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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. Probing Embryonic Stem Cell Autocrine and Paracrine Signaling Using Microfluidics

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    Przybyla, Laralynne; Voldman, Joel

    2012-07-01

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

  5. 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)

  6. Autocrine and Paracrine Mechanisms Promoting Chemoresistance in Cholangiocarcinoma

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    Massimiliano Cadamuro

    2017-01-01

    Full Text Available Resistance to conventional chemotherapeutic agents, a typical feature of cholangiocarcinoma, prevents the efficacy of the therapeutic arsenal usually used to combat malignancy in humans. Mechanisms of chemoresistance by neoplastic cholangiocytes include evasion of drug-induced apoptosis mediated by autocrine and paracrine cues released in the tumor microenvironment. Here, recent evidence regarding molecular mechanisms of chemoresistance is reviewed, as well as associations between well-developed chemoresistance and activation of the cancer stem cell compartment. It is concluded that improved understanding of the complex interplay between apoptosis signaling and the promotion of cell survival represent potentially productive areas for active investigation, with the ultimate aim of encouraging future studies to unveil new, effective strategies able to overcome current limitations on treatment.

  7. Autocrine Signaling and Quorum Sensing: Extreme Ends of a Common Spectrum.

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    Doğaner, Berkalp A; Yan, Lawrence K Q; Youk, Hyun

    2016-04-01

    'Secrete-and-sense cells' can communicate by secreting a signaling molecule while also producing a receptor that detects the molecule. The cell can potentially 'talk' to itself ('self-communication') or talk to neighboring cells with the same receptor ('neighbor communication'). The predominant forms of secrete-and-sense cells are self-communicating 'autocrine cells', which are largely found in animals, and neighbor-communicating 'quorum sensing cells', which are mostly associated with bacteria. While assumed to function independently of one another, recent studies have discovered quorum-sensing organs and autocrine-signaling microbes. Moreover, similar types of genetic circuit control many autocrine and quorum-sensing cells. Here, we outline these recent findings and explain how autocrine and quorum sensing are two sides of a many-sided 'dice' created by the versatile secrete-and-sense cell.

  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

    2016-08-01

    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.

  9. 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.

  10. 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

    2016-03-01

    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.

  11. Cysteinyl leukotrienes are autocrine and paracrine regulators of fibrocyte function.

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    Vannella, Kevin M; McMillan, Tracy R; Charbeneau, Ryan P; Wilke, Carol A; Thomas, Peedikayil E; Toews, Galen B; Peters-Golden, Marc; Moore, Bethany B

    2007-12-01

    Pulmonary fibrosis is characterized by the accumulation of fibroblasts and myofibroblasts. These cells may accumulate from three potential sources: the expansion of resident lung fibroblasts, the process of epithelial-mesenchymal transition, or the recruitment and differentiation of circulating mesenchymal precursors known as fibrocytes. We have previously demonstrated that fibrocytes participate in lung fibrogenesis following administration of FITC to mice. We now demonstrate that leukotriene-deficient 5-LO(-/-) mice are protected from FITC-induced fibrosis. Both murine and human fibrocytes express both cysteinyl leukotriene receptor (CysLT) 1 and CysLT2. In addition, fibrocytes are capable of producing CysLTs and can be regulated via the autocrine or paracrine secretion of these lipid mediators. Exogenous administration of leukotriene (LT) D(4), but not LTC(4) induces proliferation of both murine and human fibrocytes in a dose-dependent manner. Consistent with this result, CysLT1 receptor antagonists are able to block the mitogenic effects of exogenous LTD(4) on fibrocytes. Endogenous production of CysLTs contributes to basal fibrocyte proliferation, but does not alter fibrocyte responses to basic fibroblast growth factor. Although CysLTs can induce the migration of fibrocytes in vitro, they do not appear to be essential for fibrocyte recruitment to the lung in vivo, possibly due to compensatory chemokine-mediated recruitment signals. However, CysLTs do appear to regulate the proliferation of fibrocytes once they are recruited to the lung. These data provide mechanistic insight into the therapeutic benefit of leukotriene synthesis inhibitors and CysLT1 receptor antagonists in animal models of fibrosis.

  12. Autocrine CCL19 blocks dendritic cell migration toward weak gradients of CCL21

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    Hansen, Morten; Met, Özcan; Larsen, Niels Bent

    2016-01-01

    the effect of autocrine CCL19 on in vitro migration of human DCs toward CCL21. Results. Using human monocyte-derived DCs in a 3D chemotaxis assay, we are the first to demonstrate that CCL19 more potently induces directed migration of human DCs compared with CCL21. When comparing migration of type 1 DCs......Background aims. Maturation of dendritic cells (DCs) induces their homing from peripheral to lymphatic tissues guided by CCL21. However, in vitro matured human monocyte-derived DC cancer vaccines injected intradermally migrate poorly to lymph nodes (LNs). In vitro maturation protocols generate DCs...... and PGE2-DCs, migration of type 1 DCs was strikingly impaired compared with PGE2-DCs, but only toward low concentrations of CCL21. When type 1 DCs were cultured overnight in fresh culture medium (reducing autocrine CCL19 levels), a rescuing effect was observed on migration toward low concentrations of CCL...

  13. Exosomes mediate stromal mobilization of autocrine Wnt-PCP signaling in breast cancer cell migration.

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    Luga, Valbona; Zhang, Liang; Viloria-Petit, Alicia M; Ogunjimi, Abiodun A; Inanlou, Mohammad R; Chiu, Elaine; Buchanan, Marguerite; Hosein, Abdel Nasser; Basik, Mark; Wrana, Jeffrey L

    2012-12-21

    Stroma in the tumor microenvironment plays a critical role in cancer progression, but how it promotes metastasis is poorly understood. Exosomes are small vesicles secreted by many cell types and enable a potent mode of intercellular communication. Here, we report that fibroblast-secreted exosomes promote breast cancer cell (BCC) protrusive activity and motility via Wnt-planar cell polarity (PCP) signaling. We show that exosome-stimulated BCC protrusions display mutually exclusive localization of the core PCP complexes, Fzd-Dvl and Vangl-Pk. In orthotopic mouse models of breast cancer, coinjection of BCCs with fibroblasts dramatically enhances metastasis that is dependent on PCP signaling in BCCs and the exosome component, Cd81 in fibroblasts. Moreover, we demonstrate that trafficking in BCCs promotes tethering of autocrine Wnt11 to fibroblast-derived exosomes. This work reveals an intercellular communication pathway whereby fibroblast exosomes mobilize autocrine Wnt-PCP signaling to drive BCC invasive behavior.

  14. Autocrine growth regulation of human glomerular mesangial cells is primarily mediated by basic fibroblast growth factor.

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    Francki, A.; Uciechowski, P.; Floege, J; von der Ohe, J.; Resch, K.; Radeke, H. H.

    1995-01-01

    For various forms of human glomerulonephritis a close relationship between inflammatory injury and a local mesangial proliferative response has been described. Herein, we used primary cultures of human glomerular mesangial cells (HMCs) from five different donors to determine the autocrine growth-inducing capacity of their supernatants after stimulation with different cytokines and lipopolysaccharide (LPS) to determine whether this effect is due to basic fibroblast growth factor (bFGF). The ba...

  15. Laminins promote postsynaptic maturation by an autocrine mechanism at the neuromuscular junction

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    Nishimune, Hiroshi; Jarad, George; Moulson, Casey L.; Müller, Ulrich; Miner, Jeffrey H.; Valdez, Gregorio; Sanes, Joshua R

    2008-01-01

    A prominent feature of synaptic maturation at the neuromuscular junction (NMJ) is the topological transformation of the acetylcholine receptor (AChR)-rich postsynaptic membrane from an ovoid plaque into a complex array of branches. We show here that laminins play an autocrine role in promoting this transformation. Laminins containing the α4, α5, and β2 subunits are synthesized by muscle fibers and concentrated in the small portion of the basal lamina that passes through the synaptic cleft at ...

  16. Autocrine extracellular purinergic signaling in epithelial cells derived from polycystic kidneys.

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    Schwiebert, Erik M; Wallace, Darren P; Braunstein, Gavin M; King, Sandi R; Peti-Peterdi, Janos; Hanaoka, Kazushige; Guggino, William B; Guay-Woodford, Lisa M; Bell, P Darwin; Sullivan, Lawrence P; Grantham, Jared J; Taylor, Amanda L

    2002-04-01

    ATP and its metabolites are potent autocrine agonists that act extracellularly within tissues to affect epithelial function. In polycystic kidneys, renal tubules become dilated and/or encapsulated as cysts, creating abnormal microenvironments for autocrine signaling. Previously, our laboratory has shown that high-nanomolar to micromolar quantities of ATP are released from cell monolayers in vitro and detectable in cyst fluids from microdissected human autosomal dominant polycystic kidney (ADPKD) cysts. Here, we show enhanced ATP release from autosomal recessive polycystic kidney (ARPKD) and ADPKD epithelial cell models. RT-PCR and immunoblotting for P2Y G protein-coupled receptors and P2X purinergic receptor channels show expression of mRNA and/or protein for multiple subtypes from both families. Assays of cytosolic Ca(2+) concentration and secretory Cl(-) transport show P2Y and P2X purinergic receptor-mediated stimulation of Cl(-) secretion via cytosolic Ca(2+)-dependent signaling. Therefore, we hypothesize that autocrine purinergic signaling may augment detrimentally cyst volume expansion in ADPKD or tubule dilation in ARPKD, accelerating disease progression.

  17. 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.

  18. 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.

  19. 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.

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

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    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.

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

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    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.

  2. 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

  3. Regulation of Dense-Core Granule Replenishment by Autocrine BMP Signalling in Drosophila Secondary Cells.

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    Redhai, Siamak; Hellberg, Josephine E E U; Wainwright, Mark; Perera, Sumeth W; Castellanos, Felix; Kroeger, Benjamin; Gandy, Carina; Leiblich, Aaron; Corrigan, Laura; Hilton, Thomas; Patel, Benjamin; Fan, Shih-Jung; Hamdy, Freddie; Goberdhan, Deborah C I; Wilson, Clive

    2016-10-01

    Regulated secretion by glands and neurons involves release of signalling molecules and enzymes selectively concentrated in dense-core granules (DCGs). Although we understand how many secretagogues stimulate DCG release, how DCG biogenesis is then accelerated to replenish the DCG pool remains poorly characterised. Here we demonstrate that each prostate-like secondary cell (SC) in the paired adult Drosophila melanogaster male accessory glands contains approximately ten large DCGs, which are loaded with the Bone Morphogenetic Protein (BMP) ligand Decapentaplegic (Dpp). These DCGs can be marked in living tissue by a glycophosphatidylinositol (GPI) lipid-anchored form of GFP. In virgin males, BMP signalling is sporadically activated by constitutive DCG secretion. Upon mating, approximately four DCGs are typically released immediately, increasing BMP signalling, primarily via an autocrine mechanism. Using inducible knockdown specifically in adult SCs, we show that secretion requires the Soluble NSF Attachment Protein, SNAP24. Furthermore, mating-dependent BMP signalling not only promotes cell growth, but is also necessary to accelerate biogenesis of new DCGs, restoring DCG number within 24 h. Our analysis therefore reveals an autocrine BMP-mediated feedback mechanism for matching DCG release to replenishment as secretion rates fluctuate, and might explain why in other disease-relevant systems, like pancreatic β-cells, BMP signalling is also implicated in the control of secretion.

  4. Autocrine glutamatergic transmission for the regulation of embryonal carcinoma stem cells.

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    Teng, Lin; Lei, Hui-Min; Sun, Fan; An, Shi-Min; Tang, Ya-Bin; Meng, Shuang; Wang, Cong-Hui; Shen, Ying; Chen, Hong-Zhuan; Zhu, Liang

    2016-08-02

    Glutamate behaves as the principal excitatory neurotransmitter in the vertebrate central nervous system and recently demonstrates intercellular signaling activities in periphery cancer cells. How the glutamatergic transmission is organized and operated in cancer stem cells remains undefined. We have identified a glutamatergic transmission circuit in embryonal carcinoma stem cells. The circuit is organized and operated in an autocrine mechanism and suppresses the cell proliferation and motility. Biological analyses determined a repertoire of glutamatergic transmission components, glutaminase, vesicular glutamate transporter, glutamate NMDA receptor, and cell membrane excitatory amino-acid transporter, for glutamate biosynthesis, package for secretion, reaction, and reuptake in mouse and human embryonal carcinoma stem cells. The glutamatergic components were also identified in mouse transplanted teratocarcinoma and in human primary teratocarcinoma tissues. Released glutamate acting as the signal was directly quantified by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Genetic and pharmacological abolishment of the endogenously released glutamate-induced tonic activation of the NMDA receptors increased the cell proliferation and motility. The finding suggests that embryonal carcinoma stem cells can be actively regulated by establishing a glutamatergic autocrine/paracrine niche via releasing and responding to the transmitter.

  5. IL-17C regulates the innate immune function of epithelial cells in an autocrine manner.

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    Ramirez-Carrozzi, Vladimir; Sambandam, Arivazhagan; Luis, Elizabeth; Lin, Zhongua; Jeet, Surinder; Lesch, Justin; Hackney, Jason; Kim, Janice; Zhou, Meijuan; Lai, Joyce; Modrusan, Zora; Sai, Tao; Lee, Wyne; Xu, Min; Caplazi, Patrick; Diehl, Lauri; de Voss, Jason; Balazs, Mercedesz; Gonzalez, Lino; Singh, Harinder; Ouyang, Wenjun; Pappu, Rajita

    2011-10-12

    Interleukin 17C (IL-17C) is a member of the IL-17 family that is selectively induced in epithelia by bacterial challenge and inflammatory stimuli. Here we show that IL-17C functioned in a unique autocrine manner, binding to a receptor complex consisting of the receptors IL-17RA and IL-17RE, which was preferentially expressed on tissue epithelial cells. IL-17C stimulated epithelial inflammatory responses, including the expression of proinflammatory cytokines, chemokines and antimicrobial peptides, which were similar to those induced by IL-17A and IL-17F. However, IL-17C was produced by distinct cellular sources, such as epithelial cells, in contrast to IL-17A, which was produced mainly by leukocytes, especially those of the T(H)17 subset of helper T cells. Whereas IL-17C promoted inflammation in an imiquimod-induced skin-inflammation model, it exerted protective functions in dextran sodium sulfate-induced colitis. Thus, IL-17C is an essential autocrine cytokine that regulates innate epithelial immune responses.

  6. Autocrine growth factors are involved in branching morphogenesis of mouse lung epithelium.

    Science.gov (United States)

    Okada, Kimiko; Noda, Masatsugu; Nogawa, Hiroyuki

    2013-01-01

    The current model for branching morphogenesis of mouse lung proposes that the epithelium bifurcates as cells pursue separate sources of fibroblast growth factor (FGF) 10, secreted from mesenchymal tissue through interactions with epithelial tissue. If so, it may be assumed that the lung epithelium will grow into a uniform, expanding ball (without branching) when uniformly exposed to a constant concentration of FGF10. To test this hypothesis, we cultured Matrigel-embedded lung epithelium explants in FGF10-supplemented medium while shaking the culture dishes. Shaking cultures with FGF10 resulted in inferior epithelial branching compared to control cultures at rest. However, this effect was unexpectedly accompanied by poor growth rather than by ball-like expansion. When using FGF1, epithelial cultures grew and branched similarly well under either culture condition. Thus, we hypothesized that FGF10 signaling must be mediated by autocrine FGFs, such as FGF1, which might easily diffuse through the culture medium in the shaking culture. Reverse transcription-polymerase chain reaction analyses showed that FGF9 as well as FGF1 were expressed in the epithelium in vivo and in FGF10-stimulated epithelium in vitro, and FGF9 induced epithelial branching at a much lower concentration than FGF10. These results suggest that FGF1 and FGF9 may mediate FGF10 signaling and induce branching in the lung epithelium via autocrine signaling.

  7. 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

  8. 'Big'-insulin-like growth factor-II signaling is an autocrine survival pathway in gastrointestinal stromal tumors.

    NARCIS (Netherlands)

    Rikhof, B.; Graaf, W.T.A. van der; Suurmeijer, A.J.H.; Doorn, J. van; Meersma, G.J.; Groenen, P.J.T.A.; Schuuring, E.M.; Meijer, C.; Jong, S. de

    2012-01-01

    New treatment targets need to be identified in gastrointestinal stromal tumors (GISTs) to extend the treatment options for patients experiencing failure with small-molecule tyrosine kinase inhibitors, such as imatinib. Insulin-like growth factor (IGF)-II acts as an autocrine factor in several tumor

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    synthesised PRL in breast cancer. We analysed the expression of PRL in human breast cancer tumours using qPCR analysis and in situ hybridization (ISH). PRL mRNA expression was very low or undetectable in the majority of samples in three cDNA arrays representing samples from 144 breast cancer patients...... and in 13 of 14 breast cancer cell lines when analysed by qPCR. In accordance, PRL expression did not reach detectable levels in any of the 19 human breast carcinomas or 5 cell lines, which were analysed using a validated ISH protocol. Two T47D-derived breast cancer cell lines were stably transfected......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...

  10. Interfollicular epidermal stem cells self-renew via autocrine Wnt signaling.

    Science.gov (United States)

    Lim, Xinhong; Tan, Si Hui; Koh, Winston Lian Chye; Chau, Rosanna Man Wah; Yan, Kelley S; Kuo, Calvin J; van Amerongen, Renée; Klein, Allon Moshe; Nusse, Roel

    2013-12-06

    The skin is a classical example of a tissue maintained by stem cells. However, the identity of the stem cells that maintain the interfollicular epidermis and the source of the signals that control their activity remain unclear. Using mouse lineage tracing and quantitative clonal analyses, we showed that the Wnt target gene Axin2 marks interfollicular epidermal stem cells. These Axin2-expressing cells constitute the majority of the basal epidermal layer, compete neutrally, and require Wnt/β-catenin signaling to proliferate. The same cells contribute robustly to wound healing, with no requirement for a quiescent stem cell subpopulation. By means of double-labeling RNA in situ hybridization in mice, we showed that the Axin2-expressing cells themselves produce Wnt signals as well as long-range secreted Wnt inhibitors, suggesting an autocrine mechanism of stem cell self-renewal.

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

    Science.gov (United States)

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

    2016-01-26

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

  12. Adiponectin action: a combination of endocrine and autocrine/paracrine effects

    Directory of Open Access Journals (Sweden)

    Gary eSweeney

    2011-11-01

    Full Text Available The widespread physiological actions of adiponectin have now been well characterized as clinical studies and work in animal models have established strong correlations between circulating adiponectin levels and various disease-related outcomes. Thus, conventional thinking attributes many of adiponectins beneficial effects to endocrine actions of adipose-derived adiponectin. However, it is now clear that several tissues can themselves produce adiponectin and there is growing evidence that locally produced adiponectin can mediate functionally important autocrine or paracrine effects. In this review article we discuss regulation of adiponectin production, its mechanism of action via receptor isoforms and signaling pathways and its principal physiological effects (ie. metabolic and cardiovascular. The role of endocrine actions of adiponectin and changes in local production of adiponectin or its receptors in whole body physiology is discussed.

  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. Chemical Hypoxia Brings to Light Altered Autocrine Sphingosine-1-Phosphate Signalling in Rheumatoid Arthritis Synovial Fibroblasts

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    Chenqi Zhao

    2015-01-01

    Full Text Available Emerging evidence suggests a role for sphingosine-1-phosphate (S1P in various aspects of rheumatoid arthritis (RA pathogenesis. In this study we compared the effect of chemical hypoxia induced by cobalt chloride (CoCl2 on the expression of S1P metabolic enzymes and cytokine/chemokine secretion in normal fibroblast-like synoviocytes (FLS and RAFLS. RAFLS incubated with CoCl2, but not S1P, produced less IL-8 and MCP-1 than normal FLS. Furthermore, incubation with the S1P2 and S1P3 receptor antagonists, JTE-013 and CAY10444, reduced CoCl2-mediated chemokine production in normal FLS but not in RAFLS. RAFLS showed lower levels of intracellular S1P and enhanced mRNA expression of S1P phosphatase 1 (SGPP1 and S1P lyase (SPL, the enzymes that are involved in intracellular S1P degradation, when compared to normal FLS. Incubation with CoCl2 decreased SGPP1 mRNA and protein and SPL mRNA as well. Inhibition of SPL enhanced CoCl2-mediated cytokine/chemokine release and restored autocrine activation of S1P2 and S1P3 receptors in RAFLS. The results suggest that the sphingolipid pathway regulating the intracellular levels of S1P is dysregulated in RAFLS and has a significant impact on cell autocrine activation by S1P. Altered sphingolipid metabolism in FLS from patients with advanced RA raises the issue of synovial cell burnout due to chronic inflammation.

  15. SDF-1α is a novel autocrine activator of platelets operating through its receptor CXCR4.

    Science.gov (United States)

    Walsh, Tony G; Harper, Matthew T; Poole, Alastair W

    2015-01-01

    Platelets store and secrete the chemokine stromal cell-derived factor (SDF)-1α upon platelet activation, but the ability of platelet-derived SDF-1α to signal in an autocrine/paracrine manner mediating functional platelet responses relevant to thrombosis and haemostasis is unknown. We sought to explore the role of platelet-derived SDF-1α and its receptors, CXCR4 and CXCR7 in facilitating platelet activation and determine the mechanism facilitating SDF-1α-mediated regulation of platelet function. Using human washed platelets, CXCR4 inhibition, but not CXCR7 blockade significantly abrogated collagen-mediated platelet aggregation, dense granule secretion and thromboxane (Tx) A2 production. Time-dependent release of SDF-1α from collagen-activated platelets supports a functional role for SDF-1α in this regard. Using an in vitro whole blood perfusion assay, collagen-induced thrombus formation was substantially reduced with CXCR4 inhibition. In washed platelets, recombinant SDF-1α in the range of 20-100 ng/mL(-1) could significantly enhance platelet aggregation responses to a threshold concentration of collagen. These enhancements were completely dependent on CXCR4, but not CXCR7, which triggered TxA2 production and dense granule secretion. Rises in cAMP were significantly blunted by SDF-1α, which could also enhance collagen-mediated Ca2+ mobilisation, both of which were mediated by CXCR4. This potentiating effect of SDF-1α primarily required TxA2 signalling acting upstream of dense granule secretion, whereas blockade of ADP signalling could only partially attenuate SDF-1α-induced platelet activation. Therefore, this study supports a potentially novel autocrine/paracrine role for platelet-derived SDF-1α during thrombosis and haemostasis, through a predominantly TxA2-dependent and ADP-independent pathway.

  16. Positive Feedback Loop of Autocrine BDNF from Microglia Causes Prolonged Microglia Activation

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    Xin Zhang

    2014-08-01

    Full Text Available Background/Aims: Microglia, which represent the immune cells of the central nervous system (CNS, have long been a subject of study in CNS disease research. Substantial evidence indicates that microglial activation functions as a strong neuro-inflammatory response in neuropathic pain, promoting the release of pro-inflammatory cytokines, such as tumor necrosis factor (TNF-α. In addition, activated microglia release brain-derived neurotrophic factor (BDNF, which acts as a powerful cytokine. In this study, we performed a series of in vitro experiments to examine whether a positive autocrine feedback loop existed between microglia-derived BDNF and subsequent microglial activation as well as the mechanisms underlying this positive feedback loop. Methods: Because ATP is a classic inducer of microglial activation, firstly, we examined ATP-activated microglia in the present study. Secondly, we used TrkB/Fc, the BDNF sequester, to eliminate the effects of endogenous BDNF. ATP-stimulated microglia without BDNF was examined. Finally, we used exogenous BDNF to further determine whether BDNF could directly activate BV2 microglia. In all experiments, to quantify BV2 microglia activation, the protein levels of CD11b, a microglial activation marker, were measured by western blot. A Transwell migration assay was used to examine microglial migration. To assess the synthesis and release of proinflammatory cytokines, western blot was used to measure BDNF synthesis, and ELISA was used to quantify TNF-α release. Results: In our present research, we have observed that ATP dramatically activates microglia, enhancing microglial migration, increasing the synthesis of BDNF and up-regulating the release of TNF-α. Microglial activation is inhibited following the sequestration of endogenous BDNF, resulting in impaired microglial migration and decreased TNF-α release. Furthermore, exogenous BDNF can also activate microglia to subsequently enhance migration and increase TNF

  17. 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.

  18. 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.

  19. Laminins promote postsynaptic maturation by an autocrine mechanism at the neuromuscular junction.

    Science.gov (United States)

    Nishimune, Hiroshi; Valdez, Gregorio; Jarad, George; Moulson, Casey L; Müller, Ulrich; Miner, Jeffrey H; Sanes, Joshua R

    2008-09-22

    A prominent feature of synaptic maturation at the neuromuscular junction (NMJ) is the topological transformation of the acetylcholine receptor (AChR)-rich postsynaptic membrane from an ovoid plaque into a complex array of branches. We show here that laminins play an autocrine role in promoting this transformation. Laminins containing the alpha4, alpha5, and beta2 subunits are synthesized by muscle fibers and concentrated in the small portion of the basal lamina that passes through the synaptic cleft at the NMJ. Topological maturation of AChR clusters was delayed in targeted mutant mice lacking laminin alpha5 and arrested in mutants lacking both alpha4 and alpha5. Analysis of chimeric laminins in vivo and of mutant myotubes cultured aneurally demonstrated that the laminins act directly on muscle cells to promote postsynaptic maturation. Immunohistochemical studies in vivo and in vitro along with analysis of targeted mutants provide evidence that laminin-dependent aggregation of dystroglycan in the postsynaptic membrane is a key step in synaptic maturation. Another synaptically concentrated laminin receptor, Bcam, is dispensable. Together with previous studies implicating laminins as organizers of presynaptic differentiation, these results show that laminins coordinate post- with presynaptic maturation.

  20. 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.

  1. 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.

  2. Autocrine abscisic acid plays a key role in quartz-induced macrophage activation.

    Science.gov (United States)

    Magnone, Mirko; Sturla, Laura; Jacchetti, Emanuela; Scarfì, Sonia; Bruzzone, Santina; Usai, Cesare; Guida, Lucrezia; Salis, Annalisa; Damonte, Gianluca; De Flora, Antonio; Zocchi, Elena

    2012-03-01

    Inhalation of quartz induces silicosis, a lung disease where alveolar macrophages release inflammatory mediators, including prostaglandin-E(2) (PGE(2)) and tumor necrosis factor α (TNF-α). Here we report the pivotal role of abscisic acid (ABA), a recently discovered human inflammatory hormone, in silica-induced activation of murine RAW264.7 macrophages and of rat alveolar macrophages (AMs). Stimulation of both RAW264.7 cells and AMs with quartz induced a significant increase of ABA release (5- and 10-fold, respectively), compared to untreated cells. In RAW264.7 cells, autocrine ABA released after quartz stimulation sequentially activates the plasma membrane receptor LANCL2 and NADPH oxidase, generating a Ca(2+) influx resulting in NFκ B nuclear translocation and PGE(2) and TNF-α release (3-, 2-, and 3.5-fold increase, respectively, compared to control, unstimulated cells). Quartz-stimulated RAW264.7 cells silenced for LANCL2 or preincubated with a monoclonal antibody against ABA show an almost complete inhibition of NFκ B nuclear translocation and PGE(2) and TNF-α release compared to controls electroporated with a scramble oligonucleotide or preincubated with an unrelated antibody. AMs showed similar early and late ABA-induced responses as RAW264.7 cells. These findings identify ABA and LANCL2 as key mediators in quartz-induced inflammation, providing possible new targets for antisilicotic therapy.

  3. 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.

  4. 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.

  5. Autocrine motility factor promotes HER2 cleavage and signaling in breast cancer cells

    Science.gov (United States)

    Kho, Dhong Hyo; Nangia-Makker, Pratima; Balan, Vitaly; Hogan, Victor; Tait, Larry; Wang, Yi; Raz, Avraham

    2013-01-01

    Trastuzumab (Herceptin®) is an effective targeted therapy in HER2 overexpressing human breast carcinoma. However, many HER2-positive patients initially or eventually become resistant to this treatment, so elucidating mechanisms of trastuzumab resistance that emerge in breast carcinoma cells is clinically important. Here we show that autocrine motility factor (AMF) binds to HER2 and induces cleavage to the ectodomain-deleted and constitutively active form p95HER2. Mechanistic investigations indicated that interaction of AMF with HER2 triggers HER2 phosphorylation and metalloprotease-mediated ectodomain shedding, activating PI3K and MAPK signaling and ablating the ability of trastuzumab to inhibit breast carcinoma cell growth. Further, we found that HER2 expression and AMF secretion were inversely related in breast carcinoma cells. Based on this evidence that AMF may contribute to HER2-mediated breast cancer progression, our findings suggest that AMF-HER2 interaction might be a novel target for therapeutic management of breast cancer patients whose disease is resistant to trastuzumab. PMID:23248119

  6. 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.

  7. Autocrine/paracrine dopamine in the salivary glands of the blacklegged tick Ixodes scapularis.

    Science.gov (United States)

    Koči, Juraj; Simo, Ladislav; Park, Yoonseong

    2014-03-01

    Dopamine (DA) is known to be the most potent activator of tick salivary secretion, which is an essential component of successful tick feeding. We examined the quantitative changes of catecholamines using a method coupling high-pressure liquid chromatography with electrochemical detection (HPLC-ECD). We also investigated the levels of catecholamines conjugated to other molecules utilising appropriate methods to hydrolyse the conjugates. Three different biological samples, salivary glands, synganglia, ovaries and haemolymph were compared, and the largest quantity of DA was detected in salivary gland extracts (up to ∼100pg/tick), supporting the hypothesis that autocrine/paracrine dopamine activates salivary secretion. Quantitative changes of catecholamines in the salivary glands over the entire blood feeding duration were examined. The amount of dopamine in the salivary glands increased until the day 5 of feeding, at which the rapid engorgement phase began. We also detected a small but significant amount of norepinephrine in the salivary glands. Interestingly, saliva collected after induction of salivary secretion by the cholinergic agonist pilocarpine contained a large amount of DA sulphate with a trace amount of DA, suggesting a potential biological role of DA sulphate in tick saliva.

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

    Directory of Open Access Journals (Sweden)

    Pan Zhongzong

    2009-01-01

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

  10. 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...

  11. Autocrine regulation of interferon gamma in mesenchymal stem cells plays a role in early osteoblastogenesis.

    Science.gov (United States)

    Duque, Gustavo; Huang, Dao Chao; Macoritto, Michael; Rivas, Daniel; Yang, Xian Fang; Ste-Marie, Louis Georges; Kremer, Richard

    2009-03-01

    Interferon (IFN)gamma is a strong inhibitor of osteoclast differentiation and activity. However, its role in osteoblastogenesis has not been carefully examined. Using microarray expression analysis, we found that several IFNgamma-inducible genes were upregulated during early phases of osteoblast differentiation of human mesenchymal stem cells (hMSCs). We therefore hypothesized that IFNgamma may play a role in this process. We first observed a strong and transient increase in IFNgamma production following hMSC induction to differentiate into osteoblasts. We next blocked this endogenous production using a knockdown approach with small interfering RNA and observed a strong inhibition of hMSC differentiation into osteoblasts with a concomitant decrease in Runx2, a factor indispensable for osteoblast development. Additionally, exogenous addition of IFNgamma accelerated hMSC differentiation into osteoblasts in a dose-dependent manner and induced higher levels of Runx2 expression during the early phase of differentiation. We next examined IFNgamma signaling in vivo in IFNgamma receptor 1 knockout (IFNgammaR1(-/-)) mice. Compared with their wild-type littermates, IFNgammaR1(-/-) mice exhibited a reduction in bone mineral density. As in the in vitro experiments, MSCs obtained from IFNgammaR1(-/-) mice showed a lower capacity to differentiate into osteoblasts. In summary, we demonstrate that the presence of IFNgamma plays an important role during the commitment of MSCs into the osteoblastic lineage both in vitro and in vivo, and that this process can be accelerated by exogenous addition of IFNgamma. These data therefore support a new role for IFNgamma as an autocrine regulator of hMSC differentiation and as a potential new target of bone-forming cells in vivo.

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-03-28

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

  14. Autocrine VEGF-VEGFR2-Neuropilin-1 signaling promotes glioma stem-like cell viability and tumor growth

    DEFF Research Database (Denmark)

    Hamerlik, Petra; Lathia, Justin D; Rasmussen, Rikke;

    2012-01-01

    glioma stem-like cells (GSCs), whose viability, self-renewal, and tumorigenicity rely, at least in part, on signaling through the VEGF-VEGFR2-Neuropilin-1 (NRP1) axis. We find that the limited impact of bevacizumab-mediated VEGF blockage may reflect ongoing autocrine signaling through VEGF-VEGFR2-NRP1......, which is associated with VEGFR2-NRP1 recycling and a pool of active VEGFR2 within a cytosolic compartment of a subset of human GBM cells. Whereas bevacizumab failed to inhibit prosurvival effects of VEGFR2-mediated signaling, GSC viability under unperturbed or radiation-evoked stress conditions...

  15. Corticotropin-releasing hormone: an autocrine hormone that promotes lipogenesis in human sebocytes.

    Science.gov (United States)

    Zouboulis, Christos C; Seltmann, Holger; Hiroi, Naoki; Chen, WenChieh; Young, Maggie; Oeff, Marina; Scherbaum, Werner A; Orfanos, Constantin E; McCann, Samuel M; Bornstein, Stefan R

    2002-05-14

    Sebaceous glands may be involved in a pathway conceptually similar to that of the hypothalamic-pituitary-adrenal (HPA) axis. Such a pathway has been described and may occur in human skin and lately in the sebaceous glands because they express neuropeptide receptors. Corticotropin-releasing hormone (CRH) is the most proximal element of the HPA axis, and it acts as central coordinator for neuroendocrine and behavioral responses to stress. To further examine the probability of an HPA equivalent pathway, we investigated the expression of CRH, CRH-binding protein (CRH-BP), and CRH receptors (CRH-R) in SZ95 sebocytes in vitro and their regulation by CRH and several other hormones. CRH, CRH-BP, CRH-R1, and CRH-R2 were detectable in SZ95 sebocytes at the mRNA and protein levels: CRH-R1 was the predominant type (CRH-R1/CRH-R2 = 2). CRH was biologically active on human sebocytes: it induced biphasic increase in synthesis of sebaceous lipids with a maximum stimulation at 10(-7) M and up-regulated mRNA levels of 3 beta- hydroxysteroid dehydrogenase/Delta(5-4) isomerase, although it did not affect cell viability, cell proliferation, or IL-1 beta-induced IL-8 release. CRH, dehydroepiandrosterone, and 17 beta-estradiol did not modulate CRH-R expression, whereas testosterone at 10(-7) M down-regulated CRH-R1 and CRH-R2 mRNA expression at 6 to 24 h, and growth hormone (GH) switched CRH-R1 mRNA expression to CRH-R2 at 24 h. Based on these findings, CRH may be an autocrine hormone for human sebocytes that exerts homeostatic lipogenic activity, whereas testosterone and growth hormone induce CRH negative feedback. The findings implicate CRH in the clinical development of acne, seborrhea, androgenetic alopecia, skin aging, xerosis, and other skin disorders associated with alterations in lipid formation of sebaceous origin.

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

    Directory of Open Access Journals (Sweden)

    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.

  17. Fibroblast growth factor receptor 4 (FGFR4) and fibroblast growth factor 19 (FGF19) autocrine enhance breast cancer cells survival.

    Science.gov (United States)

    Tiong, Kai Hung; Tan, Boon Shing; Choo, Heng Lungh; Chung, Felicia Fei-Lei; Hii, Ling-Wei; Tan, Si Hoey; Khor, Nelson Tze Woei; Wong, Shew Fung; See, Sze-Jia; Tan, Yuen-Fen; Rosli, Rozita; Cheong, Soon-Keng; Leong, Chee-Onn

    2016-09-06

    Basal-like breast cancer is an aggressive tumor subtype with poor prognosis. The discovery of underlying mechanisms mediating tumor cell survival, and the development of novel agents to target these pathways, is a priority for patients with basal-like breast cancer. From a functional screen to identify key drivers of basal-like breast cancer cell growth, we identified fibroblast growth factor receptor 4 (FGFR4) as a potential mediator of cell survival. We found that FGFR4 mediates cancer cell survival predominantly via activation of PI3K/AKT. Importantly, a subset of basal-like breast cancer cells also secrete fibroblast growth factor 19 (FGF19), a canonical ligand specific for FGFR4. siRNA-mediated silencing of FGF19 or neutralization of extracellular FGF19 by anti-FGF19 antibody (1A6) decreases AKT phosphorylation, suppresses cancer cell growth and enhances doxorubicin sensitivity only in the FGFR4+/FGF19+ breast cancer cells. Consistently, FGFR4/FGF19 co-expression was also observed in 82 out of 287 (28.6%) primary breast tumors, and their expression is strongly associated with AKT phosphorylation, Ki-67 staining, higher tumor stage and basal-like phenotype. In summary, our results demonstrated the presence of an FGFR4/FGF19 autocrine signaling that mediates the survival of a subset of basal-like breast cancer cells and suggest that inactivation of this autocrine loop may potentially serve as a novel therapeutic intervention for future treatment of breast cancers.

  18. Connective tissue growth factor and β-catenin constitute an autocrine loop for activation in rat sarcomatoid mesothelioma.

    Science.gov (United States)

    Jiang, Li; Yamashita, Yoriko; Chew, Shan-Hwu; Akatsuka, Shinya; Ukai, Shun; Wang, Shenqi; Nagai, Hirotaka; Okazaki, Yasumasa; Takahashi, Takashi; Toyokuni, Shinya

    2014-08-01

    Due to the formerly widespread use of asbestos, malignant mesothelioma (MM) is increasingly frequent worldwide. MM is classified into epithelioid (EM), sarcomatoid (SM), and biphasic subtypes. SM is less common than EM but is recognized as the most aggressive type of MM, and these patients have a poor prognosis. To identify genes responsible for the aggressiveness of SM, we induced EM and SM in rats, using asbestos, and compared their transcriptomes. Based on the results, we focused on connective tissue growth factor (Ctgf), whose expression was significantly increased in SM compared with EM; EM itself exhibited an increased expression of Ctgf compared with normal mesothelium. Particularly in SM, Ctgf was a major regulator of MM proliferation and invasion through activation of the β-catenin-TCF-LEF signalling pathway, which is autocrine and formed a positive feedback loop via LRP6 as a receptor for secreted Ctgf. High Ctgf expression also played a role in the epithelial-mesenchymal transition in MM. Furthermore, Ctgf is a novel serum biomarker for both early diagnosis and determining the MM prognosis in rats. These data link Ctgf to SM through the LRP6-GSK3β-β-catenin-TCF-Ctgf autocrine axis and suggest Ctgf as a therapeutic target.

  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.

  20. Autocrine/Paracrine Human Growth Hormone-stimulated MicroRNA 96-182-183 Cluster Promotes Epithelial-Mesenchymal Transition and Invasion in Breast Cancer.

    Science.gov (United States)

    Zhang, Weijie; Qian, Pengxu; Zhang, Xiao; Zhang, Min; Wang, Hong; Wu, Mingming; Kong, Xiangjun; Tan, Sheng; Ding, Keshuo; Perry, Jo K; Wu, Zhengsheng; Cao, Yuan; Lobie, Peter E; Zhu, Tao

    2015-05-29

    Human growth hormone (hGH) plays critical roles in pubertal mammary gland growth, development, and sexual maturation. Accumulated studies have reported that autocrine/paracrine hGH is an orthotopically expressed oncoprotein that promotes normal mammary epithelial cell oncogenic transformation. Autocrine/paracrine hGH has also been reported to promote mammary epithelial cell epithelial-mesenchymal transition (EMT) and invasion. However, the underlying mechanism remains largely obscure. MicroRNAs (miRNAs) are reported to be involved in regulation of multiple cellular functions of cancer. To determine whether autocrine/paracrine hGH promotes EMT and invasion through modulation of miRNA expression, we performed microarray profiling using MCF-7 cells stably expressing wild type or a translation-deficient hGH gene and identified miR-96-182-183 as an autocrine/paracrine hGH-regulated miRNA cluster. Forced expression of miR-96-182-183 conferred on epithelioid MCF-7 cells a mesenchymal phenotype and promoted invasive behavior in vitro and dissemination in vivo. Moreover, we observed that miR-96-182-183 promoted EMT and invasion by directly and simultaneously suppressing BRMS1L (breast cancer metastasis suppressor 1-like) gene expression. miR-96 and miR-182 also targeted GHR, providing a potential negative feedback loop in the hGH-GHR signaling pathway. We further demonstrated that autocrine/paracrine hGH stimulated miR-96-182-183 expression and facilitated EMT and invasion via STAT3 and STAT5 signaling. Consistent with elevated expression of autocrine/paracrine hGH in metastatic breast cancer tissue, miR-96-182-183 expression was also remarkably enhanced. Hence, we delineate the roles of the miRNA-96-182-183 cluster and elucidate a novel hGH-GHR-STAT3/STAT5-miR-96-182-183-BRMS1L-ZEB1/E47-EMT/invasion axis, which provides further understanding of the mechanism of autocrine/paracrine hGH-stimulated EMT and invasion in breast cancer.

  1. An FGF autocrine loop initiated in second heart field mesoderm regulates morphogenesis at the arterial pole of the heart

    Science.gov (United States)

    Park, Eon Joo; Watanabe, Yusuke; Smyth, Graham; Miyagawa-Tomita, Sachiko; Meyers, Erik; Klingensmith, John; Camenisch, Todd; Buckingham, Margaret; Moon, Anne M.

    2009-01-01

    In order to understand how secreted signals regulate complex morphogenetic events, it is crucial to identify their cellular targets. By conditional inactivation of Fgfr1 and Fgfr2 and overexpression of the FGF antagonist sprouty 2 in different cell types, we have dissected the role of FGF signaling during heart outflow tract development in mouse. Contrary to expectation, cardiac neural crest and endothelial cells are not primary paracrine targets. FGF signaling within second heart field mesoderm is required for remodeling of the outflow tract: when disrupted, outflow myocardium fails to produce extracellular matrix and TGFβ and BMP signals essential for endothelial cell transformation and invasion of cardiac neural crest. We conclude that an autocrine regulatory loop, initiated by the reception of FGF signals by the mesoderm, regulates correct morphogenesis at the arterial pole of the heart. These findings provide new insight into how FGF signaling regulates context-dependent cellular responses during development. PMID:18832392

  2. 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.

  3. Vasoreparative dysfunction of CD34+ cells in diabetic individuals involves hypoxic desensitization and impaired autocrine/paracrine mechanisms.

    Directory of Open Access Journals (Sweden)

    Yagna P R Jarajapu

    Full Text Available We hypothesized that endothelial progenitor cells derived from individuals with diabetes would exhibit functional defects including inability to respond to hypoxia and altered paracrine/autocrine function that would impair the angiogenic potential of these cells. Circulating mononuclear cells isolated from diabetic (n = 69 and nondiabetic (n = 46 individuals were used to grow endothelial colony forming cells (ECFC, early endothelial progenitor cells (eEPCs and isolate CD34+ cells. ECFCs and eEPCs were established from only 15% of the diabetic individuals tested thus directing our main effort toward examination of CD34+ cells. CD34+ cells were plated in basal medium to obtain cell-free conditioned medium (CM. In CM derived from CD34+ cells of diabetic individuals (diabetic-CM, the levels of stem cell factor, hepatocyte growth factor, and thrombopoietin were lower, and IL-1β and tumor necrosis factor (TNFα levels were higher than CM derived from nondiabetic individuals (nondiabetic-CM. Hypoxia did not upregulate HIF1α in CD34+ cells of diabetic origin. Migration and proliferation of nondiabetic CD34+ cells toward diabetic-CM were lower compared to nondiabetic-CM. Attenuation of pressure-induced constriction, potentiation of bradykinin relaxation, and generation of cGMP and cAMP in arterioles were observed with nondiabetic-CM, but not with diabetic-CM. Diabetic-CM failed to induce endothelial tube formation from vascular tissue. These results suggest that diabetic subjects with microvascular complications exhibit severely limited capacity to generate ex-vivo expanded endothelial progenitor populations and that the vasoreparative dysfunction observed in diabetic CD34+ cells is due to impaired autocrine/paracrine function and reduced sensitivity to hypoxia.

  4. Vasoreparative dysfunction of CD34+ cells in diabetic individuals involves hypoxic desensitization and impaired autocrine/paracrine mechanisms.

    Science.gov (United States)

    Jarajapu, Yagna P R; Hazra, Sugata; Segal, Mark; Li Calzi, Sergio; LiCalzi, Sergio; Jadhao, Chandra; Jhadao, Chandra; Qian, Kevin; Mitter, Sayak K; Raizada, Mohan K; Boulton, Michael E; Grant, Maria B

    2014-01-01

    We hypothesized that endothelial progenitor cells derived from individuals with diabetes would exhibit functional defects including inability to respond to hypoxia and altered paracrine/autocrine function that would impair the angiogenic potential of these cells. Circulating mononuclear cells isolated from diabetic (n = 69) and nondiabetic (n = 46) individuals were used to grow endothelial colony forming cells (ECFC), early endothelial progenitor cells (eEPCs) and isolate CD34+ cells. ECFCs and eEPCs were established from only 15% of the diabetic individuals tested thus directing our main effort toward examination of CD34+ cells. CD34+ cells were plated in basal medium to obtain cell-free conditioned medium (CM). In CM derived from CD34+ cells of diabetic individuals (diabetic-CM), the levels of stem cell factor, hepatocyte growth factor, and thrombopoietin were lower, and IL-1β and tumor necrosis factor (TNFα) levels were higher than CM derived from nondiabetic individuals (nondiabetic-CM). Hypoxia did not upregulate HIF1α in CD34+ cells of diabetic origin. Migration and proliferation of nondiabetic CD34+ cells toward diabetic-CM were lower compared to nondiabetic-CM. Attenuation of pressure-induced constriction, potentiation of bradykinin relaxation, and generation of cGMP and cAMP in arterioles were observed with nondiabetic-CM, but not with diabetic-CM. Diabetic-CM failed to induce endothelial tube formation from vascular tissue. These results suggest that diabetic subjects with microvascular complications exhibit severely limited capacity to generate ex-vivo expanded endothelial progenitor populations and that the vasoreparative dysfunction observed in diabetic CD34+ cells is due to impaired autocrine/paracrine function and reduced sensitivity to hypoxia.

  5. Characterization of the autocrine/paracrine function of vitamin D in human gingival fibroblasts and periodontal ligament cells.

    Directory of Open Access Journals (Sweden)

    Kaining Liu

    Full Text Available BACKGROUND: We previously demonstrated that 25-hydroxyvitamin D(3, the precursor of 1α,25-dihydroxyvitamin D(3, is abundant around periodontal soft tissues. Here we investigate whether 25-hydroxyvitamin D(3 is converted to 1α,25-dihydroxyvitamin D(3 in periodontal soft tissue cells and explore the possibility of an autocrine/paracrine function of 1α,25-dihydroxyvitamin D(3 in periodontal soft tissue cells. METHODOLOGY/PRINCIPAL FINDINGS: We established primary cultures of human gingival fibroblasts and human periodontal ligament cells from 5 individual donors. We demonstrated that 1α-hydroxylase was expressed in human gingival fibroblasts and periodontal ligament cells, as was cubilin. After incubation with the 1α-hydroxylase substrate 25-hydroxyvitamin D(3, human gingival fibroblasts and periodontal ligament cells generated detectable 1α,25-dihydroxyvitamin D(3 that resulted in an up-regulation of CYP24A1 and RANKL mRNA. A specific knockdown of 1α-hydroxylase in human gingival fibroblasts and periodontal ligament cells using siRNA resulted in a significant reduction in both 1α,25-dihydroxyvitamin D(3 production and mRNA expression of CYP24A1 and RANKL. The classical renal regulators of 1α-hydroxylase (parathyroid hormone, calcium and 1α,25-dihydroxyvitamin D(3 and Porphyromonas gingivalis lipopolysaccharide did not influence 1α-hydroxylase expression significantly, however, interleukin-1β and sodium butyrate strongly induced 1α-hydroxylase expression in human gingival fibroblasts and periodontal ligament cells. CONCLUSIONS/SIGNIFICANCE: In this study, the expression, activity and functionality of 1α-hydroxylase were detected in human gingival fibroblasts and periodontal ligament cells, raising the possibility that vitamin D acts in an autocrine/paracrine manner in these cells.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. Autocrine role of estrogens in the augmentation of luteinizing hormone receptor formation in cultured rat granulosa cells.

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    Kessel, B; Liu, Y X; Jia, X C; Hsueh, A J

    1985-06-01

    The effects of estrogens on gonadotropin-stimulated luteinizing hormone (LH) receptor formation were examined in primary cultures of rat granulosa cells. Granulosa cells were cultured for 3 days with increasing concentrations of follicle-stimulating hormone (FSH) in the presence or absence of native and synthetic estrogens. Follicle-stimulating hormone stimulated LH receptor formation in a dose-dependent fashion, and estrogens enhanced the FSH-stimulated LH receptor content by decreasing the apparent ED50 of FSH. At 6.25 ng/ml FSH, the enhancement in LH receptor was estrogen dose dependent, with an ED50 value of about 3 X 10(-9) M for 17 beta-estradiol. The increased LH receptor content seen in cells treated with FSH and estrogen was correlated with increased cAMP production by these cells in response to LH stimulation. Time course studies revealed enhancement of FSH-stimulated LH receptor induction at 48 and 72 h of culture. Granulosa cells were also cultured with FSH for 2 days to induce functional LH receptors, then further cultured for 3 days with LH in the presence or absence of estrogens. At 30 ng/ml LH, increasing concentrations of estrogens maintained LH receptor content in a dose-dependent fashion, with their relative estrogenic potencies in keeping with reported binding affinities to estrogen receptors. An autocrine role of estrogens on LH receptor formation was further tested in granulosa cells treated with FSH and an aromatase substrate (androstenedione) to increase estrogen biosynthesis. Cotreatment with semipurified estrogen antibodies partially blocked the FSH stimulation of LH receptors, whereas nonimmune serum was ineffective. Also, inclusion of diethylstilbestrol prevented the inhibitory effect of the estrogen antibodies. Thus, local estrogens in ovarian follicles may play an autocrine role in granulosa cells to enhance LH receptor formation and to increase granulosa cell responsiveness to the LH surge, with subsequent ovulation and adequate

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-01-18

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

  12. Activation of vitamin D regulates response of human bronchial epithelial cells to Aspergillus fumigatus in an autocrine fashion.

    Science.gov (United States)

    Li, Pei; Wu, Ting; Su, Xin; Shi, Yi

    2015-01-01

    Aspergillus fumigatus (A. fumigatus) is one of the most common fungi to cause diseases in humans. Recent evidence has demonstrated that airway epithelial cells play an important role in combating A. fumigatus through inflammatory responses. Human airway epithelial cells have been proven to synthesize the active vitamin D, which plays a key role in regulating inflammation. The present study was conducted to investigate the impact of A. fumigatus infection on the activation of vitamin D and the role of vitamin D activation in A. fumigatus-elicited antifungal immunity in normal human airway epithelial cells. We found that A. fumigatus swollen conidia (SC) induced the expression of 1α-hydroxylase, the enzyme catalyzing the synthesis of active vitamin D, and vitamin D receptor (VDR) in 16HBE cells and led to increased local generation of active vitamin D. Locally activated vitamin D amplified SC-induced expression of antimicrobial peptides in 16HBE cells but attenuated SC-induced production of cytokines in an autocrine fashion. Furthermore, we identified β-glucan, the major A. fumigatus cell wall component, as the causative agent for upregulation of 1α-hydroxylase and VDR in 16HBE cells. Therefore, activation of vitamin D is inducible and provides a bidirectional regulation of the responses to A. fumigatus in 16HBE cells.

  13. Role of TGF-β in Survival of Phagocytizing Microglia: Autocrine Suppression of TNF-α Production and Oxidative Stress.

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    Ryu, Keun-Young; Cho, Geum-Sil; Piao, Hua Zi; Kim, Won-Ki

    2012-12-01

    Microglia are recognized as residential macrophageal cells in the brain. Activated microglia play a critical role in removal of dead or damaged cells through phagocytosis activity. During phagocytosis, however, microglia should survive under the harmful condition of self-producing ROS and pro-inflammatory mediators. TGF-β has been known as a classic anti-inflammatory cytokine and controls both initiation and resolution of inflammation by counter-acting inflammatory cytokines. In the present study, to understand the self-protective mechanism, we studied time-dependent change of TNF-α and TGF-β production in microglia phagocytizing opsonized-beads (i.e., polystyrene microspheres). We found that microglia phagocytized opsonized-bead in a time-dependent manner and simultaneously produced both TNF-α and TGF-β. However, while TNF-α production gradually decreased after 6 h, TGF-β production remained at increased level. Microglial cells pre-treated with lipopolysaccharides (a strong immunostimulant, LPS) synergistically increased the production of TNF-α and TGF-β both. However, LPS-pretreated microglia produced TNF-α in a more sustained manner and became more vulnerable, probably due to the marked and sustained production of TNF-α and reduced TGF-β. Intracellular oxidative stress appears to change in parallel with the microglial production of TNF-α. These results indicate TGF-β contributes for the survival of phagocytizing microglia through autocrine suppression of TNF-α production and oxidative stress.

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

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    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

  15. Autocrine induction of invasion and metastasis by tumor-associated trypsin inhibitor in human colon cancer cells.

    Science.gov (United States)

    Gouyer, V; Fontaine, D; Dumont, P; de Wever, O; Fontayne-Devaud, H; Leteurtre, E; Truant, S; Delacour, D; Drobecq, H; Kerckaert, J-P; de Launoit, Y; Bracke, M; Gespach, C; Desseyn, J-L; Huet, G

    2008-07-03

    From the conditioned medium of the human colon carcinoma cells, HT-29 5M21 (CM-5M21), expressing a spontaneous invasive phenotype, tumor-associated trypsin inhibitor (TATI) was identified and characterized by proteomics, cDNA microarray approaches and functional analyses. Both CM-5M21 and recombinant TATI, but not the K18Y-TATI mutant at the protease inhibitor site, trigger collagen type I invasion by several human adenoma and carcinoma cells of the colon and breast, through phosphoinositide-3-kinase, protein kinase C and Rho-GTPases/Rho kinase-dependent pathways. Conversely, the proinvasive action of TATI in parental HT29 cells was alleviated by the TATI antibody PSKAN2 and the K18Y-TATI mutant. Stable expression of K18Y-TATI in HT-29 5M21 cells downregulated tumor growth, angiogenesis and the expression of several metastasis-related genes, including CSPG4 (13.8-fold), BMP-7 (9.7-fold), the BMP antagonist CHORDIN (5.2-fold), IGFBP-2 and IGF2 (9.6- and 4.6-fold). Accordingly, ectopic expression of KY-TATI inhibited the development of lung metastases from HT-29 5M21 tumor xenografts in immunodeficient mice. These findings identify TATI as an autocrine transforming factor potentially involved in early and late events of colon cancer progression, including local invasion of the primary tumor and its metastatic spread. Targeting TATI, its molecular partners and effectors may bring novel therapeutic applications for high-grade human solid tumors in the digestive and urogenital systems.

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

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    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.

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

    Science.gov (United States)

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

    2012-01-01

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

  18. 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

  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.

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    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. 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.

  2. 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.

  3. 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.

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

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    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.

  5. 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.

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

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    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.

  7. The first trimester human trophoblast cell line ACH-3P: A novel tool to study autocrine/paracrine regulatory loops of human trophoblast subpopulations – TNF-α stimulates MMP15 expression

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    Knöfler Martin

    2007-12-01

    Full Text Available Abstract Background The trophoblast compartment of the placenta comprises various subpopulations with distinct functions. They interact among each other by secreted signals thus forming autocrine or paracrine regulatory loops. We established a first trimester trophoblast cell line (ACH-3P by fusion of primary human first trimester trophoblasts (week 12 of gestation with a human choriocarcinoma cell line (AC1-1. Results Expression of trophoblast markers (cytokeratin-7, integrins, matrix metalloproteinases, invasion abilities and transcriptome of ACH-3P closely resembled primary trophoblasts. Morphology, cytogenetics and doubling time was similar to the parental AC1-1 cells. The different subpopulations of trophoblasts e.g., villous and extravillous trophoblasts also exist in ACH-3P cells and can be immuno-separated by HLA-G surface expression. HLA-G positive ACH-3P display pseudopodia and a stronger expression of extravillous trophoblast markers. Higher expression of insulin-like growth factor II receptor and human chorionic gonadotropin represents the basis for the known autocrine stimulation of extravillous trophoblasts. Conclusion We conclude that ACH-3P represent a tool to investigate interaction of syngeneic trophoblast subpopulations. These cells are particularly suited for studies into autocrine and paracrine regulation of various aspects of trophoblast function. As an example a novel effect of TNF-α on matrix metalloproteinase 15 in HLA-G positive ACH-3P and explants was found.

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

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    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.

  9. 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.

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

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    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.

  11. A phosphatase-independent gain-of-function mutation in PTEN triggers aberrant cell growth in astrocytes through an autocrine IGF-1 loop.

    Science.gov (United States)

    Fernández, S; Genis, L; Torres-Alemán, I

    2014-08-07

    Loss-of-function mutations in the phosphatase PTEN (phosphatase and tensin homolog deleted on chromosome10) contribute to aberrant cell growth in part through upregulation of the mitogenic IGF-1/PI3K/Akt pathway. In turn, this pathway exerts a homeostatic feedback over PTEN. Using mutagenesis analysis to explore a possible impact of this mutual control on astrocyte growth, we found that truncation of the C-terminal region of PTEN (Δ51) associates with a marked increase in NFκB activity, a transcription factor overactivated in astrocyte tumors. Whereas mutations of PTEN are considered to lead to a loss-of-function, PTENΔ51, a truncation that comprises a region frequently mutated in human gliomas, displayed a neomorphic (gain-of-function) activity that was independent of its phosphatase activity. This gain-of-function of PTENΔ51 includes stimulation of IGF-1 synthesis through protein kinase A activation of the IGF-1 promoter. Increased IGF-1 originates an autocrine loop that activates Akt and NFκB. Constitutive activation of NFκB in PTENΔ51-expressing astrocytes leads to aberrant cell growth; astrocytes expressing this mutant PTEN generate colonies in vitro and tumors in vivo. Mutations converting a tumor suppressor such as PTEN into a tumor promoter through a gain-of-function involving IGF-1 production may further our understanding of the role played by this growth factor in glioma growth and help us define druggable targets for personalized therapy.

  12. Binding of FGF2 to FGFR2 in an autocrine mode in trophectoderm cells is indispensable for mouse blastocyst formation through PKC-p38 pathway.

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    Yang, Jing; Zhang, Dan; Yu, Ying; Zhang, Run-Ju; Hu, Xiao-Ling; Huang, He-Feng; Lu, Yong-Chao

    2015-01-01

    Fibroblast growth factors (FGF1, FGF2 and FGF4) and fibroblast growth factor receptors (FGFR1, FGFR2, FGFR3 and FGFR4) have been reported to be expressed in preimplantation embryos and be required for their development. However, the functions of these molecules in trophectoderm cells (TEs) that lead to the formation of the blastocyst as well as the underlying mechanism have not been elucidated. The present study has demonstrated for the first time that endogenous FGF2 secreted by TEs can regulate protein expression and distribution in TEs via the FGFR2-mediated activation of PKC and p38, which are important for the development of expanded blastocysts. This finding provides the first explanation for the long-observed phenomenon that only high concentrations of exogenous FGFs have effects on embryonic development, but in vivo the amount of endogenous FGFs are trace. Besides, the present results suggest that FGF2/FGFR2 may act in an autocrine fashion and activate the downstream PKC/p38 pathway in TEs during expanded blastocyst formation.

  13. An IL-12/Shh-C domain fusion protein-based IL-12 autocrine loop for sustained natural killer cell activation.

    Science.gov (United States)

    Zhu, Lining; Zhao, Zhihui; Wei, Yanzhang; Marcotte, William; Wagner, Thomas E; Yu, Xianzhong

    2012-08-01

    The dependency of activated natural killer (NK) cells on the continuous support of exogenous interleukin (IL)-2 for their in vivo survival, tumor localization and consequently, their antitumor effect, is a major obstacle for NK cell-mediated tumor therapy. In the present study, a fusion gene between IL-12 and mouse sonic hedgehog C-terminal domain (Shh-C) was constructed. The fusion protein was autocatalytically processed to form cholesterol-modified IL-12 molecules and an autocrine loop of IL-12 was established for the sustained activation of NK cells. The transduced NK cells matured more rapidly in vitro with the enhanced expression of granule-related proteins. NKIL-12/Shh-C cells reached the same proliferation rate as NK cells transduced with enhanced green fluorescent protein (EGFP)/Shh-C (NKEGFP/Shh-C) with Shh-C cells 5 and 7 days after transduction was significantly higher than that in the supernatants of NKIL-12 cells. Immunofluorescent staining of lung tissues from B16-bearing mice which had received an intravenous injection of lentivirus-transduced NK cells without exogenous IL-2 confirmed that donor NK cells successfully infiltrated into the lung tissues. The survival time of the mice which had received NKIL-12/Shh-C cells was significantly prolonged compared to the mice which had received NKEGFP/Shh-C cells.

  14. Overexpressing the novel autocrine/endocrine adipokine WISP2 induces hyperplasia of the heart, white and brown adipose tissues and prevents insulin resistance

    Science.gov (United States)

    Grünberg, John R.; Hoffmann, Jenny M.; Hedjazifar, Shahram; Nerstedt, Annika; Jenndahl, Lachmi; Elvin, Johannes; Castellot, John; Wei, Lan; Movérare-Skrtic, Sofia; Ohlsson, Claes; Holm, Louise Mannerås; Bäckhed, Fredrik; Syed, Ismail; Bosch, Fatima; Saghatelian, Alan; Kahn, Barbara B.; Hammarstedt, Ann; Smith, Ulf

    2017-01-01

    WISP2 is a novel adipokine, most highly expressed in the adipose tissue and primarily in undifferentiated mesenchymal cells. As a secreted protein, it is an autocrine/paracrine activator of canonical WNT signaling and, as an intracellular protein, it helps to maintain precursor cells undifferentiated. To examine effects of increased WISP2 in vivo, we generated an aP2-WISP2 transgenic (Tg) mouse. These mice had increased serum levels of WISP2, increased lean body mass and whole body energy expenditure, hyperplastic brown/white adipose tissues and larger hyperplastic hearts. Obese Tg mice remained insulin sensitive, had increased glucose uptake by adipose cells and skeletal muscle in vivo and ex vivo, increased GLUT4, increased ChREBP and markers of adipose tissue lipogenesis. Serum levels of the novel fatty acid esters of hydroxy fatty acids (FAHFAs) were increased and transplantation of Tg adipose tissue improved glucose tolerance in recipient mice supporting a role of secreted FAHFAs. The growth-promoting effect of WISP2 was shown by increased BrdU incorporation in vivo and Tg serum increased mesenchymal precursor cell proliferation in vitro. In contrast to conventional canonical WNT ligands, WISP2 expression was inhibited by BMP4 thereby allowing normal induction of adipogenesis. WISP2 is a novel secreted regulator of mesenchymal tissue cellularity. PMID:28240264

  15. Autocrine/paracrine prostaglandin E2 production by non-small cell lung cancer cells regulates matrix metalloproteinase-2 and CD44 in cyclooxygenase-2-dependent invasion.

    Science.gov (United States)

    Dohadwala, Mariam; Batra, Raj K; Luo, Jie; Lin, Ying; Krysan, Kostyantyn; Pold, Mehis; Sharma, Sherven; Dubinett, Steven M

    2002-12-27

    Tumor cyclooxygenase-2 (COX-2) expression is known to be associated with enhanced tumor invasiveness. In the present study, we evaluated the importance of the COX-2 product prostaglandin E2 (PGE2) and its signaling through the EP4 receptor in mediating non-small cell lung cancer (NSCLC) invasiveness. Genetic inhibition of tumor COX-2 led to diminished matrix metalloproteinase (MMP)-2, CD44, and EP4 receptor expression and invasion. Treatment of NSCLC cells with exogenous 16,16-dimethylprostaglandin E2 significantly increased EP4 receptor, CD44, and MMP-2 expression and matrigel invasion. In contrast, anti-PGE2 decreased EP4 receptor, CD44, and MMP-2 expression in NSCLC cells. EP4 receptor signaling was found to be central to this process, because antisense oligonucleotide-mediated inhibition of tumor cell EP4 receptors significantly decreased CD44 expression. In addition, agents that increased intracellular cAMP, as is typical of EP4 receptor signaling, markedly increased CD44 expression. Moreover, MMP-2-AS treatment decreased PGE2-mediated CD44 expression, and CD44-AS treatment decreased MMP-2 expression. Thus, PGE2-mediated effects through EP4 required the parallel induction of both CD44 and MMP-2 expression because genetic inhibition of either MMP-2 or CD44 expression effectively blocked PGE2-mediated invasion in NSCLC. These findings indicate that PGE2 regulates COX-2-dependent, CD44- and MMP-2-mediated invasion in NSCLC in an autocrine/paracrine manner via EP receptor signaling. Thus, blocking PGE2 production or activity by genetic or pharmacological interventions may prove to be beneficial in chemoprevention or treatment of NSCLC.

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

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    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.

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

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    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.

  18. Autocrine regulation of TGF-β1-induced cell migration by exocytosis of ATP and activation of P2 receptors in human lung cancer cells.

    Science.gov (United States)

    Takai, Erina; Tsukimoto, Mitsutoshi; Harada, Hitoshi; Sawada, Keisuke; Moriyama, Yoshinori; Kojima, Shuji

    2012-11-01

    TGF-β1 plays a key role in cancer progression through induction of various biological effects, including cell migration. Extracellular nucleotides, such as ATP, released from cells play a role in signaling through activation of P2 receptors. We show here that exocytosis of ATP followed by activation of P2 receptors play a key role in TGF-β1-induced actin remodeling associated with cell migration. Treatment with TGF-β1 facilitated migration of human lung cancer A549 cells, which was blocked by pretreatment with ecto-nucleotidase and P2 receptor antagonists. ATP and P2 agonists facilitated cell migration. TGF-β1-induced actin remodeling, which contributes to cell migration, was also suppressed by pretreatment with ecto-nucleotidase and P2 receptor antagonists. Knockdown of P2X7 receptor suppressed TGF-β1-induced migration and actin remodeling. These results indicate the involvement of TGF-β1-induced ATP release in cell migration, at least in part, through activation of P2X7 receptors. TGF-β1 caused release of ATP from A549 cells within 10 minutes. Both ATP-enriched vesicles and expression of a vesicular nucleotide transporter (VNUT) SLC17A9, which is responsible for exocytosis of ATP, were found in cytosol of A549 cells. TGF-β1 failed to induce release of ATP from SLC17A9-knockdown cells. TGF-β1-induced cell migration and actin remodeling were also decreased in SLC17A9-knockdown cells. These results suggest the importance of exocytosis of ATP in cell migration. We conclude that autocrine signaling through exocytosis of ATP and activation of P2 receptors is required for the amplification of TGF-β1-induced migration of lung cancer cells.

  19. 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.

  20. Analysis of secretome changes uncovers an autocrine/paracrine component in the modulation of cell proliferation and motility by c-Myc.

    Science.gov (United States)

    Pocsfalvi, Gabriella; Votta, Giuseppina; De Vincenzo, Anna; Fiume, Immacolata; Raj, Delfin Albert Amal; Marra, Giancarlo; Stoppelli, Maria Patrizia; Iaccarino, Ingram

    2011-12-02

    Proteins secreted by cancer cells are a major component of tumor microenvironment. However, little is known on the impact of single oncogenic lesions on the expression of secreted proteins at early stages of tumor development. Because c-Myc overexpression is among the most frequent alterations in cancer, here we investigated the effect of sustained c-Myc expression on the secretome of a nontransformed human epithelial cell line (hT-RPE). By using a quantitative proteomic approach, we have identified 125 proteins in conditioned media of hT-RPE/MycER cells upon c-Myc induction. Analysis of the 49 proteins significantly down-regulated by c-Myc revealed a marked enrichment of factors associated with growth inhibition and cellular senescence. Accordingly, media conditioned by hT-RPE cells expressing c-Myc show an increased ability to sustain hT-RPE cellular proliferation/viability. We also find a marked down-regulation of several structural and regulatory components of the extracellular matrix (ECM), which correlates with an increased chemotactic potency of the conditioned media toward fibroblasts, a major cellular component of tumor stroma. In accordance with these data, the expression of the majority of the genes encoding proteins down-regulated in hT-RPE was significantly reduced also in colorectal adenomatous polyps, early tumors in which c-Myc is invariably overexpressed. These findings help to elucidate the significance of c-Myc overexpression at early stages of tumor development and uncover a remarkable autocrine/paracrine component in the ability of c-Myc to stimulate proliferation, sustain tumor maintenance, and modulate cell migration.

  1. Paracrine SDF-1α signaling mediates the effects of PSCs on GEM chemoresistance through an IL-6 autocrine loop in pancreatic cancer cells.

    Science.gov (United States)

    Zhang, Hui; Wu, Huanwen; Guan, Jian; Wang, Li; Ren, Xinyu; Shi, Xiaohua; Liang, Zhiyong; Liu, Tonghua

    2015-02-20

    Pancreatic cancer exhibits the poorest prognosis among all tumors and is characterized by high resistance to the currently available chemotherapeutic agents. Our previous studies have suggested that stromal components could promote the chemoresistance of pancreatic cancer cells (PCCs). Here, we explored the roles of pancreatic stellate cells (PSCs) and the SDF-1α/CXCR4 axis in pancreatic cancer chemoresitance. Our results showed that primary PSCs typically expressed SDF-1α, whereas its receptor CXCR4 was highly expressed in PCCs. PSC-conditioned medium (PSC-CM) inhibited Gemcitabine (GEM)-induced cytotoxicity and apoptosis in the human PCC line Panc-1, which was antagonized by an SDF-1α neutralizing Ab. Recombinant human SDF-1α (rhSDF-1α) increased IL-6 expression and secretion in Panc-1 cells in a time and dose-dependent manner, and this effect was suppressed by the CXCR4 antagonist AMD3100. rhSDF-1α protected Panc-1 cells from GEM-induced apoptosis, and the protective effect was significantly reduced by blocking IL-6 using a neutralizing antibody. Moreover, rhSDF-1α increased FAK, ERK1/2, AKT and P38 phosphorylation in Panc-1 cells, and either FAK or ERK1/2 inhibition suppressed SDF-1α-upregulated IL-6 expression. SDF-1α-induced AKT activation was almost completely blocked by FAK inhibition. In conclusion, we demonstrate for the first time that PSCs promote the chemoresistance of PCCs to GEM, and this effect is mediated by paracrine SDF-1α/CXCR4 signaling-induced activation of the intracellular FAK-AKT and ERK1/2 signaling pathways and a subsequent IL-6 autocrine loop in PCCs. Our findings indicate that blocking the PSC-PCC interaction by inhibiting SDF-1α/CXCR4 signaling may be a promising therapeutic strategy for overcoming chemoresistance in pancreatic cancer.

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

    Directory of Open Access Journals (Sweden)

    Liliana Endo-Munoz

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

  3. Phosphoglucose isomerase/autocrine motility factor mediates epithelial-mesenchymal transition regulated by miR-200 in breast cancer cells.

    Science.gov (United States)

    Ahmad, Aamir; Aboukameel, Amro; Kong, Dejuan; Wang, Zhiwei; Sethi, Seema; Chen, Wei; Sarkar, Fazlul H; Raz, Avraham

    2011-05-01

    Phosphoglucose isomerase/autocrine motility factor (PGI/AMF) plays an important role in glycolysis and gluconeogenesis and is associated with invasion and metastasis of cancer cells. We have previously shown its role in the induction of epithelial-mesenchymal transition (EMT) in breast cancer cells, which led to increased aggressiveness; however, the molecular mechanism by which PGI/AMF regulates EMT is not known. Here we show, for the first time, that PGI/AMF overexpression led to an increase in the DNA-binding activity of NF-κB, which, in turn, led to increased expression of ZEB1/ZEB2. The microRNA-200s (miR-200s) miR-200a, miR-200b, and miR-200c are known to negatively regulate the expression of ZEB1/ZEB2, and we found that the expression of miR-200s was lost in PGI/AMF overexpressing MCF-10A cells and in highly invasive MDA-MB-231 cells, which was consistent with increased expression of ZEB1/ZEB2. Moreover, silencing of PGI/AMF expression in MDA-MB-231 cells led to overexpression of miR-200s, which was associated with reversal of EMT phenotype (i.e., mesenchymal-epithelial transition), and these findings were consistent with alterations in the relative expression of epithelial (E-cadherin) and mesenchymal (vimentin, ZEB1, ZEB2) markers and decreased aggressiveness as judged by clonogenic, motility, and invasion assays. Moreover, either reexpression of miR-200 or silencing of PGI/AMF suppressed pulmonary metastases of MDA-MB-231 cells in vivo, and anti-miR-200 treatment in vivo resulted in increased metastases. Collectively, these results suggest a role of miR-200s in PGI/AMF-induced EMT and thus approaches for upregulation of miR-200s could be a novel therapeutic strategy for the treatment of highly invasive breast cancer.

  4. 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.

  5. Predicting future of predictive analysis

    OpenAIRE

    Piyush, Duggal

    2014-01-01

    With enormous growth in analytical data and insight about advantage of managing future brings Predictive Analysis in picture. It really has potential to be called one of efficient and competitive technologies that give an edge to business operations. The possibility to predict future market conditions and to know customers’ needs and behavior in advance is the area of interest of every organization. Other areas of interest may be maintenance prediction where we tend to predict when and where ...

  6. Predictive medicine

    NARCIS (Netherlands)

    Boenink, Marianne; Have, ten Henk

    2015-01-01

    In the last part of the twentieth century, predictive medicine has gained currency as an important ideal in biomedical research and health care. Research in the genetic and molecular basis of disease suggested that the insights gained might be used to develop tests that predict the future health sta

  7. 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.

  8. Transfection of rat myoblasts with leuflvirus carrying autocrine motility factor gene%携带自分泌运动因子基因的慢病毒载体转染大鼠成肌细胞

    Institute of Scientific and Technical Information of China (English)

    李任; 金岚; 田怡; 牙祖蒙

    2009-01-01

    目的 探索高效、安全的自分泌运动因子(autocrine motility factor,AMF)基因转染方法 ,为携带AMF基因的成肌细胞移植提供实验依据. 方法 取SD大鼠胸肌,用组织块培养法原代培养成肌细胞,纯化、鉴定、扩增成肌细胞;构建携带AMF及增强型绿色荧光蛋白(enhancedgreen fluorescent protein,EGFP)基因的猫免疫缺陷病毒(feline immuneddieiency vires,FIV)慢病毒载体;后者转染至成肌细胞;用荧光显微镜、激光共聚焦显微镜检测EGFP以确定转染的阳性率;应用免疫组化方法 检测AMF的表达. 结果 经过2周的原代培养及纯化,可获得纯度为98%的成肌细胞,在转染复数(multiplieity ofinfection,MOI)为100时,可获得90.4%(P<0.01)的转染阳性率,而转染后的AMF基因能正常表达. 结论 组织块培养法适合成肌细胞的原代培养;FIV载体能以高转染率将AMF基因转至大鼠成肌细胞,并获得高效的表达.该方法 为一种较理想的AMF基因转染模式.%Objective To explore a safe and high efficiency way of gene transfection of autocrine motility factor(AMF) in order to provide experimental basis for transplantation of myoblasts carrying AMF gone. Methods Sprague Dawley rat myoblasts were cultured, purified, proliferated and immunohisto-chemically verified. Then, the myoblasts were transfected with AMF and eGFP (enhanced green fluores-cent protein) gene by FIV (feline immunodeficiency virus). Fluorescence microscope and laser scanning confocal microscope were employed to detect eGFP so as to verify positive transfection rate. Expression of AMF was detected by immunohistochemical method. Results Myoblasts with 98% purity could he ob-tained after two weeks of primary culture and purification. Positive transfection rate reached 90.4% when MOI (multiplicity of infection) was 100 (P <0.01). The transfected AMF gene could express normally. Conclusions Explant culture is a proper way in rat myoblast culture. Meanwhile, AMF gene can

  9. 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.

  10. 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.

  11. Role of autocrine osteopontin in promoting multiple functions of murine Nf1+/-osteoclast%自分泌骨桥蛋白在Nf1+/-小鼠破骨细胞功能增强中的作用

    Institute of Scientific and Technical Information of China (English)

    李会杰; 刘亚玲; 井永敏; 张英泽; 王振昊; 闫金成

    2013-01-01

    Objective To detect the osteopontin (OPN) autocrine function of the osteoclasts in neurofibromatosis type 1 heterozygote (Nfl+/-) and wild type (Nfl+/+) mice.Test the osteoclasts function of neurofibromatosis type 1 heterozygote (Nfl+/-) and wild type (Nil+/+) mice with exogenous neutralizing OPN antibody,analysis the role of autocrine OPN in the hyperfunction of osteoclast in neurofibromatosis type 1.Methods Culture the low density bone marrow cells from Nfl heterozygote (Nfl+/-) and wild type (Nfl+/+) mice (4-6 weeks old) with macrophage colony-stimulating factor (M-CSF) and receptor activator of NF-κB ligand(RANKL),Measure.the OPN concentration in osteoclast culture superenant with ELISA.Culture the low density bone marrow cells from Nf1+/-and Nf1+/+ mice with or without exogenous neutralizing antibody for OPN.The function of osteoclasts and osteoclast progenitors in formation,migration,adhesion,and bone absorption were tested.Results A significantly higher concentration of OPN was detected in the Nf1+/-osteoclast culture media as compared to that of wild type.In control,Osteoclast functions,including migration,adhesion,and bone resorption of Nf1 +/-were higher than that of wild type.Addition OPN neutralizing antibody to the Nf1+/-OCL significantly reduced OCL formation.Neutralizing OPN antibody diminished both wild type and Nf1+/-OCL adhensiontion,Anti-OPN minimized OCL migration in both wild type and Nf1 +/-OCL cultures as measured by the transwell assays.Neutralizing OPN antibody diminished both wild type and Nf1+/-OCL pit formation,P>0.05 for comparing Nfl+/-vs.wild type OCLs with anti-OPN antibody.Conclusion The hyperfunction of osteoclast in Nf1 heterozygote is related with autocrine osteopontin,inhibition of OPN may be an effective treatment for bone destruction of neurofibromatosis type 1.%目的 研究体外培养的Nf1+/-小鼠破骨细胞合成、分泌骨桥蛋白(osteopontin,OPN)的能力,应用OPN中和抗体抑制破骨细胞分泌的OPN,测

  12. 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...

  13. Functional Erythropoietin Autocrine Loop in Melanoma

    OpenAIRE

    Kumar, Suresh M; Acs, Geza; Fang, Dong; Herlyn, Meenhard; Elder, David E.; Xu, Xiaowei

    2005-01-01

    Although erythropoietin (Epo) is a known stimulator of erythropoiesis, recent evidence suggests that its biological functions are not confined to hematopoietic cells. To elucidate the role of Epo and erythropoietin receptor (EpoR) in melanoma, we examined the expression and function of these proteins in melanocytes and melanoma cells. We found increased expression of Epo in melanoma cells compared to melanocyte in vitro. EpoR was also strongly expressed in all of the melanoma cell lines and t...

  14. Making detailed predictions makes (some) predictions worse

    Science.gov (United States)

    Kelly, Theresa F.

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

  15. 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

  16. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

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

    Genomic prediction uses markers (SNPs) across the whole genome to predict individual breeding values at an early growth stage potentially before large scale phenotyping. One of the applications of genomic prediction in plant breeding is to identify the best individual candidate lines to contribut...

  17. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

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

    2015-01-01

    Genomic prediction uses markers (SNPs) across the whole genome to predict individual breeding values at an early growth stage potentially before large scale phenotyping. One of the applications of genomic prediction in plant breeding is to identify the best individual candidate lines to contribut...

  18. Applied predictive control

    CERN Document Server

    Sunan, Huang; Heng, Lee Tong

    2002-01-01

    The presence of considerable time delays in the dynamics of many industrial processes, leading to difficult problems in the associated closed-loop control systems, is a well-recognized phenomenon. The performance achievable in conventional feedback control systems can be significantly degraded if an industrial process has a relatively large time delay compared with the dominant time constant. Under these circumstances, advanced predictive control is necessary to improve the performance of the control system significantly. The book is a focused treatment of the subject matter, including the fundamentals and some state-of-the-art developments in the field of predictive control. Three main schemes for advanced predictive control are addressed in this book: • Smith Predictive Control; • Generalised Predictive Control; • a form of predictive control based on Finite Spectrum Assignment. A substantial part of the book addresses application issues in predictive control, providing several interesting case studie...

  19. 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.

  20. 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...

  1. Distribution Free Prediction Bands

    CERN Document Server

    Lei, Jing

    2012-01-01

    We study distribution free, nonparametric prediction bands with a special focus on their finite sample behavior. First we investigate and develop different notions of finite sample coverage guarantees. Then we give a new prediction band estimator by combining the idea of "conformal prediction" (Vovk et al. 2009) with nonparametric conditional density estimation. The proposed estimator, called COPS (Conformal Optimized Prediction Set), always has finite sample guarantee in a stronger sense than the original conformal prediction estimator. Under regularity conditions the estimator converges to an oracle band at a minimax optimal rate. A fast approximation algorithm and a data driven method for selecting the bandwidth are developed. The method is illustrated first in simulated data. Then, an application shows that the proposed method gives desirable prediction intervals in an automatic way, as compared to the classical linear regression modeling.

  2. 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.

  3. Solar Cycle Predictions

    Science.gov (United States)

    Pesnell, William Dean

    2012-01-01

    Solar cycle predictions are needed to plan long-term space missions; just like weather predictions are needed to plan the launch. Fleets of satellites circle the Earth collecting many types of science data, protecting astronauts, and relaying information. All of these satellites are sensitive at some level to solar cycle effects. Predictions of drag on LEO spacecraft are one of the most important. Launching a satellite with less propellant can mean a higher orbit, but unanticipated solar activity and increased drag can make that a Pyrrhic victory as you consume the reduced propellant load more rapidly. Energetic events at the Sun can produce crippling radiation storms that endanger all assets in space. Solar cycle predictions also anticipate the shortwave emissions that cause degradation of solar panels. Testing solar dynamo theories by quantitative predictions of what will happen in 5-20 years is the next arena for solar cycle predictions. A summary and analysis of 75 predictions of the amplitude of the upcoming Solar Cycle 24 is presented. The current state of solar cycle predictions and some anticipations how those predictions could be made more accurate in the future will be discussed.

  4. 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....

  5. 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.

  6. 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...... query sequences these probabilities are obtained by a neural net that has previously been trained on a variety of functionally important features. On a training set of sequences we assess the relevance of individual functional categories for identifying a given structural family. Using a combination...... of the most relevant categories, the likelihood of a query sequence to belong to a specific family can be estimated. Results: The performance of the method is evaluated using cross-validation. For a fixed structural family and for every sequence, a score is calculated that measures the evidence for family...

  7. '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...

  8. 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.

  9. 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...

  10. The Prediction Value

    NARCIS (Netherlands)

    Koster, M.; Kurz, S.; Lindner, I.; Napel, S.

    2013-01-01

    We introduce the prediction value (PV) as a measure of players’ informational importance in probabilistic TU games. The latter combine a standard TU game and a probability distribution over the set of coalitions. Player i’s prediction value equals the difference between the conditional expectations

  11. Prediction by Compression

    CERN Document Server

    Ratsaby, Joel

    2010-01-01

    It is well known that text compression can be achieved by predicting the next symbol in the stream of text data based on the history seen up to the current symbol. The better the prediction the more skewed the conditional probability distribution of the next symbol and the shorter the codeword that needs to be assigned to represent this next symbol. What about the opposite direction ? suppose we have a black box that can compress text stream. Can it be used to predict the next symbol in the stream ? We introduce a criterion based on the length of the compressed data and use it to predict the next symbol. We examine empirically the prediction error rate and its dependency on some compression parameters.

  12. 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

  13. Evolution prediction from tomography

    Science.gov (United States)

    Dominy, Jason M.; Venuti, Lorenzo Campos; Shabani, Alireza; Lidar, Daniel A.

    2017-03-01

    Quantum process tomography provides a means of measuring the evolution operator for a system at a fixed measurement time t. The problem of using that tomographic snapshot to predict the evolution operator at other times is generally ill-posed since there are, in general, infinitely many distinct and compatible solutions. We describe the prediction, in some "maximal ignorance" sense, of the evolution of a quantum system based on knowledge only of the evolution operator for finitely many times 0evolution at times away from the measurement times. Even if the original evolution is unitary, the predicted evolution is described by a non-unitary, completely positive map.

  14. 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.

  15. Wind Power Prediction Investigation

    Directory of Open Access Journals (Sweden)

    Yuanlong Liu

    2013-02-01

    Full Text Available Daily and real-time forecast data of wind power is predicted in this study using three methods, which are Kalman filter model, GARCH model and time-series-based BP neural network model. Then, owing to evaluation to the calculation of accuracy and qualification rate, the best method, the time-series-based BP neural network model, was selected for its highest accuracy. Moreover, the prediction error influence due to convergence of wind turbine is on consideration according to the evaluation. Finally, suggestions of improving the prediction accuracy were put forward based on the discussion of accuracy-obstacle factors.

  16. Chapter VII. Predicting Fertility

    Science.gov (United States)

    Section 2. Visual and Microscopic Approaches for Differentiating Unfertilized Germinal Discs and Early dead Embryos from Pre-Incubated Blastoderms Section 3. Predicting the Duration of fertility by Counting Sperm in the Outer Perivitelline Layer of Laid Eggs...

  17. Outcome predictability biases learning.

    Science.gov (United States)

    Griffiths, Oren; Mitchell, Chris J; Bethmont, Anna; Lovibond, Peter F

    2015-01-01

    Much of contemporary associative learning research is focused on understanding how and when the associative history of cues affects later learning about those cues. Very little work has investigated the effects of the associative history of outcomes on human learning. Three experiments extended the "learned irrelevance" paradigm from the animal conditioning literature to examine the influence of an outcome's prior predictability on subsequent learning of relationships between cues and that outcome. All 3 experiments found evidence for the idea that learning is biased by the prior predictability of the outcome. Previously predictable outcomes were readily associated with novel predictive cues, whereas previously unpredictable outcomes were more readily associated with novel nonpredictive cues. This finding highlights the importance of considering the associative history of outcomes, as well as cues, when interpreting multistage designs. Associative and cognitive explanations of this certainty matching effect are discussed.

  18. 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.

  19. Highlights, predictions, and changes.

    Science.gov (United States)

    Jeang, Kuan-Teh

    2012-11-15

    Recent literature highlights at Retrovirology are described. Predictions are made regarding "hot" retrovirology research trends for the coming year based on recent journal access statistics. Changes in Retrovirology editor and the frequency of the Retrovirology Prize are announced.

  20. 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...

  1. Predicted value of $0 \\, \

    CERN Document Server

    Maedan, Shinji

    2016-01-01

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

  2. Predicting Online Purchasing Behavior

    OpenAIRE

    W.R BUCKINX; D. VAN DEN POEL

    2003-01-01

    This empirical study investigates the contribution of different types of predictors to the purchasing behaviour at an online store. We use logit modelling to predict whether or not a purchase is made during the next visit to the website using both forward and backward variable-selection techniques, as well as Furnival and Wilson’s global score search algorithm to find the best subset of predictors. We contribute to the literature by using variables from four different categories in predicting...

  3. Nonparametric Predictive Regression

    OpenAIRE

    Ioannis Kasparis; Elena Andreou; Phillips, Peter C.B.

    2012-01-01

    A unifying framework for inference is developed in predictive regressions where the predictor has unknown integration properties and may be stationary or nonstationary. Two easily implemented nonparametric F-tests are proposed. The test statistics are related to those of Kasparis and Phillips (2012) and are obtained by kernel regression. The limit distribution of these predictive tests holds for a wide range of predictors including stationary as well as non-stationary fractional and near unit...

  4. Aircraft Noise Prediction

    OpenAIRE

    2014-01-01

    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 add...

  5. 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.

  6. 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.

  7. Cytomics in predictive medicine

    Science.gov (United States)

    Tarnok, Attila; Valet, Guenther K.

    2004-07-01

    Predictive Medicine aims at the detection of changes in patient's disease state prior to the manifestation of deterioration or improvement of the current status. Patient-specific, disease-course predictions with >95% or >99% accuracy during therapy would be highly valuable for everyday medicine. If these predictors were available, disease aggravation or progression, frequently accompanied by irreversible tissue damage or therapeutic side effects, could then potentially be avoided by early preventive therapy. The molecular analysis of heterogeneous cellular systems (Cytomics) by cytometry in conjunction with pattern-oriented bioinformatic analysis of the multiparametric cytometric and other data provides a promising approach to individualized or personalized medical treatment or disease management. Predictive medicine is best implemented by cell oriented measurements e.g. by flow or image cytometry. Cell oriented gene or protein arrays as well as bead arrays for the capture of solute molecules form serum, plasma, urine or liquor are equally of high value. Clinical applications of predictive medicine by Cytomics will include multi organ failure in sepsis or non infectious posttraumatic shock in intensive care, or the pretherapeutic identification of high risk patients in cancer cytostatic. Early individualized therapy may provide better survival chances for individual patient at concomitant cost containment. Predictive medicine guided early reduction or stop of therapy may lower or abrogate potential therapeutic side effects. Further important aspects of predictive medicine concern the preoperative identification of patients with a tendency for postoperative complications or coronary artery disease patients with an increased tendency for restenosis. As a consequence, better patient care and new forms of inductive scientific hypothesis development based on the interpretation of predictive data patterns are at reach.

  8. 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.

  9. Predicting tile drainage discharge

    DEFF Research Database (Denmark)

    Iversen, Bo Vangsø; Kjærgaard, Charlotte; Petersen, Rasmus Jes;

    of the water load coming from the tile drainage system is therefore essential. This work aims at predicting tile drainage discharge using dynamic as well as a statistical predictive models. A large dataset of historical tile drain discharge data, daily discharge values as well as yearly average values were......More than 50 % of Danish agricultural areas are expected to be artificial tile drained. Transport of water and nutrients through the tile drain system to the aquatic environment is expected to be significant. For different mitigation strategies such as constructed wetlands an exact knowledge...... used in the analysis. For the dynamic modelling, a simple linear reservoir model was used where different outlets in the model represented tile drain as well as groundwater discharge outputs. This modelling was based on daily measured tile drain discharge values. The statistical predictive model...

  10. Partially predictable chaos

    CERN Document Server

    Wernecke, Hendrik; Gros, Claudius

    2016-01-01

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

  11. Basis of predictive mycology.

    Science.gov (United States)

    Dantigny, Philippe; Guilmart, Audrey; Bensoussan, Maurice

    2005-04-15

    For over 20 years, predictive microbiology focused on food-pathogenic bacteria. Few studies concerned modelling fungal development. On one hand, most of food mycologists are not familiar with modelling techniques; on the other hand, people involved in modelling are developing tools dedicated to bacteria. Therefore, there is a tendency to extend the use of models that were developed for bacteria to moulds. However, some mould specificities should be taken into account. The use of specific models for predicting germination and growth of fungi was advocated previously []. This paper provides a short review of fungal modelling studies.

  12. Prediction of Antibody Epitopes

    DEFF Research Database (Denmark)

    Nielsen, Morten; Marcatili, Paolo

    2015-01-01

    Antibodies recognize their cognate antigens in a precise and effective way. In order to do so, they target regions of the antigenic molecules that have specific features such as large exposed areas, presence of charged or polar atoms, specific secondary structure elements, and lack of similarity...... to 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...

  13. 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

  14. Nuclear level density predictions

    Directory of Open Access Journals (Sweden)

    Bucurescu Dorel

    2015-01-01

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

  15. A Characterization of Prediction Errors

    OpenAIRE

    Meek, Christopher

    2016-01-01

    Understanding prediction errors and determining how to fix them is critical to building effective predictive systems. In this paper, we delineate four types of prediction errors and demonstrate that these four types characterize all prediction errors. In addition, we describe potential remedies and tools that can be used to reduce the uncertainty when trying to determine the source of a prediction error and when trying to take action to remove a prediction errors.

  16. 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.

  17. 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.

  18. 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 been...

  19. 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:

  20. Space Weather Prediction

    Science.gov (United States)

    2014-10-31

    Mason University (Odstrcil), worked to modify the WSA-Enlil operational solar wind model so that it runs in a more realistic, time-dependent fashion...Ruždjak, D., Cliver, E., Svalgaard, L., and Roth , M., “On solar cycle predictions and reconstructions,” Astronomy & Astrophysics, 496, Mar 2009, pp

  1. Predicting Visibility of Aircraft

    Science.gov (United States)

    Watson, Andrew; Ramirez, Cesar V.; Salud, Ellen

    2009-01-01

    Visual detection of aircraft by human observers is an important element of aviation safety. To assess and ensure safety, it would be useful to be able to be able to predict the visibility, to a human observer, of an aircraft of specified size, shape, distance, and coloration. Examples include assuring safe separation among aircraft and between aircraft and unmanned vehicles, design of airport control towers, and efforts to enhance or suppress the visibility of military and rescue vehicles. We have recently developed a simple metric of pattern visibility, the Spatial Standard Observer (SSO). In this report we examine whether the SSO can predict visibility of simulated aircraft images. We constructed a set of aircraft images from three-dimensional computer graphic models, and measured the luminance contrast threshold for each image from three human observers. The data were well predicted by the SSO. Finally, we show how to use the SSO to predict visibility range for aircraft of arbitrary size, shape, distance, and coloration. PMID:19462007

  2. Predicting Reasoning from Memory

    Science.gov (United States)

    Heit, Evan; Hayes, Brett K.

    2011-01-01

    In an effort to assess the relations between reasoning and memory, in 8 experiments, the authors examined how well responses on an inductive reasoning task are predicted from responses on a recognition memory task for the same picture stimuli. Across several experimental manipulations, such as varying study time, presentation frequency, and the…

  3. Predictive models in urology.

    Science.gov (United States)

    Cestari, Andrea

    2013-01-01

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

  4. 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...

  5. Highlights, predictions, and changes

    Directory of Open Access Journals (Sweden)

    Jeang Kuan-Teh

    2012-11-01

    Full Text Available Abstract Recent literature highlights at Retrovirology are described. Predictions are made regarding “hot” retrovirology research trends for the coming year based on recent journal access statistics. Changes in Retrovirology editor and the frequency of the Retrovirology Prize are announced.

  6. Highlights, predictions, and changes

    OpenAIRE

    Jeang Kuan-Teh

    2012-01-01

    Abstract Recent literature highlights at Retrovirology are described. Predictions are made regarding “hot” retrovirology research trends for the coming year based on recent journal access statistics. Changes in Retrovirology editor and the frequency of the Retrovirology Prize are announced.

  7. 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…

  8. Neurological abnormalities predict disability

    DEFF Research Database (Denmark)

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

    2014-01-01

    To investigate the role of neurological abnormalities and magnetic resonance imaging (MRI) lesions in predicting global functional decline in a cohort of initially independent-living elderly subjects. The Leukoaraiosis And DISability (LADIS) Study, involving 11 European centres, was primarily aimed...

  9. Hypotheses and Inductive Predictions

    NARCIS (Netherlands)

    ROMEYN, J.-W.

    2008-01-01

    ABSTRACT. This paper studies the use of hypotheses schemes in generating inductive predictions. After discussing Carnap–Hintikka inductive logic, hypotheses schemes are defined and illustrated with two partitions. One partition results in the Carnapian continuum of inductive methods, the other resul

  10. 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…

  11. Predicting rainfall beyond tomorrow

    Science.gov (United States)

    NOAA’s Climate Prediction Center issues climate precipitation forecasts that offer potential support for water resource managers and farmers and ranchers in New Mexico, but the forecasts are frequently misunderstood and not widely used in practical decision making. The objectives of this newsletter ...

  12. Genetically optimizing weather predictions

    Science.gov (United States)

    Potter, S. B.; Staats, Kai; Romero-Colmenero, Encarni

    2016-07-01

    humidity, air pressure, wind speed and wind direction) into a database. Built upon this database, we have developed a remarkably simple approach to derive a functional weather predictor. The aim is provide up to the minute local weather predictions in order to e.g. prepare dome environment conditions ready for night time operations or plan, prioritize and update weather dependent observing queues. In order to predict the weather for the next 24 hours, we take the current live weather readings and search the entire archive for similar conditions. Predictions are made against an averaged, subsequent 24 hours of the closest matches for the current readings. We use an Evolutionary Algorithm to optimize our formula through weighted parameters. The accuracy of the predictor is routinely tested and tuned against the full, updated archive to account for seasonal trends and total, climate shifts. The live (updated every 5 minutes) SALT weather predictor can be viewed here: http://www.saao.ac.za/ sbp/suthweather_predict.html

  13. 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.

  14. 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.

  15. FGF19 functions as autocrine growth factor for hepatoblastoma

    OpenAIRE

    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 in...

  16. Autocrine and Paracrine Hh Signaling Regulate Prostate Development

    Science.gov (United States)

    2010-09-01

    development and tumorigenesis (13). The forkhead transcription factor Foxe1 was established as a downstream target of the Shh pathway in hair follicle morpho...in the epithelium of the developing prostate; activate Hh target genes expressed in the surrounding mesenchyme and influence prostate ductal growth...postanatally. We propose this temporal growth effects is mediated by the discordant regulation of a subset of target genes by Hh signaling in the prenatal and

  17. 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

  18. 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...

  19. Essays on Earnings Predictability

    DEFF Research Database (Denmark)

    Bruun, Mark

    affect the accuracy of analysts´earnings forecasts. Finally, the objective of the dissertation is to investigate how the stock market is affected by the accuracy of corporate earnings projections. The dissertation contributes to a deeper understanding of these issues. First, it is shown how earnings...... of analysts’ earnings forecasts. Furthermore, the dissertation shows how the stock market’s reaction to the disclosure of information about corporate earnings depends on how well corporate earnings can be predicted. The dissertation indicates that the stock market’s reaction to the disclosure of earnings...... forecasts are not more accurate than the simpler forecasts based on a historical timeseries of earnings. Secondly, the dissertation shows how accounting standards affect analysts’ earnings predictions. Accounting conservatism contributes to a more volatile earnings process, which lowers the accuracy...

  20. 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.

  1. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

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

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

  2. 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...

  3. Prediction of the

    Directory of Open Access Journals (Sweden)

    Prasenjit Dey

    2016-06-01

    Full Text Available The aerodynamic behavior of a square cylinder with rounded corner edges in steady flow regime in the range of Reynolds number (Re 5–45; is predicted by Artificial Neural Network (ANN using MATLAB. The ANN has trained by back propagation algorithm. The ANN requires input and output data to train the network, which is obtained from the commercial Computational Fluid Dynamics (CFD software FLUENT in the present study. In FLUENT, all the governing equations are discretized by the finite volume method. Results from numerical simulation and back propagation based ANN have been compared. It has been discovered that the ANN predicts the aerodynamic behavior correctly within the given range of the training data. It is additionally observed that back propagation based ANN is an effective tool to forecast the aerodynamic behavior than simulation, that has very much longer computational time.

  4. Predictability of Critical Transitions

    CERN Document Server

    Zhang, Xiaozhu; Hallerberg, Sarah

    2015-01-01

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

  5. 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.

  6. Urban pluvial flood prediction

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Nielsen, Jesper Ellerbæk; Jensen, David Getreuer

    2016-01-01

    historically and in real-time. There is a rather untested potential in real-time prediction of urban floods. In this paper radar data observations with different spatial and temporal resolution, radar nowcasts of 0–2 h lead time, and numerical weather models with lead times up to 24 h are used as inputs......Flooding produced by high-intensive local rainfall and drainage system capacity exceedance can have severe impacts in cities. In order to prepare cities for these types of flood events – especially in the future climate – it is valuable to be able to simulate these events numerically both...... to an integrated flood and drainage systems model in order to investigate the relative difference between different inputs in predicting future floods. The system is tested on a small town Lystrup in Denmark, which has been flooded in 2012 and 2014. Results show it is possible to generate detailed flood maps...

  7. Predictability of Solar Flares

    Science.gov (United States)

    Mares, Peter; Balasubramaniam, K. S.

    2009-05-01

    Solar flares are significant drivers of space weather. With the availability of high cadence solar chromospheric and photospheric data from the USAF's Optical Solar PAtrol Network (OSPAN; photosphere and chromosphere imaging) Telescope and the Global Oscillations Network Group (GONG; photosphere magnetic imaging), at the National Solar Observatory, we have gained insights into potential uses of the data for solar flare prediction. We apply the Principal Component Analysis (PCA) to parameterize the flaring system and extract consistent observables at solar chromospheric and photospheric layers that indicate a viable recognition of flaring activity. Rather than limiting ourselves to a few known indicators of solar activity, PCA helps us to characterize the entire system using several tens of variables for each observed layer. The components of the Eigen vectors derived from PCA help us recognize and quantify innate characteristics of solar flares and compare them. We will present an analysis of these results to explore the viability of PCA to assist in predicting solar flares.

  8. Predicting Anthracycline Benefit

    DEFF Research Database (Denmark)

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

    2015-01-01

    as measured with a centromere enumeration probe (CEP17) predicted sensitivity to anthracyclines, we report here an individual patient-level pooled analysis of data from five trials comparing anthracycline-based chemotherapy with CMF (cyclophosphamide, methotrexate, and fluorouracil) as adjuvant chemotherapy.......6% (TOP2A) of 3,846 patient cases with available tissue. Both CEP17and TOP2A treatment-by-marker interactions remained significant in adjusted analyses for recurrence-free and overall survival, whereas HER2 did not. A combined CEP17 and TOP2A-adjusted model predicted anthracycline benefit across all five...... trials for both recurrence-free (hazard ratio, 0.64; 95% CI, 0.51 to 0.82; P = .001) and overall survival (hazard ratio, 0.66; 95% CI, 0.51 to 0.85; P = .005). CONCLUSION: This prospectively planned individual-patient pooled analysis of patient cases from five adjuvant trials confirms that patients whose...

  9. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

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

    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 the way predicted by the law of small numbers as formalized in recent behavioral theory. In particular......, 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”....

  10. Crystal structure and prediction.

    Science.gov (United States)

    Thakur, Tejender S; Dubey, Ritesh; Desiraju, Gautam R

    2015-04-01

    The notion of structure is central to the subject of chemistry. This review traces the development of the idea of crystal structure since the time when a crystal structure could be determined from a three-dimensional diffraction pattern and assesses the feasibility of computationally predicting an unknown crystal structure of a given molecule. Crystal structure prediction is of considerable fundamental and applied importance, and its successful execution is by no means a solved problem. The ease of crystal structure determination today has resulted in the availability of large numbers of crystal structures of higher-energy polymorphs and pseudopolymorphs. These structural libraries lead to the concept of a crystal structure landscape. A crystal structure of a compound may accordingly be taken as a data point in such a landscape.

  11. 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.

  12. Predictive dynamic digital holography

    Science.gov (United States)

    Sulaiman, Sennan; Gibson, Steve; Spencer, Mark

    2016-09-01

    Digital holography has received recent attention for many imaging and sensing applications, including imaging through turbulent and turbid media, adaptive optics, three dimensional projective display technology and optical tweezing. A significant obstacle for digital holography in real-time applications, such as wavefront sensing for high energy laser systems and high speed imaging for target tracking, is the fact that digital holography is computationally intensive; it requires iterative virtual wavefront propagation and hill-climbing to optimize some sharpness criteria. This paper demonstrates real-time methods for digital holography based on approaches developed recently at UCLA for optimal and adaptive identification, prediction, and control of optical wavefronts. The methods presented integrate minimum variance wavefront prediction into digital holography schemes to short-circuit the computationally intensive algorithms for iterative propagation of virtual wavefronts and hill climbing for sharpness optimization.

  13. 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.

  14. 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.

  15. Characterization of Mesoscale Predictability

    Science.gov (United States)

    2013-09-30

    assimilation to either create pairs of different initial conditions (Bei and Zhang 2007, Mapes et al. 2008) or to initialize a large ensemble (Durran et...curves over all wave numbers where the error had not yet saturated. Following the terminology suggested by Mapes et al. (2008), the evolution of... Mapes , B., S. Tulich, T. Nasuno, and M. Satoh, 2008: Predictability aspects of global aqua- planet simulations with explicit convection. J. Meteor. Soc

  16. Nominal Model Predictive Control

    OpenAIRE

    Grüne, Lars

    2014-01-01

    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...

  17. 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...

  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.

  19. Prediction of Algebraic Instabilities

    Science.gov (United States)

    Zaretzky, Paula; King, Kristina; Hill, Nicole; Keithley, Kimberlee; Barlow, Nathaniel; Weinstein, Steven; Cromer, Michael

    2016-11-01

    A widely unexplored type of hydrodynamic instability is examined - large-time algebraic growth. Such growth occurs on the threshold of (exponentially) neutral stability. A new methodology is provided for predicting the algebraic growth rate of an initial disturbance, when applied to the governing differential equation (or dispersion relation) describing wave propagation in dispersive media. Several types of algebraic instabilities are explored in the context of both linear and nonlinear waves.

  20. 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.

  1. Kuiper Belt Occultation Predictions

    CERN Document Server

    Fraser, Wesley C; Trujillo, Chad; Stephens, Andrew W; Kavelaars, JJ; Brown, Michael E; Bianco, Federica B; Boyle, Richard P; Brucker, Melissa J; Hetherington, Nathan; Joner, Michael; Keel, William C; Langill, Phil P; Lister, Tim; McMillan, Russet J; Young, Leslie

    2013-01-01

    Here we present observations of 7 large Kuiper Belt Objects. From these observations, we extract a point source catalog with $\\sim0.01"$ precision, and astrometry of our target Kuiper Belt Objects with $0.04-0.08"$ precision within that catalog. We have developed a new technique to predict the future occurrence of stellar occultations by Kuiper Belt Objects. The technique makes use of a maximum likelihood approach which determines the best-fit adjustment to cataloged orbital elements of an object. Using simulations of a theoretical object, we discuss the merits and weaknesses of this technique compared to the commonly adopted ephemeris offset approach. We demonstrate that both methods suffer from separate weaknesses, and thus, together provide a fair assessment of the true uncertainty in a particular prediction. We present occultation predictions made by both methods for the 7 tracked objects, with dates as late as 2015. Finally, we discuss observations of three separate close passages of Quaoar to field star...

  2. Predicting Human Cooperation.

    Directory of Open Access Journals (Sweden)

    John J Nay

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

  3. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

    2016-11-29

    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  4. 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.

  5. 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...

  6. 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...... and water–MEG–aliphatic hydrocarbons LLE using interaction parameters obtained from the binary data alone. Moreover, it is demonstrated that the NRHB equation of state is a versatile tool which can be employed equally well to mixtures with pharmaceuticals and solvents, including mixed solvents, as well...

  7. 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 marine atmospheric and submersed South Scandinavian environment. The design parameters are based on sequential measurements of 86 chloride profiles taken over ten years from 13 different types of concrete. The design parameters provide the input for an analytical model for chloride profiles as function...

  8. 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

  9. 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....

  10. Consciousness -- A Verifiable Prediction

    Science.gov (United States)

    Panchapakesan, N.

    2014-07-01

    Consciousness may or may not be completely within the realm of science. We have argued elsewhere that there is a high probability that it is not within the purview of science, just like humanities and arts are outside science. Even social sciences do not come under science when human interactions are involved. Here, we suggest a possible experiment to decide whether it is part of science. We suggest that a scientific signal may be available to investigate the prediction in the form of an electromagnetic brainwave background radiation.

  11. Predicting photothermal field performance

    Science.gov (United States)

    Gonzalez, C. C.; Ross, R. G., Jr.

    1984-01-01

    Photothermal field performance in flat plate solar collectors was predicted. An analytical model which incorporates the measured dependency between transmittance loss and UV and temperature exposure levels was developed. The model uses SOLMET weather data extrapolated to 30 years for various sites and module mounting configurations. It is concluded that the temperature is the key to photothermally induced transmittance loss. The sensitivity of transmittance loss to UV level is nonlinear with minimum in curve near one sun. The ethylene vinyl acetate (EVA) results are consistent with 30 year life allocation.

  12. 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.

  13. Theory use in social predictions.

    Science.gov (United States)

    Bazinger, Claudia; Kühberger, Anton

    2012-12-01

    In a commentary to our article on the role of theory and simulation in social predictions, Krueger (2012) argues that the role of theory is neglected in social psychology for a good reason. He considers evidence indicating that people readily generalize from themselves to others. In response, we stress the role of theoretical knowledge in predicting other people's behavior. Importantly, prediction by simulation and prediction by theory can lead to high as well as to low correlations between own and predicted behavior. This renders correlations largely useless for identifying the prediction strategy. We argue that prediction by theory is a serious alternative to prediction by simulation, and that reliance on correlation has led to a bias toward simulation.

  14. Theory use in social predictions

    OpenAIRE

    Bazinger, Claudia; Kühberger, Anton

    2012-01-01

    In a commentary to our article on the role of theory and simulation in social predictions, Krueger (2012) argues that the role of theory is neglected in social psychology for a good reason. He considers evidence indicating that people readily generalize from themselves to others. In response, we stress the role of theoretical knowledge in predicting other people’s behavior. Importantly, prediction by simulation and prediction by theory can lead to high as well as to low correlations between o...

  15. 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....

  16. Epitope prediction methods

    DEFF Research Database (Denmark)

    Karosiene, Edita

    Major histocompatibility complex (MHC) molecules play a crucial role in adaptive immunity by sampling peptides from self and non-self proteins to be recognised by the immune system. MHC molecules present peptides on cell surfaces for recognition by CD8+ and CD4+ T lymphocytes that can initiate...... immune responses. Therefore, it is of great importance to be able to identify peptides that bind to MHC molecules, in order to understand the nature of immune responses and discover T cell epitopes useful for designing new vaccines and immunotherapies. MHC molecules in humans, referred to as human...... 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...

  17. 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....... The relationships between permeability and porosity from core data were first examined using Kozeny’s equation. The data were analyzed for any correlations to the specific surface of the grain, Sg, and to the hydraulic property defined as the flow zone indicator (FZI). These two methods use two different approaches...... to enhance permeability prediction fromKozeny’s equation. The FZI is based on a concept of a tortuous flow path in a granular bed. The Sg concept considers the pore space that is exposed to fluid flow and models permeability resulting from effective flow parallel to pressure drop. The porosity-permeability...

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

  19. 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.

  20. Predictive coarse-graining

    Science.gov (United States)

    Schöberl, Markus; Zabaras, Nicholas; Koutsourelakis, Phaedon-Stelios

    2017-03-01

    We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a probabilistic coarse-to-fine map. This corresponds to a directed probabilistic model where the coarse variables play the role of latent generators of the fine scale (all-atom) data. From an information-theoretic perspective, the framework proposed provides an improvement upon the relative entropy method [1] and is capable of quantifying the uncertainty due to the information loss that unavoidably takes place during the coarse-graining process. Furthermore, it can be readily extended to a fully Bayesian model where various sources of uncertainties are reflected in the posterior of the model parameters. The latter can be used to produce not only point estimates of fine-scale reconstructions or macroscopic observables, but more importantly, predictive posterior distributions on these quantities. Predictive posterior distributions reflect the confidence of the model as a function of the amount of data and the level of coarse-graining. The issues of model complexity and model selection are seamlessly addressed by employing a hierarchical prior that favors the discovery of sparse solutions, revealing the most prominent features in the coarse-grained model. A flexible and parallelizable Monte Carlo - Expectation-Maximization (MC-EM) scheme is proposed for carrying out inference and learning tasks. A comparative assessment of the proposed methodology is presented for a lattice spin system and the SPC/E water model.

  1. Protein docking prediction using predicted protein-protein interface

    Directory of Open Access Journals (Sweden)

    Li Bin

    2012-01-01

    Full Text Available Abstract Background Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. Results We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm, is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. Conclusion We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

  2. Data-Based Predictive Control with Multirate Prediction Step

    Science.gov (United States)

    Barlow, Jonathan S.

    2010-01-01

    Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

  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. Emerging approaches in predictive toxicology.

    Science.gov (United States)

    Zhang, Luoping; McHale, Cliona M; Greene, Nigel; Snyder, Ronald D; Rich, Ivan N; Aardema, Marilyn J; Roy, Shambhu; Pfuhler, Stefan; Venkatactahalam, Sundaresan

    2014-12-01

    Predictive toxicology plays an important role in the assessment of toxicity of chemicals and the drug development process. While there are several well-established in vitro and in vivo assays that are suitable for predictive toxicology, recent advances in high-throughput analytical technologies and model systems are expected to have a major impact on the field of predictive toxicology. This commentary provides an overview of the state of the current science and a brief discussion on future perspectives for the field of predictive toxicology for human toxicity. Computational models for predictive toxicology, needs for further refinement and obstacles to expand computational models to include additional classes of chemical compounds are highlighted. Functional and comparative genomics approaches in predictive toxicology are discussed with an emphasis on successful utilization of recently developed model systems for high-throughput analysis. The advantages of three-dimensional model systems and stem cells and their use in predictive toxicology testing are also described.

  5. Useful theories make predictions.

    Science.gov (United States)

    Howes, Andrew

    2012-01-01

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

  6. 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...

  7. 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.

  8. Predicting the unpredictable.

    Science.gov (United States)

    Bonabeau, Eric

    2002-03-01

    The collective behavior of people in crowds, markets, and organizations has long been a mystery. Why, for instance, do employee bonuses sometimes lead to decreases in productivity? Why do some products generate tremendous buzz, seemingly out of nowhere, while others languish despite multimillion-dollar marketing campaigns? How could a simple clerical error snowball into a catastrophic loss that bankrupts a financial institution? Traditional approaches like spreadsheet and regression analyses have failed to explain such "emergent phenomena," says Eric Bonabeau, because they work from the top down, trying to apply global equations and frameworks to a particular situation. But the behavior of emergent phenomena, contends Bonabeau, is formed from the bottom up--starting with the local interactions of individuals who alter their actions in response to other participants. Together, the myriad interactions result in a group behavior that can easily elude any top-down analysis. But now, thanks to "agent-based modeling," some companies are finding ways to analyze--and even predict--emergent phenomena. Macy's, for instance, has used the technology to investigate better ways to design its department stores. Hewlett-Packard has run agent-based simulations to anticipate how changes in its hiring strategy would affect its corporate culture. And Société Générale has used the technology to determine the operational risk of its asset management group. This article discusses emergent phenomena in detail and explains why they have become more prevalent in recent years. In addition to providing real-world examples of companies that have improved their business practices through agent-based modeling, Bonabeau also examines the future of this technology and points to several fields that may be revolutionized by its use.

  9. Predictive regressions for macroeconomic data

    OpenAIRE

    Fukang Zhu; Zongwu Cai; Liang Peng

    2014-01-01

    Researchers have constantly asked whether stock returns can be predicted by some macroeconomic data. However, it is known that macroeconomic data may exhibit nonstationarity and/or heavy tails, which complicates existing testing procedures for predictability. In this paper we propose novel empirical likelihood methods based on some weighted score equations to test whether the monthly CRSP value-weighted index can be predicted by the log dividend-price ratio or the log earnings-price ratio. Th...

  10. Networked and Distributed Predictive Control

    CERN Document Server

    Christofides, Panagiotis D; De La Pena, David Munoz

    2011-01-01

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

  11. Total Ozone Prediction: Stratospheric Dynamics

    Science.gov (United States)

    Jackman, Charles H.; Kawa, S. Ramdy; Douglass, Anne R.

    2003-01-01

    The correct prediction of total ozone as a function of latitude and season is extremely important for global models. This exercise tests the ability of a particular model to simulate ozone. The ozone production (P) and loss (L) will be specified from a well- established global model and will be used in all GCMs for subsequent prediction of ozone. This is the "B-3 Constrained Run" from M&MII. The exercise mostly tests a model stratospheric dynamics in the prediction of total ozone. The GCM predictions will be compared and contrasted with TOMS measurements.

  12. Prediction based on mean subset

    DEFF Research Database (Denmark)

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

    2002-01-01

    , 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......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...

  13. A tutorial on conformal prediction

    CERN Document Server

    Shafer, Glenn

    2007-01-01

    Conformal prediction uses past experience to determine precise levels of confidence in new predictions. Given an error probability $\\epsilon$, together with a method that makes a prediction $\\hat{y}$ of a label $y$, it produces a set of labels, typically containing $\\hat{y}$, that also contains $y$ with probability $1-\\epsilon$. Conformal prediction can be applied to any method for producing $\\hat{y}$: a nearest-neighbor method, a support-vector machine, ridge regression, etc. Conformal prediction is designed for an on-line setting in which labels are predicted successively, each one being revealed before the next is predicted. The most novel and valuable feature of conformal prediction is that if the successive examples are sampled independently from the same distribution, then the successive predictions will be right $1-\\epsilon$ of the time, even though they are based on an accumulating dataset rather than on independent datasets. In addition to the model under which successive examples are sampled indepen...

  14. Solar Cycle Predictions (Invited Review)

    Science.gov (United States)

    Pesnell, W. Dean

    2012-11-01

    Solar cycle predictions are needed to plan long-term space missions, just as weather predictions are needed to plan the launch. Fleets of satellites circle the Earth collecting many types of science data, protecting astronauts, and relaying information. All of these satellites are sensitive at some level to solar cycle effects. Predictions of drag on low-Earth orbit spacecraft are one of the most important. Launching a satellite with less propellant can mean a higher orbit, but unanticipated solar activity and increased drag can make that a Pyrrhic victory as the reduced propellant load is consumed more rapidly. Energetic events at the Sun can produce crippling radiation storms that endanger all assets in space. Solar cycle predictions also anticipate the shortwave emissions that cause degradation of solar panels. Testing solar dynamo theories by quantitative predictions of what will happen in 5 - 20 years is the next arena for solar cycle predictions. A summary and analysis of 75 predictions of the amplitude of the upcoming Solar Cycle 24 is presented. The current state of solar cycle predictions and some anticipations of how those predictions could be made more accurate in the future are discussed.

  15. Risk prediction for invasive candidiasis

    Directory of Open Access Journals (Sweden)

    Armin Ahmed

    2014-01-01

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

  16. Risk prediction for invasive candidiasis.

    Science.gov (United States)

    Ahmed, Armin; Azim, Afzal; Baronia, Arvind Kumar; Marak, K Rungmei S K; Gurjar, Mohan

    2014-10-01

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

  17. PREDICT : model for prediction of survival in localized prostate cancer

    NARCIS (Netherlands)

    Kerkmeijer, Linda G W; Monninkhof, Evelyn M.; van Oort, Inge M.; van der Poel, Henk G.; de Meerleer, Gert; van Vulpen, Marco

    2016-01-01

    Purpose: Current models for prediction of prostate cancer-specific survival do not incorporate all present-day interventions. In the present study, a pre-treatment prediction model for patients with localized prostate cancer was developed.Methods: From 1989 to 2008, 3383 patients were treated with I

  18. 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…

  19. 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].

  20. 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.

  1. 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...

  2. Predictions for Excited Strange Baryons

    Energy Technology Data Exchange (ETDEWEB)

    Fernando, Ishara P.; Goity, Jose L. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)

    2016-04-01

    An assessment is made of predictions for excited hyperon masses which follow from flavor symmetry and consistency with a 1/N c expansion of QCD. Such predictions are based on presently established baryonic resonances. Low lying hyperon resonances which do not seem to fit into the proposed scheme are discussed.

  3. Predictions of nuclear charge radii

    Science.gov (United States)

    Bao, M.; Lu, Y.; Zhao, Y. M.; Arima, A.

    2016-12-01

    The nuclear charge radius is a fundamental property of an atomic nucleus. In this article we study the predictive power of empirical relations for experimental nuclear charge radii of neighboring nuclei and predict the unknown charge radii of 1085 nuclei based on the experimental CR2013 database within an uncertainty of 0.03 fm.

  4. 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...

  5. 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 numbe...

  6. 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.

  7. 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.

  8. 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.

  9. 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...

  10. A Regenerative Prediction Algorithm for Indian Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    SEEMA MAHAJAN

    2013-11-01

    Full Text Available Rainfall forecasting is critical for the crop planning and water management strategies. Proposed study presents a novel approach for modelling time series precipitation data. The 51 years of Indian rainfall data is used for the development of the model. We use nonlinear predictive code based on 11th order with 240 coefficients. Coefficients are optimized using gradient descendent algorithm. Algorithm is tested using 40 years of rainfall training data. Prediction error tested outside training period is found less than1% for few months. Prediction period is extended to one year by including progressive predicted values in input samples using regenerative feedback algorithm. This model is applied for different training and testing periods with average error of 2% to 10%.

  11. SIFT missense predictions for genomes.

    Science.gov (United States)

    Vaser, Robert; Adusumalli, Swarnaseetha; Leng, Sim Ngak; Sikic, Mile; Ng, Pauline C

    2016-01-01

    The SIFT (sorting intolerant from tolerant) algorithm helps bridge the gap between mutations and phenotypic variations by predicting whether an amino acid substitution is deleterious. SIFT has been used in disease, mutation and genetic studies, and a protocol for its use has been previously published with Nature Protocols. This updated protocol describes SIFT 4G (SIFT for genomes), which is a faster version of SIFT that enables practical computations on reference genomes. Users can get predictions for single-nucleotide variants from their organism of interest using the SIFT 4G annotator with SIFT 4G's precomputed databases. The scope of genomic predictions is expanded, with predictions available for more than 200 organisms. Users can also run the SIFT 4G algorithm themselves. SIFT predictions can be retrieved for 6.7 million variants in 4 min once the database has been downloaded. If precomputed predictions are not available, the SIFT 4G algorithm can compute predictions at a rate of 2.6 s per protein sequence. SIFT 4G is available from http://sift-dna.org/sift4g.

  12. Toolbox for Protein Structure Prediction.

    Science.gov (United States)

    Roche, Daniel Barry; McGuffin, Liam James

    2016-01-01

    Protein tertiary structure prediction algorithms aim to predict, from amino acid sequence, the tertiary structure of a protein. In silico protein structure prediction methods have become extremely important, as in vitro-based structural elucidation is unable to keep pace with the current growth of sequence databases due to high-throughput next-generation sequencing, which has exacerbated the gaps in our knowledge between sequences and structures.Here we briefly discuss protein tertiary structure prediction, the biennial competition for the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and its role in shaping the field. We also discuss, in detail, our cutting-edge web-server method IntFOLD2-TS for tertiary structure prediction. Furthermore, we provide a step-by-step guide on using the IntFOLD2-TS web server, along with some real world examples, where the IntFOLD server can and has been used to improve protein tertiary structure prediction and aid in functional elucidation.

  13. Prediction of Competitive Microbial Growth.

    Science.gov (United States)

    Fujikawa, Hiroshi

    2016-01-01

     Prediction of competitive microbial growth is becoming important for microbial food safety. There would be two approaches to predict competitive microbial growth with mathematical models. The first approach is the development of a growth model for competitive microbes. Among several candidates for the competition model considered, the combination of the primary growth model of the new logistic (NL) model and the competition model of the Lotka-Vorttera (LV) model showed the best performance in predicting microbial competitive growth in the mixed culture of two species. This system further successfully predicted the growth of three competitive species in mixed culture. The second approach is the application of the secondary model especially for the parameter of the maximum cell population in the primary growth model. The combination of the NL model and a polynomial model for the maximum population successfully predicted Salmonella growth in raw ground beef. This system further successfully predicted Salmonella growth in beef at various initial concentrations and temperatures. The first approach requires microbial growth data in monoculture for analysis. The second approach to the prediction of competitive growth from the viewpoint of microbial food safety would be more suitable for practical application.

  14. 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.

  15. 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

  16. 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...

  17. 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

  18. 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

  19. Predicting Success in Elementary Algebra

    Science.gov (United States)

    Mogull, R. G.; Rosengarten, W., Jr.

    1974-01-01

    The purpose of this study was to develop a device for predicting student success in a high school Elementary Algebra course. It was intended to assist guidance counselors in advising students in selecting the most appropriate mathematics course. (Editor)

  20. 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.

  1. Time-predictable Stack Caching

    DEFF Research Database (Denmark)

    Abbaspourseyedi, Sahar

    complicated and less imprecise. Time-predictable computer architectures provide solutions to this problem. As accesses to the data in caches are one source of timing unpredictability, devising methods for improving the timepredictability of caches are important. Stack data, with statically analyzable......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...... addresses, provides an opportunity to predict and tighten the WCET of accesses to data in caches. In this thesis, we introduce the time-predictable stack cache design and implementation within a time-predictable processor. We introduce several optimizations to our design for tightening the WCET while...

  2. Shortcomings in wheat yield predictions

    Science.gov (United States)

    Semenov, Mikhail A.; Mitchell, Rowan A. C.; Whitmore, Andrew P.; Hawkesford, Malcolm J.; Parry, Martin A. J.; Shewry, Peter R.

    2012-06-01

    Predictions of a 40-140% increase in wheat yield by 2050, reported in the UK Climate Change Risk Assessment, are based on a simplistic approach that ignores key factors affecting yields and hence are seriously misleading.

  3. New Tool to Predict Glaucoma

    Science.gov (United States)

    ... News About Us Donate In This Section A New Tool to Predict Glaucoma email Send this article ... determine if a patient has glaucoma. Recently, a new tool has become available to eye care specialists ...

  4. 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.

  5. Dividend Predictability around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

    in the time-series dimension (time variation in dividend yields strongly predicts future dividend growth rates) and in the cross- country dimension (sorting countries into portfolios depending on their lagged dividend yield produces a spread in dividend growth rates of more than 20% p.a.). In an economic...... assessment of this finding, we show that cash flow predictability is stronger in smaller and medium- sized countries because these countries also have more volatile cash flow growth and higher idiosyncratic return volatility....

  6. 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

  7. GIPSy: Genomic island prediction software.

    Science.gov (United States)

    Soares, Siomar C; Geyik, Hakan; Ramos, Rommel T J; de Sá, Pablo H C G; Barbosa, Eudes G V; Baumbach, Jan; Figueiredo, Henrique C P; Miyoshi, Anderson; Tauch, Andreas; Silva, Artur; Azevedo, Vasco

    2016-08-20

    Bacteria are highly diverse organisms that are able to adapt to a broad range of environments and hosts due to their high genomic plasticity. Horizontal gene transfer plays a pivotal role in this genome plasticity and in evolution by leaps through the incorporation of large blocks of genome sequences, ordinarily known as genomic islands (GEIs). GEIs may harbor genes encoding virulence, metabolism, antibiotic resistance and symbiosis-related functions, namely pathogenicity islands (PAIs), metabolic islands (MIs), resistance islands (RIs) and symbiotic islands (SIs). Although many software for the prediction of GEIs exist, they only focus on PAI prediction and present other limitations, such as complicated installation and inconvenient user interfaces. Here, we present GIPSy, the genomic island prediction software, a standalone and user-friendly software for the prediction of GEIs, built on our previously developed pathogenicity island prediction software (PIPS). We also present four application cases in which we crosslink data from literature to PAIs, MIs, RIs and SIs predicted by GIPSy. Briefly, GIPSy correctly predicted the following previously described GEIs: 13 PAIs larger than 30kb in Escherichia coli CFT073; 1 MI for Burkholderia pseudomallei K96243, which seems to be a miscellaneous island; 1 RI of Acinetobacter baumannii AYE, named AbaR1; and, 1 SI of Mesorhizobium loti MAFF303099 presenting a mosaic structure. GIPSy is the first life-style-specific genomic island prediction software to perform analyses of PAIs, MIs, RIs and SIs, opening a door for a better understanding of bacterial genome plasticity and the adaptation to new traits.

  8. High sensitivity RNA pseudoknot prediction

    OpenAIRE

    Huang, Xiaolu; Ali, Hesham

    2006-01-01

    Most ab initio pseudoknot predicting methods provide very few folding scenarios for a given RNA sequence and have low sensitivities. RNA researchers, in many cases, would rather sacrifice the specificity for a much higher sensitivity for pseudoknot detection. In this study, we introduce the Pseudoknot Local Motif Model and Dynamic Partner Sequence Stacking (PLMM_DPSS) algorithm which predicts all PLM model pseudoknots within an RNA sequence in a neighboring-region-interference-free fashion. T...

  9. Prediction of the Chandler wobble

    Science.gov (United States)

    Zotov, L.; Bizouard, C.

    2015-08-01

    Chandler wobble amplitude have been decreasing in 2010s as in 1930s. We try to predict its future behaviour through prediction of its complex envelope. The excitation of the Chandler wobble (ChW) reconstructed by Panteleev's filter was also analized. The equation for the complex envelope propagation through the Euler-Liouville equation was derived. Similarities with the climate change characteristics are discussed.

  10. Predictive Characteristics of Malignant Pheochromocytoma

    OpenAIRE

    Park, Junsoo; Song, Cheryn; Park, Myungchan; Yoo, Sangjun; Park, Se Jun; Hong, SeokJun; Hong, Bumsik; Kim, Choung-Soo; Ahn, Hanjong

    2011-01-01

    Purpose The prognosis of patients with malignant pheochromocytoma is poor, but the predictive factors are not well understood. We aimed to identify the clinical characteristics predictive of malignancy after initial surgical removal in patients with pheochromocytoma. Materials and Methods We retrospectively reviewed the records of 152 patients diagnosed with pheochromocytoma, including 5 (3.3%) with metastasis at the time of the initial surgical excision and 12 (7.9%) who developed metastasis...

  11. 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.

  12. Strategy and methodology of dynamical analogue prediction

    Institute of Scientific and Technical Information of China (English)

    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.

  13. Neural Elements for Predictive Coding

    Directory of Open Access Journals (Sweden)

    Stewart SHIPP

    2016-11-01

    Full Text Available Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backwards in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many ‘illusory’ instances of perception where what is seen (heard, etc is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forwards and backwards pathways should be completely separate, given their functional distinction; this aspect of circuitry – that neurons with extrinsically bifurcating axons do not project in both directions – has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy formulation of predictive coding is combined with the classic ‘canonical microcircuit’ and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a updates in the microcircuitry of primate visual cortex, and (b rapid technical advances made

  14. Predictive mechanisms in idiom comprehension.

    Science.gov (United States)

    Vespignani, Francesco; Canal, Paolo; Molinaro, Nicola; Fonda, Sergio; Cacciari, Cristina

    2010-08-01

    Prediction is pervasive in human cognition and plays a central role in language comprehension. At an electrophysiological level, this cognitive function contributes substantially in determining the amplitude of the N400. In fact, the amplitude of the N400 to words within a sentence has been shown to depend on how predictable those words are: The more predictable a word, the smaller the N400 elicited. However, predictive processing can be based on different sources of information that allow anticipation of upcoming constituents and integration in context. In this study, we investigated the ERPs elicited during the comprehension of idioms, that is, prefabricated multiword strings stored in semantic memory. When a reader recognizes a string of words as an idiom before the idiom ends, she or he can develop expectations concerning the incoming idiomatic constituents. We hypothesized that the expectations driven by the activation of an idiom might differ from those driven by discourse-based constraints. To this aim, we compared the ERP waveforms elicited by idioms and two literal control conditions. The results showed that, in both cases, the literal conditions exhibited a more negative potential than the idiomatic condition. Our analyses suggest that before idiom recognition the effect is due to modulation of the N400 amplitude, whereas after idiom recognition a P300 for the idiomatic sentence has a fundamental role in the composition of the effect. These results suggest that two distinct predictive mechanisms are at work during language comprehension, based respectively on probabilistic information and on categorical template matching.

  15. Sentence-Level Attachment Prediction

    Science.gov (United States)

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

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

  16. Intelligent Prediction of Ship Maneuvering

    Directory of Open Access Journals (Sweden)

    Miroslaw Lacki

    2016-09-01

    Full Text Available In this paper the author presents an idea of the intelligent ship maneuvering prediction system with the usage of neuroevolution. This may be also be seen as the ship handling system that simulates a learning process of an autonomous control unit, created with artificial neural network. The control unit observes input signals and calculates the values of required parameters of the vessel maneuvering in confined waters. In neuroevolution such units are treated as individuals in population of artificial neural networks, which through environmental sensing and evolutionary algorithms learn to perform given task efficiently. The main task of the system is to learn continuously and predict the values of a navigational parameters of the vessel after certain amount of time, regarding an influence of its environment. The result of a prediction may occur as a warning to navigator to aware him about incoming threat.

  17. High sensitivity RNA pseudoknot prediction.

    Science.gov (United States)

    Huang, Xiaolu; Ali, Hesham

    2007-01-01

    Most ab initio pseudoknot predicting methods provide very few folding scenarios for a given RNA sequence and have low sensitivities. RNA researchers, in many cases, would rather sacrifice the specificity for a much higher sensitivity for pseudoknot detection. In this study, we introduce the Pseudoknot Local Motif Model and Dynamic Partner Sequence Stacking (PLMM_DPSS) algorithm which predicts all PLM model pseudoknots within an RNA sequence in a neighboring-region-interference-free fashion. The PLM model is derived from the existing Pseudobase entries. The innovative DPSS approach calculates the optimally lowest stacking energy between two partner sequences. Combined with the Mfold, PLMM_DPSS can also be used in predicting complicated pseudoknots. The test results of PLMM_DPSS, PKNOTS, iterated loop matching, pknotsRG and HotKnots with Pseudobase sequences have shown that PLMM_DPSS is the most sensitive among the five methods. PLMM_DPSS also provides manageable pseudoknot folding scenarios for further structure determination.

  18. Algorithms for Protein Structure Prediction

    DEFF Research Database (Denmark)

    Paluszewski, Martin

    The problem of predicting the three-dimensional structure of a protein given its amino acid sequence is one of the most important open problems in bioinformatics. One of the carbon atoms in amino acids is the C-atom and the overall structure of a protein is often represented by a so-called C...... is competitive in quality and speed with other state-of-the-art decoy generation algorithms. Our third C-trace reconstruction approach is based on bee-colony optimization [24]. We demonstrate why this algorithm has some important properties that makes it suitable for protein structure prediction. Our approach......-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...

  19. Algorithms for Drug Sensitivity Prediction

    Directory of Open Access Journals (Sweden)

    Carlos De Niz

    2016-11-01

    Full Text Available Precision medicine entails the design of therapies that are matched for each individual patient. Thus, predictive modeling of drug responses for specific patients constitutes a significant challenge for personalized therapy. In this article, we consider a review of approaches that have been proposed to tackle the drug sensitivity prediction problem especially with respect to personalized cancer therapy. We first discuss modeling approaches that are based on genomic characterizations alone and further the discussion by including modeling techniques that integrate both genomic and functional information. A comparative analysis of the prediction performance of four representative algorithms, elastic net, random forest, kernelized Bayesian multi-task learning and deep learning, reflecting the broad classes of regularized linear, ensemble, kernelized and neural network-based models, respectively, has been included in the paper. The review also considers the challenges that need to be addressed for successful implementation of the algorithms in clinical practice.

  20. 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...

  1. 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.

  2. 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.

  3. 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.

  4. Prediction of dental caries activity

    OpenAIRE

    Crossner, Claes-Göran

    1980-01-01

    The aim of the present thesis was to find a test for prediction of caries activity which would be useful in routine clinical work.Correlations between oral health, general health, food habits and socioeconomic conditions were investigated in 4- and 8-year-old children. It was found that the salivary secretion rate and the prevalence of oral lactobacilli were factors which might be useful in caries prediction.In 5- and 8-year-old children negative correlations between caries frequency and secr...

  5. 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)

  6. Dinosaur fossils predict body temperatures.

    Directory of Open Access Journals (Sweden)

    James F Gillooly

    2006-07-01

    Full Text Available Perhaps the greatest mystery surrounding dinosaurs concerns whether they were endotherms, ectotherms, or some unique intermediate form. Here we present a model that yields estimates of dinosaur body temperature based on ontogenetic growth trajectories obtained from fossil bones. The model predicts that dinosaur body temperatures increased with body mass from approximately 25 degrees C at 12 kg to approximately 41 degrees C at 13,000 kg. The model also successfully predicts observed increases in body temperature with body mass for extant crocodiles. These results provide direct evidence that dinosaurs were reptiles that exhibited inertial homeothermy.

  7. 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...

  8. 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...

  9. 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…

  10. 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.

  11. Predicting Leakage in Labyrinth Seals

    Science.gov (United States)

    Morrison, G. L.; Rhode, D. L.; Cogan, K. C.; Chi, D.; Demko, J.

    1985-01-01

    Analytical and empirical methods evaluated. 264-page report presents comprehensive information on leakage in labyrinth seals. Summarizes previous analyses of leakage, reviews leakage tests conducted by authors and evaluates various analytical and experimental methods of determining leakage and discusses leakage prediction techniques.

  12. Navy Nearshore Ocean Prediction Systems

    Science.gov (United States)

    2014-09-01

    Visualization Studio. Oceanography | September 2014 81 Predicting the dynamics of the nearshore environment is important to many different aspects...insertions/extractions. Wave and current conditions, along with local geological conditions, can determine the extent of mine burial , which can impact...and models, including the Simulating WAves ABSTR AC T. Knowledge of the nearshore ocean environment is important for naval operations, including

  13. Predicting severity of paranoid schizophrenia

    OpenAIRE

    Kolesnichenko Elena Vladimirovna

    2015-01-01

    Clinical symptoms, course and outcomes of paranoid schizophrenia are polymorphic. 206 cases of paranoid schizophrenia were investigated. Clinical predictors were collected from hospital records and interviews. Quantitative assessment of the severity of schizophrenia as special indexes was used. Schizoid, epileptoid, psychasthenic and conformal accentuation of personality in the premorbid, early onset of psychosis, paranoid and hallucinatory-paranoid variants of onset predicted more expressed ...

  14. 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

  15. 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.

  16. 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.

  17. Predictability of Mobile Phone Associations

    DEFF Research Database (Denmark)

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

    2010-01-01

    Prediction and understanding of human behavior is of high importance in many modern applications and research areas ranging from context-aware services, wireless resource allocation to social sciences. In this study we collect a novel dataset using standard mobile phones and analyze how the predi......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...... representation, and general behavior. This is of vital interest in the development of context-aware services which rely on forecasting based on mobile phone sensors....

  18. 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

  19. 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...

  20. Predicting Volleyball Serve-Reception

    NARCIS (Netherlands)

    Paulo, Ana; Zaal, Frank T J M; Fonseca, Sofia; Araujo, Duarte

    2016-01-01

    Serve and serve-reception performance have predicted success in volleyball. Given the impact of serve-reception on the game, we aimed at understanding what it is in the serve and receiver's actions that determines the selection of the type of pass used in serve-reception and its efficacy. Four high-

  1. 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…

  2. Making predictions skill level analysis

    Science.gov (United States)

    Katarína, Krišková; Marián, Kireš

    2017-01-01

    The current trend in the education is focused on skills that are cross-subject and have a great importance for the pupil future life. Pupils should acquire different types of skills during their education to be prepared for future careers and life in the 21st century. Physics as a subject offers many opportunities for pupils' skills development. One of the skills that are expected to be developed in physics and also in other sciences is making predictions. The prediction, in the meaning of the argument about what may happen in the future, is an integral part of the empirical cognition, in which students confront existing knowledge and experience with new, hitherto unknown and surprising phenomena. The extent of the skill is the formulation of hypotheses, which is required in the upper secondary physics education. In the contribution, the prediction skill is specified and its eventual levels are classified. Authors focus on the tools for skill level determination based on the analysis of pupils` worksheets. Worksheets are the part of the educational activities conducted within the Inquiry Science Laboratory Steelpark. Based on the formulation of pupils' prediction the pupils thinking can be seen and their understanding of the topic, as well as preconceptions and misconceptions.

  3. Predictive medical information and underwriting.

    Science.gov (United States)

    Dodge, John H

    2007-01-01

    Medical underwriting involves the application of actuarial science by analyzing medical information to predict the future risk of a claim. The objective is that individuals with like risk are treated in a like manner so that the premium paid is proportional to the risk of future claim.

  4. 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.

  5. 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

  6. 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

  7. 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

  8. Predictive Terminal Guidance With Tuning of Prediction Horizon & Constrained Control .

    Directory of Open Access Journals (Sweden)

    S. E. Talole

    2000-07-01

    Full Text Available Continvojs time-predictive control approach is employed to formulate an output tracking nonlinear, optimal, terminal guidance ,law for re-entry vehicles. The notable features of this formulation are that the system equations are not linearised and the evaluation of the guidanceequations does not need the information of vehicle parameters, such as drag and mass. The formulation allows to impose the physical constrains on the control inputs, i..e. on the demanded lateral acceleliations through a saturation mapping and the controls are obtained using a fixed pointiteration algorithm which converges typically in a few iterations. Further, a simple method of tuning the prediction horizon needed in the guidance equations is presented. Numerical simulations show that the guidance law achieves almost zero terminal errors in all states despite large errors in initial Conditions.

  9. Multiphase, multicomponent phase behavior prediction

    Science.gov (United States)

    Dadmohammadi, Younas

    Accurate prediction of phase behavior of fluid mixtures in the chemical industry is essential for designing and operating a multitude of processes. Reliable generalized predictions of phase equilibrium properties, such as pressure, temperature, and phase compositions offer an attractive alternative to costly and time consuming experimental measurements. The main purpose of this work was to assess the efficacy of recently generalized activity coefficient models based on binary experimental data to (a) predict binary and ternary vapor-liquid equilibrium systems, and (b) characterize liquid-liquid equilibrium systems. These studies were completed using a diverse binary VLE database consisting of 916 binary and 86 ternary systems involving 140 compounds belonging to 31 chemical classes. Specifically the following tasks were undertaken: First, a comprehensive assessment of the two common approaches (gamma-phi (gamma-ϕ) and phi-phi (ϕ-ϕ)) used for determining the phase behavior of vapor-liquid equilibrium systems is presented. Both the representation and predictive capabilities of these two approaches were examined, as delineated form internal and external consistency tests of 916 binary systems. For the purpose, the universal quasi-chemical (UNIQUAC) model and the Peng-Robinson (PR) equation of state (EOS) were used in this assessment. Second, the efficacy of recently developed generalized UNIQUAC and the nonrandom two-liquid (NRTL) for predicting multicomponent VLE systems were investigated. Third, the abilities of recently modified NRTL model (mNRTL2 and mNRTL1) to characterize liquid-liquid equilibria (LLE) phase conditions and attributes, including phase stability, miscibility, and consolute point coordinates, were assessed. The results of this work indicate that the ϕ-ϕ approach represents the binary VLE systems considered within three times the error of the gamma-ϕ approach. A similar trend was observed for the for the generalized model predictions using

  10. Predictive Control of Speededness in Adaptive Testing

    Science.gov (United States)

    van der Linden, Wim J.

    2009-01-01

    An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…

  11. 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...

  12. 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

  13. Algorithms for Protein Structure Prediction

    DEFF Research Database (Denmark)

    Paluszewski, Martin

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

  14. 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...

  15. 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.

  16. 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.

  17. Confidence Estimation in Structured Prediction

    CERN Document Server

    Mejer, Avihai

    2011-01-01

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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Predictive State Temporal Difference Learning

    CERN Document Server

    Boots, Byron

    2010-01-01

    We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications, reinforcement learning (RL) is complicated by the fact that state is either high-dimensional or partially observable. Therefore, RL methods are designed to work with features of state rather than state itself, and the success or failure of learning is often determined by the suitability of the selected features. By comparison, subspace identification (SSID) methods are designed to select a feature set which preserves as much information as possible about state. In this paper we connect the two approaches, looking at the problem of reinforcement learning with a large set of features, each of which may only be marginally useful for value function approximation. We introduce a new algorithm for this situation, called Predictive State Temporal Difference (PSTD) learning. As in SSID for predictive state representations, PSTD finds a line...

  5. Shoulder dystocia: prediction and management.

    Science.gov (United States)

    Hill, Meghan G; Cohen, Wayne R

    2016-01-01

    Shoulder dystocia is a complication of vaginal delivery and the primary factor associated with brachial plexus injury. In this review, we discuss the risk factors for shoulder dystocia and propose a framework for the prediction and prevention of the complication. A recommended approach to management when shoulder dystocia occurs is outlined, with review of the maneuvers used to relieve the obstruction with minimal risk of fetal and maternal injury.

  6. Predicted halflives for cluster radioactivities

    Science.gov (United States)

    Poenaru, D. N.; Greiner, W.; Ivascu, M.

    1989-10-01

    The main results of the analytical superasymmetric fission model, describing in a unified manner cluster radioactivities, alpha-decay and cold fission processes, are briefly reviewed. Predicted halflives for 14C, 24, 25, 26Ne, 28, 30Mg and 32Si radioactivities in the range 10 11-10 26 s and the corresponding branching ratios relative to α-decay 10 -16 - 10 -9 have been experimentally confirmed within 1.5 orders of magnitude.

  7. 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....

  8. Dim prospects for earthquake prediction

    Science.gov (United States)

    Geller, Robert J.

    I was misquoted by C. Lomnitz's [1998] Forum letter (Eos, August 4, 1998, p. 373), which said: [I wonder whether Sasha Gusev [1998] actually believes that branding earthquake prediction a ‘proven nonscience’ [Geller, 1997a] is a paradigm for others to copy.”Readers are invited to verify for themselves that neither “proven nonscience” norv any similar phrase was used by Geller [1997a].

  9. ESPC Regional Arctic Prediction System

    Science.gov (United States)

    2014-09-30

    the Navy the capability to conduct short-term (1 week) to extended (2 weeks) coupled weather forecasts for the Arctic region. APPROACH To...sensitivity of the Arctic weather forecast to key numerical parameters; and 5) conduct extensive validation and verification of the coupled system and...SEP 2014 2. REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE ESPC Regional Arctic Prediction System 5a. CONTRACT

  10. Structure Prediction of Membrane Proteins

    Institute of Scientific and Technical Information of China (English)

    Chunlong Zhou; Yao Zheng; Yan Zhou

    2004-01-01

    There is a large gap between the number of membrane protein (MP) sequences and that of their decoded 3D structures, especially high-resolution structures, due to difficulties in crystal preparation of MPs. However, detailed knowledge of the 3D structure is required for the fundamental understanding of the function of an MP and the interactions between the protein and its inhibitors or activators. In this paper, some computational approaches that have been used to predict MP structures are discussed and compared.

  11. 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.

  12. The Clinical Prediction of Dangerousness.

    Science.gov (United States)

    1985-05-01

    executive potential, psychopathy , suicidality and so forth. Unfor- tunately, this is not the case. There tend to be substantial dif- ferences among...Prediction from case material to personality data. New York Archives of Psychology, 29 (No. 207). Hare, R. D. (1970). Psychopathy : Theory and research. New...1967). Psychopathy , mental deficiency, aggressiveness, and the XYY syndrome. Nature, 214, (5087), 500-501. Wexler, D. (1979). Patients, therapists

  13. 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.

  14. Finite Unification: Theory and Predictions

    Directory of Open Access Journals (Sweden)

    Sven Heinemeyer

    2010-06-01

    Full Text Available All-loop Finite Unified Theories (FUTs are very interesting N=1 supersymmetric Grand Unified Theories (GUTs which not only realise an old field theoretic dream but also have a remarkable predictive power due to the required reduction of couplings. The reduction of the dimensionless couplings in N=1 GUTs is achieved by searching for renormalization group invariant (RGI relations among them holding beyond the unification scale. Finiteness results from the fact that there exist RGI relations among dimensionless couplings that guarantee the vanishing of all beta-functions in certain N=1 GUTs even to all orders. Furthermore developments in the soft supersymmetry breaking sector of N=1 GUTs and FUTs lead to exact RGI relations, i.e. reduction of couplings, in this dimensionful sector of the theory too. Based on the above theoretical framework phenomenologically consistent FUTS have been constructed. Here we present FUT models based on the SU(5 and SU(3^3 gauge groups and their predictions. Of particular interest is the Higgs mass prediction of one of the models which is expected to be tested at the LHC.

  15. Using Predictive Analytics to Predict Power Outages from Severe Weather

    Science.gov (United States)

    Wanik, D. W.; Anagnostou, E. N.; Hartman, B.; Frediani, M. E.; Astitha, M.

    2015-12-01

    The distribution of reliable power is essential to businesses, public services, and our daily lives. With the growing abundance of data being collected and created by industry (i.e. outage data), government agencies (i.e. land cover), and academia (i.e. weather forecasts), we can begin to tackle problems that previously seemed too complex to solve. In this session, we will present newly developed tools to aid decision-support challenges at electric distribution utilities that must mitigate, prepare for, respond to and recover from severe weather. We will show a performance evaluation of outage predictive models built for Eversource Energy (formerly Connecticut Light & Power) for storms of all types (i.e. blizzards, thunderstorms and hurricanes) and magnitudes (from 20 to >15,000 outages). High resolution weather simulations (simulated with the Weather and Research Forecast Model) were joined with utility outage data to calibrate four types of models: a decision tree (DT), random forest (RF), boosted gradient tree (BT) and an ensemble (ENS) decision tree regression that combined predictions from DT, RF and BT. The study shows that the ENS model forced with weather, infrastructure and land cover data was superior to the other models we evaluated, especially in terms of predicting the spatial distribution of outages. This research has the potential to be used for other critical infrastructure systems (such as telecommunications, drinking water and gas distribution networks), and can be readily expanded to the entire New England region to facilitate better planning and coordination among decision-makers when severe weather strikes.

  16. Predictive and Neural Predictive Control of Uncertain Systems

    Science.gov (United States)

    Kelkar, Atul G.

    2000-01-01

    Accomplishments and future work are:(1) Stability analysis: the work completed includes characterization of stability of receding horizon-based MPC in the setting of LQ paradigm. The current work-in-progress includes analyzing local as well as global stability of the closed-loop system under various nonlinearities; for example, actuator nonlinearities; sensor nonlinearities, and other plant nonlinearities. Actuator nonlinearities include three major types of nonlineaxities: saturation, dead-zone, and (0, 00) sector. (2) Robustness analysis: It is shown that receding horizon parameters such as input and output horizon lengths have direct effect on the robustness of the system. (3) Code development: A matlab code has been developed which can simulate various MPC formulations. The current effort is to generalize the code to include ability to handle all plant types and all MPC types. (4) Improved predictor: It is shown that MPC design using better predictors that can minimize prediction errors. It is shown analytically and numerically that Smith predictor can provide closed-loop stability under GPC operation for plants with dead times where standard optimal predictor fails. (5) Neural network predictors: When neural network is used as predictor it can be shown that neural network predicts the plant output within some finite error bound under certain conditions. Our preliminary study shows that with proper choice of update laws and network architectures such bound can be obtained. However, much work needs to be done to obtain a similar result in general case.

  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. Learning to predict chemical reactions.

    Science.gov (United States)

    Kayala, Matthew A; Azencott, Chloé-Agathe; Chen, Jonathan H; Baldi, Pierre

    2011-09-26

    Being able to predict the course of arbitrary chemical reactions is essential to the theory and applications of organic chemistry. Approaches to the reaction prediction problems can be organized around three poles corresponding to: (1) physical laws; (2) rule-based expert systems; and (3) inductive machine learning. Previous approaches at these poles, respectively, are not high throughput, are not generalizable or scalable, and lack sufficient data and structure to be implemented. We propose a new approach to reaction prediction utilizing elements from each pole. Using a physically inspired conceptualization, we describe single mechanistic reactions as interactions between coarse approximations of molecular orbitals (MOs) and use topological and physicochemical attributes as descriptors. Using an existing rule-based system (Reaction Explorer), we derive a restricted chemistry data set consisting of 1630 full multistep reactions with 2358 distinct starting materials and intermediates, associated with 2989 productive mechanistic steps and 6.14 million unproductive mechanistic steps. And from machine learning, we pose identifying productive mechanistic steps as a statistical ranking, information retrieval problem: given a set of reactants and a description of conditions, learn a ranking model over potential filled-to-unfilled MO interactions such that the top-ranked mechanistic steps yield the major products. The machine learning implementation follows a two-stage approach, in which we first train atom level reactivity filters to prune 94.00% of nonproductive reactions with a 0.01% error rate. Then, we train an ensemble of ranking models on pairs of interacting MOs to learn a relative productivity function over mechanistic steps in a given system. Without the use of explicit transformation patterns, the ensemble perfectly ranks the productive mechanism at the top 89.05% of the time, rising to 99.86% of the time when the top four are considered. Furthermore, the system

  19. Predicting Ship Fuel Consumption: Update.

    Science.gov (United States)

    1996-07-01

    ship propulsion fuel consumption as a function of ship speed for U.S. Navy combatant and auxiliary ships. Prediction is based on fitting an analytic function to published ship class speed-fuel use data using nonlinear regression. The form of the analytic function fitted is motivated by the literature on ship powering and resistance. The report discusses data sources and data issues, and the impact of ship propulsion plant configuration on fuel use. The regression coefficients of the exponential function fitted, tabular numerical comparison of

  20. Prenatal prediction of pulmonary hypoplasia.

    Science.gov (United States)

    Triebwasser, Jourdan E; Treadwell, Marjorie C

    2017-03-15

    Pulmonary hypoplasia, although rare, is associated with significant neonatal morbidity and mortality. Conditions associated with pulmonary hypoplasia include those which limit normal thoracic capacity or movement, including skeletal dysplasias and abdominal wall defects; those with mass effect, including congenital diaphragmatic hernia and pleural effusions; and those with decreased amniotic fluid, including preterm, premature rupture of membranes, and genitourinary anomalies. The ability to predict severe pulmonary hypoplasia prenatally aids in family counseling, as well as obstetric and neonatal management. The objective of this review is to outline the imaging techniques that are widely used prenatally to assess pulmonary hypoplasia and to discuss the limitations of these methods.

  1. Predicted halflives for cluster radioactivities

    Energy Technology Data Exchange (ETDEWEB)

    Poenaru, D.N. (Institutul Central de Fizica, Bucharest (Romania); Frankfurt Univ. (Germany, F.R.). Inst. fuer Theoretische Physik); Greiner, W. (Frankfurt Univ. (Germany, F.R.). Inst. fuer Theoretische Physik); Ivascu, M. (Institutul Central de Fizica, Bucharest (Romania))

    1989-10-09

    The main results of the analytical superasymmetric fission model, describing in a unified manner cluster radioactivities, alpha-decay and cold fission processes, are briefly reviewed. Predicted halflives for {sup 14}C, {sup 24,25,26}Ne, {sup 28,30}Mg and {sup 32}Si radioactivities in the range 10{sup 11}-10{sup 26} s and the corresponding branching ratios relative to {alpha}-decay 10{sup -16}-10{sup -9} have been experimentally confirmed within 1.5 orders of magnitude. (orig.).

  2. 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.

  3. 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.

  4. Making predictions in the multiverse

    Energy Technology Data Exchange (ETDEWEB)

    Freivogel, Ben, E-mail: benfreivogel@gmail.com [Center for Theoretical Physics and Laboratory for Nuclear Science, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States)

    2011-10-21

    I describe reasons to think we are living in an eternally inflating multiverse where the observable 'constants' of nature vary from place to place. The major obstacle to making predictions in this context is that we must regulate the infinities of eternal inflation. I review a number of proposed regulators, or measures. Recent work has ruled out a number of measures by showing that they conflict with observation, and focused attention on a few proposals. Further, several different measures have been shown to be equivalent. I describe some of the many nontrivial tests these measures will face as we learn more from theory, experiment and observation.

  5. Radio Channel State Prediction by Kalman Filter

    Directory of Open Access Journals (Sweden)

    Peter Ziacik

    2005-01-01

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

  6. MPC-Relevant Prediction-Error Identification

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays. It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model......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...

  7. The limits to stock return predictability

    OpenAIRE

    Robertson, D.; Wright, Stephen

    2009-01-01

    We examine predictive return regressions from a new angle. We ask what observable\\ud univariate properties of returns tell us about the “predictive space” that defines the true\\ud predictive model: the triplet ¡\\ud λ, R2\\ud x, ρ¢\\ud , where λ is the predictor’s persistence, R2\\ud x is the\\ud predictive R-squared, and ρ is the "Stambaugh Correlation" (between innovations in the\\ud predictive system). When returns are nearly white noise, and the variance ratio slopes\\ud downwards, the predictive...

  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. 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...

  10. Emotional arousal predicts intertemporal choice.

    Science.gov (United States)

    Lempert, Karolina M; Johnson, Eli; Phelps, Elizabeth A

    2016-08-01

    People generally prefer immediate rewards to rewards received after a delay, often even when the delayed reward is larger. This phenomenon is known as temporal discounting. It has been suggested that preferences for immediate rewards may be due to their being more concrete than delayed rewards. This concreteness may evoke an enhanced emotional response. Indeed, manipulating the representation of a future reward to make it more concrete has been shown to heighten the reward's subjective emotional intensity, making people more likely to choose it. Here the authors use an objective measure of arousal-pupil dilation-to investigate if emotional arousal mediates the influence of delayed reward concreteness on choice. They recorded pupil dilation responses while participants made choices between immediate and delayed rewards. They manipulated concreteness through time interval framing: delayed rewards were presented either with the date on which they would be received (e.g., "$30, May 3"; DATE condition, more concrete) or in terms of delay to receipt (e.g., "$30, 7 days; DAYS condition, less concrete). Contrary to prior work, participants were not overall more patient in the DATE condition. However, there was individual variability in response to time framing, and this variability was predicted by differences in pupil dilation between conditions. Emotional arousal increased as the subjective value of delayed rewards increased, and predicted choice of the delayed reward on each trial. This study advances our understanding of the role of emotion in temporal discounting. (PsycINFO Database Record

  11. Menopause prediction and potential implications.

    Science.gov (United States)

    Daan, Nadine M P; Fauser, Bart C J M

    2015-11-01

    Reproductive ageing in women is characterized by a decline in both the quantity and quality of oocytes. Menopause is reached upon exhaustion of the resting primordial follicle pool, occurring on average at 51 years of age (range 40-60 years). The mean global age at natural menopause (ANM) appears robust, suggesting a distinct genetic control. Accordingly, a strong correlation in ANM is observed between mothers and daughters. Few specific genetic determinants of ANM have been identified. Substantial efforts have been made to predict ANM by using anti-Müllerian hormone (AMH) levels. AMH serum concentrations at reproductive age predict ANM, but precision is currently limited. Early ANM is associated with early preceding fertility loss, whereas late menopause is associated with reduced morbidity and mortality later in life. Menopause affects various women's health aspects, including bone density, breast, the cardiovascular system, mood/cognitive function and sexual well-being. If the current trend of increasing human life expectancy persists, women will soon spend half their life postmenopause. Unfortunately, increased longevity does not coincide with an equal increase in years spend in good health. Future research should focus on determinants of long term health effects of ANM, and efforts to improve women's postmenopausal health and quality of life.

  12. Predictive simulation of nonlinear ultrasonics

    Science.gov (United States)

    Shen, Yanfeng; Giurgiutiu, Victor

    2012-04-01

    Most of the nonlinear ultrasonic studies to date have been experimental, but few theoretical predictive studies exist, especially for Lamb wave ultrasonic. Compared with nonlinear bulk waves and Rayleigh waves, nonlinear Lamb waves for structural health monitoring become more challenging due to their multi-mode dispersive features. In this paper, predictive study of nonlinear Lamb waves is done with finite element simulation. A pitch-catch method is used to interrogate a plate with a "breathing crack" which opens and closes under tension and compression. Piezoelectric wafer active sensors (PWAS) used as transmitter and receiver are modeled with coupled field elements. The "breathing crack" is simulated via "element birth and death" technique. The ultrasonic waves generated by the transmitter PWAS propagate into the structure, interact with the "breathing crack", acquire nonlinear features, and are picked up by the receiver PWAS. The features of the wave packets at the receiver PWAS are studied and discussed. The received signal is processed with Fast Fourier Transform to show the higher harmonics nonlinear characteristics. A baseline free damage index is introduced to assess the presence and the severity of the crack. The paper finishes with summary, conclusions, and suggestions for future work.

  13. Conditional replenishment using motion prediction

    Science.gov (United States)

    Hein, D. N.; Jones, H. W., Jr.

    1979-01-01

    Conditional replenishment is an interframe video compression method that uses correlation in time to reduce video transmission rates. This method works by detecting and sending only the changing portions of the image and by having the receiver use the video data from the previous frame for the non-changing portion. The amount of compression that can be achieved through this technique depends to a large extent on the rate of change within the image, and can vary from 10 to 1 to less than 2 to 1. An additional 3 to 1 reduction in rate is obtained by the intraframe coding of data blocks using a 2-dimensional variable rate Hadamard transform coder. A further additional 2 to 1 rate reduction is achieved by using motion prediction. Motion prediction works by measuring the relative displacements of a subpicture from one frame to the next. The subpicture can then be transmitted by sending only the value of the 2-dimensional displacement. Computer simulations have demonstrated that data rates of 2 to 4 Mega-bits/second can be achieved while still retaining good fidelity in the image.

  14. Predicting educational achievement from DNA

    Science.gov (United States)

    Selzam, S; Krapohl, E; von Stumm, S; O'Reilly, P F; Rimfeld, K; Kovas, Y; Dale, P S; Lee, J J; Plomin, R

    2017-01-01

    A genome-wide polygenic score (GPS), derived from a 2013 genome-wide association study (N=127,000), explained 2% of the variance in total years of education (EduYears). In a follow-up study (N=329,000), a new EduYears GPS explains up to 4%. Here, we tested the association between this latest EduYears GPS and educational achievement scores at ages 7, 12 and 16 in an independent sample of 5825 UK individuals. We found that EduYears GPS explained greater amounts of variance in educational achievement over time, up to 9% at age 16, accounting for 15% of the heritable variance. This is the strongest GPS prediction to date for quantitative behavioral traits. Individuals in the highest and lowest GPS septiles differed by a whole school grade at age 16. Furthermore, EduYears GPS was associated with general cognitive ability (~3.5%) and family socioeconomic status (~7%). There was no evidence of an interaction between EduYears GPS and family socioeconomic status on educational achievement or on general cognitive ability. These results are a harbinger of future widespread use of GPS to predict genetic risk and resilience in the social and behavioral sciences. PMID:27431296

  15. 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;...

  16. 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...

  17. Collective prediction based on community structure

    Science.gov (United States)

    Jiang, Yasong; Li, Taisong; Zhang, Yan; Yan, Yonghong

    2017-01-01

    Collective prediction algorithms have been used to improve performances when network structures are involved in prediction tasks. The training dataset of such tasks often contain information of content, links and labels, while the testing dataset have only content and link information. Conventional collective prediction algorithms conduct predictions based on the content of a node and the information of its direct neighbors with a base classifier. However, the information of some direct neighbor nodes may be not consistent with the target one. In addition, the information of indirect neighbors can be helpful when that of direct neighbors is scant. In this paper, instead of using information of direct neighbors, we propose to apply community structures in networks to prediction tasks. A community detection method is aggregated into the collective prediction process to improve prediction performance. Experimental results show that the proposed algorithm outperforms a number of standard prediction algorithms specially under conditions that labeled training dataset are limited.

  18. 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

  19. 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 ...

  20. 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)

  1. The Use of Linear Programming for Prediction.

    Science.gov (United States)

    Schnittjer, Carl J.

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

  2. Interpreting Prediction Market Prices as Probabilities

    OpenAIRE

    Wolfers, Justin; Zitzewitz, Eric

    2006-01-01

    While most empirical analysis of prediction markets treats prices of binary options as predictions of the probability of future events, Manski (2004) has recently argued that there is little existing theory supporting this practice. We provide relevant analytic foundations, describing sufficient conditions under which prediction markets prices correspond with mean beliefs. Beyond these specific sufficient conditions, we show that for a broad class of models prediction market prices are usuall...

  3. ADAPTIVE GENERALIZED PREDICTIVE CONTROL OF SWITCHED SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    WANG Yi-jing; WANG Long

    2005-01-01

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

  4. Hydrological Ensemble Prediction System (HEPS)

    Science.gov (United States)

    Thielen-Del Pozo, J.; Schaake, J.; Martin, E.; Pailleux, J.; Pappenberger, F.

    2010-09-01

    Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Following on the success of the use of ensembles for weather forecasting, the hydrological community now moves increasingly towards Hydrological Ensemble Prediction Systems (HEPS) for improved flood forecasting using operationally available NWP products as inputs. However, these products are often generated on relatively coarse scales compared to hydrologically relevant basin units and suffer systematic biases that may have considerable impact when passed through the non-linear hydrological filters. Therefore, a better understanding on how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes is necessary. The "Hydrologic Ensemble Prediction Experiment" (HEPEX), is an international initiative consisting of hydrologists, meteorologist and end-users to advance probabilistic hydrologic forecast techniques for flood, drought and water management applications. Different aspects of the hydrological ensemble processor are being addressed including • Production of useful meteorological products relevant for hydrological applications, ranging from nowcasting products to seasonal forecasts. The importance of hindcasts that are consistent with the operational weather forecasts will be discussed to support bias correction and downscaling, statistically meaningful verification of HEPS, and the development and testing of operating rules; • Need for downscaling and post-processing of weather ensembles to reduce bias before entering hydrological applications; • Hydrological model and parameter uncertainty and how to correct and

  5. 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...

  6. Using "Prediction" to Promote Mathematical Reasoning

    Science.gov (United States)

    Kim, Ok-Kyeong; Kasmer, Lisa

    2007-01-01

    This article introduces prediction as a useful tool to promote mathematical reasoning. First, the article addresses prediction expectations in state standards and gives examples. It also provides a classroom example and activities to illustrate what prediction can look like and how it can serve as a building block for the development of students'…

  7. BDDCS Class Prediction for New Molecular Entities

    DEFF Research Database (Denmark)

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

    2012-01-01

    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...

  8. 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...

  9. 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

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. Methods of rock burst prediction

    Energy Technology Data Exchange (ETDEWEB)

    Genkin, V.A.; Minin, Yu.Ya.; Morozov, G.D.; Proskuryakov, V.M.; Cmirnov, V.A.

    1979-07-01

    Some methods of predicting rock bursts in underground coal and iron ore mines are evaluated: using BP-18 indenters and the MGD indenter with automatic recording; seismic method consisting in measuring the speed of shock waves travelling through various layers (apparatus SB-20 is designed for use in coal mines); electrometric method (measuring resistance between two electrodes when electric currents flow through coal and rocks). The design of the AEhSSh-1 measuring instrument, used in the electrometric method in coal mines is also described. Each of the methods is described and mathematical fomulae used as their theoretical basis are presented. The calculating process is explained and brief information on the design and use of the measuring instrument is given. The methods are evaluated from the viewpoint of precision. (In Russian)

  15. Rhythmic complexity and predictive coding

    DEFF Research Database (Denmark)

    Vuust, Peter; Witek, Maria A G

    2014-01-01

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

  16. V1500 Cygni - A prediction

    Energy Technology Data Exchange (ETDEWEB)

    Katz, J.I. (Washington University, Saint Louis, MO (USA))

    1991-06-01

    Scmidt and Stockman (1991) have discovered that V1500 Cygni (Nova Cygni 1975) resembles an AM Herculis star, but with the degenerate dwarf rotating 1.8 percent faster than synchronously, and relaxing toward synchronism on a time scale of less than 200 yr. The inferred spin-down torque is unexpectedly large. It is suggested that this torque results from the interaction of the degenerate star's magnetosphere with a radiation-driven wind from the secondary, and a rapid decay of the spin-down torque, which will soon be observable is predicted. Analogous hydrodynamic torques may also phase-lock the synchronous AM Herculis stars. Study of these systems may help understand torques on neutron stars. 9 refs.

  17. Pretest Predictions for Ventilation Tests

    Energy Technology Data Exchange (ETDEWEB)

    Y. Sun; H. Yang; H.N. Kalia

    2007-01-17

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

  18. Universal Prior Prediction for Communication

    CERN Document Server

    Lomnitz, Yuval

    2011-01-01

    We consider the problem of communicating over an unknown and arbitrarily varying channel, using feedback. This paper focuses on the problem of determining the input behavior, or more specifically, a prior which is used to randomly generate a codebook. We pose the problem of setting the prior as a universal sequential prediction problem using information theoretic abstractions of the communication channel. For the case where the channel is block-wise constant, we show it is possible to asymptotically approach the best rate that can be attained by any system using a fixed prior. For the case where the channel may change on each symbol, we combine a rateless coding scheme with a prior predictor and asymptotically approach the capacity of the average channel universally for every sequence of channels.

  19. 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

  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. 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 matrices...... different loss functions. Numerical experiments demonstrate that joint analysis of data from multiple sources via coupled factorisation improves the link prediction performance and the selection of right loss function and tensor model is crucial for accurately predicting missing links....

  2. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    is a realization of a continuous-discrete multivariate stochastic transfer function model. The proposed prediction error-methods are demonstrated for a SISO system parameterized by the transfer functions with time delays of a continuous-discrete-time linear stochastic system. The simulations for this case suggest......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...... computational resources. The identification method is suitable for predictive control....

  3. 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.

  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. The 2007 TAC SCM Prediction Challenge

    Science.gov (United States)

    Pardoe, David; Stone, Peter

    The TAC SCM Prediction Challenge presents an opportunity for agents designed for the full TAC SCM game to compete solely on their ability to make predictions. Participants are presented with situations from actual TAC SCM games and are evaluated on their prediction accuracy in four categories: current and future computer prices, and current and future component prices. This paper introduces the Prediction Challenge and presents the results from 2007 along with an analysis of how the predictions of the participants compare to each other.

  6. 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.

  7. 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,...

  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. An Introduction to Artificial Prediction Markets

    CERN Document Server

    Barbu, Adrian

    2011-01-01

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

  10. Evolution of property predictability during conceptual design

    DEFF Research Database (Denmark)

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

    2005-01-01

    A product is designed with the purpose of possessing certain properties, which are prescribed as requirements in the design specification. This paper studies the evolution of property predictability during the early phases of design in a case study context. By the term property predictability, we...... refer to the designers’ confidence in predicting product properties based on the available information. In the case study, with use of the produced design models at four different stages of concept concretisation, the designers evaluated their confidence in predicting product properties related...... to the requirements set for the task. As a result, we identified three different patterns of property predictability behaviour. These patterns consist of properties of which predictability is relatively high throughout the early phases of the design process, properties of which predictability shows a high increase...

  11. Predictive testing for Huntington's disease.

    Science.gov (United States)

    Tibben, Aad

    2007-04-30

    Worldwide, predictive testing for Huntington's disease has become an accepted clinical application that has allowed many individuals from HD-families to proceed with their life without the uncertainty of being at risk. International guidelines have extensively contributed to establishing counselling programmes of high quality, and have served as a model for other genetic disorders. Psychological follow-up studies have increased the insight into the far-reaching impact of test results for all individuals involved. Although the guidelines have served as a useful frame of reference, clinical experience has shown the importance of a case-by-case approach to do justice to the specific needs of the individual test candidate. Issues such as ambiguous test results, lack of awareness in a test candidate of early signs of the disease, non-compliance to the test protocol, or the test candidate's need for information on the relationship between age at onset and CAG-repeat require careful consideration. Receiving a test result is only one of the transition points in the life of an individual at risk; such result needs to be valued from a life-cycle perspective.

  12. Color prediction in textile application

    Science.gov (United States)

    De Lucia, Maurizio; Buonopane, Massimo

    2004-09-01

    Nowadays production systems of fancy yarns for knits allow the creation of extremely complex products in which many effects are obtained by means of color alteration. Current production technique consists in defining type and quantity of fibers by making preliminary samples. This samples are then compared with a reference one. This comparison is based on operator experience. Many samples are required in order to achieve a sample similar to the reference one. This work requires time and then additional costs for a textile manufacturer. In addition, the methodology is subjective. Nowadays, spectrophotometers are the only devices that seem to be able to provide objective indications. They are based on a spectral analysis of the light reflected by the knit material. In this paper the study of a new method for color evaluation of a mix of wool fibers with different colors is presented. First of all fiber characterization were carried out through scattering and absorption coefficients using the Kubelka-Munk theory. Then the estimated color was compared with a reference item, in order to define conformity by means of objective parameters. Finally, theoretical characterization was compared with the measured quantity. This allowed estimation of prediction quality.

  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. Time estimation predicts mathematical intelligence.

    Directory of Open Access Journals (Sweden)

    Peter Kramer

    Full Text Available BACKGROUND: Performing mental subtractions affects time (duration estimates, and making time estimates disrupts mental subtractions. This interaction has been attributed to the concurrent involvement of time estimation and arithmetic with general intelligence and working memory. Given the extant evidence of a relationship between time and number, here we test the stronger hypothesis that time estimation correlates specifically with mathematical intelligence, and not with general intelligence or working-memory capacity. METHODOLOGY/PRINCIPAL FINDINGS: Participants performed a (prospective time estimation experiment, completed several subtests of the WAIS intelligence test, and self-rated their mathematical skill. For five different durations, we found that time estimation correlated with both arithmetic ability and self-rated mathematical skill. Controlling for non-mathematical intelligence (including working memory capacity did not change the results. Conversely, correlations between time estimation and non-mathematical intelligence either were nonsignificant, or disappeared after controlling for mathematical intelligence. CONCLUSIONS/SIGNIFICANCE: We conclude that time estimation specifically predicts mathematical intelligence. On the basis of the relevant literature, we furthermore conclude that the relationship between time estimation and mathematical intelligence is likely due to a common reliance on spatial ability.

  15. 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.

  16. Prediction of violent mechanochemical processes

    Energy Technology Data Exchange (ETDEWEB)

    Graham, R.A.; Anderson, M.U.; Holman, G.T.; Baer, M.R.

    1997-01-01

    Energetic materials, such as high explosives, propellants and ballotechnics, are widely used as energy sources in the design of numerous devices, components and processes. Although most energetic materials are selected for safe operation, their high energy densities have the potential for inadvertent initiation and subsequent powerful energy transformations. This potential for damage or injury places a heavy burden on careful analysis of safety issues as part of the design process. As a result, considerable effort has been devoted to empirical testing of initiation conditions, and development of scientific models of initiation processes that have been incorporated into computer models for numerical simulation of initiation of reaction. Nevertheless, in many cases, there is still only rudimentary understanding of the processes of initiation. Mechanochemical processes are perhaps the least understood of the various excitation mechanisms. In these energy transformation processes mechanical stimuli lead directly to initiation and substantial reaction under conditions not thought to be capable of reaction. There are no established scientific models of the initiation of mechanochemical reactions in energetic materials. Mechanochemical reactions can be initiated by enhanced solid state chemical reactivity, changes in reactant configuration, and localization of initiation energy. Such solid state reactions are difficult to understand, either empirically or scientifically, as they are inherently nonequilibrium processes; scientific models currently used assume equilibrium thermochemical conditions and materials behaviors. The present work was undertaken as a first step in developing a scientific basis for prediction of the initiation of mechanochemical processes in high energy density solids.

  17. Flavor effects on leptogenesis predictions

    CERN Document Server

    Blanchet, S; Bari, Pasquale Di; Blanchet, Steve

    2006-01-01

    Flavor effects in leptogenesis reduce the region of the see-saw parameter space where the final predictions do not depend on the initial conditions, the strong wash-out regime. In this case we show that the lowest bounds holding on the lightest right-handed (RH) neutrino mass and on the reheating temperature for hierarchical heavy neutrinos, do not get relaxed compared to the usual ones in the one-flavor approximation, M_1 (T_reh) \\gtrsim 3 (1.5) x 10^9 GeV. Flavor effects can however relax down to these minimal values the lower bounds holding for fixed large values of the decay parameter K_1. We discuss a relevant definite example showing that, when the known information on the neutrino mixing matrix is employed, the lower bounds for K_1 \\gg 10, are relaxed by a factor 2-3 for light hierarchical neutrinos, without any dependence on \\theta_13 and on possible phases. On the other hand, going beyond the limit of light hierarchical neutrinos and taking into account Majorana phases, the lower bounds can be relaxe...

  18. 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.

  19. Predictive Modeling of Cardiac Ischemia

    Science.gov (United States)

    Anderson, Gary T.

    1996-01-01

    The goal of the Contextual Alarms Management System (CALMS) project is to develop sophisticated models to predict the onset of clinical cardiac ischemia before it occurs. The system will continuously monitor cardiac patients and set off an alarm when they appear about to suffer an ischemic episode. The models take as inputs information from patient history and combine it with continuously updated information extracted from blood pressure, oxygen saturation and ECG lines. Expert system, statistical, neural network and rough set methodologies are then used to forecast the onset of clinical ischemia before it transpires, thus allowing early intervention aimed at preventing morbid complications from occurring. The models will differ from previous attempts by including combinations of continuous and discrete inputs. A commercial medical instrumentation and software company has invested funds in the project with a goal of commercialization of the technology. The end product will be a system that analyzes physiologic parameters and produces an alarm when myocardial ischemia is present. If proven feasible, a CALMS-based system will be added to existing heart monitoring hardware.

  20. 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.

  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. Probabilistic approach to earthquake prediction.

    Directory of Open Access Journals (Sweden)

    G. D'Addezio

    2002-06-01

    Full Text Available The evaluation of any earthquake forecast hypothesis requires the application of rigorous statistical methods. It implies a univocal definition of the model characterising the concerned anomaly or precursor, so as it can be objectively recognised in any circumstance and by any observer.A valid forecast hypothesis is expected to maximise successes and minimise false alarms. The probability gain associated to a precursor is also a popular way to estimate the quality of the predictions based on such precursor. Some scientists make use of a statistical approach based on the computation of the likelihood of an observed realisation of seismic events, and on the comparison of the likelihood obtained under different hypotheses. This method can be extended to algorithms that allow the computation of the density distribution of the conditional probability of earthquake occurrence in space, time and magnitude. Whatever method is chosen for building up a new hypothesis, the final assessment of its validity should be carried out by a test on a new and independent set of observations. The implementation of this test could, however, be problematic for seismicity characterised by long-term recurrence intervals. Even using the historical record, that may span time windows extremely variable between a few centuries to a few millennia, we have a low probability to catch more than one or two events on the same fault. Extending the record of earthquakes of the past back in time up to several millennia, paleoseismology represents a great opportunity to study how earthquakes recur through time and thus provide innovative contributions to time-dependent seismic hazard assessment. Sets of paleoseimologically dated earthquakes have been established for some faults in the Mediterranean area: the Irpinia fault in Southern Italy, the Fucino fault in Central Italy, the El Asnam fault in Algeria and the Skinos fault in Central Greece. By using the age of the

  3. Predictive depth coding of wavelet transformed images

    Science.gov (United States)

    Lehtinen, Joonas

    1999-10-01

    In this paper, a new prediction based method, predictive depth coding, for lossy wavelet image compression is presented. It compresses a wavelet pyramid composition by predicting the number of significant bits in each wavelet coefficient quantized by the universal scalar quantization and then by coding the prediction error with arithmetic coding. The adaptively found linear prediction context covers spatial neighbors of the coefficient to be predicted and the corresponding coefficients on lower scale and in the different orientation pyramids. In addition to the number of significant bits, the sign and the bits of non-zero coefficients are coded. The compression method is tested with a standard set of images and the results are compared with SFQ, SPIHT, EZW and context based algorithms. Even though the algorithm is very simple and it does not require any extra memory, the compression results are relatively good.

  4. Algorithm for Predicting Protein Secondary Structure

    CERN Document Server

    Senapati, K K; Bhaumik, D

    2010-01-01

    Predicting protein structure from amino acid sequence is one of the most important unsolved problems of molecular biology and biophysics.Not only would a successful prediction algorithm be a tremendous advance in the understanding of the biochemical mechanisms of proteins, but, since such an algorithm could conceivably be used to design proteins to carry out specific functions.Prediction of the secondary structure of a protein (alpha-helix, beta-sheet, coil) is an important step towards elucidating its three dimensional structure as well as its function. In this research, we use different Hidden Markov models for protein secondary structure prediction. In this paper we have proposed an algorithm for predicting protein secondary structure. We have used Hidden Markov model with sliding window for secondary structure prediction.The secondary structure has three regular forms, for each secondary structural element we are using one Hidden Markov Model.

  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. 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...

  7. 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.

  8. 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.

  9. Predicting Group Evolution in the Social Network

    OpenAIRE

    Bródka, Piotr; Kazienko, Przemysław; Kołoszczyk, Bartosz

    2012-01-01

    Groups - social communities are important components of entire societies, analysed by means of the social network concept. Their immanent feature is continuous evolution over time. If we know how groups in the social network has evolved we can use this information and try to predict the next step in the given group evolution. In the paper, a new aproach for group evolution prediction is presented and examined. Experimental studies on four evolving social networks revealed that (i) the predict...

  10. Deterministic prediction of surface wind speed variations

    OpenAIRE

    Drisya, G. V.; Kiplangat, D. C.; Asokan, K; K. Satheesh Kumar

    2014-01-01

    Accurate prediction of wind speed is an important aspect of various tasks related to wind energy management such as wind turbine predictive control and wind power scheduling. The most typical characteristic of wind speed data is its persistent temporal variations. Most of the techniques reported in the literature for prediction of wind speed and power are based on statistical methods or probabilistic distribution of wind speed data. In this paper we demonstrate that determin...

  11. Disagreement, Uncertainty and the True Predictive Density

    OpenAIRE

    Fabian Krüger; Ingmar Nolte

    2011-01-01

    This paper generalizes the discussion about disagreement versus uncertainty in macroeconomic survey data by emphasizing the importance of the (unknown) true predictive density. Using a forecast combination approach, we ask whether cross sections of survey point forecasts help to approximate the true predictive density. We find that although these cross-sections perform poorly individually, their inclusion into combined predictive densities can significantly improve upon densities relying sole...

  12. Shape Prediction Linear Algorithm Using Fuzzy

    Directory of Open Access Journals (Sweden)

    Navjot Kaur

    2012-10-01

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

  13. Predicting Process Behaviour using Deep Learning

    OpenAIRE

    Evermann, Joerg; Rehse, Jana-Rebecca; Fettke, Peter

    2016-01-01

    Predicting business process behaviour, such as the final state of a running process, the remaining time to completion or the next activity of a running process, is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process. This is both a novel method in process prediction, which has largely relied ...

  14. Forecasting hotspots using predictive visual analytics approach

    Science.gov (United States)

    Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David

    2014-12-30

    A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

  15. EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH

    OpenAIRE

    Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.

    2014-01-01

    The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain,...

  16. Do university entrance exams predict academic achievement?

    OpenAIRE

    Häkkinen, Iida

    2004-01-01

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

  17. 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.

  18. 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......-forward neural network with one hidden layer on a data set identical to the one used in earlier work....

  19. Predictive Model Assessment for Count Data

    Science.gov (United States)

    2007-09-05

    critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts...the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. We consider a recent suggestion by Baker and...Figure 5. Boxplots for various scores for patent data count regressions. 11 Table 1 Four predictive models for larynx cancer counts in Germany, 1998–2002

  20. 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.

  1. Deterministic prediction of surface wind speed variations

    Science.gov (United States)

    Drisya, G. V.; Kiplangat, D. C.; Asokan, K.; Satheesh Kumar, K.

    2014-11-01

    Accurate prediction of wind speed is an important aspect of various tasks related to wind energy management such as wind turbine predictive control and wind power scheduling. The most typical characteristic of wind speed data is its persistent temporal variations. Most of the techniques reported in the literature for prediction of wind speed and power are based on statistical methods or probabilistic distribution of wind speed data. In this paper we demonstrate that deterministic forecasting methods can make accurate short-term predictions of wind speed using past data, at locations where the wind dynamics exhibit chaotic behaviour. The predictions are remarkably accurate up to 1 h with a normalised RMSE (root mean square error) of less than 0.02 and reasonably accurate up to 3 h with an error of less than 0.06. Repeated application of these methods at 234 different geographical locations for predicting wind speeds at 30-day intervals for 3 years reveals that the accuracy of prediction is more or less the same across all locations and time periods. Comparison of the results with f-ARIMA model predictions shows that the deterministic models with suitable parameters are capable of returning improved prediction accuracy and capturing the dynamical variations of the actual time series more faithfully. These methods are simple and computationally efficient and require only records of past data for making short-term wind speed forecasts within practically tolerable margin of errors.

  2. 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.

  3. 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....

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Tail Risk Premia and Return Predictability

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Todorov, Viktor; Xu, Lai

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

  9. Predicting division plane position and orientation.

    Science.gov (United States)

    Minc, Nicolas; Piel, Matthieu

    2012-04-01

    Predicting cellular behavior is a major challenge in cell and developmental biology. Since the late nineteenth century, empirical rules have been formulated to predict the position and orientation of mitotic cleavage planes in plant and animal cells. Here, we review the history of division plane orientation rules and discuss recent experimental and theoretical studies that refine these rules and provide mechanistic insights into how division can be predicted. We describe why some of these rules may better apply to certain cell types and developmental contexts and discuss how they could be integrated in the future to allow the prediction of division positioning in tissues.

  10. Predicting Player Churn In the Wild

    DEFF Research Database (Denmark)

    Hadiji, Fabian; Sifa, Rafet; Drachen, Anders;

    2014-01-01

    a crucial value, allowing developers to obtain data-driven insights to inform design, development and marketing strategies. One of the key challenges is modeling and predicting player churn. This paper presents the first cross-game study of churn prediction in Free-to-Play games. Churn in games is discussed...... with the individual retention model for each game in the dataset used, we develop a broadly applicable churn prediction model, which does not rely on gamedesign specific features. The presented classifiers are applied on a dataset covering five free-to-play games resulting in high accuracy churn prediction....

  11. RNA structure prediction: progress and perspective

    CERN Document Server

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

    2014-01-01

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

  12. 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.

  13. 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

  14. 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

  15. Continuous-Discrete Time Prediction-Error Identification Relevant for Linear Model Predictive Control

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays. It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model......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...

  16. Improved query difficulty prediction for the web

    NARCIS (Netherlands)

    Hauff, C.; Murdock, V.; Baeza-Yates, R.

    2008-01-01

    Query performance prediction aims to predict whether a query will have a high average precision given retrieval from a particular collection, or low average precision. An accurate estimator of the quality of search engine results can allow the search engine to decide to which queries to apply query

  17. 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

  18. 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...

  19. Case studies in archaeological predictive modelling

    NARCIS (Netherlands)

    Verhagen, Jacobus Wilhelmus Hermanus Philippus

    2007-01-01

    In this thesis, a collection of papers is put together dealing with various quantitative aspects of predictive modelling and archaeological prospection. Among the issues covered are the effects of survey bias on the archaeological data used for predictive modelling, and the complexities of testing p

  20. The relative value of operon predictions

    NARCIS (Netherlands)

    Brouwer, Rutger W. W.; Kuipers, Oscar P.; van Hijum, Sacha A. F. T.

    2008-01-01

    For most organisms, computational operon predictions are the only source of genome-wide operon information. Operon prediction methods described in literature are based on (a combination of) the following five criteria: (i) intergenic distance, (ii) conserved gene clusters, (iii) functional relation,

  1. 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.

  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 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...

  4. Predicting Involuntary Separation of Enlisted Personnel.

    Science.gov (United States)

    1980-01-01

    involuntary separation 20 ABSTRACT tConinue on rev -.. side It rect.ssaty and id.. nif hy block rnmhirl ,This report contains lh’ results of a study to compare...Subsample Size - 1000 Predicted 1 593 204 590 217 Base Rate - 65% Predicted 0 57 146 ( A1 133 Classification Accuracy (7’) 73.9 72.3 Subsample Size

  5. Optimal Online Prediction in Adversarial Environments

    Science.gov (United States)

    Bartlett, Peter L.

    In many prediction problems, including those that arise in computer security and computational finance, the process generating the data is best modelled as an adversary with whom the predictor competes. Even decision problems that are not inherently adversarial can be usefully modeled in this way, since the assumptions are sufficiently weak that effective prediction strategies for adversarial settings are very widely applicable.

  6. Different Methods of Predicting Permeability in Shale

    DEFF Research Database (Denmark)

    Mbia, Ernest Ncha; Fabricius, Ida Lykke; Krogsbøll, Anette

    Permeability is often very difficult to measure or predict in shale lithology. In this work we are determining shale permeability from consolidation tests data using Wissa et al., (1971) approach and comparing the results with predicted permeability from Kozeny’s model. Core and cuttings materials...

  7. 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 it...

  8. 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

  9. 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…

  10. An Improved Algorithm for Predicting Free Recalls

    Science.gov (United States)

    Laming, Donald

    2008-01-01

    Laming [Laming, D. (2006). "Predicting free recalls." "Journal of Experimental Psychology: Learning, Memory, and Cognition," 32, 1146-1163] has shown that, in a free-recall experiment in which the participants rehearsed out loud, entire sequences of recalls could be predicted, to a useful degree of precision, from the prior sequences of stimuli…

  11. 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

  12. Climate Predictability and Long Term Memory

    Science.gov (United States)

    Zhu, X.; Blender, R.; Fraedrich, K.; Liu, Z.

    2010-09-01

    The benefit of climate Long Term Memory (LTM) for long term prediction is assessed using data from a millennium control simulation with the atmosphere ocean general circulation model ECHAM5/MPIOM. The forecast skills are evaluated for surface temperature time series at individual grid points. LTM is characterised by the Hurst exponent in the power-law scaling of the fluctuation function which is determined by detrended fluctuation analysis (DFA). LTM with a Hurst exponent close to 0.9 occurs mainly in high latitude oceans, which are also characterized by high potential predictability. Climate predictability is diagnosed in terms of potentially predictable variance fractions. Explicit prediction experiments for various time steps are conducted on a grid point basis using an auto-correlation (AR1) predictor: in regions with LTM, prediction skills are beyond that expected from red noise persistence; exceptions occur in some areas in the southern oceans and over the northern hemisphere continents. Extending the predictability analysis to the fully forced simulation shows large improvement in prediction skills.

  13. How to Establish Clinical Prediction Models

    Directory of Open Access Journals (Sweden)

    Yong-ho Lee

    2016-03-01

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

  14. 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...

  15. 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

  16. 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.

  17. Prediction during sentence comprehension in aphasia

    Directory of Open Access Journals (Sweden)

    Michael Walsh Dickey

    2014-04-01

    Full Text Available Much recent psycholinguistic work has focused on prediction in language comprehension (Altmann & Kamide, 1999; Federmeier, 2007; Levy, 2008. Unimpaired adults predict upcoming words and phrases based on material in the preceding context, like verbs (Altmann & Kamide, 1999 or constraining sentence contexts (Federmeier, 2007. Several models have tied rapid prediction to the language production system (Federmeier, 2007; Pickering & Garrod, 2013; Dell & Chang, 2014. Evidence for this link comes from that fact that older adults with lower verbal fluency show less predictive behavior (Federmeier, et al., 2010; DeLong, et al., 2012. Prediction in aphasic language comprehension has not been widely investigated, even though constraining sentence contexts are strongly facilitative for naming in aphasia (e.g., Love & Webb, 1977. Mack, et al. (2013 found in a visual-world task that people with aphasia (PWA do not predict upcoming objects based on verbs (cf. Altmann & Kamide, 1999. This finding suggests that prediction may be reduced in aphasia. However, it is unclear whether reduced prediction was caused by language-production impairments: all the PWA in their study had non-fluent aphasia. The current study examined whether PWA show evidence of prediction based on constraining sentence contexts (e.g., Federmeier, 2007. Specifically, it tested whether they exhibited facilitation for highly predictable words in reading, using materials that have previously demonstrated strong predictability effects for unimpaired adults (Rayner, et al., 2004. In addition, it tested whether differences in language-production ability among PWA accounted for differences in predictive behavior (viz. Pickering & Garrod, 2013; Dell & Chang, 2014. Eight PWA read sentences adapted from Rayner, et al. (2004 in a self-paced reading task. The materials crossed word frequency with predictability: high- vs. low-frequency words (bottle/diaper were preceded by contexts which made them

  18. 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) ...

  19. Predicting Students’ Academic Performance in Iranian Schools

    Directory of Open Access Journals (Sweden)

    Mostafa Namjoo

    2014-05-01

    Full Text Available Data mining is the process of extracting valuable and novel knowledge from large data. It is analysis of data sets for finding patterns, relationships and help to summarize the knowledge for various goals. This investigation is motivated to study the students’ academic performance in high schools during 4 years which are collected from the department of education, Shiraz, Iran. Since one of the main challenges in Iranian schools is, prediction of students’ academic performance and their success in university entrance exam, therefore, we applied different classification and prediction algorithms on students’ data for discovering the possibility of predicting students’ scores before examination. Our results show that, it is possible to predict students’ gender, marks with applying classification and prediction algorithms and verifying some factors which are mentioned in this paper

  20. 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.

  1. Green building performance prediction/assessment

    Energy Technology Data Exchange (ETDEWEB)

    Papamichael, Konstantinos

    2000-02-01

    To make decisions, building designers need to predict and assess the performance of their ideas with respect to various criteria, such as comfort, esthetics, energy, environmental impact, economics, etc. Performance prediction with respect to environmental impact requires complicated models and massive computations, which are usually possible only through computer-based tools. This paper focuses on the use of computer-based tools for predicting and assessing building performance with respect to environmental impact criteria for the design of green buildings. It contains analyses of green performance prediction/assessment and descriptions of available tools, along with discussions on their use by different types of users. Finally, it includes analyses of the cost and benefits of green performance prediction and assessment.

  2. The Link Prediction Problem in Bipartite Networks

    CERN Document Server

    Kunegis, Jérôme; Albayrak, Sahin

    2010-01-01

    We define and study the link prediction problem in bipartite networks, specializing general link prediction algorithms to the bipartite case. In a graph, a link prediction function of two vertices denotes the similarity or proximity of the vertices. Common link prediction functions for general graphs are defined using paths of length two between two nodes. Since in a bipartite graph adjacency vertices can only be connected by paths of odd lengths, these functions do not apply to bipartite graphs. Instead, a certain class of graph kernels (spectral transformation kernels) can be generalized to bipartite graphs when the positive-semidefinite kernel constraint is relaxed. This generalization is realized by the odd component of the underlying spectral transformation. This construction leads to several new link prediction pseudokernels such as the matrix hyperbolic sine, which we examine for rating graphs, authorship graphs, folksonomies, document--feature networks and other types of bipartite networks.

  3. 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.

  4. Predictability crisis in early universe cosmology

    Science.gov (United States)

    Smeenk, Chris

    2014-05-01

    Inflationary cosmology has been widely accepted due to its successful predictions: for a "generic" initial state, inflation produces a homogeneous, flat, bubble with an appropriate spectrum of density perturbations. However, the discovery that inflation is "generically eternal," leading to a vast multiverse of inflationary bubbles with different low-energy physics, threatens to undermine this account. There is a "predictability crisis" in eternal inflation, because extracting predictions apparently requires a well-defined measure over the multiverse. This has led to discussions of anthropic predictions based on a measure over the multiverse, and an assumption that we are typical observers. I will give a pessimistic assessment of attempts to make predictions in this sense, emphasizing in particular problems that arise even if a unique measure can be found.

  5. 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...

  6. 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...

  7. 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.

  8. 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.

  9. Predicting RNA Structure Using Mutual Information

    DEFF Research Database (Denmark)

    Freyhult, E.; Moulton, V.; Gardner, P. P.

    2005-01-01

    Background: With the ever-increasing number of sequenced RNAs and the establishment of new RNA databases, such as the Comparative RNA Web Site and Rfam, there is a growing need for accurately and automatically predicting RNA structures from multiple alignments. Since RNA secondary structure......, to display and predict conserved RNA secondary structure (including pseudoknots) from an alignment. Results: We show that MIfold can be used to predict simple pseudoknots, and that the performance can be adjusted to make it either more sensitive or more selective. We also demonstrate that the overall...... performance of MIfold improves with the number of aligned sequences for certain types of RNA sequences. In addition, we show that, for these sequences, MIfold is more sensitive but less selective than the related RNAalifold structure prediction program and is comparable with the COVE structure prediction...

  10. 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......, for which three point forecasting methods are considered as input. The probabilistic forecasts generated are evaluated based on their reliability and sharpness, while compared to forecasts based on quantile regression and the climatology benchmark. The operational application of adapted resampling...

  11. Using Neutral Network in Predicting Corporate Failure

    Directory of Open Access Journals (Sweden)

    Huong G. Nguyen

    2005-01-01

    Full Text Available This study investigates the predictive power of three neutral network models: Multi-layer neural network, probabilistic neural network, and logistic regression model in predicting corporate failure. Basing on the database provided by The Corporate Scorecard Group (CSG, we combine financial ratios which deem to be significant predictors of corporate bankruptcy in many previous empirical studies to build our predictive models and test it against the holdout sample. On comparison of the results, we find that three models are good at predicting probability of corporate failure. Moreover, probabilistic neural network model outperforms the others. Therefore, neutral networks are useful and probabilistic neutral network is a promising tool for the prediction of corporate failure.

  12. Interactions of timing and prediction error learning.

    Science.gov (United States)

    Kirkpatrick, Kimberly

    2014-01-01

    Timing and prediction error learning have historically been treated as independent processes, but growing evidence has indicated that they are not orthogonal. Timing emerges at the earliest time point when conditioned responses are observed, and temporal variables modulate prediction error learning in both simple conditioning and cue competition paradigms. In addition, prediction errors, through changes in reward magnitude or value alter timing of behavior. Thus, there appears to be a bi-directional interaction between timing and prediction error learning. Modern theories have attempted to integrate the two processes with mixed success. A neurocomputational approach to theory development is espoused, which draws on neurobiological evidence to guide and constrain computational model development. Heuristics for future model development are presented with the goal of sparking new approaches to theory development in the timing and prediction error fields.

  13. 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.

  14. 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.

  15. 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

  16. PTRANSP Tests of TGLF and Predictions for ITER

    Energy Technology Data Exchange (ETDEWEB)

    Robert V. Budny, Xingqiu Yuan, S. Jardin, G. Hammett, G. Staebler, J. Kinsey, members of the ITPA Transport and Confinement Topical Group, and JET EFDA Contributors

    2012-09-23

    A new numerical solver for stiff transport predictions has been developed and implemented in the PTRANSP predictive transport code. The TGLF and GLF23 predictive codes have been incorporated in the solver, verified by comparisons with predictions from the XPTOR code, and validated by comparing predicted and measured profiles. Predictions for ITER baseline plasmas are presented.

  17. 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.

  18. 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.

  19. 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.

  20. Critical review of prostate cancer predictive tools.

    Science.gov (United States)

    Shariat, Shahrokh F; Kattan, Michael W; Vickers, Andrew J; Karakiewicz, Pierre I; Scardino, Peter T

    2009-12-01

    Prostate cancer is a very complex disease, and the decision-making process requires the clinician to balance clinical benefits, life expectancy, comorbidities and potential treatment-related side effects. Accurate prediction of clinical outcomes may help in the difficult process of making decisions related to prostate cancer. In this review, we discuss attributes of predictive tools and systematically review those available for prostate cancer. Types of tools include probability formulas, look-up and propensity scoring tables, risk-class stratification prediction tools, classification and regression tree analysis, nomograms and artificial neural networks. Criteria to evaluate tools include discrimination, calibration, generalizability, level of complexity, decision analysis and ability to account for competing risks and conditional probabilities. The available predictive tools and their features, with a focus on nomograms, are described. While some tools are well-calibrated, few have been externally validated or directly compared with other tools. In addition, the clinical consequences of applying predictive tools need thorough assessment. Nevertheless, predictive tools can facilitate medical decision-making by showing patients tailored predictions of their outcomes with various alternatives. Additionally, accurate tools may improve clinical trial design.

  1. Consensus contact prediction by linear programming.

    Science.gov (United States)

    Gao, Xin; Bu, Dongbo; Li, Shuai Cheng; Li, Ming; Xu, Jinbo

    2007-01-01

    Protein inter-residue contacts are of great use for protein structure determination or prediction. Recent CASP events have shown that a few accurately predicted contacts can help improve both computational efficiency and prediction accuracy of the ab inito folding methods. This paper develops an integer linear programming (ILP) method for consensus-based contact prediction. In contrast to the simple "majority voting" method assuming that all the individual servers are equal and independent, our method evaluates their correlations using the maximum likelihood method and constructs some latent independent servers using the principal component analysis technique. Then, we use an integer linear programming model to assign weights to these latent servers in order to maximize the deviation between the correct contacts and incorrect ones; our consensus prediction server is the weighted combination of these latent servers. In addition to the consensus information, our method also uses server-independent correlated mutation (CM) as one of the prediction features. Experimental results demonstrate that our contact prediction server performs better than the "majority voting" method. The accuracy of our method for the top L/5 contacts on CASP7 targets is 73.41%, which is much higher than previously reported studies. On the 16 free modeling (FM) targets, our method achieves an accuracy of 37.21%.

  2. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo

    2016-10-01

    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  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. Prediction of properties of intraply hybrid composites

    Science.gov (United States)

    Chamis, C. C.; Sinclair, J. H.

    1979-01-01

    Equations based on the mixtures rule are presented for predicting the physical, thermal, hygral, and mechanical properties of unidirectional intraply hybrid composites (UIHC) from the corresponding properties of their constituent composites. Bounds were derived for uniaxial longitudinal strengths, tension, compression, and flexure of UIHC. The equations predict shear and flexural properties which agree with experimental data from UIHC. Use of these equations in a composites mechanics computer code predicted flexural moduli which agree with experimental data from various intraply hybrid angleplied laminates (IHAL). It is indicated, briefly, how these equations can be used in conjunction with composite mechanics and structural analysis during the analysis/design process.

  5. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...

  6. 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.

  7. 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

  8. Link Prediction in Complex Networks: A Survey

    CERN Document Server

    Lu, Linyuan

    2010-01-01

    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 labelled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.

  9. Prediction of the environmental fate of chemicals.

    Science.gov (United States)

    Vighi, M; Calamari, D

    1993-01-01

    An overview is presented of the possibilities of applying multimedia compartmental evaluative models, and in particular the fugacity approach, to predict the environmental distribution and fate of organic chemicals. The use of this predictive approach for the evaluation of exposure to pollutants in the aquatic system is described, with reference to different environments or discharge patterns (surface and groundwaters, point and diffuse sources of pollution). The value and limitations of this approach are noted and the need for more research to improve predictive capability and practical usefulness is indicated. Finally some practical applications of evaluative models in the proposal of quantitative indices for ecotoxicological evaluation of risk from chemicals are described.

  10. Bursting frequency prediction in turbulent boundary layers

    Energy Technology Data Exchange (ETDEWEB)

    LIOU,WILLIAM W.; FANG,YICHUNG

    2000-02-01

    The frequencies of the bursting events associated with the streamwise coherent structures of spatially developing incompressible turbulent boundary layers were predicted using global numerical solution of the Orr-Sommerfeld and the vertical vorticity equations of hydrodynamic stability problems. The structures were modeled as wavelike disturbances associated with the turbulent mean flow. The global method developed here involves the use of second and fourth order accurate finite difference formula for the differential equations as well as the boundary conditions. An automated prediction tool, BURFIT, was developed. The predicted resonance frequencies were found to agree very well with previous results using a local shooting technique and measured data.

  11. Tropical Cyclone Prediction Using COAMPS-TC

    Science.gov (United States)

    2014-09-01

    Oceanography | Vol. 27, No.3104 S P E C I A L I S S U E O N N AV Y O P E R AT I O N A L M O D E L S Tropical Cyclone Prediction Using COAMPS...Ocean/ Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS®-TC) has been developed for prediction of tropical cyclone track, structure...and intensity. The COAMPS-TC has been tested in real time in both uncoupled and coupled modes over the past several tropical cyclone seasons in

  12. Predicting risky behavior in social communities

    CERN Document Server

    Simpson, Olivia

    2016-01-01

    Predicting risk profiles of individuals in networks (e.g.~susceptibility to a particular disease, or likelihood of smoking) is challenging for a variety of reasons. For one, `local' features (such as an individual's demographic information) may lack sufficient information to make informative predictions; this is especially problematic when predicting `risk,' as the relevant features may be precisely those that an individual is disinclined to reveal in a survey. Secondly, even if such features are available, they still may miss crucial information, as `risk' may be a function not just of an individual's features but also those of their friends and social communities. Here, we predict individual's risk profiles as a function of both their local features and those of their friends. Instead of modeling influence from the social network directly (which proved difficult as friendship links may be sparse and partially observed), we instead model influence by discovering social communities in the network that may be ...

  13. Predicting Engine Parameters using the Optical Spectrum

    Data.gov (United States)

    National Aeronautics and Space Administration — The Optical Plume Anomaly Detection (OPAD) system is under development to predict engine anomalies and engine parameters of the Space Shuttle's Main Engine (SSME)....

  14. Prediction of deformity in spinal tuberculosis

    NARCIS (Netherlands)

    Jutte, Paul; Wuite, Sander; The, Bertram; van Altena, Richard; Veldhuizen, Albert

    2007-01-01

    Tuberculosis of the spine may cause kyphosis, which may in turn cause late paraplegia, respiratory compromise, and unsightly deformity. Surgical correction therefore may be considered for large or progressive deformities. We retrospectively analyzed clinical and radiographic parameters to predict th

  15. Asthma Medication Ratio Predicts Emergency Depart...

    Data.gov (United States)

    U.S. Department of Health & Human Services — According to findings reported in Asthma Medication Ratio Predicts Emergency Department Visits and Hospitalizations in Children with Asthma, published in Volume 3,...

  16. Predictability of extreme events in social media

    CERN Document Server

    Miotto, José M

    2014-01-01

    It is part of our daily social-media experience that seemingly ordinary items (videos, news, publications, etc.) unexpectedly gain an enormous amount of attention. Here we investigate how unexpected these events are. We propose a method that, given some information on the items, quantifies the predictability of events, i.e., the potential of identifying in advance the most successful items defined as the upper bound for the quality of any prediction based on the same information. Applying this method to different data, ranging from views in YouTube videos to posts in Usenet discussion groups, we invariantly find that the predictability increases for the most extreme events. This indicates that, despite the inherently stochastic collective dynamics of users, efficient prediction is possible for the most extreme events.

  17. A Course in... Model Predictive Control.

    Science.gov (United States)

    Arkun, Yaman; And Others

    1988-01-01

    Describes a graduate engineering course which specializes in model predictive control. Lists course outline and scope. Discusses some specific topics and teaching methods. Suggests final projects for the students. (MVL)

  18. Improving predictions by cross pollination in time

    Science.gov (United States)

    Schevenhoven, Francine; Selten, Frank

    2016-04-01

    Given a set of imperfect weather models, one could ask how these models can be combined in order to improve weather predictions produced with these models. In this study we explore a technique called cross-pollination in time (CPT, Smith 2001). In the CPT approach the models exchange states during the prediction. The number of possible predictions grows quickly with time and a strategy to retain only a small number of predictions, called pruning, needs to be developed. In the learning phase a pruning strategy is proposed based on retaining those solutions that remain closest to the truth. From the learning phase probabilities are derived that determine weights to be applied to the imperfect models in the forecast phase. The CPT technique is explored using low-order dynamical systems and applied to a global atmospheric model. First results indicate that the CPT approach improves the forecast quality over the individual models.

  19. Software architecture and design for reliability predictability

    CERN Document Server

    Semegn, Assefa D

    2011-01-01

    Reliability prediction of a software product is complex due to interdependence and interactions among components and the difficulty of representing this behavior with tractable models. Models developed by making simplifying assumptions about the software

  20. Financial distress prediction and operating leases

    NARCIS (Netherlands)

    Lückerath – Rovers, M.

    2009-01-01

    This study investigates whether including operating lease commitments in financial distress prediction models would increase the classification accuracy of these models. Classification accuracy measures the percentages of correctly classified companies in either of the two categories (healthy or fin