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Sample records for outage-limited cellular network

  1. MSAT and cellular hybrid networking

    NASA Technical Reports Server (NTRS)

    Baranowsky, Patrick W., II

    1993-01-01

    Westinghouse Electric Corporation is developing both the Communications Ground Segment and the Series 1000 Mobile Phone for American Mobile Satellite Corporation's (AMSC's) Mobile Satellite (MSAT) system. The success of the voice services portion of this system depends, to some extent, upon the interoperability of the cellular network and the satellite communication circuit switched communication channels. This paper will describe the set of user-selectable cellular interoperable modes (cellular first/satellite second, etc.) provided by the Mobile Phone and described how they are implemented with the ground segment. Topics including roaming registration and cellular-to-satellite 'seamless' call handoff will be discussed, along with the relevant Interim Standard IS-41 Revision B Cellular Radiotelecommunications Intersystem Operations and IOS-553 Mobile Station - Land Station Compatibility Specification.

  2. Predicting and Analyzing Cellular Networks

    NASA Astrophysics Data System (ADS)

    Singh, Mona

    High-throughput experimental technologies, along with computational predictions, have resulted in large-scale biological networks for numerous organisms. Global analyses of biological networks provide new opportunities for revealing protein functions and pathways, and for uncovering cellular organization principles. In my talk, I will discuss a number of approaches we have developed over the years for the complementary problems of predicting interactions and analyzing interaction networks. First, I will describe a genomic approach for uncovering high-confidence regulatory interactions, and show how it can be effectively combined with a framework for predicting regulatory interactions for proteins with known structural domains but unknown binding specificity. Next, I will describe algorithms for analyzing protein interaction networks in order to uncover protein function and functional modules, and demonstrate the importance of considering the topological structure of interaction networks in order to make high quality predictions. Finally, I will present a framework for explicitly incorporating known attributes of individual proteins into the analysis of biological networks, and utilize it to discover recurring network patterns underlying a range of biological processes.

  3. Micromechanics of cellularized biopolymer networks

    PubMed Central

    Jones, Christopher A. R.; Cibula, Matthew; Feng, Jingchen; Krnacik, Emma A.; McIntyre, David H.; Levine, Herbert; Sun, Bo

    2015-01-01

    Collagen gels are widely used in experiments on cell mechanics because they mimic the extracellular matrix in physiological conditions. Collagen gels are often characterized by their bulk rheology; however, variations in the collagen fiber microstructure and cell adhesion forces cause the mechanical properties to be inhomogeneous at the cellular scale. We study the mechanics of type I collagen on the scale of tens to hundreds of microns by using holographic optical tweezers to apply pN forces to microparticles embedded in the collagen fiber network. We find that in response to optical forces, particle displacements are inhomogeneous, anisotropic, and asymmetric. Gels prepared at 21 °C and 37 °C show qualitative difference in their micromechanical characteristics. We also demonstrate that contracting cells remodel the micromechanics of their surrounding extracellular matrix in a strain- and distance-dependent manner. To further understand the micromechanics of cellularized extracellular matrix, we have constructed a computational model which reproduces the main experiment findings. PMID:26324923

  4. Aging cellular networks: chaperones as major participants.

    PubMed

    Soti, C; Csermely, P

    2007-01-01

    We increasingly rely on the network approach to understand the complexity of cellular functions. Chaperones (heat shock proteins) are key "networkers", which sequester and repair damaged proteins. In order to link the network approach and chaperones with the aging process, we first summarize the properties of aging networks suggesting a "weak link theory of aging". This theory suggests that age-related random damage primarily affects the overwhelming majority of the low affinity, transient interactions (weak links) in cellular networks leading to increased noise, destabilization and diversity. These processes may be further amplified by age-specific network remodelling and by the sequestration of weakly linked cellular proteins to protein aggregates of aging cells. Chaperones are weakly linked hubs (i.e., network elements with a large number of connections) and inter-modular bridge elements of protein-protein interaction, signalling and mitochondrial networks. As aging proceeds, the increased overload of damaged proteins is an especially important element contributing to cellular disintegration and destabilization. Additionally, chaperone overload may contribute to the increase of "noise" in aging cells, which leads to an increased stochastic resonance resulting in a deficient discrimination between signals and noise. Chaperone- and other multi-target therapies, which restore the missing weak links in aging cellular networks, may emerge as important anti-aging interventions. PMID:16814508

  5. Stability of Stochastic Neutral Cellular Neural Networks

    NASA Astrophysics Data System (ADS)

    Chen, Ling; Zhao, Hongyong

    In this paper, we study a class of stochastic neutral cellular neural networks. By constructing a suitable Lyapunov functional and employing the nonnegative semi-martingale convergence theorem we give some sufficient conditions ensuring the almost sure exponential stability of the networks. The results obtained are helpful to design stability of networks when stochastic noise is taken into consideration. Finally, two examples are provided to show the correctness of our analysis.

  6. Inferring cellular networks – a review

    PubMed Central

    Markowetz, Florian; Spang, Rainer

    2007-01-01

    In this review we give an overview of computational and statistical methods to reconstruct cellular networks. Although this area of research is vast and fast developing, we show that most currently used methods can be organized by a few key concepts. The first part of the review deals with conditional independence models including Gaussian graphical models and Bayesian networks. The second part discusses probabilistic and graph-based methods for data from experimental interventions and perturbations. PMID:17903286

  7. Heterogeneous Force Chains in Cellularized Biopolymer Network

    NASA Astrophysics Data System (ADS)

    Liang, Long; Jones, Christopher Allen Rucksack; Sun, Bo; Jiao, Yang

    Biopolymer Networks play an important role in coordinating and regulating collective cellular dynamics via a number of signaling pathways. Here, we investigate the mechanical response of a model biopolymer network due to the active contraction of embedded cells. Specifically, a graph (bond-node) model derived from confocal microscopy data is used to represent the network microstructure, and cell contraction is modeled by applying correlated displacements at specific nodes, representing the focal adhesion sites. A force-based stochastic relaxation method is employed to obtain force-balanced network under cell contraction. We find that the majority of the forces are carried by a small number of heterogeneous force chains emerged from the contracting cells. The force chains consist of fiber segments that either possess a high degree of alignment before cell contraction or are aligned due to the reorientation induced by cell contraction. Large fluctuations of the forces along different force chains are observed. Importantly, the decay of the forces along the force chains is significantly slower than the decay of radially averaged forces in the system, suggesting that the fibreous nature of biopolymer network structure could support long-range mechanical signaling between cells.

  8. Cellular automata modelling of biomolecular networks dynamics.

    PubMed

    Bonchev, D; Thomas, S; Apte, A; Kier, L B

    2010-01-01

    The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215

  9. Optimal flux patterns in cellular metabolic networks

    SciTech Connect

    Almaas, E

    2007-01-20

    The availability of whole-cell level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30,000 random cellular environments. The distribution of reaction fluxes is heavy-tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations have relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reaction are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central-carbon metabolic pathways for the sample of random environments.

  10. Optimal flux patterns in cellular metabolic networks

    NASA Astrophysics Data System (ADS)

    Almaas, Eivind

    2007-06-01

    The availability of whole-cell-level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate the metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30 000 random cellular environments. The distribution of reaction fluxes is heavy tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations has relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reactions are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central carbon metabolic pathways for the sample of random environments.

  11. A Wireless Communications Laboratory on Cellular Network Planning

    ERIC Educational Resources Information Center

    Dawy, Z.; Husseini, A.; Yaacoub, E.; Al-Kanj, L.

    2010-01-01

    The field of radio network planning and optimization (RNPO) is central for wireless cellular network design, deployment, and enhancement. Wireless cellular operators invest huge sums of capital on deploying, launching, and maintaining their networks in order to ensure competitive performance and high user satisfaction. This work presents a lab…

  12. Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

    PubMed

    Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

    2015-01-01

    An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction. PMID:26167934

  13. Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning

    PubMed Central

    Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

    2015-01-01

    An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction. PMID:26167934

  14. Energy efficiency analysis of relay-assisted cellular networks

    NASA Astrophysics Data System (ADS)

    Yu, Huan; Li, Yunzhou; Kountouris, Marios; Xu, Xibin; Wang, Jing

    2014-12-01

    To meet the demand for higher throughput, improved coverage and enhanced reliability, future wireless cellular networks face significant technical challenges. One promising solution is to place relay stations between transmitters and receivers in the cellular network. Meanwhile, as energy consumption reduction has been an important concern for the wireless industry, energy-efficient communications is of prime interest for future networks. In this paper, we study whether and how relays can improve the energy efficiency of cellular networks. Specifically, the energy efficiency of relay-assisted cellular networks is analyzed using tools of stochastic geometry. We first derive the coverage probability for the macro base station (MBS) to user (UE), the MBS to relay station (RS), and the RS to UE links, and then we model the power consumption at the MBS and RS. Based on the analytical model and expressions, the energy efficiency of relay-assisted cellular networks is then evaluated and is shown to be strictly quasi-concave on the transmit power for MBS to UE link or the RS to UE link. Numerical results show that the energy efficiency first improves while it hits a ceiling as the MBS density increases.

  15. Extracting insight from noisy cellular networks.

    PubMed

    Landry, Christian R; Levy, Emmanuel D; Abd Rabbo, Diala; Tarassov, Kirill; Michnick, Stephen W

    2013-11-21

    Network biologists attempt to extract meaningful relationships among genes or their products from very noisy data. We argue that what we categorize as noisy data may sometimes reflect noisy biology and therefore may shield a hidden meaning about how networks evolve and how matter is organized in the cell. We present practical solutions, based on existing evolutionary and biophysical concepts, through which our understanding of cell biology can be enormously enriched. PMID:24267884

  16. A new small-world network created by Cellular Automata

    NASA Astrophysics Data System (ADS)

    Ruan, Yuhong; Li, Anwei

    2016-08-01

    In this paper, we generate small-world networks by the Cellular Automaton based on starting with one-dimensional regular networks. Besides the common properties of small-world networks with small average shortest path length and large clustering coefficient, the small-world networks generated in this way have other properties: (i) The edges which are cut in the regular network can be controlled that whether the edges are reconnected or not, and (ii) the number of the edges of the small-world network model equals the number of the edges of the original regular network. In other words, the average degree of the small-world network model equals to the average degree of the original regular network.

  17. 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.

  18. Stochastic cellular automata model of neural networks.

    PubMed

    Goltsev, A V; de Abreu, F V; Dorogovtsev, S N; Mendes, J F F

    2010-06-01

    We propose a stochastic dynamical model of noisy neural networks with complex architectures and discuss activation of neural networks by a stimulus, pacemakers, and spontaneous activity. This model has a complex phase diagram with self-organized active neural states, hybrid phase transitions, and a rich array of behaviors. We show that if spontaneous activity (noise) reaches a threshold level then global neural oscillations emerge. Stochastic resonance is a precursor of this dynamical phase transition. These oscillations are an intrinsic property of even small groups of 50 neurons. PMID:20866454

  19. Personal communication in traditional cellular networks

    NASA Astrophysics Data System (ADS)

    Neuer, Ellwood I.

    1996-01-01

    The purpose of this paper is to describe the flow of calls through the mobile network as it applies to the operation of Basic and Enhanced Services. Included in the discussion is the overall network layout, the physical connections between the network entities, and the signaling protocols which allow the entities to be integrated. The specific functionality of the applications and services are not detailed as the specific implementation varies from vendor to vendor and from service provider to service provider. The Enhanced Services Platform is installed in a service providers network in order to offer mobile subscribers services and applications which would otherwise not be available. The service providers' objective is to increase revenue/subscriber, increase subscriber loyalty/decrease churn, and build competitive advantages through differentiation. The services provided on the Enhanced Services platform can be viewed as either Basic or Enhanced. For the purpose of this paper, Basic Services refers to Numeric Paging, Call Answering, and Voice Messaging while Enhanced Services refers to FAX Messaging, One Number Service, Voice Dialing and other Voice Recognition applications, Information Services including FAX on Demand, and Automated Call Routing.

  20. Increasing cellular coverage within integrated terrestrial/satellite mobile networks

    NASA Technical Reports Server (NTRS)

    Castro, Jonathan P.

    1995-01-01

    When applying the hierarchical cellular concept, the satellite acts as giant umbrella cell covering a region with some terrestrial cells. If a mobile terminal traversing the region arrives to the border-line or limits of a regular cellular ground service, network transition occurs and the satellite system continues the mobile coverage. To adequately assess the boundaries of service of a mobile satellite system an a cellular network within an integrated environment, this paper provides an optimized scheme to predict when a network transition may be necessary. Under the assumption of a classified propagation phenomenon and Lognormal shadowing, the study applies an analytical approach to estimate the location of a mobile terminal based on a reception of the signal strength emitted by a base station.

  1. Optimising base station location for UMTS cellular networks

    NASA Astrophysics Data System (ADS)

    Kalata, G.; Pozniak-Koszalka, I.; Koszalka, L.; Kasprzak, A.

    2014-12-01

    Rapid development of universal mobile telecommunication systems put demands on tools for assisting planning of cellular network infrastructure. The tools need to focus on critical issues in modern cellular networks and techniques used for previous generation system no longer serve useful. In this paper, an algorithm based on Branch & Bound approach is proposed for solving base station location problem, covering interference levels, traffic demands and power control mechanism. The efficiency of the algorithm is evaluated with respect to existing approaches for solving this problem - using the designed and implemented experimentation system.

  2. Millimeter-Wave Evolution for 5G Cellular Networks

    NASA Astrophysics Data System (ADS)

    Sakaguchi, Kei; Tran, Gia Khanh; Shimodaira, Hidekazu; Nanba, Shinobu; Sakurai, Toshiaki; Takinami, Koji; Siaud, Isabelle; Strinati, Emilio Calvanese; Capone, Antonio; Karls, Ingolf; Arefi, Reza; Haustein, Thomas

    Triggered by the explosion of mobile traffic, 5G (5th Generation) cellular network requires evolution to increase the system rate 1000 times higher than the current systems in 10 years. Motivated by this common problem, there are several studies to integrate mm-wave access into current cellular networks as multi-band heterogeneous networks to exploit the ultra-wideband aspect of the mm-wave band. The authors of this paper have proposed comprehensive architecture of cellular networks with mm-wave access, where mm-wave small cell basestations and a conventional macro basestation are connected to Centralized-RAN (C-RAN) to effectively operate the system by enabling power efficient seamless handover as well as centralized resource control including dynamic cell structuring to match the limited coverage of mm-wave access with high traffic user locations via user-plane/control-plane splitting. In this paper, to prove the effectiveness of the proposed 5G cellular networks with mm-wave access, system level simulation is conducted by introducing an expected future traffic model, a measurement based mm-wave propagation model, and a centralized cell association algorithm by exploiting the C-RAN architecture. The numerical results show the effectiveness of the proposed network to realize 1000 times higher system rate than the current network in 10 years which is not achieved by the small cells using commonly considered 3.5 GHz band. Furthermore, the paper also gives latest status of mm-wave devices and regulations to show the feasibility of using mm-wave in the 5G systems.

  3. Cellular neural networks for welding arc thermograms segmentation

    NASA Astrophysics Data System (ADS)

    Jamrozik, Wojciech

    2014-09-01

    Machine vision systems are used in many areas for monitoring of technological processes. Among this processes welding takes important place, where often infrared cameras are used. Besides reliable hardware, successful application of vision systems requires suitable software based on proper algorithms. One of most important group of image processing algorithms is connected to image segmentation. Obtainment of exact boundary of an object that changes shape in time, such as the welding arc, represented on a thermogram is not a trivial task. In the paper a segmentation method using supervised approach based on a cellular neural networks is presented. Simulated annealing and genetic algorithm were used for training of the network (template optimization). Comparison of proposed method to a well elaborated segmentation method based on region growing approach was made. Obtained results prove that the cellular neural network can be a valuable tool for infrared welding pool images segmentation.

  4. The role of actin networks in cellular mechanosensing

    NASA Astrophysics Data System (ADS)

    Azatov, Mikheil

    Physical processes play an important role in many biological phenomena, such as wound healing, organ development, and tumor metastasis. During these processes, cells constantly interact with and adapt to their environment by exerting forces to mechanically probe the features of their surroundings and generating appropriate biochemical responses. The mechanisms underlying how cells sense the physical properties of their environment are not well understood. In this thesis, I present my studies to investigate cellular responses to the stiffness and topography of the environment. In order to sense the physical properties of their environment, cells dynamically reorganize the structure of their actin cytoskeleton, a dynamic network of biopolymers, altering the shape and spatial distribution of protein assemblies. Several observations suggest that proteins that crosslink actin filaments may play an important role in cellular mechanosensitivity. Palladin is an actin-crosslinking protein that is found in the lamellar actin network, stress fibers and focal adhesions, cellular structures that are critical for mechanosensing of the physical environment. By virtue of its close interactions with these structures in the cell, palladin may play an important role in cell mechanics. However, the role of actin crosslinkers in general, and palladin in particular, in cellular force generation and mechanosensing is not well known. I have investigated the role of palladin in regulating the plasticity of the actin cytoskeleton and cellular force generation in response to alterations in substrate stiffness. I have shown that the expression levels of palladin modulate the forces exerted by cells and their ability to sense substrate stiffness. Perturbation experiments also suggest that palladin levels in cells altered myosin motor activity. These results suggest that the actin crosslinkers, such as palladin, and myosin motors coordinate for optimal cell function and to prevent aberrant

  5. Analysing Dynamical Behavior of Cellular Networks via Stochastic Bifurcations

    PubMed Central

    Zakharova, Anna; Kurths, Jürgen; Vadivasova, Tatyana; Koseska, Aneta

    2011-01-01

    The dynamical structure of genetic networks determines the occurrence of various biological mechanisms, such as cellular differentiation. However, the question of how cellular diversity evolves in relation to the inherent stochasticity and intercellular communication remains still to be understood. Here, we define a concept of stochastic bifurcations suitable to investigate the dynamical structure of genetic networks, and show that under stochastic influence, the expression of given proteins of interest is defined via the probability distribution of the phase variable, representing one of the genes constituting the system. Moreover, we show that under changing stochastic conditions, the probabilities of expressing certain concentration values are different, leading to different functionality of the cells, and thus to differentiation of the cells in the various types. PMID:21647432

  6. Using Cellular Communication Networks To Detect Air Pollution.

    PubMed

    David, Noam; Gao, H Oliver

    2016-09-01

    Accurate real time monitoring of atmospheric conditions at ground level is vital for hazard warning, meteorological forecasting, and various environmental applications required for public health and safety. However, conventional monitoring facilities are costly and often insufficient, for example, since they are not representative of the larger space and are not deployed densely enough in the field. There have been numerous scientific works showing the ability of commercial microwave links that comprise the data transmission infrastructure in cellular communication networks to monitor hydrometeors as a potential complementary solution. However, despite the large volume of research carried out in this emerging field during the past decade, no study has shown the ability of the system to provide critical information regarding air quality. Here we reveal the potential for identifying atmospheric conditions prone to air pollution by detecting temperature inversions that trap pollutants at ground level. The technique is based on utilizing standard signal measurements from an existing cellular network during routine operation. PMID:27490182

  7. Performance evaluation of cellular phone network based portable ECG device.

    PubMed

    Hong, Joo-Hyun; Cha, Eun-Jong; Lee, Tae-Soo

    2008-01-01

    In this study, cellular phone network based portable ECG device was developed and three experiments were performed to evaluate the accuracy, reliability and operability, applicability during daily life of the developed device. First, ECG signals were measured using the developed device and Biopac device (reference device) during sitting and marking time and compared to verify the accuracy of R-R intervals. Second, the reliable data transmission to remote server was verified on two types of simulated emergency event using patient simulator. Third, during daily life with five types of motion, accuracy of data transmission to remote server was verified on two types of event occurring. By acquiring and comparing subject's biomedical signal and motion signal, the accuracy, reliability and operability, applicability during daily life of the developed device were verified. Therefore, cellular phone network based portable ECG device can monitor patient with inobtrusive manner. PMID:19162767

  8. Cellular Automata with network incubation in information technology diffusion

    NASA Astrophysics Data System (ADS)

    Guseo, Renato; Guidolin, Mariangela

    2010-06-01

    Innovation diffusion of network goods determines direct network externalities that depress sales for long periods and delay full benefits. We model this effect through a multiplicative dynamic market potential driven by a latent individual threshold embedded in a special Cellular Automata representation. The corresponding mean field approximation of its aggregate version is a Riccati equation with a closed form solution. This allows the detection of a change-point time separating an incubation period from a subsequent take-off due to a collective threshold (critical mass). Weighted nonlinear least squares are the main inferential methodology. An application is analysed with reference to USA fax machine diffusion.

  9. Ion beam analysis based on cellular nonlinear networks

    NASA Astrophysics Data System (ADS)

    Senger, V.; Tetzlaff, R.; Reichau, H.; Ratzinger, U.

    2011-07-01

    The development of a non- destructive measurement method for ion beam parameters has been treated in various projects. Although results are promising, the high complexity of beam dynamics has made it impossible to implement a real time process control up to now. In this paper we will propose analysing methods based on the dynamics of Cellular Nonlinear Networks (CNN) that can be implemented on pixel parallel CNN based architectures and yield satisfying results even at low resolutions.

  10. Network Medicine: From Cellular Networks to the Human Diseasome

    NASA Astrophysics Data System (ADS)

    Barabasi, Albert-Laszlo

    2014-03-01

    Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The tools of network science offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction not only enrich our understanding of complex systems, but are also essential to identify new disease genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases.

  11. Tensegrity II. How structural networks influence cellular information processing networks

    NASA Technical Reports Server (NTRS)

    Ingber, Donald E.

    2003-01-01

    The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion) can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.

  12. Hybrid Spectral Efficient Cellular Network Deployment to Reduce RF Pollution

    NASA Astrophysics Data System (ADS)

    Katiyar, Sumit; K. Jain, R.; K. Agrawal, N.

    2012-09-01

    As the mobile telecommunication systems are growing tremendously all over the world, the numbers of handheld and base stations are also rapidly growing and it became very popular to see these base stations distributed everywhere in the neighborhood and on roof tops which has caused a considerable amount of panic to the public in Palestine concerning wither the radiated electromagnetic fields from these base stations may cause any health effect or hazard. Recently UP High Court in India ordered for removal of BTS towers from residential area, it has created panic among cellular communication network designers too. Green cellular networks could be a solution for the above problem. This paper deals with green cellular networks with the help of multi-layer overlaid hierarchical structure (macro / micro / pico / femto cells). Macrocell for area coverage, micro for pedestrian and a slow moving traffic while pico for indoor use and femto for individual high capacity users. This could be the answer of the problem of energy conservation and enhancement of spectral density also.

  13. ATR inhibition rewires cellular signaling networks induced by replication stress.

    PubMed

    Wagner, Sebastian A; Oehler, Hannah; Voigt, Andrea; Dalic, Denis; Freiwald, Anja; Serve, Hubert; Beli, Petra

    2016-02-01

    The slowing down or stalling of replication forks is commonly known as replication stress and arises from multiple causes such as DNA lesions, nucleotide depletion, RNA-DNA hybrids, and oncogene activation. The ataxia telangiectasia and Rad3-related kinase (ATR) plays an essential role in the cellular response to replication stress and inhibition of ATR has emerged as therapeutic strategy for the treatment of cancers that exhibit high levels of replication stress. However, the cellular signaling induced by replication stress and the substrate spectrum of ATR has not been systematically investigated. In this study, we employed quantitative MS-based proteomics to define the cellular signaling after nucleotide depletion-induced replication stress and replication fork collapse following ATR inhibition. We demonstrate that replication stress results in increased phosphorylation of a subset of proteins, many of which are involved in RNA splicing and transcription and have previously not been associated with the cellular replication stress response. Furthermore, our data reveal the ATR-dependent phosphorylation following replication stress and discover novel putative ATR target sites on MCM6, TOPBP1, RAD51AP1, and PSMD4. We establish that ATR inhibition rewires cellular signaling networks induced by replication stress and leads to the activation of the ATM-driven double-strand break repair signaling. PMID:26572502

  14. Distinctive Behaviors of Druggable Proteins in Cellular Networks

    PubMed Central

    Workman, Paul; Al-Lazikani, Bissan

    2015-01-01

    The interaction environment of a protein in a cellular network is important in defining the role that the protein plays in the system as a whole, and thus its potential suitability as a drug target. Despite the importance of the network environment, it is neglected during target selection for drug discovery. Here, we present the first systematic, comprehensive computational analysis of topological, community and graphical network parameters of the human interactome and identify discriminatory network patterns that strongly distinguish drug targets from the interactome as a whole. Importantly, we identify striking differences in the network behavior of targets of cancer drugs versus targets from other therapeutic areas and explore how they may relate to successful drug combinations to overcome acquired resistance to cancer drugs. We develop, computationally validate and provide the first public domain predictive algorithm for identifying druggable neighborhoods based on network parameters. We also make available full predictions for 13,345 proteins to aid target selection for drug discovery. All target predictions are available through canSAR.icr.ac.uk. Underlying data and tools are available at https://cansar.icr.ac.uk/cansar/publications/druggable_network_neighbourhoods/. PMID:26699810

  15. Network Coordinated Opportunistic Beamforming in Downlink Cellular Networks

    NASA Astrophysics Data System (ADS)

    Shin, Won-Yong; Jung, Bang Chul

    We propose a network coordinated opportunistic beamforming (NC-OBF) protocol for downlink K-cell networks with M-antenna base stations (BSs). In the NC-OBF scheme, based on pseudo-randomly generated BF vectors, a user scheduling strategy is introduced, where each BS opportunistically selects a set of mobile stations (MSs) whose desired signals generate the minimum interference to the other MSs. Its performance is then analyzed in terms of degrees-of-freedom (DoFs). As our achievability result, it is shown that KM DoFs are achievable if the number N of MSs in a cell scales at least as SNRKM-1, where SNR denotes the received signal-to-noise ratio. Furthermore, by deriving the corresponding upper bound on the DoFs, it is shown that the NC-OBF scheme is DoF-optimal. Note that the proposed scheme does not require the global channel state information and dimension expansion, thereby resulting in easier implementation.

  16. Mechanics of composite actin networks: in vitro and cellular perspectives

    NASA Astrophysics Data System (ADS)

    Upadhyaya, Arpita

    2014-03-01

    Actin filaments and associated actin binding proteins play an essential role in governing the mechanical properties of eukaryotic cells. Even though cells have multiple actin binding proteins (ABPs) that exist simultaneously to maintain the structural and mechanical integrity of the cellular cytoskeleton, how these proteins work together to determine the properties of actin networks is not well understood. The ABP, palladin, is essential for the integrity of cell morphology and movement during development. Palladin coexists with alpha-actinin in stress fibers and focal adhesions and binds to both actin and alpha-actinin. To obtain insight into how mutually interacting actin crosslinking proteins modulate the properties of actin networks, we have characterized the micro-structure and mechanics of actin networks crosslinked with palladin and alpha-actinin. Our studies on composite networks of alpha-actinin/palladin/actin show that palladin and alpha-actinin synergistically determine network viscoelasticity. We have further examined the role of palladin in cellular force generation and mechanosensing. Traction force microscopy revealed that TAFs are sensitive to substrate stiffness as they generate larger forces on substrates of increased stiffness. Contrary to expectations, knocking down palladin increased the forces generated by cells, and also inhibited the ability to sense substrate stiffness for very stiff gels. This was accompanied by significant differences in the actin organization and adhesion dynamics of palladin knock down cells. Perturbation experiments also suggest altered myosin activity in palladin KD cells. Our results suggest that the actin crosslinkers such as palladin and myosin motors coordinate for optimal cell function and to prevent aberrant behavior as in cancer metastasis.

  17. Study and Simulation of Traffic Behavior in Cellular Network

    NASA Astrophysics Data System (ADS)

    Madhup, D. K.; Shrestha, C. L.; Sharma, R. K.

    2007-07-01

    Cellular radio systems accommodate a large number of users with a limited radio spectrum. The concept of trunking allows a large number of users to share the relatively small number of channels in a cell by providing access to each user, on demand, from a pool of available channels. Traffic engineering deals with provisioning of communication circuits in a given area for a number of subscribers with a required grade of service. Traffic in any cell depends upon the number of users, the average request rate and average call duration. Certain number of channels is required for the required GOS. To design an optimum capacity cellular system, traffic behavior on that system is important. The number of channel required can be estimated by using Erlang formula and Erlang table. Erlang table is not always useful to calculate the probability of blocking in various complex scenarios such as channel borrowing strategies. When the total number of channel available in a given cell are divided to serve partly for newly generated calls and partly for handover calls, and if they use dynamic channel assignment strategies like channel borrowing, then the probability of blocking can't be calculated from Erlang table. Simulation model of the behavior help us to determine the blocking and the channel utilization while using various channel assignment strategies. The title "Study and Simulation of Traffic Behavior in Cellular Network" entail the study of the blocking probability of traffic in cellular network for static channel assignment strategies and dynamic channel borrowing strategies through MATLAB programming language and graphic user interface (GUI). The result shows that the dynamic scheme can perform better than static maximizing the overall utilization of the circuits and minimizing the overall blocking.

  18. Country-wide rainfall maps from cellular communication networks

    PubMed Central

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2013-01-01

    Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal’s attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space–time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km2), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

  19. Country-wide rainfall maps from cellular communication networks.

    PubMed

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2013-02-19

    Accurate and timely surface precipitation measurements are crucial for water resources management, agriculture, weather prediction, climate research, as well as ground validation of satellite-based precipitation estimates. However, the majority of the land surface of the earth lacks such data, and in many parts of the world the density of surface precipitation gauging networks is even rapidly declining. This development can potentially be counteracted by using received signal level data from the enormous number of microwave links used worldwide in commercial cellular communication networks. Along such links, radio signals propagate from a transmitting antenna at one base station to a receiving antenna at another base station. Rain-induced attenuation and, subsequently, path-averaged rainfall intensity can be retrieved from the signal's attenuation between transmitter and receiver. Here, we show how one such a network can be used to retrieve the space-time dynamics of rainfall for an entire country (The Netherlands, ∼35,500 km(2)), based on an unprecedented number of links (∼2,400) and a rainfall retrieval algorithm that can be applied in real time. This demonstrates the potential of such networks for real-time rainfall monitoring, in particular in those parts of the world where networks of dedicated ground-based rainfall sensors are often virtually absent. PMID:23382210

  20. Cutting the Wires: Modularization of Cellular Networks for Experimental Design

    PubMed Central

    Lang, Moritz; Summers, Sean; Stelling, Jörg

    2014-01-01

    Understanding naturally evolved cellular networks requires the consecutive identification and revision of the interactions between relevant molecular species. In this process, initially often simplified and incomplete networks are extended by integrating new reactions or whole subnetworks to increase consistency between model predictions and new measurement data. However, increased consistency with experimental data alone is not sufficient to show the existence of biomolecular interactions, because the interplay of different potential extensions might lead to overall similar dynamics. Here, we present a graph-based modularization approach to facilitate the design of experiments targeted at independently validating the existence of several potential network extensions. Our method is based on selecting the outputs to measure during an experiment, such that each potential network extension becomes virtually insulated from all others during data analysis. Each output defines a module that only depends on one hypothetical network extension, and all other outputs act as virtual inputs to achieve insulation. Given appropriate experimental time-series measurements of the outputs, our modules can be analyzed, simulated, and compared to the experimental data separately. Our approach exemplifies the close relationship between structural systems identification and modularization, an interplay that promises development of related approaches in the future. PMID:24411264

  1. Emulating fire propagation by using cellular nonlinear networks

    NASA Astrophysics Data System (ADS)

    Buscarino, A.; Fortuna, L.; Frasca, M.; Xibilia, M. G.

    2012-09-01

    In this paper a new approach based on Cellular Nonlinear Networks (CNNs) for modeling the diffusion of forest fires is presented. Based on a model relying on an hyperbolic reaction-diffusion equation, the proposed approach exploits the peculiarity of CNNs allowing the investigation of different types of forest fires, also considering specific morphological characteristics of the terrain and the presence of external perturbations like wind flows. Results show the emergence of particular phenomena really observed in wildfires, allowing to assess the validity of the approach.

  2. Application-Aware Dynamic Retransmission Control in Mobile Cellular Networks

    NASA Astrophysics Data System (ADS)

    Halima, Nadhir Ben; Kliazovich, Dzmitry; Granelli, Fabrizio

    This paper proposes an application-aware cross-layer approach between application/transport layers on the mobile terminal and link layer at the wireless base station to enable dynamic control on the strength of per-packet error protection for multimedia and data transfers. Specifically, in the context of cellular networks, the proposed scheme allows to control the desired level of Hybrid ARQ (HARQ) protection by using an in-band control feedback channel. Such protection is dynamically adapted on a per-packet basis and depends on the perceptual importance of different packets as well as on the reception history of the flow.

  3. Sources of Uncertainty in Rainfall Maps from Cellular Communication Networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2015-04-01

    and quantify the sources of uncertainty in such rainfall maps, but also to test the actual and optimal performance of one commercial microwave network from one of the cellular providers in The Netherlands.

  4. GPM ground validation via commercial cellular networks: an exploratory approach

    NASA Astrophysics Data System (ADS)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Brasjen, Noud; Uijlenhoet, Remko

    2016-04-01

    The suitability of commercial microwave link networks for ground validation of GPM (Global Precipitation Measurement) data is evaluated here. Two state-of-the-art rainfall products are compared over the land surface of the Netherlands for a period of 7 months, i.e., rainfall maps from commercial cellular communication networks and Integrated Multi-satellite Retrievals for GPM (IMERG). Commercial microwave link networks are nowadays the core component in telecommunications worldwide. Rainfall rates can be retrieved from measurements of attenuation between transmitting and receiving antennas. If adequately set up, these networks enable rainfall monitoring tens of meters above the ground at high spatiotemporal resolutions (temporal sampling of seconds to tens of minutes, and spatial sampling of hundreds of meters to tens of kilometers). The GPM mission is the successor of TRMM (Tropical Rainfall Measurement Mission). For two years now, IMERG offers rainfall estimates across the globe (180°W - 180°E and 60°N - 60°S) at spatiotemporal resolutions of 0.1° x 0.1° every 30 min. These two data sets are compared against a Dutch gauge-adjusted radar data set, considered to be the ground truth given its accuracy, spatiotemporal resolution and availability. The suitability of microwave link networks in satellite rainfall evaluation is of special interest, given the independent character of this technique, its high spatiotemporal resolutions and availability. These are valuable assets for water management and modeling of floods, landslides, and weather extremes; especially in places where rain gauge networks are scarce or poorly maintained, or where weather radar networks are too expensive to acquire and/or maintain.

  5. Cellular telephone-based wide-area radiation detection network

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2009-06-09

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  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. Sigma-delta cellular neural network for 2D modulation.

    PubMed

    Aomori, Hisashi; Otake, Tsuyoshi; Takahashi, Nobuaki; Tanaka, Mamoru

    2008-01-01

    Although sigma-delta modulation is widely used for analog-to-digital (A/D) converters, sigma-delta concepts are only for 1D signals. Signal processing in the digital domain is extremely useful for 2D signals such as used in image processing, medical imaging, ultrasound imaging, and so on. The intricate task that provides true 2D sigma-delta modulation is feasible in the spatial domain sigma-delta modulation using the discrete-time cellular neural network (DT-CNN) with a C-template. In the proposed architecture, the A-template is used for a digital-to-analog converter (DAC), the C-template works as an integrator, and the nonlinear output function is used for the bilevel output. In addition, due to the cellular neural network (CNN) characteristics, each pixel of an image corresponds to a cell of a CNN, and each cell is connected spatially by the A-template. Therefore, the proposed system can be thought of as a very large-scale and super-parallel sigma-delta modulator. Moreover, the spatio-temporal dynamics is designed to obtain an optimal reconstruction signal. The experimental results show the excellent reconstruction performance and capabilities of the CNN as a sigma-delta modulator. PMID:18215502

  8. Mesoscale assembly of chemically modified graphene into complex cellular networks

    NASA Astrophysics Data System (ADS)

    Barg, Suelen; Perez, Felipe Macul; Ni, Na; Do Vale Pereira, Paula; Maher, Robert C.; Garcia-Tuñon, Esther; Eslava, Salvador; Agnoli, Stefano; Mattevi, Cecilia; Saiz, Eduardo

    2014-07-01

    The widespread technological introduction of graphene beyond electronics rests on our ability to assemble this two-dimensional building block into three-dimensional structures for practical devices. To achieve this goal we need fabrication approaches that are able to provide an accurate control of chemistry and architecture from nano to macroscopic levels. Here, we describe a versatile technique to build ultralight (density ≥1 mg cm-3) cellular networks based on the use of soft templates and the controlled segregation of chemically modified graphene to liquid interfaces. These novel structures can be tuned for excellent conductivity; versatile mechanical response (elastic-brittle to elastomeric, reversible deformation, high energy absorption) and organic absorption capabilities (above 600 g per gram of material). The approach can be used to uncover the basic principles that will guide the design of practical devices that by combining unique mechanical and functional performance will generate new technological opportunities.

  9. Automatic generation of multipath algorithms in the cellular nonlinear network

    NASA Astrophysics Data System (ADS)

    Preciado, Victor M.; Guinea, Domingo; Montufar-Chaveznava, Rodrigo

    2001-04-01

    The objective of this work is to generate a learning machine capable of find solutions for complex image processing task by Cellular Neural Network (CNN's). First a general machine for automatic analog algorithm design independent of the problem to solve is created, this is accomplished through an evolutionary strategy that is an extension of genetic programming. Second, this work introduces a suite of sub- mechanisms that increase the power of genetic programming and contribute to reduce the enormous space search for producing a plentiful search. Some concepts in this section are related with AI theory, in such a way that in this work we are in the intersection field of AI and Image Processing by CNN.

  10. A 'bioproduction breadboard': programming, assembling, and actuating cellular networks.

    PubMed

    Zargar, Amin; Payne, Gregory F; Bentley, William E

    2015-12-01

    With advances in synthetic biology and biofabrication, cellular networks can be functionalized and connected with unprecedented sophistication. We describe a platform for the creation of a 'bioproduction breadboard'. This would consist of physically isolated product-producing cell populations, product capture devices, and other unit operations that function as programmed in place, using unique, orthogonal inputs. For product synthesis, customized cell populations would be connected through standardized, generic inputs allowing 'plug and play' functionality and primary, user-mediated regulation. In addition, through autonomous pathway redirection and balancing, the cells themselves would provide secondary, self-directed regulation to optimize bioproduction. By leveraging specialization and division of labor, we envision diverse cell populations linked to create new pathway designs. PMID:26342587

  11. Edge detection of noisy images based on cellular neural networks

    NASA Astrophysics Data System (ADS)

    Li, Huaqing; Liao, Xiaofeng; Li, Chuandong; Huang, Hongyu; Li, Chaojie

    2011-09-01

    This paper studies a technique employing both cellular neural networks (CNNs) and linear matrix inequality (LMI) for edge detection of noisy images. Our main work focuses on training templates of noise reduction and edge detection CNNs. Based on the Lyapunov stability theorem, we derive a criterion for global asymptotical stability of a unique equilibrium of the noise reduction CNN. Then we design an approach to train edge detection templates, and this approach can detect the edge precisely and efficiently, i.e., by only one iteration. Finally, we illustrate performance of the proposed methodology from the aspect of peak signal to noise ratio (PSNR) through computer simulations. Moreover, some comparisons are also given to prove that our method outperforms classical operators in gray image edge detection.

  12. Mesoscale assembly of chemically modified graphene into complex cellular networks

    PubMed Central

    Barg, Suelen; Perez, Felipe Macul; Ni, Na; do Vale Pereira, Paula; Maher, Robert C.; Garcia-Tuñon, Esther; Eslava, Salvador; Agnoli, Stefano; Mattevi, Cecilia; Saiz, Eduardo

    2014-01-01

    The widespread technological introduction of graphene beyond electronics rests on our ability to assemble this two-dimensional building block into three-dimensional structures for practical devices. To achieve this goal we need fabrication approaches that are able to provide an accurate control of chemistry and architecture from nano to macroscopic levels. Here, we describe a versatile technique to build ultralight (density ≥1 mg cm−3) cellular networks based on the use of soft templates and the controlled segregation of chemically modified graphene to liquid interfaces. These novel structures can be tuned for excellent conductivity; versatile mechanical response (elastic-brittle to elastomeric, reversible deformation, high energy absorption) and organic absorption capabilities (above 600 g per gram of material). The approach can be used to uncover the basic principles that will guide the design of practical devices that by combining unique mechanical and functional performance will generate new technological opportunities. PMID:24999766

  13. Country-wide rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

    2013-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular telecommunication networks may be employed for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall monitoring using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. Here we show how one cellular telecommunication network can be used to retrieve the space-time dynamics of rainfall for an entire country. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (2400) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both

  14. Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

    PubMed Central

    2011-01-01

    Background With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate the physiological effect of chemicals, including potential toxicity. Here we investigate a biologically motivated model for estimating tissue level responses by aggregating the behavior of a cell population. We assume that the molecular state of individual cells is independently governed by discrete non-deterministic signaling mechanisms. This results in noisy but highly reproducible aggregate level responses that are consistent with experimental data. Results We developed an asynchronous threshold Boolean network simulation algorithm to model signal transduction in a single cell, and then used an ensemble of these models to estimate the aggregate response across a cell population. Using published data, we derived a putative crosstalk network involving growth factors and cytokines - i.e., Epidermal Growth Factor, Insulin, Insulin like Growth Factor Type 1, and Tumor Necrosis Factor α - to describe early signaling events in cell proliferation signal transduction. Reproducibility of the modeling technique across ensembles of Boolean networks representing cell populations is investigated. Furthermore, we compare our simulation results to experimental observations of hepatocytes reported in the literature. Conclusion A systematic analysis of the results following differential stimulation of this model by growth factors and cytokines suggests that: (a) using Boolean network ensembles with asynchronous updating provides biologically plausible noisy individual cellular responses with reproducible mean behavior for large cell populations, and (b) with sufficient data our model can estimate the response to different concentrations of extracellular ligands. Our results suggest that this

  15. Cellular computational networks--a scalable architecture for learning the dynamics of large networked systems.

    PubMed

    Luitel, Bipul; Venayagamoorthy, Ganesh Kumar

    2014-02-01

    Neural networks for implementing large networked systems such as smart electric power grids consist of multiple inputs and outputs. Many outputs lead to a greater number of parameters to be adapted. Each additional variable increases the dimensionality of the problem and hence learning becomes a challenge. Cellular computational networks (CCNs) are a class of sparsely connected dynamic recurrent networks (DRNs). By proper selection of a set of input elements for each output variable in a given application, a DRN can be modified into a CCN which significantly reduces the complexity of the neural network and allows use of simple training methods for independent learning in each cell thus making it scalable. This article demonstrates this concept of developing a CCN using dimensionality reduction in a DRN for scalability and better performance. The concept has been analytically explained and empirically verified through application. PMID:24300549

  16. Sources of uncertainty in rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-03-01

    ground truth). Thus, we were able to not only identify and quantify the sources of uncertainty in such rainfall maps, but also to test the actual and optimal performance of one commercial microwave network from one of the cellular providers in the Netherlands.

  17. Cellular and network mechanisms of genetically-determined absence seizures.

    PubMed

    Pinault, Didier; O'Brien, Terence J

    2005-01-01

    The absence epilepsies are characterized by recurrent episodes of loss of consciousness associated with generalized spike-and-wave discharges, with an abrupt onset and offset, in the thalamocortical system. In the absence of detailed neurophysiological studies in humans, many of the concepts regarding the pathophysiological basis of absence seizures are based on studies in animal models. Each of these models has its particular strengths and limitations, and the validity of findings from these models for the human condition cannot be assumed. Consequently, studies in different models have produced some conflicting findings and conclusions. A long-standing concept, based primarily from studies in vivo in cats and in vitro brain slices, is that these paroxysmal electrical events develop suddenly from sleep-related spindle oscillations. More specifically, it is proposed that the initial mechanisms that underlie absence-related spike-and-wave discharges are located in the thalamus, involving especially the thalamic reticular nucleus. By contrast, more recent studies in well-established, genetic models of absence epilepsy in rats demonstrate that spike-and-wave discharges originate in a cortical focus and develop from a wake-related natural corticothalamic sensorimotor rhythm. In this review we integrate recent findings showing that, in both the thalamus and the neocortex, genetically-determined, absence-related spike-and-wave discharges are the manifestation of hypersynchronized, cellular, rhythmic excitations and inhibitions that result from a combination of complex, intrinsic, synaptic mechanisms. Arguments are put forward supporting the hypothesis that layer VI corticothalamic neurons act as 'drivers' in the generation of spike-and-wave discharges in the somatosensory thalamocortical system that result in corticothalamic resonances particularly initially involving the thalamic reticular nucleus. However an important unresolved question is: what are the cellular and

  18. Environmental Monitoring using Measurements from Cellular Network Infrastructure

    NASA Astrophysics Data System (ADS)

    David, N.; Gao, O. H.

    2015-12-01

    atmospheric phenomena using current and future planned frequencies of cellular network infrastructure will be introduced.

  19. Cellular nonlinear networks for strike-point localization at JET

    NASA Astrophysics Data System (ADS)

    Arena, P.; Fortuna, L.; Bruno, M.; Vagliasindi, G.; Murari, A.; Andrew, P.; Mazzitelli, G.

    2005-11-01

    At JET, the potential of fast image processing for real-time purposes is thoroughly investigated. Particular attention is devoted to smart sensors based on system on chip technology. The data of the infrared cameras were processed with a chip implementing a cellular nonlinear network (CNN) structure so as to support and complement the magnetic diagnostics in the real-time localization of the strike-point position in the divertor. The circuit consists of two layers of complementary metal-oxide semiconductor components, the first being the sensor and the second implementing the actual CNN. This innovative hardware has made it possible to determine the position of the maximum thermal load with a time resolution of the order of 30 ms. Good congruency has been found with the measurement from the thermocouples in the divertor, proving the potential of the infrared data in locating the region of the maximum thermal load. The results are also confirmed by JET magnetic codes, both those used for the equilibrium reconstructions and those devoted to the identification of the plasma boundary.

  20. Radio Resource Allocation on Complex 4G Wireless Cellular Networks

    NASA Astrophysics Data System (ADS)

    Psannis, Kostas E.

    2015-09-01

    In this article we consider the heuristic algorithm which improves step by step wireless data delivery over LTE cellular networks by using the total transmit power with the constraint on users’ data rates, and the total throughput with the constraints on the total transmit power as well as users’ data rates, which are jointly integrated into a hybrid-layer design framework to perform radio resource allocation for multiple users, and to effectively decide the optimal system parameter such as modulation and coding scheme (MCS) in order to adapt to the varying channel quality. We propose new heuristic algorithm which balances the accessible data rate, the initial data rates of each user allocated by LTE scheduler, the priority indicator which signals delay- throughput- packet loss awareness of the user, and the buffer fullness by achieving maximization of radio resource allocation for multiple users. It is noted that the overall performance is improved with the increase in the number of users, due to multiuser diversity. Experimental results illustrate and validate the accuracy of the proposed methodology.

  1. Network signatures of cellular immortalization in human lymphoblastoid cell lines

    SciTech Connect

    Shim, Sung-Mi; Jung, So-Young; Nam, Hye-Young; Kim, Hye-Ryun; Lee, Mee-Hee; Kim, Jun-Woo; Han, Bok-Ghee; Jeon, Jae-Pil

    2013-11-15

    Highlights: •We identified network signatures of LCL immortalization from transcriptomic profiles. •More than 41% of DEGs are possibly regulated by miRNAs in LCLs. •MicroRNA target genes in LCLs are involved in apoptosis and immune-related functions. •This approach is useful to find functional miRNA targets in specific cell conditions. -- Abstract: Human lymphoblastoid cell line (LCL) has been used as an in vitro cell model in genetic and pharmacogenomic studies, as well as a good model for studying gene expression regulatory machinery using integrated genomic analyses. In this study, we aimed to identify biological networks of LCL immortalization from transcriptomic profiles of microRNAs and their target genes in LCLs. We first selected differentially expressed genes (DEGs) and microRNAs (DEmiRs) between early passage LCLs (eLCLs) and terminally differentiated late passage LCLs (tLCLs). The in silico and correlation analysis of these DEGs and DEmiRs revealed that 1098 DEG–DEmiR pairs were found to be positively (n = 591 pairs) or negatively (n = 507 pairs) correlated with each other. More than 41% of DEGs are possibly regulated by miRNAs in LCL immortalizations. The target DEGs of DEmiRs were enriched for cellular functions associated with apoptosis, immune response, cell death, JAK–STAT cascade and lymphocyte activation while non-miRNA target DEGs were over-represented for basic cell metabolisms. The target DEGs correlated negatively with miR-548a-3p and miR-219-5p were significantly associated with protein kinase cascade, and the lymphocyte proliferation and apoptosis, respectively. In addition, the miR-106a and miR-424 clusters located in the X chromosome were enriched in DEmiR–mRNA pairs for LCL immortalization. In this study, the integrated transcriptomic analysis of LCLs could identify functional networks of biologically active microRNAs and their target genes involved in LCL immortalization.

  2. When are two multi-layer cellular neural networks the same?

    PubMed

    Ban, Jung-Chao; Chang, Chih-Hung

    2016-07-01

    This paper aims to characterize whether a multi-layer cellular neural network is of deep architecture; namely, when can an n-layer cellular neural network be replaced by an m-layer cellular neural network for mnetwork is revealed. PMID:27085113

  3. Predict drug-protein interaction in cellular networking.

    PubMed

    Xiao, Xuan; Min, Jian-Liang; Wang, Pu; Chou, Kuo-Chen

    2013-01-01

    Involved with many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, GPCRs (G-protein-coupled receptors) are the most frequent targets for drug development: over 50% of all prescription drugs currently on the market are actually acting by targeting GPCRs directly or indirectly. Found in every living thing and nearly all cells, ion channels play crucial roles for many vital functions in life, such as heartbeat, sensory transduction, and central nervous system response. Their dysfunction may have significant impact to human health, and hence ion channels are deemed as "the next GPCRs". To develop GPCR-targeting or ion-channel-targeting drugs, the first important step is to identify the interactions between potential drug compounds with the two kinds of protein receptors in the cellular networking. In this minireview, we are to introduce two predictors. One is called iGPCR-Drug accessible at http://www.jci-bioinfo.cn/iGPCR-Drug/; the other called iCDI-PseFpt at http://www.jci-bioinfo.cn/iCDI-PseFpt. The former is for identifying the interactions of drug compounds with GPCRs; while the latter for that with ion channels. In both predictors, the drug compound was formulated by the two-dimensional molecular fingerprint, and the protein receptor by the pseudo amino acid composition generated with the grey model theory, while the operation engine was the fuzzy K-nearest neighbor algorithm. For the convenience of most experimental pharmaceutical and medical scientists, a step-bystep guide is provided on how to use each of the two web-servers to get the desired results without the need to follow the complicated mathematics involved originally for their establishment. PMID:23889048

  4. Design mobile satellite system architecture as an integral part of the cellular access digital network

    NASA Technical Reports Server (NTRS)

    Chien, E. S. K.; Marinho, J. A.; Russell, J. E., Sr.

    1988-01-01

    The Cellular Access Digital Network (CADN) is the access vehicle through which cellular technology is brought into the mainstream of the evolving integrated telecommunications network. Beyond the integrated end-to-end digital access and per call network services provisioning of the Integrated Services Digital Network (ISDN), the CADN engenders the added capability of mobility freedom via wireless access. One key element of the CADN network architecture is the standard user to network interface that is independent of RF transmission technology. Since the Mobile Satellite System (MSS) is envisioned to not only complement but also enhance the capabilities of the terrestrial cellular telecommunications network, compatibility and interoperability between terrestrial cellular and mobile satellite systems are vitally important to provide an integrated moving telecommunications network of the future. From a network standpoint, there exist very strong commonalities between the terrestrial cellular system and the mobile satellite system. Therefore, the MSS architecture should be designed as an integral part of the CADN. This paper describes the concept of the CADN, the functional architecture of the MSS, and the user-network interface signaling protocols.

  5. Analysis of Blocking Rate and Bandwidth Usage of Mobile IPTV Services in Wireless Cellular Networks

    PubMed Central

    Li, Mingfu

    2014-01-01

    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes. PMID:25379521

  6. Analysis of blocking rate and bandwidth usage of mobile IPTV services in wireless cellular networks.

    PubMed

    Li, Mingfu

    2014-01-01

    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes. PMID:25379521

  7. Traffic Driven Analysis of Cellular and WiFi Networks

    ERIC Educational Resources Information Center

    Paul, Utpal Kumar

    2012-01-01

    Since the days Internet traffic proliferated, measurement, monitoring and analysis of network traffic have been critical to not only the basic understanding of large networks, but also to seek improvements in resource management, traffic engineering and security. At the current times traffic in wireless local and wide area networks are facing…

  8. Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks.

    PubMed

    White, Forest M; Wolf-Yadlin, Alejandro

    2016-06-12

    Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks. PMID:27049636

  9. Methods for the Analysis of Protein Phosphorylation–Mediated Cellular Signaling Networks

    NASA Astrophysics Data System (ADS)

    White, Forest M.; Wolf-Yadlin, Alejandro

    2016-06-01

    Protein phosphorylation–mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

  10. Effects of cellular homeostatic intrinsic plasticity on dynamical and computational properties of biological recurrent neural networks.

    PubMed

    Naudé, Jérémie; Cessac, Bruno; Berry, Hugues; Delord, Bruno

    2013-09-18

    Homeostatic intrinsic plasticity (HIP) is a ubiquitous cellular mechanism regulating neuronal activity, cardinal for the proper functioning of nervous systems. In invertebrates, HIP is critical for orchestrating stereotyped activity patterns. The functional impact of HIP remains more obscure in vertebrate networks, where higher order cognitive processes rely on complex neural dynamics. The hypothesis has emerged that HIP might control the complexity of activity dynamics in recurrent networks, with important computational consequences. However, conflicting results about the causal relationships between cellular HIP, network dynamics, and computational performance have arisen from machine-learning studies. Here, we assess how cellular HIP effects translate into collective dynamics and computational properties in biological recurrent networks. We develop a realistic multiscale model including a generic HIP rule regulating the neuronal threshold with actual molecular signaling pathways kinetics, Dale's principle, sparse connectivity, synaptic balance, and Hebbian synaptic plasticity (SP). Dynamic mean-field analysis and simulations unravel that HIP sets a working point at which inputs are transduced by large derivative ranges of the transfer function. This cellular mechanism ensures increased network dynamics complexity, robust balance with SP at the edge of chaos, and improved input separability. Although critically dependent upon balanced excitatory and inhibitory drives, these effects display striking robustness to changes in network architecture, learning rates, and input features. Thus, the mechanism we unveil might represent a ubiquitous cellular basis for complex dynamics in neural networks. Understanding this robustness is an important challenge to unraveling principles underlying self-organization around criticality in biological recurrent neural networks. PMID:24048833

  11. Cues for cellular assembly of vascular elastin networks

    NASA Astrophysics Data System (ADS)

    Kothapalli, Chandrasekhar R.

    Elastin, a structural protein distributed in the extracellular matrix of vascular tissues is critical to the maintenance of vascular mechanics, besides regulation of cell-signaling pathways involved in injury response and morphogenesis. Thus, congenital absence or disease-mediated degradation of vascular elastin and its malformation within native vessels due to innately poor elastin synthesis by adult vascular cells compromise vascular homeostasis. Current elastin regenerative strategies using tissue engineering principles are limited by the progressive destabilization of tropoelastin mRNA expression in adult vascular cells and the unavailability of scaffolds that can provide cellular cues necessary to up-regulate elastin synthesis and regenerate faithful mimics of native elastin. Since our earlier studies demonstrated the elastogenic utility of hyaluronan (HA)-based cues, we have currently sought to identify a unique set of culture conditions based on HA fragments (0.756-2000 kDa), growth factors (TGF-beta1, IGF-1) and other biomolecules (Cu2+ ions, LOX), which will together enhance synthesis, crosslinking, maturation and fibrous elastin matrix formation by adult SMCs, under both healthy and inflammatory conditions. It was observed that TGF-beta1 (1 ng/mL) together with HA oligomers (0.2 microg/mL) synergistically suppressed SMC proliferation, enhanced tropoelastin (8-fold) and matrix elastin synthesis (5.5-fold), besides improving matrix yield (4.5-fold), possibly by increasing production and activity of lysyl oxidase (LOX). Though addition of IGF-1 alone did not offer any advantage, HA fragments (20-200 kDa) in the presence of IGF-1 stimulated tropoelastin and soluble elastin synthesis more than 2.2-fold, with HMW HA contributing for ˜5-fold increase in crosslinked matrix elastin synthesis. Similarly, 0.1 M of Cu2+ ions, alone or together with HA fragments stimulated synthesis of tropoelastin (4-fold) and crosslinked matrix elastin (4.5-fold), via increases in

  12. Participatory sensing as an enabler for self-organisation in future cellular networks

    NASA Astrophysics Data System (ADS)

    Imran, Muhammad Ali; Imran, Ali; Onireti, Oluwakayode

    2013-12-01

    In this short review paper we summarise the emerging challenges in the field of participatory sensing for the self-organisation of the next generation of wireless cellular networks. We identify the potential of participatory sensing in enabling the self-organisation, deployment optimisation and radio resource management of wireless cellular networks. We also highlight how this approach can meet the future goals for the next generation of cellular system in terms of infrastructure sharing, management of multiple radio access techniques, flexible usage of spectrum and efficient management of very small data cells.

  13. Performance evaluation of power control algorithms in wireless cellular networks

    NASA Astrophysics Data System (ADS)

    Temaneh-Nyah, C.; Iita, V.

    2014-10-01

    Power control in a mobile communication network intents to control the transmission power levels in such a way that the required quality of service (QoS) for the users is guaranteed with lowest possible transmission powers. Most of the studies of power control algorithms in the literature are based on some kind of simplified assumptions which leads to compromise in the validity of the results when applied in a real environment. In this paper, a CDMA network was simulated. The real environment was accounted for by defining the analysis area and the network base stations and mobile stations are defined by their geographical coordinates, the mobility of the mobile stations is accounted for. The simulation also allowed for a number of network parameters including the network traffic, and the wireless channel models to be modified. Finally, we present the simulation results of a convergence speed based comparative analysis of three uplink power control algorithms.

  14. Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

    EPA Science Inventory

    With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate t...

  15. Tools and Models for Integrating Multiple Cellular Networks

    SciTech Connect

    Gerstein, Mark

    2015-11-06

    In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novel algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed

  16. C. elegans Metabolic Gene Regulatory Networks Govern the Cellular Economy

    PubMed Central

    Watson, Emma; Walhout, Albertha J.M.

    2014-01-01

    Diet greatly impacts metabolism in health and disease. In response to the presence or absence of specific nutrients, metabolic gene regulatory networks sense the metabolic state of the cell and regulate metabolic flux accordingly, for instance by the transcriptional control of metabolic enzymes. Here we discuss recent insights regarding metazoan metabolic regulatory networks using the nematode Caenorhabditis elegans as a model, including the modular organization of metabolic gene regulatory networks, the prominent impact of diet on the transcriptome and metabolome, specialized roles of nuclear hormone receptors in responding to dietary conditions, regulation of metabolic genes and metabolic regulators by microRNAs, and feedback between metabolic genes and their regulators. PMID:24731597

  17. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    PubMed

    Hjorth, Johannes J J; Dawitz, Julia; Kroon, Tim; Pires, Johny; Dassen, Valerie J; Berkhout, Janna A; Emperador Melero, Javier; Nadadhur, Aish G; Alevra, Mihai; Toonen, Ruud F; Heine, Vivi M; Mansvelder, Huibert D; Meredith, Rhiannon M

    2016-04-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature "silent" cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity-based pixel correlations to identify cellular-based regions of interest (ROIs) and coincident cell activity. However, using activity-based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell-dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi-automatically detect cells within developing neuronal networks that were imaged using calcium-sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers. PMID:26097169

  18. 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.

  19. Quantifying Uncertainties in Rainfall Maps from Cellular Communication Networks

    NASA Astrophysics Data System (ADS)

    Uijlenhoet, R.; Rios Gaona, M. F.; Overeem, A.; Leijnse, H.

    2014-12-01

    The core idea behind rainfall retrievals from commercial microwave link networks is to measure the decrease in power due to attenuation of the electromagnetic signal by raindrops along the link path. Accurate rainfall measurements are of vital importance in hydrological applications, for instance, flash-flood early-warning systems, agriculture, and climate modeling. Hence, such an alternative technique fulfills the need for measurements with higher resolution in time and space, especially in places where standard rain gauge-networks are scarce or poorly maintained. Rainfall estimation via commercial microwave link networks, at country-wide scales, has recently been demonstrated. Despite their potential applicability in rainfall estimation at higher spatiotemporal resolutions, the uncertainties present in link-based rainfall maps are not yet fully comprehended. Now we attempt to quantify the inherent sources of uncertainty present in interpolated maps computed from commercial microwave link rainfall retrievals. In order to disentangle these sources of uncertainty we identified four main sources of error: 1) microwave link measurements, 2) availability of microwave link measurements, 3) spatial distribution of the network, and 4) interpolation methodology. We computed more than 1000 rainfall fields, for The Netherlands, from real and simulated microwave link data. These rainfall fields were compared to quality-controlled gauge-adjusted radar rainfall maps considered as ground-truth. Thus we were able to quantify the contribution of errors in microwave link measurements to the overall uncertainty. The actual performance of the commercial microwave link network is affected by the intermittent availability of the links, not only in time but also in space. We simulated a fully-operational network in time and space, and thus we quantified the role of the availability of microwave link measurements to the overall uncertainty. This research showed that the largest source of

  20. Resource Management in QoS-Aware Wireless Cellular Networks

    ERIC Educational Resources Information Center

    Zhang, Zhi

    2011-01-01

    Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study…

  1. Application of Cellular Automata to Detection of Malicious Network Packets

    ERIC Educational Resources Information Center

    Brown, Robert L.

    2014-01-01

    A problem in computer security is identification of attack signatures in network packets. An attack signature is a pattern of bits that characterizes a particular attack. Because there are many kinds of attacks, there are potentially many attack signatures. Furthermore, attackers may seek to avoid detection by altering the attack mechanism so that…

  2. Reverse engineering cellular decisions for hybrid reconfigurable network modeling

    NASA Astrophysics Data System (ADS)

    Blair, Howard A.; Saranak, Jureepan; Foster, Kenneth W.

    2011-06-01

    Cells as microorganisms and within multicellular organisms make robust decisions. Knowing how these complex cells make decisions is essential to explain, predict or mimic their behavior. The discovery of multi-layer multiple feedback loops in the signaling pathways of these modular hybrid systems suggests their decision making is sophisticated. Hybrid systems coordinate and integrate signals of various kinds: discrete on/off signals, continuous sensory signals, and stochastic and continuous fluctuations to regulate chemical concentrations. Such signaling networks can form reconfigurable networks of attractors and repellors giving them an extra level of organization that has resilient decision making built in. Work on generic attractor and repellor networks and on the already identified feedback networks and dynamic reconfigurable regulatory topologies in biological cells suggests that biological systems probably exploit such dynamic capabilities. We present a simple behavior of the swimming unicellular alga Chlamydomonas that involves interdependent discrete and continuous signals in feedback loops. We show how to rigorously verify a hybrid dynamical model of a biological system with respect to a declarative description of a cell's behavior. The hybrid dynamical systems we use are based on a unification of discrete structures and continuous topologies developed in prior work on convergence spaces. They involve variables of discrete and continuous types, in the sense of type theory in mathematical logic. A unification such as afforded by convergence spaces is necessary if one wants to take account of the affect of the structural relationships within each type on the dynamics of the system.

  3. Frequency-dependent micromechanics of cellularized biopolymer networks

    NASA Astrophysics Data System (ADS)

    Jones, Chris; Kim, Jihan; McIntyre, David; Sun, Bo

    Mechanical interactions between cells and the extracellular matrix (ECM) influence many cellular behaviors such as growth, differentiation, and migration. These are dynamic processes in which the cells actively remodel the ECM. Reconstituted collagen gel is a common model ECM for studying cell-ECM interactions in vitro because collagen is the most abundant component of mammalian ECM and gives the ECM its material stiffness. We embed micron-sized particles in collagen and use holographic optical tweezers to apply forces to the particles in multiple directions and over a range of frequencies up to 10 Hz. We calculate the local compliance and show that it is dependent on both the direction and frequency of the applied force. Performing the same measurement on many particles allows us to characterize the spatial inhomogeneity of the mechanical properties and shows that the compliance decreases at higher frequencies. Performing these measurements on cell-populated collagen gels shows that cellular remodeling of the ECM changes the mechanical properties of the collagen and we investigate whether this change is dependent on the local strain and distance from nearby cells.

  4. Cellular network entropy as the energy potential in Waddington's differentiation landscape

    NASA Astrophysics Data System (ADS)

    Banerji, Christopher R. S.; Miranda-Saavedra, Diego; Severini, Simone; Widschwendter, Martin; Enver, Tariq; Zhou, Joseph X.; Teschendorff, Andrew E.

    2013-10-01

    Differentiation is a key cellular process in normal tissue development that is significantly altered in cancer. Although molecular signatures characterising pluripotency and multipotency exist, there is, as yet, no single quantitative mark of a cellular sample's position in the global differentiation hierarchy. Here we adopt a systems view and consider the sample's network entropy, a measure of signaling pathway promiscuity, computable from a sample's genome-wide expression profile. We demonstrate that network entropy provides a quantitative, in-silico, readout of the average undifferentiated state of the profiled cells, recapitulating the known hierarchy of pluripotent, multipotent and differentiated cell types. Network entropy further exhibits dynamic changes in time course differentiation data, and in line with a sample's differentiation stage. In disease, network entropy predicts a higher level of cellular plasticity in cancer stem cell populations compared to ordinary cancer cells. Importantly, network entropy also allows identification of key differentiation pathways. Our results are consistent with the view that pluripotency is a statistical property defined at the cellular population level, correlating with intra-sample heterogeneity, and driven by the degree of signaling promiscuity in cells. In summary, network entropy provides a quantitative measure of a cell's undifferentiated state, defining its elevation in Waddington's landscape.

  5. Logical Modeling and Dynamical Analysis of Cellular Networks

    PubMed Central

    Abou-Jaoudé, Wassim; Traynard, Pauline; Monteiro, Pedro T.; Saez-Rodriguez, Julio; Helikar, Tomáš; Thieffry, Denis; Chaouiya, Claudine

    2016-01-01

    The logical (or logic) formalism is increasingly used to model regulatory and signaling networks. Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models. After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle. PMID:27303434

  6. Dynamical modeling and analysis of large cellular regulatory networks

    NASA Astrophysics Data System (ADS)

    Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

    2013-06-01

    The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

  7. Cellular metabolic network analysis: discovering important reactions in Treponema pallidum.

    PubMed

    Chen, Xueying; Zhao, Min; Qu, Hong

    2015-01-01

    T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pallidum, critical reactions are identified. As a comparison, we also apply the analytical approaches to the metabolic network of H. pylori to find coregulated drug targets and unique drug targets for different microorganisms. Based on the clustering results, all reactions are further classified into various roles. Therefore, the general picture of their metabolic network is obtained and two types of reactions, both of which are involved in nucleic acid metabolism, are found to be essential for T. pallidum. It is also discovered that both hubs of reactions and the isolated reactions in purine and pyrimidine metabolisms play important roles in T. pallidum. These reactions could be potential drug targets for treating syphilis. PMID:26495292

  8. Cellular Metabolic Network Analysis: Discovering Important Reactions in Treponema pallidum

    PubMed Central

    Chen, Xueying; Zhao, Min; Qu, Hong

    2015-01-01

    T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pallidum, critical reactions are identified. As a comparison, we also apply the analytical approaches to the metabolic network of H. pylori to find coregulated drug targets and unique drug targets for different microorganisms. Based on the clustering results, all reactions are further classified into various roles. Therefore, the general picture of their metabolic network is obtained and two types of reactions, both of which are involved in nucleic acid metabolism, are found to be essential for T. pallidum. It is also discovered that both hubs of reactions and the isolated reactions in purine and pyrimidine metabolisms play important roles in T. pallidum. These reactions could be potential drug targets for treating syphilis. PMID:26495292

  9. Multiperiod cellular network design via price-influenced simulated annealing (PISA).

    PubMed

    Menon, Syam; Amiri, Ali

    2006-06-01

    Cellular telecommunications systems tend to be more flexible than traditional ones. As a result, traditional approaches to telecommunications network design are often inappropriate for the design of cellular networks, and approaches that explicitly incorporate the increased flexibility into the design process need to be developed. This paper presents one such multiperiod cellular network design problem and solves it via a hybrid heuristic that incorporates ideas from linear programming (LP) and simulated annealing (SA). Extensive computational results comparing the performance of the heuristic with the lower bound obtained from the LP relaxation are presented. These results indicate that this price-influenced simulated annealing (PISA) procedure is extremely efficient, consistently providing solutions with average gaps of 0.30% or less in fewer than 30 s. PMID:16761813

  10. Protease-associated cellular networks in malaria parasite Plasmodium falciparum

    PubMed Central

    2011-01-01

    Background Malaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzymes that play essential roles in parasite growth and invasion. The possibility of designing specific inhibitors for proteases makes them promising drug targets. Previously, combining a comparative genomics approach and a machine learning approach, we identified the complement of proteases (degradome) in the malaria parasite Plasmodium falciparum and its sibling species [1-3], providing a catalog of targets for functional characterization and rational inhibitor design. Network analysis represents another route to revealing the role of proteins in the biology of parasites and we use this approach here to expand our understanding of the systems involving the proteases of P. falciparum. Results We investigated the roles of proteases in the parasite life cycle by constructing a network using protein-protein association data from the STRING database [4], and analyzing these data, in conjunction with the data from protein-protein interaction assays using the yeast 2-hybrid (Y2H) system [5], blood stage microarray experiments [6-8], proteomics [9-12], literature text mining, and sequence homology analysis. Seventy-seven (77) out of 124 predicted proteases were associated with at least one other protein, constituting 2,431 protein-protein interactions (PPIs). These proteases appear to play diverse roles in metabolism, cell cycle regulation, invasion and infection. Their degrees of connectivity (i.e., connections to other proteins), range from one to 143. The largest protease-associated sub-network is the ubiquitin-proteasome system which is crucial for protein recycling and stress response. Proteases are also implicated in heat shock response, signal peptide processing, cell cycle

  11. [Construction and structural analysis of integrated cellular network of Corynebacterium glutamicum].

    PubMed

    Jiang, Jinguo; Song, Lifu; Zheng, Ping; Jia, Shiru; Sun, Jibin

    2012-05-01

    Corynebacterium glutamicum is one of the most important traditional industrial microorganisms and receiving more and more attention towards a novel cellular factory due to the recently rapid development in genomics and genetic operation toolboxes for Corynebacterium. However, compared to other model organisms such as Escherichia coli, there were few studies on its metabolic regulation, especially a genome-scale integrated cellular network model currently missing for Corynebacterium, which hindered the systematic study of Corynebacterium glutamicum and large-scale rational design and optimization for strains. Here, by gathering relevant information from a number of public databases, we successfully constructed an integrated cellular network, which was composed of 1384 reactions, 1276 metabolites, 88 transcriptional factors and 999 pairs of transcriptional regulatory relationships. The transcriptional regulatory sub-network could be arranged into five layers and the metabolic sub-network presented a clear bow-tie structure. We proposed a new method to extract complex metabolic and regulatory sub-network for product-orientated study taking lysine biosynthesis as an example. The metabolic and regulatory sub-network extracted by our method was more close to the real functional network than the simplex biochemical pathways. The results would be greatly helpful for understanding the high-yielding biomechanism for amino acids and the re-design of the industrial strains. PMID:22916496

  12. A malignant cellular network in gliomas: potential clinical implications.

    PubMed

    Osswald, Matthias; Solecki, Gergely; Wick, Wolfgang; Winkler, Frank

    2016-04-01

    The recent discovery of distinct, ultra-long, and highly functional membrane protrusions in gliomas, particularly in astrocytomas, extends our understanding of how these tumors progress in the brain and how they resist therapies. In this article, we will focus on ideas on how to target these membrane protrusions, for which we have suggested the term "tumor microtubes" (TMs), and the malignant multicellular network they form. First, we discuss TM-specific features and their differential biological functions known so far. Second, the connection between 1p/19q codeletion and the inability to form functional TMs via certain neurodevelopmental pathways is presented; this could provide an explanation for the distinct clinical features of oligodendrogliomas. Third, the role of TMs for primary and potentially also adaptive resistance to cytotoxic therapies is highlighted. Fourth, avenues for therapeutic approaches to inhibit TM formation and/or function are discussed, with a focus on disruption (or exploitation) of network functionality. Finally, we propose ideas on how to use TMs as a biomarker in glioma patients. An increasing understanding of TMs in clinical and preclinical settings will show us whether they really are a long-sought-after Achilles' heel of treatment-resistant gliomas. PMID:26995789

  13. Cellular Origins of Type IV Collagen Networks in Developing Glomeruli

    PubMed Central

    Abrahamson, Dale R.; Hudson, Billy G.; Stroganova, Larysa; Borza, Dorin-Bogdan; St. John, Patricia L.

    2009-01-01

    Laminin and type IV collagen composition of the glomerular basement membrane changes during glomerular development and maturation. Although it is known that both glomerular endothelial cells and podocytes produce different laminin isoforms at the appropriate stages of development, the cellular origins for the different type IV collagen heterotrimers that appear during development are unknown. Here, immunoelectron microscopy demonstrated that endothelial cells, mesangial cells, and podocytes of immature glomeruli synthesize collagen α1α2α1(IV). However, intracellular labeling revealed that podocytes, but not endothelial or mesangial cells, contain collagen α3α4α5(IV). To evaluate the origins of collagen IV further, we transplanted embryonic kidneys from Col4a3-null mutants (Alport mice) into kidneys of newborn, wildtype mice. Hybrid glomeruli within grafts containing numerous host-derived, wildtype endothelial cells never expressed collagen α3α4α5(IV). Finally, confocal microscopy of glomeruli from infant Alport mice that had been dually labeled with anti-collagen α5(IV) and the podocyte marker anti-GLEPP1 showed immunolabeling exclusively within podocytes. Together, these results indicate that collagen α3α4α5(IV) originates solely from podocytes; therefore, glomerular Alport disease is a genetic defect that manifests specifically within this cell type. PMID:19423686

  14. Cellular origins of type IV collagen networks in developing glomeruli.

    PubMed

    Abrahamson, Dale R; Hudson, Billy G; Stroganova, Larysa; Borza, Dorin-Bogdan; St John, Patricia L

    2009-07-01

    Laminin and type IV collagen composition of the glomerular basement membrane changes during glomerular development and maturation. Although it is known that both glomerular endothelial cells and podocytes produce different laminin isoforms at the appropriate stages of development, the cellular origins for the different type IV collagen heterotrimers that appear during development are unknown. Here, immunoelectron microscopy demonstrated that endothelial cells, mesangial cells, and podocytes of immature glomeruli synthesize collagen alpha 1 alpha 2 alpha1(IV). However, intracellular labeling revealed that podocytes, but not endothelial or mesangial cells, contain collagen alpha 3 alpha 4 alpha 5(IV). To evaluate the origins of collagen IV further, we transplanted embryonic kidneys from Col4a3-null mutants (Alport mice) into kidneys of newborn, wildtype mice. Hybrid glomeruli within grafts containing numerous host-derived, wildtype endothelial cells never expressed collagen alpha 3 alpha 4 alpha 5(IV). Finally, confocal microscopy of glomeruli from infant Alport mice that had been dually labeled with anti-collagen alpha 5(IV) and the podocyte marker anti-GLEPP1 showed immunolabeling exclusively within podocytes. Together, these results indicate that collagen alpha 3 alpha 4 alpha 5(IV) originates solely from podocytes; therefore, glomerular Alport disease is a genetic defect that manifests specifically within this cell type. PMID:19423686

  15. The role of topological features of intercellular communication networks by the synchronization of cellular oscillators

    NASA Astrophysics Data System (ADS)

    Markovič, R.; Gosak, M.; Marhl, M.

    2012-08-01

    Because of the complexity of processes that govern the regulatory mechanisms which control the cellular functions and dynamic behavior, mathematical models and numerical simulations are needed to fully grasp the mechanisms and functions of biological rhythms. In the last decade the theory of complex networks is frequently applied to address those issues. In the present paper we investigate theoretically the role of the intercellular communication network structure by synchronization of cellular oscillators. Motivated by the fact that in biological systems the interplay between the network structure and the dynamics taking place on it is closely interrelated, we develop a spatial network representation of an ensemble of cells in which we can tune the network organization between a scale-free network with dominating long-range connections and a homogeneous network with mostly adjacent neurons connected. Our results reveal that for noise-induced oscillations in excitable cells and for chaotic bursting oscillations the most synchronized response is obtained for the intermediate regime where long-as well as short-range connections constitute the intercellular network. On the other hand, for periodic oscillations it is found than the scale-free network topology ensures the greatest collective response. We argue that those findings are related to flexibility properties of individual cells.

  16. A Mathematical Model to study the Dynamics of Epithelial Cellular Networks

    PubMed Central

    Abate, Alessandro; Vincent, Stéphane; Dobbe, Roel; Silletti, Alberto; Master, Neal; Axelrod, Jeffrey D.; Tomlin, Claire J.

    2013-01-01

    Epithelia are sheets of connected cells that are essential across the animal kingdom. Experimental observations suggest that the dynamical behavior of many single-layered epithelial tissues has strong analogies with that of specific mechanical systems, namely large networks consisting of point masses connected through spring-damper elements and undergoing the influence of active and dissipating forces. Based on this analogy, this work develops a modeling framework to enable the study of the mechanical properties and of the dynamic behavior of large epithelial cellular networks. The model is built first by creating a network topology that is extracted from the actual cellular geometry as obtained from experiments, then by associating a mechanical structure and dynamics to the network via spring-damper elements. This scalable approach enables running simulations of large network dynamics: the derived modeling framework in particular is predisposed to be tailored to study general dynamics (for example, morphogenesis) of various classes of single-layered epithelial cellular networks. In this contribution we test the model on a case study of the dorsal epithelium of the Drosophila melanogaster embryo during early dorsal closure (and, less conspicuously, germband retraction). PMID:23221083

  17. Identification of driving network of cellular differentiation from single sample time course gene expression data

    NASA Astrophysics Data System (ADS)

    Chen, Ye; Wolanyk, Nathaniel; Ilker, Tunc; Gao, Shouguo; Wang, Xujing

    Methods developed based on bifurcation theory have demonstrated their potential in driving network identification for complex human diseases, including the work by Chen, et al. Recently bifurcation theory has been successfully applied to model cellular differentiation. However, there one often faces a technical challenge in driving network prediction: time course cellular differentiation study often only contains one sample at each time point, while driving network prediction typically require multiple samples at each time point to infer the variation and interaction structures of candidate genes for the driving network. In this study, we investigate several methods to identify both the critical time point and the driving network through examination of how each time point affects the autocorrelation and phase locking. We apply these methods to a high-throughput sequencing (RNA-Seq) dataset of 42 subsets of thymocytes and mature peripheral T cells at multiple time points during their differentiation (GSE48138 from GEO). We compare the predicted driving genes with known transcription regulators of cellular differentiation. We will discuss the advantages and limitations of our proposed methods, as well as potential further improvements of our methods.

  18. The Electrophysiological MEMS Device with Micro Channel Array for Cellular Network Analysis

    NASA Astrophysics Data System (ADS)

    Tonomura, Wataru; Kurashima, Toshiaki; Takayama, Yuzo; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Konishi, Satoshi

    This paper describes a new type of MCA (Micro Channel Array) for simultaneous multipoint measurement of cellular network. Presented MCA employing the measurement principles of the patch-clamp technique is designed for advanced neural network analysis which has been studied by co-authors using 64ch MEA (Micro Electrode Arrays) system. First of all, sucking and clamping of cells through channels of developed MCA is expected to improve electrophysiological signal detections. Electrophysiological sensing electrodes integrated around individual channels of MCA by using MEMS (Micro Electro Mechanical System) technologies are electrically isolated for simultaneous multipoint measurement. In this study, we tested the developed MCA using the non-cultured rat's cerebral cortical slice and the hippocampal neurons. We could measure the spontaneous action potential of the slice simultaneously at multiple points and culture the neurons on developed MCA. Herein, we describe the experimental results together with the design and fabrication of the electrophysiological MEMS device with MCA for cellular network analysis.

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

    NASA Astrophysics Data System (ADS)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    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. Here we give a detailed description of the employed rainfall retrieval algorithm and provide the corresponding code. Moreover, the code (in the scripting language "R") is made available including a data set of commercial microwave links. The purpose of this paper is to promote rainfall monitoring utilizing microwave links from cellular communication networks as an alternative or complementary means for global, continental-scale rainfall monitoring.

  20. A self-learning call admission control scheme for CDMA cellular networks.

    PubMed

    Liu, Derong; Zhang, Yi; Zhang, Huaguang

    2005-09-01

    In the present paper, a call admission control scheme that can learn from the network environment and user behavior is developed for code division multiple access (CDMA) cellular networks that handle both voice and data services. The idea is built upon a novel learning control architecture with only a single module instead of two or three modules in adaptive critic designs (ACDs). The use of adaptive critic approach for call admission control in wireless cellular networks is new. The call admission controller can perform learning in real-time as well as in offline environments and the controller improves its performance as it gains more experience. Another important contribution in the present work is the choice of utility function for the present self-learning control approach which makes the present learning process much more efficient than existing learning control methods. The performance of our algorithm will be shown through computer simulation and compared with existing algorithms. PMID:16252828

  1. 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.

  2. Cellular automata with object-oriented features for parallel molecular network modeling.

    PubMed

    Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

    2005-06-01

    Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented. PMID:16117022

  3. Interference Avoiding Radio Resource Allocation Scheme for Multi-hop OFDMA Cellular Networks with Random Topology

    NASA Astrophysics Data System (ADS)

    Lim, Sunggook; Lee, Jaiyong

    Relaying technology is the one of the solutions to expand the coverage and enhance the throughput of a cellular network with low cost, therefore numerous smart relay stations (RSs) which are able to schedule its own transmission frame and manage radio resources allocated by its serving base station (BS) will be deployed within the cellular network. while more RSs are deployed, the network topology is turning to the random topology. In the random topology, however, conventional frequency reuse schemes based on the uniformly distributed RSs are not adoptable because of the randomness for locations of RSs. Another problem is severe increase of interference during the transmission period for an access link because more transmitters including BSs and RSs are existed within a cell. We suggest the random-topology frequency reuse (RFR) scheme supporting the frequency reuse in the cellular multi-hop network with random topology to reduce intra-cell interference. The simulation results show RFR is reducing the overall intra-cell interference compared to the full allocation scheme whose reuse factor is one. The throughput and average signal to interference plus noise ratio (SINR) is still greater than the full allocation scheme although the spectral efficiency is lower than the compared scheme.

  4. Relating the sequential dynamics of excitatory neural networks to synaptic cellular automata.

    PubMed

    Nekorkin, V I; Dmitrichev, A S; Kasatkin, D V; Afraimovich, V S

    2011-12-01

    We have developed a new approach for the description of sequential dynamics of excitatory neural networks. Our approach is based on the dynamics of synapses possessing the short-term plasticity property. We suggest a model of such synapses in the form of a second-order system of nonlinear ODEs. In the framework of the model two types of responses are realized-the fast and the slow ones. Under some relations between their timescales a cellular automaton (CA) on the graph of connections is constructed. Such a CA has only a finite number of attractors and all of them are periodic orbits. The attractors of the CA determine the regimes of sequential dynamics of the original neural network, i.e., itineraries along the network and the times of successive firing of neurons in the form of bunches of spikes. We illustrate our approach on the example of a Morris-Lecar neural network. PMID:22225361

  5. Two programmed replicative lifespans of Saccharomyces cerevisiae formed by the endogenous molecular-cellular network.

    PubMed

    Hu, Jie; Zhu, Xiaomei; Wang, Xinan; Yuan, Ruoshi; Zheng, Wei; Xu, Minjuan; Ao, Ping

    2014-12-01

    Cellular replicative capacity is a therapeutic target for regenerative medicine as well as cancer treatment. The mechanism of replicative senescence and cell immortality is still unclear. We investigated the diauxic growth of Saccharomyces cerevisiae and demonstrate that the replicative capacity revealed by the yeast growth curve can be understood by using the dynamical property of the molecular-cellular network regulating S. cerevisiae. The endogenous network we proposed has a limit cycle when pheromone signaling is disabled, consistent with the exponential growth phase with an infinite replicative capacity. In the post-diauxic phase, the cooperative effect of the pheromone activated mitogen-activated protein kinase (MAPK) signaling pathway with the cell cycle leads to a fixed point attractor instead of the limit cycle. The cells stop dividing after several generations counting from the beginning of the post-diauxic growth. By tuning the MAPK pathway, S. cerevisiae therefore programs the number of offsprings it replicates. PMID:24447585

  6. A new cellular nonlinear network emulation on FPGA for EEG signal processing in epilepsy

    NASA Astrophysics Data System (ADS)

    Müller, Jens; Müller, Jan; Tetzlaff, Ronald

    2011-05-01

    For processing of EEG signals, we propose a new architecture for the hardware emulation of discrete-time Cellular Nonlinear Networks (DT-CNN). Our results show the importance of a high computational accuracy in EEG signal prediction that cannot be achieved with existing analogue VLSI circuits. The refined architecture of the processing elements and its resource schedule, the cellular network structure with local couplings, the FPGA-based embedded system containing the DT-CNN, and the data flow in the entire system will be discussed in detail. The proposed DT-CNN design has been implemented and tested on an Xilinx FPGA development platform. The embedded co-processor with a multi-threading kernel is utilised for control and pre-processing tasks and data exchange to the host via Ethernet. The performance of the implemented DT-CNN has been determined for a popular example and compared to that of a conventional computer.

  7. Application of GA in optimization of pore network models generated by multi-cellular growth algorithms

    NASA Astrophysics Data System (ADS)

    Jamshidi, Saeid; Boozarjomehry, Ramin Bozorgmehry; Pishvaie, Mahmoud Reza

    2009-10-01

    In pore network modeling, the void space of a rock sample is represented at the microscopic scale by a network of pores connected by throats. Construction of a reasonable representation of the geometry and topology of the pore space will lead to a reliable prediction of the properties of porous media. Recently, the theory of multi-cellular growth (or L-systems) has been used as a flexible tool for generation of pore network models which do not require any special information such as 2D SEM or 3D pore space images. In general, the networks generated by this method are irregular pore network models which are inherently closer to the complicated nature of the porous media rather than regular lattice networks. In this approach, the construction process is controlled only by the production rules that govern the development process of the network. In this study, genetic algorithm has been used to obtain the optimum values of the uncertain parameters of these production rules to build an appropriate irregular lattice network capable of the prediction of both static and hydraulic information of the target porous medium.

  8. Application of neural networks to channel assignment for cellular CDMA networks with multiple services and mobile base stations

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    1996-03-01

    The use of artificial neural networks to the channel assignment problem for cellular code- division multiple access (CDMA) telecommunications systems is considered. CDMA takes advantage of voice activity and spatial isolation because its capacity is only interference limited, unlike time-division multiple access (TDMA) and frequency-division multiple access (FDMA) where capacities are bandwidth limited. Any reduction in interference in CDMA translates linearly into increased capacity. FDMA and TDMA use a frequency reuse pattern as a method to increase capacity, while CDMA reuses the same frequency for all cells and gains a reuse efficiency by means of orthogonal codes. The latter method can improve system capacity by factors of four to six over digital TDMA or FDMA. Cellular carriers are planning to provide multiple communication services using CDMA in the next generation cellular system infrastructure. The approach of this study is the use of neural network methods for automatic and local network control, based on traffic behavior in specific cell cites and demand history. The goal is to address certain problems associated with the management of mobile and personal communication services in a cellular radio communications environment. In planning a cellular radio network, the operator assigns channels to the radio cells so that the probability of the processed carrier-to-interference ratio, CII, exceeding a predefined value is sufficiently low. The RF propagation, determined from the topography and infrastructure in the operating area, is used in conjunction with the densities of expected communications traffic to formulate interference constraints. These constraints state which radio cells may use the same code (channel) or adjacent channels at a time. The traffic loading and the number of service grades can also be used to calculate the number of required channels (codes) for each cell. The general assignment problem is the task of assigning the required number

  9. Cellular Neural Network Models of Growth and Immune of Effector Cells Response to Cancer

    NASA Astrophysics Data System (ADS)

    Su, Yongmei; Min, Lequan

    Four reaction-diffusion cellular neural network (R-D CNN) models are set up based on the differential equation models for the growths of effector cells and cancer cells, and the model of the immune response to cancer proposed by Allison et al. The CNN models have different reaction-diffusion coefficients and coupling parameters. The R-D CNN models may provide possible quantitative interpretations, and are good in agreement with the in vitro experiment data reported by Allison et al.

  10. Measuring information flow in cellular networks by the systems biology method through microarray data

    PubMed Central

    Chen, Bor-Sen; Li, Cheng-Wei

    2015-01-01

    In general, it is very difficult to measure the information flow in a cellular network directly. In this study, based on an information flow model and microarray data, we measured the information flow in cellular networks indirectly by using a systems biology method. First, we used a recursive least square parameter estimation algorithm to identify the system parameters of coupling signal transduction pathways and the cellular gene regulatory network (GRN). Then, based on the identified parameters and systems theory, we estimated the signal transductivities of the coupling signal transduction pathways from the extracellular signals to each downstream protein and the information transductivities of the GRN between transcription factors in response to environmental events. According to the proposed method, the information flow, which is characterized by signal transductivity in coupling signaling pathways and information transductivity in the GRN, can be estimated by microarray temporal data or microarray sample data. It can also be estimated by other high-throughput data such as next-generation sequencing or proteomic data. Finally, the information flows of the signal transduction pathways and the GRN in leukemia cancer cells and non-leukemia normal cells were also measured to analyze the systematic dysfunction in this cancer from microarray sample data. The results show that the signal transductivities of signal transduction pathways change substantially from normal cells to leukemia cancer cells. PMID:26082788

  11. A New Cellular Architecture for Information Retrieval from Sensor Networks through Embedded Service and Security Protocols

    PubMed Central

    Shahzad, Aamir; Landry, René; Lee, Malrey; Xiong, Naixue; Lee, Jongho; Lee, Changhoon

    2016-01-01

    Substantial changes have occurred in the Information Technology (IT) sectors and with these changes, the demand for remote access to field sensor information has increased. This allows visualization, monitoring, and control through various electronic devices, such as laptops, tablets, i-Pads, PCs, and cellular phones. The smart phone is considered as a more reliable, faster and efficient device to access and monitor industrial systems and their corresponding information interfaces anywhere and anytime. This study describes the deployment of a protocol whereby industrial system information can be securely accessed by cellular phones via a Supervisory Control And Data Acquisition (SCADA) server. To achieve the study goals, proprietary protocol interconnectivity with non-proprietary protocols and the usage of interconnectivity services are considered in detail. They support the visualization of the SCADA system information, and the related operations through smart phones. The intelligent sensors are configured and designated to process real information via cellular phones by employing information exchange services between the proprietary protocol and non-proprietary protocols. SCADA cellular access raises the issue of security flaws. For these challenges, a cryptography-based security method is considered and deployed, and it could be considered as a part of a proprietary protocol. Subsequently, transmission flows from the smart phones through a cellular network. PMID:27314351

  12. A New Cellular Architecture for Information Retrieval from Sensor Networks through Embedded Service and Security Protocols.

    PubMed

    Shahzad, Aamir; Landry, René; Lee, Malrey; Xiong, Naixue; Lee, Jongho; Lee, Changhoon

    2016-01-01

    Substantial changes have occurred in the Information Technology (IT) sectors and with these changes, the demand for remote access to field sensor information has increased. This allows visualization, monitoring, and control through various electronic devices, such as laptops, tablets, i-Pads, PCs, and cellular phones. The smart phone is considered as a more reliable, faster and efficient device to access and monitor industrial systems and their corresponding information interfaces anywhere and anytime. This study describes the deployment of a protocol whereby industrial system information can be securely accessed by cellular phones via a Supervisory Control And Data Acquisition (SCADA) server. To achieve the study goals, proprietary protocol interconnectivity with non-proprietary protocols and the usage of interconnectivity services are considered in detail. They support the visualization of the SCADA system information, and the related operations through smart phones. The intelligent sensors are configured and designated to process real information via cellular phones by employing information exchange services between the proprietary protocol and non-proprietary protocols. SCADA cellular access raises the issue of security flaws. For these challenges, a cryptography-based security method is considered and deployed, and it could be considered as a part of a proprietary protocol. Subsequently, transmission flows from the smart phones through a cellular network. PMID:27314351

  13. An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities.

    PubMed

    Matsubara, Takashi; Torikai, Hiroyuki

    2016-04-01

    Modeling and implementation approaches for the reproduction of input-output relationships in biological nervous tissues contribute to the development of engineering and clinical applications. However, because of high nonlinearity, the traditional modeling and implementation approaches encounter difficulties in terms of generalization ability (i.e., performance when reproducing an unknown data set) and computational resources (i.e., computation time and circuit elements). To overcome these difficulties, asynchronous cellular automaton-based neuron (ACAN) models, which are described as special kinds of cellular automata that can be implemented as small asynchronous sequential logic circuits have been proposed. This paper presents a novel type of such ACAN and a theoretical analysis of its excitability. This paper also presents a novel network of such neurons, which can mimic input-output relationships of biological and nonlinear ordinary differential equation model neural networks. Numerical analyses confirm that the presented network has a higher generalization ability than other major modeling and implementation approaches. In addition, Field-Programmable Gate Array-implementations confirm that the presented network requires lower computational resources. PMID:25974951

  14. Phase transitions in pancreatic islet cellular networks and implications for type-1 diabetes

    NASA Astrophysics Data System (ADS)

    Stamper, I. J.; Jackson, Elais; Wang, Xujing

    2014-01-01

    In many aspects the onset of a chronic disease resembles a phase transition in a complex dynamic system: Quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. In this study we examine a special case, the onset of type-1 diabetes (T1D), a disease that results from loss of the insulin-producing pancreatic islet β cells. Within each islet, the β cells are electrically coupled to each other via gap-junctional channels. This intercellular coupling enables the β cells to synchronize their insulin release, thereby generating the multiscale temporal rhythms in blood insulin that are critical to maintaining blood glucose homeostasis. Using percolation theory we show how normal islet function is intrinsically linked to network connectivity. In particular, the critical amount of β-cell death at which the islet cellular network loses site percolation is consistent with laboratory and clinical observations of the threshold loss of β cells that causes islet functional failure. In addition, numerical simulations confirm that the islet cellular network needs to be percolated for β cells to synchronize. Furthermore, the interplay between site percolation and bond strength predicts the existence of a transient phase of islet functional recovery after onset of T1D and introduction of treatment, potentially explaining the honeymoon phenomenon. Based on these results, we hypothesize that the onset of T1D may be the result of a phase transition of the islet β-cell network.

  15. Motion adaptive vertical handoff in cellular/WLAN heterogeneous wireless network.

    PubMed

    Li, Limin; Ma, Lin; Xu, Yubin; Fu, Yunhai

    2014-01-01

    In heterogeneous wireless network, vertical handoff plays an important role for guaranteeing quality of service and overall performance of network. Conventional vertical handoff trigger schemes are mostly developed from horizontal handoff in homogeneous cellular network. Basically, they can be summarized as hysteresis-based and dwelling-timer-based algorithms, which are reliable on avoiding unnecessary handoff caused by the terminals dwelling at the edge of WLAN coverage. However, the coverage of WLAN is much smaller compared with cellular network, while the motion types of terminals can be various in a typical outdoor scenario. As a result, traditional algorithms are less effective in avoiding unnecessary handoff triggered by vehicle-borne terminals with various speeds. Besides that, hysteresis and dwelling-timer thresholds usually need to be modified to satisfy different channel environments. For solving this problem, a vertical handoff algorithm based on Q-learning is proposed in this paper. Q-learning can provide the decider with self-adaptive ability for handling the terminals' handoff requests with different motion types and channel conditions. Meanwhile, Neural Fuzzy Inference System (NFIS) is embedded to retain a continuous perception of the state space. Simulation results verify that the proposed algorithm can achieve lower unnecessary handoff probability compared with the other two conventional algorithms. PMID:24741347

  16. Motion Adaptive Vertical Handoff in Cellular/WLAN Heterogeneous Wireless Network

    PubMed Central

    Ma, Lin; Xu, Yubin; Fu, Yunhai

    2014-01-01

    In heterogeneous wireless network, vertical handoff plays an important role for guaranteeing quality of service and overall performance of network. Conventional vertical handoff trigger schemes are mostly developed from horizontal handoff in homogeneous cellular network. Basically, they can be summarized as hysteresis-based and dwelling-timer-based algorithms, which are reliable on avoiding unnecessary handoff caused by the terminals dwelling at the edge of WLAN coverage. However, the coverage of WLAN is much smaller compared with cellular network, while the motion types of terminals can be various in a typical outdoor scenario. As a result, traditional algorithms are less effective in avoiding unnecessary handoff triggered by vehicle-borne terminals with various speeds. Besides that, hysteresis and dwelling-timer thresholds usually need to be modified to satisfy different channel environments. For solving this problem, a vertical handoff algorithm based on Q-learning is proposed in this paper. Q-learning can provide the decider with self-adaptive ability for handling the terminals' handoff requests with different motion types and channel conditions. Meanwhile, Neural Fuzzy Inference System (NFIS) is embedded to retain a continuous perception of the state space. Simulation results verify that the proposed algorithm can achieve lower unnecessary handoff probability compared with the other two conventional algorithms. PMID:24741347

  17. A computable cellular stress network model for non-diseased pulmonary and cardiovascular tissue

    PubMed Central

    2011-01-01

    Background Humans and other organisms are equipped with a set of responses that can prevent damage from exposure to a multitude of endogenous and environmental stressors. If these stress responses are overwhelmed, this can result in pathogenesis of diseases, which is reflected by an increased development of, e.g., pulmonary and cardiac diseases in humans exposed to chronic levels of environmental stress, including inhaled cigarette smoke (CS). Systems biology data sets (e.g., transcriptomics, phosphoproteomics, metabolomics) could enable comprehensive investigation of the biological impact of these stressors. However, detailed mechanistic networks are needed to determine which specific pathways are activated in response to different stressors and to drive the qualitative and eventually quantitative assessment of these data. A current limiting step in this process is the availability of detailed mechanistic networks that can be used as an analytical substrate. Results We have built a detailed network model that captures the biology underlying the physiological cellular response to endogenous and exogenous stressors in non-diseased mammalian pulmonary and cardiovascular cells. The contents of the network model reflect several diverse areas of signaling, including oxidative stress, hypoxia, shear stress, endoplasmic reticulum stress, and xenobiotic stress, that are elicited in response to common pulmonary and cardiovascular stressors. We then tested the ability of the network model to identify the mechanisms that are activated in response to CS, a broad inducer of cellular stress. Using transcriptomic data from the lungs of mice exposed to CS, the network model identified a robust increase in the oxidative stress response, largely mediated by the anti-oxidant NRF2 pathways, consistent with previous reports on the impact of CS exposure in the mammalian lung. Conclusions The results presented here describe the construction of a cellular stress network model and its

  18. Increasing the coverage area through relay node deployment in long term evolution advanced cellular networks

    NASA Astrophysics Data System (ADS)

    Aldhaibani, Jaafar A.; Ahmad, R. B.; Yahya, A.; Azeez, Suzan A.

    2015-05-01

    Wireless multi-hop relay networks have become very important technologies in mobile communications. These networks ensure high throughput and coverage extension with a low cost. The poor capacity at cell edges is not enough to meet with growing demand of high capacity and throughput irrespective of user's placement in the cellular network. In this paper we propose optimal placement of relay node that provides maximum achievable rate at users and enhances the throughput and coverage at cell edge region. The proposed scheme is based on the outage probability at users and taken on account the interference between nodes. Numerical analyses along with simulation results indicated there are an improvement in capacity for users at the cell edge is 40% increment from all cell capacity.

  19. Optimal design of sewer networks using cellular automata-based hybrid methods: Discrete and continuous approaches

    NASA Astrophysics Data System (ADS)

    Afshar, M. H.; Rohani, M.

    2012-01-01

    In this article, cellular automata based hybrid methods are proposed for the optimal design of sewer networks and their performance is compared with some of the common heuristic search methods. The problem of optimal design of sewer networks is first decomposed into two sub-optimization problems which are solved iteratively in a two stage manner. In the first stage, the pipe diameters of the network are assumed fixed and the nodal cover depths of the network are determined by solving a nonlinear sub-optimization problem. A cellular automata (CA) method is used for the solution of the optimization problem with the network nodes considered as the cells and their cover depths as the cell states. In the second stage, the nodal cover depths calculated from the first stage are fixed and the pipe diameters are calculated by solving a second nonlinear sub-optimization problem. Once again a CA method is used to solve the optimization problem of the second stage with the pipes considered as the CA cells and their corresponding diameters as the cell states. Two different updating rules are derived and used for the CA of the second stage depending on the treatment of the pipe diameters. In the continuous approach, the pipe diameters are considered as continuous variables and the corresponding updating rule is derived mathematically from the original objective function of the problem. In the discrete approach, however, an adhoc updating rule is derived and used taking into account the discrete nature of the pipe diameters. The proposed methods are used to optimally solve two sewer network problems and the results are presented and compared with those obtained by other methods. The results show that the proposed CA based hybrid methods are more efficient and effective than the most powerful search methods considered in this work.

  20. Cellular neural network-based hybrid approach toward automatic image registration

    NASA Astrophysics Data System (ADS)

    Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

    2013-01-01

    Image registration is a key component of various image processing operations that involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however, inability to properly model object shape as well as contextual information has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, adaptive resampling, and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

  1. A multimedia session-aware QoS provisioning scheme for cellular networks

    NASA Astrophysics Data System (ADS)

    Rizvi, Mona E.; Olariu, Stephan

    2005-03-01

    Multimedia applications often involve a set of cooperating streams that together form a multimedia session. We propose a novel local QoS provisioning scheme for cellular networks that is aware of the relationships between the streams that compose a session. As a rule, existing schemes either allow composite streams to compete with one another for resources or else provide QoS to the session as an atomic entity, leaving to the application the task of managing QoS for the individual streams. Our new MUltimedia SessIon-aware Cellular (MUSIC) QoS provisioning scheme manages the QoS of the individual streams in a session, and with the knowledge of their relationships, it prevents competition between the streams. Further, by allowing an application-specified prioritization between streams in a session, MUSIC scheme features a significant improvement in performance over session-unaware schemes.

  2. Segmentation algorithm via Cellular Neural/Nonlinear Network: implementation on Bio-inspired hardware platform

    NASA Astrophysics Data System (ADS)

    Karabiber, Fethullah; Vecchio, Pietro; Grassi, Giuseppe

    2011-12-01

    The Bio-inspired (Bi-i) Cellular Vision System is a computing platform consisting of sensing, array sensing-processing, and digital signal processing. The platform is based on the Cellular Neural/Nonlinear Network (CNN) paradigm. This article presents the implementation of a novel CNN-based segmentation algorithm onto the Bi-i system. Each part of the algorithm, along with the corresponding implementation on the hardware platform, is carefully described through the article. The experimental results, carried out for Foreman and Car-phone video sequences, highlight the feasibility of the approach, which provides a frame rate of about 26 frames/s. Comparisons with existing CNN-based methods show that the conceived approach is more accurate, thus representing a good trade-off between real-time requirements and accuracy.

  3. 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.

  4. Cellular network formation of hydrophobic alkanethiol capped gold nanoparticles on mica surface mediated by water islands.

    PubMed

    John, Neena S; Raina, Gargi; Sharma, Ashutosh; Kulkarni, Giridhar U

    2010-09-01

    Dendritic and cellular networks of nanoparticles are known to form commonly either by random diffusion-limited aggregation or by solvent evaporation dynamics. Using alkanethiol capped gold nanoparticles deposited on mica imaged under ambient and controlled water vapor conditions by atomic force microscope and in situ scanning electron microscope, respectively, we show a third mechanism in action. The cellular network consisting of open and closed polygons is formed by the nucleation and lateral growth of adsorbed water islands, the contact lines of which push the randomly distributed hydrophobic nanoparticles along the growth directions, eventually leading to the polygonal structure formation as the boundaries of the growing islands meet. Such nanoparticle displacement has been possible due to the weakly adhering nature of the hydrophilic substrate, mica. These results demonstrate an important but hitherto neglected effect of adsorbed water in the structure formation on hydrophilic substrates and provide a facile tool for the fabrication of nanoparticle networks without specific particle or substrate modifications and without a tight control on particle deposition conditions during the solvent evaporation. PMID:20831330

  5. Alzheimer's as a Systems-Level Disease Involving the Interplay of Multiple Cellular Networks.

    PubMed

    Castrillo, Juan I; Oliver, Stephen G

    2016-01-01

    Alzheimer's disease (AD), and many neurodegenerative disorders, are multifactorial in nature. They involve a combination of genomic, epigenomic, interactomic and environmental factors. Progress is being made, and these complex diseases are beginning to be understood as having their origin in altered states of biological networks at the cellular level. In the case of AD, genomic susceptibility and mechanisms leading to (or accompanying) the impairment of the central Amyloid Precursor Protein (APP) processing and tau networks are widely accepted as major contributors to the diseased state. The derangement of these networks may result in both the gain and loss of functions, increased generation of toxic species (e.g., toxic soluble oligomers and aggregates) and imbalances, whose effects can propagate to supra-cellular levels. Although well sustained by empirical data and widely accepted, this global perspective often overlooks the essential roles played by the main counteracting homeostatic networks (e.g., protein quality control/proteostasis, unfolded protein response, protein folding chaperone networks, disaggregases, ER-associated degradation/ubiquitin proteasome system, endolysosomal network, autophagy, and other stress-protective and clearance networks), whose relevance to AD is just beginning to be fully realized. In this chapter, an integrative perspective is presented. Alzheimer's disease is characterized to be a result of: (a) intrinsic genomic/epigenomic susceptibility and, (b) a continued dynamic interplay between the deranged networks and the central homeostatic networks of nerve cells. This interplay of networks will underlie both the onset and rate of progression of the disease in each individual. Integrative Systems Biology approaches are required to effect its elucidation. Comprehensive Systems Biology experiments at different 'omics levels in simple model organisms, engineered to recapitulate the basic features of AD may illuminate the onset and

  6. Robust tracking by cellular automata and neural networks with nonlocal weights

    NASA Astrophysics Data System (ADS)

    Ososkov, Gennadii A.

    1995-04-01

    A modified rotor model of the Hopfield neural networks (HNN) is proposed for finding tracks in multiwire proportional chambers. That requires us to apply both raw data prefiltering by cellular automaton and HNN weights furnishing by a special robust multiplier. Then this model is developed to be applicable for a more general type of data and detectors. As an example, data processing of ionospheric measurements are considered. For handling tracks detected by high pressure drift chambers with their up-down ambiguity a modification of deformable templates method is proposed. A new concept of controlled HNN is proposed for solving the so-called track-match problem.

  7. Existence and stability of traveling wave solutions for multilayer cellular neural networks

    NASA Astrophysics Data System (ADS)

    Hsu, Cheng-Hsiung; Lin, Jian-Jhong; Yang, Tzi-Sheng

    2015-08-01

    The purpose of this article is to investigate the existence and stability of traveling wave solutions for one-dimensional multilayer cellular neural networks. We first establish the existence of traveling wave solutions using the truncated technique. Then we study the asymptotic behaviors of solutions for the Cauchy problem of the neural model. Applying two kinds of comparison principles and the weighed energy method, we show that all solutions of the Cauchy problem converge exponentially to the traveling wave solutions provided that the initial data belong to a suitable weighted space.

  8. A new design for reconfigurable XOR function based on cellular neural networks

    NASA Astrophysics Data System (ADS)

    Liu, Yanyi; Liu, Wenbo

    2014-10-01

    We have described a new method to construct the reconfigurable XOR logic circuit by using the modification of the standard uncoupled cellular neural network (CNN) cells. The modification of the cell is easier to implement in engineering applications. The scheme proposed in this paper, using the modification of standard uncoupled CNN cells, allows less hardware consumption in comparison to the utilisation of chaos computing system or harnessing piecewise-linear systems. The template parameters of the modified cell have been discussed, and the physical circuit implementing the reconfigurable two-input and three-input XOR function has also been presented.

  9. Anisotropic optical flow algorithm based on self-adaptive cellular neural network

    NASA Astrophysics Data System (ADS)

    Zhang, Congxuan; Chen, Zhen; Li, Ming; Sun, Kaiqiong

    2013-01-01

    An anisotropic optical flow estimation method based on self-adaptive cellular neural networks (CNN) is proposed. First, a novel optical flow energy function which contains a robust data term and an anisotropic smoothing term is projected. Next, the CNN model which has the self-adaptive feedback operator and threshold is presented according to the Euler-Lagrange partial differential equations of the proposed optical flow energy function. Finally, the elaborate evaluation experiments indicate the significant effects of the various proposed strategies for optical flow estimation, and the comparison results with the other methods show that the proposed algorithm has better performance in computing accuracy and efficiency.

  10. Functional recognition imaging using artificial neural networks: applications to rapid cellular identification via broadband electromechanical response

    NASA Astrophysics Data System (ADS)

    Nikiforov, M. P.; Reukov, V. V.; Thompson, G. L.; Vertegel, A. A.; Guo, S.; Kalinin, S. V.; Jesse, S.

    2009-10-01

    Functional recognition imaging in scanning probe microscopy (SPM) using artificial neural network identification is demonstrated. This approach utilizes statistical analysis of complex SPM responses at a single spatial location to identify the target behavior, which is reminiscent of associative thinking in the human brain, obviating the need for analytical models. We demonstrate, as an example of recognition imaging, rapid identification of cellular organisms using the difference in electromechanical activity over a broad frequency range. Single-pixel identification of model Micrococcus lysodeikticus and Pseudomonas fluorescens bacteria is achieved, demonstrating the viability of the method.

  11. Evolving Transport Networks With Cellular Automata Models Inspired by Slime Mould.

    PubMed

    Tsompanas, Michail-Antisthenis I; Sirakoulis, Georgios Ch; Adamatzky, Andrew I

    2015-09-01

    Man-made transport networks and their design are closely related to the shortest path problem and considered amongst the most debated problems of computational intelligence. Apart from using conventional or bio-inspired computer algorithms, many researchers tried to solve this kind of problem using biological computing substrates, gas-discharge solvers, prototypes of a mobile droplet, and hot ice computers. In this aspect, another example of biological computer is the plasmodium of acellular slime mould Physarum polycephalum (P. polycephalum), which is a large single cell visible by an unaided eye and has been proven as a reliable living substrate for implementing biological computing devices for computational geometry, graph-theoretical problems, and optimization and imitation of transport networks. Although P. polycephalum is easy to experiment with, computing devices built with the living slime mould are extremely slow; it takes slime mould days to execute a computation. Consequently, mapping key computing mechanisms of the slime mould onto silicon would allow us to produce efficient bio-inspired computing devices to tackle with hard to solve computational intelligence problems like the aforementioned. Toward this direction, a cellular automaton (CA)-based, Physarum-inspired, network designing model is proposed. This novel CA-based model is inspired by the propagating strategy, the formation of tubular networks, and the computing abilities of the plasmodium of P. polycephalum. The results delivered by the CA model demonstrate a good match with several previously published results of experimental laboratory studies on imitation of man-made transport networks with P. polycephalum. Consequently, the proposed CA model can be used as a virtual, easy-to-access, and biomimicking laboratory emulator that will economize large time periods needed for biological experiments while producing networks almost identical to the tubular networks of the real-slime mould. PMID

  12. Multilayer cellular neural network and fuzzy C-mean classifiers: comparison and performance analysis

    NASA Astrophysics Data System (ADS)

    Trujillo San-Martin, Maite; Hlebarov, Vejen; Sadki, Mustapha

    2004-11-01

    Neural Networks and Fuzzy systems are considered two of the most important artificial intelligent algorithms which provide classification capabilities obtained through different learning schemas which capture knowledge and process it according to particular rule-based algorithms. These methods are especially suited to exploit the tolerance for uncertainty and vagueness in cognitive reasoning. By applying these methods with some relevant knowledge-based rules extracted using different data analysis tools, it is possible to obtain a robust classification performance for a wide range of applications. This paper will focus on non-destructive testing quality control systems, in particular, the study of metallic structures classification according to the corrosion time using a novel cellular neural network architecture, which will be explained in detail. Additionally, we will compare these results with the ones obtained using the Fuzzy C-means clustering algorithm and analyse both classifiers according to its classification capabilities.

  13. Evaluating a Novel Cellular Automata-Based Distributed Power Management Approach for Mobile Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Adabi, Sepideh; Adabi, Sahar; Rezaee, Ali

    According to the traditional definition of Wireless Sensor Networks (WSNs), static sensors have limited the feasibility of WSNs in some kind of approaches, so the mobility was introduced in WSN. Mobile nodes in a WSN come equipped with battery and from the point of deployment, this battery reserve becomes a valuable resource since it cannot be replenished. Hence, maximizing the network lifetime by minimizing the energy is an important challenge in Mobile WSN. Energy conservation can be accomplished by different approaches. In this paper, we presented an energy conservation solution based on Cellular Automata. The main objective of this solution is based on dynamically adjusting the transmission range and switching between operational states of the sensor nodes.

  14. Cellular telephone-based radiation sensor and wide-area detection network

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2006-12-12

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  15. Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification

    PubMed Central

    2016-01-01

    For many complex diseases, an earlier and more reliable diagnosis is considered a key prerequisite for developing more effective therapies to prevent or delay disease progression. Classical statistical learning approaches for specimen classification using omics data, however, often cannot provide diagnostic models with sufficient accuracy and robustness for heterogeneous diseases like cancers or neurodegenerative disorders. In recent years, new approaches for building multivariate biomarker models on omics data have been proposed, which exploit prior biological knowledge from molecular networks and cellular pathways to address these limitations. This survey provides an overview of these recent developments and compares pathway- and network-based specimen classification approaches in terms of their utility for improving model robustness, accuracy and biological interpretability. Different routes to translate omics-based multifactorial biomarker models into clinical diagnostic tests are discussed, and a previous study is presented as example. PMID:26141830

  16. Effect of crystals and fibrous network polymer additives on cellular morphology of microcellular foams

    NASA Astrophysics Data System (ADS)

    Miyamoto, Ryoma; Utano, Tatsumi; Yasuhara, Shunya; Ishihara, Shota; Ohshima, Masahiro

    2015-05-01

    In this study, the core-back foam injection molding was used for preparing microcelluar polypropylene (PP) foam with either a 1,3:2,4 bis-O-(4-methylbenzylidene)-D-sorbitol gelling agent (Gel-all MD) or a fibros network polymer additive (Metablen 3000). Both agent and addiive could effectively control the celluar morphology in foams but somehow different ways. In course of cooling the polymer with Gel-all MD in the mold caity, the agent enhanced the crystal nucleation and resulted in the large number of small crystals. The crystals acted as effective bubble nucleation agent in foaming process. Thus, the agent reduced the cell size and increased the cell density, drastically. Furthermore, the small crystals provided an inhomogenuity to the expanding cell wall and produced the high open cell content with nano-scale fibril structure. Gell-all as well as Metablene 3000 formed a gel-like fibrous network in melt. The network increased the elongational viscosity and tended to prevent the cell wall from breaking up. The foaming temperature window was widened by the presence of the network. Especially, the temperature window where the macro-fibrous structure was formed was expanded to the higher temperature. The effects of crystal nucleating agent and PTFE on crystals' size and number, viscoelsticity, rheological propreties of PP and cellular morphology were compared and thorougly investigated.

  17. ComPPI: a cellular compartment-specific database for protein–protein interaction network analysis

    PubMed Central

    Veres, Daniel V.; Gyurkó, Dávid M.; Thaler, Benedek; Szalay, Kristóf Z.; Fazekas, Dávid; Korcsmáros, Tamás; Csermely, Peter

    2015-01-01

    Here we present ComPPI, a cellular compartment-specific database of proteins and their interactions enabling an extensive, compartmentalized protein–protein interaction network analysis (URL: http://ComPPI.LinkGroup.hu). ComPPI enables the user to filter biologically unlikely interactions, where the two interacting proteins have no common subcellular localizations and to predict novel properties, such as compartment-specific biological functions. ComPPI is an integrated database covering four species (S. cerevisiae, C. elegans, D. melanogaster and H. sapiens). The compilation of nine protein–protein interaction and eight subcellular localization data sets had four curation steps including a manually built, comprehensive hierarchical structure of >1600 subcellular localizations. ComPPI provides confidence scores for protein subcellular localizations and protein–protein interactions. ComPPI has user-friendly search options for individual proteins giving their subcellular localization, their interactions and the likelihood of their interactions considering the subcellular localization of their interacting partners. Download options of search results, whole-proteomes, organelle-specific interactomes and subcellular localization data are available on its website. Due to its novel features, ComPPI is useful for the analysis of experimental results in biochemistry and molecular biology, as well as for proteome-wide studies in bioinformatics and network science helping cellular biology, medicine and drug design. PMID:25348397

  18. Uniqueness and stability of traveling waves for cellular neural networks with multiple delays

    NASA Astrophysics Data System (ADS)

    Yu, Zhi-Xian; Mei, Ming

    2016-01-01

    In this paper, we investigate the properties of traveling waves to a class of lattice differential equations for cellular neural networks with multiple delays. Following the previous study [38] on the existence of the traveling waves, here we focus on the uniqueness and the stability of these traveling waves. First of all, by establishing the a priori asymptotic behavior of traveling waves and applying Ikehara's theorem, we prove the uniqueness (up to translation) of traveling waves ϕ (n - ct) with c ≤c* for the cellular neural networks with multiple delays, where c* < 0 is the critical wave speed. Then, by the weighted energy method together with the squeezing technique, we further show the global stability of all non-critical traveling waves for this model, that is, for all monotone waves with the speed c

  19. A quantitative chaperone interaction network reveals the architecture of cellular protein homeostasis pathways.

    PubMed

    Taipale, Mikko; Tucker, George; Peng, Jian; Krykbaeva, Irina; Lin, Zhen-Yuan; Larsen, Brett; Choi, Hyungwon; Berger, Bonnie; Gingras, Anne-Claude; Lindquist, Susan

    2014-07-17

    Chaperones are abundant cellular proteins that promote the folding and function of their substrate proteins (clients). In vivo, chaperones also associate with a large and diverse set of cofactors (cochaperones) that regulate their specificity and function. However, how these cochaperones regulate protein folding and whether they have chaperone-independent biological functions is largely unknown. We combined mass spectrometry and quantitative high-throughput LUMIER assays to systematically characterize the chaperone-cochaperone-client interaction network in human cells. We uncover hundreds of chaperone clients, delineate their participation in specific cochaperone complexes, and establish a surprisingly distinct network of protein-protein interactions for cochaperones. As a salient example of the power of such analysis, we establish that NUDC family cochaperones specifically associate with structurally related but evolutionarily distinct β-propeller folds. We provide a framework for deciphering the proteostasis network and its regulation in development and disease and expand the use of chaperones as sensors for drug-target engagement. PMID:25036637

  20. Network, cellular, and molecular mechanisms underlying long-term memory formation.

    PubMed

    Carasatorre, Mariana; Ramírez-Amaya, Víctor

    2013-01-01

    The neural network stores information through activity-dependent synaptic plasticity that occurs in populations of neurons. Persistent forms of synaptic plasticity may account for long-term memory storage, and the most salient forms are the changes in the structure of synapses. The theory proposes that encoding should use a sparse code and evidence suggests that this can be achieved through offline reactivation or by sparse initial recruitment of the network units. This idea implies that in some cases the neurons that underwent structural synaptic plasticity might be a subpopulation of those originally recruited; However, it is not yet clear whether all the neurons recruited during acquisition are the ones that underwent persistent forms of synaptic plasticity and responsible for memory retrieval. To determine which neural units underlie long-term memory storage, we need to characterize which are the persistent forms of synaptic plasticity occurring in these neural ensembles and the best hints so far are the molecular signals underlying structural modifications of the synapses. Structural synaptic plasticity can be achieved by the activity of various signal transduction pathways, including the NMDA-CaMKII and ACh-MAPK. These pathways converge with the Rho family of GTPases and the consequent ERK 1/2 activation, which regulates multiple cellular functions such as protein translation, protein trafficking, and gene transcription. The most detailed explanation may come from models that allow us to determine the contribution of each piece of this fascinating puzzle that is the neuron and the neural network. PMID:22976275

  1. Proof-of-Concept of a Millimeter-Wave Integrated Heterogeneous Network for 5G Cellular.

    PubMed

    Okasaka, Shozo; Weiler, Richard J; Keusgen, Wilhelm; Pudeyev, Andrey; Maltsev, Alexander; Karls, Ingolf; Sakaguchi, Kei

    2016-01-01

    The fifth-generation mobile networks (5G) will not only enhance mobile broadband services, but also enable connectivity for a massive number of Internet-of-Things devices, such as wireless sensors, meters or actuators. Thus, 5G is expected to achieve a 1000-fold or more increase in capacity over 4G. The use of the millimeter-wave (mmWave) spectrum is a key enabler to allowing 5G to achieve such enhancement in capacity. To fully utilize the mmWave spectrum, 5G is expected to adopt a heterogeneous network (HetNet) architecture, wherein mmWave small cells are overlaid onto a conventional macro-cellular network. In the mmWave-integrated HetNet, splitting of the control plane (CP) and user plane (UP) will allow continuous connectivity and increase the capacity of the mmWave small cells. mmWave communication can be used not only for access linking, but also for wireless backhaul linking, which will facilitate the installation of mmWave small cells. In this study, a proof-of-concept (PoC) was conducted to demonstrate the practicality of a prototype mmWave-integrated HetNet, using mmWave technologies for both backhaul and access. PMID:27571074

  2. Firing patterns in a random network cellular automata model of the brain

    NASA Astrophysics Data System (ADS)

    Acedo, L.; Lamprianidou, E.; Moraño, J.-A.; Villanueva-Oller, J.; Villanueva, R.-J.

    2015-10-01

    One of the main challenges in the simulation of even reduced areas of the brain is the presence of a large number of neurons and a large number of connections among them. Even from a theoretical point of view, the behaviour of dynamical models of complex networks with high connectivity is unknown, precisely because the cost of computation is still unaffordable and it will likely be in the near future. In this paper we discuss the simulation of a cellular automata network model of the brain including up to one million sites with a maximum average of three hundred connections per neuron. This level of connectivity was achieved thanks to a distributed computing environment based on the BOINC (Berkeley Open Infrastructure for Network Computing) platform. Moreover, in this work we consider the interplay among excitatory neurons (which induce the excitation of their neighbours) and inhibitory neurons (which prevent resting neurons from firing and induce firing neurons to pass to the refractory state). Our objective is to classify the normal (noisy but asymptotically constant patterns) and the abnormal (high oscillations with spindle-like behaviour) patterns of activity in the model brain and their stability and parameter ranges in order to determine the role of excitatory and inhibitory compensatory effects in healthy and diseased individuals.

  3. Viral Replication Protein Inhibits Cellular Cofilin Actin Depolymerization Factor to Regulate the Actin Network and Promote Viral Replicase Assembly

    PubMed Central

    Kovalev, Nikolay; de Castro Martín, Isabel Fernández; Barajas, Daniel; Risco, Cristina; Nagy, Peter D.

    2016-01-01

    RNA viruses exploit host cells by co-opting host factors and lipids and escaping host antiviral responses. Previous genome-wide screens with Tomato bushy stunt virus (TBSV) in the model host yeast have identified 18 cellular genes that are part of the actin network. In this paper, we show that the p33 viral replication factor interacts with the cellular cofilin (Cof1p), which is an actin depolymerization factor. Using temperature-sensitive (ts) Cof1p or actin (Act1p) mutants at a semi-permissive temperature, we find an increased level of TBSV RNA accumulation in yeast cells and elevated in vitro activity of the tombusvirus replicase. We show that the large p33 containing replication organelle-like structures are located in the close vicinity of actin patches in yeast cells or around actin cable hubs in infected plant cells. Therefore, the actin filaments could be involved in VRC assembly and the formation of large viral replication compartments containing many individual VRCs. Moreover, we show that the actin network affects the recruitment of viral and cellular components, including oxysterol binding proteins and VAP proteins to form membrane contact sites for efficient transfer of sterols to the sites of replication. Altogether, the emerging picture is that TBSV, via direct interaction between the p33 replication protein and Cof1p, controls cofilin activities to obstruct the dynamic actin network that leads to efficient subversion of cellular factors for pro-viral functions. In summary, the discovery that TBSV interacts with cellular cofilin and blocks the severing of existing filaments and the formation of new actin filaments in infected cells opens a new window to unravel the way by which viruses could subvert/co-opt cellular proteins and lipids. By regulating the functions of cofilin and the actin network, which are central nodes in cellular pathways, viruses could gain supremacy in subversion of cellular factors for pro-viral functions. PMID:26863541

  4. A novel method to assess human population exposure induced by a wireless cellular network.

    PubMed

    Varsier, Nadège; Plets, David; Corre, Yoann; Vermeeren, Günter; Joseph, Wout; Aerts, Sam; Martens, Luc; Wiart, Joe

    2015-09-01

    This paper presents a new metric to evaluate electromagnetic exposure induced by wireless cellular networks. This metric takes into account the exposure induced by base station antennas as well as exposure induced by wireless devices to evaluate average global exposure of the population in a specific geographical area. The paper first explains the concept and gives the formulation of the Exposure Index (EI). Then, the EI computation is illustrated through simple phone call scenarios (indoor office, in train) and a complete macro urban data long-term evolution scenario showing how, based on simulations, radio-planning predictions, realistic population statistics, user traffic data, and specific absorption rate calculations can be combined to assess the index. Bioelectromagnetics. 36:451-463, 2015. © 2015 Wiley Periodicals, Inc. PMID:26113174

  5. Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

    PubMed Central

    Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

    2012-01-01

    Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

  6. Modeling of trophospheric ozone concentrations using genetically trained multi-level cellular neural networks

    NASA Astrophysics Data System (ADS)

    Ozcan, H. Kurtulus; Bilgili, Erdem; Sahin, Ulku; Ucan, O. Nuri; Bayat, Cuma

    2007-09-01

    Tropospheric ozone concentrations, which are an important air pollutant, are modeled by the use of an artificial intelligence structure. Data obtained from air pollution measurement stations in the city of Istanbul are utilized in constituting the model. A supervised algorithm for the evaluation of ozone concentration using a genetically trained multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. A genetic algorithm is used in the optimization of CNN templates. The model results and the actual measurement results are compared and statistically evaluated. It is observed that seasonal changes in ozone concentrations are reflected effectively by the concentrations estimated by the multilevel-CNN model structure, with a correlation value of 0.57 ascertained between actual and model results. It is shown that the multilevel-CNN modeling technique is as satisfactory as other modeling techniques in associating the data in a complex medium in air pollution applications.

  7. Convergence and attractivity of memristor-based cellular neural networks with time delays.

    PubMed

    Qin, Sitian; Wang, Jun; Xue, Xiaoping

    2015-03-01

    This paper presents theoretical results on the convergence and attractivity of memristor-based cellular neural networks (MCNNs) with time delays. Based on a realistic memristor model, an MCNN is modeled using a differential inclusion. The essential boundedness of its global solutions is proven. The state of MCNNs is further proven to be convergent to a critical-point set located in saturated region of the activation function, when the initial state locates in a saturated region. It is shown that the state convergence time period is finite and can be quantitatively estimated using given parameters. Furthermore, the positive invariance and attractivity of state in non-saturated regions are also proven. The simulation results of several numerical examples are provided to substantiate the results. PMID:25562569

  8. Parallelism on the Intel 860 Hypercube:. Ising Magnets, Hydrodynamical Cellular Automata and Neural Networks

    NASA Astrophysics Data System (ADS)

    Kohring, G. A.; Stauffer, D.

    Geometric parallelization was tested on the Intel Hypercube with 32 MIMD processors of 1860 type, each with 16 Mbytes of distributed memory. We applied it to Ising models in two and three dimensions as well as to neural networks and two-dimensional hydrodynamic cellular automata. For system sizes suited to this machine, up to 60960*60960 and 1410*1410*1408 Ising spins, we found nearly hundred percent parallel efficiency in spite of the needed inter-processor communications. For small systems, the observed deviations from full efficiency were compared with the scaling concepts of Heermann and Burkitt and of Jakobs and Gerling. For Ising models, we determined the Glauber kinetic exponent z≃2.18 in two dimensions and confirmed the stretched exponential relaxation of the magnetization towards the spontaneous magnetization below Tc. For three dimensions we found z≃2.09 and simple exponential relaxation.

  9. Global Detection of Live Virtual Machine Migration Based on Cellular Neural Networks

    PubMed Central

    Xie, Kang; Yang, Yixian; Zhang, Ling; Jing, Maohua; Xin, Yang; Li, Zhongxian

    2014-01-01

    In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better. PMID:24959631

  10. Smart-Pixel Array Processors Based on Optimal Cellular Neural Networks for Space Sensor Applications

    NASA Technical Reports Server (NTRS)

    Fang, Wai-Chi; Sheu, Bing J.; Venus, Holger; Sandau, Rainer

    1997-01-01

    A smart-pixel cellular neural network (CNN) with hardware annealing capability, digitally programmable synaptic weights, and multisensor parallel interface has been under development for advanced space sensor applications. The smart-pixel CNN architecture is a programmable multi-dimensional array of optoelectronic neurons which are locally connected with their local neurons and associated active-pixel sensors. Integration of the neuroprocessor in each processor node of a scalable multiprocessor system offers orders-of-magnitude computing performance enhancements for on-board real-time intelligent multisensor processing and control tasks of advanced small satellites. The smart-pixel CNN operation theory, architecture, design and implementation, and system applications are investigated in detail. The VLSI (Very Large Scale Integration) implementation feasibility was illustrated by a prototype smart-pixel 5x5 neuroprocessor array chip of active dimensions 1380 micron x 746 micron in a 2-micron CMOS technology.

  11. Global detection of live virtual machine migration based on cellular neural networks.

    PubMed

    Xie, Kang; Yang, Yixian; Zhang, Ling; Jing, Maohua; Xin, Yang; Li, Zhongxian

    2014-01-01

    In order to meet the demands of operation monitoring of large scale, autoscaling, and heterogeneous virtual resources in the existing cloud computing, a new method of live virtual machine (VM) migration detection algorithm based on the cellular neural networks (CNNs), is presented. Through analyzing the detection process, the parameter relationship of CNN is mapped as an optimization problem, in which improved particle swarm optimization algorithm based on bubble sort is used to solve the problem. Experimental results demonstrate that the proposed method can display the VM migration processing intuitively. Compared with the best fit heuristic algorithm, this approach reduces the processing time, and emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI) implementation allowing the VM migration detection to be performed better. PMID:24959631

  12. Co-evolutionary networks of genes and cellular processes across fungal species

    PubMed Central

    Tuller, Tamir; Kupiec, Martin; Ruppin, Eytan

    2009-01-01

    Background The introduction of measures such as evolutionary rate and propensity for gene loss have significantly advanced our knowledge of the evolutionary history and selection forces acting upon individual genes and cellular processes. Results We present two new measures, the 'relative evolutionary rate pattern' (rERP), which records the relative evolutionary rates of conserved genes across the different branches of a species' phylogenetic tree, and the 'copy number pattern' (CNP), which quantifies the rate of gene loss of less conserved genes. Together, these measures yield a high-resolution study of the co-evolution of genes in 9 fungal species, spanning 3,540 sets of orthologs. We find that the evolutionary tempo of conserved genes varies in different evolutionary periods. The co-evolution of genes' Gene Ontology categories exhibits a significant correlation with their functional distance in the Gene Ontology hierarchy, but not with their location on chromosomes, showing that cellular functions are a more important driving force in gene co-evolution than their chromosomal proximity. Two fundamental patterns of co-evolution of conserved genes, cooperative and reciprocal, are identified; only genes co-evolving cooperatively functionally back each other up. The co-evolution of conserved and less conserved genes exhibits both commonalities and differences; DNA metabolism is positively correlated with nuclear traffic, transcription processes and vacuolar biology in both analyses. Conclusions Overall, this study charts the first global network view of gene co-evolution in fungi. The future application of the approach presented here to other phylogenetic trees holds much promise in characterizing the forces that shape cellular co-evolution. PMID:19416514

  13. BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling

    PubMed Central

    Feng, Song; Ollivier, Julien F.; Swain, Peter S.; Soyer, Orkun S.

    2015-01-01

    Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. PMID:26101250

  14. Intragranular cellular segregation network structure strengthening 316L stainless steel prepared by selective laser melting

    NASA Astrophysics Data System (ADS)

    Zhong, Yuan; Liu, Leifeng; Wikman, Stefan; Cui, Daqing; Shen, Zhijian

    2016-03-01

    A feasibility study was performed to fabricate ITER In-Vessel components by Selective Laser Melting (SLM) supported by Fusion for Energy (F4E). Almost fully dense 316L stainless steel (SS316L) components were prepared from gas-atomized powder and with optimized SLM processing parameters. Tensile tests and Charpy-V tests were carried out at 22 °C and 250 °C and the results showed that SLM SS316L fulfill the RCC-MR code. Microstructure characterization reveals the presence of hierarchical macro-, micro- and nano-structures in as-built samples that were very different from SS316L microstructures prepared by other established methods. The formation of a characteristic intragranular cellular segregation network microstructure appears to contribute to the increase of yield strength without losing ductility. Silicon oxide nano-inclusions were formed during the SLM process that generated a micro-hardness fluctuation in the building direction. The combined influence of a cellular microstructure and the nano-inclusions constraints the size of ductile dimples to nano-scale. The crack propagation is hindered by a pinning effect that improves the defect-tolerance of the SLM SS316L. This work proves that it was possible to manufacture SS316L with properties suitable for ITER First Wall panels. Further studies on irradiation properties of SLM SS316L and manufacturing of larger real-size components are needed.

  15. Computerized detection of pulmonary nodules using cellular neural networks in CT images

    NASA Astrophysics Data System (ADS)

    Zhang, Xiangwei; McLennan, Geoffrey; Hoffman, Eric A.; Sonka, Milan

    2004-05-01

    The purpose of this study is to develop a computer-aided diagnosis (CAD) system to detect small-sized (from 2mm to 10mm) non-pleural pulmonary nodules in high resolution helical CT scans. A new 3D automated scheme using cellular neural networks is presented. Different from most previous methods, this scheme employed the local shape property to perform voxel classification. The shape index feature successfully captured the local shape difference between nodules and non-nodules, especially vessels. A 3D discrete-time cellular neural network (DTCNN) was constructed to give a reliable voxel classification by collecting information in a neighborhood. To tailor it for lung nodule detection, this DTCNN was trained using genetic algorithms (GAs) to derive the shape index variation pattern of nodules. 19 clinical thoracic CT cases involving a total of 4838 sectional images were used in this work, with 2 scans forming the training set, and the remaining 17 cases being the testing set. The evaluation was composed of two stages. During the first stage, a pulmonologist and our CAD system independently detected nodules in the testing set. Then, the suspected nodule areas located by the computer were reviewed by the pulmonologist to confirm nodules missed by the human in the first review. There were 32 true nodules detected by the computer but missed by the pulmonologist in the first review, in which 30 non-juxtapleural nodules were found. Considering the nodules detected by the pulmonologist during the first and second reviews as the truth, 52 of 62 non-pleural nodules were detected by the CAD system (sensitivity being 83.9%), with the number of false positives being 3.47 per case.

  16. Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks

    PubMed Central

    Foremski, Paweł; Gorawski, Michał; Grochla, Krzysztof; Polys, Konrad

    2015-01-01

    The paper presents a practical application of the crowdsensing idea to measure human mobility and signal coverage in cellular networks. Currently, virtually everyone is carrying a mobile phone, which may be used as a sensor to gather research data by measuring, e.g., human mobility and radio signal levels. However, many users are unwilling to participate in crowdsensing experiments. This work begins with the analysis of the barriers for engaging people in crowdsensing. A survey showed that people who agree to participate in crowdsensing expect a minimum impact on their battery lifetime and phone usage habits. To address these requirements, this paper proposes an application for measuring the location and signal strength data based on energy-efficient GPS tracking, which allows one to perform the measurements of human mobility and radio signal levels with minimum energy utilization and without any engagement of the user. The method described combines measurements from the accelerometer with effective management of the GPS to monitor the user mobility with the decrease in battery lifetime by approximately 20%. To show the applicability of the proposed platform, the sample results of signal level distribution and coverage maps gathered for an LTE network and representing human mobility are shown. PMID:26340633

  17. Cellular Nonlinear Networks for the emergence of perceptual states: application to robot navigation control.

    PubMed

    Arena, Paolo; De Fiore, Sebastiano; Patané, Luca

    2009-01-01

    In this paper a new general purpose perceptual control architecture, based on nonlinear neural lattices, is presented and applied to solve robot navigation tasks. Insects show the ability to react to certain stimuli with simple reflexes, using direct sensory-motor pathways, which can be considered as basic behaviors, inherited and pre-wired. Relevant brain centres, known as Mushroom Bodies (MB) and Central Complex (CX) were recently identified in insects: though their functional details are not yet fully understood, it is known that they provide secondary pathways allowing the emergence of cognitive behaviors. These are gained through the coordination of the basic abilities to satisfy the insect's needs. Taking inspiration from this evidence, our architecture modulates, through a reinforcement learning, a set of competitive and concurrent basic behaviors in order to accomplish the task assigned through a reward function. The core of the architecture is constituted by the so-called Representation layer, used to create a concise picture of the current environment situation, fusing together different stimuli for the emergence of perceptual states. These perceptual states are steady state solutions of lattices of Reaction-Diffusion Cellular Nonlinear Networks (RD-CNN), designed to show Turing patterns. The exploitation of the dynamics of the multiple equilibria of the network is emphasized through the adaptive shaping of the basins of attraction for each emerged pattern. New experimental campaigns on standard robotic platforms are reported to demonstrate the potentiality and the effectiveness of the approach. PMID:19596552

  18. Measurement and interpolation uncertainties in rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify and quantify the sources of uncertainty in such rainfall maps, but also test the actual and optimal performance of one commercial microwave network from one of the cellular providers in the Netherlands. Errors in microwave link measurements were found to be the source that contributes most to the overall uncertainty.

  19. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    NASA Astrophysics Data System (ADS)

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-11-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

  20. Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

    PubMed Central

    Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

    2015-01-01

    Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases. PMID:26608097

  1. Noise-robust realization of Turing-complete cellular automata by using neural networks with pattern representation

    NASA Astrophysics Data System (ADS)

    Oku, Makito; Aihara, Kazuyuki

    2010-11-01

    A modularly-structured neural network model is considered. Each module, which we call a ‘cell’, consists of two parts: a Hopfield neural network model and a multilayered perceptron. An array of such cells is used to simulate the Rule 110 cellular automaton with high accuracy even when all the units of neural networks are replaced by stochastic binary ones. We also find that noise not only degrades but also facilitates computation if the outputs of multilayered perceptrons are below the threshold required to update the states of the cells, which is a stochastic resonance in computation.

  2. Astrocytic gap junctional networks suppress cellular damage in an in vitro model of ischemia

    SciTech Connect

    Shinotsuka, Takanori; Yasui, Masato; Nuriya, Mutsuo

    2014-02-07

    Highlights: • Astrocytes exhibit characteristic changes in [Ca{sup 2+}]{sub i} under OGD. • Astrocytic [Ca{sup 2+}]{sub i} increase is synchronized with a neuronal anoxic depolarization. • Gap junctional couplings protect neurons as well as astrocytes during OGD. - Abstract: Astrocytes play pivotal roles in both the physiology and the pathophysiology of the brain. They communicate with each other via extracellular messengers as well as through gap junctions, which may exacerbate or protect against pathological processes in the brain. However, their roles during the acute phase of ischemia and the underlying cellular mechanisms remain largely unknown. To address this issue, we imaged changes in the intracellular calcium concentration ([Ca{sup 2+}]{sub i}) in astrocytes in mouse cortical slices under oxygen/glucose deprivation (OGD) condition using two-photon microscopy. Under OGD, astrocytes showed [Ca{sup 2+}]{sub i} oscillations followed by larger and sustained [Ca{sup 2+}]{sub i} increases. While the pharmacological blockades of astrocytic receptors for glutamate and ATP had no effect, the inhibitions of gap junctional intercellular coupling between astrocytes significantly advanced the onset of the sustained [Ca{sup 2+}]{sub i} increase after OGD exposure. Interestingly, the simultaneous recording of the neuronal membrane potential revealed that the onset of the sustained [Ca{sup 2+}]{sub i} increase in astrocytes was synchronized with the appearance of neuronal anoxic depolarization. Furthermore, the blockade of gap junctional coupling resulted in a concurrent faster appearance of neuronal depolarizations, which remain synchronized with the sustained [Ca{sup 2+}]{sub i} increase in astrocytes. These results indicate that astrocytes delay the appearance of the pathological responses of astrocytes and neurons through their gap junction-mediated intercellular network under OGD. Thus, astrocytic gap junctional networks provide protection against tissue damage

  3. On-chip training for cellular neural networks using iterative annealing

    NASA Astrophysics Data System (ADS)

    Feiden, Dirk; Tetzlaff, Ronald

    2003-04-01

    Cellular Neural Network-Universal Machines (CNN-UM) are analog devices, which are excellently suited for image processing. A big challenge thereby is the determination of CNN templates for special image processing tasks. In many cases appropriate templates can only be found by a parameter optimization. The determination of templates for complex applications in the area of CNN is usually performed by using a CNN software simulator. Unfortunately, in many cases the determined templates cannot be used in hardware realizations of CNN caused by realization effects. In order to find robust templates, which are not only working on CNN simulators, but also on hardware implementations, we present in this contribution a new kind of on-chip-multi-template-training. Furthermore, as a possible application, we will also present a CNN-based solution of the problem of Pattern Matching, which is a processing step in many areas of image processing, like e.g. in Motion Estimation, Image- and Video-Compression.

  4. Residual Separation of Magnetic Fields Using a Cellular Neural Network Approach

    NASA Astrophysics Data System (ADS)

    Albora, A. M.; Özmen, A.; Uçan, O. N.

    - In this paper, a Cellular Neural Network (CNN) has been applied to a magnetic regional/residual anomaly separation problem. CNN is an analog parallel computing paradigm defined in space and characterized by the locality of connections between processing neurons. The behavior of the CNN is defined by the template matrices A, B and the template vector I. We have optimized weight coefficients of these templates using Recurrent Perceptron Learning Algorithm (RPLA). The advantages of CNN as a real-time stochastic method are that it introduces little distortion to the shape of the original image and that it is not effected significantly by factors such as the overlap of power spectra of residual fields. The proposed method is tested using synthetic examples and the average depth of the buried objects has been estimated by power spectrum analysis. Next the CNN approach is applied to magnetic data over the Golalan chromite mine in Elazig which lies East of Turkey. This area is among the largest and richest chromite masses of the world. We compared the performance of CNN to classical derivative approaches.

  5. Data fusion and classification using a hybrid intrinsic cellular inference network

    NASA Astrophysics Data System (ADS)

    Woodley, Robert; Walenz, Brett; Seiffertt, John; Robinette, Paul; Wunsch, Donald

    2010-04-01

    Hybrid Intrinsic Cellular Inference Network (HICIN) is designed for battlespace decision support applications. We developed an automatic method of generating hypotheses for an entity-attribute classifier. The capability and effectiveness of a domain specific ontology was used to generate automatic categories for data classification. Heterogeneous data is clustered using an Adaptive Resonance Theory (ART) inference engine on a sample (unclassified) data set. The data set is the Lahman baseball database. The actual data is immaterial to the architecture, however, parallels in the data can be easily drawn (i.e., "Team" maps to organization, "Runs scored/allowed" to Measure of organization performance (positive/negative), "Payroll" to organization resources, etc.). Results show that HICIN classifiers create known inferences from the heterogonous data. These inferences are not explicitly stated in the ontological description of the domain and are strictly data driven. HICIN uses data uncertainty handling to reduce errors in the classification. The uncertainty handling is based on subjective logic. The belief mass allows evidence from multiple sources to be mathematically combined to increase or discount an assertion. In military operations the ability to reduce uncertainty will be vital in the data fusion operation.

  6. Memristor-based cellular nonlinear/neural network: design, analysis, and applications.

    PubMed

    Duan, Shukai; Hu, Xiaofang; Dong, Zhekang; Wang, Lidan; Mazumder, Pinaki

    2015-06-01

    Cellular nonlinear/neural network (CNN) has been recognized as a powerful massively parallel architecture capable of solving complex engineering problems by performing trillions of analog operations per second. The memristor was theoretically predicted in the late seventies, but it garnered nascent research interest due to the recent much-acclaimed discovery of nanocrossbar memories by engineers at the Hewlett-Packard Laboratory. The memristor is expected to be co-integrated with nanoscale CMOS technology to revolutionize conventional von Neumann as well as neuromorphic computing. In this paper, a compact CNN model based on memristors is presented along with its performance analysis and applications. In the new CNN design, the memristor bridge circuit acts as the synaptic circuit element and substitutes the complex multiplication circuit used in traditional CNN architectures. In addition, the negative differential resistance and nonlinear current-voltage characteristics of the memristor have been leveraged to replace the linear resistor in conventional CNNs. The proposed CNN design has several merits, for example, high density, nonvolatility, and programmability of synaptic weights. The proposed memristor-based CNN design operations for implementing several image processing functions are illustrated through simulation and contrasted with conventional CNNs. Monte-Carlo simulation has been used to demonstrate the behavior of the proposed CNN due to the variations in memristor synaptic weights. PMID:25069124

  7. Numerically evaluated functional equivalence between chaotic dynamics in neural networks and cellular automata under totalistic rules.

    PubMed

    Takada, Ryu; Munetaka, Daigo; Kobayashi, Shoji; Suemitsu, Yoshikazu; Nara, Shigetoshi

    2007-09-01

    Chaotic dynamics in a recurrent neural network model and in two-dimensional cellular automata, where both have finite but large degrees of freedom, are investigated from the viewpoint of harnessing chaos and are applied to motion control to indicate that both have potential capabilities for complex function control by simple rule(s). An important point is that chaotic dynamics generated in these two systems give us autonomous complex pattern dynamics itinerating through intermediate state points between embedded patterns (attractors) in high-dimensional state space. An application of these chaotic dynamics to complex controlling is proposed based on an idea that with the use of simple adaptive switching between a weakly chaotic regime and a strongly chaotic regime, complex problems can be solved. As an actual example, a two-dimensional maze, where it should be noted that the spatial structure of the maze is one of typical ill-posed problems, is solved with the use of chaos in both systems. Our computer simulations show that the success rate over 300 trials is much better, at least, than that of a random number generator. Our functional simulations indicate that both systems are almost equivalent from the viewpoint of functional aspects based on our idea, harnessing of chaos. PMID:19003512

  8. Synchronization schemes for coupled identical Yang-Yang type fuzzy cellular neural networks

    NASA Astrophysics Data System (ADS)

    Xia, Yonghui; Yang, Zijiang; Han, Maoan

    2009-09-01

    This paper proposes an adaptive procedure to the problem of synchronization for a class of coupled identical Yang-Yang type fuzzy cellular neural networks (YYFCNN) with time-varying delays. Based on the simple adaptive controller, a set of sufficient conditions are developed to guarantee the synchronization of the coupled YYFCNN with time-varying delays. The results are much different from previous ones. It is proved that two coupled identical YYFCNN with time-varying delays can achieve synchronization by enhancing the coupled strength dynamically. In addition, this kind of controller is simple to be implemented and it is fairly robust against the effect of weak noise in the given time series. The approaches are based on using the invariance principle of functional differential equations, constructing a general Lyapunov-Krasovskii functional and employing a linear matrix inequality (LMI). An illustrative example and its simulations show the feasibility of our results. Finally, an application is given to show how to apply the presented synchronization scheme of YYFCNN to secure communication.

  9. The potential of cellular network infrastructures for sudden rainfall monitoring in dry climate regions

    NASA Astrophysics Data System (ADS)

    David, N.; Alpert, P.; Messer, H.

    2013-09-01

    Monitoring of precipitation and in particular sudden rain, in rural dry climate regions, is a subject of great significance in several weather related processes such as soil erosion, flash flooding, triggering epidemics and more. The rainfall monitoring facilities in these regions and as a result precipitation data are, however, commonly, severely lacking. As was recently shown, cellular networks infrastructures supply high resolution precipitation measurements at ground level while often being situated in dry areas, covering large parts of these climatic zones. The potential found in these systems to provide early monitoring and essential precipitation information, directly from arid regions, based on standard measurements of commercial microwave links, is exemplified here over the Negev and the Southern Judean desert, South Israel. We present the results of two different rainfall events occurred in these regions. It is shown that the microwave system measured precipitation between at least 50 min (in case 1) and at least 1 h and 40 min (in case 2) before each of the sparse rain gauges. During each case, the radar system, located relatively far from the arid sites, provided measurements from heights of at least 1500 m and 2000 m above surface, respectively. A third case study demonstrates a relative advantage of microwave links to measure precipitation intensity with respect to the radar system, over an area of complex topography located in northeastern Israel, which is relatively far (~ 150 km) from the radar.

  10. A universal concept based on cellular neural networks for ultrafast and flexible solving of differential equations.

    PubMed

    Chedjou, Jean Chamberlain; Kyamakya, Kyandoghere

    2015-04-01

    This paper develops and validates a comprehensive and universally applicable computational concept for solving nonlinear differential equations (NDEs) through a neurocomputing concept based on cellular neural networks (CNNs). High-precision, stability, convergence, and lowest-possible memory requirements are ensured by the CNN processor architecture. A significant challenge solved in this paper is that all these cited computing features are ensured in all system-states (regular or chaotic ones) and in all bifurcation conditions that may be experienced by NDEs.One particular quintessence of this paper is to develop and demonstrate a solver concept that shows and ensures that CNN processors (realized either in hardware or in software) are universal solvers of NDE models. The solving logic or algorithm of given NDEs (possible examples are: Duffing, Mathieu, Van der Pol, Jerk, Chua, Rössler, Lorenz, Burgers, and the transport equations) through a CNN processor system is provided by a set of templates that are computed by our comprehensive templates calculation technique that we call nonlinear adaptive optimization. This paper is therefore a significant contribution and represents a cutting-edge real-time computational engineering approach, especially while considering the various scientific and engineering applications of this ultrafast, energy-and-memory-efficient, and high-precise NDE solver concept. For illustration purposes, three NDE models are demonstratively solved, and related CNN templates are derived and used: the periodically excited Duffing equation, the Mathieu equation, and the transport equation. PMID:25794380

  11. Adiponectin fine-tuning of liver regeneration dynamics revealed through cellular network modelling.

    PubMed

    Correnti, Jason M; Cook, Daniel; Aksamitiene, Edita; Swarup, Aditi; Ogunnaike, Babatunde; Vadigepalli, Rajanikanth; Hoek, Jan B

    2015-01-15

    Following partial hepatectomy, the liver initiates a regenerative programme involving hepatocyte priming and replication driven by the coordinated actions of cytokine and growth factors. We investigated the mechanisms underlying adiponectin's (Adn) regulation of liver regeneration through modulation of these mediators. Adn(-/-) mice showed delayed onset of hepatocyte replication, but accelerated cell cycle progression relative to wild-type mice, suggesting Adn has multiple effects fine-tuning the kinetics of liver regeneration. We developed a computational model describing the molecular and physiological kinetics of liver regeneration in Adn(-/-) mice. We employed this computational model to evaluate the underlying regulatory mechanisms. Our analysis predicted that Adn is required for an efficient early cytokine response to partial hepatectomy, but is inhibitory to later growth factor actions. Consistent with this prediction, Adn knockout reduced hepatocyte responses to interleukin-6 during the priming phase, but enhanced growth factor levels through peak hepatocyte replication. By contrast, supraphysiological concentrations of Adn resulting from rosiglitazone treatment suppressed regeneration by reducing growth factor levels during S phase, consistent with computational predictions. Together, these results revealed that Adn fine-tunes the progression of liver regeneration through dynamically modulating molecular mediator networks and cellular interactions within the liver. PMID:25630259

  12. Adiponectin fine-tuning of liver regeneration dynamics revealed through cellular network modelling

    PubMed Central

    Correnti, Jason M; Cook, Daniel; Aksamitiene, Edita; Swarup, Aditi; Ogunnaike, Babatunde; Vadigepalli, Rajanikanth; Hoek, Jan B

    2015-01-01

    Following partial hepatectomy, the liver initiates a regenerative programme involving hepatocyte priming and replication driven by the coordinated actions of cytokine and growth factors. We investigated the mechanisms underlying adiponectin's (Adn) regulation of liver regeneration through modulation of these mediators. Adn–/– mice showed delayed onset of hepatocyte replication, but accelerated cell cycle progression relative to wild-type mice, suggesting Adn has multiple effects fine-tuning the kinetics of liver regeneration. We developed a computational model describing the molecular and physiological kinetics of liver regeneration in Adn–/– mice. We employed this computational model to evaluate the underlying regulatory mechanisms. Our analysis predicted that Adn is required for an efficient early cytokine response to partial hepatectomy, but is inhibitory to later growth factor actions. Consistent with this prediction, Adn knockout reduced hepatocyte responses to interleukin-6 during the priming phase, but enhanced growth factor levels through peak hepatocyte replication. By contrast, supraphysiological concentrations of Adn resulting from rosiglitazone treatment suppressed regeneration by reducing growth factor levels during S phase, consistent with computational predictions. Together, these results revealed that Adn fine-tunes the progression of liver regeneration through dynamically modulating molecular mediator networks and cellular interactions within the liver. PMID:25630259

  13. Design and simulation of cellular nonlinear networks using single-electron tunneling transistor technology

    NASA Astrophysics Data System (ADS)

    Gerousis, Costa P.

    It is currently predicted that semiconductor device scaling will end at the 22-nm device feature size (7 nm physical channel length) according to the International Technology Roadmap for Semiconductors. The main challenge is then to develop innovative technologies that will extend the scaling beyond roadmap projection. Any new technology must be well matched with complementary metal oxide semiconductor (CMOS) technology and scaleable beyond CMOS scaling projections and must provide low-power high-speed signal processing. Nanotechnology will become an appealing option for developing devices for integrated circuits with dimensions and performances well beyond roadmap predictions. Such devices, based on the controllable transfer of charge between dots or 'islands', can take advantage of the quantum mechanical effects, such as tunneling and energy quantization, which would normally occur at the nanometer scale. An outstanding challenge is in arranging such nanodevices in new architectures that can be integrated on a single chip. In particular, locally interconnected architectures are believed to be necessary to alleviate the problems associated with increasing interconnect length and complexity in ultra-dense circuits. The goal of this work is to investigate the use of nanoelectronic structures in cellular non-linear network (CNN) architectures for potential application in future high-density and low-power CMOS-nanodevice hybrid circuits. The operation of the single-electron tunneling (SET) transistor is first reviewed, followed by a discussion of simple CNN linear architectures using a SET inverter topology as the basis for the non-linear transfer characteristics for individual cells to be used in analog processing arrays for image-processing applications. The basic SET CNN cell acts as a summing node that is capacitively coupled to the inputs and outputs of nearest neighbor cells. Monte Carlo simulation results are used to show CNN-like behavior in attempting to

  14. Spatio-temporal analysis of brain electrical activity in epilepsy based on cellular nonlinear networks

    NASA Astrophysics Data System (ADS)

    Gollas, Frank; Tetzlaff, Ronald

    2009-05-01

    Epilepsy is the most common chronic disorder of the nervous system. Generally, epileptic seizures appear without foregoing sign or warning. The problem of detecting a possible pre-seizure state in epilepsy from EEG signals has been addressed by many authors over the past decades. Different approaches of time series analysis of brain electrical activity already are providing valuable insights into the underlying complex dynamics. But the main goal the identification of an impending epileptic seizure with a sufficient specificity and reliability, has not been achieved up to now. An algorithm for a reliable, automated prediction of epileptic seizures would enable the realization of implantable seizure warning devices, which could provide valuable information to the patient and time/event specific drug delivery or possibly a direct electrical nerve stimulation. Cellular Nonlinear Networks (CNN) are promising candidates for future seizure warning devices. CNN are characterized by local couplings of comparatively simple dynamical systems. With this property these networks are well suited to be realized as highly parallel, analog computer chips. Today available CNN hardware realizations exhibit a processing speed in the range of TeraOps combined with low power consumption. In this contribution new algorithms based on the spatio-temporal dynamics of CNN are considered in order to analyze intracranial EEG signals and thus taking into account mutual dependencies between neighboring regions of the brain. In an identification procedure Reaction-Diffusion CNN (RD-CNN) are determined for short segments of brain electrical activity, by means of a supervised parameter optimization. RD-CNN are deduced from Reaction-Diffusion Systems, which usually are applied to investigate complex phenomena like nonlinear wave propagation or pattern formation. The Local Activity Theory provides a necessary condition for emergent behavior in RD-CNN. In comparison linear spatio

  15. Implementation of a cellular neural network-based segmentation algorithm on the bio-inspired vision system

    NASA Astrophysics Data System (ADS)

    Karabiber, Fethullah; Grassi, Giuseppe; Vecchio, Pietro; Arik, Sabri; Yalcin, M. Erhan

    2011-01-01

    Based on the cellular neural network (CNN) paradigm, the bio-inspired (bi-i) cellular vision system is a computing platform consisting of state-of-the-art sensing, cellular sensing-processing and digital signal processing. This paper presents the implementation of a novel CNN-based segmentation algorithm onto the bi-i system. The experimental results, carried out for different benchmark video sequences, highlight the feasibility of the approach, which provides a frame rate of about 26 frame/sec. Comparisons with existing CNN-based methods show that, even though these methods are from two to six times faster than the proposed one, the conceived approach is more accurate and, consequently, represents a satisfying trade-off between real-time requirements and accuracy.

  16. Impedance matching network for high frequency ultrasonic transducer for cellular applications.

    PubMed

    Kim, Min Gon; Yoon, Sangpil; Kim, Hyung Ham; Shung, K Kirk

    2016-02-01

    An approach for the design of an impedance matching network (IMN) for high frequency ultrasonic transducers with large apertures based on impedance analysis for cellular applications is presented in this paper. The main objectives were to maximize energy transmission from the excitation source to the ultrasonic transducers for cell manipulation and to achieve low input parameters for the safe operation of an ultrasonic transducer because the piezoelectric material in high frequency ultrasonic transducers is prone to breakage due to its being extremely thin. Two ultrasonic transducers, which were made of lithium niobate single crystal with the thickness of 15 μm, having apertures of 4.3 mm (fnumber=1.23) and 2.6mm (fnumber=0.75) were tested. L-type IMN was selected for high sensitivity and compact design of the ultrasonic transducers. The target center frequency was chosen as the frequency where the electrical admittance (|Y|) and phase angle (θz) from impedance analysis was maximal and zero, respectively. The reference center frequency and reference echo magnitude were selected as the center frequency and echo magnitude, measured by pulse-echo testing, of the ultrasonic transducer without IMN. Initial component values and topology of IMN were determined using the Smith chart, and pulse-echo testing was analyzed to verify the performance of the ultrasonic transducers with and without IMN. After several iterations between changing component values and topology of IMN, and pulse-echo measurement of the ultrasonic transducer with IMN, optimized component values and topology of IMN were chosen when the measured center frequency from pulse-echo testing was comparable to the target frequency, and the measured echo magnitude was at least 30% larger than the reference echo magnitude. Performance of an ultrasonic transducer with and without IMN was tested by observing a tangible dent on the surface of a plastic petridish and single cell response after an acoustic pulse was

  17. Intrinsic noise, dissipation cost, and robustness of cellular networks: The underlying energy landscape of MAPK signal transduction

    PubMed Central

    Lapidus, Saul; Han, Bo; Wang, Jin

    2008-01-01

    We develop a probabilistic method for analyzing global features of a cellular network under intrinsic statistical fluctuations, which is important when there are finite numbers of molecules. By making a self-consistent mean field approximation of splitting the variables in order to reduce the large number of degrees of freedom, which is reasonable for a not very strongly interacting network, we discovered that the underlying energy landscape of the mitogen-activated protein kinases (MAPKs) signal transduction network (with experimentally measured or inferred parameters such as chemical reaction rate coefficients in the network) is funneled toward a global minimum characterized by the nonequilibrium steady-state fixed point of the system at the end of the signal transduction process. For this system, we also show that the energy landscape is robust against intrinsic fluctuations and random perturbation to the inherent chemical reaction rates. The ratio of the slope versus the roughness of the energy landscape becomes a quantitative measure of robustness and stability of the network. Furthermore, we quantify the dissipation cost of this nonequilibrium system through entropy production, caused by the nonequilibrium flux in the system. We found that a lower dissipation cost corresponds to a more robust network. This least dissipation property might provide a design principle for robust and functional networks. Finally, we find the possibility of bistable and oscillatory-like solutions, which are important for cell fate decisions, upon perturbations. The method described here can be used in a variety of biological networks. PMID:18420822

  18. Geometric phase transition in the cellular network of the pancreatic islets may underlie the onset of type 1diabetes

    NASA Astrophysics Data System (ADS)

    Wang, Xujing

    Living systems are characterized by complexity in structure and emergent dynamic orders. In many aspects the onset of a chronic disease resembles phase transition in a dynamic system: quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. In this study we investigate this idea in a real example, the insulin-producing pancreatic islet β-cells and the onset of type 1 diabetes. Within each islet, the β-cells are electrically coupled to each other, and function as a network with synchronized actions. Using percolation theory we show how normal islet function is intrinsically linked to network connectivity, and the critical point where the islet cellular network loses site percolation, is consistent with laboratory and clinical observations of the threshold β-cell loss that causes islet functional failure. Numerical simulations confirm that the islet cellular network needs to be percolated for β-cells to synchronize. Furthermore, the interplay between site percolation and bond strength predicts the existence of a transient phase of islet functional recovery after disease onset and introduction of treatment, potentially explaining a long time mystery in the clinical study of type 1 diabetes: the honeymoon phenomenon. Based on these results, we hypothesized that the onset of T1D may be the result of a phase transition of the islet β-cell network. We further discuss the potential applications in identifying disease-driving factors, and the critical parameters that are predictive of disease onset.

  19. An asynchronous communication system based on the hyperchaotic system of 6th-order cellular neural network

    NASA Astrophysics Data System (ADS)

    Wang, Xingyuan; Xu, Bing; Luo, Chao

    2012-11-01

    This paper proposes a novel asynchronous communication scheme. Based on this scheme, a model using the hyperchaotic system of 6th-order Cellular Neural Network (CNN) is designed. This scheme enhances the security of asynchronous communication compared to the conventional ones. It is noteworthy that the proposed communication scheme does not depend on synchronization, and almost all chaotic systems can be involved in this scheme. Numerical simulations show the effectiveness of this scheme.

  20. Mechanical models of the cellular cytoskeletal network for the analysis of intracellular mechanical properties and force distributions: a review.

    PubMed

    Chen, Ting-Jung; Wu, Chia-Ching; Su, Fong-Chin

    2012-12-01

    The cytoskeleton, which is the major mechanical component of cells, supports the cell body and regulates the cellular motility to assist the cell in performing its biological functions. Several cytoskeletal network models have been proposed to investigate the mechanical properties of cells. This review paper summarizes these models with a focus on the prestressed cable network, the semi-flexible chain network, the open-cell foam, the tensegrity, and the granular models. The components, material parameters, types of connection joints, tension conditions, and the advantages and disadvantages of each model are evaluated from a structural and biological point of view. The underlying mechanisms that are associated with the morphological changes of spreading cells are expected to be simulated using a cytoskeletal model; however, it is still paid less attention most likely due to the lack of a suitable cytoskeletal model that can accurately model the spreading process. In this review article, the established cytoskeletal models are hoped to provide useful information for the development of future cytoskeletal models with different degrees of cell attachment for the study of the mechanical mechanisms underlying the cellular behaviors in response to external stimulations. PMID:23062682

  1. Position and Velocity Tracking in Cellular Networks Using the Kalman Filter

    SciTech Connect

    Olama, Mohammed M; Djouadi, Seddik M; Kuruganti, Phani Teja

    2009-01-01

    Access to the right information anytime, anywhere is becoming the new driving force for the information technology revolution. The 'right' information's relevance is based on the user's profile and his/her current geographical position and/or time. Location Based Service (LBS) is an innovative technology that provides information or makes information available based on the geographical location of the mobile user. Analysts predict that LBSs will lead to new applications, generating billions of US dollars worldwide (Leite, 2001; Searle, 2001). The need for an efficient and accurate mobile station (MS) positioning system is growing day by day. The ability to pinpoint the location of an individual has an obvious and vital value in the context of emergency services (Chan, 2003; Olama et al., 2008). Pinpointing the location of people and other valuable assets also opens the door to a new world of previously unimagined information services and m-commerce probabilities. For example, availability of services like 'Where is the nearest ATM?', 'Check traffic conditions on the highway on my route', 'Find a parking lot nearby', as well as answers to 'Where is my advisor?', and 'Where is my car?' will be an everyday rule in our lives (Charalambous & Panayiotou, 2004). A technology independent LBS architecture can be considered as comprised by three main parts (Girodon, 2002): A user requesting information, a mobile network operator and its partners, and several content providers (e.g. data, maps). The subscriber requests a personalized service dependant on his geographic location. The system will ask the Location Services Manager (which is in charge of handling requests, i.e., send/receive to the Location Calculator and the Content Providers) to pinpoint the location of the mobile. The Location Services Manager (LSM), using the Location Calculator, will ask the Content Provider (CP) to supply qualified information according to the mobile's geographical position. The LSM will

  2. Comparative analysis of Salmonella susceptibility and tolerance to the biocide chlorhexidine identifies a complex cellular defense network.

    PubMed

    Condell, Orla; Power, Karen A; Händler, Kristian; Finn, Sarah; Sheridan, Aine; Sergeant, Kjell; Renaut, Jenny; Burgess, Catherine M; Hinton, Jay C D; Nally, Jarlath E; Fanning, Séamus

    2014-01-01

    Chlorhexidine is one of the most widely used biocides in health and agricultural settings as well as in the modern food industry. It is a cationic biocide of the biguanide class. Details of its mechanism of action are largely unknown. The frequent use of chlorhexidine has been questioned recently, amidst concerns that an overuse of this compound may select for bacteria displaying an altered susceptibility to antimicrobials, including clinically important anti-bacterial agents. We generated a Salmonella enterica serovar Typhimurium isolate (ST24(CHX)) that exhibited a high-level tolerant phenotype to chlorhexidine, following several rounds of in vitro selection, using sub-lethal concentrations of the biocide. This mutant showed altered suceptibility to a panel of clinically important antimicrobial compounds. Here we describe a genomic, transcriptomic, proteomic, and phenotypic analysis of the chlorhexidine tolerant S. Typhimurium compared with its isogenic sensitive progenitor. Results from this study describe a chlorhexidine defense network that functions in both the reference chlorhexidine sensitive isolate and the tolerant mutant. The defense network involved multiple cell targets including those associated with the synthesis and modification of the cell wall, the SOS response, virulence, and a shift in cellular metabolism toward anoxic pathways, some of which were regulated by CreB and Fur. In addition, results indicated that chlorhexidine tolerance was associated with more extensive modifications of the same cellular processes involved in this proposed network, as well as a divergent defense response involving the up-regulation of additional targets such as the flagellar apparatus and an altered cellular phosphate metabolism. These data show that sub-lethal concentrations of chlorhexidine induce distinct changes in exposed Salmonella, and our findings provide insights into the mechanisms of action and tolerance to this biocidal agent. PMID:25136333

  3. Comparative analysis of Salmonella susceptibility and tolerance to the biocide chlorhexidine identifies a complex cellular defense network

    PubMed Central

    Condell, Orla; Power, Karen A.; Händler, Kristian; Finn, Sarah; Sheridan, Aine; Sergeant, Kjell; Renaut, Jenny; Burgess, Catherine M.; Hinton, Jay C. D.; Nally, Jarlath E.; Fanning, Séamus

    2014-01-01

    Chlorhexidine is one of the most widely used biocides in health and agricultural settings as well as in the modern food industry. It is a cationic biocide of the biguanide class. Details of its mechanism of action are largely unknown. The frequent use of chlorhexidine has been questioned recently, amidst concerns that an overuse of this compound may select for bacteria displaying an altered susceptibility to antimicrobials, including clinically important anti-bacterial agents. We generated a Salmonella enterica serovar Typhimurium isolate (ST24CHX) that exhibited a high-level tolerant phenotype to chlorhexidine, following several rounds of in vitro selection, using sub-lethal concentrations of the biocide. This mutant showed altered suceptibility to a panel of clinically important antimicrobial compounds. Here we describe a genomic, transcriptomic, proteomic, and phenotypic analysis of the chlorhexidine tolerant S. Typhimurium compared with its isogenic sensitive progenitor. Results from this study describe a chlorhexidine defense network that functions in both the reference chlorhexidine sensitive isolate and the tolerant mutant. The defense network involved multiple cell targets including those associated with the synthesis and modification of the cell wall, the SOS response, virulence, and a shift in cellular metabolism toward anoxic pathways, some of which were regulated by CreB and Fur. In addition, results indicated that chlorhexidine tolerance was associated with more extensive modifications of the same cellular processes involved in this proposed network, as well as a divergent defense response involving the up-regulation of additional targets such as the flagellar apparatus and an altered cellular phosphate metabolism. These data show that sub-lethal concentrations of chlorhexidine induce distinct changes in exposed Salmonella, and our findings provide insights into the mechanisms of action and tolerance to this biocidal agent. PMID:25136333

  4. Delay-dependent exponential passivity of uncertain cellular neural networks with discrete and distributed time-varying delays.

    PubMed

    Du, Yuanhua; Zhong, Shouming; Xu, Jia; Zhou, Nan

    2015-05-01

    This paper is concerned with the delay-dependent exponential passivity analysis issue for uncertain cellular neural networks with discrete and distributed time-varying delays. By decomposing the delay interval into multiple equidistant subintervals and multiple nonuniform subintervals, a suitable augmented Lyapunov-Krasovskii functionals are constructed on these intervals. A set of novel sufficient conditions are obtained to guarantee the exponential passivity analysis issue for the considered system. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed results. PMID:25702046

  5. Exact quantification of cellular robustness in genome-scale metabolic networks

    PubMed Central

    Gerstl, Matthias P.; Klamt, Steffen; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2016-01-01

    Motivation: Robustness, the ability of biological networks to uphold their functionality in spite of perturbations, is a key characteristic of all living systems. Although several theoretical approaches have been developed to formalize robustness, it still eludes an exact quantification. Here, we present a rigorous and quantitative approach for the structural robustness of metabolic networks by measuring their ability to tolerate random reaction (or gene) knockouts. Results: In analogy to reliability theory, based on an explicit consideration of all possible knockout sets, we exactly quantify the probability of failure for a given network function (e.g. growth). This measure can be computed if the network’s minimal cut sets (MSCs) are known. We show that even in genome-scale metabolic networks the probability of (network) failure can be reliably estimated from MSCs with lowest cardinalities. We demonstrate the applicability of our theory by analyzing the structural robustness of multiple Enterobacteriaceae and Blattibacteriaceae and show a dramatically low structural robustness for the latter. We find that structural robustness develops from the ability to proliferate in multiple growth environments consistent with experimentally found knowledge. Conclusion: The probability of (network) failure provides thus a reliable and easily computable measure of structural robustness and redundancy in (genome-scale) metabolic networks. Availability and implementation: Source code is available under the GNU General Public License at https://github.com/mpgerstl/networkRobustnessToolbox. Contact: juergen.zanghellini@boku.ac.at Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26543173

  6. The Speckle Noise Reduction and the Boundary Enhancement on Medical Ultrasound Images using the Cellular Neural Networks

    NASA Astrophysics Data System (ADS)

    Park, Hyunkyung; Miyazaki, Ryota; Nishimura, Toshihiro; Tamaki, Yasuhiro

    The purpose is to remove the speckle noise and to emphasize the boundary of a tumor by filtering based on the intensity difference in the medical ultrasound images. The proposed method is evaluated using numerical phantom simulating ultrasound B-mode images, and the effect is confirmed by applying to medical ultrasound images. Therefore, some important features such as tissue boundaries and small tumors may be overlooked. A CNN (cellular neural networks) for the speckle reduction and the edge enhancement are proposed in this paper. A CNN which is a kind of recurrent neural network can deal with images by the weight of neurons called a cell. It could be obtained more detail images recognition compared with the previous studies. A determination template parameters of the CNN for ultrasound image processing is discussed. The experimental results show effectiveness of applying the proposed method to boundary enhancement and the speckle reduction of medical ultrasound image.

  7. Multi-Hop Link Capacity of Multi-Route Multi-Hop MRC Diversity for a Virtual Cellular Network

    NASA Astrophysics Data System (ADS)

    Daou, Imane; Kudoh, Eisuke; Adachi, Fumiyuki

    In virtual cellular network (VCN), proposed for high-speed mobile communications, the signal transmitted from a mobile terminal is received by some wireless ports distributed in each virtual cell and relayed to the central port that acts as a gateway to the core network. In this paper, we apply the multi-route MHMRC diversity in order to decrease the transmit power and increase the multi-hop link capacity. The transmit power, the interference power and the link capacity are evaluated for DS-CDMA multi-hop VCN by computer simulation. The multi-route MHMRC diversity can be applied to not only DS-CDMA but also other access schemes (i. e. MC-CDMA, OFDM, etc.).

  8. Mitigating Handoff Call Dropping in Wireless Cellular Networks: A Call Admission Control Technique

    NASA Astrophysics Data System (ADS)

    Ekpenyong, Moses Effiong; Udoh, Victoria Idia; Bassey, Udoma James

    2016-06-01

    Handoff management has been an important but challenging issue in the field of wireless communication. It seeks to maintain seamless connectivity of mobile users changing their points of attachment from one base station to another. This paper derives a call admission control model and establishes an optimal step-size coefficient (k) that regulates the admission probability of handoff calls. An operational CDMA network carrier was investigated through the analysis of empirical data collected over a period of 1 month, to verify the performance of the network. Our findings revealed that approximately 23 % of calls in the existing system were lost, while 40 % of the calls (on the average) were successfully admitted. A simulation of the proposed model was then carried out under ideal network conditions to study the relationship between the various network parameters and validate our claim. Simulation results showed that increasing the step-size coefficient degrades the network performance. Even at optimum step-size (k), the network could still be compromised in the presence of severe network crises, but our model was able to recover from these problems and still functions normally.

  9. Beta Cell Formation in vivo Through Cellular Networking, Integration and Processing (CNIP) in Wild Type Adult Mice.

    PubMed

    Doiron, Bruno; Hu, Wenchao; DeFronzo, Ralph A

    2016-01-01

    Insulin replacement therapy is essential in type 1 diabetic individuals and is required in ~40- 50% of type 2 diabetics during their lifetime. Prior attempts at beta cell regeneration have relied upon pancreatic injury to induce beta cell proliferation, dedifferentiation and activation of the embryonic pathway, or stem cell replacement. We report an alternative method to transform adult non-stem (somatic) cells into pancreatic beta cells. The Cellular Networking, Integration and Processing (CNIP) approach targets cellular mechanisms involved in pancreatic function in the organ's adult state and utilizes a synergistic mechanism that integrates three important levels of cellular regulation to induce beta cell formation: (i) glucose metabolism, (ii) membrane receptor function, and (iii) gene transcription. The aim of the present study was to induce pancreatic beta cell formation in vivo in adult animals without stem cells and without dedifferentiating cells to recapitulate the embryonic pathway as previously published (1-3). Our results employing CNIP demonstrate that: (i) insulin secreting cells can be generated in adult pancreatic tissue in vivo and circumvent the problem of generating endocrine (glucagon and somatostatin) cells that exert deleterious effects on glucose homeostasis, and (ii) longterm normalization of glucose tolerance and insulin secretion can be achieved in a wild type diabetic mouse model. The CNIP cocktail has the potential to be used as a preventative or therapeutic treatment or cure for both type 1 and type 2 diabetes. PMID:26696016

  10. A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

    PubMed

    Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

    2016-03-01

    Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle. PMID:27087101

  11. The dynamic and geometric phase transition in the cellular network of pancreatic islet

    NASA Astrophysics Data System (ADS)

    Wang, Xujing

    2013-03-01

    The pancreatic islet is a micro-organ that contains several thousands of endocrine cells, majority of which being the insulin releasing β - cells . - cellsareexcitablecells , andarecoupledtoeachother through gap junctional channels. Here, using percolation theory, we investigate the role of network structure in determining the dynamics of the β-cell network. We show that the β-cell synchronization depends on network connectivity. More specifically, as the site occupancy is reducing, initially the β-cell synchronization is barely affected, until it reaches around a critical value, where the synchronization exhibit a sudden rapid decline, followed by an slow exponential tail. This critical value coincides with the critical site open probability for percolation transition. The dependence over bond strength is similar, exhibiting critical-behavior like dependence around a certain value of bond strength. These results suggest that the β-cell network undergoes a dynamic phase transition when the network is percolated. We further apply the findings to study diabetes. During the development of diabetes, the β - cellnetworkconnectivitydecreases . Siteoccupancyreducesfromthe reducing β-cell mass, and the bond strength is increasingly impaired from β-cell stress and chronic hyperglycemia. We demonstrate that the network dynamics around the percolation transition explain the disease dynamics around onset, including a long time mystery in diabetes, the honeymoon phenomenon.

  12. A modified size-dependent core-shell model and its application in the wave propagation of square cellular networks

    NASA Astrophysics Data System (ADS)

    Xu, Xiao-Jian; Wang, Ya-Chuan; Wang, Bo; Zhang, Kai

    2016-06-01

    We propose a modified core-shell model to depict the size-dependent elastic properties of materials with several different cross-sections. By using the Young-Laplace equation, a modified Euler-Bernoulli equation, which has taken a power-law relation between the bulk and surface moduli into account, is derived. A finite element method of the modified Euler-Bernoulli equation is formulated, and assembled to investigate the dispersion relations of the infinite two-dimensional periodic square cellular networks. The effectiveness of the proposed core-shell model is verified by comparing with results of the experiments and the molecular dynamics simulations available in the literature. Numerical results show that surface effects play an important role on the cellular networks with small diameters, large aspect ratios and high wave frequencies. Meanwhile, the analytical expressions for the size-dependent elastic modulus may be useful for the study of the size-dependent elasticity of materials and structures at small length scales.

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

    PubMed

    Chen, Po-Wei; Chen, Bor-Sen

    2011-08-01

    Naturally, a cellular network consisted of a large amount of interacting cells is complex. These cells have to be synchronized in order to emerge their phenomena for some biological purposes. However, the inherently stochastic intra and intercellular interactions are noisy and delayed from biochemical processes. In this study, a robust synchronization scheme is proposed for a nonlinear stochastic time-delay coupled cellular network (TdCCN) in spite of the time-varying process delay and intracellular parameter perturbations. Furthermore, a nonlinear stochastic noise filtering ability is also investigated for this synchronized TdCCN against stochastic intercellular and environmental disturbances. Since it is very difficult to solve a robust synchronization problem with the Hamilton-Jacobi inequality (HJI) matrix, a linear matrix inequality (LMI) is employed to solve this problem via the help of a global linearization method. Through this robust synchronization analysis, we can gain a more systemic insight into not only the robust synchronizability but also the noise filtering ability of TdCCN under time-varying process delays, intracellular perturbations and intercellular disturbances. The measures of robustness and noise filtering ability of a synchronized TdCCN have potential application to the designs of neuron transmitters, on-time mass production of biochemical molecules, and synthetic biology. Finally, a benchmark of robust synchronization design in Escherichia coli repressilators is given to confirm the effectiveness of the proposed methods. PMID:21624379

  14. Coverage Extension and Balancing the Transmitted Power of the Moving Relay Node at LTE-A Cellular Network

    PubMed Central

    Aldhaibani, Jaafar A.; Yahya, Abid; Ahmad, R. Badlishah

    2014-01-01

    The poor capacity at cell boundaries is not enough to meet the growing demand and stringent design which required high capacity and throughput irrespective of user's location in the cellular network. In this paper, we propose new schemes for an optimum fixed relay node (RN) placement in LTE-A cellular network to enhance throughput and coverage extension at cell edge region. The proposed approach mitigates interferences between all nodes and ensures optimum utilization with the optimization of transmitted power. Moreover, we proposed a new algorithm to balance the transmitted power of moving relay node (MR) over cell size and providing required SNR and throughput at the users inside vehicle along with reducing the transmitted power consumption by MR. The numerical analysis along with the simulation results indicates that an improvement in capacity for users is 40% increment at downlink transmission from cell capacity. Furthermore, the results revealed that there is saving nearly 75% from transmitted power in MR after using proposed balancing algorithm. ATDI simulator was used to verify the numerical results, which deals with real digital cartographic and standard formats for terrain. PMID:24672378

  15. The role of glutathione reductase and related enzymes on cellular redox homoeostasis network.

    PubMed

    Couto, Narciso; Wood, Jennifer; Barber, Jill

    2016-06-01

    In this review article we examine the role of glutathione reductase in the regulation, modulation and maintenance of cellular redox homoeostasis. Glutathione reductase is responsible for maintaining the supply of reduced glutathione; one of the most abundant reducing thiols in the majority of cells. In its reduced form, glutathione plays key roles in the cellular control of reactive oxygen species. Reactive oxygen species act as intracellular and extracellular signalling molecules and complex cross talk between levels of reactive oxygen species, levels of oxidised and reduced glutathione and other thiols, and antioxidant enzymes such as glutathione reductase determine the most suitable conditions for redox control within a cell or for activation of programmed cell death. Additionally, we discuss the translation and expression of glutathione reductase in a number of organisms including yeast and humans. In yeast and human cells, a single gene expresses more than one form of glutathione reductase, destined for residence in the cytoplasm or for translocation to different organelles; in plants, however, two genes encoding this protein have been described. In general, insects and kinetoplastids (a group of protozoa, including Plasmodia and Trypanosoma) do not express glutathione reductase or glutathione biosynthetic enzymes. Instead, they express either the thioredoxin system or the trypanothione system. The thioredoxin system is also present in organisms that have the glutathione system and there may be overlapping functions with cross-talk between the two systems. Finally we evaluate therapeutic targets to overcome oxidative stress associated cellular disorders. PMID:26923386

  16. Analysis of the local organization and dynamics of cellular actin networks

    PubMed Central

    Luo, Weiwei; Yu, Cheng-han; Lieu, Zi Zhao; Allard, Jun; Mogilner, Alex; Sheetz, Michael P.

    2013-01-01

    A ctin filaments, with the aid of multiple accessory proteins, self-assemble into a variety of network patterns. We studied the organization and dynamics of the actin network in nonadhesive regions of cells bridging fibronectin-coated adhesive strips. The network was formed by actin nodes associated with and linked by myosin II and containing the formin disheveled-associated activator of morphogenesis 1 (DAAM1) and the cross-linker filamin A (FlnA). After Latrunculin A (LatA) addition, actin nodes appeared to be more prominent and demonstrated drift-diffusion motion. Superresolution microscopy revealed that, in untreated cells, DAAM1 formed patches with a similar spatial arrangement to the actin nodes. Node movement (diffusion coefficient and velocity) in LatA-treated cells was dependent on the level and activity of myosin IIA, DAAM1, and FlnA. Based on our results, we developed a computational model of the dynamic formin-filamin-actin asters that can self-organize into a contractile actomyosin network. We suggest that such networks are critical for connecting distant parts of the cell to maintain the mechanical coherence of the cytoplasm. PMID:24081490

  17. Analysis of the local organization and dynamics of cellular actin networks.

    PubMed

    Luo, Weiwei; Yu, Cheng-han; Lieu, Zi Zhao; Allard, Jun; Mogilner, Alex; Sheetz, Michael P; Bershadsky, Alexander D

    2013-09-30

    Actin filaments, with the aid of multiple accessory proteins, self-assemble into a variety of network patterns. We studied the organization and dynamics of the actin network in nonadhesive regions of cells bridging fibronectin-coated adhesive strips. The network was formed by actin nodes associated with and linked by myosin II and containing the formin disheveled-associated activator of morphogenesis 1 (DAAM1) and the cross-linker filamin A (FlnA). After Latrunculin A (LatA) addition, actin nodes appeared to be more prominent and demonstrated drift-diffusion motion. Superresolution microscopy revealed that, in untreated cells, DAAM1 formed patches with a similar spatial arrangement to the actin nodes. Node movement (diffusion coefficient and velocity) in LatA-treated cells was dependent on the level and activity of myosin IIA, DAAM1, and FlnA. Based on our results, we developed a computational model of the dynamic formin-filamin-actin asters that can self-organize into a contractile actomyosin network. We suggest that such networks are critical for connecting distant parts of the cell to maintain the mechanical coherence of the cytoplasm. PMID:24081490

  18. Rainfall measurements from cellular networks microwave links : an alternative ground reference for satellite validation and hydrology in Africa .

    NASA Astrophysics Data System (ADS)

    Gosset, Marielle; cazenave, frederic; Zougmore, françois; Doumounia, Ali; kacou, Modeste

    2015-04-01

    In many part of the Tropics the ground based gauge networks are sparse, often degrading and accessing this data for monitoring rainfall or for validating satellite products is sometime difficult. Here, an alternative rainfall measuring technique is proposed and tested in West Africa. It is based on using commercial microwave links from cellular telephone networks to detect and quantify rainfall. Rainfall monitoring based on commercial terrestrial microwave links has been tested for the first time in Burkina Faso, in Sahel. The rainfall regime is characterized by intense rainfall intensities brought by mesoscale Convective systems (MCS), generated by deep organized convection. The region is subjected to drought as well as dramatic floods associated with the intense rainfall provided by a few MCSs. The hydrometeorological risk is increasing and need to be monitored. In collaboration with the national cellular phone operator, Telecel Faso, the attenuation on 29 km long microwave links operating at 7 GHz was monitored at 1s time rate for the monsoon season 2012. The time series of attenuation is transformed into rain rates and compared with rain gauge data. The method is successful in quantifying rainfall: 95% of the rainy days are detected. The correlation with the daily raingauge series is 0.8 and the season bias is 5%. The correlation at the 5 min time step within each event is also high. We will present the quantitative results, discuss the uncertainties and compare the time series and the 2D maps with those derived from a polarimetric radar. The results demonstrate the potential interest of exploiting national and regional wireless telecommunication networks to provide rainfall maps for various applications : urban hydrology, agro-hydrological risk monitoring, satellite validation and development of combined rainfall products. We will also present the outcome of the first international Rain Cell Africa workshop held in Ouagadougou early 2015.

  19. 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

  20. 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.

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

    PubMed

    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

  2. Actin-binding proteins: the long road to understanding the dynamic landscape of cellular actin networks.

    PubMed

    Lappalainen, Pekka

    2016-08-15

    The actin cytoskeleton supports a vast number of cellular processes in nonmuscle cells. It is well established that the organization and dynamics of the actin cytoskeleton are controlled by a large array of actin-binding proteins. However, it was only 40 years ago that the first nonmuscle actin-binding protein, filamin, was identified and characterized. Filamin was shown to bind and cross-link actin filaments into higher-order structures and contribute to phagocytosis in macrophages. Subsequently many other nonmuscle actin-binding proteins were identified and characterized. These proteins regulate almost all steps of the actin filament assembly and disassembly cycles, as well as the arrangement of actin filaments into diverse three-dimensional structures. Although the individual biochemical activities of most actin-regulatory proteins are relatively well understood, knowledge of how these proteins function together in a common cytoplasm to control actin dynamics and architecture is only beginning to emerge. Furthermore, understanding how signaling pathways and mechanical cues control the activities of various actin-binding proteins in different cellular, developmental, and pathological processes will keep researchers busy for decades. PMID:27528696

  3. Biological pattern generation: the cellular and computational logic of networks in motion.

    PubMed

    Grillner, Sten

    2006-12-01

    In 1900, Ramón y Cajal advanced the neuron doctrine, defining the neuron as the fundamental signaling unit of the nervous system. Over a century later, neurobiologists address the circuit doctrine: the logic of the core units of neuronal circuitry that control animal behavior. These are circuits that can be called into action for perceptual, conceptual, and motor tasks, and we now need to understand whether there are coherent and overriding principles that govern the design and function of these modules. The discovery of central motor programs has provided crucial insight into the logic of one prototypic set of neural circuits: those that generate motor patterns. In this review, I discuss the mode of operation of these pattern generator networks and consider the neural mechanisms through which they are selected and activated. In addition, I will outline the utility of computational models in analysis of the dynamic actions of these motor networks. PMID:17145498

  4. Cellular and circuit models of increased resting-state network gamma activity in schizophrenia.

    PubMed

    White, R S; Siegel, S J

    2016-05-01

    Schizophrenia (SCZ) is a disorder characterized by positive symptoms (hallucinations, delusions), negative symptoms (blunted affect, alogia, reduced sociability, and anhedonia), as well as persistent cognitive deficits (memory, concentration, and learning). While the biology underlying subjective experiences is difficult to study, abnormalities in electroencephalographic (EEG) measures offer a means to dissect potential circuit and cellular changes in brain function. EEG is indispensable for studying cerebral information processing due to the introduction of techniques for the decomposition of event-related activity into its frequency components. Specifically, brain activity in the gamma frequency range (30-80Hz) is thought to underlie cognitive function and may be used as an endophenotype to aid in diagnosis and treatment of SCZ. In this review we address evidence indicating that there is increased resting-state gamma power in SCZ. We address how modeling this aspect of the illness in animals may help treatment development as well as providing insights into the etiology of SCZ. PMID:26577758

  5. Mobility-Aware Caching and Computation Offloading in 5G Ultra-Dense Cellular Networks

    PubMed Central

    Chen, Min; Hao, Yixue; Qiu, Meikang; Song, Jeungeun; Wu, Di; Humar, Iztok

    2016-01-01

    Recent trends show that Internet traffic is increasingly dominated by content, which is accompanied by the exponential growth of traffic. To cope with this phenomena, network caching is introduced to utilize the storage capacity of diverse network devices. In this paper, we first summarize four basic caching placement strategies, i.e., local caching, Device-to-Device (D2D) caching, Small cell Base Station (SBS) caching and Macrocell Base Station (MBS) caching. However, studies show that so far, much of the research has ignored the impact of user mobility. Therefore, taking the effect of the user mobility into consideration, we proposes a joint mobility-aware caching and SBS density placement scheme (MS caching). In addition, differences and relationships between caching and computation offloading are discussed. We present a design of a hybrid computation offloading and support it with experimental results, which demonstrate improved performance in terms of energy cost. Finally, we discuss the design of an incentive mechanism by considering network dynamics, differentiated user’s quality of experience (QoE) and the heterogeneity of mobile terminals in terms of caching and computing capabilities. PMID:27347975

  6. Mobility-Aware Caching and Computation Offloading in 5G Ultra-Dense Cellular Networks.

    PubMed

    Chen, Min; Hao, Yixue; Qiu, Meikang; Song, Jeungeun; Wu, Di; Humar, Iztok

    2016-01-01

    Recent trends show that Internet traffic is increasingly dominated by content, which is accompanied by the exponential growth of traffic. To cope with this phenomena, network caching is introduced to utilize the storage capacity of diverse network devices. In this paper, we first summarize four basic caching placement strategies, i.e., local caching, Device-to-Device (D2D) caching, Small cell Base Station (SBS) caching and Macrocell Base Station (MBS) caching. However, studies show that so far, much of the research has ignored the impact of user mobility. Therefore, taking the effect of the user mobility into consideration, we proposes a joint mobility-aware caching and SBS density placement scheme (MS caching). In addition, differences and relationships between caching and computation offloading are discussed. We present a design of a hybrid computation offloading and support it with experimental results, which demonstrate improved performance in terms of energy cost. Finally, we discuss the design of an incentive mechanism by considering network dynamics, differentiated user's quality of experience (QoE) and the heterogeneity of mobile terminals in terms of caching and computing capabilities. PMID:27347975

  7. Cellular location and major terminal networks of the orexinergic system in the brain of two megachiropterans.

    PubMed

    Dell, Leigh-Anne; Kruger, Jean-Leigh; Pettigrew, John D; Manger, Paul R

    2013-11-01

    The present study describes the distribution of orexin-A immunoreactive neurons and their terminal networks in the brains of two species of megachiropterans. In general the organization of the orexinergic system in the mammalian brain is conserved across species, but as one of two groups of mammals that fly and have a high metabolic rate, it was of interest to determine whether there were any specific differences in the organization of this system in the megachiropterans. Orexinergic neurons were limited in distribution to the hypothalamus, and formed three distinct clusters, or nuclei, a main cluster with a perifornical location, a zona incerta cluster in the dorsolateral hypothalamus and an optic tract cluster in the ventrolateral hypothalamus. The nuclear parcellation of the orexinergic system in the megachiropterans is similar to that seen in many mammals, but differs from the microchiropterans where the optic tract cluster is absent. The terminal networks of the orexinergic neurons in the megachiropterans was similar to that seen in a range of mammalian species, with significant terminal networks being found in the hypothalamus, cholinergic pedunculopontine and laterodorsal tegemental nuclei, the noradrenergic locus coeruleus complex, all serotonergic nuclei, the paraventricular nuclei of the epithalamus and adjacent to the habenular nuclei. While the megachiropteran orexinergic system is typically mammalian in form, it does differ from that reported for microchiropterans, and thus provides an additional neural character arguing for independent evolution of these two chiropteran suborders. PMID:24041616

  8. From molecular interaction to acute promyelocytic leukemia: Calculating leukemogenesis and remission from endogenous molecular-cellular network.

    PubMed

    Yuan, Ruoshi; Zhu, Xiaomei; Radich, Jerald P; Ao, Ping

    2016-01-01

    Acute promyelocytic leukemia (APL) remains the best example of a malignancy that can be cured clinically by differentiation therapy. We demonstrate that APL may emerge from a dynamical endogenous molecular-cellular network obtained from normal, non-cancerous molecular interactions such as signal transduction and translational regulation under physiological conditions. This unifying framework, which reproduces APL, normal progenitor, and differentiated granulocytic phenotypes as different robust states from the network dynamics, has the advantage to study transition between these states, i.e. critical drivers for leukemogenesis and targets for differentiation. The simulation results quantitatively reproduce microarray profiles of NB4 and HL60 cell lines in response to treatment and normal neutrophil differentiation, and lead to new findings such as biomarkers for APL and additional molecular targets for arsenic trioxide therapy. The modeling shows APL and normal states mutually suppress each other, both in "wiring" and in dynamical cooperation. Leukemogenesis and recovery under treatment may be a consequence of spontaneous or induced transitions between robust states, through "passes" or "dragging" by drug effects. Our approach rationalizes leukemic complexity and constructs a platform towards extending differentiation therapy by performing "dry" molecular biology experiments. PMID:27098097

  9. From molecular interaction to acute promyelocytic leukemia: Calculating leukemogenesis and remission from endogenous molecular-cellular network

    PubMed Central

    Yuan, Ruoshi; Zhu, Xiaomei; Radich, Jerald P.; Ao, Ping

    2016-01-01

    Acute promyelocytic leukemia (APL) remains the best example of a malignancy that can be cured clinically by differentiation therapy. We demonstrate that APL may emerge from a dynamical endogenous molecular-cellular network obtained from normal, non-cancerous molecular interactions such as signal transduction and translational regulation under physiological conditions. This unifying framework, which reproduces APL, normal progenitor, and differentiated granulocytic phenotypes as different robust states from the network dynamics, has the advantage to study transition between these states, i.e. critical drivers for leukemogenesis and targets for differentiation. The simulation results quantitatively reproduce microarray profiles of NB4 and HL60 cell lines in response to treatment and normal neutrophil differentiation, and lead to new findings such as biomarkers for APL and additional molecular targets for arsenic trioxide therapy. The modeling shows APL and normal states mutually suppress each other, both in “wiring” and in dynamical cooperation. Leukemogenesis and recovery under treatment may be a consequence of spontaneous or induced transitions between robust states, through “passes” or “dragging” by drug effects. Our approach rationalizes leukemic complexity and constructs a platform towards extending differentiation therapy by performing “dry” molecular biology experiments. PMID:27098097

  10. TRPV1 mediates cellular uptake of anandamide and thus promotes endothelial cell proliferation and network-formation

    PubMed Central

    Hofmann, Nicole A.; Barth, Sonja; Waldeck-Weiermair, Markus; Klec, Christiane; Strunk, Dirk; Malli, Roland; Graier, Wolfgang F.

    2014-01-01

    ABSTRACT Anandamide (N-arachidonyl ethanolamide, AEA) is an endogenous cannabinoid that is involved in various pathological conditions, including cardiovascular diseases and tumor-angiogenesis. Herein, we tested the involvement of classical cannabinoid receptors (CBRs) and the Ca2+-channel transient receptor potential vanilloid 1 (TRPV1) on cellular AEA uptake and its effect on endothelial cell proliferation and network-formation. Uptake of the fluorescence-labeled anandamide (SKM4-45-1) was monitored in human endothelial colony-forming cells (ECFCs) and a human endothelial-vein cell line (EA.hy926). Involvement of the receptors during AEA translocation was determined by selective pharmacological inhibition (AM251, SR144528, CID16020046, SB366791) and molecular interference by TRPV1-selective siRNA-mediated knock-down and TRPV1 overexpression. We show that exclusively TRPV1 contributes essentially to AEA transport into endothelial cells in a Ca2+-independent manner. This TRPV1 function is a prerequisite for AEA-induced endothelial cell proliferation and network-formation. Our findings point to a so far unknown moonlighting function of TRPV1 as Ca2+-independent contributor/regulator of AEA uptake. We propose TRPV1 as representing a promising target for development of pharmacological therapies against AEA-triggered endothelial cell functions, including their stimulatory effect on tumor-angiogenesis. PMID:25395667

  11. The p53 network: Cellular and systemic DNA damage responses in aging and cancer

    PubMed Central

    Reinhardt, H. Christian; Schumacher, Björn

    2014-01-01

    Genome instability contributes to cancer development and accelerates age-related pathologies as evidenced by a variety of congenital cancer susceptibility and progeroid syndromes that are caused by defects in genome maintenance mechanisms. DNA damage response pathways that are mediated through the tumor suppressor p53 play an important role in the cell intrinsic responses to genome instability, including a transient cell cycle arrest, senescence and apoptosis. Both senescence and apoptosis are powerful tumor suppressive pathways preventing the uncontrolled proliferation of transformed cells. However, both pathways can potentially deplete stem and progenitor cell pools, thus promoting tissue degeneration and organ failure, which are both hallmarks of aging. p53 signaling is also involved in mediating non-cell autonomous interactions with the innate immune system and in the systemic adjustments during the aging process. The network of p53 target genes thus functions as an important regulator of cancer prevention and the physiology of aging. PMID:22265392

  12. Evolving gene regulation networks into cellular networks guiding adaptive behavior: an outline how single cells could have evolved into a centralized neurosensory system

    PubMed Central

    Fritzsch, Bernd; Jahan, Israt; Pan, Ning; Elliott, Karen L.

    2014-01-01

    Understanding the evolution of the neurosensory system of man, able to reflect on its own origin, is one of the major goals of comparative neurobiology. Details of the origin of neurosensory cells, their aggregation into central nervous systems and associated sensory organs, their localized patterning into remarkably different cell types aggregated into variably sized parts of the central nervous system begin to emerge. Insights at the cellular and molecular level begin to shed some light on the evolution of neurosensory cells, partially covered in this review. Molecular evidence suggests that high mobility group (HMG) proteins of pre-metazoans evolved into the definitive Sox [SRY (sex determining region Y)-box] genes used for neurosensory precursor specification in metazoans. Likewise, pre-metazoan basic helix-loop-helix (bHLH) genes evolved in metazoans into the group A bHLH genes dedicated to neurosensory differentiation in bilaterians. Available evidence suggests that the Sox and bHLH genes evolved a cross-regulatory network able to synchronize expansion of precursor populations and their subsequent differentiation into novel parts of the brain or sensory organs. Molecular evidence suggests metazoans evolved patterning gene networks early and not dedicated to neuronal development. Only later in evolution were these patterning gene networks tied into the increasing complexity of diffusible factors, many of which were already present in pre-metazoans, to drive local patterning events. It appears that the evolving molecular basis of neurosensory cell development may have led, in interaction with differentially expressed patterning genes, to local network modifications guiding unique specializations of neurosensory cells into sensory organs and various areas of the central nervous system. PMID:25416504

  13. A Dynamic Programming Approach for Base Station Sleeping in Cellular Networks

    NASA Astrophysics Data System (ADS)

    Gong, Jie; Zhou, Sheng; Niu, Zhisheng

    The energy consumption of the information and communication technology (ICT) industry, which has become a serious problem, is mostly due to the network infrastructure rather than the mobile terminals. In this paper, we focus on reducing the energy consumption of base stations (BSs) by adjusting their working modes (active or sleep). Specifically, the objective is to minimize the energy consumption while satisfying quality of service (QoS, e.g., blocking probability) requirement and, at the same time, avoiding frequent mode switching to reduce signaling and delay overhead. The problem is modeled as a dynamic programming (DP) problem, which is NP-hard in general. Based on cooperation among neighboring BSs, a low-complexity algorithm is proposed to reduce the size of state space as well as that of action space. Simulations demonstrate that, with the proposed algorithm, the active BS pattern well meets the time variation and the non-uniform spatial distribution of system traffic. Moreover, the tradeoff between the energy saving from BS sleeping and the cost of switching is well balanced by the proposed scheme.

  14. Ultra-Porous Nanoparticle Networks: A Biomimetic Coating Morphology for Enhanced Cellular Response and Infiltration

    PubMed Central

    Nasiri, Noushin; Ceramidas, Anthony; Mukherjee, Shayanti; Panneerselvan, Anitha; Nisbet, David R.; Tricoli, Antonio

    2016-01-01

    Orthopedic treatments are amongst the most common cause of surgery and are responsible for a large share of global healthcare expenditures. Engineering materials that can hasten bone integration will improve the quality of life of millions of patients per year and reduce associated medical costs. Here, we present a novel hierarchical biomimetic coating that mimics the inorganic constituent of mammalian bones with the aim of improving osseointegration of metallic implants. We exploit the thermally-driven self-organization of metastable core-shell nanoparticles during their aerosol self-assembly to rapidly fabricate robust, ultra-porous nanoparticle networks (UNN) of crystalline hydroxyapatite (HAp). Comparative analysis of the response of osteoblast cells to the ultra-porous nanostructured HAp surfaces and to the spin coated HAp surfaces revealed superior osseointegrative properties of the UNN coatings with significant cell and filopodia infiltration. This flexible synthesis approach for the engineering of UNN HAp coatings on titanium implants provides a platform technology to study the bone-implant interface for improved osseointegration and osteoconduction. PMID:27076035

  15. Incorporation of aggrecan in interpenetrating network hydrogels to improve cellular performance for cartilage tissue engineering.

    PubMed

    Ingavle, Ganesh C; Frei, Anthony W; Gehrke, Stevin H; Detamore, Michael S

    2013-06-01

    Interpenetrating network (IPN) hydrogels were recently introduced to the cartilage tissue engineering literature, with the approach of encapsulating cells in thermally gelling agarose that is then soaked in a poly(ethylene glycol) diacrylate (PEGDA) solution, which is then photopolymerized. These IPNs possess significantly enhanced mechanical performance desirable for cartilage regeneration, potentially allowing patients to return to weight-bearing activities quickly after surgical implantation. In an effort to improve cell viability and performance, inspiration was drawn from previous studies that have elicited positive chondrogenic responses to aggrecan, the proteoglycan largely responsible for the compressive stiffness of cartilage. Aggrecan was incorporated into the IPNs in conservative concentrations (40 μg/mL), and its effect was contrasted with the incorporation of chondroitin sulfate (CS), the primary glycosaminoglycan associated with aggrecan. Aggrecan was incorporated by physical entrapment within agarose and methacrylated CS was incorporated by copolymerization with PEGDA. The IPNs incorporating aggrecan or CS exhibited over 50% viability with encapsulated chondrocytes after 6 weeks. Both aggrecan and CS improved cell viability by 15.6% and 20%, respectively, relative to pure IPNs at 6 weeks culture time. In summary, we have introduced the novel approach of including a raw material from cartilage, namely aggrecan, to serve as a bioactive signal to cells encapsulated in IPN hydrogels for cartilage tissue engineering, which led to improved performance of encapsulated chondrocytes. PMID:23379843

  16. Structurally Dynamic Cellular Networks as Models for Planck Scale Physics and the Quantum Vacuum

    NASA Astrophysics Data System (ADS)

    Requardt, Manfred

    Starting from the working hypothesis that both physics and the corresponding mathematics have to be described by means of discrete concepts on the Planck scale, one of the many problems one has to face in this enterprise is to find the discrete protoforms of the building blocks of our ordinary continuum physics and mathematics. We regard these continuum concepts and continuum space-time (S-T) in particular as being emergent, coarse-grained and derived relative to an underlying erratic and disordered microscopic substratum which is expected to play by quite different rules. A central role in our analysis is played by a geometric renormalization group which creates (among other things) a kind of sparse translocal network of correlations in classical continuous space-time and underlies in our view such mysterious phenomena as holography and the black hole entropy-area law. The same point of view holds for quantum theory which we also regard as a low-energy, coarse-grained continuum theory, being emergent from something more fundamental.

  17. Ultra-Porous Nanoparticle Networks: A Biomimetic Coating Morphology for Enhanced Cellular Response and Infiltration.

    PubMed

    Nasiri, Noushin; Ceramidas, Anthony; Mukherjee, Shayanti; Panneerselvan, Anitha; Nisbet, David R; Tricoli, Antonio

    2016-01-01

    Orthopedic treatments are amongst the most common cause of surgery and are responsible for a large share of global healthcare expenditures. Engineering materials that can hasten bone integration will improve the quality of life of millions of patients per year and reduce associated medical costs. Here, we present a novel hierarchical biomimetic coating that mimics the inorganic constituent of mammalian bones with the aim of improving osseointegration of metallic implants. We exploit the thermally-driven self-organization of metastable core-shell nanoparticles during their aerosol self-assembly to rapidly fabricate robust, ultra-porous nanoparticle networks (UNN) of crystalline hydroxyapatite (HAp). Comparative analysis of the response of osteoblast cells to the ultra-porous nanostructured HAp surfaces and to the spin coated HAp surfaces revealed superior osseointegrative properties of the UNN coatings with significant cell and filopodia infiltration. This flexible synthesis approach for the engineering of UNN HAp coatings on titanium implants provides a platform technology to study the bone-implant interface for improved osseointegration and osteoconduction. PMID:27076035

  18. Evidence for progressive reduction and loss of telocytes in the dermal cellular network of systemic sclerosis.

    PubMed

    Manetti, Mirko; Guiducci, Serena; Ruffo, Martina; Rosa, Irene; Faussone-Pellegrini, Maria Simonetta; Matucci-Cerinic, Marco; Ibba-Manneschi, Lidia

    2013-04-01

    Telocytes, a peculiar type of stromal cells, have been recently identified in a variety of tissues and organs, including human skin. Systemic sclerosis (SSc, scleroderma) is a complex connective tissue disease characterized by fibrosis of the skin and internal organs. We presently investigated telocyte distribution and features in the skin of SSc patients compared with normal skin. By an integrated immunohistochemical and transmission electron microscopy approach, we confirmed that telocytes were present in human dermis, where they were mainly recognizable by their typical ultrastructural features and were immunophenotypically characterized by CD34 expression. Our findings also showed that dermal telocytes were immunophenotypically negative for CD31/PECAM-1 (endothelial cells), α-SMA (myofibroblasts, pericytes, vascular smooth muscle cells), CD11c (dendritic cells, macrophages), CD90/Thy-1 (fibroblasts) and c-kit/CD117 (mast cells). In normal skin, telocytes were organized to form three-dimensional networks distributed among collagen bundles and elastic fibres, and surrounded microvessels, nerves and skin adnexa (hair follicles, sebaceous and sweat glands). Telocytes displayed severe ultrastructural damages (swollen mitochondria, cytoplasmic vacuolization, lipofuscinic bodies) suggestive of ischaemia-induced cell degeneration and were progressively lost from the clinically affected skin of SSc patients. Telocyte damage and loss evolved differently according to SSc subsets and stages, being more rapid and severe in diffuse SSc. Briefly, in human skin telocytes are a distinct stromal cell population. In SSc skin, the progressive loss of telocytes might (i) contribute to the altered three-dimensional organization of the extracellular matrix, (ii) reduce the control of fibroblast, myofibroblast and mast cell activity, and (iii) impair skin regeneration and/or repair. PMID:23444845

  19. Mapping the Hsp90 Genetic Network Reveals Ergosterol Biosynthesis and Phosphatidylinositol-4-Kinase Signaling as Core Circuitry Governing Cellular Stress

    PubMed Central

    O’Meara, Teresa R.; Valaei, Seyedeh Fereshteh; Diezmann, Stephanie; Cowen, Leah E.

    2016-01-01

    Candida albicans is a leading human fungal pathogen that causes life-threatening systemic infections. A key regulator of C. albicans stress response, drug resistance, morphogenesis, and virulence is the molecular chaperone Hsp90. Targeting Hsp90 provides a powerful strategy to treat fungal infections, however, the therapeutic utility of current inhibitors is compromised by toxicity due to inhibition of host Hsp90. To identify components of the Hsp90-dependent circuitry governing virulence and drug resistance that are sufficiently divergent for selective targeting in the pathogen, we pioneered chemical genomic profiling of the Hsp90 genetic network in C. albicans. Here, we screen mutant collections covering ~10% of the genome for hypersensitivity to Hsp90 inhibition in multiple environmental conditions. We identify 158 HSP90 chemical genetic interactors, most of which are important for growth only in specific environments. We discovered that the sterol C-22 desaturase gene ERG5 and the phosphatidylinositol-4-kinase (PI4K) gene STT4 are HSP90 genetic interactors under multiple conditions, suggesting a function upstream of Hsp90. By systematic analysis of the ergosterol biosynthetic cascade, we demonstrate that defects in ergosterol biosynthesis induce cellular stress that overwhelms Hsp90’s functional capacity. By analysis of the phosphatidylinositol pathway, we demonstrate that there is a genetic interaction between the PI4K Stt4 and Hsp90. We also establish that Stt4 is required for normal actin polarization through regulation of Wal1, and suggest a model in which defects in actin remodeling induces stress that creates a cellular demand for Hsp90 that exceeds its functional capacity. Consistent with this model, actin inhibitors are synergistic with Hsp90 inhibitors. We highlight new connections between Hsp90 and virulence traits, demonstrating that Erg5 and Stt4 enable activation of macrophage pyroptosis. This work uncovers novel circuitry regulating Hsp90

  20. Mapping the Hsp90 Genetic Network Reveals Ergosterol Biosynthesis and Phosphatidylinositol-4-Kinase Signaling as Core Circuitry Governing Cellular Stress.

    PubMed

    O'Meara, Teresa R; Veri, Amanda O; Polvi, Elizabeth J; Li, Xinliu; Valaei, Seyedeh Fereshteh; Diezmann, Stephanie; Cowen, Leah E

    2016-06-01

    Candida albicans is a leading human fungal pathogen that causes life-threatening systemic infections. A key regulator of C. albicans stress response, drug resistance, morphogenesis, and virulence is the molecular chaperone Hsp90. Targeting Hsp90 provides a powerful strategy to treat fungal infections, however, the therapeutic utility of current inhibitors is compromised by toxicity due to inhibition of host Hsp90. To identify components of the Hsp90-dependent circuitry governing virulence and drug resistance that are sufficiently divergent for selective targeting in the pathogen, we pioneered chemical genomic profiling of the Hsp90 genetic network in C. albicans. Here, we screen mutant collections covering ~10% of the genome for hypersensitivity to Hsp90 inhibition in multiple environmental conditions. We identify 158 HSP90 chemical genetic interactors, most of which are important for growth only in specific environments. We discovered that the sterol C-22 desaturase gene ERG5 and the phosphatidylinositol-4-kinase (PI4K) gene STT4 are HSP90 genetic interactors under multiple conditions, suggesting a function upstream of Hsp90. By systematic analysis of the ergosterol biosynthetic cascade, we demonstrate that defects in ergosterol biosynthesis induce cellular stress that overwhelms Hsp90's functional capacity. By analysis of the phosphatidylinositol pathway, we demonstrate that there is a genetic interaction between the PI4K Stt4 and Hsp90. We also establish that Stt4 is required for normal actin polarization through regulation of Wal1, and suggest a model in which defects in actin remodeling induces stress that creates a cellular demand for Hsp90 that exceeds its functional capacity. Consistent with this model, actin inhibitors are synergistic with Hsp90 inhibitors. We highlight new connections between Hsp90 and virulence traits, demonstrating that Erg5 and Stt4 enable activation of macrophage pyroptosis. This work uncovers novel circuitry regulating Hsp90

  1. A cellular nonlinear network: real-time technology for the analysis of microfluidic phenomena in blood vessels

    NASA Astrophysics Data System (ADS)

    Sapuppo, F.; Bucolo, M.; Intaglietta, M.; Fortuna, L.; Arena, P.

    2006-02-01

    A new approach to the observation and analysis of dynamic structural and functional parameters in the microcirculation is described. The new non-invasive optical system is based on cellular nonlinear networks (CNNs), highly integrated analogue processor arrays whose processing elements, the cells, interact directly within a finite local neighbourhood. CNNs, thanks to their parallel processing feature and spatially distributed structure, are widely used to solve high-speed image processing and recognition problems and in the description and modelling of biological dynamics through the solution of time continuous partial differential equations (PDEs). They are therefore considered extremely suitable for spatial-temporal dynamic characterization of fluidic phenomena at micrometric to nanometric scales, such as blood flow in microvessels and its interaction with the cells of the vessel wall. A CNN universal machine (CNN-UM) structure was used to implement, via simulation and hardware (ACE16k), the algorithms to determine the functional capillarity density (FCD) and red blood cell velocity (RBCV) in capillaries obtained by intravital microscopy during in vivo experiments on hamsters. The system exploits the moving particles to distinguish the functional capillaries from the stationary background. This information is used to reconstruct a map and to calculate the velocity of the moving objects.

  2. Decoding genome-wide GadEWX-transcriptional regulatory networks reveals multifaceted cellular responses to acid stress in Escherichia coli

    PubMed Central

    Seo, Sang Woo; Kim, Donghyuk; O'Brien, Edward J.; Szubin, Richard; Palsson, Bernhard O.

    2015-01-01

    The regulators GadE, GadW and GadX (which we refer to as GadEWX) play a critical role in the transcriptional regulation of the glutamate-dependent acid resistance (GDAR) system in Escherichia coli K-12 MG1655. However, the genome-wide regulatory role of GadEWX is still unknown. Here we comprehensively reconstruct the genome-wide GadEWX transcriptional regulatory network and RpoS involvement in E. coli K-12 MG1655 under acidic stress. Integrative data analysis reveals that GadEWX regulons consist of 45 genes in 31 transcription units and 28 of these genes were associated with RpoS-binding sites. We demonstrate that GadEWX directly and coherently regulate several proton-generating/consuming enzymes with pairs of negative-feedback loops for pH homeostasis. In addition, GadEWX regulate genes with assorted functions, including molecular chaperones, acid resistance, stress response and other regulatory activities. These results show how GadEWX simultaneously coordinate many cellular processes to produce the overall response of E. coli to acid stress. PMID:26258987

  3. A 181 GOPS AKAZE Accelerator Employing Discrete-Time Cellular Neural Networks for Real-Time Feature Extraction.

    PubMed

    Jiang, Guangli; Liu, Leibo; Zhu, Wenping; Yin, Shouyi; Wei, Shaojun

    2015-01-01

    This paper proposes a real-time feature extraction VLSI architecture for high-resolution images based on the accelerated KAZE algorithm. Firstly, a new system architecture is proposed. It increases the system throughput, provides flexibility in image resolution, and offers trade-offs between speed and scaling robustness. The architecture consists of a two-dimensional pipeline array that fully utilizes computational similarities in octaves. Secondly, a substructure (block-serial discrete-time cellular neural network) that can realize a nonlinear filter is proposed. This structure decreases the memory demand through the removal of data dependency. Thirdly, a hardware-friendly descriptor is introduced in order to overcome the hardware design bottleneck through the polar sample pattern; a simplified method to realize rotation invariance is also presented. Finally, the proposed architecture is designed in TSMC 65 nm CMOS technology. The experimental results show a performance of 127 fps in full HD resolution at 200 MHz frequency. The peak performance reaches 181 GOPS and the throughput is double the speed of other state-of-the-art architectures. PMID:26404305

  4. A 181 GOPS AKAZE Accelerator Employing Discrete-Time Cellular Neural Networks for Real-Time Feature Extraction

    PubMed Central

    Jiang, Guangli; Liu, Leibo; Zhu, Wenping; Yin, Shouyi; Wei, Shaojun

    2015-01-01

    This paper proposes a real-time feature extraction VLSI architecture for high-resolution images based on the accelerated KAZE algorithm. Firstly, a new system architecture is proposed. It increases the system throughput, provides flexibility in image resolution, and offers trade-offs between speed and scaling robustness. The architecture consists of a two-dimensional pipeline array that fully utilizes computational similarities in octaves. Secondly, a substructure (block-serial discrete-time cellular neural network) that can realize a nonlinear filter is proposed. This structure decreases the memory demand through the removal of data dependency. Thirdly, a hardware-friendly descriptor is introduced in order to overcome the hardware design bottleneck through the polar sample pattern; a simplified method to realize rotation invariance is also presented. Finally, the proposed architecture is designed in TSMC 65 nm CMOS technology. The experimental results show a performance of 127 fps in full HD resolution at 200 MHz frequency. The peak performance reaches 181 GOPS and the throughput is double the speed of other state-of-the-art architectures. PMID:26404305

  5. Decoding genome-wide GadEWX-transcriptional regulatory networks reveals multifaceted cellular responses to acid stress in Escherichia coli.

    PubMed

    Seo, Sang Woo; Kim, Donghyuk; O'Brien, Edward J; Szubin, Richard; Palsson, Bernhard O

    2015-01-01

    The regulators GadE, GadW and GadX (which we refer to as GadEWX) play a critical role in the transcriptional regulation of the glutamate-dependent acid resistance (GDAR) system in Escherichia coli K-12 MG1655. However, the genome-wide regulatory role of GadEWX is still unknown. Here we comprehensively reconstruct the genome-wide GadEWX transcriptional regulatory network and RpoS involvement in E. coli K-12 MG1655 under acidic stress. Integrative data analysis reveals that GadEWX regulons consist of 45 genes in 31 transcription units and 28 of these genes were associated with RpoS-binding sites. We demonstrate that GadEWX directly and coherently regulate several proton-generating/consuming enzymes with pairs of negative-feedback loops for pH homeostasis. In addition, GadEWX regulate genes with assorted functions, including molecular chaperones, acid resistance, stress response and other regulatory activities. These results show how GadEWX simultaneously coordinate many cellular processes to produce the overall response of E. coli to acid stress. PMID:26258987

  6. Proteomic, cellular, and network analyses reveal new DUSP3 interactions with nucleolar proteins in HeLa cells.

    PubMed

    Panico, Karine; Forti, Fabio Luis

    2013-12-01

    DUSP3 (or Vaccinia virus phosphatase VH1-related; VHR) is a small dual-specificity phosphatase known to dephosphorylate c-Jun N-terminal kinases and extracellular signal-regulated kinases. In human cervical cancer cells, DUSP3 is overexpressed, localizes preferentially to the nucleus, and plays a key role in cellular proliferation and senescence triggering. Other DUSP3 functions are still unknown, as illustrated by recent and unpublished results from our group showing that this enzyme mediates DNA damage response or repair processes. In this study, we sought to identify new interactions between DUSP3 and proteins directly or indirectly involved in or correlated with its biological roles in HeLa cells exposed to gamma or UV radiation. By using GST-DUSP as bait, we pulled down interacting proteins and identified them by LC-MS/MS. Of the 46 proteins obtained, six hits were extensively validated by immune techniques; the proteins Nucleophosmin, HnRNP C1/C2, and Nucleolin were the most promising targets found to directly interact with DUSP3. We then analyzed the DUSP3 interactomes using physical protein-protein interaction networks using our hits as the seed list. The validated hits as well as unvalidated hits fluctuated on the DUSP3 interactomes of HeLa cells, independent of the time post radiation, which confirmed our proteomic and experimental data and clearly showed the proximity of DUSP3 to proteins involved in processes intimately related to DNA repair and senescence, such as Ku70 and Tert, via interactions with nucleolar proteins, which were identified in this study, that regulate DNA/RNA structure and functions. PMID:24245651

  7. Modeling land use and land cover changes in a vulnerable coastal region using artificial neural networks and cellular automata.

    PubMed

    Qiang, Yi; Lam, Nina S N

    2015-03-01

    As one of the most vulnerable coasts in the continental USA, the Lower Mississippi River Basin (LMRB) region has endured numerous hazards over the past decades. The sustainability of this region has drawn great attention from the international, national, and local communities, wanting to understand how the region as a system develops under intense interplay between the natural and human factors. A major problem in this deltaic region is significant land loss over the years due to a combination of natural and human factors. The main scientific and management questions are what factors contribute to the land use land cover (LULC) changes in this region, can we model the changes, and how would the LULC look like in the future given the current factors? This study analyzed the LULC changes of the region between 1996 and 2006 by utilizing an artificial neural network (ANN) to derive the LULC change rules from 15 human and natural variables. The rules were then used to simulate future scenarios in a cellular automation model. A stochastic element was added in the model to represent factors that were not included in the current model. The analysis was conducted for two sub-regions in the study area for comparison. The results show that the derived ANN models could simulate the LULC changes with a high degree of accuracy (above 92 % on average). A total loss of 263 km(2) in wetlands from 2006 to 2016 was projected, whereas the trend of forest loss will cease. These scenarios provide useful information to decision makers for better planning and management of the region. PMID:25647797

  8. Cellular resilience.

    PubMed

    Smirnova, Lena; Harris, Georgina; Leist, Marcel; Hartung, Thomas

    2015-01-01

    Cellular resilience describes the ability of a cell to cope with environmental changes such as toxicant exposure. If cellular metabolism does not collapse directly after the hit or end in programmed cell death, the ensuing stress responses promote a new homeostasis under stress. The processes of reverting "back to normal" and reversal of apoptosis ("anastasis") have been studied little at the cellular level. Cell types show astonishingly similar vulnerability to most toxicants, except for those that require a very specific target, metabolism or mechanism present only in specific cell types. The majority of chemicals triggers "general cytotoxicity" in any cell at similar concentrations. We hypothesize that cells differ less in their vulnerability to a given toxicant than in their resilience (coping with the "hit"). In many cases, cells do not return to the naive state after a toxic insult. The phenomena of "pre-conditioning", "tolerance" and "hormesis" describe this for low-dose exposures to toxicants that render the cell more resistant to subsequent hits. The defense and resilience programs include epigenetic changes that leave a "memory/scar" - an alteration as a consequence of the stress the cell has experienced. These memories might have long-term consequences, both positive (resistance) and negative, that contribute to chronic and delayed manifestations of hazard and, ultimately, disease. This article calls for more systematic analyses of how cells cope with toxic perturbations in the long-term after stressor withdrawal. A technical prerequisite for these are stable (organotypic) cultures and a characterization of stress response molecular networks. PMID:26536287

  9. Stackelberg Game Based Power Allocation for Physical Layer Security of Device-to-device Communication Underlaying Cellular Networks

    NASA Astrophysics Data System (ADS)

    Qu, Junyue; Cai, Yueming; Wu, Dan; Chen, Hualiang

    2014-05-01

    The problem of power allocation for device-to-device (D2D) underlay communication to improve physical layer security is addressed. Specifically, to improve the secure communication of the cellular users, we introduce a Stackelberg game for allocating the power of the D2D link under a total power constraint and a rate constraint at the D2D pair. In the introduced Stackelberg game the D2D pair works as a seller and the cellular UEs work as buyers. Firstly, because the interference signals from D2D pair are unknown to both the legitimate receiver and the illegitimate eavesdropper, it is possible that a cellular UE decline to participate in the introduced Stackelberg game. So the condition under which a legitimate user will participate in the introduced Stackelberg game is discussed. Then, based on the Stackelberg game, we propose a semi-distributed power allocation algorithm, which is proved to conclude after finite-time iterations. In the end, some simulations are presented to verify the performance improvement in the physical layer security of cellular UEs using the proposed power allocation algorithm. We can determine that with the proposed algorithm, while the D2D pair's communication demand is met, the physical layer security of cellular UEs can be improved.

  10. Multiscale modeling of cellular epigenetic states: stochasticity in molecular networks, chromatin folding in cell nuclei, and tissue pattern formation of cells

    PubMed Central

    Liang, Jie; Cao, Youfang; Gürsoy, Gamze; Naveed, Hammad; Terebus, Anna; Zhao, Jieling

    2016-01-01

    Genome sequences provide the overall genetic blueprint of cells, but cells possessing the same genome can exhibit diverse phenotypes. There is a multitude of mechanisms controlling cellular epigenetic states and that dictate the behavior of cells. Among these, networks of interacting molecules, often under stochastic control, depending on the specific wirings of molecular components and the physiological conditions, can have a different landscape of cellular states. In addition, chromosome folding in three-dimensional space provides another important control mechanism for selective activation and repression of gene expression. Fully differentiated cells with different properties grow, divide, and interact through mechanical forces and communicate through signal transduction, resulting in the formation of complex tissue patterns. Developing quantitative models to study these multi-scale phenomena and to identify opportunities for improving human health requires development of theoretical models, algorithms, and computational tools. Here we review recent progress made in these important directions. PMID:27480462

  11. Global Exponential Stability of Almost Periodic Solution for Neutral-Type Cohen-Grossberg Shunting Inhibitory Cellular Neural Networks with Distributed Delays and Impulses

    PubMed Central

    Xu, Lijun; Jiang, Qi; Gu, Guodong

    2016-01-01

    A kind of neutral-type Cohen-Grossberg shunting inhibitory cellular neural networks with distributed delays and impulses is considered. Firstly, by using the theory of impulsive differential equations and the contracting mapping principle, the existence and uniqueness of the almost periodic solution for the above system are obtained. Secondly, by constructing a suitable Lyapunov functional, the global exponential stability of the unique almost periodic solution is also investigated. The work in this paper improves and extends some results in recent years. As an application, an example and numerical simulations are presented to demonstrate the feasibility and effectiveness of the main results. PMID:27190502

  12. New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

    PubMed

    Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

    2012-01-21

    Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction

  13. Interaction between cellular voltage-sensitive conductance and network parameters in a model of neocortex can generate epileptiform bursting.

    SciTech Connect

    van Drongelen, W.; Lee, H. C.; Koch, H.; Elsen, F.; Carroll, M. S.; Hereld, M.; Stevens, R. L.; Mathematics and Computer Science; Univ. of Chicago

    2004-01-01

    We examined the effects of both intrinsic neuronal membrane properties and network parameters on oscillatory activity in a model of neocortex. A scalable network model with six different cell types was built with the pGENESIS neural simulator. The neocortical network consisted of two types of pyramidal cells and four types of inhibitory interneurons. All cell types contained both fast sodium and delayed rectifier potassium channels for generation of action potentials. A subset of the pyramidal neurons contained an additional slow inactivating (persistent) sodium current (NaP). The neurons with the NaP current showed spontaneous bursting activity in the absence of external stimulation. The model also included a routine to calculate a simulated electroencephalogram (EEG) trace from the population activity. This revealed emergent network behavior which ranged from desynchronized activity to different types of seizure-like bursting patterns. At settings with weaker excitatory network effects, the propensity to generate seizure-like behavior increased. Strong excitatory network connectivity destroyed oscillatory behavior, whereas weak connectivity enhanced the relative importance of the spontaneously bursting cells. Our findings are in contradiction with the general opinion that strong excitatory synaptic and/or insufficient inhibition effects are associated with seizure initiation, but are in agreement with previously reported behavior in neocortex.

  14. Identification of a molecular signaling network that regulates a cellular necrotic cell death pathway by a genome wide siRNA screen

    PubMed Central

    Hitomi, Junichi; Christofferson, Dana E.; Ng, Aylwin; Yao, Jianhua; Degterev, Alexei; Xavier, Ramnik J.; Yuan, Junying

    2009-01-01

    Stimulation of death receptors by agonists such as FasL and TNFα activates apoptotic cell death in apoptotic competent conditions or a type of necrotic cell death dependent on RIP1 kinase, termed necroptosis, in apoptotic deficient conditions. In a genome-wide siRNA screen for regulators of necroptosis, we identify a set of 432 genes that regulate necroptosis, a subset of 32 genes that act downstream and/or as regulators of RIP1 kinase, 32 genes required for death receptor mediated apoptosis, and 7 genes involved in both necroptosis and apoptosis. We show that the expression of subsets of the 432 genes are enriched in the immune and nervous systems, and cellular sensitivity to necroptosis is regulated by an extensive signaling network mediating innate immunity. Interestingly, Bmf, a BH3-only Bcl-2 family member, is required for death receptor-induced necroptosis. Our study defines a cellular signaling network that regulates necroptosis and the molecular bifurcation that controls apoptosis and necroptosis. PMID:19109899

  15. Equine Infectious Anemia Virus Gag Assembly and Export Are Directed by Matrix Protein through trans-Golgi Networks and Cellular Vesicles

    PubMed Central

    Zhang, Zeli; Ma, Jian; Zhang, Xiang; Su, Chao; Yao, Qiu-Cheng

    2015-01-01

    ABSTRACT Gag intracellular assembly and export are very important processes for lentiviruses replication. Previous studies have demonstrated that equine infectious anemia virus (EIAV) matrix (MA) possesses distinct phosphoinositide affinity compared with HIV-1 MA and that phosphoinositide-mediated targeting to peripheral and internal membranes is a critical factor in EIAV assembly and release. In this study, we compared the cellular assembly sites of EIAV and HIV-1. We observed that the assembly of EIAV particles occurred on interior cellular membranes, while HIV-1 was targeted to the plasma membrane (PM) for assembly. Then, we determined that W7 and K9 in the EIAV MA N terminus were essential for Gag assembly and release but did not affect the cellular distribution of Gag. The replacement of EIAV MA with HIV-1 MA directed chimeric Gag to the PM but severely impaired Gag release. MA structural analysis indicated that the EIAV and HIV-1 MAs had similar spatial structures but that helix 1 of the EIAV MA was closer to loop 2. Further investigation indicated that EIAV Gag accumulated in the trans-Golgi network (TGN) but not the early and late endosomes. The 9 N-terminal amino acids of EIAV MA harbored the signal that directed Gag to the TGN membrane system. Additionally, we demonstrated that EIAV particles were transported to the extracellular space by the cellular vesicle system. This type of EIAV export was not associated with multivesicular bodies or microtubule depolymerization but could be inhibited by the actin-depolymerizing drug cytochalasin D, suggesting that dynamic actin depolymerization may be associated with EIAV production. IMPORTANCE In previous studies, EIAV Gag was reported to localize to both the cell interior and the plasma membrane. Here, we demonstrate that EIAV likely uses the TGN as the assembly site in contrast to HIV-1, which is targeted to the PM for assembly. These distinct assembly features are determined by the MA domain. We also identified

  16. System-Level Insights into the Cellular Interactome of a Non-Model Organism: Inferring, Modelling and Analysing Functional Gene Network of Soybean (Glycine max)

    PubMed Central

    Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

    2014-01-01

    Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome

  17. Why Are Cortical GABA Neurons Relevant to Internal Focus in Depression? A cross-level model linking cellular, biochemical, and neural network findings

    PubMed Central

    2014-01-01

    Major Depression is a complex and severe psychiatric disorder whose symptomatology encompasses a critical shift in awareness, specifically in the balance from external to internal mental focus. This is reflected by unspecific somatic symptoms and the predominance of the own cognitions manifested in increased self-focus and rumination. We posit here that sufficient empirical data has accumulated to build a coherent biological model that links these psychological concepts and symptom dimensions to observed biochemical, cellular, regional and neural network deficits. Specifically, deficits in inhibitory gamma amino butyric acid (GABA) regulating excitatory cell input/output and local cell circuit processing of information in key brain regions may underlie the shift that is observed in depressed subjects in resting state activities between the perigenual anterior cingulate cortex (PACC) and the dorsolateral prefrontal cortex (DLPFC). This regional dysbalance translates at the network level in a dysbalance between default-mode and executive networks, which psychopathologically surfaces as a shift in focus from external to internal mental content and associated symptoms (See overview in Figure 1). We focus here on primary evidence at each of those levels and on putative mechanistic links between those levels. Apart from its implications for neuropsychiatric disorders, our model provides for the first time a set of hypotheses for cross-level mechanisms of how internal and external mental contents may be constituted and balanced in healthy subjects, and thus also contributes to the neuroscientific debate on the neural correlates of consciousness. PMID:25048001

  18. Perturbation of cellular proteostasis networks identifies pathways that modulate precursor and intermediate but not mature levels of frataxin

    PubMed Central

    Nabhan, Joseph F.; Gooch, Renea L.; Piatnitski Chekler, Eugene L.; Pierce, Betsy; Bulawa, Christine E.

    2015-01-01

    Friedreich’s Ataxia is a genetic disease caused by expansion of an intronic trinucleotide repeat in the frataxin (FXN) gene yielding diminished FXN expression and consequently disease. Since increasing FXN protein levels is desirable to ameliorate pathology, we explored the role of major cellular proteostasis pathways and mitochondrial proteases in FXN processing and turnover. We targeted p97/VCP, the ubiquitin proteasome pathway (UPP), and autophagy with chemical inhibitors in cell lines and patient-derived cells. p97 inhibition by DBeQ increased precursor FXN levels, while UPP and autophagic flux modulators had variable effects predominantly on intermediate FXN. Our data suggest that these pathways cannot be modulated to influence mature functional FXN levels. We also targeted known mitochondrial proteases by RNA interference and discovered a novel protease PITRM1 that regulates intermediate FXN levels. Treatment with the aforementioned chemical and genetic modulators did not have a differential effect in patient cells containing lower amounts of FXN. Interestingly, a number of treatments caused a change in total amount of FXN protein, without an effect on mature FXN. Our results imply that regulation of FXN protein levels is complex and that total amounts can be modulated chemically and genetically without altering the absolute amount of mature FXN protein. PMID:26671574

  19. C/EBPγ Is a Critical Regulator of Cellular Stress Response Networks through Heterodimerization with ATF4.

    PubMed

    Huggins, Christopher J; Mayekar, Manasi K; Martin, Nancy; Saylor, Karen L; Gonit, Mesfin; Jailwala, Parthav; Kasoji, Manjula; Haines, Diana C; Quiñones, Octavio A; Johnson, Peter F

    2016-03-01

    The integrated stress response (ISR) controls cellular adaptations to nutrient deprivation, redox imbalances, and endoplasmic reticulum (ER) stress. ISR genes are upregulated in stressed cells, primarily by the bZIP transcription factor ATF4 through its recruitment to cis-regulatory C/EBP:ATF response elements (CAREs) together with a dimeric partner of uncertain identity. Here, we show that C/EBPγ:ATF4 heterodimers, but not C/EBPβ:ATF4 dimers, are the predominant CARE-binding species in stressed cells. C/EBPγ and ATF4 associate with genomic CAREs in a mutually dependent manner and coregulate many ISR genes. In contrast, the C/EBP family members C/EBPβ and C/EBP homologous protein (CHOP) were largely dispensable for induction of stress genes. Cebpg(-/-) mouse embryonic fibroblasts (MEFs) proliferate poorly and exhibit oxidative stress due to reduced glutathione levels and impaired expression of several glutathione biosynthesis pathway genes. Cebpg(-/-) mice (C57BL/6 background) display reduced body size and microphthalmia, similar to ATF4-null animals. In addition, C/EBPγ-deficient newborns die from atelectasis and respiratory failure, which can be mitigated by in utero exposure to the antioxidant, N-acetyl-cysteine. Cebpg(-/-) mice on a mixed strain background showed improved viability but, upon aging, developed significantly fewer malignant solid tumors than WT animals. Our findings identify C/EBPγ as a novel antioxidant regulator and an obligatory ATF4 partner that controls redox homeostasis in normal and cancerous cells. PMID:26667036

  20. Cellular Protein WDR11 Interacts with Specific Herpes Simplex Virus Proteins at the trans-Golgi Network To Promote Virus Replication

    PubMed Central

    Taylor, Kathryne E.

    2015-01-01

    ABSTRACT It has recently been proposed that the herpes simplex virus (HSV) protein ICP0 has cytoplasmic roles in blocking antiviral signaling and in promoting viral replication in addition to its well-known proteasome-dependent functions in the nucleus. However, the mechanisms through which it produces these effects remain unclear. While investigating this further, we identified a novel cytoplasmic interaction between ICP0 and the poorly characterized cellular protein WDR11. During an HSV infection, WDR11 undergoes a dramatic change in localization at late times in the viral replication cycle, moving from defined perinuclear structures to a dispersed cytoplasmic distribution. While this relocation was not observed during infection with viruses other than HSV-1 and correlated with efficient HSV-1 replication, the redistribution was found to occur independently of ICP0 expression, instead requiring viral late gene expression. We demonstrate for the first time that WDR11 is localized to the trans-Golgi network (TGN), where it interacts specifically with some, but not all, HSV virion components, in addition to ICP0. Knockdown of WDR11 in cultured human cells resulted in a modest but consistent decrease in yields of both wild-type and ICP0-null viruses, in the supernatant and cell-associated fractions, without affecting viral gene expression. Although further study is required, we propose that WDR11 participates in viral assembly and/or secondary envelopment. IMPORTANCE While the TGN has been proposed to be the major site of HSV-1 secondary envelopment, this process is incompletely understood, and in particular, the role of cellular TGN components in this pathway is unknown. Additionally, little is known about the cellular functions of WDR11, although the disruption of this protein has been implicated in multiple human diseases. Therefore, our finding that WDR11 is a TGN-resident protein that interacts with specific viral proteins to enhance viral yields improves both

  1. Hybrid alginate-polyester bimodal network hydrogel for tissue engineering--Influence of structured water on long-term cellular growth.

    PubMed

    Finosh, G T; Jayabalan, M; Vandana, S; Raghu, K G

    2015-11-01

    The development of biodegradable scaffolds (which promote cell-binding, proliferation, long-term cell viability and required biomechanical stability) for cardiac tissue engineering is a challenge. In this study, biosynthetic amphiphilic hybrid hydrogels were prepared using a graft comacromer of natural polysaccharide alginate and synthetic polyester polypropylene fumarate (PPF). Monomodal network hydrogel (HPAS-NO) and bimodal network hydrogel (HPAS-AA) were prepared. Between the two hydrogels, HPAS-AA hydrogel excels over the HPAS-NO hydrogel. HPAS-AA hydrogel is mechanically more stable in the culture medium and undergoes gradual degradation in vitro in PBS (phosphate buffered saline). HPAS-AA contains nano-porous structure and acquires structured water (non-freezing-bound water) (53.457%) along with free water (11.773%). It absorbs more plasma proteins and prevents platelet adsorption and hemolysis when contacted with blood. HPAS-AA hydrogel is cytocompatible and promote 3D cell growth (≈ 70%) of L929 fibroblast even after 18 days and H9C2 cardiomyoblasts. The enhanced and long-term cellular growth of HPAS-AA hydrogel is attributed to the cell responsive features of structured water. HPAS-AA hydrogel can be a better candidate for cardiac tissue engineering applications. PMID:25843368

  2. Irregular Cellular Learning Automata.

    PubMed

    Esnaashari, Mehdi; Meybodi, Mohammad Reza

    2015-08-01

    Cellular learning automaton (CLA) is a recently introduced model that combines cellular automaton (CA) and learning automaton (LA). The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA. This model has been used to solve problems in areas such as channel assignment in cellular networks, call admission control, image processing, and very large scale integration placement. In this paper, an extension of CLA called irregular CLA (ICLA) is introduced. This extension is obtained by removing the structure regularity assumption in CLA. Irregularity in the structure of ICLA is needed in some applications, such as computer networks, web mining, and grid computing. The concept of expediency has been introduced for ICLA and then, conditions under which an ICLA becomes expedient are analytically found. PMID:25291810

  3. Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders

    PubMed Central

    Marquet, Pierre; Depeursinge, Christian; Magistretti, Pierre J.

    2014-01-01

    Abstract. Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed. PMID:26157976

  4. Image processing with cellular nonlinear networks implemented on field-programmable gate arrays for real-time applications in nuclear fusion

    SciTech Connect

    Palazzo, S.; Vagliasindi, G.; Arena, P.; Murari, A.; Mazon, D.; De Maack, A.; Collaboration: JET-EFDA Contributors

    2010-08-15

    In the past years cameras have become increasingly common tools in scientific applications. They are now quite systematically used in magnetic confinement fusion, to the point that infrared imaging is starting to be used systematically for real-time machine protection in major devices. However, in order to guarantee that the control system can always react rapidly in case of critical situations, the time required for the processing of the images must be as predictable as possible. The approach described in this paper combines the new computational paradigm of cellular nonlinear networks (CNNs) with field-programmable gate arrays and has been tested in an application for the detection of hot spots on the plasma facing components in JET. The developed system is able to perform real-time hot spot recognition, by processing the image stream captured by JET wide angle infrared camera, with the guarantee that computational time is constant and deterministic. The statistical results obtained from a quite extensive set of examples show that this solution approximates very well an ad hoc serial software algorithm, with no false or missed alarms and an almost perfect overlapping of alarm intervals. The computational time can be reduced to a millisecond time scale for 8 bit 496x560-sized images. Moreover, in our implementation, the computational time, besides being deterministic, is practically independent of the number of iterations performed by the CNN - unlike software CNN implementations.

  5. Cellular Homeostasis and Aging.

    PubMed

    Hartl, F Ulrich

    2016-06-01

    Aging and longevity are controlled by a multiplicity of molecular and cellular signaling events that interface with environmental factors to maintain cellular homeostasis. Modulation of these pathways to extend life span, including insulin-like signaling and the response to dietary restriction, identified the cellular machineries and networks of protein homeostasis (proteostasis) and stress resistance pathways as critical players in the aging process. A decline of proteostasis capacity during aging leads to dysfunction of specific cell types and tissues, rendering the organism susceptible to a range of chronic diseases. This volume of the Annual Review of Biochemistry contains a set of two reviews addressing our current understanding of the molecular mechanisms underlying aging in model organisms and humans. PMID:27050288

  6. Preliminary Analysis of the efficacy of Artificial neural Network (ANN) and Cellular Automaton (CA) based Land Use Models in Urban Land-Use Planning

    NASA Astrophysics Data System (ADS)

    Harun, R.

    2013-05-01

    This research provides an opportunity of collaboration between urban planners and modellers by providing a clear theoretical foundations on the two most widely used urban land use models, and assessing the effectiveness of applying the models in urban planning context. Understanding urban land cover change is an essential element for sustainable urban development as it affects ecological functioning in urban ecosystem. Rapid urbanization due to growing inclination of people to settle in urban areas has increased the complexities in predicting that at what shape and size cities will grow. The dynamic changes in the spatial pattern of urban landscapes has exposed the policy makers and environmental scientists to great challenge. But geographic science has grown in symmetry to the advancements in computer science. Models and tools are developed to support urban planning by analyzing the causes and consequences of land use changes and project the future. Of all the different types of land use models available in recent days, it has been found by researchers that the most frequently used models are Cellular Automaton (CA) and Artificial Neural Networks (ANN) models. But studies have demonstrated that the existing land use models have not been able to meet the needs of planners and policy makers. There are two primary causes identified behind this prologue. First, there is inadequate understanding of the fundamental theories and application of the models in urban planning context i.e., there is a gap in communication between modellers and urban planners. Second, the existing models exclude many key drivers in the process of simplification of the complex urban system that guide urban spatial pattern. Thus the models end up being effective in assessing the impacts of certain land use policies, but cannot contribute in new policy formulation. This paper is an attempt to increase the knowledge base of planners on the most frequently used land use model and also assess the

  7. Networks.

    ERIC Educational Resources Information Center

    Maughan, George R.; Petitto, Karen R.; McLaughlin, Don

    2001-01-01

    Describes the connectivity features and options of modern campus communication and information system networks, including signal transmission (wire-based and wireless), signal switching, convergence of networks, and network assessment variables, to enable campus leaders to make sound future-oriented decisions. (EV)

  8. Investigating the specific core genetic-and-epigenetic networks of cellular mechanisms involved in human aging in peripheral blood mononuclear cells

    PubMed Central

    Li, Cheng-Wei; Wang, Wen-Hsin; Chen, Bor-Sen

    2016-01-01

    Aging is an inevitable part of life for humans, and slowing down the aging process has become a main focus of human endeavor. Here, we applied a systems biology approach to construct protein-protein interaction networks, gene regulatory networks, and epigenetic networks, i.e. genetic and epigenetic networks (GENs), of elderly individuals and young controls. We then compared these GENs to extract aging mechanisms using microarray data in peripheral blood mononuclear cells, microRNA (miRNA) data, and database mining. The core GENs of elderly individuals and young controls were obtained by applying principal network projection to GENs based on Principal Component Analysis. By comparing the core networks, we identified that to overcome the accumulated mutation of genes in the aging process the transcription factor JUN can be activated by stress signals, including the MAPK signaling, T-cell receptor signaling, and neurotrophin signaling pathways through DNA methylation of BTG3, G0S2, and AP2B1 and the regulations of mir-223 let-7d, and mir-130a. We also address the aging mechanisms in old men and women. Furthermore, we proposed that drugs designed to target these DNA methylated genes or miRNAs may delay aging. A multiple drug combination comprising phenylalanine, cholesterol, and palbociclib was finally designed for delaying the aging process. PMID:26895224

  9. Networking.

    ERIC Educational Resources Information Center

    Duvall, Betty

    Networking is an information giving and receiving system, a support system, and a means whereby women can get ahead in careers--either in new jobs or in current positions. Networking information can create many opportunities: women can talk about how other women handle situations and tasks, and previously established contacts can be used in…

  10. Adaptive stochastic cellular automata: Applications

    NASA Astrophysics Data System (ADS)

    Qian, S.; Lee, Y. C.; Jones, R. D.; Barnes, C. W.; Flake, G. W.; O'Rourke, M. K.; Lee, K.; Chen, H. H.; Sun, G. Z.; Zhang, Y. Q.; Chen, D.; Giles, C. L.

    1990-09-01

    The stochastic learning cellular automata model has been applied to the problem of controlling unstable systems. Two example unstable systems studied are controlled by an adaptive stochastic cellular automata algorithm with an adaptive critic. The reinforcement learning algorithm and the architecture of the stochastic CA controller are presented. Learning to balance a single pole is discussed in detail. Balancing an inverted double pendulum highlights the power of the stochastic CA approach. The stochastic CA model is compared to conventional adaptive control and artificial neural network approaches.