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Sample records for cell signaling network

  1. [Signaling network-based functional cell design].

    Science.gov (United States)

    Ju, Jianqi; Wei, Ping

    2017-03-25

    Cellular signaling networks act as the central processor to deal with environmental signals and regulate cell function, and determine cell fate. Using synthetic biology approach to engineer cell signaling networks is crucial for ultimately constructing man-made "cell machines". Cellular signaling networks can encode sophisticated cell information by processing quantitatively signaling dynamics, which enables multi-dimensional regulation of functional sub-circuits. Here, we first review the research progresses on the signaling coding mechanisms; and then elaborate the methodologies and applications of cells signaling engineering; finally, we envision that signaling-based cell engineering are important for the increasingly-complicated next generation synthetic biology.

  2. Primary Cilia, Signaling Networks and Cell Migration

    DEFF Research Database (Denmark)

    Veland, Iben Rønn

    Primary cilia are microtubule-based, sensory organelles that emerge from the centrosomal mother centriole to project from the surface of most quiescent cells in the human body. Ciliary entry is a tightly controlled process, involving diffusion barriers and gating complexes that maintain a unique...... and cytoskeletal organization. Further, cell migration and polarization in are impaired in Invs MEFs. In two-dimensional cell migration, the centrosome is positioned between the nucleus and the leading edge with the primary cilium directed towards the direction of migration. PDGFRα is activated in the primary......, which leads to uncontrolled cell movements. Together, the results obtained from my PhD studies reflect the high level of complexity within signaling systems regulated by the primary cilium that control cellular processes during embryonic development and in tissue homeostasis. As such, this dissertation...

  3. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Science.gov (United States)

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

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

  4. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Directory of Open Access Journals (Sweden)

    Jianfeng Xu

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

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

    Science.gov (United States)

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

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

  6. Primary Cilia, Signaling Networks and Cell Migration

    DEFF Research Database (Denmark)

    Veland, Iben Rønn

    Primary cilia are microtubule-based, sensory organelles that emerge from the centrosomal mother centriole to project from the surface of most quiescent cells in the human body. Ciliary entry is a tightly controlled process, involving diffusion barriers and gating complexes that maintain a unique...

  7. Discrete dynamic modeling of T cell survival signaling networks

    Science.gov (United States)

    Zhang, Ranran

    2009-03-01

    Biochemistry-based frameworks are often not applicable for the modeling of heterogeneous regulatory systems that are sparsely documented in terms of quantitative information. As an alternative, qualitative models assuming a small set of discrete states are gaining acceptance. This talk will present a discrete dynamic model of the signaling network responsible for the survival and long-term competence of cytotoxic T cells in the blood cancer T-LGL leukemia. We integrated the signaling pathways involved in normal T cell activation and the known deregulations of survival signaling in leukemic T-LGL, and formulated the regulation of each network element as a Boolean (logic) rule. Our model suggests that the persistence of two signals is sufficient to reproduce all known deregulations in leukemic T-LGL. It also indicates the nodes whose inactivity is necessary and sufficient for the reversal of the T-LGL state. We have experimentally validated several model predictions, including: (i) Inhibiting PDGF signaling induces apoptosis in leukemic T-LGL. (ii) Sphingosine kinase 1 and NFκB are essential for the long-term survival of T cells in T-LGL leukemia. (iii) T box expressed in T cells (T-bet) is constitutively activated in the T-LGL state. The model has identified potential therapeutic targets for T-LGL leukemia and can be used for generating long-term competent CTL necessary for tumor and cancer vaccine development. The success of this model, and of other discrete dynamic models, suggests that the organization of signaling networks has an determining role in their dynamics. Reference: R. Zhang, M. V. Shah, J. Yang, S. B. Nyland, X. Liu, J. K. Yun, R. Albert, T. P. Loughran, Jr., Network Model of Survival Signaling in LGL Leukemia, PNAS 105, 16308-16313 (2008).

  8. Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells.

    Directory of Open Access Journals (Sweden)

    Aurélien Naldi

    2017-03-01

    Full Text Available The ability to build in-depth cell signaling networks from vast experimental data is a key objective of computational biology. The spleen tyrosine kinase (Syk protein, a well-characterized key player in immune cell signaling, was surprisingly first shown by our group to exhibit an onco-suppressive function in mammary epithelial cells and corroborated by many other studies, but the molecular mechanisms of this function remain largely unsolved. Based on existing proteomic data, we report here the generation of an interaction-based network of signaling pathways controlled by Syk in breast cancer cells. Pathway enrichment of the Syk targets previously identified by quantitative phospho-proteomics indicated that Syk is engaged in cell adhesion, motility, growth and death. Using the components and interactions of these pathways, we bootstrapped the reconstruction of a comprehensive network covering Syk signaling in breast cancer cells. To generate in silico hypotheses on Syk signaling propagation, we developed a method allowing to rank paths between Syk and its targets. We first annotated the network according to experimental datasets. We then combined shortest path computation with random walk processes to estimate the importance of individual interactions and selected biologically relevant pathways in the network. Molecular and cell biology experiments allowed to distinguish candidate mechanisms that underlie the impact of Syk on the regulation of cortactin and ezrin, both involved in actin-mediated cell adhesion and motility. The Syk network was further completed with the results of our biological validation experiments. The resulting Syk signaling sub-networks can be explored via an online visualization platform.

  9. Cell type specificity of signaling: view from membrane receptors distribution and their downstream transduction networks.

    Science.gov (United States)

    He, Ying; Yu, Zhonghao; Ge, Dongya; Wang-Sattler, Rui; Thiesen, Hans-Jürgen; Xie, Lu; Li, Yixue

    2012-09-01

    Studies on cell signaling pay more attention to spatial dynamics and how such diverse organization can relate to high order of cellular capabilities. To overview the specificity of cell signaling, we integrated human receptome data with proteome spatial expression profiles to systematically investigate the specificity of receptors and receptor-triggered transduction networks across 62 normal cell types and 14 cancer types. Six percent receptors showed cell-type-specific expression, and 4% signaling networks presented enriched cell-specific proteins induced by the receptors. We introduced a concept of "response context" to annotate the cell-type dependent signaling networks. We found that most cells respond similarly to the same stimulus, as the "response contexts" presented high functional similarity. Despite this, the subtle spatial diversity can be observed from the difference in network architectures. The architecture of the signaling networks in nerve cells displayed less completeness than that in glandular cells, which indicated cellular-context dependent signaling patterns are elaborately spatially organized. Likewise, in cancer cells most signaling networks were generally dysfunctional and less complete than that in normal cells. However, glioma emerged hyper-activated transduction mechanism in malignant state. Receptor ATP6AP2 and TNFRSF21 induced rennin-angiotensin and apoptosis signaling were found likely to explain the glioma-specific mechanism. This work represents an effort to decipher context-specific signaling network from spatial dimension. Our results indicated that although a majority of cells engage general signaling response with subtle differences, the spatial dynamics of cell signaling can not only deepen our insights into different signaling mechanisms, but also help understand cell signaling in disease.

  10. Signaling by Small GTPases at Cell-Cell junctions: Protein Interactions Building Control and Networks.

    Science.gov (United States)

    Braga, Vania

    2017-09-11

    A number of interesting reports highlight the intricate network of signaling proteins that coordinate formation and maintenance of cell-cell contacts. We have much yet to learn about how the in vitro binding data is translated into protein association inside the cells and whether such interaction modulates the signaling properties of the protein. What emerges from recent studies is the importance to carefully consider small GTPase activation in the context of where its activation occurs, which upstream regulators are involved in the activation/inactivation cycle and the GTPase interacting partners that determine the intracellular niche and extent of signaling. Data discussed here unravel unparalleled cooperation and coordination of functions among GTPases and their regulators in supporting strong adhesion between cells. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

  11. Protein and signaling networks in vertebrate photoreceptor cells

    Directory of Open Access Journals (Sweden)

    Karl-Wilhelm eKoch

    2015-11-01

    Full Text Available Vertebrate photoreceptor cells are exquisite light detectors operating under very dim and bright illumination. The photoexcitation and adaptation machinery in photoreceptor cells consists of protein complexes that can form highly ordered supramolecular structures and control the homeostasis and mutual dependence of the secondary messengers cGMP and Ca2+. The visual pigment in rod photoreceptors, the G protein-coupled receptor rhodopsin is organized in tracks of dimers thereby providing a signaling platform for the dynamic scaffolding of the G protein transducin. Illuminated rhodopsin is turned off by phosphorylation catalyzed by rhodopsin kinase GRK1 under control of Ca2+-recoverin. The GRK1 protein complex partly assembles in lipid raft structures, where shutting off rhodopsin seems to be more effective. Re-synthesis of cGMP is another crucial step in the recovery of the photoresponse after illumination. It is catalyzed by membrane bound sensory guanylate cyclases and is regulated by specific neuronal Ca2+-sensor proteins called GCAPs. At least one guanylate cyclase (ROS-GC1 was shown to be part of a multiprotein complex having strong interactions with the cytoskeleton and being controlled in a multimodal Ca2+-dependent fashion. The final target of the cGMP signaling cascade is a cyclic nucleotide-gated channel that is a hetero-oligomeric protein located in the plasma membrane and interacting with accessory proteins in highly organized microdomains. We summarize results and interpretations of findings related to the inhomogeneous organization of signaling units in photoreceptor outer segments.

  12. Anthocyanins: targeting of signaling networks in cancer cells.

    Science.gov (United States)

    Sehitoglu, Muserref Hilal; Farooqi, Ammad Ahmad; Qureshi, Muhammad Zahid; Butt, Ghazala; Aras, Aliye

    2014-01-01

    It is becoming progressively more understandable that phytochemicals derived from edible plants have shown potential in modelling their interactions with their target proteins. Rapidly accumulating in-vitro and in- vivo evidence indicates that anthocyanins have anticancer activity in rodent models of cancer. More intriguingly, evaluation of bilberry anthocyanins as chemopreventive agents in twenty-five colorectal cancer patients has opened new window of opportunity in translating the findings from laboratory to clinic. Confluence of information suggests that anthocyanins treated cancer cells reveal up-regulation of tumor suppressor genes. There is a successive increase in the research-work in nutrigenomics and evidence has started to shed light on intracellular-signaling cascades as common molecular targets for anthocyanins. In this review we bring to limelight how anthocyanins induced apoptosis in cancer cells via activation of extrinsic and intrinsic pathways.

  13. A system of recurrent neural networks for modularising, parameterising and dynamic analysis of cell signalling networks.

    Science.gov (United States)

    Samarasinghe, S; Ling, H

    In this paper, we show how to extend our previously proposed novel continuous time Recurrent Neural Networks (RNN) approach that retains the advantage of continuous dynamics offered by Ordinary Differential Equations (ODE) while enabling parameter estimation through adaptation, to larger signalling networks using a modular approach. Specifically, the signalling network is decomposed into several sub-models based on important temporal events in the network. Each sub-model is represented by the proposed RNN and trained using data generated from the corresponding ODE model. Trained sub-models are assembled into a whole system RNN which is then subjected to systems dynamics and sensitivity analyses. The concept is illustrated by application to G1/S transition in cell cycle using Iwamoto et al. (2008) ODE model. We decomposed the G1/S network into 3 sub-models: (i) E2F transcription factor release; (ii) E2F and CycE positive feedback loop for elevating cyclin levels; and (iii) E2F and CycA negative feedback to degrade E2F. The trained sub-models accurately represented system dynamics and parameters were in good agreement with the ODE model. The whole system RNN however revealed couple of parameters contributing to compounding errors due to feedback and required refinement to sub-model 2. These related to the reversible reaction between CycE/CDK2 and p27, its inhibitor. The revised whole system RNN model very accurately matched dynamics of the ODE system. Local sensitivity analysis of the whole system model further revealed the most dominant influence of the above two parameters in perturbing G1/S transition, giving support to a recent hypothesis that the release of inhibitor p27 from Cyc/CDK complex triggers cell cycle stage transition. To make the model useful in a practical setting, we modified each RNN sub-model with a time relay switch to facilitate larger interval input data (≈20min) (original model used data for 30s or less) and retrained them that produced

  14. Guard Cell Signal Transduction Network: Advances in Understanding Abscisic Acid, CO2, and Ca2+ Signaling

    KAUST Repository

    Kim, Tae-Houn

    2010-05-04

    Stomatal pores are formed by pairs of specialized epidermal guard cells and serve as major gateways for both CO2 influx into plants from the atmosphere and transpirational water loss of plants. Because they regulate stomatal pore apertures via integration of both endogenous hormonal stimuli and environmental signals, guard cells have been highly developed as a model system to dissect the dynamics and mechanisms of plant-cell signaling. The stress hormone ABA and elevated levels of CO2 activate complex signaling pathways in guard cells that are mediated by kinases/phosphatases, secondary messengers, and ion channel regulation. Recent research in guard cells has led to a new hypothesis for how plants achieve specificity in intracellular calcium signaling: CO2 and ABA enhance (prime) the calcium sensitivity of downstream calcium-signaling mechanisms. Recent progress in identification of early stomatal signaling components are reviewed here, including ABA receptors and CO2-binding response proteins, as well as systems approaches that advance our understanding of guard cell-signaling mechanisms.

  15. Data-driven quantification of the robustness and sensitivity of cell signaling networks

    International Nuclear Information System (INIS)

    Mukherjee, Sayak; Seok, Sang-Cheol; Vieland, Veronica J; Das, Jayajit

    2013-01-01

    Robustness and sensitivity of responses generated by cell signaling networks has been associated with survival and evolvability of organisms. However, existing methods analyzing robustness and sensitivity of signaling networks ignore the experimentally observed cell-to-cell variations of protein abundances and cell functions or contain ad hoc assumptions. We propose and apply a data-driven maximum entropy based method to quantify robustness and sensitivity of Escherichia coli (E. coli) chemotaxis signaling network. Our analysis correctly rank orders different models of E. coli chemotaxis based on their robustness and suggests that parameters regulating cell signaling are evolutionary selected to vary in individual cells according to their abilities to perturb cell functions. Furthermore, predictions from our approach regarding distribution of protein abundances and properties of chemotactic responses in individual cells based on cell population averaged data are in excellent agreement with their experimental counterparts. Our approach is general and can be used to evaluate robustness as well as generate predictions of single cell properties based on population averaged experimental data in a wide range of cell signaling systems. (paper)

  16. The effect of Scutellaria baicalensis on the signaling network in hepatocellular carcinoma cells.

    Science.gov (United States)

    Ye, Fei; Che, Yufang; McMillen, Elizabeth; Gorski, Justin; Brodman, Douglas; Saw, Daisy; Jiang, Bo; Zhang, David Y

    2009-01-01

    Scutellaria baicalensis is an anti-inflammatory and antineoplastic Chinese herbal therapy. We have previously shown that S. baicalensis can inhibit hepatocellular carcinoma (HCC) cell growth in vitro. In this study, we sought to determine the effect of S. baicalensis on the cell signaling network using our newly developed Pathway Array technology, which screens cell signaling pathways involved in cell cycle regulation. The HCC cell line (HepG2) was treated with S. baicalensis extract in vitro. The effect on the cell cycle was analyzed by flow cytometry, and the expression of various signaling proteins was assayed with Pathway Array. Our results indicate that S. baicalensis exerts a strong growth inhibition of the HepG2 cells via G(2)/M phase arrest. The Pathway Array analysis of 56 proteins revealed a total of 14 differentially expressed proteins or phosphorylations after treatment. Of these, 9 showed a dose-dependent decrease (p53, ETS1, Cdc25B, p63, EGFR, ERK1/2, XIAP, HIF-2alpha, and Cdc25C) whereas one demonstrated a dose-dependent increase (Cyclin E) after treatment with 200 microg/ml of S. baicalensis. Using computer simulation software, we identified additional hubs in the signaling network activated by S. baicalensis. These results indicate that S. baicalensis exerts a broad effect on cell signaling networks leading to a collective inhibition of cell proliferation.

  17. In vitro membrane reconstitution of the T cell receptor proximal signaling network

    OpenAIRE

    Hui, Enfu; Vale, Ronald D.

    2014-01-01

    T-cell receptor (TCR) phosphorylation is controlled by a complex network that includes Lck, a Src family kinase (SFK), the tyrosine phosphatase CD45, and the Lck-inhibitory kinase Csk. How these competing phosphorylation and dephosphorylation reactions are modulated to produce T-cell triggering is not fully understood. Here we reconstituted this signaling network using purified enzymes on liposomes, recapitulating the membrane environment in which they normally interact. We demonstrate that L...

  18. [Cellular adhesion signal transduction network of tumor necrosis factor-alpha induced hepatocellular carcinoma cells].

    Science.gov (United States)

    Zheng, Yongchang; Du, Shunda; Xu, Haifeng; Xu, Yiyao; Zhao, Haitao; Chi, Tianyi; Lu, Xin; Sang, Xinting; Mao, Yilei

    2014-11-18

    To systemically explore the cellular adhesion signal transduction network of tumor necrosis factor-alpha (TNF-α)-induced hepatocellular carcinoma cells with bioinformatics tools. Published microarray dataset of TNF-α-induced HepG2, human transcription factor database HTRI and human protein-protein interaction database HPRD were used to construct and analyze the signal transduction network. In the signal transduction network, MYC and SP1 were the key nodes of signaling transduction. Several genes from the network were closely related with cellular adhesion.Epidermal growth factor receptor (EGFR) is a possible key gene of effectively regulating cellular adhesion during the induction of TNF-α. EGFR is a possible key gene for TNF-α-induced metastasis of hepatocellular carcinoma.

  19. Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

    Science.gov (United States)

    Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

    2011-01-01

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

  20. Synaptic network activity induces neuronal differentiation of adult hippocampal precursor cells through BDNF signaling

    Directory of Open Access Journals (Sweden)

    Harish Babu

    2009-09-01

    Full Text Available Adult hippocampal neurogenesis is regulated by activity. But how do neural precursor cells in the hippocampus respond to surrounding network activity and translate increased neural activity into a developmental program? Here we show that long-term potential (LTP-like synaptic activity within a cellular network of mature hippocampal neurons promotes neuronal differentiation of newly generated cells. In co-cultures of precursor cells with primary hippocampal neurons, LTP-like synaptic plasticity induced by addition of glycine in Mg2+-free media for 5 min, produced synchronous network activity and subsequently increased synaptic strength between neurons. Furthermore, this synchronous network activity led to a significant increase in neuronal differentiation from the co-cultured neural precursor cells. When applied directly to precursor cells, glycine and Mg2+-free solution did not induce neuronal differentiation. Synaptic plasticity-induced neuronal differentiation of precursor cells was observed in the presence of GABAergic neurotransmission blockers but was dependent on NMDA-mediated Ca2+ influx. Most importantly, neuronal differentiation required the release of brain-derived neurotrophic factor (BDNF from the underlying substrate hippocampal neurons as well as TrkB receptor phosphorylation in precursor cells. This suggests that activity-dependent stem cell differentiation within the hippocampal network is mediated via synaptically evoked BDNF signaling.

  1. In vitro membrane reconstitution of the T-cell receptor proximal signaling network.

    Science.gov (United States)

    Hui, Enfu; Vale, Ronald D

    2014-02-01

    T-cell receptor (TCR) phosphorylation is controlled by a complex network that includes Lck, a Src family kinase (SFK), the tyrosine phosphatase CD45 and the Lck-inhibitory kinase Csk. How these competing phosphorylation and dephosphorylation reactions are modulated to produce T-cell triggering is not fully understood. Here we reconstituted this signaling network using purified enzymes on liposomes, recapitulating the membrane environment in which they normally interact. We demonstrate that Lck's enzymatic activity can be regulated over an ~10-fold range by controlling its phosphorylation state. By varying kinase and phosphatase concentrations, we constructed phase diagrams that reveal ultrasensitivity in the transition from the quiescent to the phosphorylated state and demonstrate that co-clustering TCR and Lck or detaching Csk from the membrane can trigger TCR phosphorylation. Our results provide insight into the mechanism of TCR signaling as well as other signaling pathways involving SFKs.

  2. Signaling network of dendritic cells in response to pathogens: a community-input supported knowledgebase

    Directory of Open Access Journals (Sweden)

    Nudelman Irina

    2010-10-01

    Full Text Available Abstract Background Dendritic cells are antigen-presenting cells that play an essential role in linking the innate and adaptive immune systems. Much research has focused on the signaling pathways triggered upon infection of dendritic cells by various pathogens. The high level of activity in the field makes it desirable to have a pathway-based resource to access the information in the literature. Current pathway diagrams lack either comprehensiveness, or an open-access editorial interface. Hence, there is a need for a dependable, expertly curated knowledgebase that integrates this information into a map of signaling networks. Description We have built a detailed diagram of the dendritic cell signaling network, with the goal of providing researchers with a valuable resource and a facile method for community input. Network construction has relied on comprehensive review of the literature and regular updates. The diagram includes detailed depictions of pathways activated downstream of different pathogen recognition receptors such as Toll-like receptors, retinoic acid-inducible gene-I-like receptors, C-type lectin receptors and nucleotide-binding oligomerization domain-like receptors. Initially assembled using CellDesigner software, it provides an annotated graphical representation of interactions stored in Systems Biology Mark-up Language. The network, which comprises 249 nodes and 213 edges, has been web-published through the Biological Pathway Publisher software suite. Nodes are annotated with PubMed references and gene-related information, and linked to a public wiki, providing a discussion forum for updates and corrections. To gain more insight into regulatory patterns of dendritic cell signaling, we analyzed the network using graph-theory methods: bifan, feedforward and multi-input convergence motifs were enriched. This emphasis on activating control mechanisms is consonant with a network that subserves persistent and coordinated responses to

  3. Hypoxia induces a phase transition within a kinase signaling network in cancer cells.

    Science.gov (United States)

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B; Shin, Young Shik; Mischel, Paul S; Levine, R D; Heath, James R

    2013-04-09

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)--a critical component of hypoxic signaling and a compelling cancer drug target--is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier's principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles.

  4. Hypoxia induces a phase transition within a kinase signaling network in cancer cells

    Science.gov (United States)

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B.; Shin, Young Shik; Mischel, Paul S.; Levine, R. D.; Heath, James R.

    2013-01-01

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)—a critical component of hypoxic signaling and a compelling cancer drug target—is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier’s principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles. PMID:23530221

  5. Cytotoxic Vibrio T3SS1 Rewires Host Gene Expression to Subvert Cell Death Signaling and Activate Cell Survival Networks

    Science.gov (United States)

    De Nisco, Nicole J.; Kanchwala, Mohammed; Li, Peng; Fernandez, Jessie; Xing, Chao; Orth, Kim

    2017-01-01

    Bacterial effectors are potent manipulators of host signaling pathways. The marine bacterium Vibrio parahaemolyticus (V. para), delivers effectors into host cells through two type three secretion systems (T3SS). The ubiquitous T3SS1 is vital for V. para survival in the environment, whereas T3SS2 causes acute gastroenteritis in human hosts. Although the natural host is undefined, T3SS1 effectors attack highly conserved cellular processes and pathways to orchestrate non-apoptotic cell death. Much is known about how T3SS1 effectors function in isolation, but we wanted to understand how their concerted action globally affects host cell signaling. To assess the host response to T3SS1, we compared gene expression changes over time in primary fibroblasts infected with V. para that have a functional T3SS1 (T3SS1+) to those in cells infected with V. para lacking T3SS1 (T3SS1−). Overall, the host transcriptional response to both T3SS1+ and T3SS1− V. para was rapid, robust, and temporally dynamic. T3SS1 re-wired host gene expression by specifically altering the expression of 398 genes. Although T3SS1 effectors target host cells at the posttranslational level to cause cytotoxicity, network analysis indicated that V. para T3SS1 also precipitates a host transcriptional response that initially activates cell survival and represses cell death networks. The increased expression of several key pro-survival transcripts mediated by T3SS1 was dependent on a host signaling pathway that is silenced later in infection by the posttranslational action of T3SS1. Taken together, our analysis reveals a complex interplay between roles of T3SS1 as both a transcriptional and posttranslational manipulator of host cell signaling. PMID:28512145

  6. Chronic occupational exposure to arsenic induces carcinogenic gene signaling networks and neoplastic transformation in human lung epithelial cells

    International Nuclear Information System (INIS)

    Stueckle, Todd A.; Lu, Yongju; Davis, Mary E.; Wang, Liying; Jiang, Bing-Hua; Holaskova, Ida; Schafer, Rosana; Barnett, John B.; Rojanasakul, Yon

    2012-01-01

    Chronic arsenic exposure remains a human health risk; however a clear mode of action to understand gene signaling-driven arsenic carcinogenesis is currently lacking. This study chronically exposed human lung epithelial BEAS-2B cells to low-dose arsenic trioxide to elucidate cancer promoting gene signaling networks associated with arsenic-transformed (B-As) cells. Following a 6 month exposure, exposed cells were assessed for enhanced cell proliferation, colony formation, invasion ability and in vivo tumor formation compared to control cell lines. Collected mRNA was subjected to whole genome expression microarray profiling followed by in silico Ingenuity Pathway Analysis (IPA) to identify lung carcinogenesis modes of action. B-As cells displayed significant increases in proliferation, colony formation and invasion ability compared to BEAS-2B cells. B-As injections into nude mice resulted in development of primary and secondary metastatic tumors. Arsenic exposure resulted in widespread up-regulation of genes associated with mitochondrial metabolism and increased reactive oxygen species protection suggesting mitochondrial dysfunction. Carcinogenic initiation via reactive oxygen species and epigenetic mechanisms was further supported by altered DNA repair, histone, and ROS-sensitive signaling. NF-κB, MAPK and NCOR1 signaling disrupted PPARα/δ-mediated lipid homeostasis. A ‘pro-cancer’ gene signaling network identified increased survival, proliferation, inflammation, metabolism, anti-apoptosis and mobility signaling. IPA-ranked signaling networks identified altered p21, EF1α, Akt, MAPK, and NF-κB signaling networks promoting genetic disorder, altered cell cycle, cancer and changes in nucleic acid and energy metabolism. In conclusion, transformed B-As cells with their whole genome expression profile provide an in vitro arsenic model for future lung cancer signaling research and data for chronic arsenic exposure risk assessment. Highlights: ► Chronic As 2 O 3

  7. Chronic occupational exposure to arsenic induces carcinogenic gene signaling networks and neoplastic transformation in human lung epithelial cells

    Energy Technology Data Exchange (ETDEWEB)

    Stueckle, Todd A., E-mail: tstueckle@hsc.wvu.edu [Department of Basic Pharmaceutical Sciences, West Virginia University, Morgantown, WV 26506 (United States); Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, WV 26505 (United States); Lu, Yongju, E-mail: yongju6@hotmail.com [Department of Basic Pharmaceutical Sciences, West Virginia University, Morgantown, WV 26506 (United States); Davis, Mary E., E-mail: mdavis@wvu.edu [Department of Physiology, West Virginia University, Morgantown, WV 26506 (United States); Wang, Liying, E-mail: lmw6@cdc.gov [Health Effects Laboratory Division, National Institute for Occupational Safety and Health, Morgantown, WV 26505 (United States); Jiang, Bing-Hua, E-mail: bhjiang@jefferson.edu [Department of Pathology, Anatomy and Cell Biology, Thomas Jefferson University, Philadelphia, PA 19107 (United States); Holaskova, Ida, E-mail: iholaskova@hsc.wvu.edu [Department of Microbiology, Immunology and Cell Biology, West Virginia University, Morgantown, WV 26506 (United States); Schafer, Rosana, E-mail: rschafer@hsc.wvu.edu [Department of Microbiology, Immunology and Cell Biology, West Virginia University, Morgantown, WV 26506 (United States); Barnett, John B., E-mail: jbarnett@hsc.wvu.edu [Department of Microbiology, Immunology and Cell Biology, West Virginia University, Morgantown, WV 26506 (United States); Rojanasakul, Yon, E-mail: yrojan@hsc.wvu.edu [Department of Basic Pharmaceutical Sciences, West Virginia University, Morgantown, WV 26506 (United States)

    2012-06-01

    Chronic arsenic exposure remains a human health risk; however a clear mode of action to understand gene signaling-driven arsenic carcinogenesis is currently lacking. This study chronically exposed human lung epithelial BEAS-2B cells to low-dose arsenic trioxide to elucidate cancer promoting gene signaling networks associated with arsenic-transformed (B-As) cells. Following a 6 month exposure, exposed cells were assessed for enhanced cell proliferation, colony formation, invasion ability and in vivo tumor formation compared to control cell lines. Collected mRNA was subjected to whole genome expression microarray profiling followed by in silico Ingenuity Pathway Analysis (IPA) to identify lung carcinogenesis modes of action. B-As cells displayed significant increases in proliferation, colony formation and invasion ability compared to BEAS-2B cells. B-As injections into nude mice resulted in development of primary and secondary metastatic tumors. Arsenic exposure resulted in widespread up-regulation of genes associated with mitochondrial metabolism and increased reactive oxygen species protection suggesting mitochondrial dysfunction. Carcinogenic initiation via reactive oxygen species and epigenetic mechanisms was further supported by altered DNA repair, histone, and ROS-sensitive signaling. NF-κB, MAPK and NCOR1 signaling disrupted PPARα/δ-mediated lipid homeostasis. A ‘pro-cancer’ gene signaling network identified increased survival, proliferation, inflammation, metabolism, anti-apoptosis and mobility signaling. IPA-ranked signaling networks identified altered p21, EF1α, Akt, MAPK, and NF-κB signaling networks promoting genetic disorder, altered cell cycle, cancer and changes in nucleic acid and energy metabolism. In conclusion, transformed B-As cells with their whole genome expression profile provide an in vitro arsenic model for future lung cancer signaling research and data for chronic arsenic exposure risk assessment. Highlights: ► Chronic As{sub 2}O

  8. QSSPN: dynamic simulation of molecular interaction networks describing gene regulation, signalling and whole-cell metabolism in human cells.

    Science.gov (United States)

    Fisher, Ciarán P; Plant, Nicholas J; Moore, J Bernadette; Kierzek, Andrzej M

    2013-12-15

    Dynamic simulation of genome-scale molecular interaction networks will enable the mechanistic prediction of genotype-phenotype relationships. Despite advances in quantitative biology, full parameterization of whole-cell models is not yet possible. Simulation methods capable of using available qualitative data are required to develop dynamic whole-cell models through an iterative process of modelling and experimental validation. We formulate quasi-steady state Petri nets (QSSPN), a novel method integrating Petri nets and constraint-based analysis to predict the feasibility of qualitative dynamic behaviours in qualitative models of gene regulation, signalling and whole-cell metabolism. We present the first dynamic simulations including regulatory mechanisms and a genome-scale metabolic network in human cell, using bile acid homeostasis in human hepatocytes as a case study. QSSPN simulations reproduce experimentally determined qualitative dynamic behaviours and permit mechanistic analysis of genotype-phenotype relationships. The model and simulation software implemented in C++ are available in supplementary material and at http://sysbio3.fhms.surrey.ac.uk/qsspn/.

  9. Multi-OMIC profiling of survival and metabolic signaling networks in cells subjected to photodynamic therapy.

    Science.gov (United States)

    Weijer, Ruud; Clavier, Séverine; Zaal, Esther A; Pijls, Maud M E; van Kooten, Robert T; Vermaas, Klaas; Leen, René; Jongejan, Aldo; Moerland, Perry D; van Kampen, Antoine H C; van Kuilenburg, André B P; Berkers, Celia R; Lemeer, Simone; Heger, Michal

    2017-03-01

    Photodynamic therapy (PDT) is an established palliative treatment for perihilar cholangiocarcinoma that is clinically promising. However, tumors tend to regrow after PDT, which may result from the PDT-induced activation of survival pathways in sublethally afflicted tumor cells. In this study, tumor-comprising cells (i.e., vascular endothelial cells, macrophages, perihilar cholangiocarcinoma cells, and EGFR-overexpressing epidermoid cancer cells) were treated with the photosensitizer zinc phthalocyanine that was encapsulated in cationic liposomes (ZPCLs). The post-PDT survival pathways and metabolism were studied following sublethal (LC 50 ) and supralethal (LC 90 ) PDT. Sublethal PDT induced survival signaling in perihilar cholangiocarcinoma (SK-ChA-1) cells via mainly HIF-1-, NF-кB-, AP-1-, and heat shock factor (HSF)-mediated pathways. In contrast, supralethal PDT damage was associated with a dampened survival response. PDT-subjected SK-ChA-1 cells downregulated proteins associated with EGFR signaling, particularly at LC 90 . PDT also affected various components of glycolysis and the tricarboxylic acid cycle as well as metabolites involved in redox signaling. In conclusion, sublethal PDT activates multiple pathways in tumor-associated cell types that transcriptionally regulate cell survival, proliferation, energy metabolism, detoxification, inflammation/angiogenesis, and metastasis. Accordingly, tumor cells sublethally afflicted by PDT are a major therapeutic culprit. Our multi-omic analysis further unveiled multiple druggable targets for pharmacological co-intervention.

  10. Simulated evolution of signal transduction networks.

    Directory of Open Access Journals (Sweden)

    Mohammad Mobashir

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

  11. Detection and Elimination of Oncogenic Signaling Networks in Premalignant and Malignant Cells with Magnetic Resonance Imaging

    Science.gov (United States)

    2015-10-01

    Molecular Subtype Cell Line Luminal MCF7 T-47D HER2 BT474M1 KPL4 Triple Negative MDA-MB-468 MDA-MB-231 DCIS MCF10.DCIS.COM SUM225 GEMM MMTV...tumor model. 51 LUMINAL TYPE BREAST CANCER MCF-7 Tumor Figure 42A Figure 42A. MCF7 tumor imaging with HS-118 and HS165: nIR Signals. HS118 or...nm channel) from tumor area were detected by Pearl Imager. Figure 42B Figure 42B. Over time change of nIR signals from MCF7 Tumors: HS118 vs. HS165

  12. Detection and Elimination of Oncogenic Signalling Networks in Premalignant and Malignant Cells with Magnetic Resonance Imaging

    Science.gov (United States)

    2015-10-01

    Molecular Subtype Cell Line Luminal MCF7 T-47D HER2 BT474M1 KPL4 Triple Negative MDA-MB-468 MDA-MB-231 DCIS MCF10.DCIS.COM SUM225 GEMM MMTV...tumor model. 51 LUMINAL TYPE BREAST CANCER MCF-7 Tumor Figure 42A Figure 42A. MCF7 tumor imaging with HS-118 and HS165: nIR Signals. HS118 or...nm channel) from tumor area were detected by Pearl Imager. Figure 42B Figure 42B. Over time change of nIR signals from MCF7 Tumors: HS118 vs. HS165

  13. Networks in Cell Biology

    Science.gov (United States)

    Buchanan, Mark; Caldarelli, Guido; De Los Rios, Paolo; Rao, Francesco; Vendruscolo, Michele

    2010-05-01

    Introduction; 1. Network views of the cell Paolo De Los Rios and Michele Vendruscolo; 2. Transcriptional regulatory networks Sarath Chandra Janga and M. Madan Babu; 3. Transcription factors and gene regulatory networks Matteo Brilli, Elissa Calistri and Pietro Lió; 4. Experimental methods for protein interaction identification Peter Uetz, Björn Titz, Seesandra V. Rajagopala and Gerard Cagney; 5. Modeling protein interaction networks Francesco Rao; 6. Dynamics and evolution of metabolic networks Daniel Segré; 7. Hierarchical modularity in biological networks: the case of metabolic networks Erzsébet Ravasz Regan; 8. Signalling networks Gian Paolo Rossini; Appendix 1. Complex networks: from local to global properties D. Garlaschelli and G. Caldarelli; Appendix 2. Modelling the local structure of networks D. Garlaschelli and G. Caldarelli; Appendix 3. Higher-order topological properties S. Ahnert, T. Fink and G. Caldarelli; Appendix 4. Elementary mathematical concepts A. Gabrielli and G. Caldarelli; References.

  14. Cytotoxic Vibrio T3SS1 Rewires Host Gene Expression to Subvert Cell Death Signaling and Activate Cell Survival Networks

    OpenAIRE

    De Nisco, Nicole J.; Kanchwala, Mohammed; Li, Peng; Fernandez, Jessie; Xing, Chao; Orth, Kim

    2017-01-01

    Bacterial effectors are potent manipulators of host signaling pathways. The marine bacterium Vibrio parahaemolyticus (V. para), delivers effectors into host cells through two type three secretion systems (T3SS). The ubiquitous T3SS1 is vital for V. para survival in the environment, whereas T3SS2 causes acute gastroenteritis in human hosts. Although the natural host is undefined, T3SS1 effectors attack highly conserved cellular processes and pathways to orchestrate non-apoptotic cell death. Mu...

  15. Identification of the arabidopsis RAM/MOR signalling network: adding new regulatory players in plant stem cell maintenance and cell polarization

    Science.gov (United States)

    Zermiani, Monica; Begheldo, Maura; Nonis, Alessandro; Palme, Klaus; Mizzi, Luca; Morandini, Piero; Nonis, Alberto; Ruperti, Benedetto

    2015-01-01

    Background and Aims The RAM/MOR signalling network of eukaryotes is a conserved regulatory module involved in co-ordination of stem cell maintenance, cell differentiation and polarity establishment. To date, no such signalling network has been identified in plants. Methods Genes encoding the bona fide core components of the RAM/MOR pathway were identified in Arabidopsis thaliana (arabidopsis) by sequence similarity searches conducted with the known components from other species. The transcriptional network(s) of the arabidopsis RAM/MOR signalling pathway were identified by running in-depth in silico analyses for genes co-regulated with the core components. In situ hybridization was used to confirm tissue-specific expression of selected RAM/MOR genes. Key Results Co-expression data suggested that the arabidopsis RAM/MOR pathway may include genes involved in floral transition, by co-operating with chromatin remodelling and mRNA processing/post-transcriptional gene silencing factors, and genes involved in the regulation of pollen tube polar growth. The RAM/MOR pathway may act upstream of the ROP1 machinery, affecting pollen tube polar growth, based on the co-expression of its components with ROP-GEFs. In silico tissue-specific co-expression data and in situ hybridization experiments suggest that different components of the arabidopsis RAM/MOR are expressed in the shoot apical meristem and inflorescence meristem and may be involved in the fine-tuning of stem cell maintenance and cell differentiation. Conclusions The arabidopsis RAM/MOR pathway may be part of the signalling cascade that converges in pollen tube polarized growth and in fine-tuning stem cell maintenance, differentiation and organ polarity. PMID:26078466

  16. ErbB2-Driven Breast Cancer Cell Invasion Depends on a Complex Signaling Network Activating Myeloid Zinc Finger-1-Dependent Cathepsin B Expression

    DEFF Research Database (Denmark)

    Rafn, Bo; Nielsen, Christian Thomas Friberg; Andersen, Sofie Hagel

    2012-01-01

    signaling network activates the transcription of cathepsin B gene (CTSB) via myeloid zinc finger-1 transcription factor that binds to an ErbB2-responsive enhancer element in the first intron of CTSB. This work provides a model system for ErbB2-induced breast cancer cell invasiveness, reveals a signaling...

  17. Functional characterization of FLT3 receptor signaling deregulation in acute myeloid leukemia by single cell network profiling (SCNP.

    Directory of Open Access Journals (Sweden)

    David B Rosen

    Full Text Available BACKGROUND: Molecular characterization of the FMS-like tyrosine kinase 3 receptor (FLT3 in cytogenetically normal acute myeloid leukemia (AML has recently been incorporated into clinical guidelines based on correlations between FLT3 internal tandem duplications (FLT3-ITD and decreased disease-free and overall survival. These mutations result in constitutive activation of FLT3, and FLT3 inhibitors are currently undergoing trials in AML patients selected on FLT3 molecular status. However, the transient and partial responses observed suggest that FLT3 mutational status alone does not provide complete information on FLT3 biological activity at the individual patient level. Examination of variation in cellular responsiveness to signaling modulation may be more informative. METHODOLOGY/PRINCIPAL FINDINGS: Using single cell network profiling (SCNP, cells were treated with extracellular modulators and their functional responses were quantified by multiparametric flow cytometry. Intracellular signaling responses were compared between healthy bone marrow myeloblasts (BMMb and AML leukemic blasts characterized as FLT3 wild type (FLT3-WT or FLT3-ITD. Compared to healthy BMMb, FLT3-WT leukemic blasts demonstrated a wide range of signaling responses to FLT3 ligand (FLT3L, including elevated and sustained PI3K and Ras/Raf/Erk signaling. Distinct signaling and apoptosis profiles were observed in FLT3-WT and FLT3-ITD AML samples, with more uniform signaling observed in FLT3-ITD AML samples. Specifically, increased basal p-Stat5 levels, decreased FLT3L induced activation of the PI3K and Ras/Raf/Erk pathways, decreased IL-27 induced activation of the Jak/Stat pathway, and heightened apoptotic responses to agents inducing DNA damage were observed in FLT3-ITD AML samples. Preliminary analysis correlating these findings with clinical outcomes suggests that classification of patient samples based on signaling profiles may more accurately reflect FLT3 signaling

  18. E2A-PBX1 Remodels Oncogenic Signaling Networks in B-cell Precursor Acute Lymphoid Leukemia.

    Science.gov (United States)

    Duque-Afonso, Jesús; Lin, Chiou-Hong; Han, Kyuho; Wei, Michael C; Feng, Jue; Kurzer, Jason H; Schneidawind, Corina; Wong, Stephen Hon-Kit; Bassik, Michael C; Cleary, Michael L

    2016-12-01

    There is limited understanding of how signaling pathways are altered by oncogenic fusion transcription factors that drive leukemogenesis. To address this, we interrogated activated signaling pathways in a comparative analysis of mouse and human leukemias expressing the fusion protein E2A-PBX1, which is present in 5%-7% of pediatric and 50% of pre-B-cell receptor (preBCR + ) acute lymphocytic leukemia (ALL). In this study, we describe remodeling of signaling networks by E2A-PBX1 in pre-B-ALL, which results in hyperactivation of the key oncogenic effector enzyme PLCγ2. Depletion of PLCγ2 reduced proliferation of mouse and human ALLs, including E2A-PBX1 leukemias, and increased disease-free survival after secondary transplantation. Mechanistically, E2A-PBX1 bound promoter regulatory regions and activated the transcription of its key target genes ZAP70, SYK, and LCK, which encode kinases upstream of PLCγ2. Depletion of the respective upstream kinases decreased cell proliferation and phosphorylated levels of PLCγ2 (pPLCγ2). Pairwise silencing of ZAP70, SYK, or LCK showed additive effects on cell growth inhibition, providing a rationale for combination therapy with inhibitors of these kinases. Accordingly, inhibitors such as the SRC family kinase (SFK) inhibitor dasatinib reduced pPLCγ2 and inhibited proliferation of human and mouse preBCR + /E2A-PBX1 + leukemias in vitro and in vivo Furthermore, combining small-molecule inhibition of SYK, LCK, and SFK showed synergistic interactions and preclinical efficacy in the same setting. Our results show how the oncogenic fusion protein E2A-PBX1 perturbs signaling pathways upstream of PLCγ2 and renders leukemias amenable to targeted therapeutic inhibition. Cancer Res; 76(23); 6937-49. ©2016 AACR. ©2016 American Association for Cancer Research.

  19. Chronic morphine treatment attenuates cell growth of human BT474 breast cancer cells by rearrangement of the ErbB signalling network.

    Directory of Open Access Journals (Sweden)

    Inka Regine Weingaertner

    Full Text Available There is increasing evidence that opioid analgesics may interfere with tumour growth. It is currently thought that these effects are mediated by transactivation of receptor tyrosine kinase (RTK-controlled ERK1/2 and Akt signalling. The growth of many breast cancer cells is dependent on hyperactive ErbB receptor networks and one of the most successful approaches in antineoplastic therapy during the last decade was the development of ErbB-targeted therapies. However, the response rates of single therapies are often poor and resistance mechanisms evolve rapidly. To date there is no information about the ability of opioid analgesics to interfere with the growth of ErbB-driven cancers.Here we demonstrate that ErbB2 overexpressing BT474 human breast cancer cells carry fully functional endogenous µ-opioid receptors. Most interestingly, the acute opioid effects on basal and Heregulin-stimulated ERK1/2 and Akt phosphorylation changed considerably during chronic Morphine treatment. Investigation of the underlying mechanism by the use of protein kinase inhibitors and co-immunoprecipitation studies revealed that chronic Morphine treatment results in rearrangement of the ErbB signalling network leading to dissociation of ERK1/2 from Akt signalling and a switch from ErbB1/ErbB3 to ErbB1/ErbB2-dependent cell growth. In chronically Morphine-treated cells Heregulin-stimulated ERK1/2 signalling is redirected via a newly established PI3K- and metalloproteinase-dependent feedback loop. Together, these alterations result in apoptosis of BT474 cells. A similar switch in Heregulin-stimulated ERK1/2 signalling from an ErbB2-independent to an ErbB2-, PI3K- and metalloproteinase-dependent mechanism was also observed in κ-opioid receptor expressing SKBR3 human mammary adenocarcinoma cells.The present data demonstrate that the ErbB receptor network of human breast cancer cells represents a target for chronic Morphine treatment. Rearrangement of ErbB signalling by chronic

  20. Single-cell network profiling of peripheral blood mononuclear cells from healthy donors reveals age- and race-associated differences in immune signaling pathway activation.

    Science.gov (United States)

    Longo, Diane M; Louie, Brent; Putta, Santosh; Evensen, Erik; Ptacek, Jason; Cordeiro, James; Wang, Ena; Pos, Zoltan; Hawtin, Rachael E; Marincola, Francesco M; Cesano, Alessandra

    2012-02-15

    A greater understanding of the function of the human immune system at the single-cell level in healthy individuals is critical for discerning aberrant cellular behavior that occurs in settings such as autoimmunity, immunosenescence, and cancer. To achieve this goal, a systems-level approach capable of capturing the response of the interdependent immune cell types to external stimuli is required. In this study, an extensive characterization of signaling responses in multiple immune cell subpopulations within PBMCs from a cohort of 60 healthy donors was performed using single-cell network profiling (SCNP). SCNP is a multiparametric flow cytometry-based approach that enables the simultaneous measurement of basal and evoked signaling in multiple cell subsets within heterogeneous populations. In addition to establishing the interindividual degree of variation within a broad panel of immune signaling responses, the possible association of any observed variation with demographic variables including age and race was investigated. Using half of the donors as a training set, multiple age- and race-associated variations in signaling responses in discrete cell subsets were identified, and several were subsequently confirmed in the remaining samples (test set). Such associations may provide insight into age-related immune alterations associated with high infection rates and diminished protection following vaccination and into the basis for ethnic differences in autoimmune disease incidence and treatment response. SCNP allowed for the generation of a functional map of healthy immune cell signaling responses that can provide clinically relevant information regarding both the mechanisms underlying immune pathological conditions and the selection and effect of therapeutics.

  1. Neural networks in signal processing

    International Nuclear Information System (INIS)

    Govil, R.

    2000-01-01

    Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

  2. Discrete dynamic modeling of cellular signaling networks.

    Science.gov (United States)

    Albert, Réka; Wang, Rui-Sheng

    2009-01-01

    Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

  3. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.

    2013-01-01

    During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

  4. Spatio-temporal dependence of the signaling response in immune-receptor trafficking networks regulated by cell density: a theoretical model.

    Directory of Open Access Journals (Sweden)

    Pilar García-Peñarrubia

    Full Text Available Cell signaling processes involve receptor trafficking through highly connected networks of interacting components. The binding of surface receptors to their specific ligands is a key factor for the control and triggering of signaling pathways. In most experimental systems, ligand concentration and cell density vary within a wide range of values. Dependence of the signal response on cell density is related with the extracellular volume available per cell. This dependence has previously been studied using non-spatial models which assume that signaling components are well mixed and uniformly distributed in a single compartment. In this paper, a mathematical model that shows the influence exerted by cell density on the spatio-temporal evolution of ligands, cell surface receptors, and intracellular signaling molecules is developed. To this end, partial differential equations were used to model ligand and receptor trafficking dynamics through the different domains of the whole system. This enabled us to analyze several interesting features involved with these systems, namely: a how the perturbation caused by the signaling response propagates through the system; b receptor internalization dynamics and how cell density affects the robustness of dose-response curves upon variation of the binding affinity; and c that enhanced correlations between ligand input and system response are obtained under conditions that result in larger perturbations of the equilibrium ligand + surface receptor [Please see text] ligand - receptor complex. Finally, the results are compared with those obtained by considering that the above components are well mixed in a single compartment.

  5. A Cell-Signaling Network Temporally Resolves Specific versus Promiscuous Phosphorylation

    Directory of Open Access Journals (Sweden)

    Evgeny Kanshin

    2015-02-01

    Full Text Available If specific and functional kinase- or phosphatase-substrate interactions are optimized for binding compared to promiscuous interactions, then changes in phosphorylation should occur faster on functional versus promiscuous substrates. To test this hypothesis, we designed a high temporal resolution global phosphoproteomics protocol to study the high-osmolarity glycerol (HOG response in the budding yeast Saccharomyces cerevisiae. The method provides accurate, stimulus-specific measurement of phosphoproteome changes, quantitative analysis of phosphodynamics at sub-minute temporal resolution, and detection of more phosphosites. Rates of evolution of dynamic phosphosites were comparable to those of known functional phosphosites and significantly lower than static or longer-time-frame dynamic phosphosites. Kinetic profile analyses indicated that putatively functional kinase- or phosphatase-substrate interactions occur more rapidly, within 60 s, than promiscuous interactions. Finally, we report many changes in phosphorylation of proteins implicated in cytoskeletal and mitotic spindle dynamics that may underlie regulation of cell cycle and morphogenesis.

  6. Reconfigurable Analog Signal Processing by Living Cells.

    Science.gov (United States)

    Lewis, Daniel D; Chavez, Michael; Chiu, Kwan Lun; Tan, Cheemeng

    2018-01-19

    Living cells are known for their capacity for versatile signal processing, particularly the ability to respond differently to the same stimuli using biochemical networks that integrate environmental signals and reconfigure their dynamic responses. However, the complexity of natural biological networks confounds the discovery of fundamental mechanisms behind versatile signaling. Here, we study one specific aspect of reconfigurable signal processing in which a minimal biological network integrates two signals, using one to reconfigure the network's transfer function with respect to the other, producing an emergent switch between induction and repression. In contrast to known mechanisms, the new mechanism reconfigures transfer functions through genetic networks without extensive protein-protein interactions. These results provide a novel explanation for the versatility of genetic programs, and suggest a new mechanism of signal integration that may govern flexibility and plasticity of gene expression.

  7. Role of the insulin/Tor signaling network in starvation-induced programmed cell death in Drosophila oogenesis

    Science.gov (United States)

    Pritchett, T L; McCall, K

    2012-01-01

    Amino-acid starvation leads to an inhibition of cellular proliferation and the induction of programmed cell death (PCD) in the Drosophila ovary. Disruption of insulin signaling has been shown to inhibit the progression of oogenesis, but it is unclear whether this phenotype mimics starvation. Here, we investigate whether the insulin-mediated phosphoinositide kinase-3 pathway regulates PCD in mid oogenesis. We reasoned that under well-fed conditions, disruption of positive components of the insulin signaling pathway within the germline would mimic starvation and produce degenerating egg chambers. Surprisingly, mutants did not mimic starvation but instead produced many abnormal egg chambers in which the somatic follicle cells disappeared and the germline persisted. These abnormal egg chambers did not show an induction of caspases and lysosomes like that observed in wild-type (WT) degenerating egg chambers. Egg chambers from insulin signaling mutants were resistant to starvation-induced PCD, indicating that a complete block in insulin-signaling prevents the proper response to starvation. However, target of rapamycin (Tor) mutants did show a phenotype that mimicked WT starvation-induced PCD, indicating an insulin independent regulation of PCD via Tor signaling. These results suggest that inhibition of the insulin signaling pathway is not sufficient to regulate starvation-induced PCD in mid oogenesis. Furthermore, starvation-induced PCD is regulated by Tor signaling converging with the canonical insulin signaling pathway. PMID:22240900

  8. Collective Calcium Signaling of Defective Multicellular Networks

    Science.gov (United States)

    Potter, Garrett; Sun, Bo

    2015-03-01

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

  9. Defining a modular signalling network from the fly interactome.

    Science.gov (United States)

    Baudot, Anaïs; Angelelli, Jean-Baptiste; Guénoche, Alain; Jacq, Bernard; Brun, Christine

    2008-05-19

    Signalling pathways relay information by transmitting signals from cell surface receptors to intracellular effectors that eventually activate the transcription of target genes. Since signalling pathways involve several types of molecular interactions including protein-protein interactions, we postulated that investigating their organization in the context of the global protein-protein interaction network could provide a new integrated view of signalling mechanisms. Using a graph-theory based method to analyse the fly protein-protein interaction network, we found that each signalling pathway is organized in two to three different signalling modules. These modules contain canonical proteins of the signalling pathways, known regulators as well as other proteins thereby predicted to participate to the signalling mechanisms. Connections between the signalling modules are prominent as compared to the other network's modules and interactions within and between signalling modules are among the more central routes of the interaction network. Altogether, these modules form an interactome sub-network devoted to signalling with particular topological properties: modularity, density and centrality. This finding reflects the integration of the signalling system into cell functioning and its important role connecting and coordinating different biological processes at the level of the interactome.

  10. Defining a Modular Signalling Network from the Fly Interactome

    Directory of Open Access Journals (Sweden)

    Jacq Bernard

    2008-05-01

    Full Text Available Abstract Background Signalling pathways relay information by transmitting signals from cell surface receptors to intracellular effectors that eventually activate the transcription of target genes. Since signalling pathways involve several types of molecular interactions including protein-protein interactions, we postulated that investigating their organization in the context of the global protein-protein interaction network could provide a new integrated view of signalling mechanisms. Results Using a graph-theory based method to analyse the fly protein-protein interaction network, we found that each signalling pathway is organized in two to three different signalling modules. These modules contain canonical proteins of the signalling pathways, known regulators as well as other proteins thereby predicted to participate to the signalling mechanisms. Connections between the signalling modules are prominent as compared to the other network's modules and interactions within and between signalling modules are among the more central routes of the interaction network. Conclusion Altogether, these modules form an interactome sub-network devoted to signalling with particular topological properties: modularity, density and centrality. This finding reflects the integration of the signalling system into cell functioning and its important role connecting and coordinating different biological processes at the level of the interactome.

  11. Modeling evolution of crosstalk in noisy signal transduction networks

    Science.gov (United States)

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

    2018-02-01

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

  12. Defining a Modular Signalling Network from the Fly Interactome

    OpenAIRE

    Jacq Bernard; Guénoche Alain; Angelelli Jean-Baptiste; Baudot Anaïs; Brun Christine

    2008-01-01

    Abstract Background Signalling pathways relay information by transmitting signals from cell surface receptors to intracellular effectors that eventually activate the transcription of target genes. Since signalling pathways involve several types of molecular interactions including protein-protein interactions, we postulated that investigating their organization in the context of the global protein-protein interaction network could provide a new integrated view of signalling mechanisms. Results...

  13. Evaluation of phosphopeptide enrichment strategies for quantitative TMT analysis of complex network dynamics in cancer-associated cell signalling

    Directory of Open Access Journals (Sweden)

    Benedetta Lombardi

    2015-03-01

    Full Text Available Defining alterations in signalling pathways in normal and malignant cells is becoming a major field in proteomics. A number of different approaches have been established to isolate, identify and quantify phosphorylated proteins and peptides. In the current report, a comparison between SCX prefractionation versus an antibody based approach, both coupled to TiO2 enrichment and applied to TMT labelled cellular lysates, is described. The antibody strategy was more complete for enriching phosphopeptides and allowed the identification of a large set of proteins known to be phosphorylated (715 protein groups with a minimum number of not previously known phosphorylated proteins (2.

  14. Decoding signalling networks by mass spectrometry-based proteomics

    DEFF Research Database (Denmark)

    Choudhary, Chuna Ram; Mann, Matthias

    2010-01-01

    Signalling networks regulate essentially all of the biology of cells and organisms in normal and disease states. Signalling is often studied using antibody-based techniques such as western blots. Large-scale 'precision proteomics' based on mass spectrometry now enables the system...

  15. Elementary signaling modes predict the essentiality of signal transduction network components.

    Science.gov (United States)

    Wang, Rui-Sheng; Albert, Réka

    2011-03-22

    Understanding how signals propagate through signaling pathways and networks is a central goal in systems biology. Quantitative dynamic models help to achieve this understanding, but are difficult to construct and validate because of the scarcity of known mechanistic details and kinetic parameters. Structural and qualitative analysis is emerging as a feasible and useful alternative for interpreting signal transduction. In this work, we present an integrative computational method for evaluating the essentiality of components in signaling networks. This approach expands an existing signaling network to a richer representation that incorporates the positive or negative nature of interactions and the synergistic behaviors among multiple components. Our method simulates both knockout and constitutive activation of components as node disruptions, and takes into account the possible cascading effects of a node's disruption. We introduce the concept of elementary signaling mode (ESM), as the minimal set of nodes that can perform signal transduction independently. Our method ranks the importance of signaling components by the effects of their perturbation on the ESMs of the network. Validation on several signaling networks describing the immune response of mammals to bacteria, guard cell abscisic acid signaling in plants, and T cell receptor signaling shows that this method can effectively uncover the essentiality of components mediating a signal transduction process and results in strong agreement with the results of Boolean (logical) dynamic models and experimental observations. This integrative method is an efficient procedure for exploratory analysis of large signaling and regulatory networks where dynamic modeling or experimental tests are impractical. Its results serve as testable predictions, provide insights into signal transduction and regulatory mechanisms and can guide targeted computational or experimental follow-up studies. The source codes for the algorithms

  16. Reconstruction of periodic signals using neural networks

    Directory of Open Access Journals (Sweden)

    José Danilo Rairán Antolines

    2014-01-01

    Full Text Available In this paper, we reconstruct a periodic signal by using two neural networks. The first network is trained to approximate the period of a signal, and the second network estimates the corresponding coefficients of the signal's Fourier expansion. The reconstruction strategy consists in minimizing the mean-square error via backpro-pagation algorithms over a single neuron with a sine transfer function. Additionally, this paper presents mathematical proof about the quality of the approximation as well as a first modification of the algorithm, which requires less data to reach the same estimation; thus making the algorithm suitable for real-time implementations.

  17. Real-time relationship between PKA biochemical signal network dynamics and increased action potential firing rate in heart pacemaker cells

    Science.gov (United States)

    Yaniv, Yael; Ganesan, Ambhighainath; Yang, Dongmei; Ziman, Bruce D.; Lyashkov, Alexey E.; Levchenko, Andre; Zhang, Jin; Lakatta, Edward G.

    2015-01-01

    cAMP-PKA protein kinase is a key nodal signaling pathway that regulates a wide range of heart pacemaker cell functions. These functions are predicted to be involved in regulation of spontaneous action potential (AP) generation of these cells. Here we investigate if the kinetics and stoichiometry of increase in PKA activity match the increase in AP firing rate in response to β-adrenergic receptor (β-AR) stimulation or phosphodiesterase (PDE) inhibition, that alter the AP firing rate of heart sinoatrial pacemaker cells. In cultured adult rabbit pacemaker cells infected with an adenovirous expressing the FRET sensor AKAR3, the EC50 in response to graded increases in the intensity of β-AR stimulation (by Isoproterenol) the magnitude of the increases in PKA activity and the spontaneous AP firing rate were similar (0.4±0.1nM vs. 0.6±0.15nM, respectively). Moreover, the kinetics (t1/2) of the increases in PKA activity and spontaneous AP firing rate in response to β-AR stimulation or PDE inhibition were tightly linked. We characterized the system rate-limiting biochemical reactions by integrating these experimentally derived data into mechanistic-computational model. Model simulations predicted that phospholamban phosphorylation is a potent target of the increase in PKA activity that links to increase in spontaneous AP firing rate. In summary, the kinetics and stoichiometry of increases in PKA activity in response to a physiological (β-AR stimulation) or pharmacological (PDE inhibitor) stimuli match those of changes in the AP firing rate. Thus Ca2+-cAMP/PKA-dependent phosphorylation limits the rate and magnitude of increase in spontaneous AP firing rate. PMID:26241846

  18. Non-linear dimensionality reduction of signaling networks

    Science.gov (United States)

    Ivakhno, Sergii; Armstrong, J Douglas

    2007-01-01

    Background Systems wide modeling and analysis of signaling networks is essential for understanding complex cellular behaviors, such as the biphasic responses to different combinations of cytokines and growth factors. For example, tumor necrosis factor (TNF) can act as a proapoptotic or prosurvival factor depending on its concentration, the current state of signaling network and the presence of other cytokines. To understand combinatorial regulation in such systems, new computational approaches are required that can take into account non-linear interactions in signaling networks and provide tools for clustering, visualization and predictive modeling. Results Here we extended and applied an unsupervised non-linear dimensionality reduction approach, Isomap, to find clusters of similar treatment conditions in two cell signaling networks: (I) apoptosis signaling network in human epithelial cancer cells treated with different combinations of TNF, epidermal growth factor (EGF) and insulin and (II) combination of signal transduction pathways stimulated by 21 different ligands based on AfCS double ligand screen data. For the analysis of the apoptosis signaling network we used the Cytokine compendium dataset where activity and concentration of 19 intracellular signaling molecules were measured to characterise apoptotic response to TNF, EGF and insulin. By projecting the original 19-dimensional space of intracellular signals into a low-dimensional space, Isomap was able to reconstruct clusters corresponding to different cytokine treatments that were identified with graph-based clustering. In comparison, Principal Component Analysis (PCA) and Partial Least Squares – Discriminant analysis (PLS-DA) were unable to find biologically meaningful clusters. We also showed that by using Isomap components for supervised classification with k-nearest neighbor (k-NN) and quadratic discriminant analysis (QDA), apoptosis intensity can be predicted for different combinations of TNF, EGF

  19. Non-linear dimensionality reduction of signaling networks

    Directory of Open Access Journals (Sweden)

    Ivakhno Sergii

    2007-06-01

    Full Text Available Abstract Background Systems wide modeling and analysis of signaling networks is essential for understanding complex cellular behaviors, such as the biphasic responses to different combinations of cytokines and growth factors. For example, tumor necrosis factor (TNF can act as a proapoptotic or prosurvival factor depending on its concentration, the current state of signaling network and the presence of other cytokines. To understand combinatorial regulation in such systems, new computational approaches are required that can take into account non-linear interactions in signaling networks and provide tools for clustering, visualization and predictive modeling. Results Here we extended and applied an unsupervised non-linear dimensionality reduction approach, Isomap, to find clusters of similar treatment conditions in two cell signaling networks: (I apoptosis signaling network in human epithelial cancer cells treated with different combinations of TNF, epidermal growth factor (EGF and insulin and (II combination of signal transduction pathways stimulated by 21 different ligands based on AfCS double ligand screen data. For the analysis of the apoptosis signaling network we used the Cytokine compendium dataset where activity and concentration of 19 intracellular signaling molecules were measured to characterise apoptotic response to TNF, EGF and insulin. By projecting the original 19-dimensional space of intracellular signals into a low-dimensional space, Isomap was able to reconstruct clusters corresponding to different cytokine treatments that were identified with graph-based clustering. In comparison, Principal Component Analysis (PCA and Partial Least Squares – Discriminant analysis (PLS-DA were unable to find biologically meaningful clusters. We also showed that by using Isomap components for supervised classification with k-nearest neighbor (k-NN and quadratic discriminant analysis (QDA, apoptosis intensity can be predicted for different

  20. Non-linear dimensionality reduction of signaling networks.

    Science.gov (United States)

    Ivakhno, Sergii; Armstrong, J Douglas

    2007-06-08

    Systems wide modeling and analysis of signaling networks is essential for understanding complex cellular behaviors, such as the biphasic responses to different combinations of cytokines and growth factors. For example, tumor necrosis factor (TNF) can act as a proapoptotic or prosurvival factor depending on its concentration, the current state of signaling network and the presence of other cytokines. To understand combinatorial regulation in such systems, new computational approaches are required that can take into account non-linear interactions in signaling networks and provide tools for clustering, visualization and predictive modeling. Here we extended and applied an unsupervised non-linear dimensionality reduction approach, Isomap, to find clusters of similar treatment conditions in two cell signaling networks: (I) apoptosis signaling network in human epithelial cancer cells treated with different combinations of TNF, epidermal growth factor (EGF) and insulin and (II) combination of signal transduction pathways stimulated by 21 different ligands based on AfCS double ligand screen data. For the analysis of the apoptosis signaling network we used the Cytokine compendium dataset where activity and concentration of 19 intracellular signaling molecules were measured to characterise apoptotic response to TNF, EGF and insulin. By projecting the original 19-dimensional space of intracellular signals into a low-dimensional space, Isomap was able to reconstruct clusters corresponding to different cytokine treatments that were identified with graph-based clustering. In comparison, Principal Component Analysis (PCA) and Partial Least Squares - Discriminant analysis (PLS-DA) were unable to find biologically meaningful clusters. We also showed that by using Isomap components for supervised classification with k-nearest neighbor (k-NN) and quadratic discriminant analysis (QDA), apoptosis intensity can be predicted for different combinations of TNF, EGF and insulin. Prediction

  1. Signaling in large-scale neural networks

    DEFF Research Database (Denmark)

    Berg, Rune W; Hounsgaard, Jørn

    2009-01-01

    We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages of this m......We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages...... of this metabolically costly organization are analyzed by comparing with synaptically less intense networks driven by the intrinsic response properties of the network neurons....

  2. Organization of signal flow in directed networks

    International Nuclear Information System (INIS)

    Bányai, M; Bazsó, F; Négyessy, L

    2011-01-01

    Confining an answer to the question of whether and how the coherent operation of network elements is determined by the network structure is the topic of our work. We map the structure of signal flow in directed networks by analysing the degree of edge convergence and the overlap between the in- and output sets of an edge. Definitions of convergence degree and overlap are based on the shortest paths, thus they encapsulate global network properties. Using the defining notions of convergence degree and overlapping set we clarify the meaning of network causality and demonstrate the crucial role of chordless circles. In real-world networks the flow representation distinguishes nodes according to their signal transmitting, processing and control properties. The analysis of real-world networks in terms of flow representation was in accordance with the known functional properties of the network nodes. It is shown that nodes with different signal processing, transmitting and control properties are randomly connected at the global scale, while local connectivity patterns depart from randomness. The grouping of network nodes according to their signal flow properties was unrelated to the network's community structure. We present evidence that the signal flow properties of small-world-like, real-world networks cannot be reconstructed by algorithms used to generate small-world networks. Convergence degree values were calculated for regular oriented trees, and the probability density function for networks grown with the preferential attachment mechanism. For Erdos–Rényi graphs we calculated the probability density function of both convergence degrees and overlaps

  3. Quantitative phosphoproteomics to characterize signaling networks

    DEFF Research Database (Denmark)

    Rigbolt, Kristoffer T G; Blagoev, Blagoy

    2012-01-01

    for analyzing protein phosphorylation at a system-wide scale and has become the intuitive strategy for comprehensive characterization of signaling networks. Contemporary phosphoproteomics use highly optimized procedures for sample preparation, mass spectrometry and data analysis algorithms to identify...... in phosphoproteomics technology that have facilitated the application of phosphoproteomics to signaling networks and introduce examples of recent system-wide applications of quantitative phosphoproteomics. Despite the great advances in phosphoproteomics technology there are still several outstanding issues and we...

  4. Non-Invasive Optical Biosensor for Probing Cell Signaling

    OpenAIRE

    Fang, Ye

    2007-01-01

    Cell signaling mediated through a cellular target is encoded by spatial and temporal dynamics of downstream signaling networks. The coupling of temporal dynamics with spatial gradients of signaling activities guides cellular responses upon stimulation. Monitoring the integration of cell signaling in real time, if realized, would provide a new dimension for understanding cell biology and physiology. Optical biosensors including resonant waveguide grating (RWG) biosensor manifest a physiologica...

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

    Directory of Open Access Journals (Sweden)

    Andre Terzic

    2009-04-01

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

  6. Artificial neural networks for classifying olfactory signals.

    Science.gov (United States)

    Linder, R; Pöppl, S J

    2000-01-01

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

  7. Non-invasive Optical Biosensor for Probing Cell Signaling

    Directory of Open Access Journals (Sweden)

    Ye Fang

    2007-10-01

    Full Text Available Cell signaling mediated through a cellular target is encoded by spatial andtemporal dynamics of downstream signaling networks. The coupling of temporal dynamicswith spatial gradients of signaling activities guides cellular responses upon stimulation.Monitoring the integration of cell signaling in real time, if realized, would provide a newdimension for understanding cell biology and physiology. Optical biosensors includingresonant waveguide grating (RWG biosensor manifest a physiologically relevant andintegrated cellular response related to dynamic redistribution of cellular matters, thusproviding a non-invasive means for cell signaling study. This paper reviews recentprogresses in biosensor instrumentation, and theoretical considerations and potentialapplications of optical biosensors for whole cell sensing.

  8. SiGNet: A signaling network data simulator to enable signaling network inference.

    Science.gov (United States)

    Coker, Elizabeth A; Mitsopoulos, Costas; Workman, Paul; Al-Lazikani, Bissan

    2017-01-01

    Network models are widely used to describe complex signaling systems. Cellular wiring varies in different cellular contexts and numerous inference techniques have been developed to infer the structure of a network from experimental data of the network's behavior. To objectively identify which inference strategy is best suited to a specific network, a gold standard network and dataset are required. However, suitable datasets for benchmarking are difficult to find. Numerous tools exist that can simulate data for transcriptional networks, but these are of limited use for the study of signaling networks. Here, we describe SiGNet (Signal Generator for Networks): a Cytoscape app that simulates experimental data for a signaling network of known structure. SiGNet has been developed and tested against published experimental data, incorporating information on network architecture, and the directionality and strength of interactions to create biological data in silico. SiGNet is the first tool to simulate biological signaling data, enabling an accurate and systematic assessment of inference strategies. SiGNet can also be used to produce preliminary models of key biological pathways following perturbation.

  9. SiGNet: A signaling network data simulator to enable signaling network inference.

    Directory of Open Access Journals (Sweden)

    Elizabeth A Coker

    Full Text Available Network models are widely used to describe complex signaling systems. Cellular wiring varies in different cellular contexts and numerous inference techniques have been developed to infer the structure of a network from experimental data of the network's behavior. To objectively identify which inference strategy is best suited to a specific network, a gold standard network and dataset are required. However, suitable datasets for benchmarking are difficult to find. Numerous tools exist that can simulate data for transcriptional networks, but these are of limited use for the study of signaling networks. Here, we describe SiGNet (Signal Generator for Networks: a Cytoscape app that simulates experimental data for a signaling network of known structure. SiGNet has been developed and tested against published experimental data, incorporating information on network architecture, and the directionality and strength of interactions to create biological data in silico. SiGNet is the first tool to simulate biological signaling data, enabling an accurate and systematic assessment of inference strategies. SiGNet can also be used to produce preliminary models of key biological pathways following perturbation.

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

    Science.gov (United States)

    Xiong, Yan; Sheen, Jen

    2015-12-01

    Nutrient and energy sensing and signaling mechanisms constitute the most ancient and fundamental regulatory networks to control growth and development in all life forms. The target of rapamycin (TOR) protein kinase is modulated by diverse nutrient, energy, hormone and stress inputs and plays a central role in regulating cell proliferation, growth, metabolism and stress responses from yeasts to plants and animals. Recent chemical, genetic, genomic and metabolomic analyses have enabled significant progress toward molecular understanding of the TOR signaling network in multicellular plants. This review discusses the applications of new chemical tools to probe plant TOR functions and highlights recent findings and predictions on TOR-mediate biological processes. Special focus is placed on novel and evolutionarily conserved TOR kinase effectors as positive and negative signaling regulators that control transcription, translation and metabolism to support cell proliferation, growth and maintenance from embryogenesis to senescence in the plant system. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. The cell surface membrane proteins Cdo and Boc are components and targets of the Hedgehog signaling pathway and feedback network in mice.

    Science.gov (United States)

    Tenzen, Toyoaki; Allen, Benjamin L; Cole, Francesca; Kang, Jong-Sun; Krauss, Robert S; McMahon, Andrew P

    2006-05-01

    Cdo and Boc encode cell surface Ig/fibronectin superfamily members linked to muscle differentiation. Data here indicate they are also targets and signaling components of the Sonic hedgehog (Shh) pathway. Although Cdo and Boc are generally negatively regulated by Hedgehog (HH) signaling, in the neural tube Cdo is expressed within the Shh-dependent floor plate while Boc expression lies within the dorsal limit of Shh signaling. Loss of Cdo results in a Shh dosage-dependent reduction of the floor plate. In contrast, ectopic expression of Boc or Cdo results in a Shh-dependent, cell autonomous promotion of ventral cell fates and a non-cell-autonomous ventral expansion of dorsal cell identities consistent with Shh sequestration. Cdo and Boc bind Shh through a high-affinity interaction with a specific fibronectin repeat that is essential for activity. We propose a model where Cdo and Boc enhance Shh signaling within its target field.

  12. Gene Network Analysis of Glucose Linked Signaling Pathways and Their Role in Human Hepatocellular Carcinoma Cell Growth and Survival in HuH7 and HepG2 Cell Lines

    Directory of Open Access Journals (Sweden)

    Emmanuelle Berger

    2015-01-01

    Full Text Available Cancer progression may be affected by metabolism. In this study, we aimed to analyze the effect of glucose on the proliferation and/or survival of human hepatocellular carcinoma (HCC cells. Human gene datasets regulated by glucose were compared to gene datasets either dysregulated in HCC or regulated by other signaling pathways. Significant numbers of common genes suggested putative involvement in transcriptional regulations by glucose. Real-time proliferation assays using high (4.5 g/L versus low (1 g/L glucose on two human HCC cell lines and specific inhibitors of selected pathways were used for experimental validations. High glucose promoted HuH7 cell proliferation but not that of HepG2 cell line. Gene network analyses suggest that gene transcription by glucose could be mediated at 92% through ChREBP in HepG2 cells, compared to 40% in either other human cells or rodent healthy liver, with alteration of LKB1 (serine/threonine kinase 11 and NOX (NADPH oxidases signaling pathways and loss of transcriptional regulation of PPARGC1A (peroxisome-proliferator activated receptors gamma coactivator 1 target genes by high glucose. Both PPARA and PPARGC1A regulate transcription of genes commonly regulated by glycolysis, by the antidiabetic agent metformin and by NOX, suggesting their major interplay in the control of HCC progression.

  13. Cell signalling and phospholipid metabolism

    Energy Technology Data Exchange (ETDEWEB)

    Boss, W.F.

    1990-01-01

    These studies explored whether phosphoinositide (PI) has a role in plants analogous to its role in animal cells. Although no parallel activity of PI in signal transduction was found in plant cells, activity of inositol phospholipid kinase was found to be modulated by light and by cell wall degrading enzymes. These studies indicate a major role for inositol phospholipids in plant growth and development as membrane effectors but not as a source of second messengers.

  14. Real-time relationship between PKA biochemical signal network dynamics and increased action potential firing rate in heart pacemaker cells: Kinetics of PKA activation in heart pacemaker cells.

    Science.gov (United States)

    Yaniv, Yael; Ganesan, Ambhighainath; Yang, Dongmei; Ziman, Bruce D; Lyashkov, Alexey E; Levchenko, Andre; Zhang, Jin; Lakatta, Edward G

    2015-09-01

    cAMP-PKA protein kinase is a key nodal signaling pathway that regulates a wide range of heart pacemaker cell functions. These functions are predicted to be involved in regulation of spontaneous action potential (AP) generation of these cells. Here we investigate if the kinetics and stoichiometry of increase in PKA activity match the increase in AP firing rate in response to β-adrenergic receptor (β-AR) stimulation or phosphodiesterase (PDE) inhibition, that alters the AP firing rate of heart sinoatrial pacemaker cells. In cultured adult rabbit pacemaker cells infected with an adenovirus expressing the FRET sensor AKAR3, the EC50 in response to graded increases in the intensity of β-AR stimulation (by Isoproterenol) the magnitude of the increases in PKA activity and the spontaneous AP firing rate were similar (0.4±0.1nM vs. 0.6±0.15nM, respectively). Moreover, the kinetics (t1/2) of the increases in PKA activity and spontaneous AP firing rate in response to β-AR stimulation or PDE inhibition were tightly linked. We characterized the system rate-limiting biochemical reactions by integrating these experimentally derived data into a mechanistic-computational model. Model simulations predicted that phospholamban phosphorylation is a potent target of the increase in PKA activity that links to increase in spontaneous AP firing rate. In summary, the kinetics and stoichiometry of increases in PKA activity in response to a physiological (β-AR stimulation) or pharmacological (PDE inhibitor) stimuli match those of changes in the AP firing rate. Thus Ca(2+)-cAMP/PKA-dependent phosphorylation limits the rate and magnitude of increase in spontaneous AP firing rate. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Zhan Xianquan

    2010-04-01

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

  16. Signalling network construction for modelling plant defence response.

    Directory of Open Access Journals (Sweden)

    Dragana Miljkovic

    Full Text Available Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2 triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be

  17. Signaling networks associated with AKT activation in non-small cell lung cancer (NSCLC: new insights on the role of phosphatydil-inositol-3 kinase.

    Directory of Open Access Journals (Sweden)

    Marianna Scrima

    Full Text Available Aberrant activation of PI3K/AKT signalling represents one of the most common molecular alterations in lung cancer, though the relative contribution of the single components of the cascade to the NSCLC development is still poorly defined. In this manuscript we have investigated the relationship between expression and genetic alterations of the components of the PI3K/AKT pathway [KRAS, the catalytic subunit of PI3K (p110α, PTEN, AKT1 and AKT2] and the activation of AKT in 107 surgically resected NSCLCs and have analyzed the existing relationships with clinico-pathologic features. Expression analysis was performed by immunohistochemistry on Tissue Micro Arrays (TMA; mutation analysis was performed by DNA sequencing; copy number variation was determined by FISH. We report that activation of PI3K/AKT pathway in Italian NSCLC patients is associated with high grade (G3-G4 compared with G1-G2; n = 83; p<0.05 and more advanced disease (TNM stage III vs. stages I and II; n = 26; p<0.05. In addition, we found that PTEN loss (41/104, 39% and the overexpression of p110α (27/92, 29% represent the most frequent aberration observed in NSCLCs. Less frequent molecular lesions comprised the overexpression of AKT2 (18/83, 22% or AKT1 (17/96, 18%, and KRAS mutation (7/63, 11%. Our results indicate that, among all genes, only p110α overexpression was significantly associated to AKT activation in NSCLCs (p = 0.02. Manipulation of p110α expression in lung cancer cells carrying an active PI3K allele (NCI-H460 efficiently reduced proliferation of NSCLC cells in vitro and tumour growth in vivo. Finally, RNA profiling of lung epithelial cells (BEAS-2B expressing a mutant allele of PIK3 (E545K identified a network of transcription factors such as MYC, FOS and HMGA1, not previously recognised to be associated with aberrant PI3K signalling in lung cancer.

  18. Sweet Taste Receptor Signaling Network: Possible Implication for Cognitive Functioning

    Directory of Open Access Journals (Sweden)

    Menizibeya O. Welcome

    2015-01-01

    Full Text Available Sweet taste receptors are transmembrane protein network specialized in the transmission of information from special “sweet” molecules into the intracellular domain. These receptors can sense the taste of a range of molecules and transmit the information downstream to several acceptors, modulate cell specific functions and metabolism, and mediate cell-to-cell coupling through paracrine mechanism. Recent reports indicate that sweet taste receptors are widely distributed in the body and serves specific function relative to their localization. Due to their pleiotropic signaling properties and multisubstrate ligand affinity, sweet taste receptors are able to cooperatively bind multiple substances and mediate signaling by other receptors. Based on increasing evidence about the role of these receptors in the initiation and control of absorption and metabolism, and the pivotal role of metabolic (glucose regulation in the central nervous system functioning, we propose a possible implication of sweet taste receptor signaling in modulating cognitive functioning.

  19. Cytoskeleton in Mast Cell Signaling

    Science.gov (United States)

    Dráber, Pavel; Sulimenko, Vadym; Dráberová, Eduarda

    2012-01-01

    Mast cell activation mediated by the high affinity receptor for IgE (FcεRI) is a key event in allergic response and inflammation. Other receptors on mast cells, as c-Kit for stem cell factor and G protein-coupled receptors (GPCRs) synergistically enhance the FcεRI-mediated release of inflammatory mediators. Activation of various signaling pathways in mast cells results in changes in cell morphology, adhesion to substrate, exocytosis, and migration. Reorganization of cytoskeleton is pivotal in all these processes. Cytoskeletal proteins also play an important role in initial stages of FcεRI and other surface receptors induced triggering. Highly dynamic microtubules formed by αβ-tubulin dimers as well as microfilaments build up from polymerized actin are affected in activated cells by kinases/phosphatases, Rho GTPases and changes in concentration of cytosolic Ca2+. Also important are nucleation proteins; the γ-tubulin complexes in case of microtubules or Arp 2/3 complex with its nucleation promoting factors and formins in case of microfilaments. The dynamic nature of microtubules and microfilaments in activated cells depends on many associated/regulatory proteins. Changes in rigidity of activated mast cells reflect changes in intermediate filaments build up from vimentin. This review offers a critical appraisal of current knowledge on the role of cytoskeleton in mast cells signaling. PMID:22654883

  20. NT2 derived neuronal and astrocytic network signalling.

    Directory of Open Access Journals (Sweden)

    Eric J Hill

    Full Text Available A major focus of stem cell research is the generation of neurons that may then be implanted to treat neurodegenerative diseases. However, a picture is emerging where astrocytes are partners to neurons in sustaining and modulating brain function. We therefore investigated the functional properties of NT2 derived astrocytes and neurons using electrophysiological and calcium imaging approaches. NT2 neurons (NT2Ns expressed sodium dependent action potentials, as well as responses to depolarisation and the neurotransmitter glutamate. NT2Ns exhibited spontaneous and coordinated calcium elevations in clusters and in extended processes, indicating local and long distance signalling. Tetrodotoxin sensitive network activity could also be evoked by electrical stimulation. Similarly, NT2 astrocytes (NT2As exhibited morphology and functional properties consistent with this glial cell type. NT2As responded to neuronal activity and to exogenously applied neurotransmitters with calcium elevations, and in contrast to neurons, also exhibited spontaneous rhythmic calcium oscillations. NT2As also generated propagating calcium waves that were gap junction and purinergic signalling dependent. Our results show that NT2 derived astrocytes exhibit appropriate functionality and that NT2N networks interact with NT2A networks in co-culture. These findings underline the utility of such cultures to investigate human brain cell type signalling under controlled conditions. Furthermore, since stem cell derived neuron function and survival is of great importance therapeutically, our findings suggest that the presence of complementary astrocytes may be valuable in supporting stem cell derived neuronal networks. Indeed, this also supports the intriguing possibility of selective therapeutic replacement of astrocytes in diseases where these cells are either lost or lose functionality.

  1. Syndecans, signaling, and cell adhesion

    DEFF Research Database (Denmark)

    Couchman, J R; Woods, A

    1996-01-01

    structures within the heparan sulfate chains, leaving the roles of chondroitin sulfate chains and extracellular portion of the core proteins to be elucidated. Evidence that syndecans are a class of receptor involved in cell adhesion is mounting, and their small cytoplasmic domains may link...... transmembrane signaling from matrix to cytoskeleton, as proposed for other classes of adhesion receptors....

  2. Calcium signaling and cell proliferation.

    Science.gov (United States)

    Pinto, Mauro Cunha Xavier; Kihara, Alexandre Hiroaki; Goulart, Vânia A M; Tonelli, Fernanda M P; Gomes, Katia N; Ulrich, Henning; Resende, Rodrigo R

    2015-11-01

    Cell proliferation is orchestrated through diverse proteins related to calcium (Ca(2+)) signaling inside the cell. Cellular Ca(2+) influx that occurs first by various mechanisms at the plasma membrane, is then followed by absorption of Ca(2+) ions by mitochondria and endoplasmic reticulum, and, finally, there is a connection of calcium stores to the nucleus. Experimental evidence indicates that the fluctuation of Ca(2+) from the endoplasmic reticulum provides a pivotal and physiological role for cell proliferation. Ca(2+) depletion in the endoplasmatic reticulum triggers Ca(2+) influx across the plasma membrane in an phenomenon called store-operated calcium entries (SOCEs). SOCE is activated through a complex interplay between a Ca(2+) sensor, denominated STIM, localized in the endoplasmic reticulum and a Ca(2+) channel at the cell membrane, denominated Orai. The interplay between STIM and Orai proteins with cell membrane receptors and their role in cell proliferation is discussed in this review. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Phosphoproteomics-based systems analysis of signal transduction networks

    Directory of Open Access Journals (Sweden)

    Hiroko eKozuka-Hata

    2012-01-01

    Full Text Available Signal transduction systems coordinate complex cellular information to regulate biological events such as cell proliferation and differentiation. Although the accumulating evidence on widespread association of signaling molecules has revealed essential contribution of phosphorylation-dependent interaction networks to cellular regulation, their dynamic behavior is mostly yet to be analyzed. Recent technological advances regarding mass spectrometry-based quantitative proteomics have enabled us to describe the comprehensive status of phosphorylated molecules in a time-resolved manner. Computational analyses based on the phosphoproteome dynamics accelerate generation of novel methodologies for mathematical analysis of cellular signaling. Phosphoproteomics-based numerical modeling can be used to evaluate regulatory network elements from a statistical point of view. Integration with transcriptome dynamics also uncovers regulatory hubs at the transcriptional level. These omics-based computational methodologies, which have firstly been applied to representative signaling systems such as the epidermal growth factor receptor pathway, have now opened up a gate for systems analysis of signaling networks involved in immune response and cancer.

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

    Science.gov (United States)

    Coyle, Scott M

    2016-07-02

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

  5. Cytoskeleton in mast cell signaling

    Czech Academy of Sciences Publication Activity Database

    Dráber, Pavel; Sulimenko, Vadym; Dráberová, Eduarda

    2012-01-01

    Roč. 3, May (2012), s. 130 ISSN 1664-3224 R&D Projects: GA ČR GAP302/10/1701; GA ČR GPP302/11/P709; GA ČR GAP302/12/1673 Grant - others:ECST(XE) Action BM1007 Institutional research plan: CEZ:AV0Z50520514 Keywords : cytoskeleton * mast cell activation * signal transduction Subject RIV: EB - Genetics ; Molecular Biology

  6. Mechanical Cell-Cell Communication in Fibrous Networks: The Importance of Network Geometry.

    Science.gov (United States)

    Humphries, D L; Grogan, J A; Gaffney, E A

    2017-03-01

    Cells contracting in extracellular matrix (ECM) can transmit stress over long distances, communicating their position and orientation to cells many tens of micrometres away. Such phenomena are not observed when cells are seeded on substrates with linear elastic properties, such as polyacrylamide (PA) gel. The ability for fibrous substrates to support far reaching stress and strain fields has implications for many physiological processes, while the mechanical properties of ECM are central to several pathological processes, including tumour invasion and fibrosis. Theoretical models have investigated the properties of ECM in a variety of network geometries. However, the effects of network architecture on mechanical cell-cell communication have received little attention. This work investigates the effects of geometry on network mechanics, and thus the ability for cells to communicate mechanically through different networks. Cell-derived displacement fields are quantified for various network geometries while controlling for network topology, cross-link density and micromechanical properties. We find that the heterogeneity of response, fibre alignment, and substrate displacement fields are sensitive to network choice. Further, we show that certain geometries support mechanical communication over longer distances than others. As such, we predict that the choice of network geometry is important in fundamental modelling of cell-cell interactions in fibrous substrates, as well as in experimental settings, where mechanical signalling at the cellular scale plays an important role. This work thus informs the construction of theoretical models for substrate mechanics and experimental explorations of mechanical cell-cell communication.

  7. [Pluripotency candidate signaling network and transcription factors in domesticated ungulates: a review].

    Science.gov (United States)

    Zhao, Yuncheng; Chen, Bo; Zhou, Chuan; Zhang, Xiuhua; Huang, Juncheng

    2010-12-01

    Domesticated ungulates embryonic stem (ES) cells have great significances in biology and wide application prospects. This review compared the key signaling pathways related with pluripotency between mouse and human ES cells, and the difference of transcription factors in mouse, human and domesticated ungulates ES cells were elaborated. Finally the pluripotency candidate signaling network and transcription factors related in the derivation of domesticated ungulates ES cell were discussed combined with practical experience of ovine embryonic stem cell derivation in our laboratory.

  8. MSAT signalling and network management architectures

    Science.gov (United States)

    Garland, Peter; Keelty, J. Malcolm

    1989-01-01

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

  9. Systems biology. Conditional density-based analysis of T cell signaling in single-cell data.

    Science.gov (United States)

    Krishnaswamy, Smita; Spitzer, Matthew H; Mingueneau, Michael; Bendall, Sean C; Litvin, Oren; Stone, Erica; Pe'er, Dana; Nolan, Garry P

    2014-11-28

    Cellular circuits sense the environment, process signals, and compute decisions using networks of interacting proteins. To model such a system, the abundance of each activated protein species can be described as a stochastic function of the abundance of other proteins. High-dimensional single-cell technologies, such as mass cytometry, offer an opportunity to characterize signaling circuit-wide. However, the challenge of developing and applying computational approaches to interpret such complex data remains. Here, we developed computational methods, based on established statistical concepts, to characterize signaling network relationships by quantifying the strengths of network edges and deriving signaling response functions. In comparing signaling between naïve and antigen-exposed CD4(+) T lymphocytes, we find that although these two cell subtypes had similarly wired networks, naïve cells transmitted more information along a key signaling cascade than did antigen-exposed cells. We validated our characterization on mice lacking the extracellular-regulated mitogen-activated protein kinase (MAPK) ERK2, which showed stronger influence of pERK on pS6 (phosphorylated-ribosomal protein S6), in naïve cells as compared with antigen-exposed cells, as predicted. We demonstrate that by using cell-to-cell variation inherent in single-cell data, we can derive response functions underlying molecular circuits and drive the understanding of how cells process signals. Copyright © 2014, American Association for the Advancement of Science.

  10. Magnetoencephalography from signals to dynamic cortical networks

    CERN Document Server

    Aine, Cheryl

    2014-01-01

    "Magnetoencephalography (MEG) provides a time-accurate view into human brain function. The concerted action of neurons generates minute magnetic fields that can be detected---totally noninvasively---by sensitive multichannel magnetometers. The obtained millisecond accuracycomplements information obtained by other modern brain-imaging tools. Accurate timing is quintessential in normal brain function, often distorted in brain disorders. The noninvasiveness and time-sensitivityof MEG are great assets to developmental studies, as well. This multiauthored book covers an ambitiously wide range of MEG research from introductory to advanced level, from sensors to signals, and from focal sources to the dynamics of cortical networks. Written by active practioners of this multidisciplinary field, the book contains tutorials for newcomers and chapters of new challenging methods and emerging technologies to advanced MEG users. The reader will obtain a firm grasp of the possibilities of MEG in the study of audition, vision...

  11. Logic integer programming models for signaling networks.

    Science.gov (United States)

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

    2009-05-01

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

  12. Subversion of cell signaling by pathogens.

    Science.gov (United States)

    Alto, Neal M; Orth, Kim

    2012-09-01

    Pathogens exploit several eukaryotic signaling pathways during an infection. They have evolved specific effectors and toxins to hijack host cell machinery for their own benefit. Signaling molecules are preferentially targeted by pathogens because they globally regulate many cellular processes. Both viruses and bacteria manipulate and control pathways that regulate host cell survival and shape, including MAPK signaling, G-protein signaling, signals controlling cytoskeletal dynamics, and innate immune responses.

  13. Advanced Signaling Support for IP-based Networks

    OpenAIRE

    Röhricht, Martin

    2013-01-01

    This work develops a set of advanced signaling concepts for IP-based networks. It proposes a design for secure and authentic signaling and provides QoS signaling support for mobile users. Furthermore, this work develops methods which allow for scalable QoS signaling by realizing QoS-based group communication mechanisms and through aggregation of resource reservations.

  14. RMOD: a tool for regulatory motif detection in signaling network.

    Directory of Open Access Journals (Sweden)

    Jinki Kim

    Full Text Available Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod.

  15. Plato's cave algorithm: inferring functional signaling networks from early gene expression shadows.

    Directory of Open Access Journals (Sweden)

    Yishai Shimoni

    2010-06-01

    Full Text Available Improving the ability to reverse engineer biochemical networks is a major goal of systems biology. Lesions in signaling networks lead to alterations in gene expression, which in principle should allow network reconstruction. However, the information about the activity levels of signaling proteins conveyed in overall gene expression is limited by the complexity of gene expression dynamics and of regulatory network topology. Two observations provide the basis for overcoming this limitation: a. genes induced without de-novo protein synthesis (early genes show a linear accumulation of product in the first hour after the change in the cell's state; b. The signaling components in the network largely function in the linear range of their stimulus-response curves. Therefore, unlike most genes or most time points, expression profiles of early genes at an early time point provide direct biochemical assays that represent the activity levels of upstream signaling components. Such expression data provide the basis for an efficient algorithm (Plato's Cave algorithm; PLACA to reverse engineer functional signaling networks. Unlike conventional reverse engineering algorithms that use steady state values, PLACA uses stimulated early gene expression measurements associated with systematic perturbations of signaling components, without measuring the signaling components themselves. Besides the reverse engineered network, PLACA also identifies the genes detecting the functional interaction, thereby facilitating validation of the predicted functional network. Using simulated datasets, the algorithm is shown to be robust to experimental noise. Using experimental data obtained from gonadotropes, PLACA reverse engineered the interaction network of six perturbed signaling components. The network recapitulated many known interactions and identified novel functional interactions that were validated by further experiment. PLACA uses the results of experiments that are

  16. Plato's cave algorithm: inferring functional signaling networks from early gene expression shadows.

    Science.gov (United States)

    Shimoni, Yishai; Fink, Marc Y; Choi, Soon-gang; Sealfon, Stuart C

    2010-06-24

    Improving the ability to reverse engineer biochemical networks is a major goal of systems biology. Lesions in signaling networks lead to alterations in gene expression, which in principle should allow network reconstruction. However, the information about the activity levels of signaling proteins conveyed in overall gene expression is limited by the complexity of gene expression dynamics and of regulatory network topology. Two observations provide the basis for overcoming this limitation: a. genes induced without de-novo protein synthesis (early genes) show a linear accumulation of product in the first hour after the change in the cell's state; b. The signaling components in the network largely function in the linear range of their stimulus-response curves. Therefore, unlike most genes or most time points, expression profiles of early genes at an early time point provide direct biochemical assays that represent the activity levels of upstream signaling components. Such expression data provide the basis for an efficient algorithm (Plato's Cave algorithm; PLACA) to reverse engineer functional signaling networks. Unlike conventional reverse engineering algorithms that use steady state values, PLACA uses stimulated early gene expression measurements associated with systematic perturbations of signaling components, without measuring the signaling components themselves. Besides the reverse engineered network, PLACA also identifies the genes detecting the functional interaction, thereby facilitating validation of the predicted functional network. Using simulated datasets, the algorithm is shown to be robust to experimental noise. Using experimental data obtained from gonadotropes, PLACA reverse engineered the interaction network of six perturbed signaling components. The network recapitulated many known interactions and identified novel functional interactions that were validated by further experiment. PLACA uses the results of experiments that are feasible for any

  17. A logical model provides insights into T cell receptor signaling.

    Directory of Open Access Journals (Sweden)

    Julio Saez-Rodriguez

    2007-08-01

    Full Text Available Cellular decisions are determined by complex molecular interaction networks. Large-scale signaling networks are currently being reconstructed, but the kinetic parameters and quantitative data that would allow for dynamic modeling are still scarce. Therefore, computational studies based upon the structure of these networks are of great interest. Here, a methodology relying on a logical formalism is applied to the functional analysis of the complex signaling network governing the activation of T cells via the T cell receptor, the CD4/CD8 co-receptors, and the accessory signaling receptor CD28. Our large-scale Boolean model, which comprises 94 nodes and 123 interactions and is based upon well-established qualitative knowledge from primary T cells, reveals important structural features (e.g., feedback loops and network-wide dependencies and recapitulates the global behavior of this network for an array of published data on T cell activation in wild-type and knock-out conditions. More importantly, the model predicted unexpected signaling events after antibody-mediated perturbation of CD28 and after genetic knockout of the kinase Fyn that were subsequently experimentally validated. Finally, we show that the logical model reveals key elements and potential failure modes in network functioning and provides candidates for missing links. In summary, our large-scale logical model for T cell activation proved to be a promising in silico tool, and it inspires immunologists to ask new questions. We think that it holds valuable potential in foreseeing the effects of drugs and network modifications.

  18. Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling.

    Directory of Open Access Journals (Sweden)

    Masanao Sato

    Full Text Available Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2. This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i the components of the network are highly interconnected; and (ii negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector

  19. Proteomics, pathway array and signaling network-based medicine in cancer

    Directory of Open Access Journals (Sweden)

    Xu Hong

    2009-10-01

    Full Text Available Abstract Cancer is a multifaceted disease that results from dysregulated normal cellular signaling networks caused by genetic, genomic and epigenetic alterations at cell or tissue levels. Uncovering the underlying protein signaling network changes, including cell cycle gene networks in cancer, aids in understanding the molecular mechanism of carcinogenesis and identifies the characteristic signaling network signatures unique for different cancers and specific cancer subtypes. The identified signatures can be used for cancer diagnosis, prognosis, and personalized treatment. During the past several decades, the available technology to study signaling networks has significantly evolved to include such platforms as genomic microarray (expression array, SNP array, CGH array, etc. and proteomic analysis, which globally assesses genetic, epigenetic, and proteomic alterations in cancer. In this review, we compared Pathway Array analysis with other proteomic approaches in analyzing protein network involved in cancer and its utility serving as cancer biomarkers in diagnosis, prognosis and therapeutic target identification. With the advent of bioinformatics, constructing high complexity signaling networks is possible. As the use of signaling network-based cancer diagnosis, prognosis and treatment is anticipated in the near future, medical and scientific communities should be prepared to apply these techniques to further enhance personalized medicine.

  20. Using Artificial Neural Networks for ECG Signals Denoising

    Directory of Open Access Journals (Sweden)

    Zoltán Germán-Salló

    2010-12-01

    Full Text Available The authors have investigated some potential applications of artificial neural networks in electrocardiografic (ECG signal prediction. For this, the authors used an adaptive multilayer perceptron structure to predict the signal. The proposed procedure uses an artificial neural network based learning structure to estimate the (n+1th sample from n previous samples To train and adjust the network weights, the backpropagation (BP algorithm was used. In this paper, prediction of ECG signals (as time series using multi-layer feedforward neural networks will be described. The results are evaluated through approximation error which is defined as the difference between the predicted and the original signal.The prediction procedure is carried out (simulated in MATLAB environment, using signals from MIT-BIH arrhythmia database. Preliminary results are encouraging enough to extend the proposed method for other types of data signals.

  1. Multisite phosphorylation networks as signal processors for Cdk1.

    Science.gov (United States)

    Kõivomägi, Mardo; Ord, Mihkel; Iofik, Anna; Valk, Ervin; Venta, Rainis; Faustova, Ilona; Kivi, Rait; Balog, Eva Rose M; Rubin, Seth M; Loog, Mart

    2013-12-01

    The order and timing of cell-cycle events is controlled by changing substrate specificity and different activity thresholds of cyclin-dependent kinases (CDKs). However, it is not understood how a single protein kinase can trigger hundreds of switches in a sufficiently time-resolved fashion. We show that cyclin-Cdk1-Cks1-dependent phosphorylation of multisite targets in Saccharomyces cerevisiae is controlled by key substrate parameters including distances between phosphorylation sites, distribution of serines and threonines as phosphoacceptors and positioning of cyclin-docking motifs. The component mediating the key interactions in this process is Cks1, the phosphoadaptor subunit of the cyclin-Cdk1-Cks1 complex. We propose that variation of these parameters within networks of phosphorylation sites in different targets provides a wide range of possibilities for differential amplification of Cdk1 signals, thus providing a mechanism to generate a wide range of thresholds in the cell cycle.

  2. Information flow in a network of dispersed signalers-receivers

    Science.gov (United States)

    Halupka, Konrad

    2017-11-01

    I consider a stochastic model of multi-agent communication in regular network. The model describes how dispersed animals exchange information. Each agent can initiate and transfer the signal to its nearest neighbors, who may pass it farther. For an external observer of busy networks, signaling activity may appear random, even though information flow actually thrives. Only when signal initiation and transfer are at low levels do spatiotemporal autocorrelations emerge as clumping signaling activity in space and pink noise time series. Under such conditions, the costs of signaling are moderate, but the signaler can reach a large audience. I propose that real-world networks of dispersed signalers-receivers may self-organize into this state and the flow of information maintains their integrity.

  3. Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

    CERN Document Server

    Hu, Fei

    2012-01-01

    Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

  4. A modular analysis of the auxin signalling network.

    Directory of Open Access Journals (Sweden)

    Etienne Farcot

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

  5. Maximum entropy reconstructions of dynamic signaling networks from quantitative proteomics data.

    Directory of Open Access Journals (Sweden)

    Jason W Locasale

    2009-08-01

    Full Text Available Advances in mass spectrometry among other technologies have allowed for quantitative, reproducible, proteome-wide measurements of levels of phosphorylation as signals propagate through complex networks in response to external stimuli under different conditions. However, computational approaches to infer elements of the signaling network strictly from the quantitative aspects of proteomics data are not well established. We considered a method using the principle of maximum entropy to infer a network of interacting phosphotyrosine sites from pairwise correlations in a mass spectrometry data set and derive a phosphorylation-dependent interaction network solely from quantitative proteomics data. We first investigated the applicability of this approach by using a simulation of a model biochemical signaling network whose dynamics are governed by a large set of coupled differential equations. We found that in a simulated signaling system, the method detects interactions with significant accuracy. We then analyzed a growth factor mediated signaling network in a human mammary epithelial cell line that we inferred from mass spectrometry data and observe a biologically interpretable, small-world structure of signaling nodes, as well as a catalog of predictions regarding the interactions among previously uncharacterized phosphotyrosine sites. For example, the calculation places a recently identified tumor suppressor pathway through ARHGEF7 and Scribble, in the context of growth factor signaling. Our findings suggest that maximum entropy derived network models are an important tool for interpreting quantitative proteomics data.

  6. Plant cell wall signalling and receptor-like kinases.

    Science.gov (United States)

    Wolf, Sebastian

    2017-02-15

    Communication between the extracellular matrix and the cell interior is essential for all organisms as intrinsic and extrinsic cues have to be integrated to co-ordinate development, growth, and behaviour. This applies in particular to plants, the growth and shape of which is governed by deposition and remodelling of the cell wall, a rigid, yet dynamic, extracellular network. It is thus generally assumed that cell wall surveillance pathways exist to monitor the state of the wall and, if needed, elicit compensatory responses such as altered expression of cell wall remodelling and biosynthesis genes. Here, I highlight recent advances in the field of cell wall signalling in plants, with emphasis on the role of plasma membrane receptor-like kinase complexes. In addition, possible roles for cell wall-mediated signalling beyond the maintenance of cell wall integrity are discussed. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

  7. Neural network signal understanding for instrumentation

    DEFF Research Database (Denmark)

    Pau, L. F.; Johansen, F. S.

    1990-01-01

    A report is presented on the use of neural signal interpretation theory and techniques for the purpose of classifying the shapes of a set of instrumentation signals, in order to calibrate devices, diagnose anomalies, generate tuning/settings, and interpret the measurement results. Neural signal...... understanding research is surveyed, and the selected implementation and its performance in terms of correct classification rates and robustness to noise are described. Formal results on neural net training time and sensitivity to weights are given. A theory for neural control using functional link nets is given......, and an explanation facility designed to help neural signal understanding is described. The results are compared to those obtained with a knowledge-based signal interpretation system using the same instrument and data...

  8. Non-linear dimensionality reduction of signaling networks

    OpenAIRE

    Ivakhno, Sergii; Armstrong, J Douglas

    2007-01-01

    Abstract Background Systems wide modeling and analysis of signaling networks is essential for understanding complex cellular behaviors, such as the biphasic responses to different combinations of cytokines and growth factors. For example, tumor necrosis factor (TNF) can act as a proapoptotic or prosurvival factor depending on its concentration, the current state of signaling network and the presence of other cytokines. To understand combinatorial regulation in such systems, new computational ...

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

    International Nuclear Information System (INIS)

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

    1991-01-01

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

  10. Kinome-wide Decoding of Network-Attacking Mutations Rewiring Cancer Signaling

    DEFF Research Database (Denmark)

    Creixell, Pau; Schoof, Erwin M; Simpson, Craig D.

    2015-01-01

    Cancer cells acquire pathological phenotypes through accumulation of mutations that perturb signaling networks. However, global analysis of these events is currently limited. Here, we identify six types of network-attacking mutations (NAMs), including changes in kinase and SH2 modulation, network...... rewiring, and the genesis and extinction of phosphorylation sites. We developed a computational platform (ReKINect) to identify NAMs and systematically interpreted the exomes and quantitative (phospho-)proteomes of five ovarian cancer cell lines and the global cancer genome repository. We identified......-inactivating hotspots in cancer. Our method pinpoints functional NAMs, scales with the complexity of cancer genomes and cell signaling, and may enhance our capability to therapeutically target tumor-specific networks....

  11. Crosstalk between pathways enhances the controllability of signalling networks.

    Science.gov (United States)

    Wang, Dingjie; Jin, Suoqin; Zou, Xiufen

    2016-02-01

    The control of complex networks is one of the most challenging problems in the fields of biology and engineering. In this study, the authors explored the controllability and control energy of several signalling networks, which consisted of many interconnected pathways, including networks with a bow-tie architecture. On the basis of the theory of structure controllability, they revealed that biological mechanisms, such as cross-pathway interactions, compartmentalisation and so on make the networks easier to fully control. Furthermore, using numerical simulations for two realistic examples, they demonstrated that the control energy of normal networks with crosstalk is lower than in networks without crosstalk. These results indicate that the biological networks are optimally designed to achieve their normal functions from the viewpoint of the control theory. The authors' work provides a comprehensive understanding of the impact of network structures and properties on controllability.

  12. Lipid rafts and B cell signaling.

    Science.gov (United States)

    Gupta, Neetu; DeFranco, Anthony L

    2007-10-01

    B cells comprise an essential component of the humoral immune system. They are equipped with the unique ability to synthesize and secrete pathogen-neutralizing antibodies, and share with professional antigen presenting cells the ability to internalize foreign antigens, and process them for presentation to helper T cells. Recent evidence indicates that specialized cholesterol- and glycosphingolipid-rich microdomains in the plasma membrane commonly referred to as lipid rafts, serve to compartmentalize key signaling molecules during the different stages of B cell activation including B cell antigen receptor (BCR)-initiated signal transduction, endocytosis of BCR-antigen complexes, loading of antigenic peptides onto MHC class II molecules, MHC-II associated antigen presentation to helper T cells, and receipt of helper signals via the CD40 receptor. Here we review the recent literature arguing for a role of lipid rafts in the spatial organization of B cell function.

  13. Notch signalling in cancer stem cells.

    Science.gov (United States)

    Bolós, V; Blanco, M; Medina, V; Aparicio, G; Díaz-Prado, S; Grande, E

    2009-01-01

    A new theory about the development of solid tumours is emerging from the idea that solid tumours, like normal adult tissues, contain stem cells (called cancer stem cells) and arise from them. Genetic mutations encoding for proteins involved in critical signalling pathways for stem cells such as BMP, Notch, Hedgehog and Wnt would allow stem cells to undergo uncontrolled proliferation and form tumours. Taking into account that cancer stem cells (CSCs) would represent the real driving force behind tumour growth and that they may be drug resistant, new agents that target the above signalling pathways could be more effective than current anti-solid tumour therapies. In the present paper we will review the molecular basis of the Notch signalling pathway. Additionally, we will pay attention to their role in adult stem cell self-renewal, and cell fate specification and differentiation, and we will also review evidence that supports their implication in cancer.

  14. Social multimedia signals a signal processing approach to social network phenomena

    CERN Document Server

    Roy, Suman Deb

    2014-01-01

    This book provides a comprehensive coverage of the state-of-the-art in understanding media popularity and trends in online social networks through social multimedia signals. With insights from the study of popularity and sharing patterns of online media, trend spread in social media, social network analysis for multimedia and visualizing diffusion of media in online social networks. In particular, the book will address the following important issues: Understanding social network phenomena from a signal processing point of view; The existence and popularity of multimedia as shared and social me

  15. Radar signal design problem with neural network processing

    Indian Academy of Sciences (India)

    Unknown

    Abstract. Binary and ternary sequences with peaky autocorrelation, measured in terms of high discrimination and merit factor have been searched earlier, using optimization techniques. It is shown that the use of neural network processing of the return signal is much more advantageous. It opens up a new signal design ...

  16. Classification of cell signalling in tissue development.

    Science.gov (United States)

    Platt, Craig Charles; Nicholls, Clare; Brookes, Chris; Wood, Ian

    2011-02-01

    The traditional classification of signalling in biological systems is insufficient and outdated and novel efforts must take into account advances in systems theory, information theory and linguistics. We present some of the classification systems currently used both within and outside of the biological field and discuss some specific aspects of the nature of signalling in tissue development. The analytical methods used in understanding non-biological networks provide a valuable vocabulary, which requires integration and a system of classification to further facilitate development.

  17. The EEG Signal Prediction by Using Neural Network

    Directory of Open Access Journals (Sweden)

    Branko Babusiak

    2008-01-01

    Full Text Available The neural network is computational model based on the features abstraction of biological neural systems. The neural networks have many ways of usage in technical field. They have been applied successfully to speech recognition, image analysis and adaptive control, in order to construct software agents or autonomous robots. In this paper is described usage of neural networks for ECG signal prediction. The ECG signal prediction can be used for  automated detection of irregular heartbeat – extrasystole. The automated detection system of unexpected abnormalities is also described in this paper

  18. Towards the systematic discovery of signal transduction networks using phosphorylation dynamics data

    Directory of Open Access Journals (Sweden)

    Yachie Nozomu

    2010-05-01

    Full Text Available Abstract Background Phosphorylation is a ubiquitous and fundamental regulatory mechanism that controls signal transduction in living cells. The number of identified phosphoproteins and their phosphosites is rapidly increasing as a result of recent mass spectrometry-based approaches. Results We analyzed time-course phosphoproteome data obtained previously by liquid chromatography mass spectrometry with the stable isotope labeling using amino acids in cell culture (SILAC method. This provides the relative phosphorylation activities of digested peptides at each of five time points after stimulating HeLa cells with epidermal growth factor (EGF. We initially calculated the correlations between the phosphorylation dynamics patterns of every pair of peptides and connected the strongly correlated pairs to construct a network. We found that peptides extracted from the same intracellular fraction (nucleus vs. cytoplasm tended to be close together within this phosphorylation dynamics-based network. The network was then analyzed using graph theory and compared with five known signal-transduction pathways. The dynamics-based network was correlated with known signaling pathways in the NetPath and Phospho.ELM databases, and especially with the EGF receptor (EGFR signaling pathway. Although the phosphorylation patterns of many proteins were drastically changed by the EGF stimulation, our results suggest that only EGFR signaling transduction was both strongly activated and precisely controlled. Conclusions The construction of a phosphorylation dynamics-based network provides a useful overview of condition-specific intracellular signal transduction using quantitative time-course phosphoproteome data under specific experimental conditions. Detailed prediction of signal transduction based on phosphoproteome dynamics remains challenging. However, since the phosphorylation profiles of kinase-substrate pairs on the specific pathway were localized in the dynamics

  19. Detection test of wireless network signal strength and GPS positioning signal in underground pipeline

    Science.gov (United States)

    Li, Li; Zhang, Yunwei; Chen, Ling

    2018-03-01

    In order to solve the problem of selecting positioning technology for inspection robot in underground pipeline environment, the wireless network signal strength and GPS positioning signal testing are carried out in the actual underground pipeline environment. Firstly, the strength variation of the 3G wireless network signal and Wi-Fi wireless signal provided by China Telecom and China Unicom ground base stations are tested, and the attenuation law of these wireless signals along the pipeline is analyzed quantitatively and described. Then, the receiving data of the GPS satellite signal in the pipeline are tested, and the attenuation of GPS satellite signal under underground pipeline is analyzed. The testing results may be reference for other related research which need to consider positioning in pipeline.

  20. Syndecans, signaling, and cell adhesion

    DEFF Research Database (Denmark)

    Couchman, J R; Woods, A

    1996-01-01

    with the microfilament cytoskeleton, thereby mediating signaling events. The molecular details are unknown, but the conservation of regions of syndecan cytoplasmic domains, and a strong tendency for homotypic association, support the idea that the ligand-induced clustering may be a discrete source of specific...

  1. Prioritizing Signaling Information Transmission in Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Jasmina Baraković

    2011-01-01

    Full Text Available Next generation transport network is characterized by the use of in-band signaling, where Internet Protocol (IP packets carrying signaling or media information are mixed in transmission. Since transport resources are limited, when any segment of access or core network is congested, IP packets carrying signaling information may be discarded. As a consequence, it may be impossible to implement reachability and quality of service (QoS. Since present approaches are insufficient to completely address this problem, a novel approach is proposed, which is based on prioritizing signaling information transmission. To proof the concept, a simulation study was performed using Network Simulator version 2 (ns-2 and independently developed Session Initiation Protocol (SIP module. The obtained results were statistically processed using Statistical Package for the Social Sciences (SPSS version 15.0. Summarizing our research results, several issues are identified for future work.

  2. Classification of transcranial Doppler signals using artificial neural network.

    Science.gov (United States)

    Serhatlioğlu, Selami; Hardalaç, Firat; Güler, Inan

    2003-04-01

    Transcranial Doppler signals, recorded from the temporal region of brain on 110 patients were transferred to a personal computer by using a 16-bit sound card. The fast Fourier transform (FFT) method was applied to the recorded signal from each patient. Since FFT method inherently can not offer a good spectral resolution at jet blood flows, it sometimes causes wrong interpretation of transcranial Doppler signals. To do a correct and rapid diagnosis, transcranial Doppler blood flow signals were statistically arranged so that they were classified in artificial neural network. Back propagation neural network and self-organization map algorithms of artificial neural network were used for training, whereas momentum and delta-bar-delta algorithms were used for learning. The results of these algorithms were compared in the case of classification and learning.

  3. Fiber fault location utilizing traffic signal in optical network.

    Science.gov (United States)

    Zhao, Tong; Wang, Anbang; Wang, Yuncai; Zhang, Mingjiang; Chang, Xiaoming; Xiong, Lijuan; Hao, Yi

    2013-10-07

    We propose and experimentally demonstrate a method for fault location in optical communication network. This method utilizes the traffic signal transmitted across the network as probe signal, and then locates the fault by correlation technique. Compared with conventional techniques, our method has a simple structure and low operation expenditure, because no additional device is used, such as light source, modulator and signal generator. The correlation detection in this method overcomes the tradeoff between spatial resolution and measurement range in pulse ranging technique. Moreover, signal extraction process can improve the location result considerably. Experimental results show that we achieve a spatial resolution of 8 cm and detection range of over 23 km with -8-dBm mean launched power in optical network based on synchronous digital hierarchy protocols.

  4. Wnt Signaling in Cancer Stem Cell Biology

    NARCIS (Netherlands)

    de Sousa E Melo, Felipe; Vermeulen, Louis

    2016-01-01

    Aberrant regulation of Wnt signaling is a common theme seen across many tumor types. Decades of research have unraveled the epigenetic and genetic alterations that result in elevated Wnt pathway activity. More recently, it has become apparent that Wnt signaling levels identify stem-like tumor cells

  5. A modulator based regulatory network for ERα signaling pathway.

    Science.gov (United States)

    Wu, Heng-Yi; Zheng, Pengyue; Jiang, Guanglong; Liu, Yunlong; Nephew, Kenneth P; Huang, Tim H M; Li, Lang

    2012-01-01

    Estrogens control multiple functions of hormone-responsive breast cancer cells. They regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer. ERα requires distinct co-regulator or modulators for efficient transcriptional regulation, and they form a regulatory network. Knowing this regulatory network will enable systematic study of the effect of ERα on breast cancer. To investigate the regulatory network of ERα and discover novel modulators of ERα functions, we proposed an analytical method based on a linear regression model to identify translational modulators and their network relationships. In the network analysis, a group of specific modulator and target genes were selected according to the functionality of modulator and the ERα binding. Network formed from targets genes with ERα binding was called ERα genomic regulatory network; while network formed from targets genes without ERα binding was called ERα non-genomic regulatory network. Considering the active or repressive function of ERα, active or repressive function of a modulator, and agonist or antagonist effect of a modulator on ERα, the ERα/modulator/target relationships were categorized into 27 classes. Using the gene expression data and ERα Chip-seq data from the MCF-7 cell line, the ERα genomic/non-genomic regulatory networks were built by merging ERα/ modulator/target triplets (TF, M, T), where TF refers to the ERα, M refers to the modulator, and T refers to the target. Comparing these two networks, ERα non-genomic network has lower FDR than the genomic network. In order to validate these two networks, the same network analysis was performed in the gene expression data from the ZR-75.1 cell. The network overlap analysis between two

  6. Insights into biological information processing: structural and dynamical analysis of a human protein signalling network

    Energy Technology Data Exchange (ETDEWEB)

    Fuente, Alberto de la; Fotia, Giorgio; Maggio, Fabio; Mancosu, Gianmaria; Pieroni, Enrico [CRS4 Bioinformatica, Parco Tecnologico POLARIS, Ed.1, Loc Piscinamanna, Pula (Italy)], E-mail: alf@crs4.it

    2008-06-06

    We present an investigation on the structural and dynamical properties of a 'human protein signalling network' (HPSN). This biological network is composed of nodes that correspond to proteins and directed edges that represent signal flows. In order to gain insight into the organization of cell information processing this network is analysed taking into account explicitly the edge directions. We explore the topological properties of the HPSN at the global and the local scale, further applying the generating function formalism to provide a suitable comparative model. The relationship between the node degrees and the distribution of signals through the network is characterized using degree correlation profiles. Finally, we analyse the dynamical properties of small sub-graphs showing high correlation between their occurrence and dynamic stability.

  7. Signal-regulated systems and networks

    CSIR Research Space (South Africa)

    Van Zyl, TL

    2010-07-01

    Full Text Available (t)) (1) The function fi may be stochastic in nature as is often the case in self-organising systems. Further it is noted that one of the K regulatory signals may be si itself. A set R of J equations of the form given by equation (1) model a... discrete SRS: R = 8 >>>>< >>>>: s1 (t +1) = f1 s11 (t) ;s12 (t) ; : : : ;s1k (t) s2 (t +1) = f2 s21 (t) ;s22 (t) ; : : : ;s2k (t) ... sJ (t +1) = fJ (sJ1 (t) ;sJ2 (t) ; : : : ;sJk (t)) (2) Different signal regulation machines may have...

  8. Cell Survival Signaling in Neuroblastoma

    Science.gov (United States)

    Megison, Michael L.; Gillory, Lauren A.; Beierle, Elizabeth A.

    2013-01-01

    Neuroblastoma is the most common extracranial solid tumor of childhood and is responsible for over 15% of pediatric cancer deaths. Neuroblastoma tumorigenesis and malignant transformation is driven by overexpression and dominance of cell survival pathways and a lack of normal cellular senescence or apoptosis. Therefore, manipulation of cell survival pathways may decrease the malignant potential of these tumors and provide avenues for the development of novel therapeutics. This review focuses on several facets of cell survival pathways including protein kinases (PI3K, AKT, ALK, and FAK), transcription factors (NF-κB, MYCN and p53), and growth factors (IGF, EGF, PDGF, and VEGF). Modulation of each of these factors decreases the growth or otherwise hinders the malignant potential of neuroblastoma, and many therapeutics targeting these pathways are already in the clinical trial phase of development. Continued research and discovery of effective modulators of these pathways will revolutionize the treatment of neuroblastoma. PMID:22934706

  9. Activation of Apoptotic Signal in Endothelial Cells through Intracellular Signaling Molecules Blockade in Tumor-Induced Angiogenesis

    Directory of Open Access Journals (Sweden)

    Hossein Bazmara

    2015-01-01

    Full Text Available Tumor-induced angiogenesis is the bridge between avascular and vascular tumor growth phases. In tumor-induced angiogenesis, endothelial cells start to migrate and proliferate toward the tumor and build new capillaries toward the tumor. There are two stages for sprout extension during angiogenesis. The first stage is prior to anastomosis, when single sprouts extend. The second stage is after anastomosis when closed flow pathways or loops are formed and blood flows in the closed loops. Prior to anastomosis, biochemical and biomechanical signals from extracellular matrix regulate endothelial cell phenotype; however, after anastomosis, blood flow is the main regulator of endothelial cell phenotype. In this study, the critical signaling pathways of each stage are introduced. A Boolean network model is used to map environmental and flow induced signals to endothelial cell phenotype (proliferation, migration, apoptosis, and lumen formation. Using the Boolean network model, blockade of intracellular signaling molecules of endothelial cell is investigated prior to and after anastomosis and the cell fate is obtained in each case. Activation of apoptotic signal in endothelial cell can prevent the extension of new vessels and may inhibit angiogenesis. It is shown that blockade of a few signaling molecules in endothelial cell activates apoptotic signal that are proposed as antiangiogenic strategies.

  10. Radar signal transmission and switching over optical networks

    Science.gov (United States)

    Esmail, Maged A.; Ragheb, Amr; Seleem, Hussein; Fathallah, Habib; Alshebeili, Saleh

    2018-03-01

    In this paper, we experimentally demonstrate a radar signal distribution over optical networks. The use of fiber enables us to distribute radar signals to distant sites with a low power loss. Moreover, fiber networks can reduce the radar system cost, by sharing precise and expensive radar signal generation and processing equipment. In order to overcome the bandwidth challenges in electrical switches, a semiconductor optical amplifier (SOA) is used as an all-optical device for wavelength conversion to the desired port (or channel) of a wavelength division multiplexing (WDM) network. Moreover, the effect of chromatic dispersion in double sideband (DSB) signals is combated by generating optical single sideband (OSSB) signals. The optimal values of the SOA device parameters required to generate an OSSB with a high sideband suppression ratio (SSR) are determined. We considered various parameters such as injection current, pump power, and probe power. In addition, the effect of signal wavelength conversion and transmission over fiber are studied in terms of signal dynamic range.

  11. Precisely timed signal transmission in neocortical networks with reliable intermediate-range projections

    Directory of Open Access Journals (Sweden)

    Martin P Nawrot

    2009-02-01

    Full Text Available The mammalian neocortex has a remarkable ability to precisely reproduce behavioral sequences or to reliably retrieve stored information. In contrast, spiking activity in behaving animals shows a considerable trial-to-trial variability and temporal irregularity. The signal propagation and processing underlying these conflicting observations is based on fundamental neurophysiological processes like synaptic transmission, signal integration within single cells, and spike formation. Each of these steps in the neuronal signaling chain has been studied separately to a great extend, but it has been difficult to judge how they interact and sum up in active sub-networks of neocortical cells. In the present study, we experimentally assessed the precision and reliability of small neocortical networks consisting of trans-columnar, intermediate-range projections (200 – 1000 µm on a millisecond time-scale. Employing photo-uncaging of glutamate in acute slices, we activated a number of distant pre-synaptic cells in a spatiotemporally precisely controlled manner, while monitoring the resulting membrane potential fluctuations of a post-synaptic cell. We found that signal integration in this part of the network is highly reliable and temporally precise. As numerical simulations showed, the residual membrane potential variability can be attributed to amplitude variability in synaptic transmission and may significantly contribute to trial-to-trial output variability of a rate signal. However, it does not impair the temporal accuracy of signal integration. We conclude that signals from intermediate-range projections onto neocortical neurons are propagated and integrated in a highly reliable and precise manner, and may serve as a substrate for temporally precise signal transmission in neocortical networks.

  12. Metabolic networks: a signal-oriented approach to cellular models.

    Science.gov (United States)

    Lengeler, J W

    2000-01-01

    Complete genomes, far advanced proteomes, and even 'metabolomes' are available for at least a few organisms, e.g., Escherichia coli. Systematic functional analyses of such complete data sets will produce a wealth of information and promise an understanding of the dynamics of complex biological networks and perhaps even of entire living organisms. Such complete and holistic descriptions of biological systems, however, will increasingly require a quantitative analysis and the help of mathematical models for simulating whole systems. In particular, new procedures are required that allow a meaningful reduction of the information derived from complex systems that will consequently be used in the modeling process. In this review the biological elements of such a modeling procedure will be described. In a first step, complex living systems must be structured into well-defined and clearly delimited functional units, the elements of which have a common physiological goal, belong to a single genetic unit, and respond to the signals of a signal transduction system that senses changes in physiological states of the organism. These functional units occur at each level of complexity and more complex units originate by grouping several lower level elements into a single, more complex unit. To each complexity level corresponds a global regulator that is epistatic over lower level regulators. After its structuring into modules (functional units), a biological system is converted in a second step into mathematical submodels that by progressive combination can also be assembled into more aggregated model structures. Such a simplification of a cell (an organism) reduces its complexity to a level amenable to present modeling capacities. The universal biochemistry, however, promises a set of rules valid for modeling biological systems, from unicellular microorganisms and cells, to multicellular organisms and to populations.

  13. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

    Science.gov (United States)

    Teschendorff, Andrew E.; Banerji, Christopher R. S.; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-01-01

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology. PMID:25919796

  14. Sonic hedgehog signaling in basal cell carcinomas.

    Science.gov (United States)

    Daya-Grosjean, Leela; Couvé-Privat, Sophie

    2005-07-28

    The development of basal cell carcinoma, the commonest human cancer in fair skinned populations, is clearly associated with constitutive activation of sonic hedgehog signaling. Insight into the genesis of BCC came from the identification of germline mutations of the tumor suppressor gene, PATCHED, a key regulatory component of hedgehog signaling in the nevoid basal cell carcinoma syndrome. Analysis of sporadic basal cell carcinomas and those from repair deficient xeroderma pigmentosum patients has revealed mutational inactivation of PATCHED and gain of function mutations of the proto-oncogenes, SMOOTHENED and SONIC HEDGEHOG associated with solar UV exposure. The molecular mechanisms involved in alterations of the hedgehog signaling pathway that lead to the formation of basal cell carcinomas are being unraveled and has already allowed the investigation of future therapeutic strategies for treating these skin cancers.

  15. Optical Performance Monitoring and Signal Optimization in Optical Networks

    DEFF Research Database (Denmark)

    Petersen, Martin Nordal

    2006-01-01

    The thesis studies performance monitoring for the next generation optical networks. The focus is on all-optical networks with bit-rates of 10 Gb/s or above. Next generation all-optical networks offer large challenges as the optical transmitted distance increases and the occurrence of electrical......-optical-electrical regeneration points decreases. This thesis evaluates the impact of signal degrading effects that are becoming of increasing concern in all-optical high-speed networks due to all-optical switching and higher bit-rates. Especially group-velocity-dispersion (GVD) and a number of nonlinear effects will require...... enhanced attention to avoid signal degradations. The requirements for optical performance monitoring features are discussed, and the thesis evaluates the advantages and necessity of increasing the level of performance monitoring parameters in the physical layer. In particular, methods for optical...

  16. Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6

    Directory of Open Access Journals (Sweden)

    Ananthi Jebaseeli Samuelraj

    2015-01-01

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

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

    Science.gov (United States)

    Samuelraj, Ananthi Jebaseeli; Jayapal, Sundararajan

    2015-01-01

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

  18. Endoplasmic reticulum calcium signaling in nerve cells

    Directory of Open Access Journals (Sweden)

    ALEXEI VERKHRATSKY

    2004-01-01

    Full Text Available The endoplasmic reticulum (ER is an important organelle involved in various types of signaling in nerve cells. The ER serves as a dynamic Ca2+ pool being thus involved in rapid signaling events associated with cell stimulation by either electrical (action potential or chemical (neurotransmitters signals. This function is supported by Ca2+ release channels (InsP3 and ryanodine receptors and SERCA Ca2+ pumps residing in the endomembrane. In addition the ER provides a specific environment for the posttranslational protein processing and transport of various molecules towards their final destination. In parallel, the ER acts as a "calcium tunnel," which facilitates Ca2+ movements within the cell by avoiding cytoplasmic routes. Finally the ER appears as a source of numerous signals aimed at the nucleus and involved in long-lasting adaptive cellular responses. All these important functions are controlled by intra-ER free Ca2+ which integrates various signaling events and establishes a link between fast signaling, associated with ER Ca2+ release/uptake, and long-lasting adaptive responses relying primarily on the regulation of protein synthesis. Disruption of ER Ca2+ homeostasis triggers several forms of cellular stress response and is intimately involved in neurodegeneration and neuronal cell death

  19. Evolution of Hormone Signaling Networks in Plant Defense.

    Science.gov (United States)

    Berens, Matthias L; Berry, Hannah M; Mine, Akira; Argueso, Cristiana T; Tsuda, Kenichi

    2017-08-04

    Studies with model plants such as Arabidopsis thaliana have revealed that phytohormones are central regulators of plant defense. The intricate network of phytohormone signaling pathways enables plants to activate appropriate and effective defense responses against pathogens as well as to balance defense and growth. The timing of the evolution of most phytohormone signaling pathways seems to coincide with the colonization of land, a likely requirement for plant adaptations to the more variable terrestrial environments, which included the presence of pathogens. In this review, we explore the evolution of defense hormone signaling networks by combining the model plant-based knowledge about molecular components mediating phytohormone signaling and cross talk with available genome information of other plant species. We highlight conserved hubs in hormone cross talk and discuss evolutionary advantages of defense hormone cross talk. Finally, we examine possibilities of engineering hormone cross talk for improvement of plant fitness and crop production.

  20. 1st International Conference on Signal, Networks, Computing, and Systems

    CERN Document Server

    Mohapatra, Durga; Nagar, Atulya; Sahoo, Manmath

    2016-01-01

    The book is a collection of high-quality peer-reviewed research papers presented in the first International Conference on Signal, Networks, Computing, and Systems (ICSNCS 2016) held at Jawaharlal Nehru University, New Delhi, India during February 25–27, 2016. The book is organized in to two volumes and primarily focuses on theory and applications in the broad areas of communication technology, computer science and information security. The book aims to bring together the latest scientific research works of academic scientists, professors, research scholars and students in the areas of signal, networks, computing and systems detailing the practical challenges encountered and the solutions adopted.

  1. Cell signalling and phospholipid metabolism. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Boss, W.F.

    1990-12-31

    These studies explored whether phosphoinositide (PI) has a role in plants analogous to its role in animal cells. Although no parallel activity of PI in signal transduction was found in plant cells, activity of inositol phospholipid kinase was found to be modulated by light and by cell wall degrading enzymes. These studies indicate a major role for inositol phospholipids in plant growth and development as membrane effectors but not as a source of second messengers.

  2. Use of artificial neural networks in biosensor signal classification

    Directory of Open Access Journals (Sweden)

    Vlastimil Dohnal

    2008-01-01

    Full Text Available Biosensors are analytical devices that transforms chemical information, ranging from the concentration of a specific sample component to total composition analysis, into an analytical signal and that utilizes a biochemical mechanism for the chemical recognition. The complexity of biosensor construction and generation of measured signal requires the development of new method for signal eva­luation and its possible defects recognition. A new method based on artificial neural networks (ANN was developed for recognition of characteristic behavior of signals joined with malfunction of sensor. New algorithm uses unsupervised Kohonen self-organizing neural networks. The work with ANN has two phases – adaptation and prediction. During the adaptation step the classification model is build. Measured data form groups after projection into two-dimensional space based on theirs similarity. After identification of these groups and establishing the connection with signal disorders ANN can be used for evaluation of newly measured signals. This algorithm was successfully applied for 540 signal classification obtained from immobilized acetylcholinesterase biosensor measurement of organophosphate and carbamate pesticides in vegetables, fruits, spices, potatoes and soil samples. From six different signal defects were successfully classified four – low response after substrate addition, equilibration at high values, slow equilibration after substrate addition respectively low sensitivity on syntostigmine.

  3. Mapping the follicle-stimulating hormone-induced signalling networks

    Directory of Open Access Journals (Sweden)

    Pauline eGloaguen

    2011-10-01

    Full Text Available Follicle-stimulating hormone (FSH is a central regulator of male and female reproductive function. Over the last decade, there has been a growing perception of the complexity associated with FSH-induced cellular signalling. It is now clear that the canonical Gs/cAMP/PKA pathway is not the sole mechanism that must be considered in FSH biological actions. In parallel, consistent with the emerging concept of biased agonism, several examples of ligand-mediated selective signalling pathway activation by gonadotropin receptors have been reported. In this context, it is important to gain an integrative view of the signalling pathways induced by FSH and how they interconnect to form a network. In this review, we propose a first attempt at building topological maps of various pathways known to be involved in the FSH-induced signalling network. We discuss the multiple facets of FSH-induced signalling and how they converge to the hormone integrated biological response. Despite of their incompleteness, these maps of the FSH-induced signalling network represent a first step towards gaining a system-level comprehension of this hormone’s actions, which may ultimately facilitate the discovery of novel regulatory processes and therapeutic strategies for infertilities and non-steroidal contraception.

  4. Subsurface Event Detection and Classification Using Wireless Signal Networks

    Science.gov (United States)

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

    2012-01-01

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

  5. Induction of primordial germ cell-like cells from mouse embryonic stem cells by ERK signal inhibition.

    Science.gov (United States)

    Kimura, Tohru; Kaga, Yoshiaki; Ohta, Hiroshi; Odamoto, Mika; Sekita, Yoichi; Li, Kunpeng; Yamano, Noriko; Fujikawa, Keita; Isotani, Ayako; Sasaki, Norihiko; Toyoda, Masashi; Hayashi, Katsuhiko; Okabe, Masaru; Shinohara, Takashi; Saitou, Mitinori; Nakano, Toru

    2014-10-01

    Primordial germ cells (PGCs) are embryonic germ cell precursors. Specification of PGCs occurs under the influence of mesodermal induction signaling during in vivo gastrulation. Although bone morphogenetic proteins and Wnt signaling play pivotal roles in both mesodermal and PGC specification, the signal regulating PGC specification remains unknown. Coculture of mouse embryonic stem cells (ESCs) with OP9 feeder cells induces mesodermal differentiation in vitro. Using this mesodermal differentiation system, we demonstrated that PGC-like cells were efficiently induced from mouse ESCs by extracellular signal-regulated kinase (ERK) signaling inhibition. Inhibition of ERK signaling by a MAPK/ERK kinase (MEK) inhibitor upregulated germ cell marker genes but downregulated mesodermal genes. In addition, the PGC-like cells showed downregulation of DNA methylation and formed pluripotent stem cell colonies upon treatment with retinoic acid. These results show that inhibition of ERK signaling suppresses mesodermal differentiation but activates germline differentiation program in this mesodermal differentiation system. Our findings provide a new insight into the signaling networks regulating PGC specification. © 2014 AlphaMed Press.

  6. Learning Signaling Network Structures with Sparsely Distributed Data

    OpenAIRE

    Sachs, Karen; Itani, Solomon; Carlisle, Jennifer; Nolan, Garry P.; Pe'er, Dana; Lauffenburger, Douglas A.

    2009-01-01

    Flow cytometric measurement of signaling protein abundances has proved particularly useful for elucidation of signaling pathway structure. The single cell nature of the data ensures a very large dataset size, providing a statistically robust dataset for structure learning. Moreover, the approach is easily scaled to many conditions in high throughput. However, the technology suffers from a dimensionality constraint: at the cutting edge, only about 12 protein species can be measured per cell, f...

  7. On the distribution of signal phase in body area networks

    NARCIS (Netherlands)

    Wilson, S.K.; Cotton, Simon L.; Dias, Ugo S.; Scanlon, W.G.; Yacoub, Michel D.

    2010-01-01

    In this letter, we investigate the distribution of the phase component of the complex received signal observed in practical experiments using body area networks. Two phase distributions, the recently proposed κ-μ and η-μ probability densities, which together encompass the most widely used fading

  8. Application of the minimum fuel neural network to music signals

    DEFF Research Database (Denmark)

    Harbo, Anders La-Cour

    2004-01-01

    Finding an optimal representation of a signal in an over-complete dictionary is often quite difficult. Since general results in this field are not very application friendly it truly helps to specify the framework as much as possible. We investigate the method Minimum Fuel Neural Network (MFNN...

  9. NO signaling in retinal bipolar cells.

    Science.gov (United States)

    Agurto, A; Vielma, A H; Cadiz, B; Couve, E; Schmachtenberg, O

    2017-08-01

    Nitric oxide (NO) is a neuromodulator involved in physiological and pathological processes in the retina. In the inner retina, a subgroup of amacrine cells have been shown to synthesize NO, but bipolar cells remain controversial as NO sources. This study correlates NO synthesis in dark-adapted retinas, through labeling with the NO marker DAF-FM, with neuronal nitric oxide synthase (nNOS) and inducible NOS expression, and presence of the NO receptor soluble guanylate cyclase in bipolar cells. NO containing bipolar cells were morphologically identified by dialysis of DAF fluorescent cells with intracellular dyes, or by DAF labeling followed by immunohistochemistry for nNOS and other cellular markers. DAF fluorescence was observed in all types of bipolar cells that could be identified, but the most intense DAF fluorescence was observed in bipolar cells with severed processes, supporting pathological NO signaling. Among nNOS expressing bipolar cells, type 9 was confirmed unequivocally, while types 2, 3a, 3b, 4, 5, 7, 8 and the rod bipolar cell were devoid of this enzyme. These results establish specific bipolar cell types as NO sources in the inner retina, and support the involvement of NO signaling in physiological and pathological processes in the inner retina. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Cytokine signalling in embryonic stem cells

    DEFF Research Database (Denmark)

    Kristensen, David Møbjerg; Kalisz, Mark; Nielsen, Jens Høiriis

    2006-01-01

    signalling pathways have been documented. In addition, gp130 activation leads to both PI3K and Src activation. The canonical Wnt pathway is sufficient to maintain self-renewal of both human ES cells and mouse ES cells. It seems quite possible that the main pathway maintaining self-renewal in ES cells...... is the Wnt pathway, while the LIF-JAK-STAT3 pathway is present in mouse cells as an adaptation for sustaining self-renewal during embryonic diapause, a condition of delayed implantation in mammals. In keeping with this scenario, the Wnt pathway has been shown to elevate the level of c-myc. Thus, the two...

  11. Signal Processing Device (SPD) for networked radiation monitoring system

    International Nuclear Information System (INIS)

    Dharmapurikar, A.; Bhattacharya, S.; Mukhopadhyay, P.K.; Sawhney, A.; Patil, R.K.

    2010-01-01

    A networked radiation and parameter monitoring system with three tier architecture is being developed. Signal Processing Device (SPD) is a second level sub-system node in the network. SPD is an embedded system which has multiple input channels and output communication interfaces. It acquires and processes data from first level parametric sensor devices, and sends to third level devices in response to request commands received from host. It also performs scheduled diagnostic operations and passes on the information to host. It supports inputs in the form of differential digital signals and analog voltage signals. SPD communicates with higher level devices over RS232/RS422/USB channels. The system has been designed with main requirements of minimal power consumption and harsh environment in radioactive plants. This paper discusses the hardware and software design details of SPD. (author)

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

    Directory of Open Access Journals (Sweden)

    Kirouac Daniel C

    2012-05-01

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

  13. Designer cell signal processing circuits for biotechnology.

    Science.gov (United States)

    Bradley, Robert W; Wang, Baojun

    2015-12-25

    Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  14. Symmetry breaking signaling mechanisms during cell polarization

    NARCIS (Netherlands)

    Bruurs, LJM

    2017-01-01

    Breaking of cellular symmetry in order to establish an apico-basal polarity axis initiates de novo formation of cell polarity. However, symmetry breaking provides a formidable challenge from a signaling perspective, because by definition no spatial cues are present to instruct axis establishment.

  15. Regulation of monocyte differentiation by specific signaling modules and associated transcription factor networks.

    Science.gov (United States)

    Huber, René; Pietsch, Daniel; Günther, Johannes; Welz, Bastian; Vogt, Nico; Brand, Korbinian

    2014-01-01

    Monocyte/macrophages are important players in orchestrating the immune response as well as connecting innate and adaptive immunity. Myelopoiesis and monopoiesis are characterized by the interplay between expansion of stem/progenitor cells and progression towards further developed (myelo)monocytic phenotypes. In response to a variety of differentiation-inducing stimuli, various prominent signaling pathways are activated. Subsequently, specific transcription factors are induced, regulating cell proliferation and maturation. This review article focuses on the integration of signaling modules and transcriptional networks involved in the determination of monocytic differentiation.

  16. Programs for control of an analog-signal switching network

    International Nuclear Information System (INIS)

    D'Ottavio, T.; Enriquez, R.; Katz, R.; Skelly, J.

    1989-01-01

    A suite of programs has been developed to control the network of analog-signal switching multiplexers in the AGS complex. The software is driven by a relational database which describes the architecture of the multiplexer tree and the set of available analog signals. Signals are routed through a three-layer multiplexer tree, to be made available at four consoles each with three 4-trace oscilloscopes. A menu-structured operator interface program is available at each console, to accept requests to route any available analog signal to any of that console's 12 oscilloscope traces. A common routing-server program provides automatic routing-server program provides automatic routing of requested signals through the layers of multiplexers, maintaining a reservation database to denote free and in-use trunks. Expansion of the analog signal system is easily accommodated in software by adding new signals, trunks, multiplexers, or consoles to the database. Programmatic control of the triggering signals for each of the oscilloscopes is also provided. 3 refs., 4 figs., 3 tabs

  17. Transcription factor-mediated cell-to-cell signalling in plants.

    Science.gov (United States)

    Han, Xiao; Kumar, Dhinesh; Chen, Huan; Wu, Shuwei; Kim, Jae-Yean

    2014-04-01

    Plant cells utilize mobile transcription factors to transmit intercellular signals when they perceive environmental stimuli or initiate developmental programmes. Studies on these novel cell-to-cell signals have accumulated multiple pieces of evidence showing that non-cell-autonomous transcription factors play pivotal roles in most processes related to the formation and development of plant organs. Recent studies have explored the evolution of mobile transcription factors and proposed mechanisms for their trafficking through plasmodesmata, where a selective system exists to facilitate this process. Mobile transcription factors contribute to the diversity of the intercellular signalling network, which is also established by peptides, hormones, and RNAs. Crosstalk between mobile transcription factors and other intercellular molecules leads to the development of complex biological signalling networks in plants. The regulation of plasmodesmata appears to have been another major step in controlling the intercellular trafficking of transcription factors based on studies of many plasmodesmal components. Furthermore, diverse omics approaches are being successfully applied to explore a large number of candidate transcription factors as mobile signals in plants. Here, we review these fascinating discoveries to integrate current knowledge of non-cell-autonomous transcription factors.

  18. Brain Network Analysis from High-Resolution EEG Signals

    Science.gov (United States)

    de Vico Fallani, Fabrizio; Babiloni, Fabio

    Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular

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

    Science.gov (United States)

    Kim, Ji Chul; Large, Edward W

    2015-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Farber, R.

    1987-06-01

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

  1. Characterization of patient specific signaling via augmentation of Bayesian networks with disease and patient state nodes.

    Science.gov (United States)

    Sachs, Karen; Gentles, Andrew J; Youland, Ryan; Itani, Solomon; Irish, Jonathan; Nolan, Garry P; Plevritis, Sylvia K

    2009-01-01

    Characterization of patient-specific disease features at a molecular level is an important emerging field. Patients may be characterized by differences in the level and activity of relevant biomolecules in diseased cells. When high throughput, high dimensional data is available, it becomes possible to characterize differences not only in the level of the biomolecules, but also in the molecular interactions among them. We propose here a novel approach to characterize patient specific signaling, which augments high throughput single cell data with state nodes corresponding to patient and disease states, and learns a Bayesian network based on this data. Features distinguishing individual patients emerge as downstream nodes in the network. We illustrate this approach with a six phospho-protein, 30,000 cell-per-patient dataset characterizing three comparably diagnosed follicular lymphoma, and show that our approach elucidates signaling differences among them.

  2. Nonlinear Silicon Photonic Signal Processing Devices for Future Optical Networks

    Directory of Open Access Journals (Sweden)

    Cosimo Lacava

    2017-01-01

    Full Text Available In this paper, we present a review on silicon-based nonlinear devices for all optical nonlinear processing of complex telecommunication signals. We discuss some recent developments achieved by our research group, through extensive collaborations with academic partners across Europe, on optical signal processing using silicon-germanium and amorphous silicon based waveguides as well as novel materials such as silicon rich silicon nitride and tantalum pentoxide. We review the performance of four wave mixing wavelength conversion applied on complex signals such as Differential Phase Shift Keying (DPSK, Quadrature Phase Shift Keying (QPSK, 16-Quadrature Amplitude Modulation (QAM and 64-QAM that dramatically enhance the telecom signal spectral efficiency, paving the way to next generation terabit all-optical networks.

  3. Sulforaphane attenuates EGFR signaling in NSCLC cells.

    Science.gov (United States)

    Chen, Chi-Yuan; Yu, Zhu-Yun; Chuang, Yen-Shu; Huang, Rui-Mei; Wang, Tzu-Chien V

    2015-06-03

    EGFR, a receptor tyrosine kinase (RTK), is frequently overexpressed and mutated in non-small cell lung cancer (NSCLC). Tyrosine kinase inhibitors (TKIs) have been widely used in the treatment of many cancers, including NSCLC. However, intrinsic and acquired resistance to TKI remains a common obstacle. One strategy that may help overcome EGFR-TKI resistance is to target EGFR for degradation. As EGFR is a client protein of heat-shock protein 90 (HSP90) and sulforaphane is known to functionally regulate HSP90, we hypothesized that sulforaphane could attenuate EGFR-related signaling and potentially be used to treat NSCLC. Our study revealed that sulforaphane displayed antitumor activity against NSCLC cells both in vitro and in vivo. The sensitivity of NSCLC cells to sulforaphane appeared to positively correlate with the inhibition of EGFR-related signaling, which was attributed to the increased proteasomal degradation of EGFR. Combined treatment of NSCLC cells with sulforaphane plus another HSP90 inhibitor (17-AAG) enhanced the inhibition of EGFR-related signaling both in vitro and in vivo. We have shown that sulforaphane is a novel inhibitory modulator of EGFR expression and is effective in inhibiting the tumor growth of EGFR-TKI-resistant NSCLC cells. Our findings suggest that sulforaphane should be further explored for its potential clinical applications against NSCLC.

  4. Racial differences in B cell receptor signaling pathway activation.

    Science.gov (United States)

    Longo, Diane M; Louie, Brent; Mathi, Kavita; Pos, Zoltan; Wang, Ena; Hawtin, Rachael E; Marincola, Francesco M; Cesano, Alessandra

    2012-06-06

    Single-cell network profiling (SCNP) is a multi-parametric flow cytometry-based approach that simultaneously measures basal and modulated intracellular signaling activity in multiple cell subpopulations. Previously, SCNP analysis of a broad panel of immune signaling pathways in cell subsets within PBMCs from 60 healthy donors identified a race-associated difference in B cell anti-IgD-induced PI3K pathway activity. The present study extended this analysis to a broader range of signaling pathway components downstream of the B cell receptor (BCR) in European Americans and African Americans using a subset of donors from the previously analyzed cohort of 60 healthy donors. Seven BCR signaling nodes (a node is defined as a paired modulator and intracellular readout) were measured at multiple time points by SCNP in PBMCs from 10 healthy donors [5 African Americans (36-51 yrs), 5 European Americans (36-56 yrs), all males]. Analysis of BCR signaling activity in European American and African American PBMC samples revealed that, compared to the European American donors, B cells from African Americans had lower anti-IgD induced phosphorylation of multiple BCR pathway components, including the membrane proximal proteins Syk and SFK as well as proteins in the PI3K pathway (S6 and Akt), the MAPK pathways (Erk and p38), and the NF-κB pathway (NF-κB). In addition to differences in the magnitude of anti-IgD-induced pathway activation, racial differences in BCR signaling kinetic profiles were observed. Further, the frequency of IgD+ B cells differed by race and strongly correlated with BCR pathway activation. Thus, the race-related difference in BCR pathway activation appears to be attributable at least in part to a race-associated difference in IgD+ B cell frequencies. SCNP analysis enabled the identification of statistically significant race-associated differences in BCR pathway activation within PBMC samples from healthy donors. Understanding race-associated contrasts in immune

  5. Racial differences in B cell receptor signaling pathway activation

    Directory of Open Access Journals (Sweden)

    Longo Diane M

    2012-06-01

    Full Text Available Abstract Background Single-cell network profiling (SCNP is a multi-parametric flow cytometry-based approach that simultaneously measures basal and modulated intracellular signaling activity in multiple cell subpopulations. Previously, SCNP analysis of a broad panel of immune signaling pathways in cell subsets within PBMCs from 60 healthy donors identified a race-associated difference in B cell anti-IgD-induced PI3K pathway activity. Methods The present study extended this analysis to a broader range of signaling pathway components downstream of the B cell receptor (BCR in European Americans and African Americans using a subset of donors from the previously analyzed cohort of 60 healthy donors. Seven BCR signaling nodes (a node is defined as a paired modulator and intracellular readout were measured at multiple time points by SCNP in PBMCs from 10 healthy donors [5 African Americans (36-51 yrs, 5 European Americans (36-56 yrs, all males]. Results Analysis of BCR signaling activity in European American and African American PBMC samples revealed that, compared to the European American donors, B cells from African Americans had lower anti-IgD induced phosphorylation of multiple BCR pathway components, including the membrane proximal proteins Syk and SFK as well as proteins in the PI3K pathway (S6 and Akt, the MAPK pathways (Erk and p38, and the NF-κB pathway (NF-κB. In addition to differences in the magnitude of anti-IgD-induced pathway activation, racial differences in BCR signaling kinetic profiles were observed. Further, the frequency of IgD+ B cells differed by race and strongly correlated with BCR pathway activation. Thus, the race-related difference in BCR pathway activation appears to be attributable at least in part to a race-associated difference in IgD+ B cell frequencies. Conclusions SCNP analysis enabled the identification of statistically significant race-associated differences in BCR pathway activation within PBMC samples from

  6. Music Signal Processing Using Vector Product Neural Networks

    Science.gov (United States)

    Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

    2017-05-01

    We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

  7. Distributed Signal Processing for Wireless EEG Sensor Networks.

    Science.gov (United States)

    Bertrand, Alexander

    2015-11-01

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

  8. Application of the minimum fuel neural network to music signals

    DEFF Research Database (Denmark)

    Harbo, Anders La-Cour

    2004-01-01

    ) for finding sparse representations of music signals. This method is a set of two ordinary differential equations. We argue that the most important parameter for optimal use of this method is the discretization step size, and we demonstrate that this can be a priori determined. This significantly speeds up......Finding an optimal representation of a signal in an over-complete dictionary is often quite difficult. Since general results in this field are not very application friendly it truly helps to specify the framework as much as possible. We investigate the method Minimum Fuel Neural Network (MFNN...

  9. Cell to cell signalling during vertebrate limb bud development

    NARCIS (Netherlands)

    Panman, Lia

    2004-01-01

    Communication between cells is essential during embryonic development. The vertebrate limb bud provides us a model to study signalling interactions between cells during patterning of embryonic tissues and organogenesis. In chapter 1 I give an introduction about limb bud development that is focussed

  10. The RhoJ-BAD signaling network: An Achilles' heel for BRAF mutant melanomas.

    Directory of Open Access Journals (Sweden)

    Rolando Ruiz

    2017-07-01

    Full Text Available Genes and pathways that allow cells to cope with oncogene-induced stress represent selective cancer therapeutic targets that remain largely undiscovered. In this study, we identify a RhoJ signaling pathway that is a selective therapeutic target for BRAF mutant cells. RhoJ deletion in BRAF mutant melanocytes modulates the expression of the pro-apoptotic protein BAD as well as genes involved in cellular metabolism, impairing nevus formation, cellular transformation, and metastasis. Short-term treatment of nascent melanoma tumors with PAK inhibitors that block RhoJ signaling halts the growth of BRAF mutant melanoma tumors in vivo and induces apoptosis in melanoma cells in vitro via a BAD-dependent mechanism. As up to 50% of BRAF mutant human melanomas express high levels of RhoJ, these studies nominate the RhoJ-BAD signaling network as a therapeutic vulnerability for fledgling BRAF mutant human tumors.

  11. The RhoJ-BAD signaling network: An Achilles' heel for BRAF mutant melanomas.

    Science.gov (United States)

    Ruiz, Rolando; Jahid, Sohail; Harris, Melissa; Marzese, Diego M; Espitia, Francisco; Vasudeva, Priya; Chen, Chi-Fen; de Feraudy, Sebastien; Wu, Jie; Gillen, Daniel L; Krasieva, Tatiana B; Tromberg, Bruce J; Pavan, William J; Hoon, Dave S; Ganesan, Anand K

    2017-07-01

    Genes and pathways that allow cells to cope with oncogene-induced stress represent selective cancer therapeutic targets that remain largely undiscovered. In this study, we identify a RhoJ signaling pathway that is a selective therapeutic target for BRAF mutant cells. RhoJ deletion in BRAF mutant melanocytes modulates the expression of the pro-apoptotic protein BAD as well as genes involved in cellular metabolism, impairing nevus formation, cellular transformation, and metastasis. Short-term treatment of nascent melanoma tumors with PAK inhibitors that block RhoJ signaling halts the growth of BRAF mutant melanoma tumors in vivo and induces apoptosis in melanoma cells in vitro via a BAD-dependent mechanism. As up to 50% of BRAF mutant human melanomas express high levels of RhoJ, these studies nominate the RhoJ-BAD signaling network as a therapeutic vulnerability for fledgling BRAF mutant human tumors.

  12. Automation of seismic network signal interpolation: an artificial intelligence approach

    International Nuclear Information System (INIS)

    Chiaruttini, C.; Roberto, V.

    1988-01-01

    After discussing the current status of the automation in signal interpretation from seismic networks, a new approach, based on artificial-intelligence tecniques, is proposed. The knowledge of the human expert analyst is examined, with emphasis on its objects, strategies and reasoning techniques. It is argued that knowledge-based systems (or expert systems) provide the most appropriate tools for designing an automatic system, modelled on the expert behaviour

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

    Science.gov (United States)

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

    2011-08-01

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

  14. Surface sensing and signaling networks in plant pathogenic fungi.

    Science.gov (United States)

    Kou, Yanjun; Naqvi, Naweed I

    2016-09-01

    Pathogenic fungi have evolved highly varied and remarkable strategies to invade and infect their plant hosts. Typically, such fungal pathogens utilize highly specialized infection structures, morphologies or cell types produced from conidia or ascospores on the cognate host surfaces to gain entry therein. Such diverse infection strategies require intricate coordination in cell signaling and differentiation in phytopathogenic fungi. Here, we present an overview of our current understanding of cell signaling and infection-associated development that primes host penetration in the top ten plant pathogenic fungi, which utilize specific receptors to sense and respond to different surface cues, such as topographic features, hydrophobicity, hardness, plant lipids, phytohormones, and/or secreted enzymes. Subsequently, diverse signaling components such as G proteins, cyclic AMP/Protein Kinase A and MAP kinases are activated to enable the differentiation of infection structures. Recent studies have also provided fascinating insights into the spatio-temporal dynamics and specialized sequestration and trafficking of signaling moieties required for proper development of infection structures in phytopathogenic fungi. Molecular insight in such infection-related morphogenesis and cell signaling holds promise for identifying novel strategies for intervention of fungal diseases in plants. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Systems biology in physiology: the vasopressin signaling network in kidney.

    Science.gov (United States)

    Knepper, Mark A

    2012-12-01

    Over the past 80 years, physiological research has moved progressively in a reductionist direction, providing mechanistic information on a smaller and smaller scale. This trend has culminated in the present focus on "molecular physiology," which deals with the function of single molecules responsible for cellular function. There is a need to assemble the information from the molecular level into models that explain physiological function at cellular, tissue, organ, and whole organism levels. Such integration is the major focus of an approach called "systems biology." The genome sequencing projects provide a basis for a new kind of systems biology called "data-rich" systems biology that is based on large-scale data acquisition methods including protein mass spectrometry, DNA microarrays, and deep sequencing of nucleic acids. These techniques allow investigators to measure thousands of variables simultaneously in response to an external stimulus. My laboratory is applying such an approach to the question: "How does the peptide hormone vasopressin regulate water permeability in the renal collecting duct?" We are using protein mass spectrometry to identify and quantify the phosphoproteome of collecting duct cells. The response to vasopressin, presented in the form of a network model, includes a general downregulation of proline-directed kinases (MAP kinases and cyclin-dependent kinases) and upregulation of basophilic kinases (ACG kinases and calmodulin-dependent kinases). Further progress depends on characterization and localization of candidate protein kinases in these families. The ultimate goal is to use multivariate statistical techniques and differential equations to obtain predictive models describing vasopressin signaling in the renal collecting duct.

  16. Signal transduction and chemotaxis in mast cells

    Czech Academy of Sciences Publication Activity Database

    Dráber, Petr; Hálová, Ivana; Polakovičová, Iva; Kawakami, T.

    2016-01-01

    Roč. 778, jaro (2016), s. 11-23 ISSN 0014-2999 R&D Projects: GA ČR(CZ) GA14-09807S; GA ČR(CZ) GBP302/12/G101; GA ČR(CZ) GA14-00703S Institutional support: RVO:68378050 Keywords : Mast cell * IgE receptor * KIT receptor * Signal transduction * Chemotaxis * Plasma membrane Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.896, year: 2016

  17. Cerebellar endocannabinoids: retrograde signaling from purkinje cells.

    Science.gov (United States)

    Marcaggi, Païkan

    2015-06-01

    The cerebellar cortex exhibits a strikingly high expression of type 1 cannabinoid receptor (CB1), the cannabinoid binding protein responsible for the psychoactive effects of marijuana. CB1 is primarily found in presynaptic elements in the molecular layer. While the functional importance of cerebellar CB1 is supported by the effect of gene deletion or exogenous cannabinoids on animal behavior, evidence for a role of endocannabinoids in synaptic signaling is provided by in vitro experiments on superfused acute rodent cerebellar slices. These studies have demonstrated that endocannabinoids can be transiently released by Purkinje cells and signal at synapses in a direction opposite to information transfer (retrograde). Here, following a description of the reported expression pattern of the endocannabinoid system in the cerebellum, I review the accumulated in vitro data, which have addressed the mechanism of retrograde endocannabinoid signaling and identified 2-arachidonoylglycerol as the mediator of this signaling. The mechanisms leading to endocannabinoid release, the effects of CB1 activation, and the associated synaptic plasticity mechanisms are discussed and the remaining unknowns are pointed. Notably, it is argued that the spatial specificity of this signaling and the physiological conditions required for its induction need to be determined in order to understand endocannabinoid function in the cerebellar cortex.

  18. Inflammatory signals regulate hematopoietic stem cells.

    Science.gov (United States)

    Baldridge, Megan T; King, Katherine Y; Goodell, Margaret A

    2011-02-01

    Hematopoietic stem cells (HSCs) are the progenitors of all blood and immune cells, yet their role in immunity is not well understood. Most studies have focused on the ability of committed lymphoid and myeloid precursors to replenish immune cells during infection. Recent studies, however, have indicated that HSCs also proliferate in response to systemic infection and replenish effector immune cells. Inflammatory signaling molecules including interferons, tumor necrosis factor-α and Toll-like receptors are essential to the HSC response. Observing the biology of HSCs through the lens of infection and inflammation has led to the discovery of an array of immune-mediators that serve crucial roles in HSC regulation and function. Copyright © 2010 Elsevier Ltd. All rights reserved.

  19. Random Deep Belief Networks for Recognizing Emotions from Speech Signals

    Directory of Open Access Journals (Sweden)

    Guihua Wen

    2017-01-01

    Full Text Available Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

  20. Speech Subvocal Signal Processing using Packet Wavelet and Neuronal Network

    Directory of Open Access Journals (Sweden)

    Luis E. Mendoza

    2013-11-01

    Full Text Available This paper presents the results obtained from the recording, processing and classification of words in the Spanish language by means of the analysis of subvocal speech signals. The processed database has six words (forward, backward, right, left, start and stop. In this work, the signals were sensed with surface electrodes placed on the surface of the throat and acquired with a sampling frequency of 50 kHz. The signal conditioning consisted in: the location of area of interest using energy analysis, and filtering using Discrete Wavelet Transform. Finally, the feature extraction was made in the time-frequency domain using Wavelet Packet and statistical techniques for windowing. The classification was carried out with a backpropagation neural network whose training was performed with 70% of the database obtained. The correct classification rate was 75%±2.

  1. Intraspecific evolution of the intercellular signaling network underlying a robust developmental system.

    Science.gov (United States)

    Milloz, Josselin; Duveau, Fabien; Nuez, Isabelle; Félix, Marie-Anne

    2008-11-01

    Many biological systems produce an invariant output when faced with stochastic or environmental variation. This robustness of system output to variation affecting the underlying process may allow for "cryptic" genetic evolution within the system without change in output. We studied variation of cell fate patterning of Caenorhabditis elegans vulva precursors, a developmental system that relies on a simple intercellular signaling network and yields an invariant output of cell fates and lineages among C. elegans wild isolates. We first investigated the system's genetic variation in C. elegans by means of genetic tools and cell ablation to break down its buffering mechanisms. We uncovered distinct architectures of quantitative variation along the Ras signaling cascade, including compensatory variation, and differences in cell sensitivity to induction along the anteroposterior axis. In the unperturbed system, we further found variation between isolates in spatio-temporal dynamics of Ras pathway activity, which can explain the phenotypic differences revealed upon perturbation. Finally, the variation mostly affects the signaling pathways in a tissue-specific manner. We thus demonstrate and characterize microevolution of a developmental signaling network. In addition, our results suggest that the vulva genetic screens would have yielded a different mutation spectrum, especially for Wnt pathway mutations, had they been performed in another C. elegans genetic background.

  2. Prediction of oncogenic interactions and cancer-related signaling networks based on network topology.

    Directory of Open Access Journals (Sweden)

    Marcio Luis Acencio

    Full Text Available Cancer has been increasingly recognized as a systems biology disease since many investigators have demonstrated that this malignant phenotype emerges from abnormal protein-protein, regulatory and metabolic interactions induced by simultaneous structural and regulatory changes in multiple genes and pathways. Therefore, the identification of oncogenic interactions and cancer-related signaling networks is crucial for better understanding cancer. As experimental techniques for determining such interactions and signaling networks are labor-intensive and time-consuming, the development of a computational approach capable to accomplish this task would be of great value. For this purpose, we present here a novel computational approach based on network topology and machine learning capable to predict oncogenic interactions and extract relevant cancer-related signaling subnetworks from an integrated network of human genes interactions (INHGI. This approach, called graph2sig, is twofold: first, it assigns oncogenic scores to all interactions in the INHGI and then these oncogenic scores are used as edge weights to extract oncogenic signaling subnetworks from INHGI. Regarding the prediction of oncogenic interactions, we showed that graph2sig is able to recover 89% of known oncogenic interactions with a precision of 77%. Moreover, the interactions that received high oncogenic scores are enriched in genes for which mutations have been causally implicated in cancer. We also demonstrated that graph2sig is potentially useful in extracting oncogenic signaling subnetworks: more than 80% of constructed subnetworks contain more than 50% of original interactions in their corresponding oncogenic linear pathways present in the KEGG PATHWAY database. In addition, the potential oncogenic signaling subnetworks discovered by graph2sig are supported by experimental evidence. Taken together, these results suggest that graph2sig can be a useful tool for investigators involved

  3. Fuel cells for telephone networks

    International Nuclear Information System (INIS)

    Wells, J.D.; Scott, D.S.

    1993-01-01

    Critical telephone network systems are currently protected from electric utility power failures by a backup system consisting of lead-acid batteries and an engine-alternator. It is considered here an alternate power system where less expensive off-peak commercial electricity electrolyses water, while fuel cells draw continuously on the stored gas products to provide direct current for the protected equipment. The lead acid batteries are eliminated. The benefits and costs of the existing and alternate systems in scenarios with various system efficiencies, capital costs, and electric utility rates and incentives, are compared. In today's conditions, the alternate system is not economical; however, cost and performance feasibility domains are identified. 2 figs., 4 tabs., 12 refs

  4. Stability of multispecies bacterial communities: signaling networks may stabilize microbiomes.

    Directory of Open Access Journals (Sweden)

    Ádám Kerényi

    Full Text Available Multispecies bacterial communities can be remarkably stable and resilient even though they consist of cells and species that compete for environmental resources. In silico models suggest that common signals released into the environment may help selected bacterial species cluster at common locations and that sharing of public goods (i.e. molecules produced and released for mutual benefit can stabilize this coexistence. In contrast, unilateral eavesdropping on signals produced by a potentially invading species may protect a community by keeping invaders away from limited resources. Shared bacterial signals, such as those found in quorum sensing systems, may thus play a key role in fine tuning competition and cooperation within multi-bacterial communities. We suggest that in addition to metabolic complementarity, signaling dynamics may be important in further understanding complex bacterial communities such as the human, animal as well as plant microbiomes.

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

    Science.gov (United States)

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

    2016-08-01

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

  6. DMPD: The interferon signaling network and transcription factor C/EBP-beta. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 18163952 The interferon signaling network and transcription factor C/EBP-beta. Li H... The interferon signaling network and transcription factor C/EBP-beta. PubmedID 18163952 Title The interferon signaling network

  7. Endothelial cell oxidative stress and signal transduction

    Directory of Open Access Journals (Sweden)

    ROCIO FONCEA

    2000-01-01

    Full Text Available Endothelial dysfunction (ED is an early event in atherosclerotic disease, preceding clinical manifestations and complications. Increased reactive oxygen species (ROS have been implicated as important mechanisms that contribute to ED, and ROS’s may function as intracellular messengers that modulate signaling pathways. Several intracellular signal events stimulated by ROS have been defined, including the identification of two members of the mitogen activated protein kinase family (ERK1/2 and big MAP kinase, BMK1, tyrosine kinases (Src and Syk and different isoenzymes of PKC as redox-sensitive kinases. ROS regulation of signal transduction components include the modification in the activity of transcriptional factors such as NFkB and others that result in changes in gene expression and modifications in cellular responses. In order to understand the intracellular mechanisms induced by ROS in endothelial cells (EC, we are studying the response of human umbilical cord vein endothelial cells to increased ROS generation by different pro-atherogenic stimuli. Our results show that Homocysteine (Hcy and oxidized LDL (oxLDL enhance the activity and expression of oxidative stress markers, such as NFkB and heme oxygenase 1. These results suggest that these pro-atherogenic stimuli increase oxidative stress in EC, and thus explain the loss of endothelial function associated with the atherogenic process

  8. Lossless Compression Schemes for ECG Signals Using Neural Network Predictors

    Directory of Open Access Journals (Sweden)

    C. Eswaran

    2007-01-01

    Full Text Available This paper presents lossless compression schemes for ECG signals based on neural network predictors and entropy encoders. Decorrelation is achieved by nonlinear prediction in the first stage and encoding of the residues is done by using lossless entropy encoders in the second stage. Different types of lossless encoders, such as Huffman, arithmetic, and runlength encoders, are used. The performances of the proposed neural network predictor-based compression schemes are evaluated using standard distortion and compression efficiency measures. Selected records from MIT-BIH arrhythmia database are used for performance evaluation. The proposed compression schemes are compared with linear predictor-based compression schemes and it is shown that about 11% improvement in compression efficiency can be achieved for neural network predictor-based schemes with the same quality and similar setup. They are also compared with other known ECG compression methods and the experimental results show that superior performances in terms of the distortion parameters of the reconstructed signals can be achieved with the proposed schemes.

  9. Reconstruction of Micropattern Detector Signals using Convolutional Neural Networks

    Science.gov (United States)

    Flekova, L.; Schott, M.

    2017-10-01

    Micropattern gaseous detector (MPGD) technologies, such as GEMs or MicroMegas, are particularly suitable for precision tracking and triggering in high rate environments. Given their relatively low production costs, MPGDs are an exemplary candidate for the next generation of particle detectors. Having acknowledged these advantages, both the ATLAS and CMS collaborations at the LHC are exploiting these new technologies for their detector upgrade programs in the coming years. When MPGDs are utilized for triggering purposes, the measured signals need to be precisely reconstructed within less than 200 ns, which can be achieved by the usage of FPGAs. In this work, we present a novel approach to identify reconstructed signals, their timing and the corresponding spatial position on the detector. In particular, we study the effect of noise and dead readout strips on the reconstruction performance. Our approach leverages the potential of convolutional neural network (CNNs), which have recently manifested an outstanding performance in a range of modeling tasks. The proposed neural network architecture of our CNN is designed simply enough, so that it can be modeled directly by an FPGA and thus provide precise information on reconstructed signals already in trigger level.

  10. Cell fate reprogramming by control of intracellular network dynamics

    Science.gov (United States)

    Zanudo, Jorge G. T.; Albert, Reka

    Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Although the topic of controlling the dynamics of a system has a long history in control theory, most of this work is not directly applicable to intracellular networks. Here we present a network control method that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our control method takes advantage of certain function-dependent network components and their relation to steady states in order to identify control targets, which are guaranteed to drive any initial state to the target state with 100% effectiveness and need to be applied only transiently for the system to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. This work was supported by NSF Grant PHY 1205840.

  11. Direct lifts of coupled cell networks

    Science.gov (United States)

    Dias, A. P. S.; Moreira, C. S.

    2018-04-01

    In networks of dynamical systems, there are spaces defined in terms of equalities of cell coordinates which are flow-invariant under any dynamical system that has a form consistent with the given underlying network structure—the network synchrony subspaces. Given a network and one of its synchrony subspaces, any system with a form consistent with the network, restricted to the synchrony subspace, defines a new system which is consistent with a smaller network, called the quotient network of the original network by the synchrony subspace. Moreover, any system associated with the quotient can be interpreted as the restriction to the synchrony subspace of a system associated with the original network. We call the larger network a lift of the smaller network, and a lift can be interpreted as a result of the cellular splitting of the smaller network. In this paper, we address the question of the uniqueness in this lifting process in terms of the networks’ topologies. A lift G of a given network Q is said to be direct when there are no intermediate lifts of Q between them. We provide necessary and sufficient conditions for a lift of a general network to be direct. Our results characterize direct lifts using the subnetworks of all splitting cells of Q and of all split cells of G. We show that G is a direct lift of Q if and only if either the split subnetwork is a direct lift or consists of two copies of the splitting subnetwork. These results are then applied to the class of regular uniform networks and to the special classes of ring networks and acyclic networks. We also illustrate that one of the applications of our results is to the lifting bifurcation problem.

  12. Arachidonic acid: an evolutionarily conserved signaling molecule modulates plant stress signaling networks.

    Science.gov (United States)

    Savchenko, Tatyana; Walley, Justin W; Chehab, E Wassim; Xiao, Yanmei; Kaspi, Roy; Pye, Matthew F; Mohamed, Maged E; Lazarus, Colin M; Bostock, Richard M; Dehesh, Katayoon

    2010-10-01

    Fatty acid structure affects cellular activities through changes in membrane lipid composition and the generation of a diversity of bioactive derivatives. Eicosapolyenoic acids are released into plants upon infection by oomycete pathogens, suggesting they may elicit plant defenses. We exploited transgenic Arabidopsis thaliana plants (designated EP) producing eicosadienoic, eicosatrienoic, and arachidonic acid (AA), aimed at mimicking pathogen release of these compounds. We also examined their effect on biotic stress resistance by challenging EP plants with fungal, oomycete, and bacterial pathogens and an insect pest. EP plants exhibited enhanced resistance to all biotic challenges, except they were more susceptible to bacteria than the wild type. Levels of jasmonic acid (JA) were elevated and levels of salicylic acid (SA) were reduced in EP plants. Altered expression of JA and SA pathway genes in EP plants shows that eicosapolyenoic acids effectively modulate stress-responsive transcriptional networks. Exogenous application of various fatty acids to wild-type and JA-deficient mutants confirmed AA as the signaling molecule. Moreover, AA treatment elicited heightened expression of general stress-responsive genes. Importantly, tomato (Solanum lycopersicum) leaves treated with AA exhibited reduced susceptibility to Botrytis cinerea infection, confirming AA signaling in other plants. These studies support the role of AA, an ancient metazoan signaling molecule, in eliciting plant stress and defense signaling networks.

  13. Small cell networks deployment, management, and optimization

    CERN Document Server

    Claussen, Holger; Ho, Lester; Razavi, Rouzbeh; Kucera, Stepan

    2018-01-01

    Small Cell Networks: Deployment, Management, and Optimization addresses key problems of the cellular network evolution towards HetNets. It focuses on the latest developments in heterogeneous and small cell networks, as well as their deployment, operation, and maintenance. It also covers the full spectrum of the topic, from academic, research, and business to the practice of HetNets in a coherent manner. Additionally, it provides complete and practical guidelines to vendors and operators interested in deploying small cells. The first comprehensive book written by well-known researchers and engineers from Nokia Bell Labs, Small Cell Networks begins with an introduction to the subject--offering chapters on capacity scaling and key requirements of future networks. It then moves on to sections on coverage and capacity optimization, and interference management. From there, the book covers mobility management, energy efficiency, and small cell deployment, ending with a section devoted to future trends and applicat...

  14. Pathogenesis of RON receptor tyrosine kinase in cancer cells: activation mechanism, functional crosstalk, and signaling addiction.

    Science.gov (United States)

    Wang, Ming-Hai; Zhang, Ruiwen; Zhou, Yong-Qing; Yao, Hang-Ping

    2013-09-01

    The RON receptor tyrosine kinase, a member of the MET proto-oncogene family, is a pathogenic factor implicated in tumor malignancy. Specifically, aberrations in RON signaling result in increased cancer cell growth, survival, invasion, angiogenesis, and drug resistance. Biochemical events such as ligand binding, receptor overexpression, generation of structure-defected variants, and point mutations in the kinase domain contribute to RON signaling activation. Recently, functional crosstalk between RON and signaling proteins such as MET and EFGR has emerged as an additional mechanism for RON activation, which is critical for tumorigenic development. The RON signaling crosstalk acts either as a regulatory feedback loop that strengthens or enhances tumorigenic phenotype of cancer cells or serves as a signaling compensatory pathway providing a growth/survival advantage for cancer cells to escape targeted therapy. Moreover, viral oncoproteins derived from Friend leukemia or Epstein-Barr viruses interact with RON to drive viral oncogenesis. In cancer cells, RON signaling is integrated into cellular signaling network essential for cancer cell growth and survival. These activities provide the molecular basis of targeting RON for cancer treatment. In this review, we will discuss recent data that uncover the mechanisms of RON activation in cancer cells, review evidence of RON signaling crosstalk relevant to cancer malignancy, and emphasize the significance of the RON signaling addiction by cancer cells for tumor therapy. Understanding aberrant RON signaling will not only provide insight into the mechanisms of tumor pathogenesis, but also lead to the development of novel strategies for molecularly targeted cancer treatment.

  15. Fault Tolerant Neural Network for ECG Signal Classification Systems

    Directory of Open Access Journals (Sweden)

    MERAH, M.

    2011-08-01

    Full Text Available The aim of this paper is to apply a new robust hardware Artificial Neural Network (ANN for ECG classification systems. This ANN includes a penalization criterion which makes the performances in terms of robustness. Specifically, in this method, the ANN weights are normalized using the auto-prune method. Simulations performed on the MIT ? BIH ECG signals, have shown that significant robustness improvements are obtained regarding potential hardware artificial neuron failures. Moreover, we show that the proposed design achieves better generalization performances, compared to the standard back-propagation algorithm.

  16. Reverse engineering a signaling network using alternative inputs.

    Science.gov (United States)

    Tanaka, Hiromasa; Yi, Tau-Mu

    2009-10-29

    One of the goals of systems biology is to reverse engineer in a comprehensive fashion the arrow diagrams of signal transduction systems. An important tool for ordering pathway components is genetic epistasis analysis, and here we present a strategy termed Alternative Inputs (AIs) to perform systematic epistasis analysis. An alternative input is defined as any genetic manipulation that can activate the signaling pathway instead of the natural input. We introduced the concept of an "AIs-Deletions matrix" that summarizes the outputs of all combinations of alternative inputs and deletions. We developed the theory and algorithms to construct a pairwise relationship graph from the AIs-Deletions matrix capturing both functional ordering (upstream, downstream) and logical relationships (AND, OR), and then interpreting these relationships into a standard arrow diagram. As a proof-of-principle, we applied this methodology to a subset of genes involved in yeast mating signaling. This experimental pilot study highlights the robustness of the approach and important technical challenges. In summary, this research formalizes and extends classical epistasis analysis from linear pathways to more complex networks, facilitating computational analysis and reconstruction of signaling arrow diagrams.

  17. Security Enhancement of Wireless Sensor Networks Using Signal Intervals.

    Science.gov (United States)

    Moon, Jaegeun; Jung, Im Y; Yoo, Jaesoo

    2017-04-02

    Various wireless technologies, such as RF, Bluetooth, and Zigbee, have been applied to sensor communications. However, the applications of Bluetooth-based wireless sensor networks (WSN) have a security issue. In one pairing process during Bluetooth communication, which is known as simple secure pairing (SSP), the devices are required to specify I/O capability or user interference to prevent man-in-the-middle (MITM) attacks. This study proposes an enhanced SSP in which a nonce to be transferred is converted to a corresponding signal interval. The quantization level, which is used to interpret physical signal intervals, is renewed at every connection by the transferred nonce and applied to the next nonce exchange so that the same signal intervals can represent different numbers. Even if attackers eavesdrop on the signals, they cannot understand what is being transferred because they cannot determine the quantization level. Furthermore, the proposed model does not require exchanging passkeys as data, and the devices are secure in the case of using a fixed PIN. Subsequently, the new quantization level is calculated automatically whenever the same devices attempt to connect with each other. Therefore, the pairing process can be protected from MITM attacks and be convenient for users.

  18. Security Enhancement of Wireless Sensor Networks Using Signal Intervals

    Directory of Open Access Journals (Sweden)

    Jaegeun Moon

    2017-04-01

    Full Text Available Various wireless technologies, such as RF, Bluetooth, and Zigbee, have been applied to sensor communications. However, the applications of Bluetooth-based wireless sensor networks (WSN have a security issue. In one pairing process during Bluetooth communication, which is known as simple secure pairing (SSP, the devices are required to specify I/O capability or user interference to prevent man-in-the-middle (MITM attacks. This study proposes an enhanced SSP in which a nonce to be transferred is converted to a corresponding signal interval. The quantization level, which is used to interpret physical signal intervals, is renewed at every connection by the transferred nonce and applied to the next nonce exchange so that the same signal intervals can represent different numbers. Even if attackers eavesdrop on the signals, they cannot understand what is being transferred because they cannot determine the quantization level. Furthermore, the proposed model does not require exchanging passkeys as data, and the devices are secure in the case of using a fixed PIN. Subsequently, the new quantization level is calculated automatically whenever the same devices attempt to connect with each other. Therefore, the pairing process can be protected from MITM attacks and be convenient for users.

  19. Chemokines: a new dendritic cell signal for T cell activation

    Directory of Open Access Journals (Sweden)

    Christoph A Thaiss

    2011-08-01

    Full Text Available Dendritic cells (DCs are the main inducers and regulators of cytotoxic T lymphocyte (CTL responses against viruses and tumors. One checkpoint to avoid misguided CTL activation, which might damage healthy cells of the body, is the necessity for multiple activation signals, involving both antigenic as well as additional signals that reflect the presence of pathogens. DCs provide both signals when activated by ligands of pattern recognition receptors and licensed by helper lymphocytes. Recently, it has been established that such T cell licensing can be facilitated by CD4+ T helper cells (classical licensing or by NKT cells (alternative licensing. Licensing regulates the DC/CTL cross-talk at multiple layers. Direct recruitment of CTLs through chemokines released by licensed DCs has recently emerged as a common theme and has a crucial impact on the efficiency of CTL responses. Here, we discuss recent advances in our understanding of DC licensing for cross-priming and implications for the temporal and spatial regulation underlying this process. Future vaccination strategies will benefit from a deeper insight into the mechanisms that govern CTL activation.

  20. Inter-donor variation in cell subset specific immune signaling responses in healthy individuals.

    Science.gov (United States)

    Longo, Diane M; Louie, Brent; Wang, Ena; Pos, Zoltan; Marincola, Francesco M; Hawtin, Rachael E; Cesano, Alessandra

    2012-01-01

    Single cell network profiling (SCNP) is a multi-parameter flow cytometry based approach that allows for the simultaneous interrogation of intracellular signaling pathways in multiple cell subpopulations within heterogeneous tissues, without the need for individual cell subset isolation. Thus, the technology is extremely well-suited for characterizing the multitude of interconnected signaling pathways and immune cell subpopulations that regulate the function of the immune system. Recently, SCNP was applied to generate a functional map of the healthy human immune cell signaling network by profiling immune signaling pathways downstream of 12 immunomodulators in 7 distinct immune cell subsets within peripheral blood mononuclear cells (PBMCs) from 60 healthy donors. In the study reported here, the degree of inter-donor variation in the magnitude of the immune signaling responses was analyzed. The highest inter-donor differences in immune signaling pathway activity occurred following perturbation of the immune signaling network, rather than in basal signaling. When examining the full panel of immune signaling responses, as one may expect, the overall degree of inter-donor variation was positively correlated (r = 0.727) with the magnitude of node response (i.e. a larger median signaling response was associated with greater inter-donor variation). However, when examining the degree of heterogeneity across cell subpopulations for individual signaling nodes, cell subset specificity in the degree of inter-donor variation was observed for several nodes. For such nodes, relatively weak correlations between inter-donor variation and the magnitude of the response were observed. Further, within the phenotypically distinct subpopulations, a fraction of the immune signaling responses had bimodal response profiles in which (a) only a portion of the cells had elevated phospho-protein levels following modulation and (b) the proportion of responsive cells varied by donor. These data

  1. Plant morphogenesis, auxin, and the signal-trafficking network incompleteness theorem

    Directory of Open Access Journals (Sweden)

    Karl J. Niklas

    2012-03-01

    Full Text Available Plant morphogenesis (the development of form and function requires signal-trafficking and cross-talking among all levels of organization to coordinate the operation of metabolic and genomic networked systems. Many if not all of these biological features can be rendered as logic circuits supervising the operation of one or more signal-activated metabolic or genome networks. This approach simplifies complex morphogenetic phenomena and allows for their aggregation into diagrams of larger, more "global" networked systems. This conceptualization is illustrated for morphogenesis in model plants such as maize (Zea mays and Thale cress (Arabidopsis thaliana from an evolutionary perspective. The phytohormone indole-acetic acid (IAA is used as an example for a well-known signaling chemical and discussed in terms of the logic circuits and signal-activated sub-systems for hormone-mediated wall loosening and cell expansion as well as polar/lateral intercellular IAA transport. For each of these phenomena, a circuit/sub-system diagram highlights missing components, either in the logic circuit or in the sub-system it supervises, that must be identified experimentally if each of these basic phenomena is to be fully understood within a phylogen

  2. Global effects of kinase inhibitors on signaling networks revealed by quantitative phosphoproteomics

    DEFF Research Database (Denmark)

    Pan, Cuiping; Olsen, Jesper V; Daub, Henrik

    2009-01-01

    to identify the direct targets of kinase inhibitors upon affinity purification from cellular extracts. Here we introduce a complementary approach to evaluate the effects of kinase inhibitors on the entire cell signaling network. We used triple labeling SILAC (stable isotope labeling by amino acids in cell......-ABL, which is the cause of chronic myelogenous leukemia, affected nearly 1,000 phosphopeptides. In addition to the proximal effects on ABL and its immediate targets, dasatinib broadly affected the downstream MAPK pathways. Pathway mapping of regulated sites implicated a variety of cellular functions...

  3. An approach for optimally extending mathematical models of signaling networks using omics data.

    Science.gov (United States)

    Bianconi, Fortunato; Patiti, Federico; Baldelli, Elisa; Crino, Lucio; Valigi, Paolo

    2015-01-01

    Mathematical modeling is a key process in Systems Biology and the use of computational tools such as Cytoscape for omics data processing, need to be integrated in the modeling activity. In this paper we propose a new methodology for modeling signaling networks by combining ordinary differential equation models and a gene recommender system, GeneMANIA. We started from existing models, that are stored in the BioModels database, and we generated a query to use as input for the GeneMANIA algorithm. The output of the recommender system was then led back to the kinetic reactions that were finally added to the starting model. We applied the proposed methodology to EGFR-IGF1R signal transduction network, which plays an important role in translational oncology and cancer therapy of non small cell lung cancer.

  4. Dynamical Adaptation in Terrorist Cells/Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Ahmed, Zaki

    2010-01-01

    Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long...... and followers etc. In this research we analyze and predict the most likely role a particular node can adapt once a member of the network is either killed or caught. The adaptation is based on computing Bayes posteriori probability of each node and the level of the said node in the network structure....

  5. Barcoding of GPCR trafficking and signaling through the various trafficking roadmaps by compartmentalized signaling networks.

    Science.gov (United States)

    Bahouth, Suleiman W; Nooh, Mohammed M

    2017-08-01

    Proper signaling by G protein coupled receptors (GPCR) is dependent on the specific repertoire of transducing, enzymatic and regulatory kinases and phosphatases that shape its signaling output. Activation and signaling of the GPCR through its cognate G protein is impacted by G protein-coupled receptor kinase (GRK)-imprinted "barcodes" that recruit β-arrestins to regulate subsequent desensitization, biased signaling and endocytosis of the GPCR. The outcome of agonist-internalized GPCR in endosomes is also regulated by sequence motifs or "barcodes" within the GPCR that mediate its recycling to the plasma membrane or retention and eventual degradation as well as its subsequent signaling in endosomes. Given the vast number of diverse sequences in GPCR, several trafficking mechanisms for endosomal GPCR have been described. The majority of recycling GPCR, are sorted out of endosomes in a "sequence-dependent pathway" anchored around a type-1 PDZ-binding module found in their C-tails. For a subset of these GPCR, a second "barcode" imprinted onto specific GPCR serine/threonine residues by compartmentalized kinase networks was required for their efficient recycling through the "sequence-dependent pathway". Mutating the serine/threonine residues involved, produced dramatic effects on GPCR trafficking, indicating that they played a major role in setting the trafficking itinerary of these GPCR. While endosomal SNX27, retromer/WASH complexes and actin were required for efficient sorting and budding of all these GPCR, additional proteins were required for GPCR sorting via the second "barcode". Here we will review recent developments in GPCR trafficking in general and the human β 1 -adrenergic receptor in particular across the various trafficking roadmaps. In addition, we will discuss the role of GPCR trafficking in regulating endosomal GPCR signaling, which promote biochemical and physiological effects that are distinct from those generated by the GPCR signal transduction

  6. Phantom phone signals: An investigation into the prevalence and predictors of imagined cell phone signals

    NARCIS (Netherlands)

    Tanis, M.A.; Beukeboom, C.J.; Hartmann, T.; Vermeulen, I.E.

    2015-01-01

    This paper aims to elucidate the peculiar phenomenon of imagined cell phone signals, or Phantom Phone Signals (PPS), which is defined as an individual's perception of a phone signal, indicating an incoming call, message, or social media notification, when in fact no such signal was transmitted. A

  7. Uncovering signal transduction networks from high-throughput data by integer linear programming.

    Science.gov (United States)

    Zhao, Xing-Ming; Wang, Rui-Sheng; Chen, Luonan; Aihara, Kazuyuki

    2008-05-01

    Signal transduction is an important process that transmits signals from the outside of a cell to the inside to mediate sophisticated biological responses. Effective computational models to unravel such a process by taking advantage of high-throughput genomic and proteomic data are needed to understand the essential mechanisms underlying the signaling pathways. In this article, we propose a novel method for uncovering signal transduction networks (STNs) by integrating protein interaction with gene expression data. Specifically, we formulate STN identification problem as an integer linear programming (ILP) model, which can be actually solved by a relaxed linear programming algorithm and is flexible for handling various prior information without any restriction on the network structures. The numerical results on yeast MAPK signaling pathways demonstrate that the proposed ILP model is able to uncover STNs or pathways in an efficient and accurate manner. In particular, the prediction results are found to be in high agreement with current biological knowledge and available information in literature. In addition, the proposed model is simple to be interpreted and easy to be implemented even for a large-scale system.

  8. Automated Measurement and Signaling Systems for the Transactional Network

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-12-31

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

  9. Contractile network models for adherent cells.

    Science.gov (United States)

    Guthardt Torres, P; Bischofs, I B; Schwarz, U S

    2012-01-01

    Cells sense the geometry and stiffness of their adhesive environment by active contractility. For strong adhesion to flat substrates, two-dimensional contractile network models can be used to understand how force is distributed throughout the cell. Here we compare the shape and force distribution for different variants of such network models. In contrast to Hookean networks, cable networks reflect the asymmetric response of biopolymers to tension versus compression. For passive networks, contractility is modeled by a reduced resting length of the mechanical links. In actively contracting networks, a constant force couple is introduced into each link in order to model contraction by molecular motors. If combined with fixed adhesion sites, all network models lead to invaginated cell shapes, but only actively contracting cable networks lead to the circular arc morphology typical for strongly adhering cells. In this case, shape and force distribution are determined by local rather than global determinants and thus are suited to endow the cell with a robust sense of its environment. We also discuss nonlinear and adaptive linker mechanics as well as the relation to tissue shape. © 2012 American Physical Society

  10. An electrically resistive sheet of glial cells for amplifying signals of neuronal extracellular recordings

    Science.gov (United States)

    Matsumura, R.; Yamamoto, H.; Niwano, M.; Hirano-Iwata, A.

    2016-01-01

    Electrical signals of neuronal cells can be recorded non-invasively and with a high degree of temporal resolution using multielectrode arrays (MEAs). However, signals that are recorded with these devices are small, usually 0.01%-0.1% of intracellular recordings. Here, we show that the amplitude of neuronal signals recorded with MEA devices can be amplified by covering neuronal networks with an electrically resistive sheet. The resistive sheet used in this study is a monolayer of glial cells, supportive cells in the brain. The glial cells were grown on a collagen-gel film that is permeable to oxygen and other nutrients. The impedance of the glial sheet was measured by electrochemical impedance spectroscopy, and equivalent circuit simulations were performed to theoretically investigate the effect of covering the neurons with such a resistive sheet. Finally, the effect of the resistive glial sheet was confirmed experimentally, showing a 6-fold increase in neuronal signals. This technique feasibly amplifies signals of MEA recordings.

  11. Apical trafficking in epithelial cells: signals, clusters and motors.

    Science.gov (United States)

    Weisz, Ora A; Rodriguez-Boulan, Enrique

    2009-12-01

    In the early days of epithelial cell biology, researchers working with kidney and/or intestinal epithelial cell lines and with hepatocytes described the biosynthetic and recycling routes followed by apical and basolateral plasma membrane (PM) proteins. They identified the trans-Golgi network and recycling endosomes as the compartments that carried out apical-basolateral sorting. They described complex apical sorting signals that promoted association with lipid rafts, and simpler basolateral sorting signals resembling clathrin-coated-pit endocytic motifs. They also noticed that different epithelial cell types routed their apical PM proteins very differently, using either a vectorial (direct) route or a transcytotic (indirect) route. Although these original observations have generally held up, recent studies have revealed interesting complexities in the routes taken by apically destined proteins and have extended our understanding of the machinery required to sustain these elaborate sorting pathways. Here, we critically review the current status of apical trafficking mechanisms and discuss a model in which clustering is required to recruit apical trafficking machineries. Uncovering the mechanisms responsible for polarized trafficking and their epithelial-specific variations will help understand how epithelial functional diversity is generated and the pathogenesis of many human diseases.

  12. Cell fate decisions: emerging roles for metabolic signals and cell morphology.

    Science.gov (United States)

    Tatapudy, Sumitra; Aloisio, Francesca; Barber, Diane; Nystul, Todd

    2017-12-01

    Understanding how cell fate decisions are regulated is a fundamental goal of developmental and stem cell biology. Most studies on the control of cell fate decisions address the contributions of changes in transcriptional programming, epigenetic modifications, and biochemical differentiation cues. However, recent studies have found that other aspects of cell biology also make important contributions to regulating cell fate decisions. These cues can have a permissive or instructive role and are integrated into the larger network of signaling, functioning both upstream and downstream of developmental signaling pathways. Here, we summarize recent insights into how cell fate decisions are influenced by four aspects of cell biology: metabolism, reactive oxygen species (ROS), intracellular pH (pHi), and cell morphology. For each topic, we discuss how these cell biological cues interact with each other and with protein-based mechanisms for changing gene transcription. In addition, we highlight several questions that remain unanswered in these exciting and relatively new areas of the field. © 2017 The Authors.

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

    Directory of Open Access Journals (Sweden)

    Carlos R. Rangel

    2016-08-01

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

  14. Molecular signaling networks in regulation of immunity and disease

    DEFF Research Database (Denmark)

    Laursen, Janne Marie; Jensen, Stina Rikke; Sørensen, Morten

    The gut microbiota, host tissues, and the immune system form a complex network where extensive crosstalk and molecular interactions substantially impact the overall state of the system. Concomitantly, modulation of host immune function is recurrently a result of the interaction of complex......), plays a crucial role in shaping the nature of the adaptive/memorybased immune response after encountering inflammatory compounds. In the gut, the DC is continuously exposed to microbial and dietary components that are recognized by its innate pattern recognition receptors, and the phenotype developed...... and dynamic microbial communities with the immune cell compartment in the gut, and therefore the interaction between components from different gut bacteria can efficiently shape the phenotype of the immune response. A specialized antigenpresenting cell present at mucosal surfaces, the dendritic cell (DC...

  15. Simulation study on effects of signaling network structure on the developmental increase in complexity

    Energy Technology Data Exchange (ETDEWEB)

    Keranen, Soile V.E.

    2003-04-02

    The developmental increase in structural complexity in multicellular life forms depends on local, often non-periodic differences in gene expression. These depend on a network of gene-gene interactions coded within the organismal genome. To better understand how genomic information generates complex expression patterns, I have modeled the pattern forming behavior of small artificial genomes in virtual blastoderm embryos. I varied several basic properties of these genomic signaling networks, such as the number of genes, the distributions of positive (inductive) and negative (repressive) interactions, and the strengths of gene-gene interactions, and analyzed their effects on developmental pattern formation. The results show how even simple genomes can generate complex non-periodic patterns under suitable conditions. They also show how the frequency of complex patterns depended on the numbers and relative arrangements of positive and negative interactions. For example, negative co-regulation of signaling pathway components increased the likelihood of (complex) patterns relative to differential negative regulation of the pathway components. Interestingly, neither quantitative differences either in strengths of signaling interactions nor multiple response thresholds to signal concentration (as in morphogen gradients) were essential for formation of multiple, spatially unique cell types. Thus, with combinatorial code of gene regulation and hierarchical signaling interactions, it is theoretically possible to organize metazoan embryogenesis with just a small fraction of the metazoan genome. Because even small networks can generate complex patterns when they contain a suitable set of connections, evolution of metazoan complexity may have depended more on selection for favourable configurations of signaling interactions than on the increase in numbers of regulatory genes.

  16. Computational study of noise in a large signal transduction network

    Directory of Open Access Journals (Sweden)

    Ruohonen Keijo

    2011-06-01

    Full Text Available Abstract Background Biochemical systems are inherently noisy due to the discrete reaction events that occur in a random manner. Although noise is often perceived as a disturbing factor, the system might actually benefit from it. In order to understand the role of noise better, its quality must be studied in a quantitative manner. Computational analysis and modeling play an essential role in this demanding endeavor. Results We implemented a large nonlinear signal transduction network combining protein kinase C, mitogen-activated protein kinase, phospholipase A2, and β isoform of phospholipase C networks. We simulated the network in 300 different cellular volumes using the exact Gillespie stochastic simulation algorithm and analyzed the results in both the time and frequency domain. In order to perform simulations in a reasonable time, we used modern parallel computing techniques. The analysis revealed that time and frequency domain characteristics depend on the system volume. The simulation results also indicated that there are several kinds of noise processes in the network, all of them representing different kinds of low-frequency fluctuations. In the simulations, the power of noise decreased on all frequencies when the system volume was increased. Conclusions We concluded that basic frequency domain techniques can be applied to the analysis of simulation results produced by the Gillespie stochastic simulation algorithm. This approach is suited not only to the study of fluctuations but also to the study of pure noise processes. Noise seems to have an important role in biochemical systems and its properties can be numerically studied by simulating the reacting system in different cellular volumes. Parallel computing techniques make it possible to run massive simulations in hundreds of volumes and, as a result, accurate statistics can be obtained from computational studies.

  17. VLSI Cells Placement Using the Neural Networks

    International Nuclear Information System (INIS)

    Azizi, Hacene; Zouaoui, Lamri; Mokhnache, Salah

    2008-01-01

    The artificial neural networks have been studied for several years. Their effectiveness makes it possible to expect high performances. The privileged fields of these techniques remain the recognition and classification. Various applications of optimization are also studied under the angle of the artificial neural networks. They make it possible to apply distributed heuristic algorithms. In this article, a solution to placement problem of the various cells at the time of the realization of an integrated circuit is proposed by using the KOHONEN network

  18. Identification of Major Signaling Pathways in Prion Disease Progression Using Network Analysis.

    Directory of Open Access Journals (Sweden)

    Khalique Newaz

    Full Text Available Prion diseases are transmissible neurodegenerative diseases that arise due to conformational change of normal, cellular prion protein (PrPC to protease-resistant isofrom (rPrPSc. Deposition of misfolded PrpSc proteins leads to an alteration of many signaling pathways that includes immunological and apoptotic pathways. As a result, this culminates in the dysfunction and death of neuronal cells. Earlier works on transcriptomic studies have revealed some affected pathways, but it is not clear which is (are the prime network pathway(s that change during the disease progression and how these pathways are involved in crosstalks with each other from the time of incubation to clinical death. We perform network analysis on large-scale transcriptomic data of differentially expressed genes obtained from whole brain in six different mouse strain-prion strain combination models to determine the pathways involved in prion diseases, and to understand the role of crosstalks in disease propagation. We employ a notion of differential network centrality measures on protein interaction networks to identify the potential biological pathways involved. We also propose a crosstalk ranking method based on dynamic protein interaction networks to identify the core network elements involved in crosstalk with different pathways. We identify 148 DEGs (differentially expressed genes potentially related to the prion disease progression. Functional association of the identified genes implicates a strong involvement of immunological pathways. We extract a bow-tie structure that is potentially dysregulated in prion disease. We also propose an ODE model for the bow-tie network. Predictions related to diseased condition suggests the downregulation of the core signaling elements (PI3Ks and AKTs of the bow-tie network. In this work, we show using transcriptomic data that the neuronal dysfunction in prion disease is strongly related to the immunological pathways. We conclude that

  19. Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling.

    Directory of Open Access Journals (Sweden)

    Holger Fröhlich

    Full Text Available Aberrant activation of sonic Hegdehog (SHH signaling has been found to disrupt cellular differentiation in many human cancers and to increase proliferation. The SHH pathway is known to cross-talk with EGFR dependent signaling. Recent studies experimentally addressed this interplay in Daoy cells, which are presumable a model system for medulloblastoma, a highly malignant brain tumor that predominately occurs in children. Currently ongoing are several clinical trials for different solid cancers, which are designed to validate the clinical benefits of targeting the SHH in combination with other pathways. This has motivated us to investigate interactions between EGFR and SHH dependent signaling in greater depth. To our knowledge, there is no mathematical model describing the interplay between EGFR and SHH dependent signaling in medulloblastoma so far. Here we come up with a fully probabilistic approach using Dynamic Bayesian Networks (DBNs. To build our model, we made use of literature based knowledge describing SHH and EGFR signaling and integrated gene expression (Illumina and cellular location dependent time series protein expression data (Reverse Phase Protein Arrays. We validated our model by sub-sampling training data and making Bayesian predictions on the left out test data. Our predictions focusing on key transcription factors and p70S6K, showed a high level of concordance with experimental data. Furthermore, the stability of our model was tested by a parametric bootstrap approach. Stable network features were in agreement with published data. Altogether we believe that our model improved our understanding of the interplay between two highly oncogenic signaling pathways in Daoy cells. This may open new perspectives for the future therapy of Hedghog/EGF-dependent solid tumors.

  20. Combining in silico evolution and nonlinear dimensionality reduction to redesign responses of signaling networks.

    Science.gov (United States)

    Prescott, Aaron M; Abel, Steven M

    2017-01-13

    The rational design of network behavior is a central goal of synthetic biology. Here, we combine in silico evolution with nonlinear dimensionality reduction to redesign the responses of fixed-topology signaling networks and to characterize sets of kinetic parameters that underlie various input-output relations. We first consider the earliest part of the T cell receptor (TCR) signaling network and demonstrate that it can produce a variety of input-output relations (quantified as the level of TCR phosphorylation as a function of the characteristic TCR binding time). We utilize an evolutionary algorithm (EA) to identify sets of kinetic parameters that give rise to: (i) sigmoidal responses with the activation threshold varied over 6 orders of magnitude, (ii) a graded response, and (iii) an inverted response in which short TCR binding times lead to activation. We also consider a network with both positive and negative feedback and use the EA to evolve oscillatory responses with different periods in response to a change in input. For each targeted input-output relation, we conduct many independent runs of the EA and use nonlinear dimensionality reduction to embed the resulting data for each network in two dimensions. We then partition the results into groups and characterize constraints placed on the parameters by the different targeted response curves. Our approach provides a way (i) to guide the design of kinetic parameters of fixed-topology networks to generate novel input-output relations and (ii) to constrain ranges of biological parameters using experimental data. In the cases considered, the network topologies exhibit significant flexibility in generating alternative responses, with distinct patterns of kinetic rates emerging for different targeted responses.

  1. Combining in silico evolution and nonlinear dimensionality reduction to redesign responses of signaling networks

    Science.gov (United States)

    Prescott, Aaron M.; Abel, Steven M.

    2016-12-01

    The rational design of network behavior is a central goal of synthetic biology. Here, we combine in silico evolution with nonlinear dimensionality reduction to redesign the responses of fixed-topology signaling networks and to characterize sets of kinetic parameters that underlie various input-output relations. We first consider the earliest part of the T cell receptor (TCR) signaling network and demonstrate that it can produce a variety of input-output relations (quantified as the level of TCR phosphorylation as a function of the characteristic TCR binding time). We utilize an evolutionary algorithm (EA) to identify sets of kinetic parameters that give rise to: (i) sigmoidal responses with the activation threshold varied over 6 orders of magnitude, (ii) a graded response, and (iii) an inverted response in which short TCR binding times lead to activation. We also consider a network with both positive and negative feedback and use the EA to evolve oscillatory responses with different periods in response to a change in input. For each targeted input-output relation, we conduct many independent runs of the EA and use nonlinear dimensionality reduction to embed the resulting data for each network in two dimensions. We then partition the results into groups and characterize constraints placed on the parameters by the different targeted response curves. Our approach provides a way (i) to guide the design of kinetic parameters of fixed-topology networks to generate novel input-output relations and (ii) to constrain ranges of biological parameters using experimental data. In the cases considered, the network topologies exhibit significant flexibility in generating alternative responses, with distinct patterns of kinetic rates emerging for different targeted responses.

  2. BMP signaling regulates satellite cell-dependent postnatal muscle growth.

    Science.gov (United States)

    Stantzou, Amalia; Schirwis, Elija; Swist, Sandra; Alonso-Martin, Sonia; Polydorou, Ioanna; Zarrouki, Faouzi; Mouisel, Etienne; Beley, Cyriaque; Julien, Anaïs; Le Grand, Fabien; Garcia, Luis; Colnot, Céline; Birchmeier, Carmen; Braun, Thomas; Schuelke, Markus; Relaix, Frédéric; Amthor, Helge

    2017-08-01

    Postnatal growth of skeletal muscle largely depends on the expansion and differentiation of resident stem cells, the so-called satellite cells. Here, we demonstrate that postnatal satellite cells express components of the bone morphogenetic protein (BMP) signaling machinery. Overexpression of noggin in postnatal mice (to antagonize BMP ligands), satellite cell-specific knockout of Alk3 (the gene encoding the BMP transmembrane receptor) or overexpression of inhibitory SMAD6 decreased satellite cell proliferation and accretion during myofiber growth, and ultimately retarded muscle growth. Moreover, reduced BMP signaling diminished the adult satellite cell pool. Abrogation of BMP signaling in satellite cell-derived primary myoblasts strongly diminished cell proliferation and upregulated the expression of cell cycle inhibitors p21 and p57 In conclusion, these results show that BMP signaling defines postnatal muscle development by regulating satellite cell-dependent myofiber growth and the generation of the adult muscle stem cell pool. © 2017. Published by The Company of Biologists Ltd.

  3. Detecting malicious chaotic signals in wireless sensor network

    Science.gov (United States)

    Upadhyay, Ranjit Kumar; Kumari, Sangeeta

    2018-02-01

    In this paper, an e-epidemic Susceptible-Infected-Vaccinated (SIV) model has been proposed to analyze the effect of node immunization and worms attacking dynamics in wireless sensor network. A modified nonlinear incidence rate with cyrtoid type functional response has been considered using sleep and active mode approach. Detailed stability analysis and the sufficient criteria for the persistence of the model system have been established. We also established different types of bifurcation analysis for different equilibria at different critical points of the control parameters. We performed a detailed Hopf bifurcation analysis and determine the direction and stability of the bifurcating periodic solutions using center manifold theorem. Numerical simulations are carried out to confirm the theoretical results. The impact of the control parameters on the dynamics of the model system has been investigated and malicious chaotic signals are detected. Finally, we have analyzed the effect of time delay on the dynamics of the model system.

  4. In-vitro exposure of neuronal networks to the GSM-1800 signal.

    Science.gov (United States)

    Moretti, Daniela; Garenne, André; Haro, Emmanuelle; Poulletier de Gannes, Florence; Lagroye, Isabelle; Lévêque, Philippe; Veyret, Bernard; Lewis, Noëlle

    2013-12-01

    The central nervous system is the most likely target of mobile telephony radiofrequency (RF) field exposure in terms of biological effects. Several electroencephalography (EEG) studies have reported variations in the alpha-band power spectrum during and/or after RF exposure, in resting EEG and during sleep. In this context, the observation of the spontaneous electrical activity of neuronal networks under RF exposure can be an efficient tool to detect the occurrence of low-level RF effects on the nervous system. Our research group has developed a dedicated experimental setup in the GHz range for the simultaneous exposure of neuronal networks and monitoring of electrical activity. A transverse electromagnetic (TEM) cell was used to expose the neuronal networks to GSM-1800 signals at a SAR level of 3.2 W/kg. Recording of the neuronal electrical activity and detection of the extracellular spikes and bursts under exposure were performed using microelectrode arrays (MEAs). This work provides the proof of feasibility and preliminary results of the integrated investigation regarding exposure setup, culture of the neuronal network, recording of the electrical activity, and analysis of the signals obtained under RF exposure. In this pilot study on 16 cultures, there was a 30% reversible decrease in firing rate (FR) and bursting rate (BR) during a 3 min exposure to RF. Additional experiments are needed to further characterize this effect. © 2013 Wiley Periodicals, Inc.

  5. Probing Embryonic Stem Cell Autocrine and Paracrine Signaling Using Microfluidics

    Science.gov (United States)

    Przybyla, Laralynne; Voldman, Joel

    2012-07-01

    Although stem cell fate is traditionally manipulated by exogenously altering the cells' extracellular signaling environment, the endogenous autocrine and paracrine signals produced by the cells also contribute to their two essential processes: self-renewal and differentiation. Autocrine and/or paracrine signals are fundamental to both embryonic stem cell self-renewal and early embryonic development, but the nature and contributions of these signals are often difficult to fully define using conventional methods. Microfluidic techniques have been used to explore the effects of cell-secreted signals by controlling cell organization or by providing precise control over the spatial and temporal cellular microenvironment. Here we review how such techniques have begun to be adapted for use with embryonic stem cells, and we illustrate how many remaining questions in embryonic stem cell biology could be addressed using microfluidic technologies.

  6. Applying Statistical and Complex Network Methods to Explore the Key Signaling Molecules of Acupuncture Regulating Neuroendocrine-Immune Network

    OpenAIRE

    Zhang, Kuo; Guo, Xin-meng; Yan, Ya-wen; Liu, Yang-yang; Xu, Zhi-fang; Zhao, Xue; Wang, Jiang; Guo, Yi; Li, Kai; Ding, Sha-sha

    2018-01-01

    The mechanisms of acupuncture are still unclear. In order to reveal the regulatory effect of manual acupuncture (MA) on the neuroendocrine-immune (NEI) network and identify the key signaling molecules during MA modulating NEI network, we used a rat complete Freund’s adjuvant (CFA) model to observe the analgesic and anti-inflammatory effect of MA, and, what is more, we used statistical and complex network methods to analyze the data about the expression of 55 common signaling molecules of NEI ...

  7. Construction of a computable cell proliferation network focused on non-diseased lung cells

    Directory of Open Access Journals (Sweden)

    Veljkovic Emilija

    2011-07-01

    Full Text Available Abstract Background Critical to advancing the systems-level evaluation of complex biological processes is the development of comprehensive networks and computational methods to apply to the analysis of systems biology data (transcriptomics, proteomics/phosphoproteomics, metabolomics, etc.. Ideally, these networks will be specifically designed to capture the normal, non-diseased biology of the tissue or cell types under investigation, and can be used with experimentally generated systems biology data to assess the biological impact of perturbations like xenobiotics and other cellular stresses. Lung cell proliferation is a key biological process to capture in such a network model, given the pivotal role that proliferation plays in lung diseases including cancer, chronic obstructive pulmonary disease (COPD, and fibrosis. Unfortunately, no such network has been available prior to this work. Results To further a systems-level assessment of the biological impact of perturbations on non-diseased mammalian lung cells, we constructed a lung-focused network for cell proliferation. The network encompasses diverse biological areas that lead to the regulation of normal lung cell proliferation (Cell Cycle, Growth Factors, Cell Interaction, Intra- and Extracellular Signaling, and Epigenetics, and contains a total of 848 nodes (biological entities and 1597 edges (relationships between biological entities. The network was verified using four published gene expression profiling data sets associated with measured cell proliferation endpoints in lung and lung-related cell types. Predicted changes in the activity of core machinery involved in cell cycle regulation (RB1, CDKN1A, and MYC/MYCN are statistically supported across multiple data sets, underscoring the general applicability of this approach for a network-wide biological impact assessment using systems biology data. Conclusions To the best of our knowledge, this lung-focused Cell Proliferation Network

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

    Science.gov (United States)

    Wei, Pei; Gu, Rentao; Ji, Yuefeng

    2014-06-01

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

  9. Fabrication of microstamps and patterned cell network

    International Nuclear Information System (INIS)

    Seong, Nak Seon; Pak, James Jung Ho; Choi, Ju Hee; Ahn, Dong June; Hwang, Seong Min; Lee, Kyung J.

    2002-01-01

    Elastomeric stamps with micrometer-sized grids are fabricated for building biological cell networks by design. Polymerized polydimethyl-siloxane (PDMS) stamps are cast in a variety of different molds prepared by micro-electro mechanical systems (MEMS) technology. Micro square-grid patterns of 3-aminopropyl triethoxy silane (APS) are successfully imprinted on glass plates, and patterned networks of cardiac cells are obtained as designed. The resulting cellular networks clearly demonstrate that cell attachment and growth are greatly favored on APS-treated thin tracks. Here, we report the technical details related to the fabrication of microstamps, to the stamping procedure, and to the culture method. The potential applications of patterned cellular networks are also discussed

  10. Genome-Wide Analysis of the TORC1 and Osmotic Stress Signaling Network in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Jeremy Worley

    2016-02-01

    Full Text Available The Target of Rapamycin kinase Complex I (TORC1 is a master regulator of cell growth and metabolism in eukaryotes. Studies in yeast and human cells have shown that nitrogen/amino acid starvation signals act through Npr2/Npr3 and the small GTPases Gtr1/Gtr2 (Rags in humans to inhibit TORC1. However, it is unclear how other stress and starvation stimuli inhibit TORC1, and/or act in parallel with the TORC1 pathway, to control cell growth. To help answer these questions, we developed a novel automated pipeline and used it to measure the expression of a TORC1-dependent ribosome biogenesis gene (NSR1 during osmotic stress in 4700 Saccharomyces cerevisiae strains from the yeast knock-out collection. This led to the identification of 440 strains with significant and reproducible defects in NSR1 repression. The cell growth control and stress response proteins deleted in these strains form a highly connected network, including 56 proteins involved in vesicle trafficking and vacuolar function; 53 proteins that act downstream of TORC1 according to a rapamycin assay—including components of the HDAC Rpd3L, Elongator, and the INO80, CAF-1 and SWI/SNF chromatin remodeling complexes; over 100 proteins involved in signaling and metabolism; and 17 proteins that directly interact with TORC1. These data provide an important resource for labs studying cell growth control and stress signaling, and demonstrate the utility of our new, and easily adaptable, method for mapping gene regulatory networks.

  11. Atypical B cell receptor signaling: straddling immune diseases and cancer.

    Science.gov (United States)

    Faris, Mary

    2013-08-01

    The B-cell receptor (BCR) signaling pathway plays an essential role in the survival, proliferation, differentiation and trafficking of lymphocytic. Recent findings associate aberrant BCR signaling with specific disease pathologies, including B-cell malignancies and autoimmune disorders. Inhibition of the BCR signaling pathway may therefore provide promising new strategies for the treatment of B-cell diseases. This special issue of International Reviews of Immunology focuses on atypical B-cell receptor signaling, its role in immune diseases and cancer, and its implications for potential therapeutic intervention.

  12. An Effective Feedback Loop between Cell-Cell Contact Duration and Morphogen Signaling Determines Cell Fate.

    Science.gov (United States)

    Barone, Vanessa; Lang, Moritz; Krens, S F Gabriel; Pradhan, Saurabh J; Shamipour, Shayan; Sako, Keisuke; Sikora, Mateusz; Guet, Călin C; Heisenberg, Carl-Philipp

    2017-10-23

    Cell-cell contact formation constitutes an essential step in evolution, leading to the differentiation of specialized cell types. However, remarkably little is known about whether and how the interplay between contact formation and fate specification affects development. Here, we identify a positive feedback loop between cell-cell contact duration, morphogen signaling, and mesendoderm cell-fate specification during zebrafish gastrulation. We show that long-lasting cell-cell contacts enhance the competence of prechordal plate (ppl) progenitor cells to respond to Nodal signaling, required for ppl cell-fate specification. We further show that Nodal signaling promotes ppl cell-cell contact duration, generating a positive feedback loop between ppl cell-cell contact duration and cell-fate specification. Finally, by combining mathematical modeling and experimentation, we show that this feedback determines whether anterior axial mesendoderm cells become ppl or, instead, turn into endoderm. Thus, the interdependent activities of cell-cell signaling and contact formation control fate diversification within the developing embryo. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Signaling pathways regulating red blood cell aggregation.

    Science.gov (United States)

    Muravyov, Alexei; Tikhomirova, Irina

    2014-01-01

    The exposure of red blood cells (RBC) to some hormones (epinephrine, insulin and glucagon) and agonists of α- and β-adrenergic receptors (phenylephrine, clonidine and isoproterenol) may modify RBC aggregation (RBCA). Prostaglandin E1 (PGE1) significantly decreased RBCA, and PGE2 had a similar but lesser effect. Adenylyl cyclase (AC) stimulator forskolin added to RBC suspension, caused a decrease of RBCA. More marked lowering of RBCA occurred after RBC treatment by dB-cAMP. Phosphodiesterase (PDE) inhibitors markedly reduced RBCA. Ca2+ influx stimulated by A23187 was accompanied by an increase of RBCA. The blocking of Ca2+ entry into the RBC by verapamil or the chelation of Ca2+ by EGTA led to a significant RBCA decrease. Lesser changes of aggregation were found after RBC incubation with protein kinase C stimulator phorbol 12-myristate 13-acetate (PMA). A significant inhibitory effect of tyrosine protein kinase (TPK) activator cisplatin on RBCA was revealed, while selective TPK inhibitor, lavendustin, eliminated the above mentioned effect. Taken together, the data demonstrate that changes in RBCA are connected with activation of different intracellular signaling pathways. We suggest that alterations in RBCA are mainly associated with the crosstalk between the adenylyl cyclase-cAMP system and Ca2+ control mechanisms.

  14. Decoding Signal Processing at the Single-Cell Level

    Energy Technology Data Exchange (ETDEWEB)

    Wiley, H. Steven

    2017-12-01

    The ability of cells to detect and decode information about their extracellular environment is critical to generating an appropriate response. In multicellular organisms, cells must decode dozens of signals from their neighbors and extracellular matrix to maintain tissue homeostasis while still responding to environmental stressors. How cells detect and process information from their surroundings through a surprisingly limited number of signal transduction pathways is one of the most important question in biology. Despite many decades of research, many of the fundamental principles that underlie cell signal processing remain obscure. However, in this issue of Cell Systems, Gillies et al present compelling evidence that the early response gene circuit can act as a linear signal integrator, thus providing significant insight into how cells handle fluctuating signals and noise in their environment.

  15. Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications

    Directory of Open Access Journals (Sweden)

    Arjun Verma

    2016-07-01

    Full Text Available We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed.

  16. Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications.

    Science.gov (United States)

    Verma, Arjun; Fratto, Brian E; Privman, Vladimir; Katz, Evgeny

    2016-07-05

    We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed.

  17. Negative signaling in B cells: SHIP Grbs Shc.

    Science.gov (United States)

    Tridandapani, S; Kelley, T; Cooney, D; Pradhan, M; Coggeshall, K M

    1997-09-01

    Negative signaling in B cells is initiated by co-crosslinking of the antigen receptor and the Fcy receptor, resulting in cessation of B-cell signaling events and, in turn, inhibiting B-cell proliferation and antibody secretion. Here, a competitive role is proposed for SHIP in blocking the interaction of Shc with the Grb2-Sos complex of proteins that lead to Ras activation in B cells.

  18. Bacterial Networks in Cells and Communities.

    Science.gov (United States)

    Sourjik, Victor; Vorholt, Julia A

    2015-11-20

    Research on the bacterial regulatory networks is currently experiencing a true revival, driven by advances in methodology and by emergence of novel concepts. The biannual conference Bacterial Networks (BacNet15) held in May 2015, in Sant Feliu de Guíxols, Spain, covered progress in the studies of regulatory networks that control bacterial physiology, cell biology, stress responses, metabolism, collective behavior and evolution. It demonstrated how interdisciplinary approaches that combine molecular biology and biochemistry with the latest microscopy developments, whole cell (-omics) approaches and mathematical modeling can help understand design principles relevant in microbiology. It further showed how current biotechnology and medical microbiology could profit from our knowledge of and ability to engineer regulatory networks of bacteria. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Identifying colon cancer risk modules with better classification performance based on human signaling network.

    Science.gov (United States)

    Qu, Xiaoli; Xie, Ruiqiang; Chen, Lina; Feng, Chenchen; Zhou, Yanyan; Li, Wan; Huang, Hao; Jia, Xu; Lv, Junjie; He, Yuehan; Du, Youwen; Li, Weiguo; Shi, Yuchen; He, Weiming

    2014-10-01

    Identifying differences between normal and tumor samples from a modular perspective may help to improve our understanding of the mechanisms responsible for colon cancer. Many cancer studies have shown that signaling transduction and biological pathways are disturbed in disease states, and expression profiles can distinguish variations in diseases. In this study, we integrated a weighted human signaling network and gene expression profiles to select risk modules associated with tumor conditions. Risk modules as classification features by our method had a better classification performance than other methods, and one risk module for colon cancer had a good classification performance for distinguishing between normal/tumor samples and between tumor stages. All genes in the module were annotated to the biological process of positive regulation of cell proliferation, and were highly associated with colon cancer. These results suggested that these genes might be the potential risk genes for colon cancer. Copyright © 2013. Published by Elsevier Inc.

  20. Circadian period integrates network information through activation of the BMP signaling pathway.

    Directory of Open Access Journals (Sweden)

    Esteban J Beckwith

    2013-12-01

    Full Text Available Living organisms use biological clocks to maintain their internal temporal order and anticipate daily environmental changes. In Drosophila, circadian regulation of locomotor behavior is controlled by ∼150 neurons; among them, neurons expressing the PIGMENT DISPERSING FACTOR (PDF set the period of locomotor behavior under free-running conditions. To date, it remains unclear how individual circadian clusters integrate their activity to assemble a distinctive behavioral output. Here we show that the BONE MORPHOGENETIC PROTEIN (BMP signaling pathway plays a crucial role in setting the circadian period in PDF neurons in the adult brain. Acute deregulation of BMP signaling causes period lengthening through regulation of dClock transcription, providing evidence for a novel function of this pathway in the adult brain. We propose that coherence in the circadian network arises from integration in PDF neurons of both the pace of the cell-autonomous molecular clock and information derived from circadian-relevant neurons through release of BMP ligands.

  1. Signaling for synergistic activation of natural killer cells.

    Science.gov (United States)

    Kwon, Hyung-Joon; Kim, Hun Sik

    2012-12-01

    Natural killer (NK) cells play a pivotal role in early surveillance against virus infection and cellular transformation, and are also implicated in the control of inflammatory response through their effector functions of direct lysis of target cells and cytokine secretion. NK cell activation toward target cell is determined by the net balance of signals transmitted from diverse activating and inhibitory receptors. A distinct feature of NK cell activation is that stimulation of resting NK cells with single activating receptor on its own cannot mount natural cytotoxicity. Instead, specific pairs of co-activation receptors are required to unleash NK cell activation via synergy-dependent mechanism. Because each co-activation receptor uses distinct signaling modules, NK cell synergy relies on the integration of such disparate signals. This explains why the study of the mechanism underlying NK cell synergy is important and necessary. Recent studies revealed that NK cell synergy depends on the integration of complementary signals converged at a critical checkpoint element but not on simple amplification of the individual signaling to overcome intrinsic activation threshold. This review focuses on the signaling events during NK cells activation and recent advances in the study of NK cell synergy.

  2. Information theory and signal transduction systems: from molecular information processing to network inference.

    Science.gov (United States)

    Mc Mahon, Siobhan S; Sim, Aaron; Filippi, Sarah; Johnson, Robert; Liepe, Juliane; Smith, Dominic; Stumpf, Michael P H

    2014-11-01

    Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Diffusion wave and signal transduction in biological live cells

    OpenAIRE

    Fan, Tian You; Fan, Lei

    2012-01-01

    Transduction of mechanical stimuli into biochemical signals is a fundamental subject for cell physics. In the experiments of FRET signal in cells a wave propagation in nanoscope was observed. We here develop a diffusion wave concept and try to give an explanation to the experimental observation. The theoretical prediction is in good agreement to result of the experiment.

  4. Application of neural networks to signal prediction in nuclear power plant

    International Nuclear Information System (INIS)

    Wan Joo Kim; Soon Heung Chang; Byung Ho Lee

    1993-01-01

    This paper describes the feasibility study of an artificial neural network for signal prediction. The purpose of signal prediction is to estimate the value of undetected next time step signal. As the prediction method, based on the idea of auto regression, a few previous signals are inputs to the artificial neural network and the signal value of next time step is estimated with the outputs of the network. The artificial neural network can be applied to the nonlinear system and answers in short time. The training algorithm is a modified backpropagation model, which can effectively reduce the training time. The target signal of the simulation is the steam generator water level, which is one of the important parameters in nuclear power plants. The simulation result shows that the predicted value follows the real trend well

  5. Human β-Cell Proliferation and Intracellular Signaling: Part 3

    Science.gov (United States)

    Hussain, Mehboob A.; García-Ocaña, Adolfo; Vasavada, Rupangi C.; Bhushan, Anil; Bernal-Mizrachi, Ernesto

    2015-01-01

    This is the third in a series of Perspectives on intracellular signaling pathways coupled to proliferation in pancreatic β-cells. We contrast the large knowledge base in rodent β-cells with the more limited human database. With the increasing incidence of type 1 diabetes and the recognition that type 2 diabetes is also due in part to a deficiency of functioning β-cells, there is great urgency to identify therapeutic approaches to expand human β-cell numbers. Therapeutic approaches might include stem cell differentiation, transdifferentiation, or expansion of cadaver islets or residual endogenous β-cells. In these Perspectives, we focus on β-cell proliferation. Past Perspectives reviewed fundamental cell cycle regulation and its upstream regulation by insulin/IGF signaling via phosphatidylinositol-3 kinase/mammalian target of rapamycin signaling, glucose, glycogen synthase kinase-3 and liver kinase B1, protein kinase Cζ, calcium-calcineurin–nuclear factor of activated T cells, epidermal growth factor/platelet-derived growth factor family members, Wnt/β-catenin, leptin, and estrogen and progesterone. Here, we emphasize Janus kinase/signal transducers and activators of transcription, Ras/Raf/extracellular signal–related kinase, cadherins and integrins, G-protein–coupled receptors, and transforming growth factor β signaling. We hope these three Perspectives will serve to introduce these pathways to new researchers and will encourage additional investigators to focus on understanding how to harness key intracellular signaling pathways for therapeutic human β-cell regeneration for diabetes. PMID:25999530

  6. Deregulation of Interferon Signaling in Malignant Cells

    Directory of Open Access Journals (Sweden)

    Leonidas C. Platanias

    2010-02-01

    Full Text Available Interferons (IFNs are a family of cytokines with potent antiproliferative, antiviral, and immunomodulatory properties. Much has been learned about IFNs and IFN-activated signaling cascades over the last 50 years. Due to their potent antitumor effects in vitro and in vivo, recombinant IFNs have been used extensively over the years, alone or in combination with other drugs, for the treatment of various malignancies. This review summarizes the current knowledge on IFN signaling components and pathways that are deregulated in human malignancies. The relevance of deregulation of IFN signaling pathways in defective innate immune surveillance and tumorigenesis are discussed.

  7. Digital Signal Processing for a Sliceable Transceiver for Optical Access Networks

    DEFF Research Database (Denmark)

    Saldaña Cercos, Silvia; Wagner, Christoph; Vegas Olmos, Juan José

    2015-01-01

    Methods to upgrade the network infrastructure to cope with current traffic demands has attracted increasing research efforts. A promising alternative is signal slicing. Signal slicing aims at re-using low bandwidth equipment to satisfy high bandwidth traffic demands. This technique has been used ...... penalty is reported for 10 Gbps. Power savings of the order of hundreds of Watts can be obtained when using signal slicing as an alternative to 10 Gbps implemented access networks....

  8. Plasticity of the MAPK signaling network in response to mechanical stress.

    Directory of Open Access Journals (Sweden)

    Andrea M Pereira

    Full Text Available Cells display versatile responses to mechanical inputs and recent studies have identified the mitogen-activated protein kinase (MAPK cascades mediating the biological effects observed upon mechanical stimulation. Although, MAPK pathways can act insulated from each other, several mechanisms facilitate the crosstalk between the components of these cascades. Yet, the combinatorial complexity of potential molecular interactions between these elements have prevented the understanding of their concerted functions. To analyze the plasticity of the MAPK signaling network in response to mechanical stress we performed a non-saturating epistatic screen in resting and stretched conditions employing as readout a JNK responsive dJun-FRET biosensor. By knocking down MAPKs, and JNK pathway regulators, singly or in pairs in Drosophila S2R+ cells, we have uncovered unexpected regulatory links between JNK cascade kinases, Rho GTPases, MAPKs and the JNK phosphatase Puc. These relationships have been integrated in a system network model at equilibrium accounting for all experimentally validated interactions. This model allows predicting the global reaction of the network to its modulation in response to mechanical stress. It also highlights its context-dependent sensitivity.

  9. Simultaneous multichannel signal transfers via chaos in a recurrent neural network.

    Science.gov (United States)

    Soma, Ken-ichiro; Mori, Ryota; Sato, Ryuichi; Furumai, Noriyuki; Nara, Shigetoshi

    2015-05-01

    We propose neural network model that demonstrates the phenomenon of signal transfer between separated neuron groups via other chaotic neurons that show no apparent correlations with the input signal. The model is a recurrent neural network in which it is supposed that synchronous behavior between small groups of input and output neurons has been learned as fragments of high-dimensional memory patterns, and depletion of neural connections results in chaotic wandering dynamics. Computer experiments show that when a strong oscillatory signal is applied to an input group in the chaotic regime, the signal is successfully transferred to the corresponding output group, although no correlation is observed between the input signal and the intermediary neurons. Signal transfer is also observed when multiple signals are applied simultaneously to separate input groups belonging to different memory attractors. In this sense simultaneous multichannel communications are realized, and the chaotic neural dynamics acts as a signal transfer medium in which the signal appears to be hidden.

  10. Manipulating cell signaling with subcellular spatial resolution

    Czech Academy of Sciences Publication Activity Database

    Yushchenko, Dmytro A.; Nadler, A.; Schultz, C.

    2016-01-01

    Roč. 15, č. 8 (2016), s. 1023-1024 ISSN 1538-4101 Institutional support: RVO:61388963 Keywords : arachidonic acid * caging group * insulin secretion * photorelease * signaling lipids Subject RIV: CE - Biochemistry Impact factor: 3.530, year: 2016

  11. Phosphatidylinositol 3-phosphates-at the interface between cell signalling and membrane traffic.

    Science.gov (United States)

    Marat, Andrea L; Haucke, Volker

    2016-03-15

    Phosphoinositides (PIs) form a minor class of phospholipids with crucial functions in cell physiology, ranging from cell signalling and motility to a role as signposts of compartmental membrane identity. Phosphatidylinositol 3-phosphates are present at the plasma membrane and within the endolysosomal system, where they serve as key regulators of both cell signalling and of intracellular membrane traffic. Here, we provide an overview of the metabolic pathways that regulate cellular synthesis of PI 3-phosphates at distinct intracellular sites and discuss the mechanisms by which these lipids regulate cell signalling and membrane traffic. Finally, we provide a framework for how PI 3-phosphate metabolism is integrated into the cellular network. © 2016 The Authors.

  12. G-protein coupled receptor signaling architecture of mammalian immune cells.

    Directory of Open Access Journals (Sweden)

    Natalia Polouliakh

    Full Text Available A series of recent studies on large-scale networks of signaling and metabolic systems revealed that a certain network structure often called "bow-tie network" are observed. In signaling systems, bow-tie network takes a form with diverse and redundant inputs and outputs connected via a small numbers of core molecules. While arguments have been made that such network architecture enhances robustness and evolvability of biological systems, its functional role at a cellular level remains obscure. A hypothesis was proposed that such a network function as a stimuli-reaction classifier where dynamics of core molecules dictate downstream transcriptional activities, hence physiological responses against stimuli. In this study, we examined whether such hypothesis can be verified using experimental data from Alliance for Cellular Signaling (AfCS that comprehensively measured GPCR related ligands response for B-cell and macrophage. In a GPCR signaling system, cAMP and Ca2+ act as core molecules. Stimuli-response for 32 ligands to B-Cells and 23 ligands to macrophages has been measured. We found that ligands with correlated changes of cAMP and Ca2+ tend to cluster closely together within the hyperspaces of both cell types and they induced genes involved in the same cellular processes. It was found that ligands inducing cAMP synthesis activate genes involved in cell growth and proliferation; cAMP and Ca2+ molecules that increased together form a feedback loop and induce immune cells to migrate and adhere together. In contrast, ligands without a core molecules response are scattered throughout the hyperspace and do not share clusters. G-protein coupling receptors together with immune response specific receptors were found in cAMP and Ca2+ activated clusters. Analyses have been done on the original software applicable for discovering 'bow-tie' network architectures within the complex network of intracellular signaling where ab initio clustering has been

  13. G-protein coupled receptor signaling architecture of mammalian immune cells.

    Science.gov (United States)

    Polouliakh, Natalia; Nock, Richard; Nielsen, Frank; Kitano, Hiroaki

    2009-01-01

    A series of recent studies on large-scale networks of signaling and metabolic systems revealed that a certain network structure often called "bow-tie network" are observed. In signaling systems, bow-tie network takes a form with diverse and redundant inputs and outputs connected via a small numbers of core molecules. While arguments have been made that such network architecture enhances robustness and evolvability of biological systems, its functional role at a cellular level remains obscure. A hypothesis was proposed that such a network function as a stimuli-reaction classifier where dynamics of core molecules dictate downstream transcriptional activities, hence physiological responses against stimuli. In this study, we examined whether such hypothesis can be verified using experimental data from Alliance for Cellular Signaling (AfCS) that comprehensively measured GPCR related ligands response for B-cell and macrophage. In a GPCR signaling system, cAMP and Ca2+ act as core molecules. Stimuli-response for 32 ligands to B-Cells and 23 ligands to macrophages has been measured. We found that ligands with correlated changes of cAMP and Ca2+ tend to cluster closely together within the hyperspaces of both cell types and they induced genes involved in the same cellular processes. It was found that ligands inducing cAMP synthesis activate genes involved in cell growth and proliferation; cAMP and Ca2+ molecules that increased together form a feedback loop and induce immune cells to migrate and adhere together. In contrast, ligands without a core molecules response are scattered throughout the hyperspace and do not share clusters. G-protein coupling receptors together with immune response specific receptors were found in cAMP and Ca2+ activated clusters. Analyses have been done on the original software applicable for discovering 'bow-tie' network architectures within the complex network of intracellular signaling where ab initio clustering has been implemented as well

  14. Radial glial neural progenitors regulate nascent brain vascular network stabilization via inhibition of Wnt signaling.

    Directory of Open Access Journals (Sweden)

    Shang Ma

    Full Text Available The cerebral cortex performs complex cognitive functions at the expense of tremendous energy consumption. Blood vessels in the brain are known to form stereotypic patterns that facilitate efficient oxygen and nutrient delivery. Yet little is known about how vessel development in the brain is normally regulated. Radial glial neural progenitors are well known for their central role in orchestrating brain neurogenesis. Here we show that, in the late embryonic cortex, radial glial neural progenitors also play a key role in brain angiogenesis, by interacting with nascent blood vessels and regulating vessel stabilization via modulation of canonical Wnt signaling. We find that ablation of radial glia results in vessel regression, concomitant with ectopic activation of Wnt signaling in endothelial cells. Direct activation of Wnt signaling also results in similar vessel regression, while attenuation of Wnt signaling substantially suppresses regression. Radial glial ablation and ectopic Wnt pathway activation leads to elevated endothelial expression of matrix metalloproteinases, while inhibition of metalloproteinase activity significantly suppresses vessel regression. These results thus reveal a previously unrecognized role of radial glial progenitors in stabilizing nascent brain vascular network and provide novel insights into the molecular cascades through which target neural tissues regulate vessel stabilization and patterning during development and throughout life.

  15. Theta sequences of grid cell populations can provide a movement-direction signal.

    Science.gov (United States)

    Zutshi, Ipshita; Leutgeb, Jill K; Leutgeb, Stefan

    2017-10-01

    It has been proposed that path integration in mammals is performed by the convergence of internally generated speed and directional inputs onto grid cells. Although this hypothesis has been supported by the discovery that head direction, speed, and grid cells are intermixed within entorhinal cortex and by the recent finding that head-direction inputs are necessary for grid firing, many details on how grid cells are generated have remained elusive. For example, analysis of recording data suggests that substituting head direction for movement direction accrues errors that preclude the formation of grid patterns. To address this discrepancy, we propose that the organization of grid networks makes it plausible that movement-direction signals are an output from grid cells and that temporally precise grid cell sequences provide a robust directional signal to other spatial and directional cell types.

  16. On the Virtual Cell Transmission in Ultra Dense Networks

    Directory of Open Access Journals (Sweden)

    Xiaopeng Zhu

    2016-10-01

    Full Text Available Ultra dense networks (UDN are identified as one of the key enablers for 5G, since they can provide an ultra high spectral reuse factor exploiting proximal transmissions. By densifying the network infrastructure equipment, it is highly possible that each user will have one or more dedicated serving base station antennas, introducing the user-centric virtual cell paradigm. However, due to irregular deployment of a large amount of base station antennas, the interference environment becomes rather complex, thus introducing severe interferences among different virtual cells. This paper focuses on the downlink transmission scheme in UDN where a large number of users and base station antennas is uniformly spread over a certain area. An interference graph is first created based on the large-scale fadings to give a potential description of the interference relationship among the virtual cells. Then, base station antennas and users in the virtual cells within the same maximally-connected component are grouped together and merged into one new virtual cell cluster, where users are jointly served via zero-forcing (ZF beamforming. A multi-virtual-cell minimum mean square error precoding scheme is further proposed to mitigate the inter-cluster interference. Additionally, the interference alignment framework is proposed based on the low complexity virtual cell merging to eliminate the strong interference between different virtual cells. Simulation results show that the proposed interference graph-based virtual cell merging approach can attain the average user spectral efficiency performance of the grouping scheme based on virtual cell overlapping with a smaller virtual cell size and reduced signal processing complexity. Besides, the proposed user-centric transmission scheme greatly outperforms the BS-centric transmission scheme (maximum ratio transmission (MRT in terms of both the average user spectral efficiency and edge user spectral efficiency. What is more

  17. Nonimmune cells equipped with T-cell-receptor-like signaling for cancer cell ablation.

    Science.gov (United States)

    Kojima, Ryosuke; Scheller, Leo; Fussenegger, Martin

    2018-01-01

    The ability to engineer custom cell-contact-sensing output devices into human nonimmune cells would be useful for extending the applicability of cell-based cancer therapies and for avoiding risks associated with engineered immune cells. Here we have developed a new class of synthetic T-cell receptor-like signal-transduction device that functions efficiently in human nonimmune cells and triggers release of output molecules specifically upon sensing contact with a target cell. This device employs an interleukin signaling cascade, whose OFF/ON switching is controlled by biophysical segregation of a transmembrane signal-inhibitory protein from the sensor cell-target cell interface. We further show that designer nonimmune cells equipped with this device driving expression of a membrane-penetrator/prodrug-activating enzyme construct could specifically kill target cells in the presence of the prodrug, indicating its potential usefulness for target-cell-specific, cell-based enzyme-prodrug cancer therapy. Our study also contributes to the advancement of synthetic biology by extending available design principles to transmit extracellular information to cells.

  18. Signaling profiling at the single-cell level identifies a distinct signaling signature in murine hematopoietic stem cells.

    Science.gov (United States)

    Du, Juan; Wang, Jinyong; Kong, Guangyao; Jiang, Jing; Zhang, Jingfang; Liu, Yangang; Tong, Wei; Zhang, Jing

    2012-07-01

    Hematopoietic stem cell (HSC) function is tightly regulated by cytokine signaling. Although phospho-flow cytometry allows us to study signaling in defined populations of cells, there has been tremendous hurdle to carry out this study in rare HSCs due to unrecoverable critical HSC markers, low HSC number, and poor cell recovery rate. Here, we overcame these difficulties and developed a "HSC phospho-flow" method to analyze cytokine signaling in murine HSCs at the single-cell level and compare HSC signaling profile to that of multipotent progenitors (MPPs), a cell type immediately downstream of HSCs, and commonly used Lin(-) cKit(+) cells (LK cells, enriched for myeloid progenitors). We chose to study signaling evoked from three representative cytokines, stem cell factor (SCF) and thrombopoietin (TPO) that are essential for HSC function and granulocyte macrophage-colony-stimulating factor (GM-CSF) that is dispensable for HSCs. HSCs display a distinct TPO and GM-CSF signaling signature from MPPs and LK cells, which highly correlates with receptor surface expression. In contrast, although majority of LK cells express lower levels of cKit than HSCs and MPPs, SCF-evoked ERK1/2 activation in LK cells shows a significantly increased magnitude for a prolonged period. These results suggest that specific cellular context plays a more important role than receptor surface expression in SCF signaling. Our study of HSC signaling at the homeostasis stage paves the way to investigate signaling changes in HSCs under conditions of stress, aging, and hematopoietic diseases. Copyright © 2012 AlphaMed Press.

  19. Transcription factor Ebf1 regulates differentiation stage-specific signaling, proliferation, and survival of B cells.

    Science.gov (United States)

    Györy, Ildiko; Boller, Sören; Nechanitzky, Robert; Mandel, Elizabeth; Pott, Sebastian; Liu, Edison; Grosschedl, Rudolf

    2012-04-01

    The transcription factor Ebf1 is an important determinant of early B lymphopoiesis. To gain insight into the functions of Ebf1 at distinct stages of differentiation, we conditionally inactivated Ebf1. We found that Ebf1 is required for the proliferation, survival, and signaling of pro-B cells and peripheral B-cell subsets, including B1 cells and marginal zone B cells. The proliferation defect of Ebf1-deficient pro-B cells and the impaired expression of multiple cell cycle regulators are overcome by transformation with v-Abl. The survival defect of transformed Ebf1(fl/fl) pro-B cells can be rescued by the forced expression of the Ebf1 targets c-Myb or Bcl-x(L). In mature B cells, Ebf1 deficiency interferes with signaling via the B-cell-activating factor receptor (BAFF-R)- and B-cell receptor (BCR)-dependent Akt pathways. Moreover, Ebf1 is required for germinal center formation and class switch recombination. Genome-wide analyses of Ebf1-mediated gene expression and chromatin binding indicate that Ebf1 regulates both common and distinct sets of genes in early and late stage B cells. By regulating important components of transcription factor and signaling networks, Ebf1 appears to be involved in the coordination of cell proliferation, survival, and differentiation at multiple stages of B lymphopoiesis.

  20. Wnt signaling in the stem cell niche

    NARCIS (Netherlands)

    Rattis, Frédérique Marie; Voermans, Carlijn; Reya, Tannishtha

    2004-01-01

    All the cells present in the blood are derived from the hematopoietic stem cell (HSC). Because mature blood cells have a limited life span, HSCs must perpetuate themselves through self-renewal to maintain a functional hematopoietic compartment for the lifetime of an organism. This review focuses on

  1. Resolving dynamics of cell signaling via real-time imaging of the immunological synapse.

    Energy Technology Data Exchange (ETDEWEB)

    Stevens, Mark A.; Pfeiffer, Janet R. (University of New Mexico, Albuquerque, NM); Wilson, Bridget S. (University of New Mexico, Albuquerque, NM); Timlin, Jerilyn Ann; Thomas, James L. (University of New Mexico, Albuquerque, NM); Lidke, Keith A. (University of New Mexico, Albuquerque, NM); Spendier, Kathrin (University of New Mexico, Albuquerque, NM); Oliver, Janet M. (University of New Mexico, Albuquerque, NM); Carroll-Portillo, Amanda (University of New Mexico, Albuquerque, NM); Aaron, Jesse S.; Mirijanian, Dina T.; Carson, Bryan D.; Burns, Alan Richard; Rebeil, Roberto

    2009-10-01

    This highly interdisciplinary team has developed dual-color, total internal reflection microscopy (TIRF-M) methods that enable us to optically detect and track in real time protein migration and clustering at membrane interfaces. By coupling TIRF-M with advanced analysis techniques (image correlation spectroscopy, single particle tracking) we have captured subtle changes in membrane organization that characterize immune responses. We have used this approach to elucidate the initial stages of cell activation in the IgE signaling network of mast cells and the Toll-like receptor (TLR-4) response in macrophages stimulated by bacteria. To help interpret these measurements, we have undertaken a computational modeling effort to connect the protein motion and lipid interactions. This work provides a deeper understanding of the initial stages of cellular response to external agents, including dynamics of interaction of key components in the signaling network at the 'immunological synapse,' the contact region of the cell and its adversary.

  2. Protein kinase C signaling and cell cycle regulation

    OpenAIRE

    Black, Adrian R.; Black, Jennifer D.

    2013-01-01

    A link between T cell proliferation and the protein kinase C (PKC) family of serine/threonine kinases has been recognized for about thirty years. However, despite the wealth of information on PKC-mediated control of T cell activation, understanding of the effects of PKCs on the cell cycle machinery in this cell type remains limited. Studies in other systems have revealed important cell cycle-specific effects of PKC signaling that can either positively or negatively impact proliferation. Th...

  3. Atomic force microscopy and graph analysis to study the P-cadherin/SFK mechanotransduction signalling in breast cancer cells.

    Science.gov (United States)

    Ribeiro, A S; Carvalho, F A; Figueiredo, J; Carvalho, R; Mestre, T; Monteiro, J; Guedes, A F; Fonseca, M; Sanches, J; Seruca, R; Santos, N C; Paredes, J

    2016-11-24

    Physical forces mediated by cell-cell adhesion molecules, as cadherins, play a crucial role in preserving normal tissue architecture. Accordingly, altered cadherins' expression has been documented as a common event during cancer progression. However, in most studies, no data exist linking pro-tumorigenic signaling and variations in the mechanical balance mediated by adhesive forces. In breast cancer, P-cadherin overexpression increases in vivo tumorigenic ability, as well as in vitro cell invasion, by activating Src family kinase (SFK) signalling. However, it is not known how P-cadherin and SFK activation impact cell-cell biomechanical properties. In the present work, using atomic force microscopy (AFM) images, cell stiffness and cell-cell adhesion measurements, and undirected graph analysis based on microscopic images, we have demonstrated that P-cadherin overexpression promotes significant alterations in cell's morphology, by decreasing cellular height and increasing its area. It also affects biomechanical properties, by decreasing cell-cell adhesion and cell stiffness. Furthermore, cellular network analysis showed alterations in intercellular organization, which is associated with cell-cell adhesion dysfunction, destabilization of an E-cadherin/p120ctn membrane complex and increased cell invasion. Remarkably, inhibition of SFK signaling, using dasatinib, reverted the pathogenic P-cadherin induced effects by increasing cell's height, cell-cell adhesion and cell stiffness, and generating more compact epithelial aggregates, as quantified by intercellular network analysis. In conclusion, P-cadherin/SFK signalling induces topological, morphological and biomechanical cell-cell alterations, which are associated with more invasive breast cancer cells. These effects could be further reverted by dasatinib treatment, demonstrating the applicability of AFM and cell network diagrams for measuring the epithelial biomechanical properties and structural organization.

  4. Stochastic effects as a force to increase the complexity of signaling networks

    KAUST Repository

    Kuwahara, Hiroyuki

    2013-07-29

    Cellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism. However, the conditions under which molecular noise influences cellular information processing remain unclear. Here, we explore a large number of simple biological models of varying network sizes to understand the architectural conditions under which the interactions of signaling proteins can exhibit specific stochastic effects - called deviant effects - in which the average behavior of a biological system is substantially altered in the presence of molecular noise. We find that a small fraction of these networks does exhibit deviant effects and shares a common architectural feature whereas most of the networks show only insignificant levels of deviations. Interestingly, addition of seemingly unimportant interactions into protein networks gives rise to deviant effects.

  5. Retinoic acid signalling in thymocytes regulates T cell development

    DEFF Research Database (Denmark)

    Wendland, Kerstin; Sitnik, Katarzyna Maria; Kotarsky, Knut

    further enhanced in recently generated CD69+ CD4+ SP cells. To address the potential biological significance of RA signaling in developing thymocytes, we evaluated T cell development in CD4Cre-dnRAR mice, where RA signaling is blocked in thymocytes from the CD4+CD8+ double positive (DP) stage onwards due...... precursor entry and/or survival. Furthermore, CD4Cre-dnRAR mice showed a 4-fold reduction in CD4+/CD8+ SP ratio that was mainly due to enhanced accumulation of mature CD8+ SP cells, indicating that RA signaling may be directly involved in regulating thymic retention and/or post-selection expansion...

  6. CellNet: network biology applied to stem cell engineering.

    Science.gov (United States)

    Cahan, Patrick; Li, Hu; Morris, Samantha A; Lummertz da Rocha, Edroaldo; Daley, George Q; Collins, James J

    2014-08-14

    Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Discovery of intramolecular signal transduction network based on a new protein dynamics model of energy dissipation.

    Directory of Open Access Journals (Sweden)

    Cheng-Wei Ma

    Full Text Available A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins.

  8. A model-based strategy to investigate the role of microRNA regulation in cancer signalling networks.

    Science.gov (United States)

    Nikolov, Svetoslav; Vera, Julio; Schmitz, Ulf; Wolkenhauer, Olaf

    2011-03-01

    In this paper we present and discuss a model-based approach to link miRNA translational control with cell signalling networks. MicroRNAs are small regulatory RNAs that are able to regulate the activity and the stability of specific messenger RNA and have been implicated in tumour progression due to their ability to translationally regulate critical oncogenes and tumour suppressors. In our approach, data on protein-protein interactions and miRNA regulation, obtained from bioinformatics databases, are integrated with quantitative experimental data using mathematical modelling. Predictive computational simulations and qualitative (bifurcation) analyses of those mathematical models are employed to further support the investigation of such multifactorial networks in the context of cancer progression. We illustrate our approach with the C-Myc/E2F signalling network, involved in the progression of several tumour subtypes, including colorectal cancer.

  9. Different cell fates from cell-cell interactions: core architectures of two-cell bistable networks.

    Science.gov (United States)

    Rouault, Hervé; Hakim, Vincent

    2012-02-08

    The acquisition of different fates by cells that are initially in the same state is central to development. Here, we investigate the possible structures of bistable genetic networks that can allow two identical cells to acquire different fates through cell-cell interactions. Cell-autonomous bistable networks have been previously sampled using an evolutionary algorithm. We extend this evolutionary procedure to take into account interactions between cells. We obtain a variety of simple bistable networks that we classify into major subtypes. Some have long been proposed in the context of lateral inhibition through the Notch-Delta pathway, some have been more recently considered and others appear to be new and based on mechanisms not previously considered. The results highlight the role of posttranscriptional interactions and particularly of protein complexation and sequestration, which can replace cooperativity in transcriptional interactions. Some bistable networks are entirely based on posttranscriptional interactions and the simplest of these is found to lead, upon a single parameter change, to oscillations in the two cells with opposite phases. We provide qualitative explanations as well as mathematical analyses of the dynamical behaviors of various created networks. The results should help to identify and understand genetic structures implicated in cell-cell interactions and differentiation. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  10. Seismic signal auto-detecing from different features by using Convolutional Neural Network

    Science.gov (United States)

    Huang, Y.; Zhou, Y.; Yue, H.; Zhou, S.

    2017-12-01

    We try Convolutional Neural Network to detect some features of seismic data and compare their efficience. The features include whether a signal is seismic signal or noise and the arrival time of P and S phase and each feature correspond to a Convolutional Neural Network. We first use traditional STA/LTA to recongnize some events and then use templete matching to find more events as training set for the Neural Network. To make the training set more various, we add some noise to the seismic data and make some synthetic seismic data and noise. The 3-component raw signal and time-frequancy ananlyze are used as the input data for our neural network. Our Training is performed on GPUs to achieve efficient convergence. Our method improved the precision in comparison with STA/LTA and template matching. We will move to recurrent neural network to see if this kind network is better in detect P and S phase.

  11. Spatial and temporal dynamics of T cell receptor signaling with a photoactivatable agonist.

    Science.gov (United States)

    Huse, Morgan; Klein, Lawrence O; Girvin, Andrew T; Faraj, Joycelyn M; Li, Qi-Jing; Kuhns, Michael S; Davis, Mark M

    2007-07-01

    The precise timing of signals downstream of the T cell receptor (TCR) is poorly understood. To address this problem, we prepared major histocompatibility complexes containing an antigenic peptide that is biologically inert until exposed to ultraviolet (UV) light. UV irradiation of these complexes in contact with cognate T cells enabled the high-resolution temporal analysis of signaling. Phosphorylation of the LAT adaptor molecule was observed in 4 s, and diacylglycerol production and calcium flux was observed in 6-7 s. TCR activation also induced cytoskeletal polarization within 2 min. Antibody blockade of CD4 reduced the intensity of LAT phosphorylation and the speed of calcium flux. Furthermore, strong desensitization of diacylglycerol production, but not LAT phosphorylation, occurred shortly after TCR activation, suggesting that different molecular events play distinct signal-processing roles. These results establish the speed and localization of early signaling steps, and have important implications regarding the overall structure of the network.

  12. Inhibitory network interactions shape the auditory processing of natural communication signals in the songbird auditory forebrain.

    Science.gov (United States)

    Pinaud, Raphael; Terleph, Thomas A; Tremere, Liisa A; Phan, Mimi L; Dagostin, André A; Leão, Ricardo M; Mello, Claudio V; Vicario, David S

    2008-07-01

    The role of GABA in the central processing of complex auditory signals is not fully understood. We have studied the involvement of GABA A-mediated inhibition in the processing of birdsong, a learned vocal communication signal requiring intact hearing for its development and maintenance. We focused on caudomedial nidopallium (NCM), an area analogous to parts of the mammalian auditory cortex with selective responses to birdsong. We present evidence that GABA A-mediated inhibition plays a pronounced role in NCM's auditory processing of birdsong. Using immunocytochemistry, we show that approximately half of NCM's neurons are GABAergic. Whole cell patch-clamp recordings in a slice preparation demonstrate that, at rest, spontaneously active GABAergic synapses inhibit excitatory inputs onto NCM neurons via GABA A receptors. Multi-electrode electrophysiological recordings in awake birds show that local blockade of GABA A-mediated inhibition in NCM markedly affects the temporal pattern of song-evoked responses in NCM without modifications in frequency tuning. Surprisingly, this blockade increases the phasic and largely suppresses the tonic response component, reflecting dynamic relationships of inhibitory networks that could include disinhibition. Thus processing of learned natural communication sounds in songbirds, and possibly other vocal learners, may depend on complex interactions of inhibitory networks.

  13. Arterial-venous network formation during brain vascularization involves hemodynamic regulation of chemokine signaling.

    Science.gov (United States)

    Bussmann, Jeroen; Wolfe, Scot A; Siekmann, Arndt F

    2011-05-01

    During angiogenic sprouting, newly forming blood vessels need to connect to the existing vasculature in order to establish a functional circulatory loop. Previous studies have implicated genetic pathways, such as VEGF and Notch signaling, in controlling angiogenesis. We show here that both pathways similarly act during vascularization of the zebrafish central nervous system. In addition, we find that chemokine signaling specifically controls arterial-venous network formation in the brain. Zebrafish mutants for the chemokine receptor cxcr4a or its ligand cxcl12b establish a decreased number of arterial-venous connections, leading to the formation of an unperfused and interconnected blood vessel network. We further find that expression of cxcr4a in newly forming brain capillaries is negatively regulated by blood flow. Accordingly, unperfused vessels continue to express cxcr4a, whereas connection of these vessels to the arterial circulation leads to rapid downregulation of cxcr4a expression and loss of angiogenic characteristics in endothelial cells, such as filopodia formation. Together, our findings indicate that hemodynamics, in addition to genetic pathways, influence vascular morphogenesis by regulating the expression of a proangiogenic factor that is necessary for the correct pathfinding of sprouting brain capillaries.

  14. Digital Signal Processing and Control for the Study of Gene Networks

    Science.gov (United States)

    Shin, Yong-Jun

    2016-04-01

    Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

  15. Digital Signal Processing and Control for the Study of Gene Networks.

    Science.gov (United States)

    Shin, Yong-Jun

    2016-04-22

    Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

  16. Electrocardiogram (ECG Signal Modeling and Noise Reduction Using Hopfield Neural Networks

    Directory of Open Access Journals (Sweden)

    F. Bagheri

    2013-02-01

    Full Text Available The Electrocardiogram (ECG signal is one of the diagnosing approaches to detect heart disease. In this study the Hopfield Neural Network (HNN is applied and proposed for ECG signal modeling and noise reduction. The Hopfield Neural Network (HNN is a recurrent neural network that stores the information in a dynamic stable pattern. This algorithm retrieves a pattern stored in memory in response to the presentation of an incomplete or noisy version of that pattern. Computer simulation results show that this method can successfully model the ECG signal and remove high-frequency noise.

  17. Cell biology symposium: Membrane trafficking and signal transduction

    Science.gov (United States)

    In general, membrane trafficking is a broad group of processes where proteins and other large molecules are distributed throughout the cell as well as adjacent extracellular spaces. Whereas signal transduction is a process where signals are transmitted through a series of chemical or molecular event...

  18. Synaptic signal streams generated by ex vivo neuronal networks contain non-random, complex patterns.

    Science.gov (United States)

    Lee, Sangmook; Zemianek, Jill M; Shultz, Abraham; Vo, Anh; Maron, Ben Y; Therrien, Mikaela; Courtright, Christina; Guaraldi, Mary; Yanco, Holly A; Shea, Thomas B

    2014-11-01

    Cultured embryonic neurons develop functional networks that transmit synaptic signals over multiple sequentially connected neurons as revealed by multi-electrode arrays (MEAs) embedded within the culture dish. Signal streams of ex vivo networks contain spikes and bursts of varying amplitude and duration. Despite the random interactions inherent in dissociated cultures, neurons are capable of establishing functional ex vivo networks that transmit signals among synaptically connected neurons, undergo developmental maturation, and respond to exogenous stimulation by alterations in signal patterns. These characteristics indicate that a considerable degree of organization is an inherent property of neurons. We demonstrate herein that (1) certain signal types occur more frequently than others, (2) the predominant signal types change during and following maturation, (3) signal predominance is dependent upon inhibitory activity, and (4) certain signals preferentially follow others in a non-reciprocal manner. These findings indicate that the elaboration of complex signal streams comprised of a non-random distribution of signal patterns is an emergent property of ex vivo neuronal networks. Copyright © 2014. Published by Elsevier Ltd.

  19. Stem cell signaling. An integral program for tissue renewal and regeneration : Wnt signaling and stem cell control

    NARCIS (Netherlands)

    Clevers, Hans; Loh, Kyle M; Nusse, Roel

    2014-01-01

    Stem cells fuel tissue development, renewal, and regeneration, and these activities are controlled by the local stem cell microenvironment, the "niche." Wnt signals emanating from the niche can act as self-renewal factors for stem cells in multiple mammalian tissues. Wnt proteins are lipid-modified,

  20. Identification of an allosteric signaling network within Tec family kinases.

    Science.gov (United States)

    Joseph, Raji E; Xie, Qian; Andreotti, Amy H

    2010-10-22

    The Tec family kinases are tyrosine kinases that function primarily in hematopoietic cells. The catalytic activity of the Tec kinases is positively influenced by the regulatory domains outside of the kinase domain. The current lack of a full-length Tec kinase structure leaves a void in our understanding of how these positive regulatory signals are transmitted to the kinase domain. Recently, a conserved structure within kinases, the 'regulatory spine', which assembles and disassembles as a kinase switches between its active and inactive states, has been identified. Here, we define the residues that comprise the regulatory spine within Tec kinases. Compared to previously characterized systems, the Tec kinases contain an extended regulatory spine that includes a conserved methionine within the C-helix and a conserved tryptophan within the Src homology 2-kinase linker of Tec kinases. This extended regulatory spine forms a conduit for transmitting the presence of the regulatory domains of Tec kinases to the catalytic domain. We further show that mutation of the gatekeeper residue at the edge of the regulatory spine stabilizes the regulatory spine, resulting in a constitutively active kinase domain. Importantly, the regulatory spine is preassembled in this gatekeeper mutant, rendering phosphorylation on the activation loop unnecessary for its activity. Moreover, we show that the disruption of the conserved electrostatic interaction between Bruton's tyrosine kinase R544 on the activation loop and Bruton's tyrosine kinase E445 on the C-helix also aids in the assembly of the regulatory spine. Thus, the extended regulatory spine is a key structure that is critical for maintaining the activity of Tec kinases. Copyright © 2010 Elsevier Ltd. All rights reserved.

  1. The effect of suppressor of cytokine signaling 3 on GH signaling in beta-cells

    DEFF Research Database (Denmark)

    Rønn, Sif G; Hansen, Johnny A; Lindberg, Karen

    2002-01-01

    GH is an important regulator of cell growth and metabolism. In the pancreas, GH stimulates mitogenesis as well as insulin production in beta-cells. The cellular effects of GH are exerted mainly through activation of the Janus kinase-signal transducer and activator of transcription (STAT) pathway...

  2. Transforming Musical Signals through a Genre Classifying Convolutional Neural Network

    Science.gov (United States)

    Geng, S.; Ren, G.; Ogihara, M.

    2017-05-01

    Convolutional neural networks (CNNs) have been successfully applied on both discriminative and generative modeling for music-related tasks. For a particular task, the trained CNN contains information representing the decision making or the abstracting process. One can hope to manipulate existing music based on this 'informed' network and create music with new features corresponding to the knowledge obtained by the network. In this paper, we propose a method to utilize the stored information from a CNN trained on musical genre classification task. The network was composed of three convolutional layers, and was trained to classify five-second song clips into five different genres. After training, randomly selected clips were modified by maximizing the sum of outputs from the network layers. In addition to the potential of such CNNs to produce interesting audio transformation, more information about the network and the original music could be obtained from the analysis of the generated features since these features indicate how the network 'understands' the music.

  3. Model-based design of self-Adapting networked signal processing systems

    NARCIS (Netherlands)

    Oliveira Filho, J.A. de; Papp, Z.; Djapic, R.; Oostveen, J.C.

    2013-01-01

    The paper describes a model based approach for architecture design of runtime reconfigurable, large-scale, networked signal processing applications. A graph based modeling formalism is introduced to describe all relevant aspects of the design (functional, concurrency, hardware, communication,

  4. An Improved Response Surface Methodology Algorithm with an Application to Traffic Signal Optimization for Urban Networks

    Science.gov (United States)

    1995-01-01

    Prepared ca. 1995. This paper illustrates the use of the simulation-optimization technique of response surface methodology (RSM) in traffic signal optimization of urban networks. It also quantifies the gains of using the common random number (CRN) va...

  5. Experimental Demonstration of Mixed Formats and Bit Rates Signal Allocation for Spectrum-flexible Optical Networking

    DEFF Research Database (Denmark)

    Borkowski, Robert; Karinou, Fotini; Angelou, Marianna

    2012-01-01

    We report on an extensive experimental study for adaptive allocation of 16-QAM and QPSK signals inside spectrum flexible heterogeneous superchannel. Physical-layer performance parameters are extracted for use in resource allocation mechanisms of future flexible networks....

  6. Performance Comparison of Different Spread-Spectrum Signaling Schemes for Cellular Mobile Radio Networks

    National Research Council Canada - National Science Library

    Soroushnejad, Mohsen; Geraniotis, Evaggelos

    1988-01-01

    .... In particular, for the cellular radio network of [l}, which employs frequency-hopped signaling, the model of the spread-spectrum multiple-access interference has not been sufficiently accurate, whereas the model and analysis of that paper...

  7. Integration of hormonal signaling networks and mobile microRNAs is required for vascular patterning in Arabidopsis roots

    KAUST Repository

    Muraro, D.

    2013-12-31

    As multicellular organisms grow, positional information is continually needed to regulate the pattern in which cells are arranged. In the Arabidopsis root, most cell types are organized in a radially symmetric pattern; however, a symmetry-breaking event generates bisymmetric auxin and cytokinin signaling domains in the stele. Bidirectional cross-talk between the stele and the surrounding tissues involving a mobile transcription factor, SHORT ROOT (SHR), and mobile microRNA species also determines vascular pattern, but it is currently unclear how these signals integrate. We use a multicellular model to determine a minimal set of components necessary for maintaining a stable vascular pattern. Simulations perturbing the signaling network show that, in addition to the mutually inhibitory interaction between auxin and cytokinin, signaling through SHR, microRNA165/6, and PHABULOSA is required to maintain a stable bisymmetric pattern. We have verified this prediction by observing loss of bisymmetry in shr mutants. The model reveals the importance of several features of the network, namely the mutual degradation of microRNA165/6 and PHABULOSA and the existence of an additional negative regulator of cytokinin signaling. These components form a plausible mechanism capable of patterning vascular tissues in the absence of positional inputs provided by the transport of hormones from the shoot.

  8. New Modeling Approaches to Investigate Cell Signaling in Radiation Response

    Science.gov (United States)

    Plante, Ianik; Cucinotta, Francis A.; Ponomarev, Artem L.

    2011-01-01

    Ionizing radiation damages individual cells and tissues leading to harmful biological effects. Among many radiation-induced lesions, DNA double-strand breaks (DSB) are considered the key precursors of most early and late effects [1] leading to direct mutation or aberrant signal transduction processes. In response to damage, a flow of information is communicated to cells not directly hit by the radiation through signal transduction pathways [2]. Non-targeted effects (NTE), which includes bystander effects and genomic instability in the progeny of irradiated cells and tissues, may be particularly important for space radiation risk assessment [1], because astronauts are exposed to a low fluence of heavy ions and only a small fraction of cells are traversed by an ion. NTE may also have important consequences clinical radiotherapy [3]. In the recent years, new simulation tools and modeling approaches have become available to study the tissue response to radiation. The simulation of signal transduction pathways require many elements such as detailed track structure calculations, a tissue or cell culture model, knowledge of biochemical pathways and Brownian Dynamics (BD) propagators of the signaling molecules in their micro-environment. Recently, the Monte-Carlo simulation code of radiation track structure RITRACKS was used for micro and nano-dosimetry calculations [4]. RITRACKS will be used to calculate the fraction of cells traversed by an ion and delta-rays and the energy deposited in cells in a tissue model. RITRACKS also simulates the formation of chemical species by the radiolysis of water [5], notably the .OH radical. This molecule is implicated in DNA damage and in the activation of the transforming growth factor beta (TGF), a signaling molecule involved in NTE. BD algorithms for a particle near a membrane comprising receptors were also developed and will be used to simulate trajectories of signaling molecules in the micro-environment and characterize autocrine

  9. Shared signaling pathways in normal and breast cancer stem cells

    Directory of Open Access Journals (Sweden)

    Gautam K Malhotra

    2011-01-01

    Full Text Available Recent advances in our understanding of breast cancer biology have led to the identification of a subpopulation of cells within tumors that appear to be responsible for initiating and propagating the cancer. These tumor initiating cells are not only unique in their ability to generate tumors, but also share many similarities with elements of normal adult tissue stem cells, and have therefore been termed cancer stem cells (CSCs. These CSCs often inappropriately use many of the same signaling pathways utilized by their normal stem cell counterparts which may present a challenge to the development of CSC specific therapies. Here, we discuss three major stem cell signaling pathways (Notch, Wnt, and Hedgehog; with a focus on their function in normal mammary gland development and their misuse in breast cancer stem cell fate determination.

  10. Towards systematic discovery of signaling networks in budding yeast filamentous growth stress response using interventional phosphorylation data.

    Science.gov (United States)

    Zhang, Yan; Kweon, Hye Kyong; Shively, Christian; Kumar, Anuj; Andrews, Philip C

    2013-01-01

    Reversible phosphorylation is one of the major mechanisms of signal transduction, and signaling networks are critical regulators of cell growth and development. However, few of these networks have been delineated completely. Towards this end, quantitative phosphoproteomics is emerging as a useful tool enabling large-scale determination of relative phosphorylation levels. However, phosphoproteomics differs from classical proteomics by a more extensive sampling limitation due to the limited number of detectable sites per protein. Here, we propose a comprehensive quantitative analysis pipeline customized for phosphoproteome data from interventional experiments for identifying key proteins in specific pathways, discovering the protein-protein interactions and inferring the signaling network. We also made an effort to partially compensate for the missing value problem, a chronic issue for proteomics studies. The dataset used for this study was generated using SILAC (Stable Isotope Labeling with Amino acids in Cell culture) technique with interventional experiments (kinase-dead mutations). The major components of the pipeline include phosphopeptide meta-analysis, correlation network analysis and causal relationship discovery. We have successfully applied our pipeline to interventional experiments identifying phosphorylation events underlying the transition to a filamentous growth form in Saccharomyces cerevisiae. We identified 5 high-confidence proteins from meta-analysis, and 19 hub proteins from correlation analysis (Pbi2p and Hsp42p were identified by both analyses). All these proteins are involved in stress responses. Nine of them have direct or indirect evidence of involvement in filamentous growth. In addition, we tested four of our predicted proteins, Nth1p, Pbi2p, Pdr12p and Rcn2p, by interventional phenotypic experiments and all of them present differential invasive growth, providing prospective validation of our approach. This comprehensive pipeline presents a

  11. Towards systematic discovery of signaling networks in budding yeast filamentous growth stress response using interventional phosphorylation data.

    Directory of Open Access Journals (Sweden)

    Yan Zhang

    Full Text Available Reversible phosphorylation is one of the major mechanisms of signal transduction, and signaling networks are critical regulators of cell growth and development. However, few of these networks have been delineated completely. Towards this end, quantitative phosphoproteomics is emerging as a useful tool enabling large-scale determination of relative phosphorylation levels. However, phosphoproteomics differs from classical proteomics by a more extensive sampling limitation due to the limited number of detectable sites per protein. Here, we propose a comprehensive quantitative analysis pipeline customized for phosphoproteome data from interventional experiments for identifying key proteins in specific pathways, discovering the protein-protein interactions and inferring the signaling network. We also made an effort to partially compensate for the missing value problem, a chronic issue for proteomics studies. The dataset used for this study was generated using SILAC (Stable Isotope Labeling with Amino acids in Cell culture technique with interventional experiments (kinase-dead mutations. The major components of the pipeline include phosphopeptide meta-analysis, correlation network analysis and causal relationship discovery. We have successfully applied our pipeline to interventional experiments identifying phosphorylation events underlying the transition to a filamentous growth form in Saccharomyces cerevisiae. We identified 5 high-confidence proteins from meta-analysis, and 19 hub proteins from correlation analysis (Pbi2p and Hsp42p were identified by both analyses. All these proteins are involved in stress responses. Nine of them have direct or indirect evidence of involvement in filamentous growth. In addition, we tested four of our predicted proteins, Nth1p, Pbi2p, Pdr12p and Rcn2p, by interventional phenotypic experiments and all of them present differential invasive growth, providing prospective validation of our approach. This comprehensive

  12. Protein Phosphatase 2A in the Regulation of Wnt Signaling, Stem Cells, and Cancer.

    Science.gov (United States)

    Thompson, Joshua J; Williams, Christopher S

    2018-02-26

    Protein phosphorylation is a ubiquitous cellular process that allows for the nuanced and reversible regulation of protein activity. Protein phosphatase 2A (PP2A) is a heterotrimeric serine-threonine phosphatase-composed of a structural, regulatory, and catalytic subunit-that controls a variety of cellular events via protein dephosphorylation. While much is known about PP2A and its basic biochemistry, the diversity of its components-especially the multitude of regulatory subunits-has impeded the determination of PP2A function. As a consequence of this complexity, PP2A has been shown to both positively and negatively regulate signaling networks such as the Wnt pathway. Wnt signaling modulates major developmental processes, and is a dominant mediator of stem cell self-renewal, cell fate, and cancer stem cells. Because PP2A affects Wnt signaling both positively and negatively and at multiple levels, further understanding of this complex dynamic may ultimately provide insight into stem cell biology and how to better treat cancers that result from alterations in Wnt signaling. This review will summarize literature that implicates PP2A as a tumor suppressor, explore PP2A mutations identified in human malignancy, and focus on PP2A in the regulation of Wnt signaling and stem cells so as to better understand how aberrancy in this pathway can contribute to tumorigenesis.

  13. Protein Phosphatase 2A in the Regulation of Wnt Signaling, Stem Cells, and Cancer

    Directory of Open Access Journals (Sweden)

    Joshua J. Thompson

    2018-02-01

    Full Text Available Protein phosphorylation is a ubiquitous cellular process that allows for the nuanced and reversible regulation of protein activity. Protein phosphatase 2A (PP2A is a heterotrimeric serine-threonine phosphatase—composed of a structural, regulatory, and catalytic subunit—that controls a variety of cellular events via protein dephosphorylation. While much is known about PP2A and its basic biochemistry, the diversity of its components—especially the multitude of regulatory subunits—has impeded the determination of PP2A function. As a consequence of this complexity, PP2A has been shown to both positively and negatively regulate signaling networks such as the Wnt pathway. Wnt signaling modulates major developmental processes, and is a dominant mediator of stem cell self-renewal, cell fate, and cancer stem cells. Because PP2A affects Wnt signaling both positively and negatively and at multiple levels, further understanding of this complex dynamic may ultimately provide insight into stem cell biology and how to better treat cancers that result from alterations in Wnt signaling. This review will summarize literature that implicates PP2A as a tumor suppressor, explore PP2A mutations identified in human malignancy, and focus on PP2A in the regulation of Wnt signaling and stem cells so as to better understand how aberrancy in this pathway can contribute to tumorigenesis.

  14. Recurrence network analysis of experimental signals from bubbly oil-in-water flows

    International Nuclear Information System (INIS)

    Gao, Zhong-Ke; Zhang, Xin-Wang; Du, Meng; Jin, Ning-De

    2013-01-01

    Based on the signals from oil–water two-phase flow experiment, we construct and analyze recurrence networks to characterize the dynamic behavior of different flow patterns. We first take a chaotic time series as an example to demonstrate that the local property of recurrence network allows characterizing chaotic dynamics. Then we construct recurrence networks for different oil-in-water flow patterns and investigate the local property of each constructed network, respectively. The results indicate that the local topological statistic of recurrence network is very sensitive to the transitions of flow patterns and allows uncovering the dynamic flow behavior associated with chaotic unstable periodic orbits.

  15. Effect of placement of droop based generators in distribution network on small signal stability margin and network loss

    DEFF Research Database (Denmark)

    Dheer, D.K.; Doolla, S.; Bandyopadhyay, S.

    2017-01-01

    loss and stability margin is further investigated by identifying the Pareto fronts for modified IEEE 13 bus, IEEE 33 and practical 22-bus radial distribution network with application of Reference point based Non-dominated Sorting Genetic Algorithm (R-NSGA). Results were validated by time domain......For a utility-connected system, issues related to small signal stability with Distributed Generators (DGs) are insignificant due to the presence of a very strong grid. Optimally placed sources in utility connected microgrid system may not be optimal/stable in islanded condition. Among others issues......, small signal stability margin is on the fore. The present research studied the effect of location of droop-controlled DGs on small signal stability margin and network loss on a modified IEEE 13 bus system, an IEEE 33-bus distribution system and a practical 22-bus radial distribution network. A complete...

  16. In-silico prediction of drug targets, biological activities, signal pathways and regulating networks of dioscin based on bioinformatics.

    Science.gov (United States)

    Yin, Lianhong; Zheng, Lingli; Xu, Lina; Dong, Deshi; Han, Xu; Qi, Yan; Zhao, Yanyan; Xu, Youwei; Peng, Jinyong

    2015-03-05

    Inverse docking technology has been a trend of drug discovery, and bioinformatics approaches have been used to predict target proteins, biological activities, signal pathways and molecular regulating networks affected by drugs for further pharmacodynamic and mechanism studies. In the present paper, inverse docking technology was applied to screen potential targets from potential drug target database (PDTD). Then, the corresponding gene information of the obtained drug-targets was applied to predict the related biological activities, signal pathways and processes networks of the compound by using MetaCore platform. After that, some most relevant regulating networks were considered, which included the nodes and relevant pathways of dioscin. 71 potential targets of dioscin from humans, 7 from rats and 8 from mice were screened, and the prediction results showed that the most likely targets of dioscin were cyclin A2, calmodulin, hemoglobin subunit beta, DNA topoisomerase I, DNA polymerase lambda, nitric oxide synthase and UDP-N-acetylhexosamine pyrophosphorylase, etc. Many diseases including experimental autoimmune encephalomyelitis of human, temporal lobe epilepsy of rat and ankylosing spondylitis of mouse, may be inhibited by dioscin through regulating immune response alternative complement pathway, G-protein signaling RhoB regulation pathway and immune response antiviral actions of interferons, etc. The most relevant networks (5 from human, 3 from rat and 5 from mouse) indicated that dioscin may be a TOP1 inhibitor, which can treat cancer though the cell cycle- transition and termination of DNA replication pathway. Dioscin can down regulate EGFR and EGF to inhibit cancer, and also has anti-inflammation activity by regulating JNK signaling pathway. The predictions of the possible targets, biological activities, signal pathways and relevant regulating networks of dioscin provide valuable information to guide further investigation of dioscin on pharmacodynamics and

  17. Similarity in gene-regulatory networks suggests that cancer cells share characteristics of embryonic neural cells.

    Science.gov (United States)

    Zhang, Zan; Lei, Anhua; Xu, Liyang; Chen, Lu; Chen, Yonglong; Zhang, Xuena; Gao, Yan; Yang, Xiaoli; Zhang, Min; Cao, Ying

    2017-08-04

    Cancer cells are immature cells resulting from cellular reprogramming by gene misregulation, and redifferentiation is expected to reduce malignancy. It is unclear, however, whether cancer cells can undergo terminal differentiation. Here, we show that inhibition of the epigenetic modification enzyme enhancer of zeste homolog 2 (EZH2), histone deacetylases 1 and 3 (HDAC1 and -3), lysine demethylase 1A (LSD1), or DNA methyltransferase 1 (DNMT1), which all promote cancer development and progression, leads to postmitotic neuron-like differentiation with loss of malignant features in distinct solid cancer cell lines. The regulatory effect of these enzymes in neuronal differentiation resided in their intrinsic activity in embryonic neural precursor/progenitor cells. We further found that a major part of pan-cancer-promoting genes and the signal transducers of the pan-cancer-promoting signaling pathways, including the epithelial-to-mesenchymal transition (EMT) mesenchymal marker genes, display neural specific expression during embryonic neurulation. In contrast, many tumor suppressor genes, including the EMT epithelial marker gene that encodes cadherin 1 ( CDH1 ), exhibited non-neural or no expression. This correlation indicated that cancer cells and embryonic neural cells share a regulatory network, mediating both tumorigenesis and neural development. This observed similarity in regulatory mechanisms suggests that cancer cells might share characteristics of embryonic neural cells. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  18. Surface code—biophysical signals for apoptotic cell clearance

    International Nuclear Information System (INIS)

    Biermann, Mona; Maueröder, Christian; Brauner, Jan M; Chaurio, Ricardo; Herrmann, Martin; Muñoz, Luis E; Janko, Christina

    2013-01-01

    Apoptotic cell death and the clearance of dying cells play an important and physiological role in embryonic development and normal tissue turnover. In contrast to necrosis, apoptosis proceeds in an anti-inflammatory manner. It is orchestrated by the timed release and/or exposure of so-called ‘find-me’, ‘eat me’ and ‘tolerate me’ signals. Mononuclear phagocytes are attracted by various ‘find-me’ signals, including proteins, nucleotides, and phospholipids released by the dying cell, whereas the involvement of granulocytes is prevented via ‘stay away’ signals. The exposure of anionic phospholipids like phosphatidylserine (PS) by apoptotic cells on the outer leaflet of the plasma membrane is one of the main ‘eat me’ signals. PS is recognized by a number of innate receptors as well as by soluble bridging molecules on the surface of phagocytes. Importantly, phagocytes are able to discriminate between viable and apoptotic cells both exposing PS. Due to cytoskeleton remodeling PS has a higher lateral mobility on the surfaces of apoptotic cells thereby promoting receptor clustering on the phagocyte. PS not only plays an important role in the engulfment process, but also acts as ‘tolerate me’ signal inducing the release of anti-inflammatory cytokines by phagocytes. An efficient and fast clearance of apoptotic cells is required to prevent secondary necrosis and leakage of intracellular danger signals into the surrounding tissue. Failure or prolongation of the clearance process leads to the release of intracellular antigens into the periphery provoking inflammation and development of systemic inflammatory autoimmune disease like systemic lupus erythematosus. Here we review the current findings concerning apoptosis-inducing pathways, important players of apoptotic cell recognition and clearance as well as the role of membrane remodeling in the engulfment of apoptotic cells by phagocytes. (paper)

  19. Array signal processing in the NASA Deep Space Network

    Science.gov (United States)

    Pham, Timothy T.; Jongeling, Andre P.

    2004-01-01

    In this paper, we will describe the benefits of arraying and past as well as expected future use of this application. The signal processing aspects of array system are described. Field measurements via actual tracking spacecraft are also presented.

  20. Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

    KAUST Repository

    Onesto, Valentina

    2016-05-10

    Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect.

  1. Hydrogen peroxide as a signal controlling plant programmed cell death

    NARCIS (Netherlands)

    Gechev, Tsanko S.; Hille, Jacques

    2005-01-01

    Hydrogen peroxide (H2O2) has established itself as a key player in stress and programmed cell death responses, but little is known about the signaling pathways leading from H2O2 to programmed cell death in plants. Recently, identification of key regulatory mutants and near-full genome coverage

  2. BMP signalling differentially regulates distinct haematopoietic stem cell types

    NARCIS (Netherlands)

    M. Crisan (Mihaela); P. Solaimani Kartalaei (Parham); C.S. Vink (Chris); T. Yamada-Inagawa (Tomoko); K. Bollerot (Karine); W.F.J. van IJcken (Wilfred); R. Van Der Linden (Reinier); S.C. de Sousa Lopes (Susana Chuva); R. Monteiro (Rui); C.L. Mummery (Christine); E.A. Dzierzak (Elaine)

    2015-01-01

    textabstractAdult haematopoiesis is the outcome of distinct haematopoietic stem cell (HSC) subtypes with self-renewable repopulating ability, but with different haematopoietic cell lineage outputs. The molecular basis for this heterogeneity is largely unknown. BMP signalling regulates HSCs as they

  3. Discrimination of Cylinders with Different Wall Thicknesses using Neural Networks and Simulated Dolphin Sonar Signals

    DEFF Research Database (Denmark)

    Andersen, Lars Nonboe; Au, Whitlow; Larsen, Jan

    1999-01-01

    This paper describes a method integrating neural networks into a system for recognizing underwater objects. The system is based on a combination of simulated dolphin sonar signals, simulated auditory filters and artificial neural networks. The system is tested on a cylinder wall thickness...

  4. Chemoattractant signaling between tumor cells and macrophages regulates cancer cell migration, metastasis and neovascularization.

    Directory of Open Access Journals (Sweden)

    Chad E Green

    2009-08-01

    Full Text Available Tumor-associated macrophages are known to influence cancer progression by modulation of immune function, angiogenesis, and cell metastasis, however, little is known about the chemokine signaling networks that regulate this process. Utilizing CT26 colon cancer cells and RAW 264.7 macrophages as a model cellular system, we demonstrate that treatment of CT26 cells with RAW 264.7 conditioned medium induces cell migration, invasion and metastasis. Inflammatory gene microarray analysis indicated CT26-stimulated RAW 264.7 macrophages upregulate SDF-1alpha and VEGF, and that these cytokines contribute to CT26 migration in vitro. RAW 264.7 macrophages also showed a robust chemotactic response towards CT26-derived chemokines. In particular, microarray analysis and functional testing revealed CSF-1 as the major chemoattractant for RAW 264.7 macrophages. Interestingly, in the chick CAM model of cancer progression, RAW 264.7 macrophages localized specifically to the tumor periphery where they were found to increase CT26 tumor growth, microvascular density, vascular disruption, and lung metastasis, suggesting these cells home to actively invading areas of the tumor, but not the hypoxic core of the tumor mass. In support of these findings, hypoxic conditions down regulated CSF-1 production in several tumor cell lines and decreased RAW 264.7 macrophage migration in vitro. Together our findings suggest a model where normoxic tumor cells release CSF-1 to recruit macrophages to the tumor periphery where they secrete motility and angiogenic factors that facilitate tumor cell invasion and metastasis.

  5. A TDoA Localization Scheme for Underwater Sensor Networks with Use of Multilinear Chirp Signals

    Directory of Open Access Journals (Sweden)

    En Cheng

    2016-01-01

    Full Text Available Due to the multipath, Doppler, and other effects, the node location signals have high probability of access collision in the underwater acoustic sensor networks (UW-ASNs, and therefore, it causes the signal lost and the access block; therefore, it constrains the networks performance. In this paper, we take the multilinear chirp (MLC signals as the location signal to improve the anticollision ability. In order to increase the detection efficiency of MLC, we propose a fast efficient detection method called mixing change rate-fractional Fourier transform (MCR-FrFT. This method transforms the combined rates of MLC into symmetry triangle rates and then separates the multiuser signals based on the transformed rates by using FrFT. Theoretical derivation and simulation results show that the proposed method can detect the locations signals, estimate the time difference of arrival (TDoA, reduce the multiple access interference, and improve the location performance.

  6. Mast cell chemotaxis - chemoattractants and signaling pathways

    Czech Academy of Sciences Publication Activity Database

    Hálová, Ivana; Dráberová, Lubica; Dráber, Petr

    2012-01-01

    Roč. 3, May (2012), s. 119 ISSN 1664-3224 R&D Projects: GA MŠk LD12073; GA ČR GA301/09/1826; GA ČR GAP302/10/1759 Grant - others:ECST(XE) BM1007; AV ČR(CZ) MC200520901 Institutional support: RVO:68378050 Keywords : mast cell * IgE receptor * plasma membrane Subject RIV: EB - Genetics ; Molecular Biology

  7. Alteration of canonical and non-canonical WNT-signaling by crystalline silica in human lung epithelial cells

    International Nuclear Information System (INIS)

    Perkins, Timothy N.; Dentener, Mieke A.; Stassen, Frank R.; Rohde, Gernot G.; Mossman, Brooke T.; Wouters, Emiel F.M.; Reynaert, Niki L.

    2016-01-01

    Growth and development of the mature lung is a complex process orchestrated by a number of intricate developmental signaling pathways. Wingless-type MMTV-integration site (WNT) signaling plays critical roles in controlling branching morphogenesis cell differentiation, and formation of the conducting and respiratory airways. In addition, WNT pathways are often re-activated in mature lungs during repair and regeneration. WNT- signaling has been elucidated as a crucial contributor to the development of idiopathic pulmonary fibrosis as well as other hyper-proliferative lung diseases. Silicosis, a detrimental occupational lung disease caused by excessive inhalation of crystalline silica dust, is hallmarked by repeated cycles of damaging inflammation, epithelial hyperplasia, and formation of dense, hyalinized nodules of whorled collagen. However, mechanisms of epithelial cell hyperplasia and matrix deposition are not well understood, as most research efforts have focused on the pronounced inflammatory response. Microarray data from our previous studies has revealed a number of WNT-signaling and WNT-target genes altered by crystalline silica in human lung epithelial cells. In the present study, we utilize pathway analysis to designate connections between genes altered by silica in WNT-signaling networks. Furthermore, we confirm microarray findings by QRT-PCR and demonstrate both activation of canonical (β-catenin) and down-regulation of non-canonical (WNT5A) signaling in immortalized (BEAS-2B) and primary (PBEC) human bronchial epithelial cells. These findings suggest that WNT-signaling and cross-talk with other pathways (e.g. Notch), may contribute to proliferative, fibrogenic and inflammatory responses to silica in lung epithelial cells. - Highlights: • Pathway analysis reveals silica-induced WNT-signaling in lung epithelial cells. • Silica-induced canonical WNT-signaling is mediated by autocrine/paracrine signals. • Crystalline silica decreases non-canonical WNT

  8. Network evolution: rewiring and signatures of conservation in signaling.

    Directory of Open Access Journals (Sweden)

    Mark G F Sun

    Full Text Available The analysis of network evolution has been hampered by limited availability of protein interaction data for different organisms. In this study, we investigate evolutionary mechanisms in Src Homology 3 (SH3 domain and kinase interaction networks using high-resolution specificity profiles. We constructed and examined networks for 23 fungal species ranging from Saccharomyces cerevisiae to Schizosaccharomyces pombe. We quantify rates of different rewiring mechanisms and show that interaction change through binding site evolution is faster than through gene gain or loss. We found that SH3 interactions evolve swiftly, at rates similar to those found in phosphoregulation evolution. Importantly, we show that interaction changes are sufficiently rapid to exhibit saturation phenomena at the observed timescales. Finally, focusing on the SH3 interaction network, we observe extensive clustering of binding sites on target proteins by SH3 domains and a strong correlation between the number of domains that bind a target protein (target in-degree and interaction conservation. The relationship between in-degree and interaction conservation is driven by two different effects, namely the number of clusters that correspond to interaction interfaces and the number of domains that bind to each cluster leads to sequence specific conservation, which in turn results in interaction conservation. In summary, we uncover several network evolution mechanisms likely to generalize across peptide recognition modules.

  9. The highly buffered Arabidopsis immune signaling network conceals the functions of its components.

    Directory of Open Access Journals (Sweden)

    Rachel A Hillmer

    2017-05-01

    Full Text Available Plant immunity protects plants from numerous potentially pathogenic microbes. The biological network that controls plant inducible immunity must function effectively even when network components are targeted and disabled by pathogen effectors. Network buffering could confer this resilience by allowing different parts of the network to compensate for loss of one another's functions. Networks rich in buffering rely on interactions within the network, but these mechanisms are difficult to study by simple genetic means. Through a network reconstitution strategy, in which we disassemble and stepwise reassemble the plant immune network that mediates Pattern-Triggered-Immunity, we have resolved systems-level regulatory mechanisms underlying the Arabidopsis transcriptome response to the immune stimulant flagellin-22 (flg22. These mechanisms show widespread evidence of interactions among major sub-networks-we call these sectors-in the flg22-responsive transcriptome. Many of these interactions result in network buffering. Resolved regulatory mechanisms show unexpected patterns for how the jasmonate (JA, ethylene (ET, phytoalexin-deficient 4 (PAD4, and salicylate (SA signaling sectors control the transcriptional response to flg22. We demonstrate that many of the regulatory mechanisms we resolved are not detectable by the traditional genetic approach of single-gene null-mutant analysis. Similar to potential pathogenic perturbations, null-mutant effects on immune signaling can be buffered by the network.

  10. Dynamic probabilistic threshold networks to infer signaling pathways from time-course perturbation data.

    Science.gov (United States)

    Kiani, Narsis A; Kaderali, Lars

    2014-07-22

    Network inference deals with the reconstruction of molecular networks from experimental data. Given N molecular species, the challenge is to find the underlying network. Due to data limitations, this typically is an ill-posed problem, and requires the integration of prior biological knowledge or strong regularization. We here focus on the situation when time-resolved measurements of a system's response after systematic perturbations are available. We present a novel method to infer signaling networks from time-course perturbation data. We utilize dynamic Bayesian networks with probabilistic Boolean threshold functions to describe protein activation. The model posterior distribution is analyzed using evolutionary MCMC sampling and subsequent clustering, resulting in probability distributions over alternative networks. We evaluate our method on simulated data, and study its performance with respect to data set size and levels of noise. We then use our method to study EGF-mediated signaling in the ERBB pathway. Dynamic Probabilistic Threshold Networks is a new method to infer signaling networks from time-series perturbation data. It exploits the dynamic response of a system after external perturbation for network reconstruction. On simulated data, we show that the approach outperforms current state of the art methods. On the ERBB data, our approach recovers a significant fraction of the known interactions, and predicts novel mechanisms in the ERBB pathway.

  11. Topology of the network integrating salicylate and jasmonate signal transduction derived from global expression phenotyping.

    Science.gov (United States)

    Glazebrook, Jane; Chen, Wenqiong; Estes, Bram; Chang, Hur-Song; Nawrath, Christiane; Métraux, Jean-Pierre; Zhu, Tong; Katagiri, Fumiaki

    2003-04-01

    The signal transduction network controlling plant responses to pathogens includes pathways requiring the signal molecules salicylic acid (SA), jasmonic acid (JA), and ethylene (ET). The network topology was explored using global expression phenotyping of wild-type and signaling-defective mutant plants, including eds3, eds4, eds5, eds8, pad1, pad2, pad4, NahG, npr1, sid2, ein2, and coi1. Hierarchical clustering was used to define groups of mutations with similar effects on gene expression and groups of similarly regulated genes. Mutations affecting SA signaling formed two groups: one comprised of eds4, eds5, sid2, and npr1-3 affecting only SA signaling; and the other comprised of pad2, eds3, npr1-1, pad4, and NahG affecting SA signaling as well as another unknown process. Major differences between the expression patterns in NahG and the SA biosynthetic mutant sid2 suggest that NahG has pleiotropic effects beyond elimination of SA. A third group of mutants comprised of eds8, pad1, ein2, and coi1 affected ethylene and jasmonate signaling. Expression patterns of some genes revealed mutual inhibition between SA- and JA-dependent signaling, while other genes required JA and ET signaling as well as the unknown signaling process for full expression. Global expression phenotype similarities among mutants suggested, and experiments confirmed, that EDS3 affects SA signaling while EDS8 and PAD1 affect JA signaling. This work allowed modeling of network topology, definition of co-regulated genes, and placement of previously uncharacterized regulatory genes in the network.

  12. Influence of smartphone Wi-Fi signals on adipose-derived stem cells.

    Science.gov (United States)

    Lee, Sang-Soon; Kim, Hyung-Rok; Kim, Min-Sook; Park, Sanghoon; Yoon, Eul-Sik; Park, Seung-Ha; Kim, Deok-Woo

    2014-09-01

    The use of smartphones is expanding rapidly around the world, thus raising the concern of possible harmful effects of radiofrequency generated by smartphones. We hypothesized that Wi-Fi signals from smartphones may have harmful influence on adipose-derived stem cells (ASCs). An in vitro study was performed to assess the influence of Wi-Fi signals from smartphones. The ASCs were incubated under a smartphone connected to a Wi-Fi network, which was uploading files at a speed of 4.8 Mbps for 10 hours a day, for a total of 5 days. We constructed 2 kinds of control cells, one grown in 37°C and the other grown in 39°C. After 5 days of Wi-Fi exposure from the smartphone, the cells underwent cell proliferation assay, apoptosis assay, and flow cytometry analysis. Three growth factors, vascular endothelial growth factor, hepatocyte growth factor, and transforming growth factor-β, were measured from ASC-conditioned media. Cell proliferation rate was higher in Wi-Fi-exposed cells and 39°C control cells compared with 37°C control cells. Apoptosis assay, flow cytometry analysis, and growth factor concentrations showed no remarkable differences among the 3 groups. We could not find any harmful effects of Wi-Fi electromagnetic signals from smartphones. The increased proliferation of ASCs under the smartphone, however, might be attributable to the thermal effect.

  13. The Reticular Cell Network : A Robust Backbone for Immune Responses

    NARCIS (Netherlands)

    Textor, Johannes; Mandl, Judith N; de Boer, Rob J

    2016-01-01

    Lymph nodes are meeting points for circulating immune cells. A network of reticular cells that ensheathe a mesh of collagen fibers crisscrosses the tissue in each lymph node. This reticular cell network distributes key molecules and provides a structure for immune cells to move around on. During

  14. Integrating signals from the T-cell receptor and the interleukin-2 receptor.

    Directory of Open Access Journals (Sweden)

    Tilo Beyer

    2011-08-01

    Full Text Available T cells orchestrate the adaptive immune response, making them targets for immunotherapy. Although immunosuppressive therapies prevent disease progression, they also leave patients susceptible to opportunistic infections. To identify novel drug targets, we established a logical model describing T-cell receptor (TCR signaling. However, to have a model that is able to predict new therapeutic approaches, the current drug targets must be included. Therefore, as a next step we generated the interleukin-2 receptor (IL-2R signaling network and developed a tool to merge logical models. For IL-2R signaling, we show that STAT activation is independent of both Src- and PI3-kinases, while ERK activation depends upon both kinases and additionally requires novel PKCs. In addition, our merged model correctly predicted TCR-induced STAT activation. The combined network also allows information transfer from one receptor to add detail to another, thereby predicting that LAT mediates JNK activation in IL-2R signaling. In summary, the merged model not only enables us to unravel potential cross-talk, but it also suggests new experimental designs and provides a critical step towards designing strategies to reprogram T cells.

  15. Proceedings of the IEEE 2003 Neural Networks for Signal Processing Workshop

    DEFF Research Database (Denmark)

    Larsen, Jan

    adaptive signal/image processing, machine learning, and statistics in order to solve complex real-world signal processing applications. This year, two topics attracting particular interest were presented at two special sessions; one on bioinformatics and a second one on space and aeronautics. High quality...... methodology and real-world application domains and is widely entering into everyday solutions adopted by research and industry, going far beyond “traditional” neural networks and academic examples. As reflected in this collection, contemporary neural networks for signal processing combine many ideas from...

  16. Intelligent Noise Removal from EMG Signal Using Focused Time-Lagged Recurrent Neural Network

    Directory of Open Access Journals (Sweden)

    S. N. Kale

    2009-01-01

    Full Text Available Electromyography (EMG signals can be used for clinical/biomedical application and modern human computer interaction. EMG signals acquire noise while traveling through tissue, inherent noise in electronics equipment, ambient noise, and so forth. ANN approach is studied for reduction of noise in EMG signal. In this paper, it is shown that Focused Time-Lagged Recurrent Neural Network (FTLRNN can elegantly solve to reduce the noise from EMG signal. After rigorous computer simulations, authors developed an optimal FTLRNN model, which removes the noise from the EMG signal. Results show that the proposed optimal FTLRNN model has an MSE (Mean Square Error as low as 0.000067 and 0.000048, correlation coefficient as high as 0.99950 and 0.99939 for noise signal and EMG signal, respectively, when validated on the test dataset. It is also noticed that the output of the estimated FTLRNN model closely follows the real one. This network is indeed robust as EMG signal tolerates the noise variance from 0.1 to 0.4 for uniform noise and 0.30 for Gaussian noise. It is clear that the training of the network is independent of specific partitioning of dataset. It is seen that the performance of the proposed FTLRNN model clearly outperforms the best Multilayer perceptron (MLP and Radial Basis Function NN (RBF models. The simple NN model such as the FTLRNN with single-hidden layer can be employed to remove noise from EMG signal.

  17. Single-cell analysis of G-protein signal transduction.

    Science.gov (United States)

    Clister, Terri; Mehta, Sohum; Zhang, Jin

    2015-03-13

    The growing use of fluorescent biosensors to directly probe the spatiotemporal dynamics of biochemical processes in living cells has revolutionized the study of intracellular signaling. In this review, we summarize recent developments in the use of biosensors to illuminate the molecular details of G-protein-coupled receptor (GPCR) signaling pathways, which have long served as the model for our understanding of signal transduction, while also offering our perspectives on the future of this exciting field. Specifically, we highlight several ways in which biosensor-based single-cell analyses are being used to unravel many of the enduring mysteries that surround these diverse signaling pathways. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  18. Information transmission and signal permutation in active flow networks

    Science.gov (United States)

    Woodhouse, Francis G.; Fawcett, Joanna B.; Dunkel, Jörn

    2018-03-01

    Recent experiments show that both natural and artificial microswimmers in narrow channel-like geometries will self-organise to form steady, directed flows. This suggests that networks of flowing active matter could function as novel autonomous microfluidic devices. However, little is known about how information propagates through these far-from-equilibrium systems. Through a mathematical analogy with spin-ice vertex models, we investigate here the input–output characteristics of generic incompressible active flow networks (AFNs). Our analysis shows that information transport through an AFN is inherently different from conventional pressure or voltage driven networks. Active flows on hexagonal arrays preserve input information over longer distances than their passive counterparts and are highly sensitive to bulk topological defects, whose presence can be inferred from marginal input–output distributions alone. This sensitivity further allows controlled permutations on parallel inputs, revealing an unexpected link between active matter and group theory that can guide new microfluidic mixing strategies facilitated by active matter and aid the design of generic autonomous information transport networks.

  19. Neural network analysis of vibration signals in the diagnostics of ...

    African Journals Online (AJOL)

    They studied steel pipes filled with water, the surface of which 50x50 mm defect and the depth of thinning of 2 mm, 3 mm, and 5 mm. Using the ... The results of the classification by Kohonen's trained neural network show good abilities for the analysis of unknown samples and a high degree of their recognition reliability.

  20. Glycosynapses: microdomains controlling carbohydrate-dependent cell adhesion and signaling

    OpenAIRE

    Hakomori Senitiroh

    2004-01-01

    The concept of microdomains in plasma membranes was developed over two decades, following observation of polarity of membrane based on clustering of specific membrane components. Microdomains involved in carbohydrate-dependent cell adhesion with concurrent signal transduction that affect cellular phenotype are termed "glycosynapse". Three types of glycosynapse have been distinguished: "type 1" having glycosphingolipid associated with signal transducers (small G-proteins, cSrc, Src family kina...

  1. Exploring signal transduction networks using mass spectrometry-based proteomics

    NARCIS (Netherlands)

    Meijer, L.A.T.

    2012-01-01

    Mass spectrometry (MS)-based proteomics can be used to answer a diversity of biological questions. In this thesis, we describe the application of several MS-based proteomics approaches to get insight into several aspects of signal transduction. In Chapter 2, quantitative global phosphoproteomics are

  2. Robo signaling regulates the production of cranial neural crest cells.

    Science.gov (United States)

    Li, Yan; Zhang, Xiao-Tan; Wang, Xiao-Yu; Wang, Guang; Chuai, Manli; Münsterberg, Andrea; Yang, Xuesong

    2017-12-01

    Slit/Robo signaling plays an important role in the guidance of developing neurons in developing embryos. However, it remains obscure whether and how Slit/Robo signaling is involved in the production of cranial neural crest cells. In this study, we examined Robo1 deficient mice to reveal developmental defects of mouse cranial frontal and parietal bones, which are derivatives of cranial neural crest cells. Therefore, we determined the production of HNK1 + cranial neural crest cells in early chick embryo development after knock-down (KD) of Robo1 expression. Detection of markers for pre-migratory and migratory neural crest cells, PAX7 and AP-2α, showed that production of both was affected by Robo1 KD. In addition, we found that the transcription factor slug is responsible for the aberrant delamination/EMT of cranial neural crest cells induced by Robo1 KD, which also led to elevated expression of E- and N-Cadherin. N-Cadherin expression was enhanced when blocking FGF signaling with dominant-negative FGFR1 in half of the neural tube. Taken together, we show that Slit/Robo signaling influences the delamination/EMT of cranial neural crest cells, which is required for cranial bone development. Copyright © 2017. Published by Elsevier Inc.

  3. Convergent Evolution of Pathogen Effectors toward Reactive Oxygen Species Signaling Networks in Plants

    Directory of Open Access Journals (Sweden)

    Nam-Soo Jwa

    2017-09-01

    Full Text Available Microbial pathogens have evolved protein effectors to promote virulence and cause disease in host plants. Pathogen effectors delivered into plant cells suppress plant immune responses and modulate host metabolism to support the infection processes of pathogens. Reactive oxygen species (ROS act as cellular signaling molecules to trigger plant immune responses, such as pathogen-associated molecular pattern (PAMP-triggered immunity (PTI and effector-triggered immunity. In this review, we discuss recent insights into the molecular functions of pathogen effectors that target multiple steps in the ROS signaling pathway in plants. The perception of PAMPs by pattern recognition receptors leads to the rapid and strong production of ROS through activation of NADPH oxidase Respiratory Burst Oxidase Homologs (RBOHs as well as peroxidases. Specific pathogen effectors directly or indirectly interact with plant nucleotide-binding leucine-rich repeat receptors to induce ROS production and the hypersensitive response in plant cells. By contrast, virulent pathogens possess effectors capable of suppressing plant ROS bursts in different ways during infection. PAMP-triggered ROS bursts are suppressed by pathogen effectors that target mitogen-activated protein kinase cascades. Moreover, pathogen effectors target vesicle trafficking or metabolic priming, leading to the suppression of ROS production. Secreted pathogen effectors block the metabolic coenzyme NADP-malic enzyme, inhibiting the transfer of electrons to the NADPH oxidases (RBOHs responsible for ROS generation. Collectively, pathogen effectors may have evolved to converge on a common host protein network to suppress the common plant immune system, including the ROS burst and cell death response in plants.

  4. AlliedSignal solid oxide fuel cell technology

    Energy Technology Data Exchange (ETDEWEB)

    Minh, N.; Barr, K.; Kelly, P.; Montgomery, K. [AlliedSignal Aerospace Equipment Systems, Torrance, CA (United States)

    1996-12-31

    AlliedSignal has been developing high-performance, lightweight solid oxide fuel cell (SOFC) technology for a broad spectrum of electric power generation applications. This technology is well suited for use in a variety of power systems, ranging from commercial cogeneration to military mobile power sources. The AlliedSignal SOFC is based on stacking high-performance thin-electrolyte cells with lightweight metallic interconnect assemblies to form a compact structure. The fuel cell can be operated at reduced temperatures (600{degrees} to 800{degrees}C). SOFC stacks based on this design has the potential of producing 1 kW/kg and 1 ML. This paper summarizes the technical status of the design, manufacture, and operation of AlliedSignal SOFCs.

  5. Cell wall integrity signalling in human pathogenic fungi.

    Science.gov (United States)

    Dichtl, Karl; Samantaray, Sweta; Wagener, Johannes

    2016-09-01

    Fungi are surrounded by a rigid structure, the fungal cell wall. Its plasticity and composition depend on active regulation of the underlying biosynthesis and restructuring processes. This involves specialised signalling pathways that control gene expression and activities of biosynthetic enzymes. The cell wall integrity (CWI) pathway is the central signalling cascade required for the adaptation to a wide spectrum of cell wall perturbing conditions, including heat, oxidative stress and antifungals. In the recent years, great efforts were made to analyse the CWI pathway of diverse fungi. It turned out that the CWI signalling cascade is mostly conserved in the fungal kingdom. In this review, we summarise as well as compare the current knowledge on the canonical CWI pathway in the human pathogenic fungi Candida albicans, Candida glabrata, Aspergillus fumigatus and Cryptococcus neoformans. Understanding the differences and similarities in the stress responses of these organisms could become a key to improving existing or developing new antifungal therapies. © 2016 John Wiley & Sons Ltd.

  6. Protein conservation and variation suggest mechanisms of cell type-specific modulation of signaling pathways.

    Directory of Open Access Journals (Sweden)

    Martin H Schaefer

    2014-06-01

    Full Text Available Many proteins and signaling pathways are present in most cell types and tissues and yet perform specialized functions. To elucidate mechanisms by which these ubiquitous pathways are modulated, we overlaid information about cross-cell line protein abundance and variability, and evolutionary conservation onto functional pathway components and topological layers in the pathway hierarchy. We found that the input (receptors and the output (transcription factors layers evolve more rapidly than proteins in the intermediary transmission layer. In contrast, protein expression variability decreases from the input to the output layer. We observed that the differences in protein variability between the input and transmission layer can be attributed to both the network position and the tendency of variable proteins to physically interact with constitutively expressed proteins. Differences in protein expression variability and conservation are also accompanied by the tendency of conserved and constitutively expressed proteins to acquire somatic mutations, while germline mutations tend to occur in cell type-specific proteins. Thus, conserved core proteins in the transmission layer could perform a fundamental role in most cell types and are therefore less tolerant to germline mutations. In summary, we propose that the core signal transmission machinery is largely modulated by a variable input layer through physical protein interactions. We hypothesize that the bow-tie organization of cellular signaling on the level of protein abundance variability contributes to the specificity of the signal response in different cell types.

  7. Network dynamics determine the autocrine and paracrine signaling functions of TNF

    Science.gov (United States)

    Caldwell, Andrew B.; Cheng, Zhang; Vargas, Jesse D.; Birnbaum, Harry A.

    2014-01-01

    A hallmark of the inflammatory response to pathogen exposure is the production of tumor necrosis factor (TNF) that coordinates innate and adaptive immune responses by functioning in an autocrine or paracrine manner. Numerous molecular mechanisms contributing to TNF production have been identified, but how they function together in macrophages remains unclear. Here, we pursued an iterative systems biology approach to develop a quantitative understanding of the regulatory modules that control TNF mRNA synthesis and processing, mRNA half-life and translation, and protein processing and secretion. By linking the resulting model of TNF production to models of the TLR-, the TNFR-, and the NFκB signaling modules, we were able to study TNF’s functions during the inflammatory response to diverse TLR agonists. Contrary to expectation, we predicted and then experimentally confirmed that in response to lipopolysaccaride, TNF does not have an autocrine function in amplifying the NFκB response, although it plays a potent paracrine role in neighboring cells. However, in response to CpG DNA, autocrine TNF extends the duration of NFκB activity and shapes CpG-induced gene expression programs. Our systems biology approach revealed that network dynamics of MyD88 and TRIF signaling and of cytokine production and response govern the stimulus-specific autocrine and paracrine functions of TNF. PMID:25274725

  8. Interference Management with Successive Cancellation for Dense Small Cell Networks

    DEFF Research Database (Denmark)

    Lopez, Victor Fernandez; Pedersen, Klaus I.; Steiner, Jens

    2016-01-01

    Network-Assisted Interference Cancellation and Suppression (NAICS) receivers have appeared as a promising way to curb inter-cell interference in future dense network deployments. This investigation compares the performance of a NAICS receiver with successive interference cancellation capabilities...

  9. Apoptosis and signalling in acid sphingomyelinase deficient cells

    Directory of Open Access Journals (Sweden)

    Sillence Dan J

    2001-11-01

    Full Text Available Abstract Background Recent evidence suggests that the activation of a non-specific lipid scramblase during apoptosis induces the flipping of sphingomyelin from the cell surface to the cytoplasmic leaftet of the plasma membrane. Inner leaflet sphingomyelin is then cleaved to ceramide by a neutral sphingomyelinase. The production of this non-membrane forming lipid induces blebbing of the plasma membrane to aid rapid engulfment by professional phagocytes. However contrary evidence suggests that cells which are deficient in acid sphingomyelinase are defective in apoptosis signalling. This data has been interpreted as support for the activation of acid sphingomyelinase as an early signal in apoptosis. Hypothesis An alternative explanation is put forward whereby the accumulation of intracellular sphingomyelin in sphingomyelinase deficient cells leads to the formation of intracellular rafts which lead to the sequestration of important signalling molecules that are normally present on the cell surface where they perform their function. Testing the hypothesis It is expected that the subcellular distribution of important signalling molecules is altered in acid sphingomyelinase deficient cells, leading to their sequestration in late endosomes / lysosomes. Other sphingolipid storage diseases such as Niemann-Pick type C which have normal acid sphingomyelinase activity would also be expected to show the same phenotype. Implications of the hypothesis If true the hypothesis would provide a mechanism for the pathology of the sphingolipid storage diseases at the cellular level and also have implications for the role of ceramide in apoptosis.

  10. Simulation of developing human neuronal cell networks.

    Science.gov (United States)

    Lenk, Kerstin; Priwitzer, Barbara; Ylä-Outinen, Laura; Tietz, Lukas H B; Narkilahti, Susanna; Hyttinen, Jari A K

    2016-08-30

    Microelectrode array (MEA) is a widely used technique to study for example the functional properties of neuronal networks derived from human embryonic stem cells (hESC-NN). With hESC-NN, we can investigate the earliest developmental stages of neuronal network formation in the human brain. In this paper, we propose an in silico model of maturating hESC-NNs based on a phenomenological model called INEX. We focus on simulations of the development of bursts in hESC-NNs, which are the main feature of neuronal activation patterns. The model was developed with data from developing hESC-NN recordings on MEAs which showed increase in the neuronal activity during the investigated six measurement time points in the experimental and simulated data. Our simulations suggest that the maturation process of hESC-NN, resulting in the formation of bursts, can be explained by the development of synapses. Moreover, spike and burst rate both decreased at the last measurement time point suggesting a pruning of synapses as the weak ones are removed. To conclude, our model reflects the assumption that the interaction between excitatory and inhibitory neurons during the maturation of a neuronal network and the spontaneous emergence of bursts are due to increased connectivity caused by the forming of new synapses.

  11. Ground state robustness as an evolutionary design principle in signaling networks.

    Directory of Open Access Journals (Sweden)

    Onder Kartal

    Full Text Available The ability of an organism to survive depends on its capability to adapt to external conditions. In addition to metabolic versatility and efficient replication, reliable signal transduction is essential. As signaling systems are under permanent evolutionary pressure one may assume that their structure reflects certain functional properties. However, despite promising theoretical studies in recent years, the selective forces which shape signaling network topologies in general remain unclear. Here, we propose prevention of autoactivation as one possible evolutionary design principle. A generic framework for continuous kinetic models is used to derive topological implications of demanding a dynamically stable ground state in signaling systems. To this end graph theoretical methods are applied. The index of the underlying digraph is shown to be a key topological property which determines the so-called kinetic ground state (or off-state robustness. The kinetic robustness depends solely on the composition of the subdigraph with the strongly connected components, which comprise all positive feedbacks in the network. The component with the highest index in the feedback family is shown to dominate the kinetic robustness of the whole network, whereas relative size and girth of these motifs are emphasized as important determinants of the component index. Moreover, depending on topological features, the maintenance of robustness differs when networks are faced with structural perturbations. This structural off-state robustness, defined as the average kinetic robustness of a network's neighborhood, turns out to be useful since some structural features are neutral towards kinetic robustness, but show up to be supporting against structural perturbations. Among these are a low connectivity, a high divergence and a low path sum. All results are tested against real signaling networks obtained from databases. The analysis suggests that ground state robustness may

  12. A Stochastic Geometry Framework for LOS/NLOS Propagation in Dense Small Cell Networks

    DEFF Research Database (Denmark)

    Galiotto, Carlo; Kiilerich Pratas, Nuno; Marchetti, Nicola

    2015-01-01

    The need to carry out analytical studies of wireless systems often motivates the usage of simplified models which, despite their tractability, can easily lead to an overestimation of the achievable performance. In the case of dense small cells networks, the standard single slope path-loss model has......-loss model is taken into account. We first propose a stochastic geometry based framework for small cell networks where the signal propagation accounts for both the Line-of-Sight (LOS) and Non-Line-Of-Sight (NLOS) components, such as the model provided by the 3GPP for evaluation of pico-cells in Heterogeneous...

  13. Protein kinase C signaling and cell cycle regulation

    Directory of Open Access Journals (Sweden)

    Adrian R Black

    2013-01-01

    Full Text Available A link between T cell proliferation and the protein kinase C (PKC family of serine/threonine kinases has been recognized for about thirty years. However, despite the wealth of information on PKC-mediated control of T cell activation, understanding of the effects of PKCs on the cell cycle machinery in this cell type remains limited. Studies in other systems have revealed important cell cycle-specific effects of PKC signaling that can either positively or negatively impact proliferation. The outcome of PKC activation is highly context-dependent, with the precise cell cycle target(s and overall effects determined by the specific isozyme involved, the timing of PKC activation, the cell type, and the signaling environment. Although PKCs can regulate all stages of the cell cycle, they appear to predominantly affect G0/G1 and G2. PKCs can modulate multiple cell cycle regulatory molecules, including cyclins, cyclin-dependent kinases (cdks, cdk inhibitors and cdc25 phosphatases; however, evidence points to Cip/Kip cdk inhibitors and D-type cyclins as key mediators of PKC-regulated cell cycle-specific effects. Several PKC isozymes can target Cip/Kip proteins to control G0/G1→S and/or G2→M transit, while effects on D-type cyclins regulate entry into and progression through G1. Analysis of PKC signaling in T cells has largely focused on its roles in T cell activation; thus, observed cell cycle effects are mainly positive. A prominent role is emerging for PKCθ, with non-redundant functions of other isozymes also described. Additional evidence points to PKCδ as a negative regulator of the cell cycle in these cells. As in other cell types, context-dependent effects of individual isozymes have been noted in T cells, and Cip/Kip cdk inhibitors and D-type cyclins appear to be major PKC targets. Future studies are anticipated to take advantage of the similarities between these various systems to enhance understanding of PKC-mediated cell cycle regulation in

  14. Reward processing in the value-driven attention network: reward signals tracking cue identity and location.

    Science.gov (United States)

    Anderson, Brian A

    2017-03-01

    Through associative reward learning, arbitrary cues acquire the ability to automatically capture visual attention. Previous studies have examined the neural correlates of value-driven attentional orienting, revealing elevated activity within a network of brain regions encompassing the visual corticostriatal loop [caudate tail, lateral occipital complex (LOC) and early visual cortex] and intraparietal sulcus (IPS). Such attentional priority signals raise a broader question concerning how visual signals are combined with reward signals during learning to create a representation that is sensitive to the confluence of the two. This study examines reward signals during the cued reward training phase commonly used to generate value-driven attentional biases. High, compared with low, reward feedback preferentially activated the value-driven attention network, in addition to regions typically implicated in reward processing. Further examination of these reward signals within the visual system revealed information about the identity of the preceding cue in the caudate tail and LOC, and information about the location of the preceding cue in IPS, while early visual cortex represented both location and identity. The results reveal teaching signals within the value-driven attention network during associative reward learning, and further suggest functional specialization within different regions of this network during the acquisition of an integrated representation of stimulus value. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  15. Compartmentalized Signaling in Neurons: From Cell Biology to Neuroscience.

    Science.gov (United States)

    Terenzio, Marco; Schiavo, Giampietro; Fainzilber, Mike

    2017-11-01

    Neurons are the largest known cells, with complex and highly polarized morphologies. As such, neuronal signaling is highly compartmentalized, requiring sophisticated transfer mechanisms to convey and integrate information within and between sub-neuronal compartments. Here, we survey different modes of compartmentalized signaling in neurons, highlighting examples wherein the fundamental cell biological processes of protein synthesis and degradation, membrane trafficking, and organelle transport are employed to enable the encoding and integration of information, locally and globally within a neuron. Comparisons to other cell types indicate that neurons accentuate widely shared mechanisms, providing invaluable models for the compartmentalization and transfer mechanisms required and used by most eukaryotic cells. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Acute Aldosterone-mediated Signaling Networks in Distal Convoluted Tubules

    DEFF Research Database (Denmark)

    Cheng, Lei; Wu, Qi; Olesen, Emma T. B.

    2017-01-01

    The kidney distal convoluted tubule (DCT) plays an important role in modulating body sodium balance and blood pressure. Long-term effects of aldosterone to increase sodium reabsorption in the DCT are well described. However, potential effects of aldosterone to acutely modulate DCT function via non...... in abundance following aldosterone treatment. The EGFR, ERK1/2, AKT, GSK3B and P70S6K were predicted to be important pathway nodes based on the quantitative proteomics data using network analysis. Ex vivo studies in isolated mouse cortical tubules demonstrated an increase in phosphorylated (active) NCC...

  17. Signal peptide of eosinophil cationic protein is toxic to cells lacking signal peptide peptidase

    International Nuclear Information System (INIS)

    Wu, C.-M.; Chang, Margaret Dah-Tsyr

    2004-01-01

    Eosinophil cationic protein (ECP) is a toxin secreted by activated human eosinophils. The properties of mature ECP have been well studied but those of the signal peptide of ECP (ECPsp) are not clear. In this study, several chimeric proteins containing N-terminal fusion of ECPsp were generated, and introduced into Escherichia coli, Pichia pastoris, and human epidermoid carcinoma cell line A431 to study the function of ECPsp. We found that expression of ECPsp chimeric proteins inhibited the growth of E. coli and P. pastoris but not A431 cells. Primary sequence analysis and in vitro transcription/translation of ECPsp have revealed that it is a potential substrate for human signal peptide peptidase (hSPP), an intramembrane protease located in endoplasmic reticulum. In addition, knockdown of the hSPP mRNA expression in ECPsp-eGFP/A431 cells caused the growth inhibitory effect, whereas complementally expression of hSPP in P. pastoris system rescued the cell growth. Taken together, we have demonstrated that ECPsp is a toxic signal peptide, and expression of hSPP protects the cells from growth inhibition

  18. Oxidative Stress, Signal Transduction, Cell-Cell Communication

    National Research Council Canada - National Science Library

    Trosko, James

    1999-01-01

    .... The integration of intercellular communication through gap junctions and intracellular pathways plays a role in maintaining the homeostasis by controlling the expression of genes that control cell...

  19. Cell outage compensation in LTE networks: Algorithms and performance assessment

    NARCIS (Netherlands)

    Amirijoo, M.; Jorguseski, L.; Litjens, R.; Schmelz, L.C.

    2011-01-01

    Cell outage compensation is a self-healing function and as such part of the Self-Organising Networks concept for mobile wireless networks. It aims at mitigating the degradation of coverage, capacity and service quality caused by a cell or site level outage. Upon detection of such an outage, cell

  20. Comment on "A dynamic network model of mTOR signaling reveals TSC-independent mTORC2 regulation": building a model of the mTOR signaling network with a potentially faulty tool.

    Science.gov (United States)

    Manning, Brendan D

    2012-07-10

    In their study published in Science Signaling (Research Article, 27 March 2012, DOI: 10.1126/scisignal.2002469), Dalle Pezze et al. tackle the dynamic and complex wiring of the signaling network involving the protein kinase mTOR, which exists within two distinct protein complexes (mTORC1 and mTORC2) that differ in their regulation and function. The authors use a combination of immunoblotting for specific phosphorylation events and computational modeling. The primary experimental tool employed is to monitor the autophosphorylation of mTOR on Ser(2481) in cell lysates as a surrogate for mTOR activity, which the authors conclude is a specific readout for mTORC2. However, Ser(2481) phosphorylation occurs on both mTORC1 and mTORC2 and will dynamically change as the network through which these two complexes are connected is manipulated. Therefore, models of mTOR network regulation built using this tool are inherently imperfect and open to alternative explanations. Specific issues with the main conclusion made in this study, involving the TSC1-TSC2 (tuberous sclerosis complex 1 and 2) complex and its potential regulation of mTORC2, are discussed here. A broader goal of this Letter is to clarify to other investigators the caveats of using mTOR Ser(2481) phosphorylation in cell lysates as a specific readout for either of the two mTOR complexes.

  1. Tuning Cell and Tissue Development by Combining Multiple Mechanical Signals.

    Science.gov (United States)

    Sinha, Ravi; Verdonschot, Nico; Koopman, Bart; Rouwkema, Jeroen

    2017-10-01

    Mechanical signals offer a promising way to control cell and tissue development. It has been established that cells constantly probe their mechanical microenvironment and employ force feedback mechanisms to modify themselves and when possible, their environment, to reach a homeostatic state. Thus, a correct mechanical microenvironment (external forces and mechanical properties and shapes of cellular surroundings) is necessary for the proper functioning of cells. In vitro or in the case of nonbiological implants in vivo, where cells are in an artificial environment, addition of the adequate mechanical signals can, therefore, enable the cells to function normally as in vivo. Hence, a wide variety of approaches have been developed to apply mechanical stimuli (such as substrate stretch, flow-induced shear stress, substrate stiffness, topography, and modulation of attachment area) to cells in vitro. These approaches have not just revealed the effects of the mechanical signals on cells but also provided ways for probing cellular molecules and structures that can provide a mechanistic understanding of the effects. However, they remain lower in complexity compared with the in vivo conditions, where the cellular mechanical microenvironment is the result of a combination of multiple mechanical signals. Therefore, combinations of mechanical stimuli have also been applied to cells in vitro. These studies have had varying focus-developing novel platforms to apply complex combinations of mechanical stimuli, observing the co-operation/competition between stimuli, combining benefits of multiple stimuli toward an application, or uncovering the underlying mechanisms of their action. In general, they provided new insights that could not have been predicted from previous knowledge. We present here a review of several such studies and the insights gained from them, thereby making a case for such studies to be continued and further developed.

  2. Probiotic Modulation of Innate Cell Pathogen Sensing and Signaling Events

    Directory of Open Access Journals (Sweden)

    Amy Llewellyn

    2017-10-01

    Full Text Available There is a growing body of evidence documenting probiotic bacteria to have a beneficial effect to the host through their ability to modulate the mucosal immune system. Many probiotic bacteria can be considered to act as either immune activators or immune suppressors, which have appreciable influence on homeostasis, inflammatory- and suppressive-immunopathology. What is becoming apparent is the ability of these probiotics to modulate innate immune responses via direct or indirect effects on the signaling pathways that drive these activatory or suppressive/tolerogenic mechanisms. This review will focus on the immunomodulatory role of probiotics on signaling pathways in innate immune cells: from positive to negative regulation associated with innate immune cells driving gut mucosal functionality. Research investigations have shown probiotics to modulate innate functionality in many ways including, receptor antagonism, receptor expression, binding to and expression of adaptor proteins, expression of negative regulatory signal molecules, induction of micro-RNAs, endotoxin tolerisation and finally, the secretion of immunomodulatory proteins, lipids and metabolites. The detailed understanding of the immunomodulatory signaling effects of probiotic strains will facilitate strain-specific selective manipulation of innate cell signal mechanisms in the modulation of mucosal adjuvanticity, immune deviation and tolerisation in both healthy subjects and patients with inflammatory and suppressive pathology.

  3. Curcumin blocks interleukin-1 signaling in chondrosarcoma cells.

    Directory of Open Access Journals (Sweden)

    Thomas Kalinski

    Full Text Available Interleukin (IL-1 signaling plays an important role in inflammatory processes, but also in malignant processes. The essential downstream event in IL-1 signaling is the activation of nuclear factor (NF-κB, which leads to the expression of several genes that are involved in cell proliferation, invasion, angiogenesis and metastasis, among them VEGF-A. As microenvironment-derived IL-1β is required for invasion and angiogenesis in malignant tumors, also in chondrosarcomas, we investigated IL-1β-induced signal transduction and VEGF-A expression in C3842 and SW1353 chondrosarcoma cells. We additionally performed in vitro angiogenesis assays and NF-κB-related gene expression analyses. Curcumin is a substance which inhibits IL-1 signaling very early by preventing the recruitment of IL-1 receptor associated kinase (IRAK to the IL-1 receptor. We demonstrate that IL-1 signaling and VEGF-A expression are blocked by Curcumin in chondrosarcoma cells. We further show that Curcumin blocks IL-1β-induced angiogenesis and NF-κB-related gene expression. We suppose that IL-1 blockade is an additional treatment option in chondrosarcoma, either by Curcumin, its derivatives or other IL-1 blocking agents.

  4. Cilia and coordination of signaling networks during heart development

    DEFF Research Database (Denmark)

    Koefoed, Karen; Veland, Iben Rønn; Pedersen, Lotte Bang

    2014-01-01

    Primary cilia are unique sensory organelles that coordinate a wide variety of different signaling pathways to control cellular processes during development and in tissue homeostasis. Defects in function or assembly of these antenna-like structures are therefore associated with a broad range...... of developmental disorders and diseases called ciliopathies. Recent studies have indicated a major role of different populations of cilia, including nodal and cardiac primary cilia, in coordinating heart development, and defects in these cilia are associated with congenital heart diseases. Here, we present...

  5. G-Protein Coupled Receptor Signaling Architecture of Mammalian Immune Cells

    OpenAIRE

    Polouliakh, Natalia; Nock, Richard; Nielsen, Frank; Kitano, Hiroaki

    2009-01-01

    A series of recent studies on large-scale networks of signaling and metabolic systems revealed that a certain network structure often called "bow-tie network" are observed. In signaling systems, bow-tie network takes a form with diverse and redundant inputs and outputs connected via a small numbers of core molecules. While arguments have been made that such network architecture enhances robustness and evolvability of biological systems, its functional role at a cellular level remains obscure....

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

    Science.gov (United States)

    Wyatt, Sarah

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

  7. Molecular regulation of cytoskeletal rearrangements during T cell signalling.

    Science.gov (United States)

    Stradal, Theresia E B; Pusch, Rico; Kliche, Stefanie

    2006-01-01

    Regulation of the cytoskeleton in cells of the haematopoietic system is essential for fulfilling diverse tasks such as migration towards a chemoattractant, phagocytosis or cell-cell communication. This is particularly true for the many types of T cells, which are at the foundation of the adaptive immune system in vertebrates. Deregulation of actin filament turnover is known to be involved in the development of severe immunodeficiencies or immunoproliferative diseases. Therefore, molecular dissection of signalling complexes and effector molecules, which leads to controlled cytoskeletal assembly, has been the focus of immunological research in the last decade. In the past, cytoskeletal remodelling was frequently understood as the finish line of signalling, while today it becomes increasingly evident that actin and microtubule dynamics are required for proper signal transmission in many processes such as T cell activation. Significant effort is made in many laboratories to further elucidate the contribution of cytoskeletal remodelling to immune function. The objective of this article is to summarise the current knowledge on how actin and microtubules are reorganised to support the formation of structures as diverse as the immunological synapse and peripheral protrusions during cell migration.

  8. Traffic Signal Synchronization in the Saturated High-Density Grid Road Network

    Directory of Open Access Journals (Sweden)

    Xiaojian Hu

    2015-01-01

    Full Text Available Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN. Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

  9. Traffic Signal Synchronization in the Saturated High-Density Grid Road Network

    Science.gov (United States)

    Hu, Xiaojian; Lu, Jian; Wang, Wei; Zhirui, Ye

    2015-01-01

    Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN. PMID:25663835

  10. Bioelectric signal classification using a recurrent probabilistic neural network with time-series discriminant component analysis.

    Science.gov (United States)

    Hayashi, Hideaki; Shima, Keisuke; Shibanoki, Taro; Kurita, Yuichi; Tsuji, Toshio

    2013-01-01

    This paper outlines a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower-dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model that incorporates a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into a neural network so that parameters can be obtained appropriately as network coefficients according to backpropagation-through-time-based training algorithm. The network is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. In the experiments conducted during the study, the validity of the proposed network was demonstrated for EEG signals.

  11. Signal transduction events in aluminum-induced cell death in tomato suspension cells

    NARCIS (Netherlands)

    Iakimova, E.T.; Kapchina-Toteva, V.M.; Woltering, E.J.

    2007-01-01

    In this study, some of the signal transduction events involved in AlCl3-induced cell death in tomato (Lycopersicon esculentum Mill.) suspension cells were elucidated. Cells treated with 100 ¿M AlCl3 showed typical features of programmed cell death (PCD) such as nuclear and cytoplasmic condensation.

  12. Branched motifs enable long-range interactions in signaling networks through retrograde propagation.

    Directory of Open Access Journals (Sweden)

    Tharmaraj Jesan

    Full Text Available Branched structures arise in the intra-cellular signaling network when a molecule is involved in multiple enzyme-substrate reaction cascades. Such branched motifs are involved in key biological processes, e.g., immune response activated by T-cell and B-cell receptors. In this paper, we demonstrate long-range communication through retrograde propagation between branches of signaling pathways whose molecules do not directly interact. Our numerical simulations and experiments on a system comprising branches with JNK and p38MAPK as terminal molecules respectively that share a common MAP3K enzyme MEKK3/4 show that perturbing an enzyme in one branch can result in a series of changes in the activity levels of molecules "upstream" to the enzyme that eventually reaches the branch-point and affects other branches. In the absence of any evidence for explicit feedback regulation between the functionally distinct JNK and p38MAPK pathways, the experimentally observed modulation of phosphorylation amplitudes in the two pathways when a terminal kinase is inhibited implies the existence of long-range coordination through retrograde information propagation previously demonstrated in single linear reaction pathways. An important aspect of retrograde propagation in branched pathways that is distinct from previous work on retroactivity focusing exclusively on single chains is that varying the type of perturbation, e.g., between pharmaceutical agent mediated inhibition of phosphorylation or suppression of protein expression, can result in opposing responses in the other branches. This can have potential significance in designing drugs targeting key molecules which regulate multiple pathways implicated in systems-level diseases such as cancer and diabetes.

  13. Identification of cyclin A2 as the downstream effector of the nuclear phosphatidylinositol 4,5-bisphosphate signaling network.

    Science.gov (United States)

    Ho, Ka-Kei; Anderson, Alexandra A; Rosivatz, Erika; Lam, Eric W-F; Woscholski, Rüdiger; Mann, David J

    2008-02-29

    In addition to the well characterized phosphoinositide second messengers derived from the plasma membrane, increasing evidence supports the existence of a nuclear phosphoinositide signaling network. The aim of this investigation was to dissect the role played by nuclear phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P2) in cell cycle progression and to determine the cell cycle regulatory component(s) that are involved. A number of cytosolic/nuclear PtdIns(4,5)P2-deficient Swiss 3T3 cell lines were established, and their G 0/G 1/S cell cycle phase transitions induced by defined mitogens were examined. Our results demonstrate that nuclear PtdIns(4,5)P2 down-regulation caused a delay in phorbol ester-induced S phase entry and that this was at least in part channeled through cyclin A2 at the transcriptional level. In summary, these data identify cyclin A2 as a downstream effector of the nuclear PtdIns(4,5)P2 signaling network and highlight the importance of nuclear PtdIns(4,5)P2 in the regulation of mammalian mitogenesis.

  14. Neuroendocrine signaling modulates specific neural networks relevant to migraine.

    Science.gov (United States)

    Martins-Oliveira, Margarida; Akerman, Simon; Holland, Philip R; Hoffmann, Jan R; Tavares, Isaura; Goadsby, Peter J

    2017-05-01

    Migraine is a disabling brain disorder involving abnormal trigeminovascular activation and sensitization. Fasting or skipping meals is considered a migraine trigger and altered fasting glucose and insulin levels have been observed in migraineurs. Therefore peptides involved in appetite and glucose regulation including insulin, glucagon and leptin could potentially influence migraine neurobiology. We aimed to determine the effect of insulin (10U·kg -1 ), glucagon (100μg·200μl -1 ) and leptin (0.3, 1 and 3mg·kg -1 ) signaling on trigeminovascular nociceptive processing at the level of the trigeminocervical-complex and hypothalamus. Male rats were anesthetized and prepared for craniovascular stimulation. In vivo electrophysiology was used to determine changes in trigeminocervical neuronal responses to dural electrical stimulation, and phosphorylated extracellular signal-regulated kinases 1 and 2 (pERK1/2) immunohistochemistry to determine trigeminocervical and hypothalamic neural activity; both in response to intravenous administration of insulin, glucagon, leptin or vehicle control in combination with blood glucose analysis. Blood glucose levels were significantly decreased by insulin (pmigraine and impaired metabolic homeostasis may occur through disturbed glucose regulation and a transient hypothalamic dysfunction. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  15. Functional and gene network analyses of transcriptional signatures characterizing pre-weaned bovine mammary parenchyma or fat pad uncovered novel inter-tissue signaling networks during development

    Directory of Open Access Journals (Sweden)

    Lewin Harris A

    2010-05-01

    Full Text Available Abstract Background The neonatal bovine mammary fat pad (MFP surrounding the mammary parenchyma (PAR is thought to exert proliferative effects on the PAR through secretion of local modulators of growth induced by systemic hormones. We used bioinformatics to characterize transcriptomics differences between PAR and MFP from ~65 d old Holstein heifers. Data were mined to uncover potential crosstalk through the analyses of signaling molecules preferentially expressed in one tissue relative to the other. Results Over 9,000 differentially expressed genes (DEG; False discovery rate ≤ 0.05 were found of which 1,478 had a ≥1.5-fold difference between PAR and MFP. Within the DEG highly-expressed in PAR vs. MFP (n = 736 we noted significant enrichment of functions related to cell cycle, structural organization, signaling, and DNA/RNA metabolism. Only actin cytoskeletal signaling was significant among canonical pathways. DEG more highly-expressed in MFP vs. PAR (n = 742 belong to lipid metabolism, signaling, cell movement, and immune-related functions. Canonical pathways associated with metabolism and signaling, particularly immune- and metabolism-related were significantly-enriched. Network analysis uncovered a central role of MYC, TP53, and CTNNB1 in controlling expression of DEG highly-expressed in PAR vs. MFP. Similar analysis suggested a central role for PPARG, KLF2, EGR2, and EPAS1 in regulating expression of more highly-expressed DEG in MFP vs. PAR. Gene network analyses revealed putative inter-tissue crosstalk between cytokines and growth factors preferentially expressed in one tissue (e.g., ANGPTL1, SPP1, IL1B in PAR vs. MFP; ADIPOQ, IL13, FGF2, LEP in MFP vs. PAR with DEG preferentially expressed in the other tissue, particularly transcription factors or pathways (e.g., MYC, TP53, and actin cytoskeletal signaling in PAR vs. MFP; PPARG and LXR/RXR Signaling in MFP vs. PAR. Conclusions Functional analyses underscored a reciprocal influence in

  16. A signal processing analysis of Purkinje cells in vitro

    Directory of Open Access Journals (Sweden)

    Ze'ev R Abrams

    2010-05-01

    Full Text Available Cerebellar Purkinje cells in vitro fire recurrent sequences of Sodium and Calcium spikes. Here, we analyze the Purkinje cell using harmonic analysis, and our experiments reveal that its output signal is comprised of three distinct frequency bands, which are combined using Amplitude and Frequency Modulation (AM/FM. We find that the three characteristic frequencies - Sodium, Calcium and Switching – occur in various combinations in all waveforms observed using whole-cell current clamp recordings. We found that the Calcium frequency can display a frequency doubling of its frequency mode, and the Switching frequency can act as a possible generator of pauses that are typically seen in Purkinje output recordings. Using a reversibly photo-switchable kainate receptor agonist, we demonstrate the external modulation of the Calcium and Switching frequencies. These experiments and Fourier analysis suggest that the Purkinje cell can be understood as a harmonic signal oscillator, enabling a higher level of interpretation of Purkinje signaling based on modern signal processing techniques.

  17. Inquiry into Chemotherapy-Induced P53 Activation in Cancer Cells as a Model for Teaching Signal Transduction

    Science.gov (United States)

    Srougi, Melissa C.; Carson, Susan

    2013-01-01

    Intracellular and extracellular communication is conducted through an intricate and interwoven network of signal transduction pathways. The mechanisms for how cells speak with one another are of significant biological importance to both basic and industrial scientists from a number of different disciplines. We have therefore developed and…

  18. Quinolone signaling in the cell-to-cell communication system of Pseudomonas aeruginosa

    Science.gov (United States)

    Pesci, Everett C.; Milbank, Jared B. J.; Pearson, James P.; McKnight, Susan; Kende, Andrew S.; Greenberg, E. Peter; Iglewski, Barbara H.

    1999-01-01

    Numerous species of bacteria use an elegant regulatory mechanism known as quorum sensing to control the expression of specific genes in a cell-density dependent manner. In Gram-negative bacteria, quorum sensing systems function through a cell-to-cell signal molecule (autoinducer) that consists of a homoserine lactone with a fatty acid side chain. Such is the case in the opportunistic human pathogen Pseudomonas aeruginosa, which contains two quorum sensing systems (las and rhl) that operate via the autoinducers, N-(3-oxododecanoyl)-l-homoserine lactone and N-butyryl-l-homoserine lactone. The study of these signal molecules has shown that they bind to and activate transcriptional activator proteins that specifically induce numerous P. aeruginosa virulence genes. We report here that P. aeruginosa produces another signal molecule, 2-heptyl-3-hydroxy-4-quinolone, which has been designated as the Pseudomonas quinolone signal. It was found that this unique cell-to-cell signal controlled the expression of lasB, which encodes for the major virulence factor, LasB elastase. We also show that the synthesis and bioactivity of Pseudomonas quinolone signal were mediated by the P. aeruginosa las and rhl quorum sensing systems, respectively. The demonstration that 2-heptyl-3-hydroxy-4-quinolone can function as an intercellular signal sheds light on the role of secondary metabolites and shows that P. aeruginosa cell-to-cell signaling is not restricted to acyl-homoserine lactones. PMID:10500159

  19. Cancer signaling networks and their implications for personalized medicine

    DEFF Research Database (Denmark)

    Creixell, Pau

    carcinoma cell lines that could cause their resistance to cisplatin treatment. Part VI closes the thesis by summarizing its main points and proposing some future perspectives for the work presented here. All in all, this work establishes a new framework for the prediction of mechanisms underlying cancer...

  20. Adaptive coded spreading OFDM signal for dynamic-λ optical access network

    Science.gov (United States)

    Liu, Bo; Zhang, Lijia; Xin, Xiangjun

    2015-12-01

    This paper proposes and experimentally demonstrates a novel adaptive coded spreading (ACS) orthogonal frequency division multiplexing (OFDM) signal for dynamic distributed optical ring-based access network. The wavelength can be assigned to different remote nodes (RNs) according to the traffic demand of optical network unit (ONU). The ACS can provide dynamic spreading gain to different signals according to the split ratio or transmission length, which offers flexible power budget for the network. A 10×13.12 Gb/s OFDM access with ACS is successfully demonstrated over two RNs and 120 km transmission in the experiment. The demonstrated method may be viewed as one promising for future optical metro access network.

  1. Fractal analysis of spontaneous fluctuations of the BOLD signal in the human brain networks.

    Science.gov (United States)

    Li, Yi-Chia; Huang, Yun-An

    2014-05-01

    To investigate what extent brain regions are continuously interacting during resting-state, independent component analyses (ICA) was applied to analyze resting-state functional MRI (RS-fMRI) data. According to the analyzed results, it was surprisingly found that low frequency fluctuations (LFFs), which belong to the 1/f signal (a signal with power spectrum whose power spectral density is inversely proportional to the frequency), have been classified into groups using ICA; furthermore, the spatial distributions of these groups within the brain were found to resemble the spatial distributions of different networks, which manifests that the signal characteristics of RS LFFs are distinct across networks. In our work, we applied the 1/f model in the fractal analyses to further investigate this distinction. Twenty healthy participants got involved in this study. They were scanned to acquire the RS-fMRI data. The acquired data were first processed with ICA to obtain the networks of the resting brain. Afterward, the blood-oxygenation level dependent (BOLD) signals of these networks were processed with the fractal analyses for obtaining the fractal parameter α. α was found to significantly vary across networks, which reveals that the fractal characteristic of LFFs differs across networks. According to prior literatures, this difference could be brought by the discrepancy of hemodynamic response amplitude (HRA) between networks. Hence, in our work, we also performed the computational simulation to discover the relationship between α and HRA. Based on the simulation results, HRA is highly linear-correlated with the fractal characteristics of LFFs which is revealed by α. Our results support that the origin of RS-fMRI signals contains arterial fluctuations. Hence, in addition to the commonly used method such as synchrony analysis and power spectral analysis, another approach, the fractal analysis, is suggested for acquiring the information of hemodynamic responses by means

  2. Low-frequency analog signal distribution on digital photonic networks by optical delta-sigma modulation

    Science.gov (United States)

    Kanno, Atsushi; Kawanishi, Tetsuya

    2013-12-01

    We propose a delta-sigma modulation scheme for low- and medium-frequency signal transmission in a digital photonic network system. A 10-Gb/s-class optical transceiver with a delta-sigma modulator utilized as a high-speed analog-to-digital converter (ADC) provides a binary optical signal. On the signal reception side, a low-cost and slow-speed photonic receiver directly converts the binary signal into an analog signal at frequencies from several hundreds of kilohertz several tens of megahertz. Further, by using a clock and data recovery circuit at the receiver to reduce jitters, the single-sideband phase noise of the generated signals can be significantly reduced.

  3. Reconstruction of physiological signals using iterative retraining and accumulated averaging of neural network models.

    Science.gov (United States)

    McBride, Joseph; Sullivan, Adam; Xia, Henian; Petrie, Adam; Zhao, Xiaopeng

    2011-06-01

    Real-time monitoring of vital physiological signals is of significant clinical relevance. Disruptions in the signals are frequently encountered and make it difficult for precise diagnosis. Thus, the ability to accurately predict/recover the lost signals could greatly impact medical research and application. We have developed new techniques of signal reconstructions based on iterative retraining and accumulated averaging of neural networks. The effectiveness and robustness of these techniques are demonstrated using data records from the Computing in Cardiology/PhysioNet Challenge 2010. The average correlation coefficient between prediction and target for 100 records of various target signals is about 0.9. We have also explored influences of a few important parameters on the accuracy of reconstructions. The developed techniques may be used to detect changes in patient state and to recognize intervals of signal corruption.

  4. Diversity and plasticity of Th cell types predicted from regulatory network modelling.

    Directory of Open Access Journals (Sweden)

    Aurélien Naldi

    Full Text Available Alternative cell differentiation pathways are believed to arise from the concerted action of signalling pathways and transcriptional regulatory networks. However, the prediction of mammalian cell differentiation from the knowledge of the presence of specific signals and transcriptional factors is still a daunting challenge. In this respect, the vertebrate hematopoietic system, with its many branching differentiation pathways and cell types, is a compelling case study. In this paper, we propose an integrated, comprehensive model of the regulatory network and signalling pathways controlling Th cell differentiation. As most available data are qualitative, we rely on a logical formalism to perform extensive dynamical analyses. To cope with the size and complexity of the resulting network, we use an original model reduction approach together with a stable state identification algorithm. To assess the effects of heterogeneous environments on Th cell differentiation, we have performed a systematic series of simulations considering various prototypic environments. Consequently, we have identified stable states corresponding to canonical Th1, Th2, Th17 and Treg subtypes, but these were found to coexist with other transient hybrid cell types that co-express combinations of Th1, Th2, Treg and Th17 markers in an environment-dependent fashion. In the process, our logical analysis highlights the nature of these cell types and their relationships with canonical Th subtypes. Finally, our logical model can be used to explore novel differentiation pathways in silico.

  5. EEG signal classification based on artificial neural networks and amplitude spectra features

    Science.gov (United States)

    Chojnowski, K.; FrÄ czek, J.

    BCI (called Brain-Computer Interface) is an interface that allows direct communication between human brain and an external device. It bases on EEG signal collection, processing and classification. In this paper a complete BCI system is presented which classifies EEG signal using artificial neural networks. For this purpose we used a multi-layered perceptron architecture trained with the RProp algorithm. Furthermore a simple multi-threaded method for automatic network structure optimizing was shown. We presented the results of our system in the opening and closing eyes recognition task. We also showed how our system could be used for controlling devices basing on imaginary hand movements.

  6. Resolving Early Signaling Events in T-Cell Activation Leading to IL-2 and FOXP3 Transcription

    Directory of Open Access Journals (Sweden)

    Jeffrey P. Perley

    2014-11-01

    Full Text Available Signal intensity and feedback regulation are known to be major factors in the signaling events stemming from the T-cell receptor (TCR and its various coreceptors, but the exact nature of these relationships remains in question. We present a mathematical model of the complex signaling network involved in T-cell activation with cross-talk between the Erk, calcium, PKC and mTOR signaling pathways. The model parameters are adjusted to fit new and published data on TCR trafficking, Zap70, calcium, Erk and Isignaling. The regulation of the early signaling events by phosphatases, CD45 and SHP1, and the TCR dynamics are critical to determining the behavior of the model. Additional model corroboration is provided through quantitative and qualitative agreement with experimental data collected under different stimulating and knockout conditions. The resulting model is analyzed to investigate how signal intensity and feedback regulation affect TCR- and coreceptor-mediated signal transduction and their downstream transcriptional profiles to predict the outcome for a variety of stimulatory and knockdown experiments. Analysis of the model shows that: (1 SHP1 negative feedback is necessary for preventing hyperactivity in TCR signaling; (2 CD45 is required for TCR signaling, but also partially suppresses it at high expression levels; and (3 elevated FOXP3 and reduced IL-2 signaling, an expression profile often associated with T regulatory cells (Tregs, is observed when the system is subjected to weak TCR and CD28 costimulation or a severe reduction in CD45 activity.

  7. Ca2+ signaling in pancreatic acinar cells: physiology and pathophysiology

    Directory of Open Access Journals (Sweden)

    O.H. Petersen

    2009-01-01

    Full Text Available The pancreatic acinar cell is a classical model for studies of secretion and signal transduction mechanisms. Because of the extensive endoplasmic reticulum and the large granular compartment, it has been possible - by direct measurements - to obtain considerable insights into intracellular Ca2+ handling under both normal and pathological conditions. Recent studies have also revealed important characteristics of stimulus-secretion coupling mechanisms in isolated human pancreatic acinar cells. The acinar cells are potentially dangerous because of the high intra-granular concentration of proteases, which become inappropriately activated in the human disease acute pancreatitis. This disease is due to toxic Ca2+ signals generated by excessive liberation of Ca2+ from both the endoplasmic reticulum and the secretory granules.

  8. SU-PhysioDB: a physiological signals database for body area network security

    OpenAIRE

    Karaoğlan Altop, Duygu; Karaoglan Altop, Duygu; Levi, Albert; Tuzcu, Volkan

    2017-01-01

    This paper presents a new physiological signals database, SU-PhysioDB, that contains simultaneous measurements of electrocardiogram (ECG), blood pressure (BP) and body temperature (BT) signals. SU-PhysioDB can be used to evaluate the performance of the security mechanisms designed for the communication among the biosensors within Body Area Networks (BANs). We present a detailed description of our SU-PhysioDB database along with providing a performance comparison of two specific physiological ...

  9. The DSF Family of Cell-Cell Signals: An Expanding Class of Bacterial Virulence Regulators.

    Directory of Open Access Journals (Sweden)

    Robert P Ryan

    2015-07-01

    Full Text Available Many pathogenic bacteria use cell-cell signaling systems involving the synthesis and perception of diffusible signal molecules to control virulence as a response to cell density or confinement to niches. Bacteria produce signals of diverse structural classes. Signal molecules of the diffusible signal factor (DSF family are cis-2-unsaturated fatty acids. The paradigm is cis-11-methyl-2-dodecenoic acid from Xanthomonas campestris pv. campestris (Xcc, which controls virulence in this plant pathogen. Although DSF synthesis was thought to be restricted to the xanthomonads, it is now known that structurally related molecules are produced by the unrelated bacteria Burkholderia cenocepacia and Pseudomonas aeruginosa. Furthermore, signaling involving these DSF family members contributes to bacterial virulence, formation of biofilms and antibiotic tolerance in these important human pathogens. Here we review the recent advances in understanding DSF signaling and its regulatory role in different bacteria. These advances include the description of the pathway/mechanism of DSF biosynthesis, identification of novel DSF synthases and new members of the DSF family, the demonstration of a diversity of DSF sensors to include proteins with a Per-Arnt-Sim (PAS domain and the description of some of the signal transduction mechanisms that impinge on virulence factor expression. In addition, we address the role of DSF family signals in interspecies signaling that modulates the behavior of other microorganisms. Finally, we consider a number of recently reported approaches for the control of bacterial virulence through the modulation of DSF signaling.

  10. Cytokine Networks between Innate Lymphoid Cells and Myeloid Cells

    Directory of Open Access Journals (Sweden)

    Arthur Mortha

    2018-02-01

    Full Text Available Innate lymphoid cells (ILCs are an essential component of the innate immune system in vertebrates. They are developmentally rooted in the lymphoid lineage and can diverge into at least three transcriptionally distinct lineages. ILCs seed both lymphoid and non-lymphoid tissues and are locally self-maintained in tissue-resident pools. Tissue-resident ILCs execute important effector functions making them key regulator in tissue homeostasis, repair, remodeling, microbial defense, and anti-tumor immunity. Similar to T lymphocytes, ILCs possess only few sensory elements for the recognition of non-self and thus depend on extrinsic cellular sensory elements residing within the tissue. Myeloid cells, including mononuclear phagocytes (MNPs, are key sentinels of the tissue and are able to translate environmental cues into an effector profile that instructs lymphocyte responses. The adaptation of myeloid cells to the tissue state thus influences the effector program of ILCs and serves as an example of how environmental signals are integrated into the function of ILCs via a tissue-resident immune cell cross talks. This review summarizes our current knowledge on the role of myeloid cells in regulating ILC functions and discusses how feedback communication between ILCs and myeloid cells contribute to stabilize immune homeostasis in order to maintain the healthy state of an organ.

  11. A microfluidic platform for regulating signal transduction in single cells

    Science.gov (United States)

    Wong, Pak Kin; Yu, Fuqu; Sun, Ren; Ho, Chih-Ming

    2004-11-01

    Recent progress in micro cell culture systems has lead to new approaches in cell biology studies. Using micro devices for cell culturing possesses distinctive advantages over traditional methods. Length scale matching facilitates manipulation and detection at the single cell level. Previously, we have demonstrated generation of various stimulations such as spatial chemical gradient, electric field, and shear stress to study the dynamic responses of individual cells. Dynamic stimulations and continuous monitoring in a microfluidic system can be useful in studying different aspects of cellular process. In this work, we present a microfluidic platform for regulating nuclear factor kappa B (NF-kB) signal transduction in human embryonic kidney 293T cells. Time-varying bio-chemical stimulants, such as interleukin 1 and tumor necrosis factor, are introduced into the microchannel to activate the NF-kB signaling pathway. The dynamic responses of individual cells are monitored with the expression of reporter gene, green fluorescent protein. Regulation of the NF-kB activity is successfully demonstrated. This work is supported by CMISE through NASA URETI program.

  12. 14-3-3 proteins in guard cell signaling

    Directory of Open Access Journals (Sweden)

    Valérie eCotelle

    2016-01-01

    Full Text Available Guard cells are specialized cells located at the leaf surface delimiting pores which control gas exchanges between the plant and the atmosphere. To optimize the CO2 uptake necessary for photosynthesis while minimizing water loss, guard cells integrate environmental signals to adjust stomatal aperture. The size of the stomatal pore is regulated by movements of the guard cells driven by variations in their volume and turgor. As guard cells perceive and transduce a wide array of environmental cues, they provide an ideal system to elucidate early events of plant signaling. Reversible protein phosphorylation events are known to play a crucial role in the regulation of stomatal movements. However, in some cases, phosphorylation alone is not sufficient to achieve complete protein regulation, but is necessary to mediate the binding of interactors that modulate protein function. Among the phosphopeptide-binding proteins, the 14-3-3 proteins are the best characterized in plants. The 14-3-3s are found as multiple isoforms in eukaryotes and have been shown to be involved in the regulation of stomatal movements. In this review, we describe the current knowledge about 14-3-3 roles in the regulation of their binding partners in guard cells: receptors, ion pumps, channels, protein kinases and some of their substrates. Regulation of these targets by 14-3-3 proteins is discussed and related to their function in guard cells during stomatal movements in response to abiotic or biotic stresses.

  13. Romidepsin targets multiple survival signaling pathways in malignant T cells

    International Nuclear Information System (INIS)

    Valdez, B C; Brammer, J E; Li, Y; Murray, D; Liu, Y; Hosing, C; Nieto, Y; Champlin, R E; Andersson, B S

    2015-01-01

    Romidepsin is a cyclic molecule that inhibits histone deacetylases. It is Food and Drug Administration-approved for treatment of cutaneous and peripheral T-cell lymphoma, but its precise mechanism of action against malignant T cells is unknown. To better understand the biological effects of romidepsin in these cells, we exposed PEER and SUPT1 T-cell lines, and a primary sample from T-cell lymphoma patient (Patient J) to romidepsin. We then examined the consequences in some key oncogenic signaling pathways. Romidepsin displayed IC 50 values of 10.8, 7.9 and 7.0 nm in PEER, SUPT1 and Patient J cells, respectively. Strong inhibition of histone deacetylases and demethylases, increased production of reactive oxygen species and decreased mitochondrial membrane potential were observed, which may contribute to the observed DNA-damage response and apoptosis. The stress-activated protein kinase/c-Jun N-terminal kinase signaling pathway and unfolded protein response in the endoplasmic reticulum were activated, whereas the phosphatidylinositol 3-kinase/AKT/mammalian target of rapamycin (PI3K/AKT/mTOR) and β-catenin pro-survival pathways were inhibited. The decreased level of β-catenin correlated with the upregulation of its inhibitor SFRP1 through romidepsin-mediated hypomethylation of its gene promoter. Our results provide new insights into how romidepsin invokes malignant T-cell killing, show evidence of its associated DNA hypomethylating activity and offer a rationale for the development of romidepsin-containing combination therapies

  14. Rescue effects in radiobiology: Unirradiated bystander cells assist irradiated cells through intercellular signal feedback

    Energy Technology Data Exchange (ETDEWEB)

    Chen, S. [Department of Physics and Materials Science, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong); Key Laboratory of Ion Beam Bioengineering, Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); Zhao, Y. [Key Laboratory of Ion Beam Bioengineering, Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); Han, W. [Department of Physics and Materials Science, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong); Chiu, S.K. [Department of Biology and Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong); Zhu, L. [Office of Admission and Careers Advisory Service, Shenzhen University, Shenzhen 518060 (China); Wu, L. [Key Laboratory of Ion Beam Bioengineering, Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031 (China); Yu, K.N., E-mail: peter.yu@cityu.edu.hk [Department of Physics and Materials Science, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong)

    2011-01-10

    Mammalian cells respond to ionization radiation by sending out extracellular signals to affect non-irradiated neighboring cells, which is referred to as radiation induced bystander effect. In the present paper, we described a phenomenon entitled the 'rescue effects', where the bystander cells rescued the irradiated cells through intercellular signal feedback. The effect was observed in both human primary fibroblast (NHLF) and cancer cells (HeLa) using two-cell co-culture systems. After co-culturing irradiated cells with unirradiated bystander cells for 24 h, the numbers of 53BP1 foci, corresponding to the number of DNA double-strand breaks in the irradiated cells were less than those in the irradiated cells that were not co-cultured with the bystander cells (0.78 {+-} 0.04 foci/cell vs. 0.90 {+-} 0.04 foci/cell) at a statistically significant level. Similarly, both micronucleus formation and extent of apoptosis in the irradiated cells were different at statistically significant levels if they were co-cultured with the bystander cells. Furthermore, it was found that unirradiated normal cells would also reduce the micronucleus formation in irradiated cancer cells. These results suggested that the rescue effects could participate in repairing the radiation-induced DNA damages through a media-mediated signaling feedback, thereby mitigating the cytotoxicity and genotoxicity of ionizing radiation.

  15. Network Signaling Channel for Improving ZigBee Performance in Dynamic Cluster-Tree Networks

    Directory of Open Access Journals (Sweden)

    D. Hämäläinen

    2008-03-01

    Full Text Available ZigBee is one of the most potential standardized technologies for wireless sensor networks (WSNs. Yet, sufficient energy-efficiency for the lowest power WSNs is achieved only in rather static networks. This severely limits the applicability of ZigBee in outdoor and mobile applications, where operation environment is harsh and link failures are common. This paper proposes a network channel beaconing (NCB algorithm for improving ZigBee performance in dynamic cluster-tree networks. NCB reduces the energy consumption of passive scans by dedicating one frequency channel for network beacon transmissions and by energy optimizing their transmission rate. According to an energy analysis, the power consumption of network maintenance operations reduces by 70%–76% in dynamic networks. In static networks, energy overhead is negligible. Moreover, the service time for data routing increases up to 37%. The performance of NCB is validated by ns-2 simulations. NCB can be implemented as an extension on MAC and NWK layers and it is fully compatible with ZigBee.

  16. Quality-on-Demand Compression of EEG Signals for Telemedicine Applications Using Neural Network Predictors

    Directory of Open Access Journals (Sweden)

    N. Sriraam

    2011-01-01

    Full Text Available A telemedicine system using communication and information technology to deliver medical signals such as ECG, EEG for long distance medical services has become reality. In either the urgent treatment or ordinary healthcare, it is necessary to compress these signals for the efficient use of bandwidth. This paper discusses a quality on demand compression of EEG signals using neural network predictors for telemedicine applications. The objective is to obtain a greater compression gains at a low bit rate while preserving the clinical information content. A two-stage compression scheme with a predictor and an entropy encoder is used. The residue signals obtained after prediction is first thresholded using various levels of thresholds and are further quantized and then encoded using an arithmetic encoder. Three neural network models, single-layer and multi-layer perceptrons and Elman network are used and the results are compared with linear predictors such as FIR filters and AR modeling. The fidelity of the reconstructed EEG signal is assessed quantitatively using parameters such as PRD, SNR, cross correlation and power spectral density. It is found from the results that the quality of the reconstructed signal is preserved at a low PRD thereby yielding better compression results compared to results obtained using lossless scheme.

  17. Signal Network Analysis of Plant Genes Responding to Ionizing Radiation

    International Nuclear Information System (INIS)

    Kim, Dong Sub; Kim, Jinbaek; Kim, Sang Hoon

    2012-12-01

    In this project, we irradiated Arabidopsis plants with various doses of gamma-rays at the vegetative and reproductive stages to assess their radiation sensitivity. After the gene expression profiles and an analysis of the antioxidant response, we selected several Arabidopsis genes for uses of 'Radio marker genes (RMG)' and conducted over-expression and knock-down experiments to confirm the radio sensitivity. Based on these results, we applied two patents for the detection of two RMG (At3g28210 and At4g37990) and development of transgenic plants. Also, we developed a Genechip for use of high-throughput screening of Arabidopsis genes responding only to ionizing radiation and identified RMG to detect radiation leaks. Based on these results, we applied two patents associated with the use of Genechip for different types of radiation and different growth stages. Also, we conducted co-expression network study of specific expressed probes against gamma-ray stress and identified expressed patterns of duplicated genes formed by whole/500kb segmental genome duplication

  18. LRP-1 promotes cancer cell invasion by supporting ERK and inhibiting JNK signaling pathways.

    Directory of Open Access Journals (Sweden)

    Benoit Langlois

    Full Text Available BACKGROUND: The low-density lipoprotein receptor-related protein-1 (LRP-1 is an endocytic receptor mediating the clearance of various extracellular molecules involved in the dissemination of cancer cells. LRP-1 thus appeared as an attractive receptor for targeting the invasive behavior of malignant cells. However, recent results suggest that LRP-1 may facilitate the development and growth of cancer metastases in vivo, but the precise contribution of the receptor during cancer progression remains to be elucidated. The lack of mechanistic insights into the intracellular signaling networks downstream of LRP-1 has prevented the understanding of its contribution towards cancer. METHODOLOGY/PRINCIPAL FINDINGS: Through a short-hairpin RNA-mediated silencing approach, we identified LRP-1 as a main regulator of ERK and JNK signaling in a tumor cell context. Co-immunoprecipitation experiments revealed that LRP-1 constitutes an intracellular docking site for MAPK containing complexes. By using pharmacological agents, constitutively active and dominant-negative kinases, we demonstrated that LRP-1 maintains malignant cells in an adhesive state that is favorable for invasion by activating ERK and inhibiting JNK. We further demonstrated that the LRP-1-dependent regulation of MAPK signaling organizes the cytoskeletal architecture and mediates adhesive complex turnover in cancer cells. Moreover, we found that LRP-1 is tethered to the actin network and to focal adhesion sites and controls ERK and JNK targeting to talin-rich structures. CONCLUSIONS: We identified ERK and JNK as the main molecular relays by which LRP-1 regulates focal adhesion disassembly of malignant cells to support invasion.

  19. Phosphorylation site dynamics of early T-cell receptor signaling

    DEFF Research Database (Denmark)

    Chylek, Lily A; Akimov, Vyacheslav; Dengjel, Jörn

    2014-01-01

    a systems-level understanding of how these components cooperate to control signaling dynamics, especially during the crucial first seconds of stimulation. Here, we used quantitative proteomics to characterize reshaping of the T-cell phosphoproteome in response to TCR/CD28 co-stimulation, and found...... that diverse dynamic patterns emerge within seconds. We detected phosphorylation dynamics as early as 5 s and observed widespread regulation of key TCR signaling proteins by 30 s. Development of a computational model pointed to the presence of novel regulatory mechanisms controlling phosphorylation of sites...

  20. Signaling through EAAT-1/GLAST in cultured Bergmann glia cells.

    Science.gov (United States)

    Martínez-Lozada, Zila; Hernández-Kelly, Luisa C; Aguilera, José; López-Bayghen, Esther; Ortega, Arturo

    2011-11-01

    Glutamate, the major excitatory amino acid, activates a wide variety of signal transduction cascades. Synaptic plasticity relies on activity-dependent differential protein expression. Ionotropic and metabotropic glutamate receptors have been critically involved in long-term synaptic changes, although recent findings suggest that the electrogenic Na(+)-dependent glutamate transporters, responsible of its removal from the synaptic cleft, participate in glutamate-induced signaling. Transporter proteins are expressed in neurons and glia cells albeit most of the glutamate uptake occurs in the glial compartment. Within the cerebellum, Bergmann glial cells are close to glutamatergic synapses and participate actively in the recycling of glutamate through the glutamate/glutamine shuttle. In this context, we decided to investigate a plausible role of Bergmann glia glutamate transporters as signaling entities. To this end, primary cultures of chick cerebellar Bergmann glial cells were exposed to d-aspartate (D-Asp) and other transporter ligands and the serine 2448 phosphorylation pattern of the master regulator of protein synthesis, namely the mammalian target of rapamycin (mTOR), determined. An increase in mTOR phosphorylation and activity was detected. The signaling cascade included Ca(2+) influx, activation of the phosphatidylinositol 3-kinase and protein kinase B. Furthermore, transporter signaling resulted also in an increase in activator protein-1 (AP-1) binding to DNA and the up-regulation of the transcription of an AP-1 driven gene construct. These results add a novel mediator of the glutamate effects at the translational and transcriptional levels and further strengthen the notion of the critical involvement of glia cells in synaptic function. Copyright © 2011 Elsevier B.V. All rights reserved.

  1. Network management and signalling standards for CCSDS advanced orbiting system communication systems

    Science.gov (United States)

    Pietras, John

    The Consultative Committee for Space Data Systems (CCSDS) is an international organization chartered to develop and adopt communications protocols and data processing standards suitable for use in space-related communication and data processing systems. This paper briefly describes the CCSDS network management environment and reviews the current status of CCSDS recommendations for network management functional capability, use of internal standard for network management, and composition of signaling systems in support of the advanced orbiting systems services typified by the international Space Station Freedom Program. A timetable for future work in this area is presented.

  2. An alternative pathway for signal flow from rod photoreceptors to ganglion cells in mammalian retina.

    OpenAIRE

    DeVries, S H; Baylor, D A

    1995-01-01

    Rod signals in the mammalian retina are thought to reach ganglion cells over the circuit rod-->rod depolarizing bipolar cell-->AII amacrine cell-->cone bipolar cells-->ganglion cells. A possible alternative pathway involves gap junctions linking the rods and cones, the circuit being rod-->cone-->cone bipolar cells-->ganglion cells. It is not clear whether this second pathway indeed relays rod signals to ganglion cells. We studied signal flow in the isolated rabbit retina with a multielectrode...

  3. Towards convergence of wireless and wireline signal transport in broadband access networks

    DEFF Research Database (Denmark)

    Yu, Xianbin; Prince, Kamau; Tafur Monroy, Idelfonso

    2010-01-01

    Hybrid optical wireless access networks are to play an important role in the realization of the vision of delivery of broadband services to the end-user any time, anywhere and at affordable costs. We present results of experiments conducted over a field deployed optical fibre links we successfull...... demonstrated converged wireless and wireline signal transport over a common fibre infrastructure. The type of signal used in this field deployed experiments cover WiMax, Impulse-radio ultra-wideband (UWB) and coherent transmission of baseband QPSK and radio-over-fibre signals....

  4. Neural Network Based Recognition of Signal Patterns in Application to Automatic Testing of Rails

    Directory of Open Access Journals (Sweden)

    Tomasz Ciszewski

    2006-01-01

    Full Text Available The paper describes the application of neural network for recognition of signal patterns in measuring data gathered by the railroad ultrasound testing car. Digital conversion of the measuring signal allows to store and process large quantities of data. The elaboration of smart, effective and automatic procedures recognizing the obtained patterns on the basisof measured signal amplitude has been presented. The test shows only two classes of pattern recognition. In authors’ opinion if we deliver big enough quantity of training data, presented method is applicable to a system that recognizes many classes.

  5. Effect of signal noise on the learning capability of an artificial neural network

    International Nuclear Information System (INIS)

    Vega, J.J.; Reynoso, R.; Calvet, H. Carrillo

    2009-01-01

    Digital Pulse Shape Analysis (DPSA) by artificial neural networks (ANN) is becoming an important tool to extract relevant information from digitized signals in different areas. In this paper, we present a systematic evidence of how the concomitant noise that distorts the signals or patterns to be identified by an ANN set limits to its learning capability. Also, we present evidence that explains overtraining as a competition between the relevant pattern features, on the one side, against the signal noise, on the other side, as the main cause defining the shape of the error surface in weight space and, consequently, determining the steepest descent path that controls the ANN adaptation process.

  6. Vitamin D controls T cell antigen receptor signaling and activation of human T cells

    DEFF Research Database (Denmark)

    von Essen, Marina Rode; Kongsbak-Wismann, Martin; Schjerling, Peter

    2010-01-01

    Phospholipase C (PLC) isozymes are key signaling proteins downstream of many extracellular stimuli. Here we show that naive human T cells had very low expression of PLC-gamma1 and that this correlated with low T cell antigen receptor (TCR) responsiveness in naive T cells. However, TCR triggering...... led to an upregulation of approximately 75-fold in PLC-gamma1 expression, which correlated with greater TCR responsiveness. Induction of PLC-gamma1 was dependent on vitamin D and expression of the vitamin D receptor (VDR). Naive T cells did not express VDR, but VDR expression was induced by TCR...... signaling via the alternative mitogen-activated protein kinase p38 pathway. Thus, initial TCR signaling via p38 leads to successive induction of VDR and PLC-gamma1, which are required for subsequent classical TCR signaling and T cell activation....

  7. Oxidized Extracellular DNA as a Stress Signal in Human Cells

    Directory of Open Access Journals (Sweden)

    Aleksei V. Ermakov

    2013-01-01

    Full Text Available The term “cell-free DNA” (cfDNA was recently coined for DNA fragments from plasma/serum, while DNA present in in vitro cell culture media is known as extracellular DNA (ecDNA. Under oxidative stress conditions, the levels of oxidative modification of cellular DNA and the rate of cell death increase. Dying cells release their damaged DNA, thus, contributing oxidized DNA fragments to the pool of cfDNA/ecDNA. Oxidized cell-free DNA could serve as a stress signal that promotes irradiation-induced bystander effect. Evidence points to TLR9 as a possible candidate for oxidized DNA sensor. An exposure to oxidized ecDNA stimulates a synthesis of reactive oxygen species (ROS that evokes an adaptive response that includes transposition of the homologous loci within the nucleus, polymerization and the formation of the stress fibers of the actin, as well as activation of the ribosomal gene expression, and nuclear translocation of NF-E2 related factor-2 (NRF2 that, in turn, mediates induction of phase II detoxifying and antioxidant enzymes. In conclusion, the oxidized DNA is a stress signal released in response to oxidative stress in the cultured cells and, possibly, in the human body; in particular, it might contribute to systemic abscopal effects of localized irradiation treatments.

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

    Science.gov (United States)

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

    2014-10-01

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

  9. Association of reactive oxygen species-mediated signal transduction with in vitro apoptosis sensitivity in chronic lymphocytic leukemia B cells.

    Directory of Open Access Journals (Sweden)

    Adam L Palazzo

    Full Text Available BACKGROUND: Chronic lymphocytic leukemia (CLL is a B cell malignancy with a variable clinical course and unpredictable response to therapeutic agents. Single cell network profiling (SCNP utilizing flow cytometry measures alterations in signaling biology in the context of molecular changes occurring in malignancies. In this study SCNP was used to identify proteomic profiles associated with in vitro apoptotic responsiveness of CLL B cells to fludarabine, as a basis for ultimately linking these with clinical outcome. METHODOLOGY/PRINCIPAL FINDING: SCNP was used to quantify modulated-signaling of B cell receptor (BCR network proteins and in vitro F-ara-A mediated apoptosis in 23 CLL samples. Of the modulators studied the reactive oxygen species, hydrogen peroxide (H₂O₂, a known intracellular second messenger and a general tyrosine phosphatase inhibitor stratified CLL samples into two sub-groups based on the percentage of B cells in a CLL sample with increased phosphorylation of BCR network proteins. Separately, in the same patient samples, in vitro exposure to F-ara-A also identified two sub-groups with B cells showing competence or refractoriness to apoptotic induction. Statistical analysis showed that in vitro F-ara-A apoptotic proficiency was highly associated with the proficiency of CLL B cells to undergo H₂O₂-augmented signaling. CONCLUSIONS/SIGNIFICANCE: This linkage in CLL B cells among the mechanisms governing chemotherapy-induced apoptosis increased signaling of BCR network proteins and a likely role of phosphatase activity suggests a means of stratifying patients for their response to F-ara-A based regimens. Future studies will examine the clinical applicability of these findings and also the utility of this approach in relating mechanism to function of therapeutic agents.

  10. Pi sensing and signalling: from prokaryotic to eukaryotic cells.

    Science.gov (United States)

    Qi, Wanjun; Baldwin, Stephen A; Muench, Stephen P; Baker, Alison

    2016-06-15

    Phosphorus is one of the most important macronutrients and is indispensable for all organisms as a critical structural component as well as participating in intracellular signalling and energy metabolism. Sensing and signalling of phosphate (Pi) has been extensively studied and is well understood in single-cellular organisms like bacteria (Escherichia coli) and Saccharomyces cerevisiae In comparison, the mechanism of Pi regulation in plants is less well understood despite recent advances in this area. In most soils the available Pi limits crop yield, therefore a clearer understanding of the molecular basis underlying Pi sensing and signalling is of great importance for the development of plants with improved Pi use efficiency. This mini-review compares some of the main Pi regulation pathways in prokaryotic and eukaryotic cells and identifies similarities and differences among different organisms, as well as providing some insight into future research. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

  11. Nrf2 regulates cellular behaviors and Notch signaling in oral squamous cell carcinoma cells.

    Science.gov (United States)

    Fan, Hong; Paiboonrungruan, Chorlada; Zhang, Xinyan; Prigge, Justin R; Schmidt, Edward E; Sun, Zheng; Chen, Xiaoxin

    2017-11-04

    Oxidative stress is known to play a pivotal role in the development of oral squamous cell carcinoma (OSCC). We have demonstrated that activation of the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway has chemopreventive effects against oxidative stress-associated OSCC. However, Nrf2 have dual roles in cancer development; while it prevents carcinogenesis of normal cells, hyperactive Nrf2 also promotes the survival of cancer cells. This study is aimed to understand the function of Nrf2 in regulating cellular behaviors of OSCC cells, and the potential mechanisms through which Nrf2 facilitates OSCC. We established the Nrf2-overexpressing and Nrf2-knockdown OSCC cell lines, and examined the function of Nrf2 in regulating cell proliferation, migration, invasion, cell cycle and colony formation. Our data showed that Nrf2 overexpression promoted cancer phenotypes in OSCC cells, whereas Nrf2 silencing inhibited these phenotypes. In addition, Nrf2 positively regulated Notch signaling pathway in OSCC cells in vitro. Consistent with this observation, Nrf2 activation in Keap1 -/- mice resulted in not only hyperproliferation of squamous epithelial cells in mouse tongue as evidenced by increased expression of PCNA, but also activation of Notch signaling in these cells as evidenced by increased expression of NICD1 and Hes1. In conclusion, Nrf2 regulates cancer behaviors and Notch signaling in OSCC cells. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Analysis of market signals in a competitive electricity market using components of network rental

    International Nuclear Information System (INIS)

    Amarasinghe, L.Y.C.; Annakkage, U.D.

    2009-01-01

    In the competitive electricity market, Locational Marginal Prices (LMPs) are important pricing signals for the participants as the effects of transmission losses and binding constraints are embedded in LMPs. While these LMPs provide valuable information at each location, they do not provide a detailed description in terms of contributing terms. The LMP components, on the other hand, show the explicit decomposition of LMP into contributing components, and thus, can be considered as better market signals. However, the effects of transmission losses cannot be explicitly seen from the LMP components. In this paper, the components of network rental is proposed to be used as a method in analyzing market signals, by decomposing the network rental into contributing components among the consumers. Since, the network rental is the surplus paid by all the consumers, components of network rental show how each consumer has actually overpaid due to losses and each binding constraint separately. A case study is also presented to demonstrate the potential of this proposed method in market signal analysis. (author)

  13. Processing of signals from an ion-elective electrode array by a neural network

    NARCIS (Netherlands)

    Bos, M.; Bos, A.; van der Linden, W.E.

    1990-01-01

    Neural network software is described for processing the signals of arrays of ion-selective electrodes. The performance of the software was tested in the simultaneous determination of calcium and copper(II) ions in binary mixtures of copper(II) nitrate and calcium chloride and the simultaneous

  14. Determination of outdoor signal propagation via visibility analysis in outdoor wireless networks

    Directory of Open Access Journals (Sweden)

    Mustafa Coşar

    2017-02-01

    Full Text Available Wireless networks on university campuses has gained importance in recent years. These networks in major areas such as university campuses, are faced with many problems during the planning, design and establishment. These problems are among the first that comes to mind, the physical properties of the campus and is selected according to the characteristics of network equipment. There is no doubt at all points of a wireless network set up in order to provide uninterrupted service and quality of the signal is expected to be good. However, it should be understood literally cannot meet these expectations. Therefore, to solve many problems to campus planning and design can be made to have acceptable signal distribution will have the appropriate use of and satisfaction with increasing effect. In this study, due to the start of construction on the North Campus of Hitit University, wireless signal spread using the current spread has been determined with the help of geographic information systems visibility analysis. An area of 56 hectares, with the total of 9 AP the acceptable signal distribution was obtained.

  15. 47 CFR 73.4157 - Network signals which adversely affect affiliate broadcast service.

    Science.gov (United States)

    2010-10-01

    ... affiliate broadcast service. 73.4157 Section 73.4157 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES RADIO BROADCAST SERVICES Rules Applicable to All Broadcast Stations § 73.4157 Network signals which adversely affect affiliate broadcast service. See Public Notice, FCC 79-387...

  16. Received signal strength in large-scale wireless relay sensor network: a stochastic ray approach

    NARCIS (Netherlands)

    Hu, L.; Chen, Y.; Scanlon, W.G.

    2011-01-01

    The authors consider a point percolation lattice representation of a large-scale wireless relay sensor network (WRSN) deployed in a cluttered environment. Each relay sensor corresponds to a grid point in the random lattice and the signal sent by the source is modelled as an ensemble of photons that

  17. Dynamical patterns of calcium signaling in a functional model of neuron-astrocyte networks

    DEFF Research Database (Denmark)

    Postnov, D.E.; Koreshkov, R.N.; Brazhe, N.A.

    2009-01-01

    We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission...

  18. Radio Signal Augmentation for Improved Training of a Convolutional Neural Network

    Science.gov (United States)

    2016-09-01

    TECHNICAL REPORT 3055 September 2016 Radio Signal Augmentation for Improved Training of a Convolutional Neural Network Daniel...Security Branch Under authority of G. Settelmayer, Head Information Operations Division EXECUTIVE SUMMARY This technical report presents the...might recognize it across various mediums, even if brush strokes do not fundamentally resemble photographic pixels. 9 4. CONCLUSION The experiments

  19. Signal Quality Outage Analysis for Ultra-Reliable Communications in Cellular Networks

    DEFF Research Database (Denmark)

    Gerardino, Guillermo Andrés Pocovi; Alvarez, Beatriz Soret; Lauridsen, Mads

    2015-01-01

    Ultra-reliable communications over wireless will open the possibility for a wide range of novel use cases and applications. In cellular networks, achieving reliable communication is challenging due to many factors, particularly the fading of the desired signal and the interference. In this regard...

  20. Neural Network Detection of Ventricular Late Potentials in ECG Signals Using Wavelet Transform Extracted Parameters

    National Research Council Canada - National Science Library

    Mousa, Ayad

    2001-01-01

    .... In this work, discrete Wavelet Transform (DWT) and Artificial Neural Networks (ANN) are applied in the analysis of ECG signals in order to identify VLPs, Results of this analysis are used to classify patients with and without VLPs in their ECGs...

  1. Interpretation of ECG Signal with a Multi-Layer Neural Network

    Directory of Open Access Journals (Sweden)

    Dumitru Ostafe

    2008-01-01

    Full Text Available In this article there are introduced the resultsobtained in the interpretation of the components of abiomedical signal, ECG, by using a multi-layer neuralnetwork, using the backpropagation algorithm. The neuralnetwork was simulated with the Neuroshell2.0 program. Thenew obtained network was used within the program ofautomate diagnosing of the ECG.

  2. A structured approach for the engineering of biochemical network models, illustrated for signalling pathways

    NARCIS (Netherlands)

    Breitling, Rainer; Gilbert, David; Heiner, Monika; Orton, Richard

    Quantitative models of biochemical networks (signal transduction cascades, metabolic pathways, gene regulatory circuits) are a central component of modern systems biology. Building and managing these complex models is a major challenge that can benefit from the application of formal methods adopted

  3. Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming.

    Science.gov (United States)

    Guziolowski, Carito; Videla, Santiago; Eduati, Federica; Thiele, Sven; Cokelaer, Thomas; Siegel, Anne; Saez-Rodriguez, Julio

    2013-09-15

    Logic modeling is a useful tool to study signal transduction across multiple pathways. Logic models can be generated by training a network containing the prior knowledge to phospho-proteomics data. The training can be performed using stochastic optimization procedures, but these are unable to guarantee a global optima or to report the complete family of feasible models. This, however, is essential to provide precise insight in the mechanisms underlaying signal transduction and generate reliable predictions. We propose the use of Answer Set Programming to explore exhaustively the space of feasible logic models. Toward this end, we have developed caspo, an open-source Python package that provides a powerful platform to learn and characterize logic models by leveraging the rich modeling language and solving technologies of Answer Set Programming. We illustrate the usefulness of caspo by revisiting a model of pro-growth and inflammatory pathways in liver cells. We show that, if experimental error is taken into account, there are thousands (11 700) of models compatible with the data. Despite the large number, we can extract structural features from the models, such as links that are always (or never) present or modules that appear in a mutual exclusive fashion. To further characterize this family of models, we investigate the input-output behavior of the models. We find 91 behaviors across the 11 700 models and we suggest new experiments to discriminate among them. Our results underscore the importance of characterizing in a global and exhaustive manner the family of feasible models, with important implications for experimental design. caspo is freely available for download (license GPLv3) and as a web service at http://caspo.genouest.org/. Supplementary materials are available at Bioinformatics online. santiago.videla@irisa.fr.

  4. Integrative modelling of the influence of MAPK network on cancer cell fate decision.

    Directory of Open Access Journals (Sweden)

    Luca Grieco

    2013-10-01

    Full Text Available The Mitogen-Activated Protein Kinase (MAPK network consists of tightly interconnected signalling pathways involved in diverse cellular processes, such as cell cycle, survival, apoptosis and differentiation. Although several studies reported the involvement of these signalling cascades in cancer deregulations, the precise mechanisms underlying their influence on the balance between cell proliferation and cell death (cell fate decision in pathological circumstances remain elusive. Based on an extensive analysis of published data, we have built a comprehensive and generic reaction map for the MAPK signalling network, using CellDesigner software. In order to explore the MAPK responses to different stimuli and better understand their contributions to cell fate decision, we have considered the most crucial components and interactions and encoded them into a logical model, using the software GINsim. Our logical model analysis particularly focuses on urinary bladder cancer, where MAPK network deregulations have often been associated with specific phenotypes. To cope with the combinatorial explosion of the number of states, we have applied novel algorithms for model reduction and for the compression of state transition graphs, both implemented into the software GINsim. The results of systematic simulations for different signal combinations and network perturbations were found globally coherent with published data. In silico experiments further enabled us to delineate the roles of specific components, cross-talks and regulatory feedbacks in cell fate decision. Finally, tentative proliferative or anti-proliferative mechanisms can be connected with established bladder cancer deregulations, namely Epidermal Growth Factor Receptor (EGFR over-expression and Fibroblast Growth Factor Receptor 3 (FGFR3 activating mutations.

  5. A network signal amplification strategy of ultrasensitive photoelectrochemical immunosensing carcinoembryonic antigen based on CdSe/melamine network as label.

    Science.gov (United States)

    Li, Jiaojiao; Zhang, Yong; Kuang, Xuan; Wang, Zhiling; Wei, Qin

    2016-11-15

    Taking advantage of CdSe/melamine network as label and Au-TiO2 as substrate, this work developed a novel kind of signal amplification strategy for fabricating photoelectrochemical (PEC) immunoassay. The melamine, a star-shaped triamino molecule, was firstly used for readily capturing CdSe QDs and forming a CdSe/melamine network, which was formed through strong interactions between the carboxyl groups of TGA-stabilized CdSe QDs and the three amino groups of each melamine molecule. In this strategy, the primary antibody (Ab1) was immobilized onto Au-TiO2 substrate, which made the photoelectric conversion efficiency increase significantly. After the formed Ab2-CdSe/melamine network labels were captured onto the electrode surface via the specific antibody-antigen interaction, the photoelectric activity could be further enhanced via the interaction between the Au-TiO2 substrate and CdSe/melamine network. Due to this amplification of PEC signals and the special structure of the label, the fabricated PEC immunosensor was applied for sensitive and specific detection of cancer biomarker carcinoembryonic antigen (CEA), and displayed a wide linear range (0.005-1000ngmL(-1)) and low detection limit (5pgmL(-1)). In addition, the immunosensor was performed with good stability and reproducibility, and the results to analyze human serum samples were satisfactory. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Hedgehog signaling establishes precursors for germline stem cell niches by regulating cell adhesion.

    Science.gov (United States)

    Lai, Chun-Ming; Lin, Kun-Yang; Kao, Shih-Han; Chen, Yi-Ning; Huang, Fu; Hsu, Hwei-Jan

    2017-05-01

    Stem cells require different types of supporting cells, or niches, to control stem cell maintenance and differentiation. However, little is known about how those niches are formed. We report that in the development of the Drosophila melanogaster ovary, the Hedgehog (Hh) gradient sets differential cell affinity for somatic gonadal precursors to specify stromal intermingled cells, which contributes to both germline stem cell maintenance and differentiation niches in the adult. We also report that Traffic Jam (an orthologue of a large Maf transcription factor in mammals) is a novel transcriptional target of Hh signaling to control cell-cell adhesion by negative regulation of E-cadherin expression. Our results demonstrate the role of Hh signaling in niche establishment by segregating somatic cell lineages for differentiation. © 2017 Lai et al.

  7. Ikaros limits follicular B cell activation by regulating B cell receptor signaling pathways

    Energy Technology Data Exchange (ETDEWEB)

    Heizmann, Beate [Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch (France); Sellars, MacLean [Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch (France); David Geffen School of Medicine at UCLA, Los Angeles, CA 90095 (United States); Macias-Garcia, Alejandra [Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch (France); Institute for Medical Engineering and Science at MIT, Cambridge, MA 02139 (United States); Chan, Susan, E-mail: scpk@igbmc.fr [Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch (France); Kastner, Philippe, E-mail: scpk@igbmc.fr [Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), INSERM U964, CNRS UMR 7104, Université de Strasbourg, 67404 Illkirch (France); Faculté de Médecine, Université de Strasbourg, Strasbourg (France)

    2016-02-12

    The Ikaros transcription factor is essential for early B cell development, but its effect on mature B cells is debated. We show that Ikaros is required to limit the response of naive splenic B cells to B cell receptor signals. Ikaros deficient follicular B cells grow larger and enter cell cycle faster after anti-IgM stimulation. Unstimulated mutant B cells show deregulation of positive and negative regulators of signal transduction at the mRNA level, and constitutive phosphorylation of ERK, p38, SYK, BTK, AKT and LYN. Stimulation results in enhanced and prolonged ERK and p38 phosphorylation, followed by hyper-proliferation. Pharmacological inhibition of ERK and p38 abrogates the increased proliferative response of Ikaros deficient cells. These results suggest that Ikaros functions as a negative regulator of follicular B cell activation.

  8. Ikaros limits follicular B cell activation by regulating B cell receptor signaling pathways

    International Nuclear Information System (INIS)

    Heizmann, Beate; Sellars, MacLean; Macias-Garcia, Alejandra; Chan, Susan; Kastner, Philippe

    2016-01-01

    The Ikaros transcription factor is essential for early B cell development, but its effect on mature B cells is debated. We show that Ikaros is required to limit the response of naive splenic B cells to B cell receptor signals. Ikaros deficient follicular B cells grow larger and enter cell cycle faster after anti-IgM stimulation. Unstimulated mutant B cells show deregulation of positive and negative regulators of signal transduction at the mRNA level, and constitutive phosphorylation of ERK, p38, SYK, BTK, AKT and LYN. Stimulation results in enhanced and prolonged ERK and p38 phosphorylation, followed by hyper-proliferation. Pharmacological inhibition of ERK and p38 abrogates the increased proliferative response of Ikaros deficient cells. These results suggest that Ikaros functions as a negative regulator of follicular B cell activation.

  9. NIRF constitutes a nodal point in the cell cycle network and is a candidate tumor suppressor.

    Science.gov (United States)

    Mori, Tsutomu; Ikeda, Daisuke D; Fukushima, Toshihiko; Takenoshita, Seiichi; Kochi, Hideo

    2011-10-01

    In biological networks, a small number of "hub" proteins play critical roles in the network integrity and functions. The cell cycle network orchestrates versatile cellular functions through interactions between many signaling modules, whose defects impair diverse cellular processes, often leading to cancer. However, the network architecture and molecular basis that ensure proper coordination between distinct modules are unclear. Here, we show that the ubiquitin ligase NIRF (also known as UHRF2), which induces G1 arrest, interacts with multiple cell cycle proteins including cyclins (A2, B1, D1 and E1), p53 and pRB, and ubiquitinates cyclins D1 and E1. Consistent with its versatility, a bioinformatic network analysis demonstrated that NIRF is an intermodular hub protein that is responsible for the coordination of multiple network modules. Notably, intermodular hubs are frequently associated with oncogenesis. Indeed, we detected loss of heterozygosity of the NIRF gene in several kinds of tumors. When a cancer outlier profile analysis was applied to the Oncomine database, loss of the NIRF gene was found at statistically significant levels in diverse tumors. Importantly, a recurrent microdeletion targeting NIRF was observed in non-small cell lung carcinoma. Furthermore, NIRF is immediately adjacent to the single nucleotide polymorphism rs719725, which is reportedly associated with the risk of colorectal cancer. These observations suggest that NIRF occupies a prominent position within the cell cycle network, and is a strong candidate for a tumor suppressor whose aberration contributes to the pathogenesis of diverse malignancies. © 2011 Landes Bioscience

  10. Sonic hedgehog signaling in Basal cell nevus syndrome.

    Science.gov (United States)

    Athar, Mohammad; Li, Changzhao; Kim, Arianna L; Spiegelman, Vladimir S; Bickers, David R

    2014-09-15

    The hedgehog (Hh) signaling pathway is considered to be a major signal transduction pathway during embryonic development, but it usually shuts down after birth. Aberrant Sonic hedgehog (Shh) activation during adulthood leads to neoplastic growth. Basal cell carcinoma (BCC) of the skin is driven by this pathway. Here, we summarize information related to the pathogenesis of this neoplasm, discuss pathways that crosstalk with Shh signaling, and the importance of the primary cilium in this neoplastic process. The identification of the basic/translational components of Shh signaling has led to the discovery of potential mechanism-driven druggable targets and subsequent clinical trials have confirmed their remarkable efficacy in treating BCCs, particularly in patients with nevoid BCC syndrome (NBCCS), an autosomal dominant disorder in which patients inherit a germline mutation in the tumor-suppressor gene Patched (Ptch). Patients with NBCCS develop dozens to hundreds of BCCs due to derepression of the downstream G-protein-coupled receptor Smoothened (SMO). Ptch mutations permit transposition of SMO to the primary cilium followed by enhanced expression of transcription factors Glis that drive cell proliferation and tumor growth. Clinical trials with the SMO inhibitor, vismodegib, showed remarkable efficacy in patients with NBCCS, which finally led to its FDA approval in 2012. ©2014 American Association for Cancer Research.

  11. Applications of autoassociative neural networks for signal validation in accident management

    International Nuclear Information System (INIS)

    Fantoni, P.; Mazzola, A.

    1994-01-01

    The OECD Halden Reactor Project has been working for several years with computer based systems for determination on plant status including early fault detection and signal validation. The method here presented explores the possibility to use a neural network approach to validate important process signals during normal and abnormal plant conditions. In BWR plants, signal validation has two important applications: reliable thermal limits calculation and reliable inputs to other computerized systems that support the operator during accident scenarious. This work shows how a properly trained autoassociative neural network can promptly detect faulty process signal measurements and produce a best estimate of the actual process value. Noise has been artificially added to the input to evaluate the network ability to respond in a very low signal to noise ratio environment. Training and test datasets have been simulated by the real time transient simulator code APROS. Future development addresses the validation of the model through the use of real data from the plant. (author). 5 refs, 17 figs

  12. EEG signal classification using PSO trained RBF neural network for epilepsy identification

    Directory of Open Access Journals (Sweden)

    Sandeep Kumar Satapathy

    Full Text Available The electroencephalogram (EEG is a low amplitude signal generated in the brain, as a result of information flow during the communication of several neurons. Hence, careful analysis of these signals could be useful in understanding many human brain disorder diseases. One such disease topic is epileptic seizure identification, which can be identified via a classification process of the EEG signal after preprocessing with the discrete wavelet transform (DWT. To classify the EEG signal, we used a radial basis function neural network (RBFNN. As shown herein, the network can be trained to optimize the mean square error (MSE by using a modified particle swarm optimization (PSO algorithm. The key idea behind the modification of PSO is to introduce a method to overcome the problem of slow searching in and around the global optimum solution. The effectiveness of this procedure was verified by an experimental analysis on a benchmark dataset which is publicly available. The result of our experimental analysis revealed that the improvement in the algorithm is significant with respect to RBF trained by gradient descent and canonical PSO. Here, two classes of EEG signals were considered: the first being an epileptic and the other being non-epileptic. The proposed method produced a maximum accuracy of 99% as compared to the other techniques. Keywords: Electroencephalography, Radial basis function neural network, Particle swarm optimization, Discrete wavelet transform, Machine learning

  13. The signal extraction of fetal heart rate based on wavelet transform and BP neural network

    Science.gov (United States)

    Yang, Xiao Hong; Zhang, Bang-Cheng; Fu, Hu Dai

    2005-04-01

    This paper briefly introduces the collection and recognition of bio-medical signals, designs the method to collect FM signals. A detailed discussion on the system hardware, structure and functions is also given. Under LabWindows/CVI,the hardware and the driver do compatible, the hardware equipment work properly actively. The paper adopts multi threading technology for real-time analysis and makes use of latency time of CPU effectively, expedites program reflect speed, improves the program to perform efficiency. One threading is collecting data; the other threading is analyzing data. Using the method, it is broaden to analyze the signal in real-time. Wavelet transform to remove the main interference in the FM and by adding time-window to recognize with BP network; Finally the results of collecting signals and BP networks are discussed. 8 pregnant women's signals of FM were collected successfully by using the sensor. The correctness rate of BP network recognition is about 83.3% by using the above measure.

  14. Role of Notch signaling in cell-fate determination of human mammary stem/progenitor cells

    International Nuclear Information System (INIS)

    Dontu, Gabriela; Jackson, Kyle W; McNicholas, Erin; Kawamura, Mari J; Abdallah, Wissam M; Wicha, Max S

    2004-01-01

    Notch signaling has been implicated in the regulation of cell-fate decisions such as self-renewal of adult stem cells and differentiation of progenitor cells along a particular lineage. Moreover, depending on the cellular and developmental context, the Notch pathway acts as a regulator of cell survival and cell proliferation. Abnormal expression of Notch receptors has been found in different types of epithelial metaplastic lesions and neoplastic lesions, suggesting that Notch may act as a proto-oncogene. The vertebrate Notch1 and Notch4 homologs are involved in normal development of the mammary gland, and mutated forms of these genes are associated with development of mouse mammary tumors. In order to determine the role of Notch signaling in mammary cell-fate determination, we have utilized a newly described in vitro system in which mammary stem/progenitor cells can be cultured in suspension as nonadherent 'mammospheres'. Notch signaling was activated using exogenous ligands, or was inhibited using previously characterized Notch signaling antagonists. Utilizing this system, we demonstrate that Notch signaling can act on mammary stem cells to promote self-renewal and on early progenitor cells to promote their proliferation, as demonstrated by a 10-fold increase in secondary mammosphere formation upon addition of a Notch-activating DSL peptide. In addition to acting on stem cells, Notch signaling is also able to act on multipotent progenitor cells, facilitating myoepithelial lineage-specific commitment and proliferation. Stimulation of this pathway also promotes branching morphogenesis in three-dimensional Matrigel cultures. These effects are completely inhibited by a Notch4 blocking antibody or a gamma secretase inhibitor that blocks Notch processing. In contrast to the effects of Notch signaling on mammary stem/progenitor cells, modulation of this pathway has no discernable effect on fully committed, differentiated, mammary epithelial cells. These studies

  15. Icaritin Reduces Oral Squamous Cell Carcinoma Progression via the Inhibition of STAT3 Signaling

    Directory of Open Access Journals (Sweden)

    Jian-Guang Yang

    2017-01-01

    Full Text Available Icaritin, a traditional Chinese medicine, possesses antitumor activity. The current study aimed to investigate icaritin effect and potential mechanism on oral squamous cell carcinoma (OSCC development. OSCC cells proliferation, apoptosis, and autophagy were analyzed after incubation with icaritin at different concentrations and incubation times. The expressions of proteins related to proliferation, apoptosis, and autophagy, as well as signal transducer and activator of transcription 3 (STAT3 signal network, were also evaluated by western blot. Furthermore, STAT3 was knocked down by siRNA transfection to determine STAT3 role in OSCC cell proliferation and apoptosis. An oral specific carcinogenesis mouse model was used to explore icaritin effect on OSCC in vivo. Icaritin significantly inhibited OSCC proliferation in vitro and reduced the expression of both the cell-cycle progression proteins cyclin A2 and cyclin D1. Besides, icaritin increased cleaved caspase 3 and cleaved poly-(ADP-ribose polymerase expression leading to apoptosis, and it activated autophagy. Icaritin significantly inhibited the expression of phospho-STAT3 (p-STAT3 in a dose- and time-dependent manner. In the in vivo experiment, the number of malignant tumors in the icaritin-treated group was significantly lower than the control. Overall, icaritin suppressed proliferation, promoted apoptosis and autophagy, and inhibited STAT3 signaling in OSCC in vitro and in vivo. In conclusion, icaritin might be a potential therapeutic agent against OSCC development.

  16. The Genome-Wide Analysis of Carcinoembryonic Antigen Signaling by Colorectal Cancer Cells Using RNA Sequencing.

    Directory of Open Access Journals (Sweden)

    Olga Bajenova

    Full Text Available Сarcinoembryonic antigen (CEA, CEACAM5, CD66 is a promoter of metastasis in epithelial cancers that is widely used as a prognostic clinical marker of metastasis. The aim of this study is to identify the network of genes that are associated with CEA-induced colorectal cancer liver metastasis. We compared the genome-wide transcriptomic profiles of CEA positive (MIP101 clone 8 and CEA negative (MIP 101 colorectal cancer cell lines with different metastatic potential in vivo. The CEA-producing cells displayed quantitative changes in the level of expression for 100 genes (over-expressed or down-regulated. They were confirmed by quantitative RT-PCR. The KEGG pathway analysis identified 4 significantly enriched pathways: cytokine-cytokine receptor interaction, MAPK signaling pathway, TGF-beta signaling pathway and pyrimidine metabolism. Our results suggest that CEA production by colorectal cancer cells triggers colorectal cancer progression by inducing the epithelial- mesenchymal transition, increasing tumor cell invasiveness into the surrounding tissues and suppressing stress and apoptotic signaling. The novel gene expression distinctions establish the relationships between the existing cancer markers and implicate new potential biomarkers for colorectal cancer hepatic metastasis.

  17. Gene network and pathway analysis of bovine mammary tissue challenged with Streptococcus uberis reveals induction of cell profileration and inhibition of PPARγ signaling as potential mechanism for the negative relationships between immune response and lipid metabolism

    DEFF Research Database (Denmark)

    Moyes, Kasey M; Drackley, James K; Morin, Dawn E

    2009-01-01

    with immune system function (e.g., CD14, IL8, IL1B, and TLR2) and negative relationships with genes involved with lipid metabolism (e.g., GPAM, SCD, FABP4, CD36, and LPL) and antioxidant activity (SOD1). Conclusion Results provided novel information into the early signaling and metabolic pathways in mammary......Background Information generated via microarrays might uncover interactions between the mammary gland and Streptococcus uberis (S. uberis) that could help identify control measures for the prevention and spread of S. uberis mastitis, as well as improve overall animal health and welfare....../or metabolic responses to mastitis challenge with S. uberis O140J. Results Streptococcus uberis IMI resulted in 2,102 (1,939 annotated) differentially expressed genes (DEG). Within this set of DEG, we uncovered 20 significantly enriched canonical pathways (with 20 to 61 genes each), the majority of which were...

  18. Detection of directional eye movements based on the electrooculogram signals through an artificial neural network

    International Nuclear Information System (INIS)

    Erkaymaz, Hande; Ozer, Mahmut; Orak, İlhami Muharrem

    2015-01-01

    The electrooculogram signals are very important at extracting information about detection of directional eye movements. Therefore, in this study, we propose a new intelligent detection model involving an artificial neural network for the eye movements based on the electrooculogram signals. In addition to conventional eye movements, our model also involves the detection of tic and blinking of an eye. We extract only two features from the electrooculogram signals, and use them as inputs for a feed-forwarded artificial neural network. We develop a new approach to compute these two features, which we call it as a movement range. The results suggest that the proposed model have a potential to become a new tool to determine the directional eye movements accurately

  19. TROVE: A User-friendly Tool for Visualizing and Analyzing Cancer Hallmarks in Signaling Networks.

    Science.gov (United States)

    Chua, Huey Eng; Bhowmick, Sourav S; Zheng, Jie

    2017-09-22

    Cancer hallmarks, a concept that seeks to explain the complexity of cancer initiation and development, provide a new perspective of studying cancer signaling which could lead to a greater understanding of this complex disease. However, to the best of our knowledge, there is currently a lack of tools that support such hallmark-based study of the cancer signaling network, thereby impeding the gain of knowledge in this area. We present TROVE, a user-friendly software that facilitates hallmark annotation, visualization and analysis in cancer signaling networks. In particular, TROVE facilitates hallmark analysis specific to particular cancer types. Available under the Eclipse Public License from: https://sites.google.com/site/cosbyntu/softwares/trove and https://github.com/trove2017/Trove. hechua@ntu.edu.sg or assourav@ntu.edu.sg. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  20. Sensors and signal transduction pathways in vertebrate cell volume regulation

    DEFF Research Database (Denmark)

    Hoffmann, Else K; Pedersen, Stine F

    2006-01-01

    to the identification of transporter binding partners such as protein kinases and phosphatases, cytoskeletal elements and lipids. Considerable progress has also been made recently in understanding the upstream elements in volume sensing and volume-sensitive signal transduction, and salient features of these systems...... will be discussed. In contrast to the simple pathway of osmosensing in yeast, cells from vertebrate organisms appear to exhibit multiple volume sensing systems, the specific mechanism(s) activated being cell type- and stimulus-dependent. Candidate sensors include integrins and growth factor receptors, while other...

  1. Cell volume homeostatic mechanisms: effectors and signalling pathways

    DEFF Research Database (Denmark)

    Hoffmann, E K; Pedersen, Stine Helene Falsig

    2011-01-01

    Cell volume homeostasis and its fine-tuning to the specific physiological context at any given moment are processes fundamental to normal cell function. The understanding of cell volume regulation owes much to August Krogh, yet has advanced greatly over the last decades. In this review, we outline...... the historical context of studies of cell volume regulation, focusing on the lineage started by Krogh, Bodil Schmidt-Nielsen, Hans-Henrik Ussing, and their students. The early work was focused on understanding the functional behaviour, kinetics and thermodynamics of the volume-regulatory ion transport mechanisms....... Later work addressed the mechanisms through which cellular signalling pathways regulate the volume regulatory effectors or flux pathways. These studies were facilitated by the molecular identification of most of the relevant channels and transporters, and more recently also by the increased...

  2. Retinoic acid signalling in thymocytes regulates T cell development

    DEFF Research Database (Denmark)

    Wendland, Kerstin; Sitnik, Katarzyna Maria; Kotarsky, Knut

    The Vitamin A derivative retinoic acid (RA) works as a ligand for a family of nuclearRA receptors (RARα, RARβ and RARγ) which form heterodimers with retinoid Xreceptors (RXR). These complexes function as ligand-activated transcription factors,recognizing specific RA responsive elements in the reg......The Vitamin A derivative retinoic acid (RA) works as a ligand for a family of nuclearRA receptors (RARα, RARβ and RARγ) which form heterodimers with retinoid Xreceptors (RXR). These complexes function as ligand-activated transcription factors,recognizing specific RA responsive elements...... in the regulatory regions of targetgenes. RA has been reported to play a direct role in regulating multiple aspects of peripheralT cell responses1, but whether endogenous RA signalling occurs in developingthymocytes and the potential impact of such signals in regulating T cell developmentremains unclear. To address......RARα. This blocks RA signalling in developing thymocytes from the DN3/4 stageonwards and thus allows us to study the role of RA in T cell development...

  3. Connection Setup Signaling Scheme with Flooding-Based Path Searching for Diverse-Metric Network

    Science.gov (United States)

    Kikuta, Ko; Ishii, Daisuke; Okamoto, Satoru; Oki, Eiji; Yamanaka, Naoaki

    Connection setup on various computer networks is now achieved by GMPLS. This technology is based on the source-routing approach, which requires the source node to store metric information of the entire network prior to computing a route. Thus all metric information must be distributed to all network nodes and kept up-to-date. However, as metric information become more diverse and generalized, it is hard to update all information due to the huge update overhead. Emerging network services and applications require the network to support diverse metrics for achieving various communication qualities. Increasing the number of metrics supported by the network causes excessive processing of metric update messages. To reduce the number of metric update messages, another scheme is required. This paper proposes a connection setup scheme that uses flooding-based signaling rather than the distribution of metric information. The proposed scheme requires only flooding of signaling messages with requested metric information, no routing protocol is required. Evaluations confirm that the proposed scheme achieves connection establishment without excessive overhead. Our analysis shows that the proposed scheme greatly reduces the number of control messages compared to the conventional scheme, while their blocking probabilities are comparable.

  4. Signal processing and neural network toolbox and its application to failure diagnosis and prognosis

    Science.gov (United States)

    Tu, Fang; Wen, Fang; Willett, Peter K.; Pattipati, Krishna R.; Jordan, Eric H.

    2001-07-01

    Many systems are comprised of components equipped with self-testing capability; however, if the system is complex involving feedback and the self-testing itself may occasionally be faulty, tracing faults to a single or multiple causes is difficult. Moreover, many sensors are incapable of reliable decision-making on their own. In such cases, a signal processing front-end that can match inference needs will be very helpful. The work is concerned with providing an object-oriented simulation environment for signal processing and neural network-based fault diagnosis and prognosis. In the toolbox, we implemented a wide range of spectral and statistical manipulation methods such as filters, harmonic analyzers, transient detectors, and multi-resolution decomposition to extract features for failure events from data collected by data sensors. Then we evaluated multiple learning paradigms for general classification, diagnosis and prognosis. The network models evaluated include Restricted Coulomb Energy (RCE) Neural Network, Learning Vector Quantization (LVQ), Decision Trees (C4.5), Fuzzy Adaptive Resonance Theory (FuzzyArtmap), Linear Discriminant Rule (LDR), Quadratic Discriminant Rule (QDR), Radial Basis Functions (RBF), Multiple Layer Perceptrons (MLP) and Single Layer Perceptrons (SLP). Validation techniques, such as N-fold cross-validation and bootstrap techniques, are employed for evaluating the robustness of network models. The trained networks are evaluated for their performance using test data on the basis of percent error rates obtained via cross-validation, time efficiency, generalization ability to unseen faults. Finally, the usage of neural networks for the prediction of residual life of turbine blades with thermal barrier coatings is described and the results are shown. The neural network toolbox has also been applied to fault diagnosis in mixed-signal circuits.

  5. Detection and classification of cardiac ischemia using vectorcardiogram signal via neural network

    Directory of Open Access Journals (Sweden)

    Ali Reza Mehri Dehnavi

    2011-01-01

    Full Text Available Background: Various techniques are used in diagnosing cardiac diseases. The electrocardiogram is one of these tools in common use. In this study vectorcardiogram (VCG signals are used as a tool for detection of cardiac ischemia. Methods: VCG signals used in this study were obtained form 60 patients suspected to have ischemia disease and 10 normal candidates. Verification of the ischemia had done by the cardiologist during strain test by the evaluation of electrocardiogram (ECG records and patient′s clinical history. The recorder device was Cardiax digital recorder system. The VCG signals were recorded in Frank lead configuration system. Results: Extracted ischemia VCG signals have been configured with 22 features. Feature dimensionalities were reduced by the use of Independent Components Analysis and Principal Component Analysis tools. Results obtained from strain test indicated that among 60 subjects, 50 had negative results and 10 had positive results. Ischemia detection of neural network using VCG parameters indicates 86% accuracy. Classification result on neural network using ECG ischemia detection parameters is 73% accurate. Accumulative evaluation including VCG analysis and strain test indicates 90% consistency. Conclusions: Regarding the obtained results in this study, VCG has higher accuracy than ECG, so that in cases which ECG signal cannot provide certain diagnosis of existence or non-existence of ischemia, VCG signal can help in a wider range. We suggest the use of VCG as an auxiliary low cost tool in ischemia detection.

  6. Reliable prediction of T-cell epitopes using neural networks with novel sequence representations

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Worning, Peder

    2003-01-01

    calculations we show that peptides that bind to the HLA A*0204 complex display signal of higher order sequence correlations. Neural networks are ideally suited to integrate such higher order correlations when predicting the binding affinity. It is this feature combined with the use of several neural networks......In this paper we describe an improved neural network method to predict T-cell class I epitopes. A novel input representation has been developed consisting of a combination of sparse encoding, Blosum encoding, and input derived from hidden Markov models. We demonstrate that the combination...... of several neural networks derived using different sequence-encoding schemes has a performance superior to neural networks derived using a single sequence-encoding scheme. The new method is shown to have a performance that is substantially higher than that of other methods. By use of mutual information...

  7. Advanced Ring-Shaped Microelectrode Assay Combined with Small Rectangular Electrode for Quasi-In vivo Measurement of Cell-to-Cell Conductance in Cardiomyocyte Network

    Science.gov (United States)

    Nomura, Fumimasa; Kaneko, Tomoyuki; Hamada, Tomoyo; Hattori, Akihiro; Yasuda, Kenji

    2013-06-01

    To predict the risk of fatal arrhythmia induced by cardiotoxicity in the highly complex human heart system, we have developed a novel quasi-in vivo electrophysiological measurement assay, which combines a ring-shaped human cardiomyocyte network and a set of two electrodes that form a large single ring-shaped electrode for the direct measurement of irregular cell-to-cell conductance occurrence in a cardiomyocyte network, and a small rectangular microelectrode for forced pacing of cardiomyocyte beating and for acquiring the field potential waveforms of cardiomyocytes. The advantages of this assay are as follows. The electrophysiological signals of cardiomyocytes in the ring-shaped network are superimposed directly on a single loop-shaped electrode, in which the information of asynchronous behavior of cell-to-cell conductance are included, without requiring a set of huge numbers of microelectrode arrays, a set of fast data conversion circuits, or a complex analysis in a computer. Another advantage is that the small rectangular electrode can control the position and timing of forced beating in a ring-shaped human induced pluripotent stem cell (hiPS)-derived cardiomyocyte network and can also acquire the field potentials of cardiomyocytes. First, we constructed the human iPS-derived cardiomyocyte ring-shaped network on the set of two electrodes, and acquired the field potential signals of particular cardiomyocytes in the ring-shaped cardiomyocyte network during simultaneous acquisition of the superimposed signals of whole-cardiomyocyte networks representing cell-to-cell conduction. Using the small rectangular electrode, we have also evaluated the response of the cell network to electrical stimulation. The mean and SD of the minimum stimulation voltage required for pacing (VMin) at the small rectangular electrode was 166+/-74 mV, which is the same as the magnitude of amplitude for the pacing using the ring-shaped electrode (179+/-33 mV). The results showed that the

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

    Science.gov (United States)

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

    2018-01-01

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

  9. A signal combining technique based on channel shortening for cooperative sensor networks

    KAUST Repository

    Hussain, Syed Imtiaz

    2010-06-01

    The cooperative relaying process needs proper coordination among the communicating and the relaying nodes. This coordination and the required capabilities may not be available in some wireless systems, e.g. wireless sensor networks where the nodes are equipped with very basic communication hardware. In this paper, we consider a scenario where the source node transmits its signal to the destination through multiple relays in an uncoordinated fashion. The destination can capture the multiple copies of the transmitted signal through a Rake receiver. We analyze a situation where the number of Rake fingers N is less than that of the relaying nodes L. In this case, the receiver can combine N strongest signals out of L. The remaining signals will be lost and act as interference to the desired signal components. To tackle this problem, we develop a novel signal combining technique based on channel shortening. This technique proposes a processing block before the Rake reception which compresses the energy of L signal components over N branches while keeping the noise level at its minimum. The proposed scheme saves the system resources and makes the received signal compatible to the available hardware. Simulation results show that it outperforms the selection combining scheme. ©2010 IEEE.

  10. Experimental video signals distribution MMF network based on IEEE 802.11 standard

    Science.gov (United States)

    Kowalczyk, Marcin; Maksymiuk, Lukasz; Siuzdak, Jerzy

    2014-11-01

    The article was focused on presentation the achievements in a scope of experimental research on transmission of digital video streams in the frame of specially realized for this purpose ROF (Radio over Fiber) network. Its construction was based on the merge of wireless IEEE 802.11 network, popularly referred as Wi-Fi, with a passive optical network PON based on multimode fibers MMF. The proposed approach can constitute interesting proposal in area of solutions in the scope of the systems monitoring extensive, within which is required covering of a large area with ensuring of a relatively high degree of immunity on the interferences transmitted signals from video IP cameras to the monitoring center and a high configuration flexibility (easily change the deployment of cameras) of such network.

  11. A Pathway Switch Directs BAFF Signaling to Distinct NFκB Transcription Factors in Maturing and Proliferating B Cells

    OpenAIRE

    Jonathan V. Almaden; Rachel Tsui; Yi C. Liu; Harry Birnbaum; Maxim N. Shokhirev; Kim A. Ngo; Jeremy C. Davis-Turak; Dennis Otero; Soumen Basak; Robert C. Rickert; Alexander Hoffmann

    2014-01-01

    SUMMARY BAFF, an activator of the noncanonical NF?B pathway, provides critical survival signals during B cell maturation and contributes to B cell proliferation. We found that the NF?B family member RelB is required ex vivo for B cell maturation, but cRel is required for proliferation. Combined molecular network modeling and experimentation revealed Nfkb2 p100 as a pathway switch; at moderate p100 synthesis rates in maturing B cells, BAFF fully utilizes p100 to generate the RelB:p52 dimer, wh...

  12. The role of starburst amacrine cells in visual signal processing.

    Science.gov (United States)

    Taylor, W R; Smith, R G

    2012-01-01

    Starburst amacrine cells (SBACs) within the adult mammalian retina provide the critical inhibition that underlies the receptive field properties of direction-selective ganglion cells (DSGCs). The SBACs generate direction-selective output of GABA that differentially inhibits the DSGCs. We review the biophysical mechanisms that produce directional GABA release from SBACs and test a network model that predicts the effects of reciprocal inhibition between adjacent SBACs. The results of the model simulations suggest that reciprocal inhibitory connections between closely spaced SBACs should be spatially selective, while connections between more widely spaced cells could be indiscriminate. SBACs were initially identified as cholinergic neurons and were subsequently shown to contain release both acetylcholine and GABA. While the role of the GABAergic transmission is well established, the role of the cholinergic transmission remains unclear. Copyright © Cambridge University Press, 2012

  13. Aberrant signaling pathways in medulloblastomas: a stem cell connection

    Directory of Open Access Journals (Sweden)

    Carolina Oliveira Rodini

    2010-12-01

    Full Text Available Medulloblastoma is a highly malignant primary tumor of the central nervous system. It represents the most frequent type of solid tumor and the leading cause of death related to cancer in early childhood. Current treatment includes surgery, chemotherapy and radiotherapy which may lead to severe cognitive impairment and secondary brain tumors. New perspectives for therapeutic development have emerged with the identification of stem-like cells displaying high tumorigenic potential and increased radio- and chemo-resistance in gliomas. Under the cancer stem cell hypothesis, transformation of neural stem cells and/or granular neuron progenitors of the cerebellum are though to be involved in medulloblastoma development. Dissecting the genetic and molecular alterations associated with this process should significantly impact both basic and applied cancer research. Based on cumulative evidences in the fields of genetics and molecular biology of medulloblastomas, we discuss the possible involvement of developmental signaling pathways as critical biochemical switches determining normal neurogenesis or tumorigenesis. From the clinical viewpoint, modulation of signaling pathways such as TGFβ, regulating neural stem cell proliferation and tumor development, might be attempted as an alternative strategy for future drug development aiming at more efficient therapies and improved clinical outcome of patients with pediatric brain cancers.

  14. Purinergic Signaling in Mast Cell Degranulation and Asthma

    Directory of Open Access Journals (Sweden)

    Zhan-Guo Gao

    2017-12-01

    Full Text Available Mast cells are responsible for the majority of allergic conditions. It was originally thought that almost all allergic events were mediated directly only via the high-affinity immunoglobulin E receptors. However, recent evidence showed that many other receptors, such as G protein-coupled receptors and ligand-gated ion channels, are also directly involved in mast cell degranulation, the release of inflammatory mediators such as histamine, serine proteases, leukotrienes, heparin, and serotonin. These mediators are responsible for the symptoms in allergic conditions such as allergic asthma. In recent years, it has been realized that purinergic signaling, induced via the activation of G protein-coupled adenosine receptors and P2Y nucleotide receptors, as well as by ATP-gated P2X receptors, plays a significant role in mast cell degranulation. Both adenosine and ATP can induce degranulation and bronchoconstriction on their own and synergistically with allergens. All three classes of receptors, adenosine, P2X and P2Y are involved in tracheal mucus secretion. This review will summarize the currently available knowledge on the role of purinergic signaling in mast cell degranulation and its most relevant disease, asthma.

  15. Endothelial juxtaposition of distinct adult stem cells activates angiogenesis signaling molecules in endothelial cells.

    Science.gov (United States)

    Mohammadi, Elham; Nassiri, Seyed Mahdi; Rahbarghazi, Reza; Siavashi, Vahid; Araghi, Atefeh

    2015-12-01

    Efficacy of therapeutic angiogenesis needs a comprehensive understanding of endothelial cell (EC) function and biological factors and cells that interplay with ECs. Stem cells are considered the key components of pro- and anti-angiogenic milieu in a wide variety of physiopathological states, and interactions of EC-stem cells have been the subject of controversy in recent years. In this study, the potential effects of three tissue-specific adult stem cells, namely rat marrow-derived mesenchymal stem cells (rBMSCs), rat adipose-derived stem cells (rADSCs) and rat muscle-derived satellite cells (rSCs), on the endothelial activation of key angiogenic signaling molecules, including VEGF, Ang-2, VEGFR-2, Tie-2, and Tie2-pho, were investigated. Human umbilical vein endothelial cells (HUVECs) and rat lung microvascular endothelial cells (RLMECs) were cocultured with the stem cells or incubated with the stem cell-derived conditioned media on Matrigel. Following HUVEC-stem cell coculture, CD31-positive ECs were flow sorted and subjected to western blotting to analyze potential changes in the expression of the pro-angiogenic signaling molecules. Elongation and co-alignment of the stem cells were seen along the EC tubes in the EC-stem cell cocultures on Matrigel, with cell-to-cell dye communication in the EC-rBMSC cocultures. Moreover, rBMSCs and rADSCs significantly improved endothelial tubulogenesis in both juxtacrine and paracrine manners. These two latter stem cells dynamically up-regulated VEGF, Ang-2, VREGR-2, and Tie-2 but down-regulated Tie2-pho and the Tie2-pho/Tie-2 ratio in HUVECs. Induction of pro-angiogenic signaling in ECs by marrow- and adipose-derived MSCs further indicates the significance of stem cell milieu in angiogenesis dynamics.

  16. Inference of Transcriptional Network for Pluripotency in Mouse Embryonic Stem Cells

    Science.gov (United States)

    Aburatani, S.

    2015-01-01

    In embryonic stem cells, various transcription factors (TFs) maintain pluripotency. To gain insights into the regulatory system controlling pluripotency, I inferred the regulatory relationships between the TFs expressed in ES cells. In this study, I applied a method based on structural equation modeling (SEM), combined with factor analysis, to 649 expression profiles of 19 TF genes measured in mouse Embryonic Stem Cells (ESCs). The factor analysis identified 19 TF genes that were regulated by several unmeasured factors. Since the known cell reprogramming TF genes (Pou5f1, Sox2 and Nanog) are regulated by different factors, each estimated factor is considered to be an input for signal transduction to control pluripotency in mouse ESCs. In the inferred network model, TF proteins were also arranged as unmeasured factors that control other TFs. The interpretation of the inferred network model revealed the regulatory mechanism for controlling pluripotency in ES cells.

  17. Interleukin 4: signalling mechanisms and control of T cell differentiation.

    Science.gov (United States)

    Paul, W E

    1997-01-01

    Interleukin 4 (IL-4) is a pleiotropic type I cytokine that controls both growth and differentiation among haemopoietic and non-haemopoietic cells. Its receptor is a heterodimer. One chain, the IL-4R alpha chain, binds IL-4 with high affinity and determines the nature of the biochemical signals that are induced. The second chain, gamma c, is required for the induction of such signals. IL-4-mediated growth depends upon activation events that involve phosphorylation of Y497 of IL-4R alpha, leading to the binding and phosphorylation of 4PS/IRS-2 in haemopoietic cells and of IRS-1 in non-haemopoietic cells. By contrast, IL-4-mediated differentiation events depend upon more distal regions of the IL-4R alpha chain that include a series of STAT-6 binding sites. The distinctive roles of these receptor domains was verified by receptor-reconstruction experiments. The 'growth' and 'differentiation' domains of the IL-4R alpha chain, independently expressed as chimeric structures with a truncated version of the IL-2R beta chain, were shown to convey their functions to the hybrid receptor. The critical role of STAT-6 in IL-4-mediated gene activation and differentiation was made clear by the finding that lymphocytes from STAT-6 knockout mice are strikingly deficient in these functions but have retained the capacity to grow, at least partially, in response to IL-4. IL-4 plays a central role in determining the phenotype of naive CD4+ T cells. In the presence of IL-4, newly primed naive T cells develop into IL-4 producers while in its absence they preferentially become gamma-interferon (IFN-gamma) producers. Recently, a specialized subpopulation of T cells, CD4+/NK1.1+ cells, has been shown to produce large amounts of IL-4 upon stimulation. Two examples of mice with deficiencies in these cells are described--beta 2-microglobulin knockout mice and SJL mice. Both show defects in the development of IL-4-producing cells and in the increase in serum IgE in response to stimulation with the

  18. An Artificial Neural Network Based Robot Controller that Uses Rat’s Brain Signals

    Directory of Open Access Journals (Sweden)

    Marsel Mano

    2013-04-01

    Full Text Available Brain machine interface (BMI has been proposed as a novel technique to control prosthetic devices aimed at restoring motor functions in paralyzed patients. In this paper, we propose a neural network based controller that maps rat’s brain signals and transforms them into robot movement. First, the rat is trained to move the robot by pressing the right and left lever in order to get food. Next, we collect brain signals with four implanted electrodes, two in the motor cortex and two in the somatosensory cortex area. The collected data are used to train and evaluate different artificial neural controllers. Trained neural controllers are employed online to map brain signals and transform them into robot motion. Offline and online classification results of rat’s brain signals show that the Radial Basis Function Neural Networks (RBFNN outperforms other neural networks. In addition, online robot control results show that even with a limited number of electrodes, the robot motion generated by RBFNN matched the motion generated by the left and right lever position.

  19. Human Age Recognition by Electrocardiogram Signal Based on Artificial Neural Network

    Science.gov (United States)

    Dasgupta, Hirak

    2016-12-01

    The objective of this work is to make a neural network function approximation model to detect human age from the electrocardiogram (ECG) signal. The input vectors of the neural network are the Katz fractal dimension of the ECG signal, frequencies in the QRS complex, male or female (represented by numeric constant) and the average of successive R-R peak distance of a particular ECG signal. The QRS complex has been detected by short time Fourier transform algorithm. The successive R peak has been detected by, first cutting the signal into periods by auto-correlation method and then finding the absolute of the highest point in each period. The neural network used in this problem consists of two layers, with Sigmoid neuron in the input and linear neuron in the output layer. The result shows the mean of errors as -0.49, 1.03, 0.79 years and the standard deviation of errors as 1.81, 1.77, 2.70 years during training, cross validation and testing with unknown data sets, respectively.

  20. Arsenic inhibits hedgehog signaling during P19 cell differentiation

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Jui Tung [Environmental Toxicology Program, Clemson University, 132 Long Hall, Clemson, SC 29634 (United States); Bain, Lisa J., E-mail: lbain@clemson.edu [Environmental Toxicology Program, Clemson University, 132 Long Hall, Clemson, SC 29634 (United States); Department of Biological Sciences, Clemson University, 132 Long Hall, Clemson, SC 29634 (United States)

    2014-12-15

    Arsenic is a toxicant found in ground water around the world, and human exposure mainly comes from drinking water or from crops grown in areas containing arsenic in soils or water. Epidemiological studies have shown that arsenic exposure during development decreased intellectual function, reduced birth weight, and altered locomotor activity, while in vitro studies have shown that arsenite decreased muscle and neuronal cell differentiation. The sonic hedgehog (Shh) signaling pathway plays an important role during the differentiation of both neurons and skeletal muscle. The purpose of this study was to investigate whether arsenic can disrupt Shh signaling in P19 mouse embryonic stem cells, leading to changes muscle and neuronal cell differentiation. P19 embryonic stem cells were exposed to 0, 0.25, or 0.5 μM of sodium arsenite for up to 9 days during cell differentiation. We found that arsenite exposure significantly reduced transcript levels of genes in the Shh pathway in both a time and dose-dependent manner. This included the Shh ligand, which was decreased 2- to 3-fold, the Gli2 transcription factor, which was decreased 2- to 3-fold, and its downstream target gene Ascl1, which was decreased 5-fold. GLI2 protein levels and transcriptional activity were also reduced. However, arsenic did not alter GLI2 primary cilium accumulation or nuclear translocation. Moreover, additional extracellular SHH rescued the inhibitory effects of arsenic on cellular differentiation due to an increase in GLI binding activity. Taken together, we conclude that arsenic exposure affected Shh signaling, ultimately decreasing the expression of the Gli2 transcription factor. These results suggest a mechanism by which arsenic disrupts cell differentiation. - Highlights: • Arsenic exposure decreases sonic hedgehog pathway-related gene expression. • Arsenic decreases GLI2 protein levels and transcriptional activity in P19 cells. • Arsenic exposure does not alter the levels of SHH

  1. RBF neural network prediction on weak electrical signals in Aloe vera var. chinensis

    Science.gov (United States)

    Wang, Lanzhou; Zhao, Jiayin; Wang, Miao

    2008-10-01

    A Gaussian radial base function (RBF) neural network forecast on signals in the Aloe vera var. chinensis by the wavelet soft-threshold denoised as the time series and using the delayed input window chosen at 50, is set up to forecast backward. There was the maximum amplitude at 310.45μV, minimum -75.15μV, average value -2.69μV and Aloe vera var. chinensis respectively. The electrical signal in Aloe vera var. chinensis is a sort of weak, unstable and low frequency signals. A result showed that it is feasible to forecast plant electrical signals for the timing by the RBF. The forecast data can be used as the preferences for the intelligent autocontrol system based on the adaptive characteristic of plants to achieve the energy saving on the agricultural production in the plastic lookum or greenhouse.

  2. A probablistic neural network classification system for signal and image processing

    Energy Technology Data Exchange (ETDEWEB)

    Bowman, B. [Lawrence Livermore National Lab., CA (United States)

    1994-11-15

    The Acoustical Heart Valve Analysis Package is a system for signal and image processing and classification. It is being developed in both Matlab and C, to provide an interactive, interpreted environment, and has been optimized for large scale matrix operations. It has been used successfully to classify acoustic signals from implanted prosthetic heart valves in human patients, and will be integrated into a commercial Heart Valve Screening Center. The system uses several standard signal processing algorithms, as well as supervised learning techniques using the probabilistic neural network (PNN). Although currently used for the acoustic heart valve application, the algorithms and modular design allow it to be used for other applications, as well. We will describe the signal classification system, and show results from a set of test valves.

  3. Cell-geometry-dependent changes in plasma membrane order direct stem cell signalling and fate.

    Science.gov (United States)

    von Erlach, Thomas C; Bertazzo, Sergio; Wozniak, Michele A; Horejs, Christine-Maria; Maynard, Stephanie A; Attwood, Simon; Robinson, Benjamin K; Autefage, Hélène; Kallepitis, Charalambos; Del Río Hernández, Armando; Chen, Christopher S; Goldoni, Silvia; Stevens, Molly M

    2018-03-01

    Cell size and shape affect cellular processes such as cell survival, growth and differentiation 1-4 , thus establishing cell geometry as a fundamental regulator of cell physiology. The contributions of the cytoskeleton, specifically actomyosin tension, to these effects have been described, but the exact biophysical mechanisms that translate changes in cell geometry to changes in cell behaviour remain mostly unresolved. Using a variety of innovative materials techniques, we demonstrate that the nanostructure and lipid assembly within the cell plasma membrane are regulated by cell geometry in a ligand-independent manner. These biophysical changes trigger signalling events involving the serine/threonine kinase Akt/protein kinase B (PKB) that direct cell-geometry-dependent mesenchymal stem cell differentiation. Our study defines a central regulatory role by plasma membrane ordered lipid raft microdomains in modulating stem cell differentiation with potential translational applications.

  4. Bactericidal Antibiotics Increase Hydroxyphenyl Fluorescein Signal by Altering Cell Morphology

    DEFF Research Database (Denmark)

    Paulander, Wilhelm; Wang, Ying; Folkesson, Sven Anders

    2014-01-01

    It was recently proposed that for bactericidal antibiotics a common killing mechanism contributes to lethality involving indirect stimulation of hydroxyl radical (OH center dot) formation. Flow cytometric detection of OH center dot by hydroxyphenyl fluorescein (HPF) probe oxidation was used...... to support this hypothesis. Here we show that increased HPF signals in antibiotics-exposed bacterial cells are explained by fluorescence associated with increased cell size, and do not reflect reactive oxygen species (ROS) concentration. Independently of antibiotics, increased fluorescence was seen...... for elongated cells expressing the oxidative insensitive green fluorescent protein (GFP). Although our data question the role of ROS in lethality of antibiotics other research approaches point to important interplays between basic bacterial metabolism and antibiotic susceptibility. To underpin...

  5. Bactericidal antibiotics increase hydroxyphenyl fluorescein signal by altering cell morphology.

    Directory of Open Access Journals (Sweden)

    Wilhelm Paulander

    Full Text Available It was recently proposed that for bactericidal antibiotics a common killing mechanism contributes to lethality involving indirect stimulation of hydroxyl radical (OH• formation. Flow cytometric detection of OH• by hydroxyphenyl fluorescein (HPF probe oxidation was used to support this hypothesis. Here we show that increased HPF signals in antibiotics-exposed bacterial cells are explained by fluorescence associated with increased cell size, and do not reflect reactive oxygen species (ROS concentration. Independently of antibiotics, increased fluorescence was seen for elongated cells expressing the oxidative insensitive green fluorescent protein (GFP. Although our data question the role of ROS in lethality of antibiotics other research approaches point to important interplays between basic bacterial metabolism and antibiotic susceptibility. To underpin such relationships, methods for detecting bacterial metabolites at a cellular level are needed.

  6. Bactericidal Antibiotics Increase Hydroxyphenyl Fluorescein Signal by Altering Cell Morphology

    Science.gov (United States)

    Folkesson, Anders; Charbon, Godefroid; Løbner-Olesen, Anders; Ingmer, Hanne

    2014-01-01

    It was recently proposed that for bactericidal antibiotics a common killing mechanism contributes to lethality involving indirect stimulation of hydroxyl radical (OH•) formation. Flow cytometric detection of OH• by hydroxyphenyl fluorescein (HPF) probe oxidation was used to support this hypothesis. Here we show that increased HPF signals in antibiotics-exposed bacterial cells are explained by fluorescence associated with increased cell size, and do not reflect reactive oxygen species (ROS) concentration. Independently of antibiotics, increased fluorescence was seen for elongated cells expressing the oxidative insensitive green fluorescent protein (GFP). Although our data question the role of ROS in lethality of antibiotics other research approaches point to important interplays between basic bacterial metabolism and antibiotic susceptibility. To underpin such relationships, methods for detecting bacterial metabolites at a cellular level are needed. PMID:24647480

  7. Persistence and storage of activity patterns in spiking recurrent cortical networks:Modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine

    Directory of Open Access Journals (Sweden)

    Jesse ePalma

    2012-06-01

    Full Text Available Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM. Theorems in the 1970’s showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 milliseconds or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners

  8. Extruded Bread Classification on the Basis of Acoustic Emission Signal With Application of Artificial Neural Networks

    Science.gov (United States)

    Świetlicka, Izabela; Muszyński, Siemowit; Marzec, Agata

    2015-04-01

    The presented work covers the problem of developing a method of extruded bread classification with the application of artificial neural networks. Extruded flat graham, corn, and rye breads differening in water activity were used. The breads were subjected to the compression test with simultaneous registration of acoustic signal. The amplitude-time records were analyzed both in time and frequency domains. Acoustic emission signal parameters: single energy, counts, amplitude, and duration acoustic emission were determined for the breads in four water activities: initial (0.362 for rye, 0.377 for corn, and 0.371 for graham bread), 0.432, 0.529, and 0.648. For classification and the clustering process, radial basis function, and self-organizing maps (Kohonen network) were used. Artificial neural networks were examined with respect to their ability to classify or to cluster samples according to the bread type, water activity value, and both of them. The best examination results were achieved by the radial basis function network in classification according to water activity (88%), while the self-organizing maps network yielded 81% during bread type clustering.

  9. The Role of Retinal Determination Gene Network (RDGN) in Hormone Signaling Transduction and Prostate Tumorigenes

    Science.gov (United States)

    2015-12-01

    MP, Wang C, Pestell RG. Acetylation of the cell-fate factor dachshund determines p53 binding and signaling modules in breast cancer . Oncotarget...cell proliferation in vivo using Ki67 immunostaining • Expression of Dach1 was shown to block prostate cancer cell proliferation in tissue culture...studies demonstrated that these interactions between Dach1 and associated proteins (with YB1 and p53) contribute to growth of other cancer ( breast

  10. Experimental characterization and mitigation of turbulence induced signal fades within an ad hoc FSO network.

    Science.gov (United States)

    Perez, Joaquin; Zvanovec, Stanislav; Ghassemlooy, Zabih; Popoola, Wasiu O

    2014-02-10

    Optical beams propagating through the turbulent atmospheric channel suffer from both the attenuation and phase distortion. Since future wireless networks are envisaged to be deployed in the ad hoc mesh topology, this paper presents the experimental laboratory characterization of mitigation of turbulence induced signal fades for two ad hoc scenarios. Results from measurements of the thermal structure constant along the propagation channels, changes of the coherence lengths for different turbulence regimes and the eye diagrams for partially correlated turbulences in free space optical channels are discussed. Based on these results future deployment of optical ad hoc networks can be more straightforwardly planned.

  11. Mast cell chemotaxis – Chemoattractants and signaling pathways

    Directory of Open Access Journals (Sweden)

    Ivana eHalova

    2012-05-01

    Full Text Available Migration of mast cells is essential for their recruitment within target tissues where they play an important role in innate and adaptive immune responses. These processes rely on the ability of mast cells to recognize appropriate chemotactic stimuli and react to them by a chemotactic response. Another level of intercellular communication is attained by production of chemoattractants by activated mast cells, which results in accumulation of mast cells and other hematopoietic cells at the sites of inflammation. Mast cells express numerous surface receptors for various ligands with properties of potent chemoattractants. They include the stem cell factor recognized by c-Kit, antigen, which binds to immunoglobulin E (IgE anchored to the high affinity IgE receptor (FcRI, highly cytokinergic IgE recognized by FcRI, lipid mediator sphingosine-1-phosphate (S1P, which binds to G-protein-coupled receptors (GPCRs. Other large groups of chemoattractants are eicosanoids [prostaglandin E2 and D2, leukotriene (LT B4, LTD4 and LTC4, and others] and chemokines (CC, CXC, C and CX3X, which also bind to various GPCRs. Further noteworthy chemoattractants are isoforms of transforming growth factor (TGF , which are sensitively recognized by TGF- serine/threonine type I and II  receptors, adenosine, C1q, C3a, and C5a components of the complement, 5-hydroxytryptamine, neuroendocrine peptide catestatin, interleukin-6, tumor necrosis factor- and others. Here we discuss the major types of chemoattractants recognized by mast cells, their target receptors, as well as signaling pathways they utilize. We also briefly deal with methods used for studies of mast cell chemotaxis and with ways of how these studies profited from the results obtained in other cellular systems.

  12. Genetic algorithm for the optimization of features and neural networks in ECG signals classification.

    Science.gov (United States)

    Li, Hongqiang; Yuan, Danyang; Ma, Xiangdong; Cui, Dianyin; Cao, Lu

    2017-01-31

    Feature extraction and classification of electrocardiogram (ECG) signals are necessary for the automatic diagnosis of cardiac diseases. In this study, a novel method based on genetic algorithm-back propagation neural network (GA-BPNN) for classifying ECG signals with feature extraction using wavelet packet decomposition (WPD) is proposed. WPD combined with the statistical method is utilized to extract the effective features of ECG signals. The statistical features of the wavelet packet coefficients are calculated as the feature sets. GA is employed to decrease the dimensions of the feature sets and to optimize the weights and biases of the back propagation neural network (BPNN). Thereafter, the optimized BPNN classifier is applied to classify six types of ECG signals. In addition, an experimental platform is constructed for ECG signal acquisition to supply the ECG data for verifying the effectiveness of the proposed method. The GA-BPNN method with the MIT-BIH arrhythmia database achieved a dimension reduction of nearly 50% and produced good classification results with an accuracy of 97.78%. The experimental results based on the established acquisition platform indicated that the GA-BPNN method achieved a high classification accuracy of 99.33% and could be efficiently applied in the automatic identification of cardiac arrhythmias.

  13. Detecting and Predicting Muscle Fatigue during Typing By SEMG Signal Processing and Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Elham Ghoochani

    2011-03-01

    Full Text Available Introduction: Repetitive strain injuries are one of the most prevalent problems in occupational diseases. Repetition, vibration and bad postures of the extremities are physical risk factors related to work that can cause chronic musculoskeletal disorders. Repetitive work on a computer with low level contraction requires the posture to be maintained for a long time, which can cause muscle fatigue. Muscle fatigue in shoulders and neck is one of the most prevalent problems reported with computer users especially during typing. Surface electromyography (SEMG signals are used for detecting muscle fatigue as a non-invasive method. Material and Methods: Nine healthy females volunteered for signal recoding during typing. EMG signals were recorded from the trapezius muscle, which is subjected to muscle fatigue during typing.  After signal analysis and feature extraction, detecting and predicting muscle fatigue was performed by using the MLP artificial neural network. Results: Recorded signals were analyzed in time and frequency domains for feature extraction. Results of classification showed that the MLP neural network can detect and predict muscle fatigue during typing with 80.79 % ± 1.04% accuracy. Conclusion: Intelligent classification and prediction of muscle fatigue can have many applications in human factors engineering (ergonomics, rehabilitation engineering and biofeedback equipment for mitigating the injuries of repetitive works.

  14. Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

    Science.gov (United States)

    Smith, Aaron; Evans, Michael; Downey, Joseph

    2017-01-01

    National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

  15. An empirical Bayesian approach for model-based inference of cellular signaling networks

    Directory of Open Access Journals (Sweden)

    Klinke David J

    2009-11-01

    Full Text Available Abstract Background A common challenge in systems biology is to infer mechanistic descriptions of biological process given limited observations of a biological system. Mathematical models are frequently used to represent a belief about the causal relationships among proteins within a signaling network. Bayesian methods provide an attractive framework for inferring the validity of those beliefs in the context of the available data. However, efficient sampling of high-dimensional parameter space and appropriate convergence criteria provide barriers for implementing an empirical Bayesian approach. The objective of this study was to apply an Adaptive Markov chain Monte Carlo technique to a typical study of cellular signaling pathways. Results As an illustrative example, a kinetic model for the early signaling events associated with the epidermal growth factor (EGF signaling network was calibrated against dynamic measurements observed in primary rat hepatocytes. A convergence criterion, based upon the Gelman-Rubin potential scale reduction factor, was applied to the model predictions. The posterior distributions of the parameters exhibited complicated structure, including significant covariance between specific parameters and a broad range of variance among the parameters. The model predictions, in contrast, were narrowly distributed and were used to identify areas of agreement among a collection of experimental studies. Conclusion In summary, an empirical Bayesian approach was developed for inferring the confidence that one can place in a particular model that describes signal transduction mechanisms and for inferring inconsistencies in experimental measurements.

  16. GABAergic interneuron to astrocyte signalling: a neglected form of cell communication in the brain.

    Science.gov (United States)

    Losi, Gabriele; Mariotti, Letizia; Carmignoto, Giorgio

    2014-10-19

    GABAergic interneurons represent a minority of all cortical neurons and yet they efficiently control neural network activities in all brain areas. In parallel, glial cell astrocytes exert a broad control of brain tissue homeostasis and metabolism, modulate synaptic transmission and contribute to brain information processing in a dynamic interaction with neurons that is finely regulated in time and space. As most studies have focused on glutamatergic neurons and excitatory transmission, our knowledge of functional interactions between GABAergic interneurons and astrocytes is largely defective. Here, we critically discuss the currently available literature that hints at a potential relevance of this specific signalling in brain function. Astrocytes can respond to GABA through different mechanisms that include GABA receptors and transporters. GABA-activated astrocytes can, in turn, modulate local neuronal activity by releasing gliotransmitters including glutamate and ATP. In addition, astrocyte activation by different signals can modulate GABAergic neurotransmission. Full clarification of the reciprocal signalling between different GABAergic interneurons and astrocytes will improve our understanding of brain network complexity and has the potential to unveil novel therapeutic strategies for brain disorders. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  17. Analysis of EGFR signaling pathway in nasopharyngeal carcinoma cells by quantitative phosphoproteomics

    Directory of Open Access Journals (Sweden)

    He Qiu-Yan

    2011-06-01

    Full Text Available Abstract Background The epidermal growth factor receptor (EGFR is usually overexpressed in nasopharyngeal carcinoma (NPC and is associated with pathogenesis of NPC. However, the downstream signaling proteins of EGFR in NPC have not yet been completely understood at the system level. The aim of this study was identify novel downstream proteins of EGFR signaling pathway in NPC cells. Results We analyzed EGFR-regulated phosphoproteome in NPC CNE2 cells using 2D-DIGE and mass spectrometry analysis after phosphoprotein enrichment. As a result, 33 nonredundant phosphoproteins including five known EGFR-regulated proteins and twenty-eight novel EGFR-regulated proteins in CNE2 were identified, three differential phosphoproteins were selectively validated, and two differential phosphoproteins (GSTP1 and GRB2 were showed interacted with phospho-EGFR. Bioinformatics analysis showed that 32 of 33 identified proteins contain phosphorylation modification sites, and 17 identified proteins are signaling proteins. GSTP1, one of the EGFR-regulated proteins, associated with chemoresistance was analyzed. The results showed that GSTP1 could contribute to paclitaxel resistance in EGF-stimulated CNE2 cells. Furthermore, an EGFR signaling network based on the identified EGFR-regulated phosphoproteins were constructed using Pathway Studio 5.0 software, which includes canonical and novel EGFR-regulated proteins and implicates the possible biological roles for those proteins. Conclusion The data not only can extend our knowledge of canonical EGFR signaling, but also will be useful to understand the molecular mechanisms of EGFR in NPC pathogenesis and search therapeutic targets for NPC.

  18. EU-ADR healthcare database network vs. spontaneous reporting system database: preliminary comparison of signal detection.

    Science.gov (United States)

    Trifirò, Gianluca; Patadia, Vaishali; Schuemie, Martijn J; Coloma, Preciosa M; Gini, Rosa; Herings, Ron; Hippisley-Cox, Julia; Mazzaglia, Giampiero; Giaquinto, Carlo; Scotti, Lorenza; Pedersen, Lars; Avillach, Paul; Sturkenboom, Miriam C J M; van der Lei, Johan; Eu-Adr Group

    2011-01-01

    The EU-ADR project aims to exploit different European electronic healthcare records (EHR) databases for drug safety signal detection. In this paper we report the preliminary results concerning the comparison of signal detection between EU-ADR network and two spontaneous reporting databases, the Food and Drug Administration and World Health Organization databases. EU-ADR data sources consist of eight databases in four countries (Denmark, Italy, Netherlands, and United Kingdom) that are virtually linked through distributed data network. A custom-built software (Jerboa©) elaborates harmonized input data that are produced locally and generates aggregated data which are then stored in a central repository. Those data are subsequently analyzed through different statistics (i.e. Longitudinal Gamma Poisson Shrinker). As potential signals, all the drugs that are associated to six events of interest (bullous eruptions - BE, acute renal failure - ARF, acute myocardial infarction - AMI, anaphylactic shock - AS, rhabdomyolysis - RHABD, and upper gastrointestinal bleeding - UGIB) have been detected via different data mining techniques in the two systems. Subsequently a comparison concerning the number of drugs that could be investigated and the potential signals detected for each event in the spontaneous reporting systems (SRSs) and EU-ADR network was made. SRSs could explore, as potential signals, a larger number of drugs for the six events, in comparison to EU-ADR (range: 630-3,393 vs. 87-856), particularly for those events commonly thought to be potentially drug-induced (i.e. BE: 3,393 vs. 228). The highest proportion of signals detected in SRSs was found for BE, ARF and AS, while for ARF, and UGIB in EU-ADR. In conclusion, it seems that EU-ADR longitudinal database network may complement traditional spontaneous reporting system for signal detection, especially for those adverse events that are frequent in general population and are not commonly thought to be drug

  19. BMP9 signaling in stem cell differentiation and osteogenesis

    Science.gov (United States)

    Lamplot, Joseph D; Qin, Jiaqiang; Nan, Guoxin; Wang, Jinhua; Liu, Xing; Yin, Liangjun; Tomal, Justin; Li, Ruidong; Shui, Wei; Zhang, Hongyu; Kim, Stephanie H; Zhang, Wenwen; Zhang, Jiye; Kong, Yuhan; Denduluri, Sahitya; Rogers, Mary Rose; Pratt, Abdullah; Haydon, Rex C; Luu, Hue H; Angeles, Jovito; Shi, Lewis L; He, Tong-Chuan

    2013-01-01

    Bone morphogenetic proteins (BMPs) are members of the TGF-β superfamily and play a critical role in skeletal development, bone formation and stem cell differentiation. Disruptions in BMP signaling result in a variety of skeletal and extraskeletal anomalies. BMP9 is a poorly characterized member of the BMP family and is among the most osteogenic BMPs, promoting osteoblastic differentiation of mesenchymal stem cells (MSCs) both in vitro and in vivo. Recent findings from various in vivo and molecular studies strongly suggest that the mechanisms governing BMP9-mediated osteoinduction differ from other osteogenic BMPs. Many signaling pathways with diverse functions have been found to play a role in BMP9-mediated osteogenesis. Several of these pathways are also critical in the differentiation of other cell lineages, including adipocytes and chondrocytes. While BMP9 is known to be a potent osteogenic factor, it also influences several other pathways including cancer development, angiogenesis and myogenesis. Although BMP9 has been demonstrated as one of the most osteogenic BMPs, relatively little is known about the specific mechanisms responsible for these effects. BMP9 has demonstrated efficacy in promoting spinal fusion and bony non-union repair in animal models, demonstrating great translational promise. This review aims to summarize our current knowledge of BMP9-mediated osteogenesis by presenting recently completed work which may help us to further elucidate these pathways. PMID:23671813

  20. Curcumin mediates anticancer effects by modulating multiple cell signaling pathways.

    Science.gov (United States)

    Kunnumakkara, Ajaikumar B; Bordoloi, Devivasha; Harsha, Choudhary; Banik, Kishore; Gupta, Subash C; Aggarwal, Bharat B

    2017-08-01

    Curcumin, a component of a spice native to India, was first isolated in 1815 by Vogel and Pelletier from the rhizomes of Curcuma longa (turmeric) and, subsequently, the chemical structure of curcumin as diferuloylmethane was reported by Milobedzka et al. [(1910) 43., 2163-2170]. Since then, this polyphenol has been shown to exhibit antioxidant, anti-inflammatory, anticancer, antiviral, antibacterial, and antifungal activities. The current review primarily focuses on the anticancer potential of curcumin through the modulation of multiple cell signaling pathways. Curcumin modulates diverse transcription factors, inflammatory cytokines, enzymes, kinases, growth factors, receptors, and various other proteins with an affinity ranging from the pM to the mM range. Furthermore, curcumin effectively regulates tumor cell growth via modulation of numerous cell signaling pathways and potentiates the effect of chemotherapeutic agents and radiation against cancer. Curcumin can interact with most of the targets that are modulated by FDA-approved drugs for cancer therapy. The focus of this review is to discuss the molecular basis for the anticancer activities of curcumin based on preclinical and clinical findings. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

  1. Systems-level identification of PKA-dependent signaling in epithelial cells.

    Science.gov (United States)

    Isobe, Kiyoshi; Jung, Hyun Jun; Yang, Chin-Rang; Claxton, J'Neka; Sandoval, Pablo; Burg, Maurice B; Raghuram, Viswanathan; Knepper, Mark A

    2017-10-17

    G protein stimulatory α-subunit (G αs )-coupled heptahelical receptors regulate cell processes largely through activation of protein kinase A (PKA). To identify signaling processes downstream of PKA, we deleted both PKA catalytic subunits using CRISPR-Cas9, followed by a "multiomic" analysis in mouse kidney epithelial cells expressing the G αs -coupled V2 vasopressin receptor. RNA-seq (sequencing)-based transcriptomics and SILAC (stable isotope labeling of amino acids in cell culture)-based quantitative proteomics revealed a complete loss of expression of the water-channel gene Aqp2 in PKA knockout cells. SILAC-based quantitative phosphoproteomics identified 229 PKA phosphorylation sites. Most of these PKA targets are thus far unannotated in public databases. Surprisingly, 1,915 phosphorylation sites with the motif x-(S/T)-P showed increased phosphooccupancy, pointing to increased activity of one or more MAP kinases in PKA knockout cells. Indeed, phosphorylation changes associated with activation of ERK2 were seen in PKA knockout cells. The ERK2 site is downstream of a direct PKA site in the Rap1GAP, Sipa1l1, that indirectly inhibits Raf1. In addition, a direct PKA site that inhibits the MAP kinase kinase kinase Map3k5 (ASK1) is upstream of JNK1 activation. The datasets were integrated to identify a causal network describing PKA signaling that explains vasopressin-mediated regulation of membrane trafficking and gene transcription. The model predicts that, through PKA activation, vasopressin stimulates AQP2 exocytosis by inhibiting MAP kinase signaling. The model also predicts that, through PKA activation, vasopressin stimulates Aqp2 transcription through induction of nuclear translocation of the acetyltransferase EP300, which increases histone H3K27 acetylation of vasopressin-responsive genes (confirmed by ChIP-seq).

  2. A protein–protein interaction network linking the energy-sensor kinase SnRK1 to multiple signaling pathways in Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Madlen Nietzsche

    2016-04-01

    Full Text Available In plants, the sucrose non-fermenting (SNF1-related protein kinase 1 (SnRK1 represents a central integrator of low energy signaling and acclimation towards many environmental stress responses. Although SnRK1 acts as a convergent point for many different environmental and metabolic signals to control growth and development, it is currently unknown how these many different signals could be translated into a cell-type or stimulus specific response since many components of SnRK1-regulated signaling pathways remain unidentified. Recently, we have demonstrated that proteins containing a domain of unknown function (DUF 581 interact with the catalytic α subunits of SnRK1 (AKIN10/11 from Arabidopsis thaliana and could potentially act as mediators conferring tissue- and stimulus-type specific differences in SnRK1 regulation. To further extend the SnRK1 signaling network in plants, we systematically screened for novel DUF581 interaction partners using the yeast two-hybrid system. A deep and exhaustive screening identified 17 interacting partners for 10 of the DUF581 proteins tested. Many of these novel interaction partners are implicated in cellular processes previously associated with SnRK1 signaling. Furthermore, we mined publicly available interaction data to identify additional DUF581 interacting proteins. A protein–protein interaction network resulting from our studies suggests connections between SnRK1 signaling and other central signaling pathways involved in growth regulation and environmental responses. These include TOR and MAP-kinase signaling as well as hormonal pathways. The resulting protein–protein interaction network promises to be effective in generating hypotheses to study the precise mechanisms SnRK1 signaling on a functional level.

  3. Cell swelling and ion redistribution assessed with intrinsic optical signals

    Directory of Open Access Journals (Sweden)

    WITTE OTTO W.

    2001-01-01

    Full Text Available Cell volume changes are associated with alterations of intrinsic optical signals (IOS. In submerged brain slices in vitro, afferent stimulation induces an increase in light transmission. As assessed by measurement of the largely membrane impermeant ion tetramethylammonium (TMA in the extracellular space, these IOS correlate with the extent and time course of the change of the extracellular space size. They have a high signal to noise ratio and allow measurements of IOS changes in the order of a few percent. Under conditions of reduced net KCl uptake (low Cl solution a directed spatial buffer mechanism (K syphoning can be demonstrated in the neocortex with widening of the extracellular space in superficial layers associated with a reduced light transmission and an increase of extracellular K concentration. The nature of the IOS under pathophysiological conditions is less clear. Spreading depressions first cause an increase of light transmission, then a decrease. Such a decrease has also been observed following application of NMDA where it was associated with structural damage. Pharmacological analyses suggest that under physiological conditions changes of extracellular space size are mainly caused by astrocytic volume changes while with strong stimuli and under pathophysiological conditions also neuronal swelling occurs. With reflected light usually signals opposite to those observed with transmitted light are seen. Recording of IOS from interface slices gives very complex signals since under these conditions an increase of light transmission has been reported to be superimposed by a decrease of the signal due to mechanical lensing effects of the slice surface. Depending on the method of measurement and the exact conditions, several mechanisms may contribute to IOS. Under well defined conditions IOS are a useful supplementary tool to monitor changes of extracellular volume both in space and time.

  4. DMPD: Lipopolysaccharide signaling in endothelial cells. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 16357866 Lipopolysaccharide signaling in endothelial cells. Dauphinee SM, Karsan A.... Lab Invest. 2006 Jan;86(1):9-22. (.png) (.svg) (.html) (.csml) Show Lipopolysaccharide signaling in endothe...lial cells. PubmedID 16357866 Title Lipopolysaccharide signaling in endothelial cells. Authors Dauphinee SM,

  5. Ras and Rheb Signaling in Survival and Cell Death

    Energy Technology Data Exchange (ETDEWEB)

    Ehrkamp, Anja [Molecular Neurobiochemistry, Ruhr University of Bochum, 44780 Bochum (Germany); Herrmann, Christian [Department of Physical Chemistry1, Protein Interaction, Ruhr University of Bochum, 44780 Bochum (Germany); Stoll, Raphael [Biomolecular NMR, Ruhr University of Bochum, 44780 Bochum (Germany); Heumann, Rolf, E-mail: rolf.heumann@rub.de [Molecular Neurobiochemistry, Ruhr University of Bochum, 44780 Bochum (Germany)

    2013-05-28

    One of the most obvious hallmarks of cancer is uncontrolled proliferation of cells partly due to independence of growth factor supply. A major component of mitogenic signaling is Ras, a small GTPase. It was the first identified human protooncogene and is known since more than three decades to promote cellular proliferation and growth. Ras was shown to support growth factor-independent survival during development and to protect from chemical or mechanical lesion-induced neuronal degeneration in postmitotic neurons. In contrast, for specific patho-physiological cases and cellular systems it has been shown that Ras may also promote cell death. Proteins from the Ras association family (Rassf, especially Rassf1 and Rassf5) are tumor suppressors that are activated by Ras-GTP, triggering apoptosis via e.g., activation of mammalian sterile 20-like (MST1) kinase. In contrast to Ras, their expression is suppressed in many types of tumours, which makes Rassf proteins an exciting model for understanding the divergent effects of Ras activity. It seems likely that the outcome of Ras signaling depends on the balance between the activation of its various downstream effectors, thus determining cellular fate towards either proliferation or apoptosis. Ras homologue enriched in brain (Rheb) is a protein from the Ras superfamily that is also known to promote proliferation, growth, and regeneration through the mammalian target of rapamycin (mTor) pathway. However, recent evidences indicate that the Rheb-mTor pathway may switch its function from a pro-growth into a cell death pathway, depending on the cellular situation. In contrast to Ras signaling, for Rheb, the cellular context is likely to modulate the whole Rheb-mTor pathway towards cellular death or survival, respectively.

  6. Ras and Rheb Signaling in Survival and Cell Death

    International Nuclear Information System (INIS)

    Ehrkamp, Anja; Herrmann, Christian; Stoll, Raphael; Heumann, Rolf

    2013-01-01

    One of the most obvious hallmarks of cancer is uncontrolled proliferation of cells partly due to independence of growth factor supply. A major component of mitogenic signaling is Ras, a small GTPase. It was the first identified human protooncogene and is known since more than three decades to promote cellular proliferation and growth. Ras was shown to support growth factor-independent survival during development and to protect from chemical or mechanical lesion-induced neuronal degeneration in postmitotic neurons. In contrast, for specific patho-physiological cases and cellular systems it has been shown that Ras may also promote cell death. Proteins from the Ras association family (Rassf, especially Rassf1 and Rassf5) are tumor suppressors that are activated by Ras-GTP, triggering apoptosis via e.g., activation of mammalian sterile 20-like (MST1) kinase. In contrast to Ras, their expression is suppressed in many types of tumours, which makes Rassf proteins an exciting model for understanding the divergent effects of Ras activity. It seems likely that the outcome of Ras signaling depends on the balance between the activation of its various downstream effectors, thus determining cellular fate towards either proliferation or apoptosis. Ras homologue enriched in brain (Rheb) is a protein from the Ras superfamily that is also known to promote proliferation, growth, and regeneration through the mammalian target of rapamycin (mTor) pathway. However, recent evidences indicate that the Rheb-mTor pathway may switch its function from a pro-growth into a cell death pathway, depending on the cellular situation. In contrast to Ras signaling, for Rheb, the cellular context is likely to modulate the whole Rheb-mTor pathway towards cellular death or survival, respectively

  7. Bluetooth-based sensor networks for remotely monitoring the physiological signals of a patient.

    Science.gov (United States)

    Zhang, Ying; Xiao, Hannan

    2009-11-01

    Integrating intelligent medical microsensors into a wireless communication network makes it possible to remotely collect physiological signals of a patient, release the patient from being tethered to monitoring medical instrumentations, and facilitate the patient's early hospital discharge. This can further improve life quality by providing continuous observation without the need of disrupting the patient's normal life, thus reducing the risk of infection significantly, and decreasing the cost of the hospital and the patient. This paper discusses the implementation issues, and describes the overall system architecture of our developed Bluetooth sensor network for patient monitoring and the corresponding heart activity sensors. It also presents our approach to developing the intelligent physiological sensor nodes involving integration of Bluetooth radio technology, hardware and software organization, and our solutions for onboard signal processing.

  8. Lipopolysaccharide-induced multinuclear cells: Increased internalization of polystyrene beads and possible signals for cell fusion

    Energy Technology Data Exchange (ETDEWEB)

    Nakanishi-Matsui, Mayumi, E-mail: nakanim@iwate-med.ac.jp; Yano, Shio; Futai, Masamitsu

    2013-11-01

    Highlights: •LPS induces multinuclear cells from murine macrophage-derived RAW264.7 cells. •Large beads are internalized by cells actively fusing to become multinuclear. •The multinuclear cell formation is inhibited by anti-inflammatory cytokine, IL10. •Signal transduction for cell fusion is different from that for inflammation. -- Abstract: A murine macrophage-derived line, RAW264.7, becomes multinuclear on stimulation with lipopolysaccharide (LPS), an outer membrane component of Gram-negative bacteria. These multinuclear cells internalized more polystyrene beads than mononuclear cells or osteoclasts (Nakanishi-Matsui, M., Yano, S., Matsumoto, N., and Futai, M., 2012). In this study, we analyzed the time courses of cell fusion in the presence of large beads. They were internalized into cells actively fusing to become multinuclear. However, the multinuclear cells once formed showed only low phagocytosis activity. These results suggest that formation of the multinuclear cells and bead internalization took place simultaneously. The formation of multinuclear cells was blocked by inhibitors for phosphoinositide 3-kinase, phospholipase C, calcineurin, and c-Jun N-terminal kinase. In addition, interleukin 6 and 10 also exhibited inhibitory effects. These signaling molecules and cytokines may play a crucial role in the LPS-induced multinuclear cell formation.

  9. Porcine pluripotency cell signaling develops from the inner cell mass to the epiblast during early development

    DEFF Research Database (Denmark)

    Hall, Vanessa Jane; Christensen, Josef; Gao, Yu

    2009-01-01

    (LIF, LIFR, GP130), FGF pathway (bFGF, FGFR1, FGFR2), BMP pathway (BMP4), and downstream-activated genes (STAT3, c-Myc, c-Fos, and SMAD4). We discovered two different expression profiles exist in the developing porcine embryo. The D6 porcine blastocyst (inner cell mass stage) is devoid......  The signaling mechanisms regulating pluripotency in porcine embryonic stem cells and embryos are unknown. In this study, we characterize cell signaling in the in-vivo porcine inner cell mass and later-stage epiblast. We evaluate expression of OCT4, NANOG, SOX2, genes within the JAK/STAT pathway...... pluripotency in human embryonic stem cells is detectable in the porcine epiblast, but not in the inner cell mass. Copyright (c) 2009 Wiley-Liss, Inc....

  10. The calcium feedback loop and T cell activation: how cytoskeleton networks control intracellular calcium flux.

    Science.gov (United States)

    Joseph, Noah; Reicher, Barak; Barda-Saad, Mira

    2014-02-01

    During T cell activation, the engagement of a T cell with an antigen-presenting cell (APC) results in rapid cytoskeletal rearrangements and a dramatic increase of intracellular calcium (Ca(2+)) concentration, downstream to T cell antigen receptor (TCR) ligation. These events facilitate the organization of an immunological synapse (IS), which supports the redistribution of receptors, signaling molecules and organelles towards the T cell-APC interface to induce downstream signaling events, ultimately supporting T cell effector functions. Thus, Ca(2+) signaling and cytoskeleton rearrangements are essential for T cell activation and T cell-dependent immune response. Rapid release of Ca(2+) from intracellular stores, e.g. the endoplasmic reticulum (ER), triggers the opening of Ca(2+) release-activated Ca(2+) (CRAC) channels, residing in the plasma membrane. These channels facilitate a sustained influx of extracellular Ca(2+) across the plasma membrane in a process termed store-operated Ca(2+) entry (SOCE). Because CRAC channels are themselves inhibited by Ca(2+) ions, additional factors are suggested to enable the sustained Ca(2+) influx required for T cell function. Among these factors, we focus here on the contribution of the actin and microtubule cytoskeleton. The TCR-mediated increase in intracellular Ca(2+) evokes a rapid cytoskeleton-dependent polarization, which involves actin cytoskeleton rearrangements and microtubule-organizing center (MTOC) reorientation. Here, we review the molecular mechanisms of Ca(2+) flux and cytoskeletal rearrangements, and further describe the way by which the cytoskeletal networks feedback to Ca(2+) signaling by controlling the spatial and temporal distribution of Ca(2+) sources and sinks, modulating TCR-dependent Ca(2+) signals, which are required for an appropriate T cell response. This article is part of a Special Issue entitled: Reciprocal influences between cell cytoskeleton and membrane channels, receptors and transporters

  11. Converged wireline and wireless signal distribution in optical fiber access networks

    DEFF Research Database (Denmark)

    Prince, Kamau

    This thesis presents results obtained during the course of my doctoral studies into the transport of fixed and wireless signaling over a converged otpical access infrastructure. In the formulation, development and assessment of a converged paradigma for multiple-services delivery via optical access...... networking infrastructure, I have demonstrated increased functionalities with existing optical technologies and commercially available optoelectronic devices. I have developed novel systems for extending the range of optical access systems, and have demonstrated the repurposing of standard digital devices...

  12. Control mechanism to prevent correlated message arrivals from degrading signaling no. 7 network performance

    Science.gov (United States)

    Kosal, Haluk; Skoog, Ronald A.

    1994-04-01

    Signaling System No. 7 (SS7) is designed to provide a connection-less transfer of signaling messages of reasonable length. Customers having access to user signaling bearer capabilities as specified in the ANSI T1.623 and CCITT Q.931 standards can send bursts of correlated messages (e.g., by doing a file transfer that results in the segmentation of a block of data into a number of consecutive signaling messages) through SS7 networks. These message bursts with short interarrival times could have an adverse impact on the delay performance of the SS7 networks. A control mechanism, Credit Manager, is investigated in this paper to regulate incoming traffic to the SS7 network by imposing appropriate time separation between messages when the incoming stream is too bursty. The credit manager has a credit bank where credits accrue at a fixed rate up to a prespecified credit bank capacity. When a message arrives, the number of octets in that message is compared to the number of credits in the bank. If the number of credits is greater than or equal to the number of octets, then the message is accepted for transmission and the number of credits in the bank is decremented by the number of octets. If the number of credits is less than the number of octets, then the message is delayed until enough credits are accumulated. This paper presents simulation results showing delay performance of the SS7 ISUP and TCAP message traffic with a range of correlated message traffic, and control parameters of the credit manager (i.e., credit generation rate and bank capacity) are determined that ensure the traffic entering the SS7 network is acceptable. The results show that control parameters can be set so that for any incoming traffic stream there is no detrimental impact on the SS7 ISUP and TCAP message delay, and the credit manager accepts a wide range of traffic patterns without causing significant delay.

  13. International Conference on VLSI, Communication, Advanced Devices, Signals & Systems and Networking

    CERN Document Server

    Shirur, Yasha; Prasad, Rekha

    2013-01-01

    This book is a collection of papers presented by renowned researchers, keynote speakers and academicians in the International Conference on VLSI, Communication, Analog Designs, Signals and Systems, and Networking (VCASAN-2013), organized by B.N.M. Institute of Technology, Bangalore, India during July 17-19, 2013. The book provides global trends in cutting-edge technologies in electronics and communication engineering. The content of the book is useful to engineers, researchers and academicians as well as industry professionals.

  14. Targeting multiple pro-apoptotic signaling pathways with curcumin in prostate cancer cells.

    Directory of Open Access Journals (Sweden)

    Mariela Rivera

    Full Text Available Curcumin, an extract from the turmeric rhizome (Curcuma longa, is known to exhibit anti-inflammatory, antioxidant, chemopreventive and antitumoral activities against aggressive and recurrent cancers. Accumulative data indicate that curcumin may induce cancer cell death. However, the detailed mechanism underlying its pro-apoptotic and anti-cancer effects remains to be elucidated. In the present study, we examined the signaling pathways triggered by curcumin, specifically, the exact molecular mechanisms of curcumin-induced apoptosis in highly metastatic human prostate cancer cells. The effect of curcumin was evaluated using for the first time in prostate cancer, a gel-free shotgun quantitative proteomic analysis coupled with Tandem Mass Tag isobaric labeling-based-signaling networks. Results were confirmed at the gene expression level by qRT-PCR and at the protein expression level by western blot and flow cytometry. Our findings revealed that curcumin induced an Endoplasmic Reticulum stress-mediated apoptosis in PC3. The mechanisms by which curcumin promoted cell death in these cells were associated with cell cycle arrest, increased reactive oxygen species, autophagy and the Unfolded Protein Response. Furthermore, the upregulation of ER stress was measured using key indicators of ER stress: Glucose-Regulated Protein 78, Inositol-Requiring Enzyme 1 alpha, Protein Disulfide isomerase and Calreticulin. Chronic ER stress induction was concomitant with the upregulation of pro-apoptotic markers (caspases 3,9,12 and Poly (ADP-ribose polymerase. The downregulated proteins include anti-apoptotic and anti-tumor markers, supporting their curcumin-induced pro-apoptotic role in prostate cancer cells. Taken together, these data suggest that curcumin may serve as a promising anticancer agent by inducing a chronic ER stress mediated cell death and activation of cell cycle arrest, UPR, autophagy and oxidative stress responses.

  15. Targeting multiple pro-apoptotic signaling pathways with curcumin in prostate cancer cells

    Science.gov (United States)

    Rivera, Mariela; Ramos, Yanilda; Rodríguez-Valentín, Madeline; López-Acevedo, Sheila; Cubano, Luis A.; Zou, Jin; Zhang, Qiang; Wang, Guangdi

    2017-01-01

    Curcumin, an extract from the turmeric rhizome (Curcuma longa), is known to exhibit anti-inflammatory, antioxidant, chemopreventive and antitumoral activities against aggressive and recurrent cancers. Accumulative data indicate that curcumin may induce cancer cell death. However, the detailed mechanism underlying its pro-apoptotic and anti-cancer effects remains to be elucidated. In the present study, we examined the signaling pathways triggered by curcumin, specifically, the exact molecular mechanisms of curcumin-induced apoptosis in highly metastatic human prostate cancer cells. The effect of curcumin was evaluated using for the first time in prostate cancer, a gel-free shotgun quantitative proteomic analysis coupled with Tandem Mass Tag isobaric labeling-based-signaling networks. Results were confirmed at the gene expression level by qRT-PCR and at the protein expression level by western blot and flow cytometry. Our findings revealed that curcumin induced an Endoplasmic Reticulum stress-mediated apoptosis in PC3. The mechanisms by which curcumin promoted cell death in these cells were associated with cell cycle arrest, increased reactive oxygen species, autophagy and the Unfolded Protein Response. Furthermore, the upregulation of ER stress was measured using key indicators of ER stress: Glucose-Regulated Protein 78, Inositol-Requiring Enzyme 1 alpha, Protein Disulfide isomerase and Calreticulin. Chronic ER stress induction was concomitant with the upregulation of pro-apoptotic markers (caspases 3,9,12) and Poly (ADP-ribose) polymerase. The downregulated proteins include anti-apoptotic and anti-tumor markers, supporting their curcumin-induced pro-apoptotic role in prostate cancer cells. Taken together, these data suggest that curcumin may serve as a promising anticancer agent by inducing a chronic ER stress mediated cell death and activation of cell cycle arrest, UPR, autophagy and oxidative stress responses. PMID:28628644

  16. Wnt/β-catenin signaling regulates cancer stem cells in lung cancer A549 cells

    International Nuclear Information System (INIS)

    Teng, Ying; Wang, Xiuwen; Wang, Yawei; Ma, Daoxin

    2010-01-01

    Wnt/β-catenin signaling plays an important role not only in cancer, but also in cancer stem cells. In this study, we found that β-catenin and OCT-4 was highly expressed in cisplatin (DDP) selected A549 cells. Stimulating A549 cells with lithium chloride (LiCl) resulted in accumulation of β-catenin and up-regulation of a typical Wnt target gene cyclin D1. This stimulation also significantly enhanced proliferation, clone formation, migration and drug resistance abilities in A549 cells. Moreover, the up-regulation of OCT-4, a stem cell marker, was observed through real-time PCR and Western blotting. In a reverse approach, we inhibited Wnt signaling by knocking down the expression of β-catenin using RNA interference technology. This inhibition resulted in down-regulation of the Wnt target gene cyclin D1 as well as the proliferation, clone formation, migration and drug resistance abilities. Meanwhile, the expression of OCT-4 was reduced after the inhibition of Wnt/β-catenin signaling. Taken together, our study provides strong evidence that canonical Wnt signaling plays an important role in lung cancer stem cell properties, and it also regulates OCT-4, a lung cancer stem cell marker.

  17. Bow-tie signaling in c-di-GMP: Machine learning in a simple biochemical network.

    Directory of Open Access Journals (Sweden)

    Jinyuan Yan

    2017-08-01

    Full Text Available Bacteria of many species rely on a simple molecule, the intracellular secondary messenger c-di-GMP (Bis-(3'-5'-cyclic dimeric guanosine monophosphate, to make a vital choice: whether to stay in one place and form a biofilm, or to leave it in search of better conditions. The c-di-GMP network has a bow-tie shaped architecture that integrates many signals from the outside world-the input stimuli-into intracellular c-di-GMP levels that then regulate genes for biofilm formation or for swarming motility-the output phenotypes. How does the 'uninformed' process of evolution produce a network with the right input/output association and enable bacteria to make the right choice? Inspired by new data from 28 clinical isolates of Pseudomonas aeruginosa and strains evolved in laboratory experiments we propose a mathematical model where the c-di-GMP network is analogous to a machine learning classifier. The analogy immediately suggests a mechanism for learning through evolution: adaptation though incremental changes in c-di-GMP network proteins acquires knowledge from past experiences and enables bacteria to use it to direct future behaviors. Our model clarifies the elusive function of the ubiquitous c-di-GMP network, a key regulator of bacterial social traits associated with virulence. More broadly, the link between evolution and machine learning can help explain how natural selection across fluctuating environments produces networks that enable living organisms to make sophisticated decisions.

  18. Dissect the Dynamic Molecular Circuits of Cell Cycle Control through Network Evolution Model

    Directory of Open Access Journals (Sweden)

    Yang Peng

    2017-01-01

    Full Text Available The molecular circuits of cell cycle control serve as a key hub to integrate from endogenous and environmental signals into a robust biological decision driving cell growth and division. Dysfunctional cell cycle control is highlighted in a wide spectrum of human cancers. More importantly the mainstay anticancer treatment such as radiation therapy and chemotherapy targets the hallmark of uncontrolled cell proliferation in cancer cells by causing DNA damage, cell cycle arrest, and cell death. Given the functional importance of cell cycle control, the regulatory mechanisms that drive the cell division have been extensively investigated in a huge number of studies by conventional single-gene approaches. However the complexity of cell cycle control renders a significant barrier to understand its function at a network level. In this study, we used mathematical modeling through modern graph theory and differential equation systems. We believe our network evolution model can help us understand the dynamic cell cycle control in tumor evolution and optimizing dosing schedules for radiation therapy and chemotherapy targeting cell cycle.

  19. Multiple Roles of MYC in Integrating Regulatory Networks of Pluripotent Stem Cells

    Science.gov (United States)

    Fagnocchi, Luca; Zippo, Alessio

    2017-01-01

    Pluripotent stem cells (PSCs) are defined by their self-renewal potential, which permits their unlimited propagation, and their pluripotency, being able to generate cell of the three embryonic lineages. These properties render PSCs a valuable tool for both basic and medical research. To induce and stabilize the pluripotent state, complex circuitries involving signaling pathways, transcription regulators and epigenetic mechanisms converge on a core transcriptional regulatory network of PSCs, thus determining their cell identity. Among the transcription factors, MYC represents a central hub, which modulates and integrates multiple mechanisms involved both in the maintenance of pluripotency and in cell reprogramming. Indeed, it instructs the PSC-specific cell cycle, metabolism and epigenetic landscape, contributes to limit exit from pluripotency and modulates signaling cascades affecting the PSC identity. Moreover, MYC extends its regulation on pluripotency by controlling PSC-specific non-coding RNAs. In this report, we review the MYC-controlled networks, which support the pluripotent state and discuss how their perturbation could affect cell identity. We further discuss recent finding demonstrating a central role of MYC in triggering epigenetic memory in PSCs, which depends on the establishment of a WNT-centered self-reinforcing circuit. Finally, we comment on the therapeutic implications of the role of MYC in affecting PSCs. Indeed, PSCs are used for both disease and cancer modeling and to derive cells for regenerative medicine. For these reasons, unraveling the MYC-mediated mechanism in those cells is fundamental to exploit their full potential and to identify therapeutic targets. PMID:28217689

  20. Damage detection using the signal entropy of an ultrasonic sensor network

    Science.gov (United States)

    Rojas, E.; Baltazar, A.; Loh, K. J.

    2015-07-01

    Piezoelectric ultrasonic sensors used to propagate guided waves can potentially be implemented to inspect large areas in engineering structures. However, the inherent dispersion and noise of guided acoustic signals, multiple echoes in the structure, as well as a lack of an approximate or exact model, limit their use as a continuous structural health monitoring system. In this work, the implementation of a network of piezoelectric sensors randomly placed on a plate-like structure to detect and locate artificial damage is studied. A network of macro fiber composite (MFC) sensors working in a pitch-catch configuration was set on an aluminum thin plate 1.9 mm in thickness. Signals were analyzed in the time-scale domain using the discrete wavelet transform. The objectives of this work were threefold, namely to first develop a damage index based on the entropy distribution using short time wavelet entropy of the ultrasonic waves generated by a sensor network, second to determine the performance of an array of spare MFC sensors to detect artificial damage, and third to implement a time-of-arrival (TOA) algorithm on the gathered signals for damage location of an artificial circular discontinuity. Our preliminary test results show that the proposed methodology provides sufficient information for damage detection, which, once combined with the TOA algorithm, allows localization of the damage.