Programmed Fetal Membrane Senescence and Exosome-Mediated Signaling: A Mechanism Associated With Timing of Human Parturition

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Ramkumar Menon

2017-08-01

Full Text Available Human parturition is an inflammatory process that involves both fetal and maternal compartments. The precise immune cell interactions have not been well delineated in human uterine tissues during parturition, but insights into human labor initiation have been informed by studies in animal models. Unfortunately, the timing of parturition relative to fetal maturation varies among viviparous species—indicative of different phylogenetic clocks and alarms—but what is clear is that important common pathways must converge to control the birth process. Herein, we hypothesize a novel signaling mechanism initiated by human fetal membrane aging and senescence-associated inflammation. Programmed events of fetal membrane aging coincide with fetal growth and organ maturation. Mechanistically, senescence involves in telomere shortening and activation of p38 mitogen-activated signaling kinase resulting in aging-associated phenotypic transition. Senescent tissues release inflammatory signals that are propagated via exosomes to cause functional changes in maternal uterine tissues. In vitro, oxidative stress causes increased release of inflammatory mediators (senescence-associated secretory phenotype and damage-associated molecular pattern markers that can be packaged inside the exosomes. These exosomes traverse through tissues layers, reach maternal tissues to increase overall inflammatory load transitioning them from a quiescent to active state. Animal model studies have shown that fetal exosomes can travel from fetal to the maternal side. Thus, aging fetal membranes and membrane-derived exosomes cargo fetal signals to the uterus and cervix and may trigger parturition. This review highlights a novel hypothesis in human parturition research based on data from ongoing research using human fetal membrane model system.

Total Lipopolysaccharide from the Human Gut Microbiome Silences Toll-Like Receptor Signaling.

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d'Hennezel, Eva; Abubucker, Sahar; Murphy, Leon O; Cullen, Thomas W

2017-01-01

Cohabitation of microbial communities with the host enables the formation of a symbiotic relationship that maintains homeostasis in the gut and beyond. One prevailing model suggests that this relationship relies on the capacity of host cells and tissues to remain tolerant to the strong immune stimulation generated by the microbiota such as the activation of Toll-like receptor 4 (TLR4) pathways by lipopolysaccharide (LPS). Indeed, gut microbial LPS is thought to be one of the most potent activators of innate immune signaling and an important mediator of the microbiome's influence on host physiology. In this study, we performed computational and experimental analyses of healthy human fecal samples to examine the TLR4 signaling capacity of the gut microbiota. These analyses revealed that an immunoinhibitory activity of LPS, conserved across the members of the order Bacteroidales and derived from an underacylated structural feature, silences TLR4 signaling for the entire consortium of organisms inhabiting the human gut. Comparative analysis of metagenomic data from the Human Microbiome Project and healthy-donor samples indicates that immune silencing via LPS is a microbe-intrinsic feature in all healthy adults. These findings challenge the current belief that robust TLR4 signaling is a feature of the microbiome and demonstrate that microbiome-derived LPS has the ability to facilitate host tolerance of gut microbes. These findings have broad implications for how we model host-microbe interactions and for our understanding of microbiome-linked disease. IMPORTANCE While the ability for humans to host a complex microbial ecosystem is an essential property of life, the mechanisms allowing for immune tolerance of such a large microbial load are not completely understood and are currently the focus of intense research. This study shows that an important proinflammatory pathway that is commonly triggered by pathogenic bacteria upon interaction with the host is, in fact

Covert Sexual Signaling: Human Flirtation and Implications for other Social Species

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Andrew Gersick

2014-07-01

Full Text Available According to signaling theory and a large body of supporting evidence, males across many taxa produce courtship signals that honestly advertise their quality. The cost of producing or performing these signals maintains signal honesty, such that females are typically able to choose the best males by selecting those that produce the loudest, brightest, longest, or otherwise highest-intensity signals, using signal strength as a measure of quality. Set against this background, human flirting behavior, characterized by its frequent subtlety or covertness, is mysterious. Here we propose that the explanation for subtle and ambiguous signals in human courtship lies in socially imposed costs that (a vary with social context and (b are amplified by the unusual ways in which language makes all interactions potentially public. Flirting is a class of courtship signaling that conveys the signaler's intentions and desirability to the intended receiver while minimizing the costs that would accompany an overt courtship attempt. This proposal explains humans' taxonomically unusual courtship displays and generates a number of novel predictions for both humans and non-human social animals. Individuals who are courting should vary the intensity of their signals to suit the level of risk attached to the particular social configuration, and receivers may assess this flexible matching of signal to context as an indicator of the signaler's broader behavioral flexibility and social intelligence.

Methods to Manipulate and Monitor Wnt Signaling in Human Pluripotent Stem Cells.

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Huggins, Ian J; Brafman, David; Willert, Karl

2016-01-01

Human pluripotent stem cells (hPSCs) may revolutionize medical practice by providing: (a) a renewable source of cells for tissue replacement therapies, (b) a powerful system to model human diseases in a dish, and (c) a platform for examining efficacy and safety of novel drugs. Furthermore, these cells offer a unique opportunity to study early human development in vitro, in particular, the process by which a seemingly uniform cell population interacts to give rise to the three main embryonic lineages: ectoderm, endoderm. and mesoderm. This process of lineage allocation is regulated by a number of inductive signals that are mediated by growth factors, including FGF, TGFβ, and Wnt. In this book chapter, we introduce a set of tools, methods, and protocols to specifically manipulate the Wnt signaling pathway with the intention of altering the cell fate outcome of hPSCs.

Spatio-temporal Model of Endogenous ROS and Raft-Dependent WNT/Beta-Catenin Signaling Driving Cell Fate Commitment in Human Neural Progenitor Cells

Science.gov (United States)

Haack, Fiete; Lemcke, Heiko; Ewald, Roland; Rharass, Tareck; Uhrmacher, Adelinde M.

2015-01-01

Canonical WNT/β-catenin signaling is a central pathway in embryonic development, but it is also connected to a number of cancers and developmental disorders. Here we apply a combined in-vitro and in-silico approach to investigate the spatio-temporal regulation of WNT/β-catenin signaling during the early neural differentiation process of human neural progenitors cells (hNPCs), which form a new prospect for replacement therapies in the context of neurodegenerative diseases. Experimental measurements indicate a second signal mechanism, in addition to canonical WNT signaling, being involved in the regulation of nuclear β-catenin levels during the cell fate commitment phase of neural differentiation. We find that the biphasic activation of β-catenin signaling observed experimentally can only be explained through a model that combines Reactive Oxygen Species (ROS) and raft dependent WNT/β-catenin signaling. Accordingly after initiation of differentiation endogenous ROS activates DVL in a redox-dependent manner leading to a transient activation of down-stream β-catenin signaling, followed by continuous auto/paracrine WNT signaling, which crucially depends on lipid rafts. Our simulation studies further illustrate the elaborate spatio-temporal regulation of DVL, which, depending on its concentration and localization, may either act as direct inducer of the transient ROS/β-catenin signal or as amplifier during continuous auto-/parcrine WNT/β-catenin signaling. In addition we provide the first stochastic computational model of WNT/β-catenin signaling that combines membrane-related and intracellular processes, including lipid rafts/receptor dynamics as well as WNT- and ROS-dependent β-catenin activation. The model’s predictive ability is demonstrated under a wide range of varying conditions for in-vitro and in-silico reference data sets. Our in-silico approach is realized in a multi-level rule-based language, that facilitates the extension and modification of the

Multi-model approach to characterize human handwriting motion.

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Chihi, I; Abdelkrim, A; Benrejeb, M

2016-02-01

This paper deals with characterization and modelling of human handwriting motion from two forearm muscle activity signals, called electromyography signals (EMG). In this work, an experimental approach was used to record the coordinates of a pen tip moving on the (x, y) plane and EMG signals during the handwriting act. The main purpose is to design a new mathematical model which characterizes this biological process. Based on a multi-model approach, this system was originally developed to generate letters and geometric forms written by different writers. A Recursive Least Squares algorithm is used to estimate the parameters of each sub-model of the multi-model basis. Simulations show good agreement between predicted results and the recorded data.

Pharmacological migraine provocation: a human model of migraine

DEFF Research Database (Denmark)

Ashina, Messoud; Hansen, Jakob Møller

2010-01-01

for migraine mechanisms. So far, however, animal models cannot predict the efficacy of new therapies for migraine. Because migraine attacks are fully reversible and can be aborted by therapy, the headache- or migraine-provoking property of naturally occurring signaling molecules can be tested in a human model....... If a naturally occurring substance can provoke migraine in human patients, then it is likely, although not certain, that blocking its effect will be effective in the treatment of acute migraine attacks. To this end, a human in vivo model of experimental headache and migraine in humans has been developed...

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.

A Circuit Model of Real Time Human Body Hydration.

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Asogwa, Clement Ogugua; Teshome, Assefa K; Collins, Stephen F; Lai, Daniel T H

2016-06-01

Changes in human body hydration leading to excess fluid losses or overload affects the body fluid's ability to provide the necessary support for healthy living. We propose a time-dependent circuit model of real-time human body hydration, which models the human body tissue as a signal transmission medium. The circuit model predicts the attenuation of a propagating electrical signal. Hydration rates are modeled by a time constant τ, which characterizes the individual specific metabolic function of the body part measured. We define a surrogate human body anthropometric parameter θ by the muscle-fat ratio and comparing it with the body mass index (BMI), we find theoretically, the rate of hydration varying from 1.73 dB/min, for high θ and low τ to 0.05 dB/min for low θ and high τ. We compare these theoretical values with empirical measurements and show that real-time changes in human body hydration can be observed by measuring signal attenuation. We took empirical measurements using a vector network analyzer and obtained different hydration rates for various BMI, ranging from 0.6 dB/min for 22.7 [Formula: see text] down to 0.04 dB/min for 41.2 [Formula: see text]. We conclude that the galvanic coupling circuit model can predict changes in the volume of the body fluid, which are essential in diagnosing and monitoring treatment of body fluid disorder. Individuals with high BMI would have higher time-dependent biological characteristic, lower metabolic rate, and lower rate of hydration.

Endogenous Nur77 Is a Specific Indicator of Antigen Receptor Signaling in Human T and B Cells.

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Ashouri, Judith F; Weiss, Arthur

2017-01-15

Distinguishing true Ag-stimulated lymphocytes from bystanders activated by the inflammatory milieu has been difficult. Nur77 is an immediate early gene whose expression is rapidly upregulated by TCR signaling in murine T cells and human thymocytes. Nur77-GFP transgenes serve as specific TCR and BCR signaling reporters in murine transgenic models. In this study, we demonstrate that endogenous Nur77 protein expression can serve as a reporter of TCR and BCR specific signaling in human PBMCs. Nur77 protein amounts were assessed by immunofluorescence and flow cytometry in T and B cells isolated from human PBMCs obtained from healthy donors that had been stimulated by their respective Ag receptors. We demonstrate that endogenous Nur77 is a more specific reporter of Ag-specific signaling events than the commonly used CD69 activation marker in both human T and B cells. This is reflective of the disparity in signaling pathways that regulate the expression of Nur77 and CD69. Assessing endogenous Nur77 protein expression has great potential to identify Ag-activated lymphocytes in human disease. Copyright © 2017 by The American Association of Immunologists, Inc.

Caenorhabditis elegans DAF-2 as a Model for Human Insulin Receptoropathies

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David A. Bulger

2017-01-01

Full Text Available Human exome sequencing has dramatically increased the rate of identification of disease-associated polymorphisms. However, examining the functional consequences of those variants has created an analytic bottleneck. Insulin-like signaling in Caenorhabditis elegans has long provided a model to assess consequences of human insulin signaling mutations, but this has not been evaluated in the context of current genetic tools. We have exploited strains derived from the Million Mutation Project (MMP and gene editing to explore further the evolutionary relationships and conservation between the human and C. elegans insulin receptors. Of 40 MMP alleles analyzed in the C. elegans insulin-like receptor gene DAF-2, 35 exhibited insulin-like signaling indistinguishable from wild-type animals, indicating tolerated mutations. Five MMP alleles proved to be novel dauer-enhancing mutations, including one new allele in the previously uncharacterized C-terminus of DAF-2. CRISPR-Cas9 genome editing was used to confirm the phenotypic consequence of six of these DAF-2 mutations and to replicate an allelic series of known human disease mutations in a highly conserved tyrosine kinase active site residue, demonstrating the utility of C. elegans for directly modeling human disease. Our results illustrate the challenges associated with prediction of the phenotypic consequences of amino acid substitutions, the value of assaying mutant isoform function in vivo, and how recently developed tools and resources afford the opportunity to expand our understanding even of highly conserved regulatory modules such as insulin signaling. This approach may prove generally useful for modeling phenotypic consequences of candidate human pathogenic mutations in conserved signaling and developmental pathways.

The ultimate intrinsic signal-to-noise ratio of loop- and dipole-like current patterns in a realistic human head model.

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Pfrommer, Andreas; Henning, Anke

2018-03-13

The ultimate intrinsic signal-to-noise ratio (UISNR) represents an upper bound for the achievable SNR of any receive coil. To reach this threshold a complete basis set of equivalent surface currents is required. This study systematically investigated to what extent either loop- or dipole-like current patterns are able to reach the UISNR threshold in a realistic human head model between 1.5 T and 11.7 T. Based on this analysis, we derived guidelines for coil designers to choose the best array element at a given field strength. Moreover, we present ideal current patterns yielding the UISNR in a realistic body model. We distributed generic current patterns on a cylindrical and helmet-shaped surface around a realistic human head model. We excited electromagnetic fields in the human head by using eigenfunctions of the spherical and cylindrical Helmholtz operator. The electromagnetic field problem was solved by a fast volume integral equation solver. At 7 T and above, adding curl-free current patterns to divergence-free current patterns substantially increased the SNR in the human head (locally >20%). This was true for the helmet-shaped and the cylindrical surface. On the cylindrical surface, dipole-like current patterns had high SNR performance in central regions at ultra-high field strength. The UISNR increased superlinearly with B0 in most parts of the cerebrum but only sublinearly in the periphery of the human head. The combination of loop and dipole elements could enhance the SNR performance in the human head at ultra-high field strength. © 2018 International Society for Magnetic Resonance in Medicine.

Distinctive Roles of Canonical and Noncanonical Wnt Signaling in Human Embryonic Cardiomyocyte Development

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Silvia Mazzotta

2016-10-01

Full Text Available Wnt signaling is a key regulator of vertebrate heart development; however, specific roles for human cardiomyocyte development remain uncertain. Here we use human embryonic stem cells (hESCs to analyze systematically in human cardiomyocyte development the expression of endogenous Wnt signaling components, monitor pathway activity, and dissect stage-specific requirements for canonical and noncanonical Wnt signaling mechanisms using small-molecule inhibitors. Our analysis suggests that WNT3 and WNT8A, via FZD7 and canonical signaling, regulate BRACHYURY expression and mesoderm induction; that WNT5A/5B, via ROR2 and noncanonical signaling, regulate MESP1 expression and cardiovascular development; and that later in development WNT2, WNT5A/5B, and WNT11, via FZD4 and FZD6, regulate functional cardiomyocyte differentiation via noncanonical Wnt signaling. Our findings confirm in human development previously proposed roles for canonical Wnt signaling in sequential stages of vertebrate cardiomyogenesis, and identify more precise roles for noncanonical signaling and for individual Wnt signal and Wnt receptor genes in human cardiomyocyte development.

Caenorhabditis elegans DAF-2 as a Model for Human Insulin Receptoropathies.

Science.gov (United States)

Bulger, David A; Fukushige, Tetsunari; Yun, Sijung; Semple, Robert K; Hanover, John A; Krause, Michael W

2017-01-05

Human exome sequencing has dramatically increased the rate of identification of disease-associated polymorphisms. However, examining the functional consequences of those variants has created an analytic bottleneck. Insulin-like signaling in Caenorhabditis elegans has long provided a model to assess consequences of human insulin signaling mutations, but this has not been evaluated in the context of current genetic tools. We have exploited strains derived from the Million Mutation Project (MMP) and gene editing to explore further the evolutionary relationships and conservation between the human and C. elegans insulin receptors. Of 40 MMP alleles analyzed in the C. elegans insulin-like receptor gene DAF-2, 35 exhibited insulin-like signaling indistinguishable from wild-type animals, indicating tolerated mutations. Five MMP alleles proved to be novel dauer-enhancing mutations, including one new allele in the previously uncharacterized C-terminus of DAF-2 CRISPR-Cas9 genome editing was used to confirm the phenotypic consequence of six of these DAF-2 mutations and to replicate an allelic series of known human disease mutations in a highly conserved tyrosine kinase active site residue, demonstrating the utility of C. elegans for directly modeling human disease. Our results illustrate the challenges associated with prediction of the phenotypic consequences of amino acid substitutions, the value of assaying mutant isoform function in vivo, and how recently developed tools and resources afford the opportunity to expand our understanding even of highly conserved regulatory modules such as insulin signaling. This approach may prove generally useful for modeling phenotypic consequences of candidate human pathogenic mutations in conserved signaling and developmental pathways. Copyright © 2017 Bulger et al.

4-tert-Octylphenol stimulates the expression of cathepsins in human breast cancer cells and xenografted breast tumors of a mouse model via an estrogen receptor-mediated signaling pathway

International Nuclear Information System (INIS)

Lee, Hye-Rim; Choi, Kyung-Chul

2013-01-01

Highlights: ► Cathepsins B and D were markedly enhanced by octylphenol (OP) in MCF-7 cells. ► OP may accelerate breast cancer cell growth and cathepsins via ER-mediated signaling. ► Breast cancer cells exposed with OP to mouse model were more aggressive. ► OP can promote metastasis through the amplification of cathepsins B and D via ER-mediated signaling pathway. -- Abstract: Endocrine disrupting chemicals (EDCs) are defined as environmental compounds that modulate steroid hormone receptor-dependent responses an abnormal manner, resulting in adverse health problems for humans such as cancer growth and metastasis. Cathepsins are proteases that have been implicated in cancer progression. However, there have been few studies about the association between cathepsins and estrogenic chemicals during the cancer progression. In this study, we examined the effect(s) of 4-tert-octylphenol (OP), a potent EDC, on the expression of cathepsins B and D in human MCF-7 breast cancer cells and a xenograft mouse model. Treatment with OP significantly induced the proliferation MCF-7 cells in an MTT assay. In addition, the expression of cathepsins B and D was markedly enhanced in MCF-7 cells at both the transcriptional and the translational levels following treatment with E2 or OP up to 48 h. These results demonstrated the ability of OP to disrupt normal transcriptional regulation of cathepsins B and D in human breast cancer cells. However, the effects of OP on cell growth or overexpression of cathepsins by inhibiting ER-mediated signaling were abolished by an ER antagonist and siRNA specific for ERα. In conclusion, our findings suggest that OP at 10 −6 M, like E2, may accelerate breast cancer cell proliferation and the expression of cathepsins through an ER-mediated signaling pathway. In addition, the breast cancer cells exposed with OP to a xenograft mouse model were more aggressive according to our histological analysis and showed markedly increased expression of

Human placental trophoblast invasion and differentiation: a particular focus on Wnt signalling

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Martin eKnöfler

2013-09-01

Full Text Available Wingless ligands, a family of secreted proteins, are critically involved in organ development and tissue homeostasis by ensuring balanced rates of stem cell proliferation, cell death and differentiation. Wnt signalling components also play crucial roles in murine placental development controlling trophoblast lineage determination, chorioallantoic fusion and placental branching morphogenesis. However, the role of the pathway in human placentation, trophoblast development and differentiation is only partly understood. Here, we summarize our present knowledge about Wnt signalling in the human placenta and discuss its potential role in physiological and aberrant trophoblast invasion, gestational diseases and choriocarcinoma formation. Differentiation of proliferative first trimester cytotrophoblasts into invasive extravillous trophoblasts is associated with nuclear recruitment of β-catenin and induction of Wnt-dependent T-cell factor 4 suggesting that canonical Wnt signalling could be important for the formation and function of extravillous trophoblasts. Indeed, activation of the pathway was shown to promote trophoblast invasion in different in vitro trophoblast model systems as well as trophoblast cell fusion. Methylation-mediated silencing of inhibitors of Wnt signalling provided evidence for epigenetic activation of the pathway in placental tissues and choriocarcinoma cells. Similarly, abundant nuclear expression of β-catenin in invasive trophoblasts of complete hydatidiform moles suggested a role for hyper-activated Wnt signalling. In contrast, upregulation of Wnt inhibitors was noticed in placentae of women with preeclampsia, a disease characterized by shallow trophoblast invasion and incomplete spiral artery remodelling. Moreover, changes in Wnt signalling have been observed upon cytomegalovirus infection and in recurrent abortions. In summary, the current literature suggests a critical role of Wnt signalling in physiological and abnormal

Vorinostat, an HDAC inhibitor attenuates epidermoid squamous cell carcinoma growth by dampening mTOR signaling pathway in a human xenograft murine model

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Kurundkar, Deepali; Srivastava, Ritesh K.; Chaudhary, Sandeep C. [Department of Dermatology and Skin Diseases Research Center, University of Alabama at Birmingham, 1530 3rd Avenue South, VH 509, Birmingham, AL 35294-0019 (United States); Ballestas, Mary E. [Department of Pediatrics Infectious Disease, Children' s of Alabama, School of Medicine, University of Alabama at Birmingham, AL (United States); Kopelovich, Levy [Division of Cancer Prevention, National Cancer Institute, 6130 Executive Blvd., Suite 2114, Bethesda, MD 20892 (United States); Elmets, Craig A. [Department of Dermatology and Skin Diseases Research Center, University of Alabama at Birmingham, 1530 3rd Avenue South, VH 509, Birmingham, AL 35294-0019 (United States); Athar, Mohammad, E-mail: mathar@uab.edu [Department of Dermatology and Skin Diseases Research Center, University of Alabama at Birmingham, 1530 3rd Avenue South, VH 509, Birmingham, AL 35294-0019 (United States)

2013-01-15

Histone deacetylase (HDAC) inhibitors are potent anticancer agents and show efficacy against various human neoplasms. Vorinostat is a potent HDAC inhibitor and has shown potential to inhibit growth of human xenograft tumors. However, its effect on the growth of skin neoplasm remains undefined. In this study, we show that vorinostat (2 μM) reduced expression of HDAC1, 2, 3, and 7 in epidermoid carcinoma A431 cells. Consistently, it increased acetylation of histone H3 and p53. Vorinostat (100 mg/kg body weight, IP) treatment reduced human xenograft tumor growth in highly immunosuppressed nu/nu mice. Histologically, the vorinostat-treated tumor showed features of well-differentiation with large necrotic areas. Based on proliferating cell nuclear antigen (PCNA) staining and expression of cyclins D1, D2, E, and A, vorinostat seems to impair proliferation by down-regulating the expression of these proteins. However, it also induced apoptosis. The mechanism by which vorinostat blocks proliferation and makes tumor cells prone to apoptosis, involved inhibition of mTOR signaling which was accompanied by reduction in cell survival AKT and extracellular-signal regulated kinase (ERK) signaling pathways. Our data provide a novel mechanism-based therapeutic intervention for cutaneous squamous cell carcinoma (SCC). Vorinostat may be utilized to cure skin neoplasms in organ transplant recipient (OTR). These patients have high morbidity and surgical removal of these lesions which frequently develop in these patients, is difficult. -- Highlights: ► Vorinostat reduces SCC growth in a xenograft murine model. ► Vorinostat dampens proliferation and induces apoptosis in tumor cells. ► Diminution in mTOR, Akt and ERK signaling underlies inhibition in proliferation. ► Vorinostat by inhibiting HDACs inhibits epithelial–mesenchymal transition.

Vorinostat, an HDAC inhibitor attenuates epidermoid squamous cell carcinoma growth by dampening mTOR signaling pathway in a human xenograft murine model

International Nuclear Information System (INIS)

Kurundkar, Deepali; Srivastava, Ritesh K.; Chaudhary, Sandeep C.; Ballestas, Mary E.; Kopelovich, Levy; Elmets, Craig A.; Athar, Mohammad

2013-01-01

Histone deacetylase (HDAC) inhibitors are potent anticancer agents and show efficacy against various human neoplasms. Vorinostat is a potent HDAC inhibitor and has shown potential to inhibit growth of human xenograft tumors. However, its effect on the growth of skin neoplasm remains undefined. In this study, we show that vorinostat (2 μM) reduced expression of HDAC1, 2, 3, and 7 in epidermoid carcinoma A431 cells. Consistently, it increased acetylation of histone H3 and p53. Vorinostat (100 mg/kg body weight, IP) treatment reduced human xenograft tumor growth in highly immunosuppressed nu/nu mice. Histologically, the vorinostat-treated tumor showed features of well-differentiation with large necrotic areas. Based on proliferating cell nuclear antigen (PCNA) staining and expression of cyclins D1, D2, E, and A, vorinostat seems to impair proliferation by down-regulating the expression of these proteins. However, it also induced apoptosis. The mechanism by which vorinostat blocks proliferation and makes tumor cells prone to apoptosis, involved inhibition of mTOR signaling which was accompanied by reduction in cell survival AKT and extracellular-signal regulated kinase (ERK) signaling pathways. Our data provide a novel mechanism-based therapeutic intervention for cutaneous squamous cell carcinoma (SCC). Vorinostat may be utilized to cure skin neoplasms in organ transplant recipient (OTR). These patients have high morbidity and surgical removal of these lesions which frequently develop in these patients, is difficult. -- Highlights: ► Vorinostat reduces SCC growth in a xenograft murine model. ► Vorinostat dampens proliferation and induces apoptosis in tumor cells. ► Diminution in mTOR, Akt and ERK signaling underlies inhibition in proliferation. ► Vorinostat by inhibiting HDACs inhibits epithelial–mesenchymal transition.

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.

Using Noninvasive Wearable Computers to Recognize Human Emotions from Physiological Signals

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Nasoz Fatma

2004-01-01

Full Text Available We discuss the strong relationship between affect and cognition and the importance of emotions in multimodal human computer interaction (HCI and user modeling. We introduce the overall paradigm for our multimodal system that aims at recognizing its users' emotions and at responding to them accordingly depending upon the current context or application. We then describe the design of the emotion elicitation experiment we conducted by collecting, via wearable computers, physiological signals from the autonomic nervous system (galvanic skin response, heart rate, temperature and mapping them to certain emotions (sadness, anger, fear, surprise, frustration, and amusement. We show the results of three different supervised learning algorithms that categorize these collected signals in terms of emotions, and generalize their learning to recognize emotions from new collections of signals. We finally discuss possible broader impact and potential applications of emotion recognition for multimodal intelligent systems.

Warning Signals for Poor Performance Improve Human-Robot Interaction

NARCIS (Netherlands)

van den Brule, Rik; Bijlstra, Gijsbert; Dotsch, Ron; Haselager, Pim; Wigboldus, Daniel HJ

2016-01-01

The present research was aimed at investigating whether human-robot interaction (HRI) can be improved by a robot’s nonverbal warning signals. Ideally, when a robot signals that it cannot guarantee good performance, people could take preventive actions to ensure the successful completion of the

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.

Robust Indoor Human Activity Recognition Using Wireless Signals.

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Wang, Yi; Jiang, Xinli; Cao, Rongyu; Wang, Xiyang

2015-07-15

Wireless signals-based activity detection and recognition technology may be complementary to the existing vision-based methods, especially under the circumstance of occlusions, viewpoint change, complex background, lighting condition change, and so on. This paper explores the properties of the channel state information (CSI) of Wi-Fi signals, and presents a robust indoor daily human activity recognition framework with only one pair of transmission points (TP) and access points (AP). First of all, some indoor human actions are selected as primitive actions forming a training set. Then, an online filtering method is designed to make actions' CSI curves smooth and allow them to contain enough pattern information. Each primitive action pattern can be segmented from the outliers of its multi-input multi-output (MIMO) signals by a proposed segmentation method. Lastly, in online activities recognition, by selecting proper features and Support Vector Machine (SVM) based multi-classification, activities constituted by primitive actions can be recognized insensitive to the locations, orientations, and speeds.

Pearls and pitfalls in human pharmacological models of migraine

DEFF Research Database (Denmark)

Ashina, Messoud; Hansen, Jakob Møller; Olesen, Jes

2013-01-01

In vitro studies have contributed to the characterization of receptors in cranial blood vessels and the identification of new possible anti-migraine agents. In vivo animal models enable the study of vascular responses, neurogenic inflammation, peptide release and genetic predisposition and thus......- or migraine-provoking property of naturally occurring signaling molecules can be tested in a human model. If such an endogenous substance can provoke migraine in human patients, then it is likely, although not certain, that blocking its effect will be effective in the treatment of acute migraine attacks...... an important role in translational migraine research leading to the identification of three new principally different targets in the treatment of acute migraine attacks and has been used to examine other endogenous signaling molecules as well as genetic susceptibility factors. New additions to the model...

Signaling hierarchy regulating human endothelial cell development

Science.gov (United States)

Our present knowledge of the regulation of mammalian endothelial cell differentiation has been largely derived from studies of mouse embryonic development. However, unique mechanisms and hierarchy of signals that govern human endothelial cell development are unknown and, thus, explored in these stud...

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.

Immunohistochemical analysis of Sonic hedgehog signalling in normal human urinary tract development

OpenAIRE

Jenkins, Dagan; Winyard, Paul J D; Woolf, Adrian S.

2007-01-01

Studies of mouse mutants have demonstrated that Sonic hedgehog (SHH) signalling has a functional role in morphogenesis and differentiation at multiple sites within the forming urinary tract, and urinary tract malformations have been reported in humans with mutations that disrupt SHH signalling. However, there is only strikingly sparse and fragmentary information about the expression of SHH and associated signalling genes in normal human urinary tract development. We used immunohistochemistry ...

Model developments for quantitative estimates of the benefits of the signals on nuclear power plant availability and economics

International Nuclear Information System (INIS)

Seong, Poong Hyun

1993-01-01

A novel framework for quantitative estimates of the benefits of signals on nuclear power plant availability and economics has been developed in this work. The models developed in this work quantify how the perfect signals affect the human operator's success in restoring the power plant to the desired state when it enters undesirable transients. Also, the models quantify the economic benefits of these perfect signals. The models have been applied to the condensate feedwater system of the nuclear power plant for demonstration. (Author)

Onco-GPCR signaling and dysregulated expression of microRNAs in human cancer.

Science.gov (United States)

Nohata, Nijiro; Goto, Yusuke; Gutkind, J Silvio

2017-01-01

The G-protein-coupled receptor (GPCR) family is the largest family of cell-surface receptors involved in signal transduction. Aberrant expression of GPCRs and G proteins are frequently associated with prevalent human diseases, including cancer. In fact, GPCRs represent the therapeutic targets of more than a quarter of the clinical drugs currently on the market. MiRNAs (miRNAs) are also aberrantly expressed in many human cancers, and they have significant roles in the initiation, development and metastasis of human malignancies. Recent studies have revealed that dysregulation of miRNAs and their target genes expression are associated with cancer progression. The emerging information suggests that miRNAs play an important role in the fine tuning of many signaling pathways, including GPCR signaling. We summarize our current knowledge of the individual functions of miRNAs regulated by GPCRs and GPCR signaling-associated molecules, and miRNAs that regulate the expression and activity of GPCRs, their endogenous ligands and their coupled heterotrimeric G proteins in human cancer.

Suppressing thyroid hormone signaling preserves cone photoreceptors in mouse models of retinal degeneration

OpenAIRE

Ma, Hongwei; Thapa, Arjun; Morris, Lynsie; Redmond, T. Michael; Baehr, Wolfgang; Ding, Xi-Qin

2014-01-01

Photoreceptors degenerate in a wide array of hereditary retinal diseases and age-related macular degeneration. There is currently no treatment available for retinal degenerations. While outnumbered roughly 20:1 by rods in the human retina, it is the cones that mediate color vision and visual acuity, and their survival is critical for vision. In this communication, we investigate whether thyroid hormone (TH) signaling affects cone viability in retinal degeneration mouse models. TH signaling is...

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.

Human female orgasm as evolved signal: a test of two hypotheses.

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Ellsworth, Ryan M; Bailey, Drew H

2013-11-01

We present the results of a study designed to empirically test predictions derived from two hypotheses regarding human female orgasm behavior as an evolved communicative trait or signal. One hypothesis tested was the female fidelity hypothesis, which posits that human female orgasm signals a woman's sexual satisfaction and therefore her likelihood of future fidelity to a partner. The other was sire choice hypothesis, which posits that women's orgasm behavior signals increased chances of fertilization. To test the two hypotheses of human female orgasm, we administered a questionnaire to 138 females and 121 males who reported that they were currently in a romantic relationship. Key predictions of the female fidelity hypothesis were not supported. In particular, orgasm was not associated with female sexual fidelity nor was orgasm associated with male perceptions of partner sexual fidelity. However, faked orgasm was associated with female sexual infidelity and lower male relationship satisfaction. Overall, results were in greater support of the sire choice signaling hypothesis than the female fidelity hypothesis. Results also suggest that male satisfaction with, investment in, and sexual fidelity to a mate are benefits that favored the selection of orgasmic signaling in ancestral females.

Retinoic Acid signalling and the control of meiotic entry in the human fetal gonad.

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Andrew J Childs

Full Text Available The development of mammalian fetal germ cells along oogenic or spermatogenic fate trajectories is dictated by signals from the surrounding gonadal environment. Germ cells in the fetal testis enter mitotic arrest, whilst those in the fetal ovary undergo sex-specific entry into meiosis, the initiation of which is thought to be mediated by selective exposure of fetal ovarian germ cells to mesonephros-derived retinoic acid (RA. Aspects of this model are hard to reconcile with the spatiotemporal pattern of germ cell differentiation in the human fetal ovary, however. We have therefore examined the expression of components of the RA synthesis, metabolism and signalling pathways, and their downstream effectors and inhibitors in germ cells around the time of the initiation of meiosis in the human fetal gonad. Expression of the three RA-synthesising enzymes, ALDH1A1, 2 and 3 in the fetal ovary and testis was equal to or greater than that in the mesonephros at 8-9 weeks gestation, indicating an intrinsic capacity within the gonad to synthesise RA. Using immunohistochemistry to detect RA receptors RARα, β and RXRα, we find germ cells to be the predominant target of RA signalling in the fetal human ovary, but also reveal widespread receptor nuclear localization indicative of signalling in the testis, suggesting that human fetal testicular germ cells are not efficiently shielded from RA by the action of the RA-metabolising enzyme CYP26B1. Consistent with this, expression of CYP26B1 was greater in the human fetal ovary than testis, although the sexually-dimorphic expression patterns of the germ cell-intrinsic regulators of meiotic initiation, STRA8 and NANOS2, appear conserved. Finally, we demonstrate that RA induces a two-fold increase in STRA8 expression in cultures of human fetal testis, but is not sufficient to cause widespread meiosis-associated gene expression. Together, these data indicate that while local production of RA within the fetal ovary may

Retinoic Acid Signalling and the Control of Meiotic Entry in the Human Fetal Gonad

Science.gov (United States)

Kinnell, Hazel L.; Anderson, Richard A.; Saunders, Philippa T. K.

2011-01-01

The development of mammalian fetal germ cells along oogenic or spermatogenic fate trajectories is dictated by signals from the surrounding gonadal environment. Germ cells in the fetal testis enter mitotic arrest, whilst those in the fetal ovary undergo sex-specific entry into meiosis, the initiation of which is thought to be mediated by selective exposure of fetal ovarian germ cells to mesonephros-derived retinoic acid (RA). Aspects of this model are hard to reconcile with the spatiotemporal pattern of germ cell differentiation in the human fetal ovary, however. We have therefore examined the expression of components of the RA synthesis, metabolism and signalling pathways, and their downstream effectors and inhibitors in germ cells around the time of the initiation of meiosis in the human fetal gonad. Expression of the three RA-synthesising enzymes, ALDH1A1, 2 and 3 in the fetal ovary and testis was equal to or greater than that in the mesonephros at 8–9 weeks gestation, indicating an intrinsic capacity within the gonad to synthesise RA. Using immunohistochemistry to detect RA receptors RARα, β and RXRα, we find germ cells to be the predominant target of RA signalling in the fetal human ovary, but also reveal widespread receptor nuclear localization indicative of signalling in the testis, suggesting that human fetal testicular germ cells are not efficiently shielded from RA by the action of the RA-metabolising enzyme CYP26B1. Consistent with this, expression of CYP26B1 was greater in the human fetal ovary than testis, although the sexually-dimorphic expression patterns of the germ cell-intrinsic regulators of meiotic initiation, STRA8 and NANOS2, appear conserved. Finally, we demonstrate that RA induces a two-fold increase in STRA8 expression in cultures of human fetal testis, but is not sufficient to cause widespread meiosis-associated gene expression. Together, these data indicate that while local production of RA within the fetal ovary may be important in

Human Wharton's jelly mesenchymal stem cells promote skin wound healing through paracrine signaling.

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Arno, Anna I; Amini-Nik, Saeid; Blit, Patrick H; Al-Shehab, Mohammed; Belo, Cassandra; Herer, Elaine; Tien, Col Homer; Jeschke, Marc G

2014-02-24

The prevalence of nonhealing wounds is predicted to increase due to the growing aging population. Despite the use of novel skin substitutes and wound dressings, poorly vascularized wound niches impair wound repair. Mesenchymal stem cells (MSCs) have been reported to provide paracrine signals to promote wound healing, but the effect of human Wharton's jelly-derived MSCs (WJ-MSCs) has not yet been described in human normal skin. Human WJ-MSCs and normal skin fibroblasts were isolated from donated umbilical cords and normal adult human skin. Fibroblasts were treated with WJ-MSC-conditioned medium (WJ-MSC-CM) or nonconditioned medium. Expression of genes involved in re-epithelialization (transforming growth factor-β2), neovascularization (hypoxia-inducible factor-1α) and fibroproliferation (plasminogen activator inhibitor-1) was upregulated in WJ-MSC-CM-treated fibroblasts (P≤0.05). WJ-MSC-CM enhanced normal skin fibroblast proliferation (P≤0.001) and migration (P≤0.05), and promoted wound healing in an excisional full-thickness skin murine model. Under our experimental conditions, WJ-MSCs enhanced skin wound healing in an in vivo mouse model.

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

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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

Signaling equilibria in sensorimotor interactions.

Science.gov (United States)

Leibfried, Felix; Grau-Moya, Jordi; Braun, Daniel A

2015-08-01

Although complex forms of communication like human language are often assumed to have evolved out of more simple forms of sensorimotor signaling, less attention has been devoted to investigate the latter. Here, we study communicative sensorimotor behavior of humans in a two-person joint motor task where each player controls one dimension of a planar motion. We designed this joint task as a game where one player (the sender) possesses private information about a hidden target the other player (the receiver) wants to know about, and where the sender's actions are costly signals that influence the receiver's control strategy. We developed a game-theoretic model within the framework of signaling games to investigate whether subjects' behavior could be adequately described by the corresponding equilibrium solutions. The model predicts both separating and pooling equilibria, in which signaling does and does not occur respectively. We observed both kinds of equilibria in subjects and found that, in line with model predictions, the propensity of signaling decreased with increasing signaling costs and decreasing uncertainty on the part of the receiver. Our study demonstrates that signaling games, which have previously been applied to economic decision-making and animal communication, provide a framework for human signaling behavior arising during sensorimotor interactions in continuous and dynamic environments. Copyright © 2015 Elsevier B.V. All rights reserved.

Human vocal attractiveness as signaled by body size projection.

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Yi Xu

Full Text Available Voice, as a secondary sexual characteristic, is known to affect the perceived attractiveness of human individuals. But the underlying mechanism of vocal attractiveness has remained unclear. Here, we presented human listeners with acoustically altered natural sentences and fully synthetic sentences with systematically manipulated pitch, formants and voice quality based on a principle of body size projection reported for animal calls and emotional human vocal expressions. The results show that male listeners preferred a female voice that signals a small body size, with relatively high pitch, wide formant dispersion and breathy voice, while female listeners preferred a male voice that signals a large body size with low pitch and narrow formant dispersion. Interestingly, however, male vocal attractiveness was also enhanced by breathiness, which presumably softened the aggressiveness associated with a large body size. These results, together with the additional finding that the same vocal dimensions also affect emotion judgment, indicate that humans still employ a vocal interaction strategy used in animal calls despite the development of complex language.

Signals and Systems in Biomedical Engineering Signal Processing and Physiological Systems Modeling

CERN Document Server

Devasahayam, Suresh R

2013-01-01

The use of digital signal processing is ubiquitous in the field of physiology and biomedical engineering. The application of such mathematical and computational tools requires a formal or explicit understanding of physiology. Formal models and analytical techniques are interlinked in physiology as in any other field. This book takes a unitary approach to physiological systems, beginning with signal measurement and acquisition, followed by signal processing, linear systems modelling, and computer simulations. The signal processing techniques range across filtering, spectral analysis and wavelet analysis. Emphasis is placed on fundamental understanding of the concepts as well as solving numerical problems. Graphs and analogies are used extensively to supplement the mathematics. Detailed models of nerve and muscle at the cellular and systemic levels provide examples for the mathematical methods and computer simulations. Several of the models are sufficiently sophisticated to be of value in understanding real wor...

A parametric framework for modelling of bioelectrical signals

CERN Document Server

Mughal, Yar Muhammad

2016-01-01

This book examines non-invasive, electrical-based methods for disease diagnosis and assessment of heart function. In particular, a formalized signal model is proposed since this offers several advantages over methods that rely on measured data alone. By using a formalized representation, the parameters of the signal model can be easily manipulated and/or modified, thus providing mechanisms that allow researchers to reproduce and control such signals. In addition, having such a formalized signal model makes it possible to develop computer tools that can be used for manipulating and understanding how signal changes result from various heart conditions, as well as for generating input signals for experimenting with and evaluating the performance of e.g. signal extraction methods. The work focuses on bioelectrical information, particularly electrical bio-impedance (EBI). Once the EBI has been measured, the corresponding signals have to be modelled for analysis. This requires a structured approach in order to move...

Signaling signatures and functional properties of anti-human CD28 superagonistic antibodies.

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Zoe Waibler

Full Text Available Superagonistic CD28 antibodies (CD28SAs activate T lymphocytes without concomitant perturbation of the TCR/CD3-complex. In rodents these reagents induce the preferential expansion of regulatory T cells and can be used for the treatment of autoimmune diseases. Unexpectedly, the humanized CD28 superagonist TGN1412 caused severe and life threatening adverse effects during a recently conducted phase I clinical trail. The underlying molecular mechanisms are as yet unclear. We show that TGN1412 as well as the commercially available CD28 superagonist ANC28.1 induce a delayed but extremely sustained calcium response in human naïve and memory CD4+ T cells but not in cynomolgus T lymphocytes. The sustained Ca++-signal was associated with the activation of multiple intracellular signaling pathways and together these events culminated in the rapid de novo synthesis of high amounts of pro-inflammatory cytokines, most notably IFN-gamma and TNF-alpha. Importantly, sustained transmembranous calcium flux, activation of Src-kinases as well as activation of PI3K were found to be absolutely required for CD28SA-mediated production of IFN-gamma and IL-2. Collectively, our data suggest a molecular basis for the severe side effects caused by TGN1412 and impinge upon the relevance of non-human primates as preclinical models for reagents that are supposed to modify the function of human T cells.

Detection of chaotic dynamics in human gait signals from mobile devices

Science.gov (United States)

DelMarco, Stephen; Deng, Yunbin

2017-05-01

The ubiquity of mobile devices offers the opportunity to exploit device-generated signal data for biometric identification, health monitoring, and activity recognition. In particular, mobile devices contain an Inertial Measurement Unit (IMU) that produces acceleration and rotational rate information from the IMU accelerometers and gyros. These signals reflect motion properties of the human carrier. It is well-known that the complexity of bio-dynamical systems gives rise to chaotic dynamics. Knowledge of chaotic properties of these systems has shown utility, for example, in detecting abnormal medical conditions and neurological disorders. Chaotic dynamics has been found, in the lab, in bio-dynamical systems data such as electrocardiogram (heart), electroencephalogram (brain), and gait data. In this paper, we investigate the following question: can we detect chaotic dynamics in human gait as measured by IMU acceleration and gyro data from mobile phones? To detect chaotic dynamics, we perform recurrence analysis on real gyro and accelerometer signal data obtained from mobile devices. We apply the delay coordinate embedding approach from Takens' theorem to reconstruct the phase space trajectory of the multi-dimensional gait dynamical system. We use mutual information properties of the signal to estimate the appropriate delay value, and the false nearest neighbor approach to determine the phase space embedding dimension. We use a correlation dimension-based approach together with estimation of the largest Lyapunov exponent to make the chaotic dynamics detection decision. We investigate the ability to detect chaotic dynamics for the different one-dimensional IMU signals, across human subject and walking modes, and as a function of different phone locations on the human carrier.

Icotinib inhibits EGFR signaling and alleviates psoriasis-like symptoms in animal models.

Science.gov (United States)

Tan, Fenlai; Yang, Guiqun; Wang, Yanping; Chen, Haibo; Yu, Bo; Li, He; Guo, Jing; Huang, Xiaoling; Deng, Yifang; Yu, Pengxia; Ding, Lieming

2018-02-01

To investigate the effects of icotinib hydrochloride and a derivative cream on epidermal growth factor receptor (EGFR) signaling and within animal psoriasis models, respectively. The effect of icotinib on EGFR signaling was examined in HaCaT cells, while its effect on angiogenesis was tested in chick embryo chorioallantoic membranes (CAM). The effectiveness of icotinib in treating psoriasis was tested in three psoriasis models, including diethylstilbestrol-treated mouse vaginal epithelial cells, mouse tail granular cell layer formation, and propranolol-induced psoriasis-like features in guinea pig ear skin. Icotinib treatment blocked EGFR signaling and reduced HaCaT cell viability as well as suppressed CAM angiogenesis. Topical application of icotinib ameliorated psoriasis-like histological characteristics in mouse and guinea pig psoriasis models. Icotinib also significantly inhibited mouse vaginal epithelium mitosis, promoted mouse tail squamous epidermal granular layer formation, and reduced the thickness of the horny layer in propranolol treated auricular dorsal surface of guinea pig. We conclude that icotinib can effectively inhibit psoriasis in animal models. Future clinical studies should be conducted to explore the therapeutic effects of icotinb in humans. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Inhibition of adipocytogenesis by canonical WNT signaling in human mesenchymal stem cells

International Nuclear Information System (INIS)

Shen, Longxiang; Glowacki, Julie; Zhou, Shuanhu

2011-01-01

The WNT signaling pathway plays important roles in the self-renewal and differentiation of mesenchymal stem cells (MSCs). Little is known about WNT signaling in adipocyte differentiation of human MSCs. In this study, we tested the hypothesis that canonical and non-canonical WNTs differentially regulate in vitro adipocytogenesis in human MSCs. The expression of adipocyte gene PPARγ2, lipoprotein lipase, and adipsin increased during adipocytogenesis of hMSCs. Simultaneously, the expression of canonical WNT2, 10B, 13, and 14 decreased, whereas non-canonical WNT4 and 11 increased, and WNT5A was unchanged. A small molecule WNT mimetic, SB-216763, increased accumulation of β-catenin protein, inhibited induction of WNT4 and 11 and inhibited adipocytogenesis. In contrast, knockdown of β-catenin with siRNA resulted in spontaneous adipocytogenesis. These findings support the view that canonical WNT signaling inhibits and non-canonical WNT signaling promotes adipocytogenesis in adult human marrow-derived mesenchymal stem cells.

An Analysis/Synthesis System of Audio Signal with Utilization of an SN Model

Directory of Open Access Journals (Sweden)

G. Rozinaj

2004-12-01

Full Text Available An SN (sinusoids plus noise model is a spectral model, in which theperiodic components of the sound are represented by sinusoids withtime-varying frequencies, amplitudes and phases. The remainingnon-periodic components are represented by a filtered noise. Thesinusoidal model utilizes physical properties of musical instrumentsand the noise model utilizes the human inability to perceive the exactspectral shape or the phase of stochastic signals. SN modeling can beapplied in a compression, transformation, separation of sounds, etc.The designed system is based on methods used in the SN modeling. Wehave proposed a model that achieves good results in audio perception.Although many systems do not save phases of the sinusoids, they areimportant for better modelling of transients, for the computation ofresidual and last but not least for stereo signals, too. One of thefundamental properties of the proposed system is the ability of thesignal reconstruction not only from the amplitude but from the phasepoint of view, as well.

AR Signaling in Human Malignancies: Prostate Cancer and Beyond.

Science.gov (United States)

Antonarakis, Emmanuel S

2018-01-18

The notion that androgens and androgen receptor (AR) signaling are the hallmarks of prostate cancer oncogenesis and disease progression is generally well accepted. What is more poorly understood is the role of AR signaling in other human malignancies. This special issue of Cancers initially reviews the role of AR in advanced prostate cancer, and then explores the potential importance of AR signaling in other epithelial malignancies. The first few articles focus on the use of novel AR-targeting therapies in castration-resistant prostate cancer and the mechanisms of resistance to novel antiandrogens, and they also outline the interaction between AR and other cellular pathways, including PI3 kinase signaling, transcriptional regulation, angiogenesis, stromal factors, Wnt signaling, and epigenetic regulation in prostate cancer. The next several articles review the possible role of androgens and AR signaling in breast cancer, bladder cancer, salivary gland cancer, and hepatocellular carcinoma, as well as the potential treatment implications of using antiandrogen therapies in these non-prostatic malignancies.

Multiple Drug Treatments That Increase cAMP Signaling Restore Long-Term Memory and Aberrant Signaling in Fragile X Syndrome Models

Science.gov (United States)

Choi, Catherine H.; Schoenfeld, Brian P.; Bell, Aaron J.; Hinchey, Joseph; Rosenfelt, Cory; Gertner, Michael J.; Campbell, Sean R.; Emerson, Danielle; Hinchey, Paul; Kollaros, Maria; Ferrick, Neal J.; Chambers, Daniel B.; Langer, Steven; Sust, Steven; Malik, Aatika; Terlizzi, Allison M.; Liebelt, David A.; Ferreiro, David; Sharma, Ali; Koenigsberg, Eric; Choi, Richard J.; Louneva, Natalia; Arnold, Steven E.; Featherstone, Robert E.; Siegel, Steven J.; Zukin, R. Suzanne; McDonald, Thomas V.; Bolduc, Francois V.; Jongens, Thomas A.; McBride, Sean M. J.

2016-01-01

Fragile X is the most common monogenic disorder associated with intellectual disability (ID) and autism spectrum disorders (ASD). Additionally, many patients are afflicted with executive dysfunction, ADHD, seizure disorder and sleep disturbances. Fragile X is caused by loss of FMRP expression, which is encoded by the FMR1 gene. Both the fly and mouse models of fragile X are also based on having no functional protein expression of their respective FMR1 homologs. The fly model displays well defined cognitive impairments and structural brain defects and the mouse model, although having subtle behavioral defects, has robust electrophysiological phenotypes and provides a tool to do extensive biochemical analysis of select brain regions. Decreased cAMP signaling has been observed in samples from the fly and mouse models of fragile X as well as in samples derived from human patients. Indeed, we have previously demonstrated that strategies that increase cAMP signaling can rescue short term memory in the fly model and restore DHPG induced mGluR mediated long term depression (LTD) in the hippocampus to proper levels in the mouse model (McBride et al., 2005; Choi et al., 2011, 2015). Here, we demonstrate that the same three strategies used previously with the potential to be used clinically, lithium treatment, PDE-4 inhibitor treatment or mGluR antagonist treatment can rescue long term memory in the fly model and alter the cAMP signaling pathway in the hippocampus of the mouse model. PMID:27445731

Cell-autonomous intracellular androgen receptor signaling drives the growth of human prostate cancer initiating cells.

Science.gov (United States)

Vander Griend, Donald J; D'Antonio, Jason; Gurel, Bora; Antony, Lizamma; Demarzo, Angelo M; Isaacs, John T

2010-01-01

The lethality of prostate cancer is due to the continuous growth of cancer initiating cells (CICs) which are often stimulated by androgen receptor (AR) signaling. However, the underlying molecular mechanism(s) for such AR-mediated growth stimulation are not fully understood. Such mechanisms may involve cancer cell-dependent induction of tumor stromal cells to produce paracrine growth factors or could involve cancer cell autonomous autocrine and/or intracellular AR signaling pathways. We utilized clinical samples, animal models and a series of AR-positive human prostate cancer cell lines to evaluate AR-mediated growth stimulation of prostate CICs. The present studies document that stromal AR expression is not required for prostate cancer growth, since tumor stroma surrounding AR-positive human prostate cancer metastases (N = 127) are characteristically AR-negative. This lack of a requirement for AR expression in tumor stromal cells is also documented by the fact that human AR-positive prostate cancer cells grow equally well when xenografted in wild-type versus AR-null nude mice. AR-dependent growth stimulation was documented to involve secretion, extracellular binding, and signaling by autocrine growth factors. Orthotopic xenograft animal studies documented that the cellautonomous autocrine growth factors which stimulate prostate CIC growth are not the andromedins secreted by normal prostate stromal cells. Such cell autonomous and extracellular autocrine signaling is necessary but not sufficient for the optimal growth of prostate CICs based upon the response to anti-androgen plus/or minus preconditioned media. AR-induced growth stimulation of human prostate CICs requires AR-dependent intracellular pathways. The identification of such AR-dependent intracellular pathways offers new leads for the development of effective therapies for prostate cancer. (c) 2009 Wiley-Liss, Inc.

Drosophila as a Model for Human Diseases-Focus on Innate Immunity in Barrier Epithelia.

Science.gov (United States)

Bergman, P; Seyedoleslami Esfahani, S; Engström, Y

2017-01-01

Epithelial immunity protects the host from harmful microbial invaders but also controls the beneficial microbiota on epithelial surfaces. When this delicate balance between pathogen and symbiont is disturbed, clinical disease often occurs, such as in inflammatory bowel disease, cystic fibrosis, or atopic dermatitis, which all can be in part linked to impairment of barrier epithelia. Many innate immune receptors, signaling pathways, and effector molecules are evolutionarily conserved between human and Drosophila. This review describes the current knowledge on Drosophila as a model for human diseases, with a special focus on innate immune-related disorders of the gut, lung, and skin. The discovery of antimicrobial peptides, the crucial role of Toll and Toll-like receptors, and the evolutionary conservation of signaling to the immune systems of both human and Drosophila are described in a historical perspective. Similarities and differences between human and Drosophila are discussed; current knowledge on receptors, signaling pathways, and effectors are reviewed, including antimicrobial peptides, reactive oxygen species, as well as autophagy. We also give examples of human diseases for which Drosophila appears to be a useful model. In addition, the limitations of the Drosophila model are mentioned. Finally, we propose areas for future research, which include using the Drosophila model for drug screening, as a validation tool for novel genetic mutations in humans and for exploratory research of microbiota-host interactions, with relevance for infection, wound healing, and cancer. © 2017 Elsevier Inc. All rights reserved.

Robust Indoor Human Activity Recognition Using Wireless Signals

Directory of Open Access Journals (Sweden)

Yi Wang

2015-07-01

Full Text Available Wireless signals–based activity detection and recognition technology may be complementary to the existing vision-based methods, especially under the circumstance of occlusions, viewpoint change, complex background, lighting condition change, and so on. This paper explores the properties of the channel state information (CSI of Wi-Fi signals, and presents a robust indoor daily human activity recognition framework with only one pair of transmission points (TP and access points (AP. First of all, some indoor human actions are selected as primitive actions forming a training set. Then, an online filtering method is designed to make actions’ CSI curves smooth and allow them to contain enough pattern information. Each primitive action pattern can be segmented from the outliers of its multi-input multi-output (MIMO signals by a proposed segmentation method. Lastly, in online activities recognition, by selecting proper features and Support Vector Machine (SVM based multi-classification, activities constituted by primitive actions can be recognized insensitive to the locations, orientations, and speeds.

Characterization of primary cilia and Hedgehog signaling during development of the human pancreas and in human pancreatic duct cancer cell lines

DEFF Research Database (Denmark)

Nielsen, Sonja K; Møllgård, Kjeld; Clement, Christian A

2008-01-01

Hedgehog (Hh) signaling controls pancreatic development and homeostasis; aberrant Hh signaling is associated with several pancreatic diseases. Here we investigated the link between Hh signaling and primary cilia in the human developing pancreatic ducts and in cultures of human pancreatic duct...... adenocarcinoma cell lines, PANC-1 and CFPAC-1. We show that the onset of Hh signaling from human embryogenesis to fetal development is associated with accumulation of Hh signaling components Smo and Gli2 in duct primary cilia and a reduction of Gli3 in the duct epithelium. Smo, Ptc, and Gli2 localized to primary...... cilia of PANC-1 and CFPAC-1 cells, which may maintain high levels of nonstimulated Hh pathway activity. These findings indicate that primary cilia are involved in pancreatic development and postnatal tissue homeostasis....

Influence of ER leak on resting cytoplasmic Ca2+ and receptor-mediated Ca2+ signalling in human macrophage.

Science.gov (United States)

Layhadi, Janice A; Fountain, Samuel J

2017-06-03

Mechanisms controlling endoplasmic reticulum (ER) Ca 2+ homeostasis are important regulators of resting cytoplasmic Ca 2+ concentration ([Ca 2+ ] cyto ) and receptor-mediated Ca 2+ signalling. Here we investigate channels responsible for ER Ca 2+ leak in THP-1 macrophage and human primary macrophage. In the absence of extracellular Ca 2+ we employ ionomycin action at the plasma membrane to stimulate ER Ca 2+ leak. Under these conditions ionomycin elevates [Ca 2+ ] cyto revealing a Ca 2+ leak response which is abolished by thapsigargin. IP 3 receptors (Xestospongin C, 2-APB), ryanodine receptors (dantrolene), and translocon (anisomycin) inhibition facilitated ER Ca 2+ leak in model macrophage, with translocon inhibition also reducing resting [Ca 2+ ] cyto . In primary macrophage, translocon inhibition blocks Ca 2+ leak but does not influence resting [Ca 2+ ] cyto . We identify a role for translocon-mediated ER Ca 2+ leak in receptor-mediated Ca 2+ signalling in both model and primary human macrophage, whereby the Ca 2+ response to ADP (P2Y receptor agonist) is augmented following anisomycin treatment. In conclusion, we demonstrate a role of ER Ca 2+ leak via the translocon in controlling resting cytoplasmic Ca 2+ in model macrophage and receptor-mediated Ca 2+ signalling in model macrophage and primary macrophage. Copyright © 2017 Elsevier Inc. All rights reserved.

Src-family kinases negatively regulate NFAT signaling in resting human T cells.

Directory of Open Access Journals (Sweden)

Alan Baer

Full Text Available T cell signaling is required for activation of both natural and therapeutic T cells including chimeric antigen receptor (CAR T cells. Identification of novel factors and pathways regulating T cell signaling may aid in development of effective T cell therapies. In resting human T cells, the majority of Src-family of tyrosine kinases (SFKs are inactive due to phosphorylation of a conserved carboxy-terminal tyrosine residue. Recently, a pool of enzymatically active SFKs has been identified in resting T cells; however, the significance of these is incompletely understood. Here, we characterized the role of active SFKs in resting human T cells. Pharmacologic inhibition of active SFKs enhanced distal TCR signaling as measured by IL-2 release and CD25 surface expression following TCR-independent activation. Mechanistically, inhibition of the active pool of SFKs induced nuclear translocation of NFAT1, and enhanced NFAT1-dependent signaling in resting T cells. The negative regulation of NFAT1 signaling was in part mediated by the Src-kinase Lck as human T cells lacking Lck had increased levels of nuclear NFAT1 and demonstrated enhanced NFAT1-dependent gene expression. Inhibition of active SFKs in resting primary human T cells also increased nuclear NFAT1 and enhanced NFAT1-dependent signaling. Finally, the calcineurin inhibitor FK506 and Cyclosporin A reversed the effect of SFKs inhibition on NFAT1. Together, these data identified a novel role of SFKs in preventing aberrant NFAT1 activation in resting T cells, and suggest that maintaining this pool of active SFKs in therapeutic T cells may increase the efficacy of T cell therapies.

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

Regression models of reactor diagnostic signals

International Nuclear Information System (INIS)

Vavrin, J.

1989-01-01

The application is described of an autoregression model as the simplest regression model of diagnostic signals in experimental analysis of diagnostic systems, in in-service monitoring of normal and anomalous conditions and their diagnostics. The method of diagnostics is described using a regression type diagnostic data base and regression spectral diagnostics. The diagnostics is described of neutron noise signals from anomalous modes in the experimental fuel assembly of a reactor. (author)

Diabetes: Models, Signals and control

Science.gov (United States)

Cobelli, C.

2010-07-01

Diabetes and its complications impose significant economic consequences on individuals, families, health systems, and countries. The control of diabetes is an interdisciplinary endeavor, which includes significant components of modeling, signal processing and control. Models: first, I will discuss the minimal (coarse) models which describe the key components of the system functionality and are capable of measuring crucial processes of glucose metabolism and insulin control in health and diabetes; then, the maximal (fine-grain) models which include comprehensively all available knowledge about system functionality and are capable to simulate the glucose-insulin system in diabetes, thus making it possible to create simulation scenarios whereby cost effective experiments can be conducted in silico to assess the efficacy of various treatment strategies - in particular I will focus on the first in silico simulation model accepted by FDA as a substitute to animal trials in the quest for optimal diabetes control. Signals: I will review metabolic monitoring, with a particular emphasis on the new continuous glucose sensors, on the crucial role of models to enhance the interpretation of their time-series signals, and on the opportunities that they present for automation of diabetes control. Control: I will review control strategies that have been successfully employed in vivo or in silico, presenting a promise for the development of a future artificial pancreas and, in particular, I will discuss a modular architecture for building closed-loop control systems, including insulin delivery and patient safety supervision layers.

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

Estrogen receptor beta signaling inhibits PDGF induced human airway smooth muscle proliferation.

Science.gov (United States)

Ambhore, Nilesh Sudhakar; Katragadda, Rathnavali; Raju Kalidhindi, Rama Satyanarayana; Thompson, Michael A; Pabelick, Christina M; Prakash, Y S; Sathish, Venkatachalem

2018-04-20

Airway smooth muscle (ASM) cell hyperplasia driven by persistent inflammation is a hallmark feature of remodeling in asthma. Sex steroid signaling in the lungs is of considerable interest, given epidemiological data showing more asthma in pre-menopausal women and aging men. Our previous studies demonstrated that estrogen receptor (ER) expression increases in asthmatic human ASM; however, very limited data are available regarding differential roles of ERα vs. ERβ isoforms in human ASM cell proliferation. In this study, we evaluated the effect of selective ERα and ERβ modulators on platelet-derived growth factor (PDGF)-stimulated ASM proliferation and the mechanisms involved. Asthmatic and non-asthmatic primary human ASM cells were treated with PDGF, 17β-estradiol, ERα-agonist and/or ERβ-agonist and/or G-protein-coupled estrogen receptor 30 (GPR30/GPER) agonist and proliferation was measured using MTT and CyQuant assays followed by cell cycle analysis. Transfection of small interfering RNA (siRNA) ERα and ERβ significantly altered the human ASM proliferation. The specificity of siRNA transfection was confirmed by Western blot analysis. Gene and protein expression of cell cycle-related antigens (PCNA and Ki67) and C/EBP were measured by RT-PCR and Western analysis, along with cell signaling proteins. PDGF significantly increased ASM proliferation in non-asthmatic and asthmatic cells. Treatment with PPT showed no significant effect on PDGF-induced proliferation, whereas WAY interestingly suppressed proliferation via inhibition of ERK1/2, Akt, and p38 signaling. PDGF-induced gene expression of PCNA, Ki67 and C/EBP in human ASM was significantly lower in cells pre-treated with WAY. Furthermore, WAY also inhibited PDGF-activated PCNA, C/EBP, cyclin-D1, and cyclin-E. Overall, we demonstrate ER isoform-specific signaling in the context of ASM proliferation. Activation of ERβ can diminish remodeling in human ASM by inhibiting pro-proliferative signaling pathways

Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model

Science.gov (United States)

Rizvi, Farheen

2016-01-01

Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.

Notch signaling is required for maintaining stem-cell features of neuroprogenitor cells derived from human embryonic stem cells

Directory of Open Access Journals (Sweden)

Chung Hyung-Min

2009-08-01

Full Text Available Abstract Background Studies have provided important findings about the roles of Notch signaling in neural development. Unfortunately, however, most of these studies have investigated the neural stem cells (NSCs of mice or other laboratory animals rather than humans, mainly owing to the difficulties associated with obtaining human brain samples. It prompted us to focus on neuroectodermal spheres (NESs which are derived from human embryonic stem cell (hESC and densely inhabited by NSCs. We here investigated the role of Notch signaling with the hESC-derived NESs. Results From hESCs, we derived NESs, the in-vitro version of brain-derived neurospheres. NES formation was confirmed by increased levels of various NSC marker genes and the emergence of rosette structures in which neuroprogenitors are known to reside. We found that Notch signaling, which maintains stem cell characteristics of in-vivo-derived neuroprogenitors, is active in these hESC-derived NESs, similar to their in-vivo counterpart. Expression levels of Notch signaling molecules such as NICD, DLLs, JAG1, HES1 and HES5 were increased in the NESs. Inhibition of the Notch signaling by a γ-secretase inhibitor reduced rosette structures, expression levels of NSC marker genes and proliferation potential in the NESs, and, if combined with withdrawal of growth factors, triggered differentiation toward neurons. Conclusion Our results indicate that the hESC-derived NESs, which share biochemical features with brain-derived neurospheres, maintain stem cell characteristics mainly through Notch signaling, which suggests that the hESC-derived NESs could be an in-vitro model for in-vivo neurogenesis.

Neuroelectronics and modeling of electrical signals for monitoring and control of Parkinson's disease

Science.gov (United States)

Chintakuntla, Ritesh R.; Abraham, Jose K.; Varadan, Vijay K.

2009-03-01

The brain and the human nervous system are perhaps the most researched but least understood components of the human body. This is so because of the complex nature of its working and the high density of functions. The monitoring of neural signals could help one better understand the working of the brain and newer recording and monitoring methods have been developed ever since it was discovered that the brain communicates internally by means of electrical pulses. Neuroelectronics is the field which deals with the interface between electronics or semiconductors to living neurons. This includes monitoring of electrical activity from the brain as well as the development of feedback devices for stimulation of parts of the brain for treatment of disorders. In this paper these electrical signals are modeled through a nano/microelectrode arrays based on the electronic equivalent model using Cadence PSD 15.0. The results were compared with those previously published models such as Kupfmuller and Jenik's model, McGrogan's Neuron Model which are based on the Hodgkin and Huxley model. We have developed and equivalent circuit model using discrete passive components to simulate the electrical activity of the neurons. The simulated circuit can be easily be modified by adding some more ionic channels and the results can be used to predict necessary external stimulus needed for stimulation of neurons affected by the Parkinson's disease (PD). Implementing such a model in PD patients could predict the necessary voltages required for the electrical stimulation of the sub-thalamus region for the control tremor motion.

Comparison of Linear Prediction Models for Audio Signals

Directory of Open Access Journals (Sweden)

2009-03-01

Full Text Available While linear prediction (LP has become immensely popular in speech modeling, it does not seem to provide a good approach for modeling audio signals. This is somewhat surprising, since a tonal signal consisting of a number of sinusoids can be perfectly predicted based on an (all-pole LP model with a model order that is twice the number of sinusoids. We provide an explanation why this result cannot simply be extrapolated to LP of audio signals. If noise is taken into account in the tonal signal model, a low-order all-pole model appears to be only appropriate when the tonal components are uniformly distributed in the Nyquist interval. Based on this observation, different alternatives to the conventional LP model can be suggested. Either the model should be changed to a pole-zero, a high-order all-pole, or a pitch prediction model, or the conventional LP model should be preceded by an appropriate frequency transform, such as a frequency warping or downsampling. By comparing these alternative LP models to the conventional LP model in terms of frequency estimation accuracy, residual spectral flatness, and perceptual frequency resolution, we obtain several new and promising approaches to LP-based audio modeling.

MASCOTTE: analytical model of eddy current signals

International Nuclear Information System (INIS)

Delsarte, G.; Levy, R.

1992-01-01

Tube examination is a major application of the eddy current technique in the nuclear and petrochemical industries. Such examination configurations being specially adapted to analytical modes, a physical model is developed on portable computers. It includes simple approximations made possible by the effective conditions of the examinations. The eddy current signal is described by an analytical formulation that takes into account the tube dimensions, the sensor conception, the physical characteristics of the defect and the examination parameters. Moreover, the model makes it possible to associate real signals and simulated signals

Stretch activates human myometrium via ERK, caldesmon and focal adhesion signaling.

Directory of Open Access Journals (Sweden)

Yunping Li

2009-10-01

Full Text Available An incomplete understanding of the molecular mechanisms responsible for myometrial activation from the quiescent pregnant state to the active contractile state during labor has hindered the development of effective therapies for preterm labor. Myometrial stretch has been implicated clinically in the initiation of labor and the etiology of preterm labor, but the molecular mechanisms involved in the human have not been determined. We investigated the mechanisms by which gestation-dependent stretch contributes to myometrial activation, by using human uterine samples from gynecologic hysterectomies and Cesarean sections. Here we demonstrate that the Ca requirement for activation of the contractile filaments in human myometrium increases with caldesmon protein content during gestation and that an increase in caldesmon phosphorylation can reverse this inhibitory effect during labor. By using phosphotyrosine screening and mass spectrometry of stretched human myometrial samples, we identify 3 stretch-activated focal adhesion proteins, FAK, p130Cas, and alpha actinin. FAK-Y397, which signals integrin engagement, is constitutively phosphorylated in term human myometrium whereas FAK-Y925, which signals downstream ERK activation, is phosphorylated during stretch. We have recently identified smooth muscle Archvillin (SmAV as an ERK regulator. A newly produced SmAV-specific antibody demonstrates gestation-specific increases in SmAV protein levels and stretch-specific increases in SmAV association with focal adhesion proteins. Thus, whereas increases in caldesmon levels suppress human myometrium contractility during pregnancy, stretch-dependent focal adhesion signaling, facilitated by the ERK activator SmAV, can contribute to myometrial activation. These results suggest that focal adhesion proteins may present new targets for drug discovery programs aimed at regulation of uterine contractility.

Monte Carlo modeling of human tooth optical coherence tomography imaging

International Nuclear Information System (INIS)

Shi, Boya; Meng, Zhuo; Wang, Longzhi; Liu, Tiegen

2013-01-01

We present a Monte Carlo model for optical coherence tomography (OCT) imaging of human tooth. The model is implemented by combining the simulation of a Gaussian beam with simulation for photon propagation in a two-layer human tooth model with non-parallel surfaces through a Monte Carlo method. The geometry and the optical parameters of the human tooth model are chosen on the basis of the experimental OCT images. The results show that the simulated OCT images are qualitatively consistent with the experimental ones. Using the model, we demonstrate the following: firstly, two types of photons contribute to the information of morphological features and noise in the OCT image of a human tooth, respectively. Secondly, the critical imaging depth of the tooth model is obtained, and it is found to decrease significantly with increasing mineral loss, simulated as different enamel scattering coefficients. Finally, the best focus position is located below and close to the dental surface by analysis of the effect of focus positions on the OCT signal and critical imaging depth. We anticipate that this modeling will become a powerful and accurate tool for a preliminary numerical study of the OCT technique on diseases of dental hard tissue in human teeth. (paper)

Characterization of NAADP-mediated calcium signaling in human spermatozoa

Energy Technology Data Exchange (ETDEWEB)

Sánchez-Tusie, A.A. [Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos (Mexico); Vasudevan, S.R.; Churchill, G.C. [Department of Pharmacology, University of Oxford, Oxford OX1 3QT, England (United Kingdom); Nishigaki, T. [Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos (Mexico); Treviño, C.L., E-mail: ctrevino@ibt.unam.mx [Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos (Mexico)

2014-01-10

Highlights: •Human sperm cells synthesize NAADP. •NAADP-AM mediates [Ca{sup 2+}]{sub i} increases in human sperm in the absence of [Ca{sup 2+}]{sub o}. •Human sperm have two acidic compartments located in the head and midpiece. -- Abstract: Ca{sup 2+} signaling in spermatozoa plays a crucial role during processes such as capacitation and release of the acrosome, but the underlying molecular mechanisms still remain unclear. Nicotinic acid adenine dinucleotide phosphate (NAADP) is a potent Ca{sup 2+}-releasing second messenger in a variety of cellular processes. The presence of a NAADP synthesizing enzyme in sea urchin sperm has been previously reported, suggesting a possible role of NAADP in sperm Ca{sup 2+} signaling. In this work we used in vitro enzyme assays to show the presence of a novel NAADP synthesizing enzyme in human sperm, and to characterize its sensitivity to Ca{sup 2+} and pH. Ca{sup 2+} fluorescence imaging studies demonstrated that the permeable form of NAADP (NAADP-AM) induces intracellular [Ca{sup 2+}] increases in human sperm even in the absence of extracellular Ca{sup 2+}. Using LysoTracker®, a fluorescent probe that selectively accumulates in acidic compartments, we identified two such stores in human sperm cells. Their acidic nature was further confirmed by the reduction in staining intensity observed upon inhibition of the endo-lysosomal proton pump with Bafilomycin, or after lysosomal bursting with glycyl-L-phenylalanine-2-naphthylamide. The selective fluorescent NAADP analog, Ned-19, stained the same subcellular regions as LysoTracker®, suggesting that these stores are the targets of NAADP action.

Human sensorimotor communication: a theory of signaling in online social interactions.

Science.gov (United States)

Pezzulo, Giovanni; Donnarumma, Francesco; Dindo, Haris

2013-01-01

Although the importance of communication is recognized in several disciplines, it is rarely studied in the context of online social interactions and joint actions. During online joint actions, language and gesture are often insufficient and humans typically use non-verbal, sensorimotor forms of communication to send coordination signals. For example, when playing volleyball, an athlete can exaggerate her movements to signal her intentions to her teammates (say, a pass to the right) or to feint an adversary. Similarly, a person who is transporting a table together with a co-actor can push the table in a certain direction to signal where and when he intends to place it. Other examples of "signaling" are over-articulating in noisy environments and over-emphasizing vowels in child-directed speech. In all these examples, humans intentionally modify their action kinematics to make their goals easier to disambiguate. At the moment no formal theory exists of these forms of sensorimotor communication and signaling. We present one such theory that describes signaling as a combination of a pragmatic and a communicative action, and explains how it simplifies coordination in online social interactions. We cast signaling within a "joint action optimization" framework in which co-actors optimize the success of their interaction and joint goals rather than only their part of the joint action. The decision of whether and how much to signal requires solving a trade-off between the costs of modifying one's behavior and the benefits in terms of interaction success. Signaling is thus an intentional strategy that supports social interactions; it acts in concert with automatic mechanisms of resonance, prediction, and imitation, especially when the context makes actions and intentions ambiguous and difficult to read. Our theory suggests that communication dynamics should be studied within theories of coordination and interaction rather than only in terms of the maximization of information

Human sensorimotor communication: a theory of signaling in online social interactions.

Directory of Open Access Journals (Sweden)

Giovanni Pezzulo

Full Text Available Although the importance of communication is recognized in several disciplines, it is rarely studied in the context of online social interactions and joint actions. During online joint actions, language and gesture are often insufficient and humans typically use non-verbal, sensorimotor forms of communication to send coordination signals. For example, when playing volleyball, an athlete can exaggerate her movements to signal her intentions to her teammates (say, a pass to the right or to feint an adversary. Similarly, a person who is transporting a table together with a co-actor can push the table in a certain direction to signal where and when he intends to place it. Other examples of "signaling" are over-articulating in noisy environments and over-emphasizing vowels in child-directed speech. In all these examples, humans intentionally modify their action kinematics to make their goals easier to disambiguate. At the moment no formal theory exists of these forms of sensorimotor communication and signaling. We present one such theory that describes signaling as a combination of a pragmatic and a communicative action, and explains how it simplifies coordination in online social interactions. We cast signaling within a "joint action optimization" framework in which co-actors optimize the success of their interaction and joint goals rather than only their part of the joint action. The decision of whether and how much to signal requires solving a trade-off between the costs of modifying one's behavior and the benefits in terms of interaction success. Signaling is thus an intentional strategy that supports social interactions; it acts in concert with automatic mechanisms of resonance, prediction, and imitation, especially when the context makes actions and intentions ambiguous and difficult to read. Our theory suggests that communication dynamics should be studied within theories of coordination and interaction rather than only in terms of the

Dressed for Sex: Red as a Female Sexual Signal in Humans

Science.gov (United States)

Elliot, Andrew J.; Pazda, Adam D.

2012-01-01

Background In many non-human primate species, a display of red by a female serves as a sexual signal to attract male conspecifics. Red is associated with sex and romance in humans, and women convey their sexual interest to men through a variety of verbal, postural, and behavioral means. In the present research, we investigate whether female red ornamentation in non-human primates has a human analog, whereby women use a behavioral display of red to signal their sexual interest to men. Methodology/Principal Findings Three studies tested the hypothesis that women use red clothing to communicate sexual interest to men in profile pictures on dating websites. In Study 1, women who imagined being interested in casual sex were more likely to display red (but not other colors) on their anticipated web profile picture. In Study 2, women who indicated interest in casual sex were more likely to prominently display red (but not other colors) on their actual web profile picture. In Study 3, women on a website dedicated to facilitating casual sexual relationships were more likely to prominently exhibit red (but not other colors) than women on a website dedicated to facilitating marital relationships. Conclusions/Significance These results establish a provocative parallel between women and non-human female primates in red signal coloration in the mating game. This research shows, for the first time, a functional use of color in women's sexual self-presentation, and highlights the need to extend research on color beyond physics, physiology, and preference to psychological functioning. PMID:22514643

Dressed for sex: red as a female sexual signal in humans.

Directory of Open Access Journals (Sweden)

Andrew J Elliot

Full Text Available BACKGROUND: In many non-human primate species, a display of red by a female serves as a sexual signal to attract male conspecifics. Red is associated with sex and romance in humans, and women convey their sexual interest to men through a variety of verbal, postural, and behavioral means. In the present research, we investigate whether female red ornamentation in non-human primates has a human analog, whereby women use a behavioral display of red to signal their sexual interest to men. METHODOLOGY/PRINCIPAL FINDINGS: Three studies tested the hypothesis that women use red clothing to communicate sexual interest to men in profile pictures on dating websites. In Study 1, women who imagined being interested in casual sex were more likely to display red (but not other colors on their anticipated web profile picture. In Study 2, women who indicated interest in casual sex were more likely to prominently display red (but not other colors on their actual web profile picture. In Study 3, women on a website dedicated to facilitating casual sexual relationships were more likely to prominently exhibit red (but not other colors than women on a website dedicated to facilitating marital relationships. CONCLUSIONS/SIGNIFICANCE: These results establish a provocative parallel between women and non-human female primates in red signal coloration in the mating game. This research shows, for the first time, a functional use of color in women's sexual self-presentation, and highlights the need to extend research on color beyond physics, physiology, and preference to psychological functioning.

Development of steroid signaling pathways during primordial follicle formation in the human fetal ovary.

Science.gov (United States)

Fowler, Paul A; Anderson, Richard A; Saunders, Philippa T; Kinnell, Hazel; Mason, J Ian; Evans, Dean B; Bhattacharya, Siladitya; Flannigan, Samantha; Franks, Stephen; Monteiro, Ana; O'Shaughnessy, Peter J

2011-06-01

Ovarian primordial follicle formation is critical for subsequent human female fertility. It is likely that steroid, and especially estrogen, signaling is required for this process, but details of the pathways involved are currently lacking. The aim was to identify and characterize key members of the steroid-signaling pathway expressed in the second trimester human fetal ovary. We conducted an observational study of the female fetus, quantifying and localizing steroid-signaling pathway members. The study was conducted at the Universities of Aberdeen, Edinburgh, and Glasgow. Ovaries were collected from 43 morphologically normal human female fetuses from women undergoing elective termination of second trimester pregnancies. We measured mRNA transcript levels and immunolocalized key steroidogenic enzymes and steroid receptors, including those encoded by ESR2, AR, and CYP19A1. Levels of mRNA encoding the steroidogenic apparatus and steroid receptors increased across the second trimester. CYP19A1 transcript increased 4.7-fold during this period with intense immunostaining for CYP19A detected in pregranulosa cells around primordial follicles and somatic cells around oocyte nests. ESR2 was localized primarily to germ cells, but androgen receptor was exclusively expressed in somatic cells. CYP17A1 and HSD3B2 were also localized to oocytes, whereas CYP11A1 was detected in oocytes and some pregranulosa cells. The human fetal ovary expresses the machinery to produce and detect multiple steroid signaling pathways, including estrogenic signaling, with the oocyte acting as a key component. This study provides a step-change in our understanding of local dynamics of steroid hormone signaling during the key period of human primordial follicle formation.

Envelope statistics of self-motion signals experienced by human subjects during everyday activities: Implications for vestibular processing.

Science.gov (United States)

Carriot, Jérome; Jamali, Mohsen; Cullen, Kathleen E; Chacron, Maurice J

2017-01-01

There is accumulating evidence that the brain's neural coding strategies are constrained by natural stimulus statistics. Here we investigated the statistics of the time varying envelope (i.e. a second-order stimulus attribute that is related to variance) of rotational and translational self-motion signals experienced by human subjects during everyday activities. We found that envelopes can reach large values across all six motion dimensions (~450 deg/s for rotations and ~4 G for translations). Unlike results obtained in other sensory modalities, the spectral power of envelope signals decreased slowly for low (2 Hz) temporal frequencies and thus was not well-fit by a power law. We next compared the spectral properties of envelope signals resulting from active and passive self-motion, as well as those resulting from signals obtained when the subject is absent (i.e. external stimuli). Our data suggest that different mechanisms underlie deviation from scale invariance in rotational and translational self-motion envelopes. Specifically, active self-motion and filtering by the human body cause deviation from scale invariance primarily for translational and rotational envelope signals, respectively. Finally, we used well-established models in order to predict the responses of peripheral vestibular afferents to natural envelope stimuli. We found that irregular afferents responded more strongly to envelopes than their regular counterparts. Our findings have important consequences for understanding the coding strategies used by the vestibular system to process natural second-order self-motion signals.

Red is not a proxy signal for female genitalia in humans.

Directory of Open Access Journals (Sweden)

Sarah E Johns

Full Text Available Red is a colour that induces physiological and psychological effects in humans, affecting competitive and sporting success, signalling and enhancing male social dominance. The colour is also associated with increased sexual attractiveness, such that women associated with red objects or contexts are regarded as more desirable. It has been proposed that human males have a biological predisposition towards the colour red such that it is 'sexually salient'. This hypothesis argues that women use the colour red to announce impending ovulation and sexual proceptivity, with this functioning as a proxy signal for genital colour, and that men show increased attraction in consequence. In the first test of this hypothesis, we show that contrary to the hypothesis, heterosexual men did not prefer redder female genitalia and, by extension, that red is not a proxy signal for genital colour. We found a relative preference for pinker genital images with redder genitalia rated significantly less sexually attractive. This effect was independent of raters' prior sexual experience and variation in female genital morphology. Our results refute the hypothesis that men's attraction to red is linked to an implied relationship to genital colour and women's signalling of fertility and sexual proceptivity.

Signals of historical interlocus gene conversion in human segmental duplications.

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Beth L Dumont

Full Text Available Standard methods of DNA sequence analysis assume that sequences evolve independently, yet this assumption may not be appropriate for segmental duplications that exchange variants via interlocus gene conversion (IGC. Here, we use high quality multiple sequence alignments from well-annotated segmental duplications to systematically identify IGC signals in the human reference genome. Our analysis combines two complementary methods: (i a paralog quartet method that uses DNA sequence simulations to identify a statistical excess of sites consistent with inter-paralog exchange, and (ii the alignment-based method implemented in the GENECONV program. One-quarter (25.4% of the paralog families in our analysis harbor clear IGC signals by the quartet approach. Using GENECONV, we identify 1477 gene conversion tracks that cumulatively span 1.54 Mb of the genome. Our analyses confirm the previously reported high rates of IGC in subtelomeric regions and Y-chromosome palindromes, and identify multiple novel IGC hotspots, including the pregnancy specific glycoproteins and the neuroblastoma breakpoint gene families. Although the duplication history of a paralog family is described by a single tree, we show that IGC has introduced incredible site-to-site variation in the evolutionary relationships among paralogs in the human genome. Our findings indicate that IGC has left significant footprints in patterns of sequence diversity across segmental duplications in the human genome, out-pacing the contributions of single base mutation by orders of magnitude. Collectively, the IGC signals we report comprise a catalog that will provide a critical reference for interpreting observed patterns of DNA sequence variation across duplicated genomic regions, including targets of recent adaptive evolution in humans.

Modeling High-Dimensional Multichannel Brain Signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert J.; Ombao, Hernando

2017-01-01

aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel

Tracking Human Mobility Using WiFi Signals

DEFF Research Database (Denmark)

Sapiezynski, Piotr; Stopczynski, Arkadiusz; Gatej, Radu

2015-01-01

We study six months of human mobility data, including WiFi and GPS traces recorded with high temporal resolution, and find that time series of WiFi scans contain a strong latent location signal. In fact, due to inherent stability and low entropy of human mobility, it is possible to assign location...... to WiFi access points based on a very small number of GPS samples and then use these access points as location beacons. Using just one GPS observation per day per person allows us to estimate the location of, and subsequently use, WiFi access points to account for 80% of mobility across a population....... These results reveal a great opportunity for using ubiquitous WiFi routers for high-resolution outdoor positioning, but also significant privacy implications of such side-channel location tracking....

Electrical signal analysis to assess the physical condition of a human or animal

Science.gov (United States)

Cox, Daryl F.; Hochanadel, Charles D.; Haynes, Howard D.

2010-06-15

The invention is a human and animal performance data acquisition, analysis, and diagnostic system for fitness and therapy devices having an interface box removably disposed on incoming power wiring to a fitness and therapy device, at least one current transducer removably disposed on said interface box for sensing current signals to said fitness and therapy device, and a means for analyzing, displaying, and reporting said current signals to determine human and animal performance on said device using measurable parameters.

Extremely low frequency electromagnetic field exposure does not modulate Toll-like receptor signaling in human peripheral blood mononuclear cells

NARCIS (Netherlands)

Kleijn, de S.; Bouwens, M.; Verburg-van Kemenade, B.M.L.; Cuppen, J.J.M.; Ferwerda, G.; Hermans, P.

2011-01-01

The effects of extremely low frequency electromagnetic fields (ELF-EMF) on human health remain unclear. It has been reported that ELF-EMF may modulate the innate immune response to microorganisms in animal models and mammalian cell-lines. With the recently gained insight in innate immune signaling

Structural basis of SUFU–GLI interaction in human Hedgehog signalling regulation

International Nuclear Information System (INIS)

Cherry, Amy L.; Finta, Csaba; Karlström, Mikael; Jin, Qianren; Schwend, Thomas; Astorga-Wells, Juan; Zubarev, Roman A.; Del Campo, Mark; Criswell, Angela R.; Sanctis, Daniele de; Jovine, Luca; Toftgård, Rune

2013-01-01

Crystal and small-angle X-ray scattering structures of full-length human SUFU alone and in complex with the conserved SYGHL motif from GLI transcription factors show major conformational changes associated with binding and reveal an intrinsically disordered region crucial for pathway activation. Hedgehog signalling plays a fundamental role in the control of metazoan development, cell proliferation and differentiation, as highlighted by the fact that its deregulation is associated with the development of many human tumours. SUFU is an essential intracellular negative regulator of mammalian Hedgehog signalling and acts by binding and modulating the activity of GLI transcription factors. Despite its central importance, little is known about SUFU regulation and the nature of SUFU–GLI interaction. Here, the crystal and small-angle X-ray scattering structures of full-length human SUFU and its complex with the key SYGHL motif conserved in all GLIs are reported. It is demonstrated that GLI binding is associated with major conformational changes in SUFU, including an intrinsically disordered loop that is also crucial for pathway activation. These findings reveal the structure of the SUFU–GLI interface and suggest a mechanism for an essential regulatory step in Hedgehog signalling, offering possibilities for the development of novel pathway modulators and therapeutics

Structural basis of SUFU–GLI interaction in human Hedgehog signalling regulation

Energy Technology Data Exchange (ETDEWEB)

Cherry, Amy L.; Finta, Csaba; Karlström, Mikael; Jin, Qianren; Schwend, Thomas [Karolinska Institutet, Novum, Hälsovägen 7, SE-141 83 Huddinge (Sweden); Astorga-Wells, Juan [Karolinska Institutet, Scheeles väg 2, SE-171 77 Stockholm (Sweden); Biomotif AB, Enhagsvägen 7, SE-182 12 Danderyd (Sweden); Zubarev, Roman A. [Karolinska Institutet, Scheeles väg 2, SE-171 77 Stockholm (Sweden); Del Campo, Mark; Criswell, Angela R. [Rigaku Americas Corporation, 9009 New Trails Drive, The Woodlands, TX 77381 (United States); Sanctis, Daniele de [European Synchrotron Radiation Facility, 6 Rue Jules Horowitz, 38043 Grenoble (France); Jovine, Luca, E-mail: luca.jovine@ki.se; Toftgård, Rune, E-mail: luca.jovine@ki.se [Karolinska Institutet, Novum, Hälsovägen 7, SE-141 83 Huddinge (Sweden)

2013-12-01

Crystal and small-angle X-ray scattering structures of full-length human SUFU alone and in complex with the conserved SYGHL motif from GLI transcription factors show major conformational changes associated with binding and reveal an intrinsically disordered region crucial for pathway activation. Hedgehog signalling plays a fundamental role in the control of metazoan development, cell proliferation and differentiation, as highlighted by the fact that its deregulation is associated with the development of many human tumours. SUFU is an essential intracellular negative regulator of mammalian Hedgehog signalling and acts by binding and modulating the activity of GLI transcription factors. Despite its central importance, little is known about SUFU regulation and the nature of SUFU–GLI interaction. Here, the crystal and small-angle X-ray scattering structures of full-length human SUFU and its complex with the key SYGHL motif conserved in all GLIs are reported. It is demonstrated that GLI binding is associated with major conformational changes in SUFU, including an intrinsically disordered loop that is also crucial for pathway activation. These findings reveal the structure of the SUFU–GLI interface and suggest a mechanism for an essential regulatory step in Hedgehog signalling, offering possibilities for the development of novel pathway modulators and therapeutics.

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.

Research on Healthy Anomaly Detection Model Based on Deep Learning from Multiple Time-Series Physiological Signals

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Kai Wang

2016-01-01

Full Text Available Health is vital to every human being. To further improve its already respectable medical technology, the medical community is transitioning towards a proactive approach which anticipates and mitigates risks before getting ill. This approach requires measuring the physiological signals of human and analyzes these data at regular intervals. In this paper, we present a novel approach to apply deep learning in physiological signals analysis that allows doctor to identify latent risks. However, extracting high level information from physiological time-series data is a hard problem faced by the machine learning communities. Therefore, in this approach, we apply model based on convolutional neural network that can automatically learn features from raw physiological signals in an unsupervised manner and then based on the learned features use multivariate Gauss distribution anomaly detection method to detect anomaly data. Our experiment is shown to have a significant performance in physiological signals anomaly detection. So it is a promising tool for doctor to identify early signs of illness even if the criteria are unknown a priori.

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.

Signal analysis of accelerometry data using gravity-based modeling

Science.gov (United States)

Davey, Neil P.; James, Daniel A.; Anderson, Megan E.

2004-03-01

Triaxial accelerometers have been used to measure human movement parameters in swimming. Interpretation of data is difficult due to interference sources including interaction of external bodies. In this investigation the authors developed a model to simulate the physical movement of the lower back. Theoretical accelerometery outputs were derived thus giving an ideal, or noiseless dataset. An experimental data collection apparatus was developed by adapting a system to the aquatic environment for investigation of swimming. Model data was compared against recorded data and showed strong correlation. Comparison of recorded and modeled data can be used to identify changes in body movement, this is especially useful when cyclic patterns are present in the activity. Strong correlations between data sets allowed development of signal processing algorithms for swimming stroke analysis using first the pure noiseless data set which were then applied to performance data. Video analysis was also used to validate study results and has shown potential to provide acceptable results.

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

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

Modeling laser velocimeter signals as triply stochastic Poisson processes

Science.gov (United States)

Mayo, W. T., Jr.

1976-01-01

Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.

Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

Science.gov (United States)

Dong, Xu; Foteinou, Panagiota T; Calvano, Steven E; Lowry, Stephen F; Androulakis, Ioannis P

2010-02-18

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions. An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades. The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve

Gamma-glutamylcyclotransferase promotes the growth of human glioma cells by activating Notch-Akt signaling

Energy Technology Data Exchange (ETDEWEB)

Shen, Shang-Hang; Yu, Ning; Liu, Xi-Yao; Tan, Guo-Wei; Wang, Zhan-Xiang, E-mail: md_wzx7189@163.com

2016-03-18

Glioma as an aggressive type tumor is rapidly growing and has become one of the leading cause of cancer-related death worldwide. γ-Glutamylcyclotransferase (GGCT) has been shown as a diagnostic marker in various cancers. To reveal whether there is a correlation between GGCT and human glioma, GGCT expression in human glioma tissues and cell lines was first determined. We found that GGCT expression was up-regulated in human glioma tissues and cell lines. Further, we demonstrate that GGCT knockdown inhibits glioma cell T98G and U251 proliferation and colony formation, whereas GGCT overexpression leads to oppose effects. GGCT overexpression promotes the expression of Notch receptors and activates Akt signaling in glioma cells, and Notch-Akt signaling is activated in glioma tissues with high expression of GGCT. Finally, we show that inhibition of Notch-Akt signaling with Notch inhibitor MK-0752 blocks the effects of GGCT on glioma proliferation and colony formation. In conclusion, GGCT plays a critical role in glioma cell proliferation and may be a potential cancer therapeutic target. - Highlights: • GGCT expression is up-regulated in human glioma tissues and cell lines. • GGCT promotes glioma cell growth and colony formation. • GGCT promotes the activation of Notch-Akt signaling in glioma cells and tissues. • Notch inhibition blocks the role of GGCT in human glioma cells.

Modeling high dimensional multichannel brain signals

KAUST Repository

Hu, Lechuan

2017-03-27

In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

Modeling high dimensional multichannel brain signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert; Ombao, Hernando

2017-01-01

In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

Modeling High-Dimensional Multichannel Brain Signals

KAUST Repository

Hu, Lechuan

2017-12-12

Our goal is to model and measure functional and effective (directional) connectivity in multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The difficulties from analyzing these data mainly come from two aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with potentially high lag order so that complex lead-lag temporal dynamics between the channels can be captured. Estimates of the VAR model will be obtained by our proposed hybrid LASSLE (LASSO + LSE) method which combines regularization (to control for sparsity) and least squares estimation (to improve bias and mean-squared error). Then we employ some measures of connectivity but put an emphasis on partial directed coherence (PDC) which can capture the directional connectivity between channels. PDC is a frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative to all possible receivers in the network. The proposed modeling approach provided key insights into potential functional relationships among simultaneously recorded sites during performance of a complex memory task. Specifically, this novel method was successful in quantifying patterns of effective connectivity across electrode locations, and in capturing how these patterns varied across trial epochs and trial types.

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).

Adaptive control of human action: The role of outcome representations and reward signals

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Hans eMarien

2013-09-01

Full Text Available The present paper aims to advance the understanding of the control of human behavior by integrating two lines of literature that so far have led separate lives. First, one line of literature is concerned with the ideomotor principle of human behavior, according to which actions are represented in terms of their outcomes. The second line of literature mainly considers the role of reward signals in adaptive control. Here, we offer a combined perspective on how outcome representations and reward signals work together to modulate adaptive control processes. We propose that reward signals signify the value of outcome representations and facilitate the recruitment of control resources in situations where behavior needs to be maintained or adapted to attain the represented outcome. We discuss recent research demonstrating how adaptive control of goal-directed behavior may emerge when outcome representations are co-activated with positive reward signals.

Modelling noninvasively measured cerebral signals during a hypoxemia challenge: steps towards individualised modelling.

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Beth Jelfs

Full Text Available Noninvasive approaches to measuring cerebral circulation and metabolism are crucial to furthering our understanding of brain function. These approaches also have considerable potential for clinical use "at the bedside". However, a highly nontrivial task and precondition if such methods are to be used routinely is the robust physiological interpretation of the data. In this paper, we explore the ability of a previously developed model of brain circulation and metabolism to explain and predict quantitatively the responses of physiological signals. The five signals all noninvasively-measured during hypoxemia in healthy volunteers include four signals measured using near-infrared spectroscopy along with middle cerebral artery blood flow measured using transcranial Doppler flowmetry. We show that optimising the model using partial data from an individual can increase its predictive power thus aiding the interpretation of NIRS signals in individuals. At the same time such optimisation can also help refine model parametrisation and provide confidence intervals on model parameters. Discrepancies between model and data which persist despite model optimisation are used to flag up important questions concerning the underlying physiology, and the reliability and physiological meaning of the signals.

Reinforcement learning signals in the human striatum distinguish learners from nonlearners during reward-based decision making.

Science.gov (United States)

Schönberg, Tom; Daw, Nathaniel D; Joel, Daphna; O'Doherty, John P

2007-11-21

The computational framework of reinforcement learning has been used to forward our understanding of the neural mechanisms underlying reward learning and decision-making behavior. It is known that humans vary widely in their performance in decision-making tasks. Here, we used a simple four-armed bandit task in which subjects are almost evenly split into two groups on the basis of their performance: those who do learn to favor choice of the optimal action and those who do not. Using models of reinforcement learning we sought to determine the neural basis of these intrinsic differences in performance by scanning both groups with functional magnetic resonance imaging. We scanned 29 subjects while they performed the reward-based decision-making task. Our results suggest that these two groups differ markedly in the degree to which reinforcement learning signals in the striatum are engaged during task performance. While the learners showed robust prediction error signals in both the ventral and dorsal striatum during learning, the nonlearner group showed a marked absence of such signals. Moreover, the magnitude of prediction error signals in a region of dorsal striatum correlated significantly with a measure of behavioral performance across all subjects. These findings support a crucial role of prediction error signals, likely originating from dopaminergic midbrain neurons, in enabling learning of action selection preferences on the basis of obtained rewards. Thus, spontaneously observed individual differences in decision making performance demonstrate the suggested dependence of this type of learning on the functional integrity of the dopaminergic striatal system in humans.

ALFY-Controlled DVL3 Autophagy Regulates Wnt Signaling, Determining Human Brain Size.

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Rotem Kadir

2016-03-01

Full Text Available Primary microcephaly is a congenital neurodevelopmental disorder of reduced head circumference and brain volume, with fewer neurons in the cortex of the developing brain due to premature transition between symmetrical and asymmetrical cellular division of the neuronal stem cell layer during neurogenesis. We now show through linkage analysis and whole exome sequencing, that a dominant mutation in ALFY, encoding an autophagy scaffold protein, causes human primary microcephaly. We demonstrate the dominant effect of the mutation in drosophila: transgenic flies harboring the human mutant allele display small brain volume, recapitulating the disease phenotype. Moreover, eye-specific expression of human mutant ALFY causes rough eye phenotype. In molecular terms, we demonstrate that normally ALFY attenuates the canonical Wnt signaling pathway via autophagy-dependent removal specifically of aggregates of DVL3 and not of Dvl1 or Dvl2. Thus, autophagic attenuation of Wnt signaling through removal of Dvl3 aggregates by ALFY acts in determining human brain size.

Human cytomegalovirus infection dysregulates the canonical Wnt/β-catenin signaling pathway.

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Magdalena Angelova

Full Text Available Human Cytomegalovirus (HCMV is a ubiquitous herpesvirus that currently infects a large percentage of the world population. Although usually asymptomatic in healthy individuals, HCMV infection during pregnancy may cause spontaneous abortions, premature delivery, or permanent neurological disabilities in infants infected in utero. During infection, the virus exerts control over a multitude of host signaling pathways. Wnt/β-catenin signaling, an essential pathway involved in cell cycle control, differentiation, embryonic development, placentation and metastasis, is frequently dysregulated by viruses. How HCMV infection affects this critical pathway is not currently known. In this study, we demonstrate that HCMV dysregulates Wnt/β-catenin signaling in dermal fibroblasts and human placental extravillous trophoblasts. Infection inhibits Wnt-induced transcriptional activity of β-catenin and expression of β-catenin target genes in these cells. HCMV infection leads to β-catenin protein accumulation in a discrete juxtanuclear region. Levels of β-catenin in membrane-associated and cytosolic pools, as well as nuclear β-catenin, are reduced after infection; while transcription of the β-catenin gene is unchanged, suggesting enhanced degradation. Given the critical role of Wnt/β-catenin signaling in cellular processes, these findings represent a novel and important mechanism whereby HCMV disrupts normal cellular function.

Nitric oxide signaling depends on biotin in Jurkat human lymphoma cells.

Science.gov (United States)

Rodriguez-Melendez, Rocio; Zempleni, Janos

2009-03-01

Biotin affects gene expression through a diverse array of cell signaling pathways. Previous studies provided evidence that cGMP-dependent signaling also depends on biotin, but the mechanistic sequence of cGMP regulation by biotin is unknown. Here we tested the hypothesis that the effects of biotin in cGMP-dependent cell signaling are mediated by nitric oxide (NO). Human lymphoid (Jurkat) cells were cultured in media containing deficient (0.025 nmol/L), physiological (0.25 nmol/L), and pharmacological (10 nmol/L) concentrations of biotin for 5 wk. Both levels of intracellular biotin and NO exhibited a dose-dependent relationship in regard to biotin concentrations in culture media. Effects of biotin on NO levels were disrupted by the NO synthase (NOS) inhibitor N-monomethyl-arginine. Biotin-dependent production of NO was linked with biotin-dependent expression of endothelial and neuronal NOS, but not inducible NOS. Previous studies revealed that NO is an activator of guanylate cyclase. Consistent with these previous observations, biotin-dependent generation of NO increased the abundance of cGMP in Jurkat cells. Finally, the biotin-dependent generation of cGMP increased protein kinase G activity. Collectively, the results of this study are consistent with the hypothesis that biotin-dependent cGMP signaling in human lymphoid cells is mediated by NO.

In Vitro Modeling of Blood-Brain Barrier with Human iPSC-Derived Endothelial Cells, Pericytes, Neurons, and Astrocytes via Notch Signaling

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Kohei Yamamizu

2017-03-01

Full Text Available The blood-brain barrier (BBB is composed of four cell populations, brain endothelial cells (BECs, pericytes, neurons, and astrocytes. Its role is to precisely regulate the microenvironment of the brain through selective substance crossing. Here we generated an in vitro model of the BBB by differentiating human induced pluripotent stem cells (hiPSCs into all four populations. When the four hiPSC-derived populations were co-cultured, endothelial cells (ECs were endowed with features consistent with BECs, including a high expression of nutrient transporters (CAT3, MFSD2A and efflux transporters (ABCA1, BCRP, PGP, MRP5, and strong barrier function based on tight junctions. Neuron-derived Dll1, which activates Notch signaling in ECs, was essential for the BEC specification. We performed in vitro BBB permeability tests and assessed ten clinical drugs by nanoLC-MS/MS, finding a good correlation with the BBB permeability reported in previous cases. This technology should be useful for research on human BBB physiology, pathology, and drug development.

CIRCADIAN REGULATION METABOLIC SIGNALING MECHANISMS OF HUMAN BREAST CANCER GROWTH BY THE NOCTURNAL MELATONIN SIGNAL AND THE CONSEQUENCES OF ITS DISRUPTION BY LIGHT AT NIGHT

Science.gov (United States)

Blask, David E.; Hill, Steven M.; Dauchy, Robert T.; Xiang, Shulin; Yuan, Lin; Duplessis, Tamika; Mao, Lulu; Dauchy, Erin; Sauer, Leonard A.

2011-01-01

This review article discusses recent work on the melatonin-mediated circadian regulation and integration of molecular, dietary and metabolic signaling mechanisms involved in human breast cancer growth and the consequences of circadian disruption by exposure to light-at-night (LAN). The antiproliferative effects of the circadian melatonin signal are mediated through a major mechanism involving the activation of MT1 melatonin receptors expressed in human breast cancer cell lines and xenografts. In estrogen receptor (ERα+) human breast cancer cells, melatonin suppresses both ERα mRNA expression and estrogen-induced transcriptional activity of the ERα via MT1-induced activation of Gαi2 signaling and reduction of cAMP levels. Melatonin also regulates the transactivation of additional members of the steroid hormone/nuclear receptor super-family, enzymes involved in estrogen metabolism, expression/activation of telomerase and the expression of core clock and clock-related genes. The anti-invasive/anti-metastatic actions of melatonin involve the blockade of p38 phosphorylation and the expression of matrix metalloproteinases. Melatonin also inhibits the growth of human breast cancer xenografts via another critical pathway involving MT1-mediated suppression of cAMP leading to blockade of linoleic acid (LA) uptake and its metabolism to the mitogenic signaling molecule 13-hydroxyoctadecadienoic acid (13-HODE). Down-regulation of 13-HODE reduces the activation of growth factor pathways supporting cell proliferation and survival. Experimental evidence in rats and humans indicating that LAN-induced circadian disruption of the nocturnal melatonin signal activates human breast cancer growth, metabolism and signaling provides the strongest mechanistic support, thus far, for population and ecological studies demonstrating elevated breast cancer risk in night shift workers and other individuals increasingly exposed to LAN. PMID:21605163

Notch signaling mediates granulocyte-macrophage colony-stimulating factor priming-induced transendothelial migration of human eosinophils.

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Liu, L Y; Wang, H; Xenakis, J J; Spencer, L A

2015-07-01

Priming with cytokines such as granulocyte-macrophage colony-stimulating factor (GM-CSF) enhances eosinophil migration and exacerbates the excessive accumulation of eosinophils within the bronchial mucosa of asthmatics. However, mechanisms that drive GM-CSF priming are incompletely understood. Notch signaling is an evolutionarily conserved pathway that regulates cellular processes, including migration, by integrating exogenous and cell-intrinsic cues. This study investigates the hypothesis that the priming-induced enhanced migration of human eosinophils requires the Notch signaling pathway. Using pan Notch inhibitors and newly developed human antibodies that specifically neutralize Notch receptor 1 activation, we investigated a role for Notch signaling in GM-CSF-primed transmigration of human blood eosinophils in vitro and in the airway accumulation of mouse eosinophils in vivo. Notch receptor 1 was constitutively active in freshly isolated human blood eosinophils, and inhibition of Notch signaling or specific blockade of Notch receptor 1 activation during GM-CSF priming impaired priming-enhanced eosinophil transendothelial migration in vitro. Inclusion of Notch signaling inhibitors during priming was associated with diminished ERK phosphorylation, and ERK-MAPK activation was required for GM-CSF priming-induced transmigration. In vivo in mice, eosinophil accumulation within allergic airways was impaired following systemic treatment with Notch inhibitor, or adoptive transfer of eosinophils treated ex vivo with Notch inhibitor. These data identify Notch signaling as an intrinsic pathway central to GM-CSF priming-induced eosinophil tissue migration. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Sphingosine-1-Phosphate (S1P) Signaling in Neural Progenitors.

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Callihan, Phillip; Alqinyah, Mohammed; Hooks, Shelley B

2018-01-01

Sphingosine-1-phosphate (S1P) and its receptors are important in nervous system development. Reliable in vitro human model systems are needed to further define specific roles for S1P signaling in neural development. We have described S1P-regulated signaling, survival, and differentiation in a human embryonic stem cell-derived neuroepithelial progenitor cell line (hNP1) that expresses functional S1P receptors. These cells can be further differentiated to a neuronal cell type and therefore represent a good model system to study the role of S1P signaling in human neural development. The following sections describe in detail the culture and differentiation of hNP1 cells and two assays to measure S1P signaling in these cells.

Leukotriene signaling in the extinct human subspecies Homo denisovan and Homo neanderthalensis. Structural and functional comparison with Homo sapiens.

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Adel, Susan; Kakularam, Kumar Reddy; Horn, Thomas; Reddanna, Pallu; Kuhn, Hartmut; Heydeck, Dagmar

2015-01-01

Mammalian lipoxygenases (LOXs) have been implicated in cell differentiation and in the biosynthesis of pro- and anti-inflammatory lipid mediators. The initial draft sequence of the Homo neanderthalensis genome (coverage of 1.3-fold) suggested defective leukotriene signaling in this archaic human subspecies since expression of essential proteins appeared to be corrupted. Meanwhile high quality genomic sequence data became available for two extinct human subspecies (H. neanderthalensis, Homo denisovan) and completion of the human 1000 genome project provided a comprehensive database characterizing the genetic variability of the human genome. For this study we extracted the nucleotide sequences of selected eicosanoid relevant genes (ALOX5, ALOX15, ALOX12, ALOX15B, ALOX12B, ALOXE3, COX1, COX2, LTA4H, LTC4S, ALOX5AP, CYSLTR1, CYSLTR2, BLTR1, BLTR2) from the corresponding databases. Comparison of the deduced amino acid sequences in connection with site-directed mutagenesis studies and structural modeling suggested that the major enzymes and receptors of leukotriene signaling as well as the two cyclooxygenase isoforms were fully functional in these two extinct human subspecies. Copyright © 2014 Elsevier Inc. All rights reserved.

Impaired IGF1R signaling in cells expressing longevity-associated human IGF1R alleles

OpenAIRE

Tazearslan, Cagdas; Huang, Jing; Barzilai, Nir; Suh, Yousin

2011-01-01

Dampening of insulin/insulin like growth factor-1 (IGF1) signaling results in extension of lifespan in invertebrate as well as murine models. The impact of this evolutionarily conserved pathway on modulation of human lifespan remains unclear. We previously identified two IGF1R mutations (Ala-37-Thr and Arg-407-His) that are enriched in Ashkenazi Jewish centenarians as compared to younger controls and are associated with reduced activity of the IGF1 receptor as measured in immortalized lymphoc...

On the role of exchange of power and information signals in control and stability of the human-robot interaction

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Kazerooni, H.

1991-01-01

A human's ability to perform physical tasks is limited, not only by his intelligence, but by his physical strength. If, in an appropriate environment, a machine's mechanical power is closely integrated with a human arm's mechanical power under the control of the human intellect, the resulting system will be superior to a loosely integrated combination of a human and a fully automated robot. Therefore, we must develop a fundamental solution to the problem of 'extending' human mechanical power. The work presented here defines 'extenders' as a class of robot manipulators worn by humans to increase human mechanical strength, while the wearer's intellect remains the central control system for manipulating the extender. The human, in physical contact with the extender, exchanges power and information signals with the extender. The aim is to determine the fundamental building blocks of an intelligent controller, a controller which allows interaction between humans and a broad class of computer-controlled machines via simultaneous exchange of both power and information signals. The prevalent trend in automation has been to physically separate the human from the machine so the human must always send information signals via an intermediary device (e.g., joystick, pushbutton, light switch). Extenders, however are perfect examples of self-powered machines that are built and controlled for the optimal exchange of power and information signals with humans. The human wearing the extender is in physical contact with the machine, so power transfer is unavoidable and information signals from the human help to control the machine. Commands are transferred to the extender via the contact forces and the EMG signals between the wearer and the extender. The extender augments human motor ability without accepting any explicit commands: it accepts the EMG signals and the contact force between the person's arm and the extender, and the extender 'translates' them into a desired position. In

Mapping glucose-mediated gut-to-brain signalling pathways in humans.

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Little, Tanya J; McKie, Shane; Jones, Richard B; D'Amato, Massimo; Smith, Craig; Kiss, Orsolya; Thompson, David G; McLaughlin, John T

2014-08-01

Previous fMRI studies have demonstrated that glucose decreases the hypothalamic BOLD response in humans. However, the mechanisms underlying the CNS response to glucose have not been defined. We recently demonstrated that the slowing of gastric emptying by glucose is dependent on activation of the gut peptide cholecystokinin (CCK1) receptor. Using physiological functional magnetic resonance imaging this study aimed to determine the whole brain response to glucose, and whether CCK plays a central role. Changes in blood oxygenation level-dependent (BOLD) signal were monitored using fMRI in 12 healthy subjects following intragastric infusion (250ml) of: 1M glucose+predosing with dexloxiglumide (CCK1 receptor antagonist), 1M glucose+placebo, or 0.9% saline (control)+placebo, in a single-blind, randomised fashion. Gallbladder volume, blood glucose, insulin, and GLP-1 and CCK concentrations were determined. Hunger, fullness and nausea scores were also recorded. Intragastric glucose elevated plasma glucose, insulin, and GLP-1, and reduced gall bladder volume (an in vivo assay for CCK secretion). Glucose decreased BOLD signal, relative to saline, in the brainstem and hypothalamus as well as the cerebellum, right occipital cortex, putamen and thalamus. The timing of the BOLD signal decrease was negatively correlated with the rise in blood glucose and insulin levels. The glucose+dex arm highlighted a CCK1-receptor dependent increase in BOLD signal only in the motor cortex. Glucose induces site-specific differences in BOLD response in the human brain; the brainstem and hypothalamus show a CCK1 receptor-independent reduction which is likely to be mediated by a circulatory effect of glucose and insulin, whereas the motor cortex shows an early dexloxiglumide-reversible increase in signal, suggesting a CCK1 receptor-dependent neural pathway. Copyright © 2014. Published by Elsevier Inc.

Smart driver monitoring : when signal processing meets human factors : in the driver's seat

NARCIS (Netherlands)

Aghaei, A.S.; Donmez, B.; Liu, C.C.; He, D.; Liu, G.; Plataniotis, K.N.; Chen, H.Y.W.; Sojoudi, Z.

2016-01-01

This article provides an interdisciplinary perspective on driver monitoring systems by discussing state-of-the-art signal processing solutions in the context of road safety issues identified in human factors research. Recently, the human factors community has made significant progress in

Human reliability data collection and modelling

International Nuclear Information System (INIS)

1991-09-01

The main purpose of this document is to review and outline the current state-of-the-art of the Human Reliability Assessment (HRA) used for quantitative assessment of nuclear power plants safe and economical operation. Another objective is to consider Human Performance Indicators (HPI) which can alert plant manager and regulator to departures from states of normal and acceptable operation. These two objectives are met in the three sections of this report. The first objective has been divided into two areas, based on the location of the human actions being considered. That is, the modelling and data collection associated with control room actions are addressed first in chapter 1 while actions outside the control room (including maintenance) are addressed in chapter 2. Both chapters 1 and 2 present a brief outline of the current status of HRA for these areas, and major outstanding issues. Chapter 3 discusses HPI. Such performance indicators can signal, at various levels, changes in factors which influence human performance. The final section of this report consists of papers presented by the participants of the Technical Committee Meeting. A separate abstract was prepared for each of these papers. Refs, figs and tabs

Phosphoinositide-3-Kinase Signaling in Human Natural Killer Cells: New Insights from Primary Immunodeficiency

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Emily M. Mace

2018-03-01

Full Text Available Human natural killer (NK cells play a critical role in the control of viral infections and malignancy. Their importance in human health and disease is illustrated by severe viral infections in patients with primary immunodeficiencies that affect NK cell function and/or development. The recent identification of patients with phosphoinositide-3-kinase (PI3K-signaling pathway mutations that can cause primary immunodeficiency provides valuable insight into the role that PI3K signaling plays in human NK cell maturation and lytic function. There is a rich literature that demonstrates a requirement for PI3K in multiple key aspects of NK cell biology, including development/maturation, homing, priming, and function. Here, I briefly review these previous studies and place them in context with recent findings from the study of primary immunodeficiency patients, particularly those with hyperactivating mutations in PI3Kδ signaling.

Mixed-signal instrumentation for large-signal device characterization and modelling

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Marchetti, M.

2013-01-01

This thesis concentrates on the development of advanced large-signal measurement and characterization tools to support technology development, model extraction and validation, and power amplifier (PA) designs that address the newly introduced third and fourth generation (3G and 4G) wideband

NOTCH2 signaling confers immature morphology and aggressiveness in human hepatocellular carcinoma cells.

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Hayashi, Yoshihiro; Osanai, Makoto; Lee, Gang-Hong

2015-10-01

The NOTCH family of membranous receptors plays key roles during development and carcinogenesis. Since NOTCH2, yet not NOTCH1 has been shown essential for murine hepatogenesis, NOTCH2 rather than NOTCH1 may be more relevant to human hepatocarcinogenesis; however, no previous studies have supported this hypothesis. We therefore assessed the role of NOTCH2 in human hepatocellular carcinoma (HCC) by immunohistochemistry and cell culture. Immunohistochemically, 19% of primary HCCs showed nuclear staining for NOTCH2, indicating activated NOTCH2 signaling. NOTCH2-positive HCCs were on average in more advanced clinical stages, and exhibited more immature cellular morphology, i.e. higher nuclear-cytoplasmic ratios and nuclear densities. Such features were not evident in NOTCH1‑positive HCCs. In human HCC cell lines, abundant NOTCH2 expression was associated with anaplasia, represented by loss of E-cadherin. When NOTCH2 signaling was stably downregulated in HLF cells, an anaplastic HCC cell line, the cells were attenuated in potential for in vitro invasiveness and migration, as well as in vivo tumorigenicity accompanied by histological maturation. Generally, inverse results were obtained for a differentiated HCC cell line, Huh7, manipulated to overexpress activated NOTCH2. These findings suggested that the NOTCH2 signaling may confer aggressive behavior and immature morphology in human HCC cells.

Effects of human fatigue on speech signals

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Stamoulis, Catherine

2004-05-01

Cognitive performance may be significantly affected by fatigue. In the case of critical personnel, such as pilots, monitoring human fatigue is essential to ensure safety and success of a given operation. One of the modalities that may be used for this purpose is speech, which is sensitive to respiratory changes and increased muscle tension of vocal cords, induced by fatigue. Age, gender, vocal tract length, physical and emotional state may significantly alter speech intensity, duration, rhythm, and spectral characteristics. In addition to changes in speech rhythm, fatigue may also affect the quality of speech, such as articulation. In a noisy environment, detecting fatigue-related changes in speech signals, particularly subtle changes at the onset of fatigue, may be difficult. Therefore, in a performance-monitoring system, speech parameters which are significantly affected by fatigue need to be identified and extracted from input signals. For this purpose, a series of experiments was performed under slowly varying cognitive load conditions and at different times of the day. The results of the data analysis are presented here.

Vorinostat, an HDAC inhibitor attenuates epidermoid squamous cell carcinoma growth by dampening mTOR signaling pathway in a human xenograft murine model.

Science.gov (United States)

Kurundkar, Deepali; Srivastava, Ritesh K; Chaudhary, Sandeep C; Ballestas, Mary E; Kopelovich, Levy; Elmets, Craig A; Athar, Mohammad

2013-01-15

Histone deacetylase (HDAC) inhibitors are potent anticancer agents and show efficacy against various human neoplasms. Vorinostat is a potent HDAC inhibitor and has shown potential to inhibit growth of human xenograft tumors. However, its effect on the growth of skin neoplasm remains undefined. In this study, we show that vorinostat (2 μM) reduced expression of HDAC1, 2, 3, and 7 in epidermoid carcinoma A431 cells. Consistently, it increased acetylation of histone H3 and p53. Vorinostat (100mg/kg body weight, IP) treatment reduced human xenograft tumor growth in highly immunosuppressed nu/nu mice. Histologically, the vorinostat-treated tumor showed features of well-differentiation with large necrotic areas. Based on proliferating cell nuclear antigen (PCNA) staining and expression of cyclins D1, D2, E, and A, vorinostat seems to impair proliferation by down-regulating the expression of these proteins. However, it also induced apoptosis. The mechanism by which vorinostat blocks proliferation and makes tumor cells prone to apoptosis, involved inhibition of mTOR signaling which was accompanied by reduction in cell survival AKT and extracellular-signal regulated kinase (ERK) signaling pathways. Our data provide a novel mechanism-based therapeutic intervention for cutaneous squamous cell carcinoma (SCC). Vorinostat may be utilized to cure skin neoplasms in organ transplant recipient (OTR). These patients have high morbidity and surgical removal of these lesions which frequently develop in these patients, is difficult. Copyright © 2012 Elsevier Inc. All rights reserved.

Novel calibration model maintenance strategy for solving the signal instability in quantitative liquid chromatography-mass spectrometry.

Science.gov (United States)

Du, Hai-Li; Chen, Zeng-Ping; Song, Mi; Chen, Yao; Yu, Ru-Qin

2014-04-18

In this contribution, a multiplicative effects model with a parameter accounting for the variations in overall sensitivity over time was proposed to reduce the effects of signal instability on quantitative results of LC-MS/MS. This method allows the use of calibration models constructed from large standard sets without having to repeat their measurement even though variations occur in sensitivity and baseline signal intensity. The performance of the proposed method was tested on two proof-of-concept model systems: the determination of the target peptide in two sets of peptide digests mixtures and the quantification of melamine and metronidazole in two sets of milk powder samples. Experimental results confirmed that multiplicative effects model could provide quite satisfactory concentration predictions for both systems with average relative predictive error values far lower than the corresponding values of various models investigated in this paper. Considering its capability in solving the problem of signal instability across samples and over time in LC-MS/MS assays and its implementation simplicity, it is expected that the multiplicative effects model can be developed and extended in many application areas such as the quantification of specific protein in cells and human plasma and other complex systems. Copyright © 2014 Elsevier B.V. All rights reserved.

Cryptosporidium parvum-induced ileo-caecal adenocarcinoma and Wnt signaling in a mouse model

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Sadia Benamrouz

2014-06-01

Full Text Available Cryptosporidium species are apicomplexan protozoans that are found worldwide. These parasites constitute a large risk to human and animal health. They cause self-limited diarrhea in immunocompetent hosts and a life-threatening disease in immunocompromised hosts. Interestingly, Cryptosporidium parvum has been related to digestive carcinogenesis in humans. Consistent with a potential tumorigenic role of this parasite, in an original reproducible animal model of chronic cryptosporidiosis based on dexamethasone-treated or untreated adult SCID mice, we formerly reported that C. parvum (strains of animal and human origin is able to induce digestive adenocarcinoma even in infections induced with very low inoculum. The aim of this study was to further characterize this animal model and to explore metabolic pathways potentially involved in the development of C. parvum-induced ileo-caecal oncogenesis. We searched for alterations in genes or proteins commonly involved in cell cycle, differentiation or cell migration, such as β-catenin, Apc, E-cadherin, Kras and p53. After infection of animals with C. parvum we demonstrated immunohistochemical abnormal localization of Wnt signaling pathway components and p53. Mutations in the selected loci of studied genes were not found after high-throughput sequencing. Furthermore, alterations in the ultrastructure of adherens junctions of the ileo-caecal neoplastic epithelia of C. parvum-infected mice were recorded using transmission electron microscopy. In conclusion, we found for the first time that the Wnt signaling pathway, and particularly the cytoskeleton network, seems to be pivotal for the development of the C. parvum-induced neoplastic process and cell migration of transformed cells. Furthermore, this model is a valuable tool in understanding the host-pathogen interactions associated with the intricate infection process of this parasite, which is able to modulate host cytoskeleton activities and several host

A pedagogical walkthrough of computational modeling and simulation of Wnt signaling pathway using static causal models in MATLAB.

Science.gov (United States)

Sinha, Shriprakash

2016-12-01

Simulation study in systems biology involving computational experiments dealing with Wnt signaling pathways abound in literature but often lack a pedagogical perspective that might ease the understanding of beginner students and researchers in transition, who intend to work on the modeling of the pathway. This paucity might happen due to restrictive business policies which enforce an unwanted embargo on the sharing of important scientific knowledge. A tutorial introduction to computational modeling of Wnt signaling pathway in a human colorectal cancer dataset using static Bayesian network models is provided. The walkthrough might aid biologists/informaticians in understanding the design of computational experiments that is interleaved with exposition of the Matlab code and causal models from Bayesian network toolbox. The manuscript elucidates the coding contents of the advance article by Sinha (Integr. Biol. 6:1034-1048, 2014) and takes the reader in a step-by-step process of how (a) the collection and the transformation of the available biological information from literature is done, (b) the integration of the heterogeneous data and prior biological knowledge in the network is achieved, (c) the simulation study is designed, (d) the hypothesis regarding a biological phenomena is transformed into computational framework, and (e) results and inferences drawn using d -connectivity/separability are reported. The manuscript finally ends with a programming assignment to help the readers get hands-on experience of a perturbation project. Description of Matlab files is made available under GNU GPL v3 license at the Google code project on https://code.google.com/p/static-bn-for-wnt-signaling-pathway and https: //sites.google.com/site/shriprakashsinha/shriprakashsinha/projects/static-bn-for-wnt-signaling-pathway. Latest updates can be found in the latter website.

Modeling Human Leukemia Immunotherapy in Humanized Mice

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Jinxing Xia

2016-08-01

Full Text Available The currently available human tumor xenograft models permit modeling of human cancers in vivo, but in immunocompromised hosts. Here we report a humanized mouse (hu-mouse model made by transplantation of human fetal thymic tissue plus hematopoietic stem cells transduced with a leukemia-associated fusion gene MLL-AF9. In addition to normal human lymphohematopoietic reconstitution as seen in non-leukemic hu-mice, these hu-mice showed spontaneous development of B-cell acute lymphoblastic leukemia (B-ALL, which was transplantable to secondary recipients with an autologous human immune system. Using this model, we show that lymphopenia markedly improves the antitumor efficacy of recipient leukocyte infusion (RLI, a GVHD-free immunotherapy that induces antitumor responses in association with rejection of donor chimerism in mixed allogeneic chimeras. Our data demonstrate the potential of this leukemic hu-mouse model in modeling leukemia immunotherapy, and suggest that RLI may offer a safe treatment option for leukemia patients with severe lymphopenia.

Inhibition of signaling between human CXCR4 and zebrafish ligands by the small molecule IT1t impairs the formation of triple-negative breast cancer early metastases in a zebrafish xenograft model

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Claudia Tulotta

2016-02-01

Full Text Available Triple-negative breast cancer (TNBC is a highly aggressive and recurrent type of breast carcinoma that is associated with poor patient prognosis. Because of the limited efficacy of current treatments, new therapeutic strategies need to be developed. The CXCR4-CXCL12 chemokine signaling axis guides cell migration in physiological and pathological processes, including breast cancer metastasis. Although targeted therapies to inhibit the CXCR4-CXCL12 axis are under clinical experimentation, still no effective therapeutic approaches have been established to block CXCR4 in TNBC. To unravel the role of the CXCR4-CXCL12 axis in the formation of TNBC early metastases, we used the zebrafish xenograft model. Importantly, we demonstrate that cross-communication between the zebrafish and human ligands and receptors takes place and human tumor cells expressing CXCR4 initiate early metastatic events by sensing zebrafish cognate ligands at the metastatic site. Taking advantage of the conserved intercommunication between human tumor cells and the zebrafish host, we blocked TNBC early metastatic events by chemical and genetic inhibition of CXCR4 signaling. We used IT1t, a potent CXCR4 antagonist, and show for the first time its promising anti-tumor effects. In conclusion, we confirm the validity of the zebrafish as a xenotransplantation model and propose a pharmacological approach to target CXCR4 in TNBC.

The Evolution of Covert Signaling.

Science.gov (United States)

Smaldino, Paul E; Flamson, Thomas J; McElreath, Richard

2018-03-20

Human sociality depends upon the benefits of mutual aid and extensive communication. However, diverse norms and preferences complicate mutual aid, and ambiguity in meaning hinders communication. Here we demonstrate that these two problems can work together to enhance cooperation through the strategic use of deliberately ambiguous signals: covert signaling. Covert signaling is the transmission of information that is accurately received by its intended audience but obscured when perceived by others. Such signals may allow coordination and enhanced cooperation while also avoiding the alienation or hostile reactions of individuals with different preferences. Although the empirical literature has identified potential mechanisms of covert signaling, such as encryption in humor, there is to date no formal theory of its dynamics. We introduce a novel mathematical model to assess when a covert signaling strategy will evolve, as well as how receiver attitudes coevolve with covert signals. Covert signaling plausibly serves an important function in facilitating within-group cooperative assortment by allowing individuals to pair up with similar group members when possible and to get along with dissimilar ones when necessary. This mechanism has broad implications for theories of signaling and cooperation, humor, social identity, political psychology, and the evolution of human cultural complexity.

Inhibition of Hedgehog signaling antagonizes serous ovarian cancer growth in a primary xenograft model.

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Christopher K McCann

Full Text Available Recent evidence links aberrant activation of Hedgehog (Hh signaling with the pathogenesis of several cancers including medulloblastoma, basal cell, small cell lung, pancreatic, prostate and ovarian. This investigation was designed to determine if inhibition of this pathway could inhibit serous ovarian cancer growth.We utilized an in vivo pre-clinical model of serous ovarian cancer to characterize the anti-tumor activity of Hh pathway inhibitors cyclopamine and a clinically applicable derivative, IPI-926. Primary human serous ovarian tumor tissue was used to generate tumor xenografts in mice that were subsequently treated with cyclopamine or IPI-926.Both compounds demonstrated significant anti-tumor activity as single agents. When IPI-926 was used in combination with paclitaxel and carboplatinum (T/C, no synergistic effect was observed, though sustained treatment with IPI-926 after cessation of T/C continued to suppress tumor growth. Hh pathway activity was analyzed by RT-PCR to assess changes in Gli1 transcript levels. A single dose of IPI-926 inhibited mouse stromal Gli1 transcript levels at 24 hours with unchanged human intra-tumor Gli1 levels. Chronic IPI-926 therapy for 21 days, however, inhibited Hh signaling in both mouse stromal and human tumor cells. Expression data from the micro-dissected stroma in human serous ovarian tumors confirmed the presence of Gli1 transcript and a significant association between elevated Gli1 transcript levels and worsened survival.IPI-926 treatment inhibits serous tumor growth suggesting the Hh signaling pathway contributes to the pathogenesis of ovarian cancer and may hold promise as a novel therapeutic target, especially in the maintenance setting.

The role of NF-κB signaling in the maintenance of pluripotency of human induced pluripotent stem cells.

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Osamu Takase

Full Text Available NF-κB signaling plays an essential role in maintaining the undifferentiated state of embryonic stem (ES cells. However, opposing roles of NF-κB have been reported in mouse and human ES cells, and the role of NF-κB in human induced pluripotent stem (iPS cells has not yet been clarified. Here, we report the role of NF-κB signaling in maintaining the undifferentiated state of human iPS cells. Compared with differentiated cells, undifferentiated human iPS cells showed an augmentation of NF-κB activity. During differentiation induced by the removal of feeder cells and FGF2, we observed a reduction in NF-κB activity, the expression of the undifferentiation markers Oct3/4 and Nanog, and the up-regulation of the differentiated markers WT-1 and Pax-2. The specific knockdown of NF-κB signaling using p65 siRNA also reduced the expression of Oct3/4 and Nanog and up-regulated WT-1 and Pax-2 but did not change the ES-like colony formation. Our results show that the augmentation of NF-κB signaling maintains the undifferentiated state of human iPS and suggest the importance of this signaling pathway in maintenance of human iPS cells.

Patterns of flavor signals in supersymmetric models

Energy Technology Data Exchange (ETDEWEB)

Goto, T. [KEK National High Energy Physics, Tsukuba (Japan)]|[Kyoto Univ. (Japan). YITP; Okada, Y. [KEK National High Energy Physics, Tsukuba (Japan)]|[Graduate Univ. for Advanced Studies, Tsukuba (Japan). Dept. of Particle and Nucelar Physics; Shindou, T. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)]|[International School for Advanced Studies, Trieste (Italy); Tanaka, M. [Osaka Univ., Toyonaka (Japan). Dept. of Physics

2007-11-15

Quark and lepton flavor signals are studied in four supersymmetric models, namely the minimal supergravity model, the minimal supersymmetric standard model with right-handed neutrinos, SU(5) supersymmetric grand unified theory with right-handed neutrinos and the minimal supersymmetric standard model with U(2) flavor symmetry. We calculate b{yields}s(d) transition observables in B{sub d} and B{sub s} decays, taking the constraint from the B{sub s}- anti B{sub s} mixing recently observed at Tevatron into account. We also calculate lepton flavor violating processes {mu} {yields} e{gamma}, {tau} {yields} {mu}{gamma} and {tau} {yields} e{gamma} for the models with right-handed neutrinos. We investigate possibilities to distinguish the flavor structure of the supersymmetry breaking sector with use of patterns of various flavor signals which are expected to be measured in experiments such as MEG, LHCb and a future Super B Factory. (orig.)

Patterns of flavor signals in supersymmetric models

International Nuclear Information System (INIS)

Goto, T.; Tanaka, M.

2007-11-01

Quark and lepton flavor signals are studied in four supersymmetric models, namely the minimal supergravity model, the minimal supersymmetric standard model with right-handed neutrinos, SU(5) supersymmetric grand unified theory with right-handed neutrinos and the minimal supersymmetric standard model with U(2) flavor symmetry. We calculate b→s(d) transition observables in B d and B s decays, taking the constraint from the B s - anti B s mixing recently observed at Tevatron into account. We also calculate lepton flavor violating processes μ → eγ, τ → μγ and τ → eγ for the models with right-handed neutrinos. We investigate possibilities to distinguish the flavor structure of the supersymmetry breaking sector with use of patterns of various flavor signals which are expected to be measured in experiments such as MEG, LHCb and a future Super B Factory. (orig.)

Detection of Signal Regulatory Protein α in Saimiri sciureus (Squirrel Monkey) by Anti-Human Monoclonal Antibody

Science.gov (United States)

de Souza, Hugo Amorim dos Santos; Costa-Correa, Edmar Henrique; Bianco-Junior, Cesare; Andrade, Márcia Cristina Ribeiro; Lima-Junior, Josué da Costa; Pratt-Riccio, Lilian Rose; Daniel-Ribeiro, Cláudio Tadeu; Totino, Paulo Renato Rivas

2017-01-01

Non-human primates (NHP) are suitable models for studying different aspects of the human system, including pathogenesis and protective immunity to many diseases. However, the lack of specific immunological reagents for neo-tropical monkeys, such as Saimiri sciureus, is still a major factor limiting studies in these models. An alternative strategy to circumvent this obstacle has been the selection of immunological reagents directed to humans, which present cross-reactivity with NHP molecules. In this context and considering the key role of inhibitory immunoreceptors—such as the signal regulatory protein α (SIRPα)—in the regulation of immune responses, in the present study, we attempted to evaluate the ability of anti-human SIRPα monoclonal antibodies to recognize SIRPα in antigen-presenting S. sciureus peripheral blood mononuclear cells (PBMC). As shown by flow cytometry analysis, the profile of anti-SIRPα staining as well as the levels of SIRPα-positive cells in PBMC from S. sciureus were similar to those observed in human PBMC. Furthermore, using anti-SIRPα monoclonal antibody, it was possible to detect a decrease of the SIRPα levels on surface of S. sciureus cells after in vitro stimulation with lipopolysaccharides. Finally, using computed-based analysis, we observed a high degree of conservation of SIRPα across six species of primates and the presence of shared epitopes in the extracellular domain between humans and Saimiri genus that could be targeted by antibodies. In conclusion, we have identified a commercially available anti-human monoclonal antibody that is able to detect SIRPα of S. sciureus monkeys and that, therefore, can facilitate the study of the immunomodulatory role of SIRPα when S. sciureus is used as a model. PMID:29312325

Detection of Signal Regulatory Protein α in Saimiri sciureus (Squirrel Monkey by Anti-Human Monoclonal Antibody

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Hugo Amorim dos Santos de Souza

2017-12-01

Full Text Available Non-human primates (NHP are suitable models for studying different aspects of the human system, including pathogenesis and protective immunity to many diseases. However, the lack of specific immunological reagents for neo-tropical monkeys, such as Saimiri sciureus, is still a major factor limiting studies in these models. An alternative strategy to circumvent this obstacle has been the selection of immunological reagents directed to humans, which present cross-reactivity with NHP molecules. In this context and considering the key role of inhibitory immunoreceptors—such as the signal regulatory protein α (SIRPα—in the regulation of immune responses, in the present study, we attempted to evaluate the ability of anti-human SIRPα monoclonal antibodies to recognize SIRPα in antigen-presenting S. sciureus peripheral blood mononuclear cells (PBMC. As shown by flow cytometry analysis, the profile of anti-SIRPα staining as well as the levels of SIRPα-positive cells in PBMC from S. sciureus were similar to those observed in human PBMC. Furthermore, using anti-SIRPα monoclonal antibody, it was possible to detect a decrease of the SIRPα levels on surface of S. sciureus cells after in vitro stimulation with lipopolysaccharides. Finally, using computed-based analysis, we observed a high degree of conservation of SIRPα across six species of primates and the presence of shared epitopes in the extracellular domain between humans and Saimiri genus that could be targeted by antibodies. In conclusion, we have identified a commercially available anti-human monoclonal antibody that is able to detect SIRPα of S. sciureus monkeys and that, therefore, can facilitate the study of the immunomodulatory role of SIRPα when S. sciureus is used as a model.

A Novel Parametric Model For The Human Respiratory System

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Clara Mihaela IONESCU

2003-12-01

Full Text Available The purpose of this work is to present some recent results in an ongoing research project between Ghent University and Chess Medical Technology Company Belgium. The overall aim of the project is to provide a fast method for identification of the human respiratory system in order to allow for an instantaneously diagnosis of the patient by the medical staff. A novel parametric model of the human respiratory system as well as the obtained experimental results is presented in this paper. A prototype apparatus developed by the company, based on the forced oscillation technique is used to record experimental data from 4 patients in this paper. Signal processing is based on spectral analysis and is followed by the parametric identification of a non-linear mechanistic model. The parametric model is equivalent to the structure of a simple electrical RLC-circuit, containing a non-linear capacitor. These parameters have a useful and easy-to-interpret physical meaning for the medical staff members.

Vibration Signal Forecasting on Rotating Machinery by means of Signal Decomposition and Neurofuzzy Modeling

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Daniel Zurita-Millán

2016-01-01

Full Text Available Vibration monitoring plays a key role in the industrial machinery reliability since it allows enhancing the performance of the machinery under supervision through the detection of failure modes. Thus, vibration monitoring schemes that give information regarding future condition, that is, prognosis approaches, are of growing interest for the scientific and industrial communities. This work proposes a vibration signal prognosis methodology, applied to a rotating electromechanical system and its associated kinematic chain. The method combines the adaptability of neurofuzzy modeling with a signal decomposition strategy to model the patterns of the vibrations signal under different fault scenarios. The model tuning is performed by means of Genetic Algorithms along with a correlation based interval selection procedure. The performance and effectiveness of the proposed method are validated experimentally with an electromechanical test bench containing a kinematic chain. The results of the study indicate the suitability of the method for vibration forecasting in complex electromechanical systems and their associated kinematic chains.

Signaling pathway networks mined from human pituitary adenoma proteomics data

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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

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

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Kirouac Daniel C

2012-05-01

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

State–time spectrum of signal transduction logic models

International Nuclear Information System (INIS)

MacNamara, Aidan; Terfve, Camille; Henriques, David; Bernabé, Beatriz Peñalver; Saez-Rodriguez, Julio

2012-01-01

Despite the current wealth of high-throughput data, our understanding of signal transduction is still incomplete. Mathematical modeling can be a tool to gain an insight into such processes. Detailed biochemical modeling provides deep understanding, but does not scale well above relatively a few proteins. In contrast, logic modeling can be used where the biochemical knowledge of the system is sparse and, because it is parameter free (or, at most, uses relatively a few parameters), it scales well to large networks that can be derived by manual curation or retrieved from public databases. Here, we present an overview of logic modeling formalisms in the context of training logic models to data, and specifically the different approaches to modeling qualitative to quantitative data (state) and dynamics (time) of signal transduction. We use a toy model of signal transduction to illustrate how different logic formalisms (Boolean, fuzzy logic and differential equations) treat state and time. Different formalisms allow for different features of the data to be captured, at the cost of extra requirements in terms of computational power and data quality and quantity. Through this demonstration, the assumptions behind each formalism are discussed, as well as their advantages and disadvantages and possible future developments. (paper)

Induction of farnesoid X receptor signaling in germ-free mice colonized with a human microbiota

DEFF Research Database (Denmark)

Wahlström, Annika; Kovatcheva-Datchary, Petia; Ståhlman, Marcus

2017-01-01

The gut microbiota influences the development and progression of metabolic diseases partly by metabolism of bile acids (BAs) and modified signaling through the farnesoid X receptor (FXR). In this study, we aimed to determine how the human gut microbiota metabolizes murine BAs and affects FXR...... signaling in colonized mice. We colonized germ-free mice with cecal content from a mouse donor or feces from a human donor and euthanized the mice after short-term (2 weeks) or long-term (15 weeks) colonization. We analyzed the gut microbiota and BA composition and expression of FXR target genes in ileum...... and liver. We found that cecal microbiota composition differed between mice colonized with mouse and human microbiota and was stable over time. Human and mouse microbiota reduced total BA levels similarly, but the humanized mice produced less secondary BAs. The human microbiota was able to reduce the levels...

Signal transmission in a human body medium-based body sensor network using a Mach-Zehnder electro-optical sensor.

Science.gov (United States)

Song, Yong; Hao, Qun; Zhang, Kai; Wang, Jingwen; Jin, Xuefeng; Sun, He

2012-11-30

The signal transmission technology based on the human body medium offers significant advantages in Body Sensor Networks (BSNs) used for healthcare and the other related fields. In previous works we have proposed a novel signal transmission method based on the human body medium using a Mach-Zehnder electro-optical (EO) sensor. In this paper, we present a signal transmission system based on the proposed method, which consists of a transmitter, a Mach-Zehnder EO sensor and a corresponding receiving circuit. Meanwhile, in order to verify the frequency response properties and determine the suitable parameters of the developed system, in-vivo measurements have been implemented under conditions of different carrier frequencies, baseband frequencies and signal transmission paths. Results indicate that the proposed system will help to achieve reliable and high speed signal transmission of BSN based on the human body medium.

Time Series Modeling of Human Operator Dynamics in Manual Control Tasks

Science.gov (United States)

Biezad, D. J.; Schmidt, D. K.

1984-01-01

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency response of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that was previously modeled to demonstrate the strengths of the method.

HP Memristor mathematical model for periodic signals and DC

KAUST Repository

Radwan, Ahmed G.

2012-07-28

In this paper mathematical models of the HP Memristor for DC and periodic signal inputs are provided. The need for a rigid model for the Memristor using conventional current and voltage quantities is essential for the development of many promising Memristors\\' applications. Unlike the previous works, which focuses on the sinusoidal input waveform, we derived rules for any periodic signals in general in terms of voltage and current. Square and triangle waveforms are studied explicitly, extending the formulas for any general square wave. The limiting conditions for saturation are also provided in case of either DC or periodic signals. The derived equations are compared to the SPICE model of the Memristor showing a perfect match.

Different Signal Enhancement Pathways of Attention and Consciousness Underlie Perception in Humans.

Science.gov (United States)

van Boxtel, Jeroen J A

2017-06-14

It is not yet known whether attention and consciousness operate through similar or largely different mechanisms. Visual processing mechanisms are routinely characterized by measuring contrast response functions (CRFs). In this report, behavioral CRFs were obtained in humans (both males and females) by measuring afterimage durations over the entire range of inducer stimulus contrasts to reveal visual mechanisms behind attention and consciousness. Deviations relative to the standard CRF, i.e., gain functions, describe the strength of signal enhancement, which were assessed for both changes due to attentional task and conscious perception. It was found that attention displayed a response-gain function, whereas consciousness displayed a contrast-gain function. Through model comparisons, which only included contrast-gain modulations, both contrast-gain and response-gain effects can be explained with a two-level normalization model, in which consciousness affects only the first level and attention affects only the second level. These results demonstrate that attention and consciousness can effectively show different gain functions because they operate through different signal enhancement mechanisms. SIGNIFICANCE STATEMENT The relationship between attention and consciousness is still debated. Mapping contrast response functions (CRFs) has allowed (neuro)scientists to gain important insights into the mechanistic underpinnings of visual processing. Here, the influence of both attention and consciousness on these functions were measured and they displayed a strong dissociation. First, attention lowered CRFs, whereas consciousness raised them. Second, attention manifests itself as a response-gain function, whereas consciousness manifests itself as a contrast-gain function. Extensive model comparisons show that these results are best explained in a two-level normalization model in which consciousness affects only the first level, whereas attention affects only the second level

Large-signal modeling method for power FETs and diodes

Energy Technology Data Exchange (ETDEWEB)

Sun Lu; Wang Jiali; Wang Shan; Li Xuezheng; Shi Hui; Wang Na; Guo Shengping, E-mail: sunlu_1019@126.co [School of Electromechanical Engineering, Xidian University, Xi' an 710071 (China)

2009-06-01

Under a large signal drive level, a frequency domain black box model of the nonlinear scattering function is introduced into power FETs and diodes. A time domain measurement system and a calibration method based on a digital oscilloscope are designed to extract the nonlinear scattering function of semiconductor devices. The extracted models can reflect the real electrical performance of semiconductor devices and propose a new large-signal model to the design of microwave semiconductor circuits.

Large-signal modeling method for power FETs and diodes

International Nuclear Information System (INIS)

Sun Lu; Wang Jiali; Wang Shan; Li Xuezheng; Shi Hui; Wang Na; Guo Shengping

2009-01-01

Under a large signal drive level, a frequency domain black box model of the nonlinear scattering function is introduced into power FETs and diodes. A time domain measurement system and a calibration method based on a digital oscilloscope are designed to extract the nonlinear scattering function of semiconductor devices. The extracted models can reflect the real electrical performance of semiconductor devices and propose a new large-signal model to the design of microwave semiconductor circuits.

Enhancement of speech signals - with a focus on voiced speech models

DEFF Research Database (Denmark)

Nørholm, Sidsel Marie

This thesis deals with speech enhancement, i.e., noise reduction in speech signals. This has applications in, e.g., hearing aids and teleconference systems. We consider a signal-driven approach to speech enhancement where a model of the speech is assumed and filters are generated based...... on this model. The basic model used in this thesis is the harmonic model which is a commonly used model for describing the voiced part of the speech signal. We show that it can be beneficial to extend the model to take inharmonicities or the non-stationarity of speech into account. Extending the model...

MPD model for radar echo signal of hypersonic targets

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Xu Xuefei

2014-08-01

Full Text Available The stop-and-go (SAG model is typically used for echo signal received by the radar using linear frequency modulation pulse compression. In this study, the authors demonstrate that this model is not applicable to hypersonic targets. Instead of SAG model, they present a more realistic echo signal model (moving-in-pulse duration (MPD for hypersonic targets. Following that, they evaluate the performances of pulse compression under the SAG and MPD models by theoretical analysis and simulations. They found that the pulse compression gain has an increase of 3 dB by using the MPD model compared with the SAG model in typical cases.

Calcium Imaging of Nerve-Mast Cell Signaling in the Human Intestine

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Sabine Buhner

2017-11-01

Full Text Available Introduction: It is suggested that an altered microenvironment in the gut wall alters communication along a mast cell nerve axis. We aimed to record for the first time signaling between mast cells and neurons in intact human submucous preparations.Methods: We used the Ca2+ sensitive dye Fluo-4 AM to simultaneously image changes in intracellular calcium [Ca+2]i (%ΔF/F in neurons and mast cells. Data are presented as median with interquartile ranges (25/75%.Results: We recorded nerve responses in 29 samples upon selective activation of 223 mast cells by IgE receptor cross linking with the antibody mAb22E7. Mast cells responded to mAb22E7 with a median [Ca+2]i increase of 20% (11/39 peaking 90 s (64/144 after the application. Only very few neurons responded and the median percentage of responding neuronal area was 0% (0/5.9. Mast cell activation remained in the presence of the fast sodium channel blocker tetrodotoxin. Specific neuronal activation by transmural electrical field stimulation (EFS in 34 samples evoked instantaneously [Ca+2]i signals in submucous neurons. This was followed by a [Ca+2]i peak response of 8%ΔF/F (4/15 in 33% of 168 mast cells in the field of view. The mast cell response was abolished by the nerve blocker tetrododoxin, reduced by the Calcitonin Gene-Related Peptide receptor 1 antagonist BIBN-4096 and the Vasoactive Intestinal Peptide receptor antagonist PG97-269, but not by blockade of the neurokinin receptors 1–3.Conclusion: The findings revealed bidirectional signaling between mast cells and submucous neurons in human gut. In our macroscopically normal preparations a nerve to mast cell signaling was very prominent whereas a mast cell to nerve signaling was rather rare.

Conceptual Network Model From Sensory Neurons to Astrocytes of the Human Nervous System.

Science.gov (United States)

Yang, Yiqun; Yeo, Chai Kiat

2015-07-01

From a single-cell animal like paramecium to vertebrates like ape, the nervous system plays an important role in responding to the variations of the environment. Compared to animals, the nervous system in the human body possesses more intricate organization and utility. The nervous system anatomy has been understood progressively, yet the explanation at the cell level regarding complete information transmission is still lacking. Along the signal pathway toward the brain, an external stimulus first activates action potentials in the sensing neuron and these electric pulses transmit along the spinal nerve or cranial nerve to the neurons in the brain. Second, calcium elevation is triggered in the branch of astrocyte at the tripartite synapse. Third, the local calcium wave expands to the entire territory of the astrocyte. Finally, the calcium wave propagates to the neighboring astrocyte via gap junction channel. In our study, we integrate the existing mathematical model and biological experiments in each step of the signal transduction to establish a conceptual network model for the human nervous system. The network is composed of four layers and the communication protocols of each layer could be adapted to entities with different characterizations. We verify our simulation results against the available biological experiments and mathematical models and provide a test case of the integrated network. As the production of conscious episode in the human nervous system is still under intense research, our model serves as a useful tool to facilitate, complement and verify current and future study in human cognition.

Corrected Four-Sphere Head Model for EEG Signals.

Science.gov (United States)

Næss, Solveig; Chintaluri, Chaitanya; Ness, Torbjørn V; Dale, Anders M; Einevoll, Gaute T; Wójcik, Daniel K

2017-01-01

The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF), skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM). We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations.

Corrected Four-Sphere Head Model for EEG Signals

Directory of Open Access Journals (Sweden)

Solveig Næss

2017-10-01

Full Text Available The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF, skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM. We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations.

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

Science.gov (United States)

Gan, Xiao; Albert, RéKa

Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

Quantative Evaluation of the Efficiency of Facial Bio-potential Signals Based on Forehead Three-Channel Electrode Placement For Facial Gesture Recognition Applicable in a Human-Machine Interface

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Iman Mohammad Rezazadeh

2010-06-01

Full Text Available Introduction: Today, facial bio-potential signals are employed in many human-machine interface applications for enhancing and empowering the rehabilitation process. The main point to achieve that goal is to record appropriate bioelectric signals from the human face by placing and configuring electrodes over it in the right way. In this paper, heuristic geometrical position and configuration of the electrodes has been proposed for improving the quality of the acquired signals and consequently enhancing the performance of the facial gesture classifier. Materials and Methods: Investigation and evaluation of the electrodes' proper geometrical position and configuration can be performed using two methods: clinical and modeling. In the clinical method, the electrodes are placed in predefined positions and the elicited signals from them are then processed. The performance of the method is evaluated based on the results obtained. On the other hand, in the modeling approach, the quality of the recorded signals and their information content are evaluated only by modeling and simulation. In this paper, both methods have been utilized together. First, suitable electrode positions and configuration were proposed and evaluated by modeling and simulation. Then, the experiment was performed with a predefined protocol on 7 healthy subjects to validate the simulation results. Here, the recorded signals were passed through parallel butterworth filter banks to obtain facial EMG, EOG and EEG signals and the RMS features of each 256 msec time slot were extracted.  By using the power of Subtractive Fuzzy C-Mean (SFCM, 8 different facial gestures (including smiling, frowning, pulling up left and right lip corners, left/right/up and down movements of the eyes were discriminated. Results: According to the three-channel electrode configuration derived from modeling of the dipoles effects on the surface electrodes and by employing the SFCM classifier, an average 94

Peroxisome proliferator-activated receptor gamma signaling in human sperm physiology.

Science.gov (United States)

Liu, Li-Li; Xian, Hua; Cao, Jing-Chen; Zhang, Chong; Zhang, Yong-Hui; Chen, Miao-Miao; Qian, Yi; Jiang, Ming

2015-01-01

Peroxisome proliferator-activated receptor gamma (PPARγ) is a member of the PPARs, which are transcription factors of the steroid receptor superfamily. PPARγ acts as an important molecule for regulating energy homeostasis, modulates the hypothalamic-pituitary-gonadal (HPG) axis, and is reciprocally regulated by HPG. In the human, PPARγ protein is highly expressed in ejaculated spermatozoa, implying a possible role of PPARγ signaling in regulating sperm energy dissipation. PPARγ protein is also expressed in Sertoli cells and germ cells (spermatocytes). Its activation can be induced during capacitation and the acrosome reaction. This mini-review will focus on how PPARγ signaling may affect fertility and sperm quality and the potential reversibility of these adverse effects.

Correlation between human observer performance and model observer performance in differential phase contrast CT

International Nuclear Information System (INIS)

Li, Ke; Garrett, John; Chen, Guang-Hong

2013-01-01

Purpose: With the recently expanding interest and developments in x-ray differential phase contrast CT (DPC-CT), the evaluation of its task-specific detection performance and comparison with the corresponding absorption CT under a given radiation dose constraint become increasingly important. Mathematical model observers are often used to quantify the performance of imaging systems, but their correlations with actual human observers need to be confirmed for each new imaging method. This work is an investigation of the effects of stochastic DPC-CT noise on the correlation of detection performance between model and human observers with signal-known-exactly (SKE) detection tasks.Methods: The detectabilities of different objects (five disks with different diameters and two breast lesion masses) embedded in an experimental DPC-CT noise background were assessed using both model and human observers. The detectability of the disk and lesion signals was then measured using five types of model observers including the prewhitening ideal observer, the nonprewhitening (NPW) observer, the nonprewhitening observer with eye filter and internal noise (NPWEi), the prewhitening observer with eye filter and internal noise (PWEi), and the channelized Hotelling observer (CHO). The same objects were also evaluated by four human observers using the two-alternative forced choice method. The results from the model observer experiment were quantitatively compared to the human observer results to assess the correlation between the two techniques.Results: The contrast-to-detail (CD) curve generated by the human observers for the disk-detection experiments shows that the required contrast to detect a disk is inversely proportional to the square root of the disk size. Based on the CD curves, the ideal and NPW observers tend to systematically overestimate the performance of the human observers. The NPWEi and PWEi observers did not predict human performance well either, as the slopes of their CD

Mathematical model reveals role of nucleotide signaling in airway surface liquid homeostasis and its dysregulation in cystic fibrosis.

Science.gov (United States)

Sandefur, Conner I; Boucher, Richard C; Elston, Timothy C

2017-08-29

Mucociliary clearance is composed of three components (i.e., mucin secretion, airway surface hydration, and ciliary-activity) which function coordinately to clear inhaled microbes and other foreign particles from airway surfaces. Airway surface hydration is maintained by water fluxes driven predominantly by active chloride and sodium ion transport. The ion channels that mediate electrogenic ion transport are regulated by extracellular purinergic signals that signal through G protein-coupled receptors. These purinoreceptors and the signaling pathways they activate have been identified as possible therapeutic targets for treating lung disease. A systems-level description of airway surface liquid (ASL) homeostasis could accelerate development of such therapies. Accordingly, we developed a mathematical model to describe the dynamic coupling of ion and water transport to extracellular purinergic signaling. We trained our model from steady-state and time-dependent experimental measurements made using normal and cystic fibrosis (CF) cultured human airway epithelium. To reproduce CF conditions, reduced chloride secretion, increased potassium secretion, and increased sodium absorption were required. The model accurately predicted ASL height under basal normal and CF conditions and the collapse of surface hydration due to the accelerated nucleotide metabolism associated with CF exacerbations. Finally, the model predicted a therapeutic strategy to deliver nucleotide receptor agonists to effectively rehydrate the ASL of CF airways.

Efficient ECG Signal Compression Using Adaptive Heart Model

National Research Council Canada - National Science Library

Szilagyi, S

2001-01-01

This paper presents an adaptive, heart-model-based electrocardiography (ECG) compression method. After conventional pre-filtering the waves from the signal are localized and the model's parameters are determined...

The V protein of Tioman virus is incapable of blocking type I interferon signaling in human cells.

Directory of Open Access Journals (Sweden)

Grégory Caignard

Full Text Available The capacity of a virus to cross species barriers is determined by the development of bona fide interactions with cellular components of new hosts, and in particular its ability to block IFN-α/β antiviral signaling. Tioman virus (TioV, a close relative of mumps virus (MuV, has been isolated in giant fruit bats in Southeast Asia. Nipah and Hendra viruses, which are present in the same bat colonies, are highly pathogenic in human. Despite serological evidences of close contacts between TioV and human populations, whether TioV is associated to some human pathology remains undetermined. Here we show that in contrast to the V protein of MuV, the V protein of TioV (TioV-V hardly interacts with human STAT2, does not degrade STAT1, and cannot block IFN-α/β signaling in human cells. In contrast, TioV-V properly binds to human STAT3 and MDA5, and thus interferes with IL-6 signaling and IFN-β promoter induction in human cells. Because STAT2 binding was previously identified as a host restriction factor for some Paramyxoviridae, we established STAT2 sequence from giant fruit bats, and binding to TioV-V was tested. Surprisingly, TioV-V interaction with STAT2 from giant fruit bats is also extremely weak and barely detectable. Altogether, our observations question the capacity of TioV to appropriately control IFN-α/β signaling in both human and giant fruit bats that are considered as its natural host.

Evaluation of the autoregression time-series model for analysis of a noisy signal

International Nuclear Information System (INIS)

Allen, J.W.

1977-01-01

The autoregression (AR) time-series model of a continuous noisy signal was statistically evaluated to determine quantitatively the uncertainties of the model order, the model parameters, and the model's power spectral density (PSD). The result of such a statistical evaluation enables an experimenter to decide whether an AR model can adequately represent a continuous noisy signal and be consistent with the signal's frequency spectrum, and whether it can be used for on-line monitoring. Although evaluations of other types of signals have been reported in the literature, no direct reference has been found to AR model's uncertainties for continuous noisy signals; yet the evaluation is necessary to decide the usefulness of AR models of typical reactor signals (e.g., neutron detector output or thermocouple output) and the potential of AR models for on-line monitoring applications. AR and other time-series models for noisy data representation are being investigated by others since such models require fewer parameters than the traditional PSD model. For this study, the AR model was selected for its simplicity and conduciveness to uncertainty analysis, and controlled laboratory bench signals were used for continuous noisy data. (author)

Human modeling in nuclear engineering

International Nuclear Information System (INIS)

Yoshikawa, Hidekazu; Furuta, Kazuo.

1994-01-01

Review on progress of research and development on human modeling methods is made from the viewpoint of its importance on total man-machine system reliability surrounding nuclear power plant operation. Basic notions on three different approaches of human modeling (behavioristics, cognitives and sociologistics) are firstly introduced, followed by the explanation of fundamental scheme to understand human cognitives at man-machine interface and the mechanisms of human error and its classification. Then, general methodologies on human cognitive model by AI are explained with the brief summary of various R and D activities now prevailing in the human modeling communities around the world. A new method of dealing with group human reliability is also introduced which is based on sociologistic mathematical model. Lastly, problems on human model validation are discussed, followed by the introduction of new experimental method to estimate human cognitive state by psycho-physiological measurement, which is a new methodology plausible for human model validation. (author)

Reduced modeling of signal transduction – a modular approach

Directory of Open Access Journals (Sweden)

Ederer Michael

2007-09-01

Full Text Available Abstract Background Combinatorial complexity is a challenging problem in detailed and mechanistic mathematical modeling of signal transduction. This subject has been discussed intensively and a lot of progress has been made within the last few years. A software tool (BioNetGen was developed which allows an automatic rule-based set-up of mechanistic model equations. In many cases these models can be reduced by an exact domain-oriented lumping technique. However, the resulting models can still consist of a very large number of differential equations. Results We introduce a new reduction technique, which allows building modularized and highly reduced models. Compared to existing approaches further reduction of signal transduction networks is possible. The method also provides a new modularization criterion, which allows to dissect the model into smaller modules that are called layers and can be modeled independently. Hallmarks of the approach are conservation relations within each layer and connection of layers by signal flows instead of mass flows. The reduced model can be formulated directly without previous generation of detailed model equations. It can be understood and interpreted intuitively, as model variables are macroscopic quantities that are converted by rates following simple kinetics. The proposed technique is applicable without using complex mathematical tools and even without detailed knowledge of the mathematical background. However, we provide a detailed mathematical analysis to show performance and limitations of the method. For physiologically relevant parameter domains the transient as well as the stationary errors caused by the reduction are negligible. Conclusion The new layer based reduced modeling method allows building modularized and strongly reduced models of signal transduction networks. Reduced model equations can be directly formulated and are intuitively interpretable. Additionally, the method provides very good

Mathematical Models Light Up Plant Signaling

NARCIS (Netherlands)

Chew, Y.H.; Smith, R.W.; Jones, H.J.; Seaton, D.D.; Grima, R.; Halliday, K.J.

2014-01-01

Plants respond to changes in the environment by triggering a suite of regulatory networks that control and synchronize molecular signaling in different tissues, organs, and the whole plant. Molecular studies through genetic and environmental perturbations, particularly in the model plant Arabidopsis

Long-Term Expansion, Enhanced Chondrogenic Potential, and Suppression of Endochondral Ossification of Adult Human MSCs via WNT Signaling Modulation

Directory of Open Access Journals (Sweden)

Roberto Narcisi

2015-03-01

Full Text Available Mesenchymal stem cells (MSCs are a potential source of chondrogenic cells for the treatment of cartilage disorders, but loss of chondrogenic potential during in vitro expansion and the propensity of cartilage to undergo hypertrophic maturation impede their therapeutic application. Here we report that the signaling protein WNT3A, in combination with FGF2, supports long-term expansion of human bone marrow-derived MSCs. The cells retained their chondrogenic potential and other phenotypic and functional properties of multipotent MSCs, which were gradually lost in the absence of WNT3A. Moreover, we discovered that endogenous WNT signals are the main drivers of the hypertrophic maturation that follows chondrogenic differentiation. Inhibition of WNT signals during differentiation prevented calcification and maintained cartilage properties following implantation in a mouse model. By maintaining potency during expansion and preventing hypertrophic maturation following differentiation, the modulation of WNT signaling removes two major obstacles that impede the clinical application of MSCs in cartilage repair.

Human Modeling for Ground Processing Human Factors Engineering Analysis

Science.gov (United States)

Stambolian, Damon B.; Lawrence, Brad A.; Stelges, Katrine S.; Steady, Marie-Jeanne O.; Ridgwell, Lora C.; Mills, Robert E.; Henderson, Gena; Tran, Donald; Barth, Tim

2011-01-01

There have been many advancements and accomplishments over the last few years using human modeling for human factors engineering analysis for design of spacecraft. The key methods used for this are motion capture and computer generated human models. The focus of this paper is to explain the human modeling currently used at Kennedy Space Center (KSC), and to explain the future plans for human modeling for future spacecraft designs

Sporadic naturally occurring melanoma in dogs as a preclinical model for human melanoma.

Science.gov (United States)

Simpson, R Mark; Bastian, Boris C; Michael, Helen T; Webster, Joshua D; Prasad, Manju L; Conway, Catherine M; Prieto, Victor M; Gary, Joy M; Goldschmidt, Michael H; Esplin, D Glen; Smedley, Rebecca C; Piris, Adriano; Meuten, Donald J; Kiupel, Matti; Lee, Chyi-Chia R; Ward, Jerrold M; Dwyer, Jennifer E; Davis, Barbara J; Anver, Miriam R; Molinolo, Alfredo A; Hoover, Shelley B; Rodriguez-Canales, Jaime; Hewitt, Stephen M

2014-01-01

Melanoma represents a significant malignancy in humans and dogs. Different from genetically engineered models, sporadic canine melanocytic neoplasms share several characteristics with human disease that could make dogs a more relevant preclinical model. Canine melanomas rarely arise in sun-exposed sites. Most occur in the oral cavity, with a subset having intra-epithelial malignant melanocytes mimicking the in situ component of human mucosal melanoma. The spectrum of canine melanocytic neoplasia includes benign lesions with some analogy to nevi, as well as invasive primary melanoma, and widespread metastasis. Growing evidence of distinct subtypes in humans, differing in somatic and predisposing germ-line genetic alterations, cell of origin, epidemiology, relationship to ultraviolet radiation and progression from benign to malignant tumors, may also exist in dogs. Canine and human mucosal melanomas appear to harbor BRAF, NRAS, and c-kit mutations uncommonly, compared with human cutaneous melanomas, although both species share AKT and MAPK signaling activation. We conclude that there is significant overlap in the clinical and histopathological features of canine and human mucosal melanomas. This represents opportunity to explore canine oral cavity melanoma as a preclinical model. © 2013 The Authors. Pigment Cell & Melanoma Research published by John Wiley & Sons Ltd.

Learning sparse generative models of audiovisual signals

OpenAIRE

Monaci, Gianluca; Sommer, Friedrich T.; Vandergheynst, Pierre

2008-01-01

This paper presents a novel framework to learn sparse represen- tations for audiovisual signals. An audiovisual signal is modeled as a sparse sum of audiovisual kernels. The kernels are bimodal functions made of synchronous audio and video components that can be positioned independently and arbitrarily in space and time. We design an algorithm capable of learning sets of such audiovi- sual, synchronous, shift-invariant functions by alternatingly solving a coding and a learning pr...

PATHLOGIC-S: a scalable Boolean framework for modelling cellular signalling.

Directory of Open Access Journals (Sweden)

Liam G Fearnley

Full Text Available Curated databases of signal transduction have grown to describe several thousand reactions, and efficient use of these data requires the development of modelling tools to elucidate and explore system properties. We present PATHLOGIC-S, a Boolean specification for a signalling model, with its associated GPL-licensed implementation using integer programming techniques. The PATHLOGIC-S specification has been designed to function on current desktop workstations, and is capable of providing analyses on some of the largest currently available datasets through use of Boolean modelling techniques to generate predictions of stable and semi-stable network states from data in community file formats. PATHLOGIC-S also addresses major problems associated with the presence and modelling of inhibition in Boolean systems, and reduces logical incoherence due to common inhibitory mechanisms in signalling systems. We apply this approach to signal transduction networks including Reactome and two pathways from the Panther Pathways database, and present the results of computations on each along with a discussion of execution time. A software implementation of the framework and model is freely available under a GPL license.

Activation of the Extracellular Signal-Regulated Kinase Signaling Is Critical for Human Umbilical Cord Mesenchymal Stem Cell Osteogenic Differentiation

Directory of Open Access Journals (Sweden)

Chen-Shuang Li

2016-01-01

Full Text Available Human umbilical cord mesenchymal stem cells (hUCMSCs are recognized as candidate progenitor cells for bone regeneration. However, the mechanism of hUCMSC osteogenesis remains unclear. In this study, we revealed that mitogen-activated protein kinases (MAPKs signaling is involved in hUCMSC osteogenic differentiation in vitro. Particularly, the activation of c-Jun N-terminal kinases (JNK and p38 signaling pathways maintained a consistent level in hUCMSCs through the entire 21-day osteogenic differentiation period. At the same time, the activation of extracellular signal-regulated kinases (ERK signaling significantly increased from day 5, peaked at day 9, and declined thereafter. Moreover, gene profiling of osteogenic markers, alkaline phosphatase (ALP activity measurement, and alizarin red staining demonstrated that the application of U0126, a specific inhibitor for ERK activation, completely prohibited hUCMSC osteogenic differentiation. However, when U0126 was removed from the culture at day 9, ERK activation and osteogenic differentiation of hUCMSCs were partially recovered. Together, these findings demonstrate that the activation of ERK signaling is essential for hUCMSC osteogenic differentiation, which points out the significance of ERK signaling pathway to regulate the osteogenic differentiation of hUCMSCs as an alternative cell source for bone tissue engineering.

Computational Biophysical, Biochemical, and Evolutionary Signature of Human R-Spondin Family Proteins, the Member of Canonical Wnt/β-Catenin Signaling Pathway

Directory of Open Access Journals (Sweden)

Ashish Ranjan Sharma

2014-01-01

Full Text Available In human, Wnt/β-catenin signaling pathway plays a significant role in cell growth, cell development, and disease pathogenesis. Four human (Rspos are known to activate canonical Wnt/β-catenin signaling pathway. Presently, (Rspos serve as therapeutic target for several human diseases. Henceforth, basic understanding about the molecular properties of (Rspos is essential. We approached this issue by interpreting the biochemical and biophysical properties along with molecular evolution of (Rspos thorough computational algorithm methods. Our analysis shows that signal peptide length is roughly similar in (Rspos family along with similarity in aa distribution pattern. In Rspo3, four N-glycosylation sites were noted. All members are hydrophilic in nature and showed alike GRAVY values, approximately. Conversely, Rspo3 contains the maximum positively charged residues while Rspo4 includes the lowest. Four highly aligned blocks were recorded through Gblocks. Phylogenetic analysis shows Rspo4 is being rooted with Rspo2 and similarly Rspo3 and Rspo1 have the common point of origin. Through phylogenomics study, we developed a phylogenetic tree of sixty proteins (n=60 with the orthologs and paralogs seed sequences. Protein-protein network was also illustrated. Results demonstrated in our study may help the future researchers to unfold significant physiological and therapeutic properties of (Rspos in various disease models.

Subsecond dopamine fluctuations in human striatum encode superposed error signals about actual and counterfactual reward

Science.gov (United States)

Kishida, Kenneth T.; Saez, Ignacio; Lohrenz, Terry; Witcher, Mark R.; Laxton, Adrian W.; Tatter, Stephen B.; White, Jason P.; Ellis, Thomas L.; Phillips, Paul E. M.; Montague, P. Read

2016-01-01

In the mammalian brain, dopamine is a critical neuromodulator whose actions underlie learning, decision-making, and behavioral control. Degeneration of dopamine neurons causes Parkinson’s disease, whereas dysregulation of dopamine signaling is believed to contribute to psychiatric conditions such as schizophrenia, addiction, and depression. Experiments in animal models suggest the hypothesis that dopamine release in human striatum encodes reward prediction errors (RPEs) (the difference between actual and expected outcomes) during ongoing decision-making. Blood oxygen level-dependent (BOLD) imaging experiments in humans support the idea that RPEs are tracked in the striatum; however, BOLD measurements cannot be used to infer the action of any one specific neurotransmitter. We monitored dopamine levels with subsecond temporal resolution in humans (n = 17) with Parkinson’s disease while they executed a sequential decision-making task. Participants placed bets and experienced monetary gains or losses. Dopamine fluctuations in the striatum fail to encode RPEs, as anticipated by a large body of work in model organisms. Instead, subsecond dopamine fluctuations encode an integration of RPEs with counterfactual prediction errors, the latter defined by how much better or worse the experienced outcome could have been. How dopamine fluctuations combine the actual and counterfactual is unknown. One possibility is that this process is the normal behavior of reward processing dopamine neurons, which previously had not been tested by experiments in animal models. Alternatively, this superposition of error terms may result from an additional yet-to-be-identified subclass of dopamine neurons. PMID:26598677

Objective Model Selection for Identifying the Human Feedforward Response in Manual Control.

Science.gov (United States)

Drop, Frank M; Pool, Daan M; van Paassen, Marinus Rene M; Mulder, Max; Bulthoff, Heinrich H

2018-01-01

Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification procedure is presented that aims at an objective model selection for identifying the human feedforward response, using linear time-invariant autoregressive with exogenous input models. A new model selection criterion is proposed to decide on the model order (number of parameters) and the presence of feedforward in addition to feedback. For a range of typical control tasks, it is shown by means of Monte Carlo computer simulations that the classical Bayesian information criterion (BIC) leads to selecting models that contain a feedforward path from data generated by a pure feedback model: "false-positive" feedforward detection. To eliminate these false-positives, the modified BIC includes an additional penalty on model complexity. The appropriate weighting is found through computer simulations with a hypothesized HC model prior to performing a tracking experiment. Experimental human-in-the-loop data will be considered in future work. With appropriate weighting, the method correctly identifies the HC dynamics in a wide range of control tasks, without false-positive results.

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

Digital Human Modeling

Science.gov (United States)

Dischinger, H. Charles, Jr.

2017-01-01

The development of models to represent human characteristics and behaviors in human factors is broad and general. The term "model" can refer to any metaphor to represent any aspect of the human; it is generally used in research to mean a mathematical tool for the simulation (often in software, which makes the simulation digital) of some aspect of human performance and for the prediction of future outcomes. This section is restricted to the application of human models in physical design, e.g., in human factors engineering. This design effort is typically human interface design, and the digital models used are anthropometric. That is, they are visual models that are the physical shape of humans and that have the capabilities and constraints of humans of a selected population. They are distinct from the avatars used in the entertainment industry (movies, video games, and the like) in precisely that regard: as models, they are created through the application of data on humans, and they are used to predict human response; body stresses workspaces. DHM enable iterative evaluation of a large number of concepts and support rapid analysis, as compared with use of physical mockups. They can be used to evaluate feasibility of escape of a suited astronaut from a damaged vehicle, before launch or after an abort (England, et al., 2012). Throughout most of human spaceflight, little attention has been paid to worksite design for ground workers. As a result of repeated damage to the Space Shuttle which adversely affected flight safety, DHM analyses of ground assembly and maintenance have been developed over the last five years for the design of new flight systems (Stambolian, 2012, Dischinger and Dunn Jackson, 2014). The intent of these analyses is to assure the design supports the work of the ground crew personnel and thereby protect the launch vehicle. They help the analyst address basic human factors engineering questions: can a worker reach the task site from the work platform

Semiconductor Modeling For Simulating Signal, Power, and Electromagneticintegrity

CERN Document Server

Leventhal, Roy

2006-01-01

Assists engineers in designing high-speed circuits. The emphasis is on semiconductor modeling, with PCB transmission line effects, equipment enclosure effects, and other modeling issues discussed as needed. This text addresses practical considerations, including process variation, model accuracy, validation and verification, and signal integrity.

Wires in the soup: quantitative models of cell signaling

Science.gov (United States)

Cheong, Raymond; Levchenko, Andre

2014-01-01

Living cells are capable of extracting information from their environments and mounting appropriate responses to a variety of associated challenges. The underlying signal transduction networks enabling this can be quite complex, necessitating for their unraveling by sophisticated computational modeling coupled with precise experimentation. Although we are still at the beginning of this process, some recent examples of integrative analysis of cell signaling are very encouraging. This review highlights the case of the NF-κB pathway in order to illustrate how a quantitative model of a signaling pathway can be gradually constructed through continuous experimental validation, and what lessons one might learn from such exercises. PMID:18291655

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 ...

Delivering key signals to the machine: seeking the electric signal that muscles emanate

International Nuclear Information System (INIS)

Hashim, A Y Bani; Maslan, M N; Izamshah, R; Mohamad, I S

2014-01-01

Due to the limitation of electric power generation in the human body, present human-machine interfaces have not been successful because of the nature of standard electronics circuit designs, which do not consider the specifications of signals that resulted from the skin. In general, the outcomes and applications of human-machine interfaces are limited to custom-designed subsystems, such as neuroprosthesis. We seek to model the bio dynamical of sub skin into equivalent mathematical definitions, descriptions, and theorems. Within the human skin, there are networks of nerves that permit the skin to function as a multi dimension transducer. We investigate the nature of structural skin. Apart from multiple networks of nerves, there are other segments within the skin such as minute muscles. We identify the segments that are active when there is an electromyography activity. When the nervous system is firing signals, the muscle is being stimulated. We evaluate the phenomena of biodynamic of the muscles that is concerned with the electromyography activity of the nervous system. In effect, we design a relationship between the human somatosensory and synthetic systems sensory as the union of a complete set of the new domain of the functional system. This classifies electromyogram waveforms linked to intent thought of an operator. The system will become the basis for delivering key signals to machine such that the machine is under operator's intent, hence slavery

Stochastic Modelling as a Tool for Seismic Signals Segmentation

Directory of Open Access Journals (Sweden)

Daniel Kucharczyk

2016-01-01

Full Text Available In order to model nonstationary real-world processes one can find appropriate theoretical model with properties following the analyzed data. However in this case many trajectories of the analyzed process are required. Alternatively, one can extract parts of the signal that have homogenous structure via segmentation. The proper segmentation can lead to extraction of important features of analyzed phenomena that cannot be described without the segmentation. There is no one universal method that can be applied for all of the phenomena; thus novel methods should be invented for specific cases. They might address specific character of the signal in different domains (time, frequency, time-frequency, etc.. In this paper we propose two novel segmentation methods that take under consideration the stochastic properties of the analyzed signals in time domain. Our research is motivated by the analysis of vibration signals acquired in an underground mine. In such signals we observe seismic events which appear after the mining activity, like blasting, provoked relaxation of rock, and some unexpected events, like natural rock burst. The proposed segmentation procedures allow for extraction of such parts of the analyzed signals which are related to mentioned events.

Signal classification using global dynamical models, Part I: Theory

International Nuclear Information System (INIS)

Kadtke, J.; Kremliovsky, M.

1996-01-01

Detection and classification of signals is one of the principal areas of signal processing, and the utilization of nonlinear information has long been considered as a way of improving performance beyond standard linear (e.g. spectral) techniques. Here, we develop a method for using global models of chaotic dynamical systems theory to define a signal classification processing chain, which is sensitive to nonlinear correlations in the data. We use it to demonstrate classification in high noise regimes (negative SNR), and argue that classification probabilities can be directly computed from ensemble statistics in the model coefficient space. We also develop a modification for non-stationary signals (i.e. transients) using non-autonomous ODEs. In Part II of this paper, we demonstrate the analysis on actual open ocean acoustic data from marine biologics. copyright 1996 American Institute of Physics

The Value of Human Capital Signals for Investment Decision Making under Uncertainty

DEFF Research Database (Denmark)

Hain, Daniel; Christensen, Jesper Lindgaard; Jurowetzki, Roman

environments as our empirical setting. A large body of research from behavioral economics illustrates that when faced with uncertain and complex decision problems, investors tend to rely on simple heuristics and rules-of thumb, derived by easily accessible and assessable signals. Yet, with increasing...... with a similar pair that did lead to an investment. Based on Crunchbase investment data, we gather via LinkedIn and further sources detailed information on the founders professional and education background. We find human capital signals from the entrepreneurs to be of higher importance for investors when...

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.

Comparative genetic screens in human cells reveal new regulatory mechanisms in WNT signaling

Science.gov (United States)

Lebensohn, Andres M; Dubey, Ramin; Neitzel, Leif R; Tacchelly-Benites, Ofelia; Yang, Eungi; Marceau, Caleb D; Davis, Eric M; Patel, Bhaven B; Bahrami-Nejad, Zahra; Travaglini, Kyle J; Ahmed, Yashi; Lee, Ethan; Carette, Jan E; Rohatgi, Rajat

2016-01-01

The comprehensive understanding of cellular signaling pathways remains a challenge due to multiple layers of regulation that may become evident only when the pathway is probed at different levels or critical nodes are eliminated. To discover regulatory mechanisms in canonical WNT signaling, we conducted a systematic forward genetic analysis through reporter-based screens in haploid human cells. Comparison of screens for negative, attenuating and positive regulators of WNT signaling, mediators of R-spondin-dependent signaling and suppressors of constitutive signaling induced by loss of the tumor suppressor adenomatous polyposis coli or casein kinase 1α uncovered new regulatory features at most levels of the pathway. These include a requirement for the transcription factor AP-4, a role for the DAX domain of AXIN2 in controlling β-catenin transcriptional activity, a contribution of glycophosphatidylinositol anchor biosynthesis and glypicans to R-spondin-potentiated WNT signaling, and two different mechanisms that regulate signaling when distinct components of the β-catenin destruction complex are lost. The conceptual and methodological framework we describe should enable the comprehensive understanding of other signaling systems. DOI: http://dx.doi.org/10.7554/eLife.21459.001 PMID:27996937

Computational Analysis and Simulation of Empathic Behaviors: a Survey of Empathy Modeling with Behavioral Signal Processing Framework.

Science.gov (United States)

Xiao, Bo; Imel, Zac E; Georgiou, Panayiotis; Atkins, David C; Narayanan, Shrikanth S

2016-05-01

Empathy is an important psychological process that facilitates human communication and interaction. Enhancement of empathy has profound significance in a range of applications. In this paper, we review emerging directions of research on computational analysis of empathy expression and perception as well as empathic interactions, including their simulation. We summarize the work on empathic expression analysis by the targeted signal modalities (e.g., text, audio, and facial expressions). We categorize empathy simulation studies into theory-based emotion space modeling or application-driven user and context modeling. We summarize challenges in computational study of empathy including conceptual framing and understanding of empathy, data availability, appropriate use and validation of machine learning techniques, and behavior signal processing. Finally, we propose a unified view of empathy computation and offer a series of open problems for future research.

A simple statistical signal loss model for deep underground garage

DEFF Research Database (Denmark)

Nguyen, Huan Cong; Gimenez, Lucas Chavarria; Kovacs, Istvan

2016-01-01

In this paper we address the channel modeling aspects for a deep-indoor scenario with extreme coverage conditions in terms of signal losses, namely underground garage areas. We provide an in-depth analysis in terms of path loss (gain) and large scale signal shadowing, and a propose simple...... propagation model which can be used to predict cellular signal levels in similar deep-indoor scenarios. The proposed frequency-independent floor attenuation factor (FAF) is shown to be in range of 5.2 dB per meter deep....

Human-machine interface based on muscular and brain signals applied to a robotic wheelchair

International Nuclear Information System (INIS)

Ferreira, A; Silva, R L; Celeste, W C; Filho, T F Bastos; Filho, M Sarcinelli

2007-01-01

This paper presents a Human-Machine Interface (HMI) based on the signals generated by eye blinks or brain activity. The system structure and the signal acquisition and processing are shown. The signals used in this work are either the signal associated to the muscular movement corresponding to an eye blink or the brain signal corresponding to visual information processing. The variance is the feature extracted from such signals in order to detect the intention of the user. The classification is performed by a variance threshold which is experimentally determined for each user during the training stage. The command options, which are going to be sent to the commanded device, are presented to the user in the screen of a PDA (Personal Digital Assistant). In the experiments here reported, a robotic wheelchair is used as the device being commanded

Human-machine interface based on muscular and brain signals applied to a robotic wheelchair

Energy Technology Data Exchange (ETDEWEB)

Ferreira, A; Silva, R L; Celeste, W C; Filho, T F Bastos; Filho, M Sarcinelli [Electrical Engineering Department, Federal University of Espirito Santo (UFES), Av. Fernando Ferrari, 514, Vitoria, 29075-910 (Brazil)

2007-11-15

This paper presents a Human-Machine Interface (HMI) based on the signals generated by eye blinks or brain activity. The system structure and the signal acquisition and processing are shown. The signals used in this work are either the signal associated to the muscular movement corresponding to an eye blink or the brain signal corresponding to visual information processing. The variance is the feature extracted from such signals in order to detect the intention of the user. The classification is performed by a variance threshold which is experimentally determined for each user during the training stage. The command options, which are going to be sent to the commanded device, are presented to the user in the screen of a PDA (Personal Digital Assistant). In the experiments here reported, a robotic wheelchair is used as the device being commanded.

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

Modelling and Analysis of Biochemical Signalling Pathway Cross-talk

Directory of Open Access Journals (Sweden)

Robin Donaldson

2010-02-01

Full Text Available Signalling pathways are abstractions that help life scientists structure the coordination of cellular activity. Cross-talk between pathways accounts for many of the complex behaviours exhibited by signalling pathways and is often critical in producing the correct signal-response relationship. Formal models of signalling pathways and cross-talk in particular can aid understanding and drive experimentation. We define an approach to modelling based on the concept that a pathway is the (synchronising parallel composition of instances of generic modules (with internal and external labels. Pathways are then composed by (synchronising parallel composition and renaming; different types of cross-talk result from different combinations of synchronisation and renaming. We define a number of generic modules in PRISM and five types of cross-talk: signal flow, substrate availability, receptor function, gene expression and intracellular communication. We show that Continuous Stochastic Logic properties can both detect and distinguish the types of cross-talk. The approach is illustrated with small examples and an analysis of the cross-talk between the TGF-b/BMP, WNT and MAPK pathways.

Cascaded analysis of signal and noise propagation through a heterogeneous breast model

International Nuclear Information System (INIS)

Mainprize, James G.; Yaffe, Martin J.

2010-01-01

Purpose: The detectability of lesions in radiographic images can be impaired by patterns caused by the surrounding anatomic structures. The presence of such patterns is often referred to as anatomic noise. Others have previously extended signal and noise propagation theory to include variable background structure as an additional noise term and used in simulations for analysis by human and ideal observers. Here, the analytic forms of the signal and noise transfer are derived to obtain an exact expression for any input random distribution and the ''power law'' filter used to generate the texture of the tissue distribution. Methods: A cascaded analysis of propagation through a heterogeneous model is derived for x-ray projection through simulated heterogeneous backgrounds. This is achieved by considering transmission through the breast as a correlated amplification point process. The analytic forms of the cascaded analysis were compared to monoenergetic Monte Carlo simulations of x-ray propagation through power law structured backgrounds. Results: As expected, it was found that although the quantum noise power component scales linearly with the x-ray signal, the anatomic noise will scale with the square of the x-ray signal. There was a good agreement between results obtained using analytic expressions for the noise power and those from Monte Carlo simulations for different background textures, random input functions, and x-ray fluence. Conclusions: Analytic equations for the signal and noise properties of heterogeneous backgrounds were derived. These may be used in direct analysis or as a tool to validate simulations in evaluating detectability.

Paradoxical Regulation of Human FGF21 by Both Fasting and Feeding Signals: Is FGF21 a Nutritional Adaptation Factor?

Science.gov (United States)

Uebanso, Takashi; Taketani, Yutaka; Yamamoto, Hironori; Amo, Kikuko; Ominami, Hirokazu; Arai, Hidekazu; Takei, Yuichiro; Masuda, Masashi; Tanimura, Ayako; Harada, Nagakatsu; Yamanaka-Okumura, Hisami; Takeda, Eiji

2011-01-01

Fibroblast growth factor 21 (FGF21) has recently emerged as a metabolic hormone involved in regulating glucose and lipid metabolism in mouse, but the regulatory mechanisms and actions of FGF21 in humans remain unclear. Here we have investigated the regulatory mechanisms of the human FGF21 gene at the transcriptional level. A deletion study of the human FGF21 promoter (−1672 to +230 bp) revealed two fasting signals, including peroxisome proliferator-activated receptor α (PPARα) and glucagon signals, that independently induced human FGF21 gene transcription in mouse primary hepatocytes. In addition, two feeding signals, glucose and xylitol, also dose-dependently induced human FGF21 gene transcription and mRNA expression in both human HepG2 cells and mouse primary hepatocytes. FGF21 protein expression and secretion were also induced by high glucose stimulation. The human FGF21 promoter (−1672 to +230 bp) was found to have a carbohydrate-responsive element at −380 to −366 bp, which is distinct from the PPAR response element (PPRE). Knock-down of the carbohydrate response element binding protein by RNAi diminished glucose-induced human FGF21 transcription. Moreover, we found that a region from −555 to −443 bp of the human FGF21 promoter region exerts an important role in the activation of basic transcription. In conclusion, human FGF21 gene expression is paradoxically and independently regulated by both fasting and feeding signals. These regulatory mechanisms suggest that human FGF21 is increased with nutritional crisis, including starvation and overfeeding. PMID:21829679

Polycystins, calcium signaling, and human diseases

International Nuclear Information System (INIS)

Delmas, Patrick; Padilla, Francoise; Osorio, Nancy; Coste, Bertrand; Raoux, Matthieu; Crest, Marcel

2004-01-01

Autosomal dominant polycystic kidney disease (ADPKD) is a major, inherited nephropathy affecting over 1:1000 of the worldwide population. It is a systemic condition with frequent hepatic and cardiovascular manifestations in addition to the progressive development of fluid-filled cysts from the tubules and collecting ducts of affected kidneys. The pathogenesis of cyst formation is currently thought to involve increased proliferation of epithelial cells, mild dedifferentiation, and fluid accumulation. In the past decade, study of ADPKD led to the discovery of a unique family of highly complex proteins, the polycystins. Loss-of-function mutations in either of two polycystin proteins, polycystin-1 or polycystin-2, give rise to ADPKD. These proteins are thought to function together as part of a multiprotein complex that may initiate Ca 2+ signals, directing attention to the regulation of intracellular Ca 2+ as a possible misstep that participates in cyst formation. Here we review what is known about the Ca 2+ signaling functions of polycystin proteins and focus on findings that have significantly advanced our physiological insight. Special attention is paid to the recently discovered role of these proteins in the mechanotransduction of the renal primary cilium and the model it suggests

A DESIGN FRAMEWORK FOR HUMAN EMOTION RECOGNITION USING ELECTROCARDIOGRAM AND SKIN CONDUCTANCE RESPONSE SIGNALS

Directory of Open Access Journals (Sweden)

KHAIRUN NISA’ MINHAD

2017-11-01

Full Text Available Identification of human emotional state while driving a vehicle can help in understanding the human behaviour. Based on this identification, a response system can be developed in order to mitigate the impact that may be resulted from the behavioural changes. However, the adaptation of emotions to the environment at most scenarios is subjective to an individual’s perspective. Many factors, mainly cultural and geography, gender, age, life style and history, level of education and professional status, can affect the detection of human emotional affective states. This work investigated sympathetic responses toward human emotions defined by using electrocardiography (ECG and skin conductance response (SCR signals recorded simultaneously. This work aimed to recognize ECG and SCR patterns of the investigated emotions measured using selected sensor. A pilot study was conducted to evaluate the proposed framework. Initial results demonstrated the importance of suitability of the stimuli used to evoke the emotions and high opportunity for the ECG and SCR signals to be used in the automotive real-time emotion recognition systems.

Sequential Markov chain Monte Carlo filter with simultaneous model selection for electrocardiogram signal modeling.

Science.gov (United States)

Edla, Shwetha; Kovvali, Narayan; Papandreou-Suppappola, Antonia

2012-01-01

Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can be used for automated disease classification, is of great importance in precluding manual annotation and providing prompt diagnosis of cardiac diseases. ECG signals consist of several segments with different morphologies (namely the P wave, QRS complex and the T wave) in a single heart beat, which can vary across individuals and diseases. Also, existing statistical ECG models exhibit a reliance upon obtaining a priori information from the ECG data by using preprocessing algorithms to initialize the filter parameters, or to define the user-specified model parameters. In this paper, we propose an ECG modeling technique using the sequential Markov chain Monte Carlo (SMCMC) filter that can perform simultaneous model selection, by adaptively choosing from different representations depending upon the nature of the data. Our results demonstrate the ability of the algorithm to track various types of ECG morphologies, including intermittently occurring ECG beats. In addition, we use the estimated model parameters as the feature set to classify between ECG signals with normal sinus rhythm and four different types of arrhythmia.

[Design of High Frequency Signal Detecting Circuit of Human Body Impedance Used for Ultrashort Wave Diathermy Apparatus].

Science.gov (United States)

Fan, Xu; Wang, Yunguang; Cheng, Haiping; Chong, Xiaochen

2016-02-01

The present circuit was designed to apply to human tissue impedance tuning and matching device in ultra-short wave treatment equipment. In order to judge if the optimum status of circuit parameter between energy emitter circuit and accepter circuit is in well syntony, we designed a high frequency envelope detect circuit to coordinate with automatic adjust device of accepter circuit, which would achieve the function of human tissue impedance matching and tuning. Using the sampling coil to receive the signal of amplitude-modulated wave, we compared the voltage signal of envelope detect circuit with electric current of energy emitter circuit. The result of experimental study was that the signal, which was transformed by the envelope detect circuit, was stable and could be recognized by low speed Analog to Digital Converter (ADC) and was proportional to the electric current signal of energy emitter circuit. It could be concluded that the voltage, transformed by envelope detect circuit can mirror the real circuit state of syntony and realize the function of human tissue impedance collecting.

Mesenchymal Wnt/β-catenin signaling limits tooth number.

Science.gov (United States)

Järvinen, Elina; Shimomura-Kuroki, Junko; Balic, Anamaria; Jussila, Maria; Thesleff, Irma

2018-02-21

Tooth agenesis is one of the predominant developmental anomalies in humans, usually affecting the permanent dentition generated by sequential tooth formation and, in most cases, caused by mutations perturbing epithelial Wnt/β-catenin signaling. In addition, loss-of-function mutations in the Wnt feedback inhibitor AXIN2 lead to human tooth agenesis. We have investigated the functions of Wnt/β-catenin signaling during sequential formation of molar teeth using mouse models. Continuous initiation of new teeth, which is observed after genetic activation of Wnt/β-catenin signaling in the oral epithelium, was accompanied by enhanced expression of Wnt antagonists and a downregulation of Wnt/β-catenin signaling in the dental mesenchyme. Genetic and pharmacological activation of mesenchymal Wnt/β-catenin signaling negatively regulated sequential tooth formation, an effect partly mediated by Bmp4. Runx2 , a gene whose loss-of-function mutations result in sequential formation of supernumerary teeth in the human cleidocranial dysplasia syndrome, suppressed the expression of Wnt inhibitors Axin2 and Drapc1 in dental mesenchyme. Our data indicate that increased mesenchymal Wnt signaling inhibits the sequential formation of teeth, and suggest that Axin2 / Runx2 antagonistic interactions modulate the level of mesenchymal Wnt/β-catenin signaling, underlying the contrasting dental phenotypes caused by human AXIN2 and RUNX2 mutations. © 2018. Published by The Company of Biologists Ltd.

Imaging of endogenous exchangeable proton signals in the human brain using frequency labeled exchange transfer imaging.

Science.gov (United States)

Yadav, Nirbhay N; Jones, Craig K; Hua, Jun; Xu, Jiadi; van Zijl, Peter C M

2013-04-01

To image endogenous exchangeable proton signals in the human brain using a recently reported method called frequency labeled exchange transfer (FLEX) MRI. As opposed to labeling exchangeable protons using saturation (i.e., chemical exchange saturation transfer, or CEST), FLEX labels exchangeable protons with their chemical shift evolution. The use of short high-power frequency pulses allows more efficient labeling of rapidly exchanging protons, while time domain acquisition allows removal of contamination from semi-solid magnetization transfer effects. FLEX-based exchangeable proton signals were detected in human brain over the 1-5 ppm frequency range from water. Conventional magnetization transfer contrast and the bulk water signal did not interfere in the FLEX spectrum. The information content of these signals differed from in vivo CEST data in that the average exchange rate of these signals was 350-400 s(-1) , much faster than the amide signal usually detected using direct saturation (∼30 s(-1) ). Similarly, fast exchanging protons could be detected in egg white in the same frequency range where amide and amine protons of mobile proteins and peptides are known to resonate. FLEX MRI in the human brain preferentially detects more rapidly exchanging amide/amine protons compared to traditional CEST experiments, thereby changing the information content of the exchangeable proton spectrum. This has the potential to open up different types of endogenous applications as well as more easy detection of rapidly exchanging protons in diaCEST agents or fast exchanging units such as water molecules in paracest agents without interference of conventional magnetization transfer contrast. Copyright © 2013 Wiley Periodicals, Inc.

Experimental investigation of the cytotoxicity of medium-borne signals in human prostate cancer cell line

International Nuclear Information System (INIS)

Sjostedt, Svetlana; Bezak, Eva

2012-01-01

Introduction. Evidence exists that exposure of non-irradiated cells to Irradiated Cell Conditioned Medium (ICCM) can cause effects similar to those resulting from direct radiation damage. This study attempts to validate the stochastic model, relating absorbed dose to the emission and processing of cell death signals by non-irradiated cells, in vitro in PC3 human prostate cancer cell line. Methods. The recipient cell survival was measured after exposure of cells to ICMM derived from donor cells: a) exposed to radiation doses from 2 Gy to 8 Gy and b) of concentrations varying from 2 x 10 2 to 6 x 10 6 irradiated with 2 Gy. Results. Exposure to ICCM, irradiated with doses between 2-8 Gy, resulted in a significant (p 2 cells was significantly higher (p < 0.5) compared to the rest of donor cell concentrations, indicating that the toxicity of ICCM depends on the cellular concentration of donor cells. Non-linear regression data fitting provided reasonable agreement with the microdosimetric model for the induction of cell killing through medium-borne signals. Conclusion. For the given cell line and given experimental conditions, significant decreases in cell survival were observed in non-irradiated cells exposed to ICCM derived from donor cells of various concentrations and irradiated with different doses

Reproductive physiology of a humanized GnRH receptor mouse model: application in evaluation of human-specific analogs.

Science.gov (United States)

Tello, Javier A; Kohout, Trudy; Pineda, Rafael; Maki, Richard A; Scott Struthers, R; Millar, Robert P

2013-07-01

The human GnRH receptor (GNRHR1) has a specific set of properties with physiological and pharmacological influences not appropriately modeled in laboratory animals or cell-based systems. To address this deficiency, we have generated human GNRHR1 knock-in mice and described their reproductive phenotype. Measurement of pituitary GNRHR1 transcripts from homozygous human GNRHR1 knock-in (ki/ki) mice revealed a severe reduction (7- to 8-fold) compared with the mouse Gnrhr1 in wild-type mice. ¹²⁵I-GnRH binding assays on pituitary membrane fractions corroborated reduced human GNRHR1 protein expression in ki/ki mice, as occurs with transfection of human GNRHR1 in cell lines. Female homozygous knock-in mice displayed normal pubertal onset, indicating that a large reduction in GNRHR1 expression is sufficient for this process. However, ki/ki females exhibited periods of prolonged estrous and/or metestrous and reduced fertility. No impairment was found in reproductive maturity or adult fertility in male ki/ki mice. Interestingly, the serum LH response to GnRH challenge was reduced in both knock-in males and females, indicating a reduced GNRHR1 signaling capacity. Small molecules targeting human GPCRs usually have poor activities at homologous rodent receptors, thus limiting their use in preclinical development. Therefore, we tested a human-specific GnRH1 antagonist, NBI-42902, in our mouse model and demonstrated abrogation of a GnRH1-induced serum LH rise in ki/ki mice and an absence of effect in littermates expressing the wild-type murine receptor. This novel model provides the opportunity to study the human receptor in vivo and for screening the activity of human-specific GnRH analogs.

Generating Human-Like Velocity-Adapted Jumping Gait from sEMG Signals for Bionic Leg’s Control

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Weiwei Yu

2017-01-01

Full Text Available In the case of dynamic motion such as jumping, an important fact in sEMG (surface Electromyogram signal based control on exoskeletons, myoelectric prostheses, and rehabilitation gait is that multichannel sEMG signals contain mass data and vary greatly with time, which makes it difficult to generate compliant gait. Inspired by the fact that muscle synergies leading to dimensionality reduction may simplify motor control and learning, this paper proposes a new approach to generate flexible gait based on muscle synergies extracted from sEMG signal. Two questions were discussed and solved, the first one concerning whether the same set of muscle synergies can explain the different phases of hopping movement with various velocities. The second one is about how to generate self-adapted gait with muscle synergies while alleviating model sensitivity to sEMG transient changes. From the experimental results, the proposed method shows good performance both in accuracy and in robustness for producing velocity-adapted vertical jumping gait. The method discussed in this paper provides a valuable reference for the sEMG-based control of bionic robot leg to generate human-like dynamic gait.

CRH promotes human colon cancer cell proliferation via IL-6/JAK2/STAT3 signaling pathway and VEGF-induced tumor angiogenesis.

Science.gov (United States)

Fang, Xianjun; Hong, Yali; Dai, Li; Qian, Yuanyuan; Zhu, Chao; Wu, Biao; Li, Shengnan

2017-11-01

Corticotrophin-releasing hormone (CRH) has been demonstrated to participate in various diseases. Our previous study showed that its receptor CRHR1 mediated the development of colitis-associated cancer in mouse model. However, the detailed mechanisms remain unclear. In this study, we explored the oncogenetic role of CRH/CRHR1 signaling in colon cancer cells. Cell proliferation and colony formation assays revealed that CRH contributed to cell proliferation. Moreover, tube formation assay showed that CRH-treated colon cancer cell supernatant significantly promoted tube formation of human umbilical vein endothelial cells (HUVECs). And these effects could be reversed by the CRHR1 specific antagonist Antalarmin. Further investigation showed that CRH significantly upregulated the expressions of interlukin-6 (IL-6) and vascular endothelial growth factor (VEGF) through activating nuclear factor-kappa B (NF-κB). The CRH-induced IL-6 promoted phosphorylation of janus kinase 2 (JAK2) and signal transducers and activators of transcription 3 (STAT3). STAT3 inhibition by Stattic significantly inhibited the CRH-induced cell proliferation. In addition, silence of VEGF resulted in declined tube formation induced by CRH. Taken together, CRH/CRHR1 signaling promoted human colon cancer cell proliferation via NF-κB/IL-6/JAK2/STAT3 signaling pathway and tumor angiogenesis via NF-κB/VEGF signaling pathway. Our results provide evidence to support a critical role for the CRH/CRHR1 signaling in colon cancer progression and suggest its potential utility as a new therapeutic target for colon cancer. © 2017 Wiley Periodicals, Inc.

Wavelet modeling of signals for non-destructive testing of concretes

International Nuclear Information System (INIS)

Shao, Zhixue; Shi, Lihua; Cai, Jian

2011-01-01

In a non-destructive test of concrete structures, ultrasonic pulses are commonly used to detect damage or embedded objects from their reflections. A wavelet modeling method is proposed here to identify the main reflections and to remove the interferences in the detected ultrasonic waves. This method assumes that if the structure is stimulated by a wavelet function with good time–frequency localization ability, the detected signal is a combination of time-delayed and amplitude-attenuated wavelets. Therefore, modeling of the detected signal by wavelets can give a straightforward and simple model of the original signal. The central time and amplitude of each wavelet represent the position and amplitude of the reflections in the detected structure. A signal processing method is also proposed to estimate the structure response to wavelet excitation from its response to a high-voltage pulse with a sharp leading edge. A signal generation card with a compact peripheral component interconnect extension for instrumentation interface is designed to produce this high-voltage pulse. The proposed method is applied to synthesized aperture focusing technology of concrete specimens and the image results are provided

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

Science.gov (United States)

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

2015-04-29

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

Validation of Nonlinear Bipolar Transistor Model by Small-Signal Measurements

DEFF Research Database (Denmark)

Vidkjær, Jens; Porra, V.; Zhu, J.

1992-01-01

A new method for the validity analysis of nonlinear transistor models is presented based on DC-and small-signal S-parameter measurements and realistic consideration of the measurement and de-embedding errors and singularities of the small-signal equivalent circuit. As an example, some analysis...... results for an extended Gummel Poon model are presented in the case of a UHF bipolar power transistor....

The actions of exogenous leucine on mTOR signalling and amino acid transporters in human myotubes

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Cameron-Smith David

2011-06-01

Full Text Available Abstract Background The branched-chain amino acid (BCAA leucine has been identified to be a key regulator of skeletal muscle anabolism. Activation of anabolic signalling occurs via the mammalian target of rapamycin (mTOR through an undefined mechanism. System A and L solute carriers transport essential amino acids across plasma membranes; however it remains unknown whether an exogenous supply of leucine regulates their gene expression. The aim of the present study was to investigate the effects of acute and chronic leucine stimulation of anabolic signalling and specific amino acid transporters, using cultured primary human skeletal muscle cells. Results Human myotubes were treated with leucine, insulin or co-treated with leucine and insulin for 30 min, 3 h or 24 h. Activation of mTOR signalling kinases were examined, together with putative nutrient sensor human vacuolar protein sorting 34 (hVps34 and gene expression of selected amino acid transporters. Phosphorylation of mTOR and p70S6K was transiently increased following leucine exposure, independently to insulin. hVps34 protein expression was also significantly increased. However, genes encoding amino acid transporters were differentially regulated by insulin and not leucine. Conclusions mTOR signalling is transiently activated by leucine within human myotubes independently of insulin stimulation. While this occurred in the absence of changes in gene expression of amino acid transporters, protein expression of hVps34 increased.

A stable and reproducible human blood-brain barrier model derived from hematopoietic stem cells.

Directory of Open Access Journals (Sweden)

Romeo Cecchelli

Full Text Available The human blood brain barrier (BBB is a selective barrier formed by human brain endothelial cells (hBECs, which is important to ensure adequate neuronal function and protect the central nervous system (CNS from disease. The development of human in vitro BBB models is thus of utmost importance for drug discovery programs related to CNS diseases. Here, we describe a method to generate a human BBB model using cord blood-derived hematopoietic stem cells. The cells were initially differentiated into ECs followed by the induction of BBB properties by co-culture with pericytes. The brain-like endothelial cells (BLECs express tight junctions and transporters typically observed in brain endothelium and maintain expression of most in vivo BBB properties for at least 20 days. The model is very reproducible since it can be generated from stem cells isolated from different donors and in different laboratories, and could be used to predict CNS distribution of compounds in human. Finally, we provide evidence that Wnt/β-catenin signaling pathway mediates in part the BBB inductive properties of pericytes.

THE SIGNAL APPROACH TO MODELLING THE BALANCE OF PAYMENT CRISIS

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O. Chernyak

2016-12-01

Full Text Available The paper considers and presents synthesis of theoretical models of balance of payment crisis and investigates the most effective ways to model the crisis in Ukraine. For mathematical formalization of balance of payment crisis, comparative analysis of the effectiveness of different calculation methods of Exchange Market Pressure Index was performed. A set of indicators that signal the growing likelihood of balance of payments crisis was defined using signal approach. With the help of minimization function thresholds indicators were selected, the crossing of which signalize increase in the probability of balance of payment crisis.

Human Thermal Model Evaluation Using the JSC Human Thermal Database

Science.gov (United States)

Bue, Grant; Makinen, Janice; Cognata, Thomas

2012-01-01

Human thermal modeling has considerable long term utility to human space flight. Such models provide a tool to predict crew survivability in support of vehicle design and to evaluate crew response in untested space environments. It is to the benefit of any such model not only to collect relevant experimental data to correlate it against, but also to maintain an experimental standard or benchmark for future development in a readily and rapidly searchable and software accessible format. The Human thermal database project is intended to do just so; to collect relevant data from literature and experimentation and to store the data in a database structure for immediate and future use as a benchmark to judge human thermal models against, in identifying model strengths and weakness, to support model development and improve correlation, and to statistically quantify a model s predictive quality. The human thermal database developed at the Johnson Space Center (JSC) is intended to evaluate a set of widely used human thermal models. This set includes the Wissler human thermal model, a model that has been widely used to predict the human thermoregulatory response to a variety of cold and hot environments. These models are statistically compared to the current database, which contains experiments of human subjects primarily in air from a literature survey ranging between 1953 and 2004 and from a suited experiment recently performed by the authors, for a quantitative study of relative strength and predictive quality of the models.

Gap Acceptance Behavior Model for Non-signalized

OpenAIRE

Fajaruddin Bin Mustakim

2015-01-01

The paper proposes field studies that were performed to determine the critical gap on the multiple rural roadways Malaysia, at non-signalized T-intersection by using The Raff and Logic Method. Critical gap between passenger car and motorcycle have been determined.   There are quite number of studied doing gap acceptance behavior model for passenger car however still few research on gap acceptance behavior model for motorcycle. Thus in this paper, logistic regression models were developed to p...

Human CD180 Transmits Signals via the PIM-1L Kinase.

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Nicole Egli

Full Text Available Toll-like receptors (TLRs are important sensors of the innate immune system that recognize conserved structural motifs and activate cells via a downstream signaling cascade. The CD180/MD1 molecular complex is an unusual member of the TLR family, since it lacks the components that are normally required for signal transduction by other TLRs. Therefore the CD180/MD 1 complex has been considered of being incapable of independently initiating cellular signals. Using chemogenetic approaches we identified specifically the membrane bound long form of PIM-1 kinase, PIM-1L as the mediator of CD180-dependent signaling. A dominant negative isoform of PIM-1L, but not of other PIM kinases, inhibited signaling elicited by cross-linking of CD180, and this effect was phenocopied by PIM inhibitors. PIM-1L was directed to the cell membrane by its N-terminal extension, where it colocalized and physically associated with CD180. Triggering CD180 also induced increased phosphorylation of the anti-apoptotic protein BAD in a PIM kinase-dependent fashion. Also in primary human B cells, which are the main cells expressing CD180 in man, cross-linking of CD180 by monoclonal antibodies stimulated cell survival and proliferation that was abrogated by specific inhibitors. By associating with PIM-1L, CD180 can thus obtain autonomous signaling capabilities, and this complex is then channeling inflammatory signals into B cell survival programs. Pharmacological inhibition of PIM-1 should therefore provide novel therapeutic options in diseases that respond to innate immune stimulation with subsequently increased B cell activity, such as lupus erythematosus or myasthenia gravis.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

Science.gov (United States)

Poplová, Michaela; Sovka, Pavel; Cifra, Michal

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Perkins, Timothy N.; Dentener, Mieke A. [Department of Respiratory Medicine, Maastricht University Medical Centre +, Maastricht University Maastricht (Netherlands); Stassen, Frank R. [Department of Medical Microbiology, Maastricht University Medical Centre +, Maastricht University Maastricht (Netherlands); Rohde, Gernot G. [Department of Respiratory Medicine, Maastricht University Medical Centre +, Maastricht University Maastricht (Netherlands); Mossman, Brooke T. [Department of Pathology, University of Vermont College of Medicine, Burlington, VT (United States); Wouters, Emiel F.M. [Department of Respiratory Medicine, Maastricht University Medical Centre +, Maastricht University Maastricht (Netherlands); Reynaert, Niki L., E-mail: n.reynaert@maastrichtuniversity.nl [Department of Respiratory Medicine, Maastricht University Medical Centre +, Maastricht University Maastricht (Netherlands)

2016-06-15

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

Nitric Oxide Mediates Crosstalk between Interleukin 1β and WNT Signaling in Primary Human Chondrocytes by Reducing DKK1 and FRZB Expression.

Science.gov (United States)

Zhong, Leilei; Schivo, Stefano; Huang, Xiaobin; Leijten, Jeroen; Karperien, Marcel; Post, Janine N

2017-11-22

Interleukin 1 beta (IL1β) and Wingless-Type MMTV Integration Site Family (WNT) signaling are major players in Osteoarthritis (OA) pathogenesis. Despite having a large functional overlap in OA onset and development, the mechanism of IL1β and WNT crosstalk has remained largely unknown. In this study, we have used a combination of computational modeling and molecular biology to reveal direct or indirect crosstalk between these pathways. Specifically, we revealed a mechanism by which IL1β upregulates WNT signaling via downregulating WNT antagonists, DKK1 and FRZB. In human chondrocytes, IL1β decreased the expression of Dickkopf-1 (DKK1) and Frizzled related protein (FRZB) through upregulation of nitric oxide synthase (iNOS), thereby activating the transcription of WNT target genes. This effect could be reversed by iNOS inhibitor 1400W, which restored DKK1 and FRZB expression and their inhibitory effect on WNT signaling. In addition, 1400W also inhibited both the matrix metalloproteinase (MMP) expression and cytokine-induced apoptosis. We concluded that iNOS/NO play a pivotal role in the inflammatory response of human OA through indirect upregulation of WNT signaling. Blocking NO production may inhibit the loss of the articular phenotype in OA by preventing downregulation of the expression of DKK1 and FRZB.

A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

Science.gov (United States)

Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

2017-11-01

Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this

Human Performance Modeling for Dynamic Human Reliability Analysis

Energy Technology Data Exchange (ETDEWEB)

Boring, Ronald Laurids [Idaho National Laboratory; Joe, Jeffrey Clark [Idaho National Laboratory; Mandelli, Diego [Idaho National Laboratory

2015-08-01

Part of the U.S. Department of Energy’s (DOE’s) Light Water Reac- tor Sustainability (LWRS) Program, the Risk-Informed Safety Margin Charac- terization (RISMC) Pathway develops approaches to estimating and managing safety margins. RISMC simulations pair deterministic plant physics models with probabilistic risk models. As human interactions are an essential element of plant risk, it is necessary to integrate human actions into the RISMC risk framework. In this paper, we review simulation based and non simulation based human reliability analysis (HRA) methods. This paper summarizes the founda- tional information needed to develop a feasible approach to modeling human in- teractions in RISMC simulations.

Small-signal model for the series resonant converter

Science.gov (United States)

King, R. J.; Stuart, T. A.

1985-01-01

The results of a previous discrete-time model of the series resonant dc-dc converter are reviewed and from these a small signal dynamic model is derived. This model is valid for low frequencies and is based on the modulation of the diode conduction angle for control. The basic converter is modeled separately from its output filter to facilitate the use of these results for design purposes. Experimental results are presented.

Modeling off-frequency binaural masking for short- and long-duration signals.

Science.gov (United States)

Nitschmann, Marc; Yasin, Ifat; Henning, G Bruce; Verhey, Jesko L

2017-08-01

Experimental binaural masking-pattern data are presented together with model simulations for 12- and 600-ms signals. The masker was a diotic 11-Hz wide noise centered on 500 Hz. The tonal signal was presented either diotically or dichotically (180° interaural phase difference) with frequencies ranging from 400 to 600 Hz. The results and the modeling agree with previous data and hypotheses; simulations with a binaural model sensitive to monaural modulation cues show that the effect of duration on off-frequency binaural masking-level differences is mainly a result of modulation cues which are only available in the monaural detection of long signals.

RAS signaling and anti-RAS therapy: lessons learned from genetically engineered mouse models, human cancer cells, and patient-related studies.

Science.gov (United States)

Fang, Bingliang

2016-01-01

Activating mutations of oncogenic RAS genes are frequently detected in human cancers. The studies in genetically engineered mouse models (GEMMs) reveal that Kras-activating mutations predispose mice to early onset tumors in the lung, pancreas, and gastrointestinal tract. Nevertheless, most of these tumors do not have metastatic phenotypes. Metastasis occurs when tumors acquire additional genetic changes in other cancer driver genes. Studies on clinical specimens also demonstrated that KRAS mutations are present in premalignant tissues and that most of KRAS mutant human cancers have co-mutations in other cancer driver genes, including TP53, STK11, CDKN2A, and KMT2C in lung cancer; APC, TP53, and PIK3CA in colon cancer; and TP53, CDKN2A, SMAD4, and MED12 in pancreatic cancer. Extensive efforts have been devoted to develop therapeutic agents that target enzymes involved in RAS posttranslational modifications, that inhibit downstream effectors of RAS signaling pathways, and that kill RAS mutant cancer cells through synthetic lethality. Recent clinical studies have revealed that sorafenib, a pan-RAF and VEGFR inhibitor, has impressive benefits for KRAS mutant lung cancer patients. Combination therapy of MEK inhibitors with either docetaxel, AKT inhibitors, or PI3K inhibitors also led to improved clinical responses in some KRAS mutant cancer patients. This review discusses knowledge gained from GEMMs, human cancer cells, and patient-related studies on RAS-mediated tumorigenesis and anti-RAS therapy. Emerging evidence demonstrates that RAS mutant cancers are heterogeneous because of the presence of different mutant alleles and/or co-mutations in other cancer driver genes. Effective subclassifications of RAS mutant cancers may be necessary to improve patients' outcomes through personalized precision medicine. © The Author 2015. Published by ABBS Editorial Office in association with Oxford University Press on behalf of the Institute of Biochemistry and Cell Biology

ERK1/2 activation in human taste bud cells regulates fatty acid signaling and gustatory perception of fat in mice and humans.

Science.gov (United States)

Subramaniam, Selvakumar; Ozdener, Mehmet Hakan; Abdoul-Azize, Souleymane; Saito, Katsuyoshi; Malik, Bilal; Maquart, Guillaume; Hashimoto, Toshihiro; Marambaud, Philippe; Aribi, Mourad; Tordoff, Michael G; Besnard, Philippe; Khan, Naim Akhtar

2016-10-01

Obesity is a major public health problem. An in-depth knowledge of the molecular mechanisms of oro-sensory detection of dietary lipids may help fight it. Humans and rodents can detect fatty acids via lipido-receptors, such as CD36 and GPR120. We studied the implication of the MAPK pathways, in particular, ERK1/2, in the gustatory detection of fatty acids. Linoleic acid, a dietary fatty acid, induced via CD36 the phosphorylation of MEK1/2-ERK1/2-ETS-like transcription factor-1 cascade, which requires Fyn-Src kinase and lipid rafts in human taste bud cells (TBCs). ERK1/2 cascade was activated by Ca 2+ signaling via opening of the calcium-homeostasis modulator-1 (CALHM1) channel. Furthermore, fatty acid-evoked Ca 2+ signaling and ERK1/2 phosphorylation were decreased in both human TBCs after small interfering RNA knockdown of CALHM1 channel and in TBCs from Calhm1 -/- mice. Targeted knockdown of ERK1/2 by small interfering RNA or PD0325901 (MEK1/2 inhibitor) in the tongue and genetic ablation of Erk1 or Calhm1 genes impaired preference for dietary fat in mice. Lingual inhibition of ERK1/2 in healthy volunteers also decreased orogustatory sensitivity for linoleic acid. Our data demonstrate that ERK1/2-MAPK cascade is regulated by the opening of CALHM1 Ca 2+ channel in TBCs to modulate orogustatory detection of dietary lipids in mice and humans.-Subramaniam, S., Ozdener, M. H., Abdoul-Azize, S., Saito, K., Malik, B., Maquart, G., Hashimoto, T., Marambaud, P., Aribi, M., Tordoff, M. G., Besnard, P., Khan, N. A. ERK1/2 activation in human taste bud cells regulates fatty acid signaling and gustatory perception of fat in mice and humans. © FASEB.

Salinomycin inhibits metastatic colorectal cancer growth and interferes with Wnt/β-catenin signaling in CD133+ human colorectal cancer cells

International Nuclear Information System (INIS)

Klose, Johannes; Eissele, Jana; Volz, Claudia; Schmitt, Steffen; Ritter, Alina; Ying, Shen; Schmidt, Thomas; Heger, Ulrike; Schneider, Martin; Ulrich, Alexis

2016-01-01

The polyether antibiotic Salinomycin (Sal) is regarded as an inhibitor of cancer stem cells. Its effectiveness on human colorectal cancer (CRC) cells in vitro has been demonstrated before. The aim of this study was to establish a murine model to investigate the effectiveness of Sal in vivo. Furthermore, we investigated the impact of Sal on Wnt/β-catenin signaling in human CD133 + CRC cells. The two murine CRC cell lines MC38 and CT26 were used to analyze the impact of Sal on tumor cell proliferation, viability, migration, cell cycle progression and cell death in vitro. For in vivo studies, CT26 cells were injected into syngeneic BALB/c mice to initiate (i) subcutaneous, (ii) orthotopic, or (iii) metastatic CRC growth. Sal was administered daily, 5-Fluoruracil served as a control. For mechanistic studies, the CD133 + and CD133 - subpopulations of human CRC cells were separated by flow cytometry and separately exposed to increasing concentrations of Sal. The impact on Wnt/β-catenin signaling was determined by Western blotting and quantitative PCR. Sal markedly impaired tumor cell viability, proliferation and migration, and induced necrotic cell death in vitro. CRC growth in vivo was likewise inhibited upon Sal treatment. Interference with Wnt signaling and reduced expression of the Wnt target genes Fibronectin and Lgr5 indicates a novel molecular mechanism, mediating anti-tumoral effects of Sal in CRC. Sal effectively impairs CRC growth in vivo. Furthermore, Sal acts as an inhibitor of Wnt/β-catenin signaling. Thus, Salinomycin represents a promising candidate for clinical CRC treatment. The online version of this article (doi:10.1186/s12885-016-2879-8) contains supplementary material, which is available to authorized users

Humanized mouse models: Application to human diseases.

Science.gov (United States)

Ito, Ryoji; Takahashi, Takeshi; Ito, Mamoru

2018-05-01

Humanized mice are superior to rodents for preclinical evaluation of the efficacy and safety of drug candidates using human cells or tissues. During the past decade, humanized mouse technology has been greatly advanced by the establishment of novel platforms of genetically modified immunodeficient mice. Several human diseases can be recapitulated using humanized mice due to the improved engraftment and differentiation capacity of human cells or tissues. In this review, we discuss current advanced humanized mouse models that recapitulate human diseases including cancer, allergy, and graft-versus-host disease. © 2017 Wiley Periodicals, Inc.

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.

Science.gov (United States)

Wu, Hau-Tieng; Wu, Han-Kuei; Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features.

A central role for TOR signalling in a yeast model for juvenile CLN3 disease

Directory of Open Access Journals (Sweden)

Michael E. Bond

2015-11-01

Full Text Available Yeasts provide an excellent genetically tractable eukaryotic system for investigating the function of genes in their biological context, and are especially relevant for those conserved genes that cause disease. We study the role of btn1, the orthologue of a human gene that underlies an early onset neurodegenerative disease (juvenile CLN3 disease, neuronal ceroid lipofuscinosis (NCLs or Batten disease in the fission yeast Schizosaccharomyces pombe. A global screen for genetic interactions with btn1 highlighted a conserved key signalling hub in which multiple components functionally relate to this conserved disease gene. This signalling hub includes two major mitogen-activated protein kinase (MAPK cascades, and centers on the Tor kinase complexes TORC1 and TORC2. We confirmed that yeast cells modelling CLN3 disease exhibit features consistent with dysfunction in the TORC pathways, and showed that modulating TORC function leads to a comprehensive rescue of defects in this yeast disease model. The same pathways may be novel targets in the development of therapies for the NCLs and related diseases.

An accurate and simple large signal model of HEMT

DEFF Research Database (Denmark)

Liu, Qing

1989-01-01

A large-signal model of discrete HEMTs (high-electron-mobility transistors) has been developed. It is simple and suitable for SPICE simulation of hybrid digital ICs. The model parameters are extracted by using computer programs and data provided by the manufacturer. Based on this model, a hybrid...

Notch signaling activation in human embryonic stem cells is required for embryonic but not trophoblastic lineage commitment

OpenAIRE

Yu, Xiaobing; Zou, Jizhong; Ye, Zhaohui; Hammond, Holly; Chen, Guibin; Tokunaga, Akinori; Mali, Prashant; Li, Yue-Ming; Civin, Curt; Gaiano, Nicholas; Cheng, Linzhao

2008-01-01

The Notch signaling pathway plays important roles in cell fate determination during embryonic development and adult life. In this study, we focus on the role of Notch signaling in governing cell fate choices in human embryonic stem (hES) cells. Using genetic and pharmacological approaches, we achieved both blockade and conditional activation of Notch signaling in several hES cell lines. We report here that activation of Notch signaling is required for undifferentiated hES cells to form the pr...

Electromagnetic modeling method for eddy current signal analysis

International Nuclear Information System (INIS)

Lee, D. H.; Jung, H. K.; Cheong, Y. M.; Lee, Y. S.; Huh, H.; Yang, D. J.

2004-10-01

An electromagnetic modeling method for eddy current signal analysis is necessary before an experiment is performed. Electromagnetic modeling methods consists of the analytical method and the numerical method. Also, the numerical methods can be divided by Finite Element Method(FEM), Boundary Element Method(BEM) and Volume Integral Method(VIM). Each modeling method has some merits and demerits. Therefore, the suitable modeling method can be chosen by considering the characteristics of each modeling. This report explains the principle and application of each modeling method and shows the comparison modeling programs

A model for generating Surface EMG signal of m. Tibialis Anterior.

Science.gov (United States)

Siddiqi, Ariba; Kumar, Dinesh; Arjunan, Sridhar P

2014-01-01

A model that simulates surface electromyogram (sEMG) signal of m. Tibialis Anterior has been developed and tested. This has a firing rate equation that is based on experimental findings. It also has a recruitment threshold that is based on observed statistical distribution. Importantly, it has considered both, slow and fast type which has been distinguished based on their conduction velocity. This model has assumed that the deeper unipennate half of the muscle does not contribute significantly to the potential induced on the surface of the muscle and has approximated the muscle to have parallel structure. The model was validated by comparing the simulated and the experimental sEMG signal recordings. Experiments were conducted on eight subjects who performed isometric dorsiflexion at 10, 20, 30, 50, 75, and 100% maximal voluntary contraction. Normalized root mean square and median frequency of the experimental and simulated EMG signal were computed and the slopes of the linearity with the force were statistically analyzed. The gradients were found to be similar (p>0.05) for both experimental and simulated sEMG signal, validating the proposed model.

Structure of human POFUT1, its requirement in ligand-independent oncogenic Notch signaling, and functional effects of Dowling-Degos mutations

Energy Technology Data Exchange (ETDEWEB)

McMillan, Brian J.; Zimmerman, Brandon; Egan, Emily D.; Lofgren, Michael; Xu, Xiang; Hesser, Anthony; Blacklow, Stephen C.

2017-03-17

Protein O-fucosyltransferase-1 (POFUT1), which transfers fucose residues to acceptor sites on serine and threonine residues of epidermal growth factor-like repeats of recipient proteins, is essential for Notch signal transduction in mammals. Here, we examine the consequences of POFUT1 loss on the oncogenic signaling associated with certain leukemia-associated mutations of human Notch1, report the structures of human POFUT1 in free and GDP-fucose bound states, and assess the effects of Dowling-Degos mutations on human POFUT1 function. CRISPR-mediated knockout of POFUT1 in U2OS cells suppresses both normal Notch1 signaling, and the ligand-independent signaling associated with leukemogenic mutations of Notch1. Normal and oncogenic signaling are rescued by wild-type POFUT1 but rescue is impaired by an active-site R240A mutation. The overall structure of the human enzyme closely resembles that of the Caenorhabditis elegans protein, with an overall backbone RMSD of 0.93 Å, despite primary sequence identity of only 39% in the mature protein. GDP-fucose binding to the human enzyme induces limited backbone conformational movement, though the side chains of R43 and D244 reorient to make direct contact with the fucose moiety in the complex. The reported Dowling-Degos mutations of POFUT1, except for M262T, fail to rescue Notch1 signaling efficiently in the CRISPR-engineered POFUT1^-/- background. Together, these studies identify POFUT1 as a potential target for cancers driven by Notch1 mutations and provide a structural roadmap for its inhibition.

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.

Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models.

Science.gov (United States)

Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei

2014-01-01

The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

Human engineering design considerations for the use of signal color enhancement in ASW displays

Energy Technology Data Exchange (ETDEWEB)

Banks, W.W.

1990-11-01

The Lawrence Livermore National Laboratory (LLNL) was requested to examine and define man-machine limits as part of the Office of Naval Technology's High Gain Initiative program (HGI). As an initial investigative area, LLNL's Systems and Human Performance effort focused upon color display interfaces and the use of color enhancement techniques to define human and system interface limits in signal detection and discrimination tasks. The knowledgeable and prudent use of color in different types of display is believed to facilitate human visual detection, discrimination and recognition in complex visual tasks. The consideration and understanding of the complex set of interacting variables associated with the prudent use of color is essential to optimize human performance, especially in the ASW community. The designers of advanced display technology and signal processing algorithms may be eventually called upon to present pre-processed information to ASW operators and researchers using the latest color enhancement techniques. These techniques, however, may be limited if one does not understand the complexity and limits of human information processing which reflects the assessed state of knowledge relevant to the use of color in displays. The initial sections of this report discuss various aspects of color presentation and the problems typically encountered, while the last section deals with a specific research proposal required to further our understanding and proper use of color enhancement methods.

Model of multicomponent micro-Doppler signal in environment MatLab

Directory of Open Access Journals (Sweden)

Kucheryavenko Alexander

2017-01-01

Full Text Available The article illustrates the problem of measuring the speed glider component targets in the presence of a turboprop effect of the reflected signal in a pulse-Doppler radar, proposed a model turboprop signal component and an algorithm for its suppression

Expression of insulin signalling components in the sensory epithelium of the human saccule

DEFF Research Database (Denmark)

Degerman, Eva; Rauch, Uwe; Lindberg, Sven

2013-01-01

signalling components in the inner ear is sparce. Our immunohistochemistry approach has shown that the insulin receptor, insulin receptor substrate 1 (IRS1), protein kinase B (PKB) and insulin-sensitive glucose transporter (GLUT4) are expressed in the sensory epithelium of the human saccule, which also...

An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification.

Science.gov (United States)

Li, Fangmin; Yang, Chao; Xia, Yuqing; Ma, Xiaolin; Zhang, Tao; Zhou, Zhou

2017-11-29

In this paper, we propose the multiwindow Adaptive S-method (AS-method) distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM) trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.

Experimental psychiatric illness and drug abuse models: from human to animal, an overview.

Science.gov (United States)

Edwards, Scott; Koob, George F

2012-01-01

Preclinical animal models have supported much of the recent rapid expansion of neuroscience research and have facilitated critical discoveries that undoubtedly benefit patients suffering from psychiatric disorders. This overview serves as an introduction for the following chapters describing both in vivo and in vitro preclinical models of psychiatric disease components and briefly describes models related to drug dependence and affective disorders. Although there are no perfect animal models of any psychiatric disorder, models do exist for many elements of each disease state or stage. In many cases, the development of certain models is essentially restricted to the human clinical laboratory domain for the purpose of maximizing validity, whereas the use of in vitro models may best represent an adjunctive, well-controlled means to model specific signaling mechanisms associated with psychiatric disease states. The data generated by preclinical models are only as valid as the model itself, and the development and refinement of animal models for human psychiatric disorders continues to be an important challenge. Collaborative relationships between basic neuroscience and clinical modeling could greatly benefit the development of new and better models, in addition to facilitating medications development.

Indirect reciprocity and the evolution of "moral signals"

Science.gov (United States)

Smead, Rory

2010-01-01

Signals regarding the behavior of others are an essential element of human moral systems and there are important evolutionary connections between language and large-scale cooperation. In particular, social communication may be required for the reputation tracking needed to stabilize indirect reciprocity. Additionally, scholars have suggested that the benefits of indirect reciprocity may have been important for the evolution of language and that social signals may have coevolved with large-scale cooperation. This paper investigates the possibility of such a coevolution. Using the tools of evolutionary game theory, we present a model that incorporates primitive "moral signaling" into a simple setting of indirect reciprocity. This model reveals some potential difficulties for the evolution of "moral signals." We find that it is possible for "moral signals" to evolve alongside indirect reciprocity, but without some external pressure aiding the evolution of a signaling system, such a coevolution is unlikely.

Galvanic microparticles increase migration of human dermal fibroblasts in a wound-healing model via reactive oxygen species pathway.

Science.gov (United States)

Tandon, Nina; Cimetta, Elisa; Villasante, Aranzazu; Kupferstein, Nicolette; Southall, Michael D; Fassih, Ali; Xie, Junxia; Sun, Ying; Vunjak-Novakovic, Gordana

2014-01-01

Electrical signals have been implied in many biological mechanisms, including wound healing, which has been associated with transient electrical currents not present in intact skin. One method to generate electrical signals similar to those naturally occurring in wounds is by supplementation of galvanic particles dispersed in a cream or gel. We constructed a three-layered model of skin consisting of human dermal fibroblasts in hydrogel (mimic of dermis), a hydrogel barrier layer (mimic of epidermis) and galvanic microparticles in hydrogel (mimic of a cream containing galvanic particles applied to skin). Using this model, we investigated the effects of the properties and amounts of Cu/Zn galvanic particles on adult human dermal fibroblasts in terms of the speed of wound closing and gene expression. The collected data suggest that the effects on wound closing are due to the ROS-mediated enhancement of fibroblast migration, which is in turn mediated by the BMP/SMAD signaling pathway. These results imply that topical low-grade electric currents via microparticles could enhance wound healing. © 2013 Elsevier Inc. All rights reserved.

Human Inferences about Sequences: A Minimal Transition Probability Model.

Directory of Open Access Journals (Sweden)

Florent Meyniel

2016-12-01

Full Text Available The brain constantly infers the causes of the inputs it receives and uses these inferences to generate statistical expectations about future observations. Experimental evidence for these expectations and their violations include explicit reports, sequential effects on reaction times, and mismatch or surprise signals recorded in electrophysiology and functional MRI. Here, we explore the hypothesis that the brain acts as a near-optimal inference device that constantly attempts to infer the time-varying matrix of transition probabilities between the stimuli it receives, even when those stimuli are in fact fully unpredictable. This parsimonious Bayesian model, with a single free parameter, accounts for a broad range of findings on surprise signals, sequential effects and the perception of randomness. Notably, it explains the pervasive asymmetry between repetitions and alternations encountered in those studies. Our analysis suggests that a neural machinery for inferring transition probabilities lies at the core of human sequence knowledge.

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.

Directory of Open Access Journals (Sweden)

Hau-Tieng Wu

Full Text Available We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features.

Fault tree model of human error based on error-forcing contexts

International Nuclear Information System (INIS)

Kang, Hyun Gook; Jang, Seung Cheol; Ha, Jae Joo

2004-01-01

In the safety-critical systems such as nuclear power plants, the safety-feature actuation is fully automated. In emergency case, the human operator could also play the role of a backup for automated systems. That is, the failure of safety-feature-actuation signal generation implies the concurrent failure of automated systems and that of manual actuation. The human operator's manual actuation failure is largely affected by error-forcing contexts (EFC). The failures of sensors and automated systems are most important ones. The sensors, the automated actuation system and the human operators are correlated in a complex manner and hard to develop a proper model. In this paper, we will explain the condition-based human reliability assessment (CBHRA) method in order to treat these complicated conditions in a practical way. In this study, we apply the CBHRA method to the manual actuation of safety features such as reactor trip and safety injection in Korean Standard Nuclear Power Plants

Vitamin D controls T cell antigen receptor signaling and activation of human T cells

DEFF Research Database (Denmark)

von Essen, Marina Rode; Kongsbak-Wismann, Martin; Schjerling, Peter

2010-01-01

Phospholipase C (PLC) isozymes are key signaling proteins downstream of many extracellular stimuli. Here we show that naive human T cells had very low expression of PLC-gamma1 and that this correlated with low T cell antigen receptor (TCR) responsiveness in naive T cells. However, TCR triggering...... led to an upregulation of approximately 75-fold in PLC-gamma1 expression, which correlated with greater TCR responsiveness. Induction of PLC-gamma1 was dependent on vitamin D and expression of the vitamin D receptor (VDR). Naive T cells did not express VDR, but VDR expression was induced by TCR...... signaling via the alternative mitogen-activated protein kinase p38 pathway. Thus, initial TCR signaling via p38 leads to successive induction of VDR and PLC-gamma1, which are required for subsequent classical TCR signaling and T cell activation....

Acoustic/seismic signal propagation and sensor performance modeling

Science.gov (United States)

Wilson, D. Keith; Marlin, David H.; Mackay, Sean

2007-04-01

Performance, optimal employment, and interpretation of data from acoustic and seismic sensors depend strongly and in complex ways on the environment in which they operate. Software tools for guiding non-expert users of acoustic and seismic sensors are therefore much needed. However, such tools require that many individual components be constructed and correctly connected together. These components include the source signature and directionality, representation of the atmospheric and terrain environment, calculation of the signal propagation, characterization of the sensor response, and mimicking of the data processing at the sensor. Selection of an appropriate signal propagation model is particularly important, as there are significant trade-offs between output fidelity and computation speed. Attenuation of signal energy, random fading, and (for array systems) variations in wavefront angle-of-arrival should all be considered. Characterization of the complex operational environment is often the weak link in sensor modeling: important issues for acoustic and seismic modeling activities include the temporal/spatial resolution of the atmospheric data, knowledge of the surface and subsurface terrain properties, and representation of ambient background noise and vibrations. Design of software tools that address these challenges is illustrated with two examples: a detailed target-to-sensor calculation application called the Sensor Performance Evaluator for Battlefield Environments (SPEBE) and a GIS-embedded approach called Battlefield Terrain Reasoning and Awareness (BTRA).

131I-CRTX internal dosimetry: animal model and human extrapolation

International Nuclear Information System (INIS)

Andrade, Henrique Martins de; Ferreira, Andrea Vidal; Soares, Marcella Araugio; Silveira, Marina Bicalho; Santos, Raquel Gouvea dos

2009-01-01

Snake venoms molecules have been shown to play a role not only in the survival and proliferation of tumor cells but also in the processes of tumor cell adhesion, migration and angiogenesis. 125 I-Crtx, a radiolabeled version of a peptide derived from Crotalus durissus terrificus snake venom, specifically binds to tumor and triggers apoptotic signalling. At the present work, 125 I-Crtx biokinetic data (evaluated in mice bearing Erlich tumor) were treated by MIRD formalism to perform Internal Dosimetry studies. Doses in several organs of mice were determinate, as well as in implanted tumor, for 131 I-Crtx. Doses results obtained for animal model were extrapolated to humans assuming a similar concentration ratio among various tissues between mouse and human. In the extrapolation, it was used human organ masses from Cristy/Eckerman phantom. Both penetrating and non-penetrating radiation from 131 I in the tissue were considered in dose calculations. (author)

Human-robot collision detection under modeling uncertainty using frequency boundary of manipulator dynamics

Energy Technology Data Exchange (ETDEWEB)

Jung, Byung Jin; Koo, Ja Choon; Choi, Hyouk Ryeol; Moon, Hyung Pil [Sungkyunkwan University, Suwon (Korea, Republic of)

2014-11-15

This paper presents the development and experimental evaluation of a collision detection method for robotic manipulators sharing a workspace with humans. Fast and robust collision detection is important for guaranteeing safety and preventing false alarms. The main cause of a false alarm is modeling error. We use the characteristic of the maximum frequency boundary of the manipulator's dynamic model. The tendency of the frequency boundary's location in the frequency domain is applied to the collision detection algorithm using a band pass filter (band designed disturbance observer, BdDOB) with changing frequency windows. Thanks to the band pass filter, which considers the frequency boundary of the dynamic model, our collision detection algorithm can extract the collision caused by the disturbance from the mixed estimation signal. As a result, the collision was successfully detected under the usage conditions of faulty sensors and uncertain model data. The experimental result of a collision between a 7-DOF serial manipulator and a human body is reported.

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.

Rac1 in human diseases: The therapeutic potential of targeting Rac1 signaling regulatory mechanisms.

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Marei, Hadir; Malliri, Angeliki

2017-07-03

Abnormal Rac1 signaling is linked to a number of debilitating human diseases, including cancer, cardiovascular diseases and neurodegenerative disorders. As such, Rac1 represents an attractive therapeutic target, yet the search for effective Rac1 inhibitors is still underway. Given the adverse effects associated with Rac1 signaling perturbation, cells have evolved several mechanisms to ensure the tight regulation of Rac1 signaling. Thus, characterizing these mechanisms can provide invaluable information regarding major cellular events that lead to aberrant Rac1 signaling. Importantly, this information can be utilized to further facilitate the development of effective pharmacological modulators that can restore normal Rac1 signaling. In this review, we focus on the pathological role of Rac1 signaling, highlighting the benefits and potential drawbacks of targeting Rac1 in a clinical setting. Additionally, we provide an overview of available compounds that target key Rac1 regulatory mechanisms and discuss future therapeutic avenues arising from our understanding of these mechanisms.

Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

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DeCarlo, Lawrence T

2003-02-01

The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

Inhibition of canonical WNT signaling attenuates human leiomyoma cell growth

Science.gov (United States)

Ono, Masanori; Yin, Ping; Navarro, Antonia; Moravek, Molly B.; Coon, John S.; Druschitz, Stacy A.; Gottardi, Cara J.; Bulun, Serdar E.

2014-01-01

Objective Dysregulation of WNT signaling plays a central role in tumor cell growth and progression. Our goal was to assess the effect of three WNT/β-catenin pathway inhibitors, Inhibitor of β-Catenin And TCF4 (ICAT), niclosamide, and XAV939 on the proliferation of primary cultures of human uterine leiomyoma cells. Design Prospective study of human leiomyoma cells obtained from myomectomy or hysterectomy. Setting University research laboratory. Patient(s) Women (n=38) aged 27–53 years undergoing surgery. Intervention(s) Adenoviral ICAT overexpression or treatment with varying concentrations of niclosamide or XAV939. Main Outcome Measure(s) Cell proliferation, cell death, WNT/β-catenin target gene expression or reporter gene regulation, β-catenin levels and cellular localization. Result(s) ICAT, niclosamide, or XAV939 inhibit WNT/β-catenin pathway activation and exert anti-proliferative effects in primary cultures of human leiomyoma cells. Conclusion(s) Three WNT/β-catenin pathway inhibitors specifically block human leiomyoma growth and proliferation, suggesting that the canonical WNT pathway may be a potential therapeutic target for the treatment of uterine leiomyoma. Our findings provide rationale for further preclinical and clinical evaluation of ICAT, niclosamide, and XAV939 as candidate anti-tumor agents for uterine leiomyoma. PMID:24534281

Identification of the feedforward component in manual control with predictable target signals.

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Drop, Frank M; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus M; Mulder, Max

2013-12-01

In the manual control of a dynamic system, the human controller (HC) often follows a visible and predictable reference path. Compared with a purely feedback control strategy, performance can be improved by making use of this knowledge of the reference. The operator could effectively introduce feedforward control in conjunction with a feedback path to compensate for errors, as hypothesized in literature. However, feedforward behavior has never been identified from experimental data, nor have the hypothesized models been validated. This paper investigates human control behavior in pursuit tracking of a predictable reference signal while being perturbed by a quasi-random multisine disturbance signal. An experiment was done in which the relative strength of the target and disturbance signals were systematically varied. The anticipated changes in control behavior were studied by means of an ARX model analysis and by fitting three parametric HC models: two different feedback models and a combined feedforward and feedback model. The ARX analysis shows that the experiment participants employed control action on both the error and the target signal. The control action on the target was similar to the inverse of the system dynamics. Model fits show that this behavior can be modeled best by the combined feedforward and feedback model.

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

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Herberich, Gerlind; Windoffer, Reinhard; Leube, Rudolf E; Aach, Til

2012-01-01

Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

Analysis and modelization of short-duration windows of seismic signals

International Nuclear Information System (INIS)

Berriani, B.; Lacoume, J.L.; Martin, N.; Cliet, C.; Dubesset, M.

1987-01-01

The spectral analysis of a seismic arrival is of a great interest, but unfortunately the common Fourier analysis is unserviceable on short-time windows. So, in order to obtain the spectral characteristics of the dominant components of a seismic signal on a short-time interval, the authors study parametric methods. At first, the autoregressive methods are able to localize a small number of non-stationary pure frequencies. But the amplitude determination is impossible with these methods. So, they develop a combination of AR and Capon's methods. In the Capon's method, the amplitude is conserved for a given frequency, at the very time when the contribution of the other frequencies is minimized. Finally, to characterize completely the different pure-frequency dominant components of the signal and to be able to reconstruct the signal and to be able to reconstruct the signal with these elements, the authors need also the phase and the attenuation; for that, they use the Prony's method where the signal is represented by a sum of damped sinusoids. This last method is used to modelize an offset VSP. It is shown that, using four frequencies and their attributes (amplitude, phase, attenuation), it is possible to modelize quasi-exactly the section. When reconstructing the signal, if one (or more) frequency is eliminated, an efficient filtering can be applied. The AR methods, and Prony's in particular, are efficient tools for signal component decomposition and information compression

A New Signal Model for Axion Cavity Searches from N -body Simulations

Energy Technology Data Exchange (ETDEWEB)

Lentz, Erik W.; Rosenberg, Leslie J. [Physics Department, University of Washington, Seattle, WA 98195-1580 (United States); Quinn, Thomas R.; Tremmel, Michael J., E-mail: lentze@phys.washington.edu, E-mail: ljrosenberg@phys.washington.edu, E-mail: trq@astro.washington.edu, E-mail: mjt29@astro.washington.edu [Astronomy Department, University of Washington, Seattle, WA 98195-1580 (United States)

2017-08-20

Signal estimates for direct axion dark matter (DM) searches have used the isothermal sphere halo model for the last several decades. While insightful, the isothermal model does not capture effects from a halo’s infall history nor the influence of baryonic matter, which has been shown to significantly influence a halo’s inner structure. The high resolution of cavity axion detectors can make use of modern cosmological structure-formation simulations, which begin from realistic initial conditions, incorporate a wide range of baryonic physics, and are capable of resolving detailed structure. This work uses a state-of-the-art cosmological N -body+Smoothed-Particle Hydrodynamics simulation to develop an improved signal model for axion cavity searches. Signal shapes from a class of galaxies encompassing the Milky Way are found to depart significantly from the isothermal sphere. A new signal model for axion detectors is proposed and projected sensitivity bounds on the Axion DM eXperiment (ADMX) data are presented.

Human Adaptive Mechatronics and Human-System Modelling

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Satoshi Suzuki

2013-03-01

Full Text Available Several topics in projects for mechatronics studies, which are 'Human Adaptive Mechatronics (HAM' and 'Human-System Modelling (HSM', are presented in this paper. The main research theme of the HAM project is a design strategy for a new intelligent mechatronics system, which enhances operators' skills during machine operation. Skill analyses and control system design have been addressed. In the HSM project, human modelling based on hierarchical classification of skills was studied, including the following five types of skills: social, planning, cognitive, motion and sensory-motor skills. This paper includes digests of these research topics and the outcomes concerning each type of skill. Relationships with other research activities, knowledge and information that will be helpful for readers who are trying to study assistive human-mechatronics systems are also mentioned.

Road Impedance Model Study under the Control of Intersection Signal

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Yunlin Luo

2015-01-01

Full Text Available Road traffic impedance model is a difficult and critical point in urban traffic assignment and route guidance. The paper takes a signalized intersection as the research object. On the basis of traditional traffic wave theory including the implementation of traffic wave model and the analysis of vehicles’ gathering and dissipating, the road traffic impedance model is researched by determining the basic travel time and waiting delay time. Numerical example results have proved that the proposed model in this paper has received better calculation performance compared to existing model, especially in flat hours. The values of mean absolute percentage error (MAPE and mean absolute deviation (MAD are separately reduced by 3.78% and 2.62 s. It shows that the proposed model has feasibility and availability in road traffic impedance under intersection signal.

Divergence of canonical danger signals: The genome-level expression patterns of human mononuclear cells subjected to heat shock or lipopolysaccharide

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Sakthivel Bhuvaneswari

2008-05-01

Full Text Available Abstract Background Peripheral blood mononuclear cells (PBMC serve a sentinel role allowing the host to efficiently sense and adapt to the presence of danger signals. Herein we have directly compared the genome-level expression patterns (microarray of a human PBMC model (THP-1 cells subjected to one of two canonical danger signals, heat shock or lipopolysaccharide (LPS. Results and Discussion Based on sequential expression and statistical filters, and in comparison to control cells, we found that 3,988 genes were differentially regulated in THP-1 cells subjected to LPS stress, and 2,921 genes were differentially regulated in THP-1 cells subjected to heat shock stress. Venn analyses demonstrated that the majority of differentially regulated genes (≥ 70% were uniquely expressed in response to one of the two danger signals. Functional analyses demonstrated that the two danger signals induced expression or repression of genes corresponding to unique pathways, molecular functions, biological processes, and gene networks. In contrast, there were 184 genes that were commonly upregulated by both stress signals, and 430 genes that were commonly downregulated by both stress signals. Interestingly, the 184 commonly upregulated genes corresponded to a gene network broadly related to inflammation, and more specifically to chemokine signaling. Conclusion These data demonstrate that the mononuclear cell responses to the canonical stress signals, heat shock and LPS, are highly divergent. However, there is a heretofore unrecognized common pattern of gene network expression corresponding to chemokine-related biology. The data also serve as a reference database for investigators in the field of stress signaling.

Study on non-linear bistable dynamics model based EEG signal discrimination analysis method.

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Ying, Xiaoguo; Lin, Han; Hui, Guohua

2015-01-01

Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.

Unified and Modular Modeling and Functional Verification Framework of Real-Time Image Signal Processors

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Abhishek Jain

2016-01-01

Full Text Available In VLSI industry, image signal processing algorithms are developed and evaluated using software models before implementation of RTL and firmware. After the finalization of the algorithm, software models are used as a golden reference model for the image signal processor (ISP RTL and firmware development. In this paper, we are describing the unified and modular modeling framework of image signal processing algorithms used for different applications such as ISP algorithms development, reference for hardware (HW implementation, reference for firmware (FW implementation, and bit-true certification. The universal verification methodology- (UVM- based functional verification framework of image signal processors using software reference models is described. Further, IP-XACT based tools for automatic generation of functional verification environment files and model map files are described. The proposed framework is developed both with host interface and with core using virtual register interface (VRI approach. This modeling and functional verification framework is used in real-time image signal processing applications including cellphone, smart cameras, and image compression. The main motivation behind this work is to propose the best efficient, reusable, and automated framework for modeling and verification of image signal processor (ISP designs. The proposed framework shows better results and significant improvement is observed in product verification time, verification cost, and quality of the designs.

An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification

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Fangmin Li

2017-11-01

Full Text Available In this paper, we propose the multiwindow Adaptive S-method (AS-method distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.

Auto-correlation in the motor/imaginary human EEG signals: A vision about the FDFA fluctuations.

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Gilney Figueira Zebende

Full Text Available In this paper we analyzed, by the FDFA root mean square fluctuation (rms function, the motor/imaginary human activity produced by a 64-channel electroencephalography (EEG. We utilized the Physionet on-line databank, a publicly available database of human EEG signals, as a standardized reference database for this study. Herein, we report the use of detrended fluctuation analysis (DFA method for EEG analysis. We show that the complex time series of the EEG exhibits characteristic fluctuations depending on the analyzed channel in the scalp-recorded EEG. In order to demonstrate the effectiveness of the proposed technique, we analyzed four distinct channels represented here by F332, F637 (frontal region of the head and P349, P654 (parietal region of the head. We verified that the amplitude of the FDFA rms function is greater for the frontal channels than for the parietal. To tabulate this information in a better way, we define and calculate the difference between FDFA (in log scale for the channels, thus defining a new path for analysis of EEG signals. Finally, related to the studied EEG signals, we obtain the auto-correlation exponent, αDFA by DFA method, that reveals self-affinity at specific time scale. Our results shows that this strategy can be applied to study the human brain activity in EEG processing.

Resveratrol Downregulates Interleukin-6-Stimulated Sonic Hedgehog Signaling in Human Acute Myeloid Leukemia

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Su, Yu-Chieh; Li, Szu-Chin; Wu, Yin-Chi; Wang, Li-Min; Chao, K. S. Clifford; Liao, Hui-Fen

2013-01-01

IL-6 and sonic hedgehog (Shh) signaling molecules are considered to maintain the growth of cancer stem cells (CSCs). Resveratrol, an important integrant in traditional Chinese medicine, possesses certain antitumor effects. However, the mechanisms on regulating acute myeloid leukemia (AML) are unclear. This study first used human subjects to demonstrate that the plasma levels of IL-6 and IL-1β in AML patients were higher and lower, respectively, than healthy donors. The expression of Shh preproproteins, and C- and N-terminal Shh peptides increased in bone marrow and peripheral blood mononuclear cells isolated from AML patients, and the plasma N-Shh secretion was greater. To further clarify the effect of IL-6 and resveratrol in Shh signaling, human AML HL-60 cells were tested. IL-6 upregulated Shh and Gli-1 expression and was accompanied by an increase of cell viability. Resveratrol significantly decreased CSC-related Shh expression, Gli-1 nuclear translocation, and cell viability in IL-6-treated HL-60 cells and had synergistic effect with Shh inhibitor cyclopamine on inhibiting cell growth. Conclusions. IL-6 stimulated the growth of AML cells through Shh signaling, and this effect might be blocked by resveratrol. Further investigations of Shh as a prognostic marker and resveratrol as a therapeutic drug target to CSCs in AML are surely warranted. PMID:23533494

Quorum sensing communication between bacteria and human cells: signals, targets and functions

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Angelika eHolm

2014-06-01

Full Text Available Both direct and long-range interactions between pathogenic Pseudomonas aeruginosa bacteria and their eukaryotic hosts are important in the outcome of infections. For cell-to-cell communication, these bacteria employ the quorum sensing (QS system to pass on information of the density of the bacterial population and collectively switch on virulence factor production, biofilm formation and resistance development. Thus, QS allows bacteria to behave as a community to perform tasks which would be impossible for individual cells, e.g. to overcome defense and immune systems and establish infections in higher organisms. This review highlights these aspects of QS and our own recent research on how P.aeruginosa communicates with human cells using the small QS signal molecules N-acyl homoserine lactones (AHL. We focus on how this conversation changes the behavior and function of neutrophils, macrophages and epithelial cells and on how the signaling machinery in human cells responsible for the recognition of AHL. Understanding the bacteria-host relationships at both cellular and molecular levels is essential for the identification of new targets and for the development of novel strategies to fight bacterial infections in the future.

Models of human operators

International Nuclear Information System (INIS)

Knee, H.E.; Schryver, J.C.

1991-01-01

Models of human behavior and cognition (HB and C) are necessary for understanding the total response of complex systems. Many such models have come available over the past thirty years for various applications. Unfortunately, many potential model users remain skeptical about their practicality, acceptability, and usefulness. Such hesitancy stems in part to disbelief in the ability to model complex cognitive processes, and a belief that relevant human behavior can be adequately accounted for through the use of commonsense heuristics. This paper will highlight several models of HB and C and identify existing and potential applications in attempt to dispel such notions. (author)

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

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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.

Dual small-molecule targeting of SMAD signaling stimulates human induced pluripotent stem cells toward neural lineages.

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Methichit Wattanapanitch

Full Text Available Incurable neurological disorders such as Parkinson's disease (PD, Huntington's disease (HD, and Alzheimer's disease (AD are very common and can be life-threatening because of their progressive disease symptoms with limited treatment options. To provide an alternative renewable cell source for cell-based transplantation and as study models for neurological diseases, we generated induced pluripotent stem cells (iPSCs from human dermal fibroblasts (HDFs and then differentiated them into neural progenitor cells (NPCs and mature neurons by dual SMAD signaling inhibitors. Reprogramming efficiency was improved by supplementing the histone deacethylase inhibitor, valproic acid (VPA, and inhibitor of p160-Rho associated coiled-coil kinase (ROCK, Y-27632, after retroviral transduction. We obtained a number of iPS colonies that shared similar characteristics with human embryonic stem cells in terms of their morphology, cell surface antigens, pluripotency-associated gene and protein expressions as well as their in vitro and in vivo differentiation potentials. After treatment with Noggin and SB431542, inhibitors of the SMAD signaling pathway, HDF-iPSCs demonstrated rapid and efficient differentiation into neural lineages. Six days after neural induction, neuroepithelial cells (NEPCs were observed in the adherent monolayer culture, which had the ability to differentiate further into NPCs and neurons, as characterized by their morphology and the expression of neuron-specific transcripts and proteins. We propose that our study may be applied to generate neurological disease patient-specific iPSCs allowing better understanding of disease pathogenesis and drug sensitivity assays.

Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex

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Kenji Ibayashi

2018-04-01

Full Text Available Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA, local field potential (LFP, and electrocorticography (ECoG are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC, we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs.

A receptor-based model for dopamine-induced fMRI signal

Science.gov (United States)

Mandeville, Joseph. B.; Sander, Christin Y. M.; Jenkins, Bruce G.; Hooker, Jacob M.; Catana, Ciprian; Vanduffel, Wim; Alpert, Nathaniel M.; Rosen, Bruce R.; Normandin, Marc D.

2013-01-01

This report describes a multi-receptor physiological model of the fMRI temporal response and signal magnitude evoked by drugs that elevate synaptic dopamine in basal ganglia. The model is formulated as a summation of dopamine’s effects at D1-like and D2-like receptor families, which produce functional excitation and inhibition, respectively, as measured by molecular indicators like adenylate cyclase or neuroimaging techniques like fMRI. Functional effects within the model are described in terms of relative changes in receptor occupancies scaled by receptor densities and neuro-vascular coupling constants. Using literature parameters, the model reconciles many discrepant observations and interpretations of pre-clinical data. Additionally, we present data showing that amphetamine stimulation produces fMRI inhibition at low doses and a biphasic response at higher doses in the basal ganglia of non-human primates (NHP), in agreement with model predictions based upon the respective levels of evoked dopamine. Because information about dopamine release is required to inform the fMRI model, we simultaneously acquired PET 11C-raclopride data in several studies to evaluate the relationship between raclopride displacement and assumptions about dopamine release. At high levels of dopamine release, results suggest that refinements of the model will be required to consistently describe the PET and fMRI data. Overall, the remarkable success of the model in describing a wide range of preclinical fMRI data indicate that this approach will be useful for guiding the design and analysis of basic science and clinical investigations and for interpreting the functional consequences of dopaminergic stimulation in normal subjects and in populations with dopaminergic neuroadaptations. PMID:23466936

Mathematical modeling of gonadotropin-releasing hormone signaling.

Science.gov (United States)

Pratap, Amitesh; Garner, Kathryn L; Voliotis, Margaritis; Tsaneva-Atanasova, Krasimira; McArdle, Craig A

2017-07-05

Gonadotropin-releasing hormone (GnRH) acts via G-protein coupled receptors on pituitary gonadotropes to control reproduction. These are G q -coupled receptors that mediate acute effects of GnRH on the exocytotic secretion of luteinizing hormone (LH) and follicle-stimulating hormone (FSH), as well as the chronic regulation of their synthesis. GnRH is secreted in short pulses and GnRH effects on its target cells are dependent upon the dynamics of these pulses. Here we overview GnRH receptors and their signaling network, placing emphasis on pulsatile signaling, and how mechanistic mathematical models and an information theoretic approach have helped further this field. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

An agent-based model of signal transduction in bacterial chemotaxis.

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Jameson Miller

2010-05-01

Full Text Available We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

An agent-based model of signal transduction in bacterial chemotaxis.

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Miller, Jameson; Parker, Miles; Bourret, Robert B; Giddings, Morgan C

2010-05-13

We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

The negative impact of Wnt signaling on megakaryocyte and primitive erythroid progenitors derived from human embryonic stem cells

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Prasuna Paluru

2014-03-01

Full Text Available The Wnt gene family consists of structurally related genes encoding secreted signaling molecules that have been implicated in many developmental processes, including regulation of cell fate and patterning during embryogenesis. Previously, we found that Wnt signaling is required for primitive or yolk sac-derived-erythropoiesis using the murine embryonic stem cell (ESC system. Here, we examine the effect of Wnt signaling on the formation of early hematopoietic progenitors derived from human ESCs. The first hematopoietic progenitor cells in the human ESC system express the pan-hematopoietic marker CD41 and the erythrocyte marker, glycophorin A or CD235. We have developed a novel serum-free, feeder-free, adherent differentiation system that can efficiently generate large numbers of CD41 + CD235+ cells. We demonstrate that this cell population contains progenitors not just for primitive erythroid and megakaryocyte cells but for the myeloid lineage as well and term this population the primitive common myeloid progenitor (CMP. Treatment of mesoderm-specified cells with Wnt3a led to a loss of hematopoietic colony-forming ability while the inhibition of canonical Wnt signaling with DKK1 led to an increase in the number of primitive CMPs. Canonical Wnt signaling also inhibits the expansion and/or survival of primitive erythrocytes and megakaryocytes, but not myeloid cells, derived from this progenitor population. These findings are in contrast to the role of Wnt signaling during mouse ESC differentiation and demonstrate the importance of the human ESC system in studying species-specific differences in development.

Omni-PolyA: a method and tool for accurate recognition of Poly(A) signals in human genomic DNA

KAUST Repository

Magana-Mora, Arturo

2017-08-15

BackgroundPolyadenylation is a critical stage of RNA processing during the formation of mature mRNA, and is present in most of the known eukaryote protein-coding transcripts and many long non-coding RNAs. The correct identification of poly(A) signals (PAS) not only helps to elucidate the 3′-end genomic boundaries of a transcribed DNA region and gene regulatory mechanisms but also gives insight into the multiple transcript isoforms resulting from alternative PAS. Although progress has been made in the in-silico prediction of genomic signals, the recognition of PAS in DNA genomic sequences remains a challenge.ResultsIn this study, we analyzed human genomic DNA sequences for the 12 most common PAS variants. Our analysis has identified a set of features that helps in the recognition of true PAS, which may be involved in the regulation of the polyadenylation process. The proposed features, in combination with a recognition model, resulted in a novel method and tool, Omni-PolyA. Omni-PolyA combines several machine learning techniques such as different classifiers in a tree-like decision structure and genetic algorithms for deriving a robust classification model. We performed a comparison between results obtained by state-of-the-art methods, deep neural networks, and Omni-PolyA. Results show that Omni-PolyA significantly reduced the average classification error rate by 35.37% in the prediction of the 12 considered PAS variants relative to the state-of-the-art results.ConclusionsThe results of our study demonstrate that Omni-PolyA is currently the most accurate model for the prediction of PAS in human and can serve as a useful complement to other PAS recognition methods. Omni-PolyA is publicly available as an online tool accessible at www.cbrc.kaust.edu.sa/omnipolya/.

Multiple intracellular signaling pathways orchestrate adipocytic differentiation of human bone marrow stromal stem cells

DEFF Research Database (Denmark)

Ayesh Hafez Ali, Dalia; Abuelreich, Sarah; Alkeraishan, Nora

2018-01-01

during adipocyte differentiation of human bone marrow stromal (mesenchymal) stem cells (hMSCs) and identified 2,589 up-regulated and 2,583 down-regulated mRNA transcripts. Pathway analysis on the up-regulated gene list untraveled enrichment in multiple signaling pathways including insulin receptor......Bone marrow adipocyte formation plays a role in bone homeostasis and whole body energy metabolism. However, the transcriptional landscape and signaling pathways associated with adipocyte lineage commitment and maturation are not fully delineated. Thus, we performed global gene expression profiling...... signaling, focal Adhesion, metapathway biotransformation, a number of metabolic pathways e.g. selenium metabolism, Benzo(a)pyrene metabolism, fatty acid, triacylglycerol, ketone body metabolism, tryptophan metabolism, and catalytic cycle of mammalian flavin-containing monooxygenase (FMOs). On the other hand...

Melatonin: a chemical photoperiodic signal with clinical significance in humans.

Science.gov (United States)

Pang, S F; Pang, C S; Poon, A M; Lee, P P; Liu, Z M; Shiu, S Y

1998-03-01

Secretion of pineal melatonin exhibits a diumal rhythm and a seasonal rhythm in humans. Night-time melatonin is high at 3-5 year-old and decreases with age. Many drugs and pathological conditions also change melatonin levels in the circulation. Melatonin has a mild sedative effect and has been used effectively in synchronizing the sleep-wake cycle of patients with sleep disorders. Immunoenhancing, anti-cancer, anti-aging and anti-oxidant effects of melatonin have been proposed. Recent studies suggest that melatonin receptors are present in central and peripheral tissues. The importance of melatonin receptors on the nervous, reproductive, immune and renal functions is implicated. Studies on the molecular biology, physiology and pathology of melatonin receptors in different tissues are progressing rapidly. The physiological and pathological changes in melatonin secretion, multifarious melatonin actions, and diverse melatonin receptors reported suggest that melatonin is a photoperiodic signal with clinical significance in humans.

Insulin Signaling, Resistance, and the Metabolic Syndrome: Insights from Mouse Models to Disease Mechanisms

Science.gov (United States)

Guo, Shaodong

2014-01-01

Insulin resistance is a major underlying mechanism for the “metabolic syndrome”, which is also known as insulin resistance syndrome. Metabolic syndrome is increasing at an alarming rate, becoming a major public and clinical problem worldwide. Metabolic syndrome is represented by a group of interrelated disorders, including obesity, hyperglycemia, hyperlipidemia, and hypertension. It is also a significant risk factor for cardiovascular disease and increased morbidity and mortality. Animal studies demonstrate that insulin and its signaling cascade normally control cell growth, metabolism and survival through activation of mitogen-activated protein kinases (MAPKs) and phosphotidylinositide-3-kinase (PI3K), of which activation of PI-3K-associated with insulin receptor substrate-1 and -2 (IRS1, 2) and subsequent Akt→Foxo1 phosphorylation cascade has a central role in control of nutrient homeostasis and organ survival. Inactivation of Akt and activation of Foxo1, through suppression IRS1 and IRS2 in different organs following hyperinsulinemia, metabolic inflammation, and over nutrition may provide the underlying mechanisms for metabolic syndrome in humans. Targeting the IRS→Akt→Foxo1 signaling cascade will likely provide a strategy for therapeutic intervention in the treatment of type 2 diabetes and its complications. This review discusses the basis of insulin signaling, insulin resistance in different mouse models, and how a deficiency of insulin signaling components in different organs contributes to the feature of the metabolic syndrome. Emphasis will be placed on the role of IRS1, IRS2, and associated signaling pathways that couple to Akt and the forkhead/winged helix transcription factor Foxo1. PMID:24281010

Molecular docking and 3D-QSAR studies on inhibitors of DNA damage signaling enzyme human PARP-1.

Science.gov (United States)

Fatima, Sabiha; Bathini, Raju; Sivan, Sree Kanth; Manga, Vijjulatha

2012-08-01

Poly (ADP-ribose) polymerase-1 (PARP-1) operates in a DNA damage signaling network. Molecular docking and three dimensional-quantitative structure activity relationship (3D-QSAR) studies were performed on human PARP-1 inhibitors. Docked conformation obtained for each molecule was used as such for 3D-QSAR analysis. Molecules were divided into a training set and a test set randomly in four different ways, partial least square analysis was performed to obtain QSAR models using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Derived models showed good statistical reliability that is evident from their r², q²(loo) and r²(pred) values. To obtain a consensus for predictive ability from all the models, average regression coefficient r²(avg) was calculated. CoMFA and CoMSIA models showed a value of 0.930 and 0.936, respectively. Information obtained from the best 3D-QSAR model was applied for optimization of lead molecule and design of novel potential inhibitors.

Model for neural signaling leap statistics

International Nuclear Information System (INIS)

Chevrollier, Martine; Oria, Marcos

2011-01-01

We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.5 0 C, awaken regime) and Levy statistics (T = 35.5 0 C, sleeping period), characterized by rare events of long range connections.

Model for neural signaling leap statistics

Science.gov (United States)

Chevrollier, Martine; Oriá, Marcos

2011-03-01

We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T = 37.5°C, awaken regime) and Lévy statistics (T = 35.5°C, sleeping period), characterized by rare events of long range connections.

Model-based Bayesian signal extraction algorithm for peripheral nerves

Science.gov (United States)

Eggers, Thomas E.; Dweiri, Yazan M.; McCallum, Grant A.; Durand, Dominique M.

2017-10-01

Objective. Multi-channel cuff electrodes have recently been investigated for extracting fascicular-level motor commands from mixed neural recordings. Such signals could provide volitional, intuitive control over a robotic prosthesis for amputee patients. Recent work has demonstrated success in extracting these signals in acute and chronic preparations using spatial filtering techniques. These extracted signals, however, had low signal-to-noise ratios and thus limited their utility to binary classification. In this work a new algorithm is proposed which combines previous source localization approaches to create a model based method which operates in real time. Approach. To validate this algorithm, a saline benchtop setup was created to allow the precise placement of artificial sources within a cuff and interference sources outside the cuff. The artificial source was taken from five seconds of chronic neural activity to replicate realistic recordings. The proposed algorithm, hybrid Bayesian signal extraction (HBSE), is then compared to previous algorithms, beamforming and a Bayesian spatial filtering method, on this test data. An example chronic neural recording is also analyzed with all three algorithms. Main results. The proposed algorithm improved the signal to noise and signal to interference ratio of extracted test signals two to three fold, as well as increased the correlation coefficient between the original and recovered signals by 10-20%. These improvements translated to the chronic recording example and increased the calculated bit rate between the recovered signals and the recorded motor activity. Significance. HBSE significantly outperforms previous algorithms in extracting realistic neural signals, even in the presence of external noise sources. These results demonstrate the feasibility of extracting dynamic motor signals from a multi-fascicled intact nerve trunk, which in turn could extract motor command signals from an amputee for the end goal of

Decoding Problem Gamblers' Signals: A Decision Model for Casino Enterprises.

Science.gov (United States)

Ifrim, Sandra

2015-12-01

The aim of the present study is to offer a validated decision model for casino enterprises. The model enables those users to perform early detection of problem gamblers and fulfill their ethical duty of social cost minimization. To this end, the interpretation of casino customers' nonverbal communication is understood as a signal-processing problem. Indicators of problem gambling recommended by Delfabbro et al. (Identifying problem gamblers in gambling venues: final report, 2007) are combined with Viterbi algorithm into an interdisciplinary model that helps decoding signals emitted by casino customers. Model output consists of a historical path of mental states and cumulated social costs associated with a particular client. Groups of problem and non-problem gamblers were simulated to investigate the model's diagnostic capability and its cost minimization ability. Each group consisted of 26 subjects and was subsequently enlarged to 100 subjects. In approximately 95% of the cases, mental states were correctly decoded for problem gamblers. Statistical analysis using planned contrasts revealed that the model is relatively robust to the suppression of signals performed by casino clientele facing gambling problems as well as to misjudgments made by staff regarding the clients' mental states. Only if the last mentioned source of error occurs in a very pronounced manner, i.e. judgment is extremely faulty, cumulated social costs might be distorted.

Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling.

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Lorenza A D'Alessandro

2015-04-01

Full Text Available Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex and cell-context specific signaling networks. Dissecting the underlying relations is crucial to predict the impact of targeted perturbations. However, a major challenge in identifying cell-context specific signaling networks is the enormous number of potentially possible interactions. Here, we report a novel hybrid mathematical modeling strategy to systematically unravel hepatocyte growth factor (HGF stimulated phosphoinositide-3-kinase (PI3K and mitogen activated protein kinase (MAPK signaling, which critically contribute to liver regeneration. By combining time-resolved quantitative experimental data generated in primary mouse hepatocytes with interaction graph and ordinary differential equation modeling, we identify and experimentally validate a network structure that represents the experimental data best and indicates specific crosstalk mechanisms. Whereas the identified network is robust against single perturbations, combinatorial inhibition strategies are predicted that result in strong reduction of Akt and ERK activation. Thus, by capitalizing on the advantages of the two modeling approaches, we reduce the high combinatorial complexity and identify cell-context specific signaling networks.

Modeling, estimation and optimal filtration in signal processing

CERN Document Server

Najim, Mohamed

2010-01-01

The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing.Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed.Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented.Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and the

Wideband Small-Signal Input dq Admittance Modeling of Six-Pulse Diode Rectifiers

DEFF Research Database (Denmark)

Yue, Xiaolong; Wang, Xiongfei; Blaabjerg, Frede

2018-01-01

This paper studies the wideband small-signal input dq admittance of six-pulse diode rectifiers. Considering the frequency coupling introduced by ripple frequency harmonics of d-and q-channel switching function, the proposed model successfully predicts the small-signal input dq admittance of six......-pulse diode rectifiers in high frequency regions that existing models fail to explain. Simulation and experimental results verify the accuracy of the proposed model....

An Endogenous Electron Spin Resonance (ESR signal discriminates nevi from melanomas in human specimens: a step forward in its diagnostic application.

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Eleonora Cesareo

Full Text Available Given the specific melanin-associated paramagnetic features, the Electron Spin Resonance (ESR, called also Electron Paramagnetic Resonance, EPR analysis has been proposed as a potential tool for non-invasive melanoma diagnosis. However, studies comparing human melanoma tissues to the most appropriate physiological counterpart (nevi have not been performed, and ESR direct correlation with melanoma clinical features has never been investigated. ESR spectrum was obtained from melanoma and non-melanoma cell-cultures as well as mouse melanoma and non-melanoma tissues and an endogenous ESR signal (g = 2.005 was found in human melanoma cells and in primary melanoma tissues explanted from mice, while it was always absent in non-melanoma samples. These characteristics of the measured ESR signal strongly suggested its connection with melanin. Quantitative analyses were then performed on paraffin-embedded human melanoma and nevus sections, and validated on an independent larger validation set, for a total of 112 sections (52 melanomas, 60 nevi. The ESR signal was significantly higher in melanomas (p = 0.0002 and was significantly different between "Low Breslow's and "High Breslow's" depth melanomas (p<0.0001. A direct correlation between ESR signal and Breslow's depth, expressed in millimetres, was found (R = 0.57; p<0.0001. The eu/pheomelanin ratio was found to be significantly different in melanomas "Low Breslow's" vs melanomas "High Breslow's" depth and in nevi vs melanomas "High Breslow's depth". Finally, ROC analysis using ESR data discriminated melanomas sections from nevi sections with up to 90% accuracy and p<0.0002. In the present study we report for the first time that ESR signal in human paraffin-embedded nevi is significantly lower than signal in human melanomas suggesting that spectrum variations may be related to qualitative melanin differences specifically occurring in melanoma cells. We therefore conclude that this ESR signal

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

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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.

A novel human-machine interface based on recognition of multi-channel facial bioelectric signals

International Nuclear Information System (INIS)

Razazadeh, Iman Mohammad; Firoozabadi, S. Mohammad; Golpayegani, S.M.R.H.; Hu, H.

2011-01-01

Full text: This paper presents a novel human-machine interface for disabled people to interact with assistive systems for a better quality of life. It is based on multichannel forehead bioelectric signals acquired by placing three pairs of electrodes (physical channels) on the Fron-tails and Temporalis facial muscles. The acquired signals are passes through a parallel filter bank to explore three different sub-bands related to facial electromyogram, electrooculogram and electroencephalogram. The root mean features of the bioelectric signals analyzed within non-overlapping 256 ms windows were extracted. The subtractive fuzzy c-means clustering method (SFCM) was applied to segment the feature space and generate initial fuzzy based Takagi-Sugeno rules. Then, an adaptive neuro-fuzzy inference system is exploited to tune up the premises and consequence parameters of the extracted SFCMs. rules. The average classifier discriminating ratio for eight different facial gestures (smiling, frowning, pulling up left/right lips corner, eye movement to left/right/up/down is between 93.04% and 96.99% according to different combinations and fusions of logical features. Experimental results show that the proposed interface has a high degree of accuracy and robustness for discrimination of 8 fundamental facial gestures. Some potential and further capabilities of our approach in human-machine interfaces are also discussed. (author)

MATHEMATICAL MODELING OF THE UNPUT DEVICES IN AUTOMATIC LOCOMOTIVE SIGNALING SYSTEM

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O. O. Gololobova

2014-03-01

Full Text Available Purpose. To examine the operation of the automatic locomotive signaling system (ALS, to find out the influence of external factors on the devices operation and the quality of the code information derived from track circuit information, as well as to enable modeling of failure occurrences that may appear during operation. Methodology. To achieve this purpose, the main obstacles in ALS operation and the reasons for their occurrence were considered and the system structure principle was researched. The mathematical model for input equipment of the continuous automatic locomotive signaling system (ALS with the number coding was developed. It was designed taking into account all the types of code signals “R”, “Y”, “RY” and equivalent scheme of replacing the filter with a frequency of 50 Hz. Findings. The operation of ALSN with a signal current frequency of 50 Hz was examined. The adequate mathematical model of input equipment of ALS with a frequency of 50 Hz was developed. Originality. The computer model of input equipment of ALS system in the environment of MATLAB+Simulink was developed. The results of the computer modeling on the outlet of the filter during delivering every type of code combination were given in the article. Practical value. With the use of developed mathematical model of ALS system operation we have an opportunity to study, research and determine behavior of the circuit during the normal operation mode and failure occurrences. Also there is a possibility to develop and apply different scheme decisions in modeling environment MATLAB+Simulink for reducing the influence of obstacles on the functional capability of ALS and to model the occurrence of possible difficulties.

Phosphoproteomic Analysis Identifies Signaling Pathways Regulated by Curcumin in Human Colon Cancer Cells.

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Sato, Tatsuhiro; Higuchi, Yutaka; Shibagaki, Yoshio; Hattori, Seisuke

2017-09-01

Curcumin, a major polyphenol of the spice turmeric, acts as a potent chemopreventive and chemotherapeutic agent in several cancer types, including colon cancer. Although various proteins have been shown to be affected by curcumin, how curcumin exerts its anticancer activity is not fully understood. Phosphoproteomic analyses were performed using SW480 and SW620 human colon cancer cells to identify curcumin-affected signaling pathways. Curcumin inhibited the growth of the two cell lines in a dose-dependent manner. Thirty-nine curcumin-regulated phosphoproteins were identified, five of which are involved in cancer signaling pathways. Detailed analyses revealed that the mTORC1 and p53 signaling pathways are main targets of curcumin. Our results provide insight into the molecular mechanisms of the anticancer activities of curcumin and future molecular targets for its clinical application. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity.

Science.gov (United States)

van Hees, Vincent T; Gorzelniak, Lukas; Dean León, Emmanuel Carlos; Eder, Martin; Pias, Marcelo; Taherian, Salman; Ekelund, Ulf; Renström, Frida; Franks, Paul W; Horsch, Alexander; Brage, Søren

2013-01-01

Human body acceleration is often used as an indicator of daily physical activity in epidemiological research. Raw acceleration signals contain three basic components: movement, gravity, and noise. Separation of these becomes increasingly difficult during rotational movements. We aimed to evaluate five different methods (metrics) of processing acceleration signals on their ability to remove the gravitational component of acceleration during standardised mechanical movements and the implications for human daily physical activity assessment. An industrial robot rotated accelerometers in the vertical plane. Radius, frequency, and angular range of motion were systematically varied. Three metrics (Euclidian norm minus one [ENMO], Euclidian norm of the high-pass filtered signals [HFEN], and HFEN plus Euclidean norm of low-pass filtered signals minus 1 g [HFEN+]) were derived for each experimental condition and compared against the reference acceleration (forward kinematics) of the robot arm. We then compared metrics derived from human acceleration signals from the wrist and hip in 97 adults (22-65 yr), and wrist in 63 women (20-35 yr) in whom daily activity-related energy expenditure (PAEE) was available. In the robot experiment, HFEN+ had lowest error during (vertical plane) rotations at an oscillating frequency higher than the filter cut-off frequency while for lower frequencies ENMO performed better. In the human experiments, metrics HFEN and ENMO on hip were most discrepant (within- and between-individual explained variance of 0.90 and 0.46, respectively). ENMO, HFEN and HFEN+ explained 34%, 30% and 36% of the variance in daily PAEE, respectively, compared to 26% for a metric which did not attempt to remove the gravitational component (metric EN). In conclusion, none of the metrics as evaluated systematically outperformed all other metrics across a wide range of standardised kinematic conditions. However, choice of metric explains different degrees of variance in

Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity.

Directory of Open Access Journals (Sweden)

Vincent T van Hees

Full Text Available INTRODUCTION: Human body acceleration is often used as an indicator of daily physical activity in epidemiological research. Raw acceleration signals contain three basic components: movement, gravity, and noise. Separation of these becomes increasingly difficult during rotational movements. We aimed to evaluate five different methods (metrics of processing acceleration signals on their ability to remove the gravitational component of acceleration during standardised mechanical movements and the implications for human daily physical activity assessment. METHODS: An industrial robot rotated accelerometers in the vertical plane. Radius, frequency, and angular range of motion were systematically varied. Three metrics (Euclidian norm minus one [ENMO], Euclidian norm of the high-pass filtered signals [HFEN], and HFEN plus Euclidean norm of low-pass filtered signals minus 1 g [HFEN+] were derived for each experimental condition and compared against the reference acceleration (forward kinematics of the robot arm. We then compared metrics derived from human acceleration signals from the wrist and hip in 97 adults (22-65 yr, and wrist in 63 women (20-35 yr in whom daily activity-related energy expenditure (PAEE was available. RESULTS: In the robot experiment, HFEN+ had lowest error during (vertical plane rotations at an oscillating frequency higher than the filter cut-off frequency while for lower frequencies ENMO performed better. In the human experiments, metrics HFEN and ENMO on hip were most discrepant (within- and between-individual explained variance of 0.90 and 0.46, respectively. ENMO, HFEN and HFEN+ explained 34%, 30% and 36% of the variance in daily PAEE, respectively, compared to 26% for a metric which did not attempt to remove the gravitational component (metric EN. CONCLUSION: In conclusion, none of the metrics as evaluated systematically outperformed all other metrics across a wide range of standardised kinematic conditions. However, choice

Use of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes (hiPSC-CMs) to Monitor Compound Effects on Cardiac Myocyte Signaling Pathways.

Science.gov (United States)

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

2015-09-01

There is a need to develop mechanism-based assays to better inform risk of cardiotoxicity. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are rapidly gaining acceptance as a biologically relevant in vitro model for use in drug discovery and cardiotoxicity screens. Utilization of hiPSC-CMs for mechanistic investigations would benefit from confirmation of the expression and activity of cellular pathways that are known to regulate cardiac myocyte viability and function. This unit describes an approach to demonstrate the presence and function of signaling pathways in hiPSC-CMs and the effects of treatments on these pathways. We present a workflow that employs protocols to demonstrate protein expression and functional integrity of signaling pathway(s) of interest and to characterize biological consequences of signaling modulation. These protocols utilize a unique combination of structural, functional, and biochemical endpoints to interrogate compound effects on cardiomyocytes. Copyright © 2015 John Wiley & Sons, Inc.

Controlling a human-computer interface system with a novel classification method that uses electrooculography signals.

Science.gov (United States)

Wu, Shang-Lin; Liao, Lun-De; Lu, Shao-Wei; Jiang, Wei-Ling; Chen, Shi-An; Lin, Chin-Teng

2013-08-01

Electrooculography (EOG) signals can be used to control human-computer interface (HCI) systems, if properly classified. The ability to measure and process these signals may help HCI users to overcome many of the physical limitations and inconveniences in daily life. However, there are currently no effective multidirectional classification methods for monitoring eye movements. Here, we describe a classification method used in a wireless EOG-based HCI device for detecting eye movements in eight directions. This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-left, up-right, and down-right) and blinking. The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future.

Exosomes Derived from Human Bone Marrow Mesenchymal Stem Cells Promote Tumor Growth Through Hedgehog Signaling Pathway

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Jin Qi

2017-08-01

Full Text Available Background/Aims: Mesenchymal stem/stromal cells (MSCs are known to home to sites of tumor microenvironments where they participate in the formation of the tumor microenvironment and to interplay with tumor cells. However, the potential functional effects of MSCs on tumor cell growth are controversial. Here, we, from the view of bone marrow MSC-derived exosomes, study the molecular mechanism of MSCs on the growth of human osteosarcoma and human gastric cancer cells. Methods: MSCs derived from human bone marrow (hBMSCs were isolated and cultured in complete DMEM/F12 supplemented with 10% exosome-depleted fetal bovine serum and 1% penicillin-streptomycin, cell culture supernatants containing exosomes were harvested and exosome purification was performed by ultracentrifugation. Osteosarcoma (MG63 and gastric cancer (SGC7901 cells, respectively, were treated with hBMSC-derived exosomes in the presence or absence of a small molecule inhibitor of Hedgehog pathway. Cell viability was measured by transwell invasion assay, scratch migration assay and CCK-8 test. The expression of the signaling molecules Smoothened, Patched-1, Gli1 and the ligand Shh were tested by western blot and RT-PCR. Results: In this study, we found that hBMSC-derived exosomes promoted MG63 and SGC7901 cell growth through the activation of Hedgehog signaling pathway. Inhibition of Hedgehog signaling pathway significantly suppressed the process of hBMSC-derived exosomes on tumor growth. Conclusion: Our findings demonstrated the new roles of hedgehog signaling pathway in the hBMSCs-derived exosomes induced tumor progression.

Genetic complexity in a Drosophila model of diabetes-associated misfolded human proinsulin.

Science.gov (United States)

Park, Soo-Young; Ludwig, Michael Z; Tamarina, Natalia A; He, Bin Z; Carl, Sarah H; Dickerson, Desiree A; Barse, Levi; Arun, Bharath; Williams, Calvin L; Miles, Cecelia M; Philipson, Louis H; Steiner, Donald F; Bell, Graeme I; Kreitman, Martin

2014-02-01

Drosophila melanogaster has been widely used as a model of human Mendelian disease, but its value in modeling complex disease has received little attention. Fly models of complex disease would enable high-resolution mapping of disease-modifying loci and the identification of novel targets for therapeutic intervention. Here, we describe a fly model of permanent neonatal diabetes mellitus and explore the complexity of this model. The approach involves the transgenic expression of a misfolded mutant of human preproinsulin, hINS(C96Y), which is a cause of permanent neonatal diabetes. When expressed in fly imaginal discs, hINS(C96Y) causes a reduction of adult structures, including the eye, wing, and notum. Eye imaginal discs exhibit defects in both the structure and the arrangement of ommatidia. In the wing, expression of hINS(C96Y) leads to ectopic expression of veins and mechano-sensory organs, indicating disruption of wild-type signaling processes regulating cell fates. These readily measurable "disease" phenotypes are sensitive to temperature, gene dose, and sex. Mutant (but not wild-type) proinsulin expression in the eye imaginal disc induces IRE1-mediated XBP1 alternative splicing, a signal for endoplasmic reticulum stress response activation, and produces global change in gene expression. Mutant hINS transgene tester strains, when crossed to stocks from the Drosophila Genetic Reference Panel, produce F1 adults with a continuous range of disease phenotypes and large broad-sense heritability. Surprisingly, the severity of mutant hINS-induced disease in the eye is not correlated with that in the notum in these crosses, nor with eye reduction phenotypes caused by the expression of two dominant eye mutants acting in two different eye development pathways, Drop (Dr) or Lobe (L), when crossed into the same genetic backgrounds. The tissue specificity of genetic variability for mutant hINS-induced disease has, therefore, its own distinct signature. The genetic dominance

On scaling of human body models

Directory of Open Access Journals (Sweden)

Hynčík L.

2007-10-01

Full Text Available Human body is not an unique being, everyone is another from the point of view of anthropometry and mechanical characteristics which means that division of the human body population to categories like 5%-tile, 50%-tile and 95%-tile from the application point of view is not enough. On the other hand, the development of a particular human body model for all of us is not possible. That is why scaling and morphing algorithms has started to be developed. The current work describes the development of a tool for scaling of the human models. The idea is to have one (or couple of standard model(s as a base and to create other models based on these basic models. One has to choose adequate anthropometrical and biomechanical parameters that describe given group of humans to be scaled and morphed among.

Constraint-based modeling and kinetic analysis of the Smad dependent TGF-beta signaling pathway.

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Zhike Zi

Full Text Available BACKGROUND: Investigation of dynamics and regulation of the TGF-beta signaling pathway is central to the understanding of complex cellular processes such as growth, apoptosis, and differentiation. In this study, we aim at using systems biology approach to provide dynamic analysis on this pathway. METHODOLOGY/PRINCIPAL FINDINGS: We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-beta signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis. The performance of the model generated by constraint-based modeling method is significantly improved compared to the model obtained by only fitting the quantitative data. The model agrees well with the experimental analysis of TGF-beta pathway, such as the time course of nuclear phosphorylated Smad, the subcellular location of Smad and signal response of Smad phosphorylation to different doses of TGF-beta. CONCLUSIONS/SIGNIFICANCE: The simulation results indicate that the signal response to TGF-beta is regulated by the balance between clathrin dependent endocytosis and non-clathrin mediated endocytosis. This model is useful to be built upon as new precise experimental data are emerging. The constraint-based modeling method can also be applied to quantitative modeling of other signaling pathways.

Human glutathione S-transferase P1-1 functions as an estrogen receptor α signaling modulator

Energy Technology Data Exchange (ETDEWEB)

Liu, Xiyuan [Department of Biological Science, Sookmyung Women’s University, Seoul (Korea, Republic of); An, Byoung Ha [Department of Food and Nutrition, College of Life Science, Sookmyung Women’s University, Seoul (Korea, Republic of); Kim, Min Jung; Park, Jong Hoon [Department of Biological Science, Sookmyung Women’s University, Seoul (Korea, Republic of); Kang, Young Sook [Department of Pharmacy, College of Pharmacy, Sookmyung Women’s University, Seoul (Korea, Republic of); Chang, Minsun, E-mail: minsunchang@sm.ac.kr [Department of Medical and Pharmaceutical Science, College of Science, Sookmyung Women’s University, Seoul (Korea, Republic of)

2014-09-26

Highlights: • GSTP induces the classical ERα signaling event. • The functional GSTP is a prerequisite for GSTP-induced ERα transcription activity. • The expression of RIP140, a transcription cofactor, was inhibited by GSTP protein. • We propose the novel non-enzymatic role of GSTP. - Abstract: Estrogen receptor α (ERα) plays a crucial role in estrogen-mediated signaling pathways and exerts its action as a nuclear transcription factor. Binding of the ligand-activated ERα to the estrogen response element (ERE) is a central part of ERα-associated signal transduction pathways and its aberrant modulation is associated with many disease conditions. Human glutathione S-transferase P1-1 (GSTP) functions as an enzyme in conjugation reactions in drug metabolism and as a regulator of kinase signaling pathways. It is overexpressed in tumors following chemotherapy and has been associated with a poor prognosis in breast cancer. In this study, a novel regulatory function of GSTP has been proposed in which GSTP modulates ERE-mediated ERα signaling events. Ectopic expression of GSTP was able to induce the ERα and ERE-mediated transcriptional activities in ERα-positive but GSTP-negative MCF7 human breast cancer cells. This inductive effect of GSTP on the ERE-transcription activity was diminished when the cells express a mutated form of the enzyme or are treated with a GSTP-specific chemical inhibitor. It was found that GSTP inhibited the expression of the receptor interacting protein 140 (RIP140), a negative regulator of ERα transcription, at both mRNA and protein levels. Our study suggests a novel non-enzymatic role of GSTP which plays a significant role in regulating the classical ERα signaling pathways via modification of transcription cofactors such as RIP140.

Model for neural signaling leap statistics

Energy Technology Data Exchange (ETDEWEB)

Chevrollier, Martine; Oria, Marcos, E-mail: oria@otica.ufpb.br [Laboratorio de Fisica Atomica e Lasers Departamento de Fisica, Universidade Federal da ParaIba Caixa Postal 5086 58051-900 Joao Pessoa, Paraiba (Brazil)

2011-03-01

We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.5{sup 0}C, awaken regime) and Levy statistics (T = 35.5{sup 0}C, sleeping period), characterized by rare events of long range connections.

Noncanonical Wnt signaling promotes osteoclast differentiation and is facilitated by the human immunodeficiency virus protease inhibitor ritonavir

International Nuclear Information System (INIS)

Santiago, Francisco; Oguma, Junya; Brown, Anthony M.C.; Laurence, Jeffrey

2012-01-01

Highlights: ► First demonstration of direct role for noncanonical Wnt in osteoclast differentiation. ► Demonstration of Ryk as a Wnt5a/b receptor in inhibition of canonical Wnt signaling. ► Modulation of noncanonical Wnt signaling by a clinically important drug, ritonavir. ► Establishes a mechanism for an important clinical problem: HIV-associated bone loss. -- Abstract: Wnt proteins that signal via the canonical Wnt/β-catenin pathway directly regulate osteoblast differentiation. In contrast, most studies of Wnt-related effects on osteoclasts involve indirect changes. While investigating bone mineral density loss in the setting of human immunodeficiency virus (HIV) infection and its treatment with the protease inhibitor ritonavir (RTV), we observed that RTV decreased nuclear localization of β-catenin, critical to canonical Wnt signaling, in primary human and murine osteoclast precursors. This occurred in parallel with upregulation of Wnt5a and Wnt5b transcripts. These Wnts typically stimulate noncanonical Wnt signaling, and this can antagonize the canonical Wnt pathway in many cell types, dependent upon Wnt receptor usage. We now document RTV-mediated upregulation of Wnt5a/b protein in osteoclast precursors. Recombinant Wnt5b and retrovirus-mediated expression of Wnt5a enhanced osteoclast differentiation from human and murine monocytic precursors, processes facilitated by RTV. In contrast, canonical Wnt signaling mediated by Wnt3a suppressed osteoclastogenesis. Both RTV and Wnt5b inhibited canonical, β-catenin/T cell factor-based Wnt reporter activation in osteoclast precursors. RTV- and Wnt5-induced osteoclast differentiation were dependent upon the receptor-like tyrosine kinase Ryk, suggesting that Ryk may act as a Wnt5a/b receptor in this context. This is the first demonstration of a direct role for Wnt signaling pathways and Ryk in regulation of osteoclast differentiation, and its modulation by a clinically important drug, ritonavir. These studies

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.

Endothelial Dysfunction in Human Diabetes Is Mediated by Wnt5a-JNK Signaling.

Science.gov (United States)

Bretón-Romero, Rosa; Feng, Bihua; Holbrook, Monika; Farb, Melissa G; Fetterman, Jessica L; Linder, Erika A; Berk, Brittany D; Masaki, Nobuyuki; Weisbrod, Robert M; Inagaki, Elica; Gokce, Noyan; Fuster, Jose J; Walsh, Kenneth; Hamburg, Naomi M

2016-03-01

Endothelial dysfunction is linked to insulin resistance, inflammatory activation, and increased cardiovascular risk in diabetes mellitus; however, the mechanisms remain incompletely understood. Recent studies have identified proinflammatory signaling of wingless-type family member (Wnt) 5a through c-jun N-terminal kinase (JNK) as a regulator of metabolic dysfunction with potential relevance to vascular function. We sought to gain evidence that increased activation of Wnt5a-JNK signaling contributes to impaired endothelial function in patients with diabetes mellitus. We measured flow-mediated dilation of the brachial artery and characterized freshly isolated endothelial cells by protein expression, eNOS activation, and nitric oxide production in 85 subjects with type 2 diabetes mellitus (n=42) and age- and sex-matched nondiabetic controls (n=43) and in human aortic endothelial cells treated with Wnt5a. Endothelial cells from patients with diabetes mellitus displayed 1.3-fold higher Wnt5a levels (P=0.01) along with 1.4-fold higher JNK activation (P<0.01) without a difference in total JNK levels. Higher JNK activation was associated with lower flow-mediated dilation, consistent with endothelial dysfunction (r=0.53, P=0.02). Inhibition of Wnt5a and JNK signaling restored insulin and A23187-mediated eNOS activation and improved nitric oxide production in endothelial cells from patients with diabetes mellitus. In endothelial cells from nondiabetic controls, rWnt5a treatment inhibited eNOS activation replicating the diabetic endothelial phenotype. In human aortic endothelial cells, Wnt5a-induced impairment of eNOS activation and nitric oxide production was reversed by Wnt5a and JNK inhibition. Our findings demonstrate that noncanonical Wnt5a signaling and JNK activity contribute to vascular insulin resistance and endothelial dysfunction and may represent a novel therapeutic opportunity to protect the vasculature in patients with diabetes mellitus. © 2016 American Heart

Improving traffic signal management and operations : a basic service model.

Science.gov (United States)

2009-12-01

This report provides a guide for achieving a basic service model for traffic signal management and : operations. The basic service model is based on simply stated and defensible operational objectives : that consider the staffing level, expertise and...

An Online Full-Body Motion Recognition Method Using Sparse and Deficient Signal Sequences

Directory of Open Access Journals (Sweden)

Chengyu Guo

2014-01-01

Full Text Available This paper presents a method to recognize continuous full-body human motion online by using sparse, low-cost sensors. The only input signals needed are linear accelerations without any rotation information, which are provided by four Wiimote sensors attached to the four human limbs. Based on the fused hidden Markov model (FHMM and autoregressive process, a predictive fusion model (PFM is put forward, which considers the different influences of the upper and lower limbs, establishes HMM for each part, and fuses them using a probabilistic fusion model. Then an autoregressive process is introduced in HMM to predict the gesture, which enables the model to deal with incomplete signal data. In order to reduce the number of alternatives in the online recognition process, a graph model is built that rejects parts of motion types based on the graph structure and previous recognition results. Finally, an online signal segmentation method based on semantics information and PFM is presented to finish the efficient recognition task. The results indicate that the method is robust with a high recognition rate of sparse and deficient signals and can be used in various interactive applications.

Development of a Modified Kernel Regression Model for a Robust Signal Reconstruction

Energy Technology Data Exchange (ETDEWEB)

Ahmed, Ibrahim; Heo, Gyunyoung [Kyung Hee University, Yongin (Korea, Republic of)

2016-10-15

The demand for robust and resilient performance has led to the use of online-monitoring techniques to monitor the process parameters and signal validation. On-line monitoring and signal validation techniques are the two important terminologies in process and equipment monitoring. These techniques are automated methods of monitoring instrument performance while the plant is operating. To implementing these techniques, several empirical models are used. One of these models is nonparametric regression model, otherwise known as kernel regression (KR). Unlike parametric models, KR is an algorithmic estimation procedure which assumes no significant parameters, and it needs no training process after its development when new observations are prepared; which is good for a system characteristic of changing due to ageing phenomenon. Although KR is used and performed excellently when applied to steady state or normal operating data, it has limitation in time-varying data that has several repetition of the same signal, especially if those signals are used to infer the other signals. The convectional KR has limitation in correctly estimating the dependent variable when time-varying data with repeated values are used to estimate the dependent variable especially in signal validation and monitoring. Therefore, we presented here in this work a modified KR that can resolve this issue which can also be feasible in time domain. Data are first transformed prior to the Euclidian distance evaluation considering their slopes/changes with respect to time. The performance of the developed model is evaluated and compared with that of conventional KR using both the lab experimental data and the real time data from CNS provided by KAERI. The result shows that the proposed developed model, having demonstrated high performance accuracy than that of conventional KR, is capable of resolving the identified limitation with convectional KR. We also discovered that there is still need to further

Enhanced Reconstitution of Human Erythropoiesis and Thrombopoiesis in an Immunodeficient Mouse Model with KitWv Mutations

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Ayano Yurino

2016-09-01

Full Text Available In human-to-mouse xenograft models, reconstitution of human hematopoiesis is usually B-lymphoid dominant. Here we show that the introduction of homozygous KitWv mutations into C57BL/6.Rag2nullIl2rgnull mice with NOD-Sirpa (BRGS strongly promoted human multi-lineage reconstitution. After xenotransplantation of human CD34+CD38− cord blood cells, these newly generated C57BL/6.Rag2nullIl2rgnullNOD-Sirpa KitWv/Wv (BRGSKWv/Wv mice showed significantly higher levels of human cell chimerism and long-term multi-lineage reconstitution compared with BRGS mice. Strikingly, this mouse displayed a robust reconstitution of human erythropoiesis and thrombopoiesis with terminal maturation in the bone marrow. Furthermore, depletion of host macrophages by clodronate administration resulted in the presence of human erythrocytes and platelets in the circulation. Thus, attenuation of mouse KIT signaling greatly enhances the multi-lineage differentiation of human hematopoietic stem and progenitor cells (HSPCs in mouse bone marrow, presumably by outcompeting mouse HSPCs to occupy suitable microenvironments. The BRGSKWv/Wv mouse model is a useful tool to study human multi-lineage hematopoiesis.

Reference analysis of the signal + background model in counting experiments

Science.gov (United States)

Casadei, D.

2012-01-01

The model representing two independent Poisson processes, labelled as ``signal'' and ``background'' and both contributing additively to the total number of counted events, is considered from a Bayesian point of view. This is a widely used model for the searches of rare or exotic events in presence of a background source, as for example in the searches performed by high-energy physics experiments. In the assumption of prior knowledge about the background yield, a reference prior is obtained for the signal alone and its properties are studied. Finally, the properties of the full solution, the marginal reference posterior, are illustrated with few examples.

A speed guidance strategy for multiple signalized intersections based on car-following model

Science.gov (United States)

Tang, Tie-Qiao; Yi, Zhi-Yan; Zhang, Jian; Wang, Tao; Leng, Jun-Qiang

2018-04-01

Signalized intersection has great roles in urban traffic system. The signal infrastructure and the driving behavior near the intersection are paramount factors that have significant impacts on traffic flow and energy consumption. In this paper, a speed guidance strategy is introduced into a car-following model to study the driving behavior and the fuel consumption in a single-lane road with multiple signalized intersections. The numerical results indicate that the proposed model can reduce the fuel consumption and the average stop times. The findings provide insightful guidance for the eco-driving strategies near the signalized intersections.

FXR silencing in human colon cancer by DNA methylation and KRAS signaling.

Science.gov (United States)

Bailey, Ann M; Zhan, Le; Maru, Dipen; Shureiqi, Imad; Pickering, Curtis R; Kiriakova, Galina; Izzo, Julie; He, Nan; Wei, Caimiao; Baladandayuthapani, Veerabhadran; Liang, Han; Kopetz, Scott; Powis, Garth; Guo, Grace L

2014-01-01

Farnesoid X receptor (FXR) is a bile acid nuclear receptor described through mouse knockout studies as a tumor suppressor for the development of colon adenocarcinomas. This study investigates the regulation of FXR in the development of human colon cancer. We used immunohistochemistry of FXR in normal tissue (n = 238), polyps (n = 32), and adenocarcinomas, staged I-IV (n = 43, 39, 68, and 9), of the colon; RT-quantitative PCR, reverse-phase protein array, and Western blot analysis in 15 colon cancer cell lines; NR1H4 promoter methylation and mRNA expression in colon cancer samples from The Cancer Genome Atlas; DNA methyltransferase inhibition; methyl-DNA immunoprecipitation (MeDIP); bisulfite sequencing; and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) knockdown assessment to investigate FXR regulation in colon cancer development. Immunohistochemistry and quantitative RT-PCR revealed that expression and function of FXR was reduced in precancerous lesions and silenced in a majority of stage I-IV tumors. FXR expression negatively correlated with phosphatidylinositol-4, 5-bisphosphate 3 kinase signaling and the epithelial-to-mesenchymal transition. The NR1H4 promoter is methylated in ~12% colon cancer The Cancer Genome Atlas samples, and methylation patterns segregate with tumor subtypes. Inhibition of DNA methylation and KRAS silencing both increased FXR expression. FXR expression is decreased early in human colon cancer progression, and both DNA methylation and KRAS signaling may be contributing factors to FXR silencing. FXR potentially suppresses epithelial-to-mesenchymal transition and other oncogenic signaling cascades, and restoration of FXR activity, by blocking silencing mechanisms or increasing residual FXR activity, represents promising therapeutic options for the treatment of colon cancer.

{sup 131}I-CRTX internal dosimetry: animal model and human extrapolation

Energy Technology Data Exchange (ETDEWEB)

Andrade, Henrique Martins de; Ferreira, Andrea Vidal; Soares, Marcella Araugio; Silveira, Marina Bicalho; Santos, Raquel Gouvea dos [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN-CNEN-MG), Belo Horizonte, MG (Brazil)], e-mail: hma@cdtn.br

2009-07-01

Snake venoms molecules have been shown to play a role not only in the survival and proliferation of tumor cells but also in the processes of tumor cell adhesion, migration and angiogenesis. {sup 125}I-Crtx, a radiolabeled version of a peptide derived from Crotalus durissus terrificus snake venom, specifically binds to tumor and triggers apoptotic signalling. At the present work, {sup 125}I-Crtx biokinetic data (evaluated in mice bearing Erlich tumor) were treated by MIRD formalism to perform Internal Dosimetry studies. Doses in several organs of mice were determinate, as well as in implanted tumor, for {sup 131}I-Crtx. Doses results obtained for animal model were extrapolated to humans assuming a similar concentration ratio among various tissues between mouse and human. In the extrapolation, it was used human organ masses from Cristy/Eckerman phantom. Both penetrating and non-penetrating radiation from {sup 131}I in the tissue were considered in dose calculations. (author)

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,

GH receptor signaling in skeletal muscle and adipose tissue in human subjects following exposure to an intravenous GH bolus

DEFF Research Database (Denmark)

Jørgensen, Jens O L; Jessen, Niels; Pedersen, Steen Bønløkke

2006-01-01

Growth hormone (GH) regulates muscle and fat metabolism, which impacts on body composition and insulin sensitivity, but the underlying GH signaling pathways have not been studied in vivo in humans. We investigated GH signaling in biopsies from muscle and abdominal fat obtained 30 (n = 3) or 60 (n...... was measured by in vitro phosphorylation of PI. STAT5 DNA binding activity was assessed with EMSA, and the expression of IGF-I and SOCS mRNA was measured by real-time RT-PCR. GH induced a 52% increase in circulating FFA levels with peak values after 155 min (P = 0.03). Tyrosine-phosphorylated STAT5...... tended to increase after GH in muscle and fat, respectively. We conclude that 1) STAT5 is acutely activated in human muscle and fat after a GH bolus, but additional downstream GH signaling was significant only in fat; 2) the direct GH effects in muscle need further characterization; and 3) this human...

A signal detection-item response theory model for evaluating neuropsychological measures.

Science.gov (United States)

Thomas, Michael L; Brown, Gregory G; Gur, Ruben C; Moore, Tyler M; Patt, Virginie M; Risbrough, Victoria B; Baker, Dewleen G

2018-02-05

Models from signal detection theory are commonly used to score neuropsychological test data, especially tests of recognition memory. Here we show that certain item response theory models can be formulated as signal detection theory models, thus linking two complementary but distinct methodologies. We then use the approach to evaluate the validity (construct representation) of commonly used research measures, demonstrate the impact of conditional error on neuropsychological outcomes, and evaluate measurement bias. Signal detection-item response theory (SD-IRT) models were fitted to recognition memory data for words, faces, and objects. The sample consisted of U.S. Infantry Marines and Navy Corpsmen participating in the Marine Resiliency Study. Data comprised item responses to the Penn Face Memory Test (PFMT; N = 1,338), Penn Word Memory Test (PWMT; N = 1,331), and Visual Object Learning Test (VOLT; N = 1,249), and self-report of past head injury with loss of consciousness. SD-IRT models adequately fitted recognition memory item data across all modalities. Error varied systematically with ability estimates, and distributions of residuals from the regression of memory discrimination onto self-report of past head injury were positively skewed towards regions of larger measurement error. Analyses of differential item functioning revealed little evidence of systematic bias by level of education. SD-IRT models benefit from the measurement rigor of item response theory-which permits the modeling of item difficulty and examinee ability-and from signal detection theory-which provides an interpretive framework encompassing the experimentally validated constructs of memory discrimination and response bias. We used this approach to validate the construct representation of commonly used research measures and to demonstrate how nonoptimized item parameters can lead to erroneous conclusions when interpreting neuropsychological test data. Future work might include the

Chromosome locations of genes encoding human signal transduction adapter proteins, Nck (NCK), Shc (SHC1), and Grb2 (GRB2)

DEFF Research Database (Denmark)

Huebner, K; Kastury, K; Druck, T

1994-01-01

"adapter" proteins, which are involved in transducing signals from receptor tyrosine kinases to downstream signal recipients such as ras, because adaptor protein genes could also, logically, serve as targets of mutation, rearrangement, or other aberration in disease. Therefore, DNAs from panels of rodent-human......Abnormalities due to chromosomal aberration or point mutation in gene products of growth factor receptors or in ras gene products, which lie on the same signaling pathway, can cause disease in animals and humans. Thus, it can be important to determine chromosomal map positions of genes encoding...... hybrids carrying defined complements of human chromosomes were assayed for the presence of the cognate genes for NCK, SHC, and GRB2, three SH2 or SH2/SH3 (Src homology 2 and 3) domain-containing adapter proteins. Additionally, NCK and SHC genes were more narrowly localized by chromosomal in situ...

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

Science.gov (United States)

Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Non Linear Programming (NLP formulation for quantitative modeling of protein signal transduction pathways.

Directory of Open Access Journals (Sweden)

Alexander Mitsos

Full Text Available Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i excessive CPU time requirements and ii loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Multiobjective Traffic Signal Control Model for Intersection Based on Dynamic Turning Movements Estimation

Directory of Open Access Journals (Sweden)

Pengpeng Jiao

2014-01-01

Full Text Available The real-time traffic signal control for intersection requires dynamic turning movements as the basic input data. It is impossible to detect dynamic turning movements directly through current traffic surveillance systems, but dynamic origin-destination (O-D estimation can obtain it. However, the combined models of dynamic O-D estimation and real-time traffic signal control are rare in the literature. A framework for the multiobjective traffic signal control model for intersection based on dynamic O-D estimation (MSC-DODE is presented. A state-space model using Kalman filtering is first formulated to estimate the dynamic turning movements; then a revised sequential Kalman filtering algorithm is designed to solve the model, and the root mean square error and mean percentage error are used to evaluate the accuracy of estimated dynamic turning proportions. Furthermore, a multiobjective traffic signal control model is put forward to achieve real-time signal control parameters and evaluation indices. Finally, based on practical survey data, the evaluation indices from MSC-DODE are compared with those from Webster method. The actual and estimated turning movements are further input into MSC-DODE, respectively, and results are also compared. Case studies show that results of MSC-DODE are better than those of Webster method and are very close to unavailable actual values.

The Five Key Questions of Human Performance Modeling.

Science.gov (United States)

Wu, Changxu

2018-01-01

Via building computational (typically mathematical and computer simulation) models, human performance modeling (HPM) quantifies, predicts, and maximizes human performance, human-machine system productivity and safety. This paper describes and summarizes the five key questions of human performance modeling: 1) Why we build models of human performance; 2) What the expectations of a good human performance model are; 3) What the procedures and requirements in building and verifying a human performance model are; 4) How we integrate a human performance model with system design; and 5) What the possible future directions of human performance modeling research are. Recent and classic HPM findings are addressed in the five questions to provide new thinking in HPM's motivations, expectations, procedures, system integration and future directions.

Skull Defects in Finite Element Head Models for Source Reconstruction from Magnetoencephalography Signals

Science.gov (United States)

Lau, Stephan; Güllmar, Daniel; Flemming, Lars; Grayden, David B.; Cook, Mark J.; Wolters, Carsten H.; Haueisen, Jens

2016-01-01

Magnetoencephalography (MEG) signals are influenced by skull defects. However, there is a lack of evidence of this influence during source reconstruction. Our objectives are to characterize errors in source reconstruction from MEG signals due to ignoring skull defects and to assess the ability of an exact finite element head model to eliminate such errors. A detailed finite element model of the head of a rabbit used in a physical experiment was constructed from magnetic resonance and co-registered computer tomography imaging that differentiated nine tissue types. Sources of the MEG measurements above intact skull and above skull defects respectively were reconstructed using a finite element model with the intact skull and one incorporating the skull defects. The forward simulation of the MEG signals reproduced the experimentally observed characteristic magnitude and topography changes due to skull defects. Sources reconstructed from measured MEG signals above intact skull matched the known physical locations and orientations. Ignoring skull defects in the head model during reconstruction displaced sources under a skull defect away from that defect. Sources next to a defect were reoriented. When skull defects, with their physical conductivity, were incorporated in the head model, the location and orientation errors were mostly eliminated. The conductivity of the skull defect material non-uniformly modulated the influence on MEG signals. We propose concrete guidelines for taking into account conducting skull defects during MEG coil placement and modeling. Exact finite element head models can improve localization of brain function, specifically after surgery. PMID:27092044

Decoding Individual Finger Movements from One Hand Using Human EEG Signals

Science.gov (United States)

Gonzalez, Jania; Ding, Lei

2014-01-01

Brain computer interface (BCI) is an assistive technology, which decodes neurophysiological signals generated by the human brain and translates them into control signals to control external devices, e.g., wheelchairs. One problem challenging noninvasive BCI technologies is the limited control dimensions from decoding movements of, mainly, large body parts, e.g., upper and lower limbs. It has been reported that complicated dexterous functions, i.e., finger movements, can be decoded in electrocorticography (ECoG) signals, while it remains unclear whether noninvasive electroencephalography (EEG) signals also have sufficient information to decode the same type of movements. Phenomena of broadband power increase and low-frequency-band power decrease were observed in EEG in the present study, when EEG power spectra were decomposed by a principal component analysis (PCA). These movement-related spectral structures and their changes caused by finger movements in EEG are consistent with observations in previous ECoG study, as well as the results from ECoG data in the present study. The average decoding accuracy of 77.11% over all subjects was obtained in classifying each pair of fingers from one hand using movement-related spectral changes as features to be decoded using a support vector machine (SVM) classifier. The average decoding accuracy in three epilepsy patients using ECoG data was 91.28% with the similarly obtained features and same classifier. Both decoding accuracies of EEG and ECoG are significantly higher than the empirical guessing level (51.26%) in all subjects (pEEG as in ECoG, and demonstrates the feasibility of discriminating finger movements from one hand using EEG. These findings are promising to facilitate the development of BCIs with rich control signals using noninvasive technologies. PMID:24416360

Complex signal-based optical coherence tomography angiography enables in vivo visualization of choriocapillaris in human choroid

Science.gov (United States)

Chu, Zhongdi; Chen, Chieh-Li; Zhang, Qinqin; Pepple, Kathryn; Durbin, Mary; Gregori, Giovanni; Wang, Ruikang K.

2017-12-01

The choriocapillaris (CC) plays an essential role in maintaining the normal functions of the human eye. There is increasing interest in the community to develop an imaging technique for visualizing the CC, yet this remains underexplored due to technical limitations. We propose an approach for the visualization of the CC in humans via a complex signal-based optical microangiography (OMAG) algorithm, based on commercially available spectral domain optical coherence tomography (SD-OCT). We show that the complex signal-based OMAG was superior to both the phase and amplitude signal-based approaches in detailing the vascular lobules previously seen with histological analysis. With this improved ability to visualize the lobular vascular networks, it is possible to identify the feeding arterioles and draining venules around the lobules, which is important in understanding the role of the CC in the pathogenesis of ocular diseases. With built-in FastTrac™ and montage scanning capabilities, we also demonstrate wide-field SD-OCT angiograms of the CC with a field of view at 9×11 mm2.

Modeling multimodal human-computer interaction

NARCIS (Netherlands)

Obrenovic, Z.; Starcevic, D.

2004-01-01

Incorporating the well-known Unified Modeling Language into a generic modeling framework makes research on multimodal human-computer interaction accessible to a wide range off software engineers. Multimodal interaction is part of everyday human discourse: We speak, move, gesture, and shift our gaze

Heartbeat Signal from Facial Video for Biometric Recognition

DEFF Research Database (Denmark)

Haque, Mohammad Ahsanul; Nasrollahi, Kamal; Moeslund, Thomas B.

2015-01-01

Different biometric traits such as face appearance and heartbeat signal from Electrocardiogram (ECG)/Phonocardiogram (PCG) are widely used in the human identity recognition. Recent advances in facial video based measurement of cardio-physiological parameters such as heartbeat rate, respiratory rate......, and blood volume pressure provide the possibility of extracting heartbeat signal from facial video instead of using obtrusive ECG or PCG sensors in the body. This paper proposes the Heartbeat Signal from Facial Video (HSFV) as a new biometric trait for human identity recognition, for the first time...... to the best of our knowledge. Feature extraction from the HSFV is accomplished by employing Radon transform on a waterfall model of the replicated HSFV. The pairwise Minkowski distances are obtained from the Radon image as the features. The authentication is accomplished by a decision tree based supervised...

Regulation of Wnt signaling by nociceptive input in animal models

Directory of Open Access Journals (Sweden)

Shi Yuqiang

2012-06-01

Full Text Available Abstract Background Central sensitization-associated synaptic plasticity in the spinal cord dorsal horn (SCDH critically contributes to the development of chronic pain, but understanding of the underlying molecular pathways is still incomplete. Emerging evidence suggests that Wnt signaling plays a crucial role in regulation of synaptic plasticity. Little is known about the potential function of the Wnt signaling cascades in chronic pain development. Results Fluorescent immunostaining results indicate that β-catenin, an essential protein in the canonical Wnt signaling pathway, is expressed in the superficial layers of the mouse SCDH with enrichment at synapses in lamina II. In addition, Wnt3a, a prototypic Wnt ligand that activates the canonical pathway, is also enriched in the superficial layers. Immunoblotting analysis indicates that both Wnt3a a β-catenin are up-regulated in the SCDH of various mouse pain models created by hind-paw injection of capsaicin, intrathecal (i.t. injection of HIV-gp120 protein or spinal nerve ligation (SNL. Furthermore, Wnt5a, a prototypic Wnt ligand for non-canonical pathways, and its receptor Ror2 are also up-regulated in the SCDH of these models. Conclusion Our results suggest that Wnt signaling pathways are regulated by nociceptive input. The activation of Wnt signaling may regulate the expression of spinal central sensitization during the development of acute and chronic pain.

Monitoring UV-induced signalling pathways in an ex vivo skin organ culture model using phospho-antibody array.

Science.gov (United States)

Lenain, Christelle; Gamboa, Bastien; Perrin, Agnes; Séraïdaris, Alexia; Bertino, Béatrice; Rival, Yves; Bernardi, Mathieu; Piwnica, David; Méhul, Bruno

2018-05-01

We investigated UV-induced signalling in an ex vivo skin organ culture model using phospho-antibody array. Phosphorylation modulations were analysed in time-course experiments following exposure to solar-simulated UV and validated by Western blot analyses. We found that UV induced P-p38 and its substrates, P-ERK1/2 and P-AKT, which were previously shown to be upregulated by UV in cultured keratinocytes and in vivo human skin. This indicates that phospho-antibody array applied to ex vivo skin organ culture is a relevant experimental system to investigate signalling events following perturbations. As the identified proteins are components of pathways implicated in skin tumorigenesis, UV-exposed skin organ culture model could be used to investigate the effect on these pathways of NMSC cancer drug candidates. In addition, we found that phospho-HCK is induced upon UV exposure, producing a new candidate for future studies investigating its role in the skin response to UV and UV-induced carcinogenesis. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Signal-enhancement reflective pulse oximeter with Fresnel lens

Science.gov (United States)

Chung, Shuang-Chao; Sun, Ching-Cherng

2016-09-01

In this paper, a new reflective pulse oximeter is proposed and demonstrated with implanting a Fresnel lens, which enhances the reflected signal. An optical simulation model incorporated with human skin characteristics is presented to evaluate the capability of the Fresnel lens. In addition, the distance between the light emitting diode and the photodiode is optimized. Compared with the other reflective oximeters, the reflected signal light detected by the photodiode is enhanced to more than 140%.

Switched Cooperative Driving Model towards Human Vehicle Copiloting Situation: A Cyberphysical Perspective

Directory of Open Access Journals (Sweden)

Yang Li

2018-01-01

Full Text Available Development of highly automated and intelligent vehicles can lead to the reduction of driver workload. However, it also causes the out-of-the-loop problem to drivers, which leaves drivers handicapped in their ability to take over manual operations in emergency situations. This contribution puts forth a new switched driving strategy to avoid some of the negative consequences associated with out-of-the-loop performance by having drivers assume manual control at periodic intervals. To minimize the impact of the transitions between automated and manual driving on traffic operations, a switched cooperative driving model towards human vehicle copiloting situation is proposed by considering the vehicle dynamics and the realistic intervehicle communication in a cyberphysical view. The design method of the switching signal for the switched cooperative driving model is given based on the Lyapunov stability theory with the comprehensive consideration of platoon stability and human factors. The good agreement between simulation results and theoretical analysis illustrates the effectiveness of the proposed methods.

DigitalHuman (DH): An Integrative Mathematical Model ofHuman Physiology

Science.gov (United States)

Hester, Robert L.; Summers, Richard L.; lIescu, Radu; Esters, Joyee; Coleman, Thomas G.

2010-01-01

Mathematical models and simulation are important tools in discovering the key causal relationships governing physiological processes and improving medical intervention when physiological complexity is a central issue. We have developed a model of integrative human physiology called DigitalHuman (DH) consisting of -5000 variables modeling human physiology describing cardiovascular, renal, respiratory, endocrine, neural and metabolic physiology. Users can view time-dependent solutions and interactively introduce perturbations by altering numerical parameters to investigate new hypotheses. The variables, parameters and quantitative relationships as well as all other model details are described in XML text files. All aspects of the model, including the mathematical equations describing the physiological processes are written in XML open source, text-readable files. Model structure is based upon empirical data of physiological responses documented within the peer-reviewed literature. The model can be used to understand proposed physiological mechanisms and physiological interactions that may not be otherwise intUitively evident. Some of the current uses of this model include the analyses of renal control of blood pressure, the central role of the liver in creating and maintaining insulin resistance, and the mechanisms causing orthostatic hypotension in astronauts. Additionally the open source aspect of the modeling environment allows any investigator to add detailed descriptions of human physiology to test new concepts. The model accurately predicts both qualitative and more importantly quantitative changes in clinically and experimentally observed responses. DigitalHuman provides scientists a modeling environment to understand the complex interactions of integrative physiology. This research was supported by.NIH HL 51971, NSF EPSCoR, and NASA

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.

RAS signalling in energy metabolism and rare human diseases.

Science.gov (United States)

Dard, L; Bellance, N; Lacombe, D; Rossignol, R

2018-05-08

The RAS pathway is a highly conserved cascade of protein-protein interactions and phosphorylation that is at the heart of signalling networks that govern proliferation, differentiation and cell survival. Recent findings indicate that the RAS pathway plays a role in the regulation of energy metabolism via the control of mitochondrial form and function but little is known on the participation of this effect in RAS-related rare human genetic diseases. Germline mutations that hyperactivate the RAS pathway have been discovered and linked to human developmental disorders that are known as RASopathies. Individuals with RASopathies, which are estimated to affect approximately 1/1000 human birth, share many overlapping characteristics, including cardiac malformations, short stature, neurocognitive impairment, craniofacial dysmorphy, cutaneous, musculoskeletal, and ocular abnormalities, hypotonia and a predisposition to developing cancer. Since the identification of the first RASopathy, type 1 neurofibromatosis (NF1), which is caused by the inactivation of neurofibromin 1, several other syndromes have been associated with mutations in the core components of the RAS-MAPK pathway. These syndromes include Noonan syndrome (NS), Noonan syndrome with multiple lentigines (NSML), which was formerly called LEOPARD syndrome, Costello syndrome (CS), cardio-facio-cutaneous syndrome (CFC), Legius syndrome (LS) and capillary malformation-arteriovenous malformation syndrome (CM-AVM). Here, we review current knowledge about the bioenergetics of the RASopathies and discuss the molecular control of energy homeostasis and mitochondrial physiology by the RAS pathway. Copyright © 2018 Elsevier B.V. All rights reserved.

Oxygen in human health from life to death – An approach to teaching redox biology and signaling to graduate and medical students

Directory of Open Access Journals (Sweden)

Margaret M. Briehl

2015-08-01

Full Text Available In the absence of oxygen human life is measured in minutes. In the presence of oxygen, normal metabolism generates reactive species (ROS that have the potential to cause cell injury contributing to human aging and disease. Between these extremes, organisms have developed means for sensing oxygen and ROS and regulating their cellular processes in response. Redox signaling contributes to the control of cell proliferation and death. Aberrant redox signaling underlies many human diseases. The attributes acquired by altered redox homeostasis in cancer cells illustrate this particularly well. This teaching review and the accompanying illustrations provide an introduction to redox biology and signaling aimed at instructors of graduate and medical students.

Wnt Signaling in Kidney Development and Disease.

Science.gov (United States)

Wang, Yongping; Zhou, Chengji J; Liu, Youhua

2018-01-01

Wnt signal cascade is an evolutionarily conserved, developmental pathway that regulates embryogenesis, injury repair, and pathogenesis of human diseases. It is well established that Wnt ligands transmit their signal via canonical, β-catenin-dependent and noncanonical, β-catenin-independent mechanisms. Mounting evidence has revealed that Wnt signaling plays a key role in controlling early nephrogenesis and is implicated in the development of various kidney disorders. Dysregulations of Wnt expression cause a variety of developmental abnormalities and human diseases, such as congenital anomalies of the kidney and urinary tract, cystic kidney, and renal carcinoma. Multiple Wnt ligands, their receptors, and transcriptional targets are upregulated during nephron formation, which is crucial for mediating the reciprocal interaction between primordial tissues of ureteric bud and metanephric mesenchyme. Renal cysts are also associated with disrupted Wnt signaling. In addition, Wnt components are important players in renal tumorigenesis. Activation of Wnt/β-catenin is instrumental for tubular repair and regeneration after acute kidney injury. However, sustained activation of this signal cascade is linked to chronic kidney diseases and renal fibrosis in patients and experimental animal models. Mechanistically, Wnt signaling controls a diverse array of biologic processes, such as cell cycle progression, cell polarity and migration, cilia biology, and activation of renin-angiotensin system. In this chapter, we have reviewed recent findings that implicate Wnt signaling in kidney development and diseases. Targeting this signaling may hold promise for future treatment of kidney disorders in patients. Copyright © 2018 Elsevier Inc. All rights reserved.

Identification of a putative nuclear export signal motif in human NANOG homeobox domain

International Nuclear Information System (INIS)

Park, Sung-Won; Do, Hyun-Jin; Huh, Sun-Hyung; Sung, Boreum; Uhm, Sang-Jun; Song, Hyuk; Kim, Nam-Hyung; Kim, Jae-Hwan

2012-01-01

Highlights: ► We found the putative nuclear export signal motif within human NANOG homeodomain. ► Leucine-rich residues are important for human NANOG homeodomain nuclear export. ► CRM1-specific inhibitor LMB blocked the potent human NANOG NES-mediated nuclear export. -- Abstract: NANOG is a homeobox-containing transcription factor that plays an important role in pluripotent stem cells and tumorigenic cells. To understand how nuclear localization of human NANOG is regulated, the NANOG sequence was examined and a leucine-rich nuclear export signal (NES) motif ( 125 MQELSNILNL 134 ) was found in the homeodomain (HD). To functionally validate the putative NES motif, deletion and site-directed mutants were fused to an EGFP expression vector and transfected into COS-7 cells, and the localization of the proteins was examined. While hNANOG HD exclusively localized to the nucleus, a mutant with both NLSs deleted and only the putative NES motif contained (hNANOG HD-ΔNLSs) was predominantly cytoplasmic, as observed by nucleo/cytoplasmic fractionation and Western blot analysis as well as confocal microscopy. Furthermore, site-directed mutagenesis of the putative NES motif in a partial hNANOG HD only containing either one of the two NLS motifs led to localization in the nucleus, suggesting that the NES motif may play a functional role in nuclear export. Furthermore, CRM1-specific nuclear export inhibitor LMB blocked the hNANOG potent NES-mediated export, suggesting that the leucine-rich motif may function in CRM1-mediated nuclear export of hNANOG. Collectively, a NES motif is present in the hNANOG HD and may be functionally involved in CRM1-mediated nuclear export pathway.

Accessing key steps of human tumor progression in vivo by using an avian embryo model

Science.gov (United States)

Hagedorn, Martin; Javerzat, Sophie; Gilges, Delphine; Meyre, Aurélie; de Lafarge, Benjamin; Eichmann, Anne; Bikfalvi, Andreas

2005-02-01

Experimental in vivo tumor models are essential for comprehending the dynamic process of human cancer progression, identifying therapeutic targets, and evaluating antitumor drugs. However, current rodent models are limited by high costs, long experimental duration, variability, restricted accessibility to the tumor, and major ethical concerns. To avoid these shortcomings, we investigated whether tumor growth on the chick chorio-allantoic membrane after human glioblastoma cell grafting would replicate characteristics of the human disease. Avascular tumors consistently formed within 2 days, then progressed through vascular endothelial growth factor receptor 2-dependent angiogenesis, associated with hemorrhage, necrosis, and peritumoral edema. Blocking of vascular endothelial growth factor receptor 2 and platelet-derived growth factor receptor signaling pathways by using small-molecule receptor tyrosine kinase inhibitors abrogated tumor development. Gene regulation during the angiogenic switch was analyzed by oligonucleotide microarrays. Defined sample selection for gene profiling permitted identification of regulated genes whose functions are associated mainly with tumor vascularization and growth. Furthermore, expression of known tumor progression genes identified in the screen (IL-6 and cysteine-rich angiogenic inducer 61) as well as potential regulators (lumican and F-box-only 6) follow similar patterns in patient glioma. The model reliably simulates key features of human glioma growth in a few days and thus could considerably increase the speed and efficacy of research on human tumor progression and preclinical drug screening. angiogenesis | animal model alternatives | glioblastoma

BDNF/TrkB signaling protects HT-29 human colon cancer cells from EGFR inhibition

International Nuclear Information System (INIS)

Brunetto de Farias, Caroline; Heinen, Tiago Elias; Pereira dos Santos, Rafael; Abujamra, Ana Lucia; Schwartsmann, Gilberto

2012-01-01

Highlights: ► BDNF protected HT-29 colorectal cancer cells from the antitumor effect of cetuximab. ► TrkB inhibition potentiated the antitumor effect of cetuximab. ► BDNF/TrkB signaling might be involved in resistance to anti-EGFR therapy. -- Abstract: The clinical success of targeted treatment of colorectal cancer (CRC) is often limited by resistance to anti-epidermal growth factor receptor (EGFR) therapy. The neurotrophin brain-derived neurotrophic factor (BDNF) and its receptor TrkB have recently emerged as anticancer targets, and we have previously shown increased BDNF levels in CRC tumor samples. Here we report the findings from in vitro experiments suggesting that BDNF/TrkB signaling can protect CRC cells from the antitumor effects of EGFR blockade. The anti-EGFR monoclonal antibody cetuximab reduced both cell proliferation and the mRNA expression of BDNF and TrkB in human HT-29 CRC cells. The inhibitory effect of cetuximab on cell proliferation and survival was counteracted by the addition of human recombinant BDNF. Finally, the Trk inhibitor K252a synergistically enhanced the effect of cetuximab on cell proliferation, and this effect was blocked by BDNF. These results provide the first evidence that increased BDNF/TrkB signaling might play a role in resistance to EGFR blockade. Moreover, it is possible that targeting TrkB could potentiate the anticancer effects of anti-EGFR therapy.

From deep-sea volcanoes to human pathogens: a conserved quorum-sensing signal in Epsilonproteobacteria.

Science.gov (United States)

Pérez-Rodríguez, Ileana; Bolognini, Marie; Ricci, Jessica; Bini, Elisabetta; Vetriani, Costantino

2015-05-01

Chemosynthetic Epsilonproteobacteria from deep-sea hydrothermal vents colonize substrates exposed to steep thermal and redox gradients. In many bacteria, substrate attachment, biofilm formation, expression of virulence genes and host colonization are partly controlled via a cell density-dependent mechanism involving signal molecules, known as quorum sensing. Within the Epsilonproteobacteria, quorum sensing has been investigated only in human pathogens that use the luxS/autoinducer-2 (AI-2) mechanism to control the expression of some of these functions. In this study we showed that luxS is conserved in Epsilonproteobacteria and that pathogenic and mesophilic members of this class inherited this gene from a thermophilic ancestor. Furthermore, we provide evidence that the luxS gene is expressed--and a quorum-sensing signal is produced--during growth of Sulfurovum lithotrophicum and Caminibacter mediatlanticus, two Epsilonproteobacteria from deep-sea hydrothermal vents. Finally, we detected luxS transcripts in Epsilonproteobacteria-dominated biofilm communities collected from deep-sea hydrothermal vents. Taken together, our findings indicate that the epsiloproteobacterial lineage of the LuxS enzyme originated in high-temperature geothermal environments and that, in vent Epsilonproteobacteria, luxS expression is linked to the production of AI-2 signals, which are likely produced in situ at deep-sea vents. We conclude that the luxS gene is part of the ancestral epsilonproteobacterial genome and represents an evolutionary link that connects thermophiles to human pathogens.

Vicarious learning from human models in monkeys.

Science.gov (United States)

Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

2012-01-01

We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

Making Faces - State-Space Models Applied to Multi-Modal Signal Processing

DEFF Research Database (Denmark)

Lehn-Schiøler, Tue

2005-01-01

The two main focus areas of this thesis are State-Space Models and multi modal signal processing. The general State-Space Model is investigated and an addition to the class of sequential sampling methods is proposed. This new algorithm is denoted as the Parzen Particle Filter. Furthermore...... optimizer can be applied to speed up convergence. The linear version of the State-Space Model, the Kalman Filter, is applied to multi modal signal processing. It is demonstrated how a State-Space Model can be used to map from speech to lip movements. Besides the State-Space Model and the multi modal...... application an information theoretic vector quantizer is also proposed. Based on interactions between particles, it is shown how a quantizing scheme based on an analytic cost function can be derived....

Does human body odor represent a significant and rewarding social signal to individuals high in social openness?

Science.gov (United States)

Lübke, Katrin T; Croy, Ilona; Hoenen, Matthias; Gerber, Johannes; Pause, Bettina M; Hummel, Thomas

2014-01-01

Across a wide variety of domains, experts differ from novices in their response to stimuli linked to their respective field of expertise. It is currently unknown whether similar patterns can be observed with regard to social expertise. The current study therefore focuses on social openness, a central social skill necessary to initiate social contact. Human body odors were used as social cues, as they inherently signal the presence of another human being. Using functional MRI, hemodynamic brain responses to body odors of women reporting a high (n = 14) or a low (n = 12) level of social openness were compared. Greater activation within the inferior frontal gyrus and the caudate nucleus was observed in high socially open individuals compared to individuals low in social openness. With the inferior frontal gyrus being a crucial part of the human mirror neuron system, and the caudate nucleus being implicated in social reward, it is discussed whether human body odor might constitute more of a significant and rewarding social signal to individuals high in social openness compared to individuals low in social openness process.

Concordant but Varied Phenotypes among Duchenne Muscular Dystrophy Patient-Specific Myoblasts Derived using a Human iPSC-Based Model

Directory of Open Access Journals (Sweden)

In Young Choi

2016-06-01

Full Text Available Duchenne muscular dystrophy (DMD remains an intractable genetic disease. Althogh there are several animal models of DMD, there is no human cell model that carries patient-specific DYSTROPHIN mutations. Here, we present a human DMD model using human induced pluripotent stem cells (hiPSCs. Our model reveals concordant disease-related phenotypes with patient-dependent variation, which are partially reversed by genetic and pharmacological approaches. Our “chemical-compound-based” strategy successfully directs hiPSCs into expandable myoblasts, which exhibit a myogenic transcriptional program, forming striated contractile myofibers and participating in muscle regeneration in vivo. DMD-hiPSC-derived myoblasts show disease-related phenotypes with patient-to-patient variability, including aberrant expression of inflammation or immune-response genes and collagens, increased BMP/TGFβ signaling, and reduced fusion competence. Furthermore, by genetic correction and pharmacological “dual-SMAD” inhibition, the DMD-hiPSC-derived myoblasts and genetically corrected isogenic myoblasts form “rescued” multi-nucleated myotubes. In conclusion, our findings demonstrate the feasibility of establishing a human “DMD-in-a-dish” model using hiPSC-based disease modeling.

Toward understanding social cues and signals in human-robot interaction: effects of robot gaze and proxemic behavior.

Science.gov (United States)

Fiore, Stephen M; Wiltshire, Travis J; Lobato, Emilio J C; Jentsch, Florian G; Huang, Wesley H; Axelrod, Benjamin

2013-01-01

As robots are increasingly deployed in settings requiring social interaction, research is needed to examine the social signals perceived by humans when robots display certain social cues. In this paper, we report a study designed to examine how humans interpret social cues exhibited by robots. We first provide a brief overview of perspectives from social cognition in humans and how these processes are applicable to human-robot interaction (HRI). We then discuss the need to examine the relationship between social cues and signals as a function of the degree to which a robot is perceived as a socially present agent. We describe an experiment in which social cues were manipulated on an iRobot Ava(TM) mobile robotics platform in a hallway navigation scenario. Cues associated with the robot's proxemic behavior were found to significantly affect participant perceptions of the robot's social presence and emotional state while cues associated with the robot's gaze behavior were not found to be significant. Further, regardless of the proxemic behavior, participants attributed more social presence and emotional states to the robot over repeated interactions than when they first interacted with it. Generally, these results indicate the importance for HRI research to consider how social cues expressed by a robot can differentially affect perceptions of the robot's mental states and intentions. The discussion focuses on implications for the design of robotic systems and future directions for research on the relationship between social cues and signals.

Towards understanding social cues and signals in human-robot interaction: Effects of robot gaze and proxemic behavior

Directory of Open Access Journals (Sweden)

Stephen M. Fiore

2013-11-01

Full Text Available As robots are increasingly deployed in settings requiring social interaction, research is needed to examine the social signals perceived by humans when robots display certain social cues. In this paper, we report a study designed to examine how humans interpret social cues exhibited by robots. We first provide a brief overview of perspectives from social cognition in humans and how these processes are applicable to human-robot interaction (HRI. We then discuss the need to examine the relationship between social cues and signals as a function of the degree to which a robot is perceived as a socially present agent. We describe an experiment in which social cues were manipulated on an iRobot Ava™ Mobile Robotics Platform in a hallway navigation scenario. Cues associated with the robot’s proxemic behavior were found to significantly affect participant perceptions of the robot’s social presence and emotional state while cues associated with the robot’s gaze behavior were not found to be significant. Further, regardless of the proxemic behavior, participants attributed more social presence and emotional states to the robot over repeated interactions than when they first interacted with it. Generally, these results indicate the importance for HRI research to consider how social cues expressed by a robot can differentially affect perceptions of the robot’s mental states and intentions. The discussion focuses on implications for the design of robotic systems and future directions for research on the relationship between social cues and signals.

Domain altering SNPs in the human proteome and their impact on signaling pathways.

Directory of Open Access Journals (Sweden)

Yichuan Liu

Full Text Available Single nucleotide polymorphisms (SNPs constitute an important mode of genetic variations observed in the human genome. A small fraction of SNPs, about four thousand out of the ten million, has been associated with genetic disorders and complex diseases. The present study focuses on SNPs that fall on protein domains, 3D structures that facilitate connectivity of proteins in cell signaling and metabolic pathways. We scanned the human proteome using the PROSITE web tool and identified proteins with SNP containing domains. We showed that SNPs that fall on protein domains are highly statistically enriched among SNPs linked to hereditary disorders and complex diseases. Proteins whose domains are dramatically altered by the presence of an SNP are even more likely to be present among proteins linked to hereditary disorders. Proteins with domain-altering SNPs comprise highly connected nodes in cellular pathways such as the focal adhesion, the axon guidance pathway and the autoimmune disease pathways. Statistical enrichment of domain/motif signatures in interacting protein pairs indicates extensive loss of connectivity of cell signaling pathways due to domain-altering SNPs, potentially leading to hereditary disorders.

MOTORCYCLE CRASH PREDICTION MODEL FOR NON-SIGNALIZED INTERSECTIONS

Directory of Open Access Journals (Sweden)

S. HARNEN

2003-01-01

Full Text Available This paper attempts to develop a prediction model for motorcycle crashes at non-signalized intersections on urban roads in Malaysia. The Generalized Linear Modeling approach was used to develop the model. The final model revealed that an increase in motorcycle and non-motorcycle flows entering an intersection is associated with an increase in motorcycle crashes. Non-motorcycle flow on major road had the greatest effect on the probability of motorcycle crashes. Approach speed, lane width, number of lanes, shoulder width and land use were also found to be significant in explaining motorcycle crashes. The model should assist traffic engineers to decide the need for appropriate intersection treatment that specifically designed for non-exclusive motorcycle lane facilities.

D2 receptor genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans.

Science.gov (United States)

Fazio, Leonardo; Blasi, Giuseppe; Taurisano, Paolo; Papazacharias, Apostolos; Romano, Raffaella; Gelao, Barbara; Ursini, Gianluca; Quarto, Tiziana; Lo Bianco, Luciana; Di Giorgio, Annabella; Mancini, Marina; Popolizio, Teresa; Rubini, Giuseppe; Bertolino, Alessandro

2011-02-14

Pre-synaptic D2 receptors regulate striatal dopamine release and DAT activity, key factors for modulation of motor pathways. A functional SNP of DRD2 (rs1076560 G>T) is associated with alternative splicing such that the relative expression of D2S (mainly pre-synaptic) vs. D2L (mainly post-synaptic) receptor isoforms is decreased in subjects with the T allele with a putative increase of striatal dopamine levels. To evaluate how DRD2 genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans, we have investigated the association of rs1076560 with BOLD fMRI activity during a motor task. To further evaluate the relationship of this circuitry with dopamine signaling, we also explored the correlation between genotype based differences in motor brain activity and pre-synaptic striatal DAT binding measured with [(123)I] FP-CIT SPECT. Fifty healthy subjects, genotyped for DRD2 rs1076560 were studied with BOLD-fMRI at 3T while performing a visually paced motor task with their right hand; eleven of these subjects also underwent [(123)I]FP-CIT SPECT. SPM5 random-effects models were used for statistical analyses. Subjects carrying the T allele had greater BOLD responses in left basal ganglia, thalamus, supplementary motor area, and primary motor cortex, whose activity was also negatively correlated with reaction time at the task. Moreover, left striatal DAT binding and activity of left supplementary motor area were negatively correlated. The present results suggest that DRD2 genetic variation was associated with focusing of responses in the whole motor network, in which activity of predictable nodes was correlated with reaction time and with striatal pre-synaptic dopamine signaling. Our results in humans may help shed light on genetic risk for neurobiological mechanisms involved in the pathophysiology of disorders with dysregulation of striatal dopamine like Parkinson's disease. Copyright © 2010 Elsevier Inc. All rights reserved.

Variables and potential models for the bleaching of luminescence signals in fluvial environments

Science.gov (United States)

Gray, Harrison J.; Mahan, Shannon

2015-01-01

Luminescence dating of fluvial sediments rests on the assumption that sufficient sunlight is available to remove a previously obtained signal in a process deemed bleaching. However, luminescence signals obtained from sediment in the active channels of rivers often contain residual signals. This paper explores and attempts to build theoretical models for the bleaching of luminescence signals in fluvial settings. We present two models, one for sediment transported in an episodic manner, such as flood-driven washes in arid environments, and one for sediment transported in a continuous manner, such as in large continental scale rivers. The episodic flow model assumes that the majority of sediment is bleached while exposed to sunlight at the near surface between flood events and predicts a power-law decay in luminescence signal with downstream transport distance. The continuous flow model is developed by combining the Beer–Lambert law for the attenuation of light through a water column with a general-order kinetics equation to produce an equation with the form of a double negative exponential. The inflection point of this equation is compared with the sediment concentration from a Rouse profile to derive a non-dimensional number capable of assessing the likely extent of bleaching for a given set of luminescence and fluvial parameters. Although these models are theoretically based and not yet necessarily applicable to real-world fluvial systems, we introduce these ideas to stimulate discussion and encourage the development of comprehensive bleaching models with predictive power.

On the genesis of spike-wave oscillations in a mean-field model of human thalamic and corticothalamic dynamics

International Nuclear Information System (INIS)

Rodrigues, Serafim; Terry, John R.; Breakspear, Michael

2006-01-01

In this Letter, the genesis of spike-wave activity-a hallmark of many generalized epileptic seizures-is investigated in a reduced mean-field model of human neural activity. Drawing upon brain modelling and dynamical systems theory, we demonstrate that the thalamic circuitry of the system is crucial for the generation of these abnormal rhythms, observing that the combination of inhibition from reticular nuclei and excitation from the cortical signal, interplay to generate the spike-wave oscillation. The mechanism revealed provides an explanation of why approaches based on linear stability and Heaviside approximations to the activation function have failed to explain the phenomena of spike-wave behaviour in mean-field models. A mathematical understanding of this transition is a crucial step towards relating spiking network models and mean-field approaches to human brain modelling

Convergent integration of animal model and human studies of bipolar disorder (manic-depressive illness).

Science.gov (United States)

Le-Niculescu, Helen; Patel, Sagar D; Niculescu, Alexander B

2010-10-01

Animal models and human studies of bipolar disorder and other psychiatric disorders are becoming increasingly integrated, prompted by recent successes. Particularly for genomics, the convergence and integration of data across species, experimental modalities and technical platforms is providing a fit-to-disease way of extracting reproducible and biologically important signal, in sharp contrast to the fit-to-cohort effect, disappointing findings to date, and limited reproducibility of human genetic analyses alone. Such work in psychiatry can provide an example of how to address other genetically complex disorders, and in turn will benefit by incorporating concepts from other areas, such as cancer biology and diabetes. Copyright © 2010. Published by Elsevier Ltd.

Numerical modelling of the pump-to-signal relative intensity noise ...

Indian Academy of Sciences (India)

An accurate numerical model to investigate the pump-to-signal relative intensity noise (RIN) transfer in two-pump fibre optical parametric amplifiers (2-P FOPAs) for low modulation frequencies is presented. Compared to other models in the field, this model takes into account the fibre loss, pump depletion as well as the gain ...

Recycling signals in the neural crest

OpenAIRE

Taneyhill, Lisa A.; Bronner-Fraser, Marianne E.

2006-01-01

Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

Recycling signals in the neural crest.

Science.gov (United States)

Taneyhill, Lisa A; Bronner-Fraser, Marianne

2005-01-01

Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

Vicarious learning from human models in monkeys.

Directory of Open Access Journals (Sweden)

Rossella Falcone

Full Text Available We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

BMP signaling in the human fetal ovary is developmentally regulated and promotes primordial germ cell apoptosis.

Science.gov (United States)

Childs, Andrew J; Kinnell, Hazel L; Collins, Craig S; Hogg, Kirsten; Bayne, Rosemary A L; Green, Samira J; McNeilly, Alan S; Anderson, Richard A

2010-08-01

Primordial germ cells (PGCs) are the embryonic precursors of gametes in the adult organism, and their development, differentiation, and survival are regulated by a combination of growth factors collectively known as the germ cell niche. Although many candidate niche components have been identified through studies on mouse PGCs, the growth factor composition of the human PGC niche has not been studied extensively. Here we report a detailed analysis of the expression of components of the bone morphogenetic protein (BMP) signaling apparatus in the human fetal ovary, from postmigratory PGC proliferation to the onset of primordial follicle formation. We find developmentally regulated and reciprocal patterns of expression of BMP2 and BMP4 and identify germ cells to be the exclusive targets of ovarian BMP signaling. By establishing long-term cultures of human fetal ovaries in which PGCs are retained within their physiological niche, we find that BMP4 negatively regulates postmigratory PGC numbers in the human fetal ovary by promoting PGC apoptosis. Finally, we report expression of both muscle segment homeobox (MSX)1 and MSX2 in the human fetal ovary and reveal a selective upregulation of MSX2 expression in human fetal ovary in response to BMP4, suggesting this gene may act as a downstream effector of BMP-induced apoptosis in the ovary, as in other systems. These data reveal for the first time growth factor regulation of human PGC development in a physiologically relevant context and have significant implications for the development of cultures systems for the in vitro maturation of germ cells, and their derivation from pluripotent stem cells.

Multiple logistic regression model of signalling practices of drivers on urban highways

Science.gov (United States)

Puan, Othman Che; Ibrahim, Muttaka Na'iya; Zakaria, Rozana

2015-05-01

Giving signal is a way of informing other road users, especially to the conflicting drivers, the intention of a driver to change his/her movement course. Other users are exposed to hazard situation and risks of accident if the driver who changes his/her course failed to give signal as required. This paper describes the application of logistic regression model for the analysis of driver's signalling practices on multilane highways based on possible factors affecting driver's decision such as driver's gender, vehicle's type, vehicle's speed and traffic flow intensity. Data pertaining to the analysis of such factors were collected manually. More than 2000 drivers who have performed a lane changing manoeuvre while driving on two sections of multilane highways were observed. Finding from the study shows that relatively a large proportion of drivers failed to give any signals when changing lane. The result of the analysis indicates that although the proportion of the drivers who failed to provide signal prior to lane changing manoeuvre is high, the degree of compliances of the female drivers is better than the male drivers. A binary logistic model was developed to represent the probability of a driver to provide signal indication prior to lane changing manoeuvre. The model indicates that driver's gender, type of vehicle's driven, speed of vehicle and traffic volume influence the driver's decision to provide a signal indication prior to a lane changing manoeuvre on a multilane urban highway. In terms of types of vehicles driven, about 97% of motorcyclists failed to comply with the signal indication requirement. The proportion of non-compliance drivers under stable traffic flow conditions is much higher than when the flow is relatively heavy. This is consistent with the data which indicates a high degree of non-compliances when the average speed of the traffic stream is relatively high.

Oncogenic Signaling by Leukemia-Associated Mutant Cbl Proteins

Science.gov (United States)

Nadeau, Scott; An, Wei; Palermo, Nick; Feng, Dan; Ahmad, Gulzar; Dong, Lin; Borgstahl, Gloria E. O.; Natarajan, Amarnath; Naramura, Mayumi; Band, Vimla; Band, Hamid

2013-01-01

Members of the Cbl protein family (Cbl, Cbl-b, and Cbl-c) are E3 ubiquitin ligases that have emerged as critical negative regulators of protein tyrosine kinase (PTK) signaling. This function reflects their ability to directly interact with activated PTKs and to target them as well as their associated signaling components for ubiquitination. Given the critical roles of PTK signaling in driving oncogenesis, recent studies in animal models and genetic analyses in human cancer have firmly established that Cbl proteins function as tumor suppressors. Missense mutations or small in-frame deletions within the regions of Cbl protein that are essential for its E3 activity have been identified in nearly 5% of leukemia patients with myelodysplastic/myeloproliferative disorders. Based on evidence from cell culture studies, in vivo models and clinical data, we discuss the potential signaling mechanisms of mutant Cbl-driven oncogenesis. Mechanistic insights into oncogenic Cbl mutants and associated animal models are likely to enhance our understanding of normal hematopoietic stem cell homeostasis and provide avenues for targeted therapy of mutant Cbl-driven cancers. PMID:23997989

Intercellular calcium signaling occurs between human osteoblasts and osteoclasts and requires activation of osteoclast P2X7 receptors

DEFF Research Database (Denmark)

Jørgensen, Niklas R; Henriksen, Zanne; Sørensen, Ole

2002-01-01

that human osteoclasts expressed functional P2Y1 receptors, but, unexpectedly, desensitization of P2Y1 did not block calcium signaling to osteoclasts. We also found that osteoclasts expressed functional P2X7 receptors and showed that pharmacological inhibition of these receptors blocked calcium signaling...

Evaluation of the lambda model for human postural control during ankle strategy.

Science.gov (United States)

Micheau, Philippe; Kron, Aymeric; Bourassa, Paul

2003-09-01

An accurate modeling of human stance might be helpful in assessing postural deficit. The objective of this article is to validate a mathematical postural control model for quiet standing posture. The postural dynamics is modeled in the sagittal plane as an inverted pendulum with torque applied at the ankle joint. The torque control system is represented by the physiological lambda model. Two neurophysiological command variables of the central nervous system, designated lambda and micro, establish the dynamic threshold muscle at which motoneuron recruitment begins. Kinematic data and electromyographic signals were collected on four young males in order to measure small voluntary sway and quiet standing posture. Validation of the mathematical model was achieved through comparison of the experimental and simulated results. The mathematical model allows computation of the unmeasurable neurophysiological commands lambda and micro that control the equilibrium position and stability. Furthermore, with the model it is possible to conclude that low-amplitude body sway during quiet stance is commanded by the central nervous system.

Persistent Amplification of DNA Damage Signal Involved in Replicative Senescence of Normal Human Diploid Fibroblasts

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Masatoshi Suzuki

2012-01-01

Full Text Available Foci of phosphorylated histone H2AX and ATM are the surrogate markers of DNA double strand breaks. We previously reported that the residual foci increased their size after irradiation, which amplifies DNA damage signals. Here, we addressed whether amplification of DNA damage signal is involved in replicative senescence of normal human diploid fibroblasts. Large phosphorylated H2AX foci (>1.5 μm diameter were specifically detected in presenescent cells. The frequency of cells with large foci was well correlated with that of cells positive for senescence-associated β-galactosidase staining. Hypoxic cell culture condition extended replicative life span of normal human fibroblast, and we found that the formation of large foci delayed in those cells. Our immuno-FISH analysis revealed that large foci partially localized at telomeres in senescent cells. Importantly, large foci of phosphorylated H2AX were always colocalized with phosphorylated ATM foci. Furthermore, Ser15-phosphorylated p53 showed colocalization with the large foci. Since the treatment of senescent cells with phosphoinositide 3-kinase inhibitor, wortmannin, suppressed p53 phosphorylation, it is suggested that amplification of DNA damage signaling sustains persistent activation of ATM-p53 pathway, which is essential for replicative senescence.

Insights into Basal Signaling Regulation, Oligomerization, and Structural Organization of the Human G-Protein Coupled Receptor 83.

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Anne Müller

Full Text Available The murine G-protein coupled receptor 83 (mGPR83 is expressed in the hypothalamus and was previously suggested to be involved in the regulation of metabolism. The neuropeptide PEN has been recently identified as a potent GPR83 ligand. Moreover, GPR83 constitutes functionally relevant hetero-oligomers with other G-protein coupled receptors (GPCR such as the ghrelin receptor (GHSR or GPR171. Previous deletion studies also revealed that the long N-terminal extracellular receptor domain (eNDo of mGPR83 may act as an intra-molecular ligand, which participates in the regulation of basal signaling activity, which is a key feature of GPCR function. Here, we investigated particular amino acids at the eNDo of human GPR83 (hGPR83 by side-directed mutagenesis to identify determinants of the internal ligand. These studies were accompanied by structure homology modeling to combine functional insights with structural information. The capacity for hetero-oligomer formation of hGPR83 with diverse family A GPCRs such as the melanocortin-4 receptor (MC4R was also investigated, with a specific emphasis on the impact of the eNDo on oligomerization and basal signaling properties. Finally, we demonstrate that hGPR83 exhibits an unusual basal signaling for different effectors, which also supports signaling promiscuity. hGPR83 interacts with a variety of hypothalamic GPCRs such as the MC4R or GHSR. These interactions are not dependent on the ectodomain and most likely occur at interfaces constituted in the transmembrane regions. Moreover, several amino acids at the transition between the eNDo and transmembrane helix 1 were identified, where mutations lead also to biased basal signaling modulation.

No Effect of TETRA Hand Portable Transmission Signals on Human Cognitive Function and Symptoms

DEFF Research Database (Denmark)

Riddervold, Ingunn Skogstad; Kjærgaard, Søren K.; Pedersen, Gert F.

2010-01-01

Current radio frequency radiation exposure guidelines rest on well-established thermal effects. However, recent research into analogue and digital transmission fields at levels covered by the exposure guidelines has indicated possible detrimental effects on human cognitive performance. To investi......Current radio frequency radiation exposure guidelines rest on well-established thermal effects. However, recent research into analogue and digital transmission fields at levels covered by the exposure guidelines has indicated possible detrimental effects on human cognitive performance....... To investigate this, we conducted a controlled climate chamber study of possible changes in cognitive performance in healthy volunteers exposed to transmission signals from TETRA hand portables (TETRA handsets). The trial deployed a balanced, randomized, double-blinded cross-over design. Performance on different...... paper-and-pencil, auditory and computer-based cognitive tasks was monitored in 53 male volunteers (mean age 36.41 years, SD 8.35) during 45-min exposure to a TETRA handset and sham control signals remotely controlled from a laboratory more than 100 km away. The main cognitive outcome was the Trail...

Ras signaling in aging and metabolic regulation.

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Slack, Cathy

2017-12-07

Aberrant signal transduction downstream of the Ras GTPase has a well-established role in tumorigenesis. Mutations that result in hyperactivation of Ras are responsible for a third of all human cancers. Hence, small molecule inhibitors of the Ras signal transduction cascade have been under intense focus as potential cancer treatments. In both invertebrate and mammalian models, emerging evidence has also implicated components of the Ras signaling pathway in aging and metabolic regulation. Here, I review the current evidence for Ras signaling in these newly discovered roles highlighting the interactions between the Ras pathway and other longevity assurance mechanisms. Defining the role of Ras signaling in maintaining age-related health may have important implications for the development of interventions that could not only increase lifespan but also delay the onset and/or progression of age-related functional decline.

Prediction of three-dimensional arm trajectories based on ECoG signals recorded from human sensorimotor cortex.

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Yasuhiko Nakanishi

Full Text Available Brain-machine interface techniques have been applied in a number of studies to control neuromotor prostheses and for neurorehabilitation in the hopes of providing a means to restore lost motor function. Electrocorticography (ECoG has seen recent use in this regard because it offers a higher spatiotemporal resolution than non-invasive EEG and is less invasive than intracortical microelectrodes. Although several studies have already succeeded in the inference of computer cursor trajectories and finger flexions using human ECoG signals, precise three-dimensional (3D trajectory reconstruction for a human limb from ECoG has not yet been achieved. In this study, we predicted 3D arm trajectories in time series from ECoG signals in humans using a novel preprocessing method and a sparse linear regression. Average Pearson's correlation coefficients and normalized root-mean-square errors between predicted and actual trajectories were 0.44~0.73 and 0.18~0.42, respectively, confirming the feasibility of predicting 3D arm trajectories from ECoG. We foresee this method contributing to future advancements in neuroprosthesis and neurorehabilitation technology.

Common activation of canonical Wnt signaling in pancreatic adenocarcinoma.

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Marina Pasca di Magliano

2007-11-01

Full Text Available Pancreatic ductal adenocarcinoma (PDA is an extremely aggressive malignancy, which carries a dismal prognosis. Activating mutations of the Kras gene are common to the vast majority of human PDA. In addition, recent studies have demonstrated that embryonic signaling pathway such as Hedgehog and Notch are inappropriately upregulated in this disease. The role of another embryonic signaling pathway, namely the canonical Wnt cascade, is still controversial. Here, we use gene array analysis as a platform to demonstrate general activation of the canonical arm of the Wnt pathway in human PDA. Furthermore, we provide evidence for Wnt activation in mouse models of pancreatic cancer. Our results also indicate that Wnt signaling might be activated downstream of Hedgehog signaling, which is an early event in PDA evolution. Wnt inhibition blocked proliferation and induced apoptosis of cultured adenocarcinoma cells, thereby providing evidence to support the development of novel therapeutical strategies for Wnt inhibition in pancreatic adenocarcinoma.

Integrated Environmental Modelling: Human decisions, human challenges

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Glynn, Pierre D.

2015-01-01

Integrated Environmental Modelling (IEM) is an invaluable tool for understanding the complex, dynamic ecosystems that house our natural resources and control our environments. Human behaviour affects the ways in which the science of IEM is assembled and used for meaningful societal applications. In particular, human biases and heuristics reflect adaptation and experiential learning to issues with frequent, sharply distinguished, feedbacks. Unfortunately, human behaviour is not adapted to the more diffusely experienced problems that IEM typically seeks to address. Twelve biases are identified that affect IEM (and science in general). These biases are supported by personal observations and by the findings of behavioural scientists. A process for critical analysis is proposed that addresses some human challenges of IEM and solicits explicit description of (1) represented processes and information, (2) unrepresented processes and information, and (3) accounting for, and cognizance of, potential human biases. Several other suggestions are also made that generally complement maintaining attitudes of watchful humility, open-mindedness, honesty and transparent accountability. These suggestions include (1) creating a new area of study in the behavioural biogeosciences, (2) using structured processes for engaging the modelling and stakeholder communities in IEM, and (3) using ‘red teams’ to increase resilience of IEM constructs and use.

Toward understanding social cues and signals in human?robot interaction: effects of robot gaze and proxemic behavior

OpenAIRE

Fiore, Stephen M.; Wiltshire, Travis J.; Lobato, Emilio J. C.; Jentsch, Florian G.; Huang, Wesley H.; Axelrod, Benjamin

2013-01-01

As robots are increasingly deployed in settings requiring social interaction, research is needed to examine the social signals perceived by humans when robots display certain social cues. In this paper, we report a study designed to examine how humans interpret social cues exhibited by robots. We first provide a brief overview of perspectives from social cognition in humans and how these processes are applicable to human–robot interaction (HRI). We then discuss the need to examine the relatio...

Improved signal model for confocal sensors accounting for object depending artifacts.

Science.gov (United States)

Mauch, Florian; Lyda, Wolfram; Gronle, Marc; Osten, Wolfgang

2012-08-27

The conventional signal model of confocal sensors is well established and has proven to be exceptionally robust especially when measuring rough surfaces. Its physical derivation however is explicitly based on plane surfaces or point like objects, respectively. Here we show experimental results of a confocal point sensor measurement of a surface standard. The results illustrate the rise of severe artifacts when measuring curved surfaces. On this basis, we present a systematic extension of the conventional signal model that is proven to be capable of qualitatively explaining these artifacts.

Hierarchical Colored Petri Nets for Modeling and Analysis of Transit Signal Priority Control Systems

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Yisheng An

2018-01-01

Full Text Available In this paper, we consider the problem of developing a model for traffic signal control with transit priority using Hierarchical Colored Petri nets (HCPN. Petri nets (PN are useful for state analysis of discrete event systems due to their powerful modeling capability and mathematical formalism. This paper focuses on their use to formalize the transit signal priority (TSP control model. In a four-phase traffic signal control model, the transit detection and two kinds of transit priority strategies are integrated to obtain the HCPN-based TSP control models. One of the advantages to use these models is the clear presentation of traffic light behaviors in terms of conditions and events that cause the detection of a priority request by a transit vehicle. Another advantage of the resulting models is that the correctness and reliability of the proposed strategies are easily analyzed. After their full reachable states are generated, the boundness, liveness, and fairness of the proposed models are verified. Experimental results show that the proposed control model provides transit vehicles with better effectiveness at intersections. This work helps advance the state of the art in the design of signal control models related to the intersection of roadways.