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Sample records for autocrine loopwhich predicts

  1. Identification and targeting of a TACE-dependent autocrine loopwhich predicts poor prognosis in breast cancer

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    Kenny, Paraic A.; Bissell, Mina J.

    2005-06-15

    The ability to proliferate independently of signals from other cell types is a fundamental characteristic of tumor cells. Using a 3D culture model of human breast cancer progression, we have delineated a protease-dependent autocrine loop which provides an oncogenic stimulus in the absence of proto-oncogene mutation. Inhibition of this protease, TACE/ADAM17, reverts the malignant phenotype by preventing mobilization of two crucial growth factors, Amphiregulin and TGF{alpha}. We show further that the efficacy of EGFR inhibitors is overcome by physiological levels of growth factors and that successful EGFR inhibition is dependent on reducing ligand bioavailability. Using existing patient outcome data, we demonstrate a strong correlation between TACE and TGF{alpha} expression in human breast cancers that is predictive of poor prognosis.

  2. Autocrine TGF-β/ZEB/microRNA-200 signal transduction drives epithelial-mesenchymal transition: Kinetic models predict minimal drug dose to inhibit metastasis.

    Science.gov (United States)

    Rateitschak, Katja; Kaderali, Lars; Wolkenhauer, Olaf; Jaster, Robert

    2016-08-01

    The epithelial-mesenchymal transition (EMT) is the crucial step that cancer cells must pass before they can undergo metastasis. The transition requires the activity of complex functional networks that downregulate properties of the epithelial phenotype and upregulate characteristics of the mesenchymal phenotype. The networks frequently include reciprocal repressions between transcription factors (TFs) driving the EMT and microRNAs (miRs) inducing the reverse process, termed mesenchymal-epithelial transition (MET). In this work we develop four kinetic models that are based on experimental data and hypotheses describing how autocrine transforming growth factor-β (TGF-β) signal transduction induces and maintains an EMT by upregulating the TFs ZEB1 and ZEB2 which repress the expression of the miR-200b/c family members. After successful model calibration we validate our models by predicting requirements for the maintenance of the mesenchymal steady state which agree with experimental data. Finally, we apply our validated kinetic models for the design of experiments in cancer therapy. We demonstrate how steady state properties of the kinetic models, combined with data from tumor-derived cell lines of individual patients, can predict the minimal amount of an inhibitor to induce a MET. PMID:27000495

  3. Autocrine Effects of Tumor-Derived Complement

    Directory of Open Access Journals (Sweden)

    Min Soon Cho

    2014-03-01

    Full Text Available We describe a role for the complement system in enhancing cancer growth. Cancer cells secrete complement proteins that stimulate tumor growth upon activation. Complement promotes tumor growth via a direct autocrine effect that is partially independent of tumor-infiltrating cytotoxic T cells. Activated C5aR and C3aR signal through the PI3K/AKT pathway in cancer cells, and silencing the PI3K or AKT gene in cancer cells eliminates the progrowth effects of C5aR and C3aR stimulation. In patients with ovarian or lung cancer, higher tumoral C3 or C5aR mRNA levels were associated with decreased overall survival. These data identify a role for tumor-derived complement proteins in promoting tumor growth, and they therefore have substantial clinical and therapeutic implications.

  4. Autocrine signal transmission with extracellular ligand degradation

    International Nuclear Information System (INIS)

    Traveling waves of cell signaling in epithelial layers orchestrate a number of important processes in developing and adult tissues. These waves can be mediated by positive feedback autocrine loops, a mode of cell signaling where binding of a diffusible extracellular ligand to a cell surface receptor can lead to further ligand release. We formulate and analyze a biophysical model that accounts for ligand-induced ligand release, extracellular ligand diffusion and ligand–receptor interaction. We focus on the case when the main mode for ligand degradation is extracellular and analyze the problem with the sharp threshold positive feedback nonlinearity. We derive expressions that link the speed of propagation and other characteristics of traveling waves to the parameters of the biophysical processes, such as diffusion rates, receptor expression level, etc. Analyzing the derived expressions we found that traveling waves in such systems can exhibit a number of unusual properties, e.g. non-monotonic dependence of the speed of propagation on ligand diffusivity. Our results for the fully developed traveling fronts can be used to analyze wave initiation from localized perturbations, a scenario that frequently arises in the in vitro models of epithelial wound healing, and guide future modeling studies of cell communication in epithelial layers

  5. Regulation of Autocrine Signaling in Subsets of Sympathetic Neurons Has Regional Effects on Tissue Innervation

    OpenAIRE

    Thomas G. McWilliams; Laura Howard; Sean Wyatt; Alun M. Davies

    2015-01-01

    Summary The regulation of innervation by target-derived factors like nerve growth factor (NGF) is the cornerstone of neurotrophic theory. Whereas autocrine signaling in neurons affecting survival and axon growth has been described, it is difficult to reconcile autocrine signaling with the idea that targets control their innervation. Here, we report that an autocrine signaling loop in developing mouse sympathetic neurons involving CD40L (TNFSF5) and CD40 (TNFRSF5) selectively enhances NGF-prom...

  6. Growth hormone and ocular dysfunction: Endocrine, paracrine or autocrine etiologies?

    Science.gov (United States)

    Harvey, Steve; Martinez-Moreno, Carlos G

    2016-08-01

    The eye is a target site for GH action and growth hormone has been implicated in diabetic retinopathy and other ocular dysfunctions. However, while this could reflect the hypersecretion of pituitary GH, the expression of the GH gene is now known to occur in ocular tissues and it could thus also reflect excess GH production within the eye itself. The possibility that ocular dysfunctions might arise from endocrine, autocrine or paracrine etiologies of GH overexpression is therefore the focus of this brief review. PMID:27082451

  7. Distinguishing autocrine and paracrine signals in hematopoietic stem cell culture using a biofunctional microcavity platform.

    Science.gov (United States)

    Müller, Eike; Wang, Weijia; Qiao, Wenlian; Bornhäuser, Martin; Zandstra, Peter W; Werner, Carsten; Pompe, Tilo

    2016-01-01

    Homeostasis of hematopoietic stem cells (HSC) in the mammalian bone marrow stem cell niche is regulated by signals of the local microenvironment. Besides juxtacrine, endocrine and metabolic cues, paracrine and autocrine signals are involved in controlling quiescence, proliferation and differentiation of HSC with strong implications on expansion and differentiation ex vivo as well as in vivo transplantation. Towards this aim, a cell culture analysis on a polymer microcavity carrier platform was combined with a partial least square analysis of a mechanistic model of cell proliferation. We could demonstrate the discrimination of specific autocrine and paracrine signals from soluble factors as stimulating and inhibitory effectors in hematopoietic stem and progenitor cell culture. From that we hypothesize autocrine signals to be predominantly involved in maintaining the quiescent state of HSC in single-cell niches and advocate our analysis platform as an unprecedented option for untangling convoluted signaling mechanisms in complex cell systems being it of juxtacrine, paracrine or autocrine origin. PMID:27535453

  8. BDNF, produced by a TPO-stimulated megakaryocytic cell line, regulates autocrine proliferation

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    Tamura, Shogo [Graduate School of Health Sciences, Hokkaido University, Sapporo (Japan); Research Fellow of the Japan Society for the Promotion of Science, Tokyo (Japan); Nagasawa, Ayumi; Masuda, Yuya; Tsunematsu, Tetsuya [Graduate School of Health Sciences, Hokkaido University, Sapporo (Japan); Hayasaka, Koji; Matsuno, Kazuhiko; Shimizu, Chikara [Division of Laboratory and Transfusion Medicine, Hokkaido University Hospital, Sapporo (Japan); Ozaki, Yukio [Department of Clinical and Laboratory Medicine, Faculty of Medicine, University of Yamanashi (Japan); Moriyama, Takanori, E-mail: moriyama@hs.hokuda.ac.jp [Medical Laboratory Science, Faculty of Health Sciences, Hokkaido University, Sapporo (Japan)

    2012-10-26

    Highlights: Black-Right-Pointing-Pointer It has been thought that BDNF is not produced in the megakaryocytic lineage. Black-Right-Pointing-Pointer MEG-01 produces BDNF upon TPO stimulation and regulates its proliferation. Black-Right-Pointing-Pointer BDNF accelerates proliferation of MEG-01 in an autocrine manner. Black-Right-Pointing-Pointer BDNF may be an autocrine MEG-CSF, which regulates megakaryopoiesis. -- Abstract: While human platelets release endogenous brain-derived neurotrophic factor (BDNF) upon activation, a previous report on MEG-01, a megakaryocytic cell line, found no trace of BDNF production, and the pathophysiological function of platelet BDNF has remained elusive. In the present study, we demonstrate that MEG-01 produces BDNF in the presence of TPO and that this serves to potentiate cell proliferation. Our in vitro findings suggest that BDNF regulates MEG-01 proliferation in an autocrine manner, and we suggest that BDNF may be a physiological autocrine regulator of megakaryocyte progenitors.

  9. BDNF, produced by a TPO-stimulated megakaryocytic cell line, regulates autocrine proliferation

    International Nuclear Information System (INIS)

    Highlights: ► It has been thought that BDNF is not produced in the megakaryocytic lineage. ► MEG-01 produces BDNF upon TPO stimulation and regulates its proliferation. ► BDNF accelerates proliferation of MEG-01 in an autocrine manner. ► BDNF may be an autocrine MEG-CSF, which regulates megakaryopoiesis. -- Abstract: While human platelets release endogenous brain-derived neurotrophic factor (BDNF) upon activation, a previous report on MEG-01, a megakaryocytic cell line, found no trace of BDNF production, and the pathophysiological function of platelet BDNF has remained elusive. In the present study, we demonstrate that MEG-01 produces BDNF in the presence of TPO and that this serves to potentiate cell proliferation. Our in vitro findings suggest that BDNF regulates MEG-01 proliferation in an autocrine manner, and we suggest that BDNF may be a physiological autocrine regulator of megakaryocyte progenitors.

  10. Autocrine-paracrine regulation of the mammary gland.

    Science.gov (United States)

    Weaver, S R; Hernandez, L L

    2016-01-01

    The mammary gland has a remarkable capacity for regulation at a local level, particularly with respect to its main function: milk secretion. Regulation of milk synthesis has significant effects on animal and human health, at the level of both the mother and the neonate. Control by the mammary gland of its essential function, milk synthesis, is an evolutionary necessity and is therefore tightly regulated at a local level. For at least the last 60 yr, researchers have been interested in elucidating the mechanisms underpinning the mammary gland's ability to self-regulate, largely without the influence from systemic hormones or signals. By the 1960s, scientists realized the importance of milk removal in the capacity of the gland to produce milk and that the dynamics of this removal, including emptying of the alveolar spaces and frequency of milking, were controlled locally as opposed to traditional systemic hormonal regulation. Using both in vitro systems and various mammalian species, including goats, marsupials, humans, and dairy cows, it has been demonstrated that the mammary gland is largely self-regulating in its capacity to support the young, which is the evolutionary basis for milk production. Local control occurs at the level of the mammary epithelial cell through pressure and stretching negative-feedback mechanisms, and also in an autocrine fashion through bioactive factors within the milk which act as inhibitors, regulating milk secretion within the alveoli themselves. It is only within the last 20 to 30 yr that potential candidates for these bioactive factors have been examined at a molecular level. Several, including parathyroid hormone-related protein, growth factors (transforming growth factor, insulin-like growth factor, epidermal growth factor), and serotonin, are synthesized within and act upon the gland and possess dynamic receptor activity resulting in diverse effects on growth, calcium homeostasis, and milk composition. This review will focus on the

  11. FGF19 functions as autocrine growth factor for hepatoblastoma

    Science.gov (United States)

    Elzi, David J.; Song, Meihua; Blackman, Barron; Weintraub, Susan T.; López-Terrada, Dolores; Chen, Yidong; Tomlinson, Gail E.; Shiio, Yuzuru

    2016-01-01

    Hepatoblastoma is the most common liver cancer in children, accounting for over 65% of all childhood liver malignancies. Hepatoblastoma is distinct from adult liver cancer in that it is not associated with hepatitis virus infection, cirrhosis, or other underlying liver pathology. The paucity of appropriate cell and animal models has been hampering the mechanistic understanding of hepatoblastoma pathogenesis. Consequently, there is no molecularly targeted therapy for hepatoblastoma. To gain insight into cytokine signaling in hepatoblastoma, we employed mass spectrometry to analyze the proteins secreted from Hep293TT hepatoblastoma cell line we established and identified the specific secretion of fibroblast growth factor 19 (FGF19), a growth factor for liver cells. We determined that silencing FGF19 by shRNAs or neutralizing secreted FGF19 by anti-FGF19 antibody inhibits the proliferation of hepatoblastoma cells. Furthermore, blocking FGF19 signaling by an FGF receptor kinase inhibitor suppressed hepatoblastoma growth. RNA expression analysis in hepatoblastoma tumors revealed that the high expression of FGF19 signaling pathway components as well as the low expression of FGF19 signaling repression targets correlates with the aggressiveness of the tumors. These results suggest the role of FGF19 as autocrine growth factor for hepatoblastoma.

  12. Autocrine-Controlled Formation and Function of Tissue-Like Aggregates by Primary Hepatocytes in Micropatterned Hydrogel Arrays

    OpenAIRE

    Williams, Courtney M.; Mehta, Geeta; Peyton, Shelly R.; Zeiger, Adam S.; Van Vliet, Krystyn J.; Griffith, Linda G.

    2010-01-01

    The liver carries out a variety of essential functions regulated in part by autocrine signaling, including hepatocyte-produced growth factors and extracellular matrix (ECM). The local concentrations of autocrine factors are governed by a balance between receptor-mediated binding at the cell surface and diffusion into the local matrix and are thus expected to be influenced by the dimensionality of the cell culture environment. To investigate the role of growth factor and ECM-modulated autocrin...

  13. Reactive Oxygen Species Alter Autocrine and Paracrine Signaling

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    Zangar, Richard C.; Bollinger, Nikki; Weber, Thomas J.; Tan, Ruimin; Markillie, Lye Meng; Karin, Norman J.

    2011-12-01

    Cytochrome P450 (P450) 3A4 (CYP3A4) is the most abundant P450 protein in human liver and intestine and is highly inducible by a variety of drugs and other compounds. The P450 catalytic cycle is known to uncouple and release reactive oxygen species (ROS), but the effects of ROS from P450 and other enzymes in the endo-plasmic reticulum have been poorly studied from the perspective of effects on cell biology. In this study, we expressed low levels of CYP3A4 in HepG2 cells, a human hepatocarcinoma cell line, and examined effects on intracellular levels of ROS and on the secretion of a variety of growth factors that are important in extracellular communication. Using the redox-sensitive dye RedoxSensor red, we demonstrate that CYP3A4 expression increases levels of ROS in viable cells. A customELISA microarray platform was employed to demonstrate that expression of CYP3A4 increased secretion of amphiregulin, intracellular adhesion molecule 1, matrix metalloprotease 2, platelet-derived growth factor (PDGF), and vascular endothelial growth factor, but suppressed secretion of CD14. The antioxidant N-acetylcysteine suppressed all P450-dependent changes in protein secretion except for CD14. Quantitative RT-PCR demonstrated that changes in protein secretion were consistently associated with corresponding changes in gene expression. Inhibition of the NF-{kappa}B pathway blocked P450 effects on PDGF secretion. CYP3A4 expression also altered protein secretion in human mammary epithelial cells and C10 mouse lung cells. Overall, these results suggest that increased ROS production in the endoplasmic reticulum alters the secretion of proteins that have key roles in paracrine and autocrine signaling.

  14. Regulation of Autocrine Signaling in Subsets of Sympathetic Neurons Has Regional Effects on Tissue Innervation

    Directory of Open Access Journals (Sweden)

    Thomas G. McWilliams

    2015-03-01

    Full Text Available The regulation of innervation by target-derived factors like nerve growth factor (NGF is the cornerstone of neurotrophic theory. Whereas autocrine signaling in neurons affecting survival and axon growth has been described, it is difficult to reconcile autocrine signaling with the idea that targets control their innervation. Here, we report that an autocrine signaling loop in developing mouse sympathetic neurons involving CD40L (TNFSF5 and CD40 (TNFRSF5 selectively enhances NGF-promoted axon growth and branching, but not survival, via CD40L reverse signaling. Because NGF negatively regulates CD40L and CD40 expression, this signaling loop operates only in neurons exposed to low levels of NGF. Consequently, the sympathetic innervation density of tissues expressing low NGF is significantly reduced in CD40-deficient mice, whereas the innervation density of tissues expressing high levels of NGF is unaffected. Our findings reveal how differential regulation of autocrine signaling in neurons has region-specific effects on axon growth and tissue innervation.

  15. Autocrine action of BDNF on dendrite development of adult-born hippocampal neurons.

    Science.gov (United States)

    Wang, Liang; Chang, Xingya; She, Liang; Xu, Duo; Huang, Wei; Poo, Mu-ming

    2015-06-01

    Dendrite development of newborn granule cells (GCs) in the dentate gyrus of adult hippocampus is critical for their incorporation into existing hippocampal circuits, but the cellular mechanisms regulating their dendrite development remains largely unclear. In this study, we examined the function of brain-derived neurotrophic factor (BDNF), which is expressed in adult-born GCs, in regulating their dendrite morphogenesis. Using retrovirus-mediated gene transfection, we found that deletion and overexpression of BDNF in adult-born GCs resulted in the reduction and elevation of dendrite growth, respectively. This effect was mainly due to the autocrine rather than paracrine action of BDNF, because deletion of BDNF only in the newborn GCs resulted in dendrite abnormality of these neurons to a similar extent as that observed in conditional knockout (cKO) mice with BDNF deleted in the entire forebrain. Furthermore, selective expression of BDNF in adult-born GCs in BDNF cKO mice fully restored normal dendrite development. The BDNF autocrine action was also required for the development of normal density of spines and normal percentage of spines containing the postsynaptic marker PSD-95, suggesting autocrine BDNF regulation of synaptogenesis. Furthermore, increased dendrite growth of adult-born GCs caused by voluntary exercise was abolished by BDNF deletion specifically in these neurons and elevated dendrite growth due to BDNF overexpression in these neurons was prevented by reducing neuronal activity with coexpression of inward rectifier potassium channels, consistent with activity-dependent autocrine BDNF secretion. Therefore, BDNF expressed in adult-born GCs plays a critical role in dendrite development by acting as an autocrine factor. PMID:26041908

  16. An autocrine γ-aminobutyric acid signaling system exists in pancreatic β-cell progenitors of fetal and postnatal mice

    OpenAIRE

    Feng, Mary M; Xiang, Yun-Yan; Wang, Shuanglian; Lu, Wei-Yang

    2013-01-01

    Gamma-aminobutyric acid (GABA) is produced and secreted by adult pancreatic β-cells, which also express GABA receptors mediating autocrine signaling and regulating β-cell proliferation. However, whether the autocrine GABA signaling involves in β-cell progenitor development or maturation remains uncertain. By means of immunohistochemistry we analyzed the expression profiles of the GABA synthesizing enzyme glutamic acid decarboxylase (GAD) and the α1-subunit of type-A GABA receptor (GABAARα1) i...

  17. Reevaluation of the proposed autocrine proliferative function of prolactin in breast cancer

    DEFF Research Database (Denmark)

    Nitze, Louise Maymann; Galsgaard, Elisabeth Douglas; Din, Nanni;

    2013-01-01

    The pituitary hormone prolactin (PRL) has been implicated in tumourigenesis. Expression of PRL and its receptor (PRLR) was reported in human breast epithelium and breast cancer cells. It was suggested that PRL may act as an autocrine/paracrine growth factor. Here, we addressed the role of locally...... synthesised PRL in breast cancer. We analysed the expression of PRL in human breast cancer tumours using qPCR analysis and in situ hybridization (ISH). PRL mRNA expression was very low or undetectable in the majority of samples in three cDNA arrays representing samples from 144 breast cancer patients and in...... reduced and the cells were no longer responsive to exogenous recombinant PRL. Taken together, these data strongly indicate that autocrine PRL signalling is unlikely to be a general mechanism promoting tumour growth in breast cancer patients....

  18. STAT3-Decoy ODN Inhibits Cytokine Autocrine of Murine Tumor Cells

    Institute of Scientific and Technical Information of China (English)

    Xi Liu; Jiayi Li; Jian Zhang

    2007-01-01

    Tumor cells usually secrete soluble factors to improve their proliferation via autocrine network or to escape from immune surveillance by inhibiting antitumor immunity, among these factors IL-10 and IL-6 play more important roles. Since both cytokines' signal transductions are mediated through the STAT3 pathway, STAT3 becomes an attractive target for tumor therapy. In present study, STAT3 of murine tumor cell lines B16 and MCA-38 was constitutively activated. After treatment with STAT3-decoy ODN, the proliferation of these tumor cells was inhibited and the transcription of IL-10 or IL-6 in tumor cells was down-regulated. These results suggested that STAT3 is a good target candidate, and STAT3-decoy ODN may possibly be used as a strategy for breaking both tumor autocrine network and tumor immunotolerance.

  19. Autocrine-Based Selection of Drugs That Target Ion Channels from Combinatorial Venom Peptide Libraries.

    Science.gov (United States)

    Zhang, Hongkai; Du, Mingjuan; Xie, Jia; Liu, Xiao; Sun, Jingying; Wang, Wei; Xin, Xiu; Possani, Lourival D; Yea, Kyungmoo; Lerner, Richard A

    2016-08-01

    Animal venoms represent a rich source of pharmacologically active peptides that interact with ion channels. However, a challenge to discovering drugs remains because of the slow pace at which venom peptides are discovered and refined. An efficient autocrine-based high-throughput selection system was developed to discover and refine venom peptides that target ion channels. The utility of this system was demonstrated by the discovery of novel Kv1.3 channel blockers from a natural venom peptide library that was formatted for autocrine-based selection. We also engineered a Kv1.3 blocker peptide (ShK) derived from sea anemone to generate a subtype-selective Kv1.3 blocker with a long half-life in vivo. PMID:27197631

  20. WNT4 mediates the autocrine effects of growth hormone in mammary carcinoma cells.

    Science.gov (United States)

    Vouyovitch, Cécile M; Perry, Jo K; Liu, Dong Xu; Bezin, Laurent; Vilain, Eric; Diaz, Jean-Jacques; Lobie, Peter E; Mertani, Hichem C

    2016-07-01

    The expression of Wingless and Int-related protein (Wnt) ligands is aberrantly high in human breast cancer. We report here that WNT4 is significantly upregulated at the mRNA and protein level in mammary carcinoma cells expressing autocrine human growth hormone (hGH). Depletion of WNT4 using small interfering (si) RNA markedly decreased the rate of human breast cancer cell proliferation induced by autocrine hGH. Forced expression of WNT4 in the nonmalignant human mammary epithelial cell line MCF-12A stimulated cell proliferation in low and normal serum conditions, enhanced cell survival and promoted anchorage-independent growth and colony formation in soft agar. The effects of sustained production of WNT4 were concomitant with upregulation of proliferative markers (c-Myc, Cyclin D1), the survival marker BCL-XL, the putative WNT4 receptor FZD6 and activation of ERK1 and STAT3. Forced expression of WNT4 resulted in phenotypic conversion of MCF-12A cells, such that they exhibited the molecular and morphological characteristics of mesenchymal cells with increased cell motility. WNT4 production resulted in increased mesenchymal and cytoskeletal remodeling markers, promoted actin cytoskeleton reorganization and led to dissolution of cell-cell contacts. In xenograft studies, tumors with autocrine hGH expressed higher levels of WNT4 and FZD6 when compared with control tumors. In addition, Oncomine data indicated that WNT4 expression is increased in neoplastic compared with normal human breast tissue. Accordingly, immunohistochemical detection of WNT4 in human breast cancer biopsies revealed higher expression in tumor tissue vs normal breast epithelium. WNT4 is thus an autocrine hGH-regulated gene involved in the growth and development of the tumorigenic phenotype. PMID:27323961

  1. Acetylcholine release by human colon cancer cells mediates autocrine stimulation of cell proliferation

    OpenAIRE

    Cheng, Kunrong; Samimi, Roxana; Xie, Guofeng; Shant, Jasleen; Drachenberg, Cinthia; Wade, Mark; Davis, Richard J.; Nomikos, George; Raufman, Jean-Pierre

    2008-01-01

    Most colon cancers overexpress M3 muscarinic receptors (M3R), and post-M3R signaling stimulates human colon cancer cell proliferation. Acetylcholine (ACh), a muscarinic receptor ligand traditionally regarded as a neurotransmitter, may be produced by nonneuronal cells. We hypothesized that ACh release by human colon cancer cells results in autocrine stimulation of proliferation. H508 human colon cancer cells, which have robust M3R expression, were used to examine effects of muscarinic receptor...

  2. AUTOCRINE/PARACRINE MODULATION OF BARORECEPTOR ACTIVITY AFTER ANTIDROMIC STIMULATION OF AORTIC DEPRESSOR NERVE IN VIVO

    OpenAIRE

    Valter J. Santana-Filho; Davis, Greg J.; Castania, Jaci A.; Ma, Xiuying; Salgado, Helio C; Abboud, Francois M.; Fazan, Rubens; Chapleau, Mark W.

    2014-01-01

    Activation of the sensory nerve endings of nonmyelinated C-fiber afferents evokes release of autocrine/paracrine factors that cause localized vasodilation, neurogenic inflammation, and modulation of sensory nerve activity. The aims of this study were to determine the effect of antidromic electrical stimulation on afferent baroreceptor activity in vivo, and investigate the role of endogenous prostanoids and hydrogen peroxide (H2O2) in mediating changes in nerve activity. Baroreceptor activity ...

  3. Interleukin 1 is an autocrine regulator of human endothelial cell growth

    International Nuclear Information System (INIS)

    Proliferation of endothelial cells is regulated through the autocrine production of growth factors and the expression of cognate surface receptors. In this study, the authors demonstrate that interleukin 1 (IL-1) is an inhibitor of endothelial growth in vitro and in vivo. IL-1 arrested growing, cultured endothelial cells in G1 phase; inhibition of proliferation was dose dependent and occurred in parallel with occupancy of endothelial surface IL-1 receptors. In an angiogenesis model, IL-1 could inhibit fibroblast growth factor-induced vessel formation. The autocrine nature of the IL-1 effect on endothelial proliferation was demonstrated by the observation that occupancy of cell-surface receptors by endogenous IL-1 depressed cell growth. The potential significance of this finding was emphasized by the detection of IL-1 in the native endothelium of human umbilical veins. A mechanism by which IL-1 may exert its inhibitory effect on endothelial cell growth was suggested by studies showing that IL-1 decreased the expression of high-affinity fibroblast growth factor binding sites on endothelium. These results point to a potentially important role of IL-1 in regulating blood vessel growth the suggest that autocrine production of inhibitory factors may be a mechanism controlling proliferation of normal cells

  4. Autocrine and paracrine actions of intestinal fibroblast-derived insulin-like growth factors.

    Science.gov (United States)

    Simmons, J G; Pucilowska, J B; Lund, P K

    1999-04-01

    Paracrine and autocrine actions of the insulin-like growth factors (IGFs) are inferred by local expression within the bowel. CCD-18Co cells, IEC-6 cells, and immunoneutralization were used to analyze whether IGFs have direct autocrine or paracrine effects on proliferation of cultured intestinal fibroblasts and epithelial cells. Growth factor expression was analyzed by ribonuclease protection assay and RT-PCR. Extracellular matrix (ECM) was analyzed for effects on cell proliferation. CCD-18Co cells express IGF-II mRNAs and low levels of IGF-I mRNA. Conditioned medium from CCD-18Co cells (CCD-CM) stimulated proliferation of IEC-6 and CCD-18Co cells. Neutralization of IGF immunoreactivity in CCD-CM reduced but did not abolish this effect. RT-PCR and immunoneutralization demonstrated that other growth factors contribute to mitogenic activity of CCD-CM. Preincubation of CCD-CM with ECM prepared from IEC-6 or CCD-18Co cells reduced its mitogenic activity. ECM from CCD-18Co cells enhanced growth factor-dependent proliferation of IEC-6 cells. IEC-6 cell ECM inhibited IGF-I action on CCD-18Co cells. We conclude that IGF-II is a potent autocrine mitogen for intestinal fibroblasts. IGF-II interacts with other fibroblast-derived growth factors and ECM to stimulate proliferation of intestinal epithelial cells in a paracrine manner. PMID:10198323

  5. EGF-Receptor-Mediated Mammary Epithelial Cell Migration is Driven by Sustained ERK Signaling from Autocrine Stimulation

    Energy Technology Data Exchange (ETDEWEB)

    Joslin, Elizabeth J.; Opresko, Lee; Wells, Alan; Wiley, H. S.; Lauffenburger, Douglas A.

    2007-10-15

    Aberrant expression of epidermal growth factor (EGF) receptor family ligands, as well as the receptors themselves, has been implicated in various types of cancers. EGF family ligands are synthesized as membrane-anchored proteins requiring proteolytic release to form the mature soluble factor. Despite the pathophysiological importance of autocrine systems, how the rate of protease-mediated ligand release quantitatively influences receptor-mediated signaling and consequent cell behavior is poorly understood. Therefore, we explored the relationship between autocrine EGF release rates and receptor-mediated ERK activation and migration in human mammary epithelial cells. A quantitative spectrum of EGF release rates was achieved using a set of chimeric transmembrane EGF ligand precursors modulated by the addition of the metalloprotease inhibitor batimastat. We found that ERK activation increased with increasing ligand release rates despite concomitant EGF receptor downregulation. Cell migration speed depended linearly on the steady-state phospho-ERK level obtained from either autocrine or exogenous ligand, but was much greater at any given phospho-ERK level for autocrine compared to exogenous stimulation. In contrast, cell proliferation rates were relatively constant across the various treatment conditions. Thus, in these cells, ERK-mediated migration stimulated by EGF receptor signaling is most sensitively regulated by autocrine ligand control mechanisms.

  6. Autocrine HBEGF expression promotes breast cancer intravasation, metastasis and macrophage-independent invasion in vivo

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Z. N.; Sharma, V. P.; Beaty, B. T.; Roh-Johnson, M.; Peterson, E. A.; Van Rooijen, N.; Kenny, P. A.; Wiley, H. S.; Condeelis, J. S.; Segall, J. E.

    2014-10-13

    Increased expression of HBEGF in estrogen receptor-negative breast tumors is correlated with enhanced metastasis to distant organ sites and more rapid disease recurrence upon removal of the primary tumor. Our previous work has demonstrated a paracrine loop between breast cancer cells and macrophages in which the tumor cells are capable of stimulating macrophages through the secretion of colony-stimulating factor-1 while the tumor-associated macrophages (TAMs), in turn, aid in tumor cell invasion by secreting epidermal growth factor. To determine how the autocrine expression of epidermal growth factor receptor (EGFR) ligands by carcinoma cells would affect this paracrine loop mechanism, and in particular whether tumor cell invasion depends on spatial ligand gradients generated by TAMs, we generated cell lines with increased HBEGF expression. We found that autocrine HBEGF expression enhanced in vivo intravasation and metastasis and resulted in a novel phenomenon in which macrophages were no longer required for in vivo invasion of breast cancer cells. In vitro studies revealed that expression of HBEGF enhanced invadopodium formation, thus providing a mechanism for cell autonomous invasion. The increased invadopodium formation was directly dependent on EGFR signaling, as demonstrated by a rapid decrease in invadopodia upon inhibition of autocrine HBEGF/EGFR signaling as well as inhibition of signaling downstream of EGFR activation. HBEGF expression also resulted in enhanced invadopodium function via upregulation of matrix metalloprotease 2 (MMP2) and MMP9 expression levels. We conclude that high levels of HBEGF expression can short-circuit the tumor cell/macrophage paracrine invasion loop, resulting in enhanced tumor invasion that is independent of macrophage signaling.

  7. Isolation of an Autocrine Growth Factor From Hepatoma HTC-SR Cells

    OpenAIRE

    Ove, Peter; Coetzee, Mona L.; Scalamogna, Philip; FRANCAVILLA, ANTONIO; Starzl, Thomas E.

    1987-01-01

    A growth factor has been isolated from HTC-SR rat hepatoma tissue culture cells which specifically stimulates DNA synthesis and cell proliferation of the HTC cells that produce it. The factor can be isolated from HTC cell conditioned medium or from an HTC cell extract. This autocrine factor has been purified 640-fold from a postmicrosomal supernatant by successive steps, involving ethanol precipitation, heating at 80°C for 10 min, chromatography on a DEAE Bio-Gel A column, and chromatography ...

  8. Inhibition of KRAS-driven tumorigenicity by interruption of an autocrine cytokine circuit

    OpenAIRE

    Zhu, Zehua; Aref, Amir R.; Cohoon, Travis J.; Barbie, Thanh U.; Imamura, Yu; Yang, Shenghong; Moody, Susan E.; Shen, Rhine R.; Schinzel, Anna C.; Thai, Tran C.; Reibel, Jacob B.; Tamayo, Pablo; Godfrey, Jason T.; Qian, Zhi Rong; Page, Asher N.

    2014-01-01

    Although the roles of mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3 kinase (PI3K) signaling in KRAS-driven tumorigenesis are well established, KRAS activates additional pathways required for tumor maintenance, inhibition of which are likely to be necessary for effective KRAS-directed therapy. Here we show that the IKK-related kinases TBK1 and IKKε promote KRAS-driven tumorigenesis by regulating autocrine CCL5 and IL-6 and identify CYT387 as a potent JAK/TBK1/IKKε inhibito...

  9. Cell wall trapping of autocrine peptides for human G-protein-coupled receptors on the yeast cell surface.

    Directory of Open Access Journals (Sweden)

    Jun Ishii

    Full Text Available G-protein-coupled receptors (GPCRs regulate a wide variety of physiological processes and are important pharmaceutical targets for drug discovery. Here, we describe a unique concept based on yeast cell-surface display technology to selectively track eligible peptides with agonistic activity for human GPCRs (Cell Wall Trapping of Autocrine Peptides (CWTrAP strategy. In our strategy, individual recombinant yeast cells are able to report autocrine-positive activity for human GPCRs by expressing a candidate peptide fused to an anchoring motif. Following expression and activation, yeast cells trap autocrine peptides onto their cell walls. Because captured peptides are incapable of diffusion, they have no impact on surrounding yeast cells that express the target human GPCR and non-signaling peptides. Therefore, individual yeast cells can assemble the autonomous signaling complex and allow single-cell screening of a yeast population. Our strategy may be applied to identify eligible peptides with agonistic activity for target human GPCRs.

  10. Dendritic cell derived IL-2 inhibits survival of terminally mature cells via an autocrine signaling pathway.

    Science.gov (United States)

    Balachander, Akhila; Nabti, Sabrina; Sobota, Radoslaw M; Foo, Shihui; Zolezzi, Francesca; Lee, Bernett T K; Poidinger, Michael; Ricciardi-Castagnoli, Paola

    2015-05-01

    DCs are crucial for sensing pathogens and triggering immune response. Upon activation by pathogen-associated molecular pattern (PAMP) ligands, GM-CSF myeloid DCs (GM-DCs) secrete several cytokines, including IL-2. DC IL-2 has been shown to be important for innate and adaptive immune responses; however, IL-2 importance in DC physiology has never been demonstrated. Here, we show that autocrine IL-2 signaling is functional in murine GM-DCs in an early time window after PAMPs stimulation. IL-2 signaling selectively activates the JAK/STAT5 pathway by assembling holo-receptor complexes at the cell surface. Using the sensitivity of targeted mass spectrometry, we show conclusively that GM-DCs express CD122, the IL-2 receptor β-chain, at steady state. In myeloid DCs, this cytokine pathway inhibits survival of PAMP-matured GM-DCs which is crucial for maintaining immune tolerance and preventing autoimmunity. Our findings suggest that immune regulation by this novel autocrine signaling pathway can potentially be used in DC immunotherapy. PMID:25652593

  11. Intracellular autocrine VEGF signaling promotes EBDC cell proliferation, which can be inhibited by Apatinib.

    Science.gov (United States)

    Peng, Sui; Zhang, Yanyan; Peng, Hong; Ke, Zunfu; Xu, Lixia; Su, Tianhong; Tsung, Allan; Tohme, Samer; Huang, Hai; Zhang, Qiuyang; Lencioni, Riccardo; Zeng, Zhirong; Peng, Baogang; Chen, Minhu; Kuang, Ming

    2016-04-10

    Tumor cells produce vascular endothelial growth factor (VEGF) which can interact with membrane or cytoplasmic VEGF receptors (VEGFRs) to promote cell growth. We aimed to investigate the role of extracellular/intracellular autocrine VEGF signaling and Apatinib, a highly selective VEGFR2 inhibitor, in extrahepatic bile duct cancer (EBDC). We found conditioned medium or recombinant human VEGF treatment promoted EBDC cell proliferation through a phospholipase C-γ1-dependent pathway. This pro-proliferative effect was diminished by VEGF, VEGFR1 or VEGFR2 neutralizing antibodies, but more significantly suppressed by intracellular VEGFR inhibitor. The rhVEGF induced intracellular VEGF signaling by promoting nuclear accumulation of pVEGFR1/2 and enhancing VEGF promoter activity, mRNA and protein expression. Internal VEGFR2 inhibitor Apatinib significantly inhibited intracellular VEGF signaling, suppressed cell proliferation in vitro and delayed xenograft tumor growth in vivo, while anti-VEGF antibody Bevacizumab showed no effect. Clinically, overexpression of pVEGFR1 and pVEGFR2 was significantly correlated with poorer overall survival (P = .007 and P = .020, respectively). In conclusion, the intracellular autocrine VEGF loop plays a predominant role in VEGF-induced cell proliferation. Apatinib is an effective intracellular VEGF pathway blocker that presents a great therapeutic potential in EBDC. PMID:26805764

  12. Human neural stem cell-induced endothelial morphogenesis requires autocrine/paracrine and juxtacrine signaling

    Science.gov (United States)

    Chou, Chung-Hsing; Modo, Michel

    2016-01-01

    Transplanted neural stem cells (NSC) interact with the host brain microenvironment. A neovascularization is commonly observed in the vicinity of the cell deposit, which is correlated with behavioral improvements. To elucidate the signaling mechanisms between human NSCs and endothelial cells (ECs), these were cocultured in an in vitro model in which NSC-induced endothelial morphogenesis produced a neurovascular environment. Soluble (autocrine/paracrine) and contact–mediated (juxtacrine) signaling molecules were evaluated for two conditionally immortalized fetal NSC lines derived from the cortical anlage (CTXOE03) and ganglionic eminence (STROC05), as well as an adult EC line (D3) derived from the cerebral microvasculature of a hippocampal biopsy. STROC05 were 4 times as efficient to induce endothelial morphogenesis compared to CTXOE03. The cascade of reciprocal interactions between NSCs and ECs in this process was determined by quantifying soluble factors, receptor mapping, and immunocytochemistry for extracellular matrix molecules. The mechanistic significance of these was further evaluated by pharmacological blockade. The sequential cell-specific regulation of autocrine/paracrine and juxtacrine signaling accounted for the differential efficiency of NSCs to induce endothelial morphogenesis. These in vitro studies shed new light on the reciprocal interactions between NSCs and ECs, which are pivotal for our mechanistic understanding of the efficacy of NSC transplantation. PMID:27374240

  13. Adipocytes promote prostate cancer stem cell self-renewal through amplification of the cholecystokinin autocrine loop

    Science.gov (United States)

    Tang, Kai-Dun; Liu, Ji; Jovanovic, Lidija; An, Jiyuan; Hill, Michelle M.; Vela, Ian; Lee, Terence Kin-Wah; Ma, Stephanie; Nelson, Colleen; Russell, Pamela J.; Clements, Judith A.; Ling, Ming-Tat

    2016-01-01

    Obesity has long been linked with prostate cancer progression, although the underlying mechanism is still largely unknown. Here, we report that adipocytes promote the enrichment of prostate cancer stem cells (CSCs) through a vicious cycle of autocrine amplification. In the presence of adipocytes, prostate cancer cells actively secrete the peptide hormone cholecystokinin (CCK), which not only stimulates prostate CSC self-renewal, but also induces cathepsin B (CTSB) production of the adipocytes. In return, CTSB facilitates further CCK secretion by the cancer cells. More importantly, inactivation of CCK receptor not only suppresses CTSB secretion by the adipocytes, but also synergizes the inhibitory effect of CTSB inhibitor on adipocyte-promoted prostate CSC self-renewal. In summary, we have uncovered a novel mechanism underlying the mutual interplay between adipocytes and prostate CSCs, which may help explaining the role of adipocytes in prostate cancer progression and provide opportunities for effective intervention. PMID:26700819

  14. Dopamine-Mediated Autocrine Inhibitory Circuit Regulating Human Insulin Secretion in Vitro

    Science.gov (United States)

    Simpson, Norman; Maffei, Antonella; Freeby, Matthew; Burroughs, Steven; Freyberg, Zachary; Javitch, Jonathan; Leibel, Rudolph L.

    2012-01-01

    We describe a negative feedback autocrine regulatory circuit for glucose-stimulated insulin secretion in purified human islets in vitro. Using chronoamperometry and in vitro glucose-stimulated insulin secretion measurements, evidence is provided that dopamine (DA), which is loaded into insulin-containing secretory granules by vesicular monoamine transporter type 2 in human β-cells, is released in response to glucose stimulation. DA then acts as a negative regulator of insulin secretion via its action on D2R, which are also expressed on β-cells. We found that antagonism of receptors participating in islet DA signaling generally drive increased glucose-stimulated insulin secretion. These in vitro observations may represent correlates of the in vivo metabolic changes associated with the use of atypical antipsychotics, such as increased adiposity. PMID:22915827

  15. Evidence for paracrine/autocrine regulation of GLP-1-producing cells

    DEFF Research Database (Denmark)

    Kappe, Camilla; Zhang, Qimin; Holst, Jens Juul;

    2013-01-01

    Glucagon-like peptide-1 (GLP-1), secreted from gut L cells upon nutrient intake, forms the basis for novel drugs against type 2 diabetes (T2D). Secretion of GLP-1 has been suggested to be impaired in T2D and in conditions associated with hyperlipidemia and insulin resistance. Further, recent...... studies support lipotoxicity of GLP-1-producing cells in vitro. However, little is known about the regulation of L-cell viability/function, the effects of insulin signaling, or the potential effects of stable GLP-1 analogs and dipeptidyl peptidase-4 (DPP-4) inhibitors. We determined effects of insulin as...... well as possible autocrine action of GLP-1 on viability/apoptosis of GLP-1-secreting cells in the presence/absence of palmitate, while also assessing direct effects on function. The studies were performed using the GLP-1-secreting cell line GLUTag, and palmitate was used to simulate hyperlipidemia. Our...

  16. CD163 and IgG codefend against cytotoxic hemoglobin via autocrine and paracrine mechanisms.

    Science.gov (United States)

    Subramanian, Karthik; Du, Ruijuan; Tan, Nguan Soon; Ho, Bow; Ding, Jeak Ling

    2013-05-15

    Lysis of RBCs during numerous clinical settings such as severe hemolytic anemia, infection, tissue injury, or blood transfusion releases the endogenous damage-associated molecular pattern, hemoglobin (Hb), into the plasma. The redox-reactive Hb generates cytotoxic reactive oxygen species, disrupting the redox balance and impairing the immune-responsive blood cells. Therefore, it is crucial to understand how the immune system defends against the cytotoxic Hb. We identified a shortcut "capture and quench" mechanism of detoxification of Hb by the monocyte scavenger receptor CD163, independent of the well-known dominant antioxidant, haptoglobin. Our findings support a highly efficient two-pass mechanism of detoxification and clearance of Hb: 1) a direct suppression of Hb-pseudoperoxidase activity by CD163, involving an autocrine loop of CD163 shedding, sequestration of Hb, recycling, and homeostasis of CD163 in human monocytes and 2) paracrine transactivation of endothelial cells by the shedded soluble CD163 (sCD163), which further detoxifies and clears residual Hb. We showed that sCD163 and IgG interact with free Hb in the plasma and subsequently the sCD163-Hb-IgG complex is endocytosed into monocytes via FcγR. The endocytosed sCD163 is recycled to restore the homeostasis of CD163 on the monocyte membrane in an autocrine cycle, whereas the internalized Hb is catabolized. Using ex vivo coculture experiments, we demonstrated that the monocyte-derived sCD163 and IgG shuttle residual plasma Hb into the proximal endothelial cells. These findings suggest that CD163 and IgG collaborate to engage monocytes and endothelial cells in a two-pass detoxification mechanism to mount a systemic defense against Hb-induced oxidative stress. PMID:23589619

  17. Prediction

    OpenAIRE

    Woollard, W.J.

    2006-01-01

    In this chapter we will look at the ways in which you can use ICT in the classroom to support hypothesis and prediction and how modern technology is enabling: pattern seeking, extrapolation and interpolation to meet the challenges of the information explosion of the 21st century.

  18. Autocrine IL-8 promotes F-actin polymerization and mediate mesenchymal transition via ELMO1-NF-κB-Snail signaling in glioma

    OpenAIRE

    Zhang, Baogang; Shi, Lihong; Lu, Shijun; Sun, Xiuning; Liu, Yuqing; Li, Hongli; Wang, Xuejian; Zhao, Chunzhen; Zhang, Heng; Wang, Ying

    2015-01-01

    Glioma is the most common form of primary malignant brain cancers. Tumor cell invasiveness is a critical challenge in the clinical management of glioma patients. The invasive biological feature of glioma cell is stimulated by both autocrine and paracrine factors including chemokine IL-8. In this study, we report that the production of IL-8 is higher in glioma tissues and cells than adjacent nontumor tissues (ANT) and normal glial cells. Autocrine IL-8 can increase the invasive ability of glio...

  19. Autocrine MCP-1/CCR2 signaling stimulates proliferation and migration of renal carcinoma cells

    Science.gov (United States)

    Küper, Christoph; Beck, Franz-Xaver; Neuhofer, Wolfgang

    2016-01-01

    The chemokine monocyte chemoattractant protein-1 [MCP-1; also known as chemokine (C-C motif) ligand 2] is an important mediator of monocyte recruitment during inflammatory processes. Pathologically high expression levels of MCP-1 by tumor cells have been observed in a variety of cancer types. In the majority of cases, high MCP-1 expression is associated with a poor prognosis, as infiltration of the tumor with inflammatory monocytes promotes tumor progression and metastasis. MCP-1 is also expressed in renal cell carcinoma (RCC). In the present study, the function and the regulation of MCP-1 was investigated in two RCC cell lines, CaKi-1 and 786-O. In both cell lines, expression of MCP-1 was significantly enhanced compared with non-cancerous control cells. As expected, secretion of MCP-1 into the medium facilitated the recruitment of peripheral blood monocytes via the chemokine (C-C motif) receptor type 2 (CCR2). As expression of CCR2 was also detected in 786-O and CaKi-1 cells, the effect of autocrine MCP-1/CCR2 signaling was evaluated in these cells. In proliferation assays, administration of an MCP-1 neutralizing antibody or of a CCR2 antagonist to CaKi-1 and 786-O cells significantly decreased cell growth; supplementation of the growth medium with recombinant human MCP-1 had no additional effect on proliferation. The migration ability of RCC cells was impaired by MCP-1 neutralization or pharmacological CCR2 inhibition, while it was stimulated by the addition of recombinant human MCP-1, compared with untreated control cells. Finally, substantial differences in the regulation of MCP-1 expression were observed between RCC cell lines. In CaKi-1 cells, expression of MCP-1 appears to be largely mediated by the transcription factor nuclear factor of activated T cells 5, while in 786-O cells, deletion of the tumor suppressor gene Von-Hippel-Lindau appeared to be responsible for MCP-1 upregulation, as suggested by previous studies. Taken together, the results of the

  20. Autocrine effects of transgenic resistin reduce palmitate and glucose oxidation in brown adipose tissue.

    Science.gov (United States)

    Pravenec, Michal; Mlejnek, Petr; Zídek, Václav; Landa, Vladimír; Šimáková, Miroslava; Šilhavý, Jan; Strnad, Hynek; Eigner, Sebastian; Eigner Henke, Kateřina; Škop, Vojtěch; Malínská, Hana; Trnovská, Jaroslava; Kazdová, Ludmila; Drahota, Zdeněk; Mráček, Tomáš; Houštěk, Josef

    2016-06-01

    Resistin has been originally identified as an adipokine that links obesity to insulin resistance in mice. In our previous studies in spontaneously hypertensive rats (SHR) expressing a nonsecreted form of mouse resistin (Retn) transgene specifically in adipose tissue (SHR-Retn), we have observed an increased lipolysis and serum free fatty acids, ectopic fat accumulation in muscles, and insulin resistance. Recently, brown adipose tissue (BAT) has been suggested to play an important role in the pathogenesis of metabolic disturbances. In the current study, we have analyzed autocrine effects of transgenic resistin on BAT glucose and lipid metabolism and mitochondrial function in the SHR-Retn vs. nontransgenic SHR controls. We observed that interscapular BAT isolated from SHR-Retn transgenic rats compared with SHR controls showed a lower relative weight (0.71 ± 0.05 vs. 0.91 ± 0.08 g/100 g body wt, P < 0.05), significantly reduced both basal and insulin stimulated incorporation of palmitate into BAT lipids (658 ± 50 vs. 856 ± 45 and 864 ± 47 vs. 1,086 ± 35 nmol/g/2 h, P ≤ 0.01, respectively), and significantly decreased palmitate oxidation (37.6 ± 4.5 vs. 57 ± 4.1 nmol/g/2 h, P = 0.007) and glucose oxidation (277 ± 34 vs. 458 ± 38 nmol/g/2 h, P = 0.001). In addition, in vivo microPET imaging revealed significantly reduced (18)F-FDG uptake in BAT induced by exposure to cold in SHR-Retn vs. control SHR (232 ± 19 vs. 334 ± 22 kBq/ml, P < 0.05). Gene expression profiles in BAT identified differentially expressed genes involved in skeletal muscle and connective tissue development, inflammation and MAPK and insulin signaling. These results provide evidence that autocrine effects of resistin attenuate differentiation and activity of BAT and thus may play a role in the pathogenesis of insulin resistance in the rat. PMID:27113533

  1. Decreased autocrine EGFR signaling in metastatic breast cancer cells inhibits tumor growth in bone and mammary fat pad.

    Science.gov (United States)

    Nickerson, Nicole K; Mohammad, Khalid S; Gilmore, Jennifer L; Crismore, Erin; Bruzzaniti, Angela; Guise, Theresa A; Foley, John

    2012-01-01

    Breast cancer metastasis to bone triggers a vicious cycle of tumor growth linked to osteolysis. Breast cancer cells and osteoblasts express the epidermal growth factor receptor (EGFR) and produce ErbB family ligands, suggesting participation of these growth factors in autocrine and paracrine signaling within the bone microenvironment. EGFR ligand expression was profiled in the bone metastatic MDA-MB-231 cells (MDA-231), and agonist-induced signaling was examined in both breast cancer and osteoblast-like cells. Both paracrine and autocrine EGFR signaling were inhibited with a neutralizing amphiregulin antibody, PAR34, whereas shRNA to the EGFR was used to specifically block autocrine signaling in MDA-231 cells. The impact of these was evaluated with proliferation, migration and gene expression assays. Breast cancer metastasis to bone was modeled in female athymic nude mice with intratibial inoculation of MDA-231 cells, and cancer cell-bone marrow co-cultures. EGFR knockdown, but not PAR34 treatment, decreased osteoclasts formed in vitro (p<0.01), reduced osteolytic lesion tumor volume (p<0.01), increased survivorship in vivo (p<0.001), and resulted in decreased MDA-231 growth in the fat pad (p<0.01). Fat pad shEGFR-MDA-231 tumors produced in nude mice had increased necrotic areas and decreased CD31-positive vasculature. shEGFR-MDA-231 cells also produced decreased levels of the proangiogenic molecules macrophage colony stimulating factor-1 (MCSF-1) and matrix metalloproteinase 9 (MMP9), both of which were decreased by EGFR inhibitors in a panel of EGFR-positive breast cancer cells. Thus, inhibiting autocrine EGFR signaling in breast cancer cells may provide a means for reducing paracrine factor production that facilitates microenvironment support in the bone and mammary gland. PMID:22276166

  2. Decreased Autocrine EGFR Signaling in Metastatic Breast Cancer Cells Inhibits Tumor Growth in Bone and Mammary Fat Pad

    OpenAIRE

    Nickerson, Nicole K.; Mohammad, Khalid S.; Gilmore, Jennifer L.; Crismore, Erin; Bruzzaniti, Angela; Guise, Theresa A.; Foley, John

    2012-01-01

    Breast cancer metastasis to bone triggers a vicious cycle of tumor growth linked to osteolysis. Breast cancer cells and osteoblasts express the epidermal growth factor receptor (EGFR) and produce ErbB family ligands, suggesting participation of these growth factors in autocrine and paracrine signaling within the bone microenvironment. EGFR ligand expression was profiled in the bone metastatic MDA-MB-231 cells (MDA-231), and agonist-induced signaling was examined in both breast cancer and oste...

  3. Decreased autocrine EGFR signaling in metastatic breast cancer cells inhibits tumor growth in bone and mammary fat pad.

    Directory of Open Access Journals (Sweden)

    Nicole K Nickerson

    Full Text Available Breast cancer metastasis to bone triggers a vicious cycle of tumor growth linked to osteolysis. Breast cancer cells and osteoblasts express the epidermal growth factor receptor (EGFR and produce ErbB family ligands, suggesting participation of these growth factors in autocrine and paracrine signaling within the bone microenvironment. EGFR ligand expression was profiled in the bone metastatic MDA-MB-231 cells (MDA-231, and agonist-induced signaling was examined in both breast cancer and osteoblast-like cells. Both paracrine and autocrine EGFR signaling were inhibited with a neutralizing amphiregulin antibody, PAR34, whereas shRNA to the EGFR was used to specifically block autocrine signaling in MDA-231 cells. The impact of these was evaluated with proliferation, migration and gene expression assays. Breast cancer metastasis to bone was modeled in female athymic nude mice with intratibial inoculation of MDA-231 cells, and cancer cell-bone marrow co-cultures. EGFR knockdown, but not PAR34 treatment, decreased osteoclasts formed in vitro (p<0.01, reduced osteolytic lesion tumor volume (p<0.01, increased survivorship in vivo (p<0.001, and resulted in decreased MDA-231 growth in the fat pad (p<0.01. Fat pad shEGFR-MDA-231 tumors produced in nude mice had increased necrotic areas and decreased CD31-positive vasculature. shEGFR-MDA-231 cells also produced decreased levels of the proangiogenic molecules macrophage colony stimulating factor-1 (MCSF-1 and matrix metalloproteinase 9 (MMP9, both of which were decreased by EGFR inhibitors in a panel of EGFR-positive breast cancer cells. Thus, inhibiting autocrine EGFR signaling in breast cancer cells may provide a means for reducing paracrine factor production that facilitates microenvironment support in the bone and mammary gland.

  4. Promotion of Human Early Embryonic Development and Blastocyst Outgrowth In Vitro Using Autocrine/Paracrine Growth Factors

    OpenAIRE

    Kawamura, Kazuhiro; Chen, Yuan; Shu, Yimin; Cheng, Yuan; Qiao, Jie; Behr, Barry; Pera, Renee A Reijo; Hsueh, Aaron J. W.

    2012-01-01

    Studies using animal models demonstrated the importance of autocrine/paracrine factors secreted by preimplantation embryos and reproductive tracts for embryonic development and implantation. Although in vitro fertilization-embryo transfer (IVF-ET) is an established procedure, there is no evidence that present culture conditions are optimal for human early embryonic development. In this study, key polypeptide ligands known to be important for early embryonic development in animal models were t...

  5. UVR induction of TGFα: a possible autocrine mechanism for the epidermal melanocytic response and for promotion of epidermal carcinogenesis

    International Nuclear Information System (INIS)

    The occurrence of the epidermal growth factor homologue, transforming growth factor α (TGFα), in embryonic and neoplastic tissues suggest that it may be an oncofetal version of epidermal growth factor. A strong case is developing for TGFα to have an autocrine mode of action in sustaining the autonomous growth of several types of tumour. We propose that TGFα normally has an autocrine role not only in stimulating the growth of some fetal tissues but also with postnatal epidermal cells in response to local stimuli-in particular ultraviolet radiation (UVR). We found that cultures of normal foreskin melanocytes do not produce detectable amounts of TGFα when grown under routine conditions, but, within 12 h of exposure to low doses of short-wavelength UVR, significant quantities of TGFα are produced. The UVR-induced TGFα is both cell associated and released into the medium of these cultures. Also, UVR has a promoting action on epidermal cells which have been initiated by carcinogenic activity. A significant part of the promoting activity may be due to autocrine stimulation of multiplication of partially transformed epidermal cells. In this regard we found that UVR induced TGFα in HeLa cells and all human melanoma lines so far tested. (author)

  6. Autocrine-controlled formation and function of tissue-like aggregates by primary hepatocytes in micropatterned hydrogel arrays.

    Science.gov (United States)

    Williams, Courtney M; Mehta, Geeta; Peyton, Shelly R; Zeiger, Adam S; Van Vliet, Krystyn J; Griffith, Linda G

    2011-04-01

    The liver carries out a variety of essential functions regulated in part by autocrine signaling, including hepatocyte-produced growth factors and extracellular matrix (ECM). The local concentrations of autocrine factors are governed by a balance between receptor-mediated binding at the cell surface and diffusion into the local matrix and are thus expected to be influenced by the dimensionality of the cell culture environment. To investigate the role of growth factor and ECM-modulated autocrine signaling in maintaining appropriate primary hepatocyte survival, metabolic functions, and polarity, we created three-dimensional cultures of defined geometry using micropatterned semisynthetic polyethylene glycol-fibrinogen hydrogels to provide a mechanically compliant, nonadhesive material platform that could be modified by cell-secreted factors. We found that in the absence of exogenous peptide growth factors or ECM, hepatocytes retain the epidermal growth factor (EGF) receptor ligands (EGF and transforming growth factor-α) and the proto-oncogenic mesenchymal epithelial transition factor (c-MET) ligand hepatocyte growth factor (HGF), along with fibronectin. Further, hepatocytes cultured in this three-dimensional microenvironment maintained high levels of liver-specific functions over the 10-day culture period. Function-blocking inhibitors of α5β1 or EGF receptor dramatically reduced cell viability and function, suggesting that signaling by both these receptors is needed for in vitro survival and function of hepatocytes in the absence of other exogenous signals. PMID:21121876

  7. GDNF protects enteric glia from apoptosis: evidence for an autocrine loop

    Directory of Open Access Journals (Sweden)

    Steinkamp Martin

    2012-01-01

    Full Text Available Abstract Background Enteric glia cells (EGC play an important role in the maintenance of intestinal mucosa integrity. During the course of acute Crohn's disease (CD, mucosal EGC progressively undergo apoptosis, though the mechanisms are largely unknown. We investigated the role of Glial-derived neurotrophic factor (GDNF in the regulation of EGC apoptosis. Methods GDNF expression and EGC apoptosis were determined by immunofluorescence using specimen from CD patients. In primary rat EGC cultures, GDNF receptors were assessed by western blot and indirect immunofluorescence microscopy. Apoptosis in cultured EGC was induced by TNF-α and IFN-γ, and the influence of GDNF on apoptosis was measured upon addition of GDNF or neutralizing anti-GDNF antibody. Results Increased GDNF expression and Caspase 3/7 activities were detected in in specimen of CD patients but not in healthy controls. Moreover, inactivation of GDNF sensitized in EGC cell to IFN-γ/TNF-α induced apoptosis. Conclusions This study proposes the existence of an autocrine anti-apoptotic loop in EGC cells which is operative in Crohn's disease and dependent of GDNF. Alterations in this novel EGC self-protecting mechanism could lead to a higher susceptibility towards apoptosis and thus contribute to disruption of the mucosal integrity and severity of inflammation in CD.

  8. MCP-1 expressed by osteoclasts stimulates osteoclastogenesis in an autocrine/paracrine manner

    International Nuclear Information System (INIS)

    Monocyte chemoattractant protein-1 (MCP-1) is a chemokine that plays a critical role in the recruitment and activation of leukocytes. Here, we describe that multinuclear osteoclast formation was significantly inhibited in cells derived from MCP-1-deficient mice. MCP-1 has been implicated in the regulation of osteoclast cell-cell fusion; however defects of multinuclear osteoclast formation in the cells from mice deficient in DC-STAMP, a seven transmembrane receptor essential for osteoclast cell-cell fusion, was not rescued by recombinant MCP-1. The lack of MCP-1 in osteoclasts resulted in a down-regulation of DC-STAMP, NFATc1, and cathepsin K, all of which were highly expressed in normal osteoclasts, suggesting that osteoclast differentiation was inhibited in MCP-1-deficient cells. MCP-1 alone did not induce osteoclastogenesis, however, the inhibition of osteoclastogenesis in MCP-1-deficient cells was restored by addition of recombinant MCP-1, indicating that osteoclastogenesis was regulated in an autocrine/paracrine manner by MCP-1 under the stimulation of RANKL in osteoclasts.

  9. Interleukin 1 as an autocrine growth factor for acute myeloid leukemia cells

    International Nuclear Information System (INIS)

    Production of interleukin 1 (IL-1) by leukemic cells was studied in 13 cases of acute myeloid leukemia. Intracytoplasmic immunofluorescence studies showed that the cells invariably contained the cytokine. Endogenous labeling studies demonstrated that acute myeloid leukemia cells produced either only the 33-kDa propeptide or both the propeptide and the 17-kDa mature form of IL-1β. The 33-kDa propeptide IL-1α was always produced but was less frequently released. Involvement of IL-1 in leukemic cell growth was investigated using two antibodies specific for IL-1 subtypes, which inhibited spontaneous cell proliferation in the six cases studied. After acid treatment of the cells, a surface receptor for IL-1 could be demonstrated, which mediated 125I-labeled IL-1-specific uptake by leukemic cells. Furthermore, recombinant IL-1α or IL-1β induced significant cell proliferation in 10 12 cases. The above findings were uncorrelated with the cytologic type (French-American-British classification) of leukemia. The studies suggest that IL-1 may act as an autocrine growth factor in most cases of acute myeloid leukemia

  10. Toxoplasma gondii exposes phosphatidylserine inducing a TGF-β1 autocrine effect orchestrating macrophage evasion

    International Nuclear Information System (INIS)

    Toxoplasmosis is a worldwide disease caused by Toxoplasma gondii. Activated macrophages control T. gondii growth by nitric oxide (NO) production. However, T. gondii active invasion inhibits NO production, allowing parasite persistence. Here we show that the mechanism used by T. gondii to inhibit NO production persisting in activated macrophages depends on phosphatidylserine (PS) exposure. Masking PS with annexin-V on parasites or activated macrophages abolished NO production inhibition and parasite persistence. NO production inhibition depended on a transforming growth factor-β1 (TGF-β1) autocrine effect confirmed by the expression of Smad 2 and 3 in infected macrophages. TGF-β1 led to inducible nitric oxide synthase (iNOS) degradation, actin filament (F-actin) depolymerization, and lack of nuclear factor-κB (NF-κB) in the nucleus. All these features were reverted by TGF-β1 neutralizing antibody treatment. Thus, T. gondii mimics the evasion mechanism used by Leishmania amazonensis and also the anti-inflammatory response evoked by apoptotic cells

  11. Autocrine effects of neuromedin B stimulate the proliferation of rat primary osteoblasts.

    Science.gov (United States)

    Saito, Hiroki; Nakamachi, Tomoya; Inoue, Kazuhiko; Ikeda, Ryuji; Kitamura, Kazuo; Minamino, Naoto; Shioda, Seiji; Miyata, Atsuro

    2013-05-01

    Neuromedin B (NMB) is a mammalian bombesin-like peptide that regulates exocrine/endocrine secretion, smooth muscle contraction, body temperature, and the proliferation of some cell types. Here, we show that mRNA encoding Nmb and its receptor (Nmbr) are expressed in rat bone tissue. Immunohistochemical analysis demonstrated that NMB and NMBR colocalize in osteoblasts, epiphyseal chondrocytes, and proliferative chondrocytes of growth plates from mouse hind limbs. Then, we investigated the effect of NMB on the proliferation of rat primary cultured osteoblasts. Proliferation assays and 5-bromo-2'-deoxyuridine incorporation assays demonstrated that NMB augments the cell number and enhances DNA synthesis in osteoblasts. Pretreatment with the NMBR antagonist BIM23127 inhibited NMB-induced cell proliferation and DNA synthesis. Western blot analysis showed that NMB activates ERK1/2 MAPK signaling in osteoblasts. Pretreatment with the MAPK/ERK kinase inhibitor U0126 attenuated NMB-induced cell proliferation and DNA synthesis. We also investigated the effects of molecules that contribute to osteoblast proliferation and differentiation on Nmb expression in osteoblasts. Real-time PCR analysis demonstrated that 17β-estradiol (E2) and transforming growth factor β1 increase and decrease Nmb mRNA expression levels respectively. Finally, proliferation assays revealed that the NMBR antagonist BIM23127 suppresses E2-induced osteoblast proliferation. These results suggest that NMB/NMBR signaling plays an autocrine or paracrine role in osteoblast proliferation and contributes to the regulation of bone formation. PMID:23428580

  12. Differential genomic imprinting regulates paracrine and autocrine roles of IGF2 in mouse adult neurogenesis.

    Science.gov (United States)

    Ferrón, S R; Radford, E J; Domingo-Muelas, A; Kleine, I; Ramme, A; Gray, D; Sandovici, I; Constancia, M; Ward, A; Menheniott, T R; Ferguson-Smith, A C

    2015-01-01

    Genomic imprinting is implicated in the control of gene dosage in neurogenic niches. Here we address the importance of Igf2 imprinting for murine adult neurogenesis in the subventricular zone (SVZ) and in the subgranular zone (SGZ) of the hippocampus in vivo. In the SVZ, paracrine IGF2 is a cerebrospinal fluid and endothelial-derived neurogenic factor requiring biallelic expression, with mutants having reduced activation of the stem cell pool and impaired olfactory bulb neurogenesis. In contrast, Igf2 is imprinted in the hippocampus acting as an autocrine factor expressed in neural stem cells (NSCs) solely from the paternal allele. Conditional mutagenesis of Igf2 in blood vessels confirms that endothelial-derived IGF2 contributes to NSC maintenance in SVZ but not in the SGZ, and that this is regulated by the biallelic expression of IGF2 in the vascular compartment. Our findings indicate that a regulatory decision to imprint or not is a functionally important mechanism of transcriptional dosage control in adult neurogenesis. PMID:26369386

  13. Type IV collagen stimulates pancreatic cancer cell proliferation, migration, and inhibits apoptosis through an autocrine loop

    International Nuclear Information System (INIS)

    Pancreatic cancer shows a highly aggressive and infiltrative growth pattern and is characterized by an abundant tumor stroma known to interact with the cancer cells, and to influence tumor growth and drug resistance. Cancer cells actively take part in the production of extracellular matrix proteins, which then become deposited into the tumor stroma. Type IV collagen, an important component of the basement membrane, is highly expressed by pancreatic cancer cells both in vivo and in vitro. In this study, the cellular effects of type IV collagen produced by the cancer cells were characterized. The expression of type IV collagen and its integrin receptors were examined in vivo in human pancreatic cancer tissue. The cellular effects of type IV collagen were studied in pancreatic cancer cell lines by reducing type IV collagen expression through RNA interference and by functional receptor blocking of integrins and their binding-sites on the type IV collagen molecule. We show that type IV collagen is expressed close to the cancer cells in vivo, forming basement membrane like structures on the cancer cell surface that colocalize with the integrin receptors. Furthermore, the interaction between type IV collagen produced by the cancer cell, and integrins on the surface of the cancer cells, are important for continuous cancer cell growth, maintenance of a migratory phenotype, and for avoiding apoptosis. We show that type IV collagen provides essential cell survival signals to the pancreatic cancer cells through an autocrine loop

  14. Inhibition of KRAS-driven tumorigenicity by interruption of an autocrine cytokine circuit.

    Science.gov (United States)

    Zhu, Zehua; Aref, Amir R; Cohoon, Travis J; Barbie, Thanh U; Imamura, Yu; Yang, Shenghong; Moody, Susan E; Shen, Rhine R; Schinzel, Anna C; Thai, Tran C; Reibel, Jacob B; Tamayo, Pablo; Godfrey, Jason T; Qian, Zhi Rong; Page, Asher N; Maciag, Karolina; Chan, Edmond M; Silkworth, Whitney; Labowsky, Mary T; Rozhansky, Lior; Mesirov, Jill P; Gillanders, William E; Ogino, Shuji; Hacohen, Nir; Gaudet, Suzanne; Eck, Michael J; Engelman, Jeffrey A; Corcoran, Ryan B; Wong, Kwok-Kin; Hahn, William C; Barbie, David A

    2014-04-01

    Although the roles of mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K) signaling in KRAS-driven tumorigenesis are well established, KRAS activates additional pathways required for tumor maintenance, the inhibition of which are likely to be necessary for effective KRAS-directed therapy. Here, we show that the IκB kinase (IKK)-related kinases Tank-binding kinase-1 (TBK1) and IKKε promote KRAS-driven tumorigenesis by regulating autocrine CCL5 and interleukin (IL)-6 and identify CYT387 as a potent JAK/TBK1/IKKε inhibitor. CYT387 treatment ablates RAS-associated cytokine signaling and impairs Kras-driven murine lung cancer growth. Combined CYT387 treatment and MAPK pathway inhibition induces regression of aggressive murine lung adenocarcinomas driven by Kras mutation and p53 loss. These observations reveal that TBK1/IKKε promote tumor survival by activating CCL5 and IL-6 and identify concurrent inhibition of TBK1/IKKε, Janus-activated kinase (JAK), and MEK signaling as an effective approach to inhibit the actions of oncogenic KRAS. PMID:24444711

  15. Autocrine and Paracrine Actions of IGF-I Signaling in Skeletal Development

    Institute of Scientific and Technical Information of China (English)

    Yongmei Wang; Daniel D. Bikle; Wenhan Chang

    2013-01-01

    Insulin-like growth factor-I (IGF-I) regulates cell growth, survival, and differentiation by acting on the IGF-I receptor, (IGF-IR)-a tyrosine kinase receptor, which elicits diverse intracellular signaling responses. All skeletal cells express IGF-I and IGF-IR. Recent studies using tissue/cell-specific gene knockout mouse models and cell culture techniques have clearly demonstrated that locally produced IGF-I is more critical than the systemic IGF-I in supporting embryonic and postnatal skeletal development and bone remodeling. Local IGF-I/IGF-IR signaling promotes the growth, survival and differentiation of chondrocytes and osteo-blasts, directly and indirectly, by altering other autocrine/paracrine signaling pathways in cartilage and bone, and by enhancing interactions among these skeletal cells through hormonal and physical means. Moreover, local IGF-I/IGF-IR signaling is critical for the anabolic bone actions of growth hormone and parathyroid hormone. Herein, we review evidence supporting the actions of local IGF-I/IGF-IR in the above aspects of skeletal development and remodeling.

  16. Autocrine fibroblast growth factor 18 mediates dexamethasone-induced osteogenic differentiation of murine mesenchymal stem cells.

    Science.gov (United States)

    Hamidouche, Zahia; Fromigué, Olivia; Nuber, Ulrike; Vaudin, Pascal; Pages, Jean-Christophe; Ebert, Regina; Jakob, Franz; Miraoui, Hichem; Marie, Pierre J

    2010-08-01

    The potential of mesenchymal stem cells (MSC) to differentiate into functional bone forming cells provides an important tool for bone regeneration. The identification of factors capable of promoting osteoblast differentiation in MSCs is therefore critical to enhance the osteogenic potential of MSCs. Using microarray analysis combined with biochemical and molecular approach, we found that FGF18, a member of the FGF family, is upregulated during osteoblast differentiation induced by dexamethasone in murine MSCs. We showed that overexpression of FGF18 by lentiviral (LV) infection, or treatment of MSCs with recombinant human (rh)FGF18 increased the expression of the osteoblast specific transcription factor Runx2, and enhanced osteoblast phenotypic marker gene expression and in vitro osteogenesis. Molecular silencing using lentiviral shRNA demonstrated that downregulation of FGFR1 or FGFR2 abrogated osteoblast gene expression induced by either LV-FGF18 or rhFGF18, indicating that FGF18 enhances osteoblast differentiation in MSCs via activation of FGFR1 or FGFR2 signaling. Biochemical and pharmacological analyses showed that the induction of phenotypic osteoblast markers by LV-FGF18 is mediated by activation of ERK1/2-MAPKs and PI3K signaling in MSCs. These results reveal that FGF18 is an essential autocrine positive regulator of the osteogenic differentiation program in murine MSCs and indicate that osteogenic differentiation induced by FGF18 in MSCs is triggered by FGFR1/FGFR2-mediated ERK1/2-MAPKs and PI3K signaling. PMID:20432451

  17. Autocrine regulation of cell proliferation by estrogen receptor-alpha in estrogen receptor-alpha-positive breast cancer cell lines

    Directory of Open Access Journals (Sweden)

    Pan Zhongzong

    2009-01-01

    Full Text Available Abstract Background Estrogen receptor-α (ERα is essential for mammary gland development and is a major oncogene in breast cancer. Since ERα is not colocalized with the cell proliferation marker Ki-67 in the normal mammary glands and the majority of primary breast tumors, it is generally believed that paracrine regulation is involved in ERα mediated cell proliferation. In the paracrine model, ERα-positive cells don't proliferate but will release some paracrine growth factors to stimulate the neighboring cells to proliferate. In a subpopulation of cancer cells in some primary breast tumors, however, ERα does colocalize with the cell proliferation marker Ki-67, suggesting an autocrine regulation by ERα in some primary breast tumors. Methods Colocalization of ERα with Ki-67 in ERα-positive breast cancer cell lines (MCF-7, T47D, and ZR75-1 was evaluated by immunofluorescent staining. Cell cycle phase dependent expression of ERα was determined by co-immunofluorescent staining of ERα and the major cyclins (D, E, A, B, and by flow cytometry analysis of ERαhigh cells. To further confirm the autocrine action of ERα, MCF-7 cells were growth arrested by ICI182780 treatment, followed by treatment with EGFR inhibitor, before estrogen stimulation and analyses for colocalization of Ki-67 and ERα and cell cycle progression. Results Colocalization of ERα with Ki-67 was present in all three ERα-positive breast cancer cell lines. Unlike that in the normal mammary glands and the majority of primary breast tumors, ERα is highly expressed throughout the cell cycle in MCF-7 cells. Without E2 stimulation, MCF-7 cells released from ICI182780 treatment remain at G1 phase. E2 stimulation of ICI182780 treated cells, however, promotes the expression and colocalization of ERα and Ki-67 as well as the cell cycle progressing through the S and G2/M phases. Inhibition of EGFR signaling does not inhibit the autocrine action of ERα. Conclusion Our data indicate

  18. Autocrine regulation of cell proliferation by estrogen receptor-alpha in estrogen receptor-alpha-positive breast cancer cell lines

    International Nuclear Information System (INIS)

    Estrogen receptor-α (ERα) is essential for mammary gland development and is a major oncogene in breast cancer. Since ERα is not colocalized with the cell proliferation marker Ki-67 in the normal mammary glands and the majority of primary breast tumors, it is generally believed that paracrine regulation is involved in ERα mediated cell proliferation. In the paracrine model, ERα-positive cells don't proliferate but will release some paracrine growth factors to stimulate the neighboring cells to proliferate. In a subpopulation of cancer cells in some primary breast tumors, however, ERα does colocalize with the cell proliferation marker Ki-67, suggesting an autocrine regulation by ERα in some primary breast tumors. Colocalization of ERα with Ki-67 in ERα-positive breast cancer cell lines (MCF-7, T47D, and ZR75-1) was evaluated by immunofluorescent staining. Cell cycle phase dependent expression of ERα was determined by co-immunofluorescent staining of ERα and the major cyclins (D, E, A, B), and by flow cytometry analysis of ERαhigh cells. To further confirm the autocrine action of ERα, MCF-7 cells were growth arrested by ICI182780 treatment, followed by treatment with EGFR inhibitor, before estrogen stimulation and analyses for colocalization of Ki-67 and ERα and cell cycle progression. Colocalization of ERα with Ki-67 was present in all three ERα-positive breast cancer cell lines. Unlike that in the normal mammary glands and the majority of primary breast tumors, ERα is highly expressed throughout the cell cycle in MCF-7 cells. Without E2 stimulation, MCF-7 cells released from ICI182780 treatment remain at G1 phase. E2 stimulation of ICI182780 treated cells, however, promotes the expression and colocalization of ERα and Ki-67 as well as the cell cycle progressing through the S and G2/M phases. Inhibition of EGFR signaling does not inhibit the autocrine action of ERα. Our data indicate that ERα can mediate estrogen-induced cell proliferation in

  19. Prediction

    CERN Document Server

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  20. L-22 enhances the invasiveness of endometrial stromal cells of adenomyosis in an autocrine manner.

    Science.gov (United States)

    Wang, Qing; Wang, Li; Shao, Jun; Wang, Yan; Jin, Li-Ping; Li, Da-Jin; Li, Ming-Qing

    2014-01-01

    It has reported that interleukin-22 (IL-22) promotes the invasion of tumor cells. IL-22 in the endometriotic milieu stimulates the proliferation of human endometrial stromal cells (ESCs). The present study aimed to elucidate whether and how IL-22 regulates the invasion of ESCs from adenomyosis. The expression of IL-22 and its receptors in normal endometrium, eutopic endometrium and ectopic lesion was analyzed by immunohistochemistry; the invasiveness of ESCs in vitro was verified by Matrigel invasion assay; and the effects of IL-22 on the correspondent functional molecules were investigated by ELISA and flow cytometry. Here we found that IL-22 and its receptors IL-22R1 and IL-10R2 in eutopic endometrium and ectopic lesion of adenomyosis were significantly higher than that of normal endometrium. Recombinant human IL-22 (rhIL-22) increased IL-22R1 and IL-10R2 levels on ESCs. Moreover, rhIL-22 promoted the invasiveness of ESCs, and inhibited the expression of metastasis suppressor gene CD82, stimulated the secretion of IL-8, RANTES, IL-6 and VEGF of ESCs. On the contrary, the neutralizing antibody for IL-22 reversed these effects. Our current study has demonstrated that IL-22 has a positive feedback on the expression of its receptors IL-22R1 and IL-10R2 on ESCs. This autocrine effect of IL-22 promotes the invasion of ESCs possibly through regulating invasion-related molecules, suggesting that the abnormal high expression of IL-22 may play an important role in ESCs invasion and finally contribute to the origin and development of adenomyosis. PMID:25337217

  1. Stimulated human mast cells secrete mitochondrial components that have autocrine and paracrine inflammatory actions.

    Directory of Open Access Journals (Sweden)

    Bodi Zhang

    Full Text Available Mast cells are hematopoietically-derived tissue immune cells that participate in acquired and innate immunity, as well as in inflammation through release of many chemokines and cytokines, especially in response to the pro-inflammatory peptide substance P (SP. Inflammation is critical in the pathogenesis of many diseases, but the trigger(s is often unknown. We investigated if mast cell stimulation leads to secretion of mitochondrial components and whether these could elicit autocrine and/or paracrine inflammatory effects. Here we show that human LAD2 mast cells stimulated by IgE/anti-IgE or by the SP led to secretion of mitochondrial particles, mitochondrial (mt mtDNA and ATP without cell death. Mitochondria purified from LAD2 cells and, when mitochondria added to mast cells trigger degranulation and release of histamine, PGD(2, IL-8, TNF, and IL-1β. This stimulatory effect is partially inhibited by an ATP receptor antagonist and by DNAse. These results suggest that the mitochondrial protein fraction may also contribute. Purified mitochondria also stimulate IL-8 and vascular endothelial growth factor (VEGF release from cultured human keratinocytes, and VEGF release from primary human microvascular endothelial cells. In order to investigate if mitochondrial components could be secreted in vivo, we injected rats intraperiotoneally (ip with compound 48/80, which mimicks the action of SP. Peritoneal mast cells degranulated and mitochondrial particles were documented by transimission electron microscopy outside the cells. We also wished to investigate if mitochondrial components secreted locally could reach the systemic circulation. Administration ip of mtDNA isolated from LAD2 cells in rats was detected in their serum within 4 hr, indicating that extravascular mtDNA could enter the systemic circulation. Secretion of mitochondrial components from stimulated live mast cells may act as "autopathogens" contributing to the pathogenesis of inflammatory

  2. Interleukin 6 promotes endometrial cancer growth through an autocrine feedback loop involving ERK–NF-κB signaling pathway

    Energy Technology Data Exchange (ETDEWEB)

    Che, Qi; Liu, Bin-Ya; Wang, Fang-Yuan; He, Yin-Yan; Lu, Wen; Liao, Yun [Department of Obstetrics and Gynecology, Shanghai First People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai (China); Gu, Wei, E-mail: krisgu70@163.com [Department of Obstetrics and Gynecology, International Peace Maternity and Child Health Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai (China); Wan, Xiao-Ping, E-mail: wanxp@sjtu.edu.cn [Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital Affiliated to Tong Ji University, Shanghai (China)

    2014-03-28

    Highlights: • IL-6 could promote endometrial cancer cells proliferation. • IL-6 promotes its own production through an autocrine feedback loop. • ERK and NF-κB pathway inhibitors inhibit IL-6 production and tumor growth. • IL-6 secretion relies on the activation of ERK–NF-κB pathway axis. • An orthotopic nude endometrial carcinoma model confirms the effect of IL-6. - Abstract: Interleukin (IL)-6 as an inflammation factor, has been proved to promote cancer proliferation in several human cancers. However, its role in endometrial cancer has not been studied clearly. Previously, we demonstrated that IL-6 promoted endometrial cancer progression through local estrogen biosynthesis. In this study, we proved that IL-6 could directly stimulate endometrial cancer cells proliferation and an autocrine feedback loop increased its production even after the withdrawal of IL-6 from the medium. Next, we analyzed the mechanism underlying IL-6 production in the feedback loop and found that its production and IL-6-stimulated cell proliferation were effectively blocked by pharmacologic inhibitors of nuclear factor-kappa B (NF-κB) and extra-cellular signal-regulated kinase (ERK). Importantly, activation of ERK was upstream of the NF-κB pathways, revealing the hierarchy of this event. Finally, we used an orthotopic nude endometrial carcinoma model to confirm the effects of IL-6 on the tumor progression. Taken together, these data indicate that IL-6 promotes endometrial carcinoma growth through an expanded autocrine regulatory loop and implicate the ERK–NF-κB pathway as a critical mediator of IL-6 production, implying IL-6 to be an important therapeutic target in endometrial carcinoma.

  3. Interleukin 6 promotes endometrial cancer growth through an autocrine feedback loop involving ERK–NF-κB signaling pathway

    International Nuclear Information System (INIS)

    Highlights: • IL-6 could promote endometrial cancer cells proliferation. • IL-6 promotes its own production through an autocrine feedback loop. • ERK and NF-κB pathway inhibitors inhibit IL-6 production and tumor growth. • IL-6 secretion relies on the activation of ERK–NF-κB pathway axis. • An orthotopic nude endometrial carcinoma model confirms the effect of IL-6. - Abstract: Interleukin (IL)-6 as an inflammation factor, has been proved to promote cancer proliferation in several human cancers. However, its role in endometrial cancer has not been studied clearly. Previously, we demonstrated that IL-6 promoted endometrial cancer progression through local estrogen biosynthesis. In this study, we proved that IL-6 could directly stimulate endometrial cancer cells proliferation and an autocrine feedback loop increased its production even after the withdrawal of IL-6 from the medium. Next, we analyzed the mechanism underlying IL-6 production in the feedback loop and found that its production and IL-6-stimulated cell proliferation were effectively blocked by pharmacologic inhibitors of nuclear factor-kappa B (NF-κB) and extra-cellular signal-regulated kinase (ERK). Importantly, activation of ERK was upstream of the NF-κB pathways, revealing the hierarchy of this event. Finally, we used an orthotopic nude endometrial carcinoma model to confirm the effects of IL-6 on the tumor progression. Taken together, these data indicate that IL-6 promotes endometrial carcinoma growth through an expanded autocrine regulatory loop and implicate the ERK–NF-κB pathway as a critical mediator of IL-6 production, implying IL-6 to be an important therapeutic target in endometrial carcinoma

  4. Age-related autocrine diabetogenic effects of transgenic resistin in spontaneously hypertensive rats: gene expression profile analysis

    Czech Academy of Sciences Publication Activity Database

    Pravenec, Michal; Zídek, Václav; Landa, Vladimír; Šimáková, Miroslava; Mlejnek, Petr; Šilhavý, J.; Maxová, M.; Kazdová, L.; Seidman, J. G.; Seidman, Ch. E.; Eminaga, S.; Gorham, J.; Wang, J.; Kurtz, T. W.

    2011-01-01

    Roč. 43, č. 7 (2011), s. 372-379. ISSN 1094-8341 R&D Projects: GA MŠk(CZ) ME08006; GA MŠk(CZ) 1M0510; GA AV ČR(CZ) IAA500110805; GA MZd(CZ) NS9759 Grant ostatní: Fondation Leducq(FR) 06CVD03 Institutional research plan: CEZ:AV0Z50110509 Keywords : transgenic rat * adipose tissue * insulin resistance * autocrine effects Subject RIV: FB - Endocrinology, Diabetology, Metabolism, Nutrition Impact factor: 2.735, year: 2011

  5. Sonic Hedgehog Signaling Protects Human Hepatocellular Carcinoma Cells Against Ionizing Radiation in an Autocrine Manner

    International Nuclear Information System (INIS)

    Purpose: Sonic hedgehog (Shh) signaling is critical to embryogenesis and resistance to chemotherapy. We aimed to examine the role of Shh signaling in the response to radiation of human hepatocellular carcinoma (HCC) cells. Methods and Materials: Response to ionizing radiation therapy (RT) was evaluated by clonogenic assay. Quantitative RT-polymerase chain reaction for patched-1 (PTCH-1) expression was performed. Cytosolic accumulation of Shh and nuclear translocation of Gli-1 were assessed by immunofluorescence. Gli-1 knockdown was done by RNA interference (RNAi). Immunoprecipitation was performed to detect Shh ligand in conditioned medium. Immunofluorescent stain for γ-H2AX was used as an index of DNA double strand breaks (DSB). Expression of proteins related to DNA damage repair was assessed by Western blotting. Results: We found that Shh ligand could protect human HCC HA22T and Sk-Hep1 cells against RT. In HA22T cells, Shh ligand activated the Shh signaling with upregulation of Shh, PTCH-1, and Gli-1 expression. The nuclear translocation of Gli-1 further supports the activation of Gli-1. The radioprotection by Shh ligand was partly blocked by Shh antibody neutralization and was abolished by Gli-1 RNAi, suggesting a critical role of Shh signaling in radiation resistance. Furthermore, we noted that soluble factors secreted into conditioned medium, either constitutively or responding to radiation, by HA22T or Sk-Hep1 cells protected subsequent culturing cells against RT. Immunoprecipitation shows the presence of Shh peptide in conditioned medium. Intriguingly, antibody neutralization of Shh ligand or knockdown of Gli-1 reversed the radioprotective effect of conditioned medium. Furthermore, Shh ligand reduced the RT-induced phosphorylation of checkpoint kinase 1 and impaired the repair of DNA DSB. Conclusions: Activation of Shh signaling protects HCC cells against ionizing radiation in an autocrine manner. Impairment of DNA damage repair might involve mechanism of

  6. Tumor necrosis factor α functions in an autocrine manner in the induction of human immunodeficiency virus expression

    International Nuclear Information System (INIS)

    Tumor necrosis factor α (TNF-α) is an immunoregulatory cytokine capable of inducing viral expression in cells chronically infected with the human immunodeficiency virus (HIV), such as the promonocytic line U1 and the T-lymphocytic line ACH-2. In the present study, the authors demonstrate an autocrine mechanism of TNF-α-mediated HIV induction. Stimulation of U1 and ACH-2 cells with phorbol 12-myristate 13-acetate (PMA) resulted in the induction of TNF-α mRNA and the secretion of TNF-α. Of note is the fact that anti-TNF-α antibodies significantly suppressed the expression of HIV in PMA-stimulated U1 and ACH-2 cells. Furthermore, anti-TNF-α antibodies also suppressed both the constitutive and inducible levels of viral expression in the chronically infected promonocytic clone U33.3. This study illustrates the interrelationship between the regulation of HIV expression and normal immunoregulatory mechanisms in that virus expression, both constitutive and induced, can be modulated by an autocrine pathway involving TNF-α, a cytokine involved in the complex network of regulation of the normal human immune response

  7. Autocrine and paracrine Shh signaling are necessary for tooth morphogenesis, but not tooth replacement in snakes and lizards (Squamata).

    Science.gov (United States)

    Handrigan, Gregory R; Richman, Joy M

    2010-01-01

    Here we study the role of Shh signaling in tooth morphogenesis and successional tooth initiation in snakes and lizards (Squamata). By characterizing the expression of Shh pathway receptor Ptc1 in the developing dentitions of three species (Eublepharis macularius, Python regius, and Pogona vitticeps) and by performing gain- and loss-of-function experiments, we demonstrate that Shh signaling is active in the squamate tooth bud and is required for its normal morphogenesis. Shh apparently mediates tooth morphogenesis by separate paracrine- and autocrine-mediated functions. According to this model, paracrine Shh signaling induces cell proliferation in the cervical loop, outer enamel epithelium, and dental papilla. Autocrine signaling within the stellate reticulum instead appears to regulate cell survival. By treating squamate dental explants with Hh antagonist cyclopamine, we induced tooth phenotypes that closely resemble the morphological and differentiation defects of vestigial, first-generation teeth in the bearded dragon P. vitticeps. Our finding that these vestigial teeth are deficient in epithelial Shh signaling further corroborates that Shh is needed for the normal development of teeth in snakes and lizards. Finally, in this study, we definitively refute a role for Shh signaling in successional dental lamina formation and conclude that other pathways regulate tooth replacement in squamates. PMID:19850027

  8. Autocrine/paracrine proliferative effect of ovarian GH and IGF-I in chicken granulosa cell cultures.

    Science.gov (United States)

    Ahumada-Solórzano, S Marisela; Martínez-Moreno, Carlos G; Carranza, Martha; Ávila-Mendoza, José; Luna-Acosta, José Luis; Harvey, Steve; Luna, Maricela; Arámburo, Carlos

    2016-08-01

    It is known that growth hormone (GH) and its receptor (GHR) are expressed in granulosa cells (GC) and thecal cells during the follicular development in the hen ovary, which suggests GH is involved in autocrine/paracrine actions in the female reproductive system. In this work, we show that the knockdown of local ovarian GH with a specific cGH siRNA in GC cultures significantly decreased both cGH mRNA expression and GH secretion to the media, and also reduced their proliferative rate. Thus, we analyzed the effect of ovarian GH and recombinant chicken GH (rcGH) on the proliferation of pre-hierarchical GCs in primary cultures. Incubation of GCs with either rcGH or conditioned media, containing predominantly a 15-kDa GH isoform, showed that both significantly increased proliferation as determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, proliferating cell nuclear antigen (PCNA) quantification and ((3)H)-thymidine incorporation ((3)H-T) assays in a dose response fashion. Both, locally produced GH and rcGH also induced the phosphorylation of Erk1/2 in GC cultures. Furthermore, GH increased IGF-I synthesis and its release into the GC culture incubation media. These results suggest that GH may act through local IGF-I to induce GC proliferation, since IGF-I immunoneutralization completely abolished the GH-induced proliferative effect. These data suggest that GH and IGF-I may play a role as autocrine/paracrine regulators during the follicular development in the hen ovary at the pre-hierarchical stage. PMID:27174747

  9. The growth and aggressive behavior of human osteosarcoma is regulated by a CaMKII-controlled autocrine VEGF signaling mechanism.

    Directory of Open Access Journals (Sweden)

    Paul G Daft

    Full Text Available Osteosarcoma (OS is a hyperproliferative malignant tumor that requires a high vascular density to maintain its large volume. Vascular Endothelial Growth Factor (VEGF plays a crucial role in angiogenesis and acts as a paracrine and autocrine agent affecting both endothelial and tumor cells. The alpha-Ca2+/Calmodulin kinase two (α-CaMKII protein is an important regulator of OS growth. Here, we investigate the role of α-CaMKII-induced VEGF in the growth and tumorigenicity of OS. We show that the pharmacologic and genetic inhibition of α-CaMKII results in decreases in VEGF gene expression (50% and protein secretion (55%, while α- CaMKII overexpression increases VEGF gene expression (250% and protein secretion (1,200%. We show that aggressive OS cells (143B express high levels of VEGF receptor 2 (VEGFR-2 and respond to exogenous VEGF (100nm by increasing intracellular calcium (30%. This response is ameliorated by the VEGFR inhibitor CBO-P11, suggesting that secreted VEGF results in autocrine stimulated α-CaMKII activation. Furthermore, we show that VEGF and α-CaMKII inhibition decreases the transactivation of the HIF-1α and AP-1 reporter constructs. Additionally, chromatin immunoprecipitation assay shows significantly decreased binding of HIF-1α and AP-1 to their responsive elements in the VEGF promoter. These data suggest that α-CaMKII regulates VEGF transcription by controlling HIF-1α and AP-1 transcriptional activities. Finally, CBO-P11, KN-93 (CaMKII inhibitor and combination therapy significantly reduced tumor burden in vivo. Our results suggest that VEGF-induced OS tumor growth is controlled by CaMKII and dual therapy by CaMKII and VEGF inhibitors could be a promising therapy against this devastating adolescent disease.

  10. Luminal and basal-like breast cancer cells show increased migration induced by hypoxia, mediated by an autocrine mechanism

    International Nuclear Information System (INIS)

    Some breast cancer patients receiving anti-angiogenic treatment show increased metastases, possibly as a result of induced hypoxia. The effect of hypoxia on tumor cell migration was assessed in selected luminal, post-EMT and basal-like breast carcinoma cell lines. Migration was assessed in luminal (MCF-7), post-EMT (MDA-MB-231, MDA-MB-435S), and basal-like (MDA-MB-468) human breast carcinoma cell lines under normal and oxygen-deprived conditions, using a collagen-based assay. Cell proliferation was determined, secreted cytokine and chemokine levels were measured using flow-cytometry and a bead-based immunoassay, and the hypoxic genes HIF-1α and CA IX were assessed using PCR. The functional effect of tumor-cell conditioned medium on the migration of neutrophil granulocytes (NG) was tested. Hypoxia caused increased migratory activity but not proliferation in all tumor cell lines, involving the release and autocrine action of soluble mediators. Conditioned medium (CM) from hypoxic cells induced migration in normoxic cells. Hypoxia changed the profile of released inflammatory mediators according to cell type. Interleukin-8 was produced only by post-EMT and basal-like cell lines, regardless of hypoxia. MCP-1 was produced by MDA-MB-435 and -468 cells, whereas IL-6 was present only in MDA-MB-231. IL-2, TNF-α, and NGF production was stimulated by hypoxia in MCF-7 cells. CM from normoxic and hypoxic MDA-MB-231 and MDA-MB-435S cells and hypoxic MCF-7 cells, but not MDA-MB-468, induced NG migration. Hypoxia increases migration by the autocrine action of released signal substances in selected luminal and basal-like breast carcinoma cell lines which might explain why anti-angiogenic treatment can worsen clinical outcome in some patients

  11. Autocrine stimulation of osteoblast activity by Wnt5a in response to TNF-α in human mesenchymal stem cells

    International Nuclear Information System (INIS)

    Highlights: ► Ankylosing spondylitis (AS) leads to bone fusions and ankylosis. ► TNF-α stimulates osteoblasts through growth factors in AS. ► We compare the involvement of canonical vs non-canonical Wnt signaling. ► Canonical Wnt signaling is not involved in TNF-α effects in differentiating hMSCs. ► TNF-α stimulates osteoblasts through Wnt5a autocrine secretion in hMSCs. -- Abstract: Although anti-tumor necrosis factor (TNF)-α treatments efficiently block inflammation in ankylosing spondylitis (AS), they are inefficient to prevent excessive bone formation. In AS, ossification seems more prone to develop in sites where inflammation has resolved following anti-TNF therapy, suggesting that TNF-α indirectly stimulates ossification. In this context, our objectives were to determine and compare the involvement of Wnt proteins, which are potent growth factors of bone formation, in the effects of TNF-α on osteoblast function. In human mesenchymal stem cells (MSCs), TNF-α significantly increased the levels of Wnt10b and Wnt5a. Associated with this effect, TNF-α stimulated tissue-non specific alkaline phosphatase (TNAP) and mineralization. This effect was mimicked by activation of the canonical β-catenin pathway with either anti-Dkk1 antibodies, lithium chloride (LiCl) or SB216763. TNF-α reduced, and activation of β-catenin had little effect on expression of osteocalcin, a late marker of osteoblast differentiation. Surprisingly, TNF-α failed to stabilize β-catenin and Dkk1 did not inhibit TNF-α effects. In fact, Dkk1 expression was also enhanced in response to TNF-α, perhaps explaining why canonical signaling by Wnt10b was not activated by TNF-α. However, we found that Wnt5a also stimulated TNAP in MSCs cultured in osteogenic conditions, and increased the levels of inflammatory markers such as COX-2. Interestingly, treatment with anti-Wnt5a antibodies reduced endogenous TNAP expression and activity. Collectively, these data suggest that increased

  12. Oxyphenisatin acetate (NSC 59687) triggers a cell starvation response leading to autophagy, mitochondrial dysfunction, and autocrine TNFα-mediated apoptosis

    International Nuclear Information System (INIS)

    Oxyphenisatin (3,3-bis(4-hydroxyphenyl)-1H-indol-2-one) and several structurally related molecules have been shown to have in vitro and in vivo antiproliferative activity. This study aims to confirm and extend mechanistic studies by focusing on oxyphenisatin acetate (OXY, NSC 59687), the pro-drug of oxyphenisatin. Results confirm that OXY inhibits the growth of the breast cancer cell lines MCF7, T47D, HS578T, and MDA-MB-468. This effect is associated with selective inhibition of translation accompanied by rapid phosphorylation of the nutrient sensing eukaryotic translation initiation factor 2α (eIF2α) kinases, GCN2 and PERK. This effect was paralleled by activation of AMP-activated protein kinase (AMPK) combined with reduced phosphorylation of the mammalian target of rapamycin (mTOR) substrates p70S6K and 4E-BP1. Microarray analysis highlighted activation of pathways involved in apoptosis induction, autophagy, RNA/protein metabolism, starvation responses, and solute transport. Pathway inhibitor combination studies suggested a role for AMPK/mTOR signaling, de novo transcription and translation, reactive oxygen species (ROS)/glutathione metabolism, calcium homeostasis and plasma membrane Na+/K+/Ca2+ transport in activity. Further examination confirmed that OXY treatment was associated with autophagy, mitochondrial dysfunction, and ROS generation. Additionally, treatment was associated with activation of both intrinsic and extrinsic apoptotic pathways. In the estrogen receptor (ER) positive MCF7 and T47D cells, OXY induced TNFα expression and TNFR1 degradation, indicating autocrine receptor-mediated apoptosis in these lines. Lastly, in an MCF7 xenograft model, OXY delivered intraperitoneally inhibited tumor growth, accompanied by phosphorylation of eIF2α and degradation of TNFR1. These data suggest that OXY induces a multifaceted cell starvation response, which ultimately induces programmed cell death. The mechanistic basis for oxyphenisatin acetate anti

  13. Autocrine stimulation of osteoblast activity by Wnt5a in response to TNF-α in human mesenchymal stem cells

    Energy Technology Data Exchange (ETDEWEB)

    Briolay, A. [ICBMS, UMR CNRS 5246, University of Lyon 1, Bâtiment Raulin, 43 Bd du 11 novembre 1918, 69622 Villeurbanne Cedex (France); Lencel, P. [Physiopathology of Inflammatory Bone Diseases, EA4490, ULCO. Quai Masset, Bassin Napoléon BP120, 62327 Boulogne/Mer (France); Bessueille, L. [ICBMS, UMR CNRS 5246, University of Lyon 1, Bâtiment Raulin, 43 Bd du 11 novembre 1918, 69622 Villeurbanne Cedex (France); Caverzasio, J. [Service of Bone Diseases, Department of Internal Medicine Specialties, University Hospital of Geneva, CH-1211 Geneva 14 (Switzerland); Buchet, R. [ICBMS, UMR CNRS 5246, University of Lyon 1, Bâtiment Raulin, 43 Bd du 11 novembre 1918, 69622 Villeurbanne Cedex (France); Magne, D., E-mail: david.magne@univ-lyon1.fr [ICBMS, UMR CNRS 5246, University of Lyon 1, Bâtiment Raulin, 43 Bd du 11 novembre 1918, 69622 Villeurbanne Cedex (France)

    2013-01-18

    Highlights: ► Ankylosing spondylitis (AS) leads to bone fusions and ankylosis. ► TNF-α stimulates osteoblasts through growth factors in AS. ► We compare the involvement of canonical vs non-canonical Wnt signaling. ► Canonical Wnt signaling is not involved in TNF-α effects in differentiating hMSCs. ► TNF-α stimulates osteoblasts through Wnt5a autocrine secretion in hMSCs. -- Abstract: Although anti-tumor necrosis factor (TNF)-α treatments efficiently block inflammation in ankylosing spondylitis (AS), they are inefficient to prevent excessive bone formation. In AS, ossification seems more prone to develop in sites where inflammation has resolved following anti-TNF therapy, suggesting that TNF-α indirectly stimulates ossification. In this context, our objectives were to determine and compare the involvement of Wnt proteins, which are potent growth factors of bone formation, in the effects of TNF-α on osteoblast function. In human mesenchymal stem cells (MSCs), TNF-α significantly increased the levels of Wnt10b and Wnt5a. Associated with this effect, TNF-α stimulated tissue-non specific alkaline phosphatase (TNAP) and mineralization. This effect was mimicked by activation of the canonical β-catenin pathway with either anti-Dkk1 antibodies, lithium chloride (LiCl) or SB216763. TNF-α reduced, and activation of β-catenin had little effect on expression of osteocalcin, a late marker of osteoblast differentiation. Surprisingly, TNF-α failed to stabilize β-catenin and Dkk1 did not inhibit TNF-α effects. In fact, Dkk1 expression was also enhanced in response to TNF-α, perhaps explaining why canonical signaling by Wnt10b was not activated by TNF-α. However, we found that Wnt5a also stimulated TNAP in MSCs cultured in osteogenic conditions, and increased the levels of inflammatory markers such as COX-2. Interestingly, treatment with anti-Wnt5a antibodies reduced endogenous TNAP expression and activity. Collectively, these data suggest that increased

  14. Knockdown of lncRNA-ATB suppresses autocrine secretion of TGF-β2 by targeting ZNF217 via miR-200c in keloid fibroblasts.

    Science.gov (United States)

    Zhu, Hua-Yu; Bai, Wen-Dong; Li, Chao; Zheng, Zhao; Guan, Hao; Liu, Jia-Qi; Yang, Xue-Kang; Han, Shi-Chao; Gao, Jian-Xin; Wang, Hong-Tao; Hu, Da-Hai

    2016-01-01

    Abnormally high activation of transforming growth factor-β (TGF-β) signaling has been demonstrated to be involved in the initiation and progression of keloids. However, the functional role of long non-coding RNA (lncRNA)-activated by TGF-β (lncRNA-ATB) in keloids has not been documented. Here we investigated the role of lncRNA-ATB in the autocrine secretion of TGF-β in keloid fibroblasts (KFs) and explored the underlying molecular mechanism. Using immunohistochemistry and quantitative RT-PCR analysis, we showed that lncRNA-ATB and ZNF217, a transcriptional activator of TGF-β, were overexpressed and miR-200c, which targets ZNF217, was under-expressed in keloid tissue and keloid fibroblasts. Through gain- and loss-of-function studies, we demonstrated that knockdown of lncRNA-ATB decreased autocrine secretion of TGF-β2 and ZNF217 expression but upregulated expression of miR-200c in KFs. Stable downregulation of ZNF217 expression decreased the autocrine secretion of TGF-β2. miR-200c was endogenously associated with lncRNA-ATB, and inhibition of miR-200c overcame the decrease in ZNF217 expression in KFs. Taken together, these findings indicate that lncRNA-ATB governs the autocrine secretion of TGF-β2 in KFs, at least in part, by downregulating the expression level of ZNF217 via miR-200c, suggesting a signaling axis consisting of lncRNA-ATB/miR-200c/ZNF217/TGF-β2. These findings may provide potential biomarkers and targets for novel diagnostic and therapeutic approaches for keloids. PMID:27090737

  15. Autocrine IL-8 promotes F-actin polymerization and mediate mesenchymal transition via ELMO1-NF-κB-Snail signaling in glioma.

    Science.gov (United States)

    Zhang, Baogang; Shi, Lihong; Lu, Shijun; Sun, Xiuning; Liu, Yuqing; Li, Hongli; Wang, Xuejian; Zhao, Chunzhen; Zhang, Heng; Wang, Ying

    2015-01-01

    Glioma is the most common form of primary malignant brain cancers. Tumor cell invasiveness is a critical challenge in the clinical management of glioma patients. The invasive biological feature of glioma cell is stimulated by both autocrine and paracrine factors including chemokine IL-8. In this study, we report that the production of IL-8 is higher in glioma tissues and cells than adjacent nontumor tissues (ANT) and normal glial cells. Autocrine IL-8 can increase the invasive ability of glioma cells by binding to CXCR1. In addition, high expression of IL-8 indicates poor prognosis of glioma patients. Furthermore, IL-8 is capable of modulating cell migration and invasion by regulating the activation of RAC1 which resulted in cytoskeletal reorganisation in an ELMO1 dependent manner. Finally, we found that IL-8 could enhance mesenchymal transition(MT) of glioma cells by activating ELMO1-NF-κB-Snail signaling. Our data indicate that IL-8 autocrine is responsible for the invasive phenotype of glioma and IL-8 may be a useful prognostic marker for glioma and novel therapeutic target for glioma invasion intervention. PMID:25870011

  16. Macrophage Migration Inhibitor Factor Upregulates MCP-1 Expression in an Autocrine Manner in Hepatocytes during Acute Mouse Liver Injury

    Science.gov (United States)

    Xie, Jieshi; Yang, Le; Tian, Lei; Li, Weiyang; Yang, Lin; Li, Liying

    2016-01-01

    Macrophage migration inhibitor factor (MIF), a multipotent innate immune mediator, is an upstream component of the inflammatory cascade in diseases such as liver disease. Monocyte chemoattractant protein-1 (MCP-1), a highly representative chemokine, is critical in liver disease pathogenesis. We investigated the role of MIF in regulating hepatocytic MCP-1 expression. MIF and MCP-1 expression were characterized by immunochemistry, RT-PCR, ELISA, and immunoblotting in CCl4-treated mouse liver and isolated hepatocytes. MIF was primarily distributed in hepatocytes, and its expression increased upon acute liver injury. Its expression was also increased in injured hepatocytes, induced by LPS or CCl4, which mimic liver injury in vitro. MIF was expressed earlier than MCP-1, strongly inducing hepatocytic MCP-1 expression. Moreover, the increase in MCP-1 expression induced by MIF was inhibited by CD74- or CD44-specific siRNAs and SB203580, a p38 MAPK inhibitor. Further, CD74 or CD44 deficiency effectively inhibited MIF-induced p38 activation. MIF inhibitor ISO-1 reduced MCP-1 expression and p38 phosphorylation in CCl4-treated mouse liver. Our results showed that MIF regulates MCP-1 expression in hepatocytes of injured liver via CD74, CD44, and p38 MAPK in an autocrine manner, providing compelling information on the role of MIF in liver injury, and implying a new regulatory mechanism for liver inflammation. PMID:27273604

  17. Autocrine function of aldehyde dehydrogenase 1 as a determinant of diet- and sex-specific differences in visceral adiposity.

    Science.gov (United States)

    Yasmeen, Rumana; Reichert, Barbara; Deiuliis, Jeffrey; Yang, Fangping; Lynch, Alisha; Meyers, Joseph; Sharlach, Molly; Shin, Sangsu; Volz, Katharina S; Green, Kari B; Lee, Kichoon; Alder, Hansjuerg; Duester, Gregg; Zechner, Rudolf; Rajagopalan, Sanjay; Ziouzenkova, Ouliana

    2013-01-01

    Mechanisms for sex- and depot-specific fat formation are unclear. We investigated the role of retinoic acid (RA) production by aldehyde dehydrogenase 1 (Aldh1a1, -a2, and -a3), the major RA-producing enzymes, on sex-specific fat depot formation. Female Aldh1a1(-/-) mice, but not males, were resistant to high-fat (HF) diet-induced visceral adipose formation, whereas subcutaneous fat was reduced similarly in both groups. Sexual dimorphism in visceral fat (VF) was attributable to elevated adipose triglyceride lipase (Atgl) protein expression localized in clusters of multilocular uncoupling protein 1 (Ucp1)-positive cells in female Aldh1a1(-/-) mice compared with males. Estrogen decreased Aldh1a3 expression, limiting conversion of retinaldehyde (Rald) to RA. Rald effectively induced Atgl levels via nongenomic mechanisms, demonstrating indirect regulation by estrogen. Experiments in transgenic mice expressing an RA receptor response element (RARE-lacZ) revealed HF diet-induced RARE activation in VF of females but not males. In humans, stromal cells isolated from VF of obese subjects also expressed higher levels of Aldh1 enzymes compared with lean subjects. Our data suggest that an HF diet mediates VF formation through a sex-specific autocrine Aldh1 switch, in which Rald-mediated lipolysis in Ucp1-positive visceral adipocytes is replaced by RA-mediated lipid accumulation. Our data suggest that Aldh1 is a potential target for sex-specific antiobesity therapy. PMID:22933113

  18. Expression of transforming growth factor alpha in plutonium-239-induced lung neoplasms in dogs: investigations of autocrine mechanisms of growth

    International Nuclear Information System (INIS)

    We have previously shown that 47% of radiation-induced lung neoplasms in dogs exhibit increased expression of epidermal growth factor receptor (EGFR). In this study, we investigated the expression of transforming growth factor alpha (TGF-alpha), a ligand for EGFR, to determine if an autocrine mechanism for growth stimulation was present in these tumors. As determined by immunohistochemistry, 59% (26/44) of the lung neoplasms examined had increased expression of TGF-alpha. Expression of TGF-alpha was not related to the etiology of the tumor, e.g., spontaneous or plutonium-induced; however, it was related to the phenotype of the tumor. Statistical analysis of the correlation of EGFR and TGF-alpha expression within the same tumor did not show a positive association; however, specific phenotypes did have statistically significant expression of EGFR or TGF-alpha, suggesting that overexpression of either the ligand or its receptor conferred a growth advantage to the neoplasm. Twenty-seven percent (32/117) of radiation-induced proliferative epithelial foci expressed TGF-alpha, and a portion of those foci (8/32) expressed both EGFR and TGF-alpha. This supports the hypothesis that these foci represent preneoplastic lesions, and suggests that those foci exhibiting increased expression of the growth factor or its receptor are at greater risk for progressing to neoplasia

  19. Ovarian cancer stem-like cells differentiate into endothelial cells and participate in tumor angiogenesis through autocrine CCL5 signaling.

    Science.gov (United States)

    Tang, Shu; Xiang, Tong; Huang, Shuo; Zhou, Jie; Wang, Zhongyu; Xie, Rongkai; Long, Haixia; Zhu, Bo

    2016-06-28

    Cancer stem cells (CSCs) are well known for their self-regeneration and tumorigenesis potential. In addition, the multi-differentiation potential of CSCs has become a popular issue and continues to attract increased research attention. Recent studies demonstrated that CSCs are able to differentiate into functional endothelial cells and participate in tumor angiogenesis. In this study, we found that ovarian cancer stem-like cells (CSLCs) activate the NF-κB and STAT3 signal pathways through autocrine CCL5 signaling and mediate their own differentiation into endothelial cells (ECs). Our data demonstrate that CSLCs differentiate into ECs morphologically and functionally. Anti-CCL5 antibodies and CCL5-shRNA lead to markedly inhibit EC differentiation and the tube formation of CSLCs, both in vitro and in vivo. Recombinant human-CCL5 significantly promotes ovarian CSLCs that differentiate into ECs and form microtube network. The CCL5-mediated EC differentiation of CSLCs depends on binding to receptors, such as CCR1, CCR3, and CCR5. The results demonstrated that CCL5-CCR1/CCR3/CCR5 activates the NF-κB and STAT3 signal pathways, subsequently mediating the differentiation of CSLCs into ECs. Therefore, this study was conducted based on the theory that CSCs improve tumor angiogenesis and provides a novel strategy for anti-angiogenesis in ovarian cancer. PMID:27033454

  20. Interleukin 24 is induced by the RET/PTC3 oncoprotein and is an autocrine growth factor for epithelial cells.

    Science.gov (United States)

    Shinohara, Shogo; Rothstein, Jay L

    2004-09-30

    Thyroid cancers, like hematological malignancies, are commonly associated with chromosomal translocations leading to the formation of fusion proteins. Through altered signaling by fusion proteins, cell death and survival pathways are disrupted and the physiological balance of cell-cell communication may be lost. A consequence of this disruption is the release of factors by stressed cells that alert the host. One type of host response is leukocytic infiltration that may develop into chronic inflammation or autoimmune disease. Although inflammation can be associated with neoplastic tissue, the mechanism driving this process is largely unknown. Therefore, to address the mechanism of cancer inflammation we investigated the effects of an oncogene in a murine model system. A comprehensive genetic analysis revealed several soluble factors that were induced by RET/papillary thyroid carcinoma (PTC)3 gene expression including several proinflammatory cytokines, chemokines and immunologically relevant costimulatory molecules. Following a large genetic screen using RP3-expressing thyroid cells, we identified a highly abundant transcript and later identified it as interleukin 24 (Il24), a cytokine with diverse tumor suppressor and inflammatory activities. We show that RET/PTC3 induces Il24 expression in rat thyrocytes and that this expression is dependent on the signaling properties of its tyrosine kinase. Likewise, RET/PTC3 induces large amounts of Il24 following expression in murine thyrocytes, but its expression is dramatically reduced in poorly differentiated carcinomas, a finding that parallels the loss of RET/PTC3 expression. Consistent with its behavior as a tumor suppressor, the loss of Il24 coincided with the loss of RET/PTC3 in poorly differentiated mouse tumors. A functional role of Il24 in the autocrine growth/survival of RET/PTC3-expressing thyroid cells was identified helping to support its role in cellular transformation. These data suggest that the induction of

  1. Autocrine production of beta-chemokines protects CMV-Specific CD4 T cells from HIV infection.

    Directory of Open Access Journals (Sweden)

    Joseph P Casazza

    2009-10-01

    Full Text Available Induction of a functional subset of HIV-specific CD4+ T cells that is resistant to HIV infection could enhance immune protection and decrease the rate of HIV disease progression. CMV-specific CD4+ T cells, which are less frequently infected than HIV-specific CD4+ T cells, are a model for such an effect. To determine the mechanism of this protection, we compared the functional response of HIV gag-specific and CMV pp65-specific CD4+ T cells in individuals co-infected with CMV and HIV. We found that CMV-specific CD4+ T cells rapidly up-regulated production of MIP-1alpha and MIP-1beta mRNA, resulting in a rapid increase in production of MIP-1alpha and MIP-1beta after cognate antigen stimulation. Production of beta-chemokines was associated with maturational phenotype and was rarely seen in HIV-specific CD4+ T cells. To test whether production of beta-chemokines by CD4+ T cells lowers their susceptibility to HIV infection, we measured cell-associated Gag DNA to assess the in vivo infection history of CMV-specific CD4+ T cells. We found that CMV-specific CD4+ T cells which produced MIP-1beta contained 10 times less Gag DNA than did those which failed to produce MIP-1beta. These data suggest that CD4+ T cells which produce MIP-1alpha and MIP-1beta bind these chemokines in an autocrine fashion which decreases the risk of in vivo HIV infection.

  2. TNF-α affects human cortical neural progenitor cell differentiation through the autocrine secretion of leukemia inhibitory factor.

    Directory of Open Access Journals (Sweden)

    Xiqian Lan

    Full Text Available Proinflammatory cytokine tumor necrosis factor-alpha (TNF-α is a crucial effector of immune responses in the brain that participates in the pathogenesis of several acute and chronic neurodegenerative disorders. Accumulating evidence has suggested that TNF-α negatively regulates embryonic and adult neurogenesis. However, the effect of TNF-α on cell fate decision in human neural progenitor cells (NPCs has rarely been studied. Our previous studies have shown that recombinant TNF-α enhances astrogliogenesis and inhibits neurogenesis of human NPCs through the STAT3 (signal transducer and activator of transcription 3 pathway. In the current study, we further elucidated the specific mechanism involved in TNF-α-induced astrogliogenesis. We found that TNF-α activated STAT3 at delayed time points (6 h and 24 h, whereas conditioned medium collected from TNF-α-treated NPCs induced an immediate STAT3 activation. These data suggest TNF-α plays an indirect role on STAT3 activation and the subsequent NPC differentiation. Further, we showed that TNF-α induced abundant amounts of the IL-6 family cytokines, including Leukemia inhibitory factor (LIF and Interleukin 6 (IL-6, in human NPCs. TNF-α-induced STAT3 phosphorylation and astrogliogenesis were abrogated by the addition of neutralizing antibody for LIF, but not for IL-6, revealing a critical role of autocrine secretion of LIF in TNF-α-induced STAT3 activation and astrogliogenesis. This study generates important data elucidating the role of TNF-α in neurogenesis and may provide insight into new therapeutic strategies for brain inflammation.

  3. Promotion of human early embryonic development and blastocyst outgrowth in vitro using autocrine/paracrine growth factors.

    Directory of Open Access Journals (Sweden)

    Kazuhiro Kawamura

    Full Text Available Studies using animal models demonstrated the importance of autocrine/paracrine factors secreted by preimplantation embryos and reproductive tracts for embryonic development and implantation. Although in vitro fertilization-embryo transfer (IVF-ET is an established procedure, there is no evidence that present culture conditions are optimal for human early embryonic development. In this study, key polypeptide ligands known to be important for early embryonic development in animal models were tested for their ability to improve human early embryo development and blastocyst outgrowth in vitro. We confirmed the expression of key ligand/receptor pairs in cleavage embryos derived from discarded human tri-pronuclear zygotes and in human endometrium. Combined treatment with key embryonic growth factors (brain-derived neurotrophic factor, colony-stimulating factor, epidermal growth factor, granulocyte macrophage colony-stimulating factor, insulin-like growth factor-1, glial cell-line derived neurotrophic factor, and artemin in serum-free media promoted >2.5-fold the development of tri-pronuclear zygotes to blastocysts. For normally fertilized embryos, day 3 surplus embryos cultured individually with the key growth factors showed >3-fold increases in the development of 6-8 cell stage embryos to blastocysts and >7-fold increase in the proportion of high quality blastocysts based on Gardner's criteria. Growth factor treatment also led to a 2-fold promotion of blastocyst outgrowth in vitro when day 7 surplus hatching blastocysts were used. When failed-to-be-fertilized oocytes were used to perform somatic cell nuclear transfer (SCNT using fibroblasts as donor karyoplasts, inclusion of growth factors increased the progression of reconstructed SCNT embryos to >4-cell stage embryos. Growth factor supplementation of serum-free cultures could promote optimal early embryonic development and implantation in IVF-ET and SCNT procedures. This approach is valuable for

  4. Voltage-independent autocrine modulation of L-type channels mediated by ATP, opioids and catecholamines in rat chromaffin cells.

    Science.gov (United States)

    Hernández-Guijo, J M; Carabelli, V; Gandía, L; García, A G; Carbone, E

    1999-10-01

    The inhibition of L-type channels induced by either bath application of ATP, opioids and catecholamines or by endogenously released neurotransmitters was investigated in rat chromaffin cells with whole-cell recordings (5 mM Ba2+). In both cases, the L-type current, isolated pharmacologically using omega-toxin peptides and potentiated by Bay K 8644, was inhibited by approximately 50% with nearly no changes to the activation-inactivation kinetics. Inhibition was voltage independent at a wide range of potentials (-20 to +50 mV) and insensitive to depolarizing prepulses (+100 mV, 50 ms). Onset and offset of the inhibition were fast (time constants: tau(on) approximately 0.9 s, tau(off) approximately 3.6 s), indicating a rapid mechanism of channel modulation. Whether induced exogenously or from the released granules content in conditions of stopped cell superfusion, the neurotransmitter action was reversible and largely prevented by either intracellular GDP-beta-S, cell treatment with pertussis toxin or simultaneous application of P2y,2x delta/mu-opioidergic and alpha/beta-adrenergic antagonists. This suggests the existence of converging modulatory pathways by which autoreceptors-activated G-proteins reduce the activity of L-type channels through fast interactions. The autocrine inhibition of L-type currents, which was absent in superfused isolated cells, was effective on cell clusters, suggesting that L-type channels may be potently inhibited by cell exocytosis under physiological conditions resembling the intact adrenal glands. PMID:10564365

  5. Vascular endothelial growth factor A, secreted in response to transforming growth factor-β1 under hypoxic conditions, induces autocrine effects on migration of prostate cancer cells

    Institute of Scientific and Technical Information of China (English)

    Eric Darrington; Miao Zhong; Bao-Han Vo; Shafiq A Khan

    2012-01-01

    Hypoxia and transforming growth factor-β1 (TGF-β1) increase vascular endothelial growth factor A (VEGFA) expression in a number of malignancies.This effect of hypoxia and TGF-β1 might be responsible for tumor progression and metastasis of advanced prostate cancer.In the present study,TGF-β1 was shown to induce VEGFA165 secretion from both normal cell lines (HPV7 and RWPE1) and prostate cancer cell lines (DU 145 and PC3).Conversely,hypoxia-stimulated VEGFA165 secretion was observed only in prostate cancer cell lines.Hypoxia induced TGF-β1 expression in PC3 prostate cancer cells,and the TGF-β type Ⅰ receptor (ALK5) kinase inhibitor partially blocked hypoxia-mediated VEGFA165 secretion.This effect of hypoxia provides a novel mechanism to increase VEGFA expression in prostate cancer cells.Although autocrine signaling of VEGFA has been implicated in prostate cancer progression and metastasis,the associated mechanism is poorly characterized.VEGFA activity is mediated via VEGF receptor (VEGFR) 1 (Fit-1 ) and 2 (Flk-1/KDR).Whereas VEGFR-1 mRNA was detected in normal prostate epithelial cells,VEGFR-2 mRNA and VEGFR protein were expressed only in PC3 cells.VEGFA165 treatment induced phosphorylation of extracellular signal-regulated kinase 1/2 (ERK1/2) in PC3 cells but not in HPV7 cells,suggesting that the autocrine function of VEGFA may be uniquely associated with prostate cancer.Activation of VEGFR-2 by VEGFA165 was shown to enhance migration of PC3 cells.A similar effect was also observed with endogenous VEGFA induced by TGF-β1 and hypoxia.These findings illustrate that an autocrine loop of VEGFA via VEGFR-2 is critical for the tumorigertic effects of TGF-β1 and hypoxia on metastatic prostate cancers.

  6. K-RAS(V12) Induces Autocrine Production of EGFR Ligands and Mediates Radioresistance Through EGFR-Dependent Akt Signaling and Activation of DNA-PKcs

    International Nuclear Information System (INIS)

    Purpose: It is known that postirradiation survival of tumor cells presenting mutated K-RAS is mediated through autocrine activation of epidermal growth factor receptor (EGFR). In this study the molecular mechanism of radioresistance of cells overexpressing mutated K-RAS(V12) was investigated. Methods and Materials: Head-and-neck cancer cells (FaDu) presenting wild-type K-RAS were transfected with empty vector or vector expressing mutated K-RAS(V12). The effect of K-RAS(V12) on autocrine production of EGFR ligands, activation of EGFR downstream pathways, DNA damage repair, and postirradiation survival was analyzed. Results: Conditioned medium collected from K-RAS(V12)–transfected cells enhanced activation of the phosphatidylinositol-3-kinase–Akt pathway and increased postirradiation survival of wild-type K-RAS parental cells when compared with controls. These effects were reversed by amphiregulin (AREG)–neutralizing antibody. In addition, secretion of the EGFR ligands AREG and transforming growth factor α was significantly increased upon overexpression of K-RAS(V12). Expression of mutated K-RAS(V12) resulted in an increase in radiation-induced DNA-dependent protein kinase catalytic subunit (DNA-PKcs) phosphorylation at S2056. This increase was accompanied by increased repair of DNA double-strand breaks. Abrogation of DNA-PKcs phosphorylation by serum depletion or AREG-neutralizing antibody underscored the role of autocrine production of EGFR ligands, namely, AREG, in regulating DNA-PKcs activation in K-RAS mutated cells. Conclusions: These data indicate that radioresistance of K-RAS mutated tumor cells is at least in part due to constitutive production of EGFR ligands, which mediate enhanced repair of DNA double-strand breaks through the EGFR–phosphatidylinositol-3-kinase–Akt cascade.

  7. Insulin-like growth factor-I is an autocrine regulator for the brain metastatic variant of a human non-small cell lung cell line.

    Science.gov (United States)

    Hwang, C C; Fang, K; Li, L; Shih, S H

    1995-08-01

    Insulin-like growth factor (IGF-I) is associated with autocrine and paracrine stimulation for cell growth and development of brain tumor cells. The function of IGF-I in the brain metastatic variant of human lung cancer cells is investigated. The cells used here were derived in vivo with intracarotid injection of human non-small cell lung carcinoma NCI-H226. The tumor was developed as a cultured cell line, H226Br. Unlike the parental cells, H226Br was tumorigenic in nu/nu nude mice. Reverse transcriptase-polymerase chain reaction showed that IGF-I transcript of H226Br is increased compared to that of parental cells. The amount of IGF-I secreted in cultured medium of H226Br is higher than that of cultured parental cells. The IGF-I receptor-specific antibody, alpha IR3, inhibits H226Br growth in serum-free culture. The results established that IGF-I is an autocrine growth regulator for human non-small cell lung cancer cells that progressed to brain. PMID:7634243

  8. Prolonged propagation of rat neural stem cells relies on inhibiting autocrine/paracrine bone morphogenetic protein and platelet derived growth factor signals

    Institute of Scientific and Technical Information of China (English)

    Yirui Sun; Liangfu Zhou; Xing Wu; Hua Liu; Qiang Yuan; Ying Mao; Jin Hu

    2011-01-01

    Continuous expansion of rat neural stem cell lines has not been achieved due to proliferation arrest and spontaneous differentiation in vitro. In the current study, neural precursor cells derived from the subventricular zone of adult rats spontaneously underwent astroglial and oligodendroglial differentiation after limited propagation. This differentiation was largely induced by autocrine or paracrine bone morphogenetic protein and platelet derived growth factor signals. The results showed that, by inhibiting bone morphogenetic protein and platelet derived growth factor signals, adult rat neural precursor cells could be extensively cultured in vitro as tripotent stem cell lines. In addition to adult rat neural stem cells, we found that bone morphogenetic protein antagonists can promote the proliferation of human neural stem cells. Therefore, the present findings illustrated the role of autocrine or paracrine bone morphogenetic protein and platelet derived growth factor signaling in determining neural stem cell self-renewal and differentiation. By antagonizing both signals, the long-term propagation of rat neural stem cell lines can be achieved.

  9. Role of pigment epithelium-derived factor in the involution of hemangioma: Autocrine growth inhibition of hemangioma-derived endothelial cells

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kyung-Jin [Department of Pharmacology, College of Medicine, Seoul National University, Seoul 110-799 (Korea, Republic of); Department of Biomedical Science, College of Medicine, Seoul National University, Seoul 110-799 (Korea, Republic of); Yun, Jang-Hyuk; Heo, Jong-Ik [Department of Pharmacology, College of Medicine, Seoul National University, Seoul 110-799 (Korea, Republic of); Lee, Eun Hui [Department of Physiology, College of Medicine, The Catholic University of Korea, Seoul 137-701 (Korea, Republic of); Min, Hye Sook [Department of Pathology, Seoul National University Hospital, Seoul 110-744 (Korea, Republic of); Choi, Tae Hyun, E-mail: psthchoi@snu.ac.kr [Department of Plastic and Reconstructive Surgery, Seoul National University Children’s Hospital, Seoul 110-744 (Korea, Republic of); Department of Pediatric Plastic and Reconstructive Surgery, Seoul National University Children’s Hospital, Seoul 110-744 (Korea, Republic of); Cho, Chung-Hyun, E-mail: iamhyun@snu.ac.kr [Department of Pharmacology, College of Medicine, Seoul National University, Seoul 110-799 (Korea, Republic of); Department of Biomedical Science, College of Medicine, Seoul National University, Seoul 110-799 (Korea, Republic of); Ischemic/Hypoxic Disease Institute, College of Medicine, Seoul National University, Seoul 110-799 (Korea, Republic of); Cancer Research Institute, College of Medicine, Seoul National University, Seoul 110-799 (Korea, Republic of)

    2014-11-14

    Highlights: • PEDF was expressed and induced during the involuting phase of IH. • PEDF inhibited the cell growth of the involuting HemECs in an autocrine manner. • PEDF suppression restored the impaired cell growth of the involuting HemECs. - Abstract: Hemangioma is a benign tumor derived from abnormal blood vessel growth. Unlike other vascular tumor counterparts, a hemangioma is known to proliferate during its early stage but it is followed by a stage of involution where regression of the tumor occurs. The critical onset leading to the involution of hemangioma is currently not well understood. This study focused on the molecular identities of the involution of hemangioma. We demonstrated that a soluble factor released from the involuting phase of hemangioma-derived endothelial cells (HemECs) and identified pigment epithelium-derived factor (PEDF) as an anti-angiogenic factor that was associated with the growth inhibition of the involuting HemECs. The growth inhibition of the involuting HemECs was reversed by suppression of PEDF in the involuting HemECs. Furthermore, we found that PEDF was more up-regulated in the involuting phase of hemangioma tissues than in the proliferating or the involuted. Taken together, we propose that PEDF accelerates the involution of hemangioma by growth inhibition of HemECs in an autocrine manner. The regulatory mechanism of PEDF expression could be a potential therapeutic target to treat hemangiomas.

  10. Role of pigment epithelium-derived factor in the involution of hemangioma: Autocrine growth inhibition of hemangioma-derived endothelial cells

    International Nuclear Information System (INIS)

    Highlights: • PEDF was expressed and induced during the involuting phase of IH. • PEDF inhibited the cell growth of the involuting HemECs in an autocrine manner. • PEDF suppression restored the impaired cell growth of the involuting HemECs. - Abstract: Hemangioma is a benign tumor derived from abnormal blood vessel growth. Unlike other vascular tumor counterparts, a hemangioma is known to proliferate during its early stage but it is followed by a stage of involution where regression of the tumor occurs. The critical onset leading to the involution of hemangioma is currently not well understood. This study focused on the molecular identities of the involution of hemangioma. We demonstrated that a soluble factor released from the involuting phase of hemangioma-derived endothelial cells (HemECs) and identified pigment epithelium-derived factor (PEDF) as an anti-angiogenic factor that was associated with the growth inhibition of the involuting HemECs. The growth inhibition of the involuting HemECs was reversed by suppression of PEDF in the involuting HemECs. Furthermore, we found that PEDF was more up-regulated in the involuting phase of hemangioma tissues than in the proliferating or the involuted. Taken together, we propose that PEDF accelerates the involution of hemangioma by growth inhibition of HemECs in an autocrine manner. The regulatory mechanism of PEDF expression could be a potential therapeutic target to treat hemangiomas

  11. Progress on Autocrine Effects of Growth Hormone%生长激素自分泌作用机制研究进展

    Institute of Scientific and Technical Information of China (English)

    齐传翔; 杨开典; 祁钰钰; 鞠辉明

    2016-01-01

    生长激素(growth hormone,GH)是由脑垂体前叶分泌的一种多肽激素,它作为一种特殊的生物活性蛋白促进机体合成代谢和蛋白质合成。GH 传统的作用机制是垂体产生 GH 开始作用于膜受体,然后刺激肝脏胰岛素生长因子(insulin-like growth factor-1,IGF-1)生成,进而影响机体多个器官发育。近年的研究表明,GH 除了内分泌作用途径,还可通过自分泌及旁分泌途径产生生物学效应。GH 自分泌可以参与调控雄性和雌性动物生殖功能;GH 自分泌对肌肉组织的代谢和生长也有重要影响,另外,GH 自分泌与肿瘤的发生有密切的关系,其在一定程度上可以促进部分癌细胞的增殖,分化与迁移。通过对 GH 自分泌作用机制的研究有望发现自分泌 GH 在动物体内新的生物学作用,也有助于研究并治疗 GH 自分泌异常引发的相关疾病。%Growth hormone (GH)is a kind of polypeptide hormones secreted by anterior pituitary.As a special bioactive protein,GH can help anabolism and protein synthesis of animals.The classical function of GH is endocrine effect,the GH produced by the pituitary acts on the membrane receptor,stimulates the production of insulin-like growth factor-1(IGF-1)from liver,then it can affect the development of many organs.More and more researches in recent years showed that GH exerts its biological effect not only by endocrine effects but also by autocrine and paracrine effects.In this study,we reviewed the autocrine effects of GH on the reproduction and fertility regulation of animals and the muscle development.In addi-tion,autocrine effect of GH has a close relationship with tumor.It can promote migration,proliferation and differentiation of the cancer cells.The study on the autocrine effects of GH can help to study its new biological effect in organisms,also help to study and control some diseases caused by abnormal autocrine effects.

  12. Regulation of Prostate Development and Benign Prostatic Hyperplasia by Autocrine Cholinergic Signaling via Maintaining the Epithelial Progenitor Cells in Proliferating Status

    Directory of Open Access Journals (Sweden)

    Naitao Wang

    2016-05-01

    Full Text Available Regulation of prostate epithelial progenitor cells is important in prostate development and prostate diseases. Our previous study demonstrated a function of autocrine cholinergic signaling (ACS in promoting prostate cancer growth and castration resistance. However, whether or not such ACS also plays a role in prostate development is unknown. Here, we report that ACS promoted the proliferation and inhibited the differentiation of prostate epithelial progenitor cells in organotypic cultures. These results were confirmed by ex vivo lineage tracing assays and in vivo renal capsule recombination assays. Moreover, we found that M3 cholinergic receptor (CHRM3 was upregulated in a large subset of benign prostatic hyperplasia (BPH tissues compared with normal tissues. Activation of CHRM3 also promoted the proliferation of BPH cells. Together, our findings identify a role of ACS in maintaining prostate epithelial progenitor cells in the proliferating state, and blockade of ACS may have clinical implications for the management of BPH.

  13. Autocrine fibronectin from differentiating mesenchymal stem cells induces the neurite elongation in vitro and promotes nerve fiber regeneration in transected spinal cord injury.

    Science.gov (United States)

    Zeng, Xiang; Ma, Yuan-Huan; Chen, Yuan-Feng; Qiu, Xue-Cheng; Wu, Jin-Lang; Ling, Eng-Ang; Zeng, Yuan-Shan

    2016-08-01

    Extracellular matrix (ECM) expression is temporally and spatially regulated during the development of stem cells. We reported previously that fibronectin (FN) secreted by bone marrow mesenchymal stem cells (MSCs) was deposited on the surface of gelatin sponge (GS) soon after culture. In this study, we aimed to assess the function of accumulated FN on neuronal differentiating MSCs as induced by Schwann cells (SCs) in three dimensional transwell co-culture system. The expression pattern and amount of FN of differentiating MSCs was examined by immunofluorescence, Western blot and immunoelectron microscopy. The results showed that FN accumulated inside GS scaffold, although its mRNA expression in MSCs was progressively decreased during neural induction. MSC-derived neuron-like cells showed spindle-shaped cell body and long extending processes on FN-decorated scaffold surface. However, after blocking of FN function by application of monoclonal antibodies, neuron-like cells showed flattened cell body with short and thick neurites, together with decreased expression of integrin β1. In vivo transplantation study revealed that autocrine FN significantly facilitated endogenous nerve fiber regeneration in spinal cord transection model. Taken together, the present results showed that FN secreted by MSCs in the early stage accumulated on the GS scaffold and promoted the neurite elongation of neuronal differentiating MSCs as well as nerve fiber regeneration after spinal cord injury. This suggests that autocrine FN has a dynamic influence on MSCs in a three dimensional culture system and its potential application for treatment of traumatic spinal cord injury. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 1902-1911, 2016. PMID:26991461

  14. Elevated hepatocyte growth factor expression as an autocrine c-Met activation mechanism in acquired resistance to sorafenib in hepatocellular carcinoma cells.

    Science.gov (United States)

    Firtina Karagonlar, Zeynep; Koc, Dogukan; Iscan, Evin; Erdal, Esra; Atabey, Neşe

    2016-04-01

    Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the third leading cause of cancer-related deaths worldwide. Limitations in HCC treatment result due to poor prognosis and resistance against traditional radiotherapy and chemotherapies. The multikinase inhibitor sorafenib is the only FDA approved drug available for advanced HCC patients, and development of second-line treatment options for patients who cannot tolerate or develop resistance to sorafenib is an urgent medical need. In this study, we established sorafenib-resistant cells from Huh7 and Mahlavu cell lines by long-term sorafenib exposure. Sorafenib-resistant HCC cells acquired spindle-shape morphology, upregulated mesenchymal markers, and showed significant increase in both migration and invasion abilities compared to their parental counterparts. Moreover, after long-term sorafenib treatment, HCC cells showed induction of hepatocyte growth factor (HGF) synthesis and secretion along with increased levels of c-Met kinase and its active phosphorylated form, indicating autocrine activation of HGF/c-Met signaling. Importantly, the combined treatment of the resistant cells with c-Met kinase inhibitor SU11274 and HGF neutralizing antibody significantly reversed the increased invasion ability of the cells. The combined treatment also significantly augmented sorafenib-induced apoptosis, suggesting restoration of sorafenib sensitivity. These results describe, for the first time, compensatory upregulation of HGF synthesis leading to autocrine activation of HGF/c-Met signaling as a novel cellular strategy in the acquisition of sorafenib resistance. Therefore, we suggest that combinatorial therapeutic strategies with HGF and c-Met inhibitors comprise promising candidates for overcoming sorafenib resistance. PMID:26790028

  15. Collagen and Stretch Modulate Autocrine Secretion of Insulin-like Growth Factor-1 and Insulin-like Growth Factor Binding Proteins from Differentiated Skeletal Muscle Cells

    Science.gov (United States)

    Perrone, Carmen E.; Fenwick-Smith, Daniela; Vandenburgh, Herman H.

    1995-01-01

    Stretch-induced skeletal muscle growth may involve increased autocrine secretion of insulin-like growth factor-1 (IGF-1) since IGF-1 is a potent growth factor for skeletal muscle hypertrophy, and stretch elevates IGF-1 mRNA levels in vivo. In tissue cultures of differentiated avian pectoralis skeletal muscle cells, nanomolar concentrations of exogenous IGF-1 stimulated growth in mechanically stretched but not static cultures. These cultures released up to 100 pg of endogenously produced IGF-1/micro-g of protein/day, as well as three major IGF binding proteins of 31, 36, and 43 kilodaltons (kDa). IGF-1 was secreted from both myofibers and fibroblasts coexisting in the muscle cultures. Repetitive stretch/relaxation of the differentiated skeletal muscle cells stimulated the acute release of IGF-1 during the first 4 h after initiating mechanical activity, but caused no increase in the long-term secretion over 24-72 h of IGF-1, or its binding proteins. Varying the intensity and frequency of stretch had no effect on the long-term efflux of IGF-1. In contrast to stretch, embedding the differentiated muscle cells in a three-dimensional collagen (Type I) matrix resulted in a 2-5-fold increase in long-term IGF-1 efflux over 24-72 h. Collagen also caused a 2-5-fold increase in the release of the IGF binding proteins. Thus, both the extracellular matrix protein type I collagen and stretch stimulate the autocrine secretion of IGF-1, but with different time kinetics. This endogenously produced growth factor may be important for the growth response of skeletal myofibers to both types of external stimuli.

  16. Constitutively active c-Met kinase in PC-3 cells is autocrine-independent and can be blocked by the Met kinase inhibitor BMS-777607

    International Nuclear Information System (INIS)

    The c-Met receptor tyrosine kinase is aberrantly activated in many solid tumors. In a prior study we showed that prostate cancer PC-3 cells exhibit constitutively activated c-Met without exogenous hepatocyte growth factor (HGF); however whether this characteristic is due to an endogenous HGF/c-Met autocrine loop remains controversial. In the current study we examined the response of PC-3 cells to an anti-HGF neutralizing antibody or a small molecule Met kinase inhibitor (BMS-777607). Cell scattering was tested by monitoring cell morphology after HGF stimulation. Cell migration was examined by both “wound-healing” and transwell assasy and invasion was detected by Matrigel-coated transwell assay. Proliferation, survival and anoikis were determined by MTT, colony formation and trypan blue exclusion assay, respectively. Gene and protein expression were assessed by real-time PCR and Western blot, respectively. Although HGF mRNA could be detected in PC-3 cells, the molecular weight of secreted “HGF” protein was inconsistent with the functional recombinant HGF. Furthermore, conditioned medium from PC-3 cell cultures was ineffective at triggering either motogenic behavior or c-Met signaling in DU145, another prostate cancer cell line expressing c-Met but lacking basal c-Met activation. PC-3 cells also were not responsive to the anti-HGF neutralizing antibody in experiments assessing proliferation, migration, or c-Met signaling. BMS-777607 treatment with micromolar doses nonetheless led to significant inhibition of multiple PC-3 cell functions including proliferation, clonogenicity, migration and invasion. At the molecular level, BMS-777607 suppressed autophosphorylated c-Met and downstream c-Src and Akt pathways. These results suggest that the constitutive c-Met activation in PC-3 is independent of autocrine stimulation. Because PC-3 cells were responsive to BMS-777607 but not the anti-HGF antibody, the findings also indicate that under circumstances where c-Met is

  17. High epiregulin expression in human U87 glioma cells relies on IRE1α and promotes autocrine growth through EGF receptor

    International Nuclear Information System (INIS)

    Epidermal growth factor (EGF) receptors contribute to the development of malignant glioma. Here we considered the possible implication of the EGFR ligand epiregulin (EREG) in glioma development in relation to the activity of the unfolded protein response (UPR) sensor IRE1α. We also examined EREG status in several glioblastoma cell lines and in malignant glioma. Expression and biological properties of EREG were analyzed in human glioma cells in vitro and in human tumor xenografts with regard to the presence of ErbB proteins and to the blockade of IRE1α. Inactivation of IRE1α was achieved by using either the dominant-negative strategy or siRNA-mediated knockdown. EREG was secreted in high amounts by U87 cells, which also expressed its cognate EGF receptor (ErbB1). A stimulatory autocrine loop mediated by EREG was evidenced by the decrease in cell proliferation using specific blocking antibodies directed against either ErbB1 (cetuximab) or EREG itself. In comparison, anti-ErbB2 antibodies (trastuzumab) had no significant effect. Inhibition of IRE1α dramatically reduced EREG expression both in cell culture and in human xenograft tumor models. The high-expression rate of EREG in U87 cells was therefore linked to IRE1α, although being modestly affected by chemical inducers of the endoplasmic reticulum stress. In addition, IRE1-mediated production of EREG did not depend on IRE1 RNase domain, as neither the selective dominant-negative invalidation of the RNase activity (IRE1 kinase active) nor the siRNA-mediated knockdown of XBP1 had significant effect on EREG expression. Finally, chemical inhibition of c-Jun N-terminal kinases (JNK) using the SP600125 compound reduced the ability of cells to express EREG, demonstrating a link between the growth factor production and JNK activation under the dependence of IRE1α. EREG may contribute to glioma progression under the control of IRE1α, as exemplified here by the autocrine proliferation loop mediated in U87 cells by the

  18. Direct autocrine inhibition and cAMP-dependent potentiation of single L-type Ca2+ channels in bovine chromaffin cells.

    Science.gov (United States)

    Carabelli, V; Hernández-Guijo, J M; Baldelli, P; Carbone, E

    2001-04-01

    Using the cell-attached recording configuration, we found that in adult bovine chromaffin cells there exists a direct membrane-delimited inhibition of single Bay K-modified L-channels mediated by opioids and ATP locally released in the recording pipette. This autocrine modulation is mediated by pertussis toxin (PTX)-sensitive G-proteins and causes a 50 % decrease of the open channel probability (Po) and an equivalent percentage increase of null sweeps at +10 mV with no changes to the activation kinetics, single channel conductance and mean open time. The decrease in Po is mainly due to an increase in the occurrence and duration of slow closed times (> 40 ms). Addition of purinergic and opioidergic antagonists (suramin and naloxone) or cell pre-treatment with PTX removes the inhibition while addition of ATP and opioids inside the pipette, but not outside, mimics the effect. Strong pre-pulses (+150 mV, 280 ms) followed by short repolarizations are unable to remove the inhibition at test potential (+10 mV). Increasing the level of cAMP by either direct application of 8-(4-chlorophenylthio)-cAMP (8-CPT-cAMP) or mixtures of forskolin and 1-methyl-3-isobutylxanthine (IBMX) potentiates the activity of L-channels by increasing the mean open time and decreasing the mean closed time and percentage of null sweeps. The cAMP-induced potentiation occurs regardless of whether the G-protein-mediated inhibition is activated by ATP and opioids or inactivated by PTX. Protein kinase inhibitors (H7 and H89) prevent the effects of cAMP without altering the basal autocrine modulation associated with PTX-sensitive G-proteins. Our results provide new evidence for the coexistence of two distinct modulations that may converge on the same neuroendocrine L-channel: a direct G-protein-dependent inhibition and a cAMP-mediated potentiation, which may work in combination to regulate Ca2+ entry during neurosecretion. PMID:11283226

  19. Autocrine production of TGF-β confers resistance to apoptosis after an epithelial-mesenchymal transition process in hepatocytes: Role of EGF receptor ligands

    International Nuclear Information System (INIS)

    Transforming growth factor-beta (TGF-β) induces apoptosis in fetal rat hepatocytes. However, a subpopulation of these cells survives, concomitant with changes in phenotype, reminiscent of an epithelial-mesenchymal transition (EMT). We have previously suggested that EMT might confer cell resistance to apoptosis (Valdes et al., Mol. Cancer Res., 1: 68-78, 2002). However, the molecular mechanisms responsible for this resistance are not explored yet. In this work, we have isolated and subcultured the population of hepatocytes that suffered the EMT process and are resistant to apoptosis (TGF-β-treated fetal hepatocytes: TβT-FH). We prove that they secrete mitogenic and survival factors, as analyzed by the proliferative and survival capacity of conditioned medium. Inhibition of the epidermal growth factor receptor (EGFR) sensitizes TβT-FH to die after serum withdrawal. TβT-FH expresses high levels of transforming growth factor-alpha (TGF-α) and heparin-binding EGF-like growth factor (HB-EGF) and shows constitutive activation of the EGFR pathway. A blocking anti-TGF-α antibody restores the capacity of cells to die. TGF-β, which is expressed by TβT-FH, mediates up-regulation of TGF-α and HB-EGF expression in those cells. In summary, results suggest that an autocrine loop of TGF-β confers resistance to apoptosis after an EMT process in hepatocytes, through the increase in the expression of EGFR ligands

  20. UVA-induced autocrine stimulation of fibroblast-derived collagenase/MMP-1 by interrelated loops of interleukin-1 and interleukin-6

    International Nuclear Information System (INIS)

    We here provide evidence that UVA-induced IL-1α and IL-1β play a central role in the induction of the synthesis both of IL-6 and collagenase/MMP-1. In contrast to the late increase of IL-1α and IL-1β mRNA levels at 6 h postirradiation, bioactivity of IL-1 is already detectable at 1 h postirradiation. This early peak of IL-1 bioactivity appears to be responsible for the induction of IL-6 synthesis and together with IL-6 lead to an increase of the steady-state mRNA level of collagenase/MMP-1 as deduced from studies using IL-1α and IL-1β antisense oligonucleotides or neutralizing antibodies against IL-1α and IL-1β. Besides the early posttranslationally controlled release of intracellular IL-1, a latter pretranslationally controlled synthesis and release of IL-1 perpetuates the UV response. From these data we suggest a UV-induced cytokine network consisting of IL-1α, IL-1β and IL-6, which via interrelated autocrine loops induce collagenase/MMP-1 and thus may contribute to the loss of interstitial collagen in cutaneous photoaging. (Author)

  1. Hepatitis C virus regulates the production of monocytic myeloid-derived suppressor cells from peripheral blood mononuclear cells through PI3K pathway and autocrine signaling.

    Science.gov (United States)

    Pang, Xiaoli; Song, Hongxiao; Zhang, Qianqian; Tu, Zhengkun; Niu, Junqi

    2016-03-01

    Hepatitis C virus (HCV) infection is a major liver disease that ultimately develops into chronic hepatitis. Consequently, such patients are predisposed to serious complications, such as hepatocellular carcinoma. In HCV-infected patients, impaired T-cell responses are associated with persistent infection. Myeloid-derived suppressor cells (MDSCs) play a pivotal role in suppressing T-cell responses. In this study, we investigated the capacity and mechanism through which HCV transforms CD14+ monocytes into monocytic (Mo)-MDSCs. We showed that HCV core protein promotes CD14+ monocytes to develop a CD14+HLA-DR/low phenotype with upregulated indoleamine 2,3-dioxygenase (IDO) expression and suppressed T-cell proliferation. Importantly, HCV-induced Mo-MDSC production was attributed to the PI3K pathway via induction of IL-10 and TNF-α secretion. This process could be reversed by polyinosinic:polycytidylic acid (polyI:C) treatment. In conclusion, our results suggest that HCV regulates Mo-MDSC production from monocytes through the PI3K pathway and autocrine cytokines. The latter can serve as effective targets for novel HCV therapies. PMID:26821305

  2. Melanoma cell-derived exosomes promote epithelial-mesenchymal transition in primary melanocytes through paracrine/autocrine signaling in the tumor microenvironment.

    Science.gov (United States)

    Xiao, Deyi; Barry, Samantha; Kmetz, Daniel; Egger, Michael; Pan, Jianmin; Rai, Shesh N; Qu, Jifu; McMasters, Kelly M; Hao, Hongying

    2016-07-01

    The tumor microenvironment is abundant with exosomes that are secreted by the cancer cells themselves. Exosomes are nanosized, organelle-like membranous structures that are increasingly being recognized as major contributors in the progression of malignant neoplasms. A critical element in melanoma progression is its propensity to metastasize, but little is known about how melanoma cell-derived exosomes modulate the microenvironment to optimize conditions for tumor progression and metastasis. Here, we provide evidence that melanoma cell-derived exosomes promote phenotype switching in primary melanocytes through paracrine/autocrine signaling. We found that the mitogen-activated protein kinase (MAPK) signaling pathway was activated during the exosome-mediated epithelial-to-mesenchymal transition (EMT)-resembling process, which promotes metastasis. Let-7i, an miRNA modulator of EMT, was also involved in this process. We further defined two other miRNA modulators of EMT (miR-191 and let-7a) in serum exosomes for differentiating stage I melanoma patients from non-melanoma subjects. These results provide the first strong molecular evidence that melanoma cell-derived exosomes promote the EMT-resembling process in the tumor microenvironment. Thus, novel strategies targeting EMT and modulating the tumor microenvironment may emerge as important approaches for the treatment of metastatic melanoma. PMID:27063098

  3. Sintered anorganic bone graft increases autocrine expression of VEGF, MMP-2 and MMP-9 during repair of critical-size bone defects.

    Science.gov (United States)

    Rocha, Caroline Andrade; Cestari, Tania Mary; Vidotti, Hugo Alberto; de Assis, Gerson Francisco; Garlet, Gustavo Pompermaier; Taga, Rumio

    2014-08-01

    This study aimed to evaluate morphometrically the bone formation and immunohistochemically the expression of vascular endothelial growth factor (VEGF) and metalloproteinase (MMP)-2 and -9 during the healing of critical-size defects treated with sintered anorganic bone (sAB). The 8-mm diameter full-thickness trephine defects created in the parietal bones of rats were filled with sAB (test group) or blood clot (CSD-control group). At 7, 14, 21, 30, 90 and 180 days postoperatively (n = 6/period) the volume of newly formed bone and total number of immunolabeled cells (Ntm) for each protein were determined. Bone formation was smaller and faster in the CSD-control group, stabilizing at 21 days (6.74 mm(3)). The peaks of VEGF, MMP-2 and MMP-9 occurred at 7 and 14 days in fibroblasts and osteoblasts, with mean reduction of 0.80 time at 21 days, keeping constant until 180 days. In the test group, sAB provided continuous bone formation between particles throughout all periods. The peak of MMP-2 was observed at 7-14 days in connective tissue cells and for VEGF and MMP-9 at 30 days in osteoblasts and osteocytes. Ntm for VEGF, MMP-2 and MMP-9 were in average, respectively, 3.70, 2.03 and 5.98 times higher than in the control group. At 180 days, newly formed bone (22.9 mm(3)) was 3.74 times greater in relation to control. The physical and chemical properties of sAB allow increased autocrine expression of VEGF, MMP-2 and MMP-9, favoring bone formation/remodeling with very good healing of cranial defects when compared to natural repair in the CSD-control. PMID:24482159

  4. FGF7 supports hematopoietic stem and progenitor cells and niche-dependent myeloblastoma cells via autocrine action on bone marrow stromal cells in vitro

    International Nuclear Information System (INIS)

    Highlights: •FGF7 is downregulated in MED1-deficient mesenchymal cells. •FGF7 produced by mesenchymal stromal cells is a novel hematopoietic niche molecule. •FGF7 supports hematopoietic progenitor cells and niche-dependent leukemia cells. •FGF7 activates FGFR2IIIb of bone marrow stromal cells in an autocrine manner. •FGF7 indirectly acts on hematopoietic cells lacking FGFR2IIIb via stromal cells. -- Abstract: FGF1 and FGF2 support hematopoietic stem and progenitor cells (HSPCs) under stress conditions. In this study, we show that fibroblast growth factor (FGF7) may be a novel niche factor for HSPC support and leukemic growth. FGF7 expression was attenuated in mouse embryonic fibroblasts (MEFs) deficient for the MED1 subunit of the Mediator transcriptional coregulator complex. When normal mouse bone marrow (BM) cells were cocultured with Med1+/+ MEFs or BM stromal cells in the presence of anti-FGF7 antibody, the growth of BM cells and the number of long-time culture-initiating cells (LTC-ICs) decreased significantly. Anti-FGF7 antibody also attenuated the proliferation and cobblestone formation of MB1 stromal cell-dependent myeloblastoma cells. The addition of recombinant FGF7 to the coculture of BM cells and Med1−/− MEFs increased BM cells and LTC-ICs. FGF7 and its cognate receptor, FGFR2IIIb, were undetectable in BM cells, but MEFs and BM stromal cells expressed both. FGF7 activated downstream targets of FGFR2IIIb in Med1+/+ and Med1−/− MEFs and BM stromal cells. Taken together, we propose that FGF7 supports HSPCs and leukemia-initiating cells indirectly via FGFR2IIIb expressed on stromal cells

  5. Autocrine protective mechanisms of human granulocyte colony-stimulating factor (G-CSF) on retinal ganglion cells after optic nerve crush.

    Science.gov (United States)

    Huang, Shun-Ping; Fang, Kan-Tang; Chang, Chung-Hsing; Huang, Tzu-Lun; Wen, Yao-Tseng; Tsai, Rong-Kung

    2016-02-01

    This study investigated the role of autocrine mechanisms in the anti-apoptotic effects of human granulocyte colony-stimulating factor (G-CSF) on retinal ganglion cells (RGCs) after optic nerve (ON) crush. We observed that both G-CSF and G-CSF receptor (G-CSFR) are expressed in normal rat retina. Further dual immunofluorescence staining showed G-CSFR immunoreactive cells were colocalized with RGCs, Müller cells, horizontal and amacrine cells. These results confirm that G-CSF is an endogenous ligand in the retina. The semi-quantitative RT-PCR finding demonstrated the transcription levels of G-CSF and G-CSFR were up-regulated after ON crush injury. G-CSF treatment further increased and prolonged the expression level of G-CSFR in the retina. G-CSF has been shown to enhance transdifferentiation of the mobilized hematopoietic stem cells into tissue to repair central nervous system injury. We test the hypothesis that the hematopoietic stem cells recruited by G-CSF treatment can transdifferentiate into RGCs after ON crush by performing sublethal irradiation of the rats 5 days before ON crush. The flow cytometric analysis showed the number of CD34 positive cells in the peripheral blood is significantly lower in the irradiated, crushed and G-CSF-treated group than the sham control group or crush and G-CSF treated group. Nevertheless, the G-CSF treatment enhances the RGC survival after sublethal irradiation and ON crush injury. These data indicate that G-CSF seems unlikely to induce hematopoietic stem cell transdifferentiation into RGCs after ON crush injury. In conclusion, G-CSF may serve an endogenous protective signaling in the retina through direct activation of intrinsic G-CSF receptors and downstream signaling pathways to rescue RGCs after ON crush injury, exogenous G-CSF administration can enhance the anti-apoptotic effects on RGCs. PMID:26518178

  6. Direct Melanoma Cell Contact Induces Stromal Cell Autocrine Prostaglandin E2-EP4 Receptor Signaling That Drives Tumor Growth, Angiogenesis, and Metastasis.

    Science.gov (United States)

    Inada, Masaki; Takita, Morichika; Yokoyama, Satoshi; Watanabe, Kenta; Tominari, Tsukasa; Matsumoto, Chiho; Hirata, Michiko; Maru, Yoshiro; Maruyama, Takayuki; Sugimoto, Yukihiko; Narumiya, Shuh; Uematsu, Satoshi; Akira, Shizuo; Murphy, Gillian; Nagase, Hideaki; Miyaura, Chisato

    2015-12-11

    The stromal cells associated with tumors such as melanoma are significant determinants of tumor growth and metastasis. Using membrane-bound prostaglandin E synthase 1 (mPges1(-/-)) mice, we show that prostaglandin E2 (PGE2) production by host tissues is critical for B16 melanoma growth, angiogenesis, and metastasis to both bone and soft tissues. Concomitant studies in vitro showed that PGE2 production by fibroblasts is regulated by direct interaction with B16 cells. Autocrine activity of PGE2 further regulates the production of angiogenic factors by fibroblasts, which are key to the vascularization of both primary and metastatic tumor growth. Similarly, cell-cell interactions between B16 cells and host osteoblasts modulate mPGES-1 activity and PGE2 production by the osteoblasts. PGE2, in turn, acts to stimulate receptor activator of NF-κB ligand expression, leading to osteoclast differentiation and bone erosion. Using eicosanoid receptor antagonists, we show that PGE2 acts on osteoblasts and fibroblasts in the tumor microenvironment through the EP4 receptor. Metastatic tumor growth and vascularization in soft tissues was abrogated by an EP4 receptor antagonist. EP4-null Ptger4(-/-) mice do not support B16 melanoma growth. In vitro, an EP4 receptor antagonist modulated PGE2 effects on fibroblast production of angiogenic factors. Our data show that B16 melanoma cells directly influence host stromal cells to generate PGE2 signals governing neoangiogenesis and metastatic growth in bone via osteoclast erosive activity as well as angiogenesis in soft tissue tumors. PMID:26475855

  7. FGF7 supports hematopoietic stem and progenitor cells and niche-dependent myeloblastoma cells via autocrine action on bone marrow stromal cells in vitro

    Energy Technology Data Exchange (ETDEWEB)

    Ishino, Ruri; Minami, Kaori; Tanaka, Satowa [Laboratory of Hematology, Division of Medical Biophysics, Kobe University Graduate School of Health Sciences, 7-10-2 Tomogaoka, Suma-ku, Kobe 654-0142 (Japan); Nagai, Mami [Consolidated Research Institute for Advanced Science and Medical Care, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 159-8555 (Japan); Matsui, Keiji; Hasegawa, Natsumi [Laboratory of Hematology, Division of Medical Biophysics, Kobe University Graduate School of Health Sciences, 7-10-2 Tomogaoka, Suma-ku, Kobe 654-0142 (Japan); Roeder, Robert G. [Laboratory of Biochemistry and Molecular Biology, The Rockefeller University, 1230 York Avenue, New York, NY 10065 (United States); Asano, Shigetaka [Consolidated Research Institute for Advanced Science and Medical Care, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 159-8555 (Japan); Ito, Mitsuhiro, E-mail: itomi@med.kobe-u.ac.jp [Laboratory of Hematology, Division of Medical Biophysics, Kobe University Graduate School of Health Sciences, 7-10-2 Tomogaoka, Suma-ku, Kobe 654-0142 (Japan); Laboratory of Biochemistry and Molecular Biology, The Rockefeller University, 1230 York Avenue, New York, NY 10065 (United States); Consolidated Research Institute for Advanced Science and Medical Care, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 159-8555 (Japan); Department of Family and Community Medicine, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe 654-0142 (Japan)

    2013-10-11

    Highlights: •FGF7 is downregulated in MED1-deficient mesenchymal cells. •FGF7 produced by mesenchymal stromal cells is a novel hematopoietic niche molecule. •FGF7 supports hematopoietic progenitor cells and niche-dependent leukemia cells. •FGF7 activates FGFR2IIIb of bone marrow stromal cells in an autocrine manner. •FGF7 indirectly acts on hematopoietic cells lacking FGFR2IIIb via stromal cells. -- Abstract: FGF1 and FGF2 support hematopoietic stem and progenitor cells (HSPCs) under stress conditions. In this study, we show that fibroblast growth factor (FGF7) may be a novel niche factor for HSPC support and leukemic growth. FGF7 expression was attenuated in mouse embryonic fibroblasts (MEFs) deficient for the MED1 subunit of the Mediator transcriptional coregulator complex. When normal mouse bone marrow (BM) cells were cocultured with Med1{sup +/+} MEFs or BM stromal cells in the presence of anti-FGF7 antibody, the growth of BM cells and the number of long-time culture-initiating cells (LTC-ICs) decreased significantly. Anti-FGF7 antibody also attenuated the proliferation and cobblestone formation of MB1 stromal cell-dependent myeloblastoma cells. The addition of recombinant FGF7 to the coculture of BM cells and Med1{sup −/−} MEFs increased BM cells and LTC-ICs. FGF7 and its cognate receptor, FGFR2IIIb, were undetectable in BM cells, but MEFs and BM stromal cells expressed both. FGF7 activated downstream targets of FGFR2IIIb in Med1{sup +/+} and Med1{sup −/−} MEFs and BM stromal cells. Taken together, we propose that FGF7 supports HSPCs and leukemia-initiating cells indirectly via FGFR2IIIb expressed on stromal cells.

  8. Progression of Osteosarcoma from a Non-Metastatic to a Metastatic Phenotype Is Causally Associated with Activation of an Autocrine and Paracrine uPA Axis.

    Directory of Open Access Journals (Sweden)

    Liliana Endo-Munoz

    Full Text Available Pulmonary metastasis is the major untreatable complication of osteosarcoma (OS resulting in 10-20% long-term survival. The factors and pathways regulating these processes remain unclear, yet their identification is crucial in order to find new therapeutic targets. In this study we used a multi-omics approach to identify molecules in metastatic and non-metastatic OS cells that may contribute to OS metastasis, followed by validation in vitro and in vivo. We found elevated levels of the urokinase plasminogen activator (uPA and of the uPA receptor (uPAR exclusively in metastatic OS cells. uPA was secreted in soluble form and as part of the protein cargo of OS-secreted extracellular vesicles, including exosomes. In addition, in the tumour microenvironment, uPA was expressed and secreted by bone marrow cells (BMC, and OS- and BMC-derived uPA significantly and specifically stimulated migration of metastatic OS cells via uPA-dependent signaling pathways. Silencing of uPAR in metastatic OS cells abrogated the migratory response to uPA in vitro and decreased metastasis in vivo. Finally, a novel small-molecule inhibitor of uPA significantly (P = 0.0004 inhibited metastasis in an orthotopic mouse model of OS. Thus, we show for the first time that malignant conversion of OS cells to a metastatic phenotype is defined by activation of the uPA/uPAR axis in both an autocrine and paracrine fashion. Furthermore, metastasis is driven by changes in OS cells as well as in the microenvironment. Finally, our data show that pharmacological inhibition of the uPA/uPAR axis with a novel small-molecule inhibitor can prevent the emergence of metastatic foci.

  9. Progression of Osteosarcoma from a Non-Metastatic to a Metastatic Phenotype Is Causally Associated with Activation of an Autocrine and Paracrine uPA Axis.

    Science.gov (United States)

    Endo-Munoz, Liliana; Cai, Na; Cumming, Andrew; Macklin, Rebecca; Merida de Long, Lilia; Topkas, Eleni; Mukhopadhyay, Pamela; Hill, Michelle; Saunders, Nicholas A

    2015-01-01

    Pulmonary metastasis is the major untreatable complication of osteosarcoma (OS) resulting in 10-20% long-term survival. The factors and pathways regulating these processes remain unclear, yet their identification is crucial in order to find new therapeutic targets. In this study we used a multi-omics approach to identify molecules in metastatic and non-metastatic OS cells that may contribute to OS metastasis, followed by validation in vitro and in vivo. We found elevated levels of the urokinase plasminogen activator (uPA) and of the uPA receptor (uPAR) exclusively in metastatic OS cells. uPA was secreted in soluble form and as part of the protein cargo of OS-secreted extracellular vesicles, including exosomes. In addition, in the tumour microenvironment, uPA was expressed and secreted by bone marrow cells (BMC), and OS- and BMC-derived uPA significantly and specifically stimulated migration of metastatic OS cells via uPA-dependent signaling pathways. Silencing of uPAR in metastatic OS cells abrogated the migratory response to uPA in vitro and decreased metastasis in vivo. Finally, a novel small-molecule inhibitor of uPA significantly (P = 0.0004) inhibited metastasis in an orthotopic mouse model of OS. Thus, we show for the first time that malignant conversion of OS cells to a metastatic phenotype is defined by activation of the uPA/uPAR axis in both an autocrine and paracrine fashion. Furthermore, metastasis is driven by changes in OS cells as well as in the microenvironment. Finally, our data show that pharmacological inhibition of the uPA/uPAR axis with a novel small-molecule inhibitor can prevent the emergence of metastatic foci. PMID:26317203

  10. Brain-borne IL-1 adjusts glucoregulation and provides fuel support to astrocytes and neurons in an autocrine/paracrine manner.

    Science.gov (United States)

    Del Rey, A; Verdenhalven, M; Lörwald, A C; Meyer, C; Hernangómez, M; Randolf, A; Roggero, E; König, A M; Heverhagen, J T; Guaza, C; Besedovsky, H O

    2016-09-01

    It is still controversial which mediators regulate energy provision to activated neural cells, as insulin does in peripheral tissues. Interleukin-1β (IL-1β) may mediate this effect as it can affect glucoregulation, it is overexpressed in the 'healthy' brain during increased neuronal activity, and it supports high-energy demanding processes such as long-term potentiation, memory and learning. Furthermore, the absence of sustained neuroendocrine and behavioral counterregulation suggests that brain glucose-sensing neurons do not perceive IL-1β-induced hypoglycemia. Here, we show that IL-1β adjusts glucoregulation by inducing its own production in the brain, and that IL-1β-induced hypoglycemia is myeloid differentiation primary response 88 protein (MyD88)-dependent and only partially counteracted by Kir6.2-mediated sensing signaling. Furthermore, we found that, opposite to insulin, IL-1β stimulates brain metabolism. This effect is absent in MyD88-deficient mice, which have neurobehavioral alterations associated to disorders in glucose homeostasis, as during several psychiatric diseases. IL-1β effects on brain metabolism are most likely maintained by IL-1β auto-induction and may reflect a compensatory increase in fuel supply to neural cells. We explore this possibility by directly blocking IL-1 receptors in neural cells. The results showed that, in an activity-dependent and paracrine/autocrine manner, endogenous IL-1 produced by neurons and astrocytes facilitates glucose uptake by these cells. This effect is exacerbated following glutamatergic stimulation and can be passively transferred between cell types. We conclude that the capacity of IL-1β to provide fuel to neural cells underlies its physiological effects on glucoregulation, synaptic plasticity, learning and memory. However, deregulation of IL-1β production could contribute to the alterations in brain glucose metabolism that are detected in several neurologic and psychiatric diseases. PMID:26643538

  11. An enhanced and sensitive autocrine stimulation by transforming growth factor-alpha is acquired in the brain metastatic variant of a human non-small-cell lung cancer cell line.

    OpenAIRE

    Fang, K.

    1996-01-01

    Transforming growth factor-alpha (TGF-alpha)-mediated autocrine regulation in human non-small-cell lung cancer (NSCLC) cells NCI-H226 and its brain metastatic variant H226Br were compared. An enhanced TGF-alpha-induced dose-dependent mitogenic responsiveness in H226Br cells was observed. Neutralising antibody that binds TGF-alpha inhibits H226Br cell growth more effectively than NCI-H226 cell growth. Binding assay with 125I-labelled epidermal growth factor (EGF) revealed that H226Br has two t...

  12. Aberrant, ectopic expression of VEGF and VEGF receptors 1 and 2 in malignant colonic epithelial cells. Implications for these cells growth via an autocrine mechanism

    Energy Technology Data Exchange (ETDEWEB)

    Ahluwalia, Amrita [Veterans Affairs Long Beach Healthcare System, Long Beach, CA (United States); Jones, Michael K. [Veterans Affairs Long Beach Healthcare System, Long Beach, CA (United States); Department of Medicine, University of California, Irvine, CA (United States); Szabo, Sandor [Veterans Affairs Long Beach Healthcare System, Long Beach, CA (United States); Department of Pathology, University of California, Irvine, CA (United States); Tarnawski, Andrzej S., E-mail: amrita.ahluwalia@va.gov [Veterans Affairs Long Beach Healthcare System, Long Beach, CA (United States); Department of Medicine, University of California, Irvine, CA (United States)

    2013-08-09

    Highlights: •Malignant colonic epithelial cells express VEGF and its receptors. •Cultured colon cancer cells secrete VEGF into the medium. •Inhibition of VEGF receptor significantly decreases colon cancer cell proliferation. •VEGF is critical for colon cancer cell growth. -- Abstract: Vascular endothelial growth factor A (referred to as VEGF) is implicated in colon cancer growth. Currently, the main accepted mechanism by which VEGF promotes colon cancer growth is via the stimulation of angiogenesis, which was originally postulated by late Judah Folkman. However, the cellular source of VEGF in colon cancer tissue; and, the expression of VEGF and its receptors VEGF-R1 and VEGF-R2 in colon cancer cells are not fully known and are subjects of controversy. Material and methods: We examined and quantified expression of VEGF, VEGF-R1 and VEGF-R2 in three different human colonic tissue arrays containing sections of adenocarcinoma (n = 43) and normal mucosa (n = 41). In human colon cancer cell lines HCT116 and HT29 and normal colon cell lines NCM356 and NCM460, we examined expression of VEGF, VEGF-R1 and VEGF-R2 mRNA and protein, VEGF production and secretion into the culture medium; and, the effect of a potent, selective inhibitor of VEGF receptors, AL-993, on cell proliferation. Results: Human colorectal cancer specimens had strong expression of VEGF in cancer cells and also expressed VEGF-R1 and VEGF-R2.In vitro studies showed that human colon cancer cell lines, HCT116 and HT29, but not normal colonic cell lines, express VEGF, VEGF-R1 and VEGF-R2 and secrete VEGF into the medium up to a concentration 2000 pg/ml within 48 h. Furthermore, we showed that inhibition of VEGF receptors using a specific VEGF-R inhibitor significantly reduced proliferation (by >50%) of cultured colon cancer cell lines. Conclusions: Our findings support the contention that VEGF generated by colon cancer cells stimulates their growth directly through an autocrine mechanism that is

  13. Interleukin-8 (IL-8) over-production and autocrine cell activation are key factors in monomethylarsonous acid [MMA(III)]-induced malignant transformation of urothelial cells

    Energy Technology Data Exchange (ETDEWEB)

    Escudero-Lourdes, C., E-mail: cescuder@uaslp.mx [Centro de Investigación y Estudios de Posgrado (CIEP), Facultad de Ciencias Químicas, Universidad Autónoma de San Luis Potosí (Mexico); Wu, T.; Camarillo, J.M.; Gandolfi, A.J. [Department of Pharmacology and Toxicology College of Pharmacy, University of Arizona. Tucson, AZ (United States)

    2012-01-01

    The association between chronic human exposure to arsenicals and bladder cancer development is well recognized; however, the underlying molecular mechanisms have not been fully determined. We propose that inflammatory responses can play a pathogenic role in arsenic-related bladder carcinogenesis. In previous studies, it was demonstrated that chronic exposure to 50 nM monomethylarsenous acid [MMA(III)] leads to malignant transformation of an immortalized model of urothelial cells (UROtsa), with only 3 mo of exposure necessary to trigger the transformation-related changes. In the three-month window of exposure, the cells over-expressed pro-inflammatory cytokines (IL-1β, IL-6 and IL-8), consistent with the sustained activation of NFKβ and AP1/c-jun, ERK2, and STAT3. IL-8 was over-expressed within hours after exposure to MMA(III), and sustained over-expression was observed during chronic exposure. In this study, we profiled IL-8 expression in UROtsa cells exposed to 50 nM MMA(III) for 1 to 5 mo. IL-8 expression was increased mainly in cells after 3 mo MMA(III) exposure, and its production was also found increased in tumors derived from these cells after heterotransplantation in SCID mice. UROtsa cells do express both receptors, CXCR1 and CXCR2, suggesting that autocrine cell activation could be important in cell transformation. Supporting this observation and consistent with IL-8 over-expression, CXCR1 internalization was significantly increased after three months of exposure to MMA(III). The expression of MMP-9, cyclin D1, bcl-2, and VGEF was significantly increased in cells exposed to MMA(III) for 3 mo, but these mitogen-activated kinases were significantly decreased after IL-8 gene silencing, together with a decrease in cell proliferation rate and in anchorage-independent colony formation. These results suggest a relevant role of IL-8 in MMA(III)-induced UROtsa cell transformation. -- Highlights: ► IL-8 is over-expressed in human MMA(III)-exposed urothelial

  14. Aberrant, ectopic expression of VEGF and VEGF receptors 1 and 2 in malignant colonic epithelial cells. Implications for these cells growth via an autocrine mechanism

    International Nuclear Information System (INIS)

    Highlights: •Malignant colonic epithelial cells express VEGF and its receptors. •Cultured colon cancer cells secrete VEGF into the medium. •Inhibition of VEGF receptor significantly decreases colon cancer cell proliferation. •VEGF is critical for colon cancer cell growth. -- Abstract: Vascular endothelial growth factor A (referred to as VEGF) is implicated in colon cancer growth. Currently, the main accepted mechanism by which VEGF promotes colon cancer growth is via the stimulation of angiogenesis, which was originally postulated by late Judah Folkman. However, the cellular source of VEGF in colon cancer tissue; and, the expression of VEGF and its receptors VEGF-R1 and VEGF-R2 in colon cancer cells are not fully known and are subjects of controversy. Material and methods: We examined and quantified expression of VEGF, VEGF-R1 and VEGF-R2 in three different human colonic tissue arrays containing sections of adenocarcinoma (n = 43) and normal mucosa (n = 41). In human colon cancer cell lines HCT116 and HT29 and normal colon cell lines NCM356 and NCM460, we examined expression of VEGF, VEGF-R1 and VEGF-R2 mRNA and protein, VEGF production and secretion into the culture medium; and, the effect of a potent, selective inhibitor of VEGF receptors, AL-993, on cell proliferation. Results: Human colorectal cancer specimens had strong expression of VEGF in cancer cells and also expressed VEGF-R1 and VEGF-R2.In vitro studies showed that human colon cancer cell lines, HCT116 and HT29, but not normal colonic cell lines, express VEGF, VEGF-R1 and VEGF-R2 and secrete VEGF into the medium up to a concentration 2000 pg/ml within 48 h. Furthermore, we showed that inhibition of VEGF receptors using a specific VEGF-R inhibitor significantly reduced proliferation (by >50%) of cultured colon cancer cell lines. Conclusions: Our findings support the contention that VEGF generated by colon cancer cells stimulates their growth directly through an autocrine mechanism that is

  15. Arsenite evokes IL-6 secretion, autocrine regulation of STAT3 signaling, and miR-21 expression, processes involved in the EMT and malignant transformation of human bronchial epithelial cells

    Energy Technology Data Exchange (ETDEWEB)

    Luo, Fei; Xu, Yuan [Institute of Toxicology, Ministry of Education, School of Public Health, Nanjing Medical University (China); The Key Laboratory of Modern Toxicology, Ministry of Education, School of Public Health, Nanjing Medical University (China); Ling, Min [Jiangsu Center for Disease Control and Prevention, Nanjing 211166, Jiangsu (China); Zhao, Yue; Xu, Wenchao [Institute of Toxicology, Ministry of Education, School of Public Health, Nanjing Medical University (China); The Key Laboratory of Modern Toxicology, Ministry of Education, School of Public Health, Nanjing Medical University (China); Liang, Xiao [Mental Health Center of Xuhui-CDC, Shanghai 200232 (China); Jiang, Rongrong; Wang, Bairu [Institute of Toxicology, Ministry of Education, School of Public Health, Nanjing Medical University (China); The Key Laboratory of Modern Toxicology, Ministry of Education, School of Public Health, Nanjing Medical University (China); Bian, Qian [Jiangsu Center for Disease Control and Prevention, Nanjing 211166, Jiangsu (China); Liu, Qizhan, E-mail: drqzliu@hotmail.com [Institute of Toxicology, Ministry of Education, School of Public Health, Nanjing Medical University (China); The Key Laboratory of Modern Toxicology, Ministry of Education, School of Public Health, Nanjing Medical University (China)

    2013-11-15

    Arsenite is an established human carcinogen, and arsenite-induced inflammation contributes to malignant transformation of cells, but the molecular mechanisms by which cancers are produced remain to be established. The present results showed that, evoked by arsenite, secretion of interleukin-6 (IL-6), a pro-inflammatory cytokine, led to the activation of STAT3, a transcription activator, and to increased levels of a microRNA, miR-21. Blocking IL-6 with anti-IL-6 antibody and inhibiting STAT3 activation reduced miR-21 expression. For human bronchial epithelial cells, cultured in the presence of anti-IL-6 antibody for 3 days, the arsenite-induced EMT and malignant transformation were reversed. Thus, IL-6, acting on STAT3 signaling, which up-regulates miR-21in an autocrine manner, contributes to the EMT induced by arsenite. These data define a link from inflammation to EMT in the arsenite-induced malignant transformation of HBE cells. This link, mediated through miRNAs, establishes a mechanism for arsenite-induced lung carcinogenesis. - Highlights: • Arsenite evokes IL-6 secretion. • IL-6 autocrine mediates STAT3 signaling and up-regulates miR-21expression. • Inflammation is involved in arsenite-induced EMT.

  16. Arsenite evokes IL-6 secretion, autocrine regulation of STAT3 signaling, and miR-21 expression, processes involved in the EMT and malignant transformation of human bronchial epithelial cells

    International Nuclear Information System (INIS)

    Arsenite is an established human carcinogen, and arsenite-induced inflammation contributes to malignant transformation of cells, but the molecular mechanisms by which cancers are produced remain to be established. The present results showed that, evoked by arsenite, secretion of interleukin-6 (IL-6), a pro-inflammatory cytokine, led to the activation of STAT3, a transcription activator, and to increased levels of a microRNA, miR-21. Blocking IL-6 with anti-IL-6 antibody and inhibiting STAT3 activation reduced miR-21 expression. For human bronchial epithelial cells, cultured in the presence of anti-IL-6 antibody for 3 days, the arsenite-induced EMT and malignant transformation were reversed. Thus, IL-6, acting on STAT3 signaling, which up-regulates miR-21in an autocrine manner, contributes to the EMT induced by arsenite. These data define a link from inflammation to EMT in the arsenite-induced malignant transformation of HBE cells. This link, mediated through miRNAs, establishes a mechanism for arsenite-induced lung carcinogenesis. - Highlights: • Arsenite evokes IL-6 secretion. • IL-6 autocrine mediates STAT3 signaling and up-regulates miR-21expression. • Inflammation is involved in arsenite-induced EMT

  17. An enhanced and sensitive autocrine stimulation by transforming growth factor-alpha is acquired in the brain metastatic variant of a human non-small-cell lung cancer cell line.

    Science.gov (United States)

    Fang, K

    1996-12-01

    Transforming growth factor-alpha (TGF-alpha)-mediated autocrine regulation in human non-small-cell lung cancer (NSCLC) cells NCI-H226 and its brain metastatic variant H226Br were compared. An enhanced TGF-alpha-induced dose-dependent mitogenic responsiveness in H226Br cells was observed. Neutralising antibody that binds TGF-alpha inhibits H226Br cell growth more effectively than NCI-H226 cell growth. Binding assay with 125I-labelled epidermal growth factor (EGF) revealed that H226Br has two types of EGF receptors (EGFRs), whereas the parental cell line, NCI-H226, has only one. H226Br cells contain twice as many EGFRs as H226 cells, as proved by Scatchard analysis and immune kinase assay. Northern analysis indicated that there is more EGFR transcript in H226Br than in NCI-H226, indicating a transcriptional EGFR gene elevation during metastasis progression. The level of accumulated immunoactive TGF-alpha is lower in the conditioned medium of H226Br than in that of NCI-H226. demonstrating down-regulation of TGF-alpha transcript. The accumulated data suggest an elevated and sensitive autocrine modulation by TGF-alpha and EGFR in immortalising the brain metastatic variant cells that were derived from a human NSCLC squamous cell line. PMID:8956792

  18. Climate prediction and predictability

    Science.gov (United States)

    Allen, Myles

    2010-05-01

    Climate prediction is generally accepted to be one of the grand challenges of the Geophysical Sciences. What is less widely acknowledged is that fundamental issues have yet to be resolved concerning the nature of the challenge, even after decades of research in this area. How do we verify or falsify a probabilistic forecast of a singular event such as anthropogenic warming over the 21st century? How do we determine the information content of a climate forecast? What does it mean for a modelling system to be "good enough" to forecast a particular variable? How will we know when models and forecasting systems are "good enough" to provide detailed forecasts of weather at specific locations or, for example, the risks associated with global geo-engineering schemes. This talk will provide an overview of these questions in the light of recent developments in multi-decade climate forecasting, drawing on concepts from information theory, machine learning and statistics. I will draw extensively but not exclusively from the experience of the climateprediction.net project, running multiple versions of climate models on personal computers.

  19. Identification of the Long-Sought Leptin in Chicken and Duck: Expression Pattern of the Highly GC-Rich Avian leptin Fits an Autocrine/Paracrine Rather Than Endocrine Function.

    Science.gov (United States)

    Seroussi, Eyal; Cinnamon, Yuval; Yosefi, Sara; Genin, Olga; Smith, Julia Gage; Rafati, Nima; Bornelöv, Susanne; Andersson, Leif; Friedman-Einat, Miriam

    2016-02-01

    More than 20 years after characterization of the key regulator of mammalian energy balance, leptin, we identified the leptin (LEP) genes of chicken (Gallus gallus) and duck (Anas platyrhynchos). The extreme guanine-cytosine content (∼70%), the location in a genomic region with low-complexity repetitive and palindromic sequence elements, the relatively low sequence conservation, and low level of expression have hampered the identification of these genes until now. In vitro-expressed chicken and duck leptins specifically activated signaling through the chicken leptin receptor in cell culture. In situ hybridization demonstrated expression of LEP mRNA in granular and Purkinje cells of the cerebellum, anterior pituitary, and in embryonic limb buds, somites, and branchial arches, suggesting roles in adult brain control of energy balance and during embryonic development. The expression patterns of LEP and the leptin receptor (LEPR) were explored in chicken, duck, and quail (Coturnix japonica) using RNA-sequencing experiments available in the Short Read Archive and by quantitative RT-PCR. In adipose tissue, LEP and LEPR were scarcely transcribed, and the expression level was not correlated to adiposity. Our identification of the leptin genes in chicken and duck genomes resolves a long lasting controversy regarding the existence of leptin genes in these species. This identification was confirmed by sequence and structural similarity, conserved exon-intron boundaries, detection in numerous genomic, and transcriptomic datasets and characterization by PCR, quantitative RT-PCR, in situ hybridization, and bioassays. Our results point to an autocrine/paracrine mode of action for bird leptin instead of being a circulating hormone as in mammals. PMID:26587783

  20. Prediction of denosumab effects on bone remodeling: A combined pharmacokinetics and finite element modeling.

    Science.gov (United States)

    Hambli, Ridha; Boughattas, Mohamed Hafedh; Daniel, Jean-Luc; Kourta, Azeddine

    2016-07-01

    Denosumab is a fully human monoclonal antibody that inhibits receptor activator of nuclearfactor-kappa B ligand (RANKL). This key mediator of osteoclast activities has been shown to inhibit osteoclast differentiation and hence, to increase bone mineral density (BMD) in treated patients. In the current study, we develop a computer model to simulate the effects of denosumab treatments (dose and duration) on the proximal femur bone remodeling process quantified by the variation in proximal femur BMD. The simulation model is based on a coupled pharmacokinetics model of denosumab with a pharmacodynamics model consisting of a mechanobiological finite element remodeling model which describes the activities of osteoclasts and osteoblasts. The mechanical behavior of bone is described by taking into account the bone material fatigue damage accumulation and mineralization. A coupled strain-damage stimulus function is proposed which controls the level of bone cell autocrine and paracrine factors. The cellular behavior is based on Komarova et al.׳s (2003) dynamic law which describes the autocrine and paracrine interactions between osteoblasts and osteoclasts and computes cell population dynamics and changes in bone mass at a discrete site of bone remodeling. Therefore, when an external mechanical stress is applied, bone formation and resorption is governed by cell dynamics rather than by adaptive elasticity approaches. The proposed finite element model was implemented in the finite element code Abaqus (UMAT routine). In order to perform a preliminary validation, in vivo human proximal femurs were selected and scanned at two different time intervals (at baseline and at a 36-month interval). Then, a 3D FE model was generated and the denosumab-remodeling algorithm was applied to the scans at t0 simulating daily walking activities for a duration of 36 months. The predicted results (density variation) were compared to existing published ones performed on a human cohort (FREEDOM

  1. Prediction Markets

    DEFF Research Database (Denmark)

    Horn, Christian Franz; Ivens, Bjørn Sven; Ohneberg, Michael;

    2014-01-01

    In recent years, Prediction Markets gained growing interest as a forecasting tool among researchers as well as practitioners, which resulted in an increasing number of publications. In order to track the latest development of research, comprising the extent and focus of research, this article...... provides a comprehensive review and classification of the literature related to the topic of Prediction Markets. Overall, 316 relevant articles, published in the timeframe from 2007 through 2013, were identified and assigned to a herein presented classification scheme, differentiating between descriptive...... works, articles of theoretical nature, application-oriented studies and articles dealing with the topic of law and policy. The analysis of the research results reveals that more than half of the literature pool deals with the application and actual function tests of Prediction Markets. The results are...

  2. Predicting protein structure classes from function predictions

    DEFF Research Database (Denmark)

    Sommer, I.; Rahnenfuhrer, J.; de Lichtenberg, Ulrik;

    2004-01-01

    We introduce a new approach to using the information contained in sequence-to-function prediction data in order to recognize protein template classes, a critical step in predicting protein structure. The data on which our method is based comprise probabilities of functional categories; for given......-to-structure prediction methods....

  3. Making detailed predictions makes (some) predictions worse

    Science.gov (United States)

    Kelly, Theresa F.

    In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

  4. Downstream prediction using a nonlinear prediction method

    Science.gov (United States)

    Adenan, N. H.; Noorani, M. S. M.

    2013-11-01

    The estimation of river flow is significantly related to the impact of urban hydrology, as this could provide information to solve important problems, such as flooding downstream. The nonlinear prediction method has been employed for analysis of four years of daily river flow data for the Langat River at Kajang, Malaysia, which is located in a downstream area. The nonlinear prediction method involves two steps; namely, the reconstruction of phase space and prediction. The reconstruction of phase space involves reconstruction from a single variable to the m-dimensional phase space in which the dimension m is based on optimal values from two methods: the correlation dimension method (Model I) and false nearest neighbour(s) (Model II). The selection of an appropriate method for selecting a combination of preliminary parameters, such as m, is important to provide an accurate prediction. From our investigation, we gather that via manipulation of the appropriate parameters for the reconstruction of the phase space, Model II provides better prediction results. In particular, we have used Model II together with the local linear prediction method to achieve the prediction results for the downstream area with a high correlation coefficient. In summary, the results show that Langat River in Kajang is chaotic, and, therefore, predictable using the nonlinear prediction method. Thus, the analysis and prediction of river flow in this area can provide river flow information to the proper authorities for the construction of flood control, particularly for the downstream area.

  5. Learning predictive clustering rules

    OpenAIRE

    Ženko, Bernard; Džeroski, Sašo; Struyf, Jan

    2005-01-01

    The two most commonly addressed data mining tasks are predictive modelling and clustering. Here we address the task of predictive clustering, which contains elements of both and generalizes them to some extent. We propose a novel approach to predictive clustering called predictive clustering rules, present an initial implementation and its preliminary experimental evaluation.

  6. Nonparametric bootstrap prediction

    OpenAIRE

    Fushiki, Tadayoshi; Komaki, Fumiyasu; Aihara, Kazuyuki

    2005-01-01

    Ensemble learning has recently been intensively studied in the field of machine learning. `Bagging' is a method of ensemble learning and uses bootstrap data to construct various predictors. The required prediction is then obtained by averaging the predictors. Harris proposed using this technique with the parametric bootstrap predictive distribution to construct predictive distributions, and showed that the parametric bootstrap predictive distribution gives asymptotically better prediction tha...

  7. Predictability of social interactions

    OpenAIRE

    Xu, Kevin S.

    2013-01-01

    The ability to predict social interactions between people has profound applications including targeted marketing and prediction of information diffusion and disease propagation. Previous work has shown that the location of an individual at any given time is highly predictable. This study examines the predictability of social interactions between people to determine whether interaction patterns are similarly predictable. I find that the locations and times of interactions for an individual are...

  8. Numerical earthquake prediction

    International Nuclear Information System (INIS)

    Can earthquakes be predicted? How should people overcome the difficulties encountered in the study of earthquake prediction? This issue can take inspiration from the experiences of weather forecast. Although weather forecasting took a period of about half a century to advance from empirical to numerical forecast, it has achieved significant success. A consensus has been reached among the Chinese seismological community that earthquake prediction must also develop from empirical forecasting to physical prediction. However, it is seldom mentioned that physical prediction is characterized by quantitatively numerical predictions based on physical laws. This article discusses five key components for numerical earthquake prediction and their current status. We conclude that numerical earthquake prediction should now be put on the planning agenda and its roadmap designed, seismic stations should be deployed and observations made according to the needs of numerical prediction, and theoretical research should be carried out. (authors)

  9. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions. PMID:27286683

  10. Neurotensin (NTS) and its receptor (NTSR1) causes EGFR, HER2 and HER3 over-expression and their autocrine/paracrine activation in lung tumors, confirming responsiveness to erlotinib

    OpenAIRE

    Younes, Mohamad; Wu, Zherui; Dupouy, Sandra; Lupo, Audrey Mansuet; Mourra, Najat; Takahashi, Takashi; Fléjou, Jean François; Trédaniel, Jean; Régnard, Jean François; Damotte, Diane; Alifano, Marco; Forgez, Patricia

    2014-01-01

    Alterations in the signaling pathways of epidermal growth factor receptors (HERs) are associated with tumor aggressiveness. Neurotensin (NTS) and its high affinity receptor (NTSR1) are up regulated in 60% of lung cancers. In a previous clinical study, NTSR1 overexpression was shown to predict a poor prognosis for 5 year overall survival in a selected population of stage I lung adenocarcinomas treated by surgery alone. In a second study, shown here, the frequent and high expression of NTSR1 wa...

  11. MDA-MB-231细胞源exosome对人脐静脉内皮细胞(HUVEC)VEGF自分泌及体外成管作用的影响%Effects of exosomes derived from MDA-MB-231 on the expression of autocrine VEGF and capillary-like tube formation in HUVECs

    Institute of Scientific and Technical Information of China (English)

    隆霜; 沈宜; 谢莹珊; 范维珂; 姜蓉; 陈黎

    2012-01-01

    目的 研究人乳腺癌MDA-MB-231细胞源exosome对人脐静脉内皮细胞(human umbilical vein endothelial cell,HUVEC)血管内皮生长因子(vascular endothelial growth factor,VEGF)自分泌及体外成管作用的影响,探讨肿瘤细胞源exosome在肿瘤微环境中对血管内皮细胞血管生成的调控作用.方法 低温超速离心及密度梯度离心法提取乳腺癌MDA-MB-231细胞源exosome;酶联免疫吸附试验(ELISA)检测HUVEC与exosome共培养24 h后上清液中VEGF的变化水平;Western blot技术检测HUVEC与exosome共培养24 h后VEGF、VEGFR2及p-VEGFR2的蛋白表达情况;RT-PCR法检测HUVEC与exosome共培养24 h后VEGF的基因表达情况;观察HUVEC与exosome共培养24 h后的体外成管能力.结果 HUVEC与exosome共培养24 h后上清液中VEGF为(110.851±18.404)pg/mL,与对照组相比差异具有统计学意义(P<0.05);Western blot结果显示,HUVEC与exosome共培养24 h后VEGF和p-VEGFR2的蛋白表达水平均增加(P<0.05);RT-PCR结果显示,HUVEC与exosome共培养24 h后VEGF的基因表达水平增加(P<0.05);体外成管实验显示,exosome显著提高了HUVEC的管腔形成能力(P<0.05).结论 乳腺癌MDA-MB-231细胞源exosome促进了血管内皮细胞VEGF的表达及分泌,激活了血管内皮细胞VEGF/VEGFR2自分泌环并提高了血管内皮细胞的体外成管能力,对促肿瘤血管生成有一定的调控作用.%Objective To investigate the effects of exosomes derived from breast cancer cell line MDA-MB-231 on the expression of autocrine vascular endothelial growth factor (VEGF) and capillary-like tube formation in human umbilical vein endothelial cells ( HUVECs) , and to observe the regulatory effect of exosomes derived from cancer cells on angiogenesis in tumor microenvironment. Methods Exosomes were purified by serial ultracentrifugation and sugar density ultracentrifugation. The expression of autocrine VEGF in HUVECs with exosomes co-cultured 24 hours were detected by

  12. Optimal predictive model selection

    OpenAIRE

    Barbieri, Maria Maddalena; Berger, James O.

    2004-01-01

    Often the goal of model selection is to choose a model for future prediction, and it is natural to measure the accuracy of a future prediction by squared error loss. Under the Bayesian approach, it is commonly perceived that the optimal predictive model is the model with highest posterior probability, but this is not necessarily the case. In this paper we show that, for selection among normal linear models, the optimal predictive model is often the median probability model, which is defined a...

  13. Predictive software design measures

    OpenAIRE

    Love, Randall James

    1994-01-01

    This research develops a set of predictive measures enabling software testers and designers to identify and target potential problem areas for additional and/or enhanced testing. Predictions are available as early in the design process as requirements allocation and as late as code walk-throughs. These predictions are based on characteristics of the design artifacts prior to coding. Prediction equations are formed at established points in the software development process...

  14. Testing earthquake predictions

    Science.gov (United States)

    Luen, Brad; Stark, Philip B.

    2008-01-01

    Statistical tests of earthquake predictions require a null hypothesis to model occasional chance successes. To define and quantify 'chance success' is knotty. Some null hypotheses ascribe chance to the Earth: Seismicity is modeled as random. The null distribution of the number of successful predictions - or any other test statistic - is taken to be its distribution when the fixed set of predictions is applied to random seismicity. Such tests tacitly assume that the predictions do not depend on the observed seismicity. Conditioning on the predictions in this way sets a low hurdle for statistical significance. Consider this scheme: When an earthquake of magnitude 5.5 or greater occurs anywhere in the world, predict that an earthquake at least as large will occur within 21 days and within an epicentral distance of 50 km. We apply this rule to the Harvard centroid-moment-tensor (CMT) catalog for 2000-2004 to generate a set of predictions. The null hypothesis is that earthquake times are exchangeable conditional on their magnitudes and locations and on the predictions - a common "nonparametric" assumption in the literature. We generate random seismicity by permuting the times of events in the CMT catalog. We consider an event successfully predicted only if (i) it is predicted and (ii) there is no larger event within 50 km in the previous 21 days. The P-value for the observed success rate is <0.001: The method successfully predicts about 5% of earthquakes, far better than 'chance' because the predictor exploits the clustering of earthquakes - occasional foreshocks - which the null hypothesis lacks. Rather than condition on the predictions and use a stochastic model for seismicity, it is preferable to treat the observed seismicity as fixed, and to compare the success rate of the predictions to the success rate of simple-minded predictions like those just described. If the proffered predictions do no better than a simple scheme, they have little value.

  15. Predicting Predictable about Natural Catastrophic Extremes

    Science.gov (United States)

    Kossobokov, Vladimir

    2015-04-01

    By definition, an extreme event is rare one in a series of kindred phenomena. Usually (e.g. in Geophysics), it implies investigating a small sample of case-histories with a help of delicate statistical methods and data of different quality, collected in various conditions. Many extreme events are clustered (far from independent) and follow fractal or some other "strange" distribution (far from uniform). Evidently, such an "unusual" situation complicates search and definition of reliable precursory behaviors to be used for forecast/prediction purposes. Making forecast/prediction claims reliable and quantitatively probabilistic in the frames of the most popular objectivists' viewpoint on probability requires a long series of "yes/no" forecast/prediction outcomes, which cannot be obtained without an extended rigorous test of the candidate method. The set of errors ("success/failure" scores and space-time measure of alarms) and other information obtained in such a control test supplies us with data necessary to judge the candidate's potential as a forecast/prediction tool and, eventually, to find its improvements. This is to be done first in comparison against random guessing, which results confidence (measured in terms of statistical significance). Note that an application of the forecast/prediction tools could be very different in cases of different natural hazards, costs and benefits that determine risks, and, therefore, requires determination of different optimal strategies minimizing reliable estimates of realistic levels of accepted losses. In their turn case specific costs and benefits may suggest a modification of the forecast/prediction tools for a more adequate "optimal" application. Fortunately, the situation is not hopeless due to the state-of-the-art understanding of the complexity and non-linear dynamics of the Earth as a Physical System and pattern recognition approaches applied to available geophysical evidences, specifically, when intending to predict

  16. Predictable or not predictable? The MOV question

    International Nuclear Information System (INIS)

    Over the past 8 years, the nuclear industry has struggled to understand the dynamic phenomena experienced during motor-operated valve (MOV) operation under differing flow conditions. For some valves and designs, their operational functionality has been found to be predictable; for others, unpredictable. Although much has been accomplished over this period of time, especially on modeling valve dynamics, the unpredictability of many valves and designs still exists. A few valve manufacturers are focusing on improving design and fabrication techniques to enhance product reliability and predictability. However, this approach does not address these issues for installed and inpredictable valves. This paper presents some of the more promising techniques that Wyle Laboratories has explored with potential for transforming unpredictable valves to predictable valves and for retrofitting installed MOVs. These techniques include optimized valve tolerancing, surrogated material evaluation, and enhanced surface treatments

  17. Visualizing Risk Prediction Models

    OpenAIRE

    Vanya Van Belle; Ben Van Calster

    2015-01-01

    Objective Risk prediction models can assist clinicians in making decisions. To boost the uptake of these models in clinical practice, it is important that end-users understand how the model works and can efficiently communicate its results. We introduce novel methods for interpretable model visualization. Methods The proposed visualization techniques are applied to two prediction models from the Framingham Heart Study for the prediction of intermittent claudication and stroke after atrial fib...

  18. Pyroshock prediction procedures

    Science.gov (United States)

    Piersol, Allan G.

    2002-05-01

    Given sufficient effort, pyroshock loads can be predicted by direct analytical procedures using Hydrocodes that analytically model the details of the pyrotechnic explosion and its interaction with adjacent structures, including nonlinear effects. However, it is more common to predict pyroshock environments using empirical procedures based upon extensive studies of past pyroshock data. Various empirical pyroshock prediction procedures are discussed, including those developed by the Jet Propulsion Laboratory, Lockheed-Martin, and Boeing.

  19. Predicting transformers oil parameters

    OpenAIRE

    Shaban, K.; El-Hag, A.; Matveev, A.

    2009-01-01

    In this paper different configurations of artificial neural networks are applied to predict various transformers oil parameters. The prediction is performed through modeling the relationship between the transformer insulation resistance extracted from the Megger test and the breakdown strength, interfacial tension, acidity and the water content of the transformers oil. The process of predicting these oil parameters statuses is carried out using two different configurations of neural networks....

  20. Is Suicide Predictable?

    OpenAIRE

    Asmaee, S; Mosavi, N; R Abdul Rashid; H Habi; Seghatoleslam, T; Naseri, A.

    2012-01-01

    Background: The current study aimed to test the hypothesis: Is suicide predictable? And try to classify the predictive factors in multiple suicide attempts. Methods: A cross-sectional study was administered to 223 multiple attempters, women who came to a medical poison centre after a suicide attempt. The participants were young, poor, and single. A Logistic Regression Analiysis was used to classify the predictive factors of suicide. Results: Women who had multiple suicide attempts exhibited a...

  1. 'Red Flag' Predictions

    DEFF Research Database (Denmark)

    Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

    -generation prediction markets and outline its unique features as a third-generation prediction market. It is argued that frontline employees gain deep insights when they execute operational activities on an ongoing basis in the organization. The experiential learning from close interaction with internal and external...

  2. Predicting the MJO

    Science.gov (United States)

    Hendon, H.

    2003-04-01

    Extended range prediction of the Madden Julian Oscillation (MJO) and seasonal prediction of MJO activity are reviewed. Skillful prediction of individual MJO events offers the possibility of forecasting increased risk of cyclone development throughout the global tropics, altered risk of extreme rainfall events in both tropics and extratropics, and displacement of storm tracks with 3-4 week lead times. The level of MJO activity within a season, which affects the mean intensity of the Australian summer monsoon and possibly the evolution of ENSO, may be governed by variations of sea surface temperature that are predictable with lead times of a few seasons. The limit of predictability for individual MJO events is unknown. Empirical-statistical schemes are skillful out to about 3 weeks and have better skill than dynamical forecast models at lead times longer than about 5 days. The dynamical forecast models typically suffer from a poor representation (or complete lack) of the MJO and large initial error. They are better used to ascertain the global impacts of the lack of the MJO rather than for determination of the limit of predictability. Dynamical extended range prediction within a GCM that has a good representation of the MJO indicates potential skill comparable to the empirical schemes. Examples of operational extended range prediction with POAMA, the new coupled seasonal forecast model at the Bureau of Meteorology that also reasonably simulates the MJO, will be presented.

  3. Improved nonlinear prediction method

    Science.gov (United States)

    Adenan, Nur Hamiza; Md Noorani, Mohd Salmi

    2014-06-01

    The analysis and prediction of time series data have been addressed by researchers. Many techniques have been developed to be applied in various areas, such as weather forecasting, financial markets and hydrological phenomena involving data that are contaminated by noise. Therefore, various techniques to improve the method have been introduced to analyze and predict time series data. In respect of the importance of analysis and the accuracy of the prediction result, a study was undertaken to test the effectiveness of the improved nonlinear prediction method for data that contain noise. The improved nonlinear prediction method involves the formation of composite serial data based on the successive differences of the time series. Then, the phase space reconstruction was performed on the composite data (one-dimensional) to reconstruct a number of space dimensions. Finally the local linear approximation method was employed to make a prediction based on the phase space. This improved method was tested with data series Logistics that contain 0%, 5%, 10%, 20% and 30% of noise. The results show that by using the improved method, the predictions were found to be in close agreement with the observed ones. The correlation coefficient was close to one when the improved method was applied on data with up to 10% noise. Thus, an improvement to analyze data with noise without involving any noise reduction method was introduced to predict the time series data.

  4. Zephyr - the prediction models

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Madsen, Henrik; Nielsen, Henrik Aalborg;

    2001-01-01

    utilities as partners and users. The new models are evaluated for five wind farms in Denmark as well as one wind farm in Spain. It is shown that the predictions based on conditional parametric models are superior to the predictions obatined by state-of-the-art parametric models....

  5. Predicting AD conversion

    DEFF Research Database (Denmark)

    Liu, Yawu; Mattila, Jussi; Ruiz, Miguel �ngel Mu�oz;

    2013-01-01

    To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool) and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA) on MRI...

  6. Prediction of Antibody Epitopes

    DEFF Research Database (Denmark)

    Nielsen, Morten; Marcatili, Paolo

    2015-01-01

    self-proteins. Given the sequence or the structure of a protein of interest, several methods exploit such features to predict the residues that are more likely to be recognized by an immunoglobulin.Here, we present two methods (BepiPred and DiscoTope) to predict linear and discontinuous antibody...

  7. Error mode prediction.

    Science.gov (United States)

    Hollnagel, E; Kaarstad, M; Lee, H C

    1999-11-01

    The study of accidents ('human errors') has been dominated by efforts to develop 'error' taxonomies and 'error' models that enable the retrospective identification of likely causes. In the field of Human Reliability Analysis (HRA) there is, however, a significant practical need for methods that can predict the occurrence of erroneous actions--qualitatively and quantitatively. The present experiment tested an approach for qualitative performance prediction based on the Cognitive Reliability and Error Analysis Method (CREAM). Predictions of possible erroneous actions were made for operators using different types of alarm systems. The data were collected as part of a large-scale experiment using professional nuclear power plant operators in a full scope simulator. The analysis showed that the predictions were correct in more than 70% of the cases, and also that the coverage of the predictions depended critically on the comprehensiveness of the preceding task analysis. PMID:10582035

  8. Evaluating prediction uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    McKay, M.D. [Los Alamos National Lab., NM (United States)

    1995-03-01

    The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented.

  9. Evaluating prediction uncertainty

    International Nuclear Information System (INIS)

    The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented

  10. Predictable return distributions

    DEFF Research Database (Denmark)

    Pedersen, Thomas Quistgaard

    This paper provides detailed insights into predictability of the entire stock and bond return distribution through the use of quantile regression. This allows us to examine speci…c parts of the return distribution such as the tails or the center, and for a suf…ciently …ne grid of quantiles we can...... predictable as a function of economic state variables. The results are, however, very different for stocks and bonds. The state variables primarily predict only location shifts in the stock return distribution, while they also predict changes in higher-order moments in the bond return distribution. Out......-of-sample analyses show that the relative accuracy of the state variables in predicting future returns varies across the distribution. A portfolio study shows that an investor with power utility can obtain economic gains by applying the empirical return distribution in portfolio decisions instead of imposing an...

  11. Is Time Predictability Quantifiable?

    DEFF Research Database (Denmark)

    Schoeberl, Martin

    2012-01-01

    Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst-case execu......Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst......-case execution time. To compare different approaches we would like to quantify time predictability. That means we need to measure time predictability. In this paper we discuss the different approaches for these measurements and conclude that time predictability is practically not quantifiable. We can only...

  12. Ground motion predictions

    International Nuclear Information System (INIS)

    Nuclear generated ground motion is defined and then related to the physical parameters that cause it. Techniques employed for prediction of ground motion peak amplitude, frequency spectra and response spectra are explored, with initial emphasis on the analysis of data collected at the Nevada Test Site (NTS). NTS postshot measurements are compared with pre-shot predictions. Applicability of these techniques to new areas, for example, Plowshare sites, must be questioned. Fortunately, the Atomic Energy Commission is sponsoring complementary studies to improve prediction capabilities primarily in new locations outside the NTS region. Some of these are discussed in the light of anomalous seismic behavior, and comparisons are given showing theoretical versus experimental results. In conclusion, current ground motion prediction techniques are applied to events off the NTS. Predictions are compared with measurements for the event Faultless and for the Plowshare events, Gasbuggy, Cabriolet, and Buggy I. (author)

  13. Structural prediction in aphasia

    Directory of Open Access Journals (Sweden)

    Tessa Warren

    2015-05-01

    Full Text Available There is considerable evidence that young healthy comprehenders predict the structure of upcoming material, and that their processing is facilitated when they encounter material matching those predictions (e.g., Staub & Clifton, 2006; Yoshida, Dickey & Sturt, 2013. However, less is known about structural prediction in aphasia. There is evidence that lexical prediction may be spared in aphasia (Dickey et al., 2014; Love & Webb, 1977; cf. Mack et al, 2013. However, predictive mechanisms supporting facilitated lexical access may not necessarily support structural facilitation. Given that many people with aphasia (PWA exhibit syntactic deficits (e.g. Goodglass, 1993, PWA with such impairments may not engage in structural prediction. However, recent evidence suggests that some PWA may indeed predict upcoming structure (Hanne, Burchert, De Bleser, & Vashishth, 2015. Hanne et al. tracked the eyes of PWA (n=8 with sentence-comprehension deficits while they listened to reversible subject-verb-object (SVO and object-verb-subject (OVS sentences in German, in a sentence-picture matching task. Hanne et al. manipulated case and number marking to disambiguate the sentences’ structure. Gazes to an OVS or SVO picture during the unfolding of a sentence were assumed to indicate prediction of the structure congruent with that picture. According to this measure, the PWA’s structural prediction was impaired compared to controls, but they did successfully predict upcoming structure when morphosyntactic cues were strong and unambiguous. Hanne et al.’s visual-world evidence is suggestive, but their forced-choice sentence-picture matching task places tight constraints on possible structural predictions. Clearer evidence of structural prediction would come from paradigms where the content of upcoming material is not as constrained. The current study used self-paced reading study to examine structural prediction among PWA in less constrained contexts. PWA (n=17 who

  14. Predicting geomagnetic activity indices

    International Nuclear Information System (INIS)

    Complete text of publication follows. Magnetically active times, e.g., Kp > 5, are notoriously difficult to predict, precisely the times when such predictions are crucial to the space weather users. Taking advantage of the routinely available solar wind measurements at Lagrangian point (L1) and nowcast Kps, Kp and Dst forecast models based on neural networks were developed with the focus on improving the forecast for active times. To satisfy different needs and operational constraints, three models were developed: (1) a model that inputs nowcast Kp and solar wind parameters and predicts Kp 1 hr ahead; (2) a model with the same input as model 1 and predicts Kp 4 hr ahead; and (3) a model that inputs only solar wind parameters and predicts Kp 1 hr ahead (the exact prediction lead time depends on the solar wind speed and the location of the solar wind monitor.) Extensive evaluations of these models and other major operational Kp forecast models show that, while the new models can predict Kps more accurately for all activities, the most dramatic improvements occur for moderate and active times. Similar Dst models were developed. Information dynamics analysis of Kp, suggests that geospace is more dominated by internal dynamics near solar minimum than near solar maximum, when it is more directly driven by external inputs, namely solar wind and interplanetary magnetic field (IMF).

  15. On Prediction of EOP

    CERN Document Server

    Malkin, Z

    2009-01-01

    Two methods of prediction of the Pole coordinates and TAI-UTC were tested -- extrapolation of the deterministic components and ARIMA. It was found that each of these methods is most effective for certain length of prognosis. For short-time prediction ARIMA algorithm yields more accurate prognosis, and for long-time one extrapolation is preferable. So, the combined algorithm is being used in practice of IAA EOP Service. The accuracy of prognosis is close to accuracy of IERS algorithms. For prediction of nutation the program KSV-1996-1 by T. Herring is being used.

  16. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

    Edriss, Vahid; Cericola, Fabio; Jensen, Jens D;

    Genomic prediction uses markers (SNPs) across the whole genome to predict individual breeding values at an early growth stage potentially before large scale phenotyping. One of the applications of genomic prediction in plant breeding is to identify the best individual candidate lines to contribute...... to next generation. The main goal of this study was to see the potential of using genomic prediction in a commercial Barley breeding program. The data used in this study was from Nordic Seed company which is located in Denmark. Around 350 advanced lines were genotyped with 9K Barely chip from...... Illumina. Traits used in this study were grain yield, plant height and heading date. Heading date is number days it takes after 1st June for plant to head. Heritabilities were 0.33, 0.44 and 0.48 for yield, height and heading, respectively for the average of nine plots. The GBLUP model was used for genomic...

  17. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

    Edriss, Vahid; Cericola, Fabio; Jensen, Jens D;

    2015-01-01

    Genomic prediction uses markers (SNPs) across the whole genome to predict individual breeding values at an early growth stage potentially before large scale phenotyping. One of the applications of genomic prediction in plant breeding is to identify the best individual candidate lines to contribute...... to next generation. The main goal of this study was to see the potential of using genomic prediction in a commercial Barley breeding program. The data used in this study was from Nordic Seed company which is located in Denmark. Around 350 advanced lines were genotyped with 9K Barely chip from...... Illumina. Traits used in this study were grain yield, plant height and heading date. Heading date is number days it takes after 1st June for plant to head. Heritabilities were 0.33, 0.44 and 0.48 for yield, height and heading, respectively for the average of nine plots. The GBLUP model was used for genomic...

  18. Predicted value of $0 \\, \

    CERN Document Server

    Maedan, Shinji

    2016-01-01

    Assuming that the lightest neutrino mass $ m_0 $ is measured, we study the influence of error of the measured $ m_0 $ on the uncertainty of the predicted value of the neutrinoless double beta decay ($0 \\, \

  19. Predictable grammatical constructions

    DEFF Research Database (Denmark)

    Lucas, Sandra

    2015-01-01

    My aim in this paper is to provide evidence from diachronic linguistics for the view that some predictable units are entrenched in grammar and consequently in human cognition, in a way that makes them functionally and structurally equal to nonpredictable grammatical units, suggesting that these...... predictable units should be considered grammatical constructions on a par with the nonpredictable constructions. Frequency has usually been seen as the only possible argument speaking in favor of viewing some formally and semantically fully predictable units as grammatical constructions. However, this paper...... semantically and formally predictable. Despite this difference, [méllo INF], like the other future periphrases, seems to be highly entrenched in the cognition (and grammar) of Early Medieval Greek language users, and consequently a grammatical construction. The syntactic evidence speaking in favor of [méllo...

  20. Robust Distributed Online Prediction

    CERN Document Server

    Dekel, Ofer; Shamir, Ohad; Xiao, Lin

    2010-01-01

    The standard model of online prediction deals with serial processing of inputs by a single processor. However, in large-scale online prediction problems, where inputs arrive at a high rate, an increasingly common necessity is to distribute the computation across several processors. A non-trivial challenge is to design distributed algorithms for online prediction, which maintain good regret guarantees. In \\cite{DMB}, we presented the DMB algorithm, which is a generic framework to convert any serial gradient-based online prediction algorithm into a distributed algorithm. Moreover, its regret guarantee is asymptotically optimal for smooth convex loss functions and stochastic inputs. On the flip side, it is fragile to many types of failures that are common in distributed environments. In this companion paper, we present variants of the DMB algorithm, which are resilient to many types of network failures, and tolerant to varying performance of the computing nodes.

  1. Nuclear level density predictions

    OpenAIRE

    Bucurescu Dorel; von Egidy Till

    2015-01-01

    Simple formulas depending only on nuclear masses were previously proposed for the parameters of the Back-Shifted Fermi Gas (BSFG) model and of the Constant Temperature (CT) model of the nuclear level density, respectively. They are now applied for the prediction of the level density parameters of all nuclei with available masses. Both masses from the new 2012 mass table and from different models are considered and the predictions are discussed in connection with nuclear regions most affected ...

  2. Predictive graph mining

    OpenAIRE

    Karwath, Andreas; De Raedt, Luc

    2004-01-01

    Graph mining approaches are extremely popular and effective in molecular databases. The vast majority of these approaches first derive interesting, i.e. frequent, patterns and then use these as features to build predictive models. Rather than building these models in a two step indirect way, the SMIREP system introduced in this paper, derives predictive rule models from molecular data directly. SMIREP combines the SMILES and SMARTS representation languages that are popular in computational ch...

  3. Operational Dust Prediction

    Science.gov (United States)

    Benedetti, Angela; Baldasano, Jose M.; Basart, Sara; Benincasa, Francesco; Boucher, Olivier; Brooks, Malcolm E.; Chen, Jen-Ping; Colarco, Peter R.; Gong, Sunlin; Huneeus, Nicolas; Jones, Luke; Lu, Sarah; Menut, Laurent; Morcrette, Jean-Jacques; Mulcahy, Jane; Nickovic, Slobodan; Garcia-Pando, Carlos P.; Reid, Jeffrey S.; Sekiyama, Thomas T.; Tanaka, Taichu Y.; Terradellas, Enric; Westphal, Douglas L.; Zhang, Xiao-Ye; Zhou, Chun-Hong

    2014-01-01

    Over the last few years, numerical prediction of dust aerosol concentration has become prominent at several research and operational weather centres due to growing interest from diverse stakeholders, such as solar energy plant managers, health professionals, aviation and military authorities and policymakers. Dust prediction in numerical weather prediction-type models faces a number of challenges owing to the complexity of the system. At the centre of the problem is the vast range of scales required to fully account for all of the physical processes related to dust. Another limiting factor is the paucity of suitable dust observations available for model, evaluation and assimilation. This chapter discusses in detail numerical prediction of dust with examples from systems that are currently providing dust forecasts in near real-time or are part of international efforts to establish daily provision of dust forecasts based on multi-model ensembles. The various models are introduced and described along with an overview on the importance of dust prediction activities and a historical perspective. Assimilation and evaluation aspects in dust prediction are also discussed.

  4. Aircraft noise prediction

    Science.gov (United States)

    Filippone, Antonio

    2014-07-01

    This contribution addresses the state-of-the-art in the field of aircraft noise prediction, simulation and minimisation. The point of view taken in this context is that of comprehensive models that couple the various aircraft systems with the acoustic sources, the propagation and the flight trajectories. After an exhaustive review of the present predictive technologies in the relevant fields (airframe, propulsion, propagation, aircraft operations, trajectory optimisation), the paper addresses items for further research and development. Examples are shown for several airplanes, including the Airbus A319-100 (CFM engines), the Bombardier Dash8-Q400 (PW150 engines, Dowty R408 propellers) and the Boeing B737-800 (CFM engines). Predictions are done with the flight mechanics code FLIGHT. The transfer function between flight mechanics and the noise prediction is discussed in some details, along with the numerical procedures for validation and verification. Some code-to-code comparisons are shown. It is contended that the field of aircraft noise prediction has not yet reached a sufficient level of maturity. In particular, some parametric effects cannot be investigated, issues of accuracy are not currently addressed, and validation standards are still lacking.

  5. Solar Cycle Prediction

    CERN Document Server

    Petrovay, K

    2010-01-01

    A review of solar cycle prediction methods and their performance is given, including forecasts for cycle 24 and focusing on aspects of the solar cycle prediction problem that have a bearing on dynamo theory. The scope of the review is further restricted to the issue of predicting the amplitude (and optionally the epoch) of an upcoming solar maximum no later than right after the start of the given cycle. Prediction methods form three main groups. Precursor methods rely on the value of some measure of solar activity or magnetism at a specified time to predict the amplitude of the following solar maximum. Their implicit assumption is that each numbered solar cycle is a consistent unit in itself, while solar activity seems to consist of a series of much less tightly intercorrelated individual cycles. Extrapolation methods, in contrast, are based on the premise that the physical process giving rise to the sunspot number record is statistically homogeneous, i.e., the mathematical regularities underlying its variati...

  6. Essays on Earnings Predictability

    DEFF Research Database (Denmark)

    Bruun, Mark

    This dissertation addresses the prediction of corporate earnings. The thesis aims to examine whether the degree of precision in earnings forecasts can be increased by basing them on historical financial ratios. Furthermore, the intent of the dissertation is to analyze whether accounting standards...... forecasts are not more accurate than the simpler forecasts based on a historical timeseries of earnings. Secondly, the dissertation shows how accounting standards affect analysts’ earnings predictions. Accounting conservatism contributes to a more volatile earnings process, which lowers the accuracy of...... analysts’ earnings forecasts. Furthermore, the dissertation shows how the stock market’s reaction to the disclosure of information about corporate earnings depends on how well corporate earnings can be predicted. The dissertation indicates that the stock market’s reaction to the disclosure of earnings...

  7. Neurological abnormalities predict disability

    DEFF Research Database (Denmark)

    Poggesi, Anna; Gouw, Alida; van der Flier, Wiesje;

    2014-01-01

    To investigate the role of neurological abnormalities and magnetic resonance imaging (MRI) lesions in predicting global functional decline in a cohort of initially independent-living elderly subjects. The Leukoaraiosis And DISability (LADIS) Study, involving 11 European centres, was primarily aimed...... at evaluating age-related white matter changes (ARWMC) as an independent predictor of the transition to disability (according to Instrumental Activities of Daily Living scale) or death in independent elderly subjects that were followed up for 3 years. At baseline, a standardized neurological examination...... abnormality independently predicted transition to disability or death [HR (95 % CI) 1.53 (1.01-2.34)]. The hazard increased with increasing number of abnormalities. Among MRI lesions, only ARWMC of severe grade independently predicted disability or death [HR (95 % CI) 2.18 (1.37-3.48)]. In our cohort...

  8. Prediction model Perla

    International Nuclear Information System (INIS)

    Prediction model Perla presents one of a tool for an evaluation of a stream ecological status. It enables a comparing with a standard. The standard is formed by a dataset of sites from all area of the Czech Republic. The sites were influenced by a human activity as few as possible. 8 variables were used for prediction (distance from source, elevation, stream width and depth, slope, substrate roughness, longitude and latitude. All of them were statistically important for benthic communities. Results do not response ecoregions, but rather stream size (type). B (EQItaxonu), EQISi, EQIASPT a EQIH appears applicable for assessment using the prediction model and for natural and human stress differentiating. Limiting values of the indices for good ecological status are suggested. On the contrary, using of EQIEPT a EQIekoprof indices would be possible only with difficulties. (authors)

  9. Permeability prediction in chalks

    DEFF Research Database (Denmark)

    Alam, Mohammad Monzurul; Fabricius, Ida Lykke; Prasad, Manika

    2011-01-01

    The velocity of elastic waves is the primary datum available for acquiring information about subsurface characteristics such as lithology and porosity. Cheap and quick (spatial coverage, ease of measurement) information of permeability can be achieved, if sonic velocity is used for permeability...... prediction, so we have investigated the use of velocity data to predict permeability. The compressional velocity fromwireline logs and core plugs of the chalk reservoir in the South Arne field, North Sea, has been used for this study. We compared various methods of permeability prediction from velocities....... The relationships between permeability and porosity from core data were first examined using Kozeny’s equation. The data were analyzed for any correlations to the specific surface of the grain, Sg, and to the hydraulic property defined as the flow zone indicator (FZI). These two methods use two...

  10. Partially predictable chaos

    CERN Document Server

    Wernecke, Hendrik; Gros, Claudius

    2016-01-01

    For a chaotic system pairs of initially close-by trajectories become eventually fully uncorrelated on the attracting set. This process of decorrelation is split into an initial decrease characterized by the maximal Lyapunov exponent and a subsequent diffusive process on the chaotic attractor causing the final loss of predictability. The time scales of both processes can be either of the same or of very different orders of magnitude. In the latter case the two trajectories linger within a finite but small distance (with respect to the overall size of the attractor) for exceedingly long times and therefore remain partially predictable. We introduce a 0-1 indicator for chaos capable of describing this scenario, arguing, in addition, that the chaotic closed braids found close to a period-doubling transition are generically partially predictable.

  11. Predicting the Sunspot Cycle

    Science.gov (United States)

    Hathaway, David H.

    2009-01-01

    The 11-year sunspot cycle was discovered by an amateur astronomer in 1844. Visual and photographic observations of sunspots have been made by both amateurs and professionals over the last 400 years. These observations provide key statistical information about the sunspot cycle that do allow for predictions of future activity. However, sunspots and the sunspot cycle are magnetic in nature. For the last 100 years these magnetic measurements have been acquired and used exclusively by professional astronomers to gain new information about the nature of the solar activity cycle. Recently, magnetic dynamo models have evolved to the stage where they can assimilate past data and provide predictions. With the advent of the Internet and open data policies, amateurs now have equal access to the same data used by professionals and equal opportunities to contribute (but, alas, without pay). This talk will describe some of the more useful prediction techniques and reveal what they say about the intensity of the upcoming sunspot cycle.

  12. Epitope prediction methods

    DEFF Research Database (Denmark)

    Karosiene, Edita

    introduces the NetMHCIIpan-3.0 predictor based on artificial neural networks, which is capable of giving binding affinities to any human MHC class II molecule. Chapter 4 of this thesis gives an overview of bioinformatics tools developed by the Immunological Bioinformatics group at Center for Biological...... machine learning techniques. Several MHC class I binding prediction algorithms have been developed and due to their high accuracy they are used by many immunologists to facilitate the conventional experimental process of epitope discovery. However, the accuracy of these methods depends on data defining...... the MHC molecule in question, making it difficult for the non-expert end-user to choose the most suitable predictor. The first paper in this thesis presents a new, publicly available, consensus method for MHC class I predictions. The NetMHCcons predictor combines three state-of-the-art prediction...

  13. Scorecard on weather predictions

    Science.gov (United States)

    Richman, Barbara T.

    No matter that several northern and eastern states were pelted by snow and sleet early in March, as far as longterm weather forecasters are concerned, winter ended on February 28. Now is the time to review their winter seasonal forecasts to determine how accurate were those predictions issued at the start of winter.The National Weather Service (NWS) predicted on November 27, 1981, that the winter season would bring colder-than-normal temperatures to the eastern half of the United States, while temperatures were expected to be higher than normal in the westernmost section (see Figure 1). The NWS made no prediction for the middle of the country, labeling the area ‘indeterminate,’ or having the same chance of experiencing above-normal temperatures as below-normal temperatures, explained Donald L. Gilman, chief of the NWS long-range forecasting group.

  14. PREDICTION OF RECESSION

    OpenAIRE

    Lee, Young Sub; Zhu, Qian

    2010-01-01

    The purpose of our research is to examine the predictive power of inverted yield curve for the recession in the near future. The data used in this research are between Jan 1, 1959 to Nov, 2008. There are 8 recessions during this period, including current one. We conducted two sets of tests. The first set consists of spread between 10-year Treasury bond and 3-month Treasury bill and spread between 10-year Treasury bond and 3-month LIBOR; and we find the predictive power of spread between 10-ye...

  15. Linguistic Structure Prediction

    CERN Document Server

    Smith, Noah A

    2011-01-01

    A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. W

  16. Atmospheric predictability revisited

    Directory of Open Access Journals (Sweden)

    Lizzie S. R. Froude

    2013-06-01

    Full Text Available This article examines the potential to improve numerical weather prediction (NWP by estimating upper and lower bounds on predictability by re-visiting the original study of Lorenz (1982 but applied to the most recent version of the European Centre for Medium Range Weather Forecasts (ECMWF forecast system, for both the deterministic and ensemble prediction systems (EPS. These bounds are contrasted with an older version of the same NWP system to see how they have changed with improvements to the NWP system. The computations were performed for the earlier seasons of DJF 1985/1986 and JJA 1986 and the later seasons of DJF 2010/2011 and JJA 2011 using the 500-hPa geopotential height field. Results indicate that for this field, we may be approaching the limit of deterministic forecasting so that further improvements might only be obtained by improving the initial state. The results also show that predictability calculations with earlier versions of the model may overestimate potential forecast skill, which may be due to insufficient internal variability in the model and because recent versions of the model are more realistic in representing the true atmospheric evolution. The same methodology is applied to the EPS to calculate upper and lower bounds of predictability of the ensemble mean forecast in order to explore how ensemble forecasting could extend the limits of the deterministic forecast. The results show that there is a large potential to improve the ensemble predictions, but for the increased predictability of the ensemble mean, there will be a trade-off in information as the forecasts will become increasingly smoothed with time. From around the 10-d forecast time, the ensemble mean begins to converge towards climatology. Until this point, the ensemble mean is able to predict the main features of the large-scale flow accurately and with high consistency from one forecast cycle to the next. By the 15-d forecast time, the ensemble mean has lost

  17. Is genetic evolution predictable?

    Science.gov (United States)

    Stern, David L; Orgogozo, Virginie

    2009-02-01

    Ever since the integration of Mendelian genetics into evolutionary biology in the early 20th century, evolutionary geneticists have for the most part treated genes and mutations as generic entities. However, recent observations indicate that all genes are not equal in the eyes of evolution. Evolutionarily relevant mutations tend to accumulate in hotspot genes and at specific positions within genes. Genetic evolution is constrained by gene function, the structure of genetic networks, and population biology. The genetic basis of evolution may be predictable to some extent, and further understanding of this predictability requires incorporation of the specific functions and characteristics of genes into evolutionary theory. PMID:19197055

  18. RETAIL BANKRUPTCY PREDICTION

    Directory of Open Access Journals (Sweden)

    Johnny Pang

    2013-01-01

    Full Text Available This study reintroduces the famous discriminant functions from Edward Altman and Begley, Ming and Watts (BMW that were used to predict bankrupts. We will formulate three new discriminant functions which differ from Altman’s and BMW’s re-estimated Altman model. Altman’s models as well as Begley, Ming and Watts’s re-estimated Altman model apply to publicly traded industries, whereas the new models formulated in this study are based on retail companies. The three new functions will provide better predictions on retail bankruptcy and they will minimize the chance of misclassifications.

  19. Prediction method abstracts

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-12-31

    This conference was held December 4--8, 1994 in Asilomar, California. The purpose of this meeting was to provide a forum for exchange of state-of-the-art information concerning the prediction of protein structure. Attention if focused on the following: comparative modeling; sequence to fold assignment; and ab initio folding.

  20. PREDICTION OF OVULATION

    Institute of Scientific and Technical Information of China (English)

    LIUYong; CHENSu-Ru; ZHOUJin-Ting; LIUJi-Ying

    1989-01-01

    The purpose or this research is: I) to observe the secretory pattern of five reproductive hormones in Chinese women with normal menstrual cyclcs, especially at the prc-ovulatory peroid; 2) to study whether urinary LH measurement could be used instead of serum LH measurement; 3) to evaluate the significance of LH-EIA kit (Right-Day) for ovulation prediction.

  1. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

    Jørgensen, Claus Bjørn; Suetens, Sigrid; Tyran, Jean-Robert

    numbers based on recent drawings. While most players pick the same set of numbers week after week without regards of numbers drawn or anything else, we find that those who do change, act on average in the way predicted by the law of small numbers as formalized in recent behavioral theory. In particular...

  2. Gate valve performance prediction

    International Nuclear Information System (INIS)

    The Electric Power Research Institute is carrying out a program to improve the performance prediction methods for motor-operated valves. As part of this program, an analytical method to predict the stem thrust required to stroke a gate valve has been developed and has been assessed against data from gate valve tests. The method accounts for the loads applied to the disc by fluid flow and for the detailed mechanical interaction of the stem, disc, guides, and seats. To support development of the method, two separate-effects test programs were carried out. One test program determined friction coefficients for contacts between gate valve parts by using material specimens in controlled environments. The other test program investigated the interaction of the stem, disc, guides, and seat using a special fixture with full-sized gate valve parts. The method has been assessed against flow-loop and in-plant test data. These tests include valve sizes from 3 to 18 in. and cover a considerable range of flow, temperature, and differential pressure. Stem thrust predictions for the method bound measured results. In some cases, the bounding predictions are substantially higher than the stem loads required for valve operation, as a result of the bounding nature of the friction coefficients in the method

  3. Prediction in OLAP Cube

    Directory of Open Access Journals (Sweden)

    Abdellah Sair

    2012-05-01

    Full Text Available Data warehouses are now offering an adequate solution for managing large volumes of data. Online analysis supports OLAP data warehouses in the process of decision support and visualization tools offer, structure and operation of data warehouse. On the other hand, data mining allows the extraction of knowledge with technical description, classification, explanation and prediction. It is therefore possible to better understand the data by coupling on-line analysis with data mining through a unified analysis process. Continuing the work of R. Ben Messaoud, where exploitation of the coupling of on-line analysis and data mining focuses on the description, visualization, classification and explanation, we propose extending the OLAP prediction capabilities. To integrate the prediction in the heart of OLAP, an approach based on automatic learning with regression trees is proposed in order to predict the value of an aggregate or a measure. We will try to express our approach using data from a service management reviews to know that it would be the average obtained by the students if we open a new module, for a department at a certain criterion.

  4. Polarization predictions for LEAR

    International Nuclear Information System (INIS)

    Large polarization properties have recently been experimentally found in quasi-two-body reactions. From these results, the additive quark model and assumptions on the relative size of some participant matrix elements (which will be motivated elsewhere as properties of colour confinement), we present prediction for the reactions pp- to YY-. (Author)

  5. Vertebral Fracture Prediction

    DEFF Research Database (Denmark)

    2008-01-01

    Vertebral Fracture Prediction A method of processing data derived from an image of at least part of a spine is provided for estimating the risk of a future fracture in vertebraeof the spine. Position data relating to at least four neighbouring vertebrae of the spine is processed. The curvature of...

  6. Chloride ingress prediction

    DEFF Research Database (Denmark)

    Frederiksen, Jens Mejer; Geiker, Mette Rica

    2008-01-01

    Prediction of chloride ingress into concrete is an important part of durability design of reinforced concrete structures exposed to chloride containing environment. This paper presents experimentally based design parameters for Portland cement concretes with and without silica fume and fly ash in...

  7. Prediction of resonant oscillation

    DEFF Research Database (Denmark)

    2010-01-01

    The invention relates to methods for prediction of parametric rolling of vessels. The methods are based on frequency domain and time domain information in order do set up a detector able to trigger an alarm when parametric roll is likely to occur. The methods use measurements of e.g. pitch and roll...

  8. Prediction of regulatory elements

    DEFF Research Database (Denmark)

    Sandelin, Albin

    2008-01-01

    -lab methods are time consuming and expensive, it is not realistic to identify TFBS for all uncharacterized genes in the genome by purely experimental means. Computational methods aimed at predicting potential regulatory regions can increase the efficiency of wet-lab experiments significantly. Here, methods...

  9. Predictive models in urology.

    Science.gov (United States)

    Cestari, Andrea

    2013-01-01

    Predictive modeling is emerging as an important knowledge-based technology in healthcare. The interest in the use of predictive modeling reflects advances on different fronts such as the availability of health information from increasingly complex databases and electronic health records, a better understanding of causal or statistical predictors of health, disease processes and multifactorial models of ill-health and developments in nonlinear computer models using artificial intelligence or neural networks. These new computer-based forms of modeling are increasingly able to establish technical credibility in clinical contexts. The current state of knowledge is still quite young in understanding the likely future direction of how this so-called 'machine intelligence' will evolve and therefore how current relatively sophisticated predictive models will evolve in response to improvements in technology, which is advancing along a wide front. Predictive models in urology are gaining progressive popularity not only for academic and scientific purposes but also into the clinical practice with the introduction of several nomograms dealing with the main fields of onco-urology. PMID:23423686

  10. Predicting coronary heart disease

    DEFF Research Database (Denmark)

    Sillesen, Henrik; Fuster, Valentin

    2012-01-01

    Atherosclerosis is the leading cause of death and disabling disease. Whereas risk factors are well known and constitute therapeutic targets, they are not useful for prediction of risk of future myocardial infarction, stroke, or death. Therefore, methods to identify atherosclerosis itself have bee...

  11. Predicting Intrinsic Motivation

    Science.gov (United States)

    Martens, Rob; Kirschner, Paul A.

    2004-01-01

    Intrinsic motivation can be predicted from participants' perceptions of the social environment and the task environment (Ryan & Deci, 2000)in terms of control, relatedness and competence. To determine the degree of independence of these factors 251 students in higher vocational education (physiotherapy and hotel management) indicated the extent to…

  12. Predicting Lotto Numbers

    NARCIS (Netherlands)

    Jorgensen, C.B.; Suetens, S.; Tyran, J.R.

    2011-01-01

    We investigate the "law of small numbers" using a unique panel data set on lotto gambling. Because we can track individual players over time, we can measure how they react to outcomes of recent lotto drawings. We can therefore test whether they behave as if they believe they can predict lotto number

  13. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

    Suetens, Sigrid; Galbo-Jørgensen, Claus B.; Tyran, Jean-Robert Karl

    2016-01-01

    We investigate the ‘law of small numbers’ using a data set on lotto gambling that allows us to measure players’ reactions to draws. While most players pick the same set of numbers week after week, we find that those who do change react on average as predicted by the law of small numbers as...

  14. Autocrine regulation of human sperm motility by tachykinins

    Directory of Open Access Journals (Sweden)

    Pinto Francisco M

    2010-08-01

    Full Text Available Abstract Background We examined the presence and function of tachykinins and the tachykinin-degrading enzymes neprilysin (NEP and neprilysin-2 (NEP2 in human spermatozoa. Methods Freshly ejaculated semen was collected from forty-eight normozoospermic human donors. We analyzed the expression of substance P, neurokinin A, neurokinin B, hemokinin-1, NEP and NEP2 in sperm cells by reverse-transcriptase polymerase chain reaction (RT-PCR, western blot and immunocytochemistry assays and evaluated the effects of the neprilysin and neprilysin-2 inhibitor phosphoramidon on sperm motility in the absence and presence of tachykinin receptor-selective antagonists. Sperm motility was measured using WHO procedures or computer-assisted sperm analysis (CASA. Results The mRNAs of the genes that encode substance P/neurokinin A (TAC1, neurokinin B (TAC3, hemokinin-1 (TAC4, neprilysin (MME and neprilysin-2 (MMEL1 were expressed in human sperm. Immunocytochemistry studies revealed that tachykinin and neprilysin proteins were present in spermatozoa and show specific and differential distributions. Phosphoramidon increased sperm progressive motility and its effects were reduced in the presence of the tachykinin receptor antagonists SR140333 (NK1 receptor-selective and SR48968 (NK2 receptor-selective but unmodified in the presence of SR142801 (NK3 receptor-selective. Conclusion These data show that tachykinins are present in human spermatozoa and participate in the regulation of sperm motility. Tachykinin activity is regulated, at least in part, by neprilysins.

  15. Autocrine effects of visfatin on hepatocyte sensitivity to insulin action

    Czech Academy of Sciences Publication Activity Database

    Škop, V.; Kontrová, K.; Zídek, Václav; Pravenec, Michal; Kazdová, L.; Mikulík, Karel; Sajdok, J.; Zídková, J.

    2010-01-01

    Roč. 59, č. 4 (2010), s. 615-618. ISSN 0862-8408 R&D Projects: GA AV ČR(CZ) IAA500110805; GA MŠk(CZ) ME08006; GA MZd(CZ) NR9387; GA MZd(CZ) NR9359 Institutional research plan: CEZ:AV0Z50110509; CEZ:AV0Z50200510 Keywords : Visfatin * RNA interference * insulin mimetic effects Subject RIV: FB - Endocrinology, Diabetology, Metabolism, Nutrition Impact factor: 1.646, year: 2010

  16. Proepithelin is an autocrine growth factor for bladder cancer

    OpenAIRE

    Lovat, Francesca; Bitto, Alessandro; Xu, Shi-Qiong; Fassan, Matteo; Goldoni, Silvia; Metalli, David; Wubah, Vera; McCue, Peter; Serrero, Ginette; Gomella, Leonard G.; Baffa, Raffaele; Iozzo, Renato V.; Morrione, Andrea

    2009-01-01

    The growth factor proepithelin functions as an important regulator of proliferation and motility. Proepithelin is overexpressed in a great variety of cancer cell lines and clinical specimens of breast, ovarian and renal cancer, as well as glioblastomas. Using recombinant proepithelin on 5637 transitional cell carcinoma-derived cells, we have shown previously that proepithelin plays a critical role in bladder cancer by promoting motility of bladder cancer cells. In this study, we used the ONCO...

  17. Theileria parva infection induces autocrine growth of bovine lymphocytes.

    OpenAIRE

    Dobbelaere, D A; Coquerelle, T M; Roditi, I J; Eichhorn, M; Williams, R O

    1988-01-01

    Bovine lymphocytes infected with the parasite Theileria parva continuously secrete a growth factor that is essential for their proliferation in vitro and also constitutively express interleukin 2 receptors on their surface. Dilution of the secreted growth factor, caused by culturing cells at low density, results in retardation of culture growth. Human recombinant interleukin 2, however, effectively substitutes for the diluted growth factor by restoring normal growth rates and also allows Thei...

  18. Neuronal, neurohormonal, and autocrine control of Xenopus melanotrope cell activity

    NARCIS (Netherlands)

    Roubos, E.W.; Scheenen, W.J.J.M.; Jenks, B.G.

    2005-01-01

    Amphibian pituitary melanotropes are used to investigate principles of neuroendocrine translation of neural input into hormonal output. Here, the steps in this translation process are outlined for the melanotrope cell of Xenopus laevis, with attention to external stimuli, neurochemical messengers, r

  19. Predicting Major Solar Eruptions

    Science.gov (United States)

    Kohler, Susanna

    2016-05-01

    Coronal mass ejections (CMEs) and solar flares are two examples of major explosions from the surface of the Sun but theyre not the same thing, and they dont have to happen at the same time. A recent study examines whether we can predict which solar flares will be closely followed by larger-scale CMEs.Image of a solar flare from May 2013, as captured by NASAs Solar Dynamics Observatory. [NASA/SDO]Flares as a Precursor?A solar flare is a localized burst of energy and X-rays, whereas a CME is an enormous cloud of magnetic flux and plasma released from the Sun. We know that some magnetic activity on the surface of the Sun triggers both a flare and a CME, whereas other activity only triggers a confined flare with no CME.But what makes the difference? Understanding this can help us learn about the underlying physical drivers of flares and CMEs. It also might help us to better predict when a CME which can pose a risk to astronauts, disrupt radio transmissions, and cause damage to satellites might occur.In a recent study, Monica Bobra and Stathis Ilonidis (Stanford University) attempt to improve our ability to make these predictions by using a machine-learning algorithm.Classification by ComputerUsing a combination of 6 or more features results in a much better predictive success (measured by the True Skill Statistic; higher positive value = better prediction) for whether a flare will be accompanied by a CME. [Bobra Ilonidis 2016]Bobra and Ilonidis used magnetic-field data from an instrument on the Solar Dynamics Observatory to build a catalog of solar flares, 56 of which were accompanied by a CME and 364 of which were not. The catalog includes information about 18 different features associated with the photospheric magnetic field of each flaring active region (for example, the mean gradient of the horizontal magnetic field).The authors apply a machine-learning algorithm known as a binary classifier to this catalog. This algorithm tries to predict, given a set of features

  20. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik;

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines the...

  1. Predicting Anthracycline Benefit

    DEFF Research Database (Denmark)

    Bartlett, John M S; McConkey, Christopher C; Munro, Alison F;

    2015-01-01

    PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite as...... measured with a centromere enumeration probe (CEP17) predicted sensitivity to anthracyclines, we report here an individual patient-level pooled analysis of data from five trials comparing anthracycline-based chemotherapy with CMF (cyclophosphamide, methotrexate, and fluorouracil) as adjuvant chemotherapy...... for early breast cancer. PATIENTS AND METHODS: Fluorescent in situ hybridization for CEP17, HER2, and TOP2A was performed in three laboratories on samples from 3,846 of 4,864 eligible patients from five trials evaluating anthracycline-containing chemotherapy versus CMF. Methodologic differences did...

  2. STRATEGY PATTERNS PREDICTION MODEL

    Directory of Open Access Journals (Sweden)

    Aram Baruch Gonzalez Perez

    2014-01-01

    Full Text Available Multi-agent systems are broadly known for being able to simulate real-life situations which require the interaction and cooperation of individuals. Opponent modeling can be used along with multi-agent systems to model complex situations such as competitions like soccer games. In this study, a model for predicting opponent moves based on their target is presented. The model is composed by an offline step (learning phase and an online one (execution phase. The offline step gets and analyses previous experiences while the online step uses the data generated by offline analysis to predict opponent moves. This model is illustrated by an experiment with the RoboCup 2D Soccer Simulator. The proposed model was tested using 22 games to create the knowledge base and getting an accuracy rate over 80%.

  3. Chaos detection and predictability

    CERN Document Server

    Gottwald, Georg; Laskar, Jacques

    2016-01-01

    Distinguishing chaoticity from regularity in deterministic dynamical systems and specifying the subspace of the phase space in which instabilities are expected to occur is of utmost importance in as disparate areas as astronomy, particle physics and climate dynamics.   To address these issues there exists a plethora of methods for chaos detection and predictability. The most commonly employed technique for investigating chaotic dynamics, i.e. the computation of Lyapunov exponents, however, may suffer a number of problems and drawbacks, for example when applied to noisy experimental data.   In the last two decades, several novel methods have been developed for the fast and reliable determination of the regular or chaotic nature of orbits, aimed at overcoming the shortcomings of more traditional techniques. This set of lecture notes and tutorial reviews serves as an introduction to and overview of modern chaos detection and predictability techniques for graduate students and non-specialists.   The book cover...

  4. Predictability of Critical Transitions

    CERN Document Server

    Zhang, Xiaozhu; Hallerberg, Sarah

    2015-01-01

    Critical transitions in multistable systems have been discussed as models for a variety of phenomena ranging from the extinctions of species to socio-economic changes and climate transitions between ice-ages and warm-ages. From bifurcation theory we can expect certain critical transitions to be preceded by a decreased recovery from external perturbations. The consequences of this critical slowing down have been observed as an increase in variance and autocorrelation prior to the transition. However especially in the presence of noise it is not clear, whether these changes in observation variables are statistically relevant such that they could be used as indicators for critical transitions. In this contribution we investigate the predictability of critical transitions in conceptual models. We study the the quadratic integrate-and-fire model and the van der Pol model, under the influence of external noise. We focus especially on the statistical analysis of the success of predictions and the overall predictabil...

  5. Comparing Spatial Predictions

    KAUST Repository

    Hering, Amanda S.

    2011-11-01

    Under a general loss function, we develop a hypothesis test to determine whether a significant difference in the spatial predictions produced by two competing models exists on average across the entire spatial domain of interest. The null hypothesis is that of no difference, and a spatial loss differential is created based on the observed data, the two sets of predictions, and the loss function chosen by the researcher. The test assumes only isotropy and short-range spatial dependence of the loss differential but does allow it to be non-Gaussian, non-zero-mean, and spatially correlated. Constant and nonconstant spatial trends in the loss differential are treated in two separate cases. Monte Carlo simulations illustrate the size and power properties of this test, and an example based on daily average wind speeds in Oklahoma is used for illustration. Supplemental results are available online. © 2011 American Statistical Association and the American Society for Qualitys.

  6. STRATEGY PATTERNS PREDICTION MODEL

    OpenAIRE

    Aram Baruch Gonzalez Perez; Jorge Adolfo Ramirez Uresti

    2014-01-01

    Multi-agent systems are broadly known for being able to simulate real-life situations which require the interaction and cooperation of individuals. Opponent modeling can be used along with multi-agent systems to model complex situations such as competitions like soccer games. In this study, a model for predicting opponent moves based on their target is presented. The model is composed by an offline step (learning phase) and an online one (execution phase). The offline step gets and analyses p...

  7. The Predictive Audit Framework

    OpenAIRE

    Kuenkaikaew, Siripan; Vasarhelyi, Miklos A.

    2013-01-01

    Assurance is an essential part of the business process of the modern enterprise. Auditing is a widely used assurance method made mandatory for public companies since 1934. The traditional (retroactive) audit provides after-the-fact audit reports, and is of limited value in the ever changing modern business environment because it is slow and backwards looking. Contemporary auditing and monitoring technologies could shorten the audit and assurance time frame. This paper proposes the predictive ...

  8. Multivariate respiratory motion prediction

    International Nuclear Information System (INIS)

    In extracranial robotic radiotherapy, tumour motion is compensated by tracking external and internal surrogates. To compensate system specific time delays, time series prediction of the external optical surrogates is used. We investigate whether the prediction accuracy can be increased by expanding the current clinical setup by an accelerometer, a strain belt and a flow sensor. Four previously published prediction algorithms are adapted to multivariate inputs—normalized least mean squares (nLMS), wavelet-based least mean squares (wLMS), support vector regression (SVR) and relevance vector machines (RVM)—and evaluated for three different prediction horizons. The measurement involves 18 subjects and consists of two phases, focusing on long term trends (M1) and breathing artefacts (M2). To select the most relevant and least redundant sensors, a sequential forward selection (SFS) method is proposed. Using a multivariate setting, the results show that the clinically used nLMS algorithm is susceptible to large outliers. In the case of irregular breathing (M2), the mean root mean square error (RMSE) of a univariate nLMS algorithm is 0.66 mm and can be decreased to 0.46 mm by a multivariate RVM model (best algorithm on average). To investigate the full potential of this approach, the optimal sensor combination was also estimated on the complete test set. The results indicate that a further decrease in RMSE is possible for RVM (to 0.42 mm). This motivates further research about sensor selection methods. Besides the optical surrogates, the sensors most frequently selected by the algorithms are the accelerometer and the strain belt. These sensors could be easily integrated in the current clinical setup and would allow a more precise motion compensation. (paper)

  9. Predictive Game Theory

    Science.gov (United States)

    Wolpert, David H.

    2005-01-01

    Probability theory governs the outcome of a game; there is a distribution over mixed strat.'s, not a single "equilibrium". To predict a single mixed strategy must use our loss function (external to the game's players. Provides a quantification of any strategy's rationality. Prove rationality falls as cost of computation rises (for players who have not previously interacted). All extends to games with varying numbers of players.

  10. Predicting helpful product reviews

    OpenAIRE

    O'Mahony, Michael P.; Cunningham, Pádraig; Smyth, Barry

    2010-01-01

    Millions of users are today posting user-generated content online, expressing their opinions on all manner of goods and services, topics and social affairs. While undoubtedly useful,user-generated content presents consumers with significant challenges in terms of information overload and quality considerations. In this paper, we address these issues in the context of product reviews and present a brief survey of our work to date on predicting review helpfulness. In particular, the performa...

  11. Individualizing fracture risk prediction

    OpenAIRE

    van Geel, Tineke A. C. M.; van den Bergh, Joop P. W.; Dinant, Geert Jan; Geusens, Piet

    2010-01-01

    Low bone mineral density (BMD) and clinical factors (CRF) have been identified as factors associated with an increased relative risk of fractures. From this observation and for clinical decision making, the concept of prediction of the individual absolute risk of fractures has emerged. It refers to the individual's risk for fractures over a certain time period, e.g. the next 5 and 10 years. Two individualized fracture risk calculation tools that are increasingly used and are available on the ...

  12. Predicting appointment breaking.

    Science.gov (United States)

    Bean, A G; Talaga, J

    1995-01-01

    The goal of physician referral services is to schedule appointments, but if too many patients fail to show up, the value of the service will be compromised. The authors found that appointment breaking can be predicted by the number of days to the scheduled appointment, the doctor's specialty, and the patient's age and gender. They also offer specific suggestions for modifying the marketing mix to reduce the incidence of no-shows. PMID:10142384

  13. Thinking about Aid Predictability

    OpenAIRE

    Andrews, Matthew; Wilhelm, Vera

    2008-01-01

    Researchers are giving more attention to aid predictability. In part, this is because of increases in the number of aid agencies and aid dollars and the growing complexity of the aid community. A growing body of research is examining key questions: Is aid unpredictable? What causes unpredictability? What can be done about it? This note draws from a selection of recent literature to bring s...

  14. Time-predictable architectures

    CERN Document Server

    Rochange, Christine; Uhrig , Sascha

    2014-01-01

    Building computers that can be used to design embedded real-time systems is the subject of this title. Real-time embedded software requires increasingly higher performances. The authors therefore consider processors that implement advanced mechanisms such as pipelining, out-of-order execution, branch prediction, cache memories, multi-threading, multicorearchitectures, etc. The authors of this book investigate the timepredictability of such schemes.

  15. Multivariate respiratory motion prediction

    Science.gov (United States)

    Dürichen, R.; Wissel, T.; Ernst, F.; Schlaefer, A.; Schweikard, A.

    2014-10-01

    In extracranial robotic radiotherapy, tumour motion is compensated by tracking external and internal surrogates. To compensate system specific time delays, time series prediction of the external optical surrogates is used. We investigate whether the prediction accuracy can be increased by expanding the current clinical setup by an accelerometer, a strain belt and a flow sensor. Four previously published prediction algorithms are adapted to multivariate inputs—normalized least mean squares (nLMS), wavelet-based least mean squares (wLMS), support vector regression (SVR) and relevance vector machines (RVM)—and evaluated for three different prediction horizons. The measurement involves 18 subjects and consists of two phases, focusing on long term trends (M1) and breathing artefacts (M2). To select the most relevant and least redundant sensors, a sequential forward selection (SFS) method is proposed. Using a multivariate setting, the results show that the clinically used nLMS algorithm is susceptible to large outliers. In the case of irregular breathing (M2), the mean root mean square error (RMSE) of a univariate nLMS algorithm is 0.66 mm and can be decreased to 0.46 mm by a multivariate RVM model (best algorithm on average). To investigate the full potential of this approach, the optimal sensor combination was also estimated on the complete test set. The results indicate that a further decrease in RMSE is possible for RVM (to 0.42 mm). This motivates further research about sensor selection methods. Besides the optical surrogates, the sensors most frequently selected by the algorithms are the accelerometer and the strain belt. These sensors could be easily integrated in the current clinical setup and would allow a more precise motion compensation.

  16. Numbers, Predictions and War

    OpenAIRE

    J.W. Grobbelaar

    2012-01-01

    Die subtitel van hierdie boek: 'Using history to evaluate combat forces and predict the outcome of battles', is 'n goeie beskrywing van die ambisieuse oogmerk van die skrywer. In die boek word 'n studie beskryf wat by die Historical Evaluation and Research Organization (afgekort: HERO) onderneem is om 'n wiskundige model daar te stel waarmee die uitkoms van enige veldslag voorspel kan word. As basis tot die studie word twee fundamentele aannames gemaak:

  17. Predicting Human Cooperation

    Science.gov (United States)

    Nay, John J.; Vorobeychik, Yevgeniy

    2016-01-01

    The Prisoner’s Dilemma has been a subject of extensive research due to its importance in understanding the ever-present tension between individual self-interest and social benefit. A strictly dominant strategy in a Prisoner’s Dilemma (defection), when played by both players, is mutually harmful. Repetition of the Prisoner’s Dilemma can give rise to cooperation as an equilibrium, but defection is as well, and this ambiguity is difficult to resolve. The numerous behavioral experiments investigating the Prisoner’s Dilemma highlight that players often cooperate, but the level of cooperation varies significantly with the specifics of the experimental predicament. We present the first computational model of human behavior in repeated Prisoner’s Dilemma games that unifies the diversity of experimental observations in a systematic and quantitatively reliable manner. Our model relies on data we integrated from many experiments, comprising 168,386 individual decisions. The model is composed of two pieces: the first predicts the first-period action using solely the structural game parameters, while the second predicts dynamic actions using both game parameters and history of play. Our model is successful not merely at fitting the data, but in predicting behavior at multiple scales in experimental designs not used for calibration, using only information about the game structure. We demonstrate the power of our approach through a simulation analysis revealing how to best promote human cooperation. PMID:27171417

  18. Eclipse prediction in Mesopotamia.

    Science.gov (United States)

    Steele, J. M.

    2000-02-01

    Among the many celestial phenomena observed in ancient Mesopotamia, eclipses, particularly eclipses of the Moon, were considered to be among the astrologically most significant events. In Babylon, by at least the middle of the seventh century BC, and probably as early as the middle of the eighth century BC, astronomical observations were being systematically conducted and recorded in a group of texts which we have come to call Astronomical Diaries. These Diaries contain many observations and predictions of eclipses. The predictions generally include the expected time of the eclipse, apparently calculated quite precisely. By the last three centuries BC, the Babylonian astronomers had developed highly advanced mathematical theories of the Moon and planets. This paper outlines the various methods which appear to have been formulated by the Mesopotamian astronomers to predict eclipses of the Sun and the Moon. It also considers the question of which of these methods were actually used in compiling the Astronomical Diaries, and speculates why these particular methods were used.

  19. Prediction in projection

    Science.gov (United States)

    Garland, Joshua; Bradley, Elizabeth

    2015-12-01

    Prediction models that capture and use the structure of state-space dynamics can be very effective. In practice, however, one rarely has access to full information about that structure, and accurate reconstruction of the dynamics from scalar time-series data—e.g., via delay-coordinate embedding—can be a real challenge. In this paper, we show that forecast models that employ incomplete reconstructions of the dynamics—i.e., models that are not necessarily true embeddings—can produce surprisingly accurate predictions of the state of a dynamical system. In particular, we demonstrate the effectiveness of a simple near-neighbor forecast technique that works with a two-dimensional time-delay reconstruction of both low- and high-dimensional dynamical systems. Even though correctness of the topology may not be guaranteed for incomplete reconstructions like this, the dynamical structure that they do capture allows for accurate predictions—in many cases, even more accurate than predictions generated using a traditional embedding. This could be very useful in the context of real-time forecasting, where the human effort required to produce a correct delay-coordinate embedding is prohibitive.

  20. Is Suicide Predictable?

    Directory of Open Access Journals (Sweden)

    S Asmaee

    2012-04-01

    Full Text Available Background:The current study aimed to test the hypothesis: Is suicide predictable? And try to classify the predictive factors in multiple suicide attempts.Methods:A cross-sectional study was administered to 223 multiple attempters, women who came to a medical poison centre after a suicide attempt.The participants were young, poor, and single.A Logistic Regression Analiysis was used to classify the predictive factors of suicide.Results:Women who had multiple suicide attempts exhibited a significant tendency to attempt suicide again. They had a history for more than two years of multiple suicide attempts, from three to as many as 18 times, plus mental illnesses such as depression and substance abuse.They also had a positive history of mental illnesses.Conclusion:Results indicate that contributing factors for another suicide attempt include previous suicide attempts, mental illness (depression,or a positive history of mental illnesses in the family affecting them at a young age, and substance abuse.

  1. Aeroacoustic Prediction Codes

    Science.gov (United States)

    Gliebe, P; Mani, R.; Shin, H.; Mitchell, B.; Ashford, G.; Salamah, S.; Connell, S.; Huff, Dennis (Technical Monitor)

    2000-01-01

    This report describes work performed on Contract NAS3-27720AoI 13 as part of the NASA Advanced Subsonic Transport (AST) Noise Reduction Technology effort. Computer codes were developed to provide quantitative prediction, design, and analysis capability for several aircraft engine noise sources. The objective was to provide improved, physics-based tools for exploration of noise-reduction concepts and understanding of experimental results. Methods and codes focused on fan broadband and 'buzz saw' noise and on low-emissions combustor noise and compliment work done by other contractors under the NASA AST program to develop methods and codes for fan harmonic tone noise and jet noise. The methods and codes developed and reported herein employ a wide range of approaches, from the strictly empirical to the completely computational, with some being semiempirical analytical, and/or analytical/computational. Emphasis was on capturing the essential physics while still considering method or code utility as a practical design and analysis tool for everyday engineering use. Codes and prediction models were developed for: (1) an improved empirical correlation model for fan rotor exit flow mean and turbulence properties, for use in predicting broadband noise generated by rotor exit flow turbulence interaction with downstream stator vanes: (2) fan broadband noise models for rotor and stator/turbulence interaction sources including 3D effects, noncompact-source effects. directivity modeling, and extensions to the rotor supersonic tip-speed regime; (3) fan multiple-pure-tone in-duct sound pressure prediction methodology based on computational fluid dynamics (CFD) analysis; and (4) low-emissions combustor prediction methodology and computer code based on CFD and actuator disk theory. In addition. the relative importance of dipole and quadrupole source mechanisms was studied using direct CFD source computation for a simple cascadeigust interaction problem, and an empirical combustor

  2. Disruption prediction at JET

    International Nuclear Information System (INIS)

    The sudden loss of the plasma magnetic confinement, known as disruption, is one of the major issue in a nuclear fusion machine as JET (Joint European Torus). Disruptions pose very serious problems to the safety of the machine. The energy stored in the plasma is released to the machine structure in few milliseconds resulting in forces that at JET reach several Mega Newtons. The problem is even more severe in the nuclear fusion power station where the forces are in the order of one hundred Mega Newtons. The events that occur during a disruption are still not well understood even if some mechanisms that can lead to a disruption have been identified and can be used to predict them. Unfortunately it is always a combination of these events that generates a disruption and therefore it is not possible to use simple algorithms to predict it. This thesis analyses the possibility of using neural network algorithms to predict plasma disruptions in real time. This involves the determination of plasma parameters every few milliseconds. A plasma boundary reconstruction algorithm, XLOC, has been developed in collaboration with Dr. D. O'Brien and Dr. J. Ellis capable of determining the plasma wall/distance every 2 milliseconds. The XLOC output has been used to develop a multilayer perceptron network to determine plasma parameters as li and qψ with which a machine operational space has been experimentally defined. If the limits of this operational space are breached the disruption probability increases considerably. Another approach for prediction disruptions is to use neural network classification methods to define the JET operational space. Two methods have been studied. The first method uses a multilayer perceptron network with softmax activation function for the output layer. This method can be used for classifying the input patterns in various classes. In this case the plasma input patterns have been divided between disrupting and safe patterns, giving the possibility of

  3. On identified predictive control

    Science.gov (United States)

    Bialasiewicz, Jan T.

    1993-01-01

    Self-tuning control algorithms are potential successors to manually tuned PID controllers traditionally used in process control applications. A very attractive design method for self-tuning controllers, which has been developed over recent years, is the long-range predictive control (LRPC). The success of LRPC is due to its effectiveness with plants of unknown order and dead-time which may be simultaneously nonminimum phase and unstable or have multiple lightly damped poles (as in the case of flexible structures or flexible robot arms). LRPC is a receding horizon strategy and can be, in general terms, summarized as follows. Using assumed long-range (or multi-step) cost function the optimal control law is found in terms of unknown parameters of the predictor model of the process, current input-output sequence, and future reference signal sequence. The common approach is to assume that the input-output process model is known or separately identified and then to find the parameters of the predictor model. Once these are known, the optimal control law determines control signal at the current time t which is applied at the process input and the whole procedure is repeated at the next time instant. Most of the recent research in this field is apparently centered around the LRPC formulation developed by Clarke et al., known as generalized predictive control (GPC). GPC uses ARIMAX/CARIMA model of the process in its input-output formulation. In this paper, the GPC formulation is used but the process predictor model is derived from the state space formulation of the ARIMAX model and is directly identified over the receding horizon, i.e., using current input-output sequence. The underlying technique in the design of identified predictive control (IPC) algorithm is the identification algorithm of observer/Kalman filter Markov parameters developed by Juang et al. at NASA Langley Research Center and successfully applied to identification of flexible structures.

  4. Foundations of predictive analytics

    CERN Document Server

    Wu, James

    2012-01-01

    Drawing on the authors' two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas. It also discusses a variety of practical topics that are frequently missing from similar texts. The book begins with the statistical and linear algebra/matrix foundation of modeling methods, from distributions to cumulant and copula functions to Cornish--Fisher expansion and o

  5. Towards Predictive Association Theories

    DEFF Research Database (Denmark)

    Kontogeorgis, Georgios; Tsivintzelis, Ioannis; Michelsen, Michael Locht;

    2011-01-01

    Association equations of state like SAFT, CPA and NRHB have been previously applied to many complex mixtures. In this work we focus on two of these models, the CPA and the NRHB equations of state and the emphasis is on the analysis of their predictive capabilities for a wide range of applications...... phase equilibria in mixtures containing glycols. The importance of considering the solvation of CO2–water (in CPA) when the model is applied to multicomponent mixtures as well as of the multiple associations in heavy glycol–water mixtures (in NRHB) is investigated....

  6. Chloride ingress prediction

    DEFF Research Database (Denmark)

    Frederiksen, Jens Mejer; Geiker, Mette Rica

    Prediction of chloride ingress into concrete is an important part of durability design of reinforced concrete structures exposed to chloride containing environment. This paper presents experimentally based design parameters for Portland cement concretes with and without silica fume and fly ash in...... marine atmospheric and submersed South Scandinavian environment. The design parameters are based on sequential measurements of 86 chloride profiles taken over ten years from 13 different types of concrete. The design parameters provide the input for an analytical model for chloride profiles as function...

  7. Mathematics of Predicting Growth

    OpenAIRE

    Nielsen, Ron W

    2015-01-01

    Abstract. Mathematical methods of analysis of data and of predicting growth are discussed. The starting point is the analysis of the growth rates, which can be expressed as a function of time or as a function of the size of the growing entity. Application of these methods is illustrated using the world economic growth but they can be applied to any type of growth.Keywords. Growth rate, Differential equations, Gross Domestic Product, Economic growth.JEL. C01, C20, C50, C53, C60, C65, C80

  8. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

    Suetens, Sigrid; Galbo-Jørgensen, Claus B.; Tyran, Jean-Robert Karl

    2015-01-01

    formalized in recent behavioral theory. In particular, players tend to bet less on numbers that have been drawn in the preceding week, as suggested by the ‘gambler’s fallacy’, and bet more on a number if it was frequently drawn in the recent past, consistent with the ‘hot-hand fallacy’.......We investigate the ‘law of small numbers’ using a data set on lotto gambling that allows us to measure players’ reactions to draws. While most players pick the same set of numbers week after week, we find that those who do change react on average as predicted by the law of small numbers as...

  9. Asphalt pavement temperature prediction

    OpenAIRE

    Minhoto, Manuel; Pais, Jorge; Pereira, Paulo

    2006-01-01

    A 3-D finite element model (FEM) was developed to calculate the lemperature of an asphtalt rubber pavement localed in the Northeast of Portugal. The goal of the case study presented in this paper is to show the good accuracy temperature prediction tha can be obtained with this model when compared with the field pavement thermal condition obtained during a year. lnput data to the model are the hourly values for solar radiation and temperature and the mean daily value of wind speed obtained fr...

  10. Predicting Sustainable Work Behavior

    DEFF Research Database (Denmark)

    Hald, Kim Sundtoft

    2013-01-01

    Sustainable work behavior is an important issue for operations managers – it has implications for most outcomes of OM. This research explores the antecedents of sustainable work behavior. It revisits and extends the sociotechnical model developed by Brown et al. (2000) on predicting safe behavior....... Employee characteristics and general attitudes towards safety and work condition are included in the extended model. A survey was handed out to 654 employees in Chinese factories. This research contributes by demonstrating how employee- characteristics and general attitudes towards safety and work...... condition influence their sustainable work behavior. A new definition of sustainable work behavior is proposed....

  11. Stress Prediction System

    Science.gov (United States)

    1995-01-01

    NASA wanted to know how astronauts' bodies would react under various gravitational pulls and space suit weights. Under contract to NASA, the University of Michigan's Center for Ergonomics developed a model capable of predicting what type of stress and what degree of load a body could stand. The algorithm generated was commercialized with the ISTU (Isometric Strength Testing Unit) Functional Capacity Evaluation System, which simulates tasks such as lifting a heavy box or pushing a cart and evaluates the exertion expended. It also identifies the muscle group that limits the subject's performance. It is an effective tool of personnel evaluation, selection and job redesign.

  12. Predicting Lotto Numbers

    OpenAIRE

    Jorgensen, C.B.; Suetens, S.; Tyran, J.R.

    2011-01-01

    We investigate the “law of small numbers” using a unique panel data set on lotto gambling. Because we can track individual players over time, we can measure how they react to outcomes of recent lotto drawings. We can therefore test whether they behave as if they believe they can predict lotto numbers based on recent drawings. While most players pick the same set of numbers week after week without regards of numbers drawn or anything else, we find that those who do change, act on average in th...

  13. Coal extraction - environmental prediction

    Energy Technology Data Exchange (ETDEWEB)

    C. Blaine Cecil; Susan J. Tewalt

    2002-08-01

    To predict and help minimize the impact of coal extraction in the Appalachian region, the U.S. Geological Survey (USGS) is addressing selected mine-drainage issues through the following four interrelated studies: spatial variability of deleterious materials in coal and coal-bearing strata; kinetics of pyrite oxidation; improved spatial geologic models of the potential for drainage from abandoned coal mines; and methodologies for the remediation of waters discharged from coal mines. As these goals are achieved, the recovery of coal resources will be enhanced. 2 figs.

  14. Energy Predictions 2011

    International Nuclear Information System (INIS)

    Even as the recession begins to subside, the energy sector is still likely to experience challenging conditions as we enter 2011. It should be remembered how very important a role energy plays in driving the global economy. Serving as a simple yet global and unified measure of economic recovery, it is oil's price range and the strength and sustainability of the recovery which will impact the ways in which all forms of energy are produced and consumed. The report aims for a closer insight into these predictions: What will happen with M and A (Mergers and Acquisitions) in the energy industry?; What are the prospects for renewables?; Will the water-energy nexus grow in importance?; How will technological leaps and bounds affect E and P (exploration and production) operations?; What about electric cars? This is the second year Deloitte's Global Energy and Resources Group has published its predictions for the year ahead. The report is based on in-depth interviews with clients, industry analysts, and senior energy practitioners from Deloitte member firms around the world.

  15. Compressor map prediction tool

    Science.gov (United States)

    Ravi, Arjun; Sznajder, Lukasz; Bennett, Ian

    2015-08-01

    Shell Global Solutions uses an in-house developed system for remote condition monitoring of centrifugal compressors. It requires field process data collected during operation to calculate and assess the machine's performance. Performance is assessed by comparing live results of polytropic head and efficiency versus design compressor curves provided by the Manufacturer. Typically, these design curves are given for specific suction conditions. The further these conditions on site deviate from those prescribed at design, the less accurate the health assessment of the compressor becomes. To address this specified problem, a compressor map prediction tool is proposed. The original performance curves of polytropic head against volumetric flow for varying rotational speeds are used as an input to define a range of Mach numbers within which the non-dimensional invariant performance curve of head and volume flow coefficient is generated. The new performance curves of polytropic head vs. flow for desired set of inlet conditions are then back calculated using the invariant non-dimensional curve. Within the range of Mach numbers calculated from design data, the proposed methodology can predict polytropic head curves at a new set of inlet conditions within an estimated 3% accuracy. The presented methodology does not require knowledge of detailed impeller geometry such as throat areas, blade number, blade angles, thicknesses nor other aspects of the aerodynamic design - diffusion levels, flow angles, etc. The only required mechanical design feature is the first impeller tip diameter. Described method makes centrifugal compressor surveillance activities more accurate, enabling precise problem isolation affecting machine's performance.

  16. Predicting Alloreactivity in Transplantation

    Directory of Open Access Journals (Sweden)

    Kirsten Geneugelijk

    2014-01-01

    Full Text Available Human leukocyte Antigen (HLA mismatching leads to severe complications after solid-organ transplantation and hematopoietic stem-cell transplantation. The alloreactive responses underlying the posttransplantation complications include both direct recognition of allogeneic HLA by HLA-specific alloantibodies and T cells and indirect T-cell recognition. However, the immunogenicity of HLA mismatches is highly variable; some HLA mismatches lead to severe clinical B-cell- and T-cell-mediated alloreactivity, whereas others are well tolerated. Definition of the permissibility of HLA mismatches prior to transplantation allows selection of donor-recipient combinations that will have a reduced chance to develop deleterious host-versus-graft responses after solid-organ transplantation and graft-versus-host responses after hematopoietic stem-cell transplantation. Therefore, several methods have been developed to predict permissible HLA-mismatch combinations. In this review we aim to give a comprehensive overview about the current knowledge regarding HLA-directed alloreactivity and several developed in vitro and in silico tools that aim to predict direct and indirect alloreactivity.

  17. Predictive assessment of reading.

    Science.gov (United States)

    Wood, Frank B; Hill, Deborah F; Meyer, Marianne S; Flowers, D Lynn

    2005-12-01

    Study 1 retrospectively analyzed neuropsychological and psychoeducational tests given to N=220 first graders, with follow-up assessments in third and eighth grade. Four predictor constructs were derived: (1) Phonemic Awareness, (2) Picture Vocabulary, (3) Rapid Naming, and (4) Single Word Reading. Together, these accounted for 88%, 76%, 69%, and 69% of the variance, respectively, in first, third, and eighth grade Woodcock Johnson Broad Reading and eighth grade Gates-MacGinitie. When Single Word Reading was excluded from the predictors, the remaining predictors still accounted for 71%, 65%, 61%, and 65% of variance in the respective outcomes. Secondary analyses of risk of low outcome showed sensitivities/specificities of 93.0/91.0, and 86.4/84.9, respectively, for predicting which students would be in the bottom 15% and 30% of actual first grade WJBR. Sensitivities/specificities were 84.8/83.3 and 80.2/81.3, respectively, for predicting the bottom 15% and 30% of actual third grade WJBR outcomes; eighth grade outcomes had sensitivities/specificities of 80.0/80.0 and 85.7/83.1, respectively, for the bottom 15% and 30% of actual eighth grade WJBR scores. Study 2 cross-validated the concurrent predictive validities in an N=500 geographically diverse sample of late kindergartners through third graders, whose ethnic and racial composition closely approximated the national early elementary school population. New tests of the same four predictor domains were used, together taking only 15 minutes to administer by teachers; the new Woodcock-Johnson III Broad Reading standard score was the concurrent criterion, whose testers were blind to the predictor results. This cross-validation showed 86% of the variance accounted for, using the same regression weights as used in Study 1. With these weights, sensitivity/specificity values for the 15% and 30% thresholds were, respectively, 91.3/88.0 and 94.1/89.1. These validities and accuracies are stronger than others reported for

  18. Cooling pond temperature prediction

    International Nuclear Information System (INIS)

    A model is described which predicts temperature responses in the environment that are associated with the operation of a natural gas fueled thermoelectric power generation station. The model is a piecewise computer simulation, limited at present to closed cooling water systems. However, the techniques developed should be applicable to a much larger class of cooling system. The problem encountered consists of two parts: (1) data characterization and (2) modeling. An efficient characterization scheme for the environmental variables greatly simplifies the task of modeling. Methods borrowed from signal theory, but not yet applied to this field are applicable to and greatly simplify the digital computer investigation of environmental data. An optimal data set, from the point of view of information per unit cost, is described for the model

  19. Motor degradation prediction methods

    International Nuclear Information System (INIS)

    Motor Operated Valve (MOV) squirrel cage AC motor rotors are susceptible to degradation under certain conditions. Premature failure can result due to high humidity/temperature environments, high running load conditions, extended periods at locked rotor conditions (i.e. > 15 seconds) or exceeding the motor's duty cycle by frequent starts or multiple valve stroking. Exposure to high heat and moisture due to packing leaks, pressure seal ring leakage or other causes can significantly accelerate the degradation. ComEd and Liberty Technologies have worked together to provide and validate a non-intrusive method using motor power diagnostics to evaluate MOV rotor condition and predict failure. These techniques have provided a quick, low radiation dose method to evaluate inaccessible motors, identify degradation and allow scheduled replacement of motors prior to catastrophic failures

  20. Chloride ingress prediction

    DEFF Research Database (Denmark)

    Frederiksen, Jens Mejer; Geiker, Mette Rica

    Prediction of chloride ingress into concrete is an important part of durability design of reinforced concrete structures exposed to chloride containing environment. This paper presents the state-of-the art: an analytical model which describes chloride profiles in concrete as function of depth and...... makes physical sense for the design engineer, i.e. the achieved chloride diffusion coefficients at 1 year and 100 years, D1 and D100 respectively, and the corresponding achieved chloride concentrations at the exposed concrete surface, C1 and C100. Data from field exposure supports the assumption of time...... dependent surface chloride concentrations and the diffusion coefficients. Model parameters for Portland cement concretes with and without silica fume and fly ash in marine atmospheric and submerged South Scandinavian environment are suggested in a companion paper based on 10 years field exposure data....

  1. Motor degradation prediction methods

    Energy Technology Data Exchange (ETDEWEB)

    Arnold, J.R.; Kelly, J.F.; Delzingaro, M.J.

    1996-12-01

    Motor Operated Valve (MOV) squirrel cage AC motor rotors are susceptible to degradation under certain conditions. Premature failure can result due to high humidity/temperature environments, high running load conditions, extended periods at locked rotor conditions (i.e. > 15 seconds) or exceeding the motor`s duty cycle by frequent starts or multiple valve stroking. Exposure to high heat and moisture due to packing leaks, pressure seal ring leakage or other causes can significantly accelerate the degradation. ComEd and Liberty Technologies have worked together to provide and validate a non-intrusive method using motor power diagnostics to evaluate MOV rotor condition and predict failure. These techniques have provided a quick, low radiation dose method to evaluate inaccessible motors, identify degradation and allow scheduled replacement of motors prior to catastrophic failures.

  2. Plume rise predictions

    International Nuclear Information System (INIS)

    Anyone involved with diffusion calculations becomes well aware of the strong dependence of maximum ground concentrations on the effective stack height, h/sub e/. For most conditions chi/sub max/ is approximately proportional to h/sub e/-2, as has been recognized at least since 1936 (Bosanquet and Pearson). Making allowance for the gradual decrease in the ratio of vertical to lateral diffusion at increasing heights, the exponent is slightly larger, say chi/sub max/ approximately h/sub e/-2.3. In inversion breakup fumigation, the exponent is somewhat smaller; very crudely, chi/sub max/ approximately h/sub e/-1.5. In any case, for an elevated emission the dependence of chi/sub max/ on h/sub e/ is substantial. It is postulated that a really clever ignorant theoretician can disguise his ignorance with dimensionless constants. For most sources the effective stack height is considerably larger than the actual source height, h/sub s/. For instance, for power plants with no downwash problems, h/sub e/ is more than twice h/sub s/ whenever the wind is less than 10 m/sec, which is most of the time. This is unfortunate for anyone who has to predict ground concentrations, for he is likely to have to calculate the plume rise, Δh. Especially when using h/sub e/ = h/sub s/ + Δh instead of h/sub s/ may reduce chi/sub max/ by a factor of anywhere from 4 to infinity. Factors to be considered in making plume rise predictions are discussed

  3. Predicting the physics of particles

    International Nuclear Information System (INIS)

    A brief account is presented of the goals and methods of particle theorists, stressing the measurable quantities they would like to predict, the conventional starting points for such predictions, and some of the techniques used to arrive at a prediction. (author)

  4. Brief-exposure to preoperative bevacizumab reveals a TGF-β signature predictive of response in HER2-negative breast cancers.

    Science.gov (United States)

    Varadan, Vinay; Kamalakaran, Sitharthan; Gilmore, Hannah; Banerjee, Nilanjana; Janevski, Angel; Miskimen, Kristy L S; Williams, Nicole; Basavanhalli, Ajay; Madabhushi, Anant; Lezon-Geyda, Kimberly; Bossuyt, Veerle; Lannin, Donald R; Abu-Khalaf, Maysa; Sikov, William; Dimitrova, Nevenka; Harris, Lyndsay N

    2016-02-01

    To best define biomarkers of response, and to shed insight on mechanism of action of certain clinically important agents for early breast cancer, we used a brief-exposure paradigm in the preoperative setting to study transcriptional changes in patient tumors that occur with one dose of therapy prior to combination chemotherapy. Tumor biopsies from breast cancer patients enrolled in two preoperative clinical trials were obtained at baseline and after one dose of bevacizumab (HER2-negative), trastuzumab (HER2-positive) or nab-paclitaxel, followed by treatment with combination chemo-biologic therapy. RNA-Sequencing based PAM50 subtyping at baseline of 46 HER2-negative patients revealed a strong association between the basal-like subtype and pathologic complete response (pCR) to chemotherapy plus bevacizumab (p ≤ 0.0027), but did not provide sufficient specificity to predict response. However, a single dose of bevacizumab resulted in down-regulation of a well-characterized TGF-β activity signature in every single breast tumor that achieved pCR (p ≤ 0.004). The TGF-β signature was confirmed to be a tumor-specific read-out of the canonical TGF-β pathway using pSMAD2 (p ≤ 0.04), with predictive power unique to brief-exposure to bevacizumab (p ≤ 0.016), but not trastuzumab or nab-paclitaxel. Down-regulation of TGF-β activity was associated with reduction in tumor hypoxia by transcription and protein levels, suggesting therapy-induced disruption of an autocrine-loop between tumor stroma and malignant cells. Modulation of the TGF-β pathway upon brief-exposure to bevacizumab may provide an early functional readout of pCR to preoperative anti-angiogenic therapy in HER2-negative breast cancer, thus providing additional avenues for exploration in both preclinical and clinical settings with these agents. PMID:26284485

  5. Earthquake prediction with electromagnetic phenomena

    International Nuclear Information System (INIS)

    Short-term earthquake (EQ) prediction is defined as prospective prediction with the time scale of about one week, which is considered to be one of the most important and urgent topics for the human beings. If this short-term prediction is realized, casualty will be drastically reduced. Unlike the conventional seismic measurement, we proposed the use of electromagnetic phenomena as precursors to EQs in the prediction, and an extensive amount of progress has been achieved in the field of seismo-electromagnetics during the last two decades. This paper deals with the review on this short-term EQ prediction, including the impossibility myth of EQs prediction by seismometers, the reason why we are interested in electromagnetics, the history of seismo-electromagnetics, the ionospheric perturbation as the most promising candidate of EQ prediction, then the future of EQ predictology from two standpoints of a practical science and a pure science, and finally a brief summary

  6. Earthquake prediction with electromagnetic phenomena

    Energy Technology Data Exchange (ETDEWEB)

    Hayakawa, Masashi, E-mail: hayakawa@hi-seismo-em.jp [Hayakawa Institute of Seismo Electomagnetics, Co. Ltd., University of Electro-Communications (UEC) Incubation Center, 1-5-1 Chofugaoka, Chofu Tokyo, 182-8585 (Japan); Advanced Wireless & Communications Research Center, UEC, Chofu Tokyo (Japan); Earthquake Analysis Laboratory, Information Systems Inc., 4-8-15, Minami-aoyama, Minato-ku, Tokyo, 107-0062 (Japan); Fuji Security Systems. Co. Ltd., Iwato-cho 1, Shinjyuku-ku, Tokyo (Japan)

    2016-02-01

    Short-term earthquake (EQ) prediction is defined as prospective prediction with the time scale of about one week, which is considered to be one of the most important and urgent topics for the human beings. If this short-term prediction is realized, casualty will be drastically reduced. Unlike the conventional seismic measurement, we proposed the use of electromagnetic phenomena as precursors to EQs in the prediction, and an extensive amount of progress has been achieved in the field of seismo-electromagnetics during the last two decades. This paper deals with the review on this short-term EQ prediction, including the impossibility myth of EQs prediction by seismometers, the reason why we are interested in electromagnetics, the history of seismo-electromagnetics, the ionospheric perturbation as the most promising candidate of EQ prediction, then the future of EQ predictology from two standpoints of a practical science and a pure science, and finally a brief summary.

  7. Update on protein structure prediction

    DEFF Research Database (Denmark)

    Hubbard, T; Tramontano, A; Barton, G; Jones, D; Sippl, M; Valencia, A; Lesk, A; Moult, J; Rost, B; Sander, C; Schneider, R; Lahm, A; Leplae, R; Buta, C; Eisenstein, M; Fjellstrom, O; Floeckner, H; Grossmann, JG; Hansen, J; Citterich, MH; Jørgensen, Flemming Steen; MarchlerBauer, A; Osuna, J; Park, J; Reinhardt, A; dePouplana, LR; RojoDominguez, A; Saudek, V; Sinclair, J; Sturrock, S; Venclovas, C; Vinals, C

    1996-01-01

    Computational tools for protein structure prediction are of great interest to molecular, structural and theoretical biologists due to a rapidly increasing number of protein sequences with no known structure. In October 1995, a workshop was held at IRBM to predict as much as possible about a number...... of proteins of biological interest using ab initio pre!diction of fold recognition methods. 112 protein sequences were collected via an open invitation for target submissions. 17 were selected for prediction during the workshop and for 11 of these a prediction of some reliability could be made. We...... believe that this was a worthwhile experiment showing that the use of a range of independent prediction methods and thorough use of existing databases can lead to credible and useful ab initio structure predictions....

  8. Introduction: Long term prediction

    International Nuclear Information System (INIS)

    Making a decision upon the right choice of a material appropriate to a given application should be based on taking into account several parameters as follows: cost, standards, regulations, safety, recycling, chemical properties, supplying, transformation, forming, assembly, mechanical and physical properties as well as the behaviour in practical conditions. Data taken from a private communication (J.H.Davidson) are reproduced presenting the life time range of materials from a couple of minutes to half a million hours corresponding to applications from missile technology up to high-temperature nuclear reactors or steam turbines. In the case of deep storage of nuclear waste the time required is completely different from these values since we have to ensure the integrity of the storage system for several thousand years. The vitrified nuclear wastes should be stored in metallic canisters made of iron and carbon steels, stainless steels, copper and copper alloys, nickel alloys or titanium alloys. Some of these materials are passivating metals, i.e. they develop a thin protective film, 2 or 3 nm thick - the so-called passive films. These films prevent general corrosion of the metal in a large range of chemical condition of the environment. In some specific condition, localized corrosion such as the phenomenon of pitting, occurs. Consequently, it is absolutely necessary to determine these chemical condition and their stability in time to understand the behavior of a given material. In other words the corrosion system is constituted by the complex material/surface/medium. For high level nuclear wastes the main features for resolving problem are concerned with: geological disposal; deep storage in clay; waste metallic canister; backfill mixture (clay-gypsum) or concrete; long term behavior; data needed for modelling and for predicting; choice of appropriate solution among several metallic candidates. The analysis of the complex material/surface/medium is of great importance

  9. Useful theories make predictions.

    Science.gov (United States)

    Howes, Andrew

    2012-01-01

    Stephen and Van Orden (this issue) propose that there is a complex system approach to cognitive science, and collectively the authors of the papers presented in this issue believe that this approach provides the means to drive a revolution in the science of the mind. Unfortunately, however illuminating, this explanation is absent and hyperbole is all too extensive. In contrast, I argue (1) that dynamic systems theory is not new to cognitive science and does not provide a basis for a revolution, (2) it is not necessary to reject cognitive science in order to explain the constraints imposed by the body and the environment, (3) it is not necessary, as Silberstein and Chemero (this issue) appear to do, to reject cognitive science in order to explain consciousness, and (4) our understanding of pragmatics is not advanced by Gibbs and Van Orden's (this issue) "self-organized criticality".? Any debate about the future of cognitive science could usefully focus on predictive adequacy. Unfortunately, this is not the approach taken by the authors of this issue. PMID:22253181

  10. Protein Chemical Shift Prediction

    CERN Document Server

    Larsen, Anders S

    2014-01-01

    The protein chemical shifts holds a large amount of information about the 3-dimensional structure of the protein. A number of chemical shift predictors based on the relationship between structures resolved with X-ray crystallography and the corresponding experimental chemical shifts have been developed. These empirical predictors are very accurate on X-ray structures but tends to be insensitive to small structural changes. To overcome this limitation it has been suggested to make chemical shift predictors based on quantum mechanical(QM) calculations. In this thesis the development of the QM derived chemical shift predictor Procs14 is presented. Procs14 is based on 2.35 million density functional theory(DFT) calculations on tripeptides and contains corrections for hydrogen bonding, ring current and the effect of the previous and following residue. Procs14 is capable at performing predictions for the 13CA, 13CB, 13CO, 15NH, 1HN and 1HA backbone atoms. In order to benchmark Procs14, a number of QM NMR calculatio...

  11. Predictability of blocking

    International Nuclear Information System (INIS)

    Tibaldi and Molteni (1990, hereafter referred to as TM) had previously investigated operational blocking predictability by the ECMWF model and the possible relationships between model systematic error and blocking in the winter season of the Northern Hemisphere, using seven years of ECMWF operational archives of analyses and day 1 to 10 forecasts. They showed that fewer blocking episodes than in the real atmosphere were generally simulated by the model, and that this deficiency increased with increasing forecast time. As a consequence of this, a major contribution to the systematic error in the winter season was shown to derive from the inability of the model to properly forecast blocking. In this study, the analysis performed in TM for the first seven winter seasons of the ECMWF operational model is extended to the subsequent five winters, during which model development, reflecting both resolution increases and parametrisation modifications, continued unabated. In addition the objective blocking index developed by TM has been applied to the observed data to study the natural low frequency variability of blocking. The ability to simulate blocking of some climate models has also been tested

  12. An exact prediction of

    International Nuclear Information System (INIS)

    We propose that the expectation value of a circular BPS-Wilson loop in N=4 supersymmetric Yang--Mills can be calculated exactly, to all orders in a 1/N expansion and to all orders in g2N. Using the AdS/CFT duality, this result yields a prediction of the value of the string amplitude with a circular boundary to all orders in α' and to all orders in gs. We then compare this result with string theory. We find that the gauge theory calculation, for large g2N and to all orders in the 1/N2 expansion, does agree with the leading string theory calculation, to all orders in gs and to lowest order in α'. We also find a relation between the expectation value of any closed smooth Wilson loop and the loop related to it by an inversion that takes a point along the loop to infinity, and compare this result, again successfully, with string theory

  13. Predictive Analysis for Social Processes II: Predictability and Warning Analysis

    CERN Document Server

    Colbaugh, Richard

    2009-01-01

    This two-part paper presents a new approach to predictive analysis for social processes. Part I identifies a class of social processes, called positive externality processes, which are both important and difficult to predict, and introduces a multi-scale, stochastic hybrid system modeling framework for these systems. In Part II of the paper we develop a systems theory-based, computationally tractable approach to predictive analysis for these systems. Among other capabilities, this analytic methodology enables assessment of process predictability, identification of measurables which have predictive power, discovery of reliable early indicators for events of interest, and robust, scalable prediction. The potential of the proposed approach is illustrated through case studies involving online markets, social movements, and protest behavior.

  14. Melanoma risk prediction models

    Directory of Open Access Journals (Sweden)

    Nikolić Jelena

    2014-01-01

    Full Text Available Background/Aim. The lack of effective therapy for advanced stages of melanoma emphasizes the importance of preventive measures and screenings of population at risk. Identifying individuals at high risk should allow targeted screenings and follow-up involving those who would benefit most. The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. Methods. This case-control study included 697 participants (341 patients and 356 controls that underwent extensive interview and skin examination in order to check risk factors for melanoma. Pairwise univariate statistical comparison was used for the coarse selection of the most significant risk factors. These factors were fed into logistic regression (LR and alternating decision trees (ADT prognostic models that were assessed for their usefulness in identification of patients at risk to develop melanoma. Validation of the LR model was done by Hosmer and Lemeshow test, whereas the ADT was validated by 10-fold cross-validation. The achieved sensitivity, specificity, accuracy and AUC for both models were calculated. The melanoma risk score (MRS based on the outcome of the LR model was presented. Results. The LR model showed that the following risk factors were associated with melanoma: sunbeds (OR = 4.018; 95% CI 1.724- 9.366 for those that sometimes used sunbeds, solar damage of the skin (OR = 8.274; 95% CI 2.661-25.730 for those with severe solar damage, hair color (OR = 3.222; 95% CI 1.984-5.231 for light brown/blond hair, the number of common naevi (over 100 naevi had OR = 3.57; 95% CI 1.427-8.931, the number of dysplastic naevi (from 1 to 10 dysplastic naevi OR was 2.672; 95% CI 1.572-4.540; for more than 10 naevi OR was 6.487; 95%; CI 1.993-21.119, Fitzpatricks phototype and the presence of congenital naevi. Red hair, phototype I and large congenital naevi were

  15. Predicting periodontitis progression?

    Science.gov (United States)

    Ferraiolo, Debra M

    2016-03-01

    Data sourcesCochrane Library, Ovid, Medline, Embase and LILACS were searched using no language restrictions and included information up to July 2014. Bibliographic references of included articles and related review articles were hand searched. On-line hand searching of recent issues of key periodontal journals was performed (Journal of Clinical Periodontology, Journal of Dental Research, Journal of Periodontal Research, Journal of Periodontology, Oral Health and Preventive Dentistry).Study selectionProspective and retrospective cohort studies were used for answering the question of prediction since there were no randomised controlled trials on this topic. Risk of bias was assessed using the validated Newcastle-Ottawa quality assessment scale for non-randomised studies. Cross-sectional studies were included in the summary of currently reported risk assessment tools but not for risk of progression of disease, due to the inability to properly assess bias in these types of studies. Titles and abstracts were scanned by two reviewers independently.Full reports were obtained for those articles meeting inclusion criteria or those with insufficient information in the title to make a decision. Any published risk assessment tool was considered. The tool was defined to include any composite measure of patient-level risk directed towards determining the probability for further disease progression in adults with periodontitis. Periodontitis was defined to include both chronic and aggressive forms in the adult population. Outcomes included changes in attachment levels and/or deepening of periodontal pockets in millimeters in study populations undergoing supportive periodontal therapy.Data extraction and synthesisData extraction was performed independently and in collaboration by two reviewers; completed evidence tables were reviewed by three reviewers. Studies were each given a descriptive summary to assess the quantity of data as well as further assessment of study variations

  16. PREDICTING TURBINE STAGE PERFORMANCE

    Science.gov (United States)

    Boyle, R. J.

    1994-01-01

    This program was developed to predict turbine stage performance taking into account the effects of complex passage geometries. The method uses a quasi-3D inviscid-flow analysis iteratively coupled to calculated losses so that changes in losses result in changes in the flow distribution. In this manner the effects of both the geometry on the flow distribution and the flow distribution on losses are accounted for. The flow may be subsonic or shock-free transonic. The blade row may be fixed or rotating, and the blades may be twisted and leaned. This program has been applied to axial and radial turbines, and is helpful in the analysis of mixed flow machines. This program is a combination of the flow analysis programs MERIDL and TSONIC coupled to the boundary layer program BLAYER. The subsonic flow solution is obtained by a finite difference, stream function analysis. Transonic blade-to-blade solutions are obtained using information from the finite difference, stream function solution with a reduced flow factor. Upstream and downstream flow variables may vary from hub to shroud and provision is made to correct for loss of stagnation pressure. Boundary layer analyses are made to determine profile and end-wall friction losses. Empirical loss models are used to account for incidence, secondary flow, disc windage, and clearance losses. The total losses are then used to calculate stator, rotor, and stage efficiency. This program is written in FORTRAN IV for batch execution and has been implemented on an IBM 370/3033 under TSS with a central memory requirement of approximately 4.5 Megs of 8 bit bytes. This program was developed in 1985.

  17. Airframe noise prediction

    Science.gov (United States)

    1990-11-01

    This Data Item 90023, an addition to the Noise Sub-series, provides the FORTRAN listing of a computer program for a semi-empirical method that calculates the far-field airframe aerodynamic noise generated by turbo-fan powered transport aircraft or gliders in one-third octave bands over a frequency range specified by the user. The overall sound pressure level is also output. The results apply for a still, lossless atmosphere; other ESDU methods may be used to correct for atmospheric attenuation, ground reflection, lateral attenuation, and wind and temperature gradients. The position of the aircraft relative to the observer is input in terms of the height at minimum range, and the elevation and azimuthal angles to the aircraft; if desired the user may obtain results over a range of those angles in 10 degree intervals. The method sums the contributions made by various components, results for which can also be output individually. The components are: the wind (conventional or delta), tailplane, fin, flaps (single/double slotted or triple slotted), leading-edge slats, and undercarriage legs and wheels (one/two wheel or four wheel units). The program requires only geometric data for each component (area and span in the case of lifting elements, flap deflection angle, and leg length and wheel diameter for the undercarriage). The program was validated for aircraft with take-off masses from 42,000 to 390,000 kg (92,000 to 860,000 lb) at airspeeds from 70 to 145 m/s (135 to 280 kn). Comparisons with available experimental data suggest a prediction rms accuracy of 1 dB at minimum range, rising to between 2 and 3 dB at 60 degrees to either side.

  18. Method-level bug prediction

    OpenAIRE

    Giger, Emanuel; D'Ambros, Marco; Pinzger, Martin; Gall, Harald

    2012-01-01

    Researchers proposed a wide range of approaches to build effective bug prediction models that take into account multiple aspects of the software development process. Such models achieved good prediction performance, guiding developers towards those parts of their system where a large share of bugs can be expected. However, most of those approaches predict bugs on file-level. This often leaves developers with a considerable amount of effort to examine all methods of a file until a bug is locat...

  19. Networked and Distributed Predictive Control

    CERN Document Server

    Christofides, Panagiotis D; De La Pena, David Munoz

    2011-01-01

    "Networked and Distributed Predictive Control" presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems - the first book to do so. The design of model predictive control systems using Lyapunov-based techniques accounting for the influence of asynchronous and delayed measurements is followed by a treatment of networked control architecture development. This shows how networked control can augment dedicated control systems in a natural way and takes advantage of additional, potentially asynchronous and delayed measurements to main

  20. Long Range Aircraft Trajectory Prediction

    OpenAIRE

    Magister, Tone

    2009-01-01

    The subject of the paper is the improvement of the aircraft future trajectory prediction accuracy for long-range airborne separation assurance. The strategic planning of safe aircraft flights and effective conflict avoidance tactics demand timely and accurate conflict detection based upon future four–dimensional airborne traffic situation prediction which is as accurate as each aircraft flight trajectory prediction. The improved kinematics model of aircraft relative flight considering flight ...

  1. Predicting cognitive change within domains

    OpenAIRE

    Duff, Kevin; Beglinger, Leigh J.; Moser, David J.; Paulsen, Jane S.

    2010-01-01

    Standardized regression based (SRB) formulas, a method for predicting cognitive change across time, traditionally use baseline performance on a neuropsychological measure to predict future performance on that same measure. However, there are instances in which the same tests may not be given at follow-up assessments (e.g., lack of continuity of provider, avoiding practice effects). The current study sought to expand this methodology by developing SRBs to predict performance on different tests...

  2. Interoceptive predictions in the brain.

    Science.gov (United States)

    Barrett, Lisa Feldman; Simmons, W Kyle

    2015-07-01

    Intuition suggests that perception follows sensation and therefore bodily feelings originate in the body. However, recent evidence goes against this logic: interoceptive experience may largely reflect limbic predictions about the expected state of the body that are constrained by ascending visceral sensations. In this Opinion article, we introduce the Embodied Predictive Interoception Coding model, which integrates an anatomical model of corticocortical connections with Bayesian active inference principles, to propose that agranular visceromotor cortices contribute to interoception by issuing interoceptive predictions. We then discuss how disruptions in interoceptive predictions could function as a common vulnerability for mental and physical illness. PMID:26016744

  3. Predicting Parameters in Deep Learning

    OpenAIRE

    Denil, Misha; Shakibi, Babak; Dinh, Laurent; Ranzato, Marc'Aurelio; De Freitas, Nando

    2013-01-01

    We demonstrate that there is significant redundancy in the parameterization of several deep learning models. Given only a few weight values for each feature it is possible to accurately predict the remaining values. Moreover, we show that not only can the parameter values be predicted, but many of them need not be learned at all. We train several different architectures by learning only a small number of weights and predicting the rest. In the best case we are able to predict more than 95% of...

  4. Risk prediction for invasive candidiasis

    Directory of Open Access Journals (Sweden)

    Armin Ahmed

    2014-01-01

    Full Text Available Over past few years, treatment of invasive candidiasis (IC has evolved from targeted therapy to prophylaxis, pre-emptive and empirical therapy. Numerous predisposing factors for IC have been grouped together in various combinations to design risk prediction models. These models in general have shown good negative predictive value, but poor positive predictive value. They are useful in selecting the population which is less likely to benefit from empirical antifungal therapy and thus prevent overuse of antifungal agents. Current article deals with various risk prediction models for IC and their external validation studies.

  5. Neural Correlates of Predictive Saccades.

    Science.gov (United States)

    Lee, Stephen M; Peltsch, Alicia; Kilmade, Maureen; Brien, Donald C; Coe, Brian C; Johnsrude, Ingrid S; Munoz, Douglas P

    2016-08-01

    Every day we generate motor responses that are timed with external cues. This phenomenon of sensorimotor synchronization has been simplified and studied extensively using finger tapping sequences that are executed in synchrony with auditory stimuli. The predictive saccade paradigm closely resembles the finger tapping task. In this paradigm, participants follow a visual target that "steps" between two fixed locations on a visual screen at predictable ISIs. Eventually, the time from target appearance to saccade initiation (i.e., saccadic RT) becomes predictive with values nearing 0 msec. Unlike the finger tapping literature, neural control of predictive behavior described within the eye movement literature has not been well established and is inconsistent, especially between neuroimaging and patient lesion studies. To resolve these discrepancies, we used fMRI to investigate the neural correlates of predictive saccades by contrasting brain areas involved with behavior generated from the predictive saccade task with behavior generated from a reactive saccade task (saccades are generated toward targets that are unpredictably timed). We observed striking differences in neural recruitment between reactive and predictive conditions: Reactive saccades recruited oculomotor structures, as predicted, whereas predictive saccades recruited brain structures that support timing in motor responses, such as the crus I of the cerebellum, and structures commonly associated with the default mode network. Therefore, our results were more consistent with those found in the finger tapping literature. PMID:27054397

  6. EVA Performance Prediction

    Science.gov (United States)

    Peacock, Brian; Maida, James; Rajulu, Sudhakar

    2004-01-01

    out for EVA activities are based more on extensive domain experience than any formal analytic structure. Conversely, physical task analysis for industrial and structured evidence from training and EV A contexts. Again on earth there is considerable evidence of human performance degradation due to encumbrance and fatigue. These industrial models generally take the form of a discounting equation. The development of performance estimates for space operations, such as timeline predictions for EVA is generally based on specific input from training activity, for example in the NBL or KC135. uniformed services tasks on earth are much more formalized. Human performance data in the space context has two sources: first there is the micro analysis of performance in structured tasks by the space physiology community and second there is the less structured evidence from training and EV A contexts.

  7. Predictability and Prediction for an Experimental Cultural Market

    Science.gov (United States)

    Colbaugh, Richard; Glass, Kristin; Ormerod, Paul

    Individuals are often influenced by the behavior of others, for instance because they wish to obtain the benefits of coordinated actions or infer otherwise inaccessible information. In such situations this social influence decreases the ex ante predictability of the ensuing social dynamics. We claim that, interestingly, these same social forces can increase the extent to which the outcome of a social process can be predicted very early in the process. This paper explores this claim through a theoretical and empirical analysis of the experimental music market described and analyzed in [1]. We propose a very simple model for this music market, assess the predictability of market outcomes through formal analysis of the model, and use insights derived through this analysis to develop algorithms for predicting market share winners, and their ultimate market shares, in the very early stages of the market. The utility of these predictive algorithms is illustrated through analysis of the experimental music market data sets [2].

  8. Predicting epileptic seizures in advance.

    Directory of Open Access Journals (Sweden)

    Negin Moghim

    Full Text Available Epilepsy is the second most common neurological disorder, affecting 0.6-0.8% of the world's population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. Antiepileptic Drugs (AEDs are used as long-term therapeutic solutions that control the condition. Of those treated with AEDs, 35% become resistant to medication. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is clearly desirable to find more effective ways of preventing seizures for such patients. The automatic detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. In addition, advance prediction of seizures can enrich our understanding of the epileptic brain. In this study, drawing on the body of work behind automatic seizure detection and prediction from digitised Invasive Electroencephalography (EEG data, a prediction algorithm, ASPPR (Advance Seizure Prediction via Pre-ictal Relabeling, is described. ASPPR facilitates the learning of predictive models targeted at recognizing patterns in EEG activity that are in a specific time window in advance of a seizure. It then exploits advanced machine learning coupled with the design and selection of appropriate features from EEG signals. Results, from evaluating ASPPR independently on 21 different patients, suggest that seizures for many patients can be predicted up to 20 minutes in advance of their onset. Compared to benchmark performance represented by a mean S1-Score (harmonic mean of Sensitivity and Specificity of 90.6% for predicting seizure onset between 0 and 5 minutes in advance, ASPPR achieves mean S1-Scores of: 96.30% for prediction between 1 and 6 minutes in advance, 96.13% for prediction between 8 and 13 minutes in advance, 94.5% for prediction between 14 and 19 minutes in advance, and 94.2% for prediction between 20 and 25 minutes in advance.

  9. Can Satellites Aid Earthquake Predictions?

    Institute of Scientific and Technical Information of China (English)

    John Roach; 李晓辉

    2004-01-01

    @@ Earthquake prediction is an imprecise science, and to illustrate the point,many experts point to the story of Tangshen①, China. On July 28, 1976, a magnitude② 7. 6 earthquake struck the city of Tangshen, China, without warning. None of the signs of the successful prediction from a year and half earlier were present. An estimated 250,000 people died.

  10. Dividend Predictability Around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

    We show that dividend growth predictability by the dividend yield is the rule rather than the exception in global equity markets. Dividend predictability is weaker, however, in large and developed markets where dividends are smoothed more, the typical firm is large, and volatility is lower. Our f...

  11. Dividend Predictability Around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

    We show that dividend-growth predictability by the dividend yield is the rule rather than the exception in global equity markets. Dividend predictability is weaker, however, in large and developed markets where dividends are smoothed more, the typical firm is large, and volatility is lower. Our f...

  12. Predicting Acoustics in Class Rooms

    DEFF Research Database (Denmark)

    Christensen, Claus Lynge; Rindel, Jens Holger

    2005-01-01

    Typical class rooms have fairly simple geometries, even so room acoustics in this type of room is difficult to predict using today's room acoustic computer modeling software. The reasons why acoustics of class rooms are harder to predict than acoustics of complicated concert halls might be...

  13. Regional downscaling of decadal predictions

    Science.gov (United States)

    Feldmann, H.

    2014-12-01

    During the last years the research field of decadal predictions gained increased attention. Its intention is to exploit the predictability derived from slowly varying components of the climate system on inter-annual to decadal time-scales. Such predictions are mostly performed using ensembles of global earth system models. The prediction systems are able to achieve a relatively high predictive skill over some oceanic regions, like the North Atlantic sector. But potential users of decadal predictions are often interested in forecasts over land areas and require a higher resolution, too. Therefore, the German research program MiKlip develops a decadal ensemble predictions system with regional downscaling as an additional option. Dynamical downscaling and a statistical-dynamical downscaling approach are applied within the MiKlip regionalization module. The global prediction system consists of the MPI-ESM model. Different RCMs are used for the downscaling, e.g. CCLM and REMO. The focus regions are Europe and Western Africa. Hindcast experiments for the period 1960 - 2013 were performed to assess the general skill of the prediction system. Of special interest is the value added by the regional downscaling. For mean quantities, like annual mean temperature and precipitation, the predictive skill is comparable between the global and the downscaled systems. For extremes on the other hand there seems to be an improvement by the RCM ensemble. The skill strongly varies on sub-continental regions and with the season. The lead time up to which a positive predictive skill can be achieved depends on the parameter and season, too. A further goal is to assess the potential for valuable information, which can be derived from predicting long-term variations of the European climate. The leading mode of decadal variability in the European/Atlantic sector is the Atlantic Multidecadal Variation (AMV). The potential predictability from AMV teleconnections especially for extreme value

  14. Universal Prediction of Selected Bits

    CERN Document Server

    Lattimore, Tor; Gavane, Vaibhav

    2011-01-01

    Many learning tasks can be viewed as sequence prediction problems. For example, online classification can be converted to sequence prediction with the sequence being pairs of input/target data and where the goal is to correctly predict the target data given input data and previous input/target pairs. Solomonoff induction is known to solve the general sequence prediction problem, but only if the entire sequence is sampled from a computable distribution. In the case of classification and discriminative learning though, only the targets need be structured (given the inputs). We show that the normalised version of Solomonoff induction can still be used in this case, and more generally that it can detect any recursive sub-pattern (regularity) within an otherwise completely unstructured sequence. It is also shown that the unnormalised version can fail to predict very simple recursive sub-patterns.

  15. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik; Navarro, J.; Barquero, C.G.

    2001-01-01

    The objective of the work is to investigatethe performance of HIRLAM in complex terrain when used as input to energy production forecasting models, and to develop a statistical model to adapt HIRLAM prediction to the wind farm. The features of the terrain, specially the topography, influence the...... performance of HIRLAM in particular with respect to wind predictions. To estimate the performance of the model two spatial resolutions (0,5 Deg. and 0.2 Deg.) and different sets of HIRLAM variables were used to predict wind speed and energy production. The predictions of energy production for the wind farms...... are calculated using on-line measurements of power production as well as HIRLAM predictions as input thus taking advantage of the auto-correlation, which is present in the power production for shorter pediction horizons. Statistical models are used to discribe the relationship between observed energy...

  16. Time-predictable Stack Caching

    DEFF Research Database (Denmark)

    Abbaspourseyedi, Sahar

    complicated and less imprecise. Time-predictable computer architectures provide solutions to this problem. As accesses to the data in caches are one source of timing unpredictability, devising methods for improving the timepredictability of caches are important. Stack data, with statically analyzable...... addresses, provides an opportunity to predict and tighten the WCET of accesses to data in caches. In this thesis, we introduce the time-predictable stack cache design and implementation within a time-predictable processor. We introduce several optimizations to our design for tightening the WCET while...... keeping the timepredictability of the design intact. Moreover, we provide a solution for reducing the cost of context switching in a system using the stack cache. In design of these caches, we use custom hardware and compiler support for delivering time-predictable stack data accesses. Furthermore, for...

  17. Prediction, Regression and Critical Realism

    DEFF Research Database (Denmark)

    Næss, Petter

    2004-01-01

    This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... of prediction necessary and possible in spatial planning of urban development. Finally, the political implications of positions within theory of science rejecting the possibility of predictions about social phenomena are addressed....... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...

  18. Prediction of molecular crystal structures

    CERN Document Server

    Beyer, T

    2001-01-01

    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of parac...

  19. Earthquake prediction by Kina Method

    International Nuclear Information System (INIS)

    Earthquake prediction has been one of the earliest desires of the man. Scientists have worked hard to predict earthquakes for a long time. The results of these efforts can generally be divided into two methods of prediction: 1) Statistical Method, and 2) Empirical Method. In the first method, earthquakes are predicted using statistics and probabilities, while the second method utilizes variety of precursors for earthquake prediction. The latter method is time consuming and more costly. However, the result of neither method has fully satisfied the man up to now. In this paper a new method entitled 'Kiana Method' is introduced for earthquake prediction. This method offers more accurate results yet lower cost comparing to other conventional methods. In Kiana method the electrical and magnetic precursors are measured in an area. Then, the time and the magnitude of an earthquake in the future is calculated using electrical, and in particular, electrical capacitors formulas. In this method, by daily measurement of electrical resistance in an area we make clear that the area is capable of earthquake occurrence in the future or not. If the result shows a positive sign, then the occurrence time and the magnitude can be estimated by the measured quantities. This paper explains the procedure and details of this prediction method. (authors)

  20. Predicting emergency diesel starting performance

    International Nuclear Information System (INIS)

    The US Department of Energy effort to extend the operational lives of commercial nuclear power plants has examined methods for predicting the performance of specific equipment. This effort focuses on performance prediction as a means for reducing equipment surveillance, maintenance, and outages. Realizing these goals will result in nuclear plants that are more reliable, have lower maintenance costs, and have longer lives. This paper describes a monitoring system that has been developed to predict starting performance in emergency diesels. A prototype system has been built and tested on an engine at Sandia National Laboratories. 2 refs

  1. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    distinguish rival prediction models with similar prediction performances. Furthermore, on the subject level a confidence score may provide useful supplementary information for new patients who want to base a medical decision on predicted risk. The ideas are illustrated and discussed using data from cancer...... modelling strategy is applied to different training sets. For each modelling strategy we estimate a confidence score based on the same repeated bootstraps. A new decomposition of the expected Brier score is obtained, as well as the estimates of population average confidence scores. The latter can be used to...

  2. Adaptive filtering prediction and control

    CERN Document Server

    Goodwin, Graham C

    2009-01-01

    Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

  3. Dividend Predictability around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

    The common perception in the literature is that current dividend yields are uninformative about future dividends, but contain some information about future stock returns. In this paper, we show that this finding reverses when looking at a broad panel of countries outside the U.S.. In particular, we...... demonstrate that aggregate dividend growth rates are highly predictable by the dividend yield and that dividend predictability is clearly stronger than return predictability in medium-sized and smaller countries that account for the majority of countries in the world. We show that this is true both in the...

  4. Predictive Data Mining in KPP

    Directory of Open Access Journals (Sweden)

    Dr. R.K. Chauhan

    2012-09-01

    Full Text Available In this paper, we have provided the Genetic Algorithm (GA used for prediction process in Knowledge Penetration Process (KPP. The said GA is implemented and its efficiency is analysed.

  5. Prediction tools in surgical oncology.

    Science.gov (United States)

    Isariyawongse, Brandon K; Kattan, Michael W

    2012-07-01

    Artificial neural networks, prediction tables, and clinical nomograms allow physicians to transmit an immense amount of prognostic information in a format that exhibits comprehensibility and brevity. Current models demonstrate the feasibility to accurately predict many oncologic outcomes, including pathologic stage, recurrence-free survival, and response to adjuvant therapy. Although emphasis should be placed on the independent validation of existing prediction tools, there is a paucity of models in the literature that focus on quality of life outcomes. The unification of tools that predict oncologic and quality of life outcomes into a comparative effectiveness table will furnish patients with cancer with the information they need to make a highly informed and individualized treatment decision. PMID:22583992

  6. Data for decay Heat Predictions

    International Nuclear Information System (INIS)

    These proceedings of a specialists' meeting on data for decay heat predictions are based on fission products yields, on delayed neutrons and on comparative evaluations on evaluated and experimental data for thermal and fast fission. Fourteen conferences were analysed

  7. Predictive Models and Computational Embryology

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  8. History of earthquake prediction researches

    International Nuclear Information System (INIS)

    The main procedures of diffusion of knowledge on earthquake prediction researches in space and time have been reconstructed. Scientific and economic constraint factors that caused difficulties or accelerations in seismic precursors researches have been investigated and commented

  9. Prediction of molecular crystal structures

    International Nuclear Information System (INIS)

    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol-1 of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy structures

  10. Can Scientific Impact Be Predicted?

    OpenAIRE

    Dong, Yuxiao; Johnson, Reid A.; Chawla, Nitesh V

    2016-01-01

    A widely used measure of scientific impact is citations. However, due to their heavy-tailed distribution, citations are fundamentally difficult to predict. Instead, to characterize scientific impact, we address two analogous questions asked by many scientific researchers: "How will my h-index evolve over time, and which of my previously or newly published papers will contribute to it?" To answer these questions, we perform two related tasks. First, we develop a model to predict authors' futur...

  11. Aeroacoustic Prediction and Noise Reduction

    OpenAIRE

    Delfs, Jan Werner

    2011-01-01

    An overview is given about aeroacoustic prediction and noise reduction technology from the field of aircraft noise. The simulation philosophy of the prediction methods is related to real world application, i.e. high Reynolds number flows, typical for aircraft. Noise reduction concepts are studied in two ways i) through a silent by design approach and b) by add-on treatments for existing aircraft components. Challenges are identified for future research.

  12. Challenges in Aircraft Noise Prediction

    OpenAIRE

    Filippone A

    2014-01-01

    This contribution addresses the problem of aircraft noise prediction using theoretical methods. The problem is set in context with the needs at several levels to produce noise characterisation from commercial aircraft powered by gas turbine engines. We describe very briefly the computational model (whilst referring the reader to the appropriate literature), and provide examples of noise predictions and comparisons with measured data, where possible. We focus on the issue of stochastic analysi...

  13. Prediction of molecular crystal structures

    Energy Technology Data Exchange (ETDEWEB)

    Beyer, Theresa

    2001-07-01

    The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol{sup -1} of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

  14. Predictive Modelling of Cellular Load

    OpenAIRE

    Carolan, Emmett; McLoone, Seamus; Farrell, Ronan

    2015-01-01

    This work examines the temporal dynamics of cellular load in four Irish regions. Large scale underutilisation of network resources is identified both at the regional level and at the level of individual cells. Cellular load is modeled and prediction intervals are generated. These prediction intervals are used to put an upper bound on usage in a particular cell at a particular time. Opportunities for improvements in network utilization by incorporating these upper bounds on usage are identifie...

  15. Working postures: prediction and evaluation

    OpenAIRE

    Delleman, N.J.

    1999-01-01

    To date, workstation designers cannot see the effects of a design on working posture before a mock-up/prototype is available. At that moment, usually the margin for creating the conditions required for adopting favourable working postures is still very limited. Posture prediction at an early design phase, i.e. at the CAD screen, would enhance full consider-ation of ergonomics among other design aspects, as well as reducing costs for proper workstation design. For prediction, however, the dete...

  16. Predicting Strategy and Listening Comprehension

    OpenAIRE

    Yongmei Jiang

    2009-01-01

    The author found certain potential obstacles that students encounter in their listening class, which she believes should be removed by a good class teaching method. However, traditional listening class fails. She goes on to explore integrating strategies into listening class, among the many strategies she choose the prediction strategy and describes it in three stages: Pre-listening, while-listening, and post-listening. Then a real model of applying prediction in listening class is given, who...

  17. Prediction of interannual climate variations

    International Nuclear Information System (INIS)

    It has been known for some time that the behavior of the short-term fluctuations of the earth's atmosphere resembles that of a chaotic non-linear dynamical system, and that the day-to-day weather cannot be predicted beyond a few weeks. However, it has also been found that the interactions of the atmosphere with the underlying oceans and the land surfaces can produce fluctuations whose time scales are much longer than the limits of deterministic prediction of weather. It is, therefore, natural to ask whether it is possible that the seasonal and longer time averages of climate fluctuations can be predicted with sufficient skill to be beneficial for social and economic applications, even though the details of day-to-day weather cannot be predicted beyond a few weeks. The main objective of the workshop was to address this question by assessing the current state of knowledge on predictability of seasonal and interannual climate variability and to investigate various possibilities for its prediction. (orig./KW)

  18. Predicting Predictable: Accuracy and Reliability of Earthquake Forecasts

    Science.gov (United States)

    Kossobokov, V. G.

    2014-12-01

    Earthquake forecast/prediction is an uncertain profession. The famous Gutenberg-Richter relationship limits magnitude range of prediction to about one unit. Otherwise, the statistics of outcomes would be related to the smallest earthquakes and may be misleading when attributed to the largest earthquakes. Moreover, the intrinsic uncertainty of earthquake sizing allows self-deceptive picking of justification "just from below" the targeted magnitude range. This might be important encouraging evidence but, by no means, can be a "helpful" additive to statistics of a rigid testing that determines reliability and efficiency of a farecast/prediction method. Usually, earthquake prediction is classified in respect to expectation time while overlooking term-less identification of earthquake prone areas, as well as spatial accuracy. The forecasts are often made for a "cell" or "seismic region" whose area is not linked to the size of target earthquakes. This might be another source for making a wrong choice in parameterization of an forecast/prediction method and, eventually, for unsatisfactory performance in a real-time application. Summing up, prediction of time and location of an earthquake of a certain magnitude range can be classified into categories listed in the Table below - Classification of earthquake prediction accuracy Temporal, in years Spatial, in source zone size (L) Long-term 10 Long-range Up to 100 Intermediate-term 1 Middle-range 5-10 Short-term 0.01-0.1 Narrow-range 2-3 Immediate 0.001 Exact 1 Note that a wide variety of possible combinations that exist is much larger than usually considered "short-term exact" one. In principle, such an accurate statement about anticipated seismic extreme might be futile due to the complexities of the Earth's lithosphere, its blocks-and-faults structure, and evidently nonlinear dynamics of the seismic process. The observed scaling of source size and preparation zone with earthquake magnitude implies exponential scales for

  19. Strategy and methodology of dynamical analogue prediction

    Institute of Scientific and Technical Information of China (English)

    REN; HongLi; CHOU; JiFan

    2007-01-01

    In order to effectively improve numerical prediction level by using current models and data, the strategy and methodology of dynamical analogue prediction (DAP) is deeply studied in the present paper. A new idea to predict the prediction errors of dynamical model on the basis of historical analogue information is put forward so as to transform the dynamical prediction problem into the estimation problem of prediction errors. In terms of such an idea, a new prediction method of final analogue correction of errors (FACE) is developed. Furthermore, the FACE is applied to extra-seasonal prediction experiments on an operational atmosphere-ocean coupled general circulation model. Prediction results of summer mean circulation and total precipitation show that the FACE can to some extent reduce prediction errors, recover prediction variances, and improve prediction skills. Besides, sensitive experiments also show that predictions based on the FACE are evidently influenced by the number of analogues, analogue-selected variables and analogy metric.

  20. Prediction of GNSS satellite clocks

    International Nuclear Information System (INIS)

    This thesis deals with the characterisation and prediction of GNSS-satellite-clocks. A prerequisite to develop powerful algorithms for the prediction of clock-corrections is the thorough study of the behaviour of the different clock-types of the satellites. In this context the predicted part of the IGU-clock-corrections provided by the Analysis Centers (ACs) of the IGS was compared to the IGS-Rapid-clock solutions to determine reasonable estimates of the quality of already existing well performing predictions. For the shortest investigated interval (three hours) all ACs obtain almost the same accuracy of 0,1 to 0,4 ns. For longer intervals the individual predictions results start to diverge. Thus, for a 12-hours- interval the differences range from nearly 10 ns (GFZ, CODE) until up to some 'tens of ns'. Based on the estimated clock corrections provided via the IGS Rapid products a simple quadratic polynomial turns out to be sufficient to describe the time series of Rubidium-clocks. On the other hand Cesium-clocks show a periodical behaviour (revolution period) with an amplitude of up to 6 ns. A clear correlation between these amplitudes and the Sun elevation angle above the orbital planes can be demonstrated. The variability of the amplitudes is supposed to be caused by temperature-variations affecting the oscillator. To account for this periodical behaviour a quadratic polynomial with an additional sinus-term was finally chosen as prediction model both for the Cesium as well as for the Rubidium clocks. The three polynomial-parameters as well as amplitude and phase shift of the periodic term are estimated within a least-square-adjustment by means of program GNSS-VC/static. Input-data are time series of the observed part of the IGU clock corrections. With the estimated parameters clock-corrections are predicted for various durations. The mean error of the prediction of Rubidium-clock-corrections for an interval of six hours reaches up to 1,5 ns. For the 12-hours

  1. Lightning prediction using radiosonde data

    Energy Technology Data Exchange (ETDEWEB)

    Weng, L.Y.; Bin Omar, J.; Siah, Y.K.; Bin Zainal Abidin, I.; Ahmad, S.K. [Univ. Tenaga, Darul Ehsan (Malaysia). College of Engineering

    2008-07-01

    Lightning is a natural phenomenon in tropical regions. Malaysia experiences very high cloud-to-ground lightning density, posing both health and economic concerns to individuals and industries. In the commercial sector, power lines, telecommunication towers and buildings are most frequently hit by lightning. In the event that a power line is hit and the protection system fails, industries which rely on that power line would cease operations temporarily, resulting in significant monetary loss. Current technology is unable to prevent lightning occurrences. However, the ability to predict lightning would significantly reduce damages from direct and indirect lightning strikes. For that reason, this study focused on developing a method to predict lightning with radiosonde data using only a simple back propagation neural network model written in C code. The study was performed at the Kuala Lumpur International Airport (KLIA). In this model, the parameters related to wind were disregarded. Preliminary results indicate that this method shows some positive results in predicting lighting. However, a larger dataset is needed in order to obtain more accurate predictions. It was concluded that future work should include wind parameters to fully capture all properties for lightning formation, subsequently its prediction. 8 refs., 5 figs.

  2. Classical universes are perfectly predictable!

    Science.gov (United States)

    Schmidt, Jan Hendrik

    I argue that in a classical universe, all the events that ever happen are encoded in each of the universe's parts. This conflicts with a statement which is widely believed to lie at the basis of relativity theory: that the events in a space-time region R determine only the events in R's domain of dependence but not those in other space-time regions. I show how, from this understanding, a new prediction method (which I call the 'Smoothness Method') can be obtained which allows us to predict future events on the basis of local observational data. Like traditional prediction methods, this method makes use of so-called ' ceteris paribus clauses', i.e. assumptions about the unobserved parts of the universe. However, these assumptions are used in a way which enables us to predict the behaviour of open systems with arbitrary accuracy, regardless of the influence of their environment-which has not been achieved by traditional methods. In a sequel to this paper (Schmidt, 1998), I will prove the Uniqueness and Predictability Theorems on which the Smoothness Method is based, and comment in more detail on its mathematical properties.

  3. Prediction Method for Regional Logistics

    Institute of Scientific and Technical Information of China (English)

    QIU Ying; LU Huapu; WANG Haiwei

    2008-01-01

    Currently applied prediction methods of regional freight traffic and freight ton-kilometer forecasting were analyzed using typical Chinese regional goods transportation characteristics.The review of prediction methods showes that practical planning experts tend to apply the traditional methods which are easier to implement.The comparison also demonstrates that a combination of traditional methods is more effective than the simple models for practical planning.Research using the statistical data for the Yangtze Delta,Pearl River Delta,and Bohai Rim areas shows that ignoring differences between transport modes impacts the prediction accuracy.The four main transport modes suit different methods.The results show that the power model is better for railways,and the linear model is better for highways and waterways.Thus a combined model gives better results for all modes.The results for regional systems can be generalized to national transportation systems.

  4. Sentence-Level Attachment Prediction

    Science.gov (United States)

    Albakour, M.-Dyaa; Kruschwitz, Udo; Lucas, Simon

    Attachment prediction is the task of automatically identifying email messages that should contain an attachment. This can be useful to tackle the problem of sending out emails but forgetting to include the relevant attachment (something that happens all too often). A common Information Retrieval (IR) approach in analyzing documents such as emails is to treat the entire document as a bag of words. Here we propose a finer-grained analysis to address the problem. We aim at identifying individual sentences within an email that refer to an attachment. If we detect any such sentence, we predict that the email should have an attachment. Using part of the Enron corpus for evaluation we find that our finer-grained approach outperforms previously reported document-level attachment prediction in similar evaluation settings.

  5. Link Prediction via Matrix Completion

    CERN Document Server

    Pech, Ratha; Pan, Liming; Cheng, Hong; Zhou, Tao

    2016-01-01

    Inspired by practical importance of social networks, economic networks, biological networks and so on, studies on large and complex networks have attracted a surge of attentions in the recent years. Link prediction is a fundamental issue to understand the mechanisms by which new links are added to the networks. We introduce the method of robust principal component analysis (robust PCA) into link prediction, and estimate the missing entries of the adjacency matrix. On one hand, our algorithm is based on the sparsity and low rank property of the matrix, on the other hand, it also performs very well when the network is dense. This is because a relatively dense real network is also sparse in comparison to the complete graph. According to extensive experiments on real networks from disparate fields, when the target network is connected and sufficiently dense, whatever it is weighted or unweighted, our method is demonstrated to be very effective and with prediction accuracy being considerably improved comparing wit...

  6. Spatial prediction and ordinary kriging

    Energy Technology Data Exchange (ETDEWEB)

    Cressie, N.

    1988-05-01

    Suppose data /Z(s/sub i/):i = 1,...,n/ are observed at spatial locations /s/sub i/:i = 1,...,n/. From these data, an unknown Z(s/sub 0/) is to be predicted at a known location s/sub 0/, or, if Z(s/sub 0/) has a component of measurement error, then a smooth version S(s/sub 0/) should be predicted. This article considers the assumptions needed to carry out the spatial prediction using ordinary kriging, and looks at how nugget effect, range, and sill of the variogram affect the predictor. It is concluded that certain commonly held interpretations of these variogram parameters should be modified.

  7. Predicting performance of parallel computations

    Science.gov (United States)

    Mak, Victor W.; Lundstrom, Stephen F.

    1990-01-01

    An accurate and computationally efficient method for predicting the performance of a class of parallel computations running on concurrent systems is described. A parallel computation is modeled as a task system with precedence relationships expressed as a series-parallel directed acyclic graph. Resources in a concurrent system are modeled as service centers in a queuing network model. Using these two models as inputs, the method outputs predictions of expected execution time of the parallel computation and the concurrent system utilization. The method is validated against both detailed simulation and actual execution on a commercial multiprocessor. Using 100 test cases, the average error of the prediction when compared to simulation statistics is 1.7 percent, with a standard deviation of 1.5 percent; the maximum error is about 10 percent.

  8. Prediction Analysis for Measles Epidemics

    Science.gov (United States)

    Sumi, Ayako; Ohtomo, Norio; Tanaka, Yukio; Sawamura, Sadashi; Olsen, Lars Folke; Kobayashi, Nobumichi

    2003-12-01

    A newly devised procedure of prediction analysis, which is a linearized version of the nonlinear least squares method combined with the maximum entropy spectral analysis method, was proposed. This method was applied to time series data of measles case notification in several communities in the UK, USA and Denmark. The dominant spectral lines observed in each power spectral density (PSD) can be safely assigned as fundamental periods. The optimum least squares fitting (LSF) curve calculated using these fundamental periods can essentially reproduce the underlying variation of the measles data. An extension of the LSF curve can be used to predict measles case notification quantitatively. Some discussions including a predictability of chaotic time series are presented.

  9. Evoked emotions predict food choice.

    Directory of Open Access Journals (Sweden)

    Jelle R Dalenberg

    Full Text Available In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA and apply Multinomial Logit Models (MLM to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively. After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores.

  10. Evoked emotions predict food choice.

    Science.gov (United States)

    Dalenberg, Jelle R; Gutjar, Swetlana; Ter Horst, Gert J; de Graaf, Kees; Renken, Remco J; Jager, Gerry

    2014-01-01

    In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA) and apply Multinomial Logit Models (MLM) to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively). After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products) for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores. PMID:25521352

  11. Parity and Predictability of Competitions

    CERN Document Server

    Ben-Naim, E; Vázquez, F

    2006-01-01

    We present an extensive statistical analysis of the results of all sports competitions in five major sports leagues in England and the United States. We characterize the parity among teams by the variance in the winning fraction from season-end standings data and quantify the predictability of games by the frequency of upsets from game results data. We introduce a novel mathematical model in which the underdog team wins with a fixed upset probability. This model quantitatively relates the parity among teams with the predictability of the games, and it can be used to estimate the upset frequency from standings data.

  12. Four Centuries of Return Predictability

    OpenAIRE

    Benjamin Golez; Peter Koudijs

    2014-01-01

    We analyze four centuries of stock prices and dividends in the Dutch, English, and U.S. market. With the exception of the post-1945 period, the dividend-to-price ratio is stationary and predicts returns throughout all four centuries. “Excess volatility” is thus a pervasive feature of financial markets. The dividend-to-price ratio also predicts dividend growth rates in all but the most recent period. Cash-flows were therefore much more important for price movements before 1945, and the dominan...

  13. Wind energy prediction; Prediccion eolica

    Energy Technology Data Exchange (ETDEWEB)

    Xiberta, B. J.; Florez, M. V. E.

    2004-07-01

    On March 12th, 2004 the Spanish Government modified the legal situation of the renewable energies following the approval of RD 436/2004. This makes necessary the development of wind energy prediction models for its entrance to the daily electricity market like the conventional energies. The improvement of physical models, meteorological models, or a combination of both, is necessary for the prediction of the wind generation. This will guarantee the wind energy full utilization and the participation in the electrical market, as well as the remuneration of the complementary services and the regulation of reactive electricity. In this way wind energy turns into a perfectly manageable one. (Author)

  14. Can we predict nuclear proliferation

    International Nuclear Information System (INIS)

    The author aims at improving nuclear proliferation prediction capacities, i.e. the capacities to identify countries susceptible to acquire nuclear weapons, to interpret sensitive activities, and to assess nuclear program modalities. He first proposes a retrospective assessment of counter-proliferation actions since 1945. Then, based on academic studies, he analyzes what causes and motivates proliferation, with notably the possibility of existence of a chain phenomenon (mechanisms driving from one program to another). He makes recommendations for a global approach to proliferation prediction, and proposes proliferation indices and indicators

  15. Plans for Aeroelastic Prediction Workshop

    Science.gov (United States)

    Heeg, Jennifer; Ballmann, Josef; Bhatia, Kumar; Blades, Eric; Boucke, Alexander; Chwalowski, Pawel; Dietz, Guido; Dowell, Earl; Florance, Jennifer P.; Hansen, Thorsten; Mani, Mori; Marvriplis, Dimitri; Perry, Boyd, III; Ritter, Markus; Schuster, David M.; Smith, Marilyn; Taylor, Paul; Whiting, Brent; Wieseman, Carol C.

    2011-01-01

    This paper summarizes the plans for the first Aeroelastic Prediction Workshop. The workshop is designed to assess the state of the art of computational methods for predicting unsteady flow fields and aeroelastic response. The goals are to provide an impartial forum to evaluate the effectiveness of existing computer codes and modeling techniques, and to identify computational and experimental areas needing additional research and development. Three subject configurations have been chosen from existing wind tunnel data sets where there is pertinent experimental data available for comparison. For each case chosen, the wind tunnel testing was conducted using forced oscillation of the model at specified frequencies

  16. Algorithms for Protein Structure Prediction

    OpenAIRE

    Paluszewski, Martin

    2008-01-01

    The problem of predicting the three-dimensional structure of a protein given itsamino acid sequence is one of the most important open problems in bioinformatics.One of the carbon atoms in amino acids is the C-atom and the overallstructure of a protein is often represented by a so-called C-trace.Here we present three different approaches for reconstruction of C-tracesfrom predictable measures. In our first approach [63, 62], the C-trace is positionedon a lattice and a tabu-search algorithm is ...

  17. Prediction of eyespot infection risks

    Directory of Open Access Journals (Sweden)

    M. Váòová

    2012-12-01

    Full Text Available The objective of the study was to design a prediction model for eyespot (Tapesia yallundae infection based on climatic factors (temperature, precipitation, air humidity. Data from experiment years 1994-2002 were used to study correlations between the eyespot infection index and individual weather characteristics. The model of prediction was constructed using multiple regression when a separate parameter is assigned to each factor, i.e. the frequency of days with optimum temperatures, humidity, and precipitation. The correlation between relative air humidity and precipitation and the infection index is significant.

  18. Protein structural domains: definition and prediction.

    Science.gov (United States)

    Ezkurdia, Iakes; Tress, Michael L

    2011-11-01

    Recognition and prediction of structural domains in proteins is an important part of structure and function prediction. This unit lists the range of tools available for domain prediction, and describes sequence and structural analysis tools that complement domain prediction methods. Also detailed are the basic domain prediction steps, along with suggested strategies for different protein sequences and potential pitfalls in domain boundary prediction. The difficult problem of domain orientation prediction is also discussed. All the resources necessary for domain boundary prediction are accessible via publicly available Web servers and databases and do not require computational expertise. PMID:22045561

  19. Zephyr - the next generation prediction

    DEFF Research Database (Denmark)

    Giebel, G.; Landberg, L.; Nielsen, Torben Skov;

    2001-01-01

    Java2TM platform and Enterprise Java Beans technology, and it will ensure that the best forecasts are given on all prediction horizons from the short range (0-9 hours) to the long range (36-48 hours). This is because the IMM approach uses online data and advanced statistical methods, which is...

  20. Can Creativity Predict Cognitive Reserve?

    Science.gov (United States)

    Palmiero, Massimiliano; Di Giacomo, Dina; Passafiume, Domenico

    2016-01-01

    Cognitive reserve relies on the ability to effectively cope with aging and brain damage by using alternate processes to approach tasks when standard approaches are no longer available. In this study, the issue if creativity can predict cognitive reserve has been explored. Forty participants (mean age: 61 years) filled out: the Cognitive Reserve…

  1. Predictability of Mobile Phone Associations

    DEFF Research Database (Denmark)

    Jensen, Bjørn Sand; Larsen, Jan; Hansen, Lars Kai;

    2010-01-01

    Prediction and understanding of human behavior is of high importance in many modern applications and research areas ranging from context-aware services, wireless resource allocation to social sciences. In this study we collect a novel dataset using standard mobile phones and analyze how the predi...

  2. Predictibility in Nowcasting of Precipitation

    Science.gov (United States)

    Zawadzki, I.; Sourcel, M.; Berenguer, M.

    2009-05-01

    Present short term precipitation forecasting is based on two methods: Lagrangian persistence (nowcasting) and numerical weather prediction (NWP). An improvement over these methods is obtained by the combination of the two. The obvious shortcoming of nowcasting is its severe limitation in capturing new development or dissipation of precipitation. NWP has the ability to predict both but very imprecisely. An attempt to correct model errors by post-processing leads to some improvement in the skill of NWP, but the improvement, although significative, is not very impressive. The goal of our effort is to take a step back and to describe, in a quantitative manner, a) the nature of the uncertainties affecting Lagrangian persistence and NWP forecasts, as well as to determineb) the physical causes of the uncertainties. We quantify the uncertainties in short term forecasting due to limitation of nowcasting algorithms and NWP to capture correctly some of the physical phenomena that determine the predictability of precipitation. The first factor considered is the diurnal cycle that appears as the one physically determined factors that limit the precision of short term prediction. We study the cycle in radar mosaics over US and compare this to nowcasts and model outputs. The seasonal and geographical dependence of the diurnal cycle is quantitatively evaluated.

  3. TRITIUM RESERVOIR STRUCTURAL PERFORMANCE PREDICTION

    Energy Technology Data Exchange (ETDEWEB)

    Lam, P.S.; Morgan, M.J

    2005-11-10

    The burst test is used to assess the material performance of tritium reservoirs in the surveillance program in which reservoirs have been in service for extended periods of time. A materials system model and finite element procedure were developed under a Savannah River Site Plant-Directed Research and Development (PDRD) program to predict the structural response under a full range of loading and aged material conditions of the reservoir. The results show that the predicted burst pressure and volume ductility are in good agreement with the actual burst test results for the unexposed units. The material tensile properties used in the calculations were obtained from a curved tensile specimen harvested from a companion reservoir by Electric Discharge Machining (EDM). In the absence of exposed and aged material tensile data, literature data were used for demonstrating the methodology in terms of the helium-3 concentration in the metal and the depth of penetration in the reservoir sidewall. It can be shown that the volume ductility decreases significantly with the presence of tritium and its decay product, helium-3, in the metal, as was observed in the laboratory-controlled burst tests. The model and analytical procedure provides a predictive tool for reservoir structural integrity under aging conditions. It is recommended that benchmark tests and analysis for aged materials be performed. The methodology can be augmented to predict performance for reservoir with flaws.

  4. Evaluation of environmental impact predictions

    International Nuclear Information System (INIS)

    An analysis and evaluation of the ecological monitoring program at the Surry Nuclear Power Plant showed that predictions of potential environmental impact made in the Final Environmental Statement (FES), which were based on generally accepted ecological principles, were not completely substantiated by environmental monitoring data. The Surry Nuclear Power Plant (Units 1 and 2) was chosen for study because of the facility's relatively continuous operating history and the availability of environmental data adequate for analysis. Preoperational and operational fish monitoring data were used to assess the validity of the FES prediction that fish would congregate in the thermal plume during winter months and would avoid the plume during summer months. Analysis of monitoring data showed that fish catch per unit effort (CPE) was generally high in the thermal plume during winter months; however, the highest fish catches occurred in the plume during the summer. Possible explanations for differences between the FES prediction and results observed in analysis of monitoring data are discussed, and general recommendations are outlined for improving impact assessment predictions

  5. On sieve bootstrap prediction intervals.

    OpenAIRE

    Andrés M. Alonso; Peña, Daniel; Romo Urroz, Juan

    2003-01-01

    In this paper we consider a sieve bootstrap method for constructing nonparametric prediction intervals for a general class of linear processes. We show that the sieve bootstrap provides consistent estimators of the conditional distribution of future values given the observed data.

  6. Cancer Risk Prediction and Assessment

    Science.gov (United States)

    Cancer prediction models provide an important approach to assessing risk and prognosis by identifying individuals at high risk, facilitating the design and planning of clinical cancer trials, fostering the development of benefit-risk indices, and enabling estimates of the population burden and cost of cancer.

  7. Intermediate-term earthquake prediction.

    Science.gov (United States)

    Keilis-Borok, V I

    1996-04-30

    An earthquake of magnitude M and linear source dimension L(M) is preceded within a few years by certain patterns of seismicity in the magnitude range down to about (M - 3) in an area of linear dimension about 5L-10L. Prediction algorithms based on such patterns may allow one to predict approximately 80% of strong earthquakes with alarms occupying altogether 20-30% of the time-space considered. An area of alarm can be narrowed down to 2L-3L when observations include lower magnitudes, down to about (M - 4). In spite of their limited accuracy, such predictions open a possibility to prevent considerable damage. The following findings may provide for further development of prediction methods: (i) long-range correlations in fault system dynamics and accordingly large size of the areas over which different observed fields could be averaged and analyzed jointly, (ii) specific symptoms of an approaching strong earthquake, (iii) the partial similarity of these symptoms worldwide, (iv) the fact that some of them are not Earth specific: we probably encountered in seismicity the symptoms of instability common for a wide class of nonlinear systems. PMID:11607660

  8. Working postures: prediction and evaluation

    NARCIS (Netherlands)

    Delleman, N.J.

    1999-01-01

    To date, workstation designers cannot see the effects of a design on working posture before a mock-up/prototype is available. At that moment, usually the margin for creating the conditions required for adopting favourable working postures is still very limited. Posture prediction at an early design

  9. Prediction of natural gas consumption

    International Nuclear Information System (INIS)

    Distributors of natural gas need to predict future consumption in order to purchase a sufficient supply on contract. Distributors that offer their customers equal payment plans need to predict the consumption of each customer 12 months in advance. Estimates of previous consumption are often used for months when meters are inaccessible, or bimonthly-read meters. Existing methods of predicting natural gas consumption, and a proposed new method for each local region are discussed. The proposed model distinguishes the consumption load factors from summer to other seasons by attempting to adjust them by introducing two parameters. The problem is then reduced to a quadratic programming problem. However, since it is not necessary to use both parameters simultaneously, the problem can be solved with a simple iterative procedure. Results show that the new model can improve the two-equation model to a certain scale. The adjustment to heat load factor can reduce the error of prediction markedly while that to base load factor influences the error marginally. 3 refs., 11 figs., 2 tabs

  10. The PredictAD project

    DEFF Research Database (Denmark)

    Antila, Kari; Lötjönen, Jyrki; Thurfjell, Lennart;

    2013-01-01

    objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data...

  11. Solution Patterns Predicting Pythagorean Triples

    Science.gov (United States)

    Ezenweani, Ugwunna Louis

    2013-01-01

    Pythagoras Theorem is an old mathematical treatise that has traversed the school curricula from secondary to tertiary levels. The patterns it produced are quite interesting that many researchers have tried to generate a kind of predictive approach to identifying triples. Two attempts, namely Diophantine equation and Brahmagupta trapezium presented…

  12. The Predictive Value of IQ.

    Science.gov (United States)

    Sternberg, Robert J.; Grigorenko, Elena L.; Bundy, Donald A.

    2001-01-01

    Reviews findings on the predictive validity of psychometric tests of intelligence. Concludes that conventional tests of intelligence can be useful but only if they are interpreted very carefully, taking into account the factors that can affect them, and in conjunction with other measures. (Author)

  13. Predictive implications of Gompertz's law

    Science.gov (United States)

    Richmond, Peter; Roehner, Bertrand M.

    2016-04-01

    Gompertz's law tells us that for humans above the age of 35 the death rate increases exponentially with a doubling time of about 10 years. Here, we show that the same law continues to hold up to age 106. At that age the death rate is about 50%. Beyond 106 there is so far no convincing statistical evidence available because the number of survivors are too small even in large nations. However, assuming that Gompertz's law continues to hold beyond 106, we conclude that the mortality rate becomes equal to 1 at age 120 (meaning that there are 1000 deaths in a population of one thousand). In other words, the upper bound of human life is near 120. The existence of this fixed-point has interesting implications. It allows us to predict the form of the relationship between death rates at age 35 and the doubling time of Gompertz's law. In order to test this prediction, we first carry out a transversal analysis for a sample of countries comprising both industrialized and developing nations. As further confirmation, we also develop a longitudinal analysis using historical data over a time period of almost two centuries. Another prediction arising from this fixed-point model, is that, above a given population threshold, the lifespan of the oldest persons is independent of the size of their national community. This prediction is also supported by empirical evidence.

  14. Multimodal Imaging Measures Predict Rearrest

    Directory of Open Access Journals (Sweden)

    Vaughn R Steele

    2015-08-01

    Full Text Available Rearrest has been predicted by hemodynamic activity in the anterior cingulate cortex (ACC during error-processing (Aharoni et al., 2013. Here we evaluate the predictive power after adding an additional imaging modality in a subsample of 45 incarcerated males from Aharoni et al. Event-related potentials (ERPs and hemodynamic activity were collected during a Go/NoGo response inhibition task. Neural measures of error-processing were obtained from the ACC and two ERP components, the error-related negativity (ERN/Ne and the error positivity (Pe. Measures from the Pe and ACC differentiated individuals who were and were not subsequently rearrested. Cox regression, logistic regression, and support vector machine (SVM neuroprediction models were calculated. Each of these models proved successful in predicting rearrest and SVM provided the strongest results. Multimodal neuroprediction SVM models with out of sample cross-validating accurately predicted rearrest (83.33%. Offenders with increased Pe amplitude and decreased ACC activation, suggesting abnormal error-processing, were at greatest risk of rearrest.

  15. Prediction of Malaysian monthly GDP

    Science.gov (United States)

    Hin, Pooi Ah; Ching, Soo Huei; Yeing, Pan Wei

    2015-12-01

    The paper attempts to use a method based on multivariate power-normal distribution to predict the Malaysian Gross Domestic Product next month. Letting r(t) be the vector consisting of the month-t values on m selected macroeconomic variables, and GDP, we model the month-(t+1) GDP to be dependent on the present and l-1 past values r(t), r(t-1),…,r(t-l+1) via a conditional distribution which is derived from a [(m+1)l+1]-dimensional power-normal distribution. The 100(α/2)% and 100(1-α/2)% points of the conditional distribution may be used to form an out-of sample prediction interval. This interval together with the mean of the conditional distribution may be used to predict the month-(t+1) GDP. The mean absolute percentage error (MAPE), estimated coverage probability and average length of the prediction interval are used as the criterions for selecting the suitable lag value l-1 and the subset from a pool of 17 macroeconomic variables. It is found that the relatively better models would be those of which 2 ≤ l ≤ 3, and involving one or two of the macroeconomic variables given by Market Indicative Yield, Oil Prices, Exchange Rate and Import Trade.

  16. Evoked Emotions Predict Food Choice

    NARCIS (Netherlands)

    Dalenberg, Jelle R.; Gutjar, Swetlana; ter Horst, Gert J.; de Graaf, Kees; Renken, Remco J.; Jager, Gerry

    2014-01-01

    In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Th

  17. Predicting sporadic Grid data transfers

    International Nuclear Information System (INIS)

    The increasingly common practice of (1) replicating datasets and (2) using resources as distributed data stores in Grid environments has lead to the problem of determining which replica can be accessed most efficiently. Due to diverse performance characteristics and load variations of several components in the end-to-end path linking these various locations, selecting a replica location from among many requires accurate prediction information of end-to-end data transfer times between the sources and sinks. In this paper, we present a prediction system that is based on combining end-to-end application throughput observations and network load variations, drawing from their merits of capturing whole system performance and variations in load patterns respectively. We develop a set of regression models to derive predictions that characterize the effect of network load variations on file transfer times. We apply these techniques to the GridFTP data movement tool, part of the Globus Toolkit(sup TM), and observe performance gains of up to 10% in prediction accuracy when compared to approaches based on past system behavior in isolation

  18. Predicting microbial traits with phylogenies.

    Science.gov (United States)

    Goberna, Marta; Verdú, Miguel

    2016-04-01

    Phylogeny reflects genetic and phenotypic traits in Bacteria and Archaea. The phylogenetic conservatism of microbial traits has prompted the application of phylogeny-based algorithms to predict unknown trait values of extant taxa based on the traits of their evolutionary relatives to estimate, for instance, rRNA gene copy numbers, gene contents or tolerance to abiotic conditions. Unlike the 'macrobial' world, microbial ecologists face scenarios potentially compromising the accuracy of trait reconstruction methods, as, for example, extremely large phylogenies and limited information on the traits of interest. We review 990 bacterial and archaeal traits from the literature and support that phylogenetic trait conservatism is widespread through the tree of life, while revealing that it is generally weak for ecologically relevant phenotypic traits and high for genetically complex traits. We then perform a simulation exercise to assess the accuracy of phylogeny-based trait predictions in common scenarios faced by microbial ecologists. Our simulations show that ca. 60% of the variation in phylogeny-based trait predictions depends on the magnitude of the trait conservatism, the number of species in the tree, the proportion of species with unknown trait values and the mean distance in the tree to the nearest neighbour with a known trait value. Results are similar for both binary and continuous traits. We discuss these results under the light of the reviewed traits and provide recommendations for the use of phylogeny-based trait predictions for microbial ecologists. PMID:26371406

  19. Summertime Thunderstorms Prediction in Belarus

    Science.gov (United States)

    Lapo, Palina; Sokolovskaya, Yaroslava; Krasouski, Aliaksandr; Svetashev, Alexander; Turishev, Leonid; Barodka, Siarhei

    2015-04-01

    Mesoscale modeling with the Weather Research & Forecasting (WRF) system makes it possible to predict thunderstorm formation events by direct numerical simulation. In the present study, we analyze the feasibility and quality of thunderstorm prediction on the territory of Belarus for the summer period of 2014 based on analysis of several characteristic parameters in WRF modeling results that can serve as indicators of thunderstorms formation. These parameters include vertical velocity distribution, convective available potential energy (CAPE), K-index, SWEAT-index, Thompson index, lifted condensation level (LCL), and others, all of them being indicators of favorable atmospheric conditions for thunderstorms development. We perform mesoscale simulations of several cases of thunderstorm development in Belarus with WRF-ARW modeling system using 3 km grid spacing, WSM6 microphysics parameterization and explicit convection (no convective parameterization). Typical modeling duration makes 48 hours, which is equivalent to next-day thunderstorm prediction in operational use. We focus our attention to most prominent cases of intense thunderstorms in Minsk. For validation purposes, we use radar and satellite data in addition to surface observations. In summertime, the territory of Belarus is quite often under the influence of atmospheric fronts and stationary anticyclones. In this study, we subdivide thunderstorm cases under consideration into 2 categories: thunderstorms related to free convection and those related to forced convection processes. Our aim is to study the differences in thunderstorm indicator parameters between these two categories of thunderstorms in order to elaborate a set of parameters that can be used for operational thunderstorm forecasting. For that purpose, we analyze characteristic features of thunderstorms development on cold atmospheric fronts as well as thunderstorms formation in stable air masses. Modeling results demonstrate good predictive skill

  20. Modeling uncertainty: Predictive accuracy as a proxy for predictive confidence

    OpenAIRE

    Rich, Robert; Tracy, Joseph

    2003-01-01

    This paper evaluates current strategies for the empirical modeling of forecast behavior. In particular, we focus on the reliability of using proxies from time series models of heteroskedasticity to describe changes in predictive confidence. We address this issue by examining the relationship between ex post forecast errors and ex ante measures of forecast uncertainty from data on inflation forecasts from the Survey of Professional Forecasters. The results provide little evidence of a strong l...

  1. Predictive Technologies: Can Smart Tools Augment the Brain's Predictive Abilities?

    Science.gov (United States)

    Pezzulo, Giovanni; D'Ausilio, Alessandro; Gaggioli, Andrea

    2016-01-01

    The ability of "looking into the future"-namely, the capacity of anticipating future states of the environment or of the body-represents a fundamental function of human (and animal) brains. A goalkeeper who tries to guess the ball's direction; a chess player who attempts to anticipate the opponent's next move; or a man-in-love who tries to calculate what are the chances of her saying yes-in all these cases, people are simulating possible future states of the world, in order to maximize the success of their decisions or actions. Research in neuroscience is showing that our ability to predict the behavior of physical or social phenomena is largely dependent on the brain's ability to integrate current and past information to generate (probabilistic) simulations of the future. But could predictive processing be augmented using advanced technologies? In this contribution, we discuss how computational technologies may be used to support, facilitate or enhance the prediction of future events, by considering exemplificative scenarios across different domains, from simpler sensorimotor decisions to more complex cognitive tasks. We also examine the key scientific and technical challenges that must be faced to turn this vision into reality. PMID:27199648

  2. Neural Networks for protein Structure Prediction

    DEFF Research Database (Denmark)

    Bohr, Henrik

    1998-01-01

    This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones, is...

  3. BDDCS Class Prediction for New Molecular Entities

    DEFF Research Database (Denmark)

    Broccatelli, Fabio; Cruciani, Gabriele; Benet, Leslie Z.;

    2012-01-01

    the prediction, which showed highest accuracy in predicting classes 2 and 3 with respect to the most populated class 1. For class 4 drugs a general lack of predictability was observed. A linear discriminant analysis (LDA) confirming the degree of accuracy for the prediction of the different BDDCS classes is tied...

  4. Positive parity pentaquarks pragmatically predicted

    International Nuclear Information System (INIS)

    We consider the possibility that the lightest pentaquark is a parity-even state, with one unit of orbital angular momentum. Working within the framework of a constituent quark model, we show that dominant spin-flavor interactions render certain parity-even states lighter than any pentaquark with all quarks in the spatial ground state. For such states, we focus on predicting the mass and decays of other members of the same SU(3) flavor multiplet. Specifically, we consider the strangeness -2 cascade pentaquarks, which are relatively immune to mixing. We take into account flavor SU(3) breaking effects originating from the strange quark mass as well as from the structure of the spin-flavor exchange interactions themselves. We predict the lightest cascade pentaquarks at approximately 1906 MeV, with a full width ∼3 times larger than that of the Θ+

  5. WAVE ASSIMILATION AND NUMERICAL PREDICTION

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    An adjoint variational method for wave data assimilation in the LAGFD-WAM wave model is proposed. The adjoint equation of the wavenumber energy spectrum balance equation is derived. And fortunately, its characteristic equations are the same as those in the LAGFD-WAM wave model. Simple experiments on the functional optimization and assimilation effectiveness during the prediction period indicated that the adjoint variational method is effective for wave assimilation and that the initial optimization of the wave model is important for the short-range wave prediction. All of this is under the assumption that the wind field is accurate, the method is the important first step for combined wind and wave data assimilation systems.

  6. Time-Predictable Computer Architecture

    Directory of Open Access Journals (Sweden)

    Schoeberl Martin

    2009-01-01

    Full Text Available Today's general-purpose processors are optimized for maximum throughput. Real-time systems need a processor with both a reasonable and a known worst-case execution time (WCET. Features such as pipelines with instruction dependencies, caches, branch prediction, and out-of-order execution complicate WCET analysis and lead to very conservative estimates. In this paper, we evaluate the issues of current architectures with respect to WCET analysis. Then, we propose solutions for a time-predictable computer architecture. The proposed architecture is evaluated with implementation of some features in a Java processor. The resulting processor is a good target for WCET analysis and still performs well in the average case.

  7. Focus on astronomical predictable events

    DEFF Research Database (Denmark)

    Jacobsen, Aase Roland

    2006-01-01

    At the Steno Museum Planetarium we have for many occasions used a countdown clock to get focus om astronomical events. A countdown clock can provide actuality to predictable events, for example The Venus Transit, Opportunity landing on Mars and The Solar Eclipse. The movement of the clock attracs...... the public and makes a point of interest in a small exhibit area. A countdown clock can be simple, but it is possible to expand the concept to an eye-catching part of a museum.......At the Steno Museum Planetarium we have for many occasions used a countdown clock to get focus om astronomical events. A countdown clock can provide actuality to predictable events, for example The Venus Transit, Opportunity landing on Mars and The Solar Eclipse. The movement of the clock attracs...

  8. Predicting Virtual Learning Environment Adoption

    DEFF Research Database (Denmark)

    Penjor, Sonam; Zander, Pär-Ola Mikael

    2016-01-01

    This study investigates the significance of Rogers’ Diffusion of Innovations (DOI) theory with regard to the use of a Virtual Learning Environment (VLE) at the Royal University of Bhutan (RUB). The focus is on different adoption types and characteristics of users. Rogers’ DOI theory is applied...... towards VLE adoption by academic staff at RUB. Few predictors were consistent with previous research on VLE adoption. There were also significant differences from previous research on predictors such as the deviation in adopter frequency from that predicted by Rogers DOI theory. Therefore, it can...... be concluded that it is misleading to rely on the DOI theory in the way it is currently operationalised for predicting VLE use....

  9. Confidence Estimation in Structured Prediction

    CERN Document Server

    Mejer, Avihai

    2011-01-01

    Structured classification tasks such as sequence labeling and dependency parsing have seen much interest by the Natural Language Processing and the machine learning communities. Several online learning algorithms were adapted for structured tasks such as Perceptron, Passive- Aggressive and the recently introduced Confidence-Weighted learning . These online algorithms are easy to implement, fast to train and yield state-of-the-art performance. However, unlike probabilistic models like Hidden Markov Model and Conditional random fields, these methods generate models that output merely a prediction with no additional information regarding confidence in the correctness of the output. In this work we fill the gap proposing few alternatives to compute the confidence in the output of non-probabilistic algorithms.We show how to compute confidence estimates in the prediction such that the confidence reflects the probability that the word is labeled correctly. We then show how to use our methods to detect mislabeled wor...

  10. Algorithms for Protein Structure Prediction

    DEFF Research Database (Denmark)

    Paluszewski, Martin

    -trace. Here we present three different approaches for reconstruction of C-traces from predictable measures. In our first approach [63, 62], the C-trace is positioned on a lattice and a tabu-search algorithm is applied to find minimum energy structures. The energy function is based on half-sphere-exposure (HSE......) is more robust than standard Monte Carlo search. In the second approach for reconstruction of C-traces, an exact branch and bound algorithm has been developed [67, 65]. The model is discrete and makes use of secondary structure predictions, HSE, CN and radius of gyration. We show how to compute good lower...... bounds for partial structures very fast. Using these lower bounds, we are able to find global minimum structures in a huge conformational space in reasonable time. We show that many of these global minimum structures are of good quality compared to the native structure. Our branch and bound algorithm...

  11. Predicting Failures in Power Grids

    CERN Document Server

    Chertkov, Michael; Stepanov, Mikhail G

    2010-01-01

    Here we develop an approach to predict power grid weak points, and specifically to efficiently identify the most probable failure modes in load distribution for a given power network. This approach is applied to two examples: Guam's power system and also the IEEE RTS-96 system, both modeled within the static Direct Current power flow model. Our algorithm is a power network adaption of the worst configuration heuristics, originally developed to study low probability events in physics and failures in error-correction. One finding is that, if the normal operational mode of the grid is sufficiently healthy, the failure modes, also called instantons, are sufficiently sparse, i.e. the failures are caused by load fluctuations at only a few buses. The technique is useful for discovering weak links which are saturated at the instantons. It can also identify overutilized and underutilized generators, thus providing predictive capability for improving the reliability of any power network.

  12. Prediction of future asset prices

    Science.gov (United States)

    Seong, Ng Yew; Hin, Pooi Ah; Ching, Soo Huei

    2014-12-01

    This paper attempts to incorporate trading volumes as an additional predictor for predicting asset prices. Denoting r(t) as the vector consisting of the time-t values of the trading volume and price of a given asset, we model the time-(t+1) asset price to be dependent on the present and l-1 past values r(t), r(t-1), ....., r(t-1+1) via a conditional distribution which is derived from a (2l+1)-dimensional power-normal distribution. A prediction interval based on the 100(α/2)% and 100(1-α/2)% points of the conditional distribution is then obtained. By examining the average lengths of the prediction intervals found by using the composite indices of the Malaysia stock market for the period 2008 to 2013, we found that the value 2 appears to be a good choice for l. With the omission of the trading volume in the vector r(t), the corresponding prediction interval exhibits a slightly longer average length, showing that it might be desirable to keep trading volume as a predictor. From the above conditional distribution, the probability that the time-(t+1) asset price will be larger than the time-t asset price is next computed. When the probability differs from 0 (or 1) by less than 0.03, the observed time-(t+1) increase in price tends to be negative (or positive). Thus the above probability has a good potential of being used as a market indicator in technical analysis.

  13. Prediction for RNA planar pseudoknots

    Institute of Scientific and Technical Information of China (English)

    Li Hengwu; Zhu Daming; Liu Zhendong; Li Hong

    2007-01-01

    Based on m-stems and semi-extensible structure, a model is presented to represent RNA planar pseudoknots, and corresponding dynamic programming algorithm is designed and implemented to predict arbitrary planar pseudoknots and simple non-planar pseudoknots with O(n4) time and O(n3) space. The algorithm folds total 245 sequences in the Pseudobase database, and the test results indicate that the algorithm has good accuracy, sensitivity and specificity.

  14. The Variables Predicting Couple Burnout

    OpenAIRE

    Çapri, Burhan; Gökçakan, Zafer

    2013-01-01

    The purpose of the study is to investigate the contributions of variables concerned with socio-demographic features, career burnout, marital adjustment, spouse support, marriage and relationship on the prediction of couple burnout of married individuals. The research group consisted of 435 married females (n= 235) and males (n= 200), who are university staff in different units of Mersin University, selected randomly from the population and who accepted to join the study voluntarily. In order ...

  15. Predicting Comprehension from Students’ Summaries

    OpenAIRE

    Dascălu, Mihai; Larise Stavarache, Lucia; Dessus, Philippe; Trausan-Matu, Stefan; McNamara, Danielle,; Bianco, Maryse

    2015-01-01

    Comprehension among young students represents a key component of their formation throughout the learning process. Moreover, scaffolding students as they learn to coherently link information, while organically construct- ing a solid knowledge base, is crucial to students’ development, but requires regular assessment and progress tracking. To this end, our aim is to provide an automated solution for analyzing and predicting students’ comprehension levels by extracting a combination of reading s...

  16. Predictive Overlapping Co-Clustering

    OpenAIRE

    Sarkar, Chandrima; Srivastava, Jaideep

    2014-01-01

    In the past few years co-clustering has emerged as an important data mining tool for two way data analysis. Co-clustering is more advantageous over traditional one dimensional clustering in many ways such as, ability to find highly correlated sub-groups of rows and columns. However, one of the overlooked benefits of co-clustering is that, it can be used to extract meaningful knowledge for various other knowledge extraction purposes. For example, building predictive models with high dimensiona...

  17. Neuroanatomy Predicts Individual Risk Attitudes

    OpenAIRE

    Gilaie-Dotan, Sharon; Tymula, Agnieszka; Cooper, Nicole; Kable, Joseph W.; Glimcher, Paul W.; Levy, Ifat

    2014-01-01

    Over the course of the last decade a multitude of studies have investigated the relationship between neural activations and individual human decision-making. Here we asked whether the anatomical features of individual human brains could be used to predict the fundamental preferences of human choosers. To that end, we quantified the risk attitudes of human decision-makers using standard economic tools and quantified the gray matter cortical volume in all brain areas using standard neurobiologi...

  18. Black holes, singularities and predictability

    International Nuclear Information System (INIS)

    The paper favours the view that singularities may play a central role in quantum gravity. The author reviews the arguments leading to the conclusion, that in the process of black hole formation and evaporation, an initial pure state evolves to a final density matrix, thus signaling a breakdown in ordinary quantum dynamical evolution. Some related issues dealing with predictability in the dynamical evolution, are also discussed. (U.K.)

  19. Preconditioned Continuation Model Predictive Control

    OpenAIRE

    Knyazev, Andrew; Fujii, Yuta; Malyshev, Alexander,

    2015-01-01

    Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) describes systems with nonlinear models and/or constraints. A Continuation/GMRES Method for NMPC, suggested by T. Ohtsuka in 2004, uses the GMRES iterative algorithm to solve a forward difference approximation $Ax=b$ of the Continuation NMPC (CNMPC) equations on every time step. The coefficient matrix $A$ of the linear system is often ill-conditioned, resulting in poor GMRES conv...

  20. Evoked Emotions Predict Food Choice

    OpenAIRE

    Dalenberg, Jelle R.; Swetlana Gutjar; ter Horst, Gert J.; Kees de Graaf; Renken, Remco J.; Gerry Jager

    2014-01-01

    In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well ...

  1. Is quantum theory predictably complete?

    International Nuclear Information System (INIS)

    Quantum theory (QT) provides statistical predictions for various physical phenomena. To verify these predictions a considerable amount of data has been accumulated in the 'measurements' performed on the ensembles of identically prepared physical systems or in the repeated 'measurements' on some trapped 'individual physical systems'. The outcomes of these measurements are, in general, some numerical time series registered by some macroscopic instruments. The various empirical probability distributions extracted from these time series were shown to be consistent with the probabilistic predictions of QT. More than 70 years ago the claim was made that QT provided the most complete description of 'individual' physical systems and outcomes of the measurements performed on 'individual' physical systems were obtained in an intrinsically random way. Spin polarization correlation experiments (SPCEs), performed to test the validity of Bell inequalities, clearly demonstrated the existence of strong long-range correlations and confirmed that the beams hitting far away detectors somehow preserve the memory of their common source which would be destroyed if the individual counts of far away detectors were purely random. Since the probabilities describe the random experiments and are not the attributes of the 'individual' physical systems, the claim that QT provides a complete description of 'individual' physical systems seems not only unjustified but also misleading and counter productive. In this paper, we point out that we even do not know whether QT is predictably complete because it has not been tested carefully enough. Namely, it was not proven that the time series of existing experimental data did not contain some stochastic fine structures that could have been averaged out by describing them in terms of the empirical probability distributions. In this paper, we advocate various statistical tests that could be used to search for such fine structures in the data and to

  2. Software Structure and WCET Predictability

    OpenAIRE

    Gebhard, Gernot; Cullmann, Christoph; Heckmann, Reinhold

    2011-01-01

    Being able to compute worst-case execution time bounds for tasks of an embedded software system with hard real-time constraints is crucial to ensure the correct (timing) behavior of the overall system. Any means to increase the (static) time predictability of the embedded software are of high interest -- especially due to the ever-growing complexity of such software systems. In this paper we study existing coding proposals and guidelines, such as MISRA-C, and investigate whether they simplify...

  3. Colored Noise Prediction Based on Neural Network

    Institute of Scientific and Technical Information of China (English)

    Gao Fei; Zhang Xiaohui

    2003-01-01

    A method for predicting colored noise by introducing prediction of nonhnear time series is presented By adopting three kinds of neural networks prediction models, the colored noise prediction is studied through changing the filter bandwidth for stochastic noise and the sampling rate for colored noise The results show that colored noise can be predicted The prediction error decreases with the increasing of the sampling rate or the narrowing of the filter bandwidth. If the parameters are selected properly, the prediction precision can meet the requirement of engineering implementation. The results offer a new reference way for increasing the ability for detecting weak signal in signal processing system

  4. A contrail cirrus prediction model

    Directory of Open Access Journals (Sweden)

    U. Schumann

    2012-05-01

    Full Text Available A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP. This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrail-cirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.

  5. A contrail cirrus prediction model

    Directory of Open Access Journals (Sweden)

    U. Schumann

    2011-11-01

    Full Text Available A new model to simulate and predict the properties of a large ensemble of contrails as a function of given air traffic and meteorology is described. The model is designed for approximate prediction of contrail cirrus cover and analysis of contrail climate impact, e.g. within aviation system optimization processes. The model simulates the full contrail life-cycle. Contrail segments form between waypoints of individual aircraft tracks in sufficiently cold and humid air masses. The initial contrail properties depend on the aircraft. The advection and evolution of the contrails is followed with a Lagrangian Gaussian plume model. Mixing and bulk cloud processes are treated quasi analytically or with an effective numerical scheme. Contrails disappear when the bulk ice content is sublimating or precipitating. The model has been implemented in a "Contrail Cirrus Prediction Tool" (CoCiP. This paper describes the model assumptions, the equations for individual contrails, and the analysis-method for contrail-cirrus cover derived from the optical depth of the ensemble of contrails and background cirrus. The model has been applied for a case study and compared to the results of other models and in-situ contrail measurements. The simple model reproduces a considerable part of observed contrail properties. Mid-aged contrails provide the largest contributions to the product of optical depth and contrail width, important for climate impact.

  6. Neuroanatomy predicts individual risk attitudes.

    Science.gov (United States)

    Gilaie-Dotan, Sharon; Tymula, Agnieszka; Cooper, Nicole; Kable, Joseph W; Glimcher, Paul W; Levy, Ifat

    2014-09-10

    Over the course of the last decade a multitude of studies have investigated the relationship between neural activations and individual human decision-making. Here we asked whether the anatomical features of individual human brains could be used to predict the fundamental preferences of human choosers. To that end, we quantified the risk attitudes of human decision-makers using standard economic tools and quantified the gray matter cortical volume in all brain areas using standard neurobiological tools. Our whole-brain analysis revealed that the gray matter volume of a region in the right posterior parietal cortex was significantly predictive of individual risk attitudes. Participants with higher gray matter volume in this region exhibited less risk aversion. To test the robustness of this finding we examined a second group of participants and used econometric tools to test the ex ante hypothesis that gray matter volume in this area predicts individual risk attitudes. Our finding was confirmed in this second group. Our results, while being silent about causal relationships, identify what might be considered the first stable biomarker for financial risk-attitude. If these results, gathered in a population of midlife northeast American adults, hold in the general population, they will provide constraints on the possible neural mechanisms underlying risk attitudes. The results will also provide a simple measurement of risk attitudes that could be easily extracted from abundance of existing medical brain scans, and could potentially provide a characteristic distribution of these attitudes for policy makers. PMID:25209279

  7. Predicting the mechanism of phospholipidosis

    Directory of Open Access Journals (Sweden)

    Lowe Robert

    2012-01-01

    Full Text Available Abstract The mechanism of phospholipidosis is still not well understood. Numerous different mechanisms have been proposed, varying from direct inhibition of the breakdown of phospholipids to the binding of a drug compound to the phospholipid, preventing breakdown. We have used a probabilistic method, the Parzen-Rosenblatt Window approach, to build a model from the ChEMBL dataset which can predict from a compound's structure both its primary pharmaceutical target and other targets with which it forms off-target, usually weaker, interactions. Using a small dataset of 182 phospholipidosis-inducing and non-inducing compounds, we predict their off-target activity against targets which could relate to phospholipidosis as a side-effect of a drug. We link these targets to specific mechanisms of inducing this lysosomal build-up of phospholipids in cells. Thus, we show that the induction of phospholipidosis is likely to occur by separate mechanisms when triggered by different cationic amphiphilic drugs. We find that both inhibition of phospholipase activity and enhanced cholesterol biosynthesis are likely to be important mechanisms. Furthermore, we provide evidence suggesting four specific protein targets. Sphingomyelin phosphodiesterase, phospholipase A2 and lysosomal phospholipase A1 are shown to be likely targets for the induction of phospholipidosis by inhibition of phospholipase activity, while lanosterol synthase is predicted to be associated with phospholipidosis being induced by enhanced cholesterol biosynthesis. This analysis provides the impetus for further experimental tests of these hypotheses.

  8. Prediction During Natural Language Comprehension.

    Science.gov (United States)

    Willems, Roel M; Frank, Stefan L; Nijhof, Annabel D; Hagoort, Peter; van den Bosch, Antal

    2016-06-01

    The notion of prediction is studied in cognitive neuroscience with increasing intensity. We investigated the neural basis of 2 distinct aspects of word prediction, derived from information theory, during story comprehension. We assessed the effect of entropy of next-word probability distributions as well as surprisal A computational model determined entropy and surprisal for each word in 3 literary stories. Twenty-four healthy participants listened to the same 3 stories while their brain activation was measured using fMRI. Reversed speech fragments were presented as a control condition. Brain areas sensitive to entropy were left ventral premotor cortex, left middle frontal gyrus, right inferior frontal gyrus, left inferior parietal lobule, and left supplementary motor area. Areas sensitive to surprisal were left inferior temporal sulcus ("visual word form area"), bilateral superior temporal gyrus, right amygdala, bilateral anterior temporal poles, and right inferior frontal sulcus. We conclude that prediction during language comprehension can occur at several levels of processing, including at the level of word form. Our study exemplifies the power of combining computational linguistics with cognitive neuroscience, and additionally underlines the feasibility of studying continuous spoken language materials with fMRI. PMID:25903464

  9. Clinical importance of predicting radiosensitivity

    International Nuclear Information System (INIS)

    Full text: The optimal use of radiation therapy in cancer treatment is hampered by the application of normal tissue tolerance limits that are derived from population averages. Such limits do not reflect the considerable differences in susceptibility to radiation injury that exist among individuals. Development of assays that accurately predicted normal tissue tolerance in individual patients would permit real application of the concept of treatment to tolerance. By adjusting doses upwards or downwards to achieve a uniform probability of complication in each patient, the therapeutic ratio, i e., the probability of an uncomplicated cure, would be increased for the population as a whole. Although the pathogenesis of radiation injury is highly complex, clinical studies have demonstrated a significant correlation between the in vitro radiosensitivity of patients' fibroblasts and their risk of developing late connective tissue type complications of radiotherapy. While such assays lack the precision and practicality to be used clinically, they do establish the principle of prediction of normal tissue tolerance. Newer assays using surrogate endpoints for cell survival and incorporating insights into the effects of radiation on cellular growth, differentiation, senescence and cytokine production are being developed. Such assays may, in the future, be complemented or replaced by molecular and/or cytogenetic probes to derive robust estimates of individual tolerance. The goal of accurate prediction of individual tolerance for clinical use, while not imminent, does seem achievable

  10. Research on Population Prediction of Guizhou Province

    Institute of Scientific and Technical Information of China (English)

    Shuang; YU; Guang; LI

    2013-01-01

    In accordance with population development of Guizhou Province in 1977-2007,this paper adopts natural growth method,model prediction method and gray system GM (1,1) model prediction method to predict population of Guizhou Province in 2020. On the basis of overall consideration of many factors of population development and future development trend of Guizhou Province,it analyzes advantages and disadvantages of three prediction methods,and obtains the prediction value of total population of Guizhou Province in 2020.

  11. Prediction of PARP Inhibition with Proteochemometric Modelling and Conformal Prediction.

    Science.gov (United States)

    Cortés-Ciriano, Isidro; Bender, Andreas; Malliavin, Thérèse

    2015-06-01

    Poly(ADP-ribose) polymerases (PARPs) play a key role in DNA damage repair. PARP inhibitors act as chemo- and radio- sensitizers and thus potentiate the cytotoxicity of DNA damaging agents. Although PARP inhibitors are currently investigated as chemotherapeutic agents, their cross-reactivity with other members of the PARP family remains unclear. Here, we apply Proteochemometric Modelling (PCM) to model the activity of 181 compounds on 12 human PARPs. We demonstrate that PCM (R0 (2) test =0.65-0.69; RMSEtest =0.95-1.01 °C) displays higher performance on the test set (interpolation) than Family QSAR and Family QSAM (Tukey's HSD, α 0.05), and outperforms Inductive Transfer knowledge among targets (Tukey's HSD, α 0.05). We benchmark the predictive signal of 8 amino acid and 11 full-protein sequence descriptors, obtaining that all of them (except for SOCN) perform at the same level of statistical significance (Tukey's HSD, α 0.05). The extrapolation power of PCM to new compounds (RMSE=1.02±0.80 °C) and targets (RMSE=1.03±0.50 °C) is comparable to interpolation, although the extrapolation ability is not uniform across the chemical and the target space. For this reason, we also provide confidence intervals calculated with conformal prediction. In addition, we present the R package conformal, which permits the calculation of confidence intervals for regression and classification caret models. PMID:27490382

  12. Predicting Abraham model solvent coefficients

    OpenAIRE

    Bradley, Jean-Claude; Abraham, Michael H; Acree, William E; Lang, Andrew SID

    2015-01-01

    Background The Abraham general solvation model can be used in a broad set of scenarios involving partitioning and solubility, yet is limited to a set of solvents with measured Abraham coefficients. Here we extend the range of applicability of Abraham’s model by creating open models that can be used to predict the solvent coefficients for all organic solvents. Results We created open random forest models for the solvent coefficients e, s, a, b, and v that had out-of-bag R2 values of 0.31, 0.77...

  13. Algorithms for appliance usage prediction

    OpenAIRE

    Truong, Ngoc Cuong

    2014-01-01

    Demand-Side Management (DSM) is one of the key elements of future Smart Electricity Grids. DSM involves mechanisms to reduce or shift the consumption of electricity in an attempt to minimise peaks. By so doing it is possible to avoid using expensive peaking plants that are also highly carbon emitting. A key challenge in DSM, however, is the need to predict energy usage from specific home appliances accurately so that consumers can be notified to shift or reduce the use of high energy-consumin...

  14. Radiometers Optimize Local Weather Prediction

    Science.gov (United States)

    2010-01-01

    Radiometrics Corporation, headquartered in Boulder, Colorado, engaged in Small Business Innovation Research (SBIR) agreements with Glenn Research Center that resulted in a pencil-beam radiometer designed to detect supercooled liquid along flight paths -- a prime indicator of dangerous icing conditions. The company has brought to market a modular radiometer that resulted from the SBIR work. Radiometrics' radiometers are used around the world as key tools for detecting icing conditions near airports and for the prediction of weather conditions like fog and convective storms, which are known to produce hail, strong winds, flash floods, and tornadoes. They are also employed for oceanographic research and soil moisture studies.

  15. Uncertainties in debris growth predictions

    International Nuclear Information System (INIS)

    The growth of artificial space debris in Earth orbit may pose a significant hazard to satellites in the future though the collision hazard to operational spacecraft is presently manageable. The stability of the environment is dependent on the growth of debris from satellite deployment, mission operations and fragmentation events. Growth trends of the trackable on-orbit population are investigated highlighting the complexities and limitations of using the data that supports this modeling. The debris produced by breakup events may be a critical aspect of the present and future environment. As a result, growth predictions produced using existing empirically-based models may have large, possibly even unacceptable, uncertainties

  16. Numerical Prediction of a Seaway

    CERN Document Server

    Dommermuth, Douglas G; Brucker, Kyle A; O'Shea, Thomas T; Wyatt, Donald C

    2014-01-01

    The ability of three wave theories to predict statistics and the crest kinematics of a seaway is quantified. The three wave theories are high-order spectral (HOS) theory, free-surface mapping (FSM), and volume-of-fluid (VOF). Issues associated with applying these methods are discussed, including free-surface adjustment, smoothing and filtering, and forcing. Two long-crested regular waves with varying bandwidth and moderate steepness are used to benchmark the performance of the wave theories. As a more stringent test, a broad-banded long-crested seaway is simulated.

  17. $\\Theta+$: Another Explanation and Prediction

    CERN Document Server

    Kishimoto, T; Kishimoto, Tadafumi; Sato, Toru

    2003-01-01

    Recently the so-called $\\Theta^+$ resonance has been reported first from SPring8\\cite{nakano} and many following experiments showed clear evidence of the state. The existence of $\\Theta^+$ is now confirmed. Since $\\Theta^+$ exclusively decays into either $K^+ n$ or $K^0 p$, it is explained to be the long waited penta-quark state which includes $ u u d d \\bar{s}$ quarks. However, one yet has to obtain consistent picture of $\\Theta^+$. We try to explain $\\Theta^+$ in a conventional picture and show that such picture leads to new prediction on kaon and pion system.

  18. Easily magnetic anomalies earthquake prediction

    Directory of Open Access Journals (Sweden)

    Jiang Min

    2016-01-01

    Full Text Available Low power consumption long time offset magnetic field detector (earthquake prediction .The design of the hardware circuit of the magnetic field detector seismic geomagnetic acquisition and pre processing module mainly includes. Electronic compass, compass. monitoring device while the magnetic azimuth for monitoring and analyzing the object, GSM, but it can also be applied to other seismic precursor information analysis, such as earthquake precursory infrasound abnormality, only need infrasound abnormality intelligent sensor replace geomagnetic anomaly intelligent sensor, and modify the relevant parameters can be.

  19. Link prediction in Foursquare network

    OpenAIRE

    Fortuna, Rok; Marovt, Urban

    2016-01-01

    Foursquare is an online social network and can be represented with a bipartite network of users and venues. A user-venue pair is connected if a user has checked-in at that venue. In the case of Foursquare, network analysis techniques can be used to enhance the user experience. One such technique is link prediction, which can be used to build a personalized recommendation system of venues. Recommendation systems in bipartite networks are very often designed using the global ranking method and ...

  20. Predicting word sense annotation agreement

    DEFF Research Database (Denmark)

    Martinez Alonso, Hector; Johannsen, Anders Trærup; Lopez de Lacalle, Oier;

    2015-01-01

    High agreement is a common objective when annotating data for word senses. However, a number of factors make perfect agreement impossible, e.g. the limitations of the sense inventories, the difficulty of the examples or the interpretation preferences of the annotations. Estimating potential...... agreement is thus a relevant task to supplement the evaluation of sense annotations. In this article we propose two methods to predict agreement on word-annotation instances. We experiment with a continuous representation and a three-way discretization of observed agreement. In spite of the difficulty of...

  1. Aviation turbulence processes, detection, prediction

    CERN Document Server

    Lane, Todd

    2016-01-01

    Anyone who has experienced turbulence in flight knows that it is usually not pleasant, and may wonder why this is so difficult to avoid. The book includes papers by various aviation turbulence researchers and provides background into the nature and causes of atmospheric turbulence that affect aircraft motion, and contains surveys of the latest techniques for remote and in situ sensing and forecasting of the turbulence phenomenon. It provides updates on the state-of-the-art research since earlier studies in the 1960s on clear-air turbulence, explains recent new understanding into turbulence generation by thunderstorms, and summarizes future challenges in turbulence prediction and avoidance.

  2. Predicting the Impact of Earthquakes

    International Nuclear Information System (INIS)

    Consistently monitor seismicity over the world to alert civilian security forces, assess hazards, model and test building and industrial facilities behavior in the event of an earthquake. Thanks to instruments unique in Europe, CEA researchers acquired extensive know-how and international renown in the field. The recent commissioning of the CENALT Tsunami Warning Center and the setup of the SEISM Institute for research on earthquake hazards is just another proof of their expertise. For want of being able to predict earthquakes, these organizations aim at limiting losses in human lives and material damage. (authors)

  3. Climate Prediction through Statistical Methods

    CERN Document Server

    Akgun, Bora; Tuter, Levent; Kurnaz, Mehmet Levent

    2008-01-01

    Climate change is a reality of today. Paleoclimatic proxies and climate predictions based on coupled atmosphere-ocean general circulation models provide us with temperature data. Using Detrended Fluctuation Analysis, we are investigating the statistical connection between the climate types of the present and these local temperatures. We are relating this issue to some well-known historic climate shifts. Our main result is that the temperature fluctuations with or without a temperature scale attached to them, can be used to classify climates in the absence of other indicators such as pan evaporation and precipitation.

  4. Prediction of burnout. Chapter 14

    International Nuclear Information System (INIS)

    A broad survey is made of the effect on burnout heat flux of various system parameters to give the reader a better initial idea of the significance of changes in individual parameters. A detailed survey is then made of various correlation equations for predicting burnout for steam -water in uniformly heated tubes, annuli, rectangular channels and rod clusters, giving details of recommended equations. Finally comments are made on the influence of heat-flux profile and swirl flow on burnout, and on the definition of dryout margin. (author)

  5. Seizure prediction and its applications.

    Science.gov (United States)

    Iasemidis, Leon D

    2011-10-01

    Epilepsy is characterized by intermittent, paroxysmal, hypersynchronous electrical activity that may remain localized and/or spread and severely disrupt the brain's normal multitask and multiprocessing function. Epileptic seizures are the hallmarks of such activity. The ability to issue warnings in real time of impending seizures may lead to novel diagnostic tools and treatments for epilepsy. Applications may range from a warning to the patient to avert seizure-associated injuries, to automatic timely administration of an appropriate stimulus. Seizure prediction could become an integral part of the treatment of epilepsy through neuromodulation, especially in the new generation of closed-loop seizure control systems. PMID:21939848

  6. Radio Channel State Prediction by Kalman Filter

    Directory of Open Access Journals (Sweden)

    Peter Ziacik

    2005-01-01

    Full Text Available In this article there is the description Kalman filter using as a radio channel state predictor. Simulator of prediction has been created in MATLAB environment and it is capable to simulate the prediction of radio signal envelope by Clark’s model of radio channel, which is implemented to the simulator. Simulations were realized for prediction range 0.41 ms and 6.24 ms and as comparing criterion we used the prediction error. It is clear from simulations, that with the duration of prediction the prediction error is enlarging, which may cause the erroneous decision of adaptation algorithms.

  7. Improving the prediction of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    李克平; 高自友; 陈天仑

    2003-01-01

    One of the features of deterministic chaos is sensitive to initial conditions. This feature limits the prediction horizons of many chaotic systems. In this paper, we propose a new prediction technique for chaotic time series. In our method, some neighbouring points of the predicted point, for which the corresponding local Lyapunov exponent is particularly large, would be discarded during estimating the local dynamics, and thus the error accumulated by the prediction algorithm is reduced. The model is tested for the convection amplitude of Lorenz systems. The simulation results indicate that the prediction technique can improve the prediction of chaotic time series.

  8. Predictive implications of Gompertz's law

    CERN Document Server

    Richmond, Peter

    2015-01-01

    Gompertz's law tells us that for humans above the age of 35 the death rate increases exponentially with a doubling time of about 10 years. Here, we show that the same law continues to hold even for ages over 100. Beyond 106 there is so far no statistical evidence available because the number of survivors is too small even in the largest nations. However assuming that Gompertz's law continues to hold beyond 106, we conclude that the mortality rate becomes equal to 1 at age 120 (meaning that there are 1,000 deaths in a population of one thousand). In other words, the upper bound of human life is near 120. The existence of this fixed-point has interesting implications. It allows us to predict the form of the relationship between death rates at age 35 and the doubling time of Gompertz's law. In order to test this prediction, we first carry out a transversal analysis for a sample of countries comprising both industrialized and developing nations. As further confirmation, we also develop a longitudinal analysis usi...

  9. PIPS: pathogenicity island prediction software.

    Directory of Open Access Journals (Sweden)

    Siomar C Soares

    Full Text Available The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene transfer. Pathogenicity islands play a major role in this type of gene transfer because they are large, horizontally acquired regions that harbor clusters of virulence genes that mediate the adhesion, colonization, invasion, immune system evasion, and toxigenic properties of the acceptor organism. Currently, pathogenicity islands are mainly identified in silico based on various characteristic features: (1 deviations in codon usage, G+C content or dinucleotide frequency and (2 insertion sequences and/or tRNA genetic flanking regions together with transposase coding genes. Several computational techniques for identifying pathogenicity islands exist. However, most of these techniques are only directed at the detection of horizontally transferred genes and/or the absence of certain genomic regions of the pathogenic bacterium in closely related non-pathogenic species. Here, we present a novel software suite designed for the prediction of pathogenicity islands (pathogenicity island prediction software, or PIPS. In contrast to other existing tools, our approach is capable of utilizing multiple features for pathogenicity island detection in an integrative manner. We show that PIPS provides better accuracy than other available software packages. As an example, we used PIPS to study the veterinary pathogen Corynebacterium pseudotuberculosis, in which we identified seven putative pathogenicity islands.

  10. Mechanism and prediction of burnout

    International Nuclear Information System (INIS)

    The lecture begins by discussing the definitions of burnout and the various parametric effects as seen from the results for burnout measurements in uniformly heated round tubes. The correlations which are developed from these measurements and their applications to the case of non-uniform axial distribution of heat flux is then discussed in general terms as an illustration of the importance of knowing more about the nature and mechanism of the burnout. The next section of the lecture is concerned with summarizing broadly the various possible mechanisms in both the sub-cooled region and the quality region. It transpires that, for tubes of reasonable length, the normal first occurrence of burnout is in the annular flow regime. A discussion of burnout mechanisms in this regime then follows, with descriptions of the various experimental techniques evolved to study the mechanism. The final section of the lecture is concerned with prediction methods for burnout in annular flow and the application of these methods to prediction of burnout in round tubes, annuli and rod bundles, with a variety of fluids

  11. Monthly Extended Predicting Experiments with Nonlinear Regional Prediction. Part Ⅰ: Prediction of Zonal Mean Flow

    Institute of Scientific and Technical Information of China (English)

    CHEN Bomin; JI Liren; YANG Peicai; ZHANG Daomin

    2006-01-01

    Systematic errors have recently been founded to be distinct in the zonal mean component forecasts,which account for a large portion of the total monthly-mean forecast errors. To overcome the difficulty of numerical model, the monthly pentad-mean nonlinear dynamic regional prediction models of the zonal meangeopotential height at 200, 300, 500, and 700 hPa based on a large number of historical data (NCEP/NCAR reanalysis data) were constituted by employing the local approximation of the phase space reconstruction theory and nonlinear spatio-temporal series prediction method. The 12-month forecast experiments of 1996indicated that the results of the nonlinear model are better than those of the persistent, climatic prediction,and T42L9 model either over the high- and mid-latitude areas of the Northern and Southern Hemispheres or the tropical area. The root-mean-square of the monthly-mean height of T42L9 model was considerably decreased with a change of 30.4%, 26.6%, 82.6%, and 39.4%, respectively, over the high- and mid-latitudes of the Northern Hemisphere, over the high- and mid-latitudes of the Southern Hemisphere, over the tropics and over the globe, and also the corresponding anomaly correlation coefficients over the four areas were respectively increased by 0.306-0.312, 0.304-0.429, 0.739-0.746, and 0.360-0.400 (averagely a relative change of 11.0% over the globe) by nonlinear correction after integration, implying that the forecasts given by nonlinear model include more useful information than those of T42L9 model.

  12. Dopamine signals mimic reward prediction errors

    OpenAIRE

    Schoenbaum, Geoffrey; Esber, Guillem R; Iordanova, Mihaela D.

    2013-01-01

    Modern theories of associative learning center on a prediction error. A study finds that artificial activation of dopamine neurons can substitute for missing reward prediction errors to rescue blocked learning.

  13. Prediction of Recovery from Coma After CPR

    Science.gov (United States)

    ... PATIENTS AND THEIR FAMILIES PREDICTION OF RECOVERY FROM COMA AFTER CPR This summary will provide you with ... tests that help doctors predict poor recovery from coma after CPR. In this case, poor recovery means ...

  14. Protein Residue Contacts and Prediction Methods

    Science.gov (United States)

    Adhikari, Badri

    2016-01-01

    In the field of computational structural proteomics, contact predictions have shown new prospects of solving the longstanding problem of ab initio protein structure prediction. In the last few years, application of deep learning algorithms and availability of large protein sequence databases, combined with improvement in methods that derive contacts from multiple sequence alignments, have shown a huge increase in the precision of contact prediction. In addition, these predicted contacts have also been used to build three-dimensional models from scratch. In this chapter, we briefly discuss many elements of protein residue–residue contacts and the methods available for prediction, focusing on a state-of-the-art contact prediction tool, DNcon. Illustrating with a case study, we describe how DNcon can be used to make ab initio contact predictions for a given protein sequence and discuss how the predicted contacts may be analyzed and evaluated. PMID:27115648

  15. Prediction of Unsteady Transonic Aerodynamics Project

    Data.gov (United States)

    National Aeronautics and Space Administration — An accurate prediction of aero-elastic effects depends on an accurate prediction of the unsteady aerodynamic forces. Perhaps the most difficult speed regime is...

  16. Dissociating Prediction Failure: Considerations from Music Perception

    DEFF Research Database (Denmark)

    Ross, Suzi; Hansen, Niels Christian

    2016-01-01

    Dissociating Prediction Failure: Considerations from Music Perception The Journal of Neuroscience, 16 March 2016, 36(11): 3103-3105;......Dissociating Prediction Failure: Considerations from Music Perception The Journal of Neuroscience, 16 March 2016, 36(11): 3103-3105;...

  17. Detection and Prediction of Epileptic Seizures

    DEFF Research Database (Denmark)

    Duun-Henriksen, Jonas

    monitoring of their brain waves. More specifically, three issues were investigated: The feasibility of automatic seizure prediction, optimization of automatic seizure detection algorithms, and the link between intra- and extracranial EEG. Regarding feasibility of automatic seizure prediction, neither the...

  18. Protein Residue Contacts and Prediction Methods.

    Science.gov (United States)

    Adhikari, Badri; Cheng, Jianlin

    2016-01-01

    In the field of computational structural proteomics, contact predictions have shown new prospects of solving the longstanding problem of ab initio protein structure prediction. In the last few years, application of deep learning algorithms and availability of large protein sequence databases, combined with improvement in methods that derive contacts from multiple sequence alignments, have shown a huge increase in the precision of contact prediction. In addition, these predicted contacts have also been used to build three-dimensional models from scratch.In this chapter, we briefly discuss many elements of protein residue-residue contacts and the methods available for prediction, focusing on a state-of-the-art contact prediction tool, DNcon. Illustrating with a case study, we describe how DNcon can be used to make ab initio contact predictions for a given protein sequence and discuss how the predicted contacts may be analyzed and evaluated. PMID:27115648

  19. The Use of Linear Programming for Prediction.

    Science.gov (United States)

    Schnittjer, Carl J.

    The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)

  20. PREDICTION OF AIRCRAFT NOISE LEVELS

    Science.gov (United States)

    Clark, B. J.

    1994-01-01

    Methods developed at the NASA Lewis Research Center for predicting the noise contributions from various aircraft noise sources have been incorporated into a computer program for predicting aircraft noise levels either in flight or in ground test. The noise sources accounted for include fan inlet and exhaust, jet, flap (for powered lift), core (combustor), turbine, and airframe. Noise propagation corrections are available in the program for atmospheric attenuation, ground reflections, extra ground attenuation, and shielding. The capacity to solve the geometrical relationships between an aircraft in flight and an observer on the ground has been included in the program to make it useful in evaluating noise estimates and footprints for various proposed engine installations. The program contains two main routines for employing the noise prediction routines. The first main routine consists of a procedure to calculate at various observer stations the time history of the noise from an aircraft flying at a specified set of speeds, orientations, and space coordinates. The various components of the noise are computed by the program. For each individual source, the noise levels are free field with no corrections for propagation losses other than spherical divergence. The total spectra may then be corrected for the usual effects of atmospheric attenuation, extra ground attenuation, ground reflection, and aircraft shielding. Next, the corresponding values of overall sound pressure level, perceived noise level, and tone-weighted perceived noise level are calculated. From the time history at each point, true effective perceived noise levels are calculated. Thus, values of effective perceived noise levels, maximum perceived noise levels, and tone-weighted perceived noise levels are found for a grid of specified points on the ground. The second main routine is designed to give the usual format of one-third octave sound pressure level values at a fixed radius for a number of user

  1. Predicting landfalling hurricane numbers from basin hurricane numbers: statistical analysis and predictions

    OpenAIRE

    Jewson, Stephen; Laepple, Thomas; O'Shay, Adam; Penzer, Jeremy; Bellone, Enrica; Nzerem, Kechi

    2007-01-01

    One possible method for predicting landfalling hurricane numbers is to first predict the number of hurricanes in the basin and then convert that prediction to a prediction of landfalling hurricane numbers using an estimated proportion. Should this work better than just predicting landfalling hurricane numbers directly? We perform a basic statistical analysis of this question in the context of a simple abstract model, and convert some previous predictions of basin numbers into landfalling numb...

  2. Prediction Markets to Forecast Electricity Demand

    OpenAIRE

    Luciano I. de Castro; Cramton, Peter

    2009-01-01

    Forecasting electricity demand for future years is an essential step in resource planning. A common approach is for the system operator to predict future demand from the estimates of individual distribution companies. However, the predictions thus obtained may be of poor quality, since the reporting incentives are unclear. We propose a prediction market as a form of forecasting future demand for electricity. We describe how to implement a simple prediction market for continuous variables, usi...

  3. ADAPTIVE GENERALIZED PREDICTIVE CONTROL OF SWITCHED SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    WANG Yi-jing; WANG Long

    2005-01-01

    The problem of adaptive generalized predictive control which consists of output prediction errors for a class of switched systems is studied. The switching law is determined by the output predictive errors of a finite number of subsystems. For the single subsystem and multiple subsystems cases, it is proved that the given direct algorithm of generalized predictive control guarantees the global convergence of the system. This algorithm overcomes the inherent drawbacks of the slow convergence and large transient errors for the conventional adaptive control.

  4. Long-term orbital lifetime predictions

    Science.gov (United States)

    Dreher, P. E.; Lyons, A. T.

    1990-10-01

    Long-term orbital lifetime predictions are analyzed. Predictions were made for three satellites: the Solar Max Mission (SMM), the Long Duration Exposure Facility (LDEF), and the Pegasus Boiler Plate (BP). A technique is discussed for determining an appropriate ballistic coefficient to use in the lifetime prediction. The orbital decay rate should be monitored regularly. Ballistic coefficient updates should be done whenever there is a significant change in the actual decay rate or in the solar activity prediction.

  5. The role of prediction in social neuroscience

    OpenAIRE

    Elliot Clayton Brown; Martin eBrüne

    2012-01-01

    Research has shown that the brain is constantly making predictions about future events. Theories of prediction in perception, action and learning suggest that the brain serves to reduce the discrepancies between expectation and actual experience, i.e. by reducing the prediction error. Forward models of action and perception propose the generation of a predictive internal representation of the expected sensory outcome, which is matched to the actual sensory feedback. Shared neural representati...

  6. The Predictiveness of Achievement Goals

    Directory of Open Access Journals (Sweden)

    Huy P. Phan

    2013-11-01

    Full Text Available Using the Revised Achievement Goal Questionnaire (AGQ-R (Elliot & Murayama, 2008, we explored first-year university students’ achievement goal orientations on the premise of the 2 × 2 model. Similar to recent studies (Elliot & Murayama, 2008; Elliot & Thrash, 2010, we conceptualized a model that included both antecedent (i.e., enactive learning experience and consequence (i.e., intrinsic motivation and academic achievement of achievement goals. Two hundred seventy-seven university students (151 women, 126 men participated in the study. Structural equation modeling procedures yielded evidence that showed the predictive effects of enactive learning experience and mastery goals on intrinsic motivation. Academic achievement was influenced intrinsic motivation, performance-approach goals, and enactive learning experience. Enactive learning experience also served as an antecedent of the four achievement goal types. On the whole, evidence obtained supports the AGQ-R and contributes, theoretically, to 2 × 2 model.

  7. Numerical prediction of slamming loads

    DEFF Research Database (Denmark)

    Seng, Sopheak; Jensen, Jørgen J; Pedersen, Preben T

    2012-01-01

    calculations in a realistic wave environment.Both the global and the local slamming loads are assessed numerically using a finite-volume formulation with the free surface captured by a volume-of-fluid technique. This numerical procedure is justified by comprehensive validation studies where numerically......It is important to include the contribution of the slamming-induced response in the structural design of large vessels with a significant bow flare. At the same time it is a challenge to develop rational tools to determine the slamming-induced loads and the prediction of their occurrence. Today it...... is normal practice to apply a standard sea-keeping procedure to determine the relative velocity distribution between the water surface and the hull and then to estimate the bottom slamming loads and the bow-flare slamming loads based on two-dimensional formulations similarly to water-entry problems...

  8. Predictable response from MCR operators

    International Nuclear Information System (INIS)

    Operating Philosophy in a nuclear power plant is the driving influence that leads to obtaining a predictable response to any operating challenge in the Main Control Room. This means that for any event or abnormal situation in the plant, every operator will take the unit to the required state, every time. This is a must in our industry. This can be achieved by clearly identifying the challenges that face the operating staff. It is essential that a balanced review be done so that there is not over emphasis on any aspect of the operator's ability to respond. The major areas discussed in this presentation are Plant, Procedures and People. Discussion will bring focus to the use of procedures and how to identify good practices that require reinforcement at the simulator, and how to identify potential vulnerabilities. The three overheads will be reviewed to illustrate the systematic approach used at Darlington Nuclear. (author)

  9. Academic Training: Predicting Natural Catastrophes

    CERN Multimedia

    Françoise Benz

    2005-01-01

    2005-2006 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 12, 13, 14, 15, 16 December from 11:00 to 12:00 - Main Auditorium, bldg. 500 Predicting Natural Catastrophes E. OKAL / Northwestern University, Evanston, USA 1. Tsunamis -- Introduction Definition of phenomenon - basic properties of the waves Propagation and dispersion Interaction with coasts - Geological and societal effects Origin of tsunamis - natural sources Scientific activities in connection with tsunamis. Ideas about simulations 2. Tsunami generation The earthquake source - conventional theory The earthquake source - normal mode theory The landslide source Near-field observation - The Plafker index Far-field observation - Directivity 3. Tsunami warning General ideas - History of efforts Mantle magnitudes and TREMOR algorithms The challenge of 'tsunami earthquakes' Energy-moment ratios and slow earthquakes Implementation and the components of warning centers 4. Tsunami surveys Principles and methodologies Fifteen years of field surveys and re...

  10. Are Some Semantic Changes Predictable?

    DEFF Research Database (Denmark)

    Schousboe, Steen

    2010-01-01

      Historical linguistics is traditionally concerned with phonology and syntax. With the exception of grammaticalization - the development of auxiliary verbs, the syntactic rather than localistic use of prepositions, etc. - semantic change has usually not been described as a result of regular deve...... developments, but only as specific meaning changes in individual words. This paper will suggest some regularities in semantic change, regularities which, like sound laws, have predictive power and can be tested against recorded languages.......  Historical linguistics is traditionally concerned with phonology and syntax. With the exception of grammaticalization - the development of auxiliary verbs, the syntactic rather than localistic use of prepositions, etc. - semantic change has usually not been described as a result of regular...

  11. Prospects for Predicting Cycle 24

    Indian Academy of Sciences (India)

    Arnab Rai Choudhuri

    2008-03-01

    Although we have reliable data of solar polar fields only from the mid-1970s, it seems that the polar field at a minimum is well correlated with the next cycle, but the strength of the cycle is not correlated with the polar field produced at its end. We explain this by suggesting that the Babcock–Leighton mechanism of poloidal field generation from tilted active regions involves randomness, whereas the other aspects of the dynamo process are more ordered. To model actual cycles, we have to ‘correct’ our theoretical dynamo model by ‘feeding’ information about the polar field at the minima. Following this process, we find that our model fits the observed sunspot numbers of cycles 21–23 reasonably well and predicts that cycle 24 will be the weakest in a century.

  12. Rhythmic complexity and predictive coding

    DEFF Research Database (Denmark)

    Vuust, Peter; Witek, Maria A G

    2014-01-01

    ofmusic (“meter”). Finally, we review empirical studies of the neural and behavioral effects ofsyncopation, polyrhythm and groove, and propose how these studies can be seen as specialcases of the PC theory.We argue that musical rhythm exploits the brain’s general principlesof prediction and propose......Musical rhythm, consisting of apparently abstract intervals of accented temporal events,has a remarkable capacity to move our minds and bodies. How does the cognitive systemenable our experiences of rhythmically complex music? In this paper, we describe somecommon forms of rhythmic complexity...... in music and propose the theory of predictivecoding (PC) as a framework for understanding how rhythm and rhythmic complexit y areprocessed in the brain. We also consider why we feel so compelled by rhythmic tensionin music. First, we consider theories of rhythm and meter perception, which...

  13. Sunspot prediction using neural networks

    Science.gov (United States)

    Villarreal, James; Baffes, Paul

    1990-01-01

    The earliest systematic observance of sunspot activity is known to have been discovered by the Chinese in 1382 during the Ming Dynasty (1368 to 1644) when spots on the sun were noticed by looking at the sun through thick, forest fire smoke. Not until after the 18th century did sunspot levels become more than a source of wonderment and curiosity. Since 1834 reliable sunspot data has been collected by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Naval Observatory. Recently, considerable effort has been placed upon the study of the effects of sunspots on the ecosystem and the space environment. The efforts of the Artificial Intelligence Section of the Mission Planning and Analysis Division of the Johnson Space Center involving the prediction of sunspot activity using neural network technologies are described.

  14. Predicting cooling tower plume dispersion

    International Nuclear Information System (INIS)

    An assessment of the effects of visible cooling tower plumes on the local environment can be a necessary part of any proposal for a new large industrial process. Predictions of the dispersion of plumes from cooling towers are based on methods developed for chimney emissions. However, the kinds of criteria used to judge the acceptability of cooling tower plumes are different from those used for stack plumes. The frequency of long elevated plumes and the frequency of ground fogging are the two main issues. It is shown that events associated with significant plumes visibility are dependent both on the operating characteristics of the tower and on the occurrence of certain meteorological conditions. The dependence on atmospheric conditions is shown to be fairly complex and simple performance criteria based on the exit conditions from the tower are not sufficient for assessments. (author)

  15. Predicting Neutrinoless Double Beta Decay

    CERN Document Server

    Hirsch, M; Valle, J W F; Moral, A V; Ma, Ernest

    2005-01-01

    We give predictions for the neutrinoless double beta decay rate in a simple variant of the A_4 family symmetry model. We show that there is a lower bound for the neutrinoless double beta decay amplitude even in the case of normal hierarchical neutrino masses, corresponding to an effective mass parameter |m_{ee}| >= 0.17 \\sqrt{\\Delta m^2_{ATM}}. This result holds both for the CP conserving and CP violating cases. In the latter case we show explicitly that the lower bound on |m_{ee}| is sensitive to the value of the Majorana phase. We conclude therefore that in our scheme, neutrinoless double beta decay may be accessible to the next generation of high sensitivity experiments.

  16. Pretest Predictions for Ventilation Tests

    International Nuclear Information System (INIS)

    The objective of this calculation is to predict the temperatures of the ventilating air, waste package surface, concrete pipe walls, and insulation that will be developed during the ventilation tests involving various test conditions. The results will be used as input to the following three areas: (1) Decisions regarding testing set-up and performance. (2) Assessing how best to scale the test phenomena measured. (3) Validating numerical approach for modeling continuous ventilation. The scope of the calculation is to identify the physical mechanisms and parameters related to thermal response in the ventilation tests, and develop and describe numerical methods that can be used to calculate the effects of continuous ventilation. Sensitivity studies to assess the impact of variation of linear power densities (linear heat loads) and ventilation air flow rates are included. The calculation is limited to thermal effect only

  17. Evolution of property predictability during conceptual design

    DEFF Research Database (Denmark)

    Salonen, Mikko; Hansen, Claus Thorp; Perttula, Matti

    design work. By the term property predictability, we refer to the designers’ confidence in predicting product properties based on the available information. Since knowledge about the design problem and solution space grows as the design process progresses, our main hypothesis for the study is that the...... level of property predictability will increase along with the progression of the design process as well....

  18. NEURAL METHODS FOR THE FINANCIAL PREDICTION

    Directory of Open Access Journals (Sweden)

    Jerzy Balicki

    2016-06-01

    Full Text Available Artificial neural networks can be used to predict share investment on the stock market, assess the reliability of credit client or predicting banking crises. Moreover, this paper discusses the principles of cooperation neural network algorithms with evolutionary method, and support vector machines. In addition, a reference is made to other methods of artificial intelligence, which are used in finance prediction.

  19. Applications for predictive microbiology to food packaging

    Science.gov (United States)

    Predictive microbiology has been used for several years in the food industry to predict microbial growth, inactivation and survival. Predictive models provide a useful tool in risk assessment, HACCP set-up and GMP for the food industry to enhance microbial food safety. This report introduces the c...

  20. PEMS. Advanced predictive emission monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Sandvig Nielsen, J.

    2010-07-15

    In the project PEMS have been developed for boilers, internal combustion engines and gas turbines. The PEMS models have been developed using two principles: The one called ''first principles'' is based on thermo-kinetic modeling of the NO{sub x}-formation by modeling conditions (like temperature, pressure and residence time) in the reaction zones. The other one is data driven using artificial neural network (ANN) and includes no physical properties and no thermo-kinetic formulation. Models of first principles have been developed for gas turbines and gas engines. Data driven models have been developed for gas turbines, gas engines and boilers. The models have been tested on data from sites located in Denmark and the Middle East. Weel and Sandvig has conducted the on-site emission measurements used for development and testing the PEMS models. For gas turbines, both the ''first principles'' and the data driven models have performed excellent considering the ability to reproduce the emission levels of NO{sub x} according to the input variables used for calibration. Data driven models for boilers and gas engines have performed excellent as well. The rather comprehensive first principle model, developed for gas engines, did not perform as well in the prediction of NO{sub x}. Possible a more complex model formulation is required for internal combustion engines. In general, both model types have been validated on data extracted from the data set used for calibration. The data for validation have been selected randomly as individual samplings, and is scattered over the entire measuring campaign. For one natural gas engine a secondary measuring campaign was conducted half a year later than the campaign used for training the data driven model. In the meantime, this engine had been through a refurbishment that included new pistons, piston rings and cylinder linings and cleaning of the cylinder heads. Despite the refurbishment, the

  1. Monthly Extended Predicting Experiments with Nonlinear Regional Prediction. Part Ⅱ: Improvement of Wave Component Prediction

    Institute of Scientific and Technical Information of China (English)

    CHEN Bomin; JI Liren; YANG Peicai; ZHANG Daomin

    2006-01-01

    Based on Chen et al. (2006), the scheme of the combination of the pentad-mean zonal height departure nonlinear prediction with the T42L9 model prediction was designed, in which the pentad zonal heights at all the 12-initial-value-input isobar levels from 50 hPa to 1000 hPa except 200, 300, 500, and 700 hPa were derived from nonlinear forecasts of the four levels by means of a good correlation between neighboring levels.Then the above pentad zonal heights at 12 isobar-levels were transformed to the spectrum coefficients of the temperature at each integration step of T42L9 model. At last, the nudging was made. On account of a variety of error accumulation, the pentad zonal components of the monthly height at isobar levels output by T42L9 model were replaced by the corresponding nonlinear results once more when integration was over.Multiple case experiments showed that such combination of two kinds of prediction made an improvement in the wave component as a result of wave-flow nonlinear interaction while reducing the systematical forecast errors. Namely the monthly-mean height anomaly correlation coefficients over the high- and mid-latitudes of the Northern Hemisphere, over the Southern Hemisphere and over the globe increased respectively from 0.249 to 0.347, from 0.286 to 0.387, and from 0.343 to 0.414 (relative changes of 31.5%, 41.0%, and 18.3%).The monthly-mean root-mean-square error (RMSE) of T42L9 model over the three areas was considerably decreased, the relative change over the globe reached 44.2%. The monthly-mean anomaly correlation coefficients of wave 4-9 over the areas were up to 0.392, 0.200, and 0.295, with the relative change of 53.8%, 94.1%,and 61.2%, and correspondingly their RMSEs were decreased respectively with the rate of 8.5%, 6.3%, and 8.1%. At the same time the monthly-mean pattern of parts of cases were presented better.

  2. A Prospect of Earthquake Prediction Research

    CERN Document Server

    Ogata, Yosihiko

    2013-01-01

    Earthquakes occur because of abrupt slips on faults due to accumulated stress in the Earth's crust. Because most of these faults and their mechanisms are not readily apparent, deterministic earthquake prediction is difficult. For effective prediction, complex conditions and uncertain elements must be considered, which necessitates stochastic prediction. In particular, a large amount of uncertainty lies in identifying whether abnormal phenomena are precursors to large earthquakes, as well as in assigning urgency to the earthquake. Any discovery of potentially useful information for earthquake prediction is incomplete unless quantitative modeling of risk is considered. Therefore, this manuscript describes the prospect of earthquake predictability research to realize practical operational forecasting in the near future.

  3. Predictive Functional Control for Fractional Order System

    Directory of Open Access Journals (Sweden)

    Morteza Abdolhosseini

    2014-01-01

    Full Text Available The fractional calculus is the area of mathematics that handles derivatives and integrals of any arbitrary order (fractional or integer, real or complex order. Predictive Functional Control (PFC is one of the most popular methods of model predictive control. The implementation of the predictive functional controller (PFC on the fractional order systems has been presented in this paper. The effect of various approximations, sensitivity analysis, tuning of predictive functional controller parameters, the effect of delay and noise analysis of the fractional-order system has been considered. It has been shown that, in fractional order system, predictive functional control gives acceptable results

  4. Conditional prediction intervals of wind power generation

    DEFF Research Database (Denmark)

    Pinson, Pierre; Kariniotakis, Georges

    2010-01-01

    A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... integrate expertise on the characteristics of prediction errors for providing conditional interval forecasts. By simultaneously generating prediction intervals with various nominal coverage rates, one obtains full predictive distributions of wind generation. Adapted resampling is applied here to the case of...

  5. Efficient marker data utilization in genomic prediction

    DEFF Research Database (Denmark)

    Edriss, Vahid

    Genomic prediction is a novel method to recognize the best animals for breeding. The aim of this PhD is to improve the accuracy of genomic prediction in dairy cattle by effeiently utilizing marker data. The thesis focuses on three aspects for improving the genomc prediction, which are: criteria of...... editing marker data, methods to handle missing genotypes and prediction using haplotypes constructed with an advanced method. The results of this study show that the accuracy of genomc prediction increases by: optimal criteria for marker data editing parameters, proper handling of missing genotypes using...

  6. Evolution of property predictability during conceptual design

    DEFF Research Database (Denmark)

    Salonen, Mikko; Hansen, Claus Thorp; Perttula, Matti

    refer to the designers’ confidence in predicting product properties based on the available information. In the case study, with use of the produced design models at four different stages of concept concretisation, the designers evaluated their confidence in predicting product properties related to the...... requirements set for the task. As a result, we identified three different patterns of property predictability behaviour. These patterns consist of properties of which predictability is relatively high throughout the early phases of the design process, properties of which predictability shows a high increase...

  7. Adaptive nonlinear prediction of ocean reverberation

    Institute of Scientific and Technical Information of China (English)

    GAN Weiming; LI Fenghua

    2009-01-01

    An adaptive nonlinear prediction algorithm is proposed to predict ocean reverber-ation based on the phase space reconstruction of nonlinear dynamic system. The prediction algorithm is tested by experimental reverberation data measured in two areas, and the one-step forward prediction results are in good agreement with the experimental data. If the errors between the predicted and experimental data are chosen as the variable to detect the target in the reverberation series, the reverberation is suppressed and the signal-to-reverberation ratio is improved.

  8. The predictability of consumer visitation patterns

    CERN Document Server

    Krumme, Coco; Cebrián, Manuel; Alex,; Pentland,; Moro, Esteban; 10.1038/srep01645

    2013-01-01

    We consider hundreds of thousands of individual economic transactions to ask: how predictable are consumers in their merchant visitation patterns? Our results suggest that, in the long-run, much of our seemingly elective activity is actually highly predictable. Notwithstanding a wide range of individual preferences, shoppers share regularities in how they visit merchant locations over time. Yet while aggregate behavior is largely predictable, the interleaving of shopping events introduces important stochastic elements at short time scales. These short- and long-scale patterns suggest a theoretical upper bound on predictability, and describe the accuracy of a Markov model in predicting a person's next location. We incorporate population-level transition probabilities in the predictive models, and find that in many cases these improve accuracy. While our results point to the elusiveness of precise predictions about where a person will go next, they suggest the existence, at large time-scales, of regularities ac...

  9. Entropy and the Predictability of Online Life

    CERN Document Server

    Sinatra, Roberta

    2014-01-01

    Using mobile phone records and information theory measures, our daily lives have been recently shown to follow strict statistical regularities, and our movement patterns are to a large extent predictable. Here, we apply entropy and predictability measures to two data sets of the behavioral actions and the mobility of a large number of players in the virtual universe of a massive multiplayer online game. We find that movements in virtual human lives follow the same high levels of predictability as offline mobility, where future movements can to some extent be predicted well if the temporal correlations of visited places are accounted for. Time series of behavioral actions show similar high levels of predictability, even when temporal correlations are neglected. Entropy conditional on specific behavioral actions reveals that in terms of predictability negative behavior has a wider variety than positive actions. The actions which contain information to best predict an individual's subsequent action are negative,...

  10. Neural network prediction of solar cycle 24

    Institute of Scientific and Technical Information of China (English)

    A. Ajabshirizadeh; N. Masoumzadeh Jouzdani; Shahram Abbassi

    2011-01-01

    The ability to predict the future behavior of solar activity has become extremely import due to its effect on the environment near the Earth. Predictions of both the amplitude and timing of the next solar cycle will assist in estimating the various consequences of space weather. The level of solar activity is usually expressed by international sunspot number (Rz). Several prediction techniques have been applied and have achieved varying degrees of success in the domain of solar activity prediction.We predict a solar index (Rz) in solar cycle 24 by using a neural network method. The neural network technique is used to analyze the time series of solar activity. According to our predictions of yearly sunspot number, the maximum of cycle 24 will occur in the year 2013 and will have an annual mean sunspot number of 65. Finally, we discuss our results in order to compare them with other suggested predictions.

  11. An Introduction to Artificial Prediction Markets

    CERN Document Server

    Barbu, Adrian

    2011-01-01

    Prediction markets are used in real life to predict outcomes of interest such as presidential elections. This paper presents a mathematical theory of artificial prediction markets for supervised learning of conditional probability estimators. The artificial prediction market is a novel method for fusing the prediction information of features or trained classifiers, where the fusion result is the contract price on the possible outcomes. The market can be trained online by updating the participants' budgets using training examples. Inspired by the real prediction markets, the equations that govern the market are derived from simple and reasonable assumptions. Efficient numerical algorithms are presented for solving these equations. The obtained artificial prediction market is shown to be a maximum likelihood estimator. It generalizes linear aggregation, existent in boosting and random forest, as well as logistic regression and some kernel methods. Furthermore, the market mechanism allows the aggregation of spec...

  12. Global scale predictability of floods

    Science.gov (United States)

    Weerts, Albrecht; Gijsbers, Peter; Sperna Weiland, Frederiek

    2016-04-01

    Flood (and storm surge) forecasting at the continental and global scale has only become possible in recent years (Emmerton et al., 2016; Verlaan et al., 2015) due to the availability of meteorological forecast, global scale precipitation products and global scale hydrologic and hydrodynamic models. Deltares has setup GLOFFIS a research-oriented multi model operational flood forecasting system based on Delft-FEWS in an open experimental ICT facility called Id-Lab. In GLOFFIS both the W3RA and PCRGLOB-WB model are run in ensemble mode using GEFS and ECMWF-EPS (latency 2 days). GLOFFIS will be used for experiments into predictability of floods (and droughts) and their dependency on initial state estimation, meteorological forcing and the hydrologic model used. Here we present initial results of verification of the ensemble flood forecasts derived with the GLOFFIS system. Emmerton, R., Stephens, L., Pappenberger, F., Pagano, T., Weerts, A., Wood, A. Salamon, P., Brown, J., Hjerdt, N., Donnelly, C., Cloke, H. Continental and Global Scale Flood Forecasting Systems, WIREs Water (accepted), 2016 Verlaan M, De Kleermaeker S, Buckman L. GLOSSIS: Global storm surge forecasting and information system 2015, Australasian Coasts & Ports Conference, 15-18 September 2015,Auckland, New Zealand.

  13. DC Motor Control Predictive Models

    Directory of Open Access Journals (Sweden)

    Ravinesh Singh

    2006-01-01

    Full Text Available DC motor speed and position controls are fundamental in vehicles in general and robotics in particular. This study presents a mathematical model for correlating the interactions of some DC motor control parameters such as duty cycle, terminal voltage, frequency and load on some responses such as output current, voltage and speed by means of response surface methodology. For this exercise, a five-level full factorial design was chosen for experimentation using a peripheral interface controller (PIC-based universal pulse width modulation (PWM H-Bridge motor controller built in-house. The significance of the mathematical model developed was ascertained using regression analysis method. The results obtained show that the mathematical models are useful not only for predicting optimum DC motor parameters for achieving the desired quality but for speed and position optimization. Using the optimal combination of these parameters is useful in minimizing the power consumption and realization of the optimal speed and invariably position control of DC motor operations.

  14. Predictive Modeling of Tokamak Configurations*

    Science.gov (United States)

    Casper, T. A.; Lodestro, L. L.; Pearlstein, L. D.; Bulmer, R. H.; Jong, R. A.; Kaiser, T. B.; Moller, J. M.

    2001-10-01

    The Corsica code provides comprehensive toroidal plasma simulation and design capabilities with current applications [1] to tokamak, reversed field pinch (RFP) and spheromak configurations. It calculates fixed and free boundary equilibria coupled to Ohm's law, sources, transport models and MHD stability modules. We are exploring operations scenarios for both the DIII-D and KSTAR tokamaks. We will present simulations of the effects of electron cyclotron heating (ECH) and current drive (ECCD) relevant to the Quiescent Double Barrier (QDB) regime on DIII-D exploring long pulse operation issues. KSTAR simulations using ECH/ECCD in negative central shear configurations explore evolution to steady state while shape evolution studies during current ramp up using a hyper-resistivity model investigate startup scenarios and limitations. Studies of high bootstrap fraction operation stimulated by recent ECH/ECCD experiments on DIIID will also be presented. [1] Pearlstein, L.D., et al, Predictive Modeling of Axisymmetric Toroidal Configurations, 28th EPS Conference on Controlled Fusion and Plasma Physics, Madeira, Portugal, June 18-22, 2001. * Work performed under the auspices of the U.S. Department of Energy by the University of California, Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48.

  15. PTIR: Predicted Tomato Interactome Resource.

    Science.gov (United States)

    Yue, Junyang; Xu, Wei; Ban, Rongjun; Huang, Shengxiong; Miao, Min; Tang, Xiaofeng; Liu, Guoqing; Liu, Yongsheng

    2016-01-01

    Protein-protein interactions (PPIs) are involved in almost all biological processes and form the basis of the entire interactomics systems of living organisms. Identification and characterization of these interactions are fundamental to elucidating the molecular mechanisms of signal transduction and metabolic pathways at both the cellular and systemic levels. Although a number of experimental and computational studies have been performed on model organisms, the studies exploring and investigating PPIs in tomatoes remain lacking. Here, we developed a Predicted Tomato Interactome Resource (PTIR), based on experimentally determined orthologous interactions in six model organisms. The reliability of individual PPIs was also evaluated by shared gene ontology (GO) terms, co-evolution, co-expression, co-localization and available domain-domain interactions (DDIs). Currently, the PTIR covers 357,946 non-redundant PPIs among 10,626 proteins, including 12,291 high-confidence, 226,553 medium-confidence, and 119,102 low-confidence interactions. These interactions are expected to cover 30.6% of the entire tomato proteome and possess a reasonable distribution. In addition, ten randomly selected PPIs were verified using yeast two-hybrid (Y2H) screening or a bimolecular fluorescence complementation (BiFC) assay. The PTIR was constructed and implemented as a dedicated database and is available at http://bdg.hfut.edu.cn/ptir/index.html without registration. PMID:27121261

  16. Predicting the outcome of roulette

    Science.gov (United States)

    Small, Michael; Tse, Chi Kong

    2012-09-01

    There have been several popular reports of various groups exploiting the deterministic nature of the game of roulette for profit. Moreover, through its history, the inherent determinism in the game of roulette has attracted the attention of many luminaries of chaos theory. In this paper, we provide a short review of that history and then set out to determine to what extent that determinism can really be exploited for profit. To do this, we provide a very simple model for the motion of a roulette wheel and ball and demonstrate that knowledge of initial position, velocity, and acceleration is sufficient to predict the outcome with adequate certainty to achieve a positive expected return. We describe two physically realizable systems to obtain this knowledge both incognito and in situ. The first system relies only on a mechanical count of rotation of the ball and the wheel to measure the relevant parameters. By applying these techniques to a standard casino-grade European roulette wheel, we demonstrate an expected return of at least 18%, well above the -2.7% expected of a random bet. With a more sophisticated, albeit more intrusive, system (mounting a digital camera above the wheel), we demonstrate a range of systematic and statistically significant biases which can be exploited to provide an improved guess of the outcome. Finally, our analysis demonstrates that even a very slight slant in the roulette table leads to a very pronounced bias which could be further exploited to substantially enhance returns.

  17. Predicting the outcome of roulette

    CERN Document Server

    Small, Michael

    2012-01-01

    There have been several popular reports of various groups exploiting the deterministic nature of the game of roulette for profit. Moreover, through its history the inherent determinism in the game of roulette has attracted the attention of many luminaries of chaos theory. In this paper we provide a short review of that history and then set out to determine to what extent that determinism can really be exploited for profit. To do this, we provide a very simple model for the motion of a roulette wheel and ball and demonstrate that knowledge of initial position, velocity and acceleration is sufficient to predict the outcome with adequate certainty to achieve a positive expected return. We describe two physically realisable systems to obtain this knowledge both incognito and {\\em in situ}. The first system relies only on a mechanical count of rotation of the ball and the wheel to measure the relevant parameters. By applying this techniques to a standard casino-grade European roulette wheel we demonstrate an expec...

  18. The MULTICOM toolbox for protein structure prediction

    Directory of Open Access Journals (Sweden)

    Cheng Jianlin

    2012-04-01

    Full Text Available Abstract Background As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or Results To meet the need, we have developed a comprehensive MULTICOM toolbox consisting of a set of protein structure and structural feature prediction tools. These tools include secondary structure prediction, solvent accessibility prediction, disorder region prediction, domain boundary prediction, contact map prediction, disulfide bond prediction, beta-sheet topology prediction, fold recognition, multiple template combination and alignment, template-based tertiary structure modeling, protein model quality assessment, and mutation stability prediction. Conclusions These tools have been rigorously tested by many users in the last several years and/or during the last three rounds of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7-9 from 2006 to 2010, achieving state-of-the-art or near performance. In order to facilitate bioinformatics research and technological development in the field, we have made the MULTICOM toolbox freely available as web services and/or software packages for academic use and scientific research. It is available at http://sysbio.rnet.missouri.edu/multicom_toolbox/.

  19. Entropy and the Predictability of Online Life

    Directory of Open Access Journals (Sweden)

    Roberta Sinatra

    2014-01-01

    Full Text Available Using mobile phone records and information theory measures, our daily lives have been recently shown to follow strict statistical regularities, and our movement patterns are, to a large extent, predictable. Here, we apply entropy and predictability measures to two datasets of the behavioral actions and the mobility of a large number of players in the virtual universe of a massive multiplayer online game. We find that movements in virtual human lives follow the same high levels of predictability as offline mobility, where future movements can, to some extent, be predicted well if the temporal correlations of visited places are accounted for. Time series of behavioral actions show similar high levels of predictability, even when temporal correlations are neglected. Entropy conditional on specific behavioral actions reveals that in terms of predictability, negative behavior has a wider variety than positive actions. The actions that contain the information to best predict an individual’s subsequent action are negative, such as attacks or enemy markings, while the positive actions of friendship marking, trade and communication contain the least amount of predictive information. These observations show that predicting behavioral actions requires less information than predicting the mobility patterns of humans for which the additional knowledge of past visited locations is crucial and that the type and sign of a social relation has an essential impact on the ability to determine future behavior.

  20. Prediction of rates of inbreeding in populations selected on best linear unbiased prediction of breeding value.

    OpenAIRE

    Bijma, P.; Woolliams, John

    2000-01-01

    Predictions for the rate of inbreeding (DeltaF) in populations with discrete generations undergoing selection on best linear unbiased prediction (BLUP) of breeding value were developed. Predictions were based on the concept of long-term genetic contributions using a recently established relationship between expected contributions and rates of inbreeding and a known procedure for predicting expected contributions. Expected contributions of individuals were predicted using a linear model, u(i)(...

  1. Prediction of mountain stream morphology

    Science.gov (United States)

    Wohl, Ellen; Merritt, David

    2005-08-01

    We use a large and diverse data set from mountain streams around the world to explore relationships between reach-scale channel morphology and control variables. The data set includes 177 step-pool reaches, 44 plane-bed reaches, and 114 pool-riffle reaches from the western United States, Panama, and New Zealand. We performed several iterations of stepwise discriminant analysis on these data. A three-variable discriminant function using slope (S), D84, and channel width (w) produced an error rate of 24% for the entire data set. Seventy percent of plane-bed reaches were correctly classified (16% incorrectly classified as pool-riffle and 14% incorrectly classified as step-pool). Sixty-seven percent of pool-riffle channels were correctly classified (31% incorrectly classified as plane-bed and 2% as step-pool). Eighty-nine percent of step-pool reaches were correctly classified (9% incorrectly classified as plane-bed and 2% as pool-riffle). The partial R2 values and F tests indicate that S is by far the most significant single explanatory variable. Comparison of the eight discriminant functions developed using different data sets indicates that no single variable is present in all functions, suggesting that the discriminant functions are sensitive to the specific stream reaches being analyzed. However, the three-variable discriminant function developed from the entire data set correctly classified 69% of the 159 channels included in an independent validation data set. The ability to accurately classify channel type in other regions using the three-variable discriminant function developed from the entire data set has important implications for water resources management, such as facilitating prediction of channel morphology using regional S-w-D84 relations calibrated with minimal field work.

  2. Prediction of tar ball formation

    Energy Technology Data Exchange (ETDEWEB)

    Khelifa, A.; Gamble, L. [Environment Canada, Ottawa, ON (Canada). Emergencies Science and Technology Division, Environmental Technology Centre, Science and Technology Branch

    2006-07-01

    The presence of small tar balls ranging in size from less than a millimetre to 60 centimetres have been observed during cleanup assessment operations following accidental oil spills on water. The tar balls are composed of heavy oil residues and suspended particulate matter (SPM) from the water column. They can be found on shorelines, settled on the seafloor and floating at or near the water surface. Their abundance on the shorelines varies from site to site and depends on the conditions of the spill and mixing conditions. Aggregation between SPM and micro-sized oil droplets occurs naturally in coastal waters and enhances the dispersion of spilled oil. Although tar balls are among the important end states of spilled oil in the marine environment, no model exists to estimate the percentage of the spilled oil that becomes tar balls. This paper offered some insight into the modeling of tar ball formation. Current modeling understanding of oil-SPM aggregate formation was used to predict tar ball formation. The formation of oil droplets was examined with respect to a range of conditions under which the formation of large droplets is expected. The role of aggregation was then presented to demonstrate the effects of concentration and type of SPM on the buoyancy of tar balls. Good agreement was found between modeling results and field data reported in the literature regarding the size and density of tar balls. Oil viscosity and mixing energy were found to be the main factors controlling the formation of tar balls. The aggregation of tar balls with SPM and shoreline material results in significant increases or decreases in density, depending on the type and concentration of SPM. 42 refs., 2 tabs., 6 figs.

  3. An iterative approach of protein function prediction

    Directory of Open Access Journals (Sweden)

    Chi Xiaoxiao

    2011-11-01

    Full Text Available Abstract Background Current approaches of predicting protein functions from a protein-protein interaction (PPI dataset are based on an assumption that the available functions of the proteins (a.k.a. annotated proteins will determine the functions of the proteins whose functions are unknown yet at the moment (a.k.a. un-annotated proteins. Therefore, the protein function prediction is a mono-directed and one-off procedure, i.e. from annotated proteins to un-annotated proteins. However, the interactions between proteins are mutual rather than static and mono-directed, although functions of some proteins are unknown for some reasons at present. That means when we use the similarity-based approach to predict functions of un-annotated proteins, the un-annotated proteins, once their functions are predicted, will affect the similarities between proteins, which in turn will affect the prediction results. In other words, the function prediction is a dynamic and mutual procedure. This dynamic feature of protein interactions, however, was not considered in the existing prediction algorithms. Results In this paper, we propose a new prediction approach that predicts protein functions iteratively. This iterative approach incorporates the dynamic and mutual features of PPI interactions, as well as the local and global semantic influence of protein functions, into the prediction. To guarantee predicting functions iteratively, we propose a new protein similarity from protein functions. We adapt new evaluation metrics to evaluate the prediction quality of our algorithm and other similar algorithms. Experiments on real PPI datasets were conducted to evaluate the effectiveness of the proposed approach in predicting unknown protein functions. Conclusions The iterative approach is more likely to reflect the real biological nature between proteins when predicting functions. A proper definition of protein similarity from protein functions is the key to predicting

  4. Multiple architecture system for wind speed prediction

    International Nuclear Information System (INIS)

    A new approach based on multiple architecture system (MAS) for the prediction of wind speed is proposed. The motivation behind the proposed approach is to combine the complementary predictive powers of multiple models in order to improve the performance of the prediction process. The proposed MAS can be implemented by associating the predictions obtained from the different regression algorithms (MLR, MLP, RBF and SVM) making up the ensemble by three fusion strategies (simple, weighted and non-linear). The efficiency of the proposed approach has been assessed on a real data set recorded from seven locations in Algeria during a period of 10 years. The experimental results point out that the proposed MAS approach is capable of improving the precision of the wind speed prediction compared to the traditional prediction methods.

  5. Prediction of aspiration in myasthenia gravis.

    Science.gov (United States)

    Koopman, Wilma J; Wiebe, Samuel; Colton-Hudson, Angela; Moosa, Tas; Smith, Dean; Bach, David; Nicolle, Michael W

    2004-02-01

    Prediction of the risk of dysphagia and aspiration is important in the management of myasthenia gravis (MG). We assessed the ability of four bedside clinical tools to predict aspiration in 20 MG patients. Patients completed a self-directed questionnaire, underwent clinical neurological assessment and a bedside speech pathology assessment, and were assessed with the quantitative myasthenia gravis (QMG) score. The ability of these tools to predict aspiration was compared with the results of a modified barium swallow. Seven patients aspirated, 4 silently. The total self-directed questionnaire score, two specific questions on the self-directed questionnaire, the prediction based on clinical neurological assessment, and the QMG bulbar subset score all correlated with aspiration. The speech pathology prediction was highly sensitive but less specific. This pilot study shows that simple clinical tools can predict which MG patients are at risk of aspiration. PMID:14755491

  6. Video Traffic Prediction Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Miloš Oravec

    2008-10-01

    Full Text Available In this paper, we consider video stream prediction for application in services likevideo-on-demand, videoconferencing, video broadcasting, etc. The aim is to predict thevideo stream for an efficient bandwidth allocation of the video signal. Efficient predictionof traffic generated by multimedia sources is an important part of traffic and congestioncontrol procedures at the network edges. As a tool for the prediction, we use neuralnetworks – multilayer perceptron (MLP, radial basis function networks (RBF networksand backpropagation through time (BPTT neural networks. At first, we briefly introducetheoretical background of neural networks, the prediction methods and the differencebetween them. We propose also video time-series processing using moving averages.Simulation results for each type of neural network together with final comparisons arepresented. For comparison purposes, also conventional (non-neural prediction isincluded. The purpose of our work is to construct suitable neural networks for variable bitrate video prediction and evaluate them. We use video traces from [1].

  7. Predictive Approaches to Control of Complex Systems

    CERN Document Server

    Karer, Gorazd

    2013-01-01

    A predictive control algorithm uses a model of the controlled system to predict the system behavior for various input scenarios and determines the most appropriate inputs accordingly. Predictive controllers are suitable for a wide range of systems; therefore, their advantages are especially evident when dealing with relatively complex systems, such as nonlinear, constrained, hybrid, multivariate systems etc. However, designing a predictive control strategy for a complex system is generally a difficult task, because all relevant dynamical phenomena have to be considered. Establishing a suitable model of the system is an essential part of predictive control design. Classic modeling and identification approaches based on linear-systems theory are generally inappropriate for complex systems; hence, models that are able to appropriately consider complex dynamical properties have to be employed in a predictive control algorithm. This book first introduces some modeling frameworks, which can encompass the most frequ...

  8. Return Predictability, Model Uncertainty, and Robust Investment

    OpenAIRE

    Lukas, Manuel

    2013-01-01

    Stock return predictability is subject to great uncertainty. In this paper we usethe model confidence set approach to quantify uncertainty about expected utilityfrom investment, accounting for potential return predictability. For monthly USdata and six representative return prediction models, we find that confidence setsare very wide, change significantly with the predictor variables, and frequentlyinclude expected utilities for which the investor prefers not to invest. The lattermotivates a ...

  9. Towards the perfect prediction of soccer matches

    OpenAIRE

    Heuer, Andreas; Rubner, Oliver

    2012-01-01

    We present a systematic approach to the prediction of soccer matches. First, we show that the information about chances for goals is by far more informative than about the actual results. Second, we present a multivariate regression approach and show how the prediction quality increases with increasing information content. This prediction quality can be explicitly expressed in terms of just two parameters. Third, by disentangling the systematic and random components of soccer matches we can i...

  10. Mobile Homophily and Social Location Prediction

    OpenAIRE

    Bapierre, Halgurt; Jesdabodi, Chakajkla; Groh, Georg

    2015-01-01

    The mobility behavior of human beings is predictable to a varying degree e.g. depending on the traits of their personality such as the trait extraversion - introversion: the mobility of introvert users may be more dominated by routines and habitual movement patterns, resulting in a more predictable mobility behavior on the basis of their own location history while, in contrast, extrovert users get about a lot and are explorative by nature, which may hamper the prediction of their mobility. Ho...

  11. Do university entrance exams predict academic achievement?

    OpenAIRE

    Häkkinen, Iida

    2004-01-01

    The study examines which factors predict academic performance at university and compares the predictive values of subject-related entrance exams and indicators of past school performance. The results show that in the fields of engineering and social sciences entrance exams predict both graduation and the number of study credits better than past performance. In education past school performance is a better predictor of graduation. Changing the admission rule to school grades would affect the a...

  12. Applications of Neural Networks in Spinning Prediction

    Institute of Scientific and Technical Information of China (English)

    程文红; 陆凯

    2003-01-01

    The neural network spinning prediction model (BP and RBF Networks) trained by data from the mill can predict yarn qualities and spinning performance. The input parameters of the model are as follows: yarn count, diameter, hauteur, bundle strength, spinning draft, spinning speed, traveler number and twist.And the output parameters are: yarn evenness, thin places, tenacity and elongation, ends-down.Predicting results match the testing data well.

  13. Empirical studies on stock return predictability

    OpenAIRE

    Wang, Jingya

    2016-01-01

    This thesis includes three essays on topics related to the predictability of market returns. I investigate i) the predictability of market returns from an adjusted version of cay ratio (cayadj), ii) the explanatory power of a conditional version of the consumption-CAPM which uses predictor variables to scale the pricing kernel, and iii) whether information about future market returns can be extracted from a large set of commodity data.The first essay studies the predictive ability of cayadj ....

  14. Sparse preconditioning for model predictive control

    OpenAIRE

    Knyazev, Andrew; Malyshev, Alexander,

    2015-01-01

    We propose fast O(N) preconditioning, where N is the number of gridpoints on the prediction horizon, for iterative solution of (non)-linear systems appearing in model predictive control methods such as forward-difference Newton-Krylov methods. The Continuation/GMRES method for nonlinear model predictive control, suggested by T. Ohtsuka in 2004, is a specific application of the Newton-Krylov method, which uses the GMRES iterative algorithm to solve a forward difference approximation of the opt...

  15. Shape Prediction Linear Algorithm Using Fuzzy

    Directory of Open Access Journals (Sweden)

    Navjot Kaur

    2012-10-01

    Full Text Available The goal of the proposed method is to develop shape prediction algorithm using fuzzy that is computationally fast and invariant. To predict the overlapping and joined shapes accurately, a method of shape prediction based on erosion and over segmentation is used to estimate values for dependent variables from previously unseen predictor values based on the variation in an underlying learning data set.

  16. RESULTS FROM A SIMPLE PREDICTION CONTEST

    OpenAIRE

    Calvin Blackwell

    2011-01-01

    In a prediction contest participants compete for a prize by submitting guesses regarding an unknown variable; the winner of the contest is the participant who submits the most accurate guess. In this paper the results of a simple prediction contest are reported. In the contest, certain members of the administration of a medium-sized university were asked to predict the number of freshmen deposits the university would receive by its spring deadline. Contest participants were told that the cont...

  17. Topology and prediction of RNA pseudoknots

    DEFF Research Database (Denmark)

    Reidys, Christian; Huang, Fenix; Andersen, Jørgen Ellegaard;

    2011-01-01

    Motivation: Several dynamic programming algorithms for predicting RNA structures with pseudoknots have been proposed that differ dramatically from one another in the classes of structures considered. Results: Here, we use the natural topological classification of RNA structures in terms of...... dynamic programming approach for energy minimization, partition function and stochastic sampling. It admits a topology-dependent parametrization of pseudoknot penalties that increases the sensitivity and positive predictive value of predicted base pairs by 10–20% compared with earlier approaches. More...

  18. Predictive Functional Control for a Parallel Robot

    OpenAIRE

    Vivas, Oscar Andrès; Poignet, Philippe; Pierrot, François

    2003-01-01

    This paper presents an efficient application of a model based predictive control in parallel mechanisms. A predictive functional control control strategy based on a simplified dynamic model is implemented. Experimental results are shown for the H4 robot, a fully parallel structure providing 3 degrees of freedom (dof) in translation and 1 dof in rotation. Predictive functional control, computed torque control and PID control strategies are compared in complex machining tasks trajectories. The ...

  19. Two Comments on Predictive Picture Coding

    Institute of Scientific and Technical Information of China (English)

    1998-01-01

    Two comments on predictive picture coding are given in this paper. 1) In lossy coding, the reconstructed values of picture samples, not its original values, should be used in the prediction formula. 2) In the design of optimum predictors, the minimum entropy or subjective assessment or other criterions, could be used, depending on the applications of the prediction encoder, instead of the minimum mean square error (MMSE) criterion.

  20. Essays on Return Predictability in Financial Markets

    OpenAIRE

    Mang, Chan R.

    2012-01-01

    My thesis examines return predictability in government bond markets and currency markets. In Chapter 1, I take the term structure model in Cochrane and Piazzesi (2008) and construct currency market prices. The implied currency market prices are then counterfactually volatile and predictable, at least with respect to commonly used predictor variables. Getting the model closer to currency market data means reducing bond risk compensation but doing so nearly eliminates predictability in bond mar...

  1. Video Traffic Prediction Using Neural Networks

    OpenAIRE

    Miloš Oravec; Miroslav Petráš; Filip Pilka

    2008-01-01

    In this paper, we consider video stream prediction for application in services likevideo-on-demand, videoconferencing, video broadcasting, etc. The aim is to predict thevideo stream for an efficient bandwidth allocation of the video signal. Efficient predictionof traffic generated by multimedia sources is an important part of traffic and congestioncontrol procedures at the network edges. As a tool for the prediction, we use neuralnetworks – multilayer perceptron (MLP), radial basis function n...

  2. AIDS: predicting cases nationally and locally.

    OpenAIRE

    Tennison, B R; Hagard, S

    1988-01-01

    Models for predicting the future course of the AIDS epidemic can be divided into five types: trend extrapolation models, compartment models, models based on the incubation period, comparison models, and models produced by expert committees. To predict the numbers of cases of AIDS in the United Kingdom and in East Anglia and Cambridge a two stage approach was chosen using trend extrapolation for the national case reports followed by reduction in scale to the two localities. The method predicte...

  3. Mining Twitter Data for Resource Usage Prediction

    OpenAIRE

    2012-01-01

    This thesis investigates the predictability of Twitter traffic for topic-related websites’ resource requirements by developing and implementing a data mining methodology. The new traffic correlation mining process is able to extract traffic surges and develop potential predictive mining and correlation techniques between Twitter and the corresponding forum. Thorough testing of this data mining methodology has been performed, and the results show that using Twitter data to predict imminent res...

  4. Predicting of Ukrainian Horticulture Market Development

    OpenAIRE

    Sokil, Yana

    2013-01-01

    For determination of community needs in garden-stuffs and berries for period 2012-2015 it is suggested to carry out prediction of consumption level of horticulture products by the construction of neuron network on the basis of architecture “8-4-1” multilayered perceptron. Initial and predicted rows of consumption level of horticulture products with the purpose of possibility exposure of the predicted volumes of horticultural products consumption for period 2012-2015 and used for developmen...

  5. Towards the perfect prediction of soccer matches

    CERN Document Server

    Heuer, Andreas

    2012-01-01

    We present a systematic approach to the prediction of soccer matches. First, we show that the information about chances for goals is by far more informative than about the actual results. Second, we present a multivariate regression approach and show how the prediction quality increases with increasing information content. This prediction quality can be explicitly expressed in terms of just two parameters. Third, by disentangling the systematic and random components of soccer matches we can identify the optimum level of predictability. These concepts are exemplified for the German Bundesliga.

  6. Earthquake prediction decision and risk matrix

    Science.gov (United States)

    Zou, Qi-Jia

    1993-08-01

    The issuance of an earthquake prediction must cause widespread social responses. It is suggested and discussed in this paper that the comprehensive decision issue for earthquake prediction considering the factors of the social and economic cost. The method of matrix decision for earthquake prediction (MDEP) is proposed in this paper and it is based on the risk matrix. The goal of decision is that search the best manner issuing earthquake prediction so that minimize the total losses of economy. The establishment and calculation of the risk matrix is discussed, and the decision results taking account of economic factors and not considering the economic factors are compared by examples in this paper.

  7. RNA structure prediction: progress and perspective

    CERN Document Server

    Shi, Ya-Zhou; Wang, Feng-Hua; Tan, Zhi-Jie

    2014-01-01

    Many recent exciting discoveries have revealed the versatility of RNAs and their importance in a variety of cellular functions which are strongly coupled to RNA structures. To understand the functions of RNAs, some structure prediction models have been developed in recent years. In this review, the progress in computational models for RNA structure prediction is introduced and the distinguishing features of many outstanding algorithms are discussed, emphasizing three dimensional (3D) structure prediction. A promising coarse-grained model for predicting RNA 3D structure, stability and salt effect is also introduced briefly. Finally, we discuss the major challenges in the RNA 3D structure modeling.

  8. Final Technical Report: Increasing Prediction Accuracy.

    Energy Technology Data Exchange (ETDEWEB)

    King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stein, Joshua [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-12-01

    PV performance models are used to quantify the value of PV plants in a given location. They combine the performance characteristics of the system, the measured or predicted irradiance and weather at a site, and the system configuration and design into a prediction of the amount of energy that will be produced by a PV system. These predictions must be as accurate as possible in order for finance charges to be minimized. Higher accuracy equals lower project risk. The Increasing Prediction Accuracy project at Sandia focuses on quantifying and reducing uncertainties in PV system performance models.

  9. Prediction of reliability of PDC CPU board

    International Nuclear Information System (INIS)

    To predict the reliability of electronic equipment including digital control systems, the data from MIL-HDBK217 and Bellcore TR-332 is used. But these data have some weakness that is old or based on inaccurate specification and environment condition. Each data shows different prediction results because each one has specific failure data and prediction methods The reliability of Wolsong 1 PDC CPU board was evaluated with various data to identify effects of different data. The results were analyzed with experienced failure data and vendor data. Through the analysis, it was demonstrated that the predicted failure rate is sensitive to the selection of data and method

  10. An overview of service lifetime prediction (SLP)

    Energy Technology Data Exchange (ETDEWEB)

    Jorgensen, G. [National Renewable Energy Laboratory, Golden, CO (United States)

    1995-11-01

    This report describes the need for service life prediction for photovoltaic cells and associated devices, coatings, and other related technologies. Information regarding outdoor exposure tests is given.

  11. Improved interpretation and validation of CFD predictions

    DEFF Research Database (Denmark)

    Popiolek, Z.; Melikov, Arsen Krikor

    2004-01-01

    The mean velocity in rooms predicted by CFD simulations based on RANS equations differs from the mean (in time) magnitude of the velocity, i.e. the mean speed, in rooms measured by low velocity thermal anemometers with omnidirectional sensor. This discrepancy results in incorrect thermal comfort...... assessment by the CFD predictions as well as incorrect validation of the predicted velocity field. In this paper the discrepancies are discussed and identified, and a method for estimating of the mean speed based on the CFD predictions of mean velocity and kinetic turbulence energy is suggested. The method...

  12. Implementation of short-term prediction

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L.; Joensen, A.; Giebel, G. [and others

    1999-03-01

    This paper will giver a general overview of the results from a EU JOULE funded project (`Implementing short-term prediction at utilities`, JOR3-CT95-0008). Reference will be given to specialised papers where applicable. The goal of the project was to implement wind farm power output prediction systems in operational environments at a number of utilities in Europe. Two models were developed, one by Risoe and one by the Technical University of Denmark (DTU). Both prediction models used HIRLAM predictions from the Danish Meteorological Institute (DMI). (au) EFP-94; EU-JOULE. 11 refs.

  13. Predictions of High Energy Experimental Results

    Directory of Open Access Journals (Sweden)

    Comay E.

    2010-10-01

    Full Text Available Eight predictions of high energy experimental results are presented. The predictions contain the $Sigma ^+$ charge radius and results of two kinds of experiments using energetic pionic beams. In addition, predictions of the failure to find the following objects are presented: glueballs, pentaquarks, Strange Quark Matter, magnetic monopoles searched by their direct interaction with charges and the Higgs boson. The first seven predictions rely on the Regular Charge-Monopole Theory and the last one relies on mathematical inconsistencies of the Higgs Lagrangian density.

  14. Stock market index prediction using neural networks

    Science.gov (United States)

    Komo, Darmadi; Chang, Chein-I.; Ko, Hanseok

    1994-03-01

    A neural network approach to stock market index prediction is presented. Actual data of the Wall Street Journal's Dow Jones Industrial Index has been used for a benchmark in our experiments where Radial Basis Function based neural networks have been designed to model these indices over the period from January 1988 to Dec 1992. A notable success has been achieved with the proposed model producing over 90% prediction accuracies observed based on monthly Dow Jones Industrial Index predictions. The model has also captured both moderate and heavy index fluctuations. The experiments conducted in this study demonstrated that the Radial Basis Function neural network represents an excellent candidate to predict stock market index.

  15. Fracture Toughness Prediction for MWCNT Reinforced Ceramics

    Energy Technology Data Exchange (ETDEWEB)

    Henager, Charles H.; Nguyen, Ba Nghiep

    2013-09-01

    This report describes the development of a micromechanics model to predict fracture toughness of multiwall carbon nanotube (MWCNT) reinforced ceramic composites to guide future experimental work for this project. The modeling work described in this report includes (i) prediction of elastic properties, (ii) development of a mechanistic damage model accounting for matrix cracking to predict the composite nonlinear stress/strain response to tensile loading to failure, and (iii) application of this damage model in a modified boundary layer (MBL) analysis using ABAQUS to predict fracture toughness and crack resistance behavior (R-curves) for ceramic materials containing MWCNTs at various volume fractions.

  16. Programming Useful Life Prediction (PULP) Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Accurately predicting Remaining Useful Life (RUL) provides significant benefits—it increases safety and reduces financial and labor resource requirements....

  17. Computer loss experience and predictions

    Science.gov (United States)

    Parker, Donn B.

    1996-03-01

    The types of losses organizations must anticipate have become more difficult to predict because of the eclectic nature of computers and the data communications and the decrease in news media reporting of computer-related losses as they become commonplace. Total business crime is conjectured to be decreasing in frequency and increasing in loss per case as a result of increasing computer use. Computer crimes are probably increasing, however, as their share of the decreasing business crime rate grows. Ultimately all business crime will involve computers in some way, and we could see a decline of both together. The important information security measures in high-loss business crime generally concern controls over authorized people engaged in unauthorized activities. Such controls include authentication of users, analysis of detailed audit records, unannounced audits, segregation of development and production systems and duties, shielding the viewing of screens, and security awareness and motivation controls in high-value transaction areas. Computer crimes that involve highly publicized intriguing computer misuse methods, such as privacy violations, radio frequency emanations eavesdropping, and computer viruses, have been reported in waves that periodically have saturated the news media during the past 20 years. We must be able to anticipate such highly publicized crimes and reduce the impact and embarrassment they cause. On the basis of our most recent experience, I propose nine new types of computer crime to be aware of: computer larceny (theft and burglary of small computers), automated hacking (use of computer programs to intrude), electronic data interchange fraud (business transaction fraud), Trojan bomb extortion and sabotage (code security inserted into others' systems that can be triggered to cause damage), LANarchy (unknown equipment in use), desktop forgery (computerized forgery and counterfeiting of documents), information anarchy (indiscriminate use of

  18. Drought Predictability and Prediction in a Changing Climate: Assessing Current Predictive Knowledge and Capabilities, User Requirements and Research Priorities

    Science.gov (United States)

    Schubert, Siegfried

    2011-01-01

    Drought is fundamentally the result of an extended period of reduced precipitation lasting anywhere from a few weeks to decades and even longer. As such, addressing drought predictability and prediction in a changing climate requires foremost that we make progress on the ability to predict precipitation anomalies on subseasonal and longer time scales. From the perspective of the users of drought forecasts and information, drought is however most directly viewed through its impacts (e.g., on soil moisture, streamflow, crop yields). As such, the question of the predictability of drought must extend to those quantities as well. In order to make progress on these issues, the WCRP drought information group (DIG), with the support of WCRP, the Catalan Institute of Climate Sciences, the La Caixa Foundation, the National Aeronautics and Space Administration, the National Oceanic and Atmospheric Administration, and the National Science Foundation, has organized a workshop to focus on: 1. User requirements for drought prediction information on sub-seasonal to centennial time scales 2. Current understanding of the mechanisms and predictability of drought on sub-seasonal to centennial time scales 3. Current drought prediction/projection capabilities on sub-seasonal to centennial time scales 4. Advancing regional drought prediction capabilities for variables and scales most relevant to user needs on sub-seasonal to centennial time scales. This introductory talk provides an overview of these goals, and outlines the occurrence and mechanisms of drought world-wide.

  19. Initial Value Predictability of Intrinsic Oceanic Modes and Implications for Decadal Prediction over North America

    Energy Technology Data Exchange (ETDEWEB)

    Branstator, Grant

    2014-12-09

    The overall aim of our project was to quantify and characterize predictability of the climate as it pertains to decadal time scale predictions. By predictability we mean the degree to which a climate forecast can be distinguished from the climate that exists at initial forecast time, taking into consideration the growth of uncertainty that occurs as a result of the climate system being chaotic. In our project we were especially interested in predictability that arises from initializing forecasts from some specific state though we also contrast this predictability with predictability arising from forecasting the reaction of the system to external forcing – for example changes in greenhouse gas concentration. Also, we put special emphasis on the predictability of prominent intrinsic patterns of the system because they often dominate system behavior. Highlights from this work include: • Development of novel methods for estimating the predictability of climate forecast models. • Quantification of the initial value predictability limits of ocean heat content and the overturning circulation in the Atlantic as they are represented in various state of the artclimate models. These limits varied substantially from model to model but on average were about a decade with North Atlantic heat content tending to be more predictable than North Pacific heat content. • Comparison of predictability resulting from knowledge of the current state of the climate system with predictability resulting from estimates of how the climate system will react to changes in greenhouse gas concentrations. It turned out that knowledge of the initial state produces a larger impact on forecasts for the first 5 to 10 years of projections. • Estimation of tbe predictability of dominant patterns of ocean variability including well-known patterns of variability in the North Pacific and North Atlantic. For the most part these patterns were predictable for 5 to 10 years. • Determination of

  20. Transfer of predictive signals across saccades

    Directory of Open Access Journals (Sweden)

    PetraVetter

    2012-06-01

    Full Text Available Predicting visual information facilitates efficient processing of visual signals. Higher visual areas can support the processing of incoming visual information by generating predictive models that are fed back to lower visual areas. Functional brain imaging has previously shown that predictions interact with visual input already at the level of the primary visual cortex (V1; Alink et al., 2010; Harrison et al., 2007. Given that fixation changes up to four times a second in natural viewing conditions, cortical predictions are effective in V1 only if they are fed back in time for the processing of the next stimulus and at the corresponding new retinotopic position. Here, we tested whether spatio-temporal predictions are updated before, during or shortly after an interhemifield saccade is executed, and thus, whether the predictive signal is transferred swiftly across hemifields. Using an apparent motion illusion, we induced an internal motion model that is known to produce a spatio-temporal prediction signal along the apparent motion trace in V1 (Muckli et al., 2005, Alink et al., 2010. We presented participants with both visually predictable and unpredictable targets on the apparent motion trace. During the task, participants saccaded across the illusion whilst detecting the target. As found previously, predictable stimuli were detected more frequently than unpredictable stimuli. Furthermore, we found that the detection advantage of predictable targets is detectable as early as 50-100 ms after saccade offset. This result demonstrates the rapid nature of the transfer of a spatio-temporally precise predictive signal across hemifields, in a paradigm previously shown to modulate V1.

  1. Meta-analysis of clinical prediction models

    NARCIS (Netherlands)

    Debray, T.P.A.

    2013-01-01

    The past decades there has been a clear shift from implicit to explicit diagnosis and prognosis. This includes appreciation of clinical -diagnostic and prognostic- prediction models, which is likely to increase with the introduction of fully computerized patient records. Prediction models aim to pro

  2. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp;

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...

  3. LocTree3 prediction of localization

    DEFF Research Database (Denmark)

    Goldberg, T.; Hecht, M.; Hamp, T.;

    2014-01-01

    The prediction of protein sub-cellular localization is an important step toward elucidating protein function. For each query protein sequence, LocTree2 applies machine learning (profile kernel SVM) to predict the native sub-cellular localization in 18 classes for eukaryotes, in six for bacteria and...

  4. PREDICTING ADVERTISING EXPENDITURES USING INTENTION SURVEYS

    NARCIS (Netherlands)

    ALSEM, KJ; LEEFLANG, PSH

    1994-01-01

    In this article we study the use of intention surveys to predict the effects of a possible entrant. The case under investigation deals with the introduction of private broadcasting in the Netherlands. Several predictions of the advertising expenditures in various media are given which depend on a nu

  5. An online railway traffic prediction model

    NARCIS (Netherlands)

    Kecman, P.; Goverde, R.M.P.

    2013-01-01

    Prediction of train positions in time and space is required for traffic control and passenger information. However, in practice only the last measured train delays are known and dispatchers must predict the arrival times of trains without adequate computer support. This paper presents a real-time to

  6. Predicting Information Flows in Network Traffic.

    Science.gov (United States)

    Hinich, Melvin J.; Molyneux, Robert E.

    2003-01-01

    Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)

  7. Prediction of treatment response to adalimumab

    DEFF Research Database (Denmark)

    Krintel, S B; Dehlendorff, C; Hetland, M L;

    2016-01-01

    At least 30% of patients with rheumatoid arthritis (RA) do not respond to biologic agents, which emphasizes the need of predictive biomarkers. We aimed to identify microRNAs (miRNAs) predictive of response to adalimumab in 180 treatment-naïve RA patients enrolled in the OPtimized treatment algori...

  8. Tail Risk Premia and Return Predictability

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Todorov, Viktor; Xu, Lai

    The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may be......-varying economic uncertainty and changes in risk aversion, or market fears, respectively....

  9. Intelligent Predictive Control of Nonlienar Processes Using

    DEFF Research Database (Denmark)

    Nørgård, Peter Magnus; Sørensen, Paul Haase; Poulsen, Niels Kjølstad;

    1996-01-01

    This paper presents a novel approach to design of generalized predictive controllers (GPC) for nonlinear processes. A neural network is used for modelling the process and a gain-scheduling type of GPC is subsequently designed. The combination of neural network models and predictive control has fr...

  10. Protein secondary structure: category assignment and predictability

    DEFF Research Database (Denmark)

    Andersen, Claus A.; Bohr, Henrik; Brunak, Søren

    2001-01-01

    structures. Single sequence prediction of the new three category assignment gives an overall prediction improvement of 3.1% and 5.1%, compared to the DSSP assignment and schemes where the helix category consists of a-helix and 3(10)-helix, respectively. These results were achieved using a standard feed...

  11. How to Establish Clinical Prediction Models.

    Science.gov (United States)

    Lee, Yong Ho; Bang, Heejung; Kim, Dae Jung

    2016-03-01

    A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice. PMID:26996421

  12. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    2010-01-01

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  13. Audiovisual biofeedback improves motion prediction accuracy

    OpenAIRE

    Pollock, Sean; Lee, Danny; Keall, Paul; Kim, Taeho

    2013-01-01

    Purpose: The accuracy of motion prediction, utilized to overcome the system latency of motion management radiotherapy systems, is hampered by irregularities present in the patients’ respiratory pattern. Audiovisual (AV) biofeedback has been shown to reduce respiratory irregularities. The aim of this study was to test the hypothesis that AV biofeedback improves the accuracy of motion prediction.

  14. Predicting facial characteristics from complex polygenic variations

    DEFF Research Database (Denmark)

    Fagertun, Jens; Wolffhechel, Karin Marie Brandt; Pers, Tune;

    2015-01-01

    traits in a linear regression. We show in this proof-of-concept study for facial trait prediction from genome-wide SNP data that some facial characteristics can be modeled by genetic information: facial width, eyebrow width, distance between eyes, and features involving mouth shape are predicted with...

  15. Beautiful mass predictions from scalar lattice QCD

    Energy Technology Data Exchange (ETDEWEB)

    Samuel, S.; Moriarty, K.J.M.

    1986-07-31

    Scalar lattice QCD methods are used to accurately predict the masses of hadrons with beauty, that is, states which contain a b quark. These states have not yet been seen in the laboratory. The accuracy of the predictions (approx.=25 MeV) make the calculation a good test of lattice methods as well as providing useful guidance for experimentalists.

  16. A blind test of photometric redshift prediction

    OpenAIRE

    Hogg, David W.; Cohen, Judith G.; Blandford, Roger; Gwyn, Stephen D. J.; Hartwick, F. D. A.; Mobasher, B.; Mazzei, Paula; Sawicki, Marcin; Lin, Huan; Yee, H. K. C.; Connolly, Andrew J; Brunner, Robert J.; Csabai, Istvan; Dickinson, Mark; SubbaRao, Mark U.

    1998-01-01

    Results of a blind test of photometric redshift predictions against spectroscopic galaxy redshifts obtained in the Hubble Deep Field with the Keck Telescope are presented. The best photometric redshift schemes predict spectroscopic redshifts with a redshift accuracy of |Delta-z|

  17. The mechanisms of prediction in language comprehension

    NARCIS (Netherlands)

    Szewczyk, J.M.

    2016-01-01

    Title: The mechanisms of prediction in language comprehension Author: Jakub Szewczyk Abstract: This thesis proefschrift focuses on two topics related to language perception: the role of animacy in language processing, and the mechanisms of language prediction. Animacy is one of the most basic dist

  18. Ultrasonic echolucent carotid plaques predict future strokes

    DEFF Research Database (Denmark)

    Grønholdt, Marie-Louise; Nordestgaard, B G; Schroeder, T V; Vorstrup, S; Sillesen, H

    2001-01-01

    We tested prospectively the hypothesis that stroke development can be predicted by echolucency of carotid atherosclerotic plaques in previously symptomatic and asymptomatic patients.......We tested prospectively the hypothesis that stroke development can be predicted by echolucency of carotid atherosclerotic plaques in previously symptomatic and asymptomatic patients....

  19. Predicting User Actions in Software Processes

    CERN Document Server

    Deynet, Michael

    2011-01-01

    This paper describes an approach for user (e.g. SW architect) assisting in software processes. The approach observes the user's action and tries to predict his next step. For this we use approaches in the area of machine learning (sequence learning) and adopt these for the use in software processes. Keywords: Software engineering, Software process description languages, Software processes, Machine learning, Sequence prediction

  20. Space Weather Prediction and Exascale Computing

    OpenAIRE

    Lapenta, Giovanni; Markidis, Stefano; Poedts, Stefaan; Vucinic, Dean

    2013-01-01

    Space weather can have a great effect on Earth's climate. Predicting the impact of space environment disturbances on Earth presents a challenge to scientists. Here, the ExaScience Lab's efforts are presented, which use exascale computing and new visualization tools to predict the arrival and impact of space events on Earth.