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Sample records for erbb signaling network

  1. SOX9 regulates ERBB signalling in pancreatic cancer development.

    Science.gov (United States)

    Grimont, Adrien; Pinho, Andreia V; Cowley, Mark J; Augereau, Cécile; Mawson, Amanda; Giry-Laterrière, Marc; Van den Steen, Géraldine; Waddell, Nicola; Pajic, Marina; Sempoux, Christine; Wu, Jianmin; Grimmond, Sean M; Biankin, Andrew V; Lemaigre, Frédéric P; Rooman, Ilse; Jacquemin, Patrick

    2015-11-01

    The transcription factor SOX9 was recently shown to stimulate ductal gene expression in pancreatic acinar-to-ductal metaplasia and to accelerate development of premalignant lesions preceding pancreatic ductal adenocarcinoma (PDAC). Here, we investigate how SOX9 operates in pancreatic tumourigenesis. We analysed genomic and transcriptomic data from surgically resected PDAC and extended the expression analysis to xenografts from PDAC samples and to PDAC cell lines. SOX9 expression was manipulated in human cell lines and mouse models developing PDAC. We found genetic aberrations in the SOX9 gene in about 15% of patient tumours. Most PDAC samples strongly express SOX9 protein, and SOX9 levels are higher in classical PDAC. This tumour subtype is associated with better patient outcome, and cell lines of this subtype respond to therapy targeting epidermal growth factor receptor (EGFR/ERBB1) signalling, a pathway essential for pancreatic tumourigenesis. In human PDAC, high expression of SOX9 correlates with expression of genes belonging to the ERBB pathway. In particular, ERBB2 expression in PDAC cell lines is stimulated by SOX9. Inactivating Sox9 expression in mice confirmed its role in PDAC initiation; it demonstrated that Sox9 stimulates expression of several members of the ERBB pathway and is required for ERBB signalling activity. By integrating data from patient samples and mouse models, we found that SOX9 regulates the ERBB pathway throughout pancreatic tumourigenesis. Our work opens perspectives for therapy targeting tumourigenic mechanisms. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  2. 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

    Aberrant ErbB2 receptor tyrosine kinase activation in breast cancer is strongly linked to an invasive disease. The molecular basis of ErbB2-driven invasion is largely unknown. We show that cysteine cathepsins B and L are elevated in ErbB2 positive primary human breast cancer and function...... as effectors of ErbB2-induced invasion in vitro. We identify Cdc42-binding protein kinase beta, extracellular regulated kinase 2, p21-activated protein kinase 4, and protein kinase C alpha as essential mediators of ErbB2-induced cysteine cathepsin expression and breast cancer cell invasiveness. The identified...

  3. Transcriptional profiling of ErbB signalling in mammary luminal epithelial cells - interplay of ErbB and IGF1 signalling through IGFBP3 regulation

    International Nuclear Information System (INIS)

    Worthington, Jenny; Bertani, Mariana; Chan, Hong-Lin; Gerrits, Bertran; Timms, John F

    2010-01-01

    Members of the ErbB family of growth factor receptors are intricately linked with epithelial cell biology, development and tumourigenesis; however, the mechanisms involved in their downstream signalling are poorly understood. Indeed, it is unclear how signal specificity is achieved and the relative contribution each receptor has to specific gene expression. Gene expression profiling of a human mammary luminal epithelial cell model of ErbB2-overexpression was carried out using cDNA microarrays with a common RNA reference approach to examine long-term overlapping and differential responses to EGF and heregulin beta1 treatment in the context of ErbB2 overexpression. Altered gene expression was validated using quantitative real time PCR and/or immunoblotting. One gene of interest was targeted for further characterisation, where the effects of siRNA-mediated silencing on IGF1-dependent signalling and cellular phenotype were examined and compared to the effects of loss of ErbB2 expression. 775 genes were differentially expressed and clustered in terms of their growth factor responsiveness. As well as identifying uncharacterized genes as novel targets of ErbB2-dependent signalling, ErbB2 overexpression augmented the induction of multiple genes involved in proliferation (e.g. MYC, MAP2K1, MAP2K3), autocrine growth factor signalling (VEGF, PDGF) and adhesion/cytoskeletal regulation (ZYX, THBS1, VCL, CNN3, ITGA2, ITGA3, NEDD9, TAGLN), linking them to the hyper-poliferative and altered adhesive phenotype of the ErbB2-overexpressing cells. We also report ErbB2-dependent down-regulation of multiple interferon-stimulated genes that may permit ErbB2-overexpressing cells to resist the anti-proliferative action of interferons. Finally, IGFBP3 was unique in its pattern of regulation and we further investigated a possible role for IGFBP3 down-regulation in ErbB2-dependent transformation through suppressed IGF1 signalling. We show that IGF1-dependent signalling and proliferation were

  4. A Novel Pathway to Down-Regulate ErbB Signaling in Mammary Epithelial

    National Research Council Canada - National Science Library

    Duan, Lei

    2001-01-01

    .... Based on these observations, this proposal is investigating the role of Cbl-mediated ubiquitination as a signal for targeting activated ErbB receptors to lysosomes where they undergo degradation...

  5. The ErbB family and androgen receptor signaling are targets of Celecoxib in prostate cancer.

    Science.gov (United States)

    Brizzolara, Antonella; Benelli, Roberto; Venè, Roberta; Barboro, Paola; Poggi, Alessandro; Tosetti, Francesca; Ferrari, Nicoletta

    2017-08-01

    Inflammation plays a central role in prostate cancer (PCa) development through significant crosstalk between the COX-2-ErbB family receptor network and androgen receptor (AR)-EGFR signaling pathways. The purpose of this work was to determine the ability of the COX-2 inhibitor Celecoxib to modulate the EGFR-AR signaling pathway in androgen-dependent PCa cells and to provide a rationale for its beneficial use in chemopreventive strategies. Functional studies of Celecoxib activity were performed on LNCaP prostate cancer cells. Western blotting, gene expression analysis, dual-luciferase reporter assay and ELISA were applied to assess the Celecoxib mechanisms of action. We found that Celecoxib, through EGF and amphiregulin (AREG) induction, caused EGFR and ErbB2 activation and consequent degradation associated with the inhibition of androgenic signaling. By upregulating the E3 ubiquitin ligase Nrdp1, Celecoxib also efficiently downregulated ErbB3, which is strongly implicated in castration-resistant prostate cancer. Lastly, Celecoxib directly regulated AR transcription and translation independent of ErbB activation by downregulating the RNA binding protein heterogeneous nuclear ribonucleoprotein K (hnRNP K). The simultaneous suppression of ErbB kinases and androgen signaling by Celecoxib represents a novel strategy to interrupt the vicious cycle of AR/ErbB cross-talk with the primary purpose of undermining their resilient signaling in prostate cancer progression. Our data provide important premises for the chemopreventive use of Celecoxib in the clinical management of prostate cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. In silico prediction of ErbB signal activation from receptor expression ...

    Indian Academy of Sciences (India)

    85

    Annals of biomedical engineering 35 1012-1025. Machado D, Costa RS, Rocha M, Ferreira EC, Tidor B, Rocha I 2011 Modeling formalisms in Systems Biology. AMB Express 1 45. McCabe Pryor M, et al. 2015 Orchestration of ErbB3 signaling through heterointeractions and homointeractions. Mol Biol Cell 26 4109-4123.

  7. Down-Regulation of Neuregulin1/ErbB4 Signaling in the Hippocampus Is Critical for Learning and Memory.

    Science.gov (United States)

    Tian, Jia; Geng, Fei; Gao, Feng; Chen, Yi-Hua; Liu, Ji-Hong; Wu, Jian-Lin; Lan, Yu-Jie; Zeng, Yuan-Ning; Li, Xiao-Wen; Yang, Jian-Ming; Gao, Tian-Ming

    2017-08-01

    Hippocampal function is important for learning and memory, and dysfunction of the hippocampus has been linked to the pathophysiology of neuropsychiatric diseases such as schizophrenia. Neuregulin1 (NRG1) and ErbB4, two susceptibility genes for schizophrenia, reportedly modulate long-term potentiation (LTP) at hippocampal Schaffer collateral (SC)-CA1 synapses. However, little is known regarding the contribution of hippocampal NRG1/ErbB4 signaling to learning and memory function. Here, quantitative real-time PCR and Western blotting were used to assess the mRNA and protein levels of NRG1 and ErbB4. Pharmacological and genetic approaches were used to manipulate NRG1/ErbB4 signaling, following which learning and memory behaviors were evaluated using the Morris water maze, Y-maze test, and the novel object recognition test. Spatial learning was found to reduce hippocampal NRG1 and ErbB4 expression. The blockade of NRG1/ErbB4 signaling in hippocampal CA1, either by neutralizing endogenous NRG1 or inhibiting/ablating ErbB4 receptor activity, enhanced hippocampus-dependent spatial learning, spatial working memory, and novel object recognition memory. Accordingly, administration of exogenous NRG1 impaired those functions. More importantly, the specific ablation of ErbB4 in parvalbumin interneurons also improved learning and memory performance. The manipulation of NRG1/ErbB4 signaling in the present study revealed that NRG1/ErbB4 activity in the hippocampus is critical for learning and memory. These findings might provide novel insights on the pathophysiological mechanisms of schizophrenia and a new target for the treatment of Alzheimer's disease, which is characterized by a progressive decline in cognitive function.

  8. Small tyrosine kinase inhibitors interrupt EGFR signaling by interacting with erbB3 and erbB4 in glioblastoma cell lines

    Energy Technology Data Exchange (ETDEWEB)

    Carrasco-Garcia, Estefania; Saceda, Miguel [Instituto de Biologia Molecular y Celular, Universidad Miguel Hernandez, 03202 Elche (Alicante) (Spain); Unidad de Investigacion, Hospital General Universitario de Elche, 03203 Elche (Alicante) (Spain); Grasso, Silvina; Rocamora-Reverte, Lourdes; Conde, Mariano; Gomez-Martinez, Angeles [Instituto de Biologia Molecular y Celular, Universidad Miguel Hernandez, 03202 Elche (Alicante) (Spain); Garcia-Morales, Pilar [Instituto de Biologia Molecular y Celular, Universidad Miguel Hernandez, 03202 Elche (Alicante) (Spain); Unidad de Investigacion, Hospital General Universitario de Elche, 03203 Elche (Alicante) (Spain); Ferragut, Jose A. [Instituto de Biologia Molecular y Celular, Universidad Miguel Hernandez, 03202 Elche (Alicante) (Spain); Martinez-Lacaci, Isabel, E-mail: imlacaci@umh.es [Instituto de Biologia Molecular y Celular, Universidad Miguel Hernandez, 03202 Elche (Alicante) (Spain); Unidad AECC de Investigacion Traslacional en Cancer, Hospital Universitario Virgen de la Arrixaca, 30120 Murcia (Spain)

    2011-06-10

    Signaling through the epidermal growth factor receptor (EGFR) is relevant in glioblastoma. We have determined the effects of the EGFR inhibitor AG1478 in glioblastoma cell lines and found that U87 and LN-229 cells were very sensitive to this drug, since their proliferation diminished and underwent a marked G{sub 1} arrest. T98 cells were a little more refractory to growth inhibition and A172 cells did not undergo a G{sub 1} arrest. This G{sub 1} arrest was associated with up-regulation of p27{sup kip1}, whose protein turnover was stabilized. EGFR autophosphorylation was blocked with AG1478 to the same extent in all the cell lines. Other small-molecule EGFR tyrosine kinase inhibitors employed in the clinic, such as gefitinib, erlotinib and lapatinib, were able to abrogate proliferation of glioblastoma cell lines, which underwent a G{sub 1} arrest. However, the EGFR monoclonal antibody, cetuximab had no effect on cell proliferation and consistently, had no effect on cell cycle either. Similarly, cetuximab did not inhibit proliferation of U87 {Delta}EGFR cells or primary glioblastoma cell cultures, whereas small-molecule EGFR inhibitors did. Activity of downstream signaling molecules of EGFR such as Akt and especially ERK1/2 was interrupted with EGFR tyrosine kinase inhibitors, whereas cetuximab treatment could not sustain this blockade over time. Small-molecule EGFR inhibitors were able to prevent phosphorylation of erbB3 and erbB4, whereas cetuximab only hindered EGFR phosphorylation, suggesting that EGFR tyrosine kinase inhibitors may mediate their anti-proliferative effects through other erbB family members. We can conclude that small-molecule EGFR inhibitors may be a therapeutic approach for the treatment of glioblastoma patients.

  9. The sorting protein PACS-2 promotes ErbB signalling by regulating recycling of the metalloproteinase ADAM17

    DEFF Research Database (Denmark)

    Dombernowsky, Sarah Louise; Samsøe-Petersen, Jacob; Petersen, Camilla Hansson

    2015-01-01

    The metalloproteinase ADAM17 activates ErbB signalling by releasing ligands from the cell surface, a key step underlying epithelial development, growth and tumour progression. However, mechanisms acutely controlling ADAM17 cell-surface availability to modulate the extent of ErbB ligand release....... PACS-2 co-localizes with ADAM17 on early endosomes and PACS-2 knockdown decreases the recycling and stability of internalized ADAM17. Hence, PACS-2 sustains ADAM17 cell-surface activity by diverting ADAM17 away from degradative pathways. Interestingly, Pacs2-deficient mice display significantly reduced...

  10. Small molecule ErbB inhibitors decrease proliferative signaling and promote apoptosis in philadelphia chromosome-positive acute lymphoblastic leukemia.

    Directory of Open Access Journals (Sweden)

    Mary E Irwin

    Full Text Available The presence of the Philadelphia chromosome in patients with acute lymphoblastic leukemia (Ph(+ALL is a negative prognostic indicator. Tyrosine kinase inhibitors (TKI that target BCR/ABL, such as imatinib, have improved treatment of Ph(+ALL and are generally incorporated into induction regimens. This approach has improved clinical responses, but molecular remissions are seen in less than 50% of patients leaving few treatment options in the event of relapse. Thus, identification of additional targets for therapeutic intervention has potential to improve outcomes for Ph+ALL. The human epidermal growth factor receptor 2 (ErbB2 is expressed in ~30% of B-ALLs, and numerous small molecule inhibitors are available to prevent its activation. We analyzed a cohort of 129 ALL patient samples using reverse phase protein array (RPPA with ErbB2 and phospho-ErbB2 antibodies and found that activity of ErbB2 was elevated in 56% of Ph(+ALL as compared to just 4.8% of Ph(-ALL. In two human Ph+ALL cell lines, inhibition of ErbB kinase activity with canertinib resulted in a dose-dependent decrease in the phosphorylation of an ErbB kinase signaling target p70S6-kinase T389 (by 60% in Z119 and 39% in Z181 cells at 3 µM. Downstream, phosphorylation of S6-kinase was also diminished in both cell lines in a dose-dependent manner (by 91% in both cell lines at 3 µM. Canertinib treatment increased expression of the pro-apoptotic protein Bim by as much as 144% in Z119 cells and 49% in Z181 cells, and further produced caspase-3 activation and consequent apoptotic cell death. Both canertinib and the FDA-approved ErbB1/2-directed TKI lapatinib abrogated proliferation and increased sensitivity to BCR/ABL-directed TKIs at clinically relevant doses. Our results suggest that ErbB signaling is an additional molecular target in Ph(+ALL and encourage the development of clinical strategies combining ErbB and BCR/ABL kinase inhibitors for this subset of ALL patients.

  11. ErbB1-4-dependent EGF/neuregulin signals and their cross talk in the central nervous system: pathological implications in schizophrenia and Parkinson’s disease

    Directory of Open Access Journals (Sweden)

    Yuriko eIwakura

    2013-02-01

    Full Text Available Ligands for ErbB1-4 receptor tyrosine kinases, such as epidermal growth factor (EGF and neuregulins, regulate brain development and function. Thus, abnormalities in their signaling are implicated in the etiology or pathology of schizophrenia and Parkinson’s disease. Among the ErbB receptors, ErbB1 and ErbB4 are expressed in dopamine and GABA neurons, while ErbB1, 2, and/or 3 are mainly present in oligodendrocytes, astrocytes and their precursors. Thus, deficits in ErbB signaling might contribute to schizophrenia neuropathology stemming from these cell types. By incorporating the latest cancer molecular biology as well as our recent progress, we discuss signal cross talk between the ErbB1-4 subunits and their neurobiological functions in each cell type. The potential contribution of virus-derived cytokines (virokines that mimic EGF and neuregulin-1 in brain diseases are also discussed.

  12. RUNX1 positively regulates the ErbB2/HER2 signaling pathway through modulating SOS1 expression in gastric cancer cells.

    Science.gov (United States)

    Mitsuda, Yoshihide; Morita, Ken; Kashiwazaki, Gengo; Taniguchi, Junichi; Bando, Toshikazu; Obara, Moeka; Hirata, Masahiro; Kataoka, Tatsuki R; Muto, Manabu; Kaneda, Yasufumi; Nakahata, Tatsutoshi; Liu, Pu Paul; Adachi, Souichi; Sugiyama, Hiroshi; Kamikubo, Yasuhiko

    2018-04-23

    The dual function of runt-related transcriptional factor 1 (RUNX1) as an oncogene or oncosuppressor has been extensively studied in various malignancies, yet its role in gastric cancer remains elusive. Up-regulation of the ErbB2/HER2 signaling pathway is frequently-encountered in gastric cancer and contributes to the maintenance of these cancer cells. This signaling cascade is partly mediated by son of sevenless homolog (SOS) family, which function as adaptor proteins in the RTK cascades. Herein we report that RUNX1 regulates the ErbB2/HER2 signaling pathway in gastric cancer cells through transactivating SOS1 expression, rendering itself an ideal target in anti-tumor strategy toward this cancer. Mechanistically, RUNX1 interacts with the RUNX1 binding DNA sequence located in SOS1 promoter and positively regulates it. Knockdown of RUNX1 led to the decreased expression of SOS1 as well as dephosphorylation of ErbB2/HER2, subsequently suppressed the proliferation of gastric cancer cells. We also found that our novel RUNX inhibitor (Chb-M') consistently led to the deactivation of the ErbB2/HER2 signaling pathway and was effective against several gastric cancer cell lines. Taken together, our work identified a novel interaction of RUNX1 and the ErbB2/HER2 signaling pathway in gastric cancer, which can potentially be exploited in the management of this malignancy.

  13. Model-based global sensitivity analysis as applied to identification of anti-cancer drug targets and biomarkers of drug resistance in the ErbB2/3 network

    Science.gov (United States)

    Lebedeva, Galina; Sorokin, Anatoly; Faratian, Dana; Mullen, Peter; Goltsov, Alexey; Langdon, Simon P.; Harrison, David J.; Goryanin, Igor

    2012-01-01

    High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a

  14. Structure-based network analysis of activation mechanisms in the ErbB family of receptor tyrosine kinases: the regulatory spine residues are global mediators of structural stability and allosteric interactions.

    Directory of Open Access Journals (Sweden)

    Kevin A James

    Full Text Available The ErbB protein tyrosine kinases are among the most important cell signaling families and mutation-induced modulation of their activity is associated with diverse functions in biological networks and human disease. We have combined molecular dynamics simulations of the ErbB kinases with the protein structure network modeling to characterize the reorganization of the residue interaction networks during conformational equilibrium changes in the normal and oncogenic forms. Structural stability and network analyses have identified local communities integrated around high centrality sites that correspond to the regulatory spine residues. This analysis has provided a quantitative insight to the mechanism of mutation-induced "superacceptor" activity in oncogenic EGFR dimers. We have found that kinase activation may be determined by allosteric interactions between modules of structurally stable residues that synchronize the dynamics in the nucleotide binding site and the αC-helix with the collective motions of the integrating αF-helix and the substrate binding site. The results of this study have pointed to a central role of the conserved His-Arg-Asp (HRD motif in the catalytic loop and the Asp-Phe-Gly (DFG motif as key mediators of structural stability and allosteric communications in the ErbB kinases. We have determined that residues that are indispensable for kinase regulation and catalysis often corresponded to the high centrality nodes within the protein structure network and could be distinguished by their unique network signatures. The optimal communication pathways are also controlled by these nodes and may ensure efficient allosteric signaling in the functional kinase state. Structure-based network analysis has quantified subtle effects of ATP binding on conformational dynamics and stability of the EGFR structures. Consistent with the NMR studies, we have found that nucleotide-induced modulation of the residue interaction networks is not

  15. Self-renewal of human embryonic stem cells requires insulin-like growth factor-1 receptor and ERBB2 receptor signaling

    Science.gov (United States)

    Wang, Linlin; Schulz, Thomas C.; Sherrer, Eric S.; Dauphin, Derek S.; Shin, Soojung; Nelson, Angelique M.; Ware, Carol B.; Zhan, Mei; Song, Chao-Zhong; Chen, Xiaoji; Brimble, Sandii N.; McLean, Amanda; Galeano, Maria J.; Uhl, Elizabeth W.; D'Amour, Kevin A.; Chesnut, Jonathan D.; Rao, Mahendra S.

    2007-01-01

    Despite progress in developing defined conditions for human embryonic stem cell (hESC) cultures, little is known about the cell-surface receptors that are activated under conditions supportive of hESC self-renewal. A simultaneous interrogation of 42 receptor tyrosine kinases (RTKs) in hESCs following stimulation with mouse embryonic fibroblast (MEF) conditioned medium (CM) revealed rapid and prominent tyrosine phosphorylation of insulin receptor (IR) and insulin-like growth factor-1 receptor (IGF1R); less prominent tyrosine phosphorylation of epidermal growth factor receptor (EGFR) family members, including ERBB2 and ERBB3; and trace phosphorylation of fibroblast growth factor receptors. Intense IGF1R and IR phosphorylation occurred in the absence of MEF conditioning (NCM) and was attributable to high concentrations of insulin in the proprietary KnockOut Serum Replacer (KSR). Inhibition of IGF1R using a blocking antibody or lentivirus-delivered shRNA reduced hESC self-renewal and promoted differentiation, while disruption of ERBB2 signaling with the selective inhibitor AG825 severely inhibited hESC proliferation and promoted apoptosis. A simple defined medium containing an IGF1 analog, heregulin-1β (a ligand for ERBB2/ERBB3), fibroblast growth factor-2 (FGF2), and activin A supported long-term growth of multiple hESC lines. These studies identify previously unappreciated RTKs that support hESC proliferation and self-renewal, and provide a rationally designed medium for the growth and maintenance of pluripotent hESCs. PMID:17761519

  16. RhNRG-1β Protects the Myocardium against Irradiation-Induced Damage via the ErbB2-ERK-SIRT1 Signaling Pathway.

    Directory of Open Access Journals (Sweden)

    Anxin Gu

    Full Text Available Radiation-induced heart disease (RIHD, which is a serious side effect of the radiotherapy applied for various tumors due to the inevitable irradiation of the heart, cannot be treated effectively using current clinical therapies. Here, we demonstrated that rhNRG-1β, an epidermal growth factor (EGF-like protein, protects myocardium tissue against irradiation-induced damage and preserves cardiac function. rhNRG-1β effectively ameliorated irradiation-induced myocardial nuclear damage in both cultured adult rat-derived cardiomyocytes and rat myocardium tissue via NRG/ErbB2 signaling. By activating ErbB2, rhNRG-1β maintained mitochondrial integrity, ATP production, respiratory chain function and the Krebs cycle status in irradiated cardiomyocytes. Moreover, the protection of irradiated cardiomyocytes and myocardium tissue by rhNRG-1β was at least partly mediated by the activation of the ErbB2-ERK-SIRT1 signaling pathway. Long-term observations further showed that rhNRG-1β administered in the peri-irradiation period exerts continuous protective effects on cardiac pump function, the myocardial energy metabolism, cardiomyocyte volume and interstitial fibrosis in the rats receiving radiation via NRG/ErbB2 signaling. Our findings indicate that rhNRG-1β can protect the myocardium against irradiation-induced damage and preserve cardiac function via the ErbB2-ERK-SIRT1 signaling pathway.

  17. Alterations in cell growth and signaling in ErbB3 binding protein-1 (Ebp1 deficient mice

    Directory of Open Access Journals (Sweden)

    Lee Myounghee

    2008-12-01

    Full Text Available Abstract Background The ErbB3 binding protein-1 (Ebp1 belongs to a family of DNA/RNA binding proteins implicated in cell growth, apoptosis and differentiation. However, the physiological role of Ebp1 in the whole organism is not known. Therefore, we generated Ebp1-deficient mice carrying a gene trap insertion in intron 2 of the Ebp1 (pa2g4 gene. Results Ebp1-/- mice were on average 30% smaller than wild type and heterozygous sex matched littermates. Growth retardation was apparent from Day 10 until Day 30. IGF-1 production and IGBP-3 and 4 protein levels were reduced in both embryo fibroblasts and adult knock-out mice. The proliferation of fibroblasts derived from Day 12.5 knock out embryos was also decreased as compared to that of wild type cells. Microarray expression analysis revealed changes in genes important in cell growth including members of the MAPK signal transduction pathway. In addition, the expression or activation of proliferation related genes such as AKT and the androgen receptor, previously demonstrated to be affected by Ebp1 expression in vitro, was altered in adult tissues. Conclusion These results indicate that Ebp1 can affect growth in an animal model, but that the expression of proliferation related genes is cell and context specific. The Ebp1-/- mouse line represents a new in vivo model to investigate Ebp1 function in the whole organism.

  18. Disruption of the ErbB signaling in adolescence increases striatal dopamine levels and affects learning and hedonic-like behavior in the adult mouse.

    Science.gov (United States)

    Golani, Idit; Tadmor, Hagar; Buonanno, Andres; Kremer, Ilana; Shamir, Alon

    2014-11-01

    The ErbB signaling pathway has been genetically and functionally implicated in schizophrenia. Numerous findings support the dysregulation of Neuregulin (NRG) and epidermal growth factor (EGF) signaling in schizophrenia. However, it is unclear whether alterations of these pathways in the adult brain or during development are involved in the pathophysiology of schizophrenia. Herein we characterized the behavioral profile and molecular changes resulting from pharmacologically blocking the ErbB signaling pathway during a critical period in the development of decision making, planning, judgments, emotions, social cognition and cognitive skills, namely adolescence. We demonstrate that chronic administration of the pan-ErbB kinase inhibitor JNJ-28871063 (JNJ) to adolescent mice elevated striatal dopamine levels and reduced preference for sucrose without affecting locomotor activity and exploratory behavior. In adulthood, adolescent JNJ-treated mice continue to consume less sucrose and needed significantly more correct-response trials to reach the learning criterion during the discrimination phase of the T-maze reversal learning task than their saline-injected controls. In addition, JNJ mice exhibited deficit in reference memory but not in working memory as measured in the radial arm maze. Inhibition of the pathway during adolescence did not affect exploratory behavior and locomotor activity in the open field, social interaction, social memory, and reversal learning in adult mice. Our data suggest that alteration of ErbB signaling during adolescence resulted in changes in the dopaminergic systems that emerge in pathological learning and hedonic behavior in adulthood, and pinpoints the possible role of the pathway in the development of cognitive skills and motivated behavior. Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.

  19. Breast cancer cells can switch between estrogen receptor alpha and ErbB signaling and combined treatment against both signaling pathways postpones development of resistance

    DEFF Research Database (Denmark)

    Sonne-Hansen, Katrine; Norrie, Ida C; Emdal, Kristina Bennet

    2010-01-01

    circumvent development of resistance. Limited effects were observed when targeting EGFR and ErbB2 with the monoclonal antibodies cetuximab, trastuzumab, and pertuzumab, whereas the pan-ErbB inhibitor CI-1033 selectively inhibited growth of fulvestrant resistant cell lines. CI-1033 inhibited Erk but not Akt...

  20. A Common Variant in ERBB4 Regulates GABA Concentrations in Human Cerebrospinal Fluid

    NARCIS (Netherlands)

    Luykx, Jurjen J.; Vinkers, Christiaan H.; Bakker, Steven C.; Visser, Wouter F.; van Boxmeer, Loes; Strengman, Eric; van Eijk, Kristel R.; Lens, Judith A.; Borgdorff, Paul; Keijzers, Peter; Kappen, Teus H.; van Dongen, Eric P. A.; Bruins, Peter; Verhoeven, Nanda M.; de Koning, Tom J.; Kahn, Rene S.; Ophoff, Roel A.

    The neuregulin 1 (NRG1) receptor ErbB4 is involved in the development of cortical inhibitory GABAergic circuits and NRG1-ErbB4 signaling has been implicated in schizophrenia (SCZ). A magnetic resonance spectroscopy (H-1-MRS) study has demonstrated that a single-nucleotide polymorphism in ERBB4,

  1. Reconstruction of cellular signal transduction networks using perturbation assays and linear programming.

    Science.gov (United States)

    Knapp, Bettina; Kaderali, Lars

    2013-01-01

    Perturbation experiments for example using RNA interference (RNAi) offer an attractive way to elucidate gene function in a high throughput fashion. The placement of hit genes in their functional context and the inference of underlying networks from such data, however, are challenging tasks. One of the problems in network inference is the exponential number of possible network topologies for a given number of genes. Here, we introduce a novel mathematical approach to address this question. We formulate network inference as a linear optimization problem, which can be solved efficiently even for large-scale systems. We use simulated data to evaluate our approach, and show improved performance in particular on larger networks over state-of-the art methods. We achieve increased sensitivity and specificity, as well as a significant reduction in computing time. Furthermore, we show superior performance on noisy data. We then apply our approach to study the intracellular signaling of human primary nave CD4(+) T-cells, as well as ErbB signaling in trastuzumab resistant breast cancer cells. In both cases, our approach recovers known interactions and points to additional relevant processes. In ErbB signaling, our results predict an important role of negative and positive feedback in controlling the cell cycle progression.

  2. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.

    2013-01-01

    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

  3. ErbB2 resembles an autoinhibited invertebrate epidermal growth factor receptor

    Energy Technology Data Exchange (ETDEWEB)

    Alvarado, Diego; Klein, Daryl E.; Lemmon, Mark A.; (UPENN-MED)

    2009-09-25

    The orphan receptor tyrosine kinase ErbB2 (also known as HER2 or Neu) transforms cells when overexpressed, and it is an important therapeutic target in human cancer. Structural studies have suggested that the oncogenic (and ligand-independent) signalling properties of ErbB2 result from the absence of a key intramolecular 'tether' in the extracellular region that autoinhibits other human ErbB receptors, including the epidermal growth factor (EGF) receptor. Although ErbB2 is unique among the four human ErbB receptors, here we show that it is the closest structural relative of the single EGF receptor family member in Drosophila melanogaster (dEGFR). Genetic and biochemical data show that dEGFR is tightly regulated by growth factor ligands, yet a crystal structure shows that it, too, lacks the intramolecular tether seen in human EGFR, ErbB3 and ErbB4. Instead, a distinct set of autoinhibitory interdomain interactions hold unliganded dEGFR in an inactive state. All of these interactions are maintained (and even extended) in ErbB2, arguing against the suggestion that ErbB2 lacks autoinhibition. We therefore suggest that normal and pathogenic ErbB2 signalling may be regulated by ligands in the same way as dEGFR. Our findings have important implications for ErbB2 regulation in human cancer, and for developing therapeutic approaches that target novel aspects of this orphan receptor.

  4. Presynaptic type III neuregulin1-ErbB signaling targets {alpha}7 nicotinic acetylcholine receptors to axons.

    Science.gov (United States)

    Hancock, Melissa L; Canetta, Sarah E; Role, Lorna W; Talmage, David A

    2008-05-05

    Type III Neuregulin1 (Nrg1) isoforms are membrane-tethered proteins capable of participating in bidirectional juxtacrine signaling. Neuronal nicotinic acetylcholine receptors (nAChRs), which can modulate the release of a rich array of neurotransmitters, are differentially targeted to presynaptic sites. We demonstrate that Type III Nrg1 back signaling regulates the surface expression of alpha7 nAChRs along axons of sensory neurons. Stimulation of Type III Nrg1 back signaling induces an increase in axonal surface alpha7 nAChRs, which results from a redistribution of preexisting intracellular pools of alpha7 rather than from increased protein synthesis. We also demonstrate that Type III Nrg1 back signaling activates a phosphatidylinositol 3-kinase signaling pathway and that activation of this pathway is required for the insertion of preexisting alpha7 nAChRs into the axonal plasma membrane. These findings, in conjunction with prior results establishing that Type III Nrg1 back signaling controls gene transcription, demonstrate that Type III Nrg1 back signaling can regulate both short-and long-term changes in neuronal function.

  5. Presynaptic type III neuregulin1-ErbB signaling targets alpha7 nicotinic acetylcholine receptors to axons.

    Science.gov (United States)

    Hancock, Melissa L; Canetta, Sarah E; Role, Lorna W; Talmage, David A

    2008-06-01

    Type III Neuregulin1 (Nrg1) isoforms are membrane-tethered proteins capable of participating in bidirectional juxtacrine signaling. Neuronal nicotinic acetylcholine receptors (nAChRs), which can modulate the release of a rich array of neurotransmitters, are differentially targeted to presynaptic sites. We demonstrate that Type III Nrg1 back signaling regulates the surface expression of alpha7 nAChRs along axons of sensory neurons. Stimulation of Type III Nrg1 back signaling induces an increase in axonal surface alpha7 nAChRs, which results from a redistribution of preexisting intracellular pools of alpha7 rather than from increased protein synthesis. We also demonstrate that Type III Nrg1 back signaling activates a phosphatidylinositol 3-kinase signaling pathway and that activation of this pathway is required for the insertion of preexisting alpha7 nAChRs into the axonal plasma membrane. These findings, in conjunction with prior results establishing that Type III Nrg1 back signaling controls gene transcription, demonstrate that Type III Nrg1 back signaling can regulate both short-and long-term changes in neuronal function.

  6. Presynaptic Type III Neuregulin1-ErbB signaling targets α7 nicotinic acetylcholine receptors to axons

    Science.gov (United States)

    Hancock, Melissa L.; Canetta, Sarah E.; Role, Lorna W.; Talmage, David A.

    2008-01-01

    Type III Neuregulin1 (Nrg1) isoforms are membrane-tethered proteins capable of participating in bidirectional juxtacrine signaling. Neuronal nicotinic acetylcholine receptors (nAChRs), which can modulate the release of a rich array of neurotransmitters, are differentially targeted to presynaptic sites. We demonstrate that Type III Nrg1 back signaling regulates the surface expression of α7 nAChRs along axons of sensory neurons. Stimulation of Type III Nrg1 back signaling induces an increase in axonal surface α7 nAChRs, which results from a redistribution of preexisting intracellular pools of α7 rather than from increased protein synthesis. We also demonstrate that Type III Nrg1 back signaling activates a phosphatidylinositol 3-kinase signaling pathway and that activation of this pathway is required for the insertion of preexisting α7 nAChRs into the axonal plasma membrane. These findings, in conjunction with prior results establishing that Type III Nrg1 back signaling controls gene transcription, demonstrate that Type III Nrg1 back signaling can regulate both short-and long-term changes in neuronal function. PMID:18458158

  7. 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.)

  8. Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance

    Directory of Open Access Journals (Sweden)

    Thieffry Denis

    2009-01-01

    Full Text Available Abstract Background In breast cancer, overexpression of the transmembrane tyrosine kinase ERBB2 is an adverse prognostic marker, and occurs in almost 30% of the patients. For therapeutic intervention, ERBB2 is targeted by monoclonal antibody trastuzumab in adjuvant settings; however, de novo resistance to this antibody is still a serious issue, requiring the identification of additional targets to overcome resistance. In this study, we have combined computational simulations, experimental testing of simulation results, and finally reverse engineering of a protein interaction network to define potential therapeutic strategies for de novo trastuzumab resistant breast cancer. Results First, we employed Boolean logic to model regulatory interactions and simulated single and multiple protein loss-of-functions. Then, our simulation results were tested experimentally by producing single and double knockdowns of the network components and measuring their effects on G1/S transition during cell cycle progression. Combinatorial targeting of ERBB2 and EGFR did not affect the response to trastuzumab in de novo resistant cells, which might be due to decoupling of receptor activation and cell cycle progression. Furthermore, examination of c-MYC in resistant as well as in sensitive cell lines, using a specific chemical inhibitor of c-MYC (alone or in combination with trastuzumab, demonstrated that both trastuzumab sensitive and resistant cells responded to c-MYC perturbation. Conclusion In this study, we connected ERBB signaling with G1/S transition of the cell cycle via two major cell signaling pathways and two key transcription factors, to model an interaction network that allows for the identification of novel targets in the treatment of trastuzumab resistant breast cancer. Applying this new strategy, we found that, in contrast to trastuzumab sensitive breast cancer cells, combinatorial targeting of ERBB receptors or of key signaling intermediates does not

  9. Vitamin E analogs trigger apoptosis in HER2/erbB2-overexpressing breast cancer cells by signaling via the mitochondrial pathway

    Czech Academy of Sciences Publication Activity Database

    Wang, X.-F.; Witting, P. K.; Salvatore, B.A.; Neužil, Jiří

    2005-01-01

    Roč. 326, č. 4 (2005), s. 282-289 ISSN 0006-291X Institutional research plan: CEZ:AV0Z5052915; CEZ:AV0Z50520514 Keywords : vitamin E analogs * apoptosis * ErbB2 Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.000, year: 2005

  10. 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.

  11. Aberrations of ERBB2 and TOP2A Genes in Breast Cancer

    DEFF Research Database (Denmark)

    Nielsen, Kirsten Vang; Müller, Sven; Møller, Susanne

    2009-01-01

    genes and the other by having amplification of ERBB2 and deletion of TOP2A. The characteristics are compared to findings on paired ERBB2 and TOP2A data from 649 patients with invasive breast cancer from a previously published biomarker study. The physical localization of FISH signals in metaphase...... spreads from cell lines showed that simultaneous amplification is not a simple co-amplification of a whole amplicon containing both genes. Most gene signals are translocated to abnormal marker chromosomes. ERBB2 genes but not TOP2A genes are present in tandem amplicons, leading to a higher ERBB2 ratio....... This observation was confirmed by patient FISH data: among 276 (43% of all patients) abnormal tumors, 67% had different ERBB2 and TOP2A status. ERBB2 amplification with normal TOP2A status was found in 36% of the abnormal tumors (15% of all patients). Simultaneous amplification of both genes was found in 28...

  12. Interaction with epsin 1 regulates the constitutive clathrin-dependent internalization of ErbB3.

    Science.gov (United States)

    Szymanska, Monika; Fosdahl, Anne Marthe; Raiborg, Camilla; Dietrich, Markus; Liestøl, Knut; Stang, Espen; Bertelsen, Vibeke

    2016-06-01

    In contrast to other members of the EGF receptor family, ErbB3 is constitutively internalized in a clathrin-dependent manner. Previous studies have shown that ErbB3 does not interact with the coated pit localized adaptor complex 2 (AP-2), and that ErbB3 lacks two AP-2 interacting internalization signals identified in the EGF receptor. Several other clathrin-associated sorting proteins which may recruit cargo into coated pits have, however, been identified, and the study was performed to identify adaptors needed for constitutive internalization of ErbB3. A high-throughput siRNA screen was used to identify adaptor proteins needed for internalization of ErbB3. Upon knock-down of candidate proteins internalization of ErbB3 was identified using an antibody-based internalization assay combined with automatic fluorescence microscopy. Among 29 candidates only knock-down of epsin 1 turned out to inhibit ErbB3. Epsin 1 has ubiquitin interacting motifs (UIMs) and we show that ErbB3 interacts with an epsin 1 deletion mutant containing these UIMs. In support of an ErbB3-epsin 1 UIM dependent interaction, we show that ErbB3 is constitutively ubiquitinated, but that both ubiquitination and the ErbB3-epsin 1 interaction increase upon ligand binding. Altogether the results are consistent with a model whereby both constitutive and ligand-induced internalization of ErbB3 are regulated through interaction with epsin 1. Internalization is an important regulator of growth factor receptor mediated signaling and the current study identify mechanisms regulating plasma membrane turnover of ErbB3. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Protein-Trap Insertional Mutagenesis Uncovers New Genes Involved in Zebrafish Skin Development, Including a Neuregulin 2a-Based ErbB Signaling Pathway Required during Median Fin Fold Morphogenesis.

    Directory of Open Access Journals (Sweden)

    Stephanie E Westcot

    Full Text Available Skin disorders are widespread, but available treatments are limited. A more comprehensive understanding of skin development mechanisms will drive identification of new treatment targets and modalities. Here we report the Zebrafish Integument Project (ZIP, an expression-driven platform for identifying new skin genes and phenotypes in the vertebrate model Danio rerio (zebrafish. In vivo selection for skin-specific expression of gene-break transposon (GBT mutant lines identified eleven new, revertible GBT alleles of genes involved in skin development. Eight genes--fras1, grip1, hmcn1, msxc, col4a4, ahnak, capn12, and nrg2a--had been described in an integumentary context to varying degrees, while arhgef25b, fkbp10b, and megf6a emerged as novel skin genes. Embryos homozygous for a GBT insertion within neuregulin 2a (nrg2a revealed a novel requirement for a Neuregulin 2a (Nrg2a-ErbB2/3-AKT signaling pathway governing the apicobasal organization of a subset of epidermal cells during median fin fold (MFF morphogenesis. In nrg2a mutant larvae, the basal keratinocytes within the apical MFF, known as ridge cells, displayed reduced pAKT levels as well as reduced apical domains and exaggerated basolateral domains. Those defects compromised proper ridge cell elongation into a flattened epithelial morphology, resulting in thickened MFF edges. Pharmacological inhibition verified that Nrg2a signals through the ErbB receptor tyrosine kinase network. Moreover, knockdown of the epithelial polarity regulator and tumor suppressor lgl2 ameliorated the nrg2a mutant phenotype. Identifying Lgl2 as an antagonist of Nrg2a-ErbB signaling revealed a significantly earlier role for Lgl2 during epidermal morphogenesis than has been described to date. Furthermore, our findings demonstrated that successive, coordinated ridge cell shape changes drive apical MFF development, making MFF ridge cells a valuable model for investigating how the coordinated regulation of cell polarity

  14. Protein-Trap Insertional Mutagenesis Uncovers New Genes Involved in Zebrafish Skin Development, Including a Neuregulin 2a-Based ErbB Signaling Pathway Required during Median Fin Fold Morphogenesis.

    Science.gov (United States)

    Westcot, Stephanie E; Hatzold, Julia; Urban, Mark D; Richetti, Stefânia K; Skuster, Kimberly J; Harm, Rhianna M; Lopez Cervera, Roberto; Umemoto, Noriko; McNulty, Melissa S; Clark, Karl J; Hammerschmidt, Matthias; Ekker, Stephen C

    2015-01-01

    Skin disorders are widespread, but available treatments are limited. A more comprehensive understanding of skin development mechanisms will drive identification of new treatment targets and modalities. Here we report the Zebrafish Integument Project (ZIP), an expression-driven platform for identifying new skin genes and phenotypes in the vertebrate model Danio rerio (zebrafish). In vivo selection for skin-specific expression of gene-break transposon (GBT) mutant lines identified eleven new, revertible GBT alleles of genes involved in skin development. Eight genes--fras1, grip1, hmcn1, msxc, col4a4, ahnak, capn12, and nrg2a--had been described in an integumentary context to varying degrees, while arhgef25b, fkbp10b, and megf6a emerged as novel skin genes. Embryos homozygous for a GBT insertion within neuregulin 2a (nrg2a) revealed a novel requirement for a Neuregulin 2a (Nrg2a)-ErbB2/3-AKT signaling pathway governing the apicobasal organization of a subset of epidermal cells during median fin fold (MFF) morphogenesis. In nrg2a mutant larvae, the basal keratinocytes within the apical MFF, known as ridge cells, displayed reduced pAKT levels as well as reduced apical domains and exaggerated basolateral domains. Those defects compromised proper ridge cell elongation into a flattened epithelial morphology, resulting in thickened MFF edges. Pharmacological inhibition verified that Nrg2a signals through the ErbB receptor tyrosine kinase network. Moreover, knockdown of the epithelial polarity regulator and tumor suppressor lgl2 ameliorated the nrg2a mutant phenotype. Identifying Lgl2 as an antagonist of Nrg2a-ErbB signaling revealed a significantly earlier role for Lgl2 during epidermal morphogenesis than has been described to date. Furthermore, our findings demonstrated that successive, coordinated ridge cell shape changes drive apical MFF development, making MFF ridge cells a valuable model for investigating how the coordinated regulation of cell polarity and cell shape

  15. ErbB receptors and cell polarity: New pathways and paradigms for understanding cell migration and invasion

    International Nuclear Information System (INIS)

    Feigin, Michael E.; Muthuswamy, Senthil K.

    2009-01-01

    The ErbB family of receptor tyrosine kinases is involved in initiation and progression of a number of human cancers, and receptor activation or overexpression correlates with poor patient survival. Research over the past two decades has elucidated the molecular mechanisms underlying ErbB-induced tumorigenesis, which has resulted in the development of effective targeted therapies. ErbB-induced signal transduction cascades regulate a wide variety of cell processes, including cell proliferation, apoptosis, cell polarity, migration and invasion. Within tumors, disruption of these core processes, through cooperative oncogenic lesions, results in aggressive, metastatic disease. This review will focus on the ErbB signaling networks that regulate migration and invasion and identify a potential role for cell polarity pathways during cancer progression

  16. Signal Processing and Neural Network Simulator

    Science.gov (United States)

    Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.

    1995-04-01

    The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

  17. Decreased internalisation of erbB1 mutants in lung cancer is linked with a mechanism conferring sensitivity to gefitinib.

    Science.gov (United States)

    Hendriks, B S; Griffiths, G J; Benson, R; Kenyon, D; Lazzara, M; Swinton, J; Beck, S; Hickinson, M; Beusmans, J M; Lauffenburger, D; de Graaf, D

    2006-11-01

    A majority of gefitinib (IRESSA)-responsive tumours in non-small cell lung cancer have been found to carry mutations in ErbB1. Previously, it has been observed that internalisation-deficient ErbB1 receptors are strong drivers of oncogenesis. Using a computational model of ErbB1 trafficking and signalling, it is found that a deficiency in ErbB1 internalisation is sufficient to explain the observed signalling phenotype of these gefitinib-responsive ErbB1 mutants in lung cancer cell lines. Experimental tests confirm that gefitinib-sensitive cell lines with and without ErbB1 mutations exhibit markedly slower internalisation rates than gefitinib-insensitive cell lines. Moreover, the computational model demonstrates that reduced ErbB1 internalisation rates are mechanistically linked to upregulated AKT signalling. Experimentally it is confirmed that impaired internalisation of ErbB1 is associated with increased AKT activity, which can be blocked by gefitinib. On the basis of these experimental and computational results, it is surmised that gefitinib sensitivity is a marker of a reliance on AKT signalling for cell survival that may be brought about by impaired ErbB1 internalisation.

  18. Signal-regulated systems and networks

    CSIR Research Space (South Africa)

    Van Zyl, TL

    2010-07-01

    Full Text Available The article presents the use of signal regulatory networks (SRNs), a biologically inspired model based on gene regulatory networks. SRNs are a way of understanding a class of self-organizing IT systems, signal-regulated systems (SRSs). This article...

  19. Growth inhibitory effects of the dual ErbB1/ErbB2 tyrosine kinase inhibitor PKI-166 on human prostate cancer xenografts.

    Science.gov (United States)

    Mellinghoff, Ingo K; Tran, Chris; Sawyers, Charles L

    2002-09-15

    Experiments with human prostate cancer cell lines have shown that forced overexpression of the ErbB2-receptor tyrosine kinase (RTK) promotes androgen-independent growth and increases androgen receptor-transcriptional activity in a ligand-independent fashion. To investigate the relationship between ErbB-RTK signaling and androgen in genetically unmanipulated human prostate cancer, we performed biochemical and biological studies with the dual ErbB1/ErbB2 RTK inhibitor PKI-166 using human prostate cancer xenograft models with isogenic sublines reflecting the transition from androgen-dependent to androgen-independent growth. In the presence of low androgen concentrations, PKI-166 showed profound growth-inhibitory effects on tumor growth, which could be partially reversed by androgen add-back. At physiological androgen concentrations, androgen withdrawal greatly enhanced the ability of PKI-166 to retard tumor growth. The level of extracellular signal-regulated kinase activation correlated with the response to PKI-166 treatment, whereas the expression levels of ErbB1 and ErbB2 did not. These results suggest that ErbB1/ErbB2 RTKs play an important role in the biology of androgen-independent prostate cancer and provide a rationale for clinical evaluation of inhibitors targeted to this pathway.

  20. Antipsychotic potential of quinazoline ErbB1 inhibitors in a schizophrenia model established with neonatal hippocampal lesioning.

    Science.gov (United States)

    Mizuno, Makoto; Iwakura, Yuriko; Shibuya, Masako; Zheng, Yingjun; Eda, Takeyoshi; Kato, Taisuke; Takasu, Yohei; Nawa, Hiroyuki

    2010-01-01

    Hyper-signaling of the epidermal growth factor receptor family (ErbB) is implicated in the pathophysiology of schizophrenia. Various quinazoline inhibitors targeting ErbB1 or ErbB2 - 4 have been developed as anti-cancer agents and might be useful for antipsychotic treatment. In the present study, we used an animal model of schizophrenia established by neonatal hippocampal lesioning and evaluated the neurobehavioral consequences of ErbB1-inhibitor treatment. Subchronic administration of the ErbB1 inhibitor ZD1839 to the cerebroventricle of rats receiving neonatal hippocampal lesioning ameliorated deficits in prepulse inhibition as well as those in the latent inhibition of tone-dependent fear learning. There were no apparent adverse effects on basal learning scores or locomotor activity, however. The administration of other ErbB1 inhibitors, PD153035 and OSI-774, similarly attenuated the prepulse inhibition impairment of this animal model. In parallel, there were decreases in ErbB1 phosphorylation in animals treated with ErbB1 inhibitors. These results indicate an antipsychotic potential of quinazoline ErbB1 inhibitors. ErbB receptor tyrosine kinases may be novel therapeutic targets for schizophrenia or its related psychotic symptoms.

  1. ERBB oncogene proteins as targets for monoclonal antibodies.

    Science.gov (United States)

    Polanovski, O L; Lebedenko, E N; Deyev, S M

    2012-03-01

    General properties of the family of tyrosine kinase ERBB receptors are considered in connection with their role in the generation of cascades of signal transduction in normal and tumor cells. Causes of acquisition of oncogene features by genes encoding these receptors and their role in tumorigenesis are analyzed. Anti-ERBB monoclonal antibodies approved for therapy are described in detail, and mechanisms of their antitumor activity and development of resistance to them are reviewed. The existing and the most promising strategies for creating and using monoclonal antibodies and their derivatives for therapy of cancer are discussed.

  2. [Bacterial synthesis, purification, and solubilization of transmembrane segments of ErbB family members].

    Science.gov (United States)

    Goncharuk, M V; Shul'ga, A A; Ermoliuk, Ia S; Tkach, E N; Goncharuk, S A; Pustovalova, Iu E; Mineev, K S; Bocharov, É V; Maslennikov, I V; Arsen'ev, A S; Kirpichnikov, M P

    2011-01-01

    A family of epidermal growth factor receptors, ErbB, represents an important class of receptor tyrosine kinases, playing a leading role in cellular growth, development and differentiation. Transmembrane domains of these receptors transduce biochemical signals across plasma membrane via lateral homo- and heterodimerization. Relatively small size of complexes of ErbB transmembrane domains with detergents or lipids allows one to study their detailed spatial structure using three-dimensional heteronuclear high-resolution NMR spectroscopy. Here, we describe the effective expression system and purification procedure for preparative-scale production of transmembrane peptides from four representatives of ErbB family, ErbB1, ErbB2, ErbB3, ErbB4, for structural studies. The recombinant peptides were produced in Escherichia coli BL21(DE3)pLysS as C-terminal extensions of thioredoxin A. The fusion protein cleavage was accomplished with the light subunit of human enterokinase. Several (10-30) milligrams of purified isotope-labeled transmembrane peptides were isolated with the use of a simple and convenient procedure, which consists of consecutive steps of immobilized metal affinity chromatography and cation-exchange chromatography. The purified peptides were reconstituted in lipid/detergent environment (micelles or bicelles) and characterized using dynamic light scattering, CD and NMR spectroscopy. The data obtained indicate that the purified ErbB transmembrane peptides are suitable for structural and dynamic studies of their homo- and heterodimer complexes using high resolution NMR spectroscopy.

  3. Modulation of the Neuregulin 1/ErbB system after skeletal muscle denervation and reinnervation.

    Science.gov (United States)

    Morano, Michela; Ronchi, Giulia; Nicolò, Valentina; Fornasari, Benedetta Elena; Crosio, Alessandro; Perroteau, Isabelle; Geuna, Stefano; Gambarotta, Giovanna; Raimondo, Stefania

    2018-03-22

    Neuregulin 1 (NRG1) is a growth factor produced by both peripheral nerves and skeletal muscle. In muscle, it regulates neuromuscular junction gene expression, acetylcholine receptor number, muscle homeostasis and satellite cell survival. NRG1 signalling is mediated by the tyrosine kinase receptors ErbB3 and ErbB4 and their co-receptors ErbB1 and ErbB2. The NRG1/ErbB system is well studied in nerve tissue after injury, but little is known about this system in skeletal muscle after denervation/reinnervation processes. Here, we performed a detailed time-course expression analysis of several NRG1 isoforms and ErbB receptors in the rat superficial digitorum flexor muscle after three types of median nerve injuries of different severities. We found that ErbB receptor expression was correlated with the innervated state of the muscle, with upregulation of ErbB2 clearly associated with the denervation state. Interestingly, the NRG1 isoforms were differently regulated depending on the nerve injury type, leading to the hypothesis that both the NRG1α and NRG1β isoforms play a key role in the muscle reaction to injury. Indeed, in vitro experiments with C2C12 atrophic myotubes revealed that both NRG1α and NRG1β treatment influences the best-known atrophic pathways, suggesting that NRG1 might play an anti-atrophic role.

  4. Role of ErbB receptors in cancer cell migration and invasion

    Directory of Open Access Journals (Sweden)

    Aline eAppert-Collin

    2015-11-01

    Full Text Available Growth factors mediate their diverse biologic responses (regulation of cellular proliferation, differentiation, migration and survival by binding to and activating cell-surface receptors with intrinsic protein kinase activity named Receptor Tyrosine Kinases (RTKs. About 60 RTKs have been identified and can be classified into more than 16 different receptor families. Their activity is normally tightly controlled and regulated. Overexpression of RTK proteins or functional alterations caused by mutations in the corresponding genes or abnormal stimulation by autocrine growth factor loops contribute to constitutive RTK signaling, resulting in alterations in the physiological activities of cells. The ErbB receptor family of RTKs comprises four distinct receptors: the EGFR (also known as ErbB1/HER1, ErbB2 (neu, HER2, ErbB3 (HER3 and ErbB4 (HER4. ErbB family members are often overexpressed, amplified, or mutated in many forms of cancer, making them important therapeutic targets. EGFR has been found to be amplified in gliomas and non-small-cell lung carcinoma while ErbB2 amplifications are seen in breast, ovarian, bladder, non-small-cell lung carcinoma, as well as several other tumor types. Several data have shown that ErbB receptor family and its downstream pathway regulate epithelial-mesenchymal transition, migration, and tumor invasion by modulating extracellular matrix components. Recent findings indicate that extracellular matrix components such as matrikines bind specifically to EGF receptor and promote cell invasion. In this review, we will present an in-depth overview of the structure, mechanisms, cell signaling, and functions of ErbB family receptors in cell adhesion and migration. Furthermore, we will describe in a last part the new strategies developed in anti-cancer therapy to inhibit ErbB family receptor activation.

  5. Novel Peptide/Protein Delivery System Targeting erbB2-Overexpressing Breast Cancer Cells

    National Research Council Canada - National Science Library

    Yu, Dihua

    2002-01-01

    .... During this funding year, we focused on the delivery of erbB2 signal-blocking ESP peptides (objective 2) . Because of the complexity of biotin-penetratin-AHNP-ESP, the synthesis was unsuccessful...

  6. 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.

  7. 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....

  8. 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

  9. Ibrutinib (ImbruvicaTM) potently inhibits ErbB receptor phosphorylation and cell viability of ErbB2-positive breast cancer cells.

    Science.gov (United States)

    Grabinski, Nicole; Ewald, Florian

    2014-12-01

    Ibrutinib (formerly PCI-32765) is a specific, irreversible, and potent inhibitor of Burton's tyrosine kinase (BTK) developed for the treatment of several forms of blood cancer. It is now an FDA-approved drug marketed under the name Imbruvica(TM) (Pharmacyclics, Inc.) and successfully used as an orally administered second-line drug in the treatment of mantle cell lymphoma. Since BTK is predominantly expressed in hematopoietic cells, the sensitivity of solid tumor cells to Ibrutinib has not been analyzed. In this study, we determined the effect of Ibrutinib on breast cancer cells. We demonstrate that Ibrutinib efficiently reduces the phosphorylation of the receptor tyrosine kinases ErbB1, ErbB2 and ErbB3, thereby suppressing AKT and MAPK signaling in ErbB2-positive (ErbB2+) breast cancer cell lines. Treatment with Ibrutinib significantly reduced the viability of ErbB2+ cell lines with IC50 values at nanomolar concentrations, suggesting therapeutic potential of Ibrutinib in breast cancer. Combined treatment with Ibrutinib and the dual PI3K/mTOR inhibitor BEZ235 synergistically reduces cell viability of ErbB2+ breast cancer cells. Combination indices below 0.25 at 50% inhibition of cell viability were determined by the Chou-Talalay method. Therefore, the combination of Ibrutinib and canonical PI3K pathway inhibitors could be a new and effective approach in the treatment of breast cancer with activated ErbB receptors. Ibrutinib could thus become a valuable component of targeted therapy in aggressive ErbB2+ breast cancer.

  10. Impact of somatic PI3K pathway and ERBB family mutations on pathological complete response (pCR) in HER2-positive breast cancer patients who received neoadjuvant HER2-targeted therapies.

    LENUS (Irish Health Repository)

    Toomey, Sinead

    2017-07-27

    The Cancer Genome Atlas analysis revealed that somatic EGFR, receptor tyrosine-protein kinase erbB-2 (ERBB2), Erb-B2 receptor tyrosine kinase 3 (ERBB3) and Erb-B2 receptor tyrosine kinase 4 (ERBB4) gene mutations (ERBB family mutations) occur alone or co-occur with somatic mutations in the gene encoding the phosphatidylinositol 3-kinase (PI3K) catalytic subunit (PIK3CA) in 19% of human epidermal growth factor receptor 2 (HER2)-positive breast cancers. Because ERBB family mutations can activate the PI3K\\/AKT pathway and likely have similar canonical signalling effects to PI3K pathway mutations, we investigated their combined impact on response to neoadjuvant HER2-targeted therapies.

  11. ErbB-2 nuclear function in breast cancer growth, metastasis and resistance to therapy.

    Science.gov (United States)

    Elizalde, Patricia V; Cordo Russo, Rosalía I; Chervo, Maria F; Schillaci, Roxana

    2016-12-01

    Approximately 15-20% of breast cancers (BC) show either membrane overexpression of ErbB-2 (MErbB-2), a member of the ErbBs family of receptor tyrosine kinases, or ERBB2 gene amplification. Until the development of MErbB-2-targeted therapies, this BC subtype, called ErbB-2-positive, was associated with increased metastatic potential and poor prognosis. Although these therapies have significantly improved overall survival and cure rates, resistance to available drugs is still a major clinical issue. In its classical mechanism, MErbB-2 activates downstream signaling cascades, which transduce its effects in BC. The fact that ErbB-2 is also present in the nucleus of BC cells was discovered over twenty years ago. Also, compelling evidence revealed a non-canonical function of nuclear ErbB-2 as a transcriptional regulator. As a deeper understanding of nuclear ErbB-2 actions would be crucial to the disclosure of its role as a biomarker and a target of therapy in BC, we will here review its function in BC, in particular, its role in growth, metastatic spreading and response to currently available MErbB-2-positive BC therapies. © 2016 Society for Endocrinology.

  12. 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.

  13. Endothelial ErbB4 deficit induces alterations in exploratory behavior and brain energy metabolism in mice.

    Science.gov (United States)

    Wu, Gang; Liu, Xiu-Xiu; Lu, Nan-Nan; Liu, Qi-Bing; Tian, Yun; Ye, Wei-Feng; Jiang, Guo-Jun; Tao, Rong-Rong; Han, Feng; Lu, Ying-Mei

    2017-06-01

    The receptor tyrosine kinase ErbB4 is present throughout the primate brain and has a distinct functional profile. In this study, we investigate the potential role of endothelial ErbB4 receptor signaling in the brain. Here, we show that the endothelial cell-specific deletion of ErbB4 induces decreased exploratory behavior in adult mice. However, the water maze task for spatial memory and the memory reconsolidation test reveal no changes; additionally, we observe no impairment in CaMKII phosphorylation in Cdh5Cre;ErbB4 f/f mice, which indicates that the endothelial ErbB4 deficit leads to decreased exploratory activity rather than direct memory deficits. Furthermore, decreased brain metabolism, which was measured using micro-positron emission tomography, is observed in the Cdh5Cre;ErbB4 f/f mice. Consistently, the immunoblot data demonstrate the downregulation of brain Glut1, phospho-ULK1 (Ser555), and TIGAR in the endothelial ErbB4 conditional knockout mice. Collectively, our findings suggest that endothelial ErbB4 plays a critical role in regulating brain function, at least in part, through maintaining normal brain energy homeostasis. Targeting ErbB4 or the modulation of endothelial ErbB4 signaling may represent a rational pharmacological approach to treat neurological disorders. © 2017 John Wiley & Sons Ltd.

  14. Overload Control in a SIP Signaling Network

    OpenAIRE

    Masataka Ohta

    2007-01-01

    The Internet telephony employs a new type of Internet communication on which a mutual communication is realized by establishing sessions. Session Initiation Protocol (SIP) is used to establish sessions between end-users. For unreliable transmission (UDP), SIP message should be retransmitted when it is lost. The retransmissions increase a load of the SIP signaling network, and sometimes lead to performance degradation when a network is overloaded. The paper proposes an overload control for a S...

  15. 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......Reversible protein phosphorylation is involved in the regulation of most, if not all, major cellular processes via dynamic signal transduction pathways. During the last decade quantitative phosphoproteomics have evolved from a highly specialized area to a powerful and versatile platform...... and quantify thousands of phosphorylations, thus providing extensive overviews of the cellular signaling networks. As a result of these developments quantitative phosphoproteomics have been applied to study processes as diverse as immunology, stem cell biology and DNA damage. Here we review the developments...

  16. Activation of ErbB3, EGFR and Erk is essential for growth of human breast cancer cell lines with acquired resistance to fulvestrant

    DEFF Research Database (Denmark)

    Frogne, Thomas; Benjaminsen, Rikke; Sonne-Hansen, Katrine

    2008-01-01

    cell lines concomitant with inhibition of Erk and unaltered Akt activation. In concert, inhibition of Erk with U0126 preferentially reduced growth of resistant cell lines. Treatment with ErbB3 neutralizing antibodies inhibited ErbB3 activation and resulted in a modest but statistically significant...... activation was observed only in the parental MCF-7 cells. The downstream kinases pAkt and pErk were increased in five of seven and in all seven resistant cell lines, respectively. Treatment with the EGFR inhibitor gefitinib preferentially inhibited growth and reduced the S phase fraction in the resistant...... growth inhibition of two resistant cell lines. These data indicate that ligand activated ErbB3 and EGFR, and Erk signaling play important roles in fulvestrant resistant cell growth. Furthermore, the decreased level of ErbB4 in resistant cells may facilitate heterodimerization of ErbB3 with EGFR and ErbB2...

  17. A peptide antagonist of the ErbB1 receptor inhibits receptor activation, tumor cell growth and migration in vitro and xenograft tumor growth in vivo

    DEFF Research Database (Denmark)

    Xu, Ruodan; Povlsen, Gro Klitgaard; Soroka, Vladislav

    2010-01-01

    The epidermal growth factor family of receptor tyrosine kinases (ErbBs) plays essential roles in tumorigenesis and cancer disease progression, and therefore has become an attractive target for structure-based drug design. ErbB receptors are activated by ligand-induced homo- and heterodimerization...... constitutes part of the dimerization arm of ErbB3. Inherbin3 binds to the extracellular domains of all four ErbB receptors, with the lowest peptide binding affinity for ErbB4. Inherbin3 functions as an antagonist of epidermal growth factor (EGF)-ErbB1 signaling. We show that Inherbin3 inhibits EGF-induced Erb....... Structural studies have revealed that ErbB receptor dimers are stabilized by receptor-receptor interactions, primarily mediated by a region in the second extracellular domain, termed the "dimerization arm". The present study is the first biological characterization of a peptide, termed Inherbin3, which...

  18. Global Optimization for Transport Network Expansion and Signal Setting

    OpenAIRE

    Liu, Haoxiang; Wang, David Z. W.; Yue, Hao

    2015-01-01

    This paper proposes a model to address an urban transport planning problem involving combined network design and signal setting in a saturated network. Conventional transport planning models usually deal with the network design problem and signal setting problem separately. However, the fact that network capacity design and capacity allocation determined by network signal setting combine to govern the transport network performance requires the optimal transport planning to consider the two pr...

  19. Activation of MAPK overrides the termination of myelin growth and replaces Nrg1/ErbB3 signals during Schwann cell development and myelination

    NARCIS (Netherlands)

    M.E. Sheean (Maria); E. McShane (Erik); C. Cheret (Cyril); J. Walcher (Jan); T. Müller (Thomas); A. Wulf-Goldenberg (Annika); S. Hoelper (Soraya); A.N. Garratt (Alistair); M. Krüger (Markus); K. Rajewsky (Klaus); D.N. Meijer (Dies); W. Birchmeier (Walter); G.R. Lewin (Gary); M. Selbach (Matthias); C. Birchmeier (Carmen)

    2014-01-01

    textabstractMyelination depends on the synthesis of large amounts of myelin transcripts and proteins and is controlled by Nrg1/ErbB/Shp2 signaling. We developed a novel pulse labeling strategy based on stable isotope labeling with amino acids in cell culture (SILAC) to measure the dynamics of myelin

  20. Characterization of Radar Signals Using Neural Networks

    Science.gov (United States)

    1990-12-01

    e***e*e*eeeeeeeeeeeesseeeeeese*eee*e*e************s /* Function Name: load.input.ptterns Number: 4.1 /* Description: This function determines wether ...XSE.last.layer Number: 8.5 */ /* Description: The function determines wether to backpropate the *f /* parameter by the sigmoidal or linear update...Sigmoidal Function," Mathematics of Control, Signals and Systems, 2:303-314 (March 1989). 6. Dayhoff, Judith E. Neural Network Architectures. New York: Van

  1. Comprehensive Binary Interaction Mapping of SH2 Domains via Fluorescence Polarization Reveals Novel Functional Diversification of ErbB Receptors

    Science.gov (United States)

    Ciaccio, Mark F.; Chuu, Chih-pin; Jones, Richard B.

    2012-01-01

    First-generation interaction maps of Src homology 2 (SH2) domains with receptor tyrosine kinase (RTK) phosphosites have previously been generated using protein microarray (PM) technologies. Here, we developed a large-scale fluorescence polarization (FP) methodology that was able to characterize interactions between SH2 domains and ErbB receptor phosphosites with higher fidelity and sensitivity than was previously achieved with PMs. We used the FP assay to query the interaction of synthetic phosphopeptides corresponding to 89 ErbB receptor intracellular tyrosine sites against 93 human SH2 domains and 2 phosphotyrosine binding (PTB) domains. From 358,944 polarization measurements, the affinities for 1,405 unique biological interactions were determined, 83% of which are novel. In contrast to data from previous reports, our analyses suggested that ErbB2 was not more promiscuous than the other ErbB receptors. Our results showed that each receptor displays unique preferences in the affinity and location of recruited SH2 domains that may contribute to differences in downstream signaling potential. ErbB1 was enriched versus the other receptors for recruitment of domains from RAS GEFs whereas ErbB2 was enriched for recruitment of domains from tyrosine and phosphatidyl inositol phosphatases. ErbB3, the kinase inactive ErbB receptor family member, was predictably enriched for recruitment of domains from phosphatidyl inositol kinases and surprisingly, was enriched for recruitment of domains from tyrosine kinases, cytoskeletal regulatory proteins, and RHO GEFs but depleted for recruitment of domains from phosphatidyl inositol phosphatases. Many novel interactions were also observed with phosphopeptides corresponding to ErbB receptor tyrosines not previously reported to be phosphorylated by mass spectrometry, suggesting the existence of many biologically relevant RTK sites that may be phosphorylated but below the detection threshold of standard mass spectrometry procedures. This

  2. Comprehensive binary interaction mapping of SH2 domains via fluorescence polarization reveals novel functional diversification of ErbB receptors.

    Directory of Open Access Journals (Sweden)

    Ronald J Hause

    Full Text Available First-generation interaction maps of Src homology 2 (SH2 domains with receptor tyrosine kinase (RTK phosphosites have previously been generated using protein microarray (PM technologies. Here, we developed a large-scale fluorescence polarization (FP methodology that was able to characterize interactions between SH2 domains and ErbB receptor phosphosites with higher fidelity and sensitivity than was previously achieved with PMs. We used the FP assay to query the interaction of synthetic phosphopeptides corresponding to 89 ErbB receptor intracellular tyrosine sites against 93 human SH2 domains and 2 phosphotyrosine binding (PTB domains. From 358,944 polarization measurements, the affinities for 1,405 unique biological interactions were determined, 83% of which are novel. In contrast to data from previous reports, our analyses suggested that ErbB2 was not more promiscuous than the other ErbB receptors. Our results showed that each receptor displays unique preferences in the affinity and location of recruited SH2 domains that may contribute to differences in downstream signaling potential. ErbB1 was enriched versus the other receptors for recruitment of domains from RAS GEFs whereas ErbB2 was enriched for recruitment of domains from tyrosine and phosphatidyl inositol phosphatases. ErbB3, the kinase inactive ErbB receptor family member, was predictably enriched for recruitment of domains from phosphatidyl inositol kinases and surprisingly, was enriched for recruitment of domains from tyrosine kinases, cytoskeletal regulatory proteins, and RHO GEFs but depleted for recruitment of domains from phosphatidyl inositol phosphatases. Many novel interactions were also observed with phosphopeptides corresponding to ErbB receptor tyrosines not previously reported to be phosphorylated by mass spectrometry, suggesting the existence of many biologically relevant RTK sites that may be phosphorylated but below the detection threshold of standard mass spectrometry

  3. Inhibition of ErbB2 by receptor tyrosine kinase inhibitors causes myofibrillar structural damage without cell death in adult rat cardiomyocytes

    International Nuclear Information System (INIS)

    Pentassuglia, Laura; Graf, Michael; Lane, Heidi; Kuramochi, Yukio; Cote, Gregory; Timolati, Francesco; Sawyer, Douglas B.; Zuppinger, Christian; Suter, Thomas M.

    2009-01-01

    Inhibition of ErbB2 (HER2) with monoclonal antibodies, an effective therapy in some forms of breast cancer, is associated with cardiotoxicity, the pathophysiology of which is poorly understood. Recent data suggest, that dual inhibition of ErbB1 (EGFR) and ErbB2 signaling is more efficient in cancer therapy, however, cardiac safety of this therapeutic approach is unknown. We therefore tested an ErbB1-(CGP059326) and an ErbB1/ErbB2-(PKI166) tyrosine kinase inhibitor in an in-vitro system of adult rat ventricular cardiomyocytes and assessed their effects on 1. cell viability, 2. myofibrillar structure, 3. contractile function, and 4. MAPK- and Akt-signaling alone or in combination with Doxorubicin. Neither CGP nor PKI induced cardiomyocyte necrosis or apoptosis. PKI but not CGP caused myofibrillar structural damage that was additive to that induced by Doxorubicin at clinically relevant doses. These changes were associated with an inhibition of excitation-contraction coupling. PKI but not CGP decreased p-Erk1/2, suggesting a role for this MAP-kinase signaling pathway in the maintenance of myofibrils. These data indicate that the ErbB2 signaling pathway is critical for the maintenance of myofibrillar structure and function. Clinical studies using ErbB2-targeted inhibitors for the treatment of cancer should be designed to include careful monitoring for cardiac dysfunction.

  4. Pertuzumab Increases 17-AAG-Induced Degradation of ErbB2, and This Effect Is Further Increased by Combining Pertuzumab with Trastuzumab

    Science.gov (United States)

    Hughes, Juliana Bentes; Rødland, Marianne Skeie; Hasmann, Max; Madshus, Inger Helene; Stang, Espen

    2012-01-01

    ErbB2 is an important oncogenic protein involved in carcinogenesis of, among others, breast, gastric, and ovarian carcinoma. Over-expression of ErbB2 is found in almost 20% of breast cancers, and this results in proliferative and anti-apoptotic signalling. ErbB2 is therefore an important treatment target. Antibodies recognizing full-length ErbB2 are clinically established, and drugs targeting the ErbB2 stabilizing heat shock protein 90 (Hsp90) are under clinical evaluation. We have investigated effects of the ErbB2-binding antibodies trastuzumab and pertuzumab alone and in combination, as well as the effect of the antibodies in combination with the Hsp90 inhibitor 17-AAG. Our results confirm the notion that combination of different ErbB2-binding antibodies more efficiently down-regulates ErbB2 than does one antibody in isolation. Additionally, our data demonstrate that ErbB2 is most efficiently down-regulated upon incubation with anti-ErbB2 antibodies in combination with Hsp90 inhibitors. The combination of anti-ErbB2 antibodies, and especially the combination of antibodies with 17-AAG, did also increase the inhibition of Akt activation of either agent, which could suggest an anti-proliferative effect. In such case, combining these agents could be beneficial in treatment of tumors not responding to trastuzumab only. PMID:24281706

  5. Pertuzumab Increases 17-AAG-Induced Degradation of ErbB2, and This Effect Is Further Increased by Combining Pertuzumab with Trastuzumab

    Directory of Open Access Journals (Sweden)

    Juliana Bentes Hughes

    2012-06-01

    Full Text Available ErbB2 is an important oncogenic protein involved in carcinogenesis of, among others, breast, gastric, and ovarian carcinoma. Over-expression of ErbB2 is found in almost 20% of breast cancers, and this results in proliferative and anti-apoptotic signalling. ErbB2 is therefore an important treatment target. Antibodies recognizing full-length ErbB2 are clinically established, and drugs targeting the ErbB2 stabilizing heat shock protein 90 (Hsp90 are under clinical evaluation. We have investigated effects of the ErbB2-binding antibodies trastuzumab and pertuzumab alone and in combination, as well as the effect of the antibodies in combination with the Hsp90 inhibitor 17-AAG. Our results confirm the notion that combination of different ErbB2-binding antibodies more efficiently down-regulates ErbB2 than does one antibody in isolation. Additionally, our data demonstrate that ErbB2 is most efficiently down-regulated upon incubation with anti-ErbB2 antibodies in combination with Hsp90 inhibitors. The combination of anti-ErbB2 antibodies, and especially the combination of antibodies with 17-AAG, did also increase the inhibition of Akt activation of either agent, which could suggest an anti-proliferative effect. In such case, combining these agents could be beneficial in treatment of tumors not responding to trastuzumab only.

  6. Towards the emerging crosstalk: ERBB family and steroid hormones.

    Science.gov (United States)

    D'Uva, Gabriele; Lauriola, Mattia

    2016-02-01

    Growth factors acting through receptor tyrosine kinases (RTKs) of ERBB family, along with steroid hormones (SH) acting through nuclear receptors (NRs), are critical signalling mediators of cellular processes. Deregulations of ERBB and steroid hormone receptors are responsible for several diseases, including cancer, thus demonstrating the central role played by both systems. This review will summarize and shed light on an emerging crosstalk between these two important receptor families. How this mutual crosstalk is attained, such as through extensive genomic and non-genomic interactions, will be addressed. In light of recent studies, we will describe how steroid hormones are able to fine-tune ERBB feedback loops, thus impacting on cellular output and providing a new key for understanding the complexity of biological processes in physiological or pathological conditions. In our understanding, the interactions between steroid hormones and RTKs deserve further attention. A system biology approach and advanced technologies for the analysis of RTK-SH crosstalk could lead to major advancements in molecular medicine, providing the basis for new routes of pharmacological intervention in several diseases, including cancer. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Examining the protective role of ErbB2 modulation in human-induced pluripotent stem cell-derived cardiomyocytes.

    Science.gov (United States)

    Eldridge, Sandy; Guo, Liang; Mussio, Jodie; Furniss, Mike; Hamre, John; Davis, Myrtle

    2014-10-01

    Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are being used as an in vitro model system in cardiac biology and in drug discovery (e.g., cardiotoxicity testing). Qualification of these cells for use in mechanistic investigations will require detailed evaluations of cardiomyocyte signaling pathways and cellular responses. ErbB signaling and the ligand neuregulin play critical roles in survival and functional integrity of cardiac myocytes. As such, we sought to characterize the expression and activity of the ErbB family of receptors. Antibody microarray analysis performed on cell lysates derived from maturing hiPSC-CMs detected expression of ∼570 signaling proteins. EGFR/ErbB1, HER2/ErbB2, and ErbB4, but not ErbB3 receptors, of the epidermal growth factor receptor family were confirmed by Western blot. Activation of ErbB signaling by neuregulin-1β (NRG, a natural ligand for ErbB4) and its modulation by trastuzumab (a monoclonal anti-ErbB2 antibody) and lapatinib (a small molecule ErbB2 tyrosine kinase inhibitor) were evaluated through assessing phosphorylation of AKT and Erk1/2, two major downstream kinases of ErbB signaling, using nanofluidic proteomic immunoassay. Downregulation of ErbB2 expression by siRNA silencing attenuated NRG-induced AKT and Erk1/2 phosphorylation. Activation of ErbB signaling with NRG, or inhibition with trastuzumab, alleviated or aggravated doxorubicin-induced cardiomyocyte damage, respectively, as assessed by a real-time cellular impedance analysis and ATP measurement. Collectively, these results support the expanded use of hiPSC-CMs to examine mechanisms of cardiotoxicity and support the value of using these cells in early assessments of cardiotoxicity or efficacy. Published by Oxford University Press on behalf of Toxicological Sciences 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  8. Neratinib induces ErbB2 ubiquitylation and endocytic degradation via HSP90 dissociation in breast cancer cells.

    Science.gov (United States)

    Zhang, Yingqiu; Zhang, Jinrui; Liu, Congcong; Du, Sha; Feng, Lu; Luan, Xuelin; Zhang, Yayun; Shi, Yulin; Wang, Taishu; Wu, Yue; Cheng, Wei; Meng, Songshu; Li, Man; Liu, Han

    2016-11-28

    Receptor tyrosine kinase ErbB2/HER2 is frequently observed to be overexpressed in human cancers, leading to over activation of downstream signaling modules. HER2 positive is a major type of breast cancer for which ErbB2 targeting is already proving to be an effective therapeutic strategy. Apart from antibodies against ErbB2, the small molecule tyrosine kinase inhibitor lapatinib has had successful clinical outcomes, and other inhibitors such as neratinib are currently undergoing clinical investigations. In this study we report the effects of lapatinib and neratinib on the mRNA and protein levels of the ErbB2 receptor. We provide evidence that neratinib-induced down regulation of ErbB2 occurs through ubiquitin-mediated endocytic sorting and lysosomal degradation. At the mechanistic level, neratinib treatment leads to HSP90 release from ErbB2 and its subsequent ubiquitylation and endocytic degradation. Our findings provide novel insights into the mechanism of ErbB2 inhibition by neratinib. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  9. 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...

  10. Neural network-based sensor signal accelerator.

    Energy Technology Data Exchange (ETDEWEB)

    Vogt, M. C.

    2000-10-16

    A strategy has been developed to computationally accelerate the response time of a generic electronic sensor. The strategy can be deployed as an algorithm in a control system or as a physical interface (on an embedded microcontroller) between a slower responding external sensor and a higher-speed control system. Optional code implementations are available to adjust algorithm performance when computational capability is limited. In one option, the actual sensor signal can be sampled at the slower rate with adaptive linear neural networks predicting the sensor's future output and interpolating intermediate synthetic output values. In another option, a synchronized collection of predictors sequentially controls the corresponding synthetic output voltage. Error is adaptively corrected in both options. The core strategy has been demonstrated with automotive oxygen sensor data. A prototype interface device is under construction. The response speed increase afforded by this strategy could greatly offset the cost of developing a replacement sensor with a faster physical response time.

  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. ErbB Proteins as Molecular Target of Dietary Phytochemicals in Malignant Diseases

    Directory of Open Access Journals (Sweden)

    Alexandru Filippi

    2017-01-01

    Full Text Available ErbB proteins overexpression, in both normal and mutated forms, is associated with invasive forms of cancer prone to metastasis and with stronger antiapoptotic mechanisms and therefore more challenging to treat. Downstream effectors of ErbB receptors mediating these phenotypic traits include MAPK, STAT, and PI3K/AKT/mTOR pathways. Various phytochemical compounds were studied for their large number of biological effects including anticancer activity. Among these compounds, epigallocatechin-3-gallate (EGCG, the main catechin from green tea leaves, and curcumin, component of the curry powder, constituted the object of numerous studies. Both compounds were shown to act directly either on ErbB expression, or on their downstream signaling molecules. In this paper we aim to review the involvement of ErbB proteins in cancer as well as the biologic activity of EGCG and curcumin in ErbB expressing and overexpressing malignancies. The problems arising in the administration of the two compounds due to their reduced bioavailability when orally administered, as well as the progress made in this field, from using novel formulations to improved dosing regimens or improved synthetic analogs, are also discussed.

  13. CRISPR-assisted receptor deletion reveals distinct roles for ERBB2 and ERBB3 in skin keratinocytes.

    Science.gov (United States)

    Dahlhoff, Maik; Gaborit, Nadège; Bultmann, Sebastian; Leonhardt, Heinrich; Yarden, Yosef; Schneider, Marlon R

    2017-10-01

    While the epidermal growth factor receptor (EGFR) is an established regulator of skin development and homeostasis, the functions of the related tyrosine kinase receptors ERBB2 and ERBB3 in this tissue have only recently been examined. Previously reported, skin-specific deletion of each of these receptors in mice resulted in similar defects in keratinocyte proliferation and migration, resulting in impaired wound healing and tumorigenesis. Because both ERBB2 and ERBB3 are targets for treating an array of cancer types, it is important to examine the consequences of receptor inhibition in human keratinocytes. Here, we employed the CRISPR/Cas9 technology to generate HaCaT cells (an established human keratinocyte cell line) lacking ERBB2 or ERBB3. HaCaT clones lacking ERBB2 or ERBB3 showed comparable reductions in cell proliferation as assessed by BrdU staining. Apoptosis, in contrast, was reduced in ERBB3-deficient HaCaT cells only. Assessment of cell migration using a wound healing (scratch) assay showed that the closure of the wound gaps was completed by 48 h in mock and in ERBB3 knockout clones. In contrast, this process was considerably delayed in ERBB2 knockout clones, and a complete closure of the gap in the latter cells did not occur before 72 h. In conclusion, both ERBB2 and ERBB3 are essential for normal proliferation of skin keratinocytes, but in contrast to ERBB3, ERBB2 is essential for migration of human keratinocytes. These observations might bear significance to patient adverse effects of therapeutic agents targeting ERBB2 and ERBB3. © 2017 Federation of European Biochemical Societies.

  14. OCAM regulates embryonic spinal cord stem cell proliferation by modulating ErbB2 receptor.

    Directory of Open Access Journals (Sweden)

    Loïc Deleyrolle

    Full Text Available The proliferation and differentiation of neural stem cells are tightly controlled by intrinsic and extrinsic cues. Cell adhesion molecules are increasingly recognized as regulators of these processes. Here we report the expression of the olfactory cell adhesion molecule (OCAM/NCAM2/RNCAM during mouse spinal cord development and in neural stem cells cultured as neurospheres. OCAM is also weakly expressed in the dormant adult stem cell niche around the central canal and is overexpressed after spinal cord injury. Both transmembrane (TM and glycosylphosphatidylinositol (GPI-linked isoforms are present in neurospheres. Electron microscopy and internalisation experiments revealed a dynamic trafficking of OCAM between the membrane and intracellular compartments. After differentiation, OCAM remains in neurons and oligodendrocytes whereas no expression is detected in astrocytes. Using OCAM knockout (KO mice, we found that mutant spinal cord stem cells showed an increased proliferation and self-renewal rates although no effect on differentiation was observed. This effect was reversed by lentivirus-mediated re-introduction of OCAM. Mechanistically, we identified the ErbB2/Neu/HER2 protein as being implicated in the enhanced proliferation of mutant cells. ErbB2 protein expression and phosphorylation level were significantly increased in KO cells whereas no difference was observed at the mRNA level. Overexpression of ErbB2 in wild-type and mutant cells also increased their growth while reintroduction of OCAM in mutant cells reduced the level of phosphorylated ErbB2. These results indicate that OCAM exerts a posttranscriptional control on the ErbB2 signalling in spinal cord stem cells. This study adds further support for considering cell adhesion molecules as regulators of the ErbB signalling.

  15. 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.

  16. 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

  17. Dynamic ErbB4 Activity in Hippocampal-Prefrontal Synchrony and Top-Down Attention in Rodents.

    Science.gov (United States)

    Tan, Zhibing; Robinson, Heath L; Yin, Dong-Min; Liu, Yu; Liu, Fang; Wang, Hongsheng; Lin, Thiri W; Xing, Guanglin; Gan, Lin; Xiong, Wen-Cheng; Mei, Lin

    2018-04-18

    Top-down attention is crucial for meaningful behaviors and impaired in various mental disorders. However, its underpinning regulatory mechanisms are poorly understood. We demonstrate that the hippocampal-prefrontal synchrony associates with levels of top-down attention. Both attention and synchrony are reduced in mutant mice of ErbB4, a receptor of neuregulin-1. We used chemical genetic and optogenetic approaches to inactivate ErbB4 kinase and ErbB4+ interneurons, respectively, both of which reduce gamma-aminobutyric acid (GABA) activity. Such inhibitions in the hippocampus impair both hippocampal-prefrontal synchrony and top-down attention, whereas those in the prefrontal cortex alter attention, but not synchrony. These observations identify a role of ErbB4-dependent GABA activity in the hippocampus in synchronizing the hippocampal-prefrontal pathway and demonstrate that acute, dynamic ErbB4 signaling is required to command top-down attention. Because both neuregulin-1 and ErbB4 are susceptibility genes of schizophrenia and major depression, our study contributes to a better understanding of these disorders. VIDEO ABSTRACT. Copyright © 2018 Elsevier Inc. All rights reserved.

  18. A fuzzy neural network for sensor signal estimation

    International Nuclear Information System (INIS)

    Na, Man Gyun

    2000-01-01

    In this work, a fuzzy neural network is used to estimate the relevant sensor signal using other sensor signals. Noise components in input signals into the fuzzy neural network are removed through the wavelet denoising technique. Principal component analysis (PCA) is used to reduce the dimension of an input space without losing a significant amount of information. A lower dimensional input space will also usually reduce the time necessary to train a fuzzy-neural network. Also, the principal component analysis makes easy the selection of the input signals into the fuzzy neural network. The fuzzy neural network parameters are optimized by two learning methods. A genetic algorithm is used to optimize the antecedent parameters of the fuzzy neural network and a least-squares algorithm is used to solve the consequent parameters. The proposed algorithm was verified through the application to the pressurizer water level and the hot-leg flowrate measurements in pressurized water reactors

  19. 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.

  20. Dopamine D1 signaling organizes network dynamics underlying working memory.

    Science.gov (United States)

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

    2016-06-01

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

  1. 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.

  2. ERBB2 mutations associated with solid variant of high-grade invasive lobular breast carcinomas.

    Science.gov (United States)

    Deniziaut, Gabrielle; Tille, Jean Christophe; Bidard, François-Clément; Vacher, Sophie; Schnitzler, Anne; Chemlali, Walid; Trémoulet, Laurence; Fuhrmann, Laetitia; Cottu, Paul; Rouzier, Roman; Bièche, Ivan; Vincent-Salomon, Anne

    2016-11-08

    ERBB2 and ERBB3 somatic gain-of-function mutations, which may be targeted by anti-ERBB2 therapies, were reported by high-throughput sequencing studies in 1% and 2% of invasive breast cancers respectively. Our study aims to determine ERBB2 and ERBB3 mutations frequencies in grade 3 and/or ERBB2-positive invasive lobular breast carcinomas (ILC). All the 529 ILC surgically-excised registered at Institut Curie in the years 2005 to 2008 were reviewed. Thirty-nine grade 3 ERBB2-negative ILC and 16 ERBB2-positive ILC were retrieved and subjected to Sanger sequencing of the ERBB2 and ERBB3 activation mutation hotspots (ERBB2: exons 8, 17, 19, 20, 21; ERBB3: exons 3, 6, 7, 8). Among the 39 grade 3 ERBB2-negative ILC, six tumors were found to have at least one detectable ERBB2 activating mutation (incidence rate: 15%, 95%CI [4%-27%]). No ERBB2 mutation was found among the 16 ERBB2-positive ILC. No ERBB3 mutation was found in any of the 55 ILC. ERBB2 mutations were statistically associated with solid ILC features (p=0.01). Survival analyses showed no significant prognostic impact of ERBB2 mutations. Our study demonstrates that high grade ERBB2-negative ILC display a high frequency of ERBB2 mutations, and should be subjected to systematic genetic screening.

  3. ErbB2 Pathway Activation upon Smad4 Loss Promotes Lung Tumor Growth and Metastasis

    Directory of Open Access Journals (Sweden)

    Jian Liu

    2015-03-01

    Full Text Available Lung cancer remains the leading cause of cancer death. Genome sequencing of lung tumors from patients with squamous cell carcinoma has identified SMAD4 to be frequently mutated. Here, we use a mouse model to determine the molecular mechanisms by which Smad4 loss leads to lung cancer progression. Mice with ablation of Pten and Smad4 in airway epithelium develop metastatic adenosquamous tumors. Comparative transcriptomic and in vivo cistromic analyses determine that loss of PTEN and SMAD4 results in ELF3 and ErbB2 pathway activation due to decreased expression of ERRFI1, a negative regulator of ERBB2 in mouse and human cells. The combinatorial inhibition of ErbB2 and Akt signaling attenuate tumor progression and cell invasion, respectively. Expression profile analysis of human lung tumors substantiated the importance of the ErbB2/Akt/ELF3 signaling pathway as both a prognostic biomarker and a therapeutic drug target for treating lung cancer.

  4. ErbB2 Pathway Activation upon Smad4 Loss Promotes Lung Tumor Growth and Metastasis.

    Science.gov (United States)

    Liu, Jian; Cho, Sung-Nam; Akkanti, Bindu; Jin, Nili; Mao, Jianqiang; Long, Weiwen; Chen, Tenghui; Zhang, Yiqun; Tang, Ximing; Wistub, Ignacio I; Creighton, Chad J; Kheradmand, Farrah; DeMayo, Francesco J

    2015-03-03

    Lung cancer remains the leading cause of cancer death. Genome sequencing of lung tumors from patients with squamous cell carcinoma has identified SMAD4 to be frequently mutated. Here, we use a mouse model to determine the molecular mechanisms by which Smad4 loss leads to lung cancer progression. Mice with ablation of Pten and Smad4 in airway epithelium develop metastatic adenosquamous tumors. Comparative transcriptomic and in vivo cistromic analyses determine that loss of PTEN and SMAD4 results in ELF3 and ErbB2 pathway activation due to decreased expression of ERRFI1, a negative regulator of ERBB2 in mouse and human cells. The combinatorial inhibition of ErbB2 and Akt signaling attenuate tumor progression and cell invasion, respectively. Expression profile analysis of human lung tumors substantiated the importance of the ErbB2/Akt/ELF3 signaling pathway as both a prognostic biomarker and a therapeutic drug target for treating lung cancer. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  5. 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

  6. Clinical Significance of ErbB Receptor Family in Urothelial Carcinoma of the Bladder: A Systematic Review and Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Yuh-Shyan Tsai

    2012-01-01

    Full Text Available The prognostic importance of examining ErbB receptor family expression in human bladder cancer remains uncertain. Using published evidence, we examined the clinical value and the updated results of clinical trials targeting ErbB receptor family members. Twenty-seven articles from 65 references related to ErbB receptor expression assessment in bladder cancer were reviewed. The estimates included the association significance, hazard ratios, and 95% confidence intervals (CIs from actuarial curves and survival analyses. A meta-analysis was done on those reports using univariate log-rank tests or a Cox-regression model. The methods of analysis and study subjects chosen varied widely among studies. The overall risks of disease progression for patients with EGFR or ErbB2 overexpression were 4.5 (95% CI: 2.5–8.4 and 1.1 (95% CI: 0.6–1.9, and the risks of mortality were 3.0 (95% CI: 1.6–5.9 and 1.1 (95% CI: 1.0–1.2, respectively. However, the significance of coexpression patterns of the ErbB receptor family remains controversial. None of six clinical trials yielded convincing results for blockading ErbB receptor signaling in urothelial carcinoma. The results of this analysis suggest that assessing co-expression patterns of the ErbB family may provide better prognostic information for bladder cancer patients.

  7. Demystifying communication signal lost for network redundancy ...

    African Journals Online (AJOL)

    These studies report on the communication signal lost factors that were analyzed and supported by evidences on coverage analysis activities for Automatic Meter Reading (AMR) systems. We have categorized the influential signal lost factors into four core elements that were concluded based on our field measurement ...

  8. Analysis and logical modeling of biological signaling transduction networks

    Science.gov (United States)

    Sun, Zhongyao

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

  9. Synchronization transmission of laser pattern signal within uncertain switched network

    Science.gov (United States)

    Lü, Ling; Li, Chengren; Li, Gang; Sun, Ao; Yan, Zhe; Rong, Tingting; Gao, Yan

    2017-06-01

    We propose a new technology for synchronization transmission of laser pattern signal within uncertain network with controllable topology. In synchronization process, the connection of dynamic network can vary at all time according to different demands. Especially, we construct the Lyapunov function of network through designing a special semi-positive definite function, and the synchronization transmission of laser pattern signal within uncertain network with controllable topology can be realized perfectly, which effectively avoids the complicated calculation for solving the second largest eignvalue of the coupling matrix of the dynamic network in order to obtain the network synchronization condition. At the same time, the uncertain parameters in dynamic equations belonging to network nodes can also be identified accurately via designing the identification laws of uncertain parameters. In addition, there are not any limitations for the synchronization target of network in the new technology, in other words, the target can either be a state variable signal of an arbitrary node within the network or an exterior signal.

  10. Processing of seismic signals from a seismometer network

    International Nuclear Information System (INIS)

    Key, F.A.; Warburton, P.J.

    1983-08-01

    A description is given of the Seismometer Network Analysis Computer (SNAC) which processes short period data from a network of seismometers (UKNET). The nine stations of the network are distributed throughout the UK and their outputs are transmitted to a control laboratory (Blacknest) where SNAC monitors the data for seismic signals. The computer gives an estimate of the source location of the detected signals and stores the waveforms. The detection logic is designed to maintain high sensitivity without excessive ''false alarms''. It is demonstrated that the system is able to detect seismic signals at an amplitude level consistent with a network of single stations and, within the limitations of signal onset time measurements made by machine, can locate the source of the seismic disturbance. (author)

  11. 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

  12. ErbB2, but not ErbB1, reinitiates proliferation and induces luminal repopulation in epithelial acini

    Energy Technology Data Exchange (ETDEWEB)

    Muthuswamy, Senthil K; Li, Dongmei; Lelievre, Sophie; Bissell, Mina J; Brugge, Joan S

    2001-08-08

    Both ErbB1 and ErbB2 are overexpressed or amplified in breast tumors. To examine the effects of activating ErbB receptors in a context that mimics polarized epithelial cells in vivo, we activated ErbB1 and ErbB2 homodimers in preformed, growth-arrested mammary acini cultured in three-dimensional basement membrane gels. Activation of ErbB2, but not that of ErbB1, led to a reinitiation of cell proliferation and altered the properties of mammary acinar structures. These altered structures share several properties with early-stage tumors, including a loss of proliferative suppression, an absence of lumen, retention of the basement membrane and a lack of invasive properties. ErbB2 activation also disrupted tight junctions and the cell polarity of polarized epithelia, whereas ErbB1 activation did not have any effect. Our results indicate that ErbB receptors differ in their ability to induce early stages of mammary carcinogenesis in vitro and this three-dimensional model system can reveal biological activities of oncogenes that cannot be examined in vitro in standard transformation assays.

  13. 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

  14. All-optical signal processing for optical packet switching networks

    NARCIS (Netherlands)

    Liu, Y.; Hill, M.T.; Calabretta, N.; Tangdiongga, E.; Geldenhuys, R.; Zhang, S.; Li, Z.; Waardt, de H.; Khoe, G.D.; Dorren, H.J.S.; Iftekharuddin, K.M.; awwal, A.A.S.

    2005-01-01

    We discuss how all-optical signal processing might play a role in future all-optical packet switched networks. We introduce a concept of optical packet switches that employ entirely all-optical signal processing technology. The optical packet switch is made out of three functional blocks: the

  15. 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.

  16. 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...... this controls directional cell migration as a physiological response. The ciliary pocket is a membrane invagination with elevated activity of clathrin-dependent endocytosis (CDE). In paper I, we show that the primary cilium regulates TGF-β signaling and the ciliary pocket is a compartment for CDE...... on formation of the primary cilium and CDE at the pocket region. The ciliary protein Inversin functions as a molecular switch between canonical and non-canonical Wnt signaling. In paper II, we show that Inversin and the primary cilium control Wnt signaling and are required for polarization and cell migration...

  17. OPNET simulation Signaling System No.7 (SS7) network interfaces

    OpenAIRE

    Ow, Kong Chung.

    2000-01-01

    This thesis presents an OPNET model and simulation of the Signaling System No.7 (SS7) network, which is dubbed the world's largest data communications network. The main focus of the study is to model one of its levels, the Message Transfer Part Level 3, in accordance with the ITU.T recommendation Q.704. An overview of SS7 that includes the evolution and basics of SS7 architecture is provided to familarize the reader with the topic. This includes the protocol stack, signaling points, signaling...

  18. 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.

  19. 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.

  20. Signaling network of the Btk family kinases.

    Science.gov (United States)

    Qiu, Y; Kung, H J

    2000-11-20

    The Btk family kinases represent new members of non-receptor tyrosine kinases, which include Btk/Atk, Itk/Emt/Tsk, Bmx/Etk, and Tec. They are characterized by having four structural modules: PH (pleckstrin homology) domain, SH3 (Src homology 3) domain, SH2 (Src homology 2) domain and kinase (Src homology 1) domain. Increasing evidence suggests that, like Src-family kinases, Btk family kinases play central but diverse modulatory roles in various cellular processes. They participate in signal transduction in response to virtually all types of extracellular stimuli which are transmitted by growth factor receptors, cytokine receptors, G-protein coupled receptors, antigen-receptors and integrins. They are regulated by many non-receptor tyrosine kinases such as Src, Jak, Syk and FAK family kinases. In turn, they regulate many of major signaling pathways including those of PI3K, PLCgamma and PKC. Both genetic and biochemical approaches have been used to dissect the signaling pathways and elucidate their roles in growth, differentiation and apoptosis. An emerging new role of this family of kinases is cytoskeletal reorganization and cell motility. The physiological importance of these kinases was amply demonstrated by their link to the development of immunodeficiency diseases, due to germ-line mutations. The present article attempts to review the structure and functions of Btk family kinases by summarizing our current knowledge on the interacting partners associated with the different modules of the kinases and the diverse signaling pathways in which they are involved.

  1. 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......-wide characterization of signalling events at the levels of post-translational modifications, protein-protein interactions and changes in protein expression. This technology delivers accurate and unbiased information about the quantitative changes of thousands of proteins and their modifications in response to any...... perturbation. Current studies focus on phosphorylation, but acetylation, methylation, glycosylation and ubiquitylation are also becoming amenable to investigation. Large-scale proteomics-based signalling research will fundamentally change our understanding of signalling networks....

  2. Evolution of SH2 domains and phosphotyrosine signalling networks

    Science.gov (United States)

    Liu, Bernard A.; Nash, Piers D.

    2012-01-01

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

  3. The ectodomain of cadherin-11 binds to erbB2 and stimulates Akt phosphorylation to promote cranial neural crest cell migration.

    Directory of Open Access Journals (Sweden)

    Ketan Mathavan

    Full Text Available During development, a multi-potent group of cells known as the cranial neural crest (CNC migrate to form craniofacial structures. Proper migration of these cells requires proteolysis of cell adhesion molecules, such as cadherins. In Xenopus laevis, preventing extracellular cleavage of cadherin-11 impairs CNC migration. However, overexpression of the soluble cleavage product (EC1-3 is capable of rescuing this phenotype. The mechanism by which EC1-3 promotes CNC migration has not been investigated until now. Here we show that EC1-3 stimulates phosphorylation of Akt, a target of PI3K, in X.laevis CNC. Through immunoprecipitation experiments, we determined that EC1-3 interacts with all ErbB receptors, PDGFRα, and FGFR1. Of these receptors, only ErbB2 was able to produce an increase in Akt phosphorylation upon treatment with a recombinant EC1-3. This increase was abrogated by mubritinib, an inhibitor of ErbB2. We were able to recapitulate this decrease in Akt phosphorylation in vivo by knocking down ErbB2 in CNC cells. Knockdown of the receptor also significantly reduced CNC migration in vivo. We confirmed the importance of ErbB2 and ErbB receptor signaling in CNC migration using mubritinib and canertinib, respectively. Mubritinib and the PI3K inhibitor LY294002 significantly decreased cell migration while canertinib nearly prevented it altogether. These data show that ErbB2 and Akt are important for CNC migration and implicate other ErbB receptors and Akt-independent signaling pathways. Our findings provide the first example of a functional interaction between the extracellular domain of a type II classical cadherin and growth factor receptors.

  4. Network features and pathway analyses of a signal transduction cascade

    Directory of Open Access Journals (Sweden)

    Ryoji Yanashima

    2009-05-01

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

  5. Activation of EGFR and ERBB2 by Helicobacter pylori Results in Survival of Gastric Epithelial Cells with DNA Damage

    Science.gov (United States)

    Chaturvedi, Rupesh; Asim, Mohammad; Piazuelo, M. Blanca; Yan, Fang; Barry, Daniel P.; Sierra, Johanna Carolina; Delgado, Alberto G.; Hill, Salisha; Casero, Robert A.; Bravo, Luis E.; Dominguez, Ricardo L.; Correa, Pelayo; Polk, D. Brent; Washington, M. Kay; Rose, Kristie L.; Schey, Kevin L.; Morgan, Douglas R.; Peek, Richard M.; Wilson, Keith T.

    2014-01-01

    BACKGROUND & AIMS The gastric cancer-causing pathogen Helicobacter pylori upregulates spermine oxidase (SMOX) in gastric epithelial cells, causing oxidative stress-induced apoptosis and DNA damage. A subpopulation of SMOXhigh cells are resistant to apoptosis, despite their high levels of DNA damage. Because epidermal growth factor receptor (EGFR) activation can regulate apoptosis, we determined its role in SMOX-mediated effects. METHODS SMOX, apoptosis, and DNA damage were measured in gastric epithelial cells from H pylori-infected Egfrwa5 mice (which have attenuated EGFR activity), Egfr wild-type mice, or in infected cells incubated with EGFR inhibitors or deficient in EGFR. Phosphoproteomic analysis was performed. Two independent tissue microarrays containing each stage of disease, from gastritis to carcinoma, and gastric biopsies from Colombian and Honduran cohorts were analyzed by immunohistochemistry. RESULTS SMOX expression and DNA damage were decreased, and apoptosis increased in H pylori-infected Egfrwa5 mice. H pylori-infected cells with deletion or inhibition of EGFR had reduced levels of SMOX, DNA damage, and DNA damagehigh apoptosislow cells. Phosphoproteomic analysis revealed increased EGFR and ERBB2 signaling. Immunoblot analysis demonstrated the presence of a phosphorylated (p)EGFR–ERBB2 heterodimer and pERBB2; knockdown of ErbB2 facilitated apoptosis of DNA damagehigh apoptosislow cells. SMOX was increased in all stages of gastric disease, peaking in tissues with intestinal metaplasia, whereas pEGFR, pEGFR–ERBB2, and pERBB2 were increased predominantly in tissues demonstrating gastritis or atrophic gastritis. Principal component analysis separated gastritis tissues from patients with cancer vs those without cancer. pEGFR, pEGFR–ERBB2, pERBB2, and SMOX were increased in gastric samples from patients whose disease progressed to intestinal metaplasia or dysplasia, compared with patients whose disease did not progress. CONCLUSIONS In an analysis

  6. Human CD3+ T-Cells with the Anti-ERBB2 Chimeric Antigen Receptor Exhibit Efficient Targeting and Induce Apoptosis in ERBB2 Overexpressing Breast Cancer Cells

    Science.gov (United States)

    Munisvaradass, Rusheni; Kumar, Suresh; Govindasamy, Chandramohan; Alnumair, Khalid S.; Mok, Pooi Ling

    2017-01-01

    Breast cancer is a common malignancy among women. The innate and adaptive immune responses failed to be activated owing to immune modulation in the tumour microenvironment. Decades of scientific study links the overexpression of human epidermal growth factor receptor 2 (ERBB2) antigen with aggressive tumours. The Chimeric Antigen Receptor (CAR) coding for specific tumour-associated antigens could initiate intrinsic T-cell signalling, inducing T-cell activation, and cytotoxic activity without the need for major histocompatibility complex recognition. This renders CAR as a potentially universal immunotherapeutic option. Herein, we aimed to establish CAR in CD3+ T-cells, isolated from human peripheral blood mononucleated cells that could subsequently target and induce apoptosis in the ERBB2 overexpressing human breast cancer cell line, SKBR3. Constructed CAR was inserted into a lentiviral plasmid containing a green fluorescent protein tag and produced as lentiviral particles that were used to transduce activated T-cells. Transduced CAR-T cells were then primed with SKBR3 cells to evaluate their functionality. Results showed increased apoptosis in SKBR3 cells co-cultured with CAR-T cells compared to the control (non–transduced T-cells). This study demonstrates that CAR introduction helps overcome the innate limitations of native T-cells leading to cancer cell apoptosis. We recommend future studies should focus on in vivo cytotoxicity of CAR-T cells against ERBB2 expressing tumours. PMID:28885562

  7. 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...

  8. 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.

  9. 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.

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

    Science.gov (United States)

    Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang

    2017-01-01

    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.

  11. All-optical network coding for DPSK signals

    DEFF Research Database (Denmark)

    An, Yi; Da Ros, Francesco; Peucheret, Christophe

    2013-01-01

    All-optical network coding for path protection is experimentally demonstrated using four-wave mixing in SOAs for10 Gbit/s NRZ-DPSK signals with error free performance. The total power penalty after two cascaded XOR stage is only 2 dB.......All-optical network coding for path protection is experimentally demonstrated using four-wave mixing in SOAs for10 Gbit/s NRZ-DPSK signals with error free performance. The total power penalty after two cascaded XOR stage is only 2 dB....

  12. 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.

  13. 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.

  14. Trastuzumab Resistance: Role for Notch Signaling

    Directory of Open Access Journals (Sweden)

    Kinnari Mehta

    2009-01-01

    Full Text Available Epidermal growth factor receptor-2 (ErbB-2/HER2 is a potent breast oncogene that has been shown to be amplified in 20% of breast cancers. Overexpression of ErbB-2 predicts for aggressive tumor behavior, resistance to some cytotoxic and antihormonal therapies, and poor overall survival. Trastuzumab, the humanized, monoclonal antibody directed against ErbB-2 has shown tremendous efficacy and improved overall survival for women when combined with a taxane-based chemotherapy. However, resistance to trastuzumab remains a major concern, most notably in women with metastatic breast cancer. Numerous mechanisms that include overexpression of alternate receptor tyrosine kinases and/or loss of critical tumor suppressors have been proposed in the last several years to elucidate trastuzumab resistance. Here we review the many possible mechanisms of action that could contribute to resistance, and novel therapies to prevent or reverse the resistant phenotype. Moreover, we provide a critical role for Notch signaling cross-talk with overlapping or new signaling networks in trastuzumab-resistant breast.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. Exercise training and return to a well-balanced diet activate the neuregulin 1/ErbB pathway in skeletal muscle of obese rats

    Science.gov (United States)

    Ennequin, Gaël; Boisseau, Nathalie; Caillaud, Kevin; Chavanelle, Vivien; Gerbaix, Maude; Metz, Lore; Etienne, Monique; Walrand, Stéphane; Masgrau, Aurélie; Guillet, Christelle; Courteix, Daniel; Niu, Airu; Li, Yi-Ping; Capel, Fréderic; Sirvent, Pascal

    2015-01-01

    Some studies suggest that the signalling pathway of neuregulin 1 (NRG1), a protein involved in the regulation of skeletal muscle metabolism, could be altered by nutritional and exercise interventions. We hypothesized that diet-induced obesity could lead to alterations of the NRG1 signalling pathway and that chronic exercise could improve NRG1 signalling in rat skeletal muscle. To test this hypothesis, male Wistar rats received a high fat/high sucrose (HF/HS) diet for 16 weeks. At the end of this period, NRG1 and ErbB expression/activity in skeletal muscle was assessed. The obese rats then continued the HF/HS diet or were switched to a well-balanced diet. Moreover, in both groups, half of the animals also performed low intensity treadmill exercise training. After another 8 weeks, NRG1 and ErbB expression/activity in skeletal muscle were tested again. The 16 week HF/HS diet induced obesity, but did not significantly affect the NRG1/ErbB signalling pathway in rat skeletal muscle. Conversely, after the switch to a well-balanced diet, NRG1 cleavage ratio and ErbB4 amount were increased. Chronic exercise training also promoted NRG1 cleavage, resulting in increased ErbB4 phosphorylation. This result was associated with increased protein expression and phosphorylation ratio of the metalloprotease ADAM17, which is involved in NRG1 shedding. Similarly, in vitro stretch-induced activation of ADAM17 in rat myoblasts induced NRG1 cleavage and ErbB4 activation. These results show that low intensity endurance training and well-balanced diet activate the NRG1-ErbB4 pathway, possibly via the metalloprotease ADAM17, in skeletal muscle of diet-induced obese rats. PMID:25820551

  1. 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).

  2. Subsurface Event Detection and Classification Using Wireless Signal Networks

    Directory of Open Access Journals (Sweden)

    Muhannad T. Suleiman

    2012-11-01

    Full Text Available 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.

  3. 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

    2012-11-05

    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.

  4. Variability of signal-to-noise ratio and the network analysis of gravitational wave burst signals

    International Nuclear Information System (INIS)

    Mohanty, S D; Rakhmanov, M; Klimenko, S; Mitselmakher, G

    2006-01-01

    The detection and estimation of gravitational wave burst signals, with a priori unknown polarization waveforms, requires the use of data from a network of detectors. Maximizing the network likelihood functional over all waveforms and sky positions yields point estimates for them as well as a detection statistic. However, the transformation from the data to estimates can become ill-conditioned over parts of the sky, resulting in significant errors in estimation. We modify the likelihood procedure by introducing a penalty functional which suppresses candidate solutions that display large signal-to-noise ratio (SNR) variability as the source is displaced on the sky. Simulations show that the resulting network analysis method performs significantly better in estimating the sky position of a source. Further, this method can be applied to any network, irrespective of the number or mutual alignment of detectors

  5. 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.

  6. 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.

  7. Biophysical constraints on the computational capacity of biochemical signaling networks

    Science.gov (United States)

    Wang, Ching-Hao; Mehta, Pankaj

    Biophysics fundamentally constrains the computations that cells can carry out. Here, we derive fundamental bounds on the computational capacity of biochemical signaling networks that utilize post-translational modifications (e.g. phosphorylation). To do so, we combine ideas from the statistical physics of disordered systems and the observation by Tony Pawson and others that the biochemistry underlying protein-protein interaction networks is combinatorial and modular. Our results indicate that the computational capacity of signaling networks is severely limited by the energetics of binding and the need to achieve specificity. We relate our results to one of the theoretical pillars of statistical learning theory, Cover's theorem, which places bounds on the computational capacity of perceptrons. PM and CHW were supported by a Simons Investigator in the Mathematical Modeling of Living Systems Grant, and NIH Grant No. 1R35GM119461 (both to PM).

  8. Traffic analysis and signal processing in optical packet switched networks

    DEFF Research Database (Denmark)

    Fjelde, Tina

    2002-01-01

    /s optical packet switched network exploiting the best of optics and electronics, is used as a thread throughout the thesis. An overview of the DAVID network architecture is given, focussing on the MAN and WAN architecture as well as the MPLS-based network hierarchy. Subsequently, the traffic performance...... of the DAVID core optical packet router, which exploits wavelength conversion and fibre delay-line buffers for contention resolution, is analysed using a numerical model developed for that purpose. The robustness of the shared recirculating loop buffer with respect to´bursty traffic is demonstrated...... the injection of an additional clock signal into the IWC is presented. Results show very good transmission capabilities combined with a high-speed response. It is argued that signal regeneration is an inherent attribute of the IWC employed as a wavelength converter due to the sinusoidal transfer function...

  9. 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)

  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. 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

  12. Signal Transduction Pathways of TNAP: Molecular Network Analyses.

    Science.gov (United States)

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

    2015-01-01

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

  13. Load-induced modulation of signal transduction networks.

    Science.gov (United States)

    Jiang, Peng; Ventura, Alejandra C; Sontag, Eduardo D; Merajver, Sofia D; Ninfa, Alexander J; Del Vecchio, Domitilla

    2011-10-11

    Biological signal transduction networks are commonly viewed as circuits that pass along information--in the process amplifying signals, enhancing sensitivity, or performing other signal-processing tasks--to transcriptional and other components. Here, we report on a "reverse-causality" phenomenon, which we call load-induced modulation. Through a combination of analytical and experimental tools, we discovered that signaling was modulated, in a surprising way, by downstream targets that receive the signal and, in doing so, apply what in physics is called a load. Specifically, we found that non-intuitive changes in response dynamics occurred for a covalent modification cycle when load was present. Loading altered the response time of a system, depending on whether the activity of one of the enzymes was maximal and the other was operating at its minimal rate or whether both enzymes were operating at submaximal rates. These two conditions, which we call "limit regime" and "intermediate regime," were associated with increased or decreased response times, respectively. The bandwidth, the range of frequency in which the system can process information, decreased in the presence of load, suggesting that downstream targets participate in establishing a balance between noise-filtering capabilities and a circuit's ability to process high-frequency stimulation. Nodes in a signaling network are not independent relay devices, but rather are modulated by their downstream targets.

  14. 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

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

    Directory of Open Access Journals (Sweden)

    Kumari Sonal Choudhary

    2016-06-01

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

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

    Science.gov (United States)

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

    2016-06-01

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

  17. 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

  18. Collective signaling behavior in a networked-oscillator model

    Science.gov (United States)

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

    2007-09-01

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

  19. 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

  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. 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.

  2. 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.

  3. A switchable spin-wave signal splitter for magnonic networks

    Science.gov (United States)

    Heussner, F.; Serga, A. A.; Brächer, T.; Hillebrands, B.; Pirro, P.

    2017-09-01

    The influence of an inhomogeneous magnetization distribution on the propagation of caustic-like spin-wave beams in unpatterned magnetic films has been investigated by utilizing micromagnetic simulations. Our study reveals a locally controllable and reconfigurable tractability of the beam directions. This feature is used to design a device combining split and switch functionalities for spin-wave signals on the micrometer scale. A coherent transmission of spin-wave signals through the device is verified. This attests the applicability in magnonic networks where the information is encoded in the phase of the spin waves.

  4. 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...

  5. 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

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

    Directory of Open Access Journals (Sweden)

    Zhi Zheng

    2012-01-01

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

  7. 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.

  8. CBL-CIPK network for calcium signaling in higher plants

    Science.gov (United States)

    Luan, Sheng

    Plants sense their environment by signaling mechanisms involving calcium. Calcium signals are encoded by a complex set of parameters and decoded by a large number of proteins including the more recently discovered CBL-CIPK network. The calcium-binding CBL proteins specifi-cally interact with a family of protein kinases CIPKs and regulate the activity and subcellular localization of these kinases, leading to the modification of kinase substrates. This represents a paradigm shift as compared to a calcium signaling mechanism from yeast and animals. One example of CBL-CIPK signaling pathways is the low-potassium response of Arabidopsis roots. When grown in low-K medium, plants develop stronger K-uptake capacity adapting to the low-K condition. Recent studies show that the increased K-uptake is caused by activation of a specific K-channel by the CBL-CIPK network. A working model for this regulatory pathway will be discussed in the context of calcium coding and decoding processes.

  9. Nonreciprocal signal routing in an active quantum network

    Science.gov (United States)

    Metelmann, A.; Türeci, H. E.

    2018-04-01

    As superconductor quantum technologies are moving towards large-scale integrated circuits, a robust and flexible approach to routing photons at the quantum level becomes a critical problem. Active circuits, which contain parametrically driven elements selectively embedded in the circuit, offer a viable solution. Here, we present a general strategy for routing nonreciprocally quantum signals between two sites of a given lattice of oscillators, implementable with existing superconducting circuit components. Our approach makes use of a dual lattice of overdamped oscillators linking the nodes of the main lattice. Solutions for spatially selective driving of the lattice elements can be found, which optimally balance coherent and dissipative hopping of microwave photons to nonreciprocally route signals between two given nodes. In certain lattices these optimal solutions are obtained at the exceptional point of the dynamical matrix of the network. We also demonstrate that signal and noise transmission characteristics can be separately optimized.

  10. 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.

  11. A peptide antagonist of ErbB receptors, Inherbin3, induces neurite outgrowth from rat cerebellar granule neurons through ErbB1 inhibition

    DEFF Research Database (Denmark)

    Xu, Ruodan; Pankratova, Stanislava; Christiansen, Søren Hofman

    2013-01-01

    ErbB receptors not only function in cancer, but are also key developmental regulators in the nervous system. We previously identified an ErbB1 peptide antagonist, Inherbin3, that is capable of inhibiting tumor growth in vitro and in vivo. In this study, we found that inhibition of ErbB1 kinase ac...

  12. The role of ERBB2 gene polymorphisms in leprosy susceptibility

    Directory of Open Access Journals (Sweden)

    Jamile Leão Rêgo

    2015-03-01

    Full Text Available Mycobacterium leprae infects skin and peripheral nerves causing deformities and disability. The M. leprae bacterium binds to ErbB2 on the Schwann cell surface causing demyelination and favoring spread of the bacilli and causing nerve injury. Polymorphisms at the ERBB2 gene were previously investigated as genetic risk factors for leprosy in two Brazilian populations but with inconsistent results. Herein we extend the analysis of ERBB2 variants to a third geographically distinct population in Brazil. Our results show that there is no association between the genotyped SNPs and the disease (p > 0.05 in this population. A gene set or pathway analysis under the genomic region of ERBB2 will be necessary to clarify its regulation under M. leprae stimulus.

  13. Potential upstream regulators of cannabinoid receptor 1 signaling in prostate cancer: a Bayesian network analysis of data from a tissue microarray.

    Science.gov (United States)

    Häggström, Jenny; Cipriano, Mariateresa; Forshell, Linus Plym; Persson, Emma; Hammarsten, Peter; Stella, Nephi; Fowler, Christopher J

    2014-08-01

    The endocannabinoid system regulates cancer cell proliferation, and in prostate cancer a high cannabinoid CB1 receptor expression is associated with a poor prognosis. Down-stream mediators of CB1 receptor signaling in prostate cancer are known, but information on potential upstream regulators is lacking. Data from a well-characterized tumor tissue microarray were used for a Bayesian network analysis using the max-min hill-climbing method. In non-malignant tissue samples, a directionality of pEGFR (the phosphorylated form of the epidermal growth factor receptor) → CB1 receptors were found regardless as to whether the endocannabinoid metabolizing enzyme fatty acid amide hydrolase (FAAH) was included as a parameter. A similar result was found in the tumor tissue, but only when FAAH was included in the analysis. A second regulatory pathway, from the growth factor receptor ErbB2 → FAAH was also identified in the tumor samples. Transfection of AT1 prostate cancer cells with CB1 receptors induced a sensitivity to the growth-inhibiting effects of the CB receptor agonist CP55,940. The sensitivity was not dependent upon the level of receptor expression. Thus a high CB1 receptor expression alone does not drive the cells towards a survival phenotype in the presence of a CB receptor agonist. The data identify two potential regulators of the endocannabinoid system in prostate cancer and allow the construction of a model of a dysregulated endocannabinoid signaling network in this tumor. Further studies should be designed to test the veracity of the predictions of the network analysis in prostate cancer and other solid tumors. © 2014 The Authors. The Prostate published by Wiley Periodicals, Inc.

  14. 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.

  15. 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.

  16. Signalling design and architecture for a proposed mobile satellite network

    Science.gov (United States)

    Yan, T.-Y.; Cheng, U.; Wang, C.

    1990-01-01

    In a frequency-division/demand-assigned multiple-access (FD/DAMA) architecture, each mobile subscriber must make a connection request to the Network Management Center before transmission for either open-end or closed-end services. Open-end services are for voice calls and long file transfer and are processed on a blocked-call-cleared basis. Closed-end services are for transmitting burst data and are processed on a first-come first-served basis. This paper presents the signalling design and architecture for non-voice services of an FD/DAMA mobile satellite network. The connection requests are made through the recently proposed multiple channel collision resolution scheme which provides a significantly higher throughput than the traditional slotted ALOHA scheme. For non-voice services, it is well known that retransmissions are necessary to ensure the delivery of a message in its entirety from the source to destination. Retransmission protocols for open-end and closed-end data transfer are investigated. The signal structure for the proposed network is derived from X-25 standards with appropriate modifications. The packet types and their usages are described in this paper.

  17. Duplicate retention in signalling proteins and constraints from network dynamics.

    Science.gov (United States)

    Soyer, O S; Creevey, C J

    2010-11-01

    Duplications are a major driving force behind evolution. Most duplicates are believed to fix through genetic drift, but it is not clear whether this process affects all duplications equally or whether there are certain gene families that are expected to show neutral expansions under certain circumstances. Here, we analyse the neutrality of duplications in different functional classes of signalling proteins based on their effects on response dynamics. We find that duplications involving intermediary proteins in a signalling network are neutral more often than those involving receptors. Although the fraction of neutral duplications in all functional classes increase with decreasing population size and selective pressure on dynamics, this effect is most pronounced for receptors, indicating a possible expansion of receptors in species with small population size. In line with such an expectation, we found a statistically significant increase in the number of receptors as a fraction of genome size in eukaryotes compared with prokaryotes. Although not confirmative, these results indicate that neutral processes can be a significant factor in shaping signalling networks and affect proteins from different functional classes differently. © 2010 The Authors. Journal Compilation © 2010 European Society For Evolutionary Biology.

  18. 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.

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

    KAUST Repository

    Kuwahara, Hiroyuki; Gao, Xin

    2013-01-01

    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

  20. Perturbation Biology: Inferring Signaling Networks in Cellular Systems

    Science.gov (United States)

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

    2013-01-01

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

  1. Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle

    Directory of Open Access Journals (Sweden)

    Ram Prahlad T

    2008-08-01

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

  2. Cancer signaling networks and their implications for personalized medicine

    DEFF Research Database (Denmark)

    Creixell, Pau

    Amongst the unique features of cancer cells perhaps the most crucial one is the change in the cellular decision-making process. While both non-cancer and cancer cells are constantly integrating different external cues that reach them and computing cellular decisions (e.g. proliferation or apoptosis......) based on the integration of these cues; this integration and consequently the cellular decisions taken by cancer cells are arguably very distinct from the decisions that would be expected from non-cancer cells. Since cellular signaling networks and its different states are the computational circuits...

  3. 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.

  4. Exercise training and return to a well-balanced diet activate the neuregulin 1/ErbB pathway in skeletal muscle of obese rats.

    Science.gov (United States)

    Ennequin, Gaël; Boisseau, Nathalie; Caillaud, Kevin; Chavanelle, Vivien; Gerbaix, Maude; Metz, Lore; Etienne, Monique; Walrand, Stéphane; Masgrau, Aurélie; Guillet, Christelle; Courteix, Daniel; Niu, Airu; Li, Yi-Ping; Capel, Fréderic; Sirvent, Pascal

    2015-06-15

    Some studies suggest that neuregulin 1 (NRG1) could be involved in the regulation of skeletal muscle energy metabolism in rodents. Here we assessed whether unbalanced diet is associated with alterations of the NRG1 signalling pathway and whether exercise and diet might restore NRG1 signalling in skeletal muscle of obese rats. We show that diet-induced obesity does not impair NRG1 signalling in rat skeletal muscle. We also report that endurance training and a well-balanced diet activate the NRG1 signalling in skeletal muscle of obese rats, possibly via a new mechanism mediated by the protease ADAM17. These results suggest that some beneficial effects of physical activity and diet in obese rats could be partly explained by stimulation of the NRG1 signalling pathway. Some studies suggest that the signalling pathway of neuregulin 1 (NRG1), a protein involved in the regulation of skeletal muscle metabolism, could be altered by nutritional and exercise interventions. We hypothesized that diet-induced obesity could lead to alterations of the NRG1 signalling pathway and that chronic exercise could improve NRG1 signalling in rat skeletal muscle. To test this hypothesis, male Wistar rats received a high fat/high sucrose (HF/HS) diet for 16 weeks. At the end of this period, NRG1 and ErbB expression/activity in skeletal muscle was assessed. The obese rats then continued the HF/HS diet or were switched to a well-balanced diet. Moreover, in both groups, half of the animals also performed low intensity treadmill exercise training. After another 8 weeks, NRG1 and ErbB expression/activity in skeletal muscle were tested again. The 16 week HF/HS diet induced obesity, but did not significantly affect the NRG1/ErbB signalling pathway in rat skeletal muscle. Conversely, after the switch to a well-balanced diet, NRG1 cleavage ratio and ErbB4 amount were increased. Chronic exercise training also promoted NRG1 cleavage, resulting in increased ErbB4 phosphorylation. This result was

  5. 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.

  6. 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.

  7. ErbB2 regulates NHEJ repair pathway by affecting erbB1-triggered IR-induced Akt activity

    International Nuclear Information System (INIS)

    Toulany, Mahmoud; Peter Rodemann, H.

    2009-01-01

    We have already reported that erbBl-PI3K-AKT signaling is an important pathway in regulating radiation sensitivity and DNA double strand break repair of human tumor cells. In the present study using small interfering RNA and pharmacological inhibitors in non-small cell lung cancer cell lines we investigated the role of Aktl on radiation-induced DNA-PKcs activity and DNA-double strand break (DNA-DSB) repair. Likewise, the function of erbB2 as hetrodimerization partner of erbBl in radiation-induced Akt activity and regulation of DNA-dsb repair through DNA-PKcs was evaluated. In A549 and H460 transfected with AKTl-siRNA radiation-induced phosphorylation of DNA-PKcs the key enzyme regulating NHEJ repair pathway was markedly inhibited. In both cell lines downregulation of Aktl led to a significant enhancement of residual DNA-DSB, i.e. impaired DNA-DSB repair. Interestingly, in cells transfected with DNA-PKcs-siRNA a lack of effect of AKTl-siRNA on enhancement of residual DNA-DSBs was observed. This results indicate that Aktl regulates NHEJ repair in a DNA-PKcs dependent manner

  8. A moderate elevation of circulating levels of IGF-I does not alter ErbB2 induced mammary tumorigenesis

    International Nuclear Information System (INIS)

    Dearth, Robert K; Kuiatse, Isere; Wang, Yu-Fen; Liao, Lan; Hilsenbeck, Susan G; Brown, Powel H; Xu, Jianming; Lee, Adrian V

    2011-01-01

    Epidemiological evidence suggests that moderately elevated levels of circulating insulin-like growth factor-I (IGF-I) are associated with increased risk of breast cancer in women. How circulating IGF-I may promote breast cancer incidence is unknown, however, increased IGF-I signaling is linked to trastuzumab resistance in ErbB2 positive breast cancer. Few models have directly examined the effect of moderately high levels of circulating IGF-I on breast cancer initiation and progression. The purpose of this study was to assess the ability of circulating IGF-I to independently initiate mammary tumorigenesis and/or accelerate the progression of ErbB2 mediated mammary tumor growth. We crossed heterozygous TTR-IGF-I mice with heterozygous MMTV-ErbB2 mice to generate 4 different genotypes: TTR-IGF-I/MMTV-ErbB2 (bigenic), TTR-IGF-I only, MMTV-ErbB2 only, and wild type (wt). Virgin females were palpated twice a week and harvested when tumors reached 1000 mm 3 . For study of normal development, blood and tissue were harvested at 4, 6 and 9 weeks of age in TTR-IGF-I and wt mice. TTR-IGF-I and TTR-IGF-I/ErbB2 bigenic mice showed a moderate 35% increase in circulating total IGF-I compared to ErbB2 and wt control mice. Elevation of circulating IGF-I had no effect upon pubertal mammary gland development. The transgenic increase in IGF-I alone wasn't sufficient to initiate mammary tumorigenesis. Elevated circulating IGF-I had no effect upon ErbB2-induced mammary tumorigenesis or metastasis, with median time to tumor formation being 30 wks and 33 wks in TTR-IGF-I/ErbB2 bigenic and ErbB2 mice respectively (p = 0.65). Levels of IGF-I in lysates from ErbB2/TTR-IGF-I tumors compared to ErbB2 was elevated in a similar manner to the circulating IGF-I, however, there was no effect on the rate of tumor growth (p = 0.23). There were no morphological differences in tumor type (solid adenocarcinomas) between bigenic and ErbB2 mammary glands. Using the first transgenic animal model to

  9. 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

  10. Effects of topologies on signal propagation in feedforward networks

    Science.gov (United States)

    Zhao, Jia; Qin, Ying-Mei; Che, Yan-Qiu

    2018-01-01

    We systematically investigate the effects of topologies on signal propagation in feedforward networks (FFNs) based on the FitzHugh-Nagumo neuron model. FFNs with different topological structures are constructed with same number of both in-degrees and out-degrees in each layer and given the same input signal. The propagation of firing patterns and firing rates are found to be affected by the distribution of neuron connections in the FFNs. Synchronous firing patterns emerge in the later layers of FFNs with identical, uniform, and exponential degree distributions, but the number of synchronous spike trains in the output layers of the three topologies obviously differs from one another. The firing rates in the output layers of the three FFNs can be ordered from high to low according to their topological structures as exponential, uniform, and identical distributions, respectively. Interestingly, the sequence of spiking regularity in the output layers of the three FFNs is consistent with the firing rates, but their firing synchronization is in the opposite order. In summary, the node degree is an important factor that can dramatically influence the neuronal network activity.

  11. Analysing 21cm signal with artificial neural network

    Science.gov (United States)

    Shimabukuro, Hayato; a Semelin, Benoit

    2018-05-01

    The 21cm signal at epoch of reionization (EoR) should be observed within next decade. We expect that cosmic 21cm signal at the EoR provides us both cosmological and astrophysical information. In order to extract fruitful information from observation data, we need to develop inversion method. For such a method, we introduce artificial neural network (ANN) which is one of the machine learning techniques. We apply the ANN to inversion problem to constrain astrophysical parameters from 21cm power spectrum. We train the architecture of the neural network with 70 training datasets and apply it to 54 test datasets with different value of parameters. We find that the quality of the parameter reconstruction depends on the sensitivity of the power spectrum to the different parameter sets at a given redshift and also find that the accuracy of reconstruction is improved by increasing the number of given redshifts. We conclude that the ANN is viable inversion method whose main strength is that they require a sparse extrapolation of the parameter space and thus should be usable with full simulation.

  12. Automated embolic signal detection using Deep Convolutional Neural Network.

    Science.gov (United States)

    Sombune, Praotasna; Phienphanich, Phongphan; Phuechpanpaisal, Sutanya; Muengtaweepongsa, Sombat; Ruamthanthong, Anuchit; Tantibundhit, Charturong

    2017-07-01

    This work investigated the potential of Deep Neural Network in detection of cerebral embolic signal (ES) from transcranial Doppler ultrasound (TCD). The resulting system is aimed to couple with TCD devices in diagnosing a risk of stroke in real-time with high accuracy. The Adaptive Gain Control (AGC) approach developed in our previous study is employed to capture suspected ESs in real-time. By using spectrograms of the same TCD signal dataset as that of our previous work as inputs and the same experimental setup, Deep Convolutional Neural Network (CNN), which can learn features while training, was investigated for its ability to bypass the traditional handcrafted feature extraction and selection process. Extracted feature vectors from the suspected ESs are later determined whether they are of an ES, artifact (AF) or normal (NR) interval. The effectiveness of the developed system was evaluated over 19 subjects going under procedures generating emboli. The CNN-based system could achieve in average of 83.0% sensitivity, 80.1% specificity, and 81.4% accuracy, with considerably much less time consumption in development. The certainly growing set of training samples and computational resources will contribute to high performance. Besides having potential use in various clinical ES monitoring settings, continuation of this promising study will benefit developments of wearable applications by leveraging learnable features to serve demographic differentials.

  13. 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.

  14. Contribution of EGFR and ErbB-3 Heterodimerization to the EGFR Mutation-Induced Gefitinib- and Erlotinib-Resistance in Non-Small-Cell Lung Carcinoma Treatments.

    Directory of Open Access Journals (Sweden)

    Debby D Wang

    Full Text Available EGFR mutation-induced drug resistance has become a major threat to the treatment of non-small-cell lung carcinoma. Essentially, the resistance mechanism involves modifications of the intracellular signaling pathways. In our work, we separately investigated the EGFR and ErbB-3 heterodimerization, regarded as the origin of intracellular signaling pathways. On one hand, we combined the molecular interaction in EGFR heterodimerization with that between the EGFR tyrosine kinase and its inhibitor. For 168 clinical subjects, we characterized their corresponding EGFR mutations using molecular interactions, with three potential dimerization partners (ErbB-2, IGF-1R and c-Met of EGFR and two of its small molecule inhibitors (gefitinib and erlotinib. Based on molecular dynamics simulations and structural analysis, we modeled these mutant-partner or mutant-inhibitor interactions using binding free energy and its components. As a consequence, the mutant-partner interactions are amplified for mutants L858R and L858R_T790M, compared to the wild type EGFR. Mutant delL747_P753insS represents the largest difference between the mutant-IGF-1R interaction and the mutant-inhibitor interaction, which explains the shorter progression-free survival of an inhibitor to this mutant type. Besides, feature sets including different energy components were constructed, and efficient regression trees were applied to map these features to the progression-free survival of an inhibitor. On the other hand, we comparably examined the interactions between ErbB-3 and its partners (EGFR mutants, IGF-1R, ErbB-2 and c-Met. Compared to others, c-Met shows a remarkably-strong binding with ErbB-3, implying its significant role in regulating ErbB-3 signaling. Moreover, EGFR mutants corresponding to poor clinical outcomes, such as L858R_T790M, possess lower binding affinities with ErbB-3 than c-Met does. This may promote the communication between ErbB-3 and c-Met in these cancer cells. The

  15. Design principles of nuclear receptor signaling: how complex networking improves signal transduction

    Science.gov (United States)

    Kolodkin, Alexey N; Bruggeman, Frank J; Plant, Nick; Moné, Martijn J; Bakker, Barbara M; Campbell, Moray J; van Leeuwen, Johannes P T M; Carlberg, Carsten; Snoep, Jacky L; Westerhoff, Hans V

    2010-01-01

    The topology of nuclear receptor (NR) signaling is captured in a systems biological graphical notation. This enables us to identify a number of ‘design' aspects of the topology of these networks that might appear unnecessarily complex or even functionally paradoxical. In realistic kinetic models of increasing complexity, calculations show how these features correspond to potentially important design principles, e.g.: (i) cytosolic ‘nuclear' receptor may shuttle signal molecules to the nucleus, (ii) the active export of NRs may ensure that there is sufficient receptor protein to capture ligand at the cytoplasmic membrane, (iii) a three conveyor belts design dissipating GTP-free energy, greatly aids response, (iv) the active export of importins may prevent sequestration of NRs by importins in the nucleus and (v) the unspecific nature of the nuclear pore may ensure signal-flux robustness. In addition, the models developed are suitable for implementation in specific cases of NR-mediated signaling, to predict individual receptor functions and differential sensitivity toward physiological and pharmacological ligands. PMID:21179018

  16. Defining the ATM-mediated barrier to tumorigenesis in somatic mammary cells following ErbB2 activation.

    Science.gov (United States)

    Reddy, Jay P; Peddibhotla, Sirisha; Bu, Wen; Zhao, Jing; Haricharan, Svasti; Du, Yi-Chieh Nancy; Podsypanina, Katrina; Rosen, Jeffrey M; Donehower, Larry A; Li, Yi

    2010-02-23

    p53, apoptosis, and senescence are frequently activated in preneoplastic lesions and are barriers to progression to malignancy. These barriers have been suggested to result from an ATM-mediated DNA damage response (DDR), which may follow oncogene-induced hyperproliferation and ensuing DNA replication stress. To elucidate the currently untested role of DDR in breast cancer initiation, we examined the effect of oncogene expression in several murine models of breast cancer. We did not observe a detectable DDR in early hyperplastic lesions arising in transgenic mice expressing several different oncogenes. However, DDR signaling was strongly induced in preneoplastic lesions arising from individual mammary cells transduced in vivo by retroviruses expressing either PyMT or ErbB2. Thus, activation of an oncogene after normal tissue development causes a DDR. Furthermore, in this somatic ErbB2 tumor model, ATM, and thus DDR, is required for p53 stabilization, apoptosis, and senescence. In palpable tumors in this model, p53 stabilization and apoptosis are lost, but unexpectedly senescence remains in many tumor cells. Thus, this murine model fully recapitulates early DDR signaling; the eventual suppression of its endpoints in tumorigenesis provides compelling evidence that ErbB2-induced aberrant mammary cell proliferation leads to an ATM-mediated DDR that activates apoptosis and senescence, and at least the former must be overcome to progress to malignancy. This in vivo study also uncovers an unexpected effect of ErbB2 activation previously known for its prosurvival roles, and suggests that protection of the ATM-mediated DDR-p53 signaling pathway may be important in breast cancer prevention.

  17. Development of an ErbB4 monoclonal antibody that blocks neuregulin-1-induced ErbB4 activation in cancer cells

    International Nuclear Information System (INIS)

    Okazaki, Shogo; Nakatani, Fumi; Masuko, Kazue; Tsuchihashi, Kenji; Ueda, Shiho; Masuko, Takashi; Saya, Hideyuki; Nagano, Osamu

    2016-01-01

    The use of monoclonal antibodies (mAbs) for cancer therapy is one of the most important strategies for current cancer treatment. The epidermal growth factor receptor (EGFR) family of receptor tyrosine kinases, which regulates cancer cell proliferation, survival, and migration, is a major molecular target for antibody-based therapy. ErbB4/HER4, which contains a ligand-binding extracellular region, is activated by several ligands, including neuregulins (NRGs), heparin-binding EGF-like growth factor, betacellulin and epiregulin. Although there are clinically approved antibodies for ErbB1 and ErbB2, there are no available therapeutic mAbs for ErbB4, and it is not known whether ErbB4 is a useful target for antibody-based cancer therapy. In this study, we developed an anti-ErbB4 mAb (clone P6-1) that suppresses NRG-dependent activation of ErbB4 and examined its effect on breast cancer cell proliferation in the extracellular matrix. - Highlights: • We newly generated four clones of human ErbB4 specific mAb. • ErbB4 mAb clone P6-1 blocks ErbB4 phosphorylation induced by NRG-1. • ErbB4 mAb clone P6-1 suppresses NRG-1-promoted breast cancer cells proliferation on three dimensional culture condition.

  18. Development of an ErbB4 monoclonal antibody that blocks neuregulin-1-induced ErbB4 activation in cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Okazaki, Shogo [Division of Gene Regulation, Institute for Advanced Medical Research, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582 (Japan); Nakatani, Fumi [Cell Biology Laboratory, Department of Pharmaceutical Sciences, Faculty of Pharmacy, Kinki University, Higashiosaka, Osaka 577-8502 Japan (Japan); Masuko, Kazue; Tsuchihashi, Kenji [Division of Gene Regulation, Institute for Advanced Medical Research, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582 (Japan); Ueda, Shiho; Masuko, Takashi [Cell Biology Laboratory, Department of Pharmaceutical Sciences, Faculty of Pharmacy, Kinki University, Higashiosaka, Osaka 577-8502 Japan (Japan); Saya, Hideyuki [Division of Gene Regulation, Institute for Advanced Medical Research, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582 (Japan); Nagano, Osamu, E-mail: osmna@sb3.so-net.ne.jp [Division of Gene Regulation, Institute for Advanced Medical Research, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582 (Japan)

    2016-01-29

    The use of monoclonal antibodies (mAbs) for cancer therapy is one of the most important strategies for current cancer treatment. The epidermal growth factor receptor (EGFR) family of receptor tyrosine kinases, which regulates cancer cell proliferation, survival, and migration, is a major molecular target for antibody-based therapy. ErbB4/HER4, which contains a ligand-binding extracellular region, is activated by several ligands, including neuregulins (NRGs), heparin-binding EGF-like growth factor, betacellulin and epiregulin. Although there are clinically approved antibodies for ErbB1 and ErbB2, there are no available therapeutic mAbs for ErbB4, and it is not known whether ErbB4 is a useful target for antibody-based cancer therapy. In this study, we developed an anti-ErbB4 mAb (clone P6-1) that suppresses NRG-dependent activation of ErbB4 and examined its effect on breast cancer cell proliferation in the extracellular matrix. - Highlights: • We newly generated four clones of human ErbB4 specific mAb. • ErbB4 mAb clone P6-1 blocks ErbB4 phosphorylation induced by NRG-1. • ErbB4 mAb clone P6-1 suppresses NRG-1-promoted breast cancer cells proliferation on three dimensional culture condition.

  19. 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.

  20. Gene regulatory and signaling networks exhibit distinct topological distributions of motifs

    Science.gov (United States)

    Ferreira, Gustavo Rodrigues; Nakaya, Helder Imoto; Costa, Luciano da Fontoura

    2018-04-01

    The biological processes of cellular decision making and differentiation involve a plethora of signaling pathways and gene regulatory circuits. These networks in turn exhibit a multitude of motifs playing crucial parts in regulating network activity. Here we compare the topological placement of motifs in gene regulatory and signaling networks and observe that it suggests different evolutionary strategies in motif distribution for distinct cellular subnetworks.

  1. Weak signal transmission in complex networks and its application in detecting connectivity.

    Science.gov (United States)

    Liang, Xiaoming; Liu, Zonghua; Li, Baowen

    2009-10-01

    We present a network model of coupled oscillators to study how a weak signal is transmitted in complex networks. Through both theoretical analysis and numerical simulations, we find that the response of other nodes to the weak signal decays exponentially with their topological distance to the signal source and the coupling strength between two neighboring nodes can be figured out by the responses. This finding can be conveniently used to detect the topology of unknown network, such as the degree distribution, clustering coefficient and community structure, etc., by repeatedly choosing different nodes as the signal source. Through four typical networks, i.e., the regular one dimensional, small world, random, and scale-free networks, we show that the features of network can be approximately given by investigating many fewer nodes than the network size, thus our approach to detect the topology of unknown network may be efficient in practical situations with large network size.

  2. 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.

  3. ERBB-2 overexpression as a risk factor for malignant phaeochromocytomas and paraganglinomas.

    Science.gov (United States)

    Wang, Weiqing; Zhong, Xu; Ye, Lei; Qi, Yan; Su, TingWei; Wei, Qing; Xie, Jing; Jiang, Lei; Jiang, Yiran; Zhou, Weiwei; Cui, Bin; Ning, Guang

    2016-06-01

    There are currently no good histological or molecular markers to differentiate benign from malignant phaeochromocytomas and paraganglinomas (PPGLs). Our previous cross-sectional study observed that ERBB-2 overexpression was associated with malignant PPGLs. This study aimed to evaluate the predictive value of ERBB-2 overexpression for metastasis in PPGLs in a large population. A total of 262 patients diagnosed as PPGLs in our institution between 2002 and 2012 were included. We analysed ERBB-2 protein expression in the primary PPGL tumours by immunohistochemistry (IHC) and ERBB-2 amplification by fluorescence in situ hybridization (FISH). Direct Sanger sequencing was performed to examine ERBB-2 exon 20 mutations. The occurrence of malignant PPGLs was documented in the follow-up period. Kaplan-Meier analysis and Cox proportional hazard models were used to evaluate the association between ERBB-2 overexpression and metastasis of PPGLs. Twenty-six (9·9%) patients had ERBB-2 overexpression in their primary PPGL tumours, which was significantly associated with ERBB-2 amplification (17/25, 68%). No ERBB-2 mutation was found. At a median follow-up of 4·5 years, a total of 23 malignant PPGLs were documented, including eight (30·8%) patients in the ERBB-2 overexpression group and 15 (6·4%) patients in the ERBB-2-negative group. The incidence rate of metastasis was 5·3 per 100 person-years vs 1·4 per 100 person-years in the ERBB-2 overexpression and ERBB-2-negative groups (P overexpression was associated with decreased metastasis-free survival (P = 0·001, log-rank test). After adjusting for primary tumour size and location, Cox regression analysis revealed that ERBB-2 overexpression was independently associated with risk of malignant PPGLs (HR = 2·78; 95% CI, 1·12-6·90; P = 0·028). Patients harbouring tumours with ERBB-2 overexpression have a significantly higher risk of developing malignant PPGLs. © 2016 John Wiley & Sons Ltd.

  4. Effect of acute acid-base disturbances on ErbB1/2 tyrosine phosphorylation in rabbit renal proximal tubules.

    Science.gov (United States)

    Skelton, Lara A; Boron, Walter F

    2013-12-15

    The renal proximal tubule (PT) is a major site for maintaining whole body pH homeostasis and is responsible for reabsorbing ∼80% of filtered HCO3(-), the major plasma buffer, into the blood. The PT adapts its rate of HCO3(-) reabsorption (JHCO3(-)) in response to acute acid-base disturbances. Our laboratory previously showed that single isolated perfused PTs adapt JHCO3(-) in response to isolated changes in basolateral (i.e., blood side) CO2 and HCO3(-) concentrations but, surprisingly, not to pH. The response to CO2 concentration can be blocked by the ErbB family tyrosine kinase inhibitor PD-168393. In the present study, we exposed enriched rabbit PT suspensions to five acute acid-base disturbances for 5 and 20 min using a panel of phosphotyrosine (pY)-specific antibodies to determine the influence of each disturbance on pan-pY, ErbB1-specific pY (four sites), and ErbB2-specific pY (two sites). We found that each acid-base treatment generated a distinct temporal pY pattern. For example, the summated responses of the individual ErbB1/2-pY sites to each disturbance showed that metabolic acidosis (normal CO2 concentration and reduced HCO3(-) concentration) produced a transient summated pY decrease (5 vs. 20 min), whereas metabolic alkalosis produced a transient increase. Respiratory acidosis (normal HCO3(-) concentration and elevated CO2 concentration) had little effect on summated pY at 5 min but produced an elevation at 20 min, whereas respiratory alkalosis produced a reduction at 20 min. Our data show that ErbB1 and ErbB2 in the PT respond to acute acid-base disturbances, consistent with the hypothesis that they are part of the signaling cascade.

  5. Ibrutinib Inhibits ERBB Receptor Tyrosine Kinases and HER2-Amplified Breast Cancer Cell Growth.

    Science.gov (United States)

    Chen, Jun; Kinoshita, Taisei; Sukbuntherng, Juthamas; Chang, Betty Y; Elias, Laurence

    2016-12-01

    Ibrutinib is a potent, small-molecule Bruton tyrosine kinase (BTK) inhibitor developed for the treatment of B-cell malignancies. Ibrutinib covalently binds to Cys481 in the ATP-binding domain of BTK. This cysteine residue is conserved among 9 other tyrosine kinases, including HER2 and EGFR, which can be targeted. Screening large panels of cell lines demonstrated that ibrutinib was growth inhibitory against some solid tumor cells, including those inhibited by other HER2/EGFR inhibitors. Among sensitive cell lines, breast cancer lines with HER2 overexpression were most potently inhibited by ibrutinib (ibrutinib coincided with downregulation of phosphorylation on HER2 and EGFR and their downstream targets, AKT and ERK. Irreversible inhibition of HER2 and EGFR in breast cancer cells was established after 30-minute incubation above 100 nmol/L or following 2-hour incubation at lower concentrations. Furthermore, ibrutinib inhibited recombinant HER2 and EGFR activity that was resistant to dialysis and rapid dilution, suggesting an irreversible interaction. The dual activity toward TEC family (BTK and ITK) and ERBB family kinases was unique to ibrutinib, as ERBB inhibitors do not inhibit or covalently bind BTK or ITK. Xenograft studies with HER2 + MDA-MB-453 and BT-474 cells in mice in conjunction with determination of pharmacokinetics demonstrated significant exposure-dependent inhibition of growth and key signaling molecules at levels that are clinically achievable. Ibrutinib's unique dual spectrum of activity against both TEC family and ERBB kinases suggests broader applications of ibrutinib in oncology. Mol Cancer Ther; 15(12); 2835-44. ©2016 AACR. ©2016 American Association for Cancer Research.

  6. The T cell STAT signaling network is reprogrammed within hours of bacteremia via secondary signals1

    Science.gov (United States)

    Hotson, Andrew N.; Hardy, Jonathan W.; Hale, Matthew B.; Contag, Christopher H.; Nolan, Garry P.

    2014-01-01

    The delicate balance between protective immunity and inflammatory disease is challenged during sepsis, a pathologic state characterized by aspects of both a hyper-active immune response and immunosuppression. The events driven by systemic infection by bacterial pathogens on the T cell signaling network that likely control these responses have not been illustrated in great detail. We characterized how intracellular signaling within the immune compartment is reprogrammed at the single cell level when the host is challenged with a high levels of pathogen. To accomplish this, we applied flow cytometry to measure the phosphorylation potential of key signal transduction proteins during acute bacterial challenge. We modeled the onset of sepsis by intravenous administration of avirulent strains of Listeria and E. coli to mice. Within six hours of bacterial challenge, T cells were globally restricted in their ability to respond to specific cytokine stimulations as determined by assessing the extent of STAT protein phosphorylation. Mechanisms by which this negative feedback response occurred included SOCS1 and SOCS3 gene up regulation and IL-6 induced endocystosis of the IL-6 receptor. In addition, macrophages were partially tolerized in their ability to respond to TLR agonists. Thus, in contrast to the view that there is a wholesale immune activation during sepsis, one immediate host response to blood borne bacteria was induction of a refractory period during which leukocyte activation by specific stimulations was attenuated. PMID:19494279

  7. [A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

    Science.gov (United States)

    Zhang, Y; Liu, A; Yu, K

    1999-06-01

    A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

  8. Role of Erbin in ErbB2-dependent breast tumor growth

    Science.gov (United States)

    Tao, Yanmei; Shen, Chengyong; Luo, Shiwen; Traoré, Wilfried; Marchetto, Sylvie; Santoni, Marie-Josée; Xu, Linlin; Wu, Biao; Shi, Chao; Mei, Jinghong; Bates, Ryan; Liu, Xihui; Zhao, Kai; Xiong, Wen-Cheng; Borg, Jean-Paul; Mei, Lin

    2014-01-01

    ErbB2 (v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 2), a receptor tyrosine kinase of the ErbB family, is overexpressed in around 25% of breast cancers. In addition to forming a heterodimer with other ErbB receptors in response to ligand stimulation, ErbB2 can be activated in a ligand-independent manner. We report here that Erbin, an ErbB2-interacting protein that was thought to act as an antitumor factor, is specifically expressed in mammary luminal epithelial cells and facilitates ErbB2-dependent proliferation of breast cancer cells and tumorigenesis in MMTV-neu transgenic mice. Disruption of their interaction decreases ErbB2-dependent proliferation, and deletion of the PDZ domain in Erbin hinders ErbB2-dependent tumor development in MMTV-neu mice. Mechanistically, Erbin forms a complex with ErbB2, promotes its interaction with the chaperon protein HSP90, and thus prevents its degradation. Finally, ErbB2 and Erbin expression correlates in human breast tumor tissues. Together, these observations establish Erbin as an ErbB2 regulator for breast tumor formation and progression. PMID:25288731

  9. Intermittent hypoxia induces the proliferation of rat vascular smooth muscle cell with the increases in epidermal growth factor family and erbB2 receptor

    Energy Technology Data Exchange (ETDEWEB)

    Kyotani, Yoji, E-mail: cd147@naramed-u.ac.jp [Department of Pharmacology, Nara Medical University School of Medicine, Kashihara 634-8521 (Japan); Department of Pharmacy, Nara Medical University Hospital, Kashihara 634-8522 (Japan); Ota, Hiroyo [Second Department of Internal Medicine, Nara Medical University School of Medicine, Kashihara 634-8522 (Japan); Department of Biochemistry, Nara Medical University School of Medicine, Kashihara 634-8521 (Japan); Itaya-Hironaka, Asako; Yamauchi, Akiyo; Sakuramoto-Tsuchida, Sumiyo [Department of Biochemistry, Nara Medical University School of Medicine, Kashihara 634-8521 (Japan); Zhao, Jing; Ozawa, Kentaro; Nagayama, Kosuke; Ito, Satoyasu [Department of Pharmacology, Nara Medical University School of Medicine, Kashihara 634-8521 (Japan); Takasawa, Shin [Department of Biochemistry, Nara Medical University School of Medicine, Kashihara 634-8521 (Japan); Kimura, Hiroshi [Second Department of Internal Medicine, Nara Medical University School of Medicine, Kashihara 634-8522 (Japan); Uno, Masayuki [Department of Pharmacy, Nara Medical University Hospital, Kashihara 634-8522 (Japan); Yoshizumi, Masanori [Department of Pharmacology, Nara Medical University School of Medicine, Kashihara 634-8521 (Japan)

    2013-11-15

    Obstructive sleep apnea is characterized by intermittent hypoxia (IH), and associated with cardiovascular diseases, such as stroke and heart failure. These cardiovascular diseases have a relation to atherosclerosis marked by the proliferation of vascular smooth muscle cells (VSMCs). In this study, we investigated the influence of IH on cultured rat aortic smooth muscle cell (RASMC). The proliferation of RASMC was significantly increased by IH without changing the level of apoptosis. In order to see what induces RASMC proliferation, we investigated the influence of normoxia (N)-, IH- and sustained hypoxia (SH)-treated cell conditioned media on RASMC proliferation. IH-treated cell conditioned medium significantly increased RASMC proliferation compared with N-treated cell conditioned medium, but SH-treated cell conditioned medium did not. We next investigated the epidermal growth factor (EGF) family as autocrine growth factors. Among the EGF family, we found significant increases in mRNAs for epiregulin (ER), amphiregulin (AR) and neuregulin-1 (NRG1) in IH-treated cells and mature ER in IH-treated cell conditioned medium. We next investigated the changes in erbB family receptors that are receptors for ER, AR and NRG1, and found that erbB2 receptor mRNA and protein expressions were increased by IH, but not by SH. Phosphorylation of erbB2 receptor at Tyr-1248 that mediates intracellular signaling for several physiological effects including cell proliferation was increased by IH, but not by SH. In addition, inhibitor for erbB2 receptor suppressed IH-induced cell proliferation. These results provide the first demonstration that IH induces VSMC proliferation, and suggest that EGF family, such as ER, AR and NRG1, and erbB2 receptor could be involved in the IH-induced VSMC proliferation. - Highlights: ●In vitro system for intermittent hypoxia (IH) and sustained hypoxia (SH). ●IH, but not SH, induces the proliferation of rat vascular smooth muscle cell. ●Epiregulin m

  10. Intermittent hypoxia induces the proliferation of rat vascular smooth muscle cell with the increases in epidermal growth factor family and erbB2 receptor

    International Nuclear Information System (INIS)

    Kyotani, Yoji; Ota, Hiroyo; Itaya-Hironaka, Asako; Yamauchi, Akiyo; Sakuramoto-Tsuchida, Sumiyo; Zhao, Jing; Ozawa, Kentaro; Nagayama, Kosuke; Ito, Satoyasu; Takasawa, Shin; Kimura, Hiroshi; Uno, Masayuki; Yoshizumi, Masanori

    2013-01-01

    Obstructive sleep apnea is characterized by intermittent hypoxia (IH), and associated with cardiovascular diseases, such as stroke and heart failure. These cardiovascular diseases have a relation to atherosclerosis marked by the proliferation of vascular smooth muscle cells (VSMCs). In this study, we investigated the influence of IH on cultured rat aortic smooth muscle cell (RASMC). The proliferation of RASMC was significantly increased by IH without changing the level of apoptosis. In order to see what induces RASMC proliferation, we investigated the influence of normoxia (N)-, IH- and sustained hypoxia (SH)-treated cell conditioned media on RASMC proliferation. IH-treated cell conditioned medium significantly increased RASMC proliferation compared with N-treated cell conditioned medium, but SH-treated cell conditioned medium did not. We next investigated the epidermal growth factor (EGF) family as autocrine growth factors. Among the EGF family, we found significant increases in mRNAs for epiregulin (ER), amphiregulin (AR) and neuregulin-1 (NRG1) in IH-treated cells and mature ER in IH-treated cell conditioned medium. We next investigated the changes in erbB family receptors that are receptors for ER, AR and NRG1, and found that erbB2 receptor mRNA and protein expressions were increased by IH, but not by SH. Phosphorylation of erbB2 receptor at Tyr-1248 that mediates intracellular signaling for several physiological effects including cell proliferation was increased by IH, but not by SH. In addition, inhibitor for erbB2 receptor suppressed IH-induced cell proliferation. These results provide the first demonstration that IH induces VSMC proliferation, and suggest that EGF family, such as ER, AR and NRG1, and erbB2 receptor could be involved in the IH-induced VSMC proliferation. - Highlights: ●In vitro system for intermittent hypoxia (IH) and sustained hypoxia (SH). ●IH, but not SH, induces the proliferation of rat vascular smooth muscle cell. ●Epiregulin m

  11. Prolyl isomerase Pin1 is highly expressed in Her2-positive breast cancer and regulates erbB2 protein stability

    Directory of Open Access Journals (Sweden)

    Lu Kun

    2008-12-01

    Full Text Available Abstract Overexpression of HER-2/Neu occurs in about 25–30% of breast cancer patients and is indicative of poor prognosis. While Her2/Neu overexpression is primarily a result of erbB2 amplification, it has recently been recognized that erbB2 levels are also regulated on the protein level. However, factors that regulate Her2/Neu protein stability are less well understood. The prolyl isomerase Pin1 catalyzes the isomerization of specific pSer/Thr-Pro motifs that have been phosphorylated in response to mitogenic signaling. We have previously reported that Pin1-catalyzed post-phosphorylational modification of signal transduction modulates the oncogenic pathways downstream from c-neu. The goal of this study was to examine the expression of prolyl isomerase Pin1 in human Her2+ breast cancer, and to study if Pin1 affects the expression of Her2/Neu itself. Methods Immunohistochemistry for Her2 and Pin1 were performed on two hundred twenty-three human breast cancers, with 59% of the specimen from primary cancers and 41% from metastatic sites. Pin1 inhibition was achieved using siRNA in Her2+ breast cancer cell lines, and its effects were studied using cell viability assays, immunoblotting and immunofluorescence. Results Sixty-four samples (28.7% stained positive for Her2 (IHC 3+, and 54% (122/223 of all breast cancers stained positive for Pin1. Of the Her2-positive cancers 40 (62.5% were also Pin1-positive, based on strong nuclear or nuclear and cytoplasmic staining. Inhibition of Pin1 via RNAi resulted in significant suppression of Her2-positive tumor cell growth in BT474, SKBR3 and AU565 cells. Pin1 inhibition greatly increased the sensitivity of Her2-positive breast cancer cells to the mTOR inhibitor Rapamycin, while it did not increase their sensitivity to Trastuzumab, suggesting that Pin1 might act on Her2 signaling. We found that Pin1 interacted with the protein complex that contains ubiquitinated erbB2 and that Pin1 inhibition accelerated erbB2

  12. A performance based evaluation of SIP signalling across converged networks

    NARCIS (Netherlands)

    Oredope, A.; Liotta, A.

    2007-01-01

    As wireless networks evolves towards the 3G and 4G architectures the mobile core networks provides a platform for all-IP convergence of mobile and fixed networks allowing for better integration of the Internet and cellular networks, providing better quality of service, charging mechanisms and

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

    Science.gov (United States)

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

    2014-01-01

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

  15. 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

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

    Directory of Open Access Journals (Sweden)

    Kuo Zhang

    2018-01-01

    Full Text Available 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 network in ST36 (Zusanli acupoint, and serum and hind foot pad tissue. The results indicate that MA had significant analgesic, anti-inflammatory effects on CFA rats; the key signaling molecules may play a key role during MA regulating NEI network, but further research is needed.

  17. 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.

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

    Institute of Scientific and Technical Information of China (English)

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

    2012-01-01

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

  19. Assuring SS7 dependability: A robustness characterization of signaling network elements

    Science.gov (United States)

    Karmarkar, Vikram V.

    1994-04-01

    Current and evolving telecommunication services will rely on signaling network performance and reliability properties to build competitive call and connection control mechanisms under increasing demands on flexibility without compromising on quality. The dimensions of signaling dependability most often evaluated are the Rate of Call Loss and End-to-End Route Unavailability. A third dimension of dependability that captures the concern about large or catastrophic failures can be termed Network Robustness. This paper is concerned with the dependability aspects of the evolving Signaling System No. 7 (SS7) networks and attempts to strike a balance between the probabilistic and deterministic measures that must be evaluated to accomplish a risk-trend assessment to drive architecture decisions. Starting with high-level network dependability objectives and field experience with SS7 in the U.S., potential areas of growing stringency in network element (NE) dependability are identified to improve against current measures of SS7 network quality, as per-call signaling interactions increase. A sensitivity analysis is presented to highlight the impact due to imperfect coverage of duplex network component or element failures (i.e., correlated failures), to assist in the setting of requirements on NE robustness. A benefit analysis, covering several dimensions of dependability, is used to generate the domain of solutions available to the network architect in terms of network and network element fault tolerance that may be specified to meet the desired signaling quality goals.

  20. Prototype real-time baseband signal combiner. [deep space network

    Science.gov (United States)

    Howard, L. D.

    1980-01-01

    The design and performance of a prototype real-time baseband signal combiner, used to enhance the received Voyager 2 spacecraft signals during the Jupiter flyby, is described. Hardware delay paths, operating programs, and firmware are discussed.

  1. Transducer of ERBB2.1 (TOB1) as a Tumor Suppressor: A Mechanistic Perspective.

    Science.gov (United States)

    Lee, Hun Seok; Kundu, Juthika; Kim, Ryong Nam; Shin, Young Kee

    2015-12-15

    Transducer of ERBB2.1 (TOB1) is a tumor-suppressor protein, which functions as a negative regulator of the receptor tyrosine-kinase ERBB2. As most of the other tumor suppressor proteins, TOB1 is inactivated in many human cancers. Homozygous deletion of TOB1 in mice is reported to be responsible for cancer development in the lung, liver, and lymph node, whereas the ectopic overexpression of TOB1 shows anti-proliferation, and a decrease in the migration and invasion abilities on cancer cells. Biochemical studies revealed that the anti-proliferative activity of TOB1 involves mRNA deadenylation and is associated with the reduction of both cyclin D1 and cyclin-dependent kinase (CDK) expressions and the induction of CDK inhibitors. Moreover, TOB1 interacts with an oncogenic signaling mediator, β-catenin, and inhibits β-catenin-regulated gene transcription. TOB1 antagonizes the v-akt murine thymoma viral oncogene (AKT) signaling and induces cancer cell apoptosis by activating BCL2-associated X (BAX) protein and inhibiting the BCL-2 and BCL-XL expressions. The tumor-specific overexpression of TOB1 results in the activation of other tumor suppressor proteins, such as mothers against decapentaplegic homolog 4 (SMAD4) and phosphatase and tensin homolog-10 (PTEN), and blocks tumor progression. TOB1-overexpressing cancer cells have limited potential of growing as xenograft tumors in nude mice upon subcutaneous implantation. This review addresses the molecular basis of TOB1 tumor suppressor function with special emphasis on its regulation of intracellular signaling pathways.

  2. Transducer of ERBB2.1 (TOB1 as a Tumor Suppressor: A Mechanistic Perspective

    Directory of Open Access Journals (Sweden)

    Hun Seok Lee

    2015-12-01

    Full Text Available Transducer of ERBB2.1 (TOB1 is a tumor-suppressor protein, which functions as a negative regulator of the receptor tyrosine-kinase ERBB2. As most of the other tumor suppressor proteins, TOB1 is inactivated in many human cancers. Homozygous deletion of TOB1 in mice is reported to be responsible for cancer development in the lung, liver, and lymph node, whereas the ectopic overexpression of TOB1 shows anti-proliferation, and a decrease in the migration and invasion abilities on cancer cells. Biochemical studies revealed that the anti-proliferative activity of TOB1 involves mRNA deadenylation and is associated with the reduction of both cyclin D1 and cyclin-dependent kinase (CDK expressions and the induction of CDK inhibitors. Moreover, TOB1 interacts with an oncogenic signaling mediator, β-catenin, and inhibits β-catenin-regulated gene transcription. TOB1 antagonizes the v-akt murine thymoma viral oncogene (AKT signaling and induces cancer cell apoptosis by activating BCL2-associated X (BAX protein and inhibiting the BCL-2 and BCL-XL expressions. The tumor-specific overexpression of TOB1 results in the activation of other tumor suppressor proteins, such as mothers against decapentaplegic homolog 4 (SMAD4 and phosphatase and tensin homolog-10 (PTEN, and blocks tumor progression. TOB1-overexpressing cancer cells have limited potential of growing as xenograft tumors in nude mice upon subcutaneous implantation. This review addresses the molecular basis of TOB1 tumor suppressor function with special emphasis on its regulation of intracellular signaling pathways.

  3. Ligand stimulation of ErbB4 and a constitutively-active ErbB4 mutant result in different biological responses in human pancreatic tumor cell lines

    International Nuclear Information System (INIS)

    Mill, Christopher P.; Gettinger, Kathleen L.; Riese, David J.

    2011-01-01

    Pancreatic cancer is the fourth leading cause of cancer death in the United States. Indeed, it has been estimated that 37,000 Americans will die from this disease in 2010. Late diagnosis, chemoresistance, and radioresistance of these tumors are major reasons for poor patient outcome, spurring the search for pancreatic cancer early diagnostic and therapeutic targets. ErbB4 (HER4) is a member of the ErbB family of receptor tyrosine kinases (RTKs), a family that also includes the Epidermal Growth Factor Receptor (EGFR/ErbB1/HER1), Neu/ErbB2/HER2, and ErbB3/HER3. These RTKs play central roles in many human malignancies by regulating cell proliferation, survival, differentiation, invasiveness, motility, and apoptosis. In this report we demonstrate that human pancreatic tumor cell lines exhibit minimal ErbB4 expression; in contrast, these cell lines exhibit varied and in some cases abundant expression and basal tyrosine phosphorylation of EGFR, ErbB2, and ErbB3. Expression of a constitutively-dimerized and -active ErbB4 mutant inhibits clonogenic proliferation of CaPan-1, HPAC, MIA PaCa-2, and PANC-1 pancreatic tumor cell lines. In contrast, expression of wild-type ErbB4 in pancreatic tumor cell lines potentiates stimulation of anchorage-independent colony formation by the ErbB4 ligand Neuregulin 1β. These results illustrate the multiple roles that ErbB4 may be playing in pancreatic tumorigenesis and tumor progression.

  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. 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.

  6. 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.

  7. ErbB polymorphisms: Insights and implications for response to targeted cancer therapeutics

    Directory of Open Access Journals (Sweden)

    Moulay A Alaoui-Jamali

    2015-02-01

    Full Text Available Advances in high-throughput genomic-scanning have expanded the repertory of genetic variations in DNA sequences encoding ErbB tyrosine kinase receptors in humans, including single nucleotide polymorphisms (SNPs, polymorphic repetitive elements, microsatellite variations, small-scale insertions and deletions. The ErbB family members: EGFR, ErbB2, ErbB3 and ErbB4 receptors are established as drivers of many aspects of tumor initiation and progression to metastasis. This knowledge has provided rationales for the development of an arsenal of anti-ErbB therapeutics, ranging from small molecule kinase inhibitors to monoclonal antibodies. Anti-ErbB agents are becoming the cornerstone therapeutics for the management of cancers that overexpress hyperactive variants of ErbB receptors, in particular ErbB2-positive breast cancer and non-small cell lung carcinomas. However, their clinical benefit has been limited to a subset of patients due to a wide heterogeneity in drug response despite the expression of the ErbB targets, attributed to intrinsic (primary and to acquired (secondary resistance. Somatic mutations in ErbB tyrosine kinase domains have been extensively investigated in preclinical and clinical setting as determinants for either high sensitivity or resistance to anti-ErbB therapeutics. In contrast, only scant information is available on the impact of SNPs, which are widespread in genes encoding ErbB receptors, on receptor structure and activity, and their predictive values for drug susceptibility. This review aims to briefly update polymorphic variations in genes encoding ErbB receptors based on recent advances in deep sequencing technologies, and to address challenging issues for a better understanding of the functional impact of single versus combined SNPs in ErbB genes to receptor topology, receptor-drug interaction, and drug susceptibility. The potential of exploiting SNPs in the era of stratified targeted therapeutics is discussed.

  8. Preubiquitinated chimeric ErbB2 is constitutively endocytosed and subsequently degraded in lysosomes

    Energy Technology Data Exchange (ETDEWEB)

    Vuong, Tram Thu [Institute of Clinical Medicine, University of Oslo, Rikshospitalet, 0027 Oslo (Norway); Berger, Christian [Department of Pathology, Oslo University Hospital, Rikshospitalet, P.O. Box 4950 Nydalen, 0424 Oslo (Norway); Bertelsen, Vibeke; Rødland, Marianne Skeie [Institute of Clinical Medicine, University of Oslo, Rikshospitalet, 0027 Oslo (Norway); Stang, Espen [Department of Pathology, Oslo University Hospital, Rikshospitalet, P.O. Box 4950 Nydalen, 0424 Oslo (Norway); Madshus, Inger Helene, E-mail: i.h.madshus@medisin.uio.no [Institute of Clinical Medicine, University of Oslo, Rikshospitalet, 0027 Oslo (Norway); Department of Pathology, Oslo University Hospital, Rikshospitalet, P.O. Box 4950 Nydalen, 0424 Oslo (Norway)

    2013-02-01

    The oncoprotein ErbB2 is endocytosis-deficient, probably due to its interaction with Heat shock protein 90. We previously demonstrated that clathrin-dependent endocytosis of ErbB2 is induced upon incubation of cells with Ansamycin derivatives, such as geldanamycin and its derivative 17-AAG. Furthermore, we have previously demonstrated that a preubiquitinated chimeric EGFR (EGFR-Ub{sub 4}) is constitutively endocytosed in a clathrin-dependent manner. We now demonstrate that also an ErbB2-Ub{sub 4} chimera is endocytosed constitutively and clathrin-dependently. Upon expression, the ErbB2-Ub{sub 4} was further ubiquitinated, and by Western blotting, we demonstrated the formation of both Lys48-linked and Lys63-linked polyubiquitin chains. ErbB2-Ub{sub 4} was constitutively internalized and eventually sorted to late endosomes and lysosomes where the fusion protein was degraded. ErbB2-Ub{sub 4} was not cleaved prior to internalization. Interestingly, over-expression of Ubiquitin Interaction Motif-containing dominant negative fragments of the clathrin adaptor proteins epsin1 and Eps15 negatively affected endocytosis of ErbB2. Altogether, this argues that ubiquitination is sufficient to induce clathrin-mediated endocytosis and lysosomal degradation of the otherwise plasma membrane localized ErbB2. Also, it appears that C-terminal cleavage is not required for endocytosis. -- Highlights: ► A chimera containing ErbB2 and a tetra-Ubiquitin chain internalizes constitutively. ► Receptor fragmentation is not required for endocytosis of ErbB2. ► Ubiquitination is sufficient to induce endocytosis and degradation of ErbB2. ► ErbB2-Ub4 is internalized clathrin-dependently.

  9. Preubiquitinated chimeric ErbB2 is constitutively endocytosed and subsequently degraded in lysosomes

    International Nuclear Information System (INIS)

    Vuong, Tram Thu; Berger, Christian; Bertelsen, Vibeke; Rødland, Marianne Skeie; Stang, Espen; Madshus, Inger Helene

    2013-01-01

    The oncoprotein ErbB2 is endocytosis-deficient, probably due to its interaction with Heat shock protein 90. We previously demonstrated that clathrin-dependent endocytosis of ErbB2 is induced upon incubation of cells with Ansamycin derivatives, such as geldanamycin and its derivative 17-AAG. Furthermore, we have previously demonstrated that a preubiquitinated chimeric EGFR (EGFR-Ub 4 ) is constitutively endocytosed in a clathrin-dependent manner. We now demonstrate that also an ErbB2-Ub 4 chimera is endocytosed constitutively and clathrin-dependently. Upon expression, the ErbB2-Ub 4 was further ubiquitinated, and by Western blotting, we demonstrated the formation of both Lys48-linked and Lys63-linked polyubiquitin chains. ErbB2-Ub 4 was constitutively internalized and eventually sorted to late endosomes and lysosomes where the fusion protein was degraded. ErbB2-Ub 4 was not cleaved prior to internalization. Interestingly, over-expression of Ubiquitin Interaction Motif-containing dominant negative fragments of the clathrin adaptor proteins epsin1 and Eps15 negatively affected endocytosis of ErbB2. Altogether, this argues that ubiquitination is sufficient to induce clathrin-mediated endocytosis and lysosomal degradation of the otherwise plasma membrane localized ErbB2. Also, it appears that C-terminal cleavage is not required for endocytosis. -- Highlights: ► A chimera containing ErbB2 and a tetra-Ubiquitin chain internalizes constitutively. ► Receptor fragmentation is not required for endocytosis of ErbB2. ► Ubiquitination is sufficient to induce endocytosis and degradation of ErbB2. ► ErbB2-Ub4 is internalized clathrin-dependently.

  10. Nonlinear signaling on biological networks: The role of stochasticity and spectral clustering

    Science.gov (United States)

    Hernandez-Hernandez, Gonzalo; Myers, Jesse; Alvarez-Lacalle, Enrique; Shiferaw, Yohannes

    2017-03-01

    Signal transduction within biological cells is governed by networks of interacting proteins. Communication between these proteins is mediated by signaling molecules which bind to receptors and induce stochastic transitions between different conformational states. Signaling is typically a cooperative process which requires the occurrence of multiple binding events so that reaction rates have a nonlinear dependence on the amount of signaling molecule. It is this nonlinearity that endows biological signaling networks with robust switchlike properties which are critical to their biological function. In this study we investigate how the properties of these signaling systems depend on the network architecture. Our main result is that these nonlinear networks exhibit bistability where the network activity can switch between states that correspond to a low and high activity level. We show that this bistable regime emerges at a critical coupling strength that is determined by the spectral structure of the network. In particular, the set of nodes that correspond to large components of the leading eigenvector of the adjacency matrix determines the onset of bistability. Above this transition the eigenvectors of the adjacency matrix determine a hierarchy of clusters, defined by its spectral properties, which are activated sequentially with increasing network activity. We argue further that the onset of bistability occurs either continuously or discontinuously depending upon whether the leading eigenvector is localized or delocalized. Finally, we show that at low network coupling stochastic transitions to the active branch are also driven by the set of nodes that contribute more strongly to the leading eigenvector. However, at high coupling, transitions are insensitive to network structure since the network can be activated by stochastic transitions of a few nodes. Thus this work identifies important features of biological signaling networks that may underlie their biological

  11. Quantitative Models of Imperfect Deception in Network Security using Signaling Games with Evidence

    OpenAIRE

    Pawlick, Jeffrey; Zhu, Quanyan

    2017-01-01

    Deception plays a critical role in many interactions in communication and network security. Game-theoretic models called "cheap talk signaling games" capture the dynamic and information asymmetric nature of deceptive interactions. But signaling games inherently model undetectable deception. In this paper, we investigate a model of signaling games in which the receiver can detect deception with some probability. This model nests traditional signaling games and complete information Stackelberg ...

  12. 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.

  13. 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.

  14. Discovery, validation and characterization of Erbb4 and Nrg1 haplotypes using data from three genome-wide association studies of schizophrenia.

    Directory of Open Access Journals (Sweden)

    Zeynep Sena Agim

    Full Text Available Schizophrenia is one of the most common and complex neuropsychiatric disorders, which is contributed both by genetic and environmental exposures. Recently, it is shown that NRG1-mediated ErbB4 signalling regulates many important cellular and molecular processes such as cellular growth, differentiation and death, particularly in myelin-producing cells, glia and neurons. Recent association studies have revealed genomic regions of NRG1 and ERBB4, which are significantly associated with risk of developing schizophrenia; however, inconsistencies exist in terms of validation of findings between distinct populations. In this study, we aim to validate the previously identified regions and to discover novel haplotypes of NRG1 and ERBB4 using logistic regression models and Haploview analyses in three independent datasets from GWAS conducted on European subjects, namely, CATIE, GAIN and nonGAIN. We identified a significant 6-kb block in ERBB4 between chromosome locations 212,156,823 and 212,162,848 in CATIE and GAIN datasets (p = 0.0206 and 0.0095, respectively. In NRG1, a significant 25-kb block, between 32,291,552 and 32,317,192, was associated with risk of schizophrenia in all CATIE, GAIN, and nonGAIN datasets (p = 0.0005, 0.0589, and 0.0143, respectively. Fine mapping and FastSNP analysis of genetic variation located within significantly associated regions proved the presence of binding sites for several transcription factors such as SRY, SOX5, CEPB, and ETS1. In this study, we have discovered and validated haplotypes of ERBB4 and NRG1 in three independent European populations. These findings suggest that these haplotypes play an important role in the development of schizophrenia by affecting transcription factor binding affinity.

  15. Cluster synchronization transmission of different external signals in discrete uncertain network

    Science.gov (United States)

    Li, Chengren; Lü, Ling; Chen, Liansong; Hong, Yixuan; Zhou, Shuang; Yang, Yiming

    2018-07-01

    We research cluster synchronization transmissions of different external signals in discrete uncertain network. Based on the Lyapunov theorem, the network controller and the identification law of uncertain adjustment parameter are designed, and they are efficiently used to achieve the cluster synchronization and the identification of uncertain adjustment parameter. In our technical scheme, the network nodes in each cluster and the transmitted external signal can be different, and they allow the presence of uncertain parameters in the network. Especially, we are free to choose the clustering topologies, the cluster number and the node number in each cluster.

  16. 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...... also for implementing full signal path symmetry in real-time oscilloscopes to provide performance and signal fidelity (i.e. lower noise and jitter). In this paper the key digital signal processing (DSP) subsystems required to achieve signal slicing are surveyed. It also presents, for the first time...... 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....

  17. 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.

  18. Multiple-failure signal validation in nuclear power plants using artificial neural networks

    International Nuclear Information System (INIS)

    Fantoni, P.F.; Mazzola, A.

    1996-01-01

    The possibility of using a neural network to validate process signals during normal and abnormal plant conditions is explored. In boiling water reactor plants, signal validation is used to generate reliable thermal limits calculation and to supply reliable inputs to other computerized systems that support the operator during accident scenarios. The way that autoassociative neural networks can promptly detect faulty process signal measurements and produce a best estimate of the actual process values even in multifailure situations is shown. A method was developed to train the network for multiple sensor-failure detection, based on a random failure simulation algorithm. Noise was artificially added to the input to evaluate the network's ability to respond in a very low signal-to-noise ratio environment. Training and test data sets were simulated by the real-time transient simulator code APROS

  19. 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,

  20. 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....

  1. Research on the Wire Network Signal Prediction Based on the Improved NNARX Model

    Science.gov (United States)

    Zhang, Zipeng; Fan, Tao; Wang, Shuqing

    It is difficult to obtain accurately the wire net signal of power system's high voltage power transmission lines in the process of monitoring and repairing. In order to solve this problem, the signal measured in remote substation or laboratory is employed to make multipoint prediction to gain the needed data. But, the obtained power grid frequency signal is delay. In order to solve the problem, an improved NNARX network which can predict frequency signal based on multi-point data collected by remote substation PMU is describes in this paper. As the error curved surface of the NNARX network is more complicated, this paper uses L-M algorithm to train the network. The result of the simulation shows that the NNARX network has preferable predication performance which provides accurate real time data for field testing and maintenance.

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

    Science.gov (United States)

    White, Forest M.; Wolf-Yadlin, Alejandro

    2016-06-01

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

  3. [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.

  4. Erbb2 up-regulation of ADAM12 expression accelerates skin cancer progression.

    Science.gov (United States)

    Rao, Velidi H; Vogel, Kristen; Yanagida, Jodi K; Marwaha, Nitin; Kandel, Amrit; Trempus, Carol; Repertinger, Susan K; Hansen, Laura A

    2015-10-01

    Solar ultraviolet (UV) radiation can cause severe damage to the skin and is the primary cause of most skin cancer. UV radiation causes DNA damage leading to mutations and also activates the Erbb2/HER2 receptor through indirect mechanisms involving reactive oxygen species. We hypothesized that Erbb2 activation accelerates the malignant progression of UV-induced skin cancer. Following the induction of benign squamous papillomas by UV exposure of v-ras(Ha) transgenic Tg.AC mice, mice were treated topically with the Erbb2 inhibitor AG825 and tumor progression monitored. AG825 treatment reduced tumor volume, increased tumor regression, and delayed the development of malignant squamous cell carcinoma (SCC). Progression to malignancy was associated with increased Erbb2 and ADAM12 (A Disintegin And Metalloproteinase 12) transcripts and protein, while inhibition of Erbb2 blocked the increase in ADAM12 message upon malignant progression. Similarly, human SCC and SCC cell lines had increased ADAM12 protein and transcripts when compared to normal controls. To determine whether Erbb2 up-regulation of ADAM12 contributed to malignant progression of skin cancer, Erbb2 expression was modulated in cultured SCC cells using forced over-expression or siRNA targeting, demonstrating up-regulation of ADAM12 by Erbb2. Furthermore, ADAM12 transfection or siRNA targeting revealed that ADAM12 increased both the migration and invasion of cutaneous SCC cells. Collectively, these results suggest Erbb2 up-regulation of ADAM12 as a novel mechanism contributing to the malignant progression of UV-induced skin cancer. Inhibition of Erbb2/HER2 reduced tumor burden, increased tumor regression, and delayed the progression of benign skin tumors to malignant SCC in UV-exposed mice. Inhibition of Erbb2 suppressed the increase in metalloproteinase ADAM12 expression in skin tumors, which in turn increased migration and tumor cell invasiveness. © 2014 Wiley Periodicals, Inc.

  5. ERBB2 in Cat Mammary Neoplasias Disclosed a Positive Correlation between RNA and Protein Low Expression Levels: A Model for erbB-2 Negative Human Breast Cancer

    Science.gov (United States)

    Abreu, Rui M. V.; Bastos, Estela; Amorim, Irina; Gut, Ivo G.; Gärtner, Fátima; Chaves, Raquel

    2013-01-01

    Human ERBB2 is a proto-oncogene that codes for the erbB-2 epithelial growth factor receptor. In human breast cancer (HBC), erbB-2 protein overexpression has been repeatedly correlated with poor prognosis. In more recent works, underexpression of this gene has been described in HBC. Moreover, it is also recognised that oncogenes that are commonly amplified or deleted encompass point mutations, and some of these are associated with HBC. In cat mammary lesions (CMLs), the overexpression of ERBB2 (27%–59.6%) has also been described, mostly at the protein level and although cat mammary neoplasias are considered to be a natural model of HBC, molecular information is still scarce. In the present work, a cat ERBB2 fragment, comprising exons 10 to 15 (ERBB2_10–15) was achieved for the first time. Allelic variants and genomic haplotype analyses were also performed, and differences between normal and CML populations were observed. Three amino acid changes, corresponding to 3 non-synonymous genomic sequence variants that were only detected in CMLs, were proposed to damage the 3D structure of the protein. We analysed the cat ERBB2 gene at the DNA (copy number determination), mRNA (expression levels assessment) and protein levels (in extra- and intra protein domains) in CML samples and correlated the last two evaluations with clinicopathological features. We found a positive correlation between the expression levels of the ERBB2 RNA and erbB-2 protein, corresponding to the intracellular region. Additionally, we detected a positive correlation between higher mRNA expression and better clinical outcome. Our results suggest that the ERBB2 gene is post-transcriptionally regulated and that proteins with truncations and single point mutations are present in cat mammary neoplastic lesions. We would like to emphasise that the recurrent occurrence of low erbB-2 expression levels in cat mammary tumours, suggests the cat mammary neoplasias as a valuable model for erbB-2 negative HBC

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

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Zhong-Ke; Zhang, Xin-Wang; Du, Meng [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China); Jin, Ning-De, E-mail: ndjin@tju.edu.cn [School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)

    2013-02-04

    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.

  7. 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.

  8. 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.

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

    OpenAIRE

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

    2016-01-01

    Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelli...

  10. 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

    , 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...... 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...

  11. 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...... in astrocytic-neuronal networks. We reproduce local and global dynamical patterns observed experimentally....

  12. Filtering and spectral processing of 1-D signals using cellular neural networks

    NARCIS (Netherlands)

    Moreira-Tamayo, O.; Pineda de Gyvez, J.

    1996-01-01

    This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

  13. Novel signal multiplexing methods for integration of services in in-building broadband multimode fibre networks

    NARCIS (Netherlands)

    Koonen, A.M.J.

    2004-01-01

    Many different services with widely ranging signal characteristics are to be supported in in-building networks: fast data transport (e.g. Gbit Ethernet), video, high-Q audio, and control signals. These services may use wired or wireless connection to the end user. In order to support them in

  14. 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.

  15. Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

    Directory of Open Access Journals (Sweden)

    Li Wang

    2013-01-01

    Full Text Available Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.

  16. The genetic and regulatory architecture of ERBB3-type 1 diabetes susceptibility locus

    DEFF Research Database (Denmark)

    Kaur, Simranjeet; Mirza, Aashiq H.; Brorsson, Caroline Anna

    2016-01-01

    -producing INS-1E cells and the genetic and regulatory architecture of the ERBB3 locus to provide insights to how rs2292239 may confer disease susceptibility. rs2292239 strongly correlated with residual β-cell function and metabolic control in children with T1D. ERBB3 locus associated lncRNA (NONHSAG011351...

  17. 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...... and experimentally validated several NAMs, including PKCγ M501I and PKD1 D665N, which encode specificity switches analogous to the appearance of kinases de novo within the kinome. We discover mutant molecular logic gates, a drift toward phospho-threonine signaling, weakening of phosphorylation motifs, and kinase...

  18. A new traffic control design method for large networks with signalized intersections

    Science.gov (United States)

    Leininger, G. G.; Colony, D. C.; Seldner, K.

    1979-01-01

    The paper presents a traffic control design technique for application to large traffic networks with signalized intersections. It is shown that the design method adopts a macroscopic viewpoint to establish a new traffic modelling procedure in which vehicle platoons are subdivided into main stream queues and turning queues. Optimization of the signal splits minimizes queue lengths in the steady state condition and improves traffic flow conditions, from the viewpoint of the traveling public. Finally, an application of the design method to a traffic network with thirty-three signalized intersections is used to demonstrate the effectiveness of the proposed technique.

  19. 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.

  20. Neural network committees for finger joint angle estimation from surface EMG signals

    Directory of Open Access Journals (Sweden)

    Reddy Narender P

    2009-01-01

    Full Text Available Abstract Background In virtual reality (VR systems, the user's finger and hand positions are sensed and used to control the virtual environments. Direct biocontrol of VR environments using surface electromyography (SEMG signals may be more synergistic and unconstraining to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models. Methodology SEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-extension rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the parameters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects. Results There was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion. Conclusion Although hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals.

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

    Science.gov (United States)

    Young-Rae Cho; Yanan Xin; Speegle, Greg

    2015-01-01

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

  2. Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

    Science.gov (United States)

    2015-01-01

    Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN2 vs immediate flash freezing (iFF) in LN2 on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen. PMID:24927040

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

    NARCIS (Netherlands)

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

    2013-01-01

    The financial crisis clearly illustrated the importance of characterizing the level of 'systemic' risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze

  4. An analysis of mobile signalling in converged networks

    NARCIS (Netherlands)

    Oredope, A.; Exarchakos, G.; Menkovski, V.; Liotta, A.

    2009-01-01

    Converged networks are viewed as a multi-access platform on which fixed and mobile communications can be easily merged into a unified system thus enabling the deployment of rich and personalized services. In this paper, we provide the outcomes of our research into the challenges introduced by

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

    African Journals Online (AJOL)

    The article is devoted to the improvement of heat network calculation and diagnostics methods. Currently used instruments have many shortcomings for the diagnosis of pipelines, including low reliability of defect detection and subjective decision-making. The authors created an experimental stand, which allows to conduct ...

  6. 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.

  7. 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

  8. Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

    International Nuclear Information System (INIS)

    Jie, Li; Wan-Qing, Yu; Ding, Xu; Feng, Liu; Wei, Wang

    2009-01-01

    Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin–Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τ syn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τ syn , suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks. (cross-disciplinary physics and related areas of science and technology)

  9. A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

    Science.gov (United States)

    Yildirim, Özal

    2018-05-01

    Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was proposed for classifying electrocardiogram (ECG) signals. For this purpose, a new wavelet-based layer is implemented to generate ECG signal sequences. The ECG signals were decomposed into frequency sub-bands at different scales in this layer. These sub-bands are used as sequences for the input of LSTM networks. New network models that include unidirectional (ULSTM) and bidirectional (BLSTM) structures are designed for performance comparisons. Experimental studies have been performed for five different types of heartbeats obtained from the MIT-BIH arrhythmia database. These five types are Normal Sinus Rhythm (NSR), Ventricular Premature Contraction (VPC), Paced Beat (PB), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB). The results show that the DBLSTM-WS model gives a high recognition performance of 99.39%. It has been observed that the wavelet-based layer proposed in the study significantly improves the recognition performance of conventional networks. This proposed network structure is an important approach that can be applied to similar signal processing problems. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. 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.

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

    KAUST Repository

    Kim, Tae-Houn; Bö hmer, Maik; Hu, Honghong; Nishimura, Noriyuki; Schroeder, Julian I.

    2010-01-01

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

  12. 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

  13. The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

    Science.gov (United States)

    Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

    2009-02-01

    Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

  14. The neuregulin receptor ErbB-4 interacts with PDZ-containing proteins at neuronal synapses

    Science.gov (United States)

    Garcia, Rolando A. G.; Vasudevan, Kuzhalini; Buonanno, Andres

    2000-01-01

    Neuregulins regulate the expression of ligand- and voltage-gated channels in neurons and skeletal muscle by the activation of their cognate tyrosine kinase receptors, ErbB 1–4. The subcellular distribution and mechanisms that regulate the localization of ErbB receptors are unknown. We have found that ErbB receptors are present in brain subcellular fractions enriched for postsynaptic densities (PSD). The ErbB-4 receptor is unique among the ErbB proteins because its C-terminal tail (T-V-V) conforms to a sequence that binds to a protein motif known as the PDZ domain. Using the yeast two-hybrid system, we found that the C-terminal region of ErbB-4 interacts with the three related membrane-associated guanylate kinases (MAGUKs) PSD-95/SAP90, PSD-93/chapsyn-110, and SAP 102, which harbor three PDZ domains, as well as with β2-syntrophin, which has a single PDZ domain. As with N-methyl-d-aspartate (NMDA) receptors, ErbB4 interacts with the first two PDZ domains of PSD-95. Using coimmunoprecipitation assays, we confirmed the direct interactions between ErbB-4 and PSD-95 in transfected heterologous cells, as well as in vivo, where both proteins are coimmunoprecipitated from brain lysates. Moreover, evidence for colocalization of these proteins was also observed by immunofluorescence in cultured hippocampal neurons. ErbB-4 colocalizes with PSD-95 and NMDA receptors at a subset of excitatory synapses apposed to synaptophysin-positive presynaptic terminals. The capacity of ErbB receptors to interact with PDZ-domain proteins at cell junctions is conserved from invertebrates to mammals. As discussed, the interactions found between receptor tyrosine kinases and MAGUKs at neuronal synapses may have important implications for activity-dependent plasticity. PMID:10725395

  15. Foreground Subtraction and Signal reconstruction in redshifted 21cm Global Signal Experiments using Artificial Neural Networks

    Science.gov (United States)

    Choudhury, Madhurima; Datta, Abhirup

    2018-05-01

    Observations of HI 21cm transition line is a promising probe into the Dark Ages and Epoch-of-Reionization. Detection of this redshifted 21cm signal is one of the key science goal for several upcoming low-frequency radio telescopes like HERA, SKA and DARE. Other global signal experiments include EDGES, LEDA, BIGHORNS, SCI-HI, SARAS. One of the major challenges for the detection of this signal is the accuracy of the foreground source removal. Several novel techniques have been explored already to remove bright foregrounds from both interferometric as well as total power experiments. Here, we present preliminary results from our investigation on application of ANN to detect 21cm global signal amidst bright galactic foreground. Following the formalism of representing the global 21cm signal by 'tanh' model, this study finds that the global 21cm signal parameters can be accurately determined even in the presence of bright foregrounds represented by 3rd order log-polynomial or higher.

  16. Reconstruction of gastric slow wave from finger photoplethysmographic signal using radial basis function neural network.

    Science.gov (United States)

    Mohamed Yacin, S; Srinivasa Chakravarthy, V; Manivannan, M

    2011-11-01

    Extraction of extra-cardiac information from photoplethysmography (PPG) signal is a challenging research problem with significant clinical applications. In this study, radial basis function neural network (RBFNN) is used to reconstruct the gastric myoelectric activity (GMA) slow wave from finger PPG signal. Finger PPG and GMA (measured using Electrogastrogram, EGG) signals were acquired simultaneously at the sampling rate of 100 Hz from ten healthy subjects. Discrete wavelet transform (DWT) was used to extract slow wave (0-0.1953 Hz) component from the finger PPG signal; this slow wave PPG was used to reconstruct EGG. A RBFNN is trained on signals obtained from six subjects in both fasting and postprandial conditions. The trained network is tested on data obtained from the remaining four subjects. In the earlier study, we have shown the presence of GMA information in finger PPG signal using DWT and cross-correlation method. In this study, we explicitly reconstruct gastric slow wave from finger PPG signal by the proposed RBFNN-based method. It was found that the network-reconstructed slow wave provided significantly higher (P wave than the correlation obtained (≈0.7) between the PPG slow wave from DWT and the EEG slow wave. Our results showed that a simple finger PPG signal can be used to reconstruct gastric slow wave using RBFNN method.

  17. The ATM signaling network in development and disease

    Science.gov (United States)

    Stracker, Travis H.; Roig, Ignasi; Knobel, Philip A.; Marjanović, Marko

    2013-01-01

    The DNA damage response (DDR) rapidly recognizes DNA lesions and initiates the appropriate cellular programs to maintain genome integrity. This includes the coordination of cell cycle checkpoints, transcription, translation, DNA repair, metabolism, and cell fate decisions, such as apoptosis or senescence (Jackson and Bartek, 2009). DNA double-strand breaks (DSBs) represent one of the most cytotoxic DNA lesions and defects in their metabolism underlie many human hereditary diseases characterized by genomic instability (Stracker and Petrini, 2011; McKinnon, 2012). Patients with hereditary defects in the DDR display defects in development, particularly affecting the central nervous system, the immune system and the germline, as well as aberrant metabolic regulation and cancer predisposition. Central to the DDR to DSBs is the ataxia-telangiectasia mutated (ATM) kinase, a master controller of signal transduction. Understanding how ATM signaling regulates various aspects of the DDR and its roles in vivo is critical for our understanding of human disease, its diagnosis and its treatment. This review will describe the general roles of ATM signaling and highlight some recent advances that have shed light on the diverse roles of ATM and related proteins in human disease. PMID:23532176

  18. The ATM signaling network in development and disease

    Directory of Open Access Journals (Sweden)

    Travis H. Stracker

    2013-03-01

    Full Text Available The DNA damage response (DDR rapidly recognizes DNA lesions and initiates the appropriate cellular programs to maintain genome integrity. This includes the coordination of cell cycle checkpoints, transcription, translation, DNA repair, metabolism and cell fate decisions, such as apoptosis or senescence(Jackson and Bartek, 2009. DNA double-strand breaks (DSBs represent one of the most cytotoxic DNA lesions and defects in their metabolism underlie many human hereditary diseases characterized by genomic instability(Stracker and Petrini, 2011;McKinnon, 2012. Patients with hereditary defects in the DDR display defects in development, particularly affecting the central nervous system (CNS, the immune system and the germline, as well as aberrant metabolic regulation and cancer predisposition. Central to the DDR to DSBs is the ATM kinase, a master controller of signal transduction. Understanding how ATM signaling regulates various aspects of the DDR and its roles in vivo is critical for our understanding of human disease, its diagnosis and its treatment. This review will describe the general roles of ATM signaling and highlight some recent advances that have shed light on the diverse roles of ATM and related proteins in human disease.

  19. 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.

  20. A combination of Trastuzumab and 17-AAG induces enhanced ubiquitinylation and lysosomal pathway-dependent ErbB2 degradation and cytotoxicity in ErbB2-overexpressing breast cancer cells.

    Science.gov (United States)

    Raja, Srikumar M; Clubb, Robert J; Bhattacharyya, Mitra; Dimri, Manjari; Cheng, Hao; Pan, Wei; Ortega-Cava, Cesar; Lakku-Reddi, Alagarsamy; Naramura, Mayumi; Band, Vimla; Band, Hamid

    2008-10-01

    ErbB2 (or Her2/Neu) overexpression in breast cancer signifies poorer prognosis, yet it has provided an avenue for targeted therapy as demonstrated by the success of the humanized monoclonal antibody Trastuzumab (Herceptin). Resistance to Trastuzumab and eventual failure in most cases, however, necessitate alternate ErbB2-targeted therapies. HSP90 inhibitors such as 17-allylaminodemethoxygeldanamycin (17-AAG), potently downregulate the cell surface ErbB2. While the precise mechanisms of Trastuzumab or 17-AAG action remain unclear, ubiquitinylation-dependent proteasomal or lysosomal degradation of ErbB2 appears to play a substantial role. As Trastuzumab and 17-AAG induce the recruitment of distinct E3 ubiquitin ligases, Cbl and CHIP respectively, to ErbB2, we hypothesized that 17-AAG and Trastuzumab combination could induce a higher level of ubiquitinylation and downregulation of ErbB2 as compared to single drug treatments. We present biochemical and cell biological evidence that combined 17-AAG and Trastuzumab treatment of ErbB2-overexpressing breast cancer cell lines leads to enhanced ubiquitinylation, downregulation from the cell surface and lysosomal degradation of ErbB2. Importantly, combined 17-AAG and Trastuzumab treatment induced synergistic growth arrest and cell death specifically in ErbB2-overexpressing but not in ErbB2-low breast cancer cells. Our results suggest the 17-AAG and Trastuzumab combination as a mechanism-based combinatorial targeted therapy for ErbB2-overexpressing breast cancer patients.

  1. 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

  2. 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.

  3. Analysis of metastasis associated signal regulatory network in colorectal cancer.

    Science.gov (United States)

    Qi, Lu; Ding, Yanqing

    2018-06-18

    Metastasis is a key factor that affects the survival and prognosis of colorectal cancer patients. To elucidate molecular mechanism associated with the metastasis of colorectal cancer, genes related to the metastasis time of colorectal cancer were screened. Then, a network was constructed with this genes. Data was obtained from colorectal cancer expression profile. Molecular mechanism elucidated the time of tumor metastasis and the expression of genes related to colorectal cancer. We found that metastasis-promoting and metastasis-inhibiting networks included protein hubs of high connectivity. These protein hubs were components of organelles. Some ribosomal proteins promoted the metastasis of colorectal cancer. In some components of organelles, such as proteasomes, mitochondrial ribosome, ATP synthase, and splicing factors, the metastasis of colorectal cancer was inhibited by some sections of these organelles. After performing survival analysis of proteins in organelles, joint survival curve of proteins was constructed in ribosomal network. This joint survival curve showed metastasis was promoted in patients with colorectal cancer (P = 0.0022939). Joint survival curve of proteins was plotted against proteasomes (P = 7 e-07), mitochondrial ribosome (P = 0.0001157), ATP synthase (P = 0.0001936), and splicing factors (P = 1.35e-05). These curves indicate that metastasis of colorectal cancer can be inhibited. After analyzing proteins that bind with organelle components, we also found that some proteins were associated with the time of colorectal cancer metastasis. Hence, different cellular components play different roles in the metastasis of colorectal cancer. Copyright © 2018 Elsevier Inc. All rights reserved.

  4. Tolerance to drought and salt stress in plants: Unraveling the signaling networks

    Directory of Open Access Journals (Sweden)

    Dortje eGolldack

    2014-04-01

    Full Text Available Tolerance of plants to abiotic stressors such as drought and salinity is triggered by complex multicomponent signaling pathways to restore cellular homeostasis and promote survival. Major plant transcription factor families such as bZIP, NAC, AP2/ERF and MYB orchestrate regulatory networks underlying abiotic stress tolerance. Sucrose nonfermenting 1-related protein kinase 2 (SnRK2 and MAPK pathways contribute to initiation of stress adaptive downstream responses and promote plant growth and development. As a convergent point of multiple abiotic cues, cellular effects of environmental stresses are not only imbalances of ionic and osmotic homeostasis but also impaired photosynthesis, cellular energy depletion, and redox imbalances. Recent evidence of regulatory systems that link sensing and signaling of environmental conditions and the intracellular redox status have shed light on interfaces of stress and energy signaling. ROS (reactive oxygen species cause severe cellular damage by peroxidation and de-esterification of membrane lipids, however, current models also define a pivotal signaling function of ROS in triggering tolerance against stress. Recent research advances suggest and support a regulatory role of ROS in the cross talks of stress triggered hormonal signaling such as the abscisic acid (ABA pathway and endogenously induced redox and metabolite signals. Here, we discuss and review the versatile molecular convergence in the abiotic stress responsive signaling networks in the context of ROS and lipid derived signals and the specific role of stomatal signaling.

  5. The Role of Notch Signaling Pathway in Breast Cancer Pathogenesis

    Science.gov (United States)

    2005-07-01

    breast cancer cells, I tested whether ErbB2 overexpression will cooperate with Notch in HMLE cells. While overexpression of activated Notch1 failed to...tyrosine kinase upstream of Ras normally found overexpressed in many breast cancers , also failed to transform HMLE cells. These observations suggested...cooperation between Notch1IC and ErbB2 signaling in transforming HMLE cells. Breast cancers typically do not harbor oncogenic Ras mutations; nevertheless

  6. 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.

  7. Cisplatin ototoxicity involves cytokines and STAT6 signaling network

    Institute of Scientific and Technical Information of China (English)

    Hyung-Jin Kim; Jeong-Dug Sul; Channy Park; Sang-Young Chung; Sung-Kyun Moon; David J Lim; Hong-Seob So; Raekil Park; Gi-Su Oh; Jeong-Han Lee; Ah-Ra Lyu; Hye-Min Ji; Sang-Heon Lee; Jeho Song; Sung-Joo Park; Yong-Ouk You

    2011-01-01

    We herein investigated the role of the STAT signaling cascade in the production of pro-inflammatory cytokines and cisplatin ototoxicity. A significant hearing impairment caused by cisplatin injection was observed in Balb/c (wild type,WT) and STAT4-/-,but not in STAT6-/- mice. Moreover,the expression levels of the protein and mRNA of proinflammatory cytokines,including TNF-α,IL-1β,and IL-6,were markedly increased in the serum and cochlea of WT and STAT4+,but not STAT6-/- mice. Organotypic culture revealed that the shape of stereocilia bundles and arrays of sensory hair cell layers in the organ of Corti from STAT6-/- mice were intact after treatment with cisplatin,whereas those from WT and STAT4-/- mice were highly distorted and disarrayed after the treatment. Cisplatin induced the phosphorylation of STAT6 in HEI-OC1 auditory cells,and the knockdown of STAT6 by STAT6-specific siRNA significantly protected HEI-OC1 auditory cells from cisplatin-induced cell death and inhibited pro-inflammatory cytokine production. We further demonstrated that IL-4 and IL-13 induced by cisplatin modulated the phosphorylation of STAT6 by binding with IL-4 receptor alpha and IL-13Rα1. These findings suggest that STAT6 signaling plays a pivotal role in cisplatin-mediated pro-inflammatory cytokine production and ototoxicity.

  8. 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 (pneuronal firing in the trigeminocervical-complex was significantly inhibited by insulin (pmetabolic homeostasis may occur through disturbed glucose regulation and a transient hypothalamic dysfunction. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  9. 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.

  10. Noise in Neural Networks: Thresholds, Hysteresis, and Neuromodulation of Signal-To-Noise

    Science.gov (United States)

    Keeler, James D.; Pichler, Elgar E.; Ross, John

    1989-03-01

    We study a neural-network model including Gaussian noise, higher-order neuronal interactions, and neuromodulation. For a first-order network, there is a threshold in the noise level (phase transition) above which the network displays only disorganized behavior and critical slowing down near the noise threshold. The network can tolerate more noise if it has higher-order feedback interactions, which also lead to hysteresis and multistability in the network dynamics. The signal-to-noise ratio can be adjusted in a biological neural network by neuromodulators such as norepinephrine. Comparisons are made to experimental results and further investigations are suggested to test the effects of hysteresis and neuromodulation in pattern recognition and learning. We propose that norepinephrine may ``quench'' the neural patterns of activity to enhance the ability to learn details.

  11. Experimental and computational tools for analysis of signaling networks in primary cells

    DEFF Research Database (Denmark)

    Schoof, Erwin M; Linding, Rune

    2014-01-01

    Cellular information processing in signaling networks forms the basis of responses to environmental stimuli. At any given time, cells receive multiple simultaneous input cues, which are processed and integrated to determine cellular responses such as migration, proliferation, apoptosis, or differ......Cellular information processing in signaling networks forms the basis of responses to environmental stimuli. At any given time, cells receive multiple simultaneous input cues, which are processed and integrated to determine cellular responses such as migration, proliferation, apoptosis......; this information is critical when trying to elucidate key proteins involved in specific cellular responses. Here, methods to generate high-quality quantitative phosphorylation data from cell lysates originating from primary cells, and how to analyze the generated data to construct quantitative signaling network...

  12. Signal reconstruction in wireless sensor networks based on a cubature Kalman particle filter

    International Nuclear Information System (INIS)

    Huang Jin-Wang; Feng Jiu-Chao

    2014-01-01

    For solving the issues of the signal reconstruction of nonlinear non-Gaussian signals in wireless sensor networks (WSNs), a new signal reconstruction algorithm based on a cubature Kalman particle filter (CKPF) is proposed in this paper. We model the reconstruction signal first and then use the CKPF to estimate the signal. The CKPF uses a cubature Kalman filter (CKF) to generate the importance proposal distribution of the particle filter and integrates the latest observation, which can approximate the true posterior distribution better. It can improve the estimation accuracy. CKPF uses fewer cubature points than the unscented Kalman particle filter (UKPF) and has less computational overheads. Meanwhile, CKPF uses the square root of the error covariance for iterating and is more stable and accurate than the UKPF counterpart. Simulation results show that the algorithm can reconstruct the observed signals quickly and effectively, at the same time consuming less computational time and with more accuracy than the method based on UKPF. (general)

  13. Communication efficiency and congestion of signal traffic in large-scale brain networks.

    Science.gov (United States)

    Mišić, Bratislav; Sporns, Olaf; McIntosh, Anthony R

    2014-01-01

    The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a "rich club" of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication.

  14. Recognition of NEMP and LEMP signals based on auto-regression model and artificial neutral network

    International Nuclear Information System (INIS)

    Li Peng; Song Lijun; Han Chao; Zheng Yi; Cao Baofeng; Li Xiaoqiang; Zhang Xueqin; Liang Rui

    2010-01-01

    Auto-regression (AR) model, one power spectrum estimation method of stationary random signals, and artificial neutral network were adopted to recognize nuclear and lightning electromagnetic pulses. Self-correlation function and Burg algorithms were used to acquire the AR model coefficients as eigenvalues, and BP artificial neural network was introduced as the classifier with different numbers of hidden layers and hidden layer nodes. The results show that AR model is effective in those signals, feature extraction, and the Burg algorithm is more effective than the self-correlation function algorithm. (authors)

  15. 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.

  16. Using neural networks to enhance the Higgs boson signal at hadron colliders

    International Nuclear Information System (INIS)

    Field, R.D.; Kanev, Y.; Tayebnejad, M.; Griffin, P.A.

    1995-01-01

    Neural networks are used to help distinguish the ZZ → ell + ell - -jet-jet signal produced by the decay of a 400 GeV Higgs boson at a proton-proton collider energy of 15 TeV from the ''ordinary'' QCD Z + jets background. The ideal case where only one event at a time enters the detector (no pile-up) and the case of multiple interactions per beam crossing (pile-up) are examined. In both cases, when used in conjunction with the standard cuts, neural networks provide an additional signal to background enhancement

  17. 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...... difference experiment and demonstrates high accuracy for small wall thickness differences. Results from the experiment are compared with results obtained by a false killer whale (pseudorca crassidens)....

  18. Optimal Signal Design for Mixed Equilibrium Networks with Autonomous and Regular Vehicles

    Directory of Open Access Journals (Sweden)

    Nan Jiang

    2017-01-01

    Full Text Available A signal design problem is studied for efficiently managing autonomous vehicles (AVs and regular vehicles (RVs simultaneously in transportation networks. AVs and RVs move on separate lanes and two types of vehicles share the green times at the same intersections. The signal design problem is formulated as a bilevel program. The lower-level model describes a mixed equilibrium where autonomous vehicles follow the Cournot-Nash (CN principle and RVs follow the user equilibrium (UE principle. In the upper-level model, signal timings are optimized at signalized intersections to allocate appropriate green times to both autonomous and RVs to minimize system travel cost. The sensitivity analysis based method is used to solve the bilevel optimization model. Various signal control strategies are evaluated through numerical examples and some insightful findings are obtained. It was found that the number of phases at intersections should be reduced for the optimal control of the AVs and RVs in the mixed networks. More importantly, incorporating AVs into the transportation network would improve the system performance due to the value of AV technologies in reducing random delays at intersections. Meanwhile, travelers prefer to choose AVs when the networks turn to be congested.

  19. The behaviour of basic autocatalytic signalling modules in isolation and embedded in networks

    Energy Technology Data Exchange (ETDEWEB)

    Krishnan, J. [Department of Chemical Engineering, Centre for Process Systems Engineering, Institute for Systems and Synthetic Biology, Imperial College London, London SW7 2AZ (United Kingdom); Mois, Kristina; Suwanmajo, Thapanar [Department of Chemical Engineering, Centre for Process Systems Engineering, Imperial College London, London SW7 2AZ (United Kingdom)

    2014-11-07

    In this paper, we examine the behaviour of basic autocatalytic feedback modules involving a species catalyzing its own production, either directly or indirectly. We first perform a systematic study of the autocatalytic feedback module in isolation, examining the effect of different factors, showing how this module is capable of exhibiting monostable threshold and bistable switch-like behaviour. We then study the behaviour of this module embedded in different kinds of basic networks including (essentially) irreversible cycles, open and closed reversible chains, and networks with additional feedback. We study the behaviour of the networks deterministically and also stochastically, using simulations, analytical work, and bifurcation analysis. We find that (i) there are significant differences between the behaviour of this module in isolation and in a network: thresholds may be altered or destroyed and bistability may be destroyed or even induced, even when the ambient network is simple. The global characteristics and topology of this network and the position of the module in the ambient network can play important and unexpected roles. (ii) There can be important differences between the deterministic and stochastic dynamics of the module embedded in networks, which may be accentuated by the ambient network. This provides new insights into the functioning of such enzymatic modules individually and as part of networks, with relevance to other enzymatic signalling modules as well.

  20. Forecast of TEXT plasma disruptions using soft X rays as input signal in a neural network

    International Nuclear Information System (INIS)

    Vannucci, A.; Oliveira, K.A.; Tajima, T.

    1999-01-01

    A feedforward neural network with two hidden layers is used to forecast major and minor disruptive instabilities in TEXT tokamak discharges. Using the experimental data of soft X ray signals as input data, the neural network is trained with one disruptive plasma discharge, and a different disruptive discharge is used for validation. After being properly trained, the networks, with the same set of weights, are used to forecast disruptions in two other plasma discharges. It is observed that the neural network is able to predict the occurrence of a disruption more than 3 ms in advance. This time interval is almost 3 times longer than the one already obtained previously when a magnetic signal from a Mirnov coil was used to feed the neural networks. Visually no indication of an upcoming disruption is seen from the experimental data this far back from the time of disruption. Finally, by observing the predictive behaviour of the network for the disruptive discharges analysed and comparing the soft X ray data with the corresponding magnetic experimental signal, it is conjectured about where inside the plasma column the disruption first started. (author)

  1. Increased level of phosphorylated akt measured by chemiluminescence-linked immunosorbent assay is a predictor of poor prognosis in primary breast cancer overexpressing ErbB-2

    International Nuclear Information System (INIS)

    Cicenas, Jonas; Urban, Patrick; Vuaroqueaux, Vincent; Labuhn, Martin; Küng, Willy; Wight, Edward; Mayhew, Mark; Eppenberger, Urs; Eppenberger-Castori, Serenella

    2005-01-01

    Akt1, Akt2 and Akt3 kinases are downstream components of phosphoinositol 3-kinase derived signals from receptor tyrosine kinases, which influence cell growth, proliferation and survival. Akt2 overexpression and amplification have been described in breast, ovarian and pancreatic cancers. The present study was designed to investigate the prognostic significance of activated Akt in primary breast cancer and its association with other tumour biomarkers. Using a two-site chemiluminescence-linked immunosorbent assay, we measured the quantitative expression levels of total phosphorylated (P-S473) Akt (Akt1/Akt2/Akt3) on cytosol fractions obtained from fresh frozen tissue samples of 156 primary breast cancer patients. Akt phosphorylation was not associated with nodal status or ErbB-2 protein expression levels. High levels of phosphorylated Akt correlated (P < 0.01) with poor prognosis, and the significance of this correlation increased (P < 0.001) in the subset of patients with ErbB-2 overexpressing tumours. In addition, phosphorylated Akt was found to be associated with mRNA expression levels of several proliferation markers (e.g. thymidylate synthase), measured using quantitative real-time RT-PCR. Our findings demonstrate that, in breast cancer patients, Akt activation is associated with tumour proliferation and poor prognosis, particularly in the subset of patients with ErbB2-overexpressing tumours

  2. Selective Inhibition of Tumor Growth by Clonal NK Cells Expressing an ErbB2/HER2-Specific Chimeric Antigen Receptor

    Science.gov (United States)

    Schönfeld, Kurt; Sahm, Christiane; Zhang, Congcong; Naundorf, Sonja; Brendel, Christian; Odendahl, Marcus; Nowakowska, Paulina; Bönig, Halvard; Köhl, Ulrike; Kloess, Stephan; Köhler, Sylvia; Holtgreve-Grez, Heidi; Jauch, Anna; Schmidt, Manfred; Schubert, Ralf; Kühlcke, Klaus; Seifried, Erhard; Klingemann, Hans G; Rieger, Michael A; Tonn, Torsten; Grez, Manuel; Wels, Winfried S

    2015-01-01

    Natural killer (NK) cells are an important effector cell type for adoptive cancer immunotherapy. Similar to T cells, NK cells can be modified to express chimeric antigen receptors (CARs) to enhance antitumor activity, but experience with CAR-engineered NK cells and their clinical development is still limited. Here, we redirected continuously expanding and clinically usable established human NK-92 cells to the tumor-associated ErbB2 (HER2) antigen. Following GMP-compliant procedures, we generated a stable clonal cell line expressing a humanized CAR based on ErbB2-specific antibody FRP5 harboring CD28 and CD3ζ signaling domains (CAR 5.28.z). These NK-92/5.28.z cells efficiently lysed ErbB2-expressing tumor cells in vitro and exhibited serial target cell killing. Specific recognition of tumor cells and antitumor activity were retained in vivo, resulting in selective enrichment of NK-92/5.28.z cells in orthotopic breast carcinoma xenografts, and reduction of pulmonary metastasis in a renal cell carcinoma model, respectively. γ-irradiation as a potential safety measure for clinical application prevented NK cell replication, while antitumor activity was preserved. Our data demonstrate that it is feasible to engineer CAR-expressing NK cells as a clonal, molecularly and functionally well-defined and continuously expandable cell therapeutic agent, and suggest NK-92/5.28.z cells as a promising candidate for use in adoptive cancer immunotherapy. PMID:25373520

  3. 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

  4. 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.

  5. Sensor signal analysis by neural networks for surveillance in nuclear reactors

    International Nuclear Information System (INIS)

    Keyvan, S.; Rabelo, L.C.

    1992-01-01

    The application of neural networks as a tool for reactor diagnostics is examined here. Reactor pump signals utilized in a wear-out monitoring system developed for early detection of the degradation of a pump shaft are analyzed as a semi-benchmark test to study the feasibility of neural networks for monitoring and surveillance in nuclear reactors. The Adaptive Resonance Theory (ART 2 and ART 2-A) paradigm of neural networks is applied in this study. The signals are collected signals as well as generated signals simulating the wear progress. The wear-out monitoring system applies noise analysis techniques, and is capable of distinguishing these signals apart and providing a measure of the progress of the degradation. This paper presents the results of the analysis of these data, and provides an evaluation on the performance of ART 2-A and ART 2 for reactor signal analysis. The selection of ART 2 is due to its desired design principles such as unsupervised learning, stability-plasticity, search-direct access, and the match-reset tradeoffs

  6. 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.

  7. Transduction motif analysis of gastric cancer based on a human signaling network

    Energy Technology Data Exchange (ETDEWEB)

    Liu, G.; Li, D.Z.; Jiang, C.S.; Wang, W. [Fuzhou General Hospital of Nanjing Command, Department of Gastroenterology, Fuzhou, China, Department of Gastroenterology, Fuzhou General Hospital of Nanjing Command, Fuzhou (China)

    2014-04-04

    To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR, MAPK14, BCL2L1, KRT18, PTPN6, CASP3, TGFBR2, AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.

  8. 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.

  9. 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....

  10. 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.

  11. Attractor Structures of Signaling Networks: Consequences of Different Conformational Barcode Dynamics and Their Relations to Network-Based Drug Design.

    Science.gov (United States)

    Szalay, Kristóf Z; Nussinov, Ruth; Csermely, Peter

    2014-06-01

    Conformational barcodes tag functional sites of proteins and are decoded by interacting molecules transmitting the incoming signal. Conformational barcodes are modified by all co-occurring allosteric events induced by post-translational modifications, pathogen, drug binding, etc. We argue that fuzziness (plasticity) of conformational barcodes may be increased by disordered protein structures, by integrative plasticity of multi-phosphorylation events, by increased intracellular water content (decreased molecular crowding) and by increased action of molecular chaperones. This leads to increased plasticity of signaling and cellular networks. Increased plasticity is both substantiated by and inducing an increased noise level. Using the versatile network dynamics tool, Turbine (www.turbine.linkgroup.hu), here we show that the 10 % noise level expected in cellular systems shifts a cancer-related signaling network of human cells from its proliferative attractors to its largest, apoptotic attractor representing their health-preserving response in the carcinogen containing and tumor suppressor deficient environment modeled in our study. Thus, fuzzy conformational barcodes may not only make the cellular system more plastic, and therefore more adaptable, but may also stabilize the complex system allowing better access to its largest attractor. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Best Signal Quality in Cellular Networks: Asymptotic Properties and Applications to Mobility Management in Small Cell Networks

    Directory of Open Access Journals (Sweden)

    Baccelli François

    2010-01-01

    Full Text Available The quickly increasing data traffic and the user demand for a full coverage of mobile services anywhere and anytime are leading mobile networking into a future of small cell networks. However, due to the high-density and randomness of small cell networks, there are several technical challenges. In this paper, we investigate two critical issues: best signal quality and mobility management. Under the assumptions that base stations are uniformly distributed in a ring-shaped region and that shadowings are lognormal, independent, and identically distributed, we prove that when the number of sites in the ring tends to infinity, then (i the maximum signal strength received at the center of the ring tends in distribution to a Gumbel distribution when properly renormalized, and (ii it is asymptotically independent of the interference. Using these properties, we derive the distribution of the best signal quality. Furthermore, an optimized random cell scanning scheme is proposed, based on the evaluation of the optimal number of sites to be scanned for maximizing the user data throughput.

  13. 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

  14. Pharmacodynamic Assay Panel for Monitoring Phospho-Signaling Networks | Office of Cancer Clinical Proteomics Research

    Science.gov (United States)

    The DNA damage response (DDR) is a highly regulated signal transduction network that orchestrates the temporal and spatial organization of protein complexes required to repair (or tolerate) DNA damage (e.g., nucleotide excision repair, base excision repair, homologous recombination, non-homologous end joining, post-replication repair).

  15. 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.

  16. 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)

  17. Anomalous Signal Detection in ELF Band Electromagnetic Wave using Multi-layer Neural Network with Wavelet Decomposition

    Science.gov (United States)

    Itai, Akitoshi; Yasukawa, Hiroshi; Takumi, Ichi; Hata, Masayasu

    It is well known that electromagnetic waves radiated from the earth's crust are useful for predicting earthquakes. We analyze the electromagnetic waves received at the extremely low frequency band of 223Hz. These observed signals contain the seismic radiation from the earth's crust, but also include several undesired signals. Our research focuses on the signal detection technique to identify an anomalous signal corresponding to the seismic radiation in the observed signal. Conventional anomalous signal detections lack a wide applicability due to their assumptions, e.g. the digital data have to be observed at the same time or the same sensor. In order to overcome the limitation related to the observed signal, we proposed the anomalous signals detection based on a multi-layer neural network which is trained by digital data observed during a span of a day. In the neural network approach, training data do not need to be recorded at the same place or the same time. However, some noises, which have a large amplitude, are detected as the anomalous signal. This paper develops a multi-layer neural network to decrease the false detection of the anomalous signal from the electromagnetic wave. The training data for the proposed network is the decomposed signal of the observed signal during several days, since the seismic radiations are often recorded from several days to a couple of weeks. Results show that the proposed neural network is useful to achieve the accurate detection of the anomalous signal that indicates seismic activity.

  18. Responses to olfactory signals reflect network structure of flower-visitor interactions.

    Science.gov (United States)

    Junker, Robert R; Höcherl, Nicole; Blüthgen, Nico

    2010-07-01

    1. Network analyses provide insights into the diversity and complexity of ecological interactions and have motivated conclusions about community stability and co-evolution. However, biological traits and mechanisms such as chemical signals regulating the interactions between individual species--the microstructure of a network--are poorly understood. 2. We linked the responses of receivers (flower visitors) towards signals (flower scent) to the structure of a highly diverse natural flower-insect network. For each interaction, we define link temperature--a newly developed metric--as the deviation of the observed interaction strength from neutrality, assuming that animals randomly interact with flowers. 3. Link temperature was positively correlated to the specific visitors' responses to floral scents, experimentally examined in a mobile olfactometer. Thus, communication between plants and consumers via phytochemical signals reflects a significant part of the microstructure in a complex network. Negative as well as positive responses towards floral scents contributed to these results, where individual experience was important apart from innate behaviour. 4. Our results indicate that: (1) biological mechanisms have a profound impact on the microstructure of complex networks that underlies the outcome of aggregate statistics, and (2) floral scents act as a filter, promoting the visitation of some flower visitors, but also inhibiting the visitation of others.

  19. Crystallization and preliminary crystallographic studies of the single-chain variable fragment of antibody chA21 in complex with an N-terminal fragment of ErbB2

    International Nuclear Information System (INIS)

    Liu, Yang; Zhou, Huihao; Zhu, Juanjuan; Gao, Yongxiang; Niu, Liwen; Liu, Jing; Teng, Maikun

    2009-01-01

    An antibody–antigen complex consisting of a single-chain variable fragment of the potential therapeutic antibody chA21 and an N-terminal fragment (residues 1–192) of the human ErbB2 extracellular domain was expressed, purified and crystallized. X-ray diffraction data were collected to 2.45 Å resolution. ErbB2 is a transmembrane tyrosine kinase, the overexpression of which causes abnormality and disorder in cell signalling and leads to cell transformation. Previously, an anti-ErbB2 single-chain chimeric antibody chA21 that specifically inhibits the growth of ErbB2-overexpressing cancer cells in vitro and in vivo was developed. Here, an antibody–antigen complex consisting of the single-chain variable fragment (scFv) of chA21 and an N-terminal fragment (residues 1–192, named EP I) of the ErbB2 extracellular domain was crystallized using the sitting-drop vapour-diffusion method. An X-ray diffraction data set was collected to 2.45 Å resolution from a single flash-cooled crystal; the crystal belonged to space group P2 1 2 1 2 1

  20. 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

  1. 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

  2. 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)

  3. 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.

  4. 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

  5. Transfer of optical signals around bends in two-dimensional linear photonic networks

    International Nuclear Information System (INIS)

    Nikolopoulos, G M

    2015-01-01

    The ability to navigate light signals in two-dimensional networks of waveguide arrays is a prerequisite for the development of all-optical integrated circuits for information processing and networking. In this article, we present a theoretical analysis of bending losses in linear photonic lattices with engineered couplings, and discuss possible ways for their minimization. In contrast to previous work in the field, the lattices under consideration operate in the linear regime, in the sense that discrete solitons cannot exist. The present results suggest that the functionality of linear waveguide networks can be extended to operations that go beyond the recently demonstrated point-to-point transfer of signals, such as blocking, routing, logic functions, etc. (paper)

  6. An input feature selection method applied to fuzzy neural networks for signal esitmation

    International Nuclear Information System (INIS)

    Na, Man Gyun; Sim, Young Rok

    2001-01-01

    It is well known that the performance of a fuzzy neural networks strongly depends on the input features selected for its training. In its applications to sensor signal estimation, there are a large number of input variables related with an output. As the number of input variables increases, the training time of fuzzy neural networks required increases exponentially. Thus, it is essential to reduce the number of inputs to a fuzzy neural networks and to select the optimum number of mutually independent inputs that are able to clearly define the input-output mapping. In this work, principal component analysis (PAC), genetic algorithms (GA) and probability theory are combined to select new important input features. A proposed feature selection method is applied to the signal estimation of the steam generator water level, the hot-leg flowrate, the pressurizer water level and the pressurizer pressure sensors in pressurized water reactors and compared with other input feature selection methods

  7. A KST framework for correlation network construction from time series signals

    Science.gov (United States)

    Qi, Jin-Peng; Gu, Quan; Zhu, Ying; Zhang, Ping

    2018-04-01

    A KST (Kolmogorov-Smirnov test and T statistic) method is used for construction of a correlation network based on the fluctuation of each time series within the multivariate time signals. In this method, each time series is divided equally into multiple segments, and the maximal data fluctuation in each segment is calculated by a KST change detection procedure. Connections between each time series are derived from the data fluctuation matrix, and are used for construction of the fluctuation correlation network (FCN). The method was tested with synthetic simulations and the result was compared with those from using KS or T only for detection of data fluctuation. The novelty of this study is that the correlation analyses was based on the data fluctuation in each segment of each time series rather than on the original time signals, which would be more meaningful for many real world applications and for analysis of large-scale time signals where prior knowledge is uncertain.

  8. Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

    Science.gov (United States)

    Acharya, U Rajendra; Oh, Shu Lih; Hagiwara, Yuki; Tan, Jen Hong; Adeli, Hojjat

    2017-09-27

    An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical activity of the brain. Traditionally, neurologists employ direct visual inspection to identify epileptiform abnormalities. This technique can be time-consuming, limited by technical artifact, provides variable results secondary to reader expertise level, and is limited in identifying abnormalities. Therefore, it is essential to develop a computer-aided diagnosis (CAD) system to automatically distinguish the class of these EEG signals using machine learning techniques. This is the first study to employ the convolutional neural network (CNN) for analysis of EEG signals. In this work, a 13-layer deep convolutional neural network (CNN) algorithm is implemented to detect normal, preictal, and seizure classes. The proposed technique achieved an accuracy, specificity, and sensitivity of 88.67%, 90.00% and 95.00%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. 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

  10. 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

  11. 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.

  12. Investigation on changes of modularity and robustness by edge-removal mutations in signaling networks.

    Science.gov (United States)

    Truong, Cong-Doan; Kwon, Yung-Keun

    2017-12-21

    Biological networks consisting of molecular components and interactions are represented by a graph model. There have been some studies based on that model to analyze a relationship between structural characteristics and dynamical behaviors in signaling network. However, little attention has been paid to changes of modularity and robustness in mutant networks. In this paper, we investigated the changes of modularity and robustness by edge-removal mutations in three signaling networks. We first observed that both the modularity and robustness increased on average in the mutant network by the edge-removal mutations. However, the modularity change was negatively correlated with the robustness change. This implies that it is unlikely that both the modularity and the robustness values simultaneously increase by the edge-removal mutations. Another interesting finding is that the modularity change was positively correlated with the degree, the number of feedback loops, and the edge betweenness of the removed edges whereas the robustness change was negatively correlated with them. We note that these results were consistently observed in randomly structure networks. Additionally, we identified two groups of genes which are incident to the highly-modularity-increasing and the highly-robustness-decreasing edges with respect to the edge-removal mutations, respectively, and observed that they are likely to be central by forming a connected component of a considerably large size. The gene-ontology enrichment of each of these gene groups was significantly different from the rest of genes. Finally, we showed that the highly-robustness-decreasing edges can be promising edgetic drug-targets, which validates the usefulness of our analysis. Taken together, the analysis of changes of robustness and modularity against edge-removal mutations can be useful to unravel novel dynamical characteristics underlying in signaling networks.

  13. Chimeric DNA Vaccines against ErbB2{sup +} Carcinomas: From Mice to Humans

    Energy Technology Data Exchange (ETDEWEB)

    Quaglino, Elena; Riccardo, Federica; Macagno, Marco; Bandini, Silvio; Cojoca, Rodica; Ercole, Elisabetta [Molecular Biotechnology Center, Department of Clinical and Biological Sciences, University of Turin, 10126 Turin (Italy); Amici, Augusto [Department of Molecular Cellular and Animal Biology, University of Camerino, 62032 Camerino (Italy); Cavallo, Federica, E-mail: federica.cavallo@unito.it [2 Department of Molecular Cellular and Animal Biology, University of Camerino, 62032 Camerino (Italy)

    2011-08-10

    DNA vaccination exploits a relatively simple and flexible technique to generate an immune response against microbial and tumor-associated antigens (TAAs). Its effectiveness is enhanced by the application of an electrical shock in the area of plasmid injection (electroporation). In our studies we exploited a sophisticated electroporation device approved for clinical use (Cliniporator, IGEA, Carpi, Italy). As the target antigen is an additional factor that dramatically modulates the efficacy of a vaccine, we selected ErbB2 receptor as a target since it is an ideal oncoantigen. It is overexpressed on the cell membrane by several carcinomas for which it plays an essential role in driving their progression. Most oncoantigens are self-tolerated molecules. To circumvent immune tolerance we generated two plasmids (RHuT and HuRT) coding for chimeric rat/human ErbB2 proteins. Their immunogenicity was compared in wild type mice naturally tolerant for mouse ErbB2, and in transgenic mice that are also tolerant for rat or human ErbB2. In several of these mice, RHuT and HuRT elicited a stronger anti-tumor response than plasmids coding for fully human or fully rat ErbB2. The ability of heterologous moiety to blunt immune tolerance could be exploited to elicit a significant immune response in patients. A clinical trial to delay the recurrence of ErbB2{sup +} carcinomas of the oral cavity, oropharynx and hypopharynx is awaiting the approval of the Italian authorities.

  14. A signal combining technique based on channel shortening for cooperative sensor networks

    KAUST Repository

    Hussain, Syed Imtiaz; Alouini, Mohamed-Slim; Hasna, Mazen Omar

    2010-01-01

    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.

  15. 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.

  16. Performance Analysis of Control Signal Transmission Technique for Cognitive Radios in Dynamic Spectrum Access Networks

    Science.gov (United States)

    Sakata, Ren; Tomioka, Tazuko; Kobayashi, Takahiro

    When cognitive radio (CR) systems dynamically use the frequency band, a control signal is necessary to indicate which carrier frequencies are currently available in the network. In order to keep efficient spectrum utilization, this control signal also should be transmitted based on the channel conditions. If transmitters dynamically select carrier frequencies, receivers have to receive control signals without knowledge of their carrier frequencies. To enable such transmission and reception, this paper proposes a novel scheme called DCPT (Differential Code Parallel Transmission). With DCPT, receivers can receive low-rate information with no knowledge of the carrier frequencies. The transmitter transmits two signals whose carrier frequencies are spaced by a predefined value. The absolute values of the carrier frequencies can be varied. When the receiver acquires the DCPT signal, it multiplies the signal by a frequency-shifted version of the signal; this yields a DC component that represents the data signal which is then demodulated. The performance was evaluated by means of numerical analysis and computer simulation. We confirmed that DCPT operates successfully even under severe interference if its parameters are appropriately configured.

  17. 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.

  18. Developmental maturation of dynamic causal control signals in higher-order cognition: a neurocognitive network model.

    Directory of Open Access Journals (Sweden)

    Kaustubh Supekar

    2012-02-01

    Full Text Available Cognitive skills undergo protracted developmental changes resulting in proficiencies that are a hallmark of human cognition. One skill that develops over time is the ability to problem solve, which in turn relies on cognitive control and attention abilities. Here we use a novel multimodal neurocognitive network-based approach combining task-related fMRI, resting-state fMRI and diffusion tensor imaging (DTI to investigate the maturation of control processes underlying problem solving skills in 7-9 year-old children. Our analysis focused on two key neurocognitive networks implicated in a wide range of cognitive tasks including control: the insula-cingulate salience network, anchored in anterior insula (AI, ventrolateral prefrontal cortex and anterior cingulate cortex, and the fronto-parietal central executive network, anchored in dorsolateral prefrontal cortex and posterior parietal cortex (PPC. We found that, by age 9, the AI node of the salience network is a major causal hub initiating control signals during problem solving. Critically, despite stronger AI activation, the strength of causal regulatory influences from AI to the PPC node of the central executive network was significantly weaker and contributed to lower levels of behavioral performance in children compared to adults. These results were validated using two different analytic methods for estimating causal interactions in fMRI data. In parallel, DTI-based tractography revealed weaker AI-PPC structural connectivity in children. Our findings point to a crucial role of AI connectivity, and its causal cross-network influences, in the maturation of dynamic top-down control signals underlying cognitive development. Overall, our study demonstrates how a unified neurocognitive network model when combined with multimodal imaging enhances our ability to generalize beyond individual task-activated foci and provides a common framework for elucidating key features of brain and cognitive

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

    Science.gov (United States)

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

    2016-03-14

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

  20. Rapid Phospho-Turnover by Receptor Tyrosine Kinases Impacts Downstream Signaling and Drug Binding

    OpenAIRE

    Kleiman, Laura B.; Maiwald, Thomas; Conzelmann, Holger; Lauffenburger, Douglas A.; Sorger, Peter K.

    2011-01-01

    Epidermal growth factor receptors (ErbB1–4) are oncogenic receptor tyrosine kinases (RTKs) that regulate diverse cellular processes. In this study, we combine measurement and mathematical modeling to quantify phospho-turnover at ErbB receptors in human cells and to determine the consequences for signaling and drug binding. We find that phosphotyrosine residues on ErbB1 have half-lives of a few seconds and therefore turn over 100–1000 times in the course of a typical immediate-early response t...

  1. The cell envelope stress response of Bacillus subtilis: from static signaling devices to dynamic regulatory network.

    Science.gov (United States)

    Radeck, Jara; Fritz, Georg; Mascher, Thorsten

    2017-02-01

    The cell envelope stress response (CESR) encompasses all regulatory events that enable a cell to protect the integrity of its envelope, an essential structure of any bacterial cell. The underlying signaling network is particularly well understood in the Gram-positive model organism Bacillus subtilis. It consists of a number of two-component systems (2CS) and extracytoplasmic function σ factors that together regulate the production of both specific resistance determinants and general mechanisms to protect the envelope against antimicrobial peptides targeting the biogenesis of the cell wall. Here, we summarize the current picture of the B. subtilis CESR network, from the initial identification of the corresponding signaling devices to unraveling their interdependence and the underlying regulatory hierarchy within the network. In the course of detailed mechanistic studies, a number of novel signaling features could be described for the 2CSs involved in mediating CESR. This includes a novel class of so-called intramembrane-sensing histidine kinases (IM-HKs), which-instead of acting as stress sensors themselves-are activated via interprotein signal transfer. Some of these IM-HKs are involved in sensing the flux of antibiotic resistance transporters, a unique mechanism of responding to extracellular antibiotic challenge.

  2. Predictive model identifies key network regulators of cardiomyocyte mechano-signaling.

    Directory of Open Access Journals (Sweden)

    Philip M Tan

    2017-11-01

    Full Text Available Mechanical strain is a potent stimulus for growth and remodeling in cells. Although many pathways have been implicated in stretch-induced remodeling, the control structures by which signals from distinct mechano-sensors are integrated to modulate hypertrophy and gene expression in cardiomyocytes remain unclear. Here, we constructed and validated a predictive computational model of the cardiac mechano-signaling network in order to elucidate the mechanisms underlying signal integration. The model identifies calcium, actin, Ras, Raf1, PI3K, and JAK as key regulators of cardiac mechano-signaling and characterizes crosstalk logic imparting differential control of transcription by AT1R, integrins, and calcium channels. We find that while these regulators maintain mostly independent control over distinct groups of transcription factors, synergy between multiple pathways is necessary to activate all the transcription factors necessary for gene transcription and hypertrophy. We also identify a PKG-dependent mechanism by which valsartan/sacubitril, a combination drug recently approved for treating heart failure, inhibits stretch-induced hypertrophy, and predict further efficacious pairs of drug targets in the network through a network-wide combinatorial search.

  3. 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.

  4. 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

  5. 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.

  6. Characterisation of eddy current signals using different types of artificial neural networks

    International Nuclear Information System (INIS)

    Shyamsunder, M.T.; Rajagopalan, C.; Jayakumar, T.; Kalyanasundaram, P.; Baldev Raj; Ray, K.K.

    1996-01-01

    Eddy current testing is one of the important techniques in nondestructive testing. Automated characterisation of eddy current signals (ECS), either in the form of lissajous patterns (figure-of-eight) or individual voltage vs. time signals is an area of growing interest. This is particularly relevant in environments where the signal-to-noise ratio (SNR) of ECS are very poor. Intelligent, timely and precise interpretation of resulting data, is the key for improving the efficiency of NDT and E. A comprehensive study has been undertaken by the authors for the characterisation of ECS having poor SNR, using three types of artificial neural networks (ANNs). The types of ANNs used in this study are [a] the error-back propagation model, [b] the binary Hopfield model and [c] the Kohonen's self-organising maps model. Eddy current signals, acquired from different types of defects such as holes and notches on stainless steel type 316 sheets were used in this study. (author)

  7. Modeling and Simulation of Bus Dispatching Policy for Timed Transfers on Signalized Networks

    Science.gov (United States)

    Cho, Hsun-Jung; Lin, Guey-Shii

    2007-12-01

    The major work of this study is to formulate the system cost functions and to integrate the bus dispatching policy with signal control. The integrated model mainly includes the flow dispersion model for links, signal control model for nodes, and dispatching control model for transfer terminals. All such models are inter-related for transfer operations in one-center transit network. The integrated model that combines dispatching policies with flexible signal control modes can be applied to assess the effectiveness of transfer operations. It is found that, if bus arrival information is reliable, an early dispatching decision made at the mean bus arrival times is preferable. The costs for coordinated operations with slack times are relatively low at the optimal common headway when applying adaptive route control. Based on such findings, a threshold function of bus headway for justifying an adaptive signal route control under various time values of auto drivers is developed.

  8. 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.

  9. 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

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

    Science.gov (United States)

    Patil, Sonali; Pincas, Hanna; Seto, Jeremy; Nudelman, German; Nudelman, Irina; Sealfon, Stuart C

    2010-10-07

    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. 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 pathogen detection. This map represents a navigable

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. Phase dynamics of complex-valued neural networks and its application to traffic signal control.

    Science.gov (United States)

    Nishikawa, Ikuko; Iritani, Takeshi; Sakakibara, Kazutoshi; Kuroe, Yasuaki

    2005-01-01

    Complex-valued Hopfield networks which possess the energy function are analyzed. The dynamics of the network with certain forms of an activation function is de-composable into the dynamics of the amplitude and phase of each neuron. Then the phase dynamics is described as a coupled system of phase oscillators with a pair-wise sinusoidal interaction. Therefore its phase synchronization mechanism is useful for the area-wide offset control of the traffic signals. The computer simulations show the effectiveness under the various traffic conditions.

  16. Enhanced signaling scheme with admission control in the hybrid optical wireless (HOW) networks

    DEFF Research Database (Denmark)

    Yan, Ying; Yu, Hao; Wessing, Henrik

    2009-01-01

    that it can support stringent Quality of Service (QoS) requirements. In this paper, we describe and evaluate a resource management framework designed for the HOW networks. There are two parts in the resource management framework The first part is the Enhanced MPCP (E-MPCP) scheme aiming at improving signaling...... dropping probability depend on several factors. These factors include the frame duration, the traffic load and the total number of shared users. The results also highlight that our proposed system achieves significant improvements over the traditional approach in terms of user QoS guarantee and network...

  17. 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.

  18. 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.

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

    Science.gov (United States)

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

    2015-01-01

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

  20. 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.

  1. Polypeptide-based nanogels co-encapsulating a synergistic combination of doxorubicin with 17-AAG show potent anti-tumor activity in ErbB2-driven breast cancer models.

    Science.gov (United States)

    Desale, Swapnil S; Raja, Srikumar M; Kim, Jong Oh; Mohapatra, Bhopal; Soni, Kruti S; Luan, Haitao; Williams, Stetson H; Bielecki, Timothy A; Feng, Dan; Storck, Matthew; Band, Vimla; Cohen, Samuel M; Band, Hamid; Bronich, Tatiana K

    2015-06-28

    ErbB2-driven breast cancers constitute 20-25% of the cases diagnosed within the USA. The humanized anti-ErbB2 monoclonal antibody, Trastuzumab (Herceptin™; Genentech), with chemotherapy is the current standard of treatment. Novel agents and strategies continue to be explored, given the challenges posed by Trastuzumab-resistance development in most patients. The HSP90 inhibitor, 17-allylaminodemethoxygeldanamycin (17-AAG), which induces ErbB2 degradation and attenuates downstream oncogenic signaling, is one such agent that showed significant promise in early phase I and II clinical trials. Its low water solubility, potential toxicities and undesirable side effects observed in patients, partly due to the Cremophor-based formulation, have been discouraging factors in the advancement of this promising drug into clinical use. Encapsulation of 17-AAG into polymeric nanoparticle formulations, particularly in synergistic combination with conventional chemotherapeutics, represents an alternative approach to overcome these problems. Herein, we report an efficient co-encapsulation of 17-AAG and doxorubicin, a clinically well-established and effective modality in breast cancer treatment, into biodegradable and biocompatible polypeptide-based nanogels. Dual drug-loaded nanogels displayed potent cytotoxicity in a breast cancer cell panel and exerted selective synergistic anticancer activity against ErbB2-overexpressing breast cancer cell lines. Analysis of ErbB2 degradation confirmed efficient 17-AAG release from nanogels with activity comparable to free 17-AAG. Furthermore, nanogels containing both 17-AAG and doxorubicin exhibited superior antitumor efficacy in vivo in an ErbB2-driven xenograft model compared to the combination of free drugs. These studies demonstrate that polypeptide-based nanogels can serve as novel nanocarriers for encapsulating 17-AAG along with other chemotherapeutics, providing an opportunity to overcome solubility issues and thereby exploit its full

  2. ABC optimized RBF network for classification of EEG signal for epileptic seizure identification

    Directory of Open Access Journals (Sweden)

    Sandeep Kumar Satapathy

    2017-03-01

    Full Text Available The brain signals usually generate certain electrical signals that can be recorded and analyzed for detection in several brain disorder diseases. These small signals are expressly called as Electroencephalogram (EEG signals. This research work analyzes the epileptic disorder in human brain through EEG signal analysis by integrating the best attributes of Artificial Bee Colony (ABC and radial basis function networks (RBFNNs. We have used Discrete Wavelet Transform (DWT technique for extraction of potential features from the signal. In our study, for classification of these signals, in this paper, the RBFNNs have been trained by a modified version of ABC algorithm. In the modified ABC, the onlooker bees are selected based on binary tournament unlike roulette wheel selection of ABC. Additionally, kernels such as Gaussian, Multi-quadric, and Inverse-multi-quadric are used for measuring the effectiveness of the method in numerous mixtures of healthy segments, seizure-free segments, and seizure segments. Our experimental outcomes confirm that RBFNN with inverse-multi-quadric kernel trained with modified ABC is significantly better than RBFNNs with other kernels trained by ABC and modified ABC.

  3. A conserved signaling network monitors delivery of sphingolipids to the plasma membrane in budding yeast.

    Science.gov (United States)

    Clarke, Jesse; Dephoure, Noah; Horecka, Ira; Gygi, Steven; Kellogg, Douglas

    2017-10-01

    In budding yeast, cell cycle progression and ribosome biogenesis are dependent on plasma membrane growth, which ensures that events of cell growth are coordinated with each other and with the cell cycle. However, the signals that link the cell cycle and ribosome biogenesis to membrane growth are poorly understood. Here we used proteome-wide mass spectrometry to systematically discover signals associated with membrane growth. The results suggest that membrane trafficking events required for membrane growth generate sphingolipid-dependent signals. A conserved signaling network appears to play an essential role in signaling by responding to delivery of sphingolipids to the plasma membrane. In addition, sphingolipid-dependent signals control phosphorylation of protein kinase C (Pkc1), which plays an essential role in the pathways that link the cell cycle and ribosome biogenesis to membrane growth. Together these discoveries provide new clues as to how growth--dependent signals control cell growth and the cell cycle. © 2017 Clarke et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  4. Expression of Eag1 K+ channel and ErbBs in human pituitary adenomas: cytoskeleton arrangement patterns in cultured cells.

    Science.gov (United States)

    del Pliego, Margarita González; Aguirre-Benítez, Elsa; Paisano-Cerón, Karina; Valdovinos-Ramírez, Irene; Rangel-Morales, Carlos; Rodríguez-Mata, Verónica; Solano-Agama, Carmen; Martín-Tapia, Dolores; de la Vega, María Teresa; Saldoval-Balanzario, Miguel; Camacho, Javier; Mendoza-Garrido, María Eugenia

    2013-01-01

    Pituitary adenomas can invade surrounded tissue, but the mechanism remains elusive. Ether à go-go-1 (Eag1) potassium channel and epidermal growth factor receptors (ErbB1 and ErbB2) have been associated to invasive phenotypes or poor prognosis in cancer patients. However, cells arrange their cytoskeleton in order to acquire a successful migration pattern. We have studied ErbBs and Eag1 expression, and cytoskeleton arrangements in 11 human pituitary adenomas. Eag1, ErbB1 and ErbB2 expression were studied by immunochemistry in tissue and cultured cells. The cytoskeleton arrangement was analyzed in cultured cells by immunofluorescence. Normal pituitary tissue showed ErbB2 expression and Eag1 only in few cells. However, Eag1 and ErbB2 were expressed in all the tumors analyzed. ErbB1 expression was observed variable and did not show specificity for a tumor characteristic. Cultured cells from micro- and macro-adenomas clinically functional organize their cytoskeleton suggesting a mesenchymal pattern, and a round leucocyte/amoeboid pattern from invasive clinically silent adenoma. Pituitary tumors over-express EGF receptors and the ErbB2 repeated expression suggests is a characteristic of adenomas. Eag 1 was express, in different extent, and could be a therapeutic target. The cytoskeleton arrangements observed suggest that pituitary tumor cells acquire different patterns: mesenchymal, and leucocyte/amoeboid, the last observed in the invasive adenomas. Amoeboid migration pattern has been associated with high invasion capacity.

  5. Breast cancer metastasis driven by ErbB2 and 14-3-3ξ: A division of labor

    OpenAIRE

    Wang, Yingqun

    2010-01-01

    Metastasis remains the leading cause of cancer morbidity and mortality. ErbB2, a metastasis-promoting oncoprotein, is overexpressed in 50–60% of noninvasive ductal carcinoma in situ (DCIS). However, only 25% of invasive breast cancer (IBC) overexpress ErbB2, indicating that ErbB2 alone is not sufficient to drive metastasis and additional risk factors are necessary for the progression of ErbB2-overexpressing DCIS to IBC. A recent study published in Cancer Cell identified 14-3-3ξ as a risk fact...

  6. 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.

  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. Implementation of an Antenna Array Signal Processing Breadboard for the Deep Space Network

    Science.gov (United States)

    Navarro, Robert

    2006-01-01

    The Deep Space Network Large Array will replace/augment 34 and 70 meter antenna assets. The array will mainly be used to support NASA's deep space telemetry, radio science, and navigation requirements. The array project will deploy three complexes in the western U.S., Australia, and European longitude each with 400 12m downlink antennas and a DSN central facility at JPL. THis facility will remotely conduct all real-time monitor and control for the network. Signal processing objectives include: provide a means to evaluate the performance of the Breadboard Array's antenna subsystem; design and build prototype hardware; demonstrate and evaluate proposed signal processing techniques; and gain experience with various technologies that may be used in the Large Array. Results are summarized..

  9. 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.

  10. 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...

  11. 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.

  12. ErbB3 mRNA leukocyte levels as a biomarker for major depressive disorder

    Directory of Open Access Journals (Sweden)

    Milanesi Elena

    2012-09-01

    Full Text Available Abstract Background In recent years, the identification of peripheral biomarkers that are associated with psychiatric diseases, such as Major Depressive Disorder (MDD, has become relevant because these biomarkers may improve the efficiency of the differential diagnosis process and indicate targets for new antidepressant drugs. Two recent candidate genes, ErbB3 and Fgfr1, are growth factors whose mRNA levels have been found to be altered in the leukocytes of patients that are affected by bipolar disorder in a depressive state. On this basis, the aim of the study was to determine if ErbB3 and Fgfr1 mRNA levels could be a biomarkers of MDD. Methods We measured by Real Time PCR ErbB3 and Fgfr1 mRNA expression levels in leukocytes of MDD patients compared with controls. Successively, to assess whether ErbB3 mRNA levels were influenced by previous antidepressant treatment we stratified our patients sample in two cohorts, comparing drug-naive versus drug-free patients. Moreover, we evaluated the levels of the transcript in MDD patients after 12 weeks of antidepressant treatment, and in prefrontal cortex of rats stressed and treated with an antidepressant drug of the same class. Results These results showed that ErbB3 but not Fgfr1 mRNA levels were reduced in leukocytes of MDD patients compared to healthy subjects. Furthermore, ErbB3 levels were not affected by antidepressant treatment in either human or animal models Conclusions Our data suggest that ErbB3 might be considered as a biomarker for MDD and that its deficit may underlie the pathopsysiology of the disease and is not a consequence of treatment. Moreover the study supports the usefulness of leukocytes as a peripheral system for identifying biomarkers in psychiatric diseases.

  13. Engineering of bispecific affinity proteins with high affinity for ERBB2 and adaptable binding to albumin.

    Directory of Open Access Journals (Sweden)

    Johan Nilvebrant

    Full Text Available The epidermal growth factor receptor 2, ERBB2, is a well-validated target for cancer diagnostics and therapy. Recent studies suggest that the over-expression of this receptor in various cancers might also be exploited for antibody-based payload delivery, e.g. antibody drug conjugates. In such strategies, the full-length antibody format is probably not required for therapeutic effect and smaller tumor-specific affinity proteins might be an alternative. However, small proteins and peptides generally suffer from fast excretion through the kidneys, and thereby require frequent administration in order to maintain a therapeutic concentration. In an attempt aimed at combining ERBB2-targeting with antibody-like pharmacokinetic properties in a small protein format, we have engineered bispecific ERBB2-binding proteins that are based on a small albumin-binding domain. Phage display selection against ERBB2 was used for identification of a lead candidate, followed by affinity maturation using second-generation libraries. Cell surface display and flow-cytometric sorting allowed stringent selection of top candidates from pools pre-enriched by phage display. Several affinity-matured molecules were shown to bind human ERBB2 with sub-nanomolar affinity while retaining the interaction with human serum albumin. Moreover, parallel selections against ERBB2 in the presence of human serum albumin identified several amino acid substitutions that dramatically modulate the albumin affinity, which could provide a convenient means to control the pharmacokinetics. The new affinity proteins competed for ERBB2-binding with the monoclonal antibody trastuzumab and recognized the native receptor on a human cancer cell line. Hence, high affinity tumor targeting and tunable albumin binding were combined in one small adaptable protein.

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

    Science.gov (United States)

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

    2008-07-15

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

  15. Real-time synchronization of wireless sensor network by 1-PPS signal

    Science.gov (United States)

    Giammarini, Marco; Pieralisi, Marco; Isidori, Daniela; Concettoni, Enrico; Cristalli, Cristina; Fioravanti, Matteo

    2015-05-01

    The use of wireless sensor networks with different nodes is desirable in a smart environment, because the network setting up and installation on preexisting structures can be done without a fixed cabled infrastructure. The flexibility of the monitoring system is fundamental where the use of a considerable quantity of cables could compromise the normal exercise, could affect the quality of acquired signal and finally increase the cost of the materials and installation. The network is composed of several intelligent "nodes", which acquires data from different kind of sensors, and then store or transmit them to a central elaboration unit. The synchronization of data acquisition is the core of the real-time wireless sensor network (WSN). In this paper, we present a comparison between different methods proposed by literature for the real-time acquisition in a WSN and finally we present our solution based on 1-Pulse-Per-Second (1-PPS) signal generated by GPS systems. The sensor node developed is a small-embedded system based on ARM microcontroller that manages the acquisition, the timing and the post-processing of the data. The communications between the sensors and the master based on IEEE 802.15.4 protocol and managed by dedicated software. Finally, we present the preliminary results obtained on a 3 floor building simulator with the wireless sensors system developed.

  16. Analysis of network motifs in cellular regulation: Structural similarities, input-output relations and signal integration.

    Science.gov (United States)

    Straube, Ronny

    2017-12-01

    Much of the complexity of regulatory networks derives from the necessity to integrate multiple signals and to avoid malfunction due to cross-talk or harmful perturbations. Hence, one may expect that the input-output behavior of larger networks is not necessarily more complex than that of smaller network motifs which suggests that both can, under certain conditions, be described by similar equations. In this review, we illustrate this approach by discussing the similarities that exist in the steady state descriptions of a simple bimolecular reaction, covalent modification cycles and bacterial two-component systems. Interestingly, in all three systems fundamental input-output characteristics such as thresholds, ultrasensitivity or concentration robustness are described by structurally similar equations. Depending on the system the meaning of the parameters can differ ranging from protein concentrations and affinity constants to complex parameter combinations which allows for a quantitative understanding of signal integration in these systems. We argue that this approach may also be extended to larger regulatory networks. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. FPGA implementation of a ZigBee wireless network control interface to transmit biomedical signals

    Science.gov (United States)

    Gómez López, M. A.; Goy, C. B.; Bolognini, P. C.; Herrera, M. C.

    2011-12-01

    In recent years, cardiac hemodynamic monitors have incorporated new technologies based on wireless sensor networks which can implement different types of communication protocols. More precisely, a digital conductance catheter system recently developed adds a wireless ZigBee module (IEEE 802.15.4 standards) to transmit cardiac signals (ECG, intraventricular pressure and volume) which would allow the physicians to evaluate the patient's cardiac status in a noninvasively way. The aim of this paper is to describe a control interface, implemented in a FPGA device, to manage a ZigBee wireless network. ZigBee technology is used due to its excellent performance including simplicity, low-power consumption, short-range transmission and low cost. FPGA internal memory stores 8-bit signals with which the control interface prepares the information packets. These data were send to the ZigBee END DEVICE module that receives and transmits wirelessly to the external COORDINATOR module. Using an USB port, the COORDINATOR sends the signals to a personal computer for displaying. Each functional block of control interface was assessed by means of temporal diagrams. Three biological signals, organized in packets and converted to RS232 serial protocol, were sucessfully transmitted and displayed in a PC screen. For this purpose, a custom-made graphical software was designed using LabView.

  18. SoxB1-driven transcriptional network underlies neural-specific interpretation of morphogen signals.

    Science.gov (United States)

    Oosterveen, Tony; Kurdija, Sanja; Ensterö, Mats; Uhde, Christopher W; Bergsland, Maria; Sandberg, Magnus; Sandberg, Rickard; Muhr, Jonas; Ericson, Johan

    2013-04-30

    The reiterative deployment of a small cadre of morphogen signals underlies patterning and growth of most tissues during embyogenesis, but how such inductive events result in tissue-specific responses remains poorly understood. By characterizing cis-regulatory modules (CRMs) associated with genes regulated by Sonic hedgehog (Shh), retinoids, or bone morphogenetic proteins in the CNS, we provide evidence that the neural-specific interpretation of morphogen signaling reflects a direct integration of these pathways with SoxB1 proteins at the CRM level. Moreover, expression of SoxB1 proteins in the limb bud confers on mesodermal cells the potential to activate neural-specific target genes upon Shh, retinoid, or bone morphogenetic protein signaling, and the collocation of binding sites for SoxB1 and morphogen-mediatory transcription factors in CRMs faithfully predicts neural-specific gene activity. Thus, an unexpectedly simple transcriptional paradigm appears to conceptually explain the neural-specific interpretation of pleiotropic signaling during vertebrate development. Importantly, genes induced in a SoxB1-dependent manner appear to constitute repressive gene regulatory networks that are directly interlinked at the CRM level to constrain the regional expression of patterning genes. Accordingly, not only does the topology of SoxB1-driven gene regulatory networks provide a tissue-specific mode of gene activation, but it also determines the spatial expression pattern of target genes within the developing neural tube.

  19. FPGA implementation of a ZigBee wireless network control interface to transmit biomedical signals

    International Nuclear Information System (INIS)

    López, M A Gómez; Goy, C B; Bolognini, P C; Herrera, M C

    2011-01-01

    In recent years, cardiac hemodynamic monitors have incorporated new technologies based on wireless sensor networks which can implement different types of communication protocols. More precisely, a digital conductance catheter system recently developed adds a wireless ZigBee module (IEEE 802.15.4 standards) to transmit cardiac signals (ECG, intraventricular pressure and volume) which would allow the physicians to evaluate the patient's cardiac status in a noninvasively way. The aim of this paper is to describe a control interface, implemented in a FPGA device, to manage a ZigBee wireless network. ZigBee technology is used due to its excellent performance including simplicity, low-power consumption, short-range transmission and low cost. FPGA internal memory stores 8-bit signals with which the control interface prepares the information packets. These data were send to the ZigBee END DEVICE module that receives and transmits wirelessly to the external COORDINATOR module. Using an USB port, the COORDINATOR sends the signals to a personal computer for displaying. Each functional block of control interface was assessed by means of temporal diagrams. Three biological signals, organized in packets and converted to RS232 serial protocol, were successfully transmitted and displayed in a PC screen. For this purpose, a custom-made graphical software was designed using LabView.

  20. Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals.

    Science.gov (United States)

    Kim, Junkyeong; Lee, Chaggil; Park, Seunghee

    2017-06-07

    Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process.

  1. ErbB4 localization to cardiac myocyte nuclei, and its role in myocyte DNA damage response

    International Nuclear Information System (INIS)

    Icli, Basak; Bharti, Ajit; Pentassuglia, Laura; Peng, Xuyang; Sawyer, Douglas B.

    2012-01-01

    Highlights: ► ErbB4 localizes to cardiac myocyte nuclei as a full-length receptor. ► Cardiac myocytes express predominantly JM-a/CYT-1 ErbB4. ► Myocyte p53 activation in response to doxorubicin requires ErbB4 activity. -- Abstract: The intracellular domain of ErbB4 receptor tyrosine kinase is known to translocate to the nucleus of cells where it can regulate p53 transcriptional activity. The purpose of this study was to examine whether ErbB4 can localize to the nucleus of adult rat ventricular myocytes (ARVM), and regulate p53 in these cells. We demonstrate that ErbB4 does locate to the nucleus of cardiac myocytes as a full-length protein, although nuclear location occurs as a full-length protein that does not require Protein Kinase C or γ-secretase activity. Consistent with this we found that only the non-cleavable JM-b isoform of ErbB4 is expressed in ARVM. Doxorubicin was used to examine ErbB4 role in regulation of a DNA damage response in ARVM. Doxorubicin induced p53 and p21 was suppressed by treatment with AG1478, an EGFR and ErbB4 kinase inhibitor, or suppression of ErbB4 expression with small interfering RNA. Thus ErbB4 localizes to the nucleus as a full-length protein, and plays a role in the DNA damage response induced by doxorubicin in cardiac myocytes.

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

    Science.gov (United States)

    Fröhlich, Holger; Bahamondez, Gloria; Götschel, Frank; Korf, Ulrike

    2015-01-01

    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.

  3. Integration of protein phosphorylation, acetylation, and methylation data sets to outline lung cancer signaling networks.

    Science.gov (United States)

    Grimes, Mark; Hall, Benjamin; Foltz, Lauren; Levy, Tyler; Rikova, Klarisa; Gaiser, Jeremiah; Cook, William; Smirnova, Ekaterina; Wheeler, Travis; Clark, Neil R; Lachmann, Alexander; Zhang, Bin; Hornbeck, Peter; Ma'ayan, Avi; Comb, Michael

    2018-05-22

    Protein posttranslational modifications (PTMs) have typically been studied independently, yet many proteins are modified by more than one PTM type, and cell signaling pathways somehow integrate this information. We coupled immunoprecipitation using PTM-specific antibodies with tandem mass tag (TMT) mass spectrometry to simultaneously examine phosphorylation, methylation, and acetylation in 45 lung cancer cell lines compared to normal lung tissue and to cell lines treated with anticancer drugs. This simultaneous, large-scale, integrative analysis of these PTMs using a cluster-filtered network (CFN) approach revealed that cell signaling pathways were outlined by clustering patterns in PTMs. We used the t-distributed stochastic neighbor embedding (t-SNE) method to identify PTM clusters and then integrated each with known protein-protein interactions (PPIs) to elucidate functional cell signaling pathways. The CFN identified known and previously unknown cell signaling pathways in lung cancer cells that were not present in normal lung epithelial tissue. In various proteins modified by more than one type of PTM, the incidence of those PTMs exhibited inverse relationships, suggesting that molecular exclusive "OR" gates determine a large number of signal transduction events. We also showed that the acetyltransferase EP300 appears to be a hub in the network of pathways involving different PTMs. In addition, the data shed light on the mechanism of action of geldanamycin, an HSP90 inhibitor. Together, the findings reveal that cell signaling pathways mediated by acetylation, methylation, and phosphorylation regulate the cytoskeleton, membrane traffic, and RNA binding protein-mediated control of gene expression. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  4. Identification and analysis of signaling networks potentially involved in breast carcinoma metastasis to the brain.

    Directory of Open Access Journals (Sweden)

    Feng Li

    Full Text Available Brain is a common site of breast cancer metastasis associated with significant neurologic morbidity, decreased quality of life, and greatly shortened survival. However, the molecular and cellular mechanisms underpinning brain colonization by breast carcinoma cells are poorly understood. Here, we used 2D-DIGE (Difference in Gel Electrophoresis proteomic analysis followed by LC-tandem mass spectrometry to identify the proteins differentially expressed in brain-targeting breast carcinoma cells (MB231-Br compared with parental MDA-MB-231 cell line. Between the two cell lines, we identified 12 proteins consistently exhibiting greater than 2-fold (p<0.05 difference in expression, which were associated by the Ingenuity Pathway Analysis (IPA with two major signaling networks involving TNFα/TGFβ-, NFκB-, HSP-70-, TP53-, and IFNγ-associated pathways. Remarkably, highly related networks were revealed by the IPA analysis of a list of 19 brain-metastasis-associated proteins identified recently by the group of Dr. A. Sierra using MDA-MB-435-based experimental system (Martin et al., J Proteome Res 2008 7:908-20, or a 17-gene classifier associated with breast cancer brain relapse reported by the group of Dr. J. Massague based on a microarray analysis of clinically annotated breast tumors from 368 patients (Bos et al., Nature 2009 459: 1005-9. These findings, showing that different experimental systems and approaches (2D-DIGE proteomics used on brain targeting cell lines or gene expression analysis of patient samples with documented brain relapse yield highly related signaling networks, suggest strongly that these signaling networks could be essential for a successful colonization of the brain by metastatic breast carcinoma cells.

  5. Synergistic target combination prediction from curated signaling networks: Machine learning meets systems biology and pharmacology.

    Science.gov (United States)

    Chua, Huey Eng; Bhowmick, Sourav S; Tucker-Kellogg, Lisa

    2017-10-01

    Given a signaling network, the target combination prediction problem aims to predict efficacious and safe target combinations for combination therapy. State-of-the-art in silico methods use Monte Carlo simulated annealing (mcsa) to modify a candidate solution stochastically, and use the Metropolis criterion to accept or reject the proposed modifications. However, such stochastic modifications ignore the impact of the choice of targets and their activities on the combination's therapeutic effect and off-target effects, which directly affect the solution quality. In this paper, we present mascot, a method that addresses this limitation by leveraging two additional heuristic criteria to minimize off-target effects and achieve synergy for candidate modification. Specifically, off-target effects measure the unintended response of a signaling network to the target combination and is often associated with toxicity. Synergy occurs when a pair of targets exerts effects that are greater than the sum of their individual effects, and is generally a beneficial strategy for maximizing effect while minimizing toxicity. mascot leverages on a machine learning-based target prioritization method which prioritizes potential targets in a given disease-associated network to select more effective targets (better therapeutic effect and/or lower off-target effects); and on Loewe additivity theory from pharmacology which assesses the non-additive effects in a combination drug treatment to select synergistic target activities. Our experimental study on two disease-related signaling networks demonstrates the superiority of mascot in comparison to existing approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. DMPD: The involvement of the interleukin-1 receptor-associated kinases (IRAKs) incellular signaling networks controlling inflammation. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available ncellular signaling networks controlling inflammation. Ringwood L, Li L. Cytokine. 2008 Apr;42(1):1-7. Epub ...ases (IRAKs) incellular signaling networks controlling inflammation. PubmedID 182...49132 Title The involvement of the interleukin-1 receptor-associated kinases (IRAKs) incellular signaling networks controlling

  7. Enhancement of signal sensitivity in a heterogeneous neural network refined from synaptic plasticity

    Energy Technology Data Exchange (ETDEWEB)

    Li Xiumin; Small, Michael, E-mail: ensmall@polyu.edu.h, E-mail: 07901216r@eie.polyu.edu.h [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hung Hom, Kowloon (Hong Kong)

    2010-08-15

    Long-term synaptic plasticity induced by neural activity is of great importance in informing the formation of neural connectivity and the development of the nervous system. It is reasonable to consider self-organized neural networks instead of prior imposition of a specific topology. In this paper, we propose a novel network evolved from two stages of the learning process, which are respectively guided by two experimentally observed synaptic plasticity rules, i.e. the spike-timing-dependent plasticity (STDP) mechanism and the burst-timing-dependent plasticity (BTDP) mechanism. Due to the existence of heterogeneity in neurons that exhibit different degrees of excitability, a two-level hierarchical structure is obtained after the synaptic refinement. This self-organized network shows higher sensitivity to afferent current injection compared with alternative archetypal networks with different neural connectivity. Statistical analysis also demonstrates that it has the small-world properties of small shortest path length and high clustering coefficients. Thus the selectively refined connectivity enhances the ability of neuronal communications and improves the efficiency of signal transmission in the network.

  8. 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.

  9. Efficient transmission of subthreshold signals in complex networks of spiking neurons.

    Science.gov (United States)

    Torres, Joaquin J; Elices, Irene; Marro, J

    2015-01-01

    We investigate the efficient transmission and processing of weak, subthreshold signals in a realistic neural medium in the presence of different levels of the underlying noise. Assuming Hebbian weights for maximal synaptic conductances--that naturally balances the network with excitatory and inhibitory synapses--and considering short-term synaptic plasticity affecting such conductances, we found different dynamic phases in the system. This includes a memory phase where population of neurons remain synchronized, an oscillatory phase where transitions between different synchronized populations of neurons appears and an asynchronous or noisy phase. When a weak stimulus input is applied to each neuron, increasing the level of noise in the medium we found an efficient transmission of such stimuli around the transition and critical points separating different phases for well-defined different levels of stochasticity in the system. We proved that this intriguing phenomenon is quite robust, as it occurs in different situations including several types of synaptic plasticity, different type and number of stored patterns and diverse network topologies, namely, diluted networks and complex topologies such as scale-free and small-world networks. We conclude that the robustness of the phenomenon in different realistic scenarios, including spiking neurons, short-term synaptic plasticity and complex networks topologies, make very likely that it could also occur in actual neural systems as recent psycho-physical experiments suggest.

  10. Efficient transmission of subthreshold signals in complex networks of spiking neurons.

    Directory of Open Access Journals (Sweden)

    Joaquin J Torres

    Full Text Available We investigate the efficient transmission and processing of weak, subthreshold signals in a realistic neural medium in the presence of different levels of the underlying noise. Assuming Hebbian weights for maximal synaptic conductances--that naturally balances the network with excitatory and inhibitory synapses--and considering short-term synaptic plasticity affecting such conductances, we found different dynamic phases in the system. This includes a memory phase where population of neurons remain synchronized, an oscillatory phase where transitions between different synchronized populations of neurons appears and an asynchronous or noisy phase. When a weak stimulus input is applied to each neuron, increasing the level of noise in the medium we found an efficient transmission of such stimuli around the transition and critical points separating different phases for well-defined different levels of stochasticity in the system. We proved that this intriguing phenomenon is quite robust, as it occurs in different situations including several types of synaptic plasticity, different type and number of stored patterns and diverse network topologies, namely, diluted networks and complex topologies such as scale-free and small-world networks. We conclude that the robustness of the phenomenon in different realistic scenarios, including spiking neurons, short-term synaptic plasticity and complex networks topologies, make very likely that it could also occur in actual neural systems as recent psycho-physical experiments suggest.

  11. Enhancement of signal sensitivity in a heterogeneous neural network refined from synaptic plasticity

    International Nuclear Information System (INIS)

    Li Xiumin; Small, Michael

    2010-01-01

    Long-term synaptic plasticity induced by neural activity is of great importance in informing the formation of neural connectivity and the development of the nervous system. It is reasonable to consider self-organized neural networks instead of prior imposition of a specific topology. In this paper, we propose a novel network evolved from two stages of the learning process, which are respectively guided by two experimentally observed synaptic plasticity rules, i.e. the spike-timing-dependent plasticity (STDP) mechanism and the burst-timing-dependent plasticity (BTDP) mechanism. Due to the existence of heterogeneity in neurons that exhibit different degrees of excitability, a two-level hierarchical structure is obtained after the synaptic refinement. This self-organized network shows higher sensitivity to afferent current injection compared with alternative archetypal networks with different neural connectivity. Statistical analysis also demonstrates that it has the small-world properties of small shortest path length and high clustering coefficients. Thus the selectively refined connectivity enhances the ability of neuronal communications and improves the efficiency of signal transmission in the network.

  12. Enzyme-Based Logic Gates and Networks with Output Signals Analyzed by Various Methods.

    Science.gov (United States)

    Katz, Evgeny

    2017-07-05

    The paper overviews various methods that are used for the analysis of output signals generated by enzyme-based logic systems. The considered methods include optical techniques (optical absorbance, fluorescence spectroscopy, surface plasmon resonance), electrochemical techniques (cyclic voltammetry, potentiometry, impedance spectroscopy, conductivity measurements, use of field effect transistor devices, pH measurements), and various mechanoelectronic methods (using atomic force microscope, quartz crystal microbalance). Although each of the methods is well known for various bioanalytical applications, their use in combination with the biomolecular logic systems is rather new and sometimes not trivial. Many of the discussed methods have been combined with the use of signal-responsive materials to transduce and amplify biomolecular signals generated by the logic operations. Interfacing of biocomputing logic systems with electronics and "smart" signal-responsive materials allows logic operations be extended to actuation functions; for example, stimulating molecular release and switchable features of bioelectronic devices, such as biofuel cells. The purpose of this review article is to emphasize the broad variability of the bioanalytical systems applied for signal transduction in biocomputing processes. All bioanalytical systems discussed in the article are exemplified with specific logic gates and multi-gate networks realized with enzyme-based biocatalytic cascades. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  13. Discovery of nitrate-CPK-NLP signalling in central nutrient-growth networks

    Science.gov (United States)

    Liu, Kun-hsiang; Niu, Yajie; Konishi, Mineko; Wu, Yue; Du, Hao; Sun Chung, Hoo; Li, Lei; Boudsocq, Marie; McCormack, Matthew; Maekawa, Shugo; Ishida, Tetsuya; Zhang, Chao; Shokat, Kevan; Yanagisawa, Shuichi; Sheen, Jen

    2018-01-01

    Nutrient signalling integrates and coordinates gene expression, metabolism and growth. However, its primary molecular mechanisms remain incompletely understood in plants and animals. Here we report novel Ca2+ signalling triggered by nitrate with live imaging of an ultrasensitive biosensor in Arabidopsis leaves and roots. A nitrate-sensitized and targeted functional genomic screen identifies subgroup III Ca2+-sensor protein kinases (CPKs) as master regulators orchestrating primary nitrate responses. A chemical switch with the engineered CPK10(M141G) kinase enables conditional analyses of cpk10,30,32 to define comprehensive nitrate-associated regulatory and developmental programs, circumventing embryo lethality. Nitrate-CPK signalling phosphorylates conserved NIN-LIKE PROTEIN (NLP) transcription factors (TFs) to specify reprogramming of gene sets for downstream TFs, transporters, N-assimilation, C/N-metabolism, redox, signalling, hormones, and proliferation. Conditional cpk10,30,32 and nlp7 similarly impair nitrate-stimulated system-wide shoot growth and root establishment. The nutrient-coupled Ca2+ signalling network integrates transcriptome and cellular metabolism with shoot-root coordination and developmental plasticity in shaping organ biomass and architecture. PMID:28489820

  14. An intelligent signal processing and pattern recognition technique for defect identification using an active sensor network

    Science.gov (United States)

    Su, Zhongqing; Ye, Lin

    2004-08-01

    The practical utilization of elastic waves, e.g. Rayleigh-Lamb waves, in high-performance structural health monitoring techniques is somewhat impeded due to the complicated wave dispersion phenomena, the existence of multiple wave modes, the high susceptibility to diverse interferences, the bulky sampled data and the difficulty in signal interpretation. An intelligent signal processing and pattern recognition (ISPPR) approach using the wavelet transform and artificial neural network algorithms was developed; this was actualized in a signal processing package (SPP). The ISPPR technique comprehensively functions as signal filtration, data compression, characteristic extraction, information mapping and pattern recognition, capable of extracting essential yet concise features from acquired raw wave signals and further assisting in structural health evaluation. For validation, the SPP was applied to the prediction of crack growth in an alloy structural beam and construction of a damage parameter database for defect identification in CF/EP composite structures. It was clearly apparent that the elastic wave propagation-based damage assessment could be dramatically streamlined by introduction of the ISPPR technique.

  15. Endocytic down-regulation of ErbB2 is stimulated by cleavage of its C-terminus

    DEFF Research Database (Denmark)

    Lerdrup, Mads; Bruun, Silas; Grandal, Michael Vibo

    2007-01-01

    inhibition of HSP90 with geldanamycin this cleavage is accompanied by proteasome-dependent endocytosis of ErbB2. However, it is unknown whether C-terminal cleavage is linked to endocytosis. To study ErbB2 cleavage and endocytic trafficking, we fused yellow fluorescent protein (YFP) and cyan fluorescent...

  16. Identification of a novel antagonist of the ErbB1 receptor capable of inhibiting migration of human glioblastoma cells

    DEFF Research Database (Denmark)

    Staberg, Mikkel; Riemer, Christian; Xu, Ruodan

    2013-01-01

    B1 targeting peptide, termed Herfin-1, was designed based on a model of the tertiary structure of the EGF-EGFR ternary complex. The binding kinetics of this peptide were determined employing surface plasmon resonance analyses. ErbB1-4 expression and phosphorylation in human glioblastoma cell lines U...... processing. RESULTS: The present study shows that Herfin-1 functions as an ErbB1 antagonist. It binds to the extracellular domain of ErbB1 with a KD value of 361 nM. In U87 and U118 cells, both expressing high levels of ErbB1, Herfin-1 inhibits EGF-induced ErbB1 phosphorylation and cell migration....... Additionally, Herfin-1 was found to increase neurite outgrowth in cerebellar granule neurons, likely through the inhibition of a sustained weak ErbB1 activation. CONCLUSIONS: Targeting the ErbB1 receptor dimerization interface is a promising strategy to inhibit receptor activation in ErbB1-expressing glioma...

  17. The Limitation of Primary Signals Entering DVB-T On-Channel-Repeater Working in SFN Network

    Directory of Open Access Journals (Sweden)

    Marek Dvorsky

    2013-01-01

    Full Text Available This paper considers an issue of signal coverage in uncovered places using a broadcasting device called a Gap Filler. The main focus is placed on the analysis of potential negative effects while signals from two and more primary transmitters simultaneously enter to the Gap Filler. In particular, in the measurements the impact of reception cross delayed signals received by the Gap Filler from two adjacent primary transmitters operating in the Single Frequency Network was analysed. The influence of different receive signal levels from two adjacent primary transmitters was also examined. In the conclusion, based on the experiments, the limiting factors useful for individual transmitters in the Single Frequency Network were determined. The analysis and finding the limit parameters can help bradcasters in further setting and debugging of the Gap Filler network. Finally, the described laboratory experiment was also verified under the real SFN network condition in border region Vsetinsko to verify the laboratory findings.

  18. Transcriptional regulatory network triggered by oxidative signals configures the early response mechanisms of japonica rice to chilling stress

    KAUST Repository

    Yun, Kil-Young; Park, Myoung Ryoul; Mohanty, Bijayalaxmi; Herath, Venura; Xu, Fuyu; Mauleon, Ramil; Wijaya, Edward; Bajic, Vladimir B.; Bruskiewich, Richard; de los Reyes, Benildo G

    2010-01-01

    -plant level analyses established a holistic view of chilling stress response mechanism of japonica rice. Early response regulatory network triggered by oxidative signals is critical for prolonged survival under sub-optimal temperature. Integration of stress

  19. Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks

    KAUST Repository

    Douik, Ahmed; Dahrouj, Hayssam; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2016-01-01

    results suggest that the proposed hybrid scheduling strategy provides appreciable gain as compared to the scheduling-level coordinated networks, with a negligible degradation to signal-level coordination.

  20. Exogenous HGF Bypasses the Effects of ErbB Inhibition on Tumor Cell Viability in Medulloblastoma Cell Lines.

    Directory of Open Access Journals (Sweden)

    Walderik W Zomerman

    Full Text Available Recent clinical trials investigating receptor tyrosine kinase (RTK inhibitors showed a limited clinical response in medulloblastoma. The present study investigated the role of micro-environmental growth factors expressed in the brain, such as HGF and EGF, in relation to the effects of hepatocyte growth factor receptor (MET and epidermal growth factor receptor family (ErbB1-4 inhibition in medulloblastoma cell lines. Medulloblastoma cell lines were treated with tyrosine kinase inhibitors crizotinib or canertinib, targeting MET and ErbB1-4, respectively. Upon treatment, cells were stimulated with VEGF-A, PDGF-AB, HGF, FGF-2 or EGF. Subsequently, we measured cell viability and expression levels of growth factors and downstream signaling proteins. Addition of HGF or EGF phosphorylated MET or EGFR, respectively, and demonstrated phosphorylation of Akt and ERK1/2 as well as increased tumor cell viability. Crizotinib and canertinib both inhibited cell viability and phosphorylation of Akt and ERK1/2. Specifically targeting MET using shRNA's resulted in decreased cell viability. Interestingly, addition of HGF to canertinib significantly enhanced cell viability as well as phosphorylation of Akt and ERK1/2. The HGF-induced bypass of canertinib was reversed by addition of crizotinib. HGF protein was hardly released by medulloblastoma cells itself. Addition of canertinib did not affect RTK cell surface or growth factor expression levels. This manuscript points to the bypassing capacity of exogenous HGF in medulloblastoma cell lines. It might be of great interest to anticipate on these results in developing novel clinical trials with a combination of MET and EGFR inhibitors in medulloblastoma.

  1. Simulating GPS radio signal to synchronize network--a new technique for redundant timing.

    Science.gov (United States)

    Shan, Qingxiao; Jun, Yang; Le Floch, Jean-Michel; Fan, Yaohui; Ivanov, Eugene N; Tobar, Michael E

    2014-07-01

    Currently, many distributed systems such as 3G mobile communications and power systems are time synchronized with a Global Positioning System (GPS) signal. If there is a GPS failure, it is difficult to realize redundant timing, and thus time-synchronized devices may fail. In this work, we develop time transfer by simulating GPS signals, which promises no extra modification to original GPS-synchronized devices. This is achieved by applying a simplified GPS simulator for synchronization purposes only. Navigation data are calculated based on a pre-assigned time at a fixed position. Pseudo-range data which describes the distance change between the space vehicle (SV) and users are calculated. Because real-time simulation requires heavy-duty computations, we use self-developed software optimized on a PC to generate data, and save the data onto memory disks while the simulator is operating. The radio signal generation is similar to the SV at an initial position, and the frequency synthesis of the simulator is locked to a pre-assigned time. A filtering group technique is used to simulate the signal transmission delay corresponding to the SV displacement. Each SV generates a digital baseband signal, where a unique identifying code is added to the signal and up-converted to generate the output radio signal at the centered frequency of 1575.42 MHz (L1 band). A prototype with a field-programmable gate array (FPGA) has been built and experiments have been conducted to prove that we can realize time transfer. The prototype has been applied to the CDMA network for a three-month long experiment. Its precision has been verified and can meet the requirements of most telecommunication systems.

  2. The yeast Sks1p kinase signaling network regulates pseudohyphal growth and glucose response.

    Directory of Open Access Journals (Sweden)

    Cole Johnson

    2014-03-01

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

  3. 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.

  4. Best response game of traffic on road network of non-signalized intersections

    Science.gov (United States)

    Yao, Wang; Jia, Ning; Zhong, Shiquan; Li, Liying

    2018-01-01

    This paper studies the traffic flow in a grid road network with non-signalized intersections. The nature of the drivers in the network is simulated such that they play an iterative snowdrift game with other drivers. A cellular automata model is applied to study the characteristics of the traffic flow and the evolution of the behaviour of the drivers during the game. The drivers use best-response as their strategy to update rules. Three major findings are revealed. First, the cooperation rate in simulation experiences staircase-shaped drop as cost to benefit ratio r increases, and cooperation rate can be derived analytically as a function of cost to benefit ratio r. Second, we find that higher cooperation rate corresponds to higher average speed, lower density and higher flow. This reveals that defectors deteriorate the efficiency of traffic on non-signalized intersections. Third, the system experiences more randomness when the density is low because the drivers will not have much opportunity to update strategy when the density is low. These findings help to show how the strategy of drivers in a traffic network evolves and how their interactions influence the overall performance of the traffic system.

  5. Identifying Network Motifs that Buffer Front-to-Back Signaling in Polarized Neutrophils

    Directory of Open Access Journals (Sweden)

    Yanqin Wang

    2013-05-01

    Full Text Available Neutrophil polarity relies on local, mutual inhibition to segregate incompatible signaling circuits to the leading and trailing edges. Mutual inhibition alone should lead to cells having strong fronts and weak backs or vice versa. However, analysis of cell-to-cell variation in human neutrophils revealed that back polarity remains consistent despite changes in front strength. How is this buffering achieved? Pharmacological perturbations and mathematical modeling revealed a functional role for microtubules in buffering back polarity by mediating positive, long-range crosstalk from front to back; loss of microtubules inhibits buffering and results in anticorrelation between front and back signaling. Furthermore, a systematic, computational search of network topologies found that a long-range, positive front-to-back link is necessary for back buffering. Our studies suggest a design principle that can be employed by polarity networks: short-range mutual inhibition establishes distinct signaling regions, after which directed long-range activation insulates one region from variations in the other.

  6. A Novel Approach for Transmission of 56 Gbit/s NRZ Signal in Access Network Using Spectrum Slicing Technique

    DEFF Research Database (Denmark)

    Spolitis, S.; Vegas Olmos, Juan José; Bobrovs, V.

    2013-01-01

    We present the spectrum slicing and stitching concept for high-capacity low optics complexity optical access networks. Spectrum slicing and stitching of a 56 Gbit/s NRZ electrical signal is experimentally demonstrated for the first time.......We present the spectrum slicing and stitching concept for high-capacity low optics complexity optical access networks. Spectrum slicing and stitching of a 56 Gbit/s NRZ electrical signal is experimentally demonstrated for the first time....

  7. AP2/EREBP transcription factors are part of gene regulatory networks and integrate metabolic, hormonal and environmental signals in stress acclimation and retrograde signalling.

    Science.gov (United States)

    Dietz, Karl-Josef; Vogel, Marc Oliver; Viehhauser, Andrea

    2010-09-01

    To optimize acclimation responses to environmental growth conditions, plants integrate and weigh a diversity of input signals. Signal integration within the signalling networks occurs at different sites including the level of transcription factor activation. Accumulating evidence assigns a major and diversified role in environmental signal integration to the family of APETALA 2/ethylene response element binding protein (AP2/EREBP) transcription factors. Presently, the Plant Transcription Factor Database 3.0 assigns 147 gene loci to this family in Arabidopsis thaliana, 200 in Populus trichocarpa and 163 in Oryza sativa subsp. japonica as compared to 13 to 14 in unicellular algae ( http://plntfdb.bio.uni-potsdam.de/v3.0/ ). AP2/EREBP transcription factors have been implicated in hormone, sugar and redox signalling in context of abiotic stresses such as cold and drought. This review exemplarily addresses present-day knowledge of selected AP2/EREBP with focus on a function in stress signal integration and retrograde signalling and defines AP2/EREBP-linked gene networks from transcriptional profiling-based graphical Gaussian models. The latter approach suggests highly interlinked functions of AP2/EREBPs in retrograde and stress signalling.

  8. Cannabinoids reduce ErbB2-driven breast cancer progression through Akt inhibition

    Directory of Open Access Journals (Sweden)

    Flores Juana M

    2010-07-01

    Full Text Available Abstract Background ErbB2-positive breast cancer is characterized by highly aggressive phenotypes and reduced responsiveness to standard therapies. Although specific ErbB2-targeted therapies have been designed, only a small percentage of patients respond to these treatments and most of them eventually relapse. The existence of this population of particularly aggressive and non-responding or relapsing patients urges the search for novel therapies. The purpose of this study was to determine whether cannabinoids might constitute a new therapeutic tool for the treatment of ErbB2-positive breast tumors. We analyzed their antitumor potential in a well established and clinically relevant model of ErbB2-driven metastatic breast cancer: the MMTV-neu mouse. We also analyzed the expression of cannabinoid targets in a series of 87 human breast tumors. Results Our results show that both Δ9-tetrahydrocannabinol, the most abundant and potent cannabinoid in marijuana, and JWH-133, a non-psychotropic CB2 receptor-selective agonist, reduce tumor growth, tumor number, and the amount/severity of lung metastases in MMTV-neu mice. Histological analyses of the tumors revealed that cannabinoids inhibit cancer cell proliferation, induce cancer cell apoptosis, and impair tumor angiogenesis. Cannabinoid antitumoral action relies, at least partially, on the inhibition of the pro-tumorigenic Akt pathway. We also found that 91% of ErbB2-positive tumors express the non-psychotropic cannabinoid receptor CB2. Conclusions Taken together, these results provide a strong preclinical evidence for the use of cannabinoid-based therapies for the management of ErbB2-positive breast cancer.

  9. Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System

    Directory of Open Access Journals (Sweden)

    Min-Seok Park

    2009-10-01

    Full Text Available This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms.

  10. Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System.

    Science.gov (United States)

    Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

    2009-01-01

    This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms.

  11. Optimization of Signal Timing of Intersections by Internal Metering of Queue Time Ratio of Vehicles in Network Scale

    Directory of Open Access Journals (Sweden)

    Mina Ghanbarikarekani

    2016-06-01

    Full Text Available Optimization of signal timing in urban network is usually done by minimizing the delay times or queue lengths. Sincethe effect of each intersection on the whole network is not considered in the mentioned methods, traffic congestion may occur in network links. Therefore, this paper has aimed to provide a timing optimization algorithm for traffic signals using internal timing policy based on balancing queue time ratio of vehicles in network links. In the proposed algorithm, the difference between the real queue time ratio and the optimum one for each link of intersection was minimized. To evaluate the efficiency of the proposed algorithm on traffic performance, the proposed algorithm was applied in a hypothetical network. By comparing the simulating software outputs, before and after implementing the algorithm, it was concluded that the queue time ratio algorithm has improved the traffic parameters by increasing the flow as well as reducing the delay time and density of the network.

  12. Network analysis of epidermal growth factor signaling using integrated genomic, proteomic and phosphorylation data.

    Directory of Open Access Journals (Sweden)

    Katrina M Waters

    Full Text Available To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

  13. Network Analysis of Epidermal Growth Factor Signaling using Integrated Genomic, Proteomic and Phosphorylation Data

    Energy Technology Data Exchange (ETDEWEB)

    Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. S.; Thrall, Brian D.

    2012-03-29

    To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

  14. Signaling-Free Max-Min Airtime Fairness in IEEE 802.11 Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Youngsoo Lee

    2016-01-01

    Full Text Available We propose a novel media access control (MAC protocol, referred to as signaling-free max-min airtime fair (SMAF MAC, to improve fairness and channel utilization in ad hoc networks based on IEEE 802.11 wireless local area networks (WLANs. We introduce busy time ratio (BTR as a measure for max-min airtime fairness. Each node estimates its BTR and adjusts the transmission duration by means of frame aggregation and fragmentation, so that it can implicitly announce the BTR to neighbor nodes. Based on the announced BTR, each of the neighbor nodes controls its contention window. In this way, the SMAF MAC works in a distributed manner without the need to know the max-min fair share of airtime, and it does not require exchanging explicit control messages among nodes to attain fairness. Moreover, we successfully incorporate the hidden node detection and resolution mechanisms into the SMAF MAC to deal with the hidden node problem in ad hoc networks. The simulation results confirm that the SMAF MAC enhances airtime fairness without degrading channel utilization, and it effectively resolves several serious problems in ad hoc networks such as the starvation, performance anomaly, and hidden node problems.

  15. 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.

  16. Analysing the 21 cm signal from the epoch of reionization with artificial neural networks

    Science.gov (United States)

    Shimabukuro, Hayato; Semelin, Benoit

    2017-07-01

    The 21 cm signal from the epoch of reionization should be observed within the next decade. While a simple statistical detection is expected with Square Kilometre Array (SKA) pathfinders, the SKA will hopefully produce a full 3D mapping of the signal. To extract from the observed data constraints on the parameters describing the underlying astrophysical processes, inversion methods must be developed. For example, the Markov Chain Monte Carlo method has been successfully applied. Here, we test another possible inversion method: artificial neural networks (ANNs). We produce a training set that consists of 70 individual samples. Each sample is made of the 21 cm power spectrum at different redshifts produced with the 21cmFast code plus the value of three parameters used in the seminumerical simulations that describe astrophysical processes. Using this set, we train the network to minimize the error between the parameter values it produces as an output and the true values. We explore the impact of the architecture of the network on the quality of the training. Then we test the trained network on the new set of 54 test samples with different values of the parameters. We find that the quality of the parameter reconstruction depends on the sensitivity of the power spectrum to the different parameters at a given redshift, that including thermal noise and sample variance decreases the quality of the reconstruction and that using the power spectrum at several redshifts as an input to the ANN improves the quality of the reconstruction. We conclude that ANNs are a viable inversion method whose main strength is that they require a sparse exploration of the parameter space and thus should be usable with full numerical simulations.

  17. Application of signal processing techniques for islanding detection of distributed generation in distribution network: A review

    International Nuclear Information System (INIS)

    Raza, Safdar; Mokhlis, Hazlie; Arof, Hamzah; Laghari, J.A.; Wang, Li

    2015-01-01

    Highlights: • Pros & cons of conventional islanding detection techniques (IDTs) are discussed. • Signal processing techniques (SPTs) ability in detecting islanding is discussed. • SPTs ability in improving performance of passive techniques are discussed. • Fourier, s-transform, wavelet, HHT & tt-transform based IDTs are reviewed. • Intelligent classifiers (ANN, ANFIS, Fuzzy, SVM) application in SPT are discussed. - Abstract: High penetration of distributed generation resources (DGR) in distribution network provides many benefits in terms of high power quality, efficiency, and low carbon emissions in power system. However, efficient islanding detection and immediate disconnection of DGR is critical in order to avoid equipment damage, grid protection interference, and personnel safety hazards. Islanding detection techniques are mainly classified into remote, passive, active, and hybrid techniques. From these, passive techniques are more advantageous due to lower power quality degradation, lower cost, and widespread usage by power utilities. However, the main limitations of these techniques are that they possess a large non detection zones and require threshold setting. Various signal processing techniques and intelligent classifiers have been used to overcome the limitations of passive islanding. Signal processing techniques, in particular, are adopted due to their versatility, stability, cost effectiveness, and ease of modification. This paper presents a comprehensive overview of signal processing techniques used to improve common passive islanding detection techniques. A performance comparison between the signal processing based islanding detection techniques with existing techniques are also provided. Finally, this paper outlines the relative advantages and limitations of the signal processing techniques in order to provide basic guidelines for researchers and field engineers in determining the best method for their system

  18. A central integrator of transcription networks in plant stress and energy signalling.

    Science.gov (United States)

    Baena-González, Elena; Rolland, Filip; Thevelein, Johan M; Sheen, Jen

    2007-08-23

    Photosynthetic plants are the principal solar energy converter sustaining life on Earth. Despite its fundamental importance, little is known about how plants sense and adapt to darkness in the daily light-dark cycle, or how they adapt to unpredictable environmental stresses that compromise photosynthesis and respiration and deplete energy supplies. Current models emphasize diverse stress perception and signalling mechanisms. Using a combination of cellular and systems screens, we show here that the evolutionarily conserved Arabidopsis thaliana protein kinases, KIN10 and KIN11 (also known as AKIN10/At3g01090 and AKIN11/At3g29160, respectively), control convergent reprogramming of transcription in response to seemingly unrelated darkness, sugar and stress conditions. Sensing and signalling deprivation of sugar and energy, KIN10 targets a remarkably broad array of genes that orchestrate transcription networks, promote catabolism and suppress anabolism. Specific bZIP transcription factors partially mediate primary KIN10 signalling. Transgenic KIN10 overexpression confers enhanced starvation tolerance and lifespan extension, and alters architecture and developmental transitions. Significantly, double kin10 kin11 deficiency abrogates the transcriptional switch in darkness and stress signalling, and impairs starch mobilization at night and growth. These studies uncover surprisingly pivotal roles of KIN10/11 in linking stress, sugar and developmental signals to globally regulate plant metabolism, energy balance, growth and survival. In contrast to the prevailing view that sucrose activates plant SnRK1s (Snf1-related protein kinases), our functional analyses of Arabidopsis KIN10/11 provide compelling evidence that SnRK1s are inactivated by sugars and share central roles with the orthologous yeast Snf1 and mammalian AMPK in energy signalling.

  19. A Spectrum Sensing Method Based on Signal Feature and Clustering Algorithm in Cognitive Wireless Multimedia Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yongwei Zhang

    2017-01-01

    Full Text Available In order to solve the problem of difficulty in determining the threshold in spectrum sensing technologies based on the random matrix theory, a spectrum sensing method based on clustering algorithm and signal feature is proposed for Cognitive Wireless Multimedia Sensor Networks. Firstly, the wireless communication signal features are obtained according to the sampling signal covariance matrix. Then, the clustering algorithm is used to classify and test the signal features. Different signal features and clustering algorithms are compared in this paper. The experimental results show that the proposed method has better sensing performance.

  20. Investigations of Escherichia coli promoter sequences with artificial neural networks: new signals discovered upstream of the transcriptional startpoint

    DEFF Research Database (Denmark)

    Pedersen, Anders Gorm; Engelbrecht, Jacob

    1995-01-01

    We present a novel method for using the learning ability of a neural network as a measure of information in local regions of input data. Using the method to analyze Escherichia coli promoters, we discover all previously described signals, and furthermore find new signals that are regularly spaced...

  1. Dynamic optical routing and simultaneous generation of millimeter-wave signals for in-building access network

    NARCIS (Netherlands)

    Zou, S.; Okonkwo, C.M.; Cao, Z.; Tran, N.C.; Tangdiongga, E.; Koonen, A.M.J.

    2012-01-01

    Two-stage optical routing using SOA and integrated micro-ring resonator, and remote generation of millimeter-wave signals by optical frequency multiplication is demonstrated for inbuilding network. Both 150Mb/s 64-QAM and 802.11a WLAN signal at 38GHz are transmitted.

  2. Deciphering the hormonal signalling network behind the systemic resistance induced by Trichoderma harzianum in tomato

    Directory of Open Access Journals (Sweden)

    Ainhoa eMartinez-Medina

    2013-06-01

    Full Text Available Root colonization by selected Trichoderma isolates can activate in the plant a systemic defence response that is effective against a broad spectrum of plant pathogens. Diverse plant hormones play pivotal roles in the regulation of the defence signalling network that leads to the induction of systemic resistance triggered by beneficial organisms (ISR. Among them, jasmonic acid (JA and ethylene (ET signalling pathways are generally essential for ISR. However, Trichoderma ISR (TISR is believed to involve a wider variety of signalling routes, interconnected in a complex network of cross-communicating hormone pathways. Using tomato as a model, an integrative analysis of the main mechanisms involved in the systemic resistance induced by Trichoderma harzianum against the necrotrophic leaf pathogen Botrytis cinerea was performed. Root colonization by T. harzianum rendered the leaves more resistant to B. cinerea independently of major effects on plant nutrition. The analysis of disease development in shoots of tomato mutant lines impaired in the synthesis of the key defence related hormones JA, ET, salicylic acid (SA and abscisic acid (ABA and the peptide prosystemin (PS evidenced the requirement of intact JA, SA and ABA signalling pathways for a functional TISR. Expression analysis of several hormone related marker genes point to the role of priming for enhanced JA-dependent defence responses upon pathogen infection. Together, our results indicate that although TISR induced in tomato against the necrotrophs is mainly based on boosted JA-dependent responses, the pathways regulated by the plant hormones SA- and ABA are also required for successful TISR development

  3. Deciphering the hormonal signalling network behind the systemic resistance induced by Trichoderma harzianum in tomato

    Science.gov (United States)

    Martínez-Medina, Ainhoa; Fernández, Iván; Sánchez-Guzmán, María J.; Jung, Sabine C.; Pascual, Jose A.; Pozo, María J.

    2013-01-01

    Root colonization by selected Trichoderma isolates can activate in the plant a systemic defense response that is effective against a broad-spectrum of plant pathogens. Diverse plant hormones play pivotal roles in the regulation of the defense signaling network that leads to the induction of systemic resistance triggered by beneficial organisms [induced systemic resistance (ISR)]. Among them, jasmonic acid (JA) and ethylene (ET) signaling pathways are generally essential for ISR. However, Trichoderma ISR (TISR) is believed to involve a wider variety of signaling routes, interconnected in a complex network of cross-communicating hormone pathways. Using tomato as a model, an integrative analysis of the main mechanisms involved in the systemic resistance induced by Trichoderma harzianum against the necrotrophic leaf pathogen Botrytis cinerea was performed. Root colonization by T. harzianum rendered the leaves more resistant to B. cinerea independently of major effects on plant nutrition. The analysis of disease development in shoots of tomato mutant lines impaired in the synthesis of the key defense-related hormones JA, ET, salicylic acid (SA), and abscisic acid (ABA), and the peptide prosystemin (PS) evidenced the requirement of intact JA, SA, and ABA signaling pathways for a functional TISR. Expression analysis of several hormone-related marker genes point to the role of priming for enhanced JA-dependent defense responses upon pathogen infection. Together, our results indicate that although TISR induced in tomato against necrotrophs is mainly based on boosted JA-dependent responses, the pathways regulated by the plant hormones SA- and ABA are also required for successful TISR development. PMID:23805146

  4. Construction and Deciphering of Human Phosphorylation-Mediated Signaling Transduction Networks.

    Science.gov (United States)

    Zhang, Menghuan; Li, Hong; He, Ying; Sun, Han; Xia, Li; Wang, Lishun; Sun, Bo; Ma, Liangxiao; Zhang, Guoqing; Li, Jing; Li, Yixue; Xie, Lu

    2015-07-02

    Protein phosphorylation is the most abundant reversible covalent modification. Human protein kinases participate in almost all biological pathways, and approximately half of the kinases are associated with disease. PhoSigNet was designed to store and display human phosphorylation-mediated signal transduction networks, with additional information related to cancer. It contains 11 976 experimentally validated directed edges and 216 871 phosphorylation sites. Moreover, 3491 differentially expressed proteins in human cancer from dbDEPC, 18 907 human cancer variation sites from CanProVar, and 388 hyperphosphorylation sites from PhosphoSitePlus were collected as annotation information. Compared with other phosphorylation-related databases, PhoSigNet not only takes the kinase-substrate regulatory relationship pairs into account, but also extends regulatory relationships up- and downstream (e.g., from ligand to receptor, from G protein to kinase, and from transcription factor to targets). Furthermore, PhoSigNet allows the user to investigate the impact of phosphorylation modifications on cancer. By using one set of in-house time series phosphoproteomics data, the reconstruction of a conditional and dynamic phosphorylation-mediated signaling network was exemplified. We expect PhoSigNet to be a useful database and analysis platform benefiting both proteomics and cancer studies.

  5. Construction of a global pain systems network highlights phospholipid signaling as a regulator of heat nociception.

    Directory of Open Access Journals (Sweden)

    G Gregory Neely

    Full Text Available The ability to perceive noxious stimuli is critical for an animal's survival in the face of environmental danger, and thus pain perception is likely to be under stringent evolutionary pressure. Using a neuronal-specific RNAi knock-down strategy in adult Drosophila, we recently completed a genome-wide functional annotation of heat nociception that allowed us to identify α2δ3 as a novel pain gene. Here we report construction of an evolutionary-conserved, system-level, global molecular pain network map. Our systems map is markedly enriched for multiple genes associated with human pain and predicts a plethora of novel candidate pain pathways. One central node of this pain network is phospholipid signaling, which has been implicated before in pain processing. To further investigate the role of phospholipid signaling in mammalian heat pain perception, we analysed the phenotype of PIP5Kα and PI3Kγ mutant mice. Intriguingly, both of these mice exhibit pronounced hypersensitivity to noxious heat and capsaicin-induced pain, which directly mapped through PI3Kγ kinase-dead knock-in mice to PI3Kγ lipid kinase activity. Using single primary sensory neuron recording, PI3Kγ function was mechanistically linked to a negative regulation of TRPV1 channel transduction. Our data provide a systems map for heat nociception and reinforces the extraordinary conservation of molecular mechanisms of nociception across different species.

  6. Using Differential Evolution to Optimize Learning from Signals and Enhance Network Security

    Energy Technology Data Exchange (ETDEWEB)

    Harmer, Paul K [Air Force Institute of Technology; Temple, Michael A [Air Force Institute of Technology; Buckner, Mark A [ORNL; Farquhar, Ethan [ORNL

    2011-01-01

    Computer and communication network attacks are commonly orchestrated through Wireless Access Points (WAPs). This paper summarizes proof-of-concept research activity aimed at developing a physical layer Radio Frequency (RF) air monitoring capability to limit unauthorizedWAP access and mprove network security. This is done using Differential Evolution (DE) to optimize the performance of a Learning from Signals (LFS) classifier implemented with RF Distinct Native Attribute (RF-DNA) fingerprints. Performance of the resultant DE-optimized LFS classifier is demonstrated using 802.11a WiFi devices under the most challenging conditions of intra-manufacturer classification, i.e., using emissions of like-model devices that only differ in serial number. Using identical classifier input features, performance of the DE-optimized LFS classifier is assessed relative to a Multiple Discriminant Analysis / Maximum Likelihood (MDA/ML) classifier that has been used for previous demonstrations. The comparative assessment is made using both Time Domain (TD) and Spectral Domain (SD) fingerprint features. For all combinations of classifier type, feature type, and signal-to-noise ratio considered, results show that the DEoptimized LFS classifier with TD features is uperior and provides up to 20% improvement in classification accuracy with proper selection of DE parameters.

  7. Construction of a Global Pain Systems Network Highlights Phospholipid Signaling as a Regulator of Heat Nociception

    Science.gov (United States)

    Mair, Norbert; Racz, Ildiko; Milinkeviciute, Giedre; Meixner, Arabella; Nayanala, Swetha; Griffin, Robert S.; Belfer, Inna; Dai, Feng; Smith, Shad; Diatchenko, Luda; Marengo, Stefano; Haubner, Bernhard J.; Novatchkova, Maria; Gibson, Dustin; Maixner, William; Pospisilik, J. Andrew; Hirsch, Emilio; Whishaw, Ian Q.; Zimmer, Andreas; Gupta, Vaijayanti; Sasaki, Junko; Kanaho, Yasunori; Sasaki, Takehiko; Kress, Michaela; Woolf, Clifford J.; Penninger, Josef M.

    2012-01-01

    The ability to perceive noxious stimuli is critical for an animal's survival in the face of environmental danger, and thus pain perception is likely to be under stringent evolutionary pressure. Using a neuronal-specific RNAi knock-down strategy in adult Drosophila, we recently completed a genome-wide functional annotation of heat nociception that allowed us to identify α2δ3 as a novel pain gene. Here we report construction of an evolutionary-conserved, system-level, global molecular pain network map. Our systems map is markedly enriched for multiple genes associated with human pain and predicts a plethora of novel candidate pain pathways. One central node of this pain network is phospholipid signaling, which has been implicated before in pain processing. To further investigate the role of phospholipid signaling in mammalian heat pain perception, we analysed the phenotype of PIP5Kα and PI3Kγ mutant mice. Intriguingly, both of these mice exhibit pronounced hypersensitivity to noxious heat and capsaicin-induced pain, which directly mapped through PI3Kγ kinase-dead knock-in mice to PI3Kγ lipid kinase activity. Using single primary sensory neuron recording, PI3Kγ function was mechanistically linked to a negative regulation of TRPV1 channel transduction. Our data provide a systems map for heat nociception and reinforces the extraordinary conservation of molecular mechanisms of nociception across different species. PMID:23236288

  8. Classification of a Driver's cognitive workload levels using artificial neural network on ECG signals.

    Science.gov (United States)

    Tjolleng, Amir; Jung, Kihyo; Hong, Wongi; Lee, Wonsup; Lee, Baekhee; You, Heecheon; Son, Joonwoo; Park, Seikwon

    2017-03-01

    An artificial neural network (ANN) model was developed in the present study to classify the level of a driver's cognitive workload based on electrocardiography (ECG). ECG signals were measured on 15 male participants while they performed a simulated driving task as a primary task with/without an N-back task as a secondary task. Three time-domain ECG measures (mean inter-beat interval (IBI), standard deviation of IBIs, and root mean squared difference of adjacent IBIs) and three frequencydomain ECG measures (power in low frequency, power in high frequency, and ratio of power in low and high frequencies) were calculated. To compensate for individual differences in heart response during the driving tasks, a three-step data processing procedure was performed to ECG signals of each participant: (1) selection of two most sensitive ECG measures, (2) definition of three (low, medium, and high) cognitive workload levels, and (3) normalization of the selected ECG measures. An ANN model was constructed using a feed-forward network and scaled conjugate gradient as a back-propagation learning rule. The accuracy of the ANN classification model was found satisfactory for learning data (95%) and testing data (82%). Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Information processing in network architecture of genome controlled signal transduction circuit. A proposed theoretical explanation.

    Science.gov (United States)

    Chakraborty, Chiranjib; Sarkar, Bimal Kumar; Patel, Pratiksha; Agoramoorthy, Govindasamy

    2012-01-01

    In this paper, Shannon information theory has been applied to elaborate cell signaling. It is proposed that in the cellular network architecture, four components viz. source (DNA), transmitter (mRNA), receiver (protein) and destination (another protein) are involved. The message transmits from source (DNA) to transmitter (mRNA) and then passes through a noisy channel reaching finally the receiver (protein). The protein synthesis process is here considered as the noisy channel. Ultimately, signal is transmitted from receiver to destination (another protein). The genome network architecture elements were compared with genetic alphabet L = {A, C, G, T} with a biophysical model based on the popular Shannon information theory. This study found the channel capacity as maximum for zero error (sigma = 0) and at this condition, transition matrix becomes a unit matrix with rank 4. The transition matrix will be erroneous and finally at sigma = 1 channel capacity will be localized maxima with a value of 0.415 due to the increased value at sigma. On the other hand, minima exists at sigma = 0.75, where all transition probabilities become 0.25 and uncertainty will be maximum resulting in channel capacity with the minima value of zero.

  10. Two time-delay dynamic model on the transmission of malicious signals in wireless sensor network

    International Nuclear Information System (INIS)

    Keshri, Neha; Mishra, Bimal Kumar

    2014-01-01

    Highlights: • Role of time delay to reduce the adversary effect in WSN is explored. • Model with two time delays is proposed to analyse spread of malicious signal in WSN. • Dynamical behaviour of worm-free equilibrium and endemic equilibrium is shown. • Threshold condition for switch of stability are obtained analytically. • Relation between stability and the two time delays is also explored. - Abstract: Deployed in a hostile environment, motes of a Wireless sensor network (WSN) could be easily compromised by the attackers because of several constraints such as limited processing capabilities, memory space, and limited battery life time etc. While transmitting the data to their neighbour motes within the network, motes are easily compromised due to resource constraints. Here time delay can play an efficient role to reduce the adversary effect on motes. In this paper, we propose an epidemic model SEIR (Susceptible–Exposed–Infectious–Recovered) with two time delays to describe the transmission dynamics of malicious signals in wireless sensor network. The first delay accounts for an exposed (latent) period while the second delay is for the temporary immunity period due to multiple worm outbreaks. The dynamical behaviour of worm-free equilibrium and endemic equilibrium is shown from the point of stability which switches under some threshold condition specified by the basic reproduction number. Our results show that the global properties of equilibria also depends on the threshold condition and that latent and temporary immunity period in a mote does not affect the stability, but they play a positive role to control malicious attack. Moreover, numerical simulations are given to support the theoretical analysis

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

    Directory of Open Access Journals (Sweden)

    Sébastien De Landtsheer

    2018-05-01

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

  12. 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.

  13. 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.

  14. Automatic sleep stage classification based on EEG signals by using neural networks and wavelet packet coefficients.

    Science.gov (United States)

    Ebrahimi, Farideh; Mikaeili, Mohammad; Estrada, Edson; Nazeran, Homer

    2008-01-01

    Currently in the world there is an alarming number of people who suffer from sleep disorders. A number of biomedical signals, such as EEG, EMG, ECG and EOG are used in sleep labs among others for diagnosis and treatment of sleep related disorders. The usual method for sleep stage classification is visual inspection by a sleep specialist. This is a very time consuming and laborious exercise. Automatic sleep stage classification can facilitate this process. The definition of sleep stages and the sleep literature show that EEG signals are similar in Stage 1 of non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep. Therefore, in this work an attempt was made to classify four sleep stages consisting of Awake, Stage 1 + REM, Stage 2 and Slow Wave Stage based on the EEG signal alone. Wavelet packet coefficients and artificial neural networks were deployed for this purpose. Seven all night recordings from Physionet database were used in the study. The results demonstrated that these four sleep stages could be automatically discriminated from each other with a specificity of 94.4 +/- 4.5%, a of sensitivity 84.2+3.9% and an accuracy of 93.0 +/- 4.0%.

  15. Spatio-temporal remodeling of functional membrane microdomains organizes the signaling networks of a bacterium.

    Directory of Open Access Journals (Sweden)

    Johannes Schneider

    2015-04-01

    Full Text Available Lipid rafts are membrane microdomains specialized in the regulation of numerous cellular processes related to membrane organization, as diverse as signal transduction, protein sorting, membrane trafficking or pathogen invasion. It has been proposed that this functional diversity would require a heterogeneous population of raft domains with varying compositions. However, a mechanism for such diversification is not known. We recently discovered that bacterial membranes organize their signal transduction pathways in functional membrane microdomains (FMMs that are structurally and functionally similar to the eukaryotic lipid rafts. In this report, we took advantage of the tractability of the prokaryotic model Bacillus subtilis to provide evidence for the coexistence of two distinct families of FMMs in bacterial membranes, displaying a distinctive distribution of proteins specialized in different biological processes. One family of microdomains harbors the scaffolding flotillin protein FloA that selectively tethers proteins specialized in regulating cell envelope turnover and primary metabolism. A second population of microdomains containing the two scaffolding flotillins, FloA and FloT, arises exclusively at later stages of cell growth and specializes in adaptation of cells to stationary phase. Importantly, the diversification of membrane microdomains does not occur arbitrarily. We discovered that bacterial cells control the spatio-temporal remodeling of microdomains by restricting the activation of FloT expression to stationary phase. This regulation ensures a sequential assembly of functionally specialized membrane microdomains to strategically organize signaling networks at the right time during the lifespan of a bacterium.

  16. An artificial neural network model of energy expenditure using nonintegrated acceleration signals.

    Science.gov (United States)

    Rothney, Megan P; Neumann, Megan; Béziat, Ashley; Chen, Kong Y

    2007-10-01

    Accelerometers are a promising tool for characterizing physical activity patterns in free living. The major limitation in their widespread use to date has been a lack of precision in estimating energy expenditure (EE), which may be attributed to the oversimplified time-integrated acceleration signals and subsequent use of linear regression models for EE estimation. In this study, we collected biaxial raw (32 Hz) acceleration signals at the hip to develop a relationship between acceleration and minute-to-minute EE in 102 healthy adults using EE data collected for nearly 24 h in a room calorimeter as the reference standard. From each 1 min of acceleration data, we extracted 10 signal characteristics (features) that we felt had the potential to characterize EE intensity. Using these data, we developed a feed-forward/back-propagation artificial neural network (ANN) model with one hidden layer (12 x 20 x 1 nodes). Results of the ANN were compared with estimations using the ActiGraph monitor, a uniaxial accelerometer, and the IDEEA monitor, an array of five accelerometers. After training and validation (leave-one-subject out) were completed, the ANN showed significantly reduced mean absolute errors (0.29 +/- 0.10 kcal/min), mean squared errors (0.23 +/- 0.14 kcal(2)/min(2)), and difference in total EE (21 +/- 115 kcal/day), compared with both the IDEEA (P types under free-living conditions.

  17. Recurrent neural network approach to quantum signal: coherent state restoration for continuous-variable quantum key distribution

    Science.gov (United States)

    Lu, Weizhao; Huang, Chunhui; Hou, Kun; Shi, Liting; Zhao, Huihui; Li, Zhengmei; Qiu, Jianfeng

    2018-05-01

    In continuous-variable quantum key distribution (CV-QKD), weak signal carrying information transmits from Alice to Bob; during this process it is easily influenced by unknown noise which reduces signal-to-noise ratio, and strongly impacts reliability and stability of the communication. Recurrent quantum neural network (RQNN) is an artificial neural network model which can perform stochastic filtering without any prior knowledge of the signal and noise. In this paper, a modified RQNN algorithm with expectation maximization algorithm is proposed to process the signal in CV-QKD, which follows the basic rule of quantum mechanics. After RQNN, noise power decreases about 15 dBm, coherent signal recognition rate of RQNN is 96%, quantum bit error rate (QBER) drops to 4%, which is 6.9% lower than original QBER, and channel capacity is notably enlarged.

  18. Detection of erbB2 copy number variations in plasma of patients with esophageal carcinoma

    International Nuclear Information System (INIS)

    Andolfo, Immacolata; Orditura, Michele; Ciardiello, Fortunato; De Vita, Fernando; Zollo, Massimo; Petrosino, Giuseppe; Vecchione, Loredana; De Antonellis, Pasqualino; Capasso, Mario; Montanaro, Donatella; Gemei, Marica; Troncone, Giancarlo; Iolascon, Achille

    2011-01-01

    Mortality is high in patients with esophageal carcinoma as tumors are rarely detected before the disease has progressed to an advanced stage. Here, we sought to isolate cell-free DNA released into the plasma of patients with esophageal carcinoma, to analyze copy number variations of marker genes in the search for early detection of tumor progression. Plasma of 41 patients with esophageal carcinoma was prospectively collected before tumor resection and chemotherapy. Our dataset resulted heterogeneous for clinical data, resembling the characteristics of the tumor. DNA from the plasma was extracted to analyze copy number variations of the erbB2 gene using real-time PCR assays. The real-time PCR assays for erbB2 gene showed significant (P = 0.001) copy number variations in the plasma of patients with esophageal carcinoma, as compared to healthy controls with high sensitivity (80%) and specificity (95%). These variations in erbB2 were negatively correlated to the progression free survival of these patients (P = 0.03), and revealed a further risk category stratification of patients with low VEGF expression levels. The copy number variation of erbB2 gene from plasma can be used as prognostic marker for early detection of patients at risk of worse clinical outcome in esophageal cancer

  19. Cdk2-Null Mice Are Resistant to ErbB-2-Induced Mammary Tumorigenesis

    Directory of Open Access Journals (Sweden)

    Dipankar Ray

    2011-05-01

    Full Text Available The concept of targeting G1 cyclin-dependent kinases (CDKs in breast cancer treatments is supported by the fact that the genetic ablation of Cdk4 had minimal impacts on normal cell proliferation in majority of cell types, resulting in near-normal mouse development, whereas such loss of Cdk4 completely abrogated ErbB-2/neu-induced mammary tumorigenesis in mice. In most human breast cancer tissues, another G1-regulatory CDK, CDK2, is also hyperactivated by various mechanisms and is believed to be an important therapeutic target. In this report, we provide genetic evidence that CDK2 is essential for proliferation and oncogenesis of murine mammary epithelial cells. We observed that 87% of Cdk2-null mice were protected from ErbB-2-induced mammary tumorigenesis. Mouse embryonic fibroblasts isolated from Cdk2-null mouse showed resistance to various oncogene-induced transformation. Previously, we have reported that hemizygous loss of Cdc25A, the major activator of CDK2, can also protect mice from ErbB-2-induced mammary tumorigenesis [Cancer Res (2007 67(14: 6605–11]. Thus, we propose that CDC25A-CDK2 pathway is critical for the oncogenic action of ErbB-2 in mammary epithelial cells, in a manner similar to Cyclin D1/CDK4 pathway.

  20. A novel mutation in the tyrosine kinase domain of ERBB2 in hepatocellular carcinoma

    International Nuclear Information System (INIS)

    Bekaii-Saab, Tanios; Williams, Nita; Plass, Christoph; Calero, Miguel Villalona; Eng, Charis

    2006-01-01

    Several studies showed that gain-of-function somatic mutations affecting the catalytic domain of EGFR in non-small cell lung carcinomas were associated with response to gefitinib and erlotinib, both EGFR-tyrosine kinase inhibitors. In addition, 4% of non-small cell lung carcinomas were shown to have ERBB2 mutations in the kinase domain. In our study, we sought to determine if similar respective gain-of-function EGFR and ERBB2 mutations were present in hepatoma and/or biliary cancers. We extracted genomic DNA from 40 hepatoma (18) and biliary cancers (22) samples, and 44 adenocarcinomas of the lung, this latter as a positive control for mutation detection. We subjected those samples to PCR-based semi-automated double stranded nucleotide sequencing targeting exons 18–21 of EGFR and ERBB2. All samples were tested against matched normal DNA. We found 11% of hepatoma, but no biliary cancers, harbored a novel ERBB2 H878Y mutation in the activating domain. These newly described mutations may play a role in predicting response to EGFR-targeted therapy in hepatoma and their role should be explored in prospective studies

  1. Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI.

    Science.gov (United States)

    Wong, Chi Wah; Olafsson, Valur; Tal, Omer; Liu, Thomas T

    2012-10-15

    Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Optimization of neural network architecture for classification of radar jamming FM signals

    Science.gov (United States)

    Soto, Alberto; Mendoza, Ariadna; Flores, Benjamin C.

    2017-05-01

    The purpose of this study is to investigate several artificial Neural Network (NN) architectures in order to design a cognitive radar system capable of optimally distinguishing linear Frequency-Modulated (FM) signals from bandlimited Additive White Gaussian Noise (AWGN). The goal is to create a theoretical framework to determine an optimal NN architecture to achieve a Probability of Detection (PD) of 95% or higher and a Probability of False Alarm (PFA) of 1.5% or lower at 5 dB Signal to Noise Ratio (SNR). Literature research reveals that the frequency-domain power spectral densities characterize a signal more efficiently than its time-domain counterparts. Therefore, the input data is preprocessed by calculating the magnitude square of the Discrete Fourier Transform of the digitally sampled bandlimited AWGN and linear FM signals to populate a matrix containing N number of samples and M number of spectra. This matrix is used as input for the NN, and the spectra are divided as follows: 70% for training, 15% for validation, and 15% for testing. The study begins by experimentally deducing the optimal number of hidden neurons (1-40 neurons), then the optimal number of hidden layers (1-5 layers), and lastly, the most efficient learning algorithm. The training algorithms examined are: Resilient Backpropagation, Scaled Conjugate Gradient, Conjugate Gradient with Powell/Beale Restarts, Polak-Ribiére Conjugate Gradient, and Variable Learning Rate Backpropagation. We determine that an architecture with ten hidden neurons (or higher), one hidden layer, and a Scaled Conjugate Gradient for training algorithm encapsulates an optimal architecture for our application.

  3. A novel DLX3-PKC integrated signaling network drives keratinocyte differentiation.

    Science.gov (United States)

    Palazzo, Elisabetta; Kellett, Meghan D; Cataisson, Christophe; Bible, Paul W; Bhattacharya, Shreya; Sun, Hong-Wei; Gormley, Anna C; Yuspa, Stuart H; Morasso, Maria I

    2017-04-01

    Epidermal homeostasis relies on a well-defined transcriptional control of keratinocyte proliferation and differentiation, which is critical to prevent skin diseases such as atopic dermatitis, psoriasis or cancer. We have recently shown that the homeobox transcription factor DLX3 and the tumor suppressor p53 co-regulate cell cycle-related signaling and that this mechanism is functionally involved in cutaneous squamous cell carcinoma development. Here we show that DLX3 expression and its downstream signaling depend on protein kinase C α (PKCα) activity in skin. We found that following 12-O-tetradecanoyl-phorbol-13-acetate (TPA) topical treatment, DLX3 expression is significantly upregulated in the epidermis and keratinocytes from mice overexpressing PKCα by transgenic targeting (K5-PKCα), resulting in cell cycle block and terminal differentiation. Epidermis lacking DLX3 (DLX3cKO), which is linked to the development of a DLX3-dependent epidermal hyperplasia with hyperkeratosis and dermal leukocyte recruitment, displays enhanced PKCα activation, suggesting a feedback regulation of DLX3 and PKCα. Of particular significance, transcriptional activation of epidermal barrier, antimicrobial peptide and cytokine genes is significantly increased in DLX3cKO skin and further increased by TPA-dependent PKC activation. Furthermore, when inhibiting PKC activity, we show that epidermal thickness, keratinocyte proliferation and inflammatory cell infiltration are reduced and the PKC-DLX3-dependent gene expression signature is normalized. Independently of PKC, DLX3 expression specifically modulates regulatory networks such as Wnt signaling, phosphatase activity and cell adhesion. Chromatin immunoprecipitation sequencing analysis of primary suprabasal keratinocytes showed binding of DLX3 to the proximal promoter regions of genes associated with cell cycle regulation, and of structural proteins and transcription factors involved in epidermal differentiation. These results indicate

  4. Neuropeptidomics Mass Spectrometry Reveals Signaling Networks Generated by Distinct Protease Pathways in Human Systems

    Science.gov (United States)

    Hook, Vivian; Bandeira, Nuno

    2015-12-01

    Neuropeptides regulate intercellular signaling as neurotransmitters of the central and peripheral nervous systems, and as peptide hormones in the endocrine system. Diverse neuropeptides of distinct primary sequences of various lengths, often with post-translational modifications, coordinate and integrate regulation of physiological functions. Mass spectrometry-based analysis of the diverse neuropeptide structures in neuropeptidomics research is necessary to define the full complement of neuropeptide signaling molecules. Human neuropeptidomics has notable importance in defining normal and dysfunctional neuropeptide signaling in human health and disease. Neuropeptidomics has great potential for expansion in translational research opportunities for defining neuropeptide mechanisms of human diseases, providing novel neuropeptide drug targets for drug discovery, and monitoring neuropeptides as biomarkers of drug responses. In consideration of the high impact of human neuropeptidomics for health, an observed gap in this discipline is the few published articles in human neuropeptidomics compared with, for example, human proteomics and related mass spectrometry disciplines. Focus on human neuropeptidomics will advance new knowledge of the complex neuropeptide signaling networks participating in the fine control of neuroendocrine systems. This commentary review article discusses several human neuropeptidomics accomplishments that illustrate the rapidly expanding diversity of neuropeptides generated by protease processing of pro-neuropeptide precursors occurring within the secretory vesicle proteome. Of particular interest is the finding that human-specific cathepsin V participates in producing enkephalin and likely other neuropeptides, indicating unique proteolytic mechanisms for generating human neuropeptides. The field of human neuropeptidomics has great promise to solve new mechanisms in disease conditions, leading to new drug targets and therapeutic agents for human

  5. Three-dimensional WS2 nanosheet networks for H2O2 produced for cell signaling

    Science.gov (United States)

    Tang, Jing; Quan, Yingzhou; Zhang, Yueyu; Jiang, Min; Al-Enizi, Abdullah M.; Kong, Biao; An, Tiance; Wang, Wenshuo; Xia, Limin; Gong, Xingao; Zheng, Gengfeng

    2016-03-01

    Hydrogen peroxide (H2O2) is an important molecular messenger for cellular signal transduction. The capability of direct probing of H2O2 in complex biological systems can offer potential for elucidating its manifold roles in living systems. Here we report the fabrication of three-dimensional (3D) WS2 nanosheet networks with flower-like morphologies on a variety of conducting substrates. The semiconducting WS2 nanosheets with largely exposed edge sites on flexible carbon fibers enable abundant catalytically active sites, excellent charge transfer, and high permeability to chemicals and biomaterials. Thus, the 3D WS2-based nano-bio-interface exhibits a wide detection range, high sensitivity and rapid response time for H2O2, and is capable of visualizing endogenous H2O2 produced in living RAW 264.7 macrophage cells and neurons. First-principles calculations further demonstrate that the enhanced sensitivity of probing H2O2 is attributed to the efficient and spontaneous H2O2 adsorption on WS2 nanosheet edge sites. The combined features of 3D WS2 nanosheet networks suggest attractive new opportunities for exploring the physiological roles of reactive oxygen species like H2O2 in living systems.Hydrogen peroxide (H2O2) is an important molecular messenger for cellular signal transduction. The capability of direct probing of H2O2 in complex biological systems can offer potential for elucidating its manifold roles in living systems. Here we report the fabrication of three-dimensional (3D) WS2 nanosheet networks with flower-like morphologies on a variety of conducting substrates. The semiconducting WS2 nanosheets with largely exposed edge sites on flexible carbon fibers enable abundant catalytically active sites, excellent charge transfer, and high permeability to chemicals and biomaterials. Thus, the 3D WS2-based nano-bio-interface exhibits a wide detection range, high sensitivity and rapid response time for H2O2, and is capable of visualizing endogenous H2O2 produced in

  6. Small Molecule Tyrosine Kinase Inhibitors of ErbB2/HER2/Neu in the Treatment of Aggressive Breast Cancer

    Directory of Open Access Journals (Sweden)

    Richard L. Schroeder

    2014-09-01

    Full Text Available The human epidermal growth factor receptor 2 (HER2 is a member of the erbB class of tyrosine kinase receptors. These proteins are normally expressed at the surface of healthy cells and play critical roles in the signal transduction cascade in a myriad of biochemical pathways responsible for cell growth and differentiation. However, it is widely known that amplification and subsequent overexpression of the HER2 encoding oncogene results in unregulated cell proliferation in an aggressive form of breast cancer known as HER2-positive breast cancer. Existing therapies such as trastuzumab (Herceptin® and lapatinib (Tyverb/Tykerb®, a monoclonal antibody inhibitor and a dual EGFR/HER2 kinase inhibitor, respectively, are currently used in the treatment of HER2-positive cancers, although issues with high recurrence and acquired resistance still remain. Small molecule tyrosine kinase inhibitors provide attractive therapeutic targets, as they are able to block cell signaling associated with many of the proposed mechanisms for HER2 resistance. In this regard we aim to present a review on the available HER2 tyrosine kinase inhibitors, as well as those currently in development. The use of tyrosine kinase inhibitors as sequential or combinatorial therapeutic strategies with other HER family inhibitors is also discussed.

  7. A Wireless Biomedical Signal Interface System-on-Chip for Body Sensor Networks.

    Science.gov (United States)

    Lei Wang; Guang-Zhong Yang; Jin Huang; Jinyong Zhang; Li Yu; Zedong Nie; Cumming, D R S

    2010-04-01

    Recent years have seen the rapid development of biosensor technology, system-on-chip design, wireless technology. and ubiquitous computing. When assembled into an autonomous body sensor network (BSN), the technologies become powerful tools in well-being monitoring, medical diagnostics, and personal connectivity. In this paper, we describe the first demonstration of a fully customized mixed-signal silicon chip that has most of the attributes required for use in a wearable or implantable BSN. Our intellectual-property blocks include low-power analog sensor interface for temperature and pH, a data multiplexing and conversion module, a digital platform based around an 8-b microcontroller, data encoding for spread-spectrum wireless transmission, and a RF section requiring very few off-chip components. The chip has been fully evaluated and tested by connection to external sensors, and it satisfied typical system requirements.

  8. 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......, we investigate the potential of several techniques to combat these main threats. The analysis shows that traditional microscopic multiple-input multiple-output schemes with 2x2 or 4x4 antenna configurations are not enough to fulfil stringent reliability requirements. It is revealed how such antenna...... schemes must be complemented with macroscopic diversity as well as interference management techniques in order to ensure the necessary SINR outage performance. Based on the obtained performance results, it is discussed which of the feasible options fulfilling the ultra-reliable criteria are most promising...

  9. AUTOMATIC SEGMENTATION OF BROADCAST AUDIO SIGNALS USING AUTO ASSOCIATIVE NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    P. Dhanalakshmi

    2010-12-01

    Full Text Available In this paper, we describe automatic segmentation methods for audio broadcast data. Today, digital audio applications are part of our everyday lives. Since there are more and more digital audio databases in place these days, the importance of effective management for audio databases have become prominent. Broadcast audio data is recorded from the Television which comprises of various categories of audio signals. Efficient algorithms for segmenting the audio broadcast data into predefined categories are proposed. Audio features namely Linear prediction coefficients (LPC, Linear prediction cepstral coefficients, and Mel frequency cepstral coefficients (MFCC are extracted to characterize the audio data. Auto Associative Neural Networks are used to segment the audio data into predefined categories using the extracted features. Experimental results indicate that the proposed algorithms can produce satisfactory results.

  10. lpNet: a linear programming approach to reconstruct signal transduction networks.

    Science.gov (United States)

    Matos, Marta R A; Knapp, Bettina; Kaderali, Lars

    2015-10-01

    With the widespread availability of high-throughput experimental technologies it has become possible to study hundreds to thousands of cellular factors simultaneously, such as coding- or non-coding mRNA or protein concentrations. Still, extracting information about the underlying regulatory or signaling interactions from these data remains a difficult challenge. We present a flexible approach towards network inference based on linear programming. Our method reconstructs the interactions of factors from a combination of perturbation/non-perturbation and steady-state/time-series data. We show both on simulated and real data that our methods are able to reconstruct the underlying networks fast and efficiently, thus shedding new light on biological processes and, in particular, into disease's mechanisms of action. We have implemented the approach as an R package available through bioconductor. This R package is freely available under the Gnu Public License (GPL-3) from bioconductor.org (http://bioconductor.org/packages/release/bioc/html/lpNet.html) and is compatible with most operating systems (Windows, Linux, Mac OS) and hardware architectures. bettina.knapp@helmholtz-muenchen.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. R2NA: Received Signal Strength (RSS Ratio-Based Node Authentication for Body Area Network

    Directory of Open Access Journals (Sweden)

    Yang Wu

    2013-12-01

    Full Text Available The body area network (BAN is an emerging branch of wireless sensor networks for personalized applications. The services in BAN usually have a high requirement on security, especially for the medical diagnosis. One of the fundamental directions to ensure security in BAN is how to provide node authentication. Traditional research using cryptography relies on prior secrets shared among nodes, which leads to high resource cost. In addition, most existing non-cryptographic solutions exploit out-of-band (OOB channels, but they need the help of additional hardware support or significant modifications to the system software. To avoid the above problems, this paper presents a proximity-based node authentication scheme, which only uses wireless modules equipped on sensors. With only one sensor and one control unit (CU in BAN, we could detect a unique physical layer characteristic, namely, the difference between the received signal strength (RSS measured on different devices in BAN. Through the above-mentioned particular difference, we can tell whether the sender is close enough to be legitimate. We validate our scheme through both theoretical analysis and experiments, which are conducted on the real Shimmer nodes. The results demonstrate that our proposed scheme has a good security performance.

  12. Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

    Directory of Open Access Journals (Sweden)

    Bader Al-Anzi

    2015-05-01

    Full Text Available An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae. A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

  13. Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

    Science.gov (United States)

    Al-Anzi, Bader; Arpp, Patrick; Gerges, Sherif; Ormerod, Christopher; Olsman, Noah; Zinn, Kai

    2015-05-01

    An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae). A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

  14. A Routing Protocol Based on Received Signal Strength for Underwater Wireless Sensor Networks (UWSNs

    Directory of Open Access Journals (Sweden)

    Meiju Li

    2017-11-01

    Full Text Available Underwater wireless sensor networks (UWSNs are featured by long propagation delay, limited energy, narrow bandwidth, high BER (Bit Error Rate and variable topology structure. These features make it very difficult to design a short delay and high energy-efficiency routing protocol for UWSNs. In this paper, a routing protocol independent of location information is proposed based on received signal strength (RSS, which is called RRSS. In RRSS, a sensor node firstly establishes a vector from the node to a sink node; the length of the vector indicates the RSS of the beacon signal (RSSB from the sink node. A node selects the next-hop along the vector according to RSSB and the RSS of a hello packet (RSSH. The node nearer to the vector has higher priority to be a candidate next-hop. To avoid data packets being delivered to the neighbor nodes in a void area, a void-avoiding algorithm is introduced. In addition, residual energy is considered when selecting the next-hop. Meanwhile, we establish mathematic models to analyze the robustness and energy efficiency of RRSS. Lastly, we conduct extensive simulations, and the simulation results show RRSS can save energy consumption and decrease end-to-end delay.

  15. Analysis of acoustic emission signals at austempering of steels using neural networks

    Science.gov (United States)

    Łazarska, Malgorzata; Wozniak, Tadeusz Z.; Ranachowski, Zbigniew; Trafarski, Andrzej; Domek, Grzegorz

    2017-05-01

    Bearing steel 100CrMnSi6-4 and tool steel C105U were used to carry out this research with the steels being austempered to obtain a martensitic-bainitic structure. During the process quite a large number of acoustic emissions (AE) were observed. These signals were then analysed using neural networks resulting in the identification of three groups of events of: high, medium and low energy and in addition their spectral characteristics were plotted. The results were presented in the form of diagrams of AE incidence as a function of time. It was demonstrated that complex transformations of austenite into martensite and bainite occurred when austempering bearing steel at 160 °C and tool steel at 130 °C respectively. The selected temperatures of isothermal quenching of the tested steels were within the area near to MS temperature, which affected the complex course of phase transition. The high activity of AE is a typical occurrence for martensitic transformation and this is the transformation mechanism that induces the generation of AE signals of higher energy in the first stage of transition. In the second stage of transformation, the initially nucleated martensite accelerates the occurrence of the next bainitic transformation.

  16. An Eco-Driving Advisory System for Continuous Signalized Intersections by Vehicular Ad Hoc Network

    Directory of Open Access Journals (Sweden)

    Wei-Hsun Lee

    2018-01-01

    Full Text Available With the vehicular ad hoc network (VANET technology which support vehicle-to-vehicle (V2V and vehicle to road side unit (V2R/R2V communications, vehicles can preview the intersection signal plan such as signal countdown message. In this paper, an ecodriving advisory system (EDAS is proposed to reduce CO2 emissions and energy consumption by letting the vehicle continuously pass through multiple intersections with the minimum possibilities of stops. We extend the isolated intersection model to multiple continuous intersections scenario. A hybrid method combining three strategies including maximized throughput model (MTM, smooth speed model (SSM, and minimized acceleration and deceleration (MinADM is designed, and it is compared with related works maximized throughput model (MaxTM, open traffic light control model (OTLCM, and predictive cruise control (PCC models. Some issues for the practical application including safe car following, queue clearing, and gliding mode are discussed and conquered. Simulation results show that the proposed model outperforms OTLCM 25.1%~81.2% in the isolated intersection scenario for the CO2 emissions and 20.5%~84.3% in averaged travel time. It also performs better than the compared PCC model in CO2 emissions (19.9%~31.2% as well as travel time (24.5%~35.9% in the multiple intersections scenario.

  17. MicroRNAs as Regulator of Signaling Networks in Metastatic Colon Cancer

    Science.gov (United States)

    Wang, Jian; Du, Yong; Liu, Xiaoming; Cho, William C.; Yang, Yinxue

    2015-01-01

    MicroRNAs (miRNAs) are a class of small, noncoding RNA molecules capable of regulating gene expression translationally and/or transcriptionally. A large number of evidence have demonstrated that miRNAs have a functional role in both physiological and pathological processes by regulating the expression of their target genes. Recently, the functionalities of miRNAs in the initiation, progression, angiogenesis, metastasis, and chemoresistance of tumors have gained increasing attentions. Particularly, the alteration of miRNA profiles has been correlated with the transformation and metastasis of various cancers, including colon cancer. This paper reports the latest findings on miRNAs involved in different signaling networks leading to colon cancer metastasis, mainly focusing on miRNA profiling and their roles in PTEN/PI3K, EGFR, TGFβ, and p53 signaling pathways of metastatic colon cancer. The potential of miRNAs used as biomarkers in the diagnosis, prognosis, and therapeutic targets in colon cancer is also discussed. PMID:26064956

  18. MicroRNAs as Regulator of Signaling Networks in Metastatic Colon Cancer.

    Science.gov (United States)

    Wang, Jian; Du, Yong; Liu, Xiaoming; Cho, William C; Yang, Yinxue

    2015-01-01

    MicroRNAs (miRNAs) are a class of small, noncoding RNA molecules capable of regulating gene expression translationally and/or transcriptionally. A large number of evidence have demonstrated that miRNAs have a functional role in both physiological and pathological processes by regulating the expression of their target genes. Recently, the functionalities of miRNAs in the initiation, progression, angiogenesis, metastasis, and chemoresistance of tumors have gained increasing attentions. Particularly, the alteration of miRNA profiles has been correlated with the transformation and metastasis of various cancers, including colon cancer. This paper reports the latest findings on miRNAs involved in different signaling networks leading to colon cancer metastasis, mainly focusing on miRNA profiling and their roles in PTEN/PI3K, EGFR, TGFβ, and p53 signaling pathways of metastatic colon cancer. The potential of miRNAs used as biomarkers in the diagnosis, prognosis, and therapeutic targets in colon cancer is also discussed.

  19. MicroRNAs as Regulator of Signaling Networks in Metastatic Colon Cancer

    Directory of Open Access Journals (Sweden)

    Jian Wang

    2015-01-01

    Full Text Available MicroRNAs (miRNAs are a class of small, noncoding RNA molecules capable of regulating gene expression translationally and/or transcriptionally. A large number of evidence have demonstrated that miRNAs have a functional role in both physiological and pathological processes by regulating the expression of their target genes. Recently, the functionalities of miRNAs in the initiation, progression, angiogenesis, metastasis, and chemoresistance of tumors have gained increasing attentions. Particularly, the alteration of miRNA profiles has been correlated with the transformation and metastasis of various cancers, including colon cancer. This paper reports the latest findings on miRNAs involved in different signaling networks leading to colon cancer metastasis, mainly focusing on miRNA profiling and their roles in PTEN/PI3K, EGFR, TGFβ, and p53 signaling pathways of metastatic colon cancer. The potential of miRNAs used as biomarkers in the diagnosis, prognosis, and therapeutic targets in colon cancer is also discussed.

  20. Traffic Congestion Evaluation and Signal Control Optimization Based on Wireless Sensor Networks: Model and Algorithms

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2012-01-01

    Full Text Available This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the congestion factor which can be used to evaluate the real-time traffic congestion status along the segment and to predict the subcritical state of traffic jams. The result is expected to support the timing phase optimization of traffic light control for the purpose of avoiding traffic congestion before its formation. We simulate the traffic monitoring based on the Mobile Century dataset and analyze the performance of traffic light control on VISSIM platform when congestion factor is introduced into the signal timing optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring and evaluate traffic congestion status with high precision. It is helpful to remarkably alleviate urban traffic congestion and decrease the average traffic delays and maximum queue length.

  1. A knowledge representation meta-model for rule-based modelling of signalling networks

    Directory of Open Access Journals (Sweden)

    Adrien Basso-Blandin

    2016-03-01

    Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

  2. Negative transcriptional control of ERBB2 gene by MBP-1 and HDAC1: diagnostic implications in breast cancer

    International Nuclear Information System (INIS)

    Contino, Flavia; Mazzarella, Claudia; Ferro, Arianna; Lo Presti, Mariavera; Roz, Elena; Lupo, Carmelo; Perconti, Giovanni; Giallongo, Agata; Feo, Salvatore

    2013-01-01

    The human ERBB2 gene is frequently amplified in breast tumors, and its high expression is associated with poor prognosis. We previously reported a significant inverse correlation between Myc promoter-binding protein-1 (MBP-1) and ERBB2 expression in primary breast invasive ductal carcinoma (IDC). MBP-1 is a transcriptional repressor of the c-MYC gene that acts by binding to the P2 promoter; only one other direct target of MBP-1, the COX2 gene, has been identified so far. To gain new insights into the functional relationship linking MBP-1 and ERBB2 in breast cancer, we have investigated the effects of MBP-1 expression on endogenous ERBB2 transcript and protein levels, as well as on transcription promoter activity, by transient-transfection of SKBr3 cells. Reporter gene and chromatin immunoprecipitation assays were used to dissect the ERBB2 promoter and identify functional MBP-1 target sequences. We also investigated the relative expression of MBP-1 and HDAC1 in IDC and normal breast tissues by immunoblot analysis and immunohistochemistry. Transfection experiments and chromatin immunoprecipitation assays in SKBr3 cells indicated that MBP-1 negatively regulates the ERBB2 gene by binding to a genomic region between nucleotide −514 and −262 of the proximal promoter; consistent with this, a concomitant recruitment of HDAC1 and loss of acetylated histone H4 was observed. In addition, we found high expression of MBP-1 and HDAC1 in normal tissues and a statistically significant inverse correlation with ErbB2 expression in the paired tumor samples. Altogether, our in vitro and in vivo data indicate that the ERBB2 gene is a novel MBP-1 target, and immunohistochemistry analysis of primary tumors suggests that the concomitant high expression of MBP-1 and HDAC1 may be considered a diagnostic marker of cancer progression for breast IDC

  3. Experiment on Synchronous Timing Signal Detection from ISDB-T Terrestrial Digital TV Signal with Application to Autonomous Distributed ITS-IVC Network

    Science.gov (United States)

    Karasawa, Yoshio; Kumagai, Taichi; Takemoto, Atsushi; Fujii, Takeo; Ito, Kenji; Suzuki, Noriyoshi

    A novel timing synchronizing scheme is proposed for use in inter-vehicle communication (IVC) with an autonomous distributed intelligent transport system (ITS). The scheme determines the timing of packet signal transmission in the IVC network and employs the guard interval (GI) timing in the orthogonal frequency divisional multiplexing (OFDM) signal currently used for terrestrial broadcasts in the Japanese digital television system (ISDB-T). This signal is used because it is expected that the automotive market will demand the capability for cars to receive terrestrial digital TV broadcasts in the near future. The use of broadcasts by automobiles presupposes that the on-board receivers are capable of accurately detecting the GI timing data in an extremely low carrier-to-noise ratio (CNR) condition regardless of a severe multipath environment which will introduce broad scatter in signal arrival times. Therefore, we analyzed actual broadcast signals received in a moving vehicle in a field experiment and showed that the GI timing signal is detected with the desired accuracy even in the case of extremely low-CNR environments. Some considerations were also given about how to use these findings.

  4. CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms.

    Science.gov (United States)

    Terfve, Camille; Cokelaer, Thomas; Henriques, David; MacNamara, Aidan; Goncalves, Emanuel; Morris, Melody K; van Iersel, Martijn; Lauffenburger, Douglas A; Saez-Rodriguez, Julio

    2012-10-18

    Cells process signals using complex and dynamic networks. Studying how this is performed in a context and cell type specific way is essential to understand signaling both in physiological and diseased situations. Context-specific medium/high throughput proteomic data measured upon perturbation is now relatively easy to obtain but formalisms that can take advantage of these features to build models of signaling are still comparatively scarce. Here we present CellNOptR, an open-source R software package for building predictive logic models of signaling networks by training networks derived from prior knowledge to signaling (typically phosphoproteomic) data. CellNOptR features different logic formalisms, from Boolean models to differential equations, in a common framework. These different logic model representations accommodate state and time values with increasing levels of detail. We provide in addition an interface via Cytoscape (CytoCopteR) to facilitate use and integration with Cytoscape network-based capabilities. Models generated with this pipeline have two key features. First, they are constrained by prior knowledge about the network but trained to data. They are therefore context and cell line specific, which results in enhanced predictive and mechanistic insights. Second, they can be built using different logic formalisms depending on the richness of the available data. Models built with CellNOptR are useful tools to understand how signals are processed by cells and how this is altered in disease. They can be used to predict the effect of perturbations (individual or in combinations), and potentially to engineer therapies that have differential effects/side effects depending on the cell type or context.

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

    Science.gov (United States)

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

    2016-10-01

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

  6. A novel DLX3–PKC integrated signaling network drives keratinocyte differentiation

    Science.gov (United States)

    Palazzo, Elisabetta; Kellett, Meghan D; Cataisson, Christophe; Bible, Paul W; Bhattacharya, Shreya; Sun, Hong-wei; Gormley, Anna C; Yuspa, Stuart H; Morasso, Maria I

    2017-01-01

    Epidermal homeostasis relies on a well-defined transcriptional control of keratinocyte proliferation and differentiation, which is critical to prevent skin diseases such as atopic dermatitis, psoriasis or cancer. We have recently shown that the homeobox transcription factor DLX3 and the tumor suppressor p53 co-regulate cell cycle-related signaling and that this mechanism is functionally involved in cutaneous squamous cell carcinoma development. Here we show that DLX3 expression and its downstream signaling depend on protein kinase C α (PKCα) activity in skin. We found that following 12-O-tetradecanoyl-phorbol-13-acetate (TPA) topical treatment, DLX3 expression is significantly upregulated in the epidermis and keratinocytes from mice overexpressing PKCα by transgenic targeting (K5-PKCα), resulting in cell cycle block and terminal differentiation. Epidermis lacking DLX3 (DLX3cKO), which is linked to the development of a DLX3-dependent epidermal hyperplasia with hyperkeratosis and dermal leukocyte recruitment, displays enhanced PKCα activation, suggesting a feedback regulation of DLX3 and PKCα. Of particular significance, transcriptional activation of epidermal barrier, antimicrobial peptide and cytokine genes is significantly increased in DLX3cKO skin and further increased by TPA-dependent PKC activation. Furthermore, when inhibiting PKC activity, we show that epidermal thickness, keratinocyte proliferation and inflammatory cell infiltration are reduced and the PKC-DLX3-dependent gene expression signature is normalized. Independently of PKC, DLX3 expression specifically modulates regulatory networks such as Wnt signaling, phosphatase activity and cell adhesion. Chromatin immunoprecipitation sequencing analysis of primary suprabasal keratinocytes showed binding of DLX3 to the proximal promoter regions of genes associated with cell cycle regulation, and of structural proteins and transcription factors involved in epidermal differentiation. These results indicate

  7. 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

  8. 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

  9. Bearings Fault Diagnosis Based on Convolutional Neural Networks with 2-D Representation of Vibration Signals as Input

    Directory of Open Access Journals (Sweden)

    Zhang Wei

    2017-01-01

    Full Text Available Periodic vibration signals captured by the accelerometers carry rich information for bearing fault diagnosis. Existing methods mostly rely on hand-crafted time-consuming preprocessing of data to acquire suitable features. In this paper, we use an easy and effective method to transform the 1-D temporal vibration signal into a 2-D image. With the signal image, convolutional Neural Network (CNN is used to train the raw vibration data. As powerful feature extractor and classifier for image recognition, CNN can learn to acquire features most suitable for the classification task by being trained. With the image format of vibration signals, the neuron in fully-connected layer of CNN can see farther and capture the periodic feature of signals. According to the results of the experiments, when fed in enough training samples, the proposed method outperforms other common methods. The proposed method can also be applied to solve intelligent diagnosis problems of other machine systems.

  10. DMPD: Glucocorticoids and the innate immune system: crosstalk with the toll-likereceptor signaling network. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 17576036 Glucocorticoids and the innate immune system: crosstalk with the toll-like...07 May 13. (.png) (.svg) (.html) (.csml) Show Glucocorticoids and the innate immune system: crosstalk with t...nd the innate immune system: crosstalk with the toll-likereceptor signaling network. Authors Chinenov Y, Rog

  11. An Evolutionarily Conserved Network Mediates Development of the zona limitans intrathalamica, a Sonic Hedgehog-Secreting Caudal Forebrain Signaling Center

    Directory of Open Access Journals (Sweden)

    Elena Sena

    2016-10-01

    Full Text Available Recent studies revealed new insights into the development of a unique caudal forebrain-signaling center: the zona limitans intrathalamica (zli. The zli is the last brain signaling center to form and the first forebrain compartment to be established. It is the only part of the dorsal neural tube expressing the morphogen Sonic Hedgehog (Shh whose activity participates in the survival, growth and patterning of neuronal progenitor subpopulations within the thalamic complex. Here, we review the gene regulatory network of transcription factors and cis-regulatory elements that underlies formation of a shh-expressing delimitated domain in the anterior brain. We discuss evidence that this network predates the origin of chordates. We highlight the contribution of Shh, Wnt and Notch signaling to zli development and discuss implications for the fact that the morphogen Shh relies on primary cilia for signal transduction. The network that underlies zli development also contributes to thalamus induction, and to its patterning once the zli has been set up. We present an overview of the brain malformations possibly associated with developmental defects in this gene regulatory network (GRN.

  12. A neural network method for identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites

    DEFF Research Database (Denmark)

    Nielsen, Henrik; Engelbrecht, Jacob; Brunak, Søren

    1997-01-01

    We have developed a new method for the identication of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs signicantly better than previous prediction schemes, and can easily be applied to genome...

  13. Rapid phospho-turnover by receptor tyrosine kinases impacts downstream signaling and drug binding.

    Science.gov (United States)

    Kleiman, Laura B; Maiwald, Thomas; Conzelmann, Holger; Lauffenburger, Douglas A; Sorger, Peter K

    2011-09-02

    Epidermal growth factor receptors (ErbB1-4) are oncogenic receptor tyrosine kinases (RTKs) that regulate diverse cellular processes. In this study, we combine measurement and mathematical modeling to quantify phospho-turnover at ErbB receptors in human cells and to determine the consequences for signaling and drug binding. We find that phosphotyrosine residues on ErbB1 have half-lives of a few seconds and therefore turn over 100-1000 times in the course of a typical immediate-early response to ligand. Rapid phospho-turnover is also observed for EGF-activated ErbB2 and ErbB3, unrelated RTKs, and multiple intracellular adaptor proteins and signaling kinases. Thus, the complexes formed on the cytoplasmic tail of active receptors and the downstream signaling kinases they control are highly dynamic and antagonized by potent phosphatases. We develop a kinetic scheme for binding of anti-ErbB1 drugs to receptors and show that rapid phospho-turnover significantly impacts their mechanisms of action. Copyright © 2011 Elsevier Inc. All rights reserved.

  14. Application of artificial neural network to search for gravitational-wave signals associated with short gamma-ray bursts

    International Nuclear Information System (INIS)

    Kim, Kyungmin; Lee, Hyun Kyu; Harry, Ian W; Hodge, Kari A; Kim, Young-Min; Lee, Chang-Hwan; Oh, John J; Oh, Sang Hoon; Son, Edwin J

    2015-01-01

    We apply a machine learning algorithm, the artificial neural network, to the search for gravitational-wave signals associated with short gamma-ray bursts (GRBs). The multi-dimensional samples consisting of data corresponding to the statistical and physical quantities from the coherent search pipeline are fed into the artificial neural network to distinguish simulated gravitational-wave signals from background noise artifacts. Our result shows that the data classification efficiency at a fixed false alarm probability (FAP) is improved by the artificial neural network in comparison to the conventional detection statistic. Specifically, the distance at 50% detection probability at a fixed false positive rate is increased about 8%–14% for the considered waveform models. We also evaluate a few seconds of the gravitational-wave data segment using the trained networks and obtain the FAP. We suggest that the artificial neural network can be a complementary method to the conventional detection statistic for identifying gravitational-wave signals related to the short GRBs. (paper)

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

    Science.gov (United States)

    Jwa, Nam-Soo; Hwang, Byung Kook

    2017-01-01

    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.

  16. 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.

  17. A membrane protein / signaling protein interaction network for Arabidopsis version AMPv2

    Directory of Open Access Journals (Sweden)

    Sylvie Lalonde

    2010-09-01

    Full Text Available Interactions between membrane proteins and the soluble fraction are essential for signal transduction and for regulating nutrient transport. To gain insights into the membrane-based interactome, 3,852 open reading frames (ORFs out of a target list of 8,383 representing membrane and signaling proteins from Arabidopsis thaliana were cloned into a Gateway compatible vector. The mating-based split-ubiquitin system was used to screen for potential protein-protein interactions (pPPIs among 490 Arabidopsis ORFs. A binary robotic screen between 142 receptor-like kinases, 72 transporters, 57 soluble protein kinases and phosphatases, 40 glycosyltransferases, 95 proteins of various functions and 89 proteins with unknown function detected 387 out of 90,370 possible PPIs. A secondary screen confirmed 343 (of 387 pPPIs between 179 proteins, yielding a scale-free network (r2=0.863. Eighty of 142 transmembrane receptor-like kinases (RLK tested positive, identifying three homomers, 63 heteromers and 80 pPPIs with other proteins. Thirty-one out of 142 RLK interactors (including RLKs had previously been found to be phosphorylated; thus interactors may be substrates for respective RLKs. None of the pPPIs described here had been reported in the major interactome databases, including potential interactors of G protein-coupled receptors, phospholipase C, and AMT ammonium transporters. Two RLKs found as putative interactors of AMT1;1 were independently confirmed using a split luciferase assay in Arabidopsis protoplasts. These RLKs may be involved in ammonium-dependent phosphorylation of the C-terminus and regulation of ammonium uptake activity. The robotic screening method established here will enable a systematic analysis of membrane protein interactions in fungi, plants and metazoa.

  18. 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.

  19. Assessment of general public exposure to lte signals compared to other cellular networks present in Thessaloniki, Greece

    International Nuclear Information System (INIS)

    Gkonis, Fotios; Boursianis, Achilles; Samaras, Theodoros

    2017-01-01

    To assess general public exposure to electromagnetic fields from Long Term Evolution (LTE) base stations, measurements at 10 sites in Thessaloniki, Greece were performed. Results are compared with other mobile cellular networks currently in use. All exposure values satisfy the guidelines for general public exposure of the International Commission on Non-Ionizing Radiation Protection (ICNIRP), as well as the reference levels by the Greek legislation at all sites. LTE electric field measurements were recorded up to 0.645 V/m. By applying the ICNIRP guidelines, the exposure ratio for all LTE signals is between 2.9 x 10"-"5 and 2.8 x 10"-"2. From the measurements results it is concluded that the average and maximum power density contribution of LTE down-link signals to the overall cellular networks signals are 7.8% and 36.7%, respectively. (authors)

  20. Poly (A+ transcriptome assessment of ERBB2-induced alterations in breast cell lines.

    Directory of Open Access Journals (Sweden)

    Dirce Maria Carraro

    Full Text Available We report the first quantitative and qualitative analysis of the poly (A⁺ transcriptome of two human mammary cell lines, differentially expressing (human epidermal growth factor receptor an oncogene over-expressed in approximately 25% of human breast tumors. Full-length cDNA populations from the two cell lines were digested enzymatically, individually tagged according to a customized method for library construction, and simultaneously sequenced by the use of the Titanium 454-Roche-platform. Comprehensive bioinformatics analysis followed by experimental validation confirmed novel genes, splicing variants, single nucleotide polymorphisms, and gene fusions indicated by RNA-seq data from both samples. Moreover, comparative analysis showed enrichment in alternative events, especially in the exon usage category, in ERBB2 over-expressing cells, data indicating regulation of alternative splicing mediated by the oncogene. Alterations in expression levels of genes, such as LOX, ATP5L, GALNT3, and MME revealed by large-scale sequencing were confirmed between cell lines as well as in tumor specimens with different ERBB2 backgrounds. This approach was shown to be suitable for structural, quantitative, and qualitative assessment of complex transcriptomes and revealed new events mediated by ERBB2 overexpression, in addition to potential molecular targets for breast cancer that are driven by this oncogene.

  1. Investigating the effect of traditional Persian music on ECG signals in young women using wavelet transform and neural networks.

    Science.gov (United States)

    Abedi, Behzad; Abbasi, Ataollah; Goshvarpour, Atefeh

    2017-05-01

    In the past few decades, several studies have reported the physiological effects of listening to music. The physiological effects of different music types on different people are different. In the present study, we aimed to examine the effects of listening to traditional Persian music on electrocardiogram (ECG) signals in young women. Twenty-two healthy females participated in this study. ECG signals were recorded under two conditions: rest and music. For each ECG signal, 20 morphological and wavelet-based features were selected. Artificial neural network (ANN) and probabilistic neural network (PNN) classifiers were used for the classification of ECG signals during and before listening to music. Collected data were separated into two data sets: train and test. Classification accuracies of 88% and 97% were achieved in train data sets using ANN and PNN, respectively. In addition, the test data set was employed for evaluating the classifiers, and classification rates of 84% and 93% were obtained using ANN and PNN, respectively. The present study investigated the effect of music on ECG signals based on wavelet transform and morphological features. The results obtained here can provide a good understanding on the effects of music on ECG signals to researchers.

  2. Multiobjective Reinforcement Learning for Traffic Signal Control Using Vehicular Ad Hoc Network

    Directory of Open Access Journals (Sweden)

    Houli Duan

    2010-01-01

    Full Text Available We propose a new multiobjective control algorithm based on reinforcement learning for urban traffic signal control, named multi-RL. A multiagent structure is used to describe the traffic system. A vehicular ad hoc network is used for the data exchange among agents. A reinforcement learning algorithm is applied to predict the overall value of the optimization objective given vehicles' states. The policy which minimizes the cumulative value of the optimization objective is regarded as the optimal one. In order to make the method adaptive to various traffic conditions, we also introduce a multiobjective control scheme in which the optimization objective is selected adaptively to real-time traffic states. The optimization objectives include the vehicle stops, the average waiting time, and the maximum queue length of the next intersection. In addition, we also accommodate a priority control to the buses and the emergency vehicles through our model. The simulation results indicated that our algorithm could perform more efficiently than traditional traffic light control methods.

  3. Statistical Modeling of Large-Scale Signal Path Loss in Underwater Acoustic Networks

    Directory of Open Access Journals (Sweden)

    Manuel Perez Malumbres

    2013-02-01

    Full Text Available In an underwater acoustic channel, the propagation conditions are known to vary in time, causing the deviation of the received signal strength from the nominal value predicted by a deterministic propagation model. To facilitate a large-scale system design in such conditions (e.g., power allocation, we have developed a statistical propagation model in which the transmission loss is treated as a random variable. By applying repetitive computation to the acoustic field, using ray tracing for a set of varying environmental conditions (surface height, wave activity, small node displacements around nominal locations, etc., an ensemble of transmission losses is compiled and later used to infer the statistical model parameters. A reasonable agreement is found with log-normal distribution, whose mean obeys a log-distance increases, and whose variance appears to be constant for a certain range of inter-node distances in a given deployment location. The statistical model is deemed useful for higher-level system planning, where simulation is needed to assess the performance of candidate network protocols under various resource allocation policies, i.e., to determine the transmit power and bandwidth allocation necessary to achieve a desired level of performance (connectivity, throughput, reliability, etc..

  4. Systems Medicine in Oncology: Signaling Network Modeling and New-Generation Decision-Support Systems.

    Science.gov (United States)

    Parodi, Silvio; Riccardi, Giuseppe; Castagnino, Nicoletta; Tortolina, Lorenzo; Maffei, Massimo; Zoppoli, Gabriele; Nencioni, Alessio; Ballestrero, Alberto; Patrone, Franco

    2016-01-01

    Two different perspectives are the main focus of this book chapter: (1) A perspective that looks to the future, with the goal of devising rational associations of targeted inhibitors against distinct altered signaling-network pathways. This goal implies a sufficiently in-depth molecular diagnosis of the personal cancer of a given patient. A sufficiently robust and extended dynamic modeling will suggest rational combinations of the abovementioned oncoprotein inhibitors. The work toward new selective drugs, in the field of medicinal chemistry, is very intensive. Rational associations of selective drug inhibitors will become progressively a more realistic goal within the next 3-5 years. Toward the possibility of an implementation in standard oncologic structures of technologically sufficiently advanced countries, new (legal) rules probably will have to be established through a consensus process, at the level of both diagnostic and therapeutic behaviors.(2) The cancer patient of today is not the patient of 5-10 years from now. How to support the choice of the most convenient (and already clinically allowed) treatment for an individual cancer patient, as of today? We will consider the present level of artificial intelligence (AI) sophistication and the continuous feeding, updating, and integration of cancer-related new data, in AI systems. We will also report briefly about one of the most important projects in this field: IBM Watson US Cancer Centers. Allowing for a temporal shift, in the long term the two perspectives should move in the same direction, with a necessary time lag between them.

  5. Comparative Phosphoproteomics Reveals an Important Role of MKK2 in Banana (Musa spp.) Cold Signal Network

    Science.gov (United States)

    Gao, Jie; Zhang, Sheng; He, Wei-Di; Shao, Xiu-Hong; Li, Chun-Yu; Wei, Yue-Rong; Deng, Gui-Ming; Kuang, Rui-Bin; Hu, Chun-Hua; Yi, Gan-Jun; Yang, Qiao-Song

    2017-01-01

    Low temperature is one of the key environmental stresses, which greatly affects global banana production. However, little is known about the global phosphoproteomes in Musa spp. and their regulatory roles in response to cold stress. In this study, we conducted a comparative phosphoproteomic profiling of cold-sensitive Cavendish Banana and relatively cold tolerant Dajiao under cold stress. Phosphopeptide abundances of five phosphoproteins involved in MKK2 interaction network, including MKK2, HY5, CaSR, STN7 and kinesin-like protein, show a remarkable difference between Cavendish Banana and Dajiao in response to cold stress. Western blotting of MKK2 protein and its T31 phosphorylated peptide verified the phosphoproteomic results of increased T31 phosphopeptide abundance with decreased MKK2 abundance in Daojiao for a time course of cold stress. Meanwhile increased expression of MKK2 with no detectable T31 phosphorylation was found in Cavendish Banana. These results suggest that the MKK2 pathway in Dajiao, along with other cold-specific phosphoproteins, appears to be associated with the molecular mechanisms of high tolerance to cold stress in Dajiao. The results also provide new evidence that the signaling pathway of cellular MKK2 phosphorylation plays an important role in abiotic stress tolerance that likely serves as a universal plant cold tolerance mechanism. PMID:28106078

  6. Application of complex discrete wavelet transform in classification of Doppler signals using complex-valued artificial neural network.

    Science.gov (United States)

    Ceylan, Murat; Ceylan, Rahime; Ozbay, Yüksel; Kara, Sadik

    2008-09-01

    In biomedical signal classification, due to the huge amount of data, to compress the biomedical waveform data is vital. This paper presents two different structures formed using feature extraction algorithms to decrease size of feature set in training and test data. The proposed structures, named as wavelet transform-complex-valued artificial neural network (WT-CVANN) and complex wavelet transform-complex-valued artificial neural network (CWT-CVANN), use real and complex discrete wavelet transform for feature extraction. The aim of using wavelet transform is to compress data and to reduce training time of network without decreasing accuracy rate. In this study, the presented structures were applied to the problem of classification in carotid arterial Doppler ultrasound signals. Carotid arterial Doppler ultrasound signals were acquired from left carotid arteries of 38 patients and 40 healthy volunteers. The patient group included 22 males and 16 females with an established diagnosis of the early phase of atherosclerosis through coronary or aortofemoropopliteal (lower extremity) angiographies (mean age, 59 years; range, 48-72 years). Healthy volunteers were young non-smokers who seem to not bear any risk of atherosclerosis, including 28 males and 12 females (mean age, 23 years; range, 19-27 years). Sensitivity, specificity and average detection rate were calculated for comparison, after training and test phases of all structures finished. These parameters have demonstrated that training times of CVANN and real-valued artificial neural network (RVANN) were reduced using feature extraction algorithms without decreasing accuracy rate in accordance to our aim.

  7. NEpiC: a network-assisted algorithm for epigenetic studies using mean and variance combined signals.

    Science.gov (United States)

    Ruan, Peifeng; Shen, Jing; Santella, Regina M; Zhou, Shuigeng; Wang, Shuang

    2016-09-19

    DNA methylation plays an important role in many biological processes. Existing epigenome-wide association studies (EWAS) have successfully identified aberrantly methylated genes in many diseases and disorders with most studies focusing on analysing methylation sites one at a time. Incorporating prior biological information such as biological networks has been proven to be powerful in identifying disease-associated genes in both gene expression studies and genome-wide association studies (GWAS) but has been under studied in EWAS. Although recent studies have noticed that there are differences in methylation variation in different groups, only a few existing methods consider variance signals in DNA methylation studies. Here, we present a network-assisted algorithm, NEpiC, that combines both mean and variance signals in searching for differentially methylated sub-networks using the protein-protein interaction (PPI) network. In simulation studies, we demonstrate the power gain from using both the prior biological information and variance signals compared to using either of the two or neither information. Applications to several DNA methylation datasets from the Cancer Genome Atlas (TCGA) project and DNA methylation data on hepatocellular carcinoma (HCC) from the Columbia University Medical Center (CUMC) suggest that the proposed NEpiC algorithm identifies more cancer-related genes and generates better replication results. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. Angry Apps: The Impact of Network Timer Selection on Power Consumption, Signalling Load, and Web QoE

    Directory of Open Access Journals (Sweden)

    Christian Schwartz

    2013-01-01

    Full Text Available The popularity of smartphones and mobile applications has experienced a considerable growth during the recent years, and this growth is expected to continue in the future. Since smartphones have only very limited energy resources, battery efficiency is one of the determining factors for a good user experience. Therefore, some smartphones tear down connectionsto the mobile network soon after a completed data transmission to reduce the power consumption of their transmission unit. However, frequent connection reestablishments caused by apps which send or receive small amounts of data often lead to a heavy signalling load within the mobile network. One of the major contributions of this paper is the investigation of the resulting tradeoff between energy consumption at the smartphone and the generated signalling traffic in the mobile network. We explain that this tradeoff can be controlled by the connection release timeout and study the impact of this parameter for a number of popular apps that cover a wide range of traffic characteristics in terms of bandwidth requirements and resulting signalling traffic. Finally, we study the impact of the timer settings on Quality of Experience (QoE for web traffic. This is an important aspect since connection establishments not only lead to signalling traffic but also increase the load time of web pages.

  9. A model system for targeted drug release triggered by biomolecular signals logically processed through enzyme logic networks.

    Science.gov (United States)

    Mailloux, Shay; Halámek, Jan; Katz, Evgeny

    2014-03-07

    A new Sense-and-Act system was realized by the integration of a biocomputing system, performing analytical processes, with a signal-responsive electrode. A drug-mimicking release process was triggered by biomolecular signals processed by different logic networks, including three concatenated AND logic gates or a 3-input OR logic gate. Biocatalytically produced NADH, controlled by various combinations of input signals, was used to activate the electrochemical system. A biocatalytic electrode associated with signal-processing "biocomputing" systems was electrically connected to another electrode coated with a polymer film, which was dissolved upon the formation of negative potential releasing entrapped drug-mimicking species, an enzyme-antibody conjugate, operating as a model for targeted immune-delivery and consequent "prodrug" activation. The system offers great versatility for future applications in controlled drug release and personalized medicine.

  10. Signaling Network Assessment of Mutations and Copy Number Variations Predict Breast Cancer Subtype-Specific Drug Targets

    Directory of Open Access Journals (Sweden)

    Naif Zaman

    2013-10-01

    Full Text Available Individual cancer cells carry a bewildering number of distinct genomic alterations (e.g., copy number variations and mutations, making it a challenge to uncover genomic-driven mechanisms governing tumorigenesis. Here, we performed exome sequencing on several breast cancer cell lines that represent two subtypes, luminal and basal. We integrated these sequencing data and functional RNAi screening data (for the identification of genes that are essential for cell proliferation and survival onto a human signaling network. Two subtype-specific networks that potentially represent core-signaling mechanisms underlying tumorigenesis were identified. Within both networks, we found that genes were differentially affected in different cell lines; i.e., in some cell lines a gene was identified through RNAi screening, whereas in others it was genomically altered. Interestingly, we found that highly connected network genes could be used to correctly classify breast tumors into subtypes on the basis of genomic alterations. Further, the networks effectively predicted subtype-specific drug targets, which were experimentally validated.

  11. Multiplex multivariate recurrence network from multi-channel signals for revealing oil-water spatial flow behavior.

    Science.gov (United States)

    Gao, Zhong-Ke; Dang, Wei-Dong; Yang, Yu-Xuan; Cai, Qing

    2017-03-01

    The exploration of the spatial dynamical flow behaviors of oil-water flows has attracted increasing interests on account of its challenging complexity and great significance. We first technically design a double-layer distributed-sector conductance sensor and systematically carry out oil-water flow experiments to capture the spatial flow information. Based on the well-established recurrence network theory, we develop a novel multiplex multivariate recurrence network (MMRN) to fully and comprehensively fuse our double-layer multi-channel signals. Then we derive the projection networks from the inferred MMRNs and exploit the average clustering coefficient and the spectral radius to quantitatively characterize the nonlinear recurrent behaviors related to the distinct flow patterns. We find that these two network measures are very sensitive to the change of flow states and the distributions of network measures enable to uncover the spatial dynamical flow behaviors underlying different oil-water flow patterns. Our method paves the way for efficiently analyzing multi-channel signals from multi-layer sensor measurement system.

  12. Hsp90 inhibitor 17-AAG reduces ErbB2 levels and inhibits proliferation of the trastuzumab resistant breast tumor cell line JIMT-1.

    Science.gov (United States)

    Zsebik, Barbara; Citri, Ami; Isola, Jorma; Yarden, Yosef; Szöllosi, János; Vereb, György

    2006-04-15

    ErbB2, a member of the EGF receptor family of tyrosine kinases is overexpressed on many tumor cells of epithelial origin and is the molecular target of trastuzumab (Herceptin), the first humanized antibody used in the therapy of solid tumors. Trastuzumab, which is thought to act, at least in part, by downregulating ErbB2 expression is only effective in approximately 30-40% of ErbB2 positive breast tumors. Geldanamycin and its derivative 17-AAG are potential antitumor agents capable of downregulating client proteins of Hsp90, including ErbB2. To investigate the ability of 17-AAG to downregulate ErbB2 in trastuzumab resistant breast cancer cells and the possibility of 17-AAG and trastuzumab potentiating each other's effect, the recently established trastuzumab resistant breast cancer cell line, JIMT-1 was compared to the known trastuzumab sensitive SKBR-3 line. Baseline and stimulus-evoked dimerization and activation levels of ErbB2, and the effects of trastuzumab and 17-AAG alone and in combination on cell proliferation and apoptosis, as well as on ErbB2 expression and phosphorylation have been measured. Baseline activation and amenability to activation and downregulation by trastuzumab was much lower in the resistant line. However, 17-AAG enhanced ErbB2 homodimerization after 5-10 min of treatment in both cell lines, and decreased proliferation with an IC50 of 70 nM for SKBR-3 and 10nM for JIMT-1. Thus, 17-AAG may be a useful drug in trastuzumab resistant ErbB2 overexpressing tumors. The antiproliferative effect of 17-AAG was positively correlated with phosphorylation and downregulation of ErbB2 and was dominated by apoptosis, although, especially at higher doses, necrosis was also present. Interestingly, IC50 values for ErbB2 downregulation and phosphorylation, in the 30-40 nM range, were not significantly different for the two cell lines. This observation and the negative correlation between resting ErbB2 levels and the antiproliferative effect of 17-AAG may

  13. Development of Filtered Bispectrum for EEG Signal Feature Extraction in Automatic Emotion Recognition Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Prima Dewi Purnamasari

    2017-05-01

    Full Text Available The development of automatic emotion detection systems has recently gained significant attention due to the growing possibility of their implementation in several applications, including affective computing and various fields within biomedical engineering. Use of the electroencephalograph (EEG signal is preferred over facial expression, as people cannot control the EEG signal generated by their brain; the EEG ensures a stronger reliability in the psychological signal. However, because of its uniqueness between individuals and its vulnerability to noise, use of EEG signals can be rather complicated. In this paper, we propose a methodology to conduct EEG-based emotion recognition by using a filtered bispectrum as the feature extraction subsystem and an artificial neural network (ANN as the classifier. The bispectrum is theoretically superior to the power spectrum because it can identify phase coupling between the nonlinear process components of the EEG signal. In the feature extraction process, to extract the information contained in the bispectrum matrices, a 3D pyramid filter is used for sampling and quantifying the bispectrum value. Experiment results show that the mean percentage of the bispectrum value from 5 × 5 non-overlapped 3D pyramid filters produces the highest recognition rate. We found that reducing the number of EEG channels down to only eight in the frontal area of the brain does not significantly affect the recognition rate, and the number of data samples used in the training process is then increased to improve the recognition rate of the system. We have also utilized a probabilistic neural network (PNN as another classifier and compared its recognition rate with that of the back-propagation neural network (BPNN, and the results show that the PNN produces a comparable recognition rate and lower computational costs. Our research shows that the extracted bispectrum values of an EEG signal using 3D filtering as a feature extraction

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