaling processes with different levels of detail: interaction graphs, logical/Boolean networks, and logic-based ordinary differential equations (ODEs). Albeit the simplest models possible, interaction graphs allow the identification of important network properties such as signaling paths, feedback loops, or global interdependencies. Logical or Boolean models can be derived from interaction graphs by constraining the logical combination of edges. Logical models can be used to study the basic input-output behavior of the system under investigation and to analyze its qualitative dynamic properties by discrete simulations. They also provide a suitable framework to identify proper intervention strategies enforcing or repressing certain behaviors. Finally, as a third formalism, Boolean networks can be transformed into logic-based ODEs enabling studies on essential quantitative and dynamic features of a signaling network, where time and states are continuous.We describe and illustrate key methods and applications of the different modeling formalisms and discuss their relationships. In particular, as one important aspect for model reuse, we will show how these three modeling approaches can be combined to a modeling pipeline (or model hierarchy) allowing one to start with the simplest representation of a signaling network (interaction graph), which can later be refined to logical

  12. An improved response surface methodology algorithm with an application to traffic signal optimization for urban networks

    SciTech Connect

    Joshi, S.S.; Rathi, A.K.; Tew, J.D.

    1995-12-31

    This paper illustrates the use of the simulation-optimization technique of response surface methodology (RSM) in traffic signal optimization of urban networks. It also quantifies the gains of using the common random number (CRN) variance reduction strategy in such an optimization procedure. An enhanced RSM algorithm which employs conjugate gradient search techniques and successive second-order models is presented instead of the conventional approach. An illustrative example using an urban traffic network exhibits the superiority of using the CRN strategy ovr direct simulation in performing traffic signal optimization. Relative performance of the two strategies is quantified with computational results using the total network-wide delay as the measure of effectivness.

  13. Signal Decompostion and Diagnostic Classification of the Electromyogram Using a Novel Neural Network Technique

    PubMed Central

    Spitzer, A.R.; Hassoun, M.; Wang, C.; Bearden, F.

    1990-01-01

    Interpretation of physiologic signals to assist medical diagnosis requires human expertise. Success in automating this process has been limited. We present a three-step method for automated interpretation of the EMG. Signal decomposition and classification steps, which have not been automated using traditional computer methods, utilize neural networks. To deal with poorly described signals, a novel decomposition method, pseudoun-supervised learning, has been developed. The resulting method is considerably more robust than prior methods.

  14. Thermally Reversible Physically Cross-Linked Hybrid Network Hydrogels Formed by Thermosensitive Hairy Nanoparticles.

    PubMed

    Wright, Roger A E; Henn, Daniel M; Zhao, Bin

    2016-08-18

    This Article reports on thermally induced reversible formation of physically cross-linked, three-dimensional network hydrogels from aqueous dispersions of thermosensitive diblock copolymer brush-grafted silica nanoparticles (hairy NPs). The hairy NPs consisted of a silica core, a water-soluble polyelectrolyte inner block of poly(2-(methacryloyloxy)ethyltrimethylammonium iodide), and a thermosensitive poly(methoxydi(ethylene glycol) methacrylate) (PDEGMMA) outer block synthesized by sequential surface-initiated atom transfer radical polymerizations and postpolymerization quaternization of tertiary amine moieties. Moderately concentrated dispersions of these hairy nanoparticles in water underwent thermally induced reversible transitions between flowing liquids to self-supporting gels upon heating. The gelation was driven by the lower critical solution temperature (LCST) transition of the PDEGMMA outer block, which upon heating self-associated into hydrophobic domains acting as physical cross-linking points for the gel network. Rheological studies showed that the sol-gel transition temperature decreased with increasing hairy NP concentration, and the gelation was achieved at concentrations as low as 3 wt %. PMID:27455167

  15. Robust Self-Healing Hydrogels Assisted by Cross-Linked Nanofiber Networks

    PubMed Central

    Fang, Yuan; Wang, Cai-Feng; Zhang, Zhi-Hong; Shao, Huan; Chen, Su

    2013-01-01

    Given increasing environmental and energy issues, mimicking nature to confer synthetic materials with self-healing property to expand their lifespan is highly desirable. Just like human skin recovers itself upon damage with the aid of nutrient-laden blood vascularization, designing smart materials with microvascular network to accelerate self-healing is workable but continues to be a challenge. Here we report a new strategy to prepare robust self-healing hydrogels assisted by a healing layer composed of electrospun cross-linked nanofiber networks containing redox agents. The hydrogels process high healing rate ranging from seconds to days and great mechanical strengths with storage modulus up to 0.1 MPa. More interestingly, when the healing layer is embedded into the crack of the hydrogel, accelerated self-healing is observed and the healing efficiency is about 80%. The healing layer encourages molecular diffusion as well as further cross-linking in the crack region of the hydrogel, responsible for enhanced healing efficiency. PMID:24091865

  16. Neuregulin 3 and erbb signalling networks in embryonic mammary gland development.

    PubMed

    Kogata, Naoko; Zvelebil, Marketa; Howard, Beatrice A

    2013-06-01

    We review the role of Neuregulin 3 (Nrg3) and Erbb receptor signalling in embryonic mammary gland development. Neuregulins are growth factors that bind and activate its cognate Erbb receptor tyrosine kinases, which form a signalling network with established roles in breast development and breast cancer. Studies have shown that Nrg3 expression profoundly impacts early stages of embryonic mammary development. Network analysis shows how Nrg/Erbb signals could integrate with other major regulators of embryonic mammary development to elicit the morphogenetic processes and cell fate decisions that occur as the mammary lineage is established.

  17. Modeling Signal Transduction Networks: A comparison of two Stochastic Kinetic Simulation Algorithms

    SciTech Connect

    Pettigrew, Michel F.; Resat, Haluk

    2005-09-15

    Simulations of a scalable four compartment reaction model based on the well known epidermal growth factor receptor (EGFR) signal transduction system are used to compare two stochastic algorithms ? StochSim and the Gibson-Gillespie. It is concluded that the Gibson-Gillespie is the algorithm of choice for most realistic cases with the possible exception of signal transduction networks characterized by a moderate number (< 100) of complex types, each with a very small population, but with a high degree of connectivity amongst the complex types. Keywords: Signal transduction networks, Stochastic simulation, StochSim, Gillespie

  18. The LINK-A lncRNA Activates Normoxic HIF1α Signaling in Triple-negative Breast Cancer

    PubMed Central

    Lin, Aifu; Li, Chunlai; Xing, Zhen; Hu, Qingsong; Liang, Ke; Han, Leng; Wang, Cheng; Hawke, David H.; Wang, Shouyu; Zhang, Yanyan; Wei, Yongkun; Ma, Guolin; Park, Peter K.; Zhou, Jianwei; Zhou, Yan; Hu, Zhibin; Zhou, Yubin; Marks, Jeffery R.; Liang, Han; Hung, Mien-Chie; Lin, Chunru; Yang, Liuqing

    2016-01-01

    Although long noncoding RNAs (lncRNAs) predominately reside in nuclear and exert their functions in many biological processes, their potential involvement in cytoplasmic signal transduction remains unexplored. Here, we identified a cytoplasmic lncRNA, Long-Intergenic Noncoding RNA for Kinase Activation (LINK-A), which mediates HB-EGF triggered, EGFR:GPNMB heterodimer-dependent HIF1α phosphorylation at Tyr565 and Ser797 by BRK and LRRK2 respectively. These events cause HIF1α stabilization, HIF1α-p300 interaction, and activation of HIF1α transcriptional programs under normoxic conditions. Mechanistically, LINK-A facilitates the recruitment of BRK to EGFR:GPNMB complex and BRK kinase activation. The BRK-dependent HIF1α Tyr565 phosphorylation interferes with Pro564 hydroxylation, leading to normoxic HIF1α stabilization. Both LINK-A and LINK-A-dependent signaling pathway activation correlate with TNBC, promoting breast cancer glycolysis reprogramming and tumorigenesis. Our findings illustrate the magnitude and diversity of cytoplasmic lncRNAs in signal transduction and highlight the important roles of lncRNAs in cancer. PMID:26751287

  19. Neural network committees for finger joint angle estimation from surface EMG signals

    PubMed Central

    Shrirao, Nikhil A; Reddy, Narender P; Kosuri, Durga R

    2009-01-01

    Background In virtual reality (VR) systems, the user's finger and hand positions are sensed and used to control the virtual environments. Direct biocontrol of VR environments using surface electromyography (SEMG) signals may be more synergistic and unconstraining to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models. Methodology SEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-extension rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the parameters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects. Results There was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion. Conclusion Although hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals. PMID:19154615

  20. Imbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in Internet gaming disorder

    PubMed Central

    Dong, Guangheng; Lin, Xiao; Hu, Yanbo; Xie, Chunming; Du, Xiaoxia

    2015-01-01

    Literatures have shown that Internet gaming disorder (IGD) subjects show impaired executive control and enhanced reward sensitivities than healthy controls. However, how these two networks jointly affect the valuation process and drive IGD subjects' online-game-seeking behaviors remains unknown. Thirty-five IGD and 36 healthy controls underwent a resting-states scan in the MRI scanner. Functional connectivity (FC) was examined within control and reward network seeds regions, respectively. Nucleus accumbens (NAcc) was selected as the node to find the interactions between these two networks. IGD subjects show decreased FC in the executive control network and increased FC in the reward network when comparing with the healthy controls. When examining the correlations between the NAcc and the executive control/reward networks, the link between the NAcc - executive control network is negatively related with the link between NAcc - reward network. The changes (decrease/increase) in IGD subjects' brain synchrony in control/reward networks suggest the inefficient/overly processing within neural circuitry underlying these processes. The inverse proportion between control network and reward network in IGD suggest that impairments in executive control lead to inefficient inhibition of enhanced cravings to excessive online game playing. This might shed light on the mechanistic understanding of IGD. PMID:25779894

  1. A network map of Interleukin-10 signaling pathway.

    PubMed

    Verma, Renu; Balakrishnan, Lavanya; Sharma, Kusum; Khan, Aafaque Ahmad; Advani, Jayshree; Gowda, Harsha; Tripathy, Srikanth Prasad; Suar, Mrutyunjay; Pandey, Akhilesh; Gandotra, Sheetal; Prasad, T S Keshava; Shankar, Subramanian

    2016-03-01

    Interleukin-10 (IL-10) is an anti-inflammatory cytokine with important immunoregulatory functions. It is primarily secreted by antigen-presenting cells such as activated T-cells, monocytes, B-cells and macrophages. In biologically functional form, it exists as a homodimer that binds to tetrameric heterodimer IL-10 receptor and induces downstream signaling. IL-10 is associated with survival, proliferation and anti-apoptotic activities of various cancers such as Burkitt lymphoma, non-Hodgkins lymphoma and non-small scell lung cancer. In addition, it plays a central role in survival and persistence of intracellular pathogens such as Leishmania donovani, Mycobacterium tuberculosis and Trypanosoma cruzi inside the host. The signaling mechanisms of IL-10 cytokine are not well explored and a well annotated pathway map has been lacking. To this end, we developed a pathway resource by manually annotating the IL-10 induced signaling molecules derived from literature. The reactions were categorized under molecular associations, activation/inhibition, catalysis, transport and gene regulation. In all, 37 molecules and 76 reactions were annotated. The IL-10 signaling pathway can be freely accessed through NetPath, a resource of signal transduction pathways previously developed by our group. PMID:26253919

  2. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks.

    PubMed

    Teschendorff, Andrew E; Banerji, Christopher R S; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-04-28

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology.

  3. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

    PubMed Central

    Teschendorff, Andrew E.; Banerji, Christopher R. S.; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-01-01

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology. PMID:25919796

  4. Integrating In Silico Resources to Map a Signaling Network

    PubMed Central

    Liu, Hanqing; Beck, Tim N.; Golemis, Erica A.; Serebriiskii, Ilya G.

    2013-01-01

    The abundance of publicly available life science databases offer a wealth of information that can support interpretation of experimentally derived data and greatly enhance hypothesis generation. Protein interaction and functional networks are not simply new renditions of existing data: they provide the opportunity to gain insights into the specific physical and functional role a protein plays as part of the biological system. In this chapter, we describe different in silico tools that can quickly and conveniently retrieve data from existing data repositories and discuss how the available tools are best utilized for different purposes. While emphasizing protein-protein interaction databases (e.g., BioGrid and IntAct), we also introduce metasearch platforms such as STRING and GeneMANIA, pathway databases (e.g., BioCarta and Pathway Commons), text mining approaches (e.g., PubMed and Chilibot), and resources for drug-protein interactions, genetic information for model organisms and gene expression information based on microarray data mining. Furthermore, we provide a simple step-by-step protocol to building customized protein-protein interaction networks in Cytoscape, a powerful network assembly and visualization program, integrating data retrieved from these various databases. As we illustrate, generation of composite interaction networks enables investigators to extract significantly more information about a given biological system than utilization of a single database or sole reliance on primary literature. PMID:24233784

  5. Orchestrating Redox Signaling Networks Through Regulatory Cysteine Switches

    PubMed Central

    Paulsen, Candice E.; Carroll, Kate S.

    2015-01-01

    Hydrogen peroxide (H2O2) acts as a second messenger that can mediate intracellular signal transduction via chemoselective oxidation of cysteine residues in signaling proteins. This Review presents current mechanistic insights into signal-mediated H2O2 production and highlights recent advances in methods to detect reactive oxygen species (ROS) and cysteine oxidation both in vitro and in cells. Selected examples from the recent literature are used to illustrate the diverse mechanisms by which H2O2 can regulate protein function. The continued development of methods to detect and quantify discrete cysteine oxoforms should further our mechanistic understanding of redox regulation of protein function and may lead to the development of new therapeutic strategies. PMID:19957967

  6. Signaling networks regulating leukocyte podosome dynamics and function

    PubMed Central

    Dovas, Athanassios; Cox, Dianne

    2011-01-01

    Podosomes are ventral adhesion structures prominent in cells of the myeloid lineage. A common aspect of these cells is that they are highly motile and are required to traverse multiple tissue barriers in order to perform their functions. Recently podosomes have gathered attention from researchers as important cellular structures that can influence cell adhesion, motility and matrix remodeling. Adhesive and soluble ligands act via transmembrane receptors and propagate signals to the leukocyte cytoskeleton via small G proteins of the Rho family, tyrosine kinases and scaffold proteins and are able to induce podosome formation and rearrangements. Manipulation of the signals that regulate podosome formation and dynamics can therefore be a strategy to interfere with leukocyte functions in a multitude of pathological settings, such as infections, atherosclerosis and arthritis. Here, we review the major signaling molecules that act in the formation and regulation of podosomes. PMID:21342664

  7. Orchestrating redox signaling networks through regulatory cysteine switches.

    PubMed

    Paulsen, Candice E; Carroll, Kate S

    2010-01-15

    Hydrogen peroxide (H(2)O(2)) acts as a second messenger that can mediate intracellular signal transduction via chemoselective oxidation of cysteine residues in signaling proteins. This Review presents current mechanistic insights into signal-mediated H(2)O(2) production and highlights recent advances in methods to detect reactive oxygen species (ROS) and cysteine oxidation both in vitro and in cells. Selected examples from the recent literature are used to illustrate the diverse mechanisms by which H(2)O(2) can regulate protein function. The continued development of methods to detect and quantify discrete cysteine oxoforms should further our mechanistic understanding of redox regulation of protein function and may lead to the development of new therapeutic strategies.

  8. Real-time in Situ Signal-to-noise Ratio Estimation for the Assessment of Operational Communications Links

    NASA Technical Reports Server (NTRS)

    Manning, Robert M.

    2002-01-01

    The work presented here formulates the rigorous statistical basis for the correct estimation of communication link SNR of a BPSK, QPSK, and for that matter, any M-ary phase-modulated digital signal from what is known about its statistical behavior at the output of the receiver demodulator. Many methods to accomplish this have been proposed and implemented in the past but all of them are based on tacit and unwarranted assumptions and are thus defective. However, the basic idea is well founded, i.e., the signal at the output of a communications demodulator has convolved within it the prevailing SNR characteristic of the link. The acquisition of the SNR characteristic is of the utmost importance to a communications system that must remain reliable in adverse propagation conditions. This work provides a correct and consistent mathematical basis for the proper statistical 'deconvolution' of the output of a demodulator to yield a measure of the SNR. The use of such techniques will alleviate the need and expense for a separate propagation link to assess the propagation conditions prevailing on the communications link. Furthermore, they are applicable for every situation involving the digital transmission of data over planetary and space communications links.

  9. Birth and death of links control disease spreading in empirical contact networks

    NASA Astrophysics Data System (ADS)

    Holme, Petter; Liljeros, Fredrik

    2014-05-01

    We investigate what structural aspects of a collection of twelve empirical temporal networks of human contacts are important to disease spreading. We scan the entire parameter spaces of the two canonical models of infectious disease epidemiology--the Susceptible-Infectious-Susceptible (SIS) and Susceptible-Infectious-Removed (SIR) models. The results from these simulations are compared to reference data where we eliminate structures in the interevent intervals, the time to the first contact in the data, or the time from the last contact to the end of the sampling. The picture we find is that the birth and death of links, and the total number of contacts over a link, are essential to predict outbreaks. On the other hand, the exact times of contacts between the beginning and end, or the interevent interval distribution, do not matter much. In other words, a simplified picture of these empirical data sets that suffices for epidemiological purposes is that links are born, is active with some intensity, and die.

  10. Linking the sender to the receiver: vocal adjustments by bats to maintain signal detection in noise

    PubMed Central

    Luo, Jinhong; Goerlitz, Holger R.; Brumm, Henrik; Wiegrebe, Lutz

    2015-01-01

    Short-term adjustments of signal characteristics allow animals to maintain reliable communication in noise. Noise-dependent vocal plasticity often involves simultaneous changes in multiple parameters. Here, we quantified for the first time the relative contributions of signal amplitude, duration, and redundancy for improving signal detectability in noise. To this end, we used a combination of behavioural experiments on pale spear-nosed bats (Phyllostomus discolor) and signal detection models. In response to increasing noise levels, all bats raised the amplitude of their echolocation calls by 1.8–7.9 dB (the Lombard effect). Bats also increased signal duration by 13%–85%, corresponding to an increase in detectability of 1.0–5.3 dB. Finally, in some noise conditions, bats increased signal redundancy by producing more call groups. Assuming optimal cognitive integration, this could result in a further detectability improvement by up to 4 dB. Our data show that while the main improvement in signal detectability was due to the Lombard effect, increasing signal duration and redundancy can also contribute markedly to improving signal detectability. Overall, our findings demonstrate that the observed adjustments of signal parameters in noise are matched to how these parameters are processed in the receiver’s sensory system, thereby facilitating signal transmission in fluctuating environments. PMID:26692325

  11. Equipment Management for Sensor Networks: Linking Physical Infrastructure and Actions to Observational Data

    NASA Astrophysics Data System (ADS)

    Jones, A. S.; Horsburgh, J. S.; Matos, M.; Caraballo, J.

    2015-12-01

    Networks conducting long term monitoring using in situ sensors need the functionality to track physical equipment as well as deployments, calibrations, and other actions related to site and equipment maintenance. The observational data being generated by sensors are enhanced if direct linkages to equipment details and actions can be made. This type of information is typically recorded in field notebooks or in static files, which are rarely linked to observations in a way that could be used to interpret results. However, the record of field activities is often relevant to analysis or post-processing of the observational data. We have developed an underlying database schema and deployed a web interface for recording and retrieving information on physical infrastructure and related actions for observational networks. The database schema for equipment was designed as an extension to the Observations Data Model 2 (ODM2), a community-developed information model for spatially discrete, feature based earth observations. The core entities of ODM2 describe location, observed variable, and timing of observations, and the equipment extension contains entities to provide additional metadata specific to the inventory of physical infrastructure and associated actions. The schema is implemented in a relational database system for storage and management with an associated web interface. We designed the web-based tools for technicians to enter and query information on the physical equipment and actions such as site visits, equipment deployments, maintenance, and calibrations. These tools were implemented for the iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) ecohydrologic observatory, and we anticipate that they will be useful for similar large-scale monitoring networks desiring to link observing infrastructure to observational data to increase the quality of sensor-based data products.

  12. Linking in with LinkedIn[R]: Three Exercises That Enhance Professional Social Networking and Career Building

    ERIC Educational Resources Information Center

    Gerard, Joseph G.

    2012-01-01

    Getting students to network with one another can be one of the biggest challenges in college courses, despite being a highly important function of higher education. Networking can, in fact, lead to that first job or to professional advancement, and technology can improve the success of individual and institutional efforts. This article describes…

  13. Classification of acousto-optic correlation signatures of spread spectrum signals using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Deberry, John W.

    1989-05-01

    The primary goal of this research was to determine if artificial Neural Networks (ANNs) can be trained to classify the correlation signatures of direct sequence and frequency-hopped spread-spectrum signals. Secondary goals were to determine: (1) if network classification performance can be modeled with a conditional probability matrix, (2) if the symmetry of the matrices can be controlled, and (3) if using a majority vote rule over independently trained networks improves classification performance. Correlation signatures of the spread-spectrum signals were obtained from United States Army Harry Diamond Laboratories. The signatures were preprocessed and separated into various training and testing data sets. Thirty samples of network responses for several sets of training conditions were gathered using a neural network simulator.

  14. Antithetical NFATc1-Sox2 and p53-miR200 signaling networks govern pancreatic cancer cell plasticity.

    PubMed

    Singh, Shiv K; Chen, Nai-Ming; Hessmann, Elisabeth; Siveke, Jens; Lahmann, Marlen; Singh, Garima; Voelker, Nadine; Vogt, Sophia; Esposito, Irene; Schmidt, Ansgar; Brendel, Cornelia; Stiewe, Thorsten; Gaedcke, Jochen; Mernberger, Marco; Crawford, Howard C; Bamlet, William R; Zhang, Jin-San; Li, Xiao-Kun; Smyrk, Thomas C; Billadeau, Daniel D; Hebrok, Matthias; Neesse, Albrecht; Koenig, Alexander; Ellenrieder, Volker

    2015-02-12

    In adaptation to oncogenic signals, pancreatic ductal adenocarcinoma (PDAC) cells undergo epithelial-mesenchymal transition (EMT), a process combining tumor cell dedifferentiation with acquisition of stemness features. However, the mechanisms linking oncogene-induced signaling pathways with EMT and stemness remain largely elusive. Here, we uncover the inflammation-induced transcription factor NFATc1 as a central regulator of pancreatic cancer cell plasticity. In particular, we show that NFATc1 drives EMT reprogramming and maintains pancreatic cancer cells in a stem cell-like state through Sox2-dependent transcription of EMT and stemness factors. Intriguingly, NFATc1-Sox2 complex-mediated PDAC dedifferentiation and progression is opposed by antithetical p53-miR200c signaling, and inactivation of the tumor suppressor pathway is essential for tumor dedifferentiation and dissemination both in genetically engineered mouse models (GEMM) and human PDAC. Based on these findings, we propose the existence of a hierarchical signaling network regulating PDAC cell plasticity and suggest that the molecular decision between epithelial cell preservation and conversion into a dedifferentiated cancer stem cell-like phenotype depends on opposing levels of p53 and NFATc1 signaling activities.

  15. Polymorphism of highly cross-linked F-actin networks: Probing multiple length scales

    NASA Astrophysics Data System (ADS)

    Nguyen, Lam T.; Hirst, Linda S.

    2011-03-01

    The assembly properties of F-actin filaments in the presence of different biological cross-linker concentrations and types have been investigated using a combined approach of fluorescence confocal microscopy and coarse-grained molecular dynamics simulation. In particular for highly cross-linked regimes, new network morphologies are observed. Complex network formation and the details of the resulting structure are strongly dependent on the ratio of cross-linkers to actin monomers and cross-linker shape but only weakly dependent on overall actin concentration and filament length. The work presented here may help to provide some fundamental understanding of how excessive cross-linkers interact with the actin filament solution, creating different structures in the cell under high cross-linker concentrations. F-actin is not only of biological importance but also, as an example of a semiflexible polymer, has attracted significant interest in its physical behavior. In combination with different cross-linkers semiflexible filaments may provide new routes to bio-materials development and act as the inspiration for new hierarchical network-based materials.

  16. Application of Radial Basis Functional Link Networks to Exploration for Proterozoic Mineral Deposits in Central Iran

    SciTech Connect

    Behnia, Pouran

    2007-06-15

    The metallogeny of Central Iran is characterized mainly by the presence of several iron, apatite, and uranium deposits of Proterozoic age. Radial Basis Function Link Networks (RBFLN) were used as a data-driven method for GIS-based predictive mapping of Proterozoic mineralization in this area. To generate the input data for RBFLN, the evidential maps comprising stratigraphic, structural, geophysical, and geochemical data were used. Fifty-eight deposits and 58 'nondeposits' were used to train the network. The operations for the application of neural networks employed in this study involve both multiclass and binary representation of evidential maps. Running RBFLN on different input data showed that an increase in the number of evidential maps and classes leads to a larger classification sum of squared error (SSE). As a whole, an increase in the number of iterations resulted in the improvement of training SSE. The results of applying RBFLN showed that a successful classification depends on the existence of spatially well distributed deposits and nondeposits throughout the study area.

  17. Automated and comprehensive link engineering supporting branched, ring, and mesh network topologies

    NASA Astrophysics Data System (ADS)

    Farina, J.; Khomchenko, D.; Yevseyenko, D.; Meester, J.; Richter, A.

    2016-02-01

    Link design, while relatively easy in the past, can become quite cumbersome with complex channel plans and equipment configurations. The task of designing optical transport systems and selecting equipment is often performed by an applications or sales engineer using simple tools, such as custom Excel spreadsheets. Eventually, every individual has their own version of the spreadsheet as well as their own methodology for building the network. This approach becomes unmanageable very quickly and leads to mistakes, bending of the engineering rules and installations that do not perform as expected. We demonstrate a comprehensive planning environment, which offers an efficient approach to unify, control and expedite the design process by controlling libraries of equipment and engineering methodologies, automating the process and providing the analysis tools necessary to predict system performance throughout the system and for all channels. In addition to the placement of EDFAs and DCEs, performance analysis metrics are provided at every step of the way. Metrics that can be tracked include power, CD and OSNR, SPM, XPM, FWM and SBS. Automated routine steps assist in design aspects such as equalization, padding and gain setting for EDFAs, the placement of ROADMs and transceivers, and creating regeneration points. DWDM networks consisting of a large number of nodes and repeater huts, interconnected in linear, branched, mesh and ring network topologies, can be designed much faster when compared with conventional design methods. Using flexible templates for all major optical components, our technology-agnostic planning approach supports the constant advances in optical communications.

  18. Differentially Expressed Transcripts and Dysregulated Signaling Pathways and Networks in African American Breast Cancer

    PubMed Central

    Stewart, Paul A.; Luks, Jennifer; Roycik, Mark D.; Sang, Qing-Xiang Amy; Zhang, Jinfeng

    2013-01-01

    African Americans (AAs) have higher mortality rate from breast cancer than that of Caucasian Americans (CAs) even when socioeconomic factors are accounted for. To better understand the driving biological factors of this health disparity, we performed a comprehensive differential gene expression analysis, including subtype- and stage-specific analysis, using the breast cancer data in the Cancer Genome Atlas (TCGA). In total, 674 unique genes and other transcripts were found differentially expressed between these two populations. The numbers of differentially expressed genes between AA and CA patients increased in each stage of tumor progression: there were 26 in stage I, 161 in stage II, and 223 in stage III. Resistin, a gene that is linked to obesity, insulin resistance, and breast cancer, was expressed more than four times higher in AA tumors. An uncharacterized, long, non-coding RNA, LOC90784, was down-regulated in AA tumors, and its expression was inversely related to cancer stage and was the lowest in triple negative AA breast tumors. Network analysis showed increased expression of a majority of components in p53 and BRCA1 subnetworks in AA breast tumor samples, and members of the aurora B and polo-like kinase signaling pathways were also highly expressed. Higher gene expression diversity was observed in more advanced stage breast tumors suggesting increased genomic instability during tumor progression. Amplified resistin expression may indicate insulin-resistant type II diabetes and obesity are associated with AA breast cancer. Expression of LOC90784 may have a protective effect on breast cancer patients, and its loss, particularly in triple negative breast cancer, could be having detrimental effects. This work helps elucidate molecular mechanisms of breast cancer health disparity and identifies putative biomarkers and therapeutic targets such as resistin, and the aurora B and polo-like kinase signaling pathways for treating AA breast cancer patients. PMID

  19. Guard Cell Signal Transduction Network: Advances in Understanding Abscisic Acid, CO2, and Ca2+ Signaling

    PubMed Central

    Kim, Tae-Houn; Böhmer, Maik; Hu, Honghong; Nishimura, Noriyuki; Schroeder, Julian I.

    2011-01-01

    Stomatal pores are formed by pairs of specialized epidermal guard cells and serve as major gateways for both CO2 influx into plants from the atmosphere and transpirational water loss of plants. Because they regulate stomatal pore apertures via integration of both endogenous hormonal stimuli and environmental signals, guard cells have been highly developed as a model system to dissect the dynamics and mechanisms of plant-cell signaling. The stress hormone ABA and elevated levels of CO2 activate complex signaling pathways in guard cells that are mediated by kinases/phosphatases, secondary messengers, and ion channel regulation. Recent research in guard cells has led to a new hypothesis for how plants achieve specificity in intracellular calcium signaling: CO2 and ABA enhance (prime) the calcium sensitivity of downstream calcium-signaling mechanisms. Recent progress in identification of early stomatal signaling components are reviewed here, including ABA receptors and CO2-binding response proteins, as well as systems approaches that advance our understanding of guard cell-signaling mechanisms. PMID:20192751

  20. Integrated signaling networks in plant responses to sedentary endoparasitic nematodes: a perspective.

    PubMed

    Li, Ruijuan; Rashotte, Aaron M; Singh, Narendra K; Weaver, David B; Lawrence, Kathy S; Locy, Robert D

    2015-01-01

    Sedentary plant endoparasitic nematodes can cause detrimental yield losses in crop plants making the study of detailed cellular, molecular, and whole plant responses to them a subject of importance. In response to invading nematodes and nematode-secreted effectors, plant susceptibility/resistance is mainly determined by the coordination of different signaling pathways including specific plant resistance genes or proteins, plant hormone synthesis and signaling pathways, as well as reactive oxygen signals that are generated in response to nematode attack. Crosstalk between various nematode resistance-related elements can be seen as an integrated signaling network regulated by transcription factors and small RNAs at the transcriptional, posttranscriptional, and/or translational levels. Ultimately, the outcome of this highly controlled signaling network determines the host plant susceptibility/resistance to nematodes.

  1. Processes entangling interactions in communities: forbidden links are more important than abundance in a hummingbird–plant network

    PubMed Central

    Vizentin-Bugoni, Jeferson; Maruyama, Pietro Kiyoshi; Sazima, Marlies

    2014-01-01

    Understanding the relative importance of multiple processes on structuring species interactions within communities is one of the major challenges in ecology. Here, we evaluated the relative importance of species abundance and forbidden links in structuring a hummingbird–plant interaction network from the Atlantic rainforest in Brazil. Our results show that models incorporating phenological overlapping and morphological matches were more accurate in predicting the observed interactions than models considering species abundance. This means that forbidden links, by imposing constraints on species interactions, play a greater role than species abundance in structuring the ecological network. We also show that using the frequency of interaction as a proxy for species abundance and network metrics to describe the detailed network structure might lead to biased conclusions regarding mechanisms generating network structure. Together, our findings suggest that species abundance can be a less important driver of species interactions in communities than previously thought. PMID:24552835

  2. Processes entangling interactions in communities: forbidden links are more important than abundance in a hummingbird-plant network.

    PubMed

    Vizentin-Bugoni, Jeferson; Maruyama, Pietro Kiyoshi; Sazima, Marlies

    2014-04-01

    Understanding the relative importance of multiple processes on structuring species interactions within communities is one of the major challenges in ecology. Here, we evaluated the relative importance of species abundance and forbidden links in structuring a hummingbird-plant interaction network from the Atlantic rainforest in Brazil. Our results show that models incorporating phenological overlapping and morphological matches were more accurate in predicting the observed interactions than models considering species abundance. This means that forbidden links, by imposing constraints on species interactions, play a greater role than species abundance in structuring the ecological network. We also show that using the frequency of interaction as a proxy for species abundance and network metrics to describe the detailed network structure might lead to biased conclusions regarding mechanisms generating network structure. Together, our findings suggest that species abundance can be a less important driver of species interactions in communities than previously thought.

  3. Dependency Links Can Hinder the Evolution of Cooperation in the Prisoner’s Dilemma Game on Lattices and Networks

    PubMed Central

    Wang, Xuwen; Nie, Sen; Wang, Binghong

    2015-01-01

    Networks with dependency links are more vulnerable when facing the attacks. Recent research also has demonstrated that the interdependent groups support the spreading of cooperation. We study the prisoner’s dilemma games on spatial networks with dependency links, in which a fraction of individual pairs is selected to depend on each other. The dependency individuals can gain an extra payoff whose value is between the payoff of mutual cooperation and the value of temptation to defect. Thus, this mechanism reflects that the dependency relation is stronger than the relation of ordinary mutual cooperation, but it is not large enough to cause the defection of the dependency pair. We show that the dependence of individuals hinders, promotes and never affects the cooperation on regular ring networks, square lattice, random and scale-free networks, respectively. The results for the square lattice and regular ring networks are demonstrated by the pair approximation. PMID:25798579

  4. Rate-based congestion control in networks with smart links, revision. B.S. Thesis - May 1988

    NASA Technical Reports Server (NTRS)

    Heybey, Andrew Tyrrell

    1990-01-01

    The author uses a network simulator to explore rate-based congestion control in networks with smart links that can feed back information to tell senders to adjust their transmission rates. This method differs in a very important way from congestion control in which a congested network component just drops packets - the most commonly used method. It is clearly advantageous for the links in the network to communicate with the end users about the network capacity, rather than the users unilaterally picking a transmission rate. The components in the middle of the network, not the end users, have information about the capacity and traffic in the network. The author experiments with three different algorithms for calculating the control rate to feed back to the users. All of the algorithms exhibit problems in the form of large queues when simulated with a configuration modeling the dynamics of a packet-voice system. However, the problems are not with the algorithms themselves, but with the fact that feedback takes time. If the network steady-state utilization is low enough that it can absorb transients in the traffic through it, then the large queues disappear. If the users are modified to start sending slowly, to allow the network to adapt to a new flow without causing congestion, a greater portion of the network's bandwidth can be used.

  5. Neural network classifier with analytic translation and scaling capabilities for optimal signal viewing

    SciTech Connect

    Vilim, R.B.; Wegerich, S.W.

    1995-12-31

    A neural network originally proposed by Szu for performing pattern recognition has been modified for use in a noisy manufacturing environment. Signals from the factory floor are frequently affine transformed and, as a consequence, a signal may not be properly aligned with respect to the input node that corresponds to the signal leading edge or with respect to the number of nodes representing the time varying part. Rater than translate and scale the presented signal, an operation which because of noise can be prone to numerical error since the signal is not smoothly varying, the network in this paper has the capability to analytically translate and scale its internal representation of the signal so that it overlays the presented signal. A response surface in the neighborhood of the stored reference signal is built during, training, and covers the range of translate and scale parameter values expected. A genetic algorithm is used to search over this hilly terrain to find the optimal values of these parameters so that the reference signal overlays the presented signal. The procedure is repeated over all hypothesized pattern classes with the best fit identifying the class.

  6. Influence of the modulation index of Mach-Zehnder modulator on intersatellite microwave photonics links with multiple RF signals

    NASA Astrophysics Data System (ADS)

    Zhu, Zihang; Zhao, Shanghong; Li, Yongjun; Chu, Xingchun; Hou, Rui

    2013-04-01

    A generalized intersatellite microwave photonics links model to study the influence of the modulation index of Mach-Zehnder modulator on the receiver sensitivity with multiple radio frequency (RF) signals is presented. An exact analytical solution of signal-to-noise and distortion ratio (SNDR) for optical double-sideband (ODSB) and optical single-sideband (OSSB) modulation is deduced with Bessel expansion and Graf's addition theorem. Numerical results show that the receiver sensitivity increases and then decreases as the increase in modulation index, there is an optimum modulation index that maximizes the receiver sensitivity and the larger channel numbers lead to lower receiver sensitivity for maintaining the SNDR at the desired level. In addition, ODSB modulation can be more attractive than OSSB modulation in intersatellite microwave photonics links, since the maximum receiver sensitivity for ODSB modulation is better than that for OSSB modulation.

  7. Constitutive and ligand-induced EGFR signaling triggers distinct and mutually exclusive downstream signaling networks

    PubMed Central

    Chakraborty, Sharmistha; Li, Li; Puliyappadamba, VineshkumarThidil; Guo, Gao; Hatanpaa, Kimmo J.; Mickey, Bruce; Souza, Rhonda F.; Vo, Peggy; Herz, Joachim; Chen, Mei-Ru; Boothman, David A.; Pandita, Tej K.; Wang, David H.; Sen, Ganes C.; Habib, Amyn A.

    2014-01-01

    EGFR overexpression plays an important oncogenic role in cancer. Regular EGFR protein levels are increased in cancer cells and the receptor then becomes constitutively active. However, downstream signals generated by constitutively activated EGFR are unknown. Here we report that the overexpressed EGFR oscillates between two distinct and mutually exclusive modes of signaling. Constitutive or non-canonical EGFR signaling activates the transcription factor IRF3 leading to expression of IFI27, IFIT1, and TRAIL. Ligand-mediated activation of EGFR switches off IRF3 dependent transcription, activates canonical ERK and Akt signals, and confers sensitivity to chemotherapy and virus-induced cell death. Mechanistically, the distinct downstream signals result from a switch of EGFR associated proteins. EGFR constitutively complexes with IRF3 and TBK1 leading to TBK1 and IRF3 phosphorylation. Addition of EGF dissociates TBK1, IRF3, and EGFR leading to a loss of IRF3 activity, Shc-EGFR association and ERK activation. Finally, we provide evidence for non-canonical EGFR signaling in glioblastoma. PMID:25503978

  8. Learning signaling network structures with sparsely distributed data.

    PubMed

    Sachs, Karen; Itani, Solomon; Carlisle, Jennifer; Nolan, Garry P; Pe'er, Dana; Lauffenburger, Douglas A

    2009-02-01

    Flow cytometric measurement of signaling protein abundances has proved particularly useful for elucidation of signaling pathway structure. The single cell nature of the data ensures a very large dataset size, providing a statistically robust dataset for structure learning. Moreover, the approach is easily scaled to many conditions in high throughput. However, the technology suffers from a dimensionality constraint: at the cutting edge, only about 12 protein species can be measured per cell, far from sufficient for most signaling pathways. Because the structure learning algorithm (in practice) requires that all variables be measured together simultaneously, this restricts structure learning to the number of variables that constitute the flow cytometer's upper dimensionality limit. To address this problem, we present here an algorithm that enables structure learning for sparsely distributed data, allowing structure learning beyond the measurement technology's upper dimensionality limit for simultaneously measurable variables. The algorithm assesses pairwise (or n-wise) dependencies, constructs "Markov neighborhoods" for each variable based on these dependencies, measures each variable in the context of its neighborhood, and performs structure learning using a constrained search.

  9. Linking Geophysical Networks to International Economic Development Through Integration of Global and National Monitoring

    NASA Astrophysics Data System (ADS)

    Lerner-Lam, A.

    2007-05-01

    Outside of the research community and mission agencies, global geophysical monitoring rarely receives sustained attention except in the aftermath of a humanitarian disaster. The recovery and rebuilding period focuses attention and resources for a short time on regional needs for geophysical observation, often at the national or sub-national level. This can result in the rapid deployment of national monitoring networks, but may overlook the longer-term benefits of integration with global networks. Even in the case of multinational disasters, such as the Indian Ocean tsunami, it has proved difficult to promote the integration of national solutions with global monitoring, research and operations infrastructure. More importantly, continuing operations at the national or sub-national scale are difficult to sustain once the resources associated with recovery and rebuilding are depleted. Except for some notable examples, the vast infrastructure associated with global geophysical monitoring is not utilized constructively to promote the integration of national networks with international efforts. This represents a missed opportunity not only for monitoring, but for developing the international research and educational collaborations necessary for technological transfer and capacity building. The recent confluence of highly visible disasters, global multi-hazard risk assessments, evaluations of the relationships between natural disasters and socio-economic development, and shifts in development agency policies, provides an opportunity to link global geophysical monitoring initiatives to central issues in international development. Natural hazard risk reduction has not been the first priority of international development agendas for understandable, mainly humanitarian reasons. However, it is now recognized that the so-called risk premium associated with making development projects more risk conscious or risk resilient is relatively small relative to potential losses. Thus

  10. Intrinsic excitability state of local neuronal population modulates signal propagation in feed-forward neural networks.

    PubMed

    Han, Ruixue; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xilei; Qin, Yingmei; Wang, Haixu

    2015-04-01

    Reliable signal propagation across distributed brain areas is an essential requirement for cognitive function, and it has been investigated extensively in computational studies where feed-forward network (FFN) is taken as a generic model. But it is still unclear how distinct local network states, which are intrinsically generated by synaptic interactions within each layer, would affect the ability of FFN to transmit information. Here we investigate the impact of such network states on propagating transient synchrony (synfire) and firing rate by a combination of numerical simulations and analytical approach. Specifically, local network dynamics is attributed to the competition between excitatory and inhibitory neurons within each layer. Our results show that concomitant with different local network states, the performance of signal propagation differs dramatically. For both synfire propagation and firing rate propagation, there exists an optimal local excitability state, respectively, that optimizes the performance of signal propagation. Furthermore, we find that long-range connections strongly change the dependence of spiking activity propagation on local network state and propose that these two factors work jointly to determine information transmission across distributed networks. Finally, a simple mean field approach that bridges response properties of long-range connectivity and local subnetworks is utilized to reveal the underlying mechanism.

  11. Intrinsic excitability state of local neuronal population modulates signal propagation in feed-forward neural networks

    NASA Astrophysics Data System (ADS)

    Han, Ruixue; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xilei; Qin, Yingmei; Wang, Haixu

    2015-04-01

    Reliable signal propagation across distributed brain areas is an essential requirement for cognitive function, and it has been investigated extensively in computational studies where feed-forward network (FFN) is taken as a generic model. But it is still unclear how distinct local network states, which are intrinsically generated by synaptic interactions within each layer, would affect the ability of FFN to transmit information. Here we investigate the impact of such network states on propagating transient synchrony (synfire) and firing rate by a combination of numerical simulations and analytical approach. Specifically, local network dynamics is attributed to the competition between excitatory and inhibitory neurons within each layer. Our results show that concomitant with different local network states, the performance of signal propagation differs dramatically. For both synfire propagation and firing rate propagation, there exists an optimal local excitability state, respectively, that optimizes the performance of signal propagation. Furthermore, we find that long-range connections strongly change the dependence of spiking activity propagation on local network state and propose that these two factors work jointly to determine information transmission across distributed networks. Finally, a simple mean field approach that bridges response properties of long-range connectivity and local subnetworks is utilized to reveal the underlying mechanism.

  12. Study in Mice Links Key Signaling Molecule to Underlying Cause of Osteogenesis Imperfecta

    MedlinePlus

    ... by mutations in a gene that codes for collagen, an abundant structural component of bone. This type ... linked to defects in enzymes that help process collagen to its mature form. These types of OI ...

  13. Dynamical system modeling via signal reduction and neural network simulation

    SciTech Connect

    Paez, T.L.; Hunter, N.F.

    1997-11-01

    Many dynamical systems tested in the field and the laboratory display significant nonlinear behavior. Accurate characterization of such systems requires modeling in a nonlinear framework. One construct forming a basis for nonlinear modeling is that of the artificial neural network (ANN). However, when system behavior is complex, the amount of data required to perform training can become unreasonable. The authors reduce the complexity of information present in system response measurements using decomposition via canonical variate analysis. They describe a method for decomposing system responses, then modeling the components with ANNs. A numerical example is presented, along with conclusions and recommendations.

  14. Bioelectric signal classification using a recurrent probabilistic neural network with time-series discriminant component analysis.

    PubMed

    Hayashi, Hideaki; Shima, Keisuke; Shibanoki, Taro; Kurita, Yuichi; Tsuji, Toshio

    2013-01-01

    This paper outlines a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower-dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model that incorporates a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into a neural network so that parameters can be obtained appropriately as network coefficients according to backpropagation-through-time-based training algorithm. The network is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. In the experiments conducted during the study, the validity of the proposed network was demonstrated for EEG signals.

  15. Noise in Neural Networks: Thresholds, Hysteresis, and Neuromodulation of Signal-To-Noise

    NASA Astrophysics Data System (ADS)

    Keeler, James D.; Pichler, Elgar E.; Ross, John

    1989-03-01

    We study a neural-network model including Gaussian noise, higher-order neuronal interactions, and neuromodulation. For a first-order network, there is a threshold in the noise level (phase transition) above which the network displays only disorganized behavior and critical slowing down near the noise threshold. The network can tolerate more noise if it has higher-order feedback interactions, which also lead to hysteresis and multistability in the network dynamics. The signal-to-noise ratio can be adjusted in a biological neural network by neuromodulators such as norepinephrine. Comparisons are made to experimental results and further investigations are suggested to test the effects of hysteresis and neuromodulation in pattern recognition and learning. We propose that norepinephrine may ``quench'' the neural patterns of activity to enhance the ability to learn details.

  16. IFT27 Links the BBSome to IFT for Maintenance of the Ciliary Signaling Compartment

    PubMed Central

    Eguether, Thibaut; San Agustin, Jovenal T.; Keady, Brian T.; Jonassen, Julie A.; Liang, Yinwen; Francis, Richard; Tobita, Kimimasa; Johnson, Colin A.; Abdelhamed, Zakia A.; Lo, Cecilia W.; Pazour, Gregory J.

    2014-01-01

    Vertebrate hedgehog signaling is coordinated by the differential localization of the receptors patched-1 and smoothened in the primary cilium. Cilia assembly is mediated by intraflagellar transport (IFT) and cilia defects disrupt hedgehog signaling, causing many structural birth defects. We generated Ift25 and Ift27 knockout mice and show they have structural birth defects indicative of hedgehog signaling dysfunction. Surprisingly ciliary assembly is not affected, but abnormal hedgehog signaling is observed in conjunction with ciliary accumulation of patched-1 and smoothened. Similarly smoothened accumulates in cilia on cells mutated for BBSome components or the BBS binding protein/regulator Lztfl1. Interestingly, the BBSome and Lztfl1 accumulate to high levels in Ift27 mutant cilia. Since Lztfl1 mutant cells accumulate BBSome but not IFT27 it is likely that Lztfl1 functions downstream of IFT27 to couple the BBSome to the IFT particle for coordinated removal of patched-1 and smoothened from cilia during hedgehog signaling. PMID:25446516

  17. Linking chemical parameters to sensory panel results through neural networks to distinguish olive oil quality.

    PubMed

    Cancilla, John C; Wang, Selina C; Díaz-Rodríguez, Pablo; Matute, Gemma; Cancilla, John D; Flynn, Dan; Torrecilla, José S

    2014-11-01

    A wide variety of olive oil samples from different origins and olive types has been chemically analyzed as well as evaluated by trained sensory panelists. Six chemical parameters have been obtained for each sample (free fatty acids, peroxide value, two UV absorption parameters (K232 and K268), 1,2-diacylglycerol content, and pyropheophytins) and linked to their quality using an artificial neural network-based model. Herein, the nonlinear algorithms were used to distinguish olive oil quality. Two different methods were defined to assess the statistical performance of the model (a K-fold cross-validation (K = 6) and three different blind tests), and both of them showed around a 95-96% correct classification rate. These results support that a relationship between the chemical and the sensory analyses exists and that the mathematical tool can potentially be implemented into a device that could be employed for various useful applications.

  18. Robust neural-network control of rigid-link electrically driven robots.

    PubMed

    Kwan, C; Lewis, F L; Dawson, D M

    1998-01-01

    A robust neural-network (NN) controller is proposed for the motion control of rigid-link electrically driven (RLED) robots. Two-layer NN's are used to approximate two very complicated nonlinear functions. The main advantage of our approach is that the NN weights are tuned on-line, with no off-line learning phase required. Most importantly, we can guarantee the uniformly ultimately bounded (UUB) stability of tracking errors and NN weights. When compared with standard adaptive robot controllers, we do not require lengthy and tedious preliminary analysis to determine a regression matrix. The controller can be regarded as a universal reusable controller because the same controller can be applied to any type of RLED robots without any modifications.

  19. A computer model for unconscious spread of anxiety-linked inhibition in cognitive networks.

    PubMed

    Blum, G S

    1989-01-01

    Unconscious inhibitory processes, triggered by a potential anxiety reaction, are reviewed in the context of an emerging rapprochement between psychodynamic and cognitive approaches in experimental psychology. Conditions underlying spread of inhibitory action to other cognitive networks are first explored in three tachistoscopic experiments utilizing words posthypnotically tied to a potential anxiety, pleasure, or neutral reaction. Response times of subjects, instructed to ignore those words while naming pictures or solving anagrams as quickly as possible, reveal a highly differentiated pattern of circumstances governing likelihood of inhibitory spread from anxiety-linked words to target stimuli. Next a computer model is constructed to simulate cognitive processes from onset of display to eventual response, and the model is then tested for its fit to the empirical data. Finally, an illustrative study shows that a subset of computer-generated predictions for spread of inhibitory action is verifiable experimentally. PMID:2920005

  20. Wavelength assignment algorithm considering the state of neighborhood links for OBS networks

    NASA Astrophysics Data System (ADS)

    Tanaka, Yu; Hirota, Yusuke; Tode, Hideki; Murakami, Koso

    2005-10-01

    Recently, Optical WDM technology is introduced into backbone networks. On the other hand, as the future optical switching scheme, Optical Burst Switching (OBS) systems become a realistic solution. OBS systems do not consider buffering in intermediate nodes. Thus, it is an important issue to avoid overlapping wavelength reservation between partially interfered paths. To solve this problem, so far, the wavelength assignment scheme which has priority management tables has been proposed. This method achieves the reduction of burst blocking probability. However, this priority management table requires huge memory space. In this paper, we propose a wavelength assignment algorithm that reduces both the number of priority management tables and burst blocking probability. To reduce priority management tables, we allocate and manage them for each link. To reduce burst blocking probability, our method announces information about the change of their priorities to intermediate nodes. We evaluate its performance in terms of the burst blocking probability and the reduction rate of priority management tables.

  1. Reconstruction of Signaling Networks Regulating Fungal Morphogenesis by Transcriptomics▿ †

    PubMed Central

    Meyer, Vera; Arentshorst, Mark; Flitter, Simon J.; Nitsche, Benjamin M.; Kwon, Min Jin; Reynaga-Peña, Cristina G.; Bartnicki-Garcia, Salomon; van den Hondel, Cees A. M. J. J.; Ram, Arthur F. J.

    2009-01-01

    Coordinated control of hyphal elongation and branching is essential for sustaining mycelial growth of filamentous fungi. In order to study the molecular machinery ensuring polarity control in the industrial fungus Aspergillus niger, we took advantage of the temperature-sensitive (ts) apical-branching ramosa-1 mutant. We show here that this strain serves as an excellent model system to study critical steps of polar growth control during mycelial development and report for the first time a transcriptomic fingerprint of apical branching for a filamentous fungus. This fingerprint indicates that several signal transduction pathways, including TORC2, phospholipid, calcium, and cell wall integrity signaling, concertedly act to control apical branching. We furthermore identified the genetic locus affected in the ramosa-1 mutant by complementation of the ts phenotype. Sequence analyses demonstrated that a single amino acid exchange in the RmsA protein is responsible for induced apical branching of the ramosa-1 mutant. Deletion experiments showed that the corresponding rmsA gene is essential for the growth of A. niger, and complementation analyses with Saccharomyces cerevisiae evidenced that RmsA serves as a functional equivalent of the TORC2 component Avo1p. TORC2 signaling is required for actin polarization and cell wall integrity in S. cerevisiae. Congruently, our microscopic investigations showed that polarized actin organization and chitin deposition are disturbed in the ramosa-1 mutant. The integration of the transcriptomic, genetic, and phenotypic data obtained in this study allowed us to reconstruct a model for cellular events involved in apical branching. PMID:19749177

  2. Protein and Signaling Networks in Vertebrate Photoreceptor Cells

    PubMed Central

    Koch, Karl-Wilhelm; Dell’Orco, Daniele

    2015-01-01

    Vertebrate photoreceptor cells are exquisite light detectors operating under very dim and bright illumination. The photoexcitation and adaptation machinery in photoreceptor cells consists of protein complexes that can form highly ordered supramolecular structures and control the homeostasis and mutual dependence of the secondary messengers cyclic guanosine monophosphate (cGMP) and Ca2+. The visual pigment in rod photoreceptors, the G protein-coupled receptor rhodopsin is organized in tracks of dimers thereby providing a signaling platform for the dynamic scaffolding of the G protein transducin. Illuminated rhodopsin is turned off by phosphorylation catalyzed by rhodopsin kinase (GRK1) under control of Ca2+-recoverin. The GRK1 protein complex partly assembles in lipid raft structures, where shutting off rhodopsin seems to be more effective. Re-synthesis of cGMP is another crucial step in the recovery of the photoresponse after illumination. It is catalyzed by membrane bound sensory guanylate cyclases (GCs) and is regulated by specific neuronal Ca2+-sensor proteins called guanylate cyclase-activating proteins (GCAPs). At least one GC (ROS-GC1) was shown to be part of a multiprotein complex having strong interactions with the cytoskeleton and being controlled in a multimodal Ca2+-dependent fashion. The final target of the cGMP signaling cascade is a cyclic nucleotide-gated (CNG) channel that is a hetero-oligomeric protein located in the plasma membrane and interacting with accessory proteins in highly organized microdomains. We summarize results and interpretations of findings related to the inhomogeneous organization of signaling units in photoreceptor outer segments. PMID:26635520

  3. Cilia and coordination of signaling networks during heart development

    PubMed Central

    Koefoed, Karen; Veland, Iben Rønn; Pedersen, Lotte Bang; Larsen, Lars Allan; Christensen, Søren Tvorup

    2014-01-01

    Primary cilia are unique sensory organelles that coordinate a wide variety of different signaling pathways to control cellular processes during development and in tissue homeostasis. Defects in function or assembly of these antenna-like structures are therefore associated with a broad range of developmental disorders and diseases called ciliopathies. Recent studies have indicated a major role of different populations of cilia, including nodal and cardiac primary cilia, in coordinating heart development, and defects in these cilia are associated with congenital heart disease. Here, we present an overview of the role of nodal and cardiac primary cilia in heart development. PMID:24345806

  4. Rho GTPases at the crossroad of signaling networks in mammals

    PubMed Central

    Wojnacki, José; Quassollo, Gonzalo; Marzolo, María-Paz; Cáceres, Alfredo

    2014-01-01

    Microtubule (MT) organization and dynamics downstream of external cues is crucial for maintaining cellular architecture and the generation of cell asymmetries. In interphase cells RhoA, Rac, and Cdc42, conspicuous members of the family of small Rho GTPases, have major roles in modulating MT stability, and hence polarized cell behaviors. However, MTs are not mere targets of Rho GTPases, but also serve as signaling platforms coupling MT dynamics to Rho GTPase activation in a variety of cellular conditions. In this article, we review some of the key studies describing the reciprocal relationship between small Rho-GTPases and MTs during migration and polarization. PMID:24691223

  5. Traffic signal synchronization in the saturated high-density grid road network.

    PubMed

    Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

    2015-01-01

    Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

  6. Traffic signal synchronization in the saturated high-density grid road network.

    PubMed

    Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

    2015-01-01

    Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN. PMID:25663835

  7. Traffic Signal Synchronization in the Saturated High-Density Grid Road Network

    PubMed Central

    Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

    2015-01-01

    Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN. PMID:25663835

  8. Multimodal signalling in the North American barn swallow: a phenotype network approach

    PubMed Central

    Wilkins, Matthew R.; Shizuka, Daizaburo; Joseph, Maxwell B.; Hubbard, Joanna K.; Safran, Rebecca J.

    2015-01-01

    Complex signals, involving multiple components within and across modalities, are common in animal communication. However, decomposing complex signals into traits and their interactions remains a fundamental challenge for studies of phenotype evolution. We apply a novel phenotype network approach for studying complex signal evolution in the North American barn swallow (Hirundo rustica erythrogaster). We integrate model testing with correlation-based phenotype networks to infer the contributions of female mate choice and male–male competition to the evolution of barn swallow communication. Overall, the best predictors of mate choice were distinct from those for competition, while moderate functional overlap suggests males and females use some of the same traits to assess potential mates and rivals. We interpret model results in the context of a network of traits, and suggest this approach allows researchers a more nuanced view of trait clustering patterns that informs new hypotheses about the evolution of communication systems. PMID:26423842

  9. Multimodal signalling in the North American barn swallow: a phenotype network approach.

    PubMed

    Wilkins, Matthew R; Shizuka, Daizaburo; Joseph, Maxwell B; Hubbard, Joanna K; Safran, Rebecca J

    2015-10-01

    Complex signals, involving multiple components within and across modalities, are common in animal communication. However, decomposing complex signals into traits and their interactions remains a fundamental challenge for studies of phenotype evolution. We apply a novel phenotype network approach for studying complex signal evolution in the North American barn swallow (Hirundo rustica erythrogaster). We integrate model testing with correlation-based phenotype networks to infer the contributions of female mate choice and male-male competition to the evolution of barn swallow communication. Overall, the best predictors of mate choice were distinct from those for competition, while moderate functional overlap suggests males and females use some of the same traits to assess potential mates and rivals. We interpret model results in the context of a network of traits, and suggest this approach allows researchers a more nuanced view of trait clustering patterns that informs new hypotheses about the evolution of communication systems.

  10. An affine continuum mechanical model for cross-linked F-actin networks with compliant linker proteins.

    PubMed

    Holzapfel, Gerhard A; Unterberger, Michael J; Ogden, Ray W

    2014-10-01

    Cross-linked actin networks are important building blocks of the cytoskeleton. In order to gain deeper insight into the interpretation of experimental data on actin networks, adequate models are required. In this paper we introduce an affine constitutive network model for cross-linked F-actin networks based on nonlinear continuum mechanics, and specialize it in order to reproduce the experimental behavior of in vitro reconstituted model networks. The model is based on the elastic properties of single filaments embedded in an isotropic matrix such that the overall properties of the composite are described by a free-energy function. In particular, we are able to obtain the experimentally determined shear and normal stress responses of cross-linked actin networks typically observed in rheometer tests. In the present study an extensive analysis is performed by applying the proposed model network to a simple shear deformation. The single filament model is then extended by incorporating the compliance of cross-linker proteins and further extended by including viscoelasticity. All that is needed for the finite element implementation is the constitutive model for the filaments, the linkers and the matrix, and the associated elasticity tensor in either the Lagrangian or Eulerian formulation. The model facilitates parameter studies of experimental setups such as micropipette aspiration experiments and we present such studies to illustrate the efficacy of this modeling approach. PMID:25043658

  11. Linking ligand perception by PEPR pattern recognition receptors to cytosolic Ca2+ elevation and downstream immune signaling in plants

    PubMed Central

    Walker, Robin K.; Zhao, Yichen; Berkowitz, Gerald A.

    2012-01-01

    Little is known about molecular steps linking perception of pathogen invasion by cell surface sentry proteins acting as pattern recognition receptors (PRRs) to downstream cytosolic Ca2+ elevation, a critical step in plant immune signaling cascades. Some PRRs recognize molecules (such as flagellin) associated with microbial pathogens (pathogen-associated molecular patterns, PAMPs), whereas others bind endogenous plant compounds (damage-associated molecular patterns, DAMPs) such as peptides released from cells upon attack. This work focuses on the Arabidopsis DAMPs plant elicitor peptides (Peps) and their receptors, PEPR1 and PEPR2. Pep application causes in vivo cGMP generation and downstream signaling that is lost when the predicted PEPR receptor guanylyl cyclase (GC) active site is mutated. Pep-induced Ca2+ elevation is attributable to cGMP activation of a Ca2+ channel. Some differences were identified between Pep/PEPR signaling and the Ca2+-dependent immune signaling initiated by the flagellin peptide flg22 and its cognate receptor Flagellin-sensing 2 (FLS2). FLS2 signaling may have a greater requirement for intracellular Ca2+ stores and inositol phosphate signaling, whereas Pep/PEPR signaling requires extracellular Ca2+. Maximal FLS2 signaling requires a functional Pep/PEPR system. This dependence was evidenced as a requirement for functional PEPR receptors for maximal flg22-dependent Ca2+ elevation, H2O2 generation, defense gene [WRKY33 and Plant Defensin 1.2 (PDF1.2)] expression, and flg22/FLS2-dependent impairment of pathogen growth. In a corresponding fashion, FLS2 loss of function impaired Pep signaling. In addition, a role for PAMP and DAMP perception in bolstering effector-triggered immunity (ETI) is reported; loss of function of either FLS2 or PEPR receptors impaired the hypersensitive response (HR) to an avirulent pathogen. PMID:23150556

  12. Linking ligand perception by PEPR pattern recognition receptors to cytosolic Ca2+ elevation and downstream immune signaling in plants.

    PubMed

    Ma, Yi; Walker, Robin K; Zhao, Yichen; Berkowitz, Gerald A

    2012-11-27

    Little is known about molecular steps linking perception of pathogen invasion by cell surface sentry proteins acting as pattern recognition receptors (PRRs) to downstream cytosolic Ca(2+) elevation, a critical step in plant immune signaling cascades. Some PRRs recognize molecules (such as flagellin) associated with microbial pathogens (pathogen-associated molecular patterns, PAMPs), whereas others bind endogenous plant compounds (damage-associated molecular patterns, DAMPs) such as peptides released from cells upon attack. This work focuses on the Arabidopsis DAMPs plant elicitor peptides (Peps) and their receptors, PEPR1 and PEPR2. Pep application causes in vivo cGMP generation and downstream signaling that is lost when the predicted PEPR receptor guanylyl cyclase (GC) active site is mutated. Pep-induced Ca(2+) elevation is attributable to cGMP activation of a Ca(2+) channel. Some differences were identified between Pep/PEPR signaling and the Ca(2+)-dependent immune signaling initiated by the flagellin peptide flg22 and its cognate receptor Flagellin-sensing 2 (FLS2). FLS2 signaling may have a greater requirement for intracellular Ca(2+) stores and inositol phosphate signaling, whereas Pep/PEPR signaling requires extracellular Ca(2+). Maximal FLS2 signaling requires a functional Pep/PEPR system. This dependence was evidenced as a requirement for functional PEPR receptors for maximal flg22-dependent Ca(2+) elevation, H(2)O(2) generation, defense gene [WRKY33 and Plant Defensin 1.2 (PDF1.2)] expression, and flg22/FLS2-dependent impairment of pathogen growth. In a corresponding fashion, FLS2