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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 Effects of Tumor-Derived Complement

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    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.

  3. Prolactin as an autocrine/paracrine factor in breast tissue.

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    Clevenger, C V; Plank, T L

    1997-01-01

    The neuroendocrine hormone prolactin (PRL) stimulates breast growth and differentiation during puberty, pregnancy, and lactation. Despite extensive and convincing data indicating that PRL significantly contributes to the pathogenesis and progression of rodent mammary carcinoma, parallel observations for human breast cancer have not been concordant. In particular, the therapeutic alteration of somatolactogenic hormone levels has not consistently altered the course of human breast cancer. Recent data, however, suggest that extra-pituitary tissues are capable of elaborating PRL; indeed, the observation of sustained serum levels of PRL in post-hypophysectomy patients supports this hypothesis. Proof of an autocrine/paracrine loop for PRL within normal and malignant human breast tissues requires that the following three criteria be met: (1) PRL must be synthesized and secreted within mammary tissues; (2) the receptor for PRL (PRLR) must be present within these tissues; and, (3) proliferative responses to autocrine/paracrine PRL must be demonstrated. These criteria have now been fulfilled in several laboratories. With the demonstration of a PRL autocrine/paracrine loop in mammary glands, the basis for the ineffective treatment of human breast cancer by prior endocrine-based anti-somatolactogenic therapies is evident. These findings provide the precedent for novel therapeutic strategies aimed at interrupting the stimulation of breast cancer growth by PRL at both endocrine and autocrine/paracrine levels.

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

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    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...

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

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    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

  6. Autocrine signaling is a key regulatory element during osteoclastogenesis

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    Paul Kopesky

    2014-07-01

    Full Text Available Osteoclasts are responsible for bone destruction in degenerative, inflammatory and metastatic bone disorders. Although osteoclastogenesis has been well-characterized in mouse models, many questions remain regarding the regulation of osteoclast formation in human diseases. We examined the regulation of human precursors induced to differentiate and fuse into multinucleated osteoclasts by receptor activator of nuclear factor kappa-B ligand (RANKL. High-content single cell microscopy enabled the time-resolved quantification of both the population of monocytic precursors and the emerging osteoclasts. We observed that prior to induction of osteoclast fusion, RANKL stimulated precursor proliferation, acting in part through an autocrine mediator. Cytokines secreted during osteoclastogenesis were resolved using multiplexed quantification combined with a Partial Least Squares Regression model to identify the relative importance of specific cytokines for the osteoclastogenesis outcome. Interleukin 8 (IL-8 was identified as one of RANKL-induced cytokines and validated for its role in osteoclast formation using inhibitors of the IL-8 cognate receptors CXCR1 and CXCR2 or an IL-8 blocking antibody. These insights demonstrate that autocrine signaling induced by RANKL represents a key regulatory component of human osteoclastogenesis.

  7. Regulation of spermatogenesis by paracrine/autocrine testicular factors

    Institute of Scientific and Technical Information of China (English)

    MahmoudHuleihel; EitanLunenfeld

    2004-01-01

    Spermatogenesis is a complex process regulated by endocrine and testicular paracrine/autocrine factors.Gonadotropins are involved in the regulation of several testicular paracrine factors, mainly of the IL-1 family and testicular hormones. Testicular cytokines and growth factors (such as IL-1, IL-6, TNF, IFN-T, LIF and SCF) were shown to affect both the germ cell proliferation and the Leydig and Sertoli cells functions and secretion. Cytokines and growth factors are produced by immune cells and in the interstitial and seminiferous tubular compartments by various testicular cells, including Sertoli, Leydig, peritubular cells, spermatogonia, differentiated spermatogonia and even spermatozoa. Corresponding cytokine and growth factor receptors were demonstrated on some of the testicular cells. These cytokines also control the secretion of the gonadotropins and testosterone in the testis. Under pathological conditions the levels of pro-inflammatory cytokines are increased and negatively affected spermatogenesis. Thus,the expression levels and the mechanisms involved in the regulation of testicular paracrine/autocrine factors should be considered in future therapeutic strategies for male infertility. (Asian J Androl 2004 Sep; 6: 259-268)

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

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    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

  9. 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

    2016-08-01

    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.

  10. 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.

  11. FGF19 functions as autocrine growth factor for hepatoblastoma

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    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

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    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. 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.

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

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    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...

  15. 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.

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

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    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

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

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    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

  18. Pancreatic cancer cells require an EGF receptor-mediated autocrine pathway for proliferation in serum-free conditions

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    Murphy, L O; Cluck, M W; Lovas, S; Ötvös, F; Murphy, R F; Schally, A V; Permert, J; Larsson, J; Knezetic, J A; Adrian, T E

    2001-01-01

    In-vitro and in-vivo studies have shown that autocrine growth factors and receptors are frequently expressed in human malignancies. Few of these studies, however, provide evidence that the identified autocrine pathway is functional. In this study, a functional autocrine growth pathway in pancreatic cancer has been identified using an in-vitro cell culture system. When pancreatic cancer cells were grown without change of medium, proliferation was greater than when either medium was replaced frequently (HPAF, CAPAN-2, PANC-1 or SW1990) or cells were grown in the presence of the EGF receptor tyrosine kinase inhibitor AG1478 or the MEK inhibitor PD098059 (HPAF or CAPAN-2). Activity of extracellular-regulated kinases (ERK) 1 and 2 and c- jun and c- fos mRNA levels were significantly elevated in CAPAN-2 cells cultured continuously in serum-free medium. Collectively, the observations indicate that the EGF receptor and the ERK MAP kinase pathway mediate autocrine signals. In contrast to previous reports, the GRP and IGF-I receptors were shown not to be required for autocrine effects on pancreatic cancer cell proliferation. Autocrine stimulation of the EGF receptor can contribute to sustained mitogenic activity and proliferation of pancreatic cancer cells. © 2001 Cancer Research Campaign http://www.bjcancer.com PMID:11286473

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

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    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

  20. 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.

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    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

    2014-09-30

    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 was correlated with a pejorative prognosis in 389 patients with stage I to III lung adenocarcinoma, and was an independent prognosis marker. Interactions between NTS and NTSR1 induce pro-oncogenic biological effects associated with neoplastic processes and tumor progression. Here we highlight the cellular mechanisms activated by Neurotensin (NTS) and its high affinity receptor (NTSR1) contributing to lung cancer cell aggressiveness. We show that the NTS autocrine and/or paracrine regulation causes EGFR, HER2, and HER3 over-expression and activation in lung tumor cells. The EGFR and HER3 autocrine activation is mediated by MMP1 activation and EGF "like" ligands (HB-EGF, Neuregulin 1) release. By establishing autocrine and/or paracrine NTS regulation, we show that tumor growth is modulated according to NTS expression, with a low growth rate in those tumors that do not express NTS. Accordingly, xenografted tumors expressing NTS and NTSR1 showed a positive response to erlotinib, whereas tumors void of NTSR1 expression had no detectable response. This is consistent with the presence of a NTS autocrine loop, leading to the sustained activation of EGFR and responsible for cancer aggressiveness. We propose the use of NTS/NTSR1 tumor expression, as a biomarker for the use of EGFR tyrosine kinase inhibitors in patients lacking EGFR mutation.

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

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    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.

  2. SF/HGF-c-Met autocrine and paracrine promote metastasis of hepatocellular carcinoma

    Institute of Scientific and Technical Information of China (English)

    Qian Xie; Kang-Da Liu; Mei-Yu Hu; Kang Zhou

    2001-01-01

    AIM: To explore the role of SF/HGF-Met autocrine and parscrine in metastasis of hepatocellular carcinoma (HCC). METHODS: SF/HGF and c-met transcription and protein expression in HCC were examined by RT-PCR and Western Blot in 4 HCC cell lines, including HepG2, Hep3B,SMMC7721 and MHCC-1, the last cell line had a higher potential of metastasis. Sf/hgf cDNA was transfected by the method of Lipofectin into SMMC7721. SF/HGF and c-met antibody were used to stimulate and block SF/HGF-c-met signal transduction. Cell morphology, mobility, and proliferation were respectively compared by microscopic observation, wound healing assay and cell growth curve. RESULTS: HCC malignancy appeared to be relative to its met-SF/HGF expression. In MHCC-1, c-met expression was much stronger than that in other cell lines with lower potential of metastasis and only SF/HGF autocrine existed in MHCC-1. After sf/hgf cDNA transfection or conditioned medium of MHCC-1 stimulation, SMMC7721 changed into elongated morphology, and the abilities of proliferation ( P < 0.05) and mobility increased. Such bio-activity could he blocked by c-met antibody ( P< 0.05). CONCLUSION: The system of SF/HGF-c-met autocrine and paracrine played an important role in development and metastasis potential of HCC. Inhibition of SF/HGF-c-met signal transduction system may reduce the growth and metastasis of HCC.

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

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    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.

  4. 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...... 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...

  5. Autocrine and/or paracrine insulin-like growth factor-I activity in skeletal muscle

    Science.gov (United States)

    Adams, Gregory R.

    2002-01-01

    Similar to bone, skeletal muscle responds and adapts to changes in loading state via mechanisms that appear to be intrinsic to the muscle. One of the mechanisms modulating skeletal muscle adaptation it thought to involve the autocrine and/or paracrine production of insulinlike growth factor-I. This brief review outlines components of the insulinlike growth factor-I system as it relates to skeletal muscle and provides the rationale for the theory that insulinlike growth factor-I is involved with muscle adaptation.

  6. 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.

  7. An angiopoietin-like protein 2 autocrine signaling promotes EMT during pancreatic ductal carcinogenesis

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    Carbone, Carmine; Piro, Geny; Fassan, Matteo; Tamburrino, Anna; Mina, Maria Mihaela; Zanotto, Marco; Chiao, Paul J; Bassi, Claudio; Scarpa, Aldo; Tortora, Giampaolo; Melisi, Davide

    2015-01-01

    The identification of the earliest molecular events responsible for the metastatic dissemination of pancreatic ductal adenocarcinoma (PDAC) remains critical for early detection, prevention, and treatment interventions. In this study, we hypothesized that an autocrine signaling between Angiopoietin-like Protein (ANGPTL)2 and its receptor leukocyte immunoglobulin-like receptor B2 (LILRB2) might be responsible for the epithelial-to-mesenchymal transition (EMT) and, the early metastatic behavior of cells in pancreatic preneoplastic lesions. We demonstrated that the sequential activation of KRAS, expression of HER2 and silencing of p16/p14 are sufficient to progressively and significantly increase the secretion of ANGPTL2, and the expression of LILRB2. Silencing the expression of ANGPTL2 reverted EMT and reduced migration in these cell lines. Blocking ANGPTL2 receptor LILRB2 in KRAS, and KRAS/HER2/p16p14shRNA LILRB2- expressing cells reduced ANGPTL2-induced cell proliferation and invasion. An increasingly significant overexpression of ANGPTL2 was observed in in a series of 68 different human PanIN and 27 PDAC lesions if compared with normal pancreatic parenchyma. These findings showed that the autocrine signaling of ANGPTL2 and its receptor LILRB2 plays key roles in sustaining EMT and the early metastatic behavior of cells in pancreatic preneoplastic lesions supporting the potential role of ANGPTL2 for early detection, metastasis prevention, and treatment in PDAC. PMID:25360865

  8. 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

  9. 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

  10. 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

  11. 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

  12. Autocrine secretion of interferon gamma negatively regulates homing of immature B cells.

    Science.gov (United States)

    Flaishon, L; Hershkoviz, R; Lantner, F; Lider, O; Alon, R; Levo, Y; Flavell, R A; Shachar, I

    2000-11-01

    The mechanism by which immature B cells are sequestered from encountering foreign antigens present in lymph nodes or sites of inflammation, before their final maturation in the spleen, has not been elucidated. We show here that immature B cells fail to home to the lymph nodes. These cells can actively exclude themselves from antigen-enriched sites by downregulating their integrin-mediated adhesion to the extracellular matrix protein, fibronectin. This inhibition is mediated by interferon gamma secretion. Perturbation of interferon gamma activity in vivo leads to the homing of immature B cells to the lymph nodes. This is the first example of autocrine regulation of immune cell migration to sites of foreign antigen presentation. PMID:11067886

  13. Purification of autocrine growth factor from conditioned medium of rat sarcoma (XC) cells.

    Science.gov (United States)

    Checiówna, D; Klein, A

    1996-01-01

    Transformation of rat cells by Rous sarcoma virus(es) induced the release of growth factors into serum-free conditioned media. An PR-RSV-transformed rat cell line, XC, produced and released polypeptide factors which promote anchorage-dependent and anchorage-independent growth of XC cells. One of the autocrine factors of XC cells was purified to homogeneity by four-step procedure: ultrafiltration, ion-exchange chromatography on MonoS, reverse-phase chromatography on Spherisorb ODS2 and gel filtration on Superose 12. The factor gave a single band on SDS-electrophoresis on polyacrylamide gel and was assumed to have a molecular weight of 16 kDa. The factor is a potent mitogen for XC cells; half-maximal stimulation of DNA synthesis was achieved at a concentration of 0.8 ng/ml. The peptide is probably one of the family of EGF-like heparin-binding growth factors.

  14. 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

  15. 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

  16. 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...

  17. 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.

  18. 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

  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. Netrin-1 is a critical autocrine/paracrine factor for osteoclast differentiation.

    Science.gov (United States)

    Mediero, Aránzazu; Ramkhelawon, Bhama; Perez-Aso, Miguel; Moore, Kathryn J; Cronstein, Bruce N

    2015-05-01

    Bone metabolism is a vital process that involves resorption by osteoclasts and formation by osteoblasts, which is closely regulated by immune cells. The neuronal guidance protein Netrin-1 regulates immune cell migration and inflammatory reactions, but its role in bone metabolism is unknown. During osteoclast differentiation, osteoclast precursors increase expression of Netrin-1 and its receptor Unc5b. Netrin-1 binds, in an autocrine and paracrine manner, to Unc5b to promote osteoclast differentiation in vitro, and absence of Netrin-1 or antibody-mediated blockade of Netrin-1 or Unc5b prevents osteoclast differentiation of both murine and human precursors. We confirmed the functional relationship of Netrin-1 in osteoclast differentiation in vivo using Netrin-1-deficient (Ntn1(-/-) ) or wild-type (WT) bone marrow transplanted mice. Notably, Ntn1(-/-) chimeras have markedly diminished osteoclasts, as well as increased cortical and trabecular bone density and volume compared with WT mice. Mechanistic studies revealed that Netrin-1 regulates osteoclast differentiation by altering cytoskeletal assembly. Netrin-1 increases regulator of Rho-GEF subfamily (LARG) and repulsive guidance molecule (RGMa) association with Unc5b, which increases expression and activation of cytoskeletal regulators RhoA and focal adhesion kinase (FAK). Netrin-1 and its receptor Unc5b likely play a role in fusion of osteoclast precursors because Netrin-1 and DC-STAMP are tightly linked. These results identify Netrin-1 as a key regulator of osteoclast differentiation that may be a new target for bone therapies.

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

    Energy Technology Data Exchange (ETDEWEB)

    Miyamoto, Kana [Department of Orthopedic Surgery, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Division of Orthopedic Research, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Department of Cell Differentiation, The Sakaguchi Laboratory of Developmental Biology, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Ninomiya, Ken [Department of Orthopedic Surgery, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Department of Cell Differentiation, The Sakaguchi Laboratory of Developmental Biology, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Sonoda, Koh-Hei [Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, 3-1-1, Maidashi, Higashi-ku, Fukuoka, Fukuoka 812-8582 (Japan); Miyauchi, Yoshiteru; Hoshi, Hiroko [Department of Orthopedic Surgery, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Division of Orthopedic Research, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Iwasaki, Ryotaro [Division of Orthopedic Research, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Department of Cell Differentiation, The Sakaguchi Laboratory of Developmental Biology, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Department of Dentistry and Oral Surgery, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Miyamoto, Hiroya [Department of Orthopedic Surgery, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); Division of Orthopedic Research, Keio University School of Medicine, 35 Shinano-machi, Shinjuku-ku, Tokyo 160-8582 (Japan); and others

    2009-06-05

    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.

  2. Autocrine and paracrine roles for ATP and serotonin in mouse taste buds.

    Science.gov (United States)

    Huang, Yijen A; Dando, Robin; Roper, Stephen D

    2009-11-01

    Receptor (type II) taste bud cells secrete ATP during taste stimulation. In turn, ATP activates adjacent presynaptic (type III) cells to release serotonin (5-hydroxytryptamine, or 5-HT) and norepinephrine (NE). The roles of these neurotransmitters in taste buds have not been fully elucidated. Here we tested whether ATP or 5-HT exert feedback onto receptor (type II) cells during taste stimulation. Our previous studies showed NE does not appear to act on adjacent taste bud cells, or at least on receptor cells. Our data show that 5-HT released from presynaptic (type III) cells provides negative paracrine feedback onto receptor cells by activating 5-HT(1A) receptors, inhibiting taste-evoked Ca(2+) mobilization in receptor cells, and reducing ATP secretion. The findings also demonstrate that ATP exerts positive autocrine feedback onto receptor (type II) cells by activating P2Y1 receptors and enhancing ATP secretion. These results begin to sort out how purinergic and aminergic transmitters function within the taste bud to modulate gustatory signaling in these peripheral sensory organs.

  3. Interleukin-19 acts as a negative autocrine regulator of activated microglia.

    Directory of Open Access Journals (Sweden)

    Hiroshi Horiuchi

    Full Text Available Activated microglia can exert either neurotoxic or neuroprotective effects, and they play pivotal roles in the pathogenesis and progression of various neurological diseases. In this study, we used cDNA microarrays to show that interleukin-19 (IL-19, an IL-10 family cytokine, is markedly upregulated in activated microglia. Furthermore, we found that microglia are the only cells in the nervous system that express the IL-19 receptor, a heterodimer of the IL-20Rα and IL-20Rβ subunits. IL-19 deficiency increased the production of such pro-inflammatory cytokines as IL-6 and tumor necrosis factor-α in activated microglia, and IL-19 treatment suppressed this effect. Moreover, in a mouse model of Alzheimer's disease, we observed upregulation of IL-19 in affected areas in association with disease progression. Our findings demonstrate that IL-19 is an anti-inflammatory cytokine, produced by activated microglia, that acts negatively on microglia in an autocrine manner. Thus, microglia may self-limit their inflammatory response by producing the negative regulator IL-19.

  4. Cyclic mechanical deformation stimulates human lung fibroblast proliferation and autocrine growth factor activity.

    Science.gov (United States)

    Bishop, J E; Mitchell, J J; Absher, P M; Baldor, L; Geller, H A; Woodcock-Mitchell, J; Hamblin, M J; Vacek, P; Low, R B

    1993-08-01

    Cellular hypertrophy and hyperplasia and increased extracellular matrix deposition are features of tissue hypertrophy resulting from increased work load. It is known, for example, that mechanical forces play a critical role in lung development, cardiovascular remodeling following pressure overload, and skeletal muscle growth. The mechanisms involved in these processes, however, remain unclear. Here we examined the effect of mechanical deformation on fibroblast function in vitro. IMR-90 human fetal lung fibroblasts grown on collagen-coated silastic membranes were subjected to cyclical mechanical deformation (10% increase in culture surface area; 1 Hz) for up to 5 days. Cell number was increased by 39% after 2 days of deformation (1.43 +/- .01 x 10(5) cells/membrane compared with control, 1.03 +/- 0.02 x 10(5) cells; mean +/- SEM; P < 0.02) increasing to 163% above control by 4 days (2.16 +/- 0.16 x 10(5) cells compared with 0.82 +/- 0.03 x 10(5) cells; P < 0.001). The medium from mechanically deformed cells was mitogenic for IMR-90 cells, with maximal activity in the medium from cells mechanically deformed for 2 days (stimulating cell replication by 35% compared with media control; P < 0.002). These data suggest that mechanical deformation stimulates human lung fibroblast replication and that this effect is mediated by the release of autocrine growth factors.

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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

  10. 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

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

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    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

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

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    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

  13. Autocrine expression of hepatocyte growth factor and its cytoprotective effect on hepatocyte poisoning

    Institute of Scientific and Technical Information of China (English)

    Yong He; Jun Zhou; Ke-Feng Dou; Yong Chen; Qing-Guo Yan; Hai-Min Li

    2004-01-01

    AIM: To construct pEGFP-hepatocyte growth factor (HGF)expression vector,the to detect its expression in transfected human hepatocytes, and to investigate the influence of autocrine HGF expression on the proliferative potential and cytoprotective effects in human hepatocytes.METHODS: Human HGF cDNA was ligated to the pEGFP vector.Recombinant plasmid was transfected into human hepatocyte line QZG with liposome. Expression of HGF protein was observed by fluorescence microscopy and immunohistochemistry. Hepatic cells were collected 24, 48, and 72 h after transfection to detect the number of [3H]-TdR uptake in DNA. DNA synthesis was observed by using PCNA stain immunohistochemistry.Acute liver cell damage was induced by carbon tetrachloride. Cytoprotective effect was observed by examining the survival rate of hepatocytes and leakage of intracellular alanine transaminase (ALT) and potassium ions.RESULTS: HGF identification of pEGFP-HGF by enzyme digestion showed that HGF fragment was cloned into BamH I and Sa/I sites of pEGFP-N3. Expression of GFP in transfected hepatocytes was observed with fluorescence microscopy.The [3H]-TdR uptake became 7 times as many as in the control group 96 h after transfection. After HGF transfection,the survival rate of hepatocytes poisoned by CCl4 significantly increased (83% vs 61%, P<0.05), and the leakage of intracellular alanine transaminase and potassium ions decreased(586 nkat/L vs1089 nkat/L, P<0.01; and 5.59 mmol/L vs6.02 mmol/L, P<0.01 respectively). Culture of transfected hepatic cells promoted the proliferation of other nontransfected cells.CONCLUSION: Transfected HGF is expressed in hepatic cells and has the activity of promoting cell division and protecting hepatic cells against poisoning.

  14. Regulation of the expression of proto-oncogenes by autocrine embryotropins in the early mouse embryo.

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    Jin, Xing Liang; O'Neill, C

    2011-06-01

    Autocrine embryotropins act as survival signals for the preimplantation embryo. In this study we examined the role of Paf in the transcription of the key proto-oncogenes Bcl2 and Fos. Transcripts were detected in oocytes and some cohorts of zygotes but not in cohorts of 2-cell, 8-cell, and blastocyst stage embryos. Immunolocalization of BCL2 and FOS showed little staining in oocytes and zygotes but increased staining in the embryo from the 2-cell to blastocyst stage. Paf (37 nM) treatment of 2-cell embryos caused an alpha-amanitin (26 μM)-sensitive increase in Bcl2 and Fos transcripts 20 min after treatment that subsided by 40 min. This increase was blocked by inhibition of calcium (by BAPTA-AM) or phosphatidylinositol-3-kinase signaling (by LY294002). Paf challenge also caused increased staining of BCL2 and FOS. Increased staining of FOS required new protein synthesis that had a half-life of 2-4 h after Paf challenge. Only a small proportion (∼12%) of individual 2-cell embryos collected from the reproductive tract had detectable Bcl2 and Fos. This dichotomous pattern of transcript expression is consistent with the known periodic actions of Paf (which has a periodicity of ∼90 min) and the relatively short half-life of the resulting transcripts. A BCL2 antagonist (HA14-1) caused a dose-dependent decrease in the capacity of cultured zygotes to develop to morphological blastocysts, which was partially reversed by the simultaneous addition of Paf to medium. The results show that Paf induces periodic transient transcriptions of key proto-oncogenes that result in the persistent presence of the resulting proteins in the preimplantation phase of development.

  15. Chronic effects of palmitate overload on nutrient-induced insulin secretion and autocrine signalling in pancreatic MIN6 beta cells.

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    Maria L Watson

    Full Text Available BACKGROUND: Sustained exposure of pancreatic β cells to an increase in saturated fatty acids induces pleiotropic effects on β-cell function, including a reduction in stimulus-induced insulin secretion. The objective of this study was to investigate the effects of chronic over supply of palmitate upon glucose- and amino acid-stimulated insulin secretion (GSIS and AASIS, respectively and autocrine-dependent insulin signalling with particular focus on the importance of ceramide, ERK and CaMKII signalling. PRINCIPAL FINDINGS: GSIS and AASIS were both stimulated by >7-fold resulting in autocrine-dependent activation of protein kinase B (PKB, also known as Akt. Insulin release was dependent upon nutrient-induced activation of calcium/calmodulin-dependent protein kinase II (CaMKII and extracellular signal-regulated kinase (ERK as their pharmacological inhibition suppressed GSIS/AASIS significantly. Chronic (48 h, 0.4 mM palmitate treatment blunted glucose/AA-induced activation of CaMKII and ERK and caused a concomitant reduction (~75% in GSIS/AASIS and autocrine-dependent activation of PKB. This inhibition could not be attributed to enhanced mitochondrial fatty acid uptake/oxidation or ceramide synthesis, which were unaffected by palmitate. In contrast, diacylglycerol synthesis was elevated suggesting increased palmitate esterification rather than oxidation may contribute to impaired stimulus-secretion coupling. Consistent with this, 2-bromopalmitate, a non-oxidisable palmitate analogue, inhibited GSIS as effectively as palmitate. CONCLUSIONS: Our results exclude changes in ceramide content or mitochondrial fatty acid handling as factors initiating palmitate-induced defects in insulin release from MIN6 β cells, but suggest that reduced CaMKII and ERK activation associated with palmitate overload may contribute to impaired stimulus-induced insulin secretion.

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

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    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.

  17. 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

  18. Vascular endothelial growth factor regulates osteoblast survival – evidence for an autocrine feedback mechanism

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    Street John

    2009-06-01

    Full Text Available Abstract Background Apoptosis of osteoblasts and osteoclasts regulates bone homeostasis. Skeletal injury in humans results in 'angiogenic' responses primarily mediated by vascular endothelial growth factor(VEGF, a protein essential for bone repair in animal models. Osteoblasts release VEGF in response to a number of stimuli and express receptors for VEGF in a differentiation dependent manner. This study investigates the putative role of VEGF in regulating the lifespan of primary human osteoblasts(PHOB in vitro. Methods PHOB were examined for VEGF receptors. Cultures were supplemented with VEGF(0–50 ng/mL, a neutralising antibody to VEGF, mAB VEGF(0.3 ug/mL and Placental Growth Factor (PlGF, an Flt-1 receptor-specific VEGF ligand(0–100 ng/mL to examine their effects on mineralised nodule assay, alkaline phosphatase assay and apoptosis.. The role of the VEGF specific antiapoptotic gene target BCl2 in apoptosis was determined. Results PHOB expressed functional VEGF receptors. VEGF 10 and 25 ng/mL increased nodule formation 2.3- and 3.16-fold and alkaline phosphatase release 2.6 and 4.1-fold respectively while 0.3 ug/mL of mAB VEGF resulted in approx 40% reductions in both. PlGF 50 ng/mL had greater effects on alkaline phosphatase release (103% increase than on nodule formation (57% increase. 10 ng/mL of VEGF inhibited spontaneous and pathological apoptosis by 83.6% and 71% respectively, while PlGF had no significant effect. Pretreatment with mAB VEGF, in the absence of exogenous VEGF resulted in a significant increase in apoptosis (14 vs 3%. VEGF 10 ng/mL increased BCl2 expression 4 fold while mAB VEGF decreased it by over 50%. Conclusion VEGF is a potent regulator of osteoblast life-span in vitro. This autocrine feedback regulates survival of these cells, mediated via a non flt-1 receptor mechanism and expression of BCl2 antiapoptotic gene.

  19. 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

  20. IL-8, a novel messenger to cross-link inflammation and tumor EMT via autocrine and paracrine pathways (Review).

    Science.gov (United States)

    Long, Xinxin; Ye, Yingnan; Zhang, Lijie; Liu, Pengpeng; Yu, Wenwen; Wei, Feng; Ren, Xiubao; Yu, Jinpu

    2016-01-01

    The epithelial-mesenchymal transition (EMT) is a process through which epithelial cells trans-differentiate and acquire an aggressive mesenchymal phenotype. In tumor cells, EMT is a vital step of tumor progression and metastasis. Amid the increasing interest in tumor EMT, only a few studies focused on the soluble mediators secreted by tumor cells passing through this phenotypic switch. In this review, we focus on the essential role of interleukin-8 (IL-8) signaling for the acquisition and maintenance of tumor EMT via direct and indirect mechanisms. Besides the autocrine loop between IL-8 and tumor cells that have gone through EMT, IL-8 could potentiate adjacent epithelial tumor cells into a mesenchymal phenotype via a paracrine mode. Moreover, understanding the role of IL-8 in EMT will provide insight into the pathogenesis of tumor progression and may facilitate the development of an effective strategy for the prevention and treatment of metastatic cancer.

  1. Autocrine Signaling Underlies Fast Repetitive Plasma Membrane Translocation of Conventional and Novel Protein Kinase C Isoforms in β Cells.

    Science.gov (United States)

    Wuttke, Anne; Yu, Qian; Tengholm, Anders

    2016-07-15

    PKC signaling has been implicated in the regulation of many cell functions, including metabolism, cell death, proliferation, and secretion. Activation of conventional and novel PKC isoforms is associated with their Ca(2+)- and/or diacylglycerol (DAG)-dependent translocation to the plasma membrane. In β cells, exocytosis of insulin granules evokes brief (<10 s) local DAG elevations ("spiking") at the plasma membrane because of autocrine activation of P2Y1 purinoceptors by ATP co-released with insulin. Using total internal reflection microscopy, fluorescent protein-tagged PKCs, and signaling biosensors, we investigated whether DAG spiking causes membrane recruitment of PKCs and whether different classes of PKCs show characteristic responses. Glucose stimulation of MIN6 cells triggered DAG spiking with concomitant repetitive translocation of the novel isoforms PKCδ, PKCϵ, and PKCη. The conventional PKCα, PKCβI, and PKCβII isoforms showed a more complex pattern with both rapid and slow translocation. K(+) depolarization-induced PKCϵ translocation entirely mirrored DAG spiking, whereas PKCβI translocation showed a sustained component, reflecting the subplasma membrane Ca(2+) concentration ([Ca(2+)]pm), with additional effect during DAG spikes. Interference with DAG spiking by purinoceptor inhibition prevented intermittent translocation of PKCs and reduced insulin secretion but did not affect [Ca(2+)]pm elevation or sustained PKCβI translocation. The muscarinic agonist carbachol induced pronounced transient PKCβI translocation and sustained recruitment of PKCϵ. When rise of [Ca(2+)]pm was prevented, the carbachol-induced DAG and PKCϵ responses were somewhat reduced, but PKCβI translocation was completely abolished. We conclude that exocytosis-induced DAG spikes efficiently recruit both conventional and novel PKCs to the β cell plasma membrane. PKC signaling is thus implicated in autocrine regulation of β cell function.

  2. Autocrine Signaling Underlies Fast Repetitive Plasma Membrane Translocation of Conventional and Novel Protein Kinase C Isoforms in β Cells*

    Science.gov (United States)

    Wuttke, Anne; Yu, Qian; Tengholm, Anders

    2016-01-01

    PKC signaling has been implicated in the regulation of many cell functions, including metabolism, cell death, proliferation, and secretion. Activation of conventional and novel PKC isoforms is associated with their Ca2+- and/or diacylglycerol (DAG)-dependent translocation to the plasma membrane. In β cells, exocytosis of insulin granules evokes brief (<10 s) local DAG elevations (“spiking”) at the plasma membrane because of autocrine activation of P2Y1 purinoceptors by ATP co-released with insulin. Using total internal reflection microscopy, fluorescent protein-tagged PKCs, and signaling biosensors, we investigated whether DAG spiking causes membrane recruitment of PKCs and whether different classes of PKCs show characteristic responses. Glucose stimulation of MIN6 cells triggered DAG spiking with concomitant repetitive translocation of the novel isoforms PKCδ, PKCϵ, and PKCη. The conventional PKCα, PKCβI, and PKCβII isoforms showed a more complex pattern with both rapid and slow translocation. K+ depolarization-induced PKCϵ translocation entirely mirrored DAG spiking, whereas PKCβI translocation showed a sustained component, reflecting the subplasma membrane Ca2+ concentration ([Ca2+]pm), with additional effect during DAG spikes. Interference with DAG spiking by purinoceptor inhibition prevented intermittent translocation of PKCs and reduced insulin secretion but did not affect [Ca2+]pm elevation or sustained PKCβI translocation. The muscarinic agonist carbachol induced pronounced transient PKCβI translocation and sustained recruitment of PKCϵ. When rise of [Ca2+]pm was prevented, the carbachol-induced DAG and PKCϵ responses were somewhat reduced, but PKCβI translocation was completely abolished. We conclude that exocytosis-induced DAG spikes efficiently recruit both conventional and novel PKCs to the β cell plasma membrane. PKC signaling is thus implicated in autocrine regulation of β cell function. PMID:27226533

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

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    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.

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

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    Zänker Kurt S

    2011-05-01

    Full Text Available Abstract Background 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. Methods 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. Results 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. Conclusions 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.

  5. 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

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

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    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

  7. 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

  8. 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

  9. 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

  10. Autocrine IL-10 activation of the STAT3 pathway is required for pathological macrophage differentiation in polycystic kidney disease

    Science.gov (United States)

    Peda, Jacqueline D.; Salah, Sally M.; Wallace, Darren P.; Fields, Patrick E.; Grantham, Connor J.; Fields, Timothy A.

    2016-01-01

    ABSTRACT Polycystic kidney disease (PKD) is characterized by slow expansion of fluid-filled cysts derived from tubules within the kidney. Cystic expansion results in injury to surrounding parenchyma and leads to inflammation, scarring and ultimately loss of renal function. Macrophages are a key element in this process, promoting cyst epithelial cell proliferation, cyst expansion and disease progression. Previously, we have shown that the microenvironment established by cystic epithelial cells can ‘program’ macrophages, inducing M2-like macrophage polarization that is characterized by expression of markers that include Arg1 and Il10. Here, we functionally characterize these macrophages, demonstrating that their differentiation enhances their ability to promote cyst cell proliferation. This observation indicates a model of reciprocal pathological interactions between cysts and the innate immune system: cyst epithelial cells promote macrophage polarization to a phenotype that, in turn, is especially efficient in promoting cyst cell proliferation and cyst growth. To better understand the genesis of this macrophage phenotype, we examined the role of IL-10, a regulatory cytokine shown to be important for macrophage-stimulated tissue repair in other settings. Herein, we show that the acquisition of the pathological macrophage phenotype requires IL-10 secretion by the macrophages. Further, we demonstrate a requirement for IL-10-dependent autocrine activation of the STAT3 pathway. These data suggest that the IL-10 pathway in macrophages plays an essential role in the pathological relationship between cysts and the innate immune system in PKD, and thus could be a potential therapeutic target. PMID:27491076

  11. 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.

  12. 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.

  13. Stable Ectopic Expression of ST6GALNAC5 Induces Autocrine MET Activation and Anchorage-Independence in MDCK Cells.

    Directory of Open Access Journals (Sweden)

    Chia Chu

    Full Text Available The epithelial-mesenchymal transition (EMT is a complex cancer progression that can boost the metastatic potential of transformed cells by inducing migration, loss of cell adhesion, and promoting proliferation under anchorage-independent conditions. A DNA microarray analysis was performed comparing parental anchorage-dependent MDCK cells and anchorage-independent MDCK cells that were engineered to express human siat7e (ST6GALNAC5. The comparison identified several genes involved in the EMT process that were differentially expressed between the anchorage-dependent and the anchorage-independent MDCK cell lines. The hepatocyte growth factor gene (hgf was found to be over-expressed in the engineered MDCK-siat7e cells at both transcription and protein expression levels. Phosphorylation analysis of the MET receptor tyrosine kinase confirmed the activation of an autocrine loop of the HGF/ MET signaling pathway in the MDCK-siat7e cells. When MET activities were suppressed by using the small-molecular inhibitor drug PF-02341066 (Crizotinib, the anchorage-independent MDCK-siat7e cells reverted to the cellular morphology of the parental anchorage-dependent MDCK cells. These observations indicate that the MET receptor plays a central role in the growth properties of the MDCK cells and its phosphorylation status is likely dependent on sialylation. Further investigation of the downstream signaling targets in the MET network showed that the degree of MDCK cell adhesion correlated with secretion levels of a matrix metalloproteinase, MMP1, suggesting a role of metalloproteinases in the EMT process. These results demonstrate that in addition to its application in biotechnology processes, MDCK-siat7e may serve as a model cell for metastasis studies to decipher the sequence of events leading up to the activation of EMT.

  14. Stable Ectopic Expression of ST6GALNAC5 Induces Autocrine MET Activation and Anchorage-Independence in MDCK Cells.

    Science.gov (United States)

    Chu, Chia; Bottaro, Donald P; Betenbaugh, Michael J; Shiloach, Joseph

    2016-01-01

    The epithelial-mesenchymal transition (EMT) is a complex cancer progression that can boost the metastatic potential of transformed cells by inducing migration, loss of cell adhesion, and promoting proliferation under anchorage-independent conditions. A DNA microarray analysis was performed comparing parental anchorage-dependent MDCK cells and anchorage-independent MDCK cells that were engineered to express human siat7e (ST6GALNAC5). The comparison identified several genes involved in the EMT process that were differentially expressed between the anchorage-dependent and the anchorage-independent MDCK cell lines. The hepatocyte growth factor gene (hgf) was found to be over-expressed in the engineered MDCK-siat7e cells at both transcription and protein expression levels. Phosphorylation analysis of the MET receptor tyrosine kinase confirmed the activation of an autocrine loop of the HGF/ MET signaling pathway in the MDCK-siat7e cells. When MET activities were suppressed by using the small-molecular inhibitor drug PF-02341066 (Crizotinib), the anchorage-independent MDCK-siat7e cells reverted to the cellular morphology of the parental anchorage-dependent MDCK cells. These observations indicate that the MET receptor plays a central role in the growth properties of the MDCK cells and its phosphorylation status is likely dependent on sialylation. Further investigation of the downstream signaling targets in the MET network showed that the degree of MDCK cell adhesion correlated with secretion levels of a matrix metalloproteinase, MMP1, suggesting a role of metalloproteinases in the EMT process. These results demonstrate that in addition to its application in biotechnology processes, MDCK-siat7e may serve as a model cell for metastasis studies to decipher the sequence of events leading up to the activation of EMT. PMID:26848584

  15. Hypertonic stress induces VEGF production in human colon cancer cell line Caco-2: inhibitory role of autocrine PGE₂.

    Directory of Open Access Journals (Sweden)

    Luciana B Gentile

    Full Text Available Vascular Endothelial Growth Factor (VEGF is a major regulator of angiogenesis. VEGF expression is up regulated in response to micro-environmental cues related to poor blood supply such as hypoxia. However, regulation of VEGF expression in cancer cells is not limited to the stress response due to increased volume of the tumor mass. Lipid mediators in particular arachidonic acid-derived prostaglandin (PGE₂ are regulators of VEGF expression and angiogenesis in colon cancer. In addition, increased osmolarity that is generated during colonic water absorption and feces consolidation seems to activate colon cancer cells and promote PGE₂ generation. Such physiological stimulation may provide signaling for cancer promotion. Here we investigated the effect of exposure to a hypertonic medium, to emulate colonic environment, on VEGF production by colon cancer cells. The role of concomitant PGE₂ generation and MAPK activation was addressed by specific pharmacological inhibition. Human colon cancer cell line Caco-2 exposed to a hypertonic environment responded with marked VEGF and PGE₂ production. VEGF production was inhibited by selective inhibitors of ERK 1/2 and p38 MAPK pathways. To address the regulatory role of PGE₂ on VEGF production, Caco-2 cells were treated with cPLA₂ (ATK and COX-2 (NS-398 inhibitors, that completely block PGE₂ generation. The Caco-2 cells were also treated with a non selective PGE₂ receptor antagonist. Each treatment significantly increased the hypertonic stress-induced VEGF production. Moreover, addition of PGE₂ or selective EP₂ receptor agonist to activated Caco-2 cells inhibited VEGF production. The autocrine inhibitory role for PGE₂ appears to be selective to hypertonic environment since VEGF production induced by exposure to CoCl₂ was decreased by inhibition of concomitant PGE₂ generation. Our results indicated that hypertonicity stimulates VEGF production in colon cancer cell lines. Also PGE

  16. 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

  17. 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.

  18. 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.

  19. The Ras/Raf/MEK/Extracellular Signal-Regulated Kinase Pathway Induces Autocrine-Paracrine Growth Inhibition via the Leukemia Inhibitory Factor/JAK/STAT Pathway

    OpenAIRE

    Park, Jong-In; Strock, Christopher J.; Ball, Douglas W.; Nelkin, Barry D.

    2003-01-01

    Sustained activation of the Ras/Raf/MEK/extracellular signal-regulated kinase (ERK) pathway can lead to cell cycle arrest in many cell types. We have found, with human medullary thyroid cancer (MTC) cells, that activated Ras or c-Raf-1 can induce growth arrest by producing and secreting an autocrine-paracrine factor. This protein was purified from cell culture medium conditioned by Raf-activated MTC cells and was identified by mass spectrometry as leukemia inhibitory factor (LIF). LIF express...

  20. Raft-dependent endocytosis of autocrine motility factor/phosphoglucose isomerase: a potential drug delivery route for tumor cells.

    Directory of Open Access Journals (Sweden)

    Liliana D Kojic

    Full Text Available BACKGROUND: Autocrine motility factor/phosphoglucose isomerase (AMF/PGI is the extracellular ligand for the gp78/AMFR receptor overexpressed in a variety of human cancers. We showed previously that raft-dependent internalization of AMF/PGI is elevated in metastatic MDA-435 cells, but not metastatic, caveolin-1-expressing MDA-231 cells, relative to non-metastatic MCF7 and dysplastic MCF10A cells suggesting that it might represent a tumor cell-specific endocytic pathway. METHODOLOGY/PRINCIPAL FINDINGS: Similarly, using flow cytometry, we demonstrate that raft-dependent endocytosis of AMF/PGI is increased in metastatic HT29 cancer cells expressing low levels of caveolin-1 relative to metastatic, caveolin-1-expressing, HCT116 colon cells and non-metastatic Caco-2 cells. Therefore, we exploited the raft-dependent internalization of AMF/PGI as a potential tumor-cell specific targeting mechanism. We synthesized an AMF/PGI-paclitaxel conjugate and found it to be as efficient as free paclitaxel in inducing cytotoxicity and apoptosis in tumor cells that readily internalize AMF/PGI compared to tumor cells that poorly internalize AMF/PGI. Murine K1735-M1 and B16-F1 melanoma cells internalize FITC-conjugated AMF/PGI and are acutely sensitive to AMF/PGI-paclitaxel mediated cytotoxicity in vitro. Moreover, following in vivo intratumoral injection, FITC-conjugated AMF/PGI is internalized in K1735-M1 tumors. Intratumoral injection of AMF/PGI-paclitaxel induced significantly higher tumor regression compared to free paclitaxel, even in B16-F1 cells, known to be resistant to taxol treatment. Treatment with AMF/PGI-paclitaxel significantly prolonged the median survival time of tumor bearing mice. Free AMF/PGI exhibited a pro-survival role, reducing the cytotoxic effect of both AMF/PGI-paclitaxel and free paclitaxel suggesting that AMF/PGI-paclitaxel targets a pathway associated with resistance to chemotherapeutic agents. AMF/PGI-FITC uptake by normal murine spleen

  1. [A TIM-3/galectin-9 autocrine stimulatory loop drives self-renewal of human myeloid leukemia stem cells and leukemia progression].

    Science.gov (United States)

    Kikushige, Yoshikane

    2016-04-01

    Acute myeloid leukemia (AML) originates from self-renewing leukemic stem cells (LSCs), an ultimate therapeutic target for AML. We previously reported that the T-cell immunoglobulin mucin-3 (TIM-3) is expressed on the LCS surface in most types of AML. Since only the TIM-3(+), i.e. not the TIM-3(-), fraction of human AML cells can reconstitute human AML in immunodeficient mice, we hypothesized that the TIM-3 has an essential function in maintaining AML LSCs. Herein, we show that TIM-3 and its ligand, galectin-9 (Gal-9), constitute an autocrine loop critical for human AML LSC development. Serum Gal-9 was significantly elevated in primary AML patients and in mice xenografted with human AML. Neutralization of Gal-9 inhibited xenogeneic reconstitution of human AML, as well as Gal-9 ligation of TIM-3 co-activated NF-κB and β-catenin signaling, suggesting that TIM-3 signaling is necessary for LSC self-renewal. Interestingly, identical changes were found to be involved in the progressive transformation of a variety of pre-leukemic disorders into myeloid leukemia. Thus, molecules constituting the TIM-3/Gal-9 autocrine loop are potential therapeutic targets applicable to most types of myeloid leukemia. PMID:27169443

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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.

  7. IL-35 promotes pancreas cancer growth through enhancement of proliferation and inhibition of apoptosis: evidence for a role as an autocrine growth factor.

    Science.gov (United States)

    Nicholl, Michael B; Ledgewood, Chelsea L; Chen, Xuhui; Bai, Qian; Qin, Chenglu; Cook, Kathryn M; Herrick, Elizabeth J; Diaz-Arias, Alberto; Moore, Bradley J; Fang, Yujiang

    2014-12-01

    Interleukin-35 (IL-35), an IL-12 cytokine family member, mediates the immune inhibitory function of regulatory T cells (Treg). We assayed the presence of IL-35 in paraffin-embedded human pancreas cancer (PCAN) and unexpectedly found IL-35 was expressed mainly by epithelial derived PCAN cells, but not by Treg. We further examined the expression and effect of exogenous IL-35 in human PCAN cell lines and found IL-35 promoted growth and inhibited apoptosis in PCAN cell lines. IL-35 induced proliferation correlated with an increase in cyclin B, cyclin D, cdk2, and cdk4 and a decrease in p27 expression, while inhibition of apoptosis was associated with an increase in Bcl-2 and a decrease in TRAILR1. We conclude IL-35 is produced by PCAN in vivo and promotes PCAN cell line growth in vitro. These results might indicate an important new role for IL-35 as an autocrine growth factor in PCAN growth.

  8. 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.

  9. 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

  10. The Ras/Raf/MEK/extracellular signal-regulated kinase pathway induces autocrine-paracrine growth inhibition via the leukemia inhibitory factor/JAK/STAT pathway.

    Science.gov (United States)

    Park, Jong-In; Strock, Christopher J; Ball, Douglas W; Nelkin, Barry D

    2003-01-01

    Sustained activation of the Ras/Raf/MEK/extracellular signal-regulated kinase (ERK) pathway can lead to cell cycle arrest in many cell types. We have found, with human medullary thyroid cancer (MTC) cells, that activated Ras or c-Raf-1 can induce growth arrest by producing and secreting an autocrine-paracrine factor. This protein was purified from cell culture medium conditioned by Raf-activated MTC cells and was identified by mass spectrometry as leukemia inhibitory factor (LIF). LIF expression upon Raf activation and subsequent activation of JAK-STAT3 was also observed in small cell lung carcinoma cells, suggesting that this autocrine-paracrine signaling may be a common response to Ras/Raf activation. LIF was sufficient to induce growth arrest and differentiation of MTC cells. This effect was mediated through the gp130/JAK/STAT3 pathway, since anti-gp130 blocking antibody or dominant-negative STAT3 blocked the effects of LIF. Thus, LIF expression provides a novel mechanism allowing Ras/Raf signaling to activate the JAK-STAT3 pathway. In addition to this cell-extrinsic growth inhibitory pathway, we find that the Ras/Raf/MEK/ERK pathway induces an intracellular growth inhibitory signal, independent of the LIF/JAK/STAT3 pathway. Therefore, activation of the Ras/Raf/MEK/ERK pathway can lead to growth arrest and differentiation via at least two different signaling pathways. This use of multiple pathways may be important for "fail-safe" induction and maintenance of cell cycle arrest.

  11. 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.

  12. 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

  13. Nodal promotes the self-renewal of human colon cancer stem cells via an autocrine manner through Smad2/3 signaling pathway.

    Science.gov (United States)

    Gong, Yuehua; Guo, Ying; Hai, Yanan; Yang, Hao; Liu, Yang; Yang, Shi; Zhang, Zhenzhen; Ma, Meng; Liu, Linhong; Li, Zheng; He, Zuping

    2014-01-01

    Colorectal cancer is one of the most common and fatal tumors. However, molecular mechanisms underlying carcinogenesis of colorectal cancer remain largely undefined. Here, we explored the expression and function of Nodal in colon cancer stem cells (CCSCs). Nodal and its receptors were present in numerous human colorectal cancer cell lines. NODAL and ALK-4 were coexpressed in human colon cancerous tissues, and NODAL, CD24, and CD44, markers for CCSCs, were expressed at higher levels in human colon cancerous tissues than adjacent noncancerous colon tissues. Human CCSCs were isolated by magnetic activated cell sorting using anti-CD24 and anti-CD44. Nodal transcript and protein were hardly detectable in CD44- or CD24-negative human colorectal cancer cell lines, whereas Nodal and its receptors were present in CCSCs. Notably, Nodal facilitated spheroid formation of human CCSCs, and phosphorylation of Smad2 and Smad3 was activated by Nodal in cells of spheres derived from human CCSCs. Collectively, these results suggest that Nodal promotes the self-renewal of human CCSCs and mediate carcinogenesis of human colorectal cancer via an autocrine manner through Smad2/3 pathway. This study provides a novel insight into molecular mechanisms controlling fate of human CCSCs and offers new targets for gene therapy of human colorectal cancer.

  14. Pro-nerve growth factor induces autocrine stimulation of breast cancer cell invasion through tropomyosin-related kinase A (TrkA) and sortilin protein.

    Science.gov (United States)

    Demont, Yohann; Corbet, Cyril; Page, Adeline; Ataman-Önal, Yasemin; Choquet-Kastylevsky, Genevieve; Fliniaux, Ingrid; Le Bourhis, Xuefen; Toillon, Robert-Alain; Bradshaw, Ralph A; Hondermarck, Hubert

    2012-01-13

    The precursor of nerve growth factor (proNGF) has been described as a biologically active polypeptide able to induce apoptosis in neuronal cells, via the neurotrophin receptor p75(NTR) and the sortilin receptor. Herein, it is shown that proNGF is produced and secreted by breast cancer cells, stimulating their invasion. Using Western blotting and mass spectrometry, proNGF was detected in a panel of breast cancer cells as well as in their conditioned media. Immunohistochemical analysis indicated an overproduction of proNGF in breast tumors, when compared with benign and normal breast biopsies, and a relationship to lymph node invasion in ductal carcinomas. Interestingly, siRNA against proNGF induced a decrease of breast cancer cell invasion that was restored by the addition of non-cleavable proNGF. The activation of TrkA, Akt, and Src, but not the MAP kinases, was observed. In addition, the proNGF invasive effect was inhibited by the Trk pharmacological inhibitor K252a, a kinase-dead TrkA, and siRNA against TrkA sortilin, neurotensin, whereas siRNA against p75(NTR) and the MAP kinase inhibitor PD98059 had no impact. These data reveal the existence of an autocrine loop stimulated by proNGF and mediated by TrkA and sortilin, with the activation of Akt and Src, for the stimulation of breast cancer cell invasion.

  15. Differential expression of autocrine motility factor receptor (AMFR) mRNA in normal and cancer cells detected by in situ hybridization

    Institute of Scientific and Technical Information of China (English)

    HUANGBAIQU; AVRAHAMRAZ

    1995-01-01

    The receptor for autocrine motility factor(AMFR) is known to be involved in the process of MF-mediated cell migration and metastasis.This paper describes the procedures of non-radioactive in situ hybridization(ISH) detection of AMFR mRNA in both paraffin-embedded surgical sections and cultured cells using either biotinylated oligonucleotide probes of digoxigenin-labeled RNA probes.The results showed that the AMFR mRNA was expressed at an enhanced level in hyperplastic and malignant tissues of breast and prostate cancer patient surgical specimens,indicating that the elevated AMFR expression was associated with the tissue malignancy.Moreover,AMFR mRNA was detected in both normal and carcinoma cells when cultured at a subconfluent density.However,AMFR expression was inhibited in confluent normal(3T3-A31 murine fibroblast and FHs 738 BL huamn bladder)cells while it continued to express in carcinoma(J82 human bladder) and metastatic(3T3-M murine fibroblast) cells irrespective of cell density.This suggested a cell-cell contact down-regulation of AMFR mRNA expression in normal but not in cancer cells.The ISH data obtained in this study are closely consistent with the AMFR protein expression pattern previously reported,implying that the differential expression of AMFR gene may be rgeualted and controlled at the transcriptional level.

  16. 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)

  17. 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

  18. 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.

  19. 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

  20. 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

  1. The effect of tyrphostins AG494 and AG1478 on the autocrine growth regulation of A549 and DU145 cells

    Directory of Open Access Journals (Sweden)

    Agnieszka Bojko

    2012-07-01

    Full Text Available We employed two selective EGFR tyrosine kinase inhibitors: AG494 (reversible and AG1478 (irreversible for growth regulation of human lung (A549 and prostate (DU145 cancer cell lines, cultured in chemically defined DMEM/F12 medium. Both tested tyrphostins significantly inhibited autocrine growth of the investigated cell lines. The action of AG494 was dose dependent, and at highest concentrations led to complete inhibition of growth. AG1478 seemed to be more effective at lower concentrations, but was unable to completely inhibit growth of A549 cells. Inhibition of EGFR kinase activity by AG494 in contrast to AG1478 had no effect on the activity of ERK in both cell lines. Both EGFR’s inhibitors induced apoptosis of the investigated lung and prostate cancer cell lines, but the proapoptotic effect of the investigated tyrphostins was greater in A549 than in DU145 cells. The tyrphostins arrested cell growth of DU145 and A549 cells in the G1 phase, similarly to other known inhibitors of EGFR. The influence of AG494 and AG1478 on the activity of two signaling proteins (AKT and ERK was dependent upon the kind of investigated cells. In the case of DU145 cells, there was an evident decline in enzymatic activity of both kinases (stronger for AG1478, while in A549, only AG1478 effectively inhibited the phosphorylation of Akt. Tyrphostins AG494 and AG1478 are ATP-competitors and are supposed to have a similar mechanism of action, but our results suggest that this is not quite true.

  2. 17β-Estradiol responsiveness of MCF-7 laboratory strains is dependent on an autocrine signal activating the IGF type I receptor

    Directory of Open Access Journals (Sweden)

    Steenbergh Paul H

    2003-07-01

    Full Text Available Abstract Background Human MCF-7 cells have been studied extensively as a model for breast cancer cell growth. Many reports have established that serum-starved MCF-7 cells can be induced to proliferate upon the sole addition of 17β-estradiol (E2. However, the extent of the mitogenic response to E2 varies in different MCF-7 strains and may even be absent. In this study we compared the E2-sensitivity of three MCF-7 laboratory strains. Results The MCF-7S line is non-responsive to E2, the MCF-7 ATCC has an intermediate response to E2, while the MCF-7 NKI is highly E2-sensitive, although the levels and activities of the estrogen receptor (ER are not significantly different. Both suramin and IGF type I receptor blocking antibodies are able to inhibit the mitogenic response to E2-treatment in MCF-7 ATCC and MCF-7 NKI cells. From this we conclude that E2-induced proliferation is dependent on IGF type I receptor activation in all three MCF-7 strains. Conclusions The results presented in this article suggest that E2-responsiveness of MCF-7 cells is dependent on the secretion of an autocrine factor activating the IGF-IR. All three strains of MCF-7 breast cancer cells investigated do not respond to E2 if the IGF-RI-pathway is blocked. Generally, breast cancer therapy is targeted at inhibiting estrogen action. This study suggests that inhibition of IGF-action in combination with anti-estrogen-treatment may provide a more effective way in treatment or even prevention of breast cancer.

  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. Expression of autocrine prolactin and the short isoform of prolactin receptor are associated with inflammatory response and apoptosis in monocytes stimulated with Mycobacterium bovis proteins.

    Science.gov (United States)

    López-Rincón, Gonzalo; Mancilla, Raúl; Pereira-Suárez, Ana L; Martínez-Neri, Priscila A; Ochoa-Zarzosa, Alejandra; Muñoz-Valle, José Francisco; Estrada-Chávez, Ciro

    2015-06-01

    Increased levels of prolactin (PRL) have recently been associated with carcinogenesis and the exacerbation of autoimmune diseases, and might be involved in the progression of tuberculosis (TB). To investigate the relationship between PRL and prolactin receptor (PRLr) expression with inflammatory response and apoptosis in monocytes, we used THP-1 cells stimulated with antigens of the Mycobacterium bovis AN5 strain culture filtrate protein (CFP-M. bovis). Western blot (WB), real-time Polymerase chain reaction (PCR), and immunocytochemistry were performed to identify both PRL and PRLr molecules. PRL bioactivity and proinflammatory cytokine detection were assessed. The results showed that PRL and PRLr messenger RNA (mRNA) were synthesized in THP-1 monocytes induced with CFP-M. bovis at peaks of 176- and 404-fold, respectively. PRL forms of 60 and 80kDa and PRLr isoforms of 40, 50, and 65kDa were also identified as time-dependent, while 60-kDa PRL, as well as 40-, and 50-kDa PRLr, were found as soluble forms in culture media and later in the nucleus of THP-1 monocytes. PRL of 60kDa released by monocytes exhibited bioactivity in Nb2 cells, and both synthesized PRL and synthesized PRLr were related with nitrite and proinflammatory cytokine levels proapoptotic activity in CFP-M. bovis-induced monocytes. Our results suggest the overexpression of a full-autocrine loop of PRL and PRLr in monocytes that enhances the inflammatory response and apoptosis after priming with M. bovis antigens.

  5. 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...

  6. 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

  7. 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

  8. 4-1BB Signaling Enhances Primary and Secondary Population Expansion of CD8+ T Cells by Maximizing Autocrine IL-2/IL-2 Receptor Signaling.

    Directory of Open Access Journals (Sweden)

    Ho S Oh

    Full Text Available 4-1BB (CD137, a member of the tumor necrosis factor receptor superfamily (TNFRSF, is primarily expressed on activated T cells and is known to enhance proliferation of T cells, prevent activation-induced cell death, and promote memory formation of CD8+ T cells. In particular, it is well acknowledged that 4-1BB triggering preferentially enhances the expansion of CD8+ T cells rather than CD4+ T cells, but the underlying mechanism remains unclear. Here we found that 4-1BB triggering markedly increased IL-2Rα (CD25 and IL-2 expressions of CD8+ T cells but minimally for CD4+ T cells. Proliferation of CD8+ T cells was moderately enhanced by direct 4-1BB triggering in the absence of signaling through IL-2Rα/IL-2 interactions, but further promoted in the presence of IL-2Rα/IL-2 interactions. Among the TNFRSF members including OX40, GITR, CD30, and CD27, 4-1BB was superior in the ability to induce IL-2Rα expression on CD8+ T cells. When the primary and secondary expansions of CD8+ T cells in vivo were examined by adoptively transferring OVA-specific CD8+ T cells along with the treatment with agonistic anti-4-1BB and/or antagonistic anti-CD25 F(ab'2 mAb, 4-1BB triggering enhanced both primary and secondary expansion of CD8+ T cells in vivo, and the 4-1BB effects were moderately suppressed in primary expansion while completely abolished in secondary expansion of OVA-specific CD8+ T cells by blocking IL-2Rα. These results suggest that 4-1BB-mediated increases of IL-2Rα and IL-2 prolong the effects of transient TCR- and 4-1BB-mediated signaling in CD8+ T cells, and that 4-1BB triggering preferentially enhances the expansion of CD8+ T cells through the amplification of autocrine IL-2/IL-2R signaling loop.

  9. 4-1BB Signaling Enhances Primary and Secondary Population Expansion of CD8+ T Cells by Maximizing Autocrine IL-2/IL-2 Receptor Signaling.

    Science.gov (United States)

    Oh, Ho S; Choi, Beom K; Kim, Young H; Lee, Don G; Hwang, Sunhee; Lee, Myoung J; Park, Sang H; Bae, Yong-Soo; Kwon, Byoung S

    2015-01-01

    4-1BB (CD137), a member of the tumor necrosis factor receptor superfamily (TNFRSF), is primarily expressed on activated T cells and is known to enhance proliferation of T cells, prevent activation-induced cell death, and promote memory formation of CD8+ T cells. In particular, it is well acknowledged that 4-1BB triggering preferentially enhances the expansion of CD8+ T cells rather than CD4+ T cells, but the underlying mechanism remains unclear. Here we found that 4-1BB triggering markedly increased IL-2Rα (CD25) and IL-2 expressions of CD8+ T cells but minimally for CD4+ T cells. Proliferation of CD8+ T cells was moderately enhanced by direct 4-1BB triggering in the absence of signaling through IL-2Rα/IL-2 interactions, but further promoted in the presence of IL-2Rα/IL-2 interactions. Among the TNFRSF members including OX40, GITR, CD30, and CD27, 4-1BB was superior in the ability to induce IL-2Rα expression on CD8+ T cells. When the primary and secondary expansions of CD8+ T cells in vivo were examined by adoptively transferring OVA-specific CD8+ T cells along with the treatment with agonistic anti-4-1BB and/or antagonistic anti-CD25 F(ab')2 mAb, 4-1BB triggering enhanced both primary and secondary expansion of CD8+ T cells in vivo, and the 4-1BB effects were moderately suppressed in primary expansion while completely abolished in secondary expansion of OVA-specific CD8+ T cells by blocking IL-2Rα. These results suggest that 4-1BB-mediated increases of IL-2Rα and IL-2 prolong the effects of transient TCR- and 4-1BB-mediated signaling in CD8+ T cells, and that 4-1BB triggering preferentially enhances the expansion of CD8+ T cells through the amplification of autocrine IL-2/IL-2R signaling loop. PMID:25962156

  10. 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.

  11. 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

  12. 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

  13. Growth of triple-negative breast cancer cells relies upon coordinate autocrine expression of the proinflammatory cytokines IL-6 and IL-8.

    Science.gov (United States)

    Hartman, Zachary C; Poage, Graham M; den Hollander, Petra; Tsimelzon, Anna; Hill, Jamal; Panupinthu, Nattapon; Zhang, Yun; Mazumdar, Abhijit; Hilsenbeck, Susan G; Mills, Gordon B; Brown, Powel H

    2013-06-01

    Triple-negative breast cancers (TNBC) are aggressive with no effective targeted therapies. A combined database analysis identified 32 inflammation-related genes differentially expressed in TNBCs and 10 proved critical for anchorage-independent growth. In TNBC cells, an LPA-LPAR2-EZH2 NF-κB signaling cascade was essential for expression of interleukin (IL)-6, IL-8, and CXCL1. Concurrent inhibition of IL-6 and IL-8 expression dramatically inhibited colony formation and cell survival in vitro and stanched tumor engraftment and growth in vivo. A Cox multivariable analysis of patient specimens revealed that IL-6 and IL-8 expression predicted patient survival times. Together these findings offer a rationale for dual inhibition of IL-6/IL-8 signaling as a therapeutic strategy to improve outcomes for patients with TNBCs.

  14. Autocrine Acetylcholine, Induced by IL-17A via NFκB and ERK1/2 Pathway Activation, Promotes MUC5AC and IL-8 Synthesis in Bronchial Epithelial Cells

    Directory of Open Access Journals (Sweden)

    Angela Marina Montalbano

    2016-01-01

    Full Text Available IL-17A is overexpressed in the lung during acute neutrophilic inflammation. Acetylcholine (ACh increases IL-8 and Muc5AC production in airway epithelial cells. We aimed to characterize the involvement of nonneuronal components of cholinergic system on IL-8 and Muc5AC production in bronchial epithelial cells stimulated with IL-17A. Bronchial epithelial cells were stimulated with recombinant human IL-17A (rhIL-17A to evaluate the ChAT expression, the ACh binding and production, the IL-8 release, and the Muc5AC production. Furthermore, the effectiveness of PD098,059 (inhibitor of MAPKK activation, Bay11-7082 (inhibitor of IkBα phosphorylation, Hemicholinium-3 (HCh-3 (choline uptake blocker, and Tiotropium bromide (Spiriva® (anticholinergic drug was tested in our in vitro model. We showed that rhIL-17A increased the expression of ChAT, the levels of ACh binding and production, and the IL-8 and Muc5AC production in stimulated bronchial epithelial cells compared with untreated cells. The pretreatment of the cells with PD098,059 and Bay11-7082 decreased the ChAT expression and the ACh production/binding, while HCh-3 and Tiotropium decreased the IL-8 and Muc5AC synthesis in bronchial epithelial cells stimulated with rhIL-17A. IL-17A is involved in the IL-8 and Muc5AC production promoting, via NFκB and ERK1/2 pathway activation, the synthesis of ChAT, and the related activity of autocrine ACh in bronchial epithelial cells.

  15. 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

  16. Co-expression of epidermal growth factor-receptor and c-erb B-2 proto-oncogene product in human salivary-gland adenocarcinoma cell line HSG and the implications for HSG cell autocrine growth.

    Science.gov (United States)

    Kyakumoto, S; Kurokawa, R; Hoshino, M; Ota, M

    1994-07-01

    The autonomous proliferation of HSG cells is mediated by an autocrine growth factor, a 46K epidermal growth factor (EGF)-like molecule. The receptor for this molecule was investigated. Immunoprecipitation and immunoblotting revealed the expression of two possible receptor molecules, EGF-R and p185erbB-2, in HSG cells. Northern blotting also revealed the co-expression of 5.6-kb EGF-R mRNA and 4.6-kb c-erb B-2 mRNA. When the purified EGF-like molecule was added to the cultures, EGF-R but not p185erbB-2 was autophosphorylated. These results suggest that, although both EGF-R and p185erbB-2 are co-expressed in HSG cells, the EGF-R is the genuine receptor for the EGF-like molecule. However, there is a possibility that p185erB-2 is involved in the signal transduction system. This possibility was examined by using specific antibodies to human EGF-R (hEGF-R), p185erbB-2, and EGF to inhibit the functions of these molecules. Addition of these three antibodies to the cultures inhibited the growth of HSG cells. The antibodies to EGF-R and p185erbB-2 also caused morphological changes such as disturbances of the plasma membrane, and some cell death. Surprisingly, the effect of the anti-p185erbB-2 antibody on growth inhibition and morphology was stronger than that of the anti-hEGF-R antibody. Thus, p185erB-2 expressed in HSG cells has an important function in the signal transduction of HSG cell growth.

  17. Successful Predictions

    Science.gov (United States)

    Pierrehumbert, R.

    2012-12-01

    In an observational science, it is not possible to test hypotheses through controlled laboratory experiments. One can test parts of the system in the lab (as is done routinely with infrared spectroscopy of greenhouse gases), but the collective behavior cannot be tested experimentally because a star or planet cannot be brought into the lab; it must, instead, itself be the lab. In the case of anthropogenic global warming, this is all too literally true, and the experiment would be quite exciting if it weren't for the unsettling fact that we and all our descendents for the forseeable future will have to continue making our home in the lab. There are nonetheless many routes though which the validity of a theory of the collective behavior can be determined. A convincing explanation must not be a"just-so" story, but must make additional predictions that can be verified against observations that were not originally used in formulating the theory. The field of Earth and planetary climate has racked up an impressive number of such predictions. I will also admit as "predictions" statements about things that happened in the past, provided that observations or proxies pinning down the past climate state were not available at the time the prediction was made. The basic prediction that burning of fossil fuels would lead to an increase of atmospheric CO2, and that this would in turn alter the Earth's energy balance so as to cause tropospheric warming, is one of the great successes of climate science. It began in the lineage of Fourier, Tyndall and Arrhenius, and was largely complete with the the radiative-convective modeling work of Manabe in the 1960's -- all well before the expected warming had progressed far enough to be observable. Similarly, long before the increase in atmospheric CO2 could be detected, Bolin formulated a carbon cycle model and used it to predict atmospheric CO2 out to the year 2000; the actual values come in at the high end of his predicted range, for

  18. 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

  19. 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...

  20. 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....

  1. 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...

  2. 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

  3. 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...

  4. Nonlinear Combustion Instability Prediction

    Science.gov (United States)

    Flandro, Gary

    2010-01-01

    The liquid rocket engine stability prediction software (LCI) predicts combustion stability of systems using LOX-LH2 propellants. Both longitudinal and transverse mode stability characteristics are calculated. This software has the unique feature of being able to predict system limit amplitude.

  5. 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.

  6. 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

  7. Predictive systems ecology.

    Science.gov (United States)

    Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G

    2013-11-22

    Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

  8. Predictability of conversation partners

    CERN Document Server

    Takaguchi, Taro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

    2011-01-01

    Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information theoretic method to the spatiotemporal data of cell-phone locations, Song et al. (2010) found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one's conversation partners is defined as the degree to which one's next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between close sensor nodes. We find t...

  9. 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...

  10. 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.

  11. Predictability of Conversation Partners

    Science.gov (United States)

    Takaguchi, Taro; Nakamura, Mitsuhiro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

    2011-08-01

    Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song , ScienceSCIEAS0036-8075 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

  12. Is Time Predictability Quantifiable?

    DEFF Research Database (Denmark)

    Schoeberl, Martin

    2012-01-01

    -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......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...... compare the worst-case execution time bounds of different architectures....

  13. 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.

  14. 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...

  15. 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...

  16. 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.

  17. 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...

  18. 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

  19. Effects of Autocrine Motility Factor (AMF) on the Migration and Invasion of Glioblastoma U251 Cells and Their Mechanism%自分泌运动因子AMF对人胶质母细胞瘤U251细胞迁移、侵袭的影响及相关机制研究

    Institute of Scientific and Technical Information of China (English)

    李阳; 汤宁; 刘哲宇; 孙铮

    2016-01-01

    为了探讨自分泌运动因子(autocrine motility factor,AMF)对人胶质母细胞瘤U251细胞迁移、侵袭影响及其相关分子机制,该实验采用了RT-PCR及免疫印迹法检测RNA干扰AMF后U251细胞中AMF的表达变化;细胞划痕实验、Transwell实验分别观察了AMF干扰前后U251细胞迁移、侵袭能力的变化;免疫印记检测AMF干扰前后细胞中总Akt、p-Akt、Sox2、基质金属蛋白酶-2(matrix metalloprotein-2,MMP-2)及MMP-9蛋白水平的变化.研究结果表明,AMF成功干扰后U251细胞的迁移和侵袭能力受到抑制,p-Akt、Sox2、MMP-2和MMP-9蛋白表达水平降低.该研究表明,AMF敲低可以通过下调PI3K/Ak信号通路活性及Sox2、MMP-2和MMP-9蛋白水平,抑制人胶质母细胞瘤U251细胞迁移和侵袭.

  20. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  1. Zephyr - The prediction models

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, T.S.; Madsen, H.; Nielsen, H.Aa. [Informatics and Mathematical Modelling - DTU, Kgs. Lyngby (Denmark); Landberg, L.; Giebel, G. [Risoe National Lab., Roskilde (Denmark)

    2006-07-01

    This paper briefly describes new models and methods for predicting the wind power output from wind farms. The system is being developed in a project which has the research organization Risoe and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Danish 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 obtained by state-of-the-art parametric models. (au)

  2. 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.

  3. 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...

  4. 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...

  5. Epitope prediction methods

    DEFF Research Database (Denmark)

    Karosiene, Edita

    leucocyte antigen (HLA) molecules, are encoded by extremely polymorphic genes on chromosome 6. Due to this polymorphism, thousands of different MHC molecules exist, making the experimental identification of peptide-MHC interactions a very costly procedure. This has primed the need for in silico peptide......-MHC prediction methods, and over the last decade several such methods have been successfully developed and used for epitope discovery purposes. My PhD project has been dedicated to improve methods for predicting peptide-MHC interactions by developing new strategies for training prediction algorithms based...... on 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...

  6. 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...

  7. Predicting toxicity of nanoparticles

    OpenAIRE

    BURELLO ENRICO; Worth, Andrew

    2011-01-01

    A statistical model based on a quantitative structure–activity relationship accurately predicts the cytotoxicity of various metal oxide nanoparticles, thus offering a way to rapidly screen nanomaterials and prioritize testing.

  8. 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.

  9. '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...... stakeholders provides unique insights not otherwise available to senior management. We outline a methodology to agglomerate these insights in a performance barometer as an important source for problem identification and innovation....

  10. Stuck pipe prediction

    KAUST Repository

    Alzahrani, Majed

    2016-03-10

    Disclosed are various embodiments for a prediction application to predict a stuck pipe. A linear regression model is generated from hook load readings at corresponding bit depths. A current hook load reading at a current bit depth is compared with a normal hook load reading from the linear regression model. A current hook load greater than a normal hook load for a given bit depth indicates the likelihood of a stuck pipe.

  11. 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.

  12. 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.

  13. 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...

  14. 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)

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. Zephyr - the prediction models

    DEFF Research Database (Denmark)

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

    2001-01-01

    This paper briefly describes new models and methods for predicationg the wind power output from wind farms. The system is being developed in a project which has the research organization Risø and the department of Informatics and Mathematical Modelling (IMM) as the modelling team and all the Danish...... 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....

  20. 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.

  1. 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.

  2. THE PREDICTION OF OVULATION

    Institute of Scientific and Technical Information of China (English)

    WANGXin-Xing; ZHAShu-Wei; WUZhou-Ya

    1989-01-01

    The authors present their work on the prediction of ovulation in forty-five women with normal menstrual cycles for a total of 72 cycles by several indices, including ultrasonography, BBT graph, cervical mucus and mittelschmerz, LH peak values were also determined for reference in 20 cases ( 20 cycles ), Results are as follows:

  3. 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...

  4. 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

  5. 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...

  6. Predicting service life margins

    Science.gov (United States)

    Egan, G. F.

    1971-01-01

    Margins are developed for equipment susceptible to malfunction due to excessive time or operation cycles, and for identifying limited life equipment so monitoring and replacing is accomplished before hardware failure. Method applies to hardware where design service is established and where reasonable expected usage prediction is made.

  7. 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

  8. Predicting Classroom Success.

    Science.gov (United States)

    Kessler, Ronald P.

    A study was conducted at Rancho Santiago College (RSC) to identify personal and academic factors that are predictive of students' success in their courses. The study examined the following possible predictors of success: language and math test scores; background characteristics; length of time out of high school; high school background; college…

  9. 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…

  10. Predictability of critical transitions

    Science.gov (United States)

    Zhang, Xiaozhu; Kuehn, Christian; Hallerberg, Sarah

    2015-11-01

    Critical transitions in multistable systems have been discussed as models for a variety of phenomena ranging from the extinctions of species to socioeconomic 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 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 predictability of the system. The performance of different indicator variables turns out to be dependent on the specific model under study and the conditions of accessing it. Furthermore, we study the influence of the magnitude of transitions on the predictive performance.

  11. 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...

  12. 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.

  13. 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.

  14. Can observers predict trustworthiness?

    NARCIS (Netherlands)

    M. Belot; V. Bhaskar; J. van de Ven

    2009-01-01

    We analyze experimental evidence on whether untrained subjects can predict how trustworthy an individual is. Two players on a TV show play a high stakes prisoner's dilemma with pre-play communication. Our subjects report probabilistic beliefs that each player cooperates, before and after communicati

  15. 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...

  16. 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

  17. 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.

  18. 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%.

  19. Predictive Hypothesis Identification

    CERN Document Server

    Hutter, Marcus

    2008-01-01

    While statistics focusses on hypothesis testing and on estimating (properties of) the true sampling distribution, in machine learning the performance of learning algorithms on future data is the primary issue. In this paper we bridge the gap with a general principle (PHI) that identifies hypotheses with best predictive performance. This includes predictive point and interval estimation, simple and composite hypothesis testing, (mixture) model selection, and others as special cases. For concrete instantiations we will recover well-known methods, variations thereof, and new ones. PHI nicely justifies, reconciles, and blends (a reparametrization invariant variation of) MAP, ML, MDL, and moment estimation. One particular feature of PHI is that it can genuinely deal with nested hypotheses.

  20. 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......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......, on average they move away from numbers that have recently been drawn, as suggested by the “gambler’s fallacy”, and move toward numbers that are on streak, i.e. have been drawn several weeks in a row, consistent with the “hot hand fallacy”....

  1. 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...

  2. Predicting Bankruptcy in Pakistan

    Directory of Open Access Journals (Sweden)

    Abdul RASHID

    2011-09-01

    Full Text Available This paper aims to identify the financial ratios that are most significant in bankruptcy prediction for the non-financial sector of Pakistan based on a sample of companies which became bankrupt over the time period 1996-2006. Twenty four financial ratios covering four important financial attributes, namely profitability, liquidity, leverage, and turnover ratios, were examined for a five-year period prior bankruptcy. The discriminant analysis produced a parsimonious model of three variables viz. sales to total assets, EBIT to current liabilities, and cash flow ratio. Our estimates provide evidence that the firms having Z-value below zero fall into the “bankrupt” whereas the firms with Z-value above zero fall into the “non-bankrupt” category. The model achieved 76.9% prediction accuracy when it is applied to forecast bankruptcies on the underlying sample.

  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. 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...

  5. TGF-β1 autocrine signalling and enamel matrix components

    Science.gov (United States)

    Kobayashi-Kinoshita, Saeko; Yamakoshi, Yasuo; Onuma, Kazuo; Yamamoto, Ryuji; Asada, Yoshinobu

    2016-01-01

    Transforming growth factor-β1 (TGF-β1) is present in porcine enamel extracts and is critical for proper mineralization of tooth enamel. Here, we show that the mRNA of latent TGF-β1 is expressed throughout amelogenesis. Latent TGF-β1 is activated by matrix metalloproteinase 20 (MMP20), coinciding with amelogenin processing by the same proteinase. Activated TGF-β1 binds to the major amelogenin cleavage products, particularly the neutral-soluble P103 amelogenin, to maintain its activity. The P103 amelogenin-TGF-β1 complex binds to TGFBR1 to induce TGF-β1 signalling. The P103 amelogenin-TGF-β1 complex is slowly cleaved by kallikrein 4 (KLK4), which is secreted into the transition- and maturation-stage enamel matrix, thereby reducing TGF-β1 activity. To exert the multiple biological functions of TGF-β1 for amelogenesis, we propose that TGF-β1 is activated or inactivated by MMP20 or KLK4 and that the amelogenin cleavage product is necessary for the in-solution mobility of TGF-β1, which is necessary for binding to its receptor on ameloblasts and retention of its activity. PMID:27633089

  6. 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

  7. TGF-β1 autocrine signalling and enamel matrix components.

    Science.gov (United States)

    Kobayashi-Kinoshita, Saeko; Yamakoshi, Yasuo; Onuma, Kazuo; Yamamoto, Ryuji; Asada, Yoshinobu

    2016-09-16

    Transforming growth factor-β1 (TGF-β1) is present in porcine enamel extracts and is critical for proper mineralization of tooth enamel. Here, we show that the mRNA of latent TGF-β1 is expressed throughout amelogenesis. Latent TGF-β1 is activated by matrix metalloproteinase 20 (MMP20), coinciding with amelogenin processing by the same proteinase. Activated TGF-β1 binds to the major amelogenin cleavage products, particularly the neutral-soluble P103 amelogenin, to maintain its activity. The P103 amelogenin-TGF-β1 complex binds to TGFBR1 to induce TGF-β1 signalling. The P103 amelogenin-TGF-β1 complex is slowly cleaved by kallikrein 4 (KLK4), which is secreted into the transition- and maturation-stage enamel matrix, thereby reducing TGF-β1 activity. To exert the multiple biological functions of TGF-β1 for amelogenesis, we propose that TGF-β1 is activated or inactivated by MMP20 or KLK4 and that the amelogenin cleavage product is necessary for the in-solution mobility of TGF-β1, which is necessary for binding to its receptor on ameloblasts and retention of its activity.

  8. 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...

  9. 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...

  10. Nominal model predictive control

    OpenAIRE

    Grüne, Lars

    2013-01-01

    5 p., to appear in Encyclopedia of Systems and Control, Tariq Samad, John Baillieul (eds.); International audience; Model Predictive Control is a controller design method which synthesizes a sampled data feedback controller from the iterative solution of open loop optimal control problems.We describe the basic functionality of MPC controllers, their properties regarding feasibility, stability and performance and the assumptions needed in order to rigorously ensure these properties in a nomina...

  11. 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)

  12. 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.

  13. 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.

  14. 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.

  15. 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...

  16. 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...

  17. 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 ...

  18. 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

  19. 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.

  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. 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.

  3. 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

  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. 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...

  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 can be generated based on historical timeseries patterns of financial ratios. This is done by modeling the return on equity and the growth-rate in equity as two separate but correlated timeseries processes which converge to a long-term, constant level. Empirical results suggest that these earnings...

  7. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

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

    2016-01-01

    as 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...

  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. 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 the spine at at least two of the neighbouring vertebrae is calculated. The different curvature values are computed to obtain a value representative of the degree of irregularity in curvature of the spine and using the degree of irregularity, an estimate of the risk of a future fracture in vertebrae...

  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. Neurological abnormalities predict disability

    DEFF Research Database (Denmark)

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

    2014-01-01

    was performed. MRI assessment included age-related white matter changes (ARWMC) grading (mild, moderate, severe according to the Fazekas' scale), count of lacunar and non-lacunar infarcts, and global atrophy rating. Of the 633 (out of the 639 enrolled) patients with follow-up information (mean age 74.1 ± 5......, presence and number of neurological examination abnormalities predicted global functional decline independent of MRI lesions typical of the aging brain and other determinants of disability in the elderly. Systematically checking for neurological examination abnormalities in older patients may be cost...

  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. 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.

  14. 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.

  15. 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

  16. 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......-permeability relationships were replaced by relationships between velocity of elastic waves and permeability using laboratory data, and the relationships were then applied to well-log data. We found that the permeability prediction in chalk and possibly other sediments with large surface areas could be improved...... significantly using the effective specific surface as the fluid-flow concept. The FZI unit is appropriate for highly permeable sedimentary rocks such as sandstones and limestones that have small surface areas....

  17. 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.

  18. 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

  19. 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

  20. 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)

  1. Update on protein structure prediction

    DEFF Research Database (Denmark)

    Hubbard, T; Tramontano, A; Barton, G;

    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...

  2. Modeling and Prediction Overview

    Energy Technology Data Exchange (ETDEWEB)

    Ermak, D L

    2002-10-18

    Effective preparation for and response to the release of toxic materials into the atmosphere hinges on accurate predictions of the dispersion pathway, concentration, and ultimate fate of the chemical or biological agent. Of particular interest is the threat to civilian populations within major urban areas, which are likely targets for potential attacks. The goals of the CBNP Modeling and Prediction area are: (1) Development of a suite of validated, multi-scale, atmospheric transport and fate modeling capabilities for chemical and biological agent releases within the complex urban environment; (2) Integration of these models and related user tools into operational emergency response systems. Existing transport and fate models are being adapted to treat the complex atmospheric flows within and around structures (e.g., buildings, subway systems, urban areas) and over terrain. Relevant source terms and the chemical and physical behavior of gas- and particle-phase species (e.g., losses due to deposition, bio-agent viability, degradation) are also being developed and incorporated into the models. Model validation is performed using both laboratory and field data. CBNP is producing and testing a suite of models with differing levels of complexity and fidelity to address the full range of user needs and applications. Lumped-parameter transport models are being developed for subway systems and building interiors, supplemented by the use of computational fluid dynamics (CFD) models to describe the circulation within large, open spaces such as auditoriums. Both sophisticated CFD transport models and simpler fast-response models are under development to treat the complex flow around individual structures and arrays of buildings. Urban parameterizations are being incorporated into regional-scale weather forecast, meteorological data assimilation, and dispersion models for problems involving larger-scale urban and suburban areas. Source term and dose response models are being

  3. 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.

  4. 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

  5. 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...

  6. 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

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. Predictions From Eternal Inflation

    Science.gov (United States)

    Leichenauer, Stefan

    We investigate the physics of eternal inflation, particularly the use of multiverse ideas to explain the observed values of the cosmological constant and the coincidences of cosmological timescales. We begin by reviewing eternal inflation, the multiverse, and the resulting measure problem. Then follows a detailed study of proposals to solve the measure problem, both analytical and numerical, including an analysis of their predictions for cosmological observables. A key outcome of this investigation is that the traditional anthropic calculations, which take into account the necessity of galaxies and heavy elements to produce observers, are redundant in our framework. The cosmological coincidence problem, the seemingly coincidental equality of the timescales of observation and of vacuum domination, is solved for the first time without appeal to detailed anthropic assumptions: very general geometric considerations do the job automatically. We also estimate a 10% likelihood that evidence for eternal inflation will be found in upcoming measurements of the energy density of the universe. Encouraged by this success, we go on to construct a modified version of the light-cone time measure which has conceptual advantages but also reproduces the phenomenology of its predecessor. We complete our study of the measure problem by noting that for a wide class of proposed solutions, including the one developed here, there is an implicit assumption being made about a catastrophic end to the universe. Finally, as a by-product of this research program we find geometries which violate some of the accepted common knowledge on holographic entropy bounds. We point this out and conjecture a general result.

  12. 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 ...

  13. 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...

  14. 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 explai......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...... with surface scattering is presented. Each of the two scattering effects is modeled as frequency dependent functions....

  15. 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

  16. Predicting Marital Success with PREPARE: A Predictive Validity Study.

    Science.gov (United States)

    Fowers, Blaine J.; Olson, David H.

    1986-01-01

    Assessed the utility of the premarital inventory, PREPARE, in predicting marital success. Conducted a three-year follow-up study with couples (N=164) who took PREPARE during their engagement. Found that the PREPARE scores from three months before marriage could predict with 80-90% accuracy which couples were separated and divorced from those that…

  17. 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].

  18. 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.

  19. Solomonoff Prediction and Occam's Razor

    NARCIS (Netherlands)

    Sterkenburg, T.F.

    2016-01-01

    Algorithmic information theory gives an idealized notion of compressibility that is often presented as an objective measure of simplicity. It is suggested at times that Solomonoff prediction, or algorithmic information theory in a predictive setting, can deliver an argument to justify Occam’s razor.

  20. 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...

  1. Predicting responses in multiple environments

    NARCIS (Netherlands)

    Malosetti Zunin, Marcos; Bustos-Korts, Daniela; Boer, Martin P.; Eeuwijk, van Fred A.

    2016-01-01

    Prediction of the phenotypes for a set of genotypes across multiple environments is a fundamental task in any plant breeding program. Genomic prediction (GP) can assist selection decisions by combining incomplete phenotypic information over multiple environments (MEs) with dense sets of markers.

  2. 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.

  3. Zephyr - the next generation prediction

    DEFF Research Database (Denmark)

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

    2001-01-01

    Two of the most successful short-term prediction models (and the only ones in operational use at utilities) are going to be merged into one: the Risø model, developed by Landberg and the Wind Power Prediction Tool WPPT, developed at the Department of Mathematical Modelling IMM of the Danish Techn...

  4. 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

  5. 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...

  6. 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...

  7. 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 predictability of mobile sensors, acting as proxies for humans, change with time scale and sensor type such as GSM and WLAN. Applying recent information theoretic methods, it is demonstrated that an upper bound on predictability is relatively high for all sensors given the complete history (typically above 90......%). The relation between time scale and the predictability bound is examined for GSM and WLAN sensors, and both are found to have predictable and non-trivial behavior even on quite short time scales. The analysis provides valuable insight into aspects such as time scale and spatial quantization, state...

  8. 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.

  9. Numerical weather prediction model tuning via ensemble prediction system

    Science.gov (United States)

    Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.

    2011-12-01

    This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

  10. The Theory of Linear Prediction

    CERN Document Server

    Vaidyanathan, PP

    2007-01-01

    Linear prediction theory has had a profound impact in the field of digital signal processing. Although the theory dates back to the early 1940s, its influence can still be seen in applications today. The theory is based on very elegant mathematics and leads to many beautiful insights into statistical signal processing. Although prediction is only a part of the more general topics of linear estimation, filtering, and smoothing, this book focuses on linear prediction. This has enabled detailed discussion of a number of issues that are normally not found in texts. For example, the theory of vecto

  11. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    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 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...

  12. 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

  13. 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...

  14. Arctic Sea Ice Predictability and the Sea Ice Prediction Network

    Science.gov (United States)

    Wiggins, H. V.; Stroeve, J. C.

    2014-12-01

    Drastic reductions in Arctic sea ice cover have increased the demand for Arctic sea ice predictions by a range of stakeholders, including local communities, resource managers, industry and the public. The science of sea-ice prediction has been challenged to keep up with these developments. Efforts such as the SEARCH Sea Ice Outlook (SIO; http://www.arcus.org/sipn/sea-ice-outlook) and the Sea Ice for Walrus Outlook have provided a forum for the international sea-ice prediction and observing community to explore and compare different approaches. The SIO, originally organized by the Study of Environmental Change (SEARCH), is now managed by the new Sea Ice Prediction Network (SIPN), which is building a collaborative network of scientists and stakeholders to improve arctic sea ice prediction. The SIO synthesizes predictions from a variety of methods, including heuristic and from a statistical and/or dynamical model. In a recent study, SIO data from 2008 to 2013 were analyzed. The analysis revealed that in some years the predictions were very successful, in other years they were not. Years that were anomalous compared to the long-term trend have proven more difficult to predict, regardless of which method was employed. This year, in response to feedback from users and contributors to the SIO, several enhancements have been made to the SIO reports. One is to encourage contributors to provide spatial probability maps of sea ice cover in September and the first day each location becomes ice-free; these are an example of subseasonal to seasonal, local-scale predictions. Another enhancement is a separate analysis of the modeling contributions. In the June 2014 SIO report, 10 of 28 outlooks were produced from models that explicitly simulate sea ice from dynamic-thermodynamic sea ice models. Half of the models included fully-coupled (atmosphere, ice, and ocean) models that additionally employ data assimilation. Both of these subsets (models and coupled models with data

  15. Chemiluminescent prediction of service life

    Science.gov (United States)

    Hassell, J. A.; Mendenhall, G. D.; Nathan, R. A.

    1976-01-01

    Technique can be used to predict polymer degradation under actual expected-use conditions, without imposing artificial conditions. Smooth or linear correlations are obtained between chemiluminescence and physical properties of purified polymer gums.

  16. Prediction based on mean subset

    DEFF Research Database (Denmark)

    Øjelund, Henrik; Brown, P. J.; Madsen, Henrik;

    2002-01-01

    Shrinkage methods have traditionally been applied in prediction problems. In this article we develop a shrinkage method (mean subset) that forms an average of regression coefficients from individual subsets of the explanatory variables. A Bayesian approach is taken to derive an expression of how...... the coefficient vectors from each subset should be weighted. It is not computationally feasible to calculate the mean subset coefficient vector for larger problems, and thus we suggest an algorithm to find an approximation to the mean subset coefficient vector. In a comprehensive Monte Carlo simulation study......, it is found that the proposed mean subset method has superior prediction performance than prediction based on the best subset method, and in some settings also better than the ridge regression and lasso methods. The conclusions drawn from the Monte Carlo study is corroborated in an example in which prediction...

  17. 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...

  18. Trading network predicts stock price.

    Science.gov (United States)

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi

    2014-01-16

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  19. Trading Network Predicts Stock Price

    Science.gov (United States)

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi

    2014-01-01

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  20. Prediction for new magnetoelectric fluorides

    NARCIS (Netherlands)

    Nenert, G.; Palstra, T. T. M.

    2007-01-01

    We use symmetry considerations in order to predict new magnetoelectric fluorides. In addition to these magnetoelectric properties, we discuss which among these fluorides are the ones susceptible to present multiferroic properties. We emphasize that several materials exhibit ferromagnetic properties.

  1. 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.

  2. 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...

  3. 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...

  4. 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...

  5. 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

  6. 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...

  7. Seasonal Drought Prediction in India

    Science.gov (United States)

    Shah, R.; Mishra, V.

    2015-12-01

    Drought is among the most costly natural disasters in India. Seasonal prediction of drought can assist planners to manage agriculture and water resources. Such information can be valuable for a country like India where 60% of agriculture is rain-fed. Here we evaluate precipitation and temperature forecast from the NCEP's CFSV2 for seasonal drought prediction in India. We demonstrate the utility of the seasonal prediction of precipitation and temperature for drought forecast at 1-2 months lead time at a high spatial resolution. Precipitation from CFSv2 showed moderate correlations with observed up to two months lead. For one month lead, we found a significant correlation between CFSv2 and observed precipitation during winter season. Air temperature from the CFSv2 showed a good correlation with observed temperature during the winter. We forced the Variable Infiltration Capacity (VIC) model with the CFSv2 forecast of precipitation and air temperature to generate forecast of hydrologic variables such as soil moisture and total runoff. We find that errors of the prediction reduce for the two month lead time in the majority of the study domain except the northern India. Skills of Initial Hydrologic Conditions combined with moderate skills of forcings based on the CFSv2 showed ability of drought prediction in India. The developed system was able to successfully predict observed top layer soil moisture and observed drought based on satellite remote sensing in India.

  8. 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)

  9. Reward positivity: Reward prediction error or salience prediction error?

    Science.gov (United States)

    Heydari, Sepideh; Holroyd, Clay B

    2016-08-01

    The reward positivity is a component of the human ERP elicited by feedback stimuli in trial-and-error learning and guessing tasks. A prominent theory holds that the reward positivity reflects a reward prediction error signal that is sensitive to outcome valence, being larger for unexpected positive events relative to unexpected negative events (Holroyd & Coles, 2002). Although the theory has found substantial empirical support, most of these studies have utilized either monetary or performance feedback to test the hypothesis. However, in apparent contradiction to the theory, a recent study found that unexpected physical punishments also elicit the reward positivity (Talmi, Atkinson, & El-Deredy, 2013). The authors of this report argued that the reward positivity reflects a salience prediction error rather than a reward prediction error. To investigate this finding further, in the present study participants navigated a virtual T maze and received feedback on each trial under two conditions. In a reward condition, the feedback indicated that they would either receive a monetary reward or not and in a punishment condition the feedback indicated that they would receive a small shock or not. We found that the feedback stimuli elicited a typical reward positivity in the reward condition and an apparently delayed reward positivity in the punishment condition. Importantly, this signal was more positive to the stimuli that predicted the omission of a possible punishment relative to stimuli that predicted a forthcoming punishment, which is inconsistent with the salience hypothesis. PMID:27184070

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. Predicting nitrogen excretion from cattle.

    Science.gov (United States)

    Reed, K F; Moraes, L E; Casper, D P; Kebreab, E

    2015-05-01

    Manure nitrogen (N) from cattle production facilities can lead to negative environmental effects, such as contribution to greenhouse gas emissions, leaching and runoff to aqueous ecosystems leading to eutrophication, and acid rain. To mitigate these effects and to improve the efficiency of N use, accurate prediction of N excretion and secretions are required. A genetic algorithm was implemented to select models to predict fecal, urinary, and total manure N excretions, and milk N secretions from 3 classes of animals: lactating dairy cows, heifers and dry cows, and steers. Two tiers of model classes were developed for each category of animals based on model input requirements. A total of 6 models for heifers and dry cows and steers and an additional 2 models for lactating dairy cattle were developed. Evaluation of the models using K-fold cross validation based on all data and using the most recent 6 yr of data showed better prediction for total manure N and fecal N compared with urinary N excretion, which was the most variable response in the database. Compared with extant models from the literature, the models developed in this study resulted in a significant improvement in prediction error for fecal and urinary N excretions from lactating cows. For total manure production by lactating cows, extant and new models were comparable in their prediction ability. Both proposed and extant models performed better than the prediction methods used by the US Environmental Protection Agency for the national inventory of greenhouse gases. Therefore, the proposed models are recommended for use in estimation of manure N from various classes of animals. PMID:25747829

  18. 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

  19. 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

  20. 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)

  1. Methods for Predicting Stock Indexes

    Directory of Open Access Journals (Sweden)

    Martha Cecilia García

    2013-11-01

    Full Text Available This paper presents a literature review on methods that have been used in the last two decades to predict Stock Market Indexes. Methods studied range from those enabling to grab the linear characteristics present in the stock market indexes, going through those that focus on non-linear features and finally hybrid methods that are more robust, since they capture linear and non-linear features. In addition, this research includes methods that use macroeconomic variables to predict indexes from different stock exchanges around the world.

  2. 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

  3. 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.

  4. 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...

  5. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    Data.gov (United States)

    U.S. Environmental Protection Agency — Data from a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating using predictive computational...

  6. 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.

  7. Evoked Emotions Predict Food Choice

    NARCIS (Netherlands)

    Dalenberg, J.R.; Gutjar, S.; Horst, ter G.J.; Graaf, de C.; Renken, R.; Jager, G.

    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

  8. Detecting failure of climate predictions

    Science.gov (United States)

    Runge, Michael C.; Stroeve, Julienne C.; Barrett, Andrew P.; McDonald-Madden, Eve

    2016-01-01

    The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty1, 2. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies3. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

  9. 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

  10. 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)

  11. Prediction models in complex terrain

    DEFF Research Database (Denmark)

    Marti, I.; Nielsen, Torben Skov; Madsen, Henrik;

    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...

  12. 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…

  13. 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

  14. Prediction of regional wind power

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, T.S.; Madsen, H.; Nielsen, H.Aa. [Informatics and Mathematical Modelling - DTU, Kgs. Lyngby (Denmark); Landberg, L.; Giebel, G. [Risoe National Lab., Roskilde (Denmark)

    2006-07-01

    This paper presents a new concept for predicting the total wind power production in a larger region based on a combination of on-line measurements of power production from selected wind farms, power measurements for all wind turbines in the area and numerical weather predictions of wind speed and wind direction. The models are implemented in the Zephyr/WPPT system an on-line software system for calculating short-term predictions of wind power currently being developed by IMM and Risoe in coorporation with Elsam, Eltra, Elkraft and SEAS the major electrical utilities with respect to wind power in Denmark. Zephyr/WPPT employs statistical models to describe the relationship between power production and the numerical weather predictions. The statistical models belong to the class of conditional parametric models a model class particular useful for estimating non-linear relationships on-line. The estimation is furthermore made adaptively in order to allow for slow changes in the system e.g. caused by the annual variations of the climate. (au)

  15. 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.

  16. 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.

  17. 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…

  18. 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.

  19. Bankruptcy Prediction with Rough Sets

    NARCIS (Netherlands)

    J.C. Bioch (Cor); V. Popova (Viara)

    2001-01-01

    textabstractThe bankruptcy prediction problem can be considered an or dinal classification problem. The classical theory of Rough Sets describes objects by discrete attributes, and does not take into account the order- ing of the attributes values. This paper proposes a modification of the Rough Set

  20. Prediction for new magnetoelectric fluorides

    OpenAIRE

    Nenert, G.; Palstra, T. T. M.

    2007-01-01

    We use symmetry considerations in order to predict new magnetoelectric fluorides. In addition to these magnetoelectric properties, we discuss which among these fluorides are the ones susceptible to present multiferroic properties. We emphasize that several materials exhibit ferromagnetic properties. This ferromagnetism should enhance the interplay between the magnetic and dielectric properties in these materials.

  1. 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.

  2. Detecting failure of climate predictions

    Science.gov (United States)

    Runge, Michael C.; Stroeve, Julienne C.; Barrett, Andrew P.; McDonald-Madden, Eve

    2016-09-01

    The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

  3. 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.

  4. 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

  5. Cast iron - a predictable material

    Directory of Open Access Journals (Sweden)

    Jorg C. Sturm

    2011-02-01

    Full Text Available High strength compacted graphite iron (CGI or alloyed cast iron components are substituting previously used non-ferrous castings in automotive power train applications. The mechanical engineering industry has recognized the value in substituting forged or welded structures with stiff and light-weight cast iron castings. New products such as wind turbines have opened new markets for an entire suite of highly reliable ductile iron cast components. During the last 20 years, casting process simulation has developed from predicting hot spots and solidification to an integral assessment tool for foundries for the entire manufacturing route of castings. The support of the feeding related layout of the casting is still one of the most important duties for casting process simulation. Depending on the alloy poured, different feeding behaviors and self-feeding capabilities need to be considered to provide a defect free casting. Therefore, it is not enough to base the prediction of shrinkage defects solely on hot spots derived from temperature fields. To be able to quantitatively predict these defects, solidification simulation had to be combined with density and mass transport calculations, in order to evaluate the impact of the solidification morphology on the feeding behavior as well as to consider alloy dependent feeding ranges. For cast iron foundries, the use of casting process simulation has become an important instrument to predict the robustness and reliability of their processes, especially since the influence of alloying elements, melting practice and metallurgy need to be considered to quantify the special shrinkage and solidification behavior of cast iron. This allows the prediction of local structures, phases and ultimately the local mechanical properties of cast irons, to asses casting quality in the foundry but also to make use of this quantitative information during design of the casting. Casting quality issues related to thermally driven

  6. 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

  7. 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

  8. 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+

  9. Simulation, situated conceptualization, and prediction.

    Science.gov (United States)

    Barsalou, Lawrence W

    2009-05-12

    Based on accumulating evidence, simulation appears to be a basic computational mechanism in the brain that supports a broad spectrum of processes from perception to social cognition. Further evidence suggests that simulation is typically situated, with the situated character of experience in the environment being reflected in the situated character of the representations that underlie simulation. A basic architecture is sketched of how the brain implements situated simulation. Within this framework, simulators implement the concepts that underlie knowledge, and situated conceptualizations capture patterns of multi-modal simulation associated with frequently experienced situations. A pattern completion inference mechanism uses current perception to activate situated conceptualizations that produce predictions via simulations on relevant modalities. Empirical findings from perception, action, working memory, conceptual processing, language and social cognition illustrate how this framework produces the extensive prediction that characterizes natural intelligence.

  10. 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.

  11. Time-Predictable Virtual Memory

    DEFF Research Database (Denmark)

    Puffitsch, Wolfgang; Schoeberl, Martin

    2016-01-01

    Virtual memory is an important feature of modern computer architectures. For hard real-time systems, memory protection is a particularly interesting feature of virtual memory. However, current memory management units are not designed for time-predictability and therefore cannot be used...... in such systems. This paper investigates the requirements on virtual memory from the perspective of hard real-time systems and presents the design of a time-predictable memory management unit. Our evaluation shows that the proposed design can be implemented efficiently. The design allows address translation...... and address range checking in constant time of two clock cycles on a cache miss. This constant time is in strong contrast to the possible cost of a miss in a translation look-aside buffer in traditional virtual memory organizations. Compared to a platform without a memory management unit, these two additional...

  12. 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......) and contact number (CN) measures only. We show that the HSE measure is much more information-rich than CN, nevertheless, HSE does not appear to provide enough information to reconstruct the C-traces of real-sized proteins. Our experiments also show that using tabu search (with our novel tabu definition......) 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...

  13. 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.

  14. The ethics of earthquake prediction.

    Science.gov (United States)

    Sol, Ayhan; Turan, Halil

    2004-10-01

    Scientists' responsibility to inform the public about their results may conflict with their responsibility not to cause social disturbance by the communication of these results. A study of the well-known Brady-Spence and Iben Browning earthquake predictions illustrates this conflict in the publication of scientifically unwarranted predictions. Furthermore, a public policy that considers public sensitivity caused by such publications as an opportunity to promote public awareness is ethically problematic from (i) a refined consequentialist point of view that any means cannot be justified by any ends, and (ii) a rights view according to which individuals should never be treated as a mere means to ends. The Parkfield experiment, the so-called paradigm case of cooperation between natural and social scientists and the political authorities in hazard management and risk communication, is also open to similar ethical criticism. For the people in the Parkfield area were not informed that the whole experiment was based on a contested seismological paradigm.

  15. 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.

  16. Predicting responses from Rasch measures.

    Science.gov (United States)

    Linacre, John M

    2010-01-01

    There is a growing family of Rasch models for polytomous observations. Selecting a suitable model for an existing dataset, estimating its parameters and evaluating its fit is now routine. Problems arise when the model parameters are to be estimated from the current data, but used to predict future data. In particular, ambiguities in the nature of the current data, or overfit of the model to the current dataset, may mean that better fit to the current data may lead to worse fit to future data. The predictive power of several Rasch and Rasch-related models are discussed in the context of the Netflix Prize. Rasch-related models are proposed based on Singular Value Decomposition (SVD) and Boltzmann Machines.

  17. On long term climate prediction

    Energy Technology Data Exchange (ETDEWEB)

    Thatcher, M.

    1990-08-01

    On the occasion of the opening of The Hadley Centre in Bracknell, Berkshire on May 25, 1990, Britain's Prime Minister, the Rt. Hon. Margaret Thatcher, FRS, related the significance of the Centre to the Scientific Assessment Report of the Inter-Governmental Panel on Climate Change which was published on the same day. The Report confirms that greenhouse gases are increasing substantially as a result of man's activites; that this will warm the Earth's surface, with serious consequences for us all, and that these consequences are capable of prediction. We want to predict them more accurately. Calling the Report an authoritative early warning system which could be ignored only at great risk to future generations, Mrs. Margaret Thatcher described the role of the Centre in enabling the establishment of a realistic international program and timetable for action.

  18. Predicting percolation thresholds in networks

    CERN Document Server

    Radicchi, Filippo

    2014-01-01

    We consider different methods, that do not rely on numerical simulations of the percolation process, to approximate percolation thresholds in networks. We perform a systematic analysis on synthetic graphs and a collection of 109 real networks to quantify their effectiveness and reliability as prediction tools. Our study reveals that the inverse of the largest eigenvalue of the non-backtracking matrix of the graph often provides a tight lower bound for true percolation threshold. However, in more than 40% of the cases, this indicator is less predictive than the naive expectation value based solely on the moments of the degree distribution. We find that the performance of all indicators becomes worse as the value of the true percolation threshold grows. Thus, none of them represents a good proxy for robustness of extremely fragile networks.

  19. Action semantics modulate action prediction.

    Science.gov (United States)

    Springer, Anne; Prinz, Wolfgang

    2010-11-01

    Previous studies have demonstrated that action prediction involves an internal action simulation that runs time-locked to the real action. The present study replicates and extends these findings by indicating a real-time simulation process (Graf et al., 2007), which can be differentiated from a similarity-based evaluation of internal action representations. Moreover, results showed that action semantics modulate action prediction accuracy. The semantic effect was specified by the processing of action verbs and concrete nouns (Experiment 1) and, more specifically, by the dynamics described by action verbs (Experiment 2) and the speed described by the verbs (e.g., "to catch" vs. "to grasp" vs. "to stretch"; Experiment 3). These results propose a linkage between action simulation and action semantics as two yet unrelated domains, a view that coincides with a recent notion of a close link between motor processes and the understanding of action language.

  20. MPC-Relevant Prediction-Error Identification

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    A prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space m...

  1. 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...

  2. 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...

  3. 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.

  4. 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.

  5. 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....

  6. 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...

  7. 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...

  8. 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 ...

  9. On Predictive Least Squares Principles

    OpenAIRE

    Wei, C. Z.

    1992-01-01

    Recently, Rissanen proposed a new model selection criterion PLS that selects the model that minimizes the accumulated squares of prediction errors. Usually, the information-based criteria, such as AIC and BIC, select the model that minimizes a loss function which can be expressed as a sum of two terms. One measures the goodness of fit and the other penalizes the complexity of the selected model. In this paper we provide such an interpretation for PLS. Using this relationship, we give sufficie...

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. 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

  17. Wine Expertise Predicts Taste Phenotype.

    Science.gov (United States)

    Hayes, John E; Pickering, Gary J

    2012-03-01

    Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance - with appropriate caveats about populations tested, outcomes measured and psychophysical methods used - an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli.

  18. 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.

  19. Statistics-Free Sports Prediction

    OpenAIRE

    Dubbs, Alexander

    2015-01-01

    We use a simple machine learning model, logistically-weighted regularized linear least squares regression, in order to predict baseball, basketball, football, and hockey games. We do so using only the thirty-year record of which visiting teams played which home teams, on what date, and what the final score was. No real "statistics" are used. The method works best in basketball, likely because it is high-scoring and has long seasons. It works better in football and hockey than in baseball, but...

  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...

  1. 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.

  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. 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.

  4. 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....

  5. 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.

  6. 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.

  7. 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)

  8. 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.

  9. Predicting outcomes: Sports and stocks.

    Science.gov (United States)

    Wood, G

    1992-06-01

    Many gamblers and most fans, players, and coaches offer causal explanations for long runs of good or bad performance in sports and financial analysts are quick to offer explanations for the daily performance of the stock market. The records of professional basketball and baseball teams and the Dow Jones daily closing average for a ten year period were evaluated for trends (streaks). The records of teams were also evaluated to assess whether the record against opponents, the home court or home field advantage, and-for baseball teams-the record of the winning and losing pitcher (excluding the current game) predicted the outcome of individual games. Recent performance is, at best, a very weak predictor of current performance and the three best predictors for baseball (pitching, home field, and record against opponent) together accounted for only 1.7% of the variance in the outcomes of individual games. We overestimate our ability to predict. This overconfidence is likely to play a role in maintaining gambling behaviors. PMID:24241784

  10. 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...

  11. 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

  12. 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.

  13. Use of Feedback in Clinical Prediction

    Science.gov (United States)

    Schroeder, Harold E.

    1972-01-01

    Results indicated that predictive accuracy is greater when feedback is applied to the basis for the prediction than when applied to gut" impressions. Judges forming hypotheses were also able to learn from experience. (Author)

  14. Limits on lexical prediction during reading.

    Science.gov (United States)

    Luke, Steven G; Christianson, Kiel

    2016-08-01

    Efficient language processing may involve generating expectations about upcoming input. To investigate the extent to which prediction might facilitate reading, a large-scale survey provided cloze scores for all 2689 words in 55 different text passages. Highly predictable words were quite rare (5% of content words), and most words had a more-expected competitor. An eye-tracking study showed sensitivity to cloze probability but no mis-prediction cost. Instead, the presence of a more-expected competitor was found to be facilitative in several measures. Further, semantic and morphosyntactic information was highly predictable even when word identity was not, and this information facilitated reading above and beyond the predictability of the full word form. The results are consistent with graded prediction but inconsistent with full lexical prediction. Implications for theories of prediction in language comprehension are discussed. PMID:27376659

  15. Statistical prediction of Late Miocene climate

    Digital Repository Service at National Institute of Oceanography (India)

    Fernandes, A.A.; Gupta, S.M.

    The theory of statistical prediction of paleoclimate (Imbrie and Kipp, 1971), which includes multiple regression analysis and factor analysis is reviewed. Necessary software is listed. An application to predicting palaeo oceanographic parameters...

  16. 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 ...

  17. 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...

  18. 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.

  19. 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

  20. 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;...

  1. 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

  2. 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...

  3. 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...

  4. 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.

  5. 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.

  6. 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...

  7. 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.

  8. 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.

  9. Nutritional prediction of pressure ulcers.

    Science.gov (United States)

    Breslow, R A; Bergstrom, N

    1994-11-01

    This article focuses on nutritional risk factors that predict the development of pressure ulcers in hospital and nursing home patients. Cross-sectional studies associate inadequate energy and protein intake; underweight; low triceps skinfold measurement; and low serum albumin, low serum cholesterol, and low hemoglobin levels with pressure ulcers. Prospective studies identify inadequate energy and protein intake, a poor score on the Braden scale (a risk assessment instrument that includes a nutrition component), and possibly low serum albumin level as risk factors for developing a pressure ulcer. Nutritionists should provide a high-energy, high-protein diet for patients at risk of development of pressure ulcers to improve their dietary intake and nutritional status.

  10. 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.

  11. 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)

  12. Time-predictable Stack Caching

    DEFF Research Database (Denmark)

    Abbaspourseyedi, Sahar

    completely. Thus, in systems with hard deadlines the worst-case execution time (WCET) of the real-time software running on them needs to be bounded. Modern architectures use features such as pipelining and caches for improving the average performance. These features, however, make the WCET analysis more...... 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......Embedded systems are computing systems for controlling and interacting with physical environments. Embedded systems with special timing constraints where the system needs to meet deadlines are referred to as real-time systems. In hard real-time systems, missing a deadline causes the system to fail...

  13. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which...

  14. Prediction of twin-arginine signal peptides

    DEFF Research Database (Denmark)

    Bendtsen, Jannick Dyrløv; Nielsen, Henrik; Widdick, D.;

    2005-01-01

    peptides and 84% of the annotated cleavage sites of these Tat signal peptides were correctly predicted. This method generates far less false positive predictions on various datasets than using simple pattern matching. Moreover, on the same datasets TatP generates less false positive predictions than...

  15. 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...

  16. 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.

  17. Return Predictability, Model Uncertainty, and Robust Investment

    DEFF Research Database (Denmark)

    Lukas, Manuel

    Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...

  18. Link prediction via generalized coupled tensor factorisation

    DEFF Research Database (Denmark)

    Ermiş, Beyza; Evrim, Acar Ataman; Taylan Cemgil, A.

    2012-01-01

    This study deals with the missing link prediction problem: the problem of predicting the existence of missing connections between entities of interest. We address link prediction using coupled analysis of relational datasets represented as heterogeneous data, i.e., datasets in the form of matrice...

  19. Predictive Analytics in Information Systems Research

    NARCIS (Netherlands)

    G. Shmueli (Galit); O.R. Koppius (Otto)

    2011-01-01

    textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as wel

  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. 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...... 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 an onshore Danish wind farm...... to the case of a large number of wind farms in Europe and Australia among others is finally discussed....

  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. 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.

  5. Protein secondary structure: category assignment and predictability

    DEFF Research Database (Denmark)

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

    2001-01-01

    In the last decade, the prediction of protein secondary structure has been optimized using essentially one and the same assignment scheme known as DSSP. We present here a different scheme, which is more predictable. This scheme predicts directly the hydrogen bonds, which stabilize the secondary...... 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-forward...

  6. BDDCS Class Prediction for New Molecular Entities

    DEFF Research Database (Denmark)

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

    2012-01-01

    M) predicts high versus low intestinal permeability rate, and vice versa, at least when uptake transporters or paracellular transport is not involved. We recently published a collection of over 900 marketed drugs classified for BDDCS. We suggest that a reliable model for predicting BDDCS class, integrated...... descriptors calculated or derived from the VolSurf+ software. For each molecule, a probability of BDDCS class membership was given, based on predicted EoM, FDA solubility (FDAS) and their confidence scores. The accuracy in predicting FDAS was 78% in training and 77% in validation, while for EoM prediction...

  7. 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.

  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. Predicting Well-Being in Europe?

    DEFF Research Database (Denmark)

    Hussain, M. Azhar

    2015-01-01

    Has the worst financial and economic crisis since the 1930s reduced the subjective wellbeing function's predictive power? Regression models for happiness are estimated for the three first rounds of the European Social Survey (ESS); 2002, 2004 and 2006. Several explanatory variables are significant...... with the expected signs and an average determination coefficient around 0.25. Based on these estimated parameters happiness is predicted for the latest three rounds of the ESS; 2008, 2010 and 2012. Happiness is slightly underestimated in both 2008 and 2010, e.g. actual happiness generally is above predicted...... happiness. Nevertheless, 73% of the predictions in 2008 and 57% of predictions in 2010 were within the margin of error. These correct prediction percentages are not unusually low - rather they are slightly higher than before the crisis. It is surprising that happiness predictions are not adversely affected...

  11. 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.

  12. Predicting Electronic Failure from Smoke

    Energy Technology Data Exchange (ETDEWEB)

    Tanaka, T.J.

    1999-01-15

    Smoke can cause electronic equipment to fail through increased leakage currents and shorts. Sandia National Laboratories is studying the increased leakage currents caused by smoke with varying characteristics. The objective is to develop models to predict the failure of electronic equipment exposed to smoke. This requires the collection of data on the conductivity of smoke and knowledge of critical electrical systems that control high-consequence operations. We have found that conductivity is a function of the type of fuel, how it is burned, and smoke density. Video recordings of highly biased dc circuits exposed in a test chamber show that during a fire, smoke is attracted to high voltages and can build fragile carbon bridges that conduct leakage currents. The movement of air breaks the bridges, so the conductivity decreases after the fire is extinguished and the test chamber is vented. During the fire, however, electronic equipment may not operate correctly, leading to problems for critical operations dependent on electronic control. The potential for electronic failure is highly dependent on the type of electrical circuit, and Sandia National Laboratories plans to include electrical circuit modeling in the failure models.

  13. Predictive properties of visual adaptation.

    Science.gov (United States)

    Chopin, Adrien; Mamassian, Pascal

    2012-04-10

    What humans perceive depends in part on what they have previously experienced. After repeated exposure to one stimulus, adaptation takes place in the form of a negative correlation between the current percept and the last displayed stimuli. Previous work has shown that this negative dependence can extend to a few minutes in the past, but the precise extent and nature of the dependence in vision is still unknown. In two experiments based on orientation judgments, we reveal a positive dependence of a visual percept with stimuli presented remotely in the past, unexpectedly and in contrast to what is known for the recent past. Previous theories of adaptation have postulated that the visual system attempts to calibrate itself relative to an ideal norm or to the recent past. We propose instead that the remote past is used to estimate the world's statistics and that this estimate becomes the reference. According to this new framework, adaptation is predictive: the most likely forthcoming percept is the one that helps the statistics of the most recent percepts match that of the remote past.

  14. 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

  15. 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.

  16. Holistic processing predicts face recognition.

    Science.gov (United States)

    Richler, Jennifer J; Cheung, Olivia S; Gauthier, Isabel

    2011-04-01

    The concept of holistic processing is a cornerstone of face-recognition research. In the study reported here, we demonstrated that holistic processing predicts face-recognition abilities on the Cambridge Face Memory Test and on a perceptual face-identification task. Our findings validate a large body of work that relies on the assumption that holistic processing is related to face recognition. These findings also reconcile the study of face recognition with the perceptual-expertise work it inspired; such work links holistic processing of objects with people's ability to individuate them. Our results differ from those of a recent study showing no link between holistic processing and face recognition. This discrepancy can be attributed to the use in prior research of a popular but flawed measure of holistic processing. Our findings salvage the central role of holistic processing in face recognition and cast doubt on a subset of the face-perception literature that relies on a problematic measure of holistic processing.

  17. 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.

  18. 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...

  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. 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/.

  1. Predictability of threshold exceedances in dynamical systems

    Science.gov (United States)

    Bódai, Tamás

    2015-12-01

    In a low-order model of the general circulation of the atmosphere we examine the predictability of threshold exceedance events of certain observables. The likelihood of such binary events-the cornerstone also for the categoric (as opposed to probabilistic) prediction of threshold exceedances-is established from long time series of one or more observables of the same system. The prediction skill is measured by a summary index of the ROC curve that relates the hit- and false alarm rates. Our results for the examined systems suggest that exceedances of higher thresholds are more predictable; or in other words: rare large magnitude, i.e., extreme, events are more predictable than frequent typical events. We find this to hold provided that the bin size for binning time series data is optimized, but not necessarily otherwise. This can be viewed as a confirmation of a counterintuitive (and seemingly contrafactual) statement that was previously formulated for more simple autoregressive stochastic processes. However, we argue that for dynamical systems in general it may be typical only, but not universally true. We argue that when there is a sufficient amount of data depending on the precision of observation, the skill of a class of data-driven categoric predictions of threshold exceedances approximates the skill of the analogous model-driven prediction, assuming strictly no model errors. Therefore, stronger extremes in terms of higher threshold levels are more predictable both in case of data- and model-driven prediction. Furthermore, we show that a quantity commonly regarded as a measure of predictability, the finite-time maximal Lyapunov exponent, does not correspond directly to the ROC-based measure of prediction skill when they are viewed as functions of the prediction lead time and the threshold level. This points to the fact that even if the Lyapunov exponent as an intrinsic property of the system, measuring the instability of trajectories, determines predictability

  2. 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)(...

  3. 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.

  4. 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...

  5. 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].

  6. 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

  7. Improve consensus via decentralized predictive mechanisms

    Science.gov (United States)

    Zhang, H.-T.; Chen, M. Z. Q.; Zhou, T.

    2009-05-01

    For biogroups and groups of self-driven agents, making decisions often depends on interactions among group members. In this paper, we seek to understand the fundamental predictive mechanisms used by group members in order to perform such coordinated behaviors. In particular, we show that the future dynamics of each node in the network can be predicted solely using local information provided by its neighbors. Using this predicted future dynamics information, we propose a decentralized predictive consensus protocol, which yields drastic improvements in terms of both consensus speed and internal communication cost. In natural science, this study provides an evidence for the idea that some decentralized predictive mechanisms may exist in widely-spread biological swarms/flocks. From the industrial point of view, incorporation of a decentralized predictive mechanism allows for not only a significant increase in the speed of convergence towards consensus but also a reduction in the communication energy required to achieve a predefined consensus performance.

  8. 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.

  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. 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 ....

  11. 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...

  12. Recommendations for PDF usage in LHC predictions

    CERN Document Server

    Placakyte, Ringaile

    2016-01-01

    A short review of the currently available modern parton distribution functions (PDFs)and the theory predictions obtained using those PDFs for several benchmark processes at LHC, including Higgs boson production, is presented in this write-up. It includes the discussion on theory assumptions made in the determination procedure of PDFs and an impact on the differences in the obtained predictions, followed by the alternative to PDF4LHC recommendations for the usage of PDF sets for theory predictions at the LHC.

  13. 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 ...

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. The U.S. Earthquake Prediction Program

    Science.gov (United States)

    Wesson, R.L.; Filson, J.R.

    1981-01-01

    Following on from the concepts of plate tectonics, the earth sciences are now embarking on a challenging course- the time prediction of geologic phenomena. Earthquake prediction is an outstanding example of this. However, earthquake prediction is not the only scientific goal. The destructive power of a large earthquake requires that we also take mitigating actions; these include earthquake engineering research to design construction that will resist earthquake shaking. Nevertheless, earthquake prediction has a vital role to play not only in the saving of lives, but in the reduction of economic loss and social disruption from large earthquakes.

  19. Theoretical prediction of crystal structures of rubrene

    Science.gov (United States)

    Obata, Shigeaki; Miura, Toshiaki; Shimoi, Yukihiro

    2014-01-01

    We theoretically predict crystal structures and molecular arrangements for rubrene molecule using CONFLEX program and compare them with the experimental ones. The most, second-most, and fourth-most stable predicted crystal structures show good agreement with the triclinic, orthorhombic, and monoclinic polymorphs of rubrene, respectively. The change in molecular conformation is also predicted between crystalline and gas phases: the tetracene backbone takes flat conformation in crystalline phase as in the observed structure. Meanwhile, it is twisted in gas phase. The theoretical prediction method used in this work provides the successful results on the determination of the three kinds of crystal structures and molecular arrangements for rubrene molecule.

  20. 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.

  1. 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....

  2. 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.

  3. 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...

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. Initial value predictability of intrinsic oceanic modes and implications for decadal prediction over North America

    Energy Technology Data Exchange (ETDEWEB)

    Branstator, Grant [National Center for Atmospheric Research, Boulder, CO (United States)

    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 art climate 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 the 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

  9. 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

  10. 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...

  11. Efficient marker data utilization in genomic prediction

    DEFF Research Database (Denmark)

    Edriss, Vahid

    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...

  12. Predictability in models of the atmospheric circulation.

    NARCIS (Netherlands)

    Houtekamer, P.L.

    1992-01-01

    It will be clear from the above discussions that skill forecasts are still in their infancy. Operational skill predictions do not exist. One is still struggling to prove that skill predictions, at any range, have any quality at all. It is not clear what the statistics of the analysis error are. The

  13. 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

  14. 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.

  15. 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......-varying economic uncertainty and changes in risk aversion, or market fears, respectively....

  16. Prediction of treatment response to adalimumab

    DEFF Research Database (Denmark)

    Krintel, Sophine 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...

  17. 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...

  18. 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)

  19. Asset Pricing Restrictions on Predictability : Frictions Matter

    NARCIS (Netherlands)

    F.A. de Roon (Frans); M. Szymanowska (Marta)

    2011-01-01

    textabstractU.S. stock portfolios sorted on size, momentum, transaction costs, M/B, I/A and ROA ratios, and industry classi…cation show considerable levels and variation of return predictability, inconsistent with asset pricing models. This means that a predictable risk premium is not equal to compe

  20. 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

  1. 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 a...

  2. Differential Prediction Generalization in College Admissions Testing

    Science.gov (United States)

    Aguinis, Herman; Culpepper, Steven A.; Pierce, Charles A.

    2016-01-01

    We introduce the concept of "differential prediction generalization" in the context of college admissions testing. Specifically, we assess the extent to which predicted first-year college grade point average (GPA) based on high-school grade point average (HSGPA) and SAT scores depends on a student's ethnicity and gender and whether this…

  3. Prediction of Railway Passenger Traffic Volume

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The current situation of the railway passenger traffic (RPT) andthe traffic marketing is analyzed. The grey model theory is adopted to establish a prediction model for the railway passenger traffic volume (RPTV). The RPTV from 2001 to 2005 is predicted with the proposed model, and a few suggestions are put forward.

  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. Prediction in ungauged estuaries: An integrated theory

    NARCIS (Netherlands)

    Savenije, H.H.G.

    2015-01-01

    Many estuaries in the world are ungauged. The International Association of Hydrological Sciences completed its science decade on Prediction in Ungauged Basins (PUB) in 2012 (Hrachowitz et al., 2013). Prediction on the basis of limited data is a challenge in hydrology, but not less so in estuaries, w

  6. Fuzzy Predictions for Strategic Decision Making

    DEFF Research Database (Denmark)

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

    This article theorizes a new way to predict firm performance based on aggregation of sensing among frontline employees about changes in operational capabilities to update strategic action plans. We frame the approach in the context of first- and second-generation prediction markets and outline its...

  7. 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...

  8. The Real World Significance of Performance Prediction

    Science.gov (United States)

    Pardos, Zachary A.; Wang, Qing Yang; Trivedi, Shubhendu

    2012-01-01

    In recent years, the educational data mining and user modeling communities have been aggressively introducing models for predicting student performance on external measures such as standardized tests as well as within-tutor performance. While these models have brought statistically reliable improvement to performance prediction, the real world…

  9. 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.

  10. 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

  11. Evolution of property predictability during conceptual design

    DEFF Research Database (Denmark)

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

    2005-01-01

    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...

  12. Evolution of property predictability during conceptual design

    DEFF Research Database (Denmark)

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

    2005-01-01

    on 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...

  13. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  14. Emotional intelligence predicts success in medical school.

    Science.gov (United States)

    Libbrecht, Nele; Lievens, Filip; Carette, Bernd; Côté, Stéphane

    2014-02-01

    Accumulating evidence suggests that effective communication and interpersonal sensitivity during interactions between doctors and patients impact therapeutic outcomes. There is an important need to identify predictors of these behaviors, because traditional tests used in medical admissions offer limited predictions of "bedside manners" in medical practice. This study examined whether emotional intelligence would predict the performance of 367 medical students in medical school courses on communication and interpersonal sensitivity. One of the dimensions of emotional intelligence, the ability to regulate emotions, predicted performance in courses on communication and interpersonal sensitivity over the next 3 years of medical school, over and above cognitive ability and conscientiousness. Emotional intelligence did not predict performance on courses on medical subject domains. The results suggest that medical schools may better predict who will communicate effectively and show interpersonal sensitivity if they include measures of emotional intelligence in their admission systems. PMID:24219393

  15. Predictability Horizon of Oceanic Rogue Waves

    CERN Document Server

    Alam, Reza

    2014-01-01

    Prediction is a central goal and a yet-unresolved challenge in the investigation of oceanic rogue waves. Here we define a horizon of predictability for oceanic rogue waves and derive, via extensive computational experiments, the first statistically-converged predictability time-scale for these structures. We show that this time-scale is a function of the sea state as well as the strength (i.e. overall height) of the expected rogue wave. The presented predictability time-scale establishes a quantitative metric on the combined temporal effect of the variety of mechanisms that together lead to the formation of a rogue wave, and is crucial for the assessment of validity of rogue waves predictions, as well as for the critical evaluation of results from the widely-used model equations. The methodology and presented results can have similar implications in other systems admitting rogue waves, e.g. nonlinear optics and plasma physics.

  16. Community Detection Based on Link Prediction Methods

    CERN Document Server

    Cheng, Hui-Min

    2016-01-01

    Community detection and link prediction are both of great significance in network analysis, which provide very valuable insights into topological structures of the network from diffrent perspectives. In this paper, we propose a novel community detection algorithm with inclusion of link prediction, motivated by the question whether link prediction can be devoted to improve the accuracy of community partition. For link prediction, we propose two novel indices to compute the similarity between each pair of nodes, one of which aims to add missing links, and the other tries to remove spurious edges. Extensive experiments are conducted on benchmark data sets, and the results of our proposed algorithm are compared with two classes of baselines. In conclusion, our proposed algorithm is competitive, revealing that link prediction does improve the precision of community detection.

  17. Hybrid Predictive Control for Dynamic Transport Problems

    CERN Document Server

    Núñez, Alfredo A; Cortés, Cristián E

    2013-01-01

    Hybrid Predictive Control for Dynamic Transport Problems develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from the area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed-integer optimization problems dynamically, is readily extendable to other industrial processes. The main topics of this book are: ●hybrid predictive control (HPC) ...

  18. Predicting the duration of the Syrian insurgency

    Directory of Open Access Journals (Sweden)

    Ulrich Pilster

    2014-08-01

    Full Text Available While there were several relatively short uprisings in Northern Africa and the Middle East during the Arab Spring, the dispute between the rebels and government forces in Syria has evolved into a full-scale civil war. We try to predict the length of the Syrian insurgency with a three-stage technique. Using out-of-sample techniques, we first assess the predictive capacity of 69 explanatory variables for insurgency duration. After determining the model with the highest predictive power, we categorize Syria according to the variables in this final model. Based on in-sample approaches, we then predict the duration of the Syrian uprising for three different scenarios. The most realistic point prediction is 5.12 years from the insurgency’s start, which suggests an end date between the end of 2016 and early 2017.

  19. Greatly improving consensus performance via predictive mechanism

    CERN Document Server

    Zhang, Hai-Tao; Chen, Michael ZhiQiang; Zhou, Tao

    2007-01-01

    An important natural phenomenon surfaces that ultrafast consensus can be achieved by introducing the predictive mechanism. By predicting the dynamics of the network several steps ahead and using this information in the design of the consensus protocol of each agent, it is shown that drastic improvement can be achieved in terms of the speed of convergence towards consensus without changing the topology of the network. Moreover, with the predictive mechanism, the range of sampling rates leading to consensus convergence is broadly expanded compared to the routine consensus protocol. In natural science, this study provides support for the idea that some predictive mechanisms exist in widely-spread biological swarms, flocks, and schools. From the industrial engineering point of view, inclusion of an efficient predictive mechanism allows for not only a significant increase in the speed of convergence toward consensus but also a reduction of the communication energy required to achieve a predefined consensus perform...

  20. Customer Churn Prediction for Broadband Internet Services

    Science.gov (United States)

    Huang, B. Q.; Kechadi, M.-T.; Buckley, B.

    Although churn prediction has been an area of research in the voice branch of telecommunications services, more focused studies on the huge growth area of Broadband Internet services are limited. Therefore, this paper presents a new set of features for broadband Internet customer churn prediction, based on Henley segments, the broadband usage, dial types, the spend of dial-up, line-information, bill and payment information, account information. Then the four prediction techniques (Logistic Regressions, Decision Trees, Multilayer Perceptron Neural Networks and Support Vector Machines) are applied in customer churn, based on the new features. Finally, the evaluation of new features and a comparative analysis of the predictors are made for broadband customer churn prediction. The experimental results show that the new features with these four modelling techniques are efficient for customer churn prediction in the broadband service field.

  1. Bounded link prediction for very large networks

    CERN Document Server

    Cui, Wei; Xu, Zhongqi

    2015-01-01

    Evaluation of link prediction methods is a hard task in very large complex networks because of the inhibitive computational cost. By setting a lower bound of the number of common neighbors (CN), we propose a new framework to efficiently and precisely evaluate the performances of CN-based similarity indices in link prediction for very large heterogeneous networks. Specifically, we propose a fast algorithm based on the parallel computing scheme to obtain all the node pairs with CN values larger than the lower bound. Furthermore, we propose a new measurement, called self-predictability, to quantify the performance of the CN-based similarity indices in link prediction, which on the other side can indicate the link predictability of a network.

  2. Decadal climate predictions using sequential learning algorithms

    CERN Document Server

    Strobach, Ehud

    2015-01-01

    Ensembles of climate models are commonly used to improve climate predictions and assess the uncertainties associated with them. Weighting the models according to their performances holds the promise of further improving their predictions. Here, we use an ensemble of decadal climate predictions to demonstrate the ability of sequential learning algorithms (SLAs) to reduce the forecast errors and reduce the uncertainties. Three different SLAs are considered, and their performances are compared with those of an equally weighted ensemble, a linear regression and the climatology. Predictions of four different variables--the surface temperature, the zonal and meridional wind, and pressure--are considered. The spatial distributions of the performances are presented, and the statistical significance of the improvements achieved by the SLAs is tested. Based on the performances of the SLAs, we propose one to be highly suitable for the improvement of decadal climate predictions.

  3. Bounded link prediction in very large networks

    Science.gov (United States)

    Cui, Wei; Pu, Cunlai; Xu, Zhongqi; Cai, Shimin; Yang, Jian; Michaelson, Andrew

    2016-09-01

    Evaluating link prediction methods is a hard task in very large complex networks due to the prohibitive computational cost. However, if we consider the lower bound of node pairs' similarity scores, this task can be greatly optimized. In this paper, we study CN index in the bounded link prediction framework, which is applicable to enormous heterogeneous networks. Specifically, we propose a fast algorithm based on the parallel computing scheme to obtain all node pairs with CN values larger than the lower bound. Furthermore, we propose a general measurement, called self-predictability, to quantify the performance of similarity indices in link prediction, which can also indicate the link predictability of networks with respect to given similarity indices.

  4. Emotional intelligence predicts success in medical school.

    Science.gov (United States)

    Libbrecht, Nele; Lievens, Filip; Carette, Bernd; Côté, Stéphane

    2014-02-01

    Accumulating evidence suggests that effective communication and interpersonal sensitivity during interactions between doctors and patients impact therapeutic outcomes. There is an important need to identify predictors of these behaviors, because traditional tests used in medical admissions offer limited predictions of "bedside manners" in medical practice. This study examined whether emotional intelligence would predict the performance of 367 medical students in medical school courses on communication and interpersonal sensitivity. One of the dimensions of emotional intelligence, the ability to regulate emotions, predicted performance in courses on communication and interpersonal sensitivity over the next 3 years of medical school, over and above cognitive ability and conscientiousness. Emotional intelligence did not predict performance on courses on medical subject domains. The results suggest that medical schools may better predict who will communicate effectively and show interpersonal sensitivity if they include measures of emotional intelligence in their admission systems.

  5. Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

    Directory of Open Access Journals (Sweden)

    Yagang Zhang

    2015-01-01

    Full Text Available This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind speed predictions. Finally we separately use the original and improved wind speed series to predict the related wind power. This proves that the corrected wind speed provides higher precision wind power predictions. This research presents a totally new direction in the wind prediction field and has profound theoretical research value and practical guiding significance.

  6. Massive Predictive Modeling using Oracle R Enterprise

    CERN Document Server

    CERN. Geneva

    2014-01-01

    R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...

  7. Machine learning methods for metabolic pathway prediction

    Directory of Open Access Journals (Sweden)

    Karp Peter D

    2010-01-01

    Full Text Available Abstract Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations.

  8. Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models

    Directory of Open Access Journals (Sweden)

    David Ebert

    2006-08-01

    Full Text Available One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created are then compared to a traditional predictive model.

  9. Dynamical functional prediction and classification, with application to traffic flow prediction

    OpenAIRE

    Chiou, Jeng-Min

    2013-01-01

    Motivated by the need for accurate traffic flow prediction in transportation management, we propose a functional data method to analyze traffic flow patterns and predict future traffic flow. In this study we approach the problem by sampling traffic flow trajectories from a mixture of stochastic processes. The proposed functional mixture prediction approach combines functional prediction with probabilistic functional classification to take distinct traffic flow patterns into account. The proba...

  10. The Residual-based Predictiveness Curve - A Visual Tool to Assess the Performance of Prediction Models

    OpenAIRE

    Casalicchio, Giuseppe; Bischl, Bernd; Boulesteix, Anne-Laure; Schmid, Matthias

    2015-01-01

    It is agreed among biostatisticians that prediction models for binary outcomes should satisfy two essential criteria: First, a prediction model should have a high discriminatory power, implying that it is able to clearly separate cases from controls. Second, the model should be well calibrated, meaning that the predicted risks should closely agree with the relative frequencies observed in the data. The focus of this work is on the predictiveness curve, which has been proposed by Huang et ...

  11. DPRESS: Localizing estimates of predictive uncertainty

    Directory of Open Access Journals (Sweden)

    Clark Robert D

    2009-07-01

    Full Text Available Abstract Background The need to have a quantitative estimate of the uncertainty of prediction for QSAR models is steadily increasing, in part because such predictions are being widely distributed as tabulated values disconnected from the models used to generate them. Classical statistical theory assumes that the error in the population being modeled is independent and identically distributed (IID, but this is often not actually the case. Such inhomogeneous error (heteroskedasticity can be addressed by providing an individualized estimate of predictive uncertainty for each particular new object u: the standard error of prediction su can be estimated as the non-cross-validated error st* for the closest object t* in the training set adjusted for its separation d from u in the descriptor space relative to the size of the training set. The predictive uncertainty factor γt* is obtained by distributing the internal predictive error sum of squares across objects in the training set based on the distances between them, hence the acronym: Distributed PRedictive Error Sum of Squares (DPRESS. Note that st* and γt*are characteristic of each training set compound contributing to the model of interest. Results The method was applied to partial least-squares models built using 2D (molecular hologram or 3D (molecular field descriptors applied to mid-sized training sets (N = 75 drawn from a large (N = 304, well-characterized pool of cyclooxygenase inhibitors. The observed variation in predictive error for the external 229 compound test sets was compared with the uncertainty estimates from DPRESS. Good qualitative and quantitative agreement was seen between the distributions of predictive error observed and those predicted using DPRESS. Inclusion of the distance-dependent term was essential to getting good agreement between the estimated uncertainties and the observed distributions of predictive error. The uncertainty estimates derived by DPRESS were

  12. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  13. Childhood asthma prediction models: a systematic review.

    Science.gov (United States)

    Smit, Henriette A; Pinart, Mariona; Antó, Josep M; Keil, Thomas; Bousquet, Jean; Carlsen, Kai H; Moons, Karel G M; Hooft, Lotty; Carlsen, Karin C Lødrup

    2015-12-01

    Early identification of children at risk of developing asthma at school age is crucial, but the usefulness of childhood asthma prediction models in clinical practice is still unclear. We systematically reviewed all existing prediction models to identify preschool children with asthma-like symptoms at risk of developing asthma at school age. Studies were included if they developed a new prediction model or updated an existing model in children aged 4 years or younger with asthma-like symptoms, with assessment of asthma done between 6 and 12 years of age. 12 prediction models were identified in four types of cohorts of preschool children: those with health-care visits, those with parent-reported symptoms, those at high risk of asthma, or children in the general population. Four basic models included non-invasive, easy-to-obtain predictors only, notably family history, allergic disease comorbidities or precursors of asthma, and severity of early symptoms. Eight extended models included additional clinical tests, mostly specific IgE determination. Some models could better predict asthma development and other models could better rule out asthma development, but the predictive performance of no single model stood out in both aspects simultaneously. This finding suggests that there is a large proportion of preschool children with wheeze for which prediction of asthma development is difficult.

  14. Predicting community composition from pairwise interactions

    Science.gov (United States)

    Friedman, Jonathan; Higgins, Logan; Gore, Jeff

    The ability to predict the structure of complex, multispecies communities is crucial for understanding the impact of species extinction and invasion on natural communities, as well as for engineering novel, synthetic communities. Communities are often modeled using phenomenological models, such as the classical generalized Lotka-Volterra (gLV) model. While a lot of our intuition comes from such models, their predictive power has rarely been tested experimentally. To directly assess the predictive power of this approach, we constructed synthetic communities comprised of up to 8 soil bacteria. We measured the outcome of competition between all species pairs, and used these measurements to predict the composition of communities composed of more than 2 species. The pairwise competitions resulted in a diverse set of outcomes, including coexistence, exclusion, and bistability, and displayed evidence for both interference and facilitation. Most pair outcomes could be captured by the gLV framework, and the composition of multispecies communities could be predicted for communities composed solely of such pairs. Our results demonstrate the predictive ability and utility of simple phenomenology, which enables accurate predictions in the absence of mechanistic details.

  15. COMBINING CLASSIFIERS FOR CREDIT RISK PREDICTION

    Institute of Scientific and Technical Information of China (English)

    Bhekisipho TWALA

    2009-01-01

    Credit risk prediction models seek to predict quality factors such as whether an individual will default (bad applicant) on a loan or not (good applicant). This can be treated as a kind of machine learning (ML) problem. Recently, the use of ML algorithms has proven to be of great practical value in solving a variety of risk problems including credit risk prediction. One of the most active areas of recent research in ML has been the use of ensemble (combining) classifiers. Research indicates that ensemble individual classifiers lead to a significant improvement in classification performance by having them vote for the most popular class. This paper explores the predicted behaviour of five classifiers for different types of noise in terms of credit risk prediction accuracy, and how could such accuracy be improved by using pairs of classifier ensembles. Benchmarking results on five credit datasets and comparison with the performance of each individual classifier on predictive accuracy at various attribute noise levels are presented. The experimental evaluation shows that the ensemble of classifiers technique has the potential to improve prediction accuracy.

  16. Body size prediction from juvenile skeletal remains.

    Science.gov (United States)

    Ruff, Christopher

    2007-05-01

    There are currently no methods for predicting body mass from juvenile skeletal remains and only a very limited number for predicting stature. In this study, stature and body mass prediction equations are generated for each year from 1 to 17 years of age using a subset of the Denver Growth Study sample, followed longitudinally (n = 20 individuals, 340 observations). Radiographic measurements of femoral distal metaphyseal and head breadth are used to predict body mass and long bone lengths are used to predict stature. In addition, pelvic bi-iliac breadth and long bone lengths are used to predict body mass in older adolescents. Relative prediction errors are equal to or smaller than those associated with similar adult estimation formulae. Body proportions change continuously throughout growth, necessitating age-specific formulae. Adult formulae overestimate stature and body mass in younger juveniles, but work well in 17-year-olds from the sample, indicating that in terms of body proportions they are representative of the general population. To illustrate use of the techniques, they are applied to the juvenile Homo erectus (ergaster) KNM-WT 15000 skeleton. New body mass and stature estimates for this specimen are similar to previous estimates derived using other methods. Body mass estimates range from 50 to 53 kg, and stature was probably slightly under 157 cm, although a precise stature estimate is difficult to determine due to differences in linear body proportions between KNM-WT 15000 and the Denver reference sample. PMID:17295297

  17. Predicting intrinsic disorder in proteins: an overview

    Institute of Scientific and Technical Information of China (English)

    Bo He; Kejun Wang; Yunlong Liu; Bin Xue; Vladimir N Uversky; A Keith Dunker

    2009-01-01

    The discovery of intrinsically disordered proteins IDP I.e., biologically active proteins that do not possess stable secondary and/or tertiary structures came as an unexpected surprise, as the existence of such proteins is in contradiction to the traditional "sequence---,structure--,function" paradigm. Accurate prediction of a protein's predisposition to be intrinsically disordered is a necessary prerequisite for the further understanding of principles and mechanisms of protein folding and function, and is a key for the elaboration of a new structural and functional hierarchy of proteins. Therefore, prediction of IDPs has attracted the attention of many researchers, and a number of prediction tools have been developed. Predictions of disorder, in turn, are playing major roles in directing labora-tory experiments that are leading to the discovery of ever more disordered proteins, and thereby leading to a positive feedback loop in the investigation of these proteins, in this review of algorithms for intrinsic disorder prediction, the basic concepts of various prediction methods for IDPs are summarized, the strengths and shortcomings of many of the methods are analyzed, and the difficulties and directions of future development of IDP prediction techniques are discussed.

  18. Correction of deposition predictions with data assimilation

    International Nuclear Information System (INIS)

    Model predictions for rapid assessment and prognosis of possible radiological consequences after an accidental release of radionuclides play an important role in nuclear emergency management. Radiological measurements (e. g., dose rate measurements) can be used to improve such model predictions. This paper describes a method for combining model predictions and measurements (data assimilation) in the deposition model of the European radiological decision support system RODOS. The data assimilation approach is based on the Ensemble Kalman Filter, a Monte Carlo variant of the Kalman filter. (orig.)

  19. Generalised empirical method for predicting surface subsidence

    International Nuclear Information System (INIS)

    Based on a simplified strata parameter, i.e. the ratio of total thickness of the strong rock beds in an overburden to the overall thickness of the overburden, a Generalised Empirical Method (GEM) is described for predicting the maximum subsidence and the shape of a complete transverse subsidence profile due to a single completely extracted longwall panel. In the method, a nomogram for predicting the maximum surface subsidence is first developed from the data collected from subsidence measurements worldwide. Then, a method is developed for predicting the shapes of complete transfer subsidence profiles for a horizontal seam and ground surface and is verified by case studies. 13 refs., 9 figs., 2 tabs

  20. Predicting Dyspnea Inducers by Molecular Topology

    Directory of Open Access Journals (Sweden)

    María Gálvez-Llompart

    2013-01-01

    Full Text Available QSAR based on molecular topology (MT is an excellent methodology used in predicting physicochemical and biological properties of compounds. This approach is applied here for the development of a mathematical model capable to recognize drugs showing dyspnea as a side effect. Using linear discriminant analysis, it was found a four-variable regression equations enabling a predictive rate of about 81% and 73% in the training and test sets of compounds, respectively. These results demonstrate that QSAR-MT is an efficient tool to predict the appearance of dyspnea associated with drug consumption.

  1. Link prediction in complex networks: A survey

    Science.gov (United States)

    Lü, Linyuan; Zhou, Tao

    2011-03-01

    Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labeled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.

  2. Predictive Navigation by Understanding Human Motion Patterns

    Directory of Open Access Journals (Sweden)

    Shu-Yun Chung

    2011-03-01

    Full Text Available To make robots coexist and share the environments with humans, robots should understand the behaviors or the intentions of humans and further predict their motions. In this paper, an A*-based predictive motion planner is represented for navigation tasks. A generalized pedestrian motion model is proposed and trained by the statistical learning method. To deal with the uncertainty, a localization, tracking and prediction framework is also introduced. The corresponding recursive Bayesian formula represented as DBNs (Dynamic Bayesian Networks is derived for real time operation. Finally, the simulations and experiments are shown to validate the idea of this paper.

  3. ACHIEVING BETTER UNDERSTANDING BY LISTENING WITH PREDICTION

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The skill of Listening with comprehension is anessential part of communication and basic to ESL/EFL learning.Prediction is also a key process in un-derstanding spoken language.This article intends tooffer a definition for prediction in ESL/EFL listening,examines its foundations,draws some insights into itsnature,and illustrates how to develop and employprediction in pre-listening and while-listening stages,also how to‘repair’prediction in the post-listeningstage,in an attempt to help listeners achieve the goalof better understanding.

  4. U.S.-Japan Quake Prediction Research

    OpenAIRE

    Kisslinger, Carl; Mikumo, Takeshi; Kanamori, Hiroo

    1988-01-01

    For the seventh time since 1964, a seminar on earthquake prediction has been convened under the U.S.-Japan Cooperation in Science Program. The purpose of the seminar was to provide an opportunity for researchers from the two countries to share recent progress and future plans in the continuing effort to develop the scientific basis for predicting earthquakes and practical means for implementing prediction technology as it emerges. Thirty-six contributors, 15 from Japan and 21 from the U.S., m...

  5. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    in the theoretical predictive equation by suggesting a data generating process, where returns are generated as linear functions of a lagged latent I(0) risk process. The observed predictor is a function of this latent I(0) process, but it is corrupted by a fractionally integrated noise. Such a process may arise due...... an instrumental variable approach and discuss issues of validity and relevance. Applying the procedure to the prediction of daily returns on the S&P 500, our empirical analysis confirms return predictability and a positive risk-return trade-off....

  6. Calorimeter prediction based on multiple exponentials

    Energy Technology Data Exchange (ETDEWEB)

    Smith, M.K. E-mail: mks@lanl.gov; Bracken, D.S

    2002-05-21

    Calorimetry allows very precise measurements of nuclear material to be carried out, but it also requires relatively long measurement times to do so. The ability to accurately predict the equilibrium response of a calorimeter would significantly reduce the amount of time required for calorimetric assays. An algorithm has been developed that is effective at predicting the equilibrium response. This multi-exponential prediction algorithm is based on an iterative technique using commercial fitting routines that fit a constant plus a variable number of exponential terms to calorimeter data. Details of the implementation and the results of trials on a large number of calorimeter data sets will be presented.

  7. Calorimeter prediction based on multiple exponentials

    International Nuclear Information System (INIS)

    Calorimetry allows very precise measurements of nuclear material to be carried out, but it also requires relatively long measurement times to do so. The ability to accurately predict the equilibrium response of a calorimeter would significantly reduce the amount of time required for calorimetric assays. An algorithm has been developed that is effective at predicting the equilibrium response. This multi-exponential prediction algorithm is based on an iterative technique using commercial fitting routines that fit a constant plus a variable number of exponential terms to calorimeter data. Details of the implementation and the results of trials on a large number of calorimeter data sets will be presented

  8. Calorimeter prediction based on multiple exponentials

    CERN Document Server

    Smith, M K

    2002-01-01

    Calorimetry allows very precise measurements of nuclear material to be carried out, but it also requires relatively long measurement times to do so. The ability to accurately predict the equilibrium response of a calorimeter would significantly reduce the amount of time required for calorimetric assays. An algorithm has been developed that is effective at predicting the equilibrium response. This multi-exponential prediction algorithm is based on an iterative technique using commercial fitting routines that fit a constant plus a variable number of exponential terms to calorimeter data. Details of the implementation and the results of trials on a large number of calorimeter data sets will be presented.

  9. Trust-based collective view prediction

    CERN Document Server

    Luo, Tiejian; Xu, Guandong; Zhou, Jia

    2013-01-01

    Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users' past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View

  10. The devil is in the specificity: the negative effect of prediction specificity on prediction accuracy.

    Science.gov (United States)

    Yoon, Song-Oh; Suk, Kwanho; Goo, Jin Kyung; Lee, Jiheon; Lee, Seon Min

    2013-07-01

    In the research reported here, we proposed and demonstrated the prediction-specificity effect, which states that people's prediction of the general outcome of an event (e.g., the winner of a soccer match) is less accurate when the prediction question is framed in a more specific manner (e.g., guessing the score) rather than in a less specific manner (e.g., guessing the winner). We demonstrated this effect by examining people's predictions on actual sports games both in field and laboratory studies. In Study 1, the analysis of 19 billion bets from a commercial sports-betting business provided evidence for the effect of prediction specificity. This effect was replicated in three controlled laboratory studies, in which participants predicted the outcomes of a series of soccer matches. Furthermore, the negative effect of prediction specificity was mediated by participants' underweighting of important holistic information during decision making. PMID:23660410

  11. Echo state network prediction method and its application in flue gas turbine condition prediction

    Science.gov (United States)

    Wang, Shaohong; Chen, Tao; Xu, Xiaoli

    2010-12-01

    On the background of the complex production process of fluid catalytic cracking energy recovery system in large-scale petrochemical refineries, this paper introduced an improved echo state network (ESN) model prediction method which is used to address the condition trend prediction problem of the key power equipment--flue gas turbine. Singular value decomposition method was used to obtain the ESN output weight. Through selecting the appropriate parameters and discarding small singular value, this method overcame the defective solution problem in the prediction by using the linear regression algorithm, improved the prediction performance of echo state network, and gave the network prediction process. In order to solve the problem of noise contained in production data, the translation-invariant wavelet transform analysis method is combined to denoise the noisy time series before prediction. Condition trend prediction results show the effectiveness of the proposed method.

  12. The devil is in the specificity: the negative effect of prediction specificity on prediction accuracy.

    Science.gov (United States)

    Yoon, Song-Oh; Suk, Kwanho; Goo, Jin Kyung; Lee, Jiheon; Lee, Seon Min

    2013-07-01

    In the research reported here, we proposed and demonstrated the prediction-specificity effect, which states that people's prediction of the general outcome of an event (e.g., the winner of a soccer match) is less accurate when the prediction question is framed in a more specific manner (e.g., guessing the score) rather than in a less specific manner (e.g., guessing the winner). We demonstrated this effect by examining people's predictions on actual sports games both in field and laboratory studies. In Study 1, the analysis of 19 billion bets from a commercial sports-betting business provided evidence for the effect of prediction specificity. This effect was replicated in three controlled laboratory studies, in which participants predicted the outcomes of a series of soccer matches. Furthermore, the negative effect of prediction specificity was mediated by participants' underweighting of important holistic information during decision making.

  13. The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing.

    Directory of Open Access Journals (Sweden)

    Kirsten Weber

    Full Text Available Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions-a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in

  14. The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing.

    Science.gov (United States)

    Weber, Kirsten; Lau, Ellen F; Stillerman, Benjamin; Kuperberg, Gina R

    2016-01-01

    Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower) predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower) predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower) predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions-a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in response to the

  15. Predicting missing links via correlation between nodes

    CERN Document Server

    Liao, Hao; Zhang, Yi-Cheng

    2014-01-01

    As a fundamental problem in many different fields, link prediction aims to estimate the likelihood of an existing link between two nodes based on the observed information. Since this problem is related to many applications ranging from uncovering missing data to predicting the evolution of networks, link prediction has been intensively investigated recently and many methods have been proposed so far. The essential challenge of link prediction is to estimate the similarity between nodes. Most of the existing methods are based on the common neighbor index and its variants. In this paper, we propose to calculate the similarity between nodes by the correlation coefficient. This method is found to be very effective when applied to calculate similarity based on high order paths. We finally fuse the correlation-based method with the resource allocation method, and find that the combined method can substantially outperform the existing methods, especially in sparse networks.

  16. Empirical Prediction of Aircraft Landing Gear Noise

    Science.gov (United States)

    Golub, Robert A. (Technical Monitor); Guo, Yue-Ping

    2005-01-01

    This report documents a semi-empirical/semi-analytical method for landing gear noise prediction. The method is based on scaling laws of the theory of aerodynamic noise generation and correlation of these scaling laws with current available test data. The former gives the method a sound theoretical foundation and the latter quantitatively determines the relations between the parameters of the landing gear assembly and the far field noise, enabling practical predictions of aircraft landing gear noise, both for parametric trends and for absolute noise levels. The prediction model is validated by wind tunnel test data for an isolated Boeing 737 landing gear and by flight data for the Boeing 777 airplane. In both cases, the predictions agree well with data, both in parametric trends and in absolute noise levels.

  17. Predicting growth fluctuation in network economy

    CERN Document Server

    Maeno, Yoshiharu

    2011-01-01

    This study presents a method to predict the growth fluctuation of firms interdependent in a network economy. The risk of downward growth fluctuation of firms is calculated from the statistics on Japanese industry.

  18. Speech Intelligibility Prediction Based on Mutual Information

    DEFF Research Database (Denmark)

    Jensen, Jesper; Taal, Cees H.

    2014-01-01

    This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related...... to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using...... a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting...

  19. Trend prediction of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    Li Aiguo; Zhao Cai; Li Zhanhuai

    2007-01-01

    To predict the trend of chaotic time series in time series analysis and time series data mining fields, a novel predicting algorithm of chaotic time series trend is presented, and an on-line segmenting algorithm is proposed to convert a time series into a binary string according to ascending or descending trend of each subsequence. The on-line segmenting algorithm is independent of the prior knowledge about time series. The naive Bayesian algorithm is then employed to predict the trend of chaotic time series according to the binary string. The experimental results of three chaotic time series demonstrate that the proposed method predicts the ascending or descending trend of chaotic time series with few error.

  20. LIFE PREDICTION APPROACH FOR RANDOM MULTIAXIAL FATIGUE

    Institute of Scientific and Technical Information of China (English)

    Wang Lei; Wang Dejun

    2005-01-01

    According to the concept of critical plane, a life prediction approach for random multiaxial fatigue is presented. First, the critical plane under the multiaxial random loading is determined based on the concept of the weight-averaged maximum shear strain direction. Then the shear and normal strain histories on the determined critical plane are calculated and taken as the subject of multiaxial load simplifying and multiaxial cycle counting. Furthermore, a multiaxial fatigue life prediction model including the parameters resulted from multiaxial cycle counting is presented and applied to calculating the fatigue damage generated from each cycle. Finally, the cumulative damage is added up using Miner's linear rule, and the fatigue prediction life is given. The experiments under multiaxial loading blocks are used for the verification of the proposed method. The prediction has a good correction with the experimental results.