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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 IL-6 mediates pituitary tumor senescence

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    Fuertes, Mariana; Ajler, Pablo; Carrizo, Guillermo; Cervio, Andrés; Sevlever, Gustavo; Stalla, Günter K.; Arzt, Eduardo

    2017-01-01

    Cellular senescence is a stable proliferative arrest state. Pituitary adenomas are frequent and mostly benign, but the mechanism for this remains unknown. IL-6 is involved in pituitary tumor progression and is produced by the tumoral cells. In a cell autonomous fashion, IL-6 participates in oncogene-induced senescence in transduced human melanocytes. Here we prove that autocrine IL-6 participates in pituitary tumor senescence. Endogenous IL-6 inhibition in somatotroph MtT/S shRNA stable clones results in decreased SA-β-gal activity and p16INK4a but increased pRb, proliferation and invasion. Nude mice injected with IL-6 silenced clones develop tumors contrary to MtT/S wild type that do not, demonstrating that clones that escape senescence are capable of becoming tumorigenic. When endogenous IL-6 is silenced, cell cultures derived from positive SA-β-gal human tumor samples decrease the expression of the senescence marker. Our results establish that IL-6 contributes to maintain senescence by its autocrine action, providing a natural model of IL-6 mediated benign adenoma senescence. PMID:27902467

  3. Autocrine Effects of Tumor-Derived Complement

    Directory of Open Access Journals (Sweden)

    Min Soon Cho

    2014-03-01

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

  4. Autocrine role of angiopoietins during megakaryocytic differentiation.

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    Ernestina Saulle

    Full Text Available The tyrosine kinase Tie-2 and its ligands Angiopoietins (Angs transduce critical signals for angiogenesis in endothelial cells. This receptor and Ang-1 are coexpressed in hematopoietic stem cells and in a subset of megakaryocytes, though a possible role of angiopoietins in megakaryocytic differentiation/proliferation remains to be demonstrated. To investigate a possible effect of Ang-1/Ang-2 on megakaryocytic proliferation/differentiation we have used both normal CD34(+ cells induced to megakaryocytic differentiation and the UT7 cells engineered to express the thrombopoietin receptor (TPOR, also known as c-mpl, UT7/mpl. Our results indicate that Ang-1/Ang-2 may have a role in megakaryopoiesis. Particularly, Ang-2 is predominantly produced and released by immature normal megakaryocytic cells and by undifferentiated UT7/mpl cells and slightly stimulated TPO-induced cell proliferation. Ang-1 production is markedly induced during megakaryocytic differentiation/maturation and potentiated TPO-driven megakaryocytic differentiation. Blocking endogenously released angiopoietins partially inhibited megakaryocytic differentiation, particularly for that concerns the process of polyploidization. According to these data it is suggested that an autocrine angiopoietin/Tie-2 loop controls megakaryocytic proliferation and differentiation.

  5. Autocrine signal transmission with extracellular ligand degradation

    International Nuclear Information System (INIS)

    Muratov, C B; Posta, F; Shvartsman, S Y

    2009-01-01

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

  6. Autocrine signal transmission with extracellular ligand degradation

    Science.gov (United States)

    Muratov, C B; Posta, F; Shvartsman, S Y

    2009-03-01

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

  7. 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.

  8. CGI-99 promotes breast cancer metastasis via autocrine interleukin-6 signaling.

    Science.gov (United States)

    Lin, C; Liao, W; Jian, Y; Peng, Y; Zhang, X; Ye, L; Cui, Y; Wang, B; Wu, X; Xiong, Z; Wu, S; Li, J; Wang, X; Song, L

    2017-06-29

    Metastatic relapse remains largely incurable and a major challenge of clinical management in breast cancer, but the underlying mechanisms are poorly understood. Herein, we report that CGI-99 is overexpressed in breast cancer tissues from patients with metastatic recurrence within 5 years. High CGI-99 significantly predicts poorer 5-year metastasis-free patient survival. We find that CGI-99 increases breast cancer stem cell properties, and potentiates efficient tumor lung colonization and outgrowth in vivo. Furthermore, we demonstrate that CGI-99 activates the autocrine interleukin-6 (IL-6)/STAT3 signaling by increasing the accumulation and activity of RNA polymerase II and p300 cofactor at the proximal promoter of IL-6. Importantly, delivery of the IL-6-receptor humanized monoclonal antibody tocilizumab robustly abrogates CGI-99-induced metastasis in vivo. Finally, we find that high levels of CGI-99 are significantly correlated with STAT3 hyperactivation in breast cancer patients. These findings reveal a potential mechanism for constitutive activation of autocrine IL-6/STAT3 signaling and may suggest a novel target for clinical intervention in breast cancer.

  9. Active CREB1 promotes a malignant TGFβ2 autocrine loop in glioblastoma.

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    Rodón, Laura; Gonzàlez-Juncà, Alba; Inda, María del Mar; Sala-Hojman, Ada; Martínez-Sáez, Elena; Seoane, Joan

    2014-10-01

    In advanced cancer, including glioblastoma, the TGFβ pathway acts as an oncogenic factor. Some tumors exhibit aberrantly high TGFβ activity, and the mechanisms underlying this phenomenon are not well understood. We have observed that TGFβ can induce TGFβ2, generating an autocrine loop leading to aberrantly high levels of TGFβ2. We identified cAMP-responsive element-binding protein 1 (CREB1) as the critical mediator of the induction of TGFβ2 by TGFβ. CREB1 binds to the TGFB2 gene promoter in cooperation with SMAD3 and is required for TGFβ to activate transcription. Moreover, the PI3K-AKT and RSK pathways regulate the TGFβ2 autocrine loop through CREB1. The levels of CREB1 and active phosphorylated CREB1 correlate with TGFβ2 in glioblastoma. In addition, using patient-derived in vivo models of glioblastoma, we found that CREB1 levels determine the expression of TGFβ2. Our results show that CREB1 can be considered a biomarker to stratify patients for anti-TGFβ treatments and a therapeutic target in glioblastoma. TGFβ is considered a promising therapeutic target, and several clinical trials using TGFβ inhibitors are generating encouraging results. Here, we discerned the molecular mechanisms responsible for the aberrantly high levels of TGFβ2 found in certain tumors, and we propose biomarkers to predict the clinical response to anti-TGFβ therapies. ©2014 American Association for Cancer Research.

  10. Self-amplifying autocrine actions of BDNF in axon development

    OpenAIRE

    Cheng, Pei-Lin; Song, Ai-Hong; Wong, Yu-Hui; Wang, Sheng; Zhang, Xiang; Poo, Mu-Ming

    2011-01-01

    A critical step in neuronal development is the formation of axon/dendrite polarity, a process involving symmetry breaking in the newborn neuron. Local self-amplifying processes could enhance and stabilize the initial asymmetry in the distribution of axon/dendrite determinants, but the identity of these processes remains elusive. We here report that BDNF, a secreted neurotrophin essential for the survival and differentiation of many neuronal populations, serves as a self-amplifying autocrine f...

  11. 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.

  12. 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.

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

    International Nuclear Information System (INIS)

    Tamura, Shogo; Nagasawa, Ayumi; Masuda, Yuya; Tsunematsu, Tetsuya; Hayasaka, Koji; Matsuno, Kazuhiko; Shimizu, Chikara; Ozaki, Yukio; Moriyama, Takanori

    2012-01-01

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

  14. Autocrine-paracrine regulation of the mammary gland.

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    Weaver, S R; Hernandez, L L

    2016-01-01

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

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

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

    1988-01-01

    Bovine lymphocytes infected with the parasite Theileria parva continuously secrete a growth factor that is essential for their proliferation in vitro and also constitutively express interleukin 2 receptors on their surface. Dilution of the secreted growth factor, caused by culturing cells at low density, results in retardation of culture growth. Human recombinant interleukin 2, however, effectively substitutes for the diluted growth factor by restoring normal growth rates and also allows Theileria-infected cells to be grown at low density without the use of feeder layers. Secretion of the growth factor and expression of the interleukin 2 receptor depend on the presence of the parasite in the cytoplasm of the host cell. Elimination of the parasite from the cell cytoplasm by the specific antitheilerial drug BW 720c results in the arrest of growth factor secretion and the disappearance of interleukin 2 receptors from the cell surface. This is accompanied by growth arrest and reversion of the infected cells to the morphology of resting lymphocytes. We propose that the continuous proliferation of infected cells in vitro is mediated by autocrine receptor activation. Images PMID:3133661

  16. Ikaros imposes a barrier to CD8+ T cell differentiation by restricting autocrine IL-2 production.

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    O'Brien, Shaun; Thomas, Rajan M; Wertheim, Gerald B; Zhang, Fuqin; Shen, Hao; Wells, Andrew D

    2014-06-01

    Naive CD4(+) T cells require signals from the TCR and CD28 to produce IL-2, expand, and differentiate. However, these same signals are not sufficient to induce autocrine IL-2 production by naive CD8(+) T cells, which require cytokines provided by other cell types to drive their differentiation. The basis for failed autocrine IL-2 production by activated CD8(+) cells is unclear. We find that Ikaros, a transcriptional repressor that silences IL-2 in anergic CD4(+) T cells, also restricts autocrine IL-2 production by CD8(+) T cells. We find that CD8(+) T cell activation in vitro in the absence of exogenous cytokines and CD4 help leads to marked induction of Ikaros, a known repressor of the Il2 gene. Naive murine CD8 T cells haplo-insufficient for Ikzf1 failed to upregulate Ikaros, produced autocrine IL-2, and differentiated in an IL-2-dependent manner into IFN-γ-producing CTLs in response to TCR/CD28 stimulation alone. Furthermore, Ikzf1 haplo-insufficient CD8(+) T cells were more effective at controlling Listeria infection and B16 melanoma growth in vivo, and they could provide help to neighboring, non-IL-2-producing cells to differentiate into IFN-γ-producing effectors. Therefore, by repressing autocrine IL-2 production, Ikaros ensures that naive CD8(+) T cells remain dependent on licensing by APCs and CD4(+) T cells, and it may therefore act as a cell-intrinsic safeguard against inappropriate CTL differentiation and immunopathology. Copyright © 2014 by The American Association of Immunologists, Inc.

  17. Endothelium-derived fibronectin regulates neonatal vascular morphogenesis in an autocrine fashion.

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    Turner, Christopher J; Badu-Nkansah, Kwabena; Hynes, Richard O

    2017-11-01

    Fibronectin containing alternatively spliced EIIIA and EIIIB domains is largely absent from mature quiescent vessels in adults, but is highly expressed around blood vessels during developmental and pathological angiogenesis. The precise functions of fibronectin and its splice variants during developmental angiogenesis however remain unclear due to the presence of cardiac, somitic, mesodermal and neural defects in existing global fibronectin KO mouse models. Using a rare family of surviving EIIIA EIIIB double KO mice, as well as inducible endothelial-specific fibronectin-deficient mutant mice, we show that vascular development in the neonatal retina is regulated in an autocrine manner by endothelium-derived fibronectin, and requires both EIIIA and EIIIB domains and the RGD-binding α5 and αv integrins for its function. Exogenous sources of fibronectin do not fully substitute for the autocrine function of endothelial fibronectin, demonstrating that fibronectins from different sources contribute differentially to specific aspects of angiogenesis.

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

    Czech Academy of Sciences Publication Activity Database

    Pravenec, Michal; Mlejnek, Petr; Zídek, Václav; Landa, Vladimír; Šimáková, Miroslava; Šilhavý, Jan; Strnad, Hynek; Eigner, Sebastian; Eigner-Henke, Kateřina; Škop, V.; Malínská, H.; Trnovská, J.; Kazdová, L.; Drahota, Zdeněk; Mráček, Tomáš; Houštěk, Josef

    2016-01-01

    Roč. 48, č. 6 (2016), s. 420-427 ISSN 1094-8341 R&D Projects: GA MŠk(CZ) LL1204; GA ČR(CZ) GB14-36804G; GA MZd(CZ) NT14325 Institutional support: RVO:67985823 ; RVO:68378050 ; RVO:61389005 Keywords : brown adipose tissue * autocrine * transgenic * spontaneously hypertensive rat Subject RIV: FB - Endocrinology, Diabetology, Metabolism, Nutrition Impact factor: 3.044, year: 2016

  19. The crystal structure of a multifunctional protein: Phosphoglucose isomerase/autocrine motility factor/neuroleukin

    OpenAIRE

    Sun, Yuh-Ju; Chou, Chia-Cheng; Chen, Wei-Shone; Wu, Rong-Tsun; Meng, Menghsiao; Hsiao, Chwan-Deng

    1999-01-01

    Phosphoglucose isomerase (PGI) plays a central role in both the glycolysis and the gluconeogenesis pathways. We present here the complete crystal structure of PGI from Bacillus stearothermophilus at 2.3-Å resolution. We show that PGI has cell-motility-stimulating activity on mouse colon cancer cells similar to that of endogenous autocrine motility factor (AMF). PGI can also enhance neurite outgrowth on neuronal progenitor cells similar to that observed for neuroleukin. The results confirm tha...

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

    International Nuclear Information System (INIS)

    Cozzolino, F.; Torcia, M.; Aldinucci, D.; Ziche, M.; Bani, D.; Almerigogna, F.; Stern, D.M.

    1990-01-01

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

  1. 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.

  2. Eosinophils as a novel cell source of prostaglandin D2: autocrine role in allergic inflammation

    Science.gov (United States)

    Luna-Gomes, Tatiana; Magalhães, Kelly G; Mesquita-Santos, Fabio P.; Bakker-Abreu, Ilka; Samico, Rafaela F.; Molinaro, Raphael; Calheiros, Andrea S.; Diaz, Bruno L.; Bozza, Patrícia T.

    2011-01-01

    Prostaglandin (PG)D2 is a key mediator of allergic inflammatory diseases that is mainly synthesized by mast cells, which constitutively express high levels of the terminal enzyme involved in PGD2 synthesis, the hematopoietic PGD synthase (H-PGDS). Here, we investigated whether eosinophils are also able to synthesize, and therefore, supply biologically active PGD2. PGD2 synthesis was evaluated within human blood eosinophils, in vitro-differentiated mouse eosinophils, and eosinophils infiltrating inflammatory site of mouse allergic reaction. Biological function of eosinophil-derived PGD2 was studied by employing inhibitors of synthesis and activity. Constitutive expression of H-PGDS was found within non-stimulated human circulating eosinophils. Acute stimulation of human eosinophils with A23187 (0.1 – 5 μM) evoked PGD2 synthesis, which was located at the nuclear envelope and was inhibited by pre-treatment with HQL-79 (10 μM), a specific H-PGDS inhibitor. Pre-stimulation of human eosinophils with arachidonic acid (AA; 10 μM) or human eotaxin (6 nM) also enhanced HQL-79-sensitive PGD2 synthesis, which, by acting on membrane-expressed specific receptors (DP1 and DP2), displayed an autocrine/paracrine ability to trigger leukotriene (LT)C4 synthesis and lipid body biogenesis, hallmark events of eosinophil activation. In vitro-differentiated mouse eosinophils also synthesized paracrine/autocrine active PGD2 in response to AA stimulation. In vivo, at late time point of the allergic reaction, infiltrating eosinophils found at the inflammatory site appeared as an auxiliary PGD2-synthesizing cell population. Our findings reveal that eosinophils are indeed able to synthesize and secrete PGD2, hence representing during allergic inflammation an extra cell source of PGD2, which functions as an autocrine signal for eosinophil activation. PMID:22102725

  3. Dictyostelium cells bind a secreted autocrine factor that represses cell proliferation

    OpenAIRE

    Choe, Jonathan M; Bakthavatsalam, Deenadayalan; Phillips, Jonathan E; Gomer, Richard H

    2009-01-01

    Abstract Background Dictyostelium cells secrete the proteins AprA and CfaD. Cells lacking either AprA or CfaD proliferate faster than wild type, while AprA or CfaD overexpressor cells proliferate slowly, indicating that AprA and CfaD are autocrine factors that repress proliferation. CfaD interacts with AprA and requires the presence of AprA to slow proliferation. To determine if CfaD is necessary for the ability of AprA to slow proliferation, whether AprA binds to cells, and if so whether the...

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

    Directory of Open Access Journals (Sweden)

    Jun Ishii

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

  5. Interferon beta 1, an intermediate in the tumor necrosis factor alpha- induced increased MHC class I expression and an autocrine regulator of the constitutive MHC class I expression

    OpenAIRE

    1987-01-01

    In conclusion, our observations indicate that the constitutive MHC class I expression is regulated by autocrine production of IFN-beta 1. TNF-alpha acts as an enhancer of the autocrine production of IFN-beta 1, and consequently as an enhancer of the MHC class I expression and viral protection.

  6. Autocrine regulation of human urothelial cell proliferation and migration during regenerative responses in vitro

    International Nuclear Information System (INIS)

    Varley, Claire; Hill, Gemma; Pellegrin, Stephanie; Shaw, Nicola J.; Selby, Peter J.; Trejdosiewicz, Ludwik K.; Southgate, Jennifer

    2005-01-01

    Regeneration of the urothelium is rapid and effective in order to maintain a barrier to urine following tissue injury. Whereas normal human urothelial (NHU) cells are mitotically quiescent and G0 arrested in situ, they rapidly enter the cell cycle upon seeding in primary culture and show reversible growth arrest at confluency. We have used this as a model to investigate the role of EGF receptor signaling in urothelial regeneration and wound-healing. Transcripts for HER-1, HER-2, and HER-3 were expressed by quiescent human urothelium in situ. Expression of HER-1 was upregulated in proliferating cultures, whereas HER-2 and HER-3 were more associated with a growth-arrested phenotype. NHU cells could be propagated in the absence of exogenous EGF, but autocrine signaling through HER-1 via the MAPK and PI3-kinase pathways was essential for proliferation and migration during urothelial wound repair. HB-EGF was expressed by urothelium in situ and HB-EGF, epiregulin, TGF-α, and amphiregulin were expressed by proliferating NHU cells. Urothelial wound repair in vitro was attenuated by neutralizing antibodies against HER-1 ligands, particularly amphiregulin. By contrast, the same ligands applied exogenously promoted migration, but inhibited proliferation, implying that HER-1 ligands provoke differential effects in NHU cells depending upon whether they are presented as soluble or juxtacrine ligands. We conclude that proliferation and migration during wound healing in NHU cells are mediated through an EGFR autocrine signalling loop and our results implicate amphiregulin as a key mediator

  7. XIAP gene expression and function is regulated by autocrine and paracrine TGF-β signaling

    Directory of Open Access Journals (Sweden)

    Van Themsche Céline

    2010-08-01

    Full Text Available Abstract Background X-linked inhibitor of apoptosis protein (XIAP is often overexpressed in cancer cells, where it plays a key role in survival and also promotes invasiveness. To date however, the extracellular signals and intracellular pathways regulating its expression and activity remain incompletely understood. We have previously showed that exposure to each of the three TGF-β (transforming growth factor beta isoforms upregulates XIAP protein content in endometrial carcinoma cells in vitro. In the present study, we have investigated the clinical relevance of TGF-β isoforms in endometrial tumours and the mechanisms through which TGF-β isoforms regulate XIAP content in uterine cancer cells. Methods TGF-β isoforms immunoreactivity in clinical samples from endometrial tumours was assessed using immunofluorescence. Two model cancer cell lines (KLE endometrial carcinoma cells and HeLa cervical cancer cells and pharmacological inhibitors were used to investigate the signalling pathways regulating XIAP expression and activity in response to autocrine and paracrine TGF-β in cancer cell. Results We have found immunoreactivity for each TGF-β isoform in clinical samples from endometrial tumours, localizing to both stromal and epithelial/cancer cells. Blockade of autocrine TGF-β signaling in KLE endometrial carcinoma cells and HeLa cervical cancer cells reduced endogenous XIAP mRNA and protein levels. In addition, each TGF-β isoform upregulated XIAP gene expression when given exogenously, in a Smad/NF-κB dependent manner. This resulted in increased polyubiquitination of PTEN (phosphatase and tensin homolog on chromosome ten, a newly identified substrate for XIAP E3 ligase activity, and in a XIAP-dependent decrease of PTEN protein levels. Although each TGF-β isoform decreased PTEN content in a XIAP- and a Smad-dependent manner, decrease of PTEN levels in response to only one isoform, TGF-β3, was blocked by PI3-K inhibitor LY294002. Conclusions

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2008-09-01

    Most colon cancers overexpress M3 muscarinic receptors (M3R), and post-M3R signaling stimulates human colon cancer cell proliferation. Acetylcholine (ACh), a muscarinic receptor ligand traditionally regarded as a neurotransmitter, may be produced by nonneuronal cells. We hypothesized that ACh release by human colon cancer cells results in autocrine stimulation of proliferation. H508 human colon cancer cells, which have robust M3R expression, were used to examine effects of muscarinic receptor antagonists, acetylcholinesterase inhibitors, and choline transport inhibitors on cell proliferation. A nonselective muscarinic receptor antagonist (atropine), a selective M3R antagonist (p-fluorohexahydro-sila-difenidol hydrochloride), and a choline transport inhibitor (hemicholinum-3) all inhibited unstimulated H508 colon cancer cell proliferation by approximately 40% (P<0.005). In contrast, two acetylcholinesterase inhibitors (eserine-hemisulfate and bis-9-amino-1,2,3,4-tetrahydroacridine) increased proliferation by 2.5- and 2-fold, respectively (P<0.005). By using quantitative real-time PCR, expression of choline acetyltransferase (ChAT), a critical enzyme for ACh synthesis, was identified in H508, WiDr, and Caco-2 colon cancer cells. By using high-performance liquid chromatography-electrochemical detection, released ACh was detected in H508 and Caco-2 cell culture media. Immunohistochemistry in surgical specimens revealed weak or no cytoplasmic staining for ChAT in normal colon enterocytes (n=25) whereas half of colon cancer specimens (n=24) exhibited moderate to strong staining (P<0.005). We conclude that ACh is an autocrine growth factor in colon cancer. Mechanisms that regulate colon epithelial cell production and release of ACh warrant further investigation.

  10. Spontaneous NF-κB activation by autocrine TNFα signaling: a computational analysis.

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    Jakub Pękalski

    Full Text Available NF-κB is a key transcription factor that regulates innate immune response. Its activity is tightly controlled by numerous feedback loops, including two negative loops mediated by NF-κB inducible inhibitors, IκBα and A20, which assure oscillatory responses, and by positive feedback loops arising due to the paracrine and autocrine regulation via TNFα, IL-1 and other cytokines. We study the NF-κB system of interlinked negative and positive feedback loops, combining bifurcation analysis of the deterministic approximation with stochastic numerical modeling. Positive feedback assures the existence of limit cycle oscillations in unstimulated wild-type cells and introduces bistability in A20-deficient cells. We demonstrated that cells of significant autocrine potential, i.e., cells characterized by high secretion of TNFα and its receptor TNFR1, may exhibit sustained cytoplasmic-nuclear NF-κB oscillations which start spontaneously due to stochastic fluctuations. In A20-deficient cells even a small TNFα expression rate qualitatively influences system kinetics, leading to long-lasting NF-κB activation in response to a short-pulsed TNFα stimulation. As a consequence, cells with impaired A20 expression or increased TNFα secretion rate are expected to have elevated NF-κB activity even in the absence of stimulation. This may lead to chronic inflammation and promote cancer due to the persistent activation of antiapoptotic genes induced by NF-κB. There is growing evidence that A20 mutations correlate with several types of lymphomas and elevated TNFα secretion is characteristic of many cancers. Interestingly, A20 loss or dysfunction also leaves the organism vulnerable to septic shock and massive apoptosis triggered by the uncontrolled TNFα secretion, which at high levels overcomes the antiapoptotic action of NF-κB. It is thus tempting to speculate that some cancers of deregulated NF-κB signaling may be prone to the pathogen-induced apoptosis.

  11. 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.

  12. Autocrine VEGF and IL-8 Promote Migration via Src/Vav2/Rac1/PAK1 Signaling in Human Umbilical Vein Endothelial Cells.

    Science.gov (United States)

    Ju, Li; Zhou, Zhiwen; Jiang, Bo; Lou, Yue; Guo, Xirong

    2017-01-01

    Pro-angiogenic factors VEGF and IL-8 play a major role in modulating the migratory potential of endothelial cells. The goal of this study was to investigate the effect of autocrine VEGF and IL-8 in the form of self-conditioned medium (CM) on human umbilical vein endothelial cells (HUVECs). Enzyme-linked immunosorbent assay (ELISA) examined the automatic secretion of VEGF and IL-8 protein by HUVECs. Western blot, small interfering RNA (siRNA), pulldown and Transwell assays were used to explore the role and the mechanism of autocrine VEGF and IL-8 in migration of HUVECs. Neutralizing VEGF and IL-8 in CM significantly abrogated CM-induced migration of HUVECs. Autocrine VEGF and IL-8 increased Src phosphorylation, Rac1 activity and PAK1 phosphorylation in a time dependent manner. Additionally, blocking Rac1 activity with Rac1 siRNA largely abolished autocrine VEGF and IL-8-induced cell migration. Vav2 siRNA suppressed autocrine VEGF and IL-8-induced Rac1 activation and cell migration. Furthermore, blocking Src signaling with PP2, a specific inhibitor for Src, markedly prevented autocrine VEGF and IL-8-induced Vav2 and Rac1 activation as well as consequently cell migration. PAK1 siRNA also significantly abolished autocrine VEGF and IL-8-induced cell migration. We demonstrated for the first time that autocrine VEGF and IL-8 promoted endothelial cell migration via the Src/Vav2/Rac1/PAK1 signaling pathway. This finding reveals the molecular mechanism in the increase of endothelial cell migration induced by autocrine growth factors and cytokines, which is expected to provide a novel therapeutic target in vascular diseases. © 2017 The Author(s)Published by S. Karger AG, Basel.

  13. Regulation of insulin-like growth factor (IGF) I receptor expression during muscle cell differentiation. Potential autocrine role of IGF-II.

    OpenAIRE

    Rosenthal, S M; Brunetti, A; Brown, E J; Mamula, P W; Goldfine, I D

    1991-01-01

    Muscle is an important target tissue for insulin-like growth factor (IGF) action. The presence of specific, high affinity IGF receptors, as well as the expression of IGF peptides and binding proteins by muscle suggest that a significant component of IGF action in this tissue is mediated through autocrine and/or paracrine mechanisms. To explore autocrine/paracrine action of IGFs in muscle, we studied the regulation of the IGF-I receptor and the expression of IGF peptides during differentiation...

  14. Paracrine and autocrine signals promoting full chondrogenic differentiation of a mesoblastic cell line.

    Science.gov (United States)

    Locker, Morgane; Kellermann, Odile; Boucquey, Marie; Khun, Huot; Huerre, Michel; Poliard, Anne

    2004-01-01

    The pluripotent mesoblastic C1 cell line was used under serum-free culture conditions to investigate how paracrine and autocrine signals cooperate to drive chondrogenesis. Sequential addition of two systemic hormones, dexamethasone and triiodothyronine, permits full chondrogenic differentiation. The cell intrinsic activation of the BMP signaling pathway and Sox9 expression occurring on mesoblastic condensation is insufficient for recruitment of the progenitors. Dexamethasone-dependent Sox9 upregulation is essential for chondrogenesis. Differentiation of lineage stem cells relies on cell autonomous regulations modulated by external signals. We used the pluripotent mesoblastic C1 cell line under serum-free culture conditions to investigate how paracrine and autocrine signals cooperate to induce differentiation of a precursor clone along the chondrogenic lineage. C1 cells, cultured as aggregates, were induced toward chondrogenesis by addition of 10(-7) M dexamethasone in serum-free medium. After 30 days, dexamethasone was replaced by 10 nM triiodothyronine to promote final hypertrophic conversion. Mature and hypertrophic phenotypes were characterized by immunocytochemistry using specific antibodies against types II and X collagens, respectively. Type II collagen, bone morphogenetic proteins (BMPs), BMP receptors, Smads, and Sox9 expression were monitored by reverse transcriptase-polymerase chain reaction (RT-PCR), Northern blot, and/or Western blot analysis. Once C1 cells have formed nodules, sequential addition of two systemic hormones is sufficient to promote full chondrogenic differentiation. In response to dexamethasone, nearly 100% of the C1 precursors engage in chondrogenesis and convert within 30 days into mature chondrocytes, which triggers a typical cartilage matrix. On day 25, a switch in type II procollagen mRNA splicing acted as a limiting step in the acquisition of the mature chondrocyte phenotype. On day 30, substitution of dexamethasone with

  15. Autocrine EGF receptor activation mediates endothelial cell migration and vascular morphogenesis induced by VEGF under interstitial flow

    International Nuclear Information System (INIS)

    Semino, Carlos E.; Kamm, Roger D.; Lauffenburger, Douglas A.

    2006-01-01

    We show here that autocrine ligand activation of epidermal growth factor (EGF) receptor in combination with interstitial flow is critically involved in the morphogenetic response of endothelial cells to VEGF stimulation. Human umbilical vein endothelial cell (HUVEC) monolayers cultured on a collagen gel and exposed to low interstitial flow in the absence of EGF and VEGF remained viable and mitotic but exhibited little evidence of vascular morphogenesis. Addition of VEGF produced a flow-dependent morphogenetic response within 48 to 72 h, characterized by branched capillary-like structures. The response was substantially abolished by inhibitors related to the autocrine EGF receptor pathway including Galardin, AG1478, PD98059, and an EGF receptor-blocking antibody, indicating that regulation of the morphogenetic process operates via autocrine EGF receptor activation. Moreover, we observed that in our system the EGF receptor was always activated independently of the interstitial flow, and, in addition, the EGF receptor inhibitors used above reduced the phosphorylation state of the receptor, correlating with inhibition of capillary morphogenesis. Finally, 5'bromo-2'-deoxyuridine (BrdU) labeling identified dividing cells at the monolayer but not in the extending capillary-like structures. EGF pathway inhibitors Galardin and AG1478 did not reduce BrdU incorporation in the monolayer, indicating that the EGF-receptor-mediated morphogenetic behavior is mainly due to cell migration rather than proliferation. Based on these results, we propose a two-step model for in vitro capillary morphogenesis in response to VEGF stimulation with interstitial fluid flow: monolayer maintenance by mitotic activity independent of EGF receptors and a migratory response mediated by autocrine EGF receptor activation wherein cells establish capillary-like structures

  16. Evidence for autocrine and paracrine regulation of allergen-induced mast cell mediator release in the guinea pig airways.

    Science.gov (United States)

    Yu, Li; Liu, Qi; Canning, Brendan J

    2018-03-05

    Mast cells play an essential role in immediate type hypersensitivity reactions and in chronic allergic diseases of the airways, including asthma. Mast cell mediator release can be modulated by locally released autacoids and circulating hormones, but surprisingly little is known about the autocrine effects of mediators released upon mast cell activation. We thus set out to characterize the autocrine and paracrine effects of mast cell mediators on mast cell activation in the guinea pig airways. By direct measures of histamine, cysteinyl-leukotriene and thromboxane release and with studies of allergen-evoked contractions of airway smooth muscle, we describe a complex interplay amongst these autacoids. Notably, we observed an autocrine effect of the cysteinyl-leukotrienes acting through cysLT 1 receptors on mast cell leukotriene release. We confirmed the results of previous studies demonstrating a marked enhancement of mast cell mediator release following cyclooxygenase inhibition, but we have extended these results by showing that COX-2 derived eicosanoids inhibit cysteinyl-leukotriene release and yet are without effect on histamine release. Given the prominent role of COX-1 inhibition in aspirin-sensitive asthma, these data implicate preformed mediators stored in granules as the initial drivers of these adverse reactions. Finally, we describe the paracrine signaling cascade leading to thromboxane synthesis in the guinea pig airways following allergen challenge, which occurs indirectly, secondary to cysLT 1 receptor activation on structural cells and/ or leukocytes within the airway wall, and a COX-2 dependent synthesis of the eicosanoid. The results highlight the importance of cell-cell and autocrine interactions in regulating allergic responses in the airways. Copyright © 2017. Published by Elsevier B.V.

  17. Activated platelet-derived growth factor autocrine pathway drives the transformed phenotype of a human glioblastoma cell line.

    Science.gov (United States)

    Vassbotn, F S; Ostman, A; Langeland, N; Holmsen, H; Westermark, B; Heldin, C H; Nistér, M

    1994-02-01

    Human glioblastoma cells (A172) were found to concomitantly express PDGF-BB and PDGF beta-receptors. The receptors were constitutively autophosphorylated in the absence of exogenous ligand, suggesting the presence of an autocrine PDGF pathway. Neutralizing PDGF antibodies as well as suramin inhibited the autonomous PDGF receptor tyrosine kinase activity and resulted in up-regulation of receptor protein. The interruption of the autocrine loop by the PDGF antibodies reversed the transformed phenotype of the glioblastoma cell, as determined by (1) diminished DNA synthesis, (2) inhibition of tumor colony growth, and (3) reversion of the transformed morphology of the tumor cells. The PDGF antibodies showed no effect on the DNA synthesis of another glioblastoma cells line (U-343MGa 31L) or on Ki-ras-transformed fibroblasts. The present study demonstrates an endogenously activated PDGF pathway in a spontaneous human glioblastoma cell line. Furthermore, we provide evidence that the autocrine PDGF pathway drives the transformed phenotype of the tumor cells, a process that can be blocked by extracellular antagonists.

  18. Autocrine regulation of ecdysone synthesis by β3-octopamine receptor in the prothoracic gland is essential for Drosophila metamorphosis.

    Science.gov (United States)

    Ohhara, Yuya; Shimada-Niwa, Yuko; Niwa, Ryusuke; Kayashima, Yasunari; Hayashi, Yoshiki; Akagi, Kazutaka; Ueda, Hitoshi; Yamakawa-Kobayashi, Kimiko; Kobayashi, Satoru

    2015-02-03

    In Drosophila, pulsed production of the steroid hormone ecdysone plays a pivotal role in developmental transitions such as metamorphosis. Ecdysone production is regulated in the prothoracic gland (PG) by prothoracicotropic hormone (PTTH) and insulin-like peptides (Ilps). Here, we show that monoaminergic autocrine regulation of ecdysone biosynthesis in the PG is essential for metamorphosis. PG-specific knockdown of a monoamine G protein-coupled receptor, β3-octopamine receptor (Octβ3R), resulted in arrested metamorphosis due to lack of ecdysone. Knockdown of tyramine biosynthesis genes expressed in the PG caused similar defects in ecdysone production and metamorphosis. Moreover, PTTH and Ilps signaling were impaired by Octβ3R knockdown in the PG, and activation of these signaling pathways rescued the defect in metamorphosis. Thus, monoaminergic autocrine signaling in the PG regulates ecdysone biogenesis in a coordinated fashion on activation by PTTH and Ilps. We propose that monoaminergic autocrine signaling acts downstream of a body size checkpoint that allows metamorphosis to occur when nutrients are sufficiently abundant.

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

    International Nuclear Information System (INIS)

    Cozzolino, F.; Rubartelli, A.; Aldinucci, D.; Sitia, R.; Torcia, M.; Shaw, A.; Di Guglielmo, R.

    1989-01-01

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

  20. Autocrine release of angiopoietin-2 mediates cerebrovascular disintegration in Moyamoya disease.

    Science.gov (United States)

    Blecharz, Kinga G; Frey, Dietmar; Schenkel, Tobias; Prinz, Vincent; Bedini, Gloria; Krug, Susanne M; Czabanka, Marcus; Wagner, Josephin; Fromm, Michael; Bersano, Anna; Vajkoczy, Peter

    2017-04-01

    Moyamoya disease is a rare steno-occlusive cerebrovascular disorder often resulting in hemorrhagic and ischemic strokes. Although sharing the same ischemic stimulus with atherosclerotic cerebrovascular disease, Moyamoya disease is characterized by a highly instable cerebrovascular system which is prone to rupture due to pathological neovascularization. To understand the molecular mechanisms underlying this instability, angiopoietin-2 gene expression was analyzed in middle cerebral artery lesions obtained from Moyamoya disease and atherosclerotic cerebrovascular disease patients. Angiopoietin-2 was significantly up-regulated in Moyamoya vessels, while serum concentrations of soluble angiopoietins were not changed. For further evaluations, cerebral endothelial cells incubated with serum from these patients in vitro were applied. In contrast to atherosclerotic cerebrovascular disease serum, Moyamoya disease serum induced an angiopoietin-2 overexpression and secretion, accompanied by loss of endothelial integrity. These effects were absent or inverse in endothelial cells of non-brain origin suggesting brain endothelium specificity. The destabilizing effects on brain endothelial cells to Moyamoya disease serum were partially suppressed by the inhibition of angiopoietin-2. Our findings define brain endothelial cells as the potential source of vessel-destabilizing factors inducing the high plasticity state and disintegration in Moyamoya disease in an autocrine manner. We also provide new insights into Moyamoya disease pathophysiology that may be helpful for preventive treatment strategies in future.

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

    International Nuclear Information System (INIS)

    Seabra, Sergio H.; Souza, Wanderley de; Matta, Renato A. da

    2004-01-01

    Toxoplasmosis is a worldwide disease caused by Toxoplasma gondii. Activated macrophages control T. gondii growth by nitric oxide (NO) production. However, T. gondii active invasion inhibits NO production, allowing parasite persistence. Here we show that the mechanism used by T. gondii to inhibit NO production persisting in activated macrophages depends on phosphatidylserine (PS) exposure. Masking PS with annexin-V on parasites or activated macrophages abolished NO production inhibition and parasite persistence. NO production inhibition depended on a transforming growth factor-β 1 (TGF-β 1 ) autocrine effect confirmed by the expression of Smad 2 and 3 in infected macrophages. TGF-β 1 led to inducible nitric oxide synthase (iNOS) degradation, actin filament (F-actin) depolymerization, and lack of nuclear factor-κB (NF-κB) in the nucleus. All these features were reverted by TGF-β 1 neutralizing antibody treatment. Thus, T. gondii mimics the evasion mechanism used by Leishmania amazonensis and also the anti-inflammatory response evoked by apoptotic cells

  2. HER2 overexpression elicits a proinflammatory IL-6 autocrine signaling loop that is critical for tumorigenesis.

    Science.gov (United States)

    Hartman, Zachary C; Yang, Xiao-Yi; Glass, Oliver; Lei, Gangjun; Osada, Takuya; Dave, Sandeep S; Morse, Michael A; Clay, Timothy M; Lyerly, Herbert K

    2011-07-01

    HER2 overexpression occurs in approximately 25% of breast cancers, where it correlates with poor prognosis. Likewise, systemic inflammation in breast cancer correlates with poor prognosis, although the process is not understood. In this study, we explored the relationship between HER2 and inflammation, comparing the effects of overexpressing wild-type or mutated inactive forms of HER2 in primary human breast cells. Wild-type HER2 elicited a profound transcriptional inflammatory profile, including marked elevation of interleukin-6 (IL-6) expression, which we established to be a critical determinant of HER2 oncogenesis. Mechanistic investigations revealed that IL-6 secretion induced by HER2 overexpression activated Stat3 and altered gene expression, enforcing an autocrine loop of IL-6/Stat3 expression. Both mouse and human in vivo models of HER2-amplified breast carcinoma relied critically on this HER2-IL-6-Stat3 signaling pathway. Our studies offer the first direct evidence linking HER2 to a systemic inflammatory mechanism that orchestrates HER2-mediated tumor growth. We suggest that the HER2-IL-6-STAT3 signaling axis we have defined in breast cancer could prompt new therapeutic or prevention strategies for treatment of HER2-amplified cancers. ©2011 AACR.

  3. Autocrine CSF-1 and CSF-1 Receptor Co-expression Promotes Renal Cell Carcinoma Growth

    Science.gov (United States)

    Menke, Julia; Kriegsmann, Jörg; Schimanski, Carl Christoph; Schwartz, Melvin M.; Schwarting, Andreas; Kelley, Vicki R.

    2011-01-01

    Renal cell carcinoma is increasing in incidence but the molecular mechanisms regulating its growth remain elusive. Co-expression of the monocytic growth factor CSF-1 and its receptor CSF-1R on renal tubular epithelial cells (TEC) will promote proliferation and anti-apoptosis during regeneration of renal tubules. Here we show that a CSF-1-dependent autocrine pathway is also responsible for the growth of renal cell carcinoma (RCC). CSF-1 and CSF-1R were co-expressed in RCC and TEC proximally adjacent to RCC. CSF-1 engagement of CSF-1R promoted RCC survival and proliferation and reduced apoptosis, in support of the likelihood that CSF-1R effector signals mediate RCC growth. In vivo CSF-1R blockade using a CSF-1R tyrosine kinase inhibitor decreased RCC proliferation and macrophage infiltration in a manner associated with a dramatic reduction in tumor mass. Further mechanistic investigations linked CSF-1 and EGF signaling in RCC. Taken together, our results suggest that budding RCC stimulates the proximal adjacent microenvironment in the kidney to release mediators of CSF-1, CSF-1R and EGF expression in RCC. Further, our findings imply that targeting CSF-1/CSF-1R signaling may be therapeutically effective in RCC. PMID:22052465

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

    International Nuclear Information System (INIS)

    Miyamoto, Kana; Ninomiya, Ken; Sonoda, Koh-Hei; Miyauchi, Yoshiteru; Hoshi, Hiroko; Iwasaki, Ryotaro; Miyamoto, Hiroya

    2009-01-01

    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.

  5. Autocrine stimulation of VEGFR-2 activates human leukemic cell growth and migration

    Science.gov (United States)

    Dias, Sergio; Hattori, Koichi; Zhu, Zhenping; Heissig, Beate; Choy, Margaret; Lane, William; Wu, Yan; Chadburn, Amy; Hyjek, Elizabeth; Gill, Muhammad; Hicklin, Daniel J.; Witte, Larry; Moore, M.A.S.; Rafii, Shahin

    2000-01-01

    Emerging data suggest that VEGF receptors are expressed by endothelial cells as well as hematopoietic stem cells. Therefore, we hypothesized that functional VEGF receptors may also be expressed in malignant counterparts of hematopoietic stem cells such as leukemias. We demonstrate that certain leukemias not only produce VEGF but also express functional VEGFR-2 in vivo and in vitro, resulting in the generation of an autocrine loop that may support leukemic cell survival and proliferation. Approximately 50% of freshly isolated leukemias expressed mRNA and protein for VEGFR-2. VEGF165 induced phosphorylation of VEGFR-2 and increased proliferation of leukemic cells, demonstrating these receptors were functional. VEGF165 also induced the expression of MMP-9 by leukemic cells and promoted their migration through reconstituted basement membrane. The neutralizing mAb IMC-1C11, specific to human VEGFR-2, inhibited leukemic cell survival in vitro and blocked VEGF165-mediated proliferation of leukemic cells and VEGF-induced leukemic cell migration. Xenotransplantation of primary leukemias and leukemic cell lines into immunocompromised nonobese diabetic mice resulted in significant elevation of human, but not murine, VEGF in plasma and death of inoculated mice within 3 weeks. Injection of IMC-1C11 inhibited proliferation of xenotransplanted human leukemias and significantly increased the survival of inoculated mice. Interruption of signaling by VEGFRs, particularly VEGFR-2, may provide a novel strategy for inhibiting leukemic cell proliferation. PMID:10953026

  6. The crystal structure of a multifunctional protein: phosphoglucose isomerase/autocrine motility factor/neuroleukin.

    Science.gov (United States)

    Sun, Y J; Chou, C C; Chen, W S; Wu, R T; Meng, M; Hsiao, C D

    1999-05-11

    Phosphoglucose isomerase (PGI) plays a central role in both the glycolysis and the gluconeogenesis pathways. We present here the complete crystal structure of PGI from Bacillus stearothermophilus at 2.3-A resolution. We show that PGI has cell-motility-stimulating activity on mouse colon cancer cells similar to that of endogenous autocrine motility factor (AMF). PGI can also enhance neurite outgrowth on neuronal progenitor cells similar to that observed for neuroleukin. The results confirm that PGI is neuroleukin and AMF. PGI has an open twisted alpha/beta structural motif consisting of two globular domains and two protruding parts. Based on this substrate-free structure, together with the previously published biological, biochemical, and modeling results, we postulate a possible substrate-binding site that is located within the domains' interface for PGI and AMF. In addition, the structure provides evidence suggesting that the top part of the large domain together with one of the protruding loops might participate in inducing the neurotrophic activity.

  7. Dictyostelium cells bind a secreted autocrine factor that represses cell proliferation

    Directory of Open Access Journals (Sweden)

    Phillips Jonathan E

    2009-02-01

    Full Text Available Abstract Background Dictyostelium cells secrete the proteins AprA and CfaD. Cells lacking either AprA or CfaD proliferate faster than wild type, while AprA or CfaD overexpressor cells proliferate slowly, indicating that AprA and CfaD are autocrine factors that repress proliferation. CfaD interacts with AprA and requires the presence of AprA to slow proliferation. To determine if CfaD is necessary for the ability of AprA to slow proliferation, whether AprA binds to cells, and if so whether the binding requires the presence of CfaD, we examined the binding and effect on proliferation of recombinant AprA. Results We find that the extracellular accumulation of AprA increases with cell density and reaches a concentration of 0.3 μg/ml near a stationary cell density. When added to wild-type or aprA- cells, recombinant AprA (rAprA significantly slows proliferation at 0.1 μg/ml and higher concentrations. From 4 to 64 μg/ml, the effect of rAprA is at a plateau, slowing but not stopping proliferation. The proliferation-inhibiting activity of rAprA is roughly the same as that of native AprA in conditioned growth medium. Proliferating aprA- cells show saturable binding of rAprA to 92,000 ± 11,000 cell-surface receptors with a KD of 0.03 ± 0.02 μg/ml. There appears to be one class of binding site, and no apparent cooperativity. Native AprA inhibits the binding of rAprA to aprA- cells with a Ki of 0.03 μg/ml, suggesting that the binding kinetics of rAprA are similar to those of native AprA. The proliferation of cells lacking CrlA, a cAMP receptor-like protein, or cells lacking CfaD are not affected by rAprA. Surprisingly, both cell types still bind rAprA. Conclusion Together, the data suggest that AprA functions as an autocrine proliferation-inhibiting factor by binding to cell surface receptors. Although AprA requires CfaD for activity, it does not require CfaD to bind to cells, suggesting the possibility that cells have an AprA receptor and a Cfa

  8. Dictyostelium cells bind a secreted autocrine factor that represses cell proliferation.

    Science.gov (United States)

    Choe, Jonathan M; Bakthavatsalam, Deenadayalan; Phillips, Jonathan E; Gomer, Richard H

    2009-02-02

    Dictyostelium cells secrete the proteins AprA and CfaD. Cells lacking either AprA or CfaD proliferate faster than wild type, while AprA or CfaD overexpressor cells proliferate slowly, indicating that AprA and CfaD are autocrine factors that repress proliferation. CfaD interacts with AprA and requires the presence of AprA to slow proliferation. To determine if CfaD is necessary for the ability of AprA to slow proliferation, whether AprA binds to cells, and if so whether the binding requires the presence of CfaD, we examined the binding and effect on proliferation of recombinant AprA. We find that the extracellular accumulation of AprA increases with cell density and reaches a concentration of 0.3 microg/ml near a stationary cell density. When added to wild-type or aprA- cells, recombinant AprA (rAprA) significantly slows proliferation at 0.1 microg/ml and higher concentrations. From 4 to 64 microg/ml, the effect of rAprA is at a plateau, slowing but not stopping proliferation. The proliferation-inhibiting activity of rAprA is roughly the same as that of native AprA in conditioned growth medium. Proliferating aprA- cells show saturable binding of rAprA to 92,000 +/- 11,000 cell-surface receptors with a KD of 0.03 +/- 0.02 microg/ml. There appears to be one class of binding site, and no apparent cooperativity. Native AprA inhibits the binding of rAprA to aprA- cells with a Ki of 0.03 mug/ml, suggesting that the binding kinetics of rAprA are similar to those of native AprA. The proliferation of cells lacking CrlA, a cAMP receptor-like protein, or cells lacking CfaD are not affected by rAprA. Surprisingly, both cell types still bind rAprA. Together, the data suggest that AprA functions as an autocrine proliferation-inhibiting factor by binding to cell surface receptors. Although AprA requires CfaD for activity, it does not require CfaD to bind to cells, suggesting the possibility that cells have an AprA receptor and a CfaD receptor, and activation of both receptors is

  9. Reversion of autocrine transformation by a dominant negative platelet-derived growth factor mutant.

    Science.gov (United States)

    Vassbotn, F S; Andersson, M; Westermark, B; Heldin, C H; Ostman, A

    1993-07-01

    A non-receptor-binding mutant of the platelet-derived growth factor (PDGF) A chain, PDGF-0, was generated by exchanging 7 amino acids in the sequence. The mutant chains formed dimers that were similar to wild-type PDGF-AA with regard to stability and rate of processing to the mature 30-kDa secreted forms. Moreover, the mutant chains formed disulfide-bonded heterodimers with the PDGF B chain in NIH 3T3 cells heterodimer underwent the same processing and secretion as PDGF-AB. Transfection of c-sis-expressing 3T3 cells with PDGF-0 significantly inhibited the transformed phenotype of these cells, as determined by the following criteria. (i) Compared with PDGF-0-negative clones, PDGF-0-producing clones showed a reverted morphology. (ii) Clones producing PDGF-0 grew more slowly than PDGF-0-negative clones, with a fivefold difference in cell number after 14 days in culture. (iii) The expression of PDGF-0 completely inhibited the ability of the c-sis-expressing 3T3 cells to form colonies in soft agar; this inhibition was overcome by the addition of recombinant PDGF-BB to the culture medium, showing that the lack of colony formation of these cells was not due to a general unresponsiveness to PDGF. The specific expression of a PDGF-0/PDGF wild-type heterodimer in COS cells revealed that the affinity of the mutant heterodimer for the PDGF alpha receptor was decreased by approximately 50-fold compared with that of PDGF-AA. Thus, we show that a non-receptor-binding PDGF A-chain mutant neutralizes in a trans-dominant manner the autocrine transforming potential of the c-sis/PDGF B chain by forming low-affinity heterodimers with wild-type PDGF chains. This method of specifically antagonizing the effect of PDGF may be useful in investigations of the role of PDGF in normal and pathological conditions.

  10. Autocrine CSF-1R signaling drives mesothelioma chemoresistance via AKT activation

    Science.gov (United States)

    Cioce, M; Canino, C; Goparaju, C; Yang, H; Carbone, M; Pass, H I

    2014-01-01

    Clinical management of malignant pleural mesothelioma (MPM) is very challenging because of the uncommon resistance of this tumor to chemotherapy. We report here increased expression of macrophage colony-stimulating-factor-1-receptor (M-CSF/CSF-1R) mRNA in mesothelioma versus normal tissue specimens and demonstrate that CSF-1R expression identifies chemoresistant cells of mesothelial nature in both primary cultures and mesothelioma cell lines. By using RNAi or ligand trapping, we demonstrate that the chemoresistance properties of those cells depend on autocrine CSF-1R signaling. At the single-cell level, the isolated CSF-1Rpos cells exhibit a complex repertoire of pluripotency, epithelial–mesenchymal transition and detoxifying factors, which define a clonogenic, chemoresistant, precursor-like cell sub-population. The simple activation of CSF-1R in untransformed mesothelial cells is sufficient to confer clonogenicity and resistance to pemetrexed, hallmarks of mesothelioma. In addition, this induced a gene expression profile highly mimicking that observed in the MPM cells endogenously expressing the receptor and the ligands, suggesting that CSF-1R expression is mainly responsible for the phenotype of the identified cell sub-populations. The survival of CSF1Rpos cells requires active AKT (v-akt murine thymoma viral oncogene homolog 1) signaling, which contributed to increased levels of nuclear, transcriptionally competent β-catenin. Inhibition of AKT reduced the transcriptional activity of β-catenin-dependent reporters and sensitized the cells to senescence-induced clonogenic death after pemetrexed treatment. This work expands what is known on the non-macrophage functions of CSF-1R and its role in solid tumors, and suggests that CSF-1R signaling may have a critical pathogenic role in a prototypical, inflammation-related cancer such as MPM and therefore may represent a promising target for therapeutic intervention. PMID:24722292

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

    Directory of Open Access Journals (Sweden)

    Bodi Zhang

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

  12. Autocrine effect of Zn²⁺ on the glucose-stimulated insulin secretion.

    Science.gov (United States)

    Slepchenko, Kira G; Daniels, Nigel A; Guo, Aili; Li, Yang V

    2015-09-01

    It is well known that zinc (Zn(2+)) is required for the process of insulin biosynthesis and the maturation of insulin secretory granules in pancreatic beta (β)-cells, and that changes in Zn(2+) levels in the pancreas have been found to be associated with diabetes. Glucose-stimulation causes a rapid co-secretion of Zn(2+) and insulin with similar kinetics. However, we do not know whether Zn(2+) regulates insulin availability and secretion. Here we investigated the effect of Zn(2+) on glucose-stimulated insulin secretion (GSIS) in isolated mouse pancreatic islets. Whereas Zn(2+) alone (control) had no effect on the basal secretion of insulin, it significantly inhibited GSIS. The application of CaEDTA, by removing the secreted Zn(2+) from the extracellular milieu of the islets, resulted in significantly increased GSIS, suggesting an overall inhibitory role of secreted Zn(2+) on GSIS. The inhibitory action of Zn(2+) was mostly mediated through the activities of KATP/Ca(2+) channels. Furthermore, during brief paired-pulse glucose-stimulated Zn(2+) secretion (GSZS), Zn(2+) secretion following the second pulse was significantly attenuated, probably by the secreted endogenous Zn(2+) after the first pulse. Such an inhibition on Zn(2+) secretion following the second pulse was completely reversed by Zn(2+) chelation, suggesting a negative feedback mechanism, in which the initial glucose-stimulated Zn(2+) release inhibits subsequent Zn(2+) secretion, subsequently inhibiting insulin co-secretion as well. Taken together, these data suggest a negative feedback mechanism on GSZS and GSIS by Zn(2+) secreted from β-cells, and the co-secreted Zn(2+) may act as an autocrine inhibitory modulator.

  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. The ROCO Kinase QkgA Is Necessary for Proliferation Inhibition by Autocrine Signals in Dictyostelium discoideum▿

    OpenAIRE

    Phillips, Jonathan E.; Gomer, Richard H.

    2010-01-01

    AprA and CfaD are secreted proteins that function as autocrine signals to inhibit cell proliferation in Dictyostelium discoideum. Cells lacking AprA or CfaD proliferate rapidly, and adding AprA or CfaD to cells slows proliferation. Cells lacking the ROCO kinase QkgA proliferate rapidly, with a doubling time 83% of that of the wild type, and overexpression of a QkgA-green fluorescent protein (GFP) fusion protein slows cell proliferation. We found that qkgA− cells accumulate normal levels of ex...

  15. An Autocrine Proliferation Repressor Regulates Dictyostelium discoideum Proliferation and Chemorepulsion Using the G Protein-Coupled Receptor GrlH

    OpenAIRE

    Yu Tang; Yuantai Wu; Sarah E. Herlihy; Francisco J. Brito-Aleman; Jose H. Ting; Chris Janetopoulos; Richard H. Gomer; Scott D. Emr

    2018-01-01

    In eukaryotic microbes, little is known about signals that inhibit the proliferation of the cells that secrete the signal, and little is known about signals (chemorepellents) that cause cells to move away from the source of the signal. Autocrine proliferation repressor protein A (AprA) is a protein secreted by the eukaryotic microbe Dictyostelium discoideum. AprA is a chemorepellent for and inhibits the proliferation of D. discoideum. We previously found that cells sense AprA using G proteins...

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

    Czech Academy of Sciences Publication Activity Database

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

    2011-01-01

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

  17. An autocrine ATP release mechanism regulates basal ciliary activity in airway epithelium.

    Science.gov (United States)

    Droguett, Karla; Rios, Mariana; Carreño, Daniela V; Navarrete, Camilo; Fuentes, Christian; Villalón, Manuel; Barrera, Nelson P

    2017-07-15

    antagonist used to block P2X7 receptors, which reduced basal CBF by 85%. Additionally, increasing extracellular ATP levels (0.1-100 μm) increased CBF, maintaining a sustained response that was suppressed in the presence of carbenoxolone. We also show that high levels of ATP (1 mm), associated with inflammatory conditions, lowered basal CBF by reducing [Ca 2+ ] i and hemichannel functionality. In summary, we provide evidence indicating that airway epithelium ATP release is the molecular autocrine mechanism regulating basal ciliary activity and is also the mediator of the ciliary response to chemical stimulation. © 2017 The Authors. The Journal of Physiology © 2017 The Physiological Society.

  18. 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.

  19. Autocrine Signaling by Wnt-5a Deregulates Chemotaxis of Leukemic Cells and Predicts Clinical Outcome in Chronic Lymphocytic Leukemia

    Czech Academy of Sciences Publication Activity Database

    Janovská, P.; Poppová, L.; Plevová, K.; Plesingerova, E.; Behal, M.; Kaucká, M.; Ovesná, P.; Hlozkova, M.; Borský, M.; Stehlíková, O.; Brychtová, Y.; Doubek, M.; Machalova, M.; Baskar, S.; Kozubík, Alois; Pospíšilová, Š.; Pavlová, Š.; Bryja, Vítězslav

    2016-01-01

    Roč. 22, č. 2 (2016), s. 459-469 ISSN 1078-0432 Institutional support: RVO:68081707 Keywords : receptor tyrosine kinase * cd38 expression * mutation status * cll cells Subject RIV: BO - Biophysics Impact factor: 9.619, year: 2016

  20. Negative feedback regulation of human platelets via autocrine activation of the platelet-derived growth factor alpha-receptor.

    Science.gov (United States)

    Vassbotn, F S; Havnen, O K; Heldin, C H; Holmsen, H

    1994-05-13

    Human platelets contain platelet-derived growth factor (PDGF) in their alpha-granules which is released during platelet exocytosis. We show by immunoprecipitation and 125I-PDGF binding experiments that human platelets have functionally active PDGF alpha-receptors, but not beta-receptors. The PDGF alpha-receptor (PDGFR-alpha) was identified as a 170-kDa glycosylated protein-tyrosine kinase as found in other cell types. Stimulation of platelets with 0.1 unit/ml thrombin resulted in a significant increase (2-5-fold) of the tyrosine phosphorylation of the PDGFR-alpha, as determined by immunoprecipitation with phosphotyrosine antiserum as well as with PDGFR-alpha antiserum. The observed thrombin-induced autophosphorylation of the PDGFR-alpha was inhibited by the addition of a neutralizing monoclonal PDGF antibody. Thus, our results suggest that the platelet PDGFR-alpha is stimulated in an autocrine manner by PDGF secreted during platelet activation. Preincubation of platelets with PDGF inhibited thrombin-induced platelet aggregation and secretion of ATP + ADP and beta-hexosaminidase. Thrombin-induced platelet aggregation was also reversed when PDGF was added 30 s after thrombin stimulation. Inhibition of the autocrine PDGF pathway during platelet activation by the PDGF antibody led to a potentiation of thrombin-induced beta-hexosaminidase secretion. Thus, the PDGFR-alpha takes part in a negative feedback regulation during platelet activation. Our demonstration of PDGF alpha-receptors on human platelets and its inhibitory function during platelet activation identifies a new possible role of PDGF in the regulation of thrombosis.

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

    Science.gov (United States)

    Daft, Paul G; Yang, Yang; Napierala, Dobrawa; Zayzafoon, Majd

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Paul G Daft

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

  3. Autocrine motility factor (neuroleukin, phosphohexose isomerase) induces cell movement through 12-lipoxygenase-dependent tyrosine phosphorylation and serine dephosphorylation events.

    Science.gov (United States)

    Timár, J; Tóth, S; Tóvári, J; Paku, S; Raz, A

    1999-01-01

    Autocrine motility factor (AMF) is one of the motility cytokines regulating tumor cell migration, therefore identification of the signaling pathway coupled with it has critical importance. Previous studies revealed several elements of this pathway predominated by lipoxygenase-PKC activations but the role for tyrosine kinases remained questionable. Motility cytokines frequently have mitogenic effect as well, producing activation of overlapping signaling pathways therefore we have used B16a melanoma cells as models where AMF has exclusive motility effect. Our studies revealed that in B16a cells AMF initiated rapid (1-5 min) activation of the protein tyrosine kinase (PTK) cascade inducing phosphorylation of 179, 125, 95 and 40/37 kD proteins which was mediated by upstream cyclo- and lipoxygenases. The phosphorylated proteins were localized to the cortical actin-stress fiber attachment zones in situ by confocal microscopy. On the other hand, AMF receptor activation induced significant decrease in overall serine-phosphorylation level of cellular proteins accompanied by serine phosphorylation of 200, 90, 78 and 65 kd proteins. The decrease in serine phosphorylation was independent of PTKs, PKC as well as cyclo- and lipoxygenases. However, AMF induced robust translocation of PKCalpha to the stress fibers and cortical actin suggesting a critical role for this kinase in the generation of the motility signal. Based on the significant decrease in serine phosphorylation after AMF stimulus in B16a cells we postulated the involvement of putative serine/threonine phosphatase(s) upstream lipoxygenase and activation of the protein tyrosine kinase cascade downstream cyclo- and lipoxygenase(s) in the previously identified autocrine motility signal.

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

    Science.gov (United States)

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

    2013-01-01

    Gamma-aminobutyric acid (GABA) is produced and secreted by adult pancreatic β-cells, which also express GABA receptors mediating autocrine signaling and regulating β-cell proliferation. However, whether the autocrine GABA signaling involves in β-cell progenitor development or maturation remains uncertain. By means of immunohistochemistry we analyzed the expression profiles of the GABA synthesizing enzyme glutamic acid decarboxylase (GAD) and the α1-subunit of type-A GABA receptor (GABAARα1) in the pancreas of mice at embryonic day 15.5 (E15.5), E18.5, postnatal day 1 (P1) and P7. Our data showed that at E15.5 the pancreatic and duodenum homeobox-1 (Pdx1) was expressed in the majority of cells in the developing pancreata. Notably, insulin immunoreactivity was identified in a subpopulation of pancreatic cells with a high level of Pdx1 expression. About 80% of the high-level Pdx-1 expressing cells in the pancreas expressed GAD and GABAARα1 at all pancreatic developmental stages. In contrast, only about 30% of the high-level Pdx-1 expressing cells in the E15.5 pancreas expressed insulin; i.e., a large number of GAD/GABAARα1-expressing cells did not express insulin at this early developmental stage. The expression level of GAD and GABAARα1 increased steadily, and progressively more GAD/GABAARα1-expressing cells expressed insulin in the course of pancreatic development. These results suggest that 1) GABA signaling proteins appear in β-cell progenitors prior to insulin expression; and 2) the increased expression of GABA signaling proteins may be involved in β-cell progenitor maturation.

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

    International Nuclear Information System (INIS)

    Voss, Melanie J; Möller, Mischa F; Powe, Desmond G; Niggemann, Bernd; Zänker, Kurt S; Entschladen, Frank

    2011-01-01

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

  6. Chemokine CXCL3 mediates prostate cancer cells proliferation, migration and gene expression changes in an autocrine/paracrine fashion.

    Science.gov (United States)

    Xin, Hua; Cao, Yu; Shao, Ming-Liang; Zhang, Wei; Zhang, Chun-Bin; Wang, Jing-Tao; Liang, Li-Chun; Shao, Wen-Wu; Qi, Ya-Ling; Li, Yue; Zhang, Ze-Yu; Yang, Zhe; Sun, Yu-Hong; Zhang, Peng-Xia; Jia, Lin-Lin; Wang, Wei-Qun

    2018-05-01

    We have previously indicated that CXCL3 was upregulated in the tissues of prostate cancer, and exogenous administration of CXCL3 played a predominant role in the tumorigenicity of prostate cancer cells. In the present study, we further explored the role and the underlying mechanism of CXCL3 overexpression in the oncogenic potential of prostate cancer in an autocrine/paracrine fashion. CXCL3-overexpressing prostate cancer cell line PC-3 and immortalized prostate stromal cell line WPMY-1 were established by gene transfection. CCK-8, transwell assays and growth of tumor xenografts were conducted to characterize the effects of CXCL3 on PC-3 cells' proliferation and migration. Western blotting was conducted to test whether CXCL3 could affect the expression of tumorigenesis-associated genes. The results showed that CXCL3 overexpression in PC-3 cells and the PC-3 cells treated with the supernatants of CXCL3-transfected WPMY-1 cells stimulated the proliferation and migration of PC-3 cells in vitro and in a nude mouse xenograft model. Western blotting revealed higher levels of p-ERK, Akt and Bcl-2 and lower levels of Bax in the tumor xenografts transplanted with CXCL3-transfected PC-3 cells. Moreover, the tumor xenografts derived from the PC-3 cells treated with supernatants of CXCL3-transfected WPMY-1 cells showed higher expression of ERK, Akt and Bcl-2 and lower expression of Bax. These findings suggest that CXCL3 autocrine/paracrine pathways are involved in the development of prostate cancer by regulating the expression of the target genes that are related to the progression of malignancies.

  7. 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

  8. PGE2 maintains self-renewal of human adult stem cells via EP2-mediated autocrine signaling and its production is regulated by cell-to-cell contact.

    Science.gov (United States)

    Lee, Byung-Chul; Kim, Hyung-Sik; Shin, Tae-Hoon; Kang, Insung; Lee, Jin Young; Kim, Jae-Jun; Kang, Hyun Kyoung; Seo, Yoojin; Lee, Seunghee; Yu, Kyung-Rok; Choi, Soon Won; Kang, Kyung-Sun

    2016-05-27

    Mesenchymal stem cells (MSCs) possess unique immunomodulatory abilities. Many studies have elucidated the clinical efficacy and underlying mechanisms of MSCs in immune disorders. Although immunoregulatory factors, such as Prostaglandin E2 (PGE2), and their mechanisms of action on immune cells have been revealed, their effects on MSCs and regulation of their production by the culture environment are less clear. Therefore, we investigated the autocrine effect of PGE2 on human adult stem cells from cord blood or adipose tissue, and the regulation of its production by cell-to-cell contact, followed by the determination of its immunomodulatory properties. MSCs were treated with specific inhibitors to suppress PGE2 secretion, and proliferation was assessed. PGE2 exerted an autocrine regulatory function in MSCs by triggering E-Prostanoid (EP) 2 receptor. Inhibiting PGE2 production led to growth arrest, whereas addition of MSC-derived PGE2 restored proliferation. The level of PGE2 production from an equivalent number of MSCs was down-regulated via gap junctional intercellular communication. This cell contact-mediated decrease in PGE2 secretion down-regulated the suppressive effect of MSCs on immune cells. In conclusion, PGE2 produced by MSCs contributes to maintenance of self-renewal capacity through EP2 in an autocrine manner, and PGE2 secretion is down-regulated by cell-to-cell contact, attenuating its immunomodulatory potency.

  9. HER2 overexpression elicits a pro-inflammatory IL-6 autocrine signaling loop that is critical for tumorigenesis

    Science.gov (United States)

    Hartman, Zachary C.; Yang, Xiao-Yi; Glass, Oliver; Lei, Gangjun; Osada, Takuya; Dave, Sandeep S.; Morse, Michael A.; Clay, Timothy M.; Lyerly, Herbert Kim

    2011-01-01

    HER2 overexpression occurs in ~25% of breast cancers where it correlates with poor prognosis. Likewise, systemic inflammation in breast cancer correlates with poor prognosis although the process is not understood. In this study, we explored the relationship between HER2 and inflammation, comparing the effects of overexpressing wild-type or mutated inactive forms of HER2 in primary human breast cells. Wild-type HER2 elicited a profound transcriptional inflammatory profile, including marked elevation of IL-6 expression, which we established to be a critical determinant of HER2 oncogenesis. Mechanistic investigations revealed that IL-6 secretion induced by HER2 overexpression activated Stat3 and altered gene expression, enforcing an autocrine loop of IL-6/Stat3 expression. Both mouse and human in vivo models of HER2 amplified breast carcinoma relied critically on this HER2-IL-6-Stat3 signaling pathway. Our studies offer the first direct evidence linking HER2 to a systemic inflammatory mechanism that orchestrates HER2-mediated tumor growth. We suggest that the HER2-IL6-STAT3 signaling axis we have defined in breast cancer could prompt new therapeutic or prevention strategies for treatment of HER2-amplified cancers. PMID:21518778

  10. Thrombin induces epithelial-mesenchymal transition and collagen production by retinal pigment epithelial cells via autocrine PDGF-receptor signaling.

    Science.gov (United States)

    Bastiaans, Jeroen; van Meurs, Jan C; van Holten-Neelen, Conny; Nagtzaam, Nicole M A; van Hagen, P Martin; Chambers, Rachel C; Hooijkaas, Herbert; Dik, Willem A

    2013-12-19

    De-differentiation of RPE cells into mesenchymal cells (epithelial-mesenchymal transition; EMT) and associated collagen production contributes to development of proliferative vitreoretinopathy (PVR). In patients with PVR, intraocular coagulation cascade activation occurs and may play an important initiating role. Therefore, we examined the effect of the coagulation proteins factor Xa and thrombin on EMT and collagen production by RPE cells. Retinal pigment epithelial cells were stimulated with factor Xa or thrombin and the effect on zonula occludens (ZO)-1, α-smooth muscle actin (α-SMA), collagen, and platelet-derived growth factor (PDGF)-B were determined by real-time quantitative-polymerase chain reaction (RQ-PCR), immunofluorescence microscopy, and HPLC and ELISA for collagen and PDGF-BB in culture supernatants, respectively. PDGF-receptor activation was determined by phosphorylation analysis and inhibition studies using the PDGF-receptor tyrosine kinase inhibitor AG1296. Thrombin reduced ZO-1 gene expression (P production of α-SMA and collagen increased. In contrast to thrombin, factor Xa hardly stimulated EMT by RPE. Thrombin clearly induced PDGF-BB production and PDGF-Rβ chain phosphorylation in RPE. Moreover, AG1296 significantly blocked the effect of thrombin on EMT and collagen production. Our findings demonstrate that thrombin is a potent inducer of EMT by RPE via autocrine activation of PDGF-receptor signaling. Coagulation cascade-induced EMT of RPE may thus contribute to the formation of fibrotic retinal membranes in PVR and should be considered as treatment target in PVR.

  11. An Autocrine Proliferation Repressor Regulates Dictyostelium discoideum Proliferation and Chemorepulsion Using the G Protein-Coupled Receptor GrlH

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    Yu Tang

    2018-02-01

    Full Text Available In eukaryotic microbes, little is known about signals that inhibit the proliferation of the cells that secrete the signal, and little is known about signals (chemorepellents that cause cells to move away from the source of the signal. Autocrine proliferation repressor protein A (AprA is a protein secreted by the eukaryotic microbe Dictyostelium discoideum. AprA is a chemorepellent for and inhibits the proliferation of D. discoideum. We previously found that cells sense AprA using G proteins, suggesting the existence of a G protein-coupled AprA receptor. To identify the AprA receptor, we screened mutants lacking putative G protein-coupled receptors. We found that, compared to the wild-type strain, cells lacking putative receptor GrlH (grlH{macron} cells show rapid proliferation, do not have large numbers of cells moving away from the edges of colonies, are insensitive to AprA-induced proliferation inhibition and chemorepulsion, and have decreased AprA binding. Expression of GrlH in grlH{macron} cells (grlH{macron}/grlHOE rescues the phenotypes described above. These data indicate that AprA signaling may be mediated by GrlH in D. discoideum.

  12. Autocrine prostaglandin E2 signaling promotes promonocytic leukemia cell survival via COX-2 expression and MAPK pathway

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    Lee, Jaetae; Lee, Young Sup

    2015-01-01

    The COX-2/PGE2 pathway has been implicated in the occurrence and progression of cancer. The underlying mechanisms facilitating the production of COX-2 and its mediator, PGE2, in cancer survival remain unknown. Herein, we investigated PGE2-induced COX-2 expression and signaling in HL-60 cells following menadione treatment. Treatment with PGE2 activated anti-apoptotic proteins such as Bcl-2 and Bcl-xL while reducing pro-apoptotic proteins, thereby enhancing cell survival. PGE2 not only induced COX-2 expression, but also prevented casapse-3, PARP, and lamin B cleavage. Silencing and inhibition of COX-2 with siRNA transfection or treatment with indomethacin led to a pronounced reduction of the extracellular levels of PGE2, and restored the menadione-induced cell death. In addition, pretreatment of cells with the MEK inhibitor PD98059 and the PKA inhibitor H89 abrogated the PGE2-induced expression of COX-2, suggesting involvement of the MAPK and PKA pathways. These results demonstrate that PGE2 signaling acts in an autocrine manner, and specific inhibition of PGE2 will provide a novel approach for the treatment of leukemia. [BMB Reports 2015; 48(2): 109-114] PMID:24965577

  13. Effects and Molecular Mechanism of GST-Irisin on Lipolysis and Autocrine Function in 3T3-L1 Adipocytes.

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    Shanshan Gao

    Full Text Available Irisin, which was recently identified as a myokine and an adipokine, transforms white adipose tissue to brown adipose tissue and has increasingly caught the attention of the medical and scientific community. However, the signaling pathway of irisin and the molecular mechanisms responsible for the lipolysis effect remain unclear. In this study, we established an efficient system for the expression and purification of GST-irisin in Escherichia coli. The biological activity of GST-irisin was verified using the cell counting kit-8 assay and by detecting the mRNA expression of uncoupling protein 1. Our data showed that GST-irisin regulates mRNA levels of lipolysis-related genes such as adipose triglyceride lipase and hormone-sensitive lipase and proteins such as the fatty acid-binding protein 4, leading to increased secretion of glycerol and decreased lipid accumulation in 3T3-L1 adipocytes. In addition, exogenous GST-irisin can increase its autocrine function in vitro by regulating the expression of fibronectin type III domain-containing protein 5. GST-irisin could regulate glucose uptake in 3T3-L1 adipocytes. Hence, we believe that recombinant GST-irisin could promote lipolysis and its secretion in vitro and can potentially prevent obesity and related metabolic diseases.

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

    Science.gov (United States)

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

    2016-06-28

    Cancer stem cells (CSCs) are well known for their self-regeneration and tumorigenesis potential. In addition, the multi-differentiation potential of CSCs has become a popular issue and continues to attract increased research attention. Recent studies demonstrated that CSCs are able to differentiate into functional endothelial cells and participate in tumor angiogenesis. In this study, we found that ovarian cancer stem-like cells (CSLCs) activate the NF-κB and STAT3 signal pathways through autocrine CCL5 signaling and mediate their own differentiation into endothelial cells (ECs). Our data demonstrate that CSLCs differentiate into ECs morphologically and functionally. Anti-CCL5 antibodies and CCL5-shRNA lead to markedly inhibit EC differentiation and the tube formation of CSLCs, both in vitro and in vivo. Recombinant human-CCL5 significantly promotes ovarian CSLCs that differentiate into ECs and form microtube network. The CCL5-mediated EC differentiation of CSLCs depends on binding to receptors, such as CCR1, CCR3, and CCR5. The results demonstrated that CCL5-CCR1/CCR3/CCR5 activates the NF-κB and STAT3 signal pathways, subsequently mediating the differentiation of CSLCs into ECs. Therefore, this study was conducted based on the theory that CSCs improve tumor angiogenesis and provides a novel strategy for anti-angiogenesis in ovarian cancer. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  15. Loss of MeCP2 disrupts cell autonomous and autocrine BDNF signaling in mouse glutamatergic neurons

    Science.gov (United States)

    Sampathkumar, Charanya; Wu, Yuan-Ju; Vadhvani, Mayur; Trimbuch, Thorsten; Eickholt, Britta; Rosenmund, Christian

    2016-01-01

    Mutations in the MECP2 gene cause the neurodevelopmental disorder Rett syndrome (RTT). Previous studies have shown that altered MeCP2 levels result in aberrant neurite outgrowth and glutamatergic synapse formation. However, causal molecular mechanisms are not well understood since MeCP2 is known to regulate transcription of a wide range of target genes. Here, we describe a key role for a constitutive BDNF feed forward signaling pathway in regulating synaptic response, general growth and differentiation of glutamatergic neurons. Chronic block of TrkB receptors mimics the MeCP2 deficiency in wildtype glutamatergic neurons, while re-expression of BDNF quantitatively rescues MeCP2 deficiency. We show that BDNF acts cell autonomous and autocrine, as wildtype neurons are not capable of rescuing growth deficits in neighboring MeCP2 deficient neurons in vitro and in vivo. These findings are relevant for understanding RTT pathophysiology, wherein wildtype and mutant neurons are intermixed throughout the nervous system. DOI: http://dx.doi.org/10.7554/eLife.19374.001 PMID:27782879

  16. An Autocrine Proliferation Repressor Regulates Dictyostelium discoideum Proliferation and Chemorepulsion Using the G Protein-Coupled Receptor GrlH.

    Science.gov (United States)

    Tang, Yu; Wu, Yuantai; Herlihy, Sarah E; Brito-Aleman, Francisco J; Ting, Jose H; Janetopoulos, Chris; Gomer, Richard H

    2018-02-13

    In eukaryotic microbes, little is known about signals that inhibit the proliferation of the cells that secrete the signal, and little is known about signals (chemorepellents) that cause cells to move away from the source of the signal. Autocrine proliferation repressor protein A (AprA) is a protein secreted by the eukaryotic microbe Dictyostelium discoideum AprA is a chemorepellent for and inhibits the proliferation of D. discoideum We previously found that cells sense AprA using G proteins, suggesting the existence of a G protein-coupled AprA receptor. To identify the AprA receptor, we screened mutants lacking putative G protein-coupled receptors. We found that, compared to the wild-type strain, cells lacking putative receptor GrlH ( grlH¯ cells) show rapid proliferation, do not have large numbers of cells moving away from the edges of colonies, are insensitive to AprA-induced proliferation inhibition and chemorepulsion, and have decreased AprA binding. Expression of GrlH in grlH¯ cells ( grlH¯/grlH OE ) rescues the phenotypes described above. These data indicate that AprA signaling may be mediated by GrlH in D. discoideum IMPORTANCE Little is known about how eukaryotic cells can count themselves and thus regulate the size of a tissue or density of cells. In addition, little is known about how eukaryotic cells can sense a repellant signal and move away from the source of the repellant, for instance, to organize the movement of cells in a developing embryo or to move immune cells out of a tissue. In this study, we found that a eukaryotic microbe uses G protein-coupled receptors to mediate both cell density sensing and chemorepulsion. Copyright © 2018 Tang et al.

  17. The ROCO kinase QkgA is necessary for proliferation inhibition by autocrine signals in Dictyostelium discoideum.

    Science.gov (United States)

    Phillips, Jonathan E; Gomer, Richard H

    2010-10-01

    AprA and CfaD are secreted proteins that function as autocrine signals to inhibit cell proliferation in Dictyostelium discoideum. Cells lacking AprA or CfaD proliferate rapidly, and adding AprA or CfaD to cells slows proliferation. Cells lacking the ROCO kinase QkgA proliferate rapidly, with a doubling time 83% of that of the wild type, and overexpression of a QkgA-green fluorescent protein (GFP) fusion protein slows cell proliferation. We found that qkgA(-) cells accumulate normal levels of extracellular AprA and CfaD. Exogenous AprA or CfaD does not slow the proliferation of cells lacking qkgA, and expression of QkgA-GFP in qkgA(-) cells rescues this insensitivity. Like cells lacking AprA or CfaD, cells lacking QkgA tend to be multinucleate, accumulate nuclei rapidly, and show a mass and protein accumulation per nucleus like those of the wild type, suggesting that QkgA negatively regulates proliferation but not growth. Despite their rapid proliferation, cells lacking AprA, CfaD, or QkgA expand as a colony on bacteria less rapidly than the wild type. Unlike AprA and CfaD, QkgA does not affect spore viability following multicellular development. Together, these results indicate that QkgA is necessary for proliferation inhibition by AprA and CfaD, that QkgA mediates some but not all of the effects of AprA and CfaD, and that QkgA may function downstream of these proteins in a signal transduction pathway regulating proliferation.

  18. Prognostic factors of craniopharyngioma with special reference to autocrine/paracrine signaling: underestimated implication of growth hormone receptor.

    Science.gov (United States)

    Ogawa, Yoshikazu; Watanabe, Mika; Tominaga, Teiji

    2015-10-01

    Craniopharyngioma is a slow-growing tumor classified as benign, but tight adhesion and significant local infiltration to the vital structures are common. In spite of improvement of modern microsurgery techniques and precise anatomical understanding not few cases of this tumor recur, and long-term tumor control and maintenance of quality of life are sometimes difficult. However, very little is known about the effects of the molecular characters of craniopharyngioma on the prognosis. Ninety eight cases of craniopharyngioma surgically treated at the Department of Neurosurgery, Tohoku University Hospital and Kohnan Hospital from April 1996 to May 2014, 45 males and 53 females aged from 2 to 80 years (mean, 40.84 years) were retrospectively reviewed, and postoperative outcomes and the possible involvement of the autocrine/paracrine mechanism were investigated. The patients were followed up at intervals of 6 months to assess tumor recurrence, and clinical outcomes were correlated with the findings of immunohistochemical examinations used growth hormone receptor (GHR) and downstream hormones. The follow-up period ranged from 3 to 209 months. Hormone expression was examined in 88 patients, of which 46 specimens (52.3 %) showed high expression of GHR. The GHR high expression group had a significantly shorter duration of postoperative stable disease compared with the low expression group (logrank test, p = 0.007). Simultaneous high expression of growth hormone (GH) and GHR was found in 33 specimens (37.5 %), and the high expression group had a significantly shorter duration of postoperative stable disease compared with the low expression group (logrank test, p = 0.011). No other hormones showed statistically significant differences in outcomes. High expression of GHR is associated with shorter duration of postoperative stable disease in patients with craniopharyngioma. If the surgical specimens were craniopharyngiomas with high GHR expression, GH supplementation

  19. 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.

  20. Proinflammatory Effect of High Glucose Concentrations on HMrSV5 Cells via the Autocrine Effect of HMGB1

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    Yuening Chu

    2017-09-01

    Full Text Available Background: Peritoneal fibrosis, in which inflammation and apoptosis play crucial pathogenic roles, is a severe complication associated with the treatment of kidney failure with peritoneal dialysis (PD using a glucose-based dialysate. Mesothelial cells (MCs take part in the inflammatory processes by producing various cytokines and chemokines, such as monocyte chemoattractant protein 1 (MCP-1 and interleukin 8 (IL-8. The apoptosis of MCs induced by high glucose levels also contributes to complications of PD. High mobility group protein B1 (HMGB1 is an inflammatory factor that has repeatedly been proven to be related to the occurrence of peritoneal dysfunction.Aim: In this study, we aimed to explore the effect and underlying mechanism of endogenous HMGB1 in high-glucose-induced MC injury.Methods: The human peritoneal MC line, HMrSV5 was cultured in high-glucose medium and incubated with recombinant HMGB1. Cellular expression of HMGB1 was blocked using HMGB1 small interfering RNA (siRNA. Apoptosis and production of inflammatory factors as well as the potential intermediary signaling pathways were examined.Results: The major findings of these analyses were: (1 MCs secreted HMGB1 from the nucleus during exposure to high glucose levels; HMGB1 acted in an autocrine fashion on the MCs to promote the production of MCP-1 and IL-8; (2 HMGB1 had little effect on high-glucose-induced apoptosis of the MCs; and (3 HMGB1-mediated MCP-1 and IL-8 production depended on the activation of MAPK signaling pathways. In conclusion, endogenous HMGB1 plays an important role in the inflammatory reaction induced by high glucose on MCs via mitogen-activated protein kinase (MAPK signaling pathways, but it seems to have little effect on high-glucose-induced apoptosis.

  1. Formation of PI 3-kinase products in platelets by thrombin, but not collagen, is dependent on synergistic autocrine stimulation, particularly through secreted ADP.

    Science.gov (United States)

    Selheim, F; Idsøe, R; Fukami, M H; Holmsen, H; Vassbotn, F S

    1999-10-05

    Platelet activation by thrombin or collagen results in secretion and synthesis of several platelet agonists that enhance the responses to the primary agonists (autocrine stimulation). To disclose the effects of thrombin and collagen on the phosphorylation of 3-phosphoinositides per se we incubated platelets with five inhibitors of platelet autocrine stimulation (IAS) that act extracellularly. We found that IAS almost totally blocked thrombin-induced production of phosphatidylinositol 3,4-bisphosphate [PtdIns(3,4)P(2)] and phosphatidylinositol 3,4,5-trisphosphate [PtdIns(3,4,5)P(3)]. In contrast, collagen induced massive production of PtdIns(3,4)P(2) and PtdIns(3,4,5)P(3) in the presence of IAS. When testing the effect of each inhibitor individually we found the strongest inhibition of thrombin-induced PtdIns(3,4)P(2) production with the ADP scavenger system CP/CPK. Furthermore, we found a strong synergistic effect between exogenously added ADP and thrombin on production of PtdIns(3,4)P(2). In contrast to the results from 3-phosphorylated phosphoinositides, CP/CPK had little effect on thrombin-induced protein tyrosine phosphorylation. Our results show the importance of autocrine stimulation in thrombin-induced accumulation of 3-phosphorylated phosphoinositides and raise the question as to whether thrombin by itself is capable of inducing PI 3-K activation. In marked contrast to thrombin, collagen per se appears to be able to trigger increased production of PtdIns(3,4)P(2) and PtdIns(3,4,5)P(3). Copyright 1999 Academic Press.

  2. Celecoxib alleviates tamoxifen-instigated angiogenic effects by ROS-dependent VEGF/VEGFR2 autocrine signaling

    International Nuclear Information System (INIS)

    Kumar, B N Prashanth; Rajput, Shashi; Dey, Kaushik Kumar; Parekh, Aditya; Das, Subhasis; Mazumdar, Abhijit; Mandal, Mahitosh

    2013-01-01

    Tamoxifen (TAM) is widely used in the chemotherapy of breast cancer and as a preventive agent against recurrence after surgery. However, extended TAM administration for breast cancer induces increased VEGF levels in patients, promoting new blood vessel formation and thereby limiting its efficacy. Celecoxib (CXB), a selective COX-2 inhibitor, suppresses VEGF gene expression by targeting the VEGF promoter responsible for its inhibitory effect. For this study, we had selected CXB as non-steroidal anti-inflammatory drug in combination with TAM for suppressing VEGF expression and simultaneously reducing doses of both the drugs. The effects of CXB combined with TAM were examined in two human breast cancer cell lines in culture, MCF7 and MDA-MB-231. Assays of proliferation, apoptosis, angiogenesis, metastasis, cell cycle distribution, and receptor signaling were performed. Here, we elucidated how the combination of TAM and CXB at nontoxic doses exerts anti-angiogenic effects by specifically targeting VEGF/VEGFR2 autocrine signaling through ROS generation. At the molecular level, TAM-CXB suppresses VHL-mediated HIF-1α activation, responsible for expression of COX-2, MMP-2 and VEGF. Besides low VEGF levels, TAM-CXB also suppresses VEGFR2 expression, confirmed through quantifying secreted VEGF levels, luciferase and RT-PCR studies. Interestingly, we observed that TAM-CXB was effective in blocking VEGFR2 promoter induced expression and further 2 fold decrease in VEGF levels was observed in combination than TAM alone in both cell lines. Secondly, TAM-CXB regulated VEGFR2 inhibits Src expression, responsible for tumor progression and metastasis. FACS and in vivo enzymatic studies showed significant increase in the reactive oxygen species upon TAM-CXB treatment. Taken together, our experimental results indicate that this additive combination shows promising outcome in anti-metastatic and apoptotic studies. In a line, our preclinical studies evidenced that this additive

  3. 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.

  4. Induction of autocrine factor inhibiting cell motility from murine B16-BL6 melanoma cells by alpha-melanocyte stimulating hormone.

    Science.gov (United States)

    Murata, J; Ayukawa, K; Ogasawara, M; Watanabe, H; Saiki, I

    1999-03-15

    We have previously reported that neuropeptide alpha-melanocyte stimulating hormone (alpha-MSH) successfully inhibited Matrigel invasion and haptotactic migration of B16-BL6 melanoma cells towards both fibronectin and laminin without affecting their growth. In the present study, we investigated the inhibitory mechanism of tumor cell motility by alpha-MSH. Alpha-MSH significantly blocked the autocrine motility factor (AMF)-enhanced cell motility. However, alpha-MSH did neither prevent the secretion of AMF from B16-BL6 cells nor alter the expression level of AMF receptor (gp78). On the other hand, alpha-MSH induced the secretion of the motility inhibitory factor(s) from B16-BL6 cells in a concentration- and time-dependent manner. The induction of the motility inhibitor(s) was proportional to increasing levels of intracellular cAMP induced by alpha-MSH as well as forskolin, and the activity was abolished by an adenylate cyclase inhibitor, 2',5'-dideoxyadenosine (DDA). The motility-inhibiting activity in conditioned medium (CM) from alpha-MSH-treated B16-BL6 cells was found to have a m.w. below 3 kDa after fractionation. This activity was abolished by boiling but insensitive to trypsin. The treatment of tumor cells with cycloheximide reduced the activity in alpha-MSH-stimulated CM. Our results suggest that alpha-MSH inhibited the motility of B16-BL6 cells through induction of autocrine factor(s).

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

    Directory of Open Access Journals (Sweden)

    Naitao Wang

    2016-05-01

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

  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

    Science.gov (United States)

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

    1995-01-01

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

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

    International Nuclear Information System (INIS)

    Auf, Gregor; Vajkoczy, Peter; Seno, Masaharu; Bikfalvi, Andreas; Minchenko, Dmitri; Minchenko, Oleksandr; Moenner, Michel; Jabouille, Arnaud; Delugin, Maylis; Guérit, Sylvaine; Pineau, Raphael; North, Sophie; Platonova, Natalia; Maitre, Marlène; Favereaux, Alexandre

    2013-01-01

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

  8. The putative bZIP transcription factor BzpN slows proliferation and functions in the regulation of cell density by autocrine signals in Dictyostelium.

    Directory of Open Access Journals (Sweden)

    Jonathan E Phillips

    Full Text Available The secreted proteins AprA and CfaD function as autocrine signals that inhibit cell proliferation in Dictyostelium discoideum, thereby regulating cell numbers by a negative feedback mechanism. We report here that the putative basic leucine zipper transcription factor BzpN plays a role in the inhibition of proliferation by AprA and CfaD. Cells lacking BzpN proliferate more rapidly than wild-type cells but do not reach a higher stationary density. Recombinant AprA inhibits wild-type cell proliferation but does not inhibit the proliferation of cells lacking BzpN. Recombinant CfaD also inhibits wild-type cell proliferation, but promotes the proliferation of cells lacking BzpN. Overexpression of BzpN results in a reduced cell density at stationary phase, and this phenotype requires AprA, CfaD, and the kinase QkgA. Conditioned media from high-density cells stops the proliferation of wild-type but not bzpN(- cells and induces a nuclear localization of a BzpN-GFP fusion protein, though this localization does not require AprA or CfaD. Together, the data suggest that BzpN is necessary for some but not all of the effects of AprA and CfaD, and that BzpN may function downstream of AprA and CfaD in a signal transduction pathway that inhibits proliferation.

  9. The Putative bZIP Transcripton Factor BzpN Slows Proliferation and Functions in the Regulation of Cell Density by Autocrine Signals in Dictyostelium

    Science.gov (United States)

    Phillips, Jonathan E.; Huang, Eryong; Shaulsky, Gad; Gomer, Richard H.

    2011-01-01

    The secreted proteins AprA and CfaD function as autocrine signals that inhibit cell proliferation in Dictyostelium discoideum, thereby regulating cell numbers by a negative feedback mechanism. We report here that the putative basic leucine zipper transcription factor BzpN plays a role in the inhibition of proliferation by AprA and CfaD. Cells lacking BzpN proliferate more rapidly than wild-type cells but do not reach a higher stationary density. Recombinant AprA inhibits wild-type cell proliferation but does not inhibit the proliferation of cells lacking BzpN. Recombinant CfaD also inhibits wild-type cell proliferation, but promotes the proliferation of cells lacking BzpN. Overexpression of BzpN results in a reduced cell density at stationary phase, and this phenotype requires AprA, CfaD, and the kinase QkgA. Conditioned media from high-density cells stops the proliferation of wild-type but not bzpN− cells and induces a nuclear localization of a BzpN-GFP fusion protein, though this localization does not require AprA or CfaD. Together, the data suggest that BzpN is necessary for some but not all of the effects of AprA and CfaD, and that BzpN may function downstream of AprA and CfaD in a signal transduction pathway that inhibits proliferation. PMID:21760904

  10. The putative bZIP transcription factor BzpN slows proliferation and functions in the regulation of cell density by autocrine signals in Dictyostelium.

    Science.gov (United States)

    Phillips, Jonathan E; Huang, Eryong; Shaulsky, Gad; Gomer, Richard H

    2011-01-01

    The secreted proteins AprA and CfaD function as autocrine signals that inhibit cell proliferation in Dictyostelium discoideum, thereby regulating cell numbers by a negative feedback mechanism. We report here that the putative basic leucine zipper transcription factor BzpN plays a role in the inhibition of proliferation by AprA and CfaD. Cells lacking BzpN proliferate more rapidly than wild-type cells but do not reach a higher stationary density. Recombinant AprA inhibits wild-type cell proliferation but does not inhibit the proliferation of cells lacking BzpN. Recombinant CfaD also inhibits wild-type cell proliferation, but promotes the proliferation of cells lacking BzpN. Overexpression of BzpN results in a reduced cell density at stationary phase, and this phenotype requires AprA, CfaD, and the kinase QkgA. Conditioned media from high-density cells stops the proliferation of wild-type but not bzpN(-) cells and induces a nuclear localization of a BzpN-GFP fusion protein, though this localization does not require AprA or CfaD. Together, the data suggest that BzpN is necessary for some but not all of the effects of AprA and CfaD, and that BzpN may function downstream of AprA and CfaD in a signal transduction pathway that inhibits proliferation.

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

    Science.gov (United States)

    Wang, Naitao; Dong, Bai-Jun; Quan, Yizhou; Chen, Qianqian; Chu, Mingliang; Xu, Jin; Xue, Wei; Huang, Yi-Ran; Yang, Ru; Gao, Wei-Qiang

    2016-05-10

    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. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  12. Nogo-B Promotes Angiogenesis in Proliferative Diabetic Retinopathy via VEGF/PI3K/Akt Pathway in an Autocrine Manner

    Directory of Open Access Journals (Sweden)

    Yuelu Zhang

    2017-10-01

    Full Text Available Background/Aims: Nogo-B, a conservative protein of endoplasmic reticulum, is a member of the reticulon family of proteins. Proliferative diabetic retinopathy (PDR is the major concerning problem of diabetic retinopathy. This study explored the role of Nogo-B in the regulation of angiogenesis in PDR patients and primary human retinal endothelial cells (HRMECs. Methods: Nogo-B was down-regulated through the use of Lentivirus-NogoB-RNAi, the effects of Nogo-B on angiogenesis under high glucose stimulation were evaluated via CCK-8 assay, wound closure assay, transwell assay, and tube formation assay. Expression of Nogo-B, VEGF, PI3K and Akt were determined by western blotting, immunofluorescence, enzyme-linked immunosorbent assay (ELISA. Co-culture systerm was used to explore cell communication. Results: Nogo-B was highly enriched in ocular tissues of PDR patients and in HRMECs exposed to high glucose. Down-regulation of Nogo-B attenuated high glucose induced cell migration and tube formation in HRMECs. Mechanistically, in comparison with the negative control group, Lentivirus-NogoB-RNAi group had exhibited reduced VEGF secretion, weakened PI3K and Akt activation. Besides, high glucose treatment promoted the secretion of Nogo-B and presented as a “long-term memory”. Conclusions: These data collectively indicated that Nogo-B promoted angiogenesis in HRMECs via VEGF/PI3K/Akt pathway in an autocrine manner.

  13. Autocrine growth induced by the insulin-related factor in the insulin-independent teratoma cell line 1246-3A

    International Nuclear Information System (INIS)

    Yamada, Yukio; Serrero, G.

    1988-01-01

    An insulin-independent teratoma-derived cell line, called 1246-3A, has been isolated from the adipogenic cell line 1246, which stringently requires insulin for proliferation. The 1246-3A cell line, which can proliferate in the absence of exogenous insulin, produces in its conditioned medium a growth factor similar to pancreatic insulin by its biological and immunological properties. This factor, called insulin-related factor (IRF), was purified and iodinated to study its binding to cell surface receptors. 125 I-labeled IRF binding to intact 1246-3A cells is lower than to 1246 cells. Cell surface binding can be restored by culturing the 1246-3A cells in the presence of an anti-porcine insulin monoclonal antibody of by acid prewash of the cells prior to performing the binding. Scatchard analysis of binding indicates that IRF secreted by the 1246-3A cells partially occupies high-affinity binding sites on the producer cells. Moreover, insulin monoclonal antibody inhibits the proliferation of the IRF-producing 1246-3A cells, suggesting that these cells are dependent on the secreted IRF for growth in culture. The authors conclude that the insulin-related factor secreted by the insulin-independent 1246-3A cells stimulates their proliferation in an autocrine fashion

  14. IL-1β Suppresses the Formation of Osteoclasts by Increasing OPG Production via an Autocrine Mechanism Involving Celecoxib-Related Prostaglandins in Chondrocytes

    Directory of Open Access Journals (Sweden)

    Yusuke Watanabe

    2009-01-01

    Full Text Available Elevated interleukin (IL-1 concentrations in synovial fluid have been implicated in joint bone and cartilage destruction. Previously, we showed that IL-1β stimulated the expression of prostaglandin (PG receptor EP4 via increased PGE2 production. However, the effect of IL-1β on osteoclast formation via chondrocytes is unclear. Therefore, we examined the effect of IL-1β and/or celecoxib on the expression of macrophage colony-stimulating factor (M-CSF, receptor activator of NF-κB ligand (RANKL, and osteoprotegerin (OPG in human chondrocytes, and the indirect effect of IL-1β on osteoclast-like cell formation using RAW264.7 cells. OPG and RANKL expression increased with IL-1β; whereas M-CSF expression decreased. Celecoxib blocked the stimulatory effect of IL-1β. Conditioned medium from IL-1β-treated chondrocytes decreased TRAP staining in RAW264.7 cells. These results suggest that IL-1β suppresses the formation of osteoclast-like cells via increased OPG production and decreased M-CSF production in chondrocytes, and OPG production may increase through an autocrine mechanism involving celecoxib-related PGs.

  15. 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

    2016-01-01

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

  16. 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.

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

    International Nuclear Information System (INIS)

    Castillo, Gaelle del; Murillo, Miguel M.; Alvarez-Barrientos, Alberto; Bertran, Esther; Fernandez, Margarita; Sanchez, Aranzazu; Fabregat, Isabel

    2006-01-01

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

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

    International Nuclear Information System (INIS)

    Ishino, Ruri; Minami, Kaori; Tanaka, Satowa; Nagai, Mami; Matsui, Keiji; Hasegawa, Natsumi; Roeder, Robert G.; Asano, Shigetaka; Ito, Mitsuhiro

    2013-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-10-11

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

  20. Microsomal Prostaglandin E Synthase-1 Facilitates an Intercellular Interaction between CD4⁺ T Cells through IL-1β Autocrine Function in Experimental Autoimmune Encephalomyelitis.

    Science.gov (United States)

    Takemiya, Takako; Takeuchi, Chisen; Kawakami, Marumi

    2017-12-19

    Microsomal prostaglandin synthetase-1 (mPGES-1) is an inducible terminal enzyme that produces prostaglandin E₂ (PGE₂). In our previous study, we investigated the role of mPGES-1 in the inflammation and demyelination observed in experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis, using mPGES - 1 -deficient ( mPGES-1 -/- ) and wild-type (wt) mice. We found that mPGES-1 facilitated inflammation, demyelination, and paralysis and was induced in vascular endothelial cells and macrophages and microglia around inflammatory foci. Here, we investigated the role of interleukin-1β (IL-1β) in the intercellular mechanism stimulated by mPGES-1 in EAE spinal cords in the presence of inflammation. We found that the area invaded by CD4-positive (CD4⁺) T cells was extensive, and that PGE₂ receptors EP1-4 were more induced in activated CD4⁺ T cells of wt mice than in those of mPGES - 1 -/- mice. Moreover, IL-1β and IL-1 receptor 1 (IL-1r1) were produced by 65% and 48% of CD4⁺ T cells in wt mice and by 44% and 27% of CD4⁺ T cells in mPGES-1 -/- mice. Furthermore, interleukin-17 (IL-17) was released from the activated CD4⁺ T cells. Therefore, mPGES-1 stimulates an intercellular interaction between CD4⁺ T cells by upregulating the autocrine function of IL-1β in activated CD4⁺ T cells, which release IL-17 to facilitate axonal and myelin damage in EAE mice.

  1. PPARα autocrine regulation of Ca²⁺-regulated exocytosis in guinea pig antral mucous cells: NO and cGMP accumulation.

    Science.gov (United States)

    Tanaka, Saori; Sugiyama, Nanae; Takahashi, Yuko; Mantoku, Daiki; Sawabe, Yukinori; Kuwabara, Hiroko; Nakano, Takashi; Shimamoto, Chikao; Matsumura, Hitoshi; Marunaka, Yoshinori; Nakahari, Takashi

    2014-12-15

    In antral mucous cells, acetylcholine (ACh, 1 μM) activates Ca(2+)-regulated exocytosis, consisting of a peak in exocytotic events that declines rapidly (initial phase) followed by a second slower decline (late phase) lasting during ACh stimulation. GW7647 [a peroxisome proliferation activation receptor α (PPARα) agonist] enhanced the ACh-stimulated initial phase, and GW6471 (a PPARα antagonist) abolished the GW7647-induced enhancement. However, GW6471 produced the delayed, but transient, increase in the ACh-stimulated late phase, and it also decreased the initial phase and produced the delayed increase in the late phase during stimulation with ACh alone. A similar delayed increase in the ACh-stimulated late phase is induced by an inhibitor of the PKG, Rp8BrPETcGMPS, suggesting that GW6471 inhibits cGMP accumulation. An inhibitor of nitric oxide synthase 1 (NOS1), N(5)-[imino(propylamino)methyl]-L-ornithine hydrochloride (N-PLA), also abolished the GW7647-induced-enhancement of ACh-stimulated initial phase but produced the delayed increase in the late phase. However, in the presence of N-PLA, an NO donor or 8BrcGMP enhanced the ACh-stimulated initial phase and abolished the delayed increase in the late phase. Moreover, GW7647 and ACh stimulated NO production and cGMP accumulation in antral mucosae, which was inhibited by GW6471 or N-PLA. Western blotting and immunohistochemistry revealed that NOS1 and PPARα colocalize in antral mucous cells. In conclusion, during ACh stimulation, a PPARα autocrine mechanism, which accumulates NO via NOS1 leading to cGMP accumulation, modulates the Ca(2+)-regulated exocytosis in antral mucous cells. Copyright © 2014 the American Physiological Society.

  2. Biotin increases glucokinase expression via soluble guanylate cyclase/protein kinase G, adenosine triphosphate production and autocrine action of insulin in pancreatic rat islets.

    Science.gov (United States)

    Vilches-Flores, Alonso; Tovar, Armando R; Marin-Hernandez, Alvaro; Rojas-Ochoa, Alberto; Fernandez-Mejia, Cristina

    2010-07-01

    Besides its role as a carboxylase prosthetic group, biotin has important effects on gene expression. However, the molecular mechanisms through which biotin exerts these effects are largely unknown. We previously found that biotin increases pancreatic glucokinase expression. We have now explored the mechanisms underlying this effect. Pancreatic islets from Wistar rats were treated with biotin, in the presence or absence of different types of inhibitors. Glucokinase mRNA and 18s rRNA abundance were determined by real-time PCR. Adenosine triphosphate (ATP) content was analyzed by fluorometry. Biotin treatment increased glucokinase mRNA abundance approximately one fold after 2 h; the effect was sustained up to 24 h. Inhibition of soluble guanylate cyclase or protein kinase G (PKG) signalling suppressed biotin-induced glucokinase expression. The cascade of events downstream of PKG in biotin-mediated gene transcription is not known. We found that inhibition of insulin secretion with diazoxide or nifedipine prevented biotin-stimulated glucokinase mRNA increase. Biotin treatment increased islet ATP content (control: 4.68+/-0.28; biotin treated: 6.62+/-0.26 pmol/islet) at 30 min. Inhibition of PKG activity suppressed the effects of biotin on ATP content. Insulin antibodies or inhibitors of phosphoinositol-3-kinase/Akt insulin signalling pathway prevented biotin-induced glucokinase expression. The nucleotide 8-Br-cGMP mimicked the biotin effects. We propose that the induction of pancreatic glucokinase mRNA by biotin involves guanylate cyclase and PKG activation, which leads to an increase in ATP content. This induces insulin secretion via ATP-sensitive potassium channels. Autocrine insulin, in turn, activates phosphoinositol-3-kinase/Akt signalling. Our results offer new insights into the pathways that participate in biotin-mediated gene expression. (c) 2010 Elsevier Inc. All rights reserved.

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

    International Nuclear Information System (INIS)

    Escudero-Lourdes, C.; Wu, T.; Camarillo, J.M.; Gandolfi, A.J.

    2012-01-01

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

  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

    International Nuclear Information System (INIS)

    Luo, Fei; Xu, Yuan; Ling, Min; Zhao, Yue; Xu, Wenchao; Liang, Xiao; Jiang, Rongrong; Wang, Bairu; Bian, Qian; Liu, Qizhan

    2013-01-01

    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. Pluripotency gene expression and growth control in cultures of peripheral blood monocytes during their conversion into programmable cells of monocytic origin (PCMO: evidence for a regulatory role of autocrine activin and TGF-β.

    Directory of Open Access Journals (Sweden)

    Hendrik Ungefroren

    Full Text Available Previous studies have shown that peripheral blood monocytes can be converted in vitro to a stem cell-like cell termed PCMO as evidenced by the re-expression of pluripotency-associated genes, transient proliferation, and the ability to adopt the phenotype of hepatocytes and insulin-producing cells upon tissue-specific differentiation. However, the regulatory interactions between cultured cells governing pluripotency and mitotic activity have remained elusive. Here we asked whether activin(s and TGF-β(s, are involved in PCMO generation. De novo proliferation of PCMO was higher under adherent vs. suspended culture conditions as revealed by the appearance of a subset of Ki67-positive monocytes and correlated with down-regulation of p21WAF1 beyond day 2 of culture. Realtime-PCR analysis showed that PCMO express ActRIIA, ALK4, TβRII, ALK5 as well as TGF-β1 and the βA subunit of activin. Interestingly, expression of ActRIIA and ALK4, and activin A levels in the culture supernatants increased until day 4 of culture, while levels of total and active TGF-β1 strongly declined. PCMO responded to both growth factors in an autocrine fashion with intracellular signaling as evidenced by a rise in the levels of phospho-Smad2 and a drop in those of phospho-Smad3. Stimulation of PCMO with recombinant activins (A, B, AB and TGF-β1 induced phosphorylation of Smad2 but not Smad3. Inhibition of autocrine activin signaling by either SB431542 or follistatin reduced both Smad2 activation and Oct4A/Nanog upregulation. Inhibition of autocrine TGF-β signaling by either SB431542 or anti-TGF-β antibody reduced Smad3 activation and strongly increased the number of Ki67-positive cells. Furthermore, anti-TGF-β antibody moderately enhanced Oct4A/Nanog expression. Our data show that during PCMO generation pluripotency marker expression is controlled positively by activin/Smad2 and negatively by TGF-β/Smad3 signaling, while relief from growth inhibition is primarily the

  6. Human Scalp Hair Follicles Are Both a Target and a Source of Prolactin, which Serves as an Autocrine and/or Paracrine Promoter of Apoptosis-Driven Hair Follicle Regression

    Science.gov (United States)

    Foitzik, Kerstin; Krause, Karoline; Conrad, Franziska; Nakamura, Motonobu; Funk, Wolfang; Paus, Ralf

    2006-01-01

    The prototypic pituitary hormone prolactin (PRL) exerts a wide variety of bioregulatory effects in mammals and is also found in extrapituitary sites, including murine skin. Here, we show by reverse transcriptase-polymerase chain reaction and immunohistology that, contrary to a previous report, human skin and normal human scalp hair follicles (HFs), in particular, express both PRL and PRL receptors (PRL-R) at the mRNA and protein level. PRL and PRL-R immunoreactivity can be detected in the epithelium of human anagen VI HFs, while the HF mesenchyme is negative. During the HF transformation from growth (anagen) to apoptosis-driven regression (catagen), PRL and PRL-R immunoreactivity appear up-regulated. Treatment of organ-cultured human scalp HFs with high-dose PRL (400 ng/ml) results in a significant inhibition of hair shaft elongation and premature catagen development, along with reduced proliferation and increased apoptosis of hair bulb keratinocytes (Ki-67/terminal dUTP nick-end labeling immunohistomorphometry). This shows that PRL receptors, expressed in HFs, are functional and that human skin and human scalp HFs are both direct targets and sources of PRL. Our data suggest that PRL acts as an autocrine hair growth modulator with catagen-promoting functions and that the hair growth-inhibitory effects of PRL demonstrated here may underlie the as yet ill-understood hair loss in patients with hyperprolactinemia. PMID:16507890

  7. Human scalp hair follicles are both a target and a source of prolactin, which serves as an autocrine and/or paracrine promoter of apoptosis-driven hair follicle regression.

    Science.gov (United States)

    Foitzik, Kerstin; Krause, Karoline; Conrad, Franziska; Nakamura, Motonobu; Funk, Wolfang; Paus, Ralf

    2006-03-01

    The prototypic pituitary hormone prolactin (PRL) exerts a wide variety of bioregulatory effects in mammals and is also found in extrapituitary sites, including murine skin. Here, we show by reverse transcriptase-polymerase chain reaction and immunohistology that, contrary to a previous report, human skin and normal human scalp hair follicles (HFs), in particular, express both PRL and PRL receptors (PRL-R) at the mRNA and protein level. PRL and PRL-R immunoreactivity can be detected in the epithelium of human anagen VI HFs, while the HF mesenchyme is negative. During the HF transformation from growth (anagen) to apoptosis-driven regression (catagen), PRL and PRL-R immunoreactivity appear up-regulated. Treatment of organ-cultured human scalp HFs with high-dose PRL (400 ng/ml) results in a significant inhibition of hair shaft elongation and premature catagen development, along with reduced proliferation and increased apoptosis of hair bulb keratinocytes (Ki-67/terminal dUTP nick-end labeling immunohistomorphometry). This shows that PRL receptors, expressed in HFs, are functional and that human skin and human scalp HFs are both direct targets and sources of PRL. Our data suggest that PRL acts as an autocrine hair growth modulator with catagen-promoting functions and that the hair growth-inhibitory effects of PRL demonstrated here may underlie the as yet ill-understood hair loss in patients with hyper-prolactinemia.

  8. 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.

  9. WALS Prediction

    NARCIS (Netherlands)

    Magnus, J.R.; Wang, W.; Zhang, Xinyu

    2012-01-01

    Abstract: Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty

  10. Recently activated naive CD4 T cells can help resting B cells, and can produce sufficient autocrine IL-4 to drive differentiation to secretion of T helper 2-type cytokines.

    Science.gov (United States)

    Croft, M; Swain, S L

    1995-05-01

    and provide cognate help to B cells. They also suggest that if activated naive CD4 cells receive multiple stimulations from Ag/APC, enough endogenous IL-4 can be produced to drive differentiation into effectors secreting type 2 cytokines. The existence of such an autocrine feedback mechanism suggests that the amount and availability of Ag could influence the nature and polarization of the Th response.

  11. Climate prediction and predictability

    Science.gov (United States)

    Allen, Myles

    2010-05-01

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

  12. Earthquake prediction

    International Nuclear Information System (INIS)

    Ward, P.L.

    1978-01-01

    The state of the art of earthquake prediction is summarized, the possible responses to such prediction are examined, and some needs in the present prediction program and in research related to use of this new technology are reviewed. Three basic aspects of earthquake prediction are discussed: location of the areas where large earthquakes are most likely to occur, observation within these areas of measurable changes (earthquake precursors) and determination of the area and time over which the earthquake will occur, and development of models of the earthquake source in order to interpret the precursors reliably. 6 figures

  13. Predictive medicine

    NARCIS (Netherlands)

    Boenink, Marianne; ten Have, 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

  14. Prediction Markets

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  15. Predicting unpredictability

    Science.gov (United States)

    Davis, Steven J.

    2018-04-01

    Analysts and markets have struggled to predict a number of phenomena, such as the rise of natural gas, in US energy markets over the past decade or so. Research shows the challenge may grow because the industry — and consequently the market — is becoming increasingly volatile.

  16. Unification predictions

    International Nuclear Information System (INIS)

    Ghilencea, D.; Ross, G.G.; Lanzagorta, M.

    1997-07-01

    The unification of gauge couplings suggests that there is an underlying (supersymmetric) unification of the strong, electromagnetic and weak interactions. The prediction of the unification scale may be the first quantitative indication that this unification may extend to unification with gravity. We make a precise determination of these predictions for a class of models which extend the multiplet structure of the Minimal Supersymmetric Standard Model to include the heavy states expected in many Grand Unified and/or superstring theories. We show that there is a strong cancellation between the 2-loop and threshold effects. As a result the net effect is smaller than previously thought, giving a small increase in both the unification scale and the value of the strong coupling at low energies. (author). 15 refs, 5 figs

  17. Predictable Medea

    Directory of Open Access Journals (Sweden)

    Elisabetta Bertolino

    2010-01-01

    Full Text Available By focusing on the tragedy of the 'unpredictable' infanticide perpetrated by Medea, the paper speculates on the possibility of a non-violent ontological subjectivity for women victims of gendered violence and whether it is possible to respond to violent actions in non-violent ways; it argues that Medea did not act in an unpredictable way, rather through the very predictable subject of resentment and violence. 'Medea' represents the story of all of us who require justice as retribution against any wrong. The presupposition is that the empowered female subjectivity of women’s rights contains the same desire of mastering others of the masculine current legal and philosophical subject. The subject of women’s rights is grounded on the emotions of resentment and retribution and refuses the categories of the private by appropriating those of the righteous, masculine and public subject. The essay opposes the essentialised stereotypes of the feminine and the maternal with an ontological approach of people as singular, corporeal, vulnerable and dependent. There is therefore an emphasis on the excluded categories of the private. Forgiveness is taken into account as a category of the private and a possibility of responding to violence with newness. A violent act is seen in relations to the community of human beings rather than through an isolated setting as in the case of the individual of human rights. In this context, forgiveness allows to risk again and being with. The result is also a rethinking of feminist actions, feminine subjectivity and of the maternal. Overall the paper opens up the Arendtian category of action and forgiveness and the Cavarerian unique and corporeal ontology of the selfhood beyond gendered stereotypes.

  18. A simple and accurate rule-based modeling framework for simulation of autocrine/paracrine stimulation of glioblastoma cell motility and proliferation by L1CAM in 2-D culture.

    Science.gov (United States)

    Caccavale, Justin; Fiumara, David; Stapf, Michael; Sweitzer, Liedeke; Anderson, Hannah J; Gorky, Jonathan; Dhurjati, Prasad; Galileo, Deni S

    2017-12-11

    Glioblastoma multiforme (GBM) is a devastating brain cancer for which there is no known cure. Its malignancy is due to rapid cell division along with high motility and invasiveness of cells into the brain tissue. Simple 2-dimensional laboratory assays (e.g., a scratch assay) commonly are used to measure the effects of various experimental perturbations, such as treatment with chemical inhibitors. Several mathematical models have been developed to aid the understanding of the motile behavior and proliferation of GBM cells. However, many are mathematically complicated, look at multiple interdependent phenomena, and/or use modeling software not freely available to the research community. These attributes make the adoption of models and simulations of even simple 2-dimensional cell behavior an uncommon practice by cancer cell biologists. Herein, we developed an accurate, yet simple, rule-based modeling framework to describe the in vitro behavior of GBM cells that are stimulated by the L1CAM protein using freely available NetLogo software. In our model L1CAM is released by cells to act through two cell surface receptors and a point of signaling convergence to increase cell motility and proliferation. A simple graphical interface is provided so that changes can be made easily to several parameters controlling cell behavior, and behavior of the cells is viewed both pictorially and with dedicated graphs. We fully describe the hierarchical rule-based modeling framework, show simulation results under several settings, describe the accuracy compared to experimental data, and discuss the potential usefulness for predicting future experimental outcomes and for use as a teaching tool for cell biology students. It is concluded that this simple modeling framework and its simulations accurately reflect much of the GBM cell motility behavior observed experimentally in vitro in the laboratory. Our framework can be modified easily to suit the needs of investigators interested in other

  19. 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.

  20. Autocrine role of vascular IL-15 in intimal thickening

    International Nuclear Information System (INIS)

    Cercek, Miha; Matsumoto, Michiaki; Li, Hongyan; Chyu, K.-Y.; Peter, Ashok; Shah, Prediman K.; Dimayuga, Paul C.

    2006-01-01

    Interleukin 15 (IL-15) is a pro-inflammatory cytokine that modulates T cell recruitment and activation, independent of antigen. It has been detected in human atherosclerotic plaques and atherosclerotic plaques of apoE-/- mice. IL-15 regulates fractalkine (FKN)-CX3CR1 chemokine signaling which is involved in atherogenesis and promotes SMC proliferation. We investigated the role of IL-15 in intimal thickening after arterial injury. Treatment of serum-stimulated SMC with IL-15 in vitro attenuated proliferation and suppressed CX3CR1 and FKN mRNA expression. The role of endogenous IL-15 in vivo was investigated in injured carotid arteries of mice. Periadventitial arterial injury resulted in increased IL-15 expression in the media and neointima, paralleled by increased IL-15 receptor α expression. Blockade of endogenous IL-15 increased intimal thickening. FKN and CX3CR1 expression increased after injury and were further augmented after IL-15 blockade. These data suggest that endogenous IL-15 attenuated intimal thickening after arterial injury. The potential mechanism of action is suppression of CX3CR1 signaling

  1. Autocrine and Paracrine Hh Signaling Regulate Prostate Development

    Science.gov (United States)

    2010-09-01

    Rev. Mol. Cell. Biol. 6, 306–317 7. Wang, B. E., Shou, J., Ross, S., Koeppen, H., De Sauvage, F. J., and Gao, W. Q. (2003) J. Biol. Chem. 278, 18506...and Placzek, M. (2006) Nat. Rev. Genet. 7, 841–850 13. Callahan, C. A., Ofstad, T., Horng, L.,Wang, J. K., Zhen, H. H., Coulombe , P. A., and Oro, A. E...Albig, A. R., and Schiemann, W. P. (2005)Mol. Biol. Cell 16, 609–625 45. Olsen, M. W., Ley , C. D., Junker, N., Hansen, A. J., Lund, E. L., and Krist

  2. Predictive modeling of complications.

    Science.gov (United States)

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

    2016-09-01

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

  3. Predicting outdoor sound

    CERN Document Server

    Attenborough, Keith; Horoshenkov, Kirill

    2014-01-01

    1. Introduction  2. The Propagation of Sound Near Ground Surfaces in a Homogeneous Medium  3. Predicting the Acoustical Properties of Outdoor Ground Surfaces  4. Measurements of the Acoustical Properties of Ground Surfaces and Comparisons with Models  5. Predicting Effects of Source Characteristics on Outdoor Sound  6. Predictions, Approximations and Empirical Results for Ground Effect Excluding Meteorological Effects  7. Influence of Source Motion on Ground Effect and Diffraction  8. Predicting Effects of Mixed Impedance Ground  9. Predicting the Performance of Outdoor Noise Barriers  10. Predicting Effects of Vegetation, Trees and Turbulence  11. Analytical Approximations including Ground Effect, Refraction and Turbulence  12. Prediction Schemes  13. Predicting Sound in an Urban Environment.

  4. 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...

  5. Predictable or not predictable? The MOV question

    International Nuclear Information System (INIS)

    Thibault, C.L.; Matzkiw, J.N.; Anderson, J.W.; Kessler, D.W.

    1994-01-01

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

  6. 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.

  7. Seismology for rockburst prediction.

    CSIR Research Space (South Africa)

    De Beer, W

    2000-02-01

    Full Text Available project GAP409 presents a method (SOOTHSAY) for predicting larger mining induced seismic events in gold mines, as well as a pattern recognition algorithm (INDICATOR) for characterising the seismic response of rock to mining and inferring future... State. Defining the time series of a specific function on a catalogue as a prediction strategy, the algorithm currently has a success rate of 53% and 65%, respectively, of large events claimed as being predicted in these two cases, with uncertainties...

  8. 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.

  9. Predictability of Conversation Partners

    Directory of Open Access Journals (Sweden)

    Taro Takaguchi

    2011-09-01

    Full Text Available 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 et al., Science 327, 1018 (2010SCIEAS0036-8075] 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.

  10. Is Time Predictability Quantifiable?

    DEFF Research Database (Denmark)

    Schoeberl, Martin

    2012-01-01

    Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst......-case 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...... compare the worst-case execution time bounds of different architectures....

  11. Predicting scholars' scientific impact.

    Directory of Open Access Journals (Sweden)

    Amin Mazloumian

    Full Text Available We tested the underlying assumption that citation counts are reliable predictors of future success, analyzing complete citation data on the careers of ~150,000 scientists. Our results show that i among all citation indicators, the annual citations at the time of prediction is the best predictor of future citations, ii future citations of a scientist's published papers can be predicted accurately (r(2 = 0.80 for a 1-year prediction, P<0.001 but iii future citations of future work are hardly predictable.

  12. 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

  13. Predictability of Stock Returns

    Directory of Open Access Journals (Sweden)

    Ahmet Sekreter

    2017-06-01

    Full Text Available Predictability of stock returns has been shown by empirical studies over time. This article collects the most important theories on forecasting stock returns and investigates the factors that affecting behavior of the stocks’ prices and the market as a whole. Estimation of the factors and the way of estimation are the key issues of predictability of stock returns.

  14. Predicting AD conversion

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  15. Predicting Free Recalls

    Science.gov (United States)

    Laming, Donald

    2006-01-01

    This article reports some calculations on free-recall data from B. Murdock and J. Metcalfe (1978), with vocal rehearsal during the presentation of a list. Given the sequence of vocalizations, with the stimuli inserted in their proper places, it is possible to predict the subsequent sequence of recalls--the predictions taking the form of a…

  16. Archaeological predictive model set.

    Science.gov (United States)

    2015-03-01

    This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

  17. Evaluating prediction uncertainty

    International Nuclear Information System (INIS)

    McKay, M.D.

    1995-03-01

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

  18. Ground motion predictions

    Energy Technology Data Exchange (ETDEWEB)

    Loux, P C [Environmental Research Corporation, Alexandria, VA (United States)

    1969-07-01

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

  19. Ground motion predictions

    International Nuclear Information System (INIS)

    Loux, P.C.

    1969-01-01

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

  20. 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

  1. Prediction of bull fertility.

    Science.gov (United States)

    Utt, Matthew D

    2016-06-01

    Prediction of male fertility is an often sought-after endeavor for many species of domestic animals. This review will primarily focus on providing some examples of dependent and independent variables to stimulate thought about the approach and methodology of identifying the most appropriate of those variables to predict bull (bovine) fertility. Although the list of variables will continue to grow with advancements in science, the principles behind making predictions will likely not change significantly. The basic principle of prediction requires identifying a dependent variable that is an estimate of fertility and an independent variable or variables that may be useful in predicting the fertility estimate. Fertility estimates vary in which parts of the process leading to conception that they infer about and the amount of variation that influences the estimate and the uncertainty thereof. The list of potential independent variables can be divided into competence of sperm based on their performance in bioassays or direct measurement of sperm attributes. A good prediction will use a sample population of bulls that is representative of the population to which an inference will be made. Both dependent and independent variables should have a dynamic range in their values. Careful selection of independent variables includes reasonable measurement repeatability and minimal correlation among variables. Proper estimation and having an appreciation of the degree of uncertainty of dependent and independent variables are crucial for using predictions to make decisions regarding bull fertility. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Bootstrap prediction and Bayesian prediction under misspecified models

    OpenAIRE

    Fushiki, Tadayoshi

    2005-01-01

    We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

  3. Prediction ranges. Annual review

    Energy Technology Data Exchange (ETDEWEB)

    Parker, J.C.; Tharp, W.H.; Spiro, P.S.; Keng, K.; Angastiniotis, M.; Hachey, L.T.

    1988-01-01

    Prediction ranges equip the planner with one more tool for improved assessment of the outcome of a course of action. One of their major uses is in financial evaluations, where corporate policy requires the performance of uncertainty analysis for large projects. This report gives an overview of the uses of prediction ranges, with examples; and risks and uncertainties in growth, inflation, and interest and exchange rates. Prediction ranges and standard deviations of 80% and 50% probability are given for various economic indicators in Ontario, Canada, and the USA, as well as for foreign exchange rates and Ontario Hydro interest rates. An explanatory note on probability is also included. 23 tabs.

  4. 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.

  5. Protein Sorting Prediction

    DEFF Research Database (Denmark)

    Nielsen, Henrik

    2017-01-01

    and drawbacks of each of these approaches is described through many examples of methods that predict secretion, integration into membranes, or subcellular locations in general. The aim of this chapter is to provide a user-level introduction to the field with a minimum of computational theory.......Many computational methods are available for predicting protein sorting in bacteria. When comparing them, it is important to know that they can be grouped into three fundamentally different approaches: signal-based, global-property-based and homology-based prediction. In this chapter, the strengths...

  6. '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......This conceptual article introduces 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 and generate innovations. We frame the approach in the context of first- and second...

  7. 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....... We use the term predictive in two situations: (i) with no use of binary interaction parameters, and (ii) multicomponent calculations using binary interaction parameters based solely on binary data. It is shown that the CPA equation of state can satisfactorily predict CO2–water–glycols–alkanes VLE...

  8. Prediction of intermetallic compounds

    International Nuclear Information System (INIS)

    Burkhanov, Gennady S; Kiselyova, N N

    2009-01-01

    The problems of predicting not yet synthesized intermetallic compounds are discussed. It is noted that the use of classical physicochemical analysis in the study of multicomponent metallic systems is faced with the complexity of presenting multidimensional phase diagrams. One way of predicting new intermetallics with specified properties is the use of modern processing technology with application of teaching of image recognition by the computer. The algorithms used most often in these methods are briefly considered and the efficiency of their use for predicting new compounds is demonstrated.

  9. Filtering and prediction

    CERN Document Server

    Fristedt, B; Krylov, N

    2007-01-01

    Filtering and prediction is about observing moving objects when the observations are corrupted by random errors. The main focus is then on filtering out the errors and extracting from the observations the most precise information about the object, which itself may or may not be moving in a somewhat random fashion. Next comes the prediction step where, using information about the past behavior of the object, one tries to predict its future path. The first three chapters of the book deal with discrete probability spaces, random variables, conditioning, Markov chains, and filtering of discrete Markov chains. The next three chapters deal with the more sophisticated notions of conditioning in nondiscrete situations, filtering of continuous-space Markov chains, and of Wiener process. Filtering and prediction of stationary sequences is discussed in the last two chapters. The authors believe that they have succeeded in presenting necessary ideas in an elementary manner without sacrificing the rigor too much. Such rig...

  10. CMAQ predicted concentration files

    Data.gov (United States)

    U.S. Environmental Protection Agency — CMAQ predicted ozone. This dataset is associated with the following publication: Gantt, B., G. Sarwar, J. Xing, H. Simon, D. Schwede, B. Hutzell, R. Mathur, and A....

  11. Methane prediction in collieries

    CSIR Research Space (South Africa)

    Creedy, DP

    1999-06-01

    Full Text Available The primary aim of the project was to assess the current status of research on methane emission prediction for collieries in South Africa in comparison with methods used and advances achieved elsewhere in the world....

  12. Climate Prediction Center - Outlooks

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Outreach > Publications > Climate Diagnostics Bulletin Climate Diagnostics Bulletin - Tropics Climate Diagnostics Bulletin - Forecast Climate Diagnostics

  13. CMAQ predicted concentration files

    Data.gov (United States)

    U.S. Environmental Protection Agency — model predicted concentrations. This dataset is associated with the following publication: Muñiz-Unamunzaga, M., R. Borge, G. Sarwar, B. Gantt, D. de la Paz, C....

  14. Comparing Spatial Predictions

    KAUST Repository

    Hering, Amanda S.; Genton, Marc G.

    2011-01-01

    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

  15. Genomic prediction using subsampling

    OpenAIRE

    Xavier, Alencar; Xu, Shizhong; Muir, William; Rainey, Katy Martin

    2017-01-01

    Background Genome-wide assisted selection is a critical tool for the?genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov chain in genomic prediction. Such method consists of fitting whole-genome regression models by subsampling observations in each rou...

  16. 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...

  17. Empirical Flutter Prediction Method.

    Science.gov (United States)

    1988-03-05

    been used in this way to discover species or subspecies of animals, and to discover different types of voter or comsumer requiring different persuasions...respect to behavior or performance or response variables. Once this were done, corresponding clusters might be sought among descriptive or predictive or...jump in a response. The first sort of usage does not apply to the flutter prediction problem. Here the types of behavior are the different kinds of

  18. 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.

  19. Stuck pipe prediction

    KAUST Repository

    Alzahrani, Majed; Alsolami, Fawaz; Chikalov, Igor; Algharbi, Salem; Aboudi, Faisal; Khudiri, Musab

    2016-01-01

    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.

  20. Genomic prediction using subsampling.

    Science.gov (United States)

    Xavier, Alencar; Xu, Shizhong; Muir, William; Rainey, Katy Martin

    2017-03-24

    Genome-wide assisted selection is a critical tool for the genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov chain in genomic prediction. Such method consists of fitting whole-genome regression models by subsampling observations in each round of a Markov Chain Monte Carlo. We evaluated the effect of subsampling bootstrap on prediction and computational parameters. Across datasets, we observed an optimal subsampling proportion of observations around 50% with replacement, and around 33% without replacement. Subsampling provided a substantial decrease in computation time, reducing the time to fit the model by half. On average, losses on predictive properties imposed by subsampling were negligible, usually below 1%. For each dataset, an optimal subsampling point that improves prediction properties was observed, but the improvements were also negligible. Combining subsampling with Gibbs sampling is an interesting ensemble algorithm. The investigation indicates that the subsampling bootstrap Markov chain algorithm substantially reduces computational burden associated with model fitting, and it may slightly enhance prediction properties.

  1. Deep Visual Attention Prediction

    Science.gov (United States)

    Wang, Wenguan; Shen, Jianbing

    2018-05-01

    In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

  2. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

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

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

  3. Transionospheric propagation predictions

    Science.gov (United States)

    Klobucher, J. A.; Basu, S.; Basu, S.; Bernhardt, P. A.; Davies, K.; Donatelli, D. E.; Fremouw, E. J.; Goodman, J. M.; Hartmann, G. K.; Leitinger, R.

    1979-01-01

    The current status and future prospects of the capability to make transionospheric propagation predictions are addressed, highlighting the effects of the ionized media, which dominate for frequencies below 1 to 3 GHz, depending upon the state of the ionosphere and the elevation angle through the Earth-space path. The primary concerns are the predictions of time delay of signal modulation (group path delay) and of radio wave scintillation. Progress in these areas is strongly tied to knowledge of variable structures in the ionosphere ranging from the large scale (thousands of kilometers in horizontal extent) to the fine scale (kilometer size). Ionospheric variability and the relative importance of various mechanisms responsible for the time histories observed in total electron content (TEC), proportional to signal group delay, and in irregularity formation are discussed in terms of capability to make both short and long term predictions. The data base upon which predictions are made is examined for its adequacy, and the prospects for prediction improvements by more theoretical studies as well as by increasing the available statistical data base are examined.

  4. 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 p......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...

  5. Essays on Earnings Predictability

    DEFF Research Database (Denmark)

    Bruun, Mark

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

  6. Pulverized coal devolatilization prediction

    International Nuclear Information System (INIS)

    Rojas, Andres F; Barraza, Juan M

    2008-01-01

    The aim of this study was to predict the two bituminous coals devolatilization at low rate of heating (50 Celsius degrade/min), with program FG-DVC (functional group Depolymerization. Vaporization and crosslinking), and to compare the devolatilization profiles predicted by program FG-DVC, which are obtained in the thermogravimetric analyzer. It was also study the volatile liberation at (10 4 k/s) in a drop-tube furnace. The tar, methane, carbon monoxide, and carbon dioxide, formation rate profiles, and the hydrogen, oxygen, nitrogen and sulphur, elemental distribution in the devolatilization products by FG-DVC program at low rate of heating was obtained; and the liberation volatile and R factor at high rate of heating was calculated. it was found that the program predicts the bituminous coals devolatilization at low rate heating, at high rate heating, a volatile liberation around 30% was obtained

  7. Predicting Ideological Prejudice.

    Science.gov (United States)

    Brandt, Mark J

    2017-06-01

    A major shortcoming of current models of ideological prejudice is that although they can anticipate the direction of the association between participants' ideology and their prejudice against a range of target groups, they cannot predict the size of this association. I developed and tested models that can make specific size predictions for this association. A quantitative model that used the perceived ideology of the target group as the primary predictor of the ideology-prejudice relationship was developed with a representative sample of Americans ( N = 4,940) and tested against models using the perceived status of and choice to belong to the target group as predictors. In four studies (total N = 2,093), ideology-prejudice associations were estimated, and these observed estimates were compared with the models' predictions. The model that was based only on perceived ideology was the most parsimonious with the smallest errors.

  8. Inverse and Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-09-27

    The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

  9. Tide Predictions, California, 2014, NOAA

    Data.gov (United States)

    U.S. Environmental Protection Agency — The predictions from the web based NOAA Tide Predictions are based upon the latest information available as of the date of the user's request. Tide predictions...

  10. Predictive maintenance primer

    International Nuclear Information System (INIS)

    Flude, J.W.; Nicholas, J.R.

    1991-04-01

    This Predictive Maintenance Primer provides utility plant personnel with a single-source reference to predictive maintenance analysis methods and technologies used successfully by utilities and other industries. It is intended to be a ready reference to personnel considering starting, expanding or improving a predictive maintenance program. This Primer includes a discussion of various analysis methods and how they overlap and interrelate. Additionally, eighteen predictive maintenance technologies are discussed in sufficient detail for the user to evaluate the potential of each technology for specific applications. This document is designed to allow inclusion of additional technologies in the future. To gather the information necessary to create this initial Primer the Nuclear Maintenance Applications Center (NMAC) collected experience data from eighteen utilities plus other industry and government sources. NMAC also contacted equipment manufacturers for information pertaining to equipment utilization, maintenance, and technical specifications. The Primer includes a discussion of six methods used by analysts to study predictive maintenance data. These are: trend analysis; pattern recognition; correlation; test against limits or ranges; relative comparison data; and statistical process analysis. Following the analysis methods discussions are detailed descriptions for eighteen technologies analysts have found useful for predictive maintenance programs at power plants and other industrial facilities. Each technology subchapter has a description of the operating principles involved in the technology, a listing of plant equipment where the technology can be applied, and a general description of the monitoring equipment. Additionally, these descriptions include a discussion of results obtained from actual equipment users and preferred analysis techniques to be used on data obtained from the technology. 5 refs., 30 figs

  11. Predicting tile drainage discharge

    DEFF Research Database (Denmark)

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

    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...... was based on a polynomial regression predicting yearly tile drain discharge values using site specific parameters such as soil type, catchment topography, etc. as predictors. Values of calibrated model parameters from the dynamic modelling were compared to the same site specific parameter as used...

  12. 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

  13. Predicting Anthracycline Benefit

    DEFF Research Database (Denmark)

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

    2015-01-01

    PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite as measu......PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite...

  14. 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...

  15. 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.

  16. Dopamine reward prediction error coding

    OpenAIRE

    Schultz, Wolfram

    2016-01-01

    Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards?an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less...

  17. Steering smog prediction

    NARCIS (Netherlands)

    R. van Liere (Robert); J.J. van Wijk (Jack)

    1997-01-01

    textabstractThe use of computational steering for smog prediction is described. This application is representative for many underlying issues found in steering high performance applications: high computing times, large data sets, and many different input parameters. After a short description of the

  18. 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...

  19. Gate valve performance prediction

    International Nuclear Information System (INIS)

    Harrison, D.H.; Damerell, P.S.; Wang, J.K.; Kalsi, M.S.; Wolfe, K.J.

    1994-01-01

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

  20. 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.

  1. 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…

  2. Predicting visibility of aircraft.

    Directory of Open Access Journals (Sweden)

    Andrew Watson

    Full Text Available 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.

  3. Climate Prediction Center

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Organization Enter Search Term(s): Search Search the CPC Go NCEP Quarterly Newsletter Climate Highlights U.S Climate-Weather El Niño/La Niña MJO Blocking AAO, AO, NAO, PNA Climatology Global Monsoons Expert

  4. Predicting Commissary Store Success

    Science.gov (United States)

    2014-12-01

    stores or if it is possible to predict that success. Multiple studies of private commercial grocery consumer preferences , habits and demographics have...appropriate number of competitors due to the nature of international cultures and consumer preferences . 2. Missing Data Four of the remaining stores

  5. Predicting Job Satisfaction.

    Science.gov (United States)

    Blai, Boris, Jr.

    Psychological theories about human motivation and accommodation to environment can be used to achieve a better understanding of the human factors that function in the work environment. Maslow's theory of human motivational behavior provided a theoretical framework for an empirically-derived method to predict job satisfaction and explore the…

  6. Ocean Prediction Center

    Science.gov (United States)

    Social Media Facebook Twitter YouTube Search Search For Go NWS All NOAA Weather Analysis & Forecasts of Commerce Ocean Prediction Center National Oceanic and Atmospheric Administration Analysis & Unified Surface Analysis Ocean Ocean Products Ice & Icebergs NIC Ice Products NAIS Iceberg Analysis

  7. 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…

  8. Predicting coronary heart disease

    DEFF Research Database (Denmark)

    Sillesen, Henrik; Fuster, Valentin

    2012-01-01

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

  9. ANTHROPOMETRIC PREDICTIVE EQUATIONS FOR ...

    African Journals Online (AJOL)

    Keywords: Anthropometry, Predictive Equations, Percentage Body Fat, Nigerian Women, Bioelectric Impedance ... such as Asians and Indians (Pranav et al., 2009), ... size (n) of at least 3o is adjudged as sufficient for the ..... of people, gender and age (Vogel eta/., 1984). .... Fish Sold at Ile-Ife Main Market, South West Nigeria.

  10. Predicting Pilot Retention

    Science.gov (United States)

    2012-06-15

    forever… Gig ‘Em! Dale W. Stanley III vii Table of Contents Page Acknowledgments...over the last 20 years. Airbus predicted that these trends would continue as emerging economies , especially in Asia, were creating a fast growing...US economy , pay differential and hiring by the major airlines contributed most to the decision to separate from the Air Force (Fullerton, 2003: 354

  11. Predicting ideological prejudice

    NARCIS (Netherlands)

    Brandt, M.J.

    2018-01-01

    A major shortcoming of current models of ideological prejudice is that although they can anticipate the direction of the association between participants’ ideology and their prejudice against a range of target groups, they cannot predict the size of this association. I developed and tested models

  12. Dopamine reward prediction error coding.

    Science.gov (United States)

    Schultz, Wolfram

    2016-03-01

    Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.

  13. Urban pluvial flood prediction

    DEFF Research Database (Denmark)

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

    2016-01-01

    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...... 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...... 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...

  14. 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.

  15. 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”....

  16. 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.

  17. 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...

  18. 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.

  19. Cultural Resource Predictive Modeling

    Science.gov (United States)

    2017-10-01

    CR cultural resource CRM cultural resource management CRPM Cultural Resource Predictive Modeling DoD Department of Defense ESTCP Environmental...resource management ( CRM ) legal obligations under NEPA and the NHPA, military installations need to demonstrate that CRM decisions are based on objective...maxim “one size does not fit all,” and demonstrate that DoD installations have many different CRM needs that can and should be met through a variety

  20. 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.

  1. 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.

  2. Adjusting estimative prediction limits

    OpenAIRE

    Masao Ueki; Kaoru Fueda

    2007-01-01

    This note presents a direct adjustment of the estimative prediction limit to reduce the coverage error from a target value to third-order accuracy. The adjustment is asymptotically equivalent to those of Barndorff-Nielsen & Cox (1994, 1996) and Vidoni (1998). It has a simpler form with a plug-in estimator of the coverage probability of the estimative limit at the target value. Copyright 2007, Oxford University Press.

  3. Space Weather Prediction

    Science.gov (United States)

    2014-10-31

    prominence eruptions and the ensuing coronal mass ejections. The ProMag is a spectro - polarimeter, consisting of a dual-beam polarization modulation unit...feeding a visible camera and an infrared camera. The instrument is designed to measure magnetic fields in solar prominences by simultaneous spectro ...as a result of coronal hole regions, we expect to improve UV predictions by incorporating an estimate of the Earth-side coronal hole regions. 5

  4. Instrument uncertainty predictions

    International Nuclear Information System (INIS)

    Coutts, D.A.

    1991-07-01

    The accuracy of measurements and correlations should normally be provided for most experimental activities. The uncertainty is a measure of the accuracy of a stated value or equation. The uncertainty term reflects a combination of instrument errors, modeling limitations, and phenomena understanding deficiencies. This report provides several methodologies to estimate an instrument's uncertainty when used in experimental work. Methods are shown to predict both the pretest and post-test uncertainty

  5. Predictive Systems Toxicology

    KAUST Repository

    Kiani, Narsis A.; Shang, Ming-Mei; Zenil, Hector; Tegner, Jesper

    2018-01-01

    In this review we address to what extent computational techniques can augment our ability to predict toxicity. The first section provides a brief history of empirical observations on toxicity dating back to the dawn of Sumerian civilization. Interestingly, the concept of dose emerged very early on, leading up to the modern emphasis on kinetic properties, which in turn encodes the insight that toxicity is not solely a property of a compound but instead depends on the interaction with the host organism. The next logical step is the current conception of evaluating drugs from a personalized medicine point-of-view. We review recent work on integrating what could be referred to as classical pharmacokinetic analysis with emerging systems biology approaches incorporating multiple omics data. These systems approaches employ advanced statistical analytical data processing complemented with machine learning techniques and use both pharmacokinetic and omics data. We find that such integrated approaches not only provide improved predictions of toxicity but also enable mechanistic interpretations of the molecular mechanisms underpinning toxicity and drug resistance. We conclude the chapter by discussing some of the main challenges, such as how to balance the inherent tension between the predictive capacity of models, which in practice amounts to constraining the number of features in the models versus allowing for rich mechanistic interpretability, i.e. equipping models with numerous molecular features. This challenge also requires patient-specific predictions on toxicity, which in turn requires proper stratification of patients as regards how they respond, with or without adverse toxic effects. In summary, the transformation of the ancient concept of dose is currently successfully operationalized using rich integrative data encoded in patient-specific models.

  6. Predictive systems ecology

    OpenAIRE

    Evans, Matthew R.; Bithell, Mike; Cornell, Stephen J.; Dall, Sasha R. X.; D?az, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J.; Lewis, Simon L.; Mace, Georgina M.; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim

    2013-01-01

    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 ...

  7. UXO Burial Prediction Fidelity

    Science.gov (United States)

    2017-07-01

    models to capture detailed projectile dynamics during the early phases of water entry are wasted with regard to sediment -penetration depth prediction...ordnance (UXO) migrates and becomes exposed over time in response to water and sediment motion.  Such models need initial sediment penetration estimates...munition’s initial penetration depth into the sediment ,  the velocity of water at the water - sediment boundary (i.e., the bottom water velocity

  8. Predictive Systems Toxicology

    KAUST Repository

    Kiani, Narsis A.

    2018-01-15

    In this review we address to what extent computational techniques can augment our ability to predict toxicity. The first section provides a brief history of empirical observations on toxicity dating back to the dawn of Sumerian civilization. Interestingly, the concept of dose emerged very early on, leading up to the modern emphasis on kinetic properties, which in turn encodes the insight that toxicity is not solely a property of a compound but instead depends on the interaction with the host organism. The next logical step is the current conception of evaluating drugs from a personalized medicine point-of-view. We review recent work on integrating what could be referred to as classical pharmacokinetic analysis with emerging systems biology approaches incorporating multiple omics data. These systems approaches employ advanced statistical analytical data processing complemented with machine learning techniques and use both pharmacokinetic and omics data. We find that such integrated approaches not only provide improved predictions of toxicity but also enable mechanistic interpretations of the molecular mechanisms underpinning toxicity and drug resistance. We conclude the chapter by discussing some of the main challenges, such as how to balance the inherent tension between the predictive capacity of models, which in practice amounts to constraining the number of features in the models versus allowing for rich mechanistic interpretability, i.e. equipping models with numerous molecular features. This challenge also requires patient-specific predictions on toxicity, which in turn requires proper stratification of patients as regards how they respond, with or without adverse toxic effects. In summary, the transformation of the ancient concept of dose is currently successfully operationalized using rich integrative data encoded in patient-specific models.

  9. 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.

  10. 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.

  11. Predicting big bang deuterium

    Energy Technology Data Exchange (ETDEWEB)

    Hata, N.; Scherrer, R.J.; Steigman, G.; Thomas, D.; Walker, T.P. [Department of Physics, Ohio State University, Columbus, Ohio 43210 (United States)

    1996-02-01

    We present new upper and lower bounds to the primordial abundances of deuterium and {sup 3}He based on observational data from the solar system and the interstellar medium. Independent of any model for the primordial production of the elements we find (at the 95{percent} C.L.): 1.5{times}10{sup {minus}5}{le}(D/H){sub {ital P}}{le}10.0{times}10{sup {minus}5} and ({sup 3}He/H){sub {ital P}}{le}2.6{times}10{sup {minus}5}. When combined with the predictions of standard big bang nucleosynthesis, these constraints lead to a 95{percent} C.L. bound on the primordial abundance deuterium: (D/H){sub best}=(3.5{sup +2.7}{sub {minus}1.8}){times}10{sup {minus}5}. Measurements of deuterium absorption in the spectra of high-redshift QSOs will directly test this prediction. The implications of this prediction for the primordial abundances of {sup 4}He and {sup 7}Li are discussed, as well as those for the universal density of baryons. {copyright} {ital 1996 The American Astronomical Society.}

  12. Disruption prediction at JET

    International Nuclear Information System (INIS)

    Milani, F.

    1998-12-01

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

  13. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

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

    2015-01-01

    to next generation. The main goal of this study was to see the potential of using genomic prediction in a commercial Barley breeding program. The data used in this study was from Nordic Seed company which is located in Denmark. Around 350 advanced lines were genotyped with 9K Barely chip from Illumina....... Traits used in this study were grain yield, plant height and heading date. Heading date is number days it takes after 1st June for plant to head. Heritabilities were 0.33, 0.44 and 0.48 for yield, height and heading, respectively for the average of nine plots. The GBLUP model was used for genomic...

  14. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  15. Predictable return distributions

    DEFF Research Database (Denmark)

    Pedersen, Thomas Quistgaard

    trace out the entire distribution. A univariate quantile regression model is used to examine stock and bond return distributions individually, while a multivariate model is used to capture their joint distribution. An empirical analysis on US data shows that certain parts of the return distributions......-of-sample analyses show that the relative accuracy of the state variables in predicting future returns varies across the distribution. A portfolio study shows that an investor with power utility can obtain economic gains by applying the empirical return distribution in portfolio decisions instead of imposing...

  16. Predicting Ground Illuminance

    Science.gov (United States)

    Lesniak, Michael V.; Tregoning, Brett D.; Hitchens, Alexandra E.

    2015-01-01

    Our Sun outputs 3.85 x 1026 W of radiation, of which roughly 37% is in the visible band. It is directly responsible for nearly all natural illuminance experienced on Earth's surface, either in the form of direct/refracted sunlight or in reflected light bouncing off the surfaces and/or atmospheres of our Moon and the visible planets. Ground illuminance, defined as the amount of visible light intercepting a unit area of surface (from all incident angles), varies over 7 orders of magnitude from day to night. It is highly dependent on well-modeled factors such as the relative positions of the Sun, Earth, and Moon. It is also dependent on less predictable factors such as local atmospheric conditions and weather.Several models have been proposed to predict ground illuminance, including Brown (1952) and Shapiro (1982, 1987). The Brown model is a set of empirical data collected from observation points around the world that has been reduced to a smooth fit of illuminance against a single variable, solar altitude. It provides limited applicability to the Moon and for cloudy conditions via multiplicative reduction factors. The Shapiro model is a theoretical model that treats the atmosphere as a three layer system of light reflectance and transmittance. It has different sets of reflectance and transmittance coefficients for various cloud types.In this paper we compare the models' predictions to ground illuminance data from an observing run at the White Sands missile range (data was obtained from the United Kingdom's Meteorology Office). Continuous illuminance readings were recorded under various cloud conditions, during both daytime and nighttime hours. We find that under clear skies, the Shapiro model tends to better fit the observations during daytime hours with typical discrepancies under 10%. Under cloudy skies, both models tend to poorly predict ground illuminance. However, the Shapiro model, with typical average daytime discrepancies of 25% or less in many cases

  17. Predicting sports betting outcomes

    OpenAIRE

    Flis, Borut

    2014-01-01

    We wish to build a model, which could predict the outcome of basketball games. The goal was to achieve an sufficient enough accuracy to make a profit in sports betting. One learning example is a game in the NBA regular season. Every example has multiple features, which describe the opposing teams. We tried many methods, which return the probability of the home team winning and the probability of the away team winning. These probabilities are used for risk analysis. We used the best model in h...

  18. Predicting chaotic time series

    International Nuclear Information System (INIS)

    Farmer, J.D.; Sidorowich, J.J.

    1987-01-01

    We present a forecasting technique for chaotic data. After embedding a time series in a state space using delay coordinates, we ''learn'' the induced nonlinear mapping using local approximation. This allows us to make short-term predictions of the future behavior of a time series, using information based only on past values. We present an error estimate for this technique, and demonstrate its effectiveness by applying it to several examples, including data from the Mackey-Glass delay differential equation, Rayleigh-Benard convection, and Taylor-Couette flow

  19. Lattice of quantum predictions

    Science.gov (United States)

    Drieschner, Michael

    1993-10-01

    What is the structure of reality? Physics is supposed to answer this question, but a purely empiristic view is not sufficient to explain its ability to do so. Quantum mechanics has forced us to think more deeply about what a physical theory is. There are preconditions every physical theory must fulfill. It has to contain, e.g., rules for empirically testable predictions. Those preconditions give physics a structure that is “a priori” in the Kantian sense. An example is given how the lattice structure of quantum mechanics can be understood along these lines.

  20. 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

  1. Prediction of regulatory elements

    DEFF Research Database (Denmark)

    Sandelin, Albin

    2008-01-01

    Finding the regulatory mechanisms responsible for gene expression remains one of the most important challenges for biomedical research. A major focus in cellular biology is to find functional transcription factor binding sites (TFBS) responsible for the regulation of a downstream gene. As wet......-lab methods are time consuming and expensive, it is not realistic to identify TFBS for all uncharacterized genes in the genome by purely experimental means. Computational methods aimed at predicting potential regulatory regions can increase the efficiency of wet-lab experiments significantly. Here, methods...

  2. Age and Stress Prediction

    Science.gov (United States)

    2000-01-01

    Genoa is a software product that predicts progressive aging and failure in a variety of materials. It is the result of a SBIR contract between the Glenn Research Center and Alpha Star Corporation. Genoa allows designers to determine if the materials they plan on applying to a structure are up to the task or if alternate materials should be considered. Genoa's two feature applications are its progressive failure simulations and its test verification. It allows for a reduction in inspection frequency, rapid design solutions, and manufacturing with low cost materials. It will benefit the aerospace, airline, and automotive industries, with future applications for other uses.

  3. Prediction of Biomolecular Complexes

    KAUST Repository

    Vangone, Anna

    2017-04-12

    Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexesBiomolecular complexes, introducing the concept of molecular dockingDocking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.

  4. Nuclear criticality predictability

    International Nuclear Information System (INIS)

    Briggs, J.B.

    1999-01-01

    As a result of lots of efforts, a large portion of the tedious and redundant research and processing of critical experiment data has been eliminated. The necessary step in criticality safety analyses of validating computer codes with benchmark critical data is greatly streamlined, and valuable criticality safety experimental data is preserved. Criticality safety personnel in 31 different countries are now using the 'International Handbook of Evaluated Criticality Safety Benchmark Experiments'. Much has been accomplished by the work of the ICSBEP. However, evaluation and documentation represents only one element of a successful Nuclear Criticality Safety Predictability Program and this element only exists as a separate entity, because this work was not completed in conjunction with the experimentation process. I believe; however, that the work of the ICSBEP has also served to unify the other elements of nuclear criticality predictability. All elements are interrelated, but for a time it seemed that communications between these elements was not adequate. The ICSBEP has highlighted gaps in data, has retrieved lost data, has helped to identify errors in cross section processing codes, and has helped bring the international criticality safety community together in a common cause as true friends and colleagues. It has been a privilege to associate with those who work so diligently to make the project a success. (J.P.N.)

  5. Ratchetting strain prediction

    International Nuclear Information System (INIS)

    Noban, Mohammad; Jahed, Hamid

    2007-01-01

    A time-efficient method for predicting ratchetting strain is proposed. The ratchetting strain at any cycle is determined by finding the ratchetting rate at only a few cycles. This determination is done by first defining the trajectory of the origin of stress in the deviatoric stress space and then incorporating this moving origin into a cyclic plasticity model. It is shown that at the beginning of the loading, the starting point of this trajectory coincides with the initial stress origin and approaches the mean stress, displaying a power-law relationship with the number of loading cycles. The method of obtaining this trajectory from a standard uniaxial asymmetric cyclic loading is presented. Ratchetting rates are calculated with the help of this trajectory and through the use of a constitutive cyclic plasticity model which incorporates deviatoric stresses and back stresses that are measured with respect to this moving frame. The proposed model is used to predict the ratchetting strain of two types of steels under single- and multi-step loadings. Results obtained agree well with the available experimental measurements

  6. Predicting space climate change

    Science.gov (United States)

    Balcerak, Ernie

    2011-10-01

    Galactic cosmic rays and solar energetic particles can be hazardous to humans in space, damage spacecraft and satellites, pose threats to aircraft electronics, and expose aircrew and passengers to radiation. A new study shows that these threats are likely to increase in coming years as the Sun approaches the end of the period of high solar activity known as “grand solar maximum,” which has persisted through the past several decades. High solar activity can help protect the Earth by repelling incoming galactic cosmic rays. Understanding the past record can help scientists predict future conditions. Barnard et al. analyzed a 9300-year record of galactic cosmic ray and solar activity based on cosmogenic isotopes in ice cores as well as on neutron monitor data. They used this to predict future variations in galactic cosmic ray flux, near-Earth interplanetary magnetic field, sunspot number, and probability of large solar energetic particle events. The researchers found that the risk of space weather radiation events will likely increase noticeably over the next century compared with recent decades and that lower solar activity will lead to increased galactic cosmic ray levels. (Geophysical Research Letters, doi:10.1029/2011GL048489, 2011)

  7. Prediction of Biomolecular Complexes

    KAUST Repository

    Vangone, Anna; Oliva, Romina; Cavallo, Luigi; Bonvin, Alexandre M. J. J.

    2017-01-01

    Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexesBiomolecular complexes, introducing the concept of molecular dockingDocking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.

  8. Energy Predictions 2011

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2010-10-15

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

  9. Energy Predictions 2011

    International Nuclear Information System (INIS)

    2010-10-01

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

  10. 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.

  11. Generalized Predictive Control and Neural Generalized Predictive Control

    Directory of Open Access Journals (Sweden)

    Sadhana CHIDRAWAR

    2008-12-01

    Full Text Available As Model Predictive Control (MPC relies on the predictive Control using a multilayer feed forward network as the plants linear model is presented. In using Newton-Raphson as the optimization algorithm, the number of iterations needed for convergence is significantly reduced from other techniques. This paper presents a detailed derivation of the Generalized Predictive Control and Neural Generalized Predictive Control with Newton-Raphson as minimization algorithm. Taking three separate systems, performances of the system has been tested. Simulation results show the effect of neural network on Generalized Predictive Control. The performance comparison of this three system configurations has been given in terms of ISE and IAE.

  12. Numerical prediction of rose growth

    NARCIS (Netherlands)

    Bernsen, E.; Bokhove, Onno; van der Sar, D.M.

    2006-01-01

    A new mathematical model is presented for the prediction of rose growth in a greenhouse. Given the measured ambient environmental conditions, the model consists of a local photosynthesis model, predicting the photosynthesis per unit leaf area, coupled to a global greenhouse model, which predicts the

  13. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation,...

  14. 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.

  15. Protein docking prediction using predicted protein-protein interface.

    Science.gov (United States)

    Li, Bin; Kihara, Daisuke

    2012-01-10

    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. 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. 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.

  16. Epitope prediction methods

    DEFF Research Database (Denmark)

    Karosiene, Edita

    Analysis. The chapter provides detailed explanations on how to use different methods for T cell epitope discovery research, explaining how input should be given as well as how to interpret the output. In the last chapter, I present the results of a bioinformatics analysis of epitopes from the yellow fever...... peptide-MHC interactions. Furthermore, using yellow fever virus epitopes, we demonstrated the power of the %Rank score when compared with the binding affinity score of MHC prediction methods, suggesting that this score should be considered to be used for selecting potential T cell epitopes. In summary...... 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...

  17. Motor degradation prediction methods

    Energy Technology Data Exchange (ETDEWEB)

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

    1996-12-01

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

  18. Filter replacement lifetime prediction

    Science.gov (United States)

    Hamann, Hendrik F.; Klein, Levente I.; Manzer, Dennis G.; Marianno, Fernando J.

    2017-10-25

    Methods and systems for predicting a filter lifetime include building a filter effectiveness history based on contaminant sensor information associated with a filter; determining a rate of filter consumption with a processor based on the filter effectiveness history; and determining a remaining filter lifetime based on the determined rate of filter consumption. Methods and systems for increasing filter economy include measuring contaminants in an internal and an external environment; determining a cost of a corrosion rate increase if unfiltered external air intake is increased for cooling; determining a cost of increased air pressure to filter external air; and if the cost of filtering external air exceeds the cost of the corrosion rate increase, increasing an intake of unfiltered external air.

  19. Neurological abnormalities predict disability

    DEFF Research Database (Denmark)

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

    2014-01-01

    To investigate the role of neurological abnormalities and magnetic resonance imaging (MRI) lesions in predicting global functional decline in a cohort of initially independent-living elderly subjects. The Leukoaraiosis And DISability (LADIS) Study, involving 11 European centres, was primarily aimed...... at evaluating age-related white matter changes (ARWMC) as an independent predictor of the transition to disability (according to Instrumental Activities of Daily Living scale) or death in independent elderly subjects that were followed up for 3 years. At baseline, a standardized neurological examination.......0 years, 45 % males), 327 (51.7 %) presented at the initial visit with ≥1 neurological abnormality and 242 (38 %) reached the main study outcome. Cox regression analyses, adjusting for MRI features and other determinants of functional decline, showed that the baseline presence of any neurological...

  20. Motor degradation prediction methods

    International Nuclear Information System (INIS)

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

    1996-01-01

    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

  1. Predictability in community dynamics.

    Science.gov (United States)

    Blonder, Benjamin; Moulton, Derek E; Blois, Jessica; Enquist, Brian J; Graae, Bente J; Macias-Fauria, Marc; McGill, Brian; Nogué, Sandra; Ordonez, Alejandro; Sandel, Brody; Svenning, Jens-Christian

    2017-03-01

    The coupling between community composition and climate change spans a gradient from no lags to strong lags. The no-lag hypothesis is the foundation of many ecophysiological models, correlative species distribution modelling and climate reconstruction approaches. Simple lag hypotheses have become prominent in disequilibrium ecology, proposing that communities track climate change following a fixed function or with a time delay. However, more complex dynamics are possible and may lead to memory effects and alternate unstable states. We develop graphical and analytic methods for assessing these scenarios and show that these dynamics can appear in even simple models. The overall implications are that (1) complex community dynamics may be common and (2) detailed knowledge of past climate change and community states will often be necessary yet sometimes insufficient to make predictions of a community's future state. © 2017 John Wiley & Sons Ltd/CNRS.

  2. Neonatal heart rate prediction.

    Science.gov (United States)

    Abdel-Rahman, Yumna; Jeremic, Aleksander; Tan, Kenneth

    2009-01-01

    Technological advances have caused a decrease in the number of infant deaths. Pre-term infants now have a substantially increased chance of survival. One of the mechanisms that is vital to saving the lives of these infants is continuous monitoring and early diagnosis. With continuous monitoring huge amounts of data are collected with so much information embedded in them. By using statistical analysis this information can be extracted and used to aid diagnosis and to understand development. In this study we have a large dataset containing over 180 pre-term infants whose heart rates were recorded over the length of their stay in the Neonatal Intensive Care Unit (NICU). We test two types of models, empirical bayesian and autoregressive moving average. We then attempt to predict future values. The autoregressive moving average model showed better results but required more computation.

  3. 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...... of depth and time, when both the surface chloride concentration and the diffusion coefficient are allowed to vary in time. The model is presented in a companion paper....

  4. Strontium 90 fallout prediction

    International Nuclear Information System (INIS)

    Sarmiento, J.L.; Gwinn, E.

    1986-01-01

    An empirical formula is developed for predicting monthly sea level strontium 90 fallout (F) in the northern hemisphere as a function of time (t), precipitation rate (P), latitude (phi), longitude (lambda), and the sea level concentration of stronium 90 in air (C): F(lambda, phi, t) = C(t, phi)[v /sub d/(phi) + v/sub w/(lambda, phi, t)], where v/sub w/(lambda, phi, t) = a(phi)[P(lambda, phi, t)/P/sub o/]/sup b//sup (//sup phi//sup )/ is the wet removal, v/sub d/(phi) is the dry removal and P 0 is 1 cm/month. The constants v/sub d/, a, and b are determined as functions of latitude by fitting land based observations. The concentration of 90 Sr in air is calculated as a function of the deseasonalized concentration at a reference latitude (C-bar/sub r//sub e//sub f/), the ratio of the observations at the latitude of interest to the reference latitude (R), and a function representing the seasonal trend in the air concentration (1 + g): C-bar(t, phi) = C/sub r//sub e//sub f/(t)R(phi)[1 + g(m, phi)]; m is the month. Zonal trends in C are shown to be relatively small. This formula can be used in conjuction with precipitation observations and/or estimates to predict fallout in the northern hemisphere for any month in the years 1954 to 1974. Error estimates are given; they do not include uncertainty due to errors in precipitation data

  5. Plume rise predictions

    International Nuclear Information System (INIS)

    Briggs, G.A.

    1976-01-01

    Anyone involved with diffusion calculations becomes well aware of the strong dependence of maximum ground concentrations on the effective stack height, h/sub e/. For most conditions chi/sub max/ is approximately proportional to h/sub e/ -2 , as has been recognized at least since 1936 (Bosanquet and Pearson). Making allowance for the gradual decrease in the ratio of vertical to lateral diffusion at increasing heights, the exponent is slightly larger, say chi/sub max/ approximately h/sub e/ - 2 . 3 . In inversion breakup fumigation, the exponent is somewhat smaller; very crudely, chi/sub max/ approximately h/sub e/ -1 . 5 . In any case, for an elevated emission the dependence of chi/sub max/ on h/sub e/ is substantial. It is postulated that a really clever ignorant theoretician can disguise his ignorance with dimensionless constants. For most sources the effective stack height is considerably larger than the actual source height, h/sub s/. For instance, for power plants with no downwash problems, h/sub e/ is more than twice h/sub s/ whenever the wind is less than 10 m/sec, which is most of the time. This is unfortunate for anyone who has to predict ground concentrations, for he is likely to have to calculate the plume rise, Δh. Especially when using h/sub e/ = h/sub s/ + Δh instead of h/sub s/ may reduce chi/sub max/ by a factor of anywhere from 4 to infinity. Factors to be considered in making plume rise predictions are discussed

  6. Predictive coarse-graining

    Energy Technology Data Exchange (ETDEWEB)

    Schöberl, Markus, E-mail: m.schoeberl@tum.de [Continuum Mechanics Group, Technical University of Munich, Boltzmannstraße 15, 85748 Garching (Germany); Zabaras, Nicholas [Institute for Advanced Study, Technical University of Munich, Lichtenbergstraße 2a, 85748 Garching (Germany); Department of Aerospace and Mechanical Engineering, University of Notre Dame, 365 Fitzpatrick Hall, Notre Dame, IN 46556 (United States); Koutsourelakis, Phaedon-Stelios [Continuum Mechanics Group, Technical University of Munich, Boltzmannstraße 15, 85748 Garching (Germany)

    2017-03-15

    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 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.

  7. 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.

  8. 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.

  9. Performance Prediction Toolkit

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-25

    The Performance Prediction Toolkit (PPT), is a scalable co-design tool that contains the hardware and middle-ware models, which accept proxy applications as input in runtime prediction. PPT relies on Simian, a parallel discrete event simulation engine in Python or Lua, that uses the process concept, where each computing unit (host, node, core) is a Simian entity. Processes perform their task through message exchanges to remain active, sleep, wake-up, begin and end. The PPT hardware model of a compute core (such as a Haswell core) consists of a set of parameters, such as clock speed, memory hierarchy levels, their respective sizes, cache-lines, access times for different cache levels, average cycle counts of ALU operations, etc. These parameters are ideally read off a spec sheet or are learned using regression models learned from hardware counters (PAPI) data. The compute core model offers an API to the software model, a function called time_compute(), which takes as input a tasklist. A tasklist is an unordered set of ALU, and other CPU-type operations (in particular virtual memory loads and stores). The PPT application model mimics the loop structure of the application and replaces the computational kernels with a call to the hardware model's time_compute() function giving tasklists as input that model the compute kernel. A PPT application model thus consists of tasklists representing kernels and the high-er level loop structure that we like to think of as pseudo code. The key challenge for the hardware model's time_compute-function is to translate virtual memory accesses into actual cache hierarchy level hits and misses.PPT also contains another CPU core level hardware model, Analytical Memory Model (AMM). The AMM solves this challenge soundly, where our previous alternatives explicitly include the L1,L2,L3 hit-rates as inputs to the tasklists. Explicit hit-rates inevitably only reflect the application modeler's best guess, perhaps informed by a few

  10. Introduction: Long term prediction

    International Nuclear Information System (INIS)

    Beranger, G.

    2003-01-01

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

  11. Predictability of blocking

    International Nuclear Information System (INIS)

    Tosi, E.; Ruti, P.; Tibaldi, S.; D'Andrea, F.

    1994-01-01

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

  12. GABA predicts visual intelligence.

    Science.gov (United States)

    Cook, Emily; Hammett, Stephen T; Larsson, Jonas

    2016-10-06

    Early psychological researchers proposed a link between intelligence and low-level perceptual performance. It was recently suggested that this link is driven by individual variations in the ability to suppress irrelevant information, evidenced by the observation of strong correlations between perceptual surround suppression and cognitive performance. However, the neural mechanisms underlying such a link remain unclear. A candidate mechanism is neural inhibition by gamma-aminobutyric acid (GABA), but direct experimental support for GABA-mediated inhibition underlying suppression is inconsistent. Here we report evidence consistent with a global suppressive mechanism involving GABA underlying the link between sensory performance and intelligence. We measured visual cortical GABA concentration, visuo-spatial intelligence and visual surround suppression in a group of healthy adults. Levels of GABA were strongly predictive of both intelligence and surround suppression, with higher levels of intelligence associated with higher levels of GABA and stronger surround suppression. These results indicate that GABA-mediated neural inhibition may be a key factor determining cognitive performance and suggests a physiological mechanism linking surround suppression and intelligence. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  13. Predictability in cellular automata.

    Science.gov (United States)

    Agapie, Alexandru; Andreica, Anca; Chira, Camelia; Giuclea, Marius

    2014-01-01

    Modelled as finite homogeneous Markov chains, probabilistic cellular automata with local transition probabilities in (0, 1) always posses a stationary distribution. This result alone is not very helpful when it comes to predicting the final configuration; one needs also a formula connecting the probabilities in the stationary distribution to some intrinsic feature of the lattice configuration. Previous results on the asynchronous cellular automata have showed that such feature really exists. It is the number of zero-one borders within the automaton's binary configuration. An exponential formula in the number of zero-one borders has been proved for the 1-D, 2-D and 3-D asynchronous automata with neighborhood three, five and seven, respectively. We perform computer experiments on a synchronous cellular automaton to check whether the empirical distribution obeys also that theoretical formula. The numerical results indicate a perfect fit for neighbourhood three and five, which opens the way for a rigorous proof of the formula in this new, synchronous case.

  14. Predictive Manufacturing: A Classification Strategy to Predict Product Failures

    DEFF Research Database (Denmark)

    Khan, Abdul Rauf; Schiøler, Henrik; Kulahci, Murat

    2018-01-01

    manufacturing analytics model that employs a big data approach to predicting product failures; third, we illustrate the issue of high dimensionality, along with statistically redundant information; and, finally, our proposed method will be compared against the well-known classification methods (SVM, K......-nearest neighbor, artificial neural networks). The results from real data show that our predictive manufacturing analytics approach, using genetic algorithms and Voronoi tessellations, is capable of predicting product failure with reasonable accuracy. The potential application of this method contributes...... to accurately predicting product failures, which would enable manufacturers to reduce production costs without compromising product quality....

  15. House Price Prediction Using LSTM

    OpenAIRE

    Chen, Xiaochen; Wei, Lai; Xu, Jiaxin

    2017-01-01

    In this paper, we use the house price data ranging from January 2004 to October 2016 to predict the average house price of November and December in 2016 for each district in Beijing, Shanghai, Guangzhou and Shenzhen. We apply Autoregressive Integrated Moving Average model to generate the baseline while LSTM networks to build prediction model. These algorithms are compared in terms of Mean Squared Error. The result shows that the LSTM model has excellent properties with respect to predict time...

  16. Long Range Aircraft Trajectory Prediction

    OpenAIRE

    Magister, Tone

    2009-01-01

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

  17. Review of Nearshore Morphologic Prediction

    Science.gov (United States)

    Plant, N. G.; Dalyander, S.; Long, J.

    2014-12-01

    The evolution of the world's erodible coastlines will determine the balance between the benefits and costs associated with human and ecological utilization of shores, beaches, dunes, barrier islands, wetlands, and estuaries. So, we would like to predict coastal evolution to guide management and planning of human and ecological response to coastal changes. After decades of research investment in data collection, theoretical and statistical analysis, and model development we have a number of empirical, statistical, and deterministic models that can predict the evolution of the shoreline, beaches, dunes, and wetlands over time scales of hours to decades, and even predict the evolution of geologic strata over the course of millennia. Comparisons of predictions to data have demonstrated that these models can have meaningful predictive skill. But these comparisons also highlight the deficiencies in fundamental understanding, formulations, or data that are responsible for prediction errors and uncertainty. Here, we review a subset of predictive models of the nearshore to illustrate tradeoffs in complexity, predictive skill, and sensitivity to input data and parameterization errors. We identify where future improvement in prediction skill will result from improved theoretical understanding, and data collection, and model-data assimilation.

  18. PREDICTED PERCENTAGE DISSATISFIED (PPD) MODEL ...

    African Journals Online (AJOL)

    HOD

    their low power requirements, are relatively cheap and are environment friendly. ... PREDICTED PERCENTAGE DISSATISFIED MODEL EVALUATION OF EVAPORATIVE COOLING ... The performance of direct evaporative coolers is a.

  19. Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

    NARCIS (Netherlands)

    Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

    2014-01-01

    In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

  20. 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].

  1. 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.

  2. Quadratic prediction of factor scores

    NARCIS (Netherlands)

    Wansbeek, T

    1999-01-01

    Factor scores are naturally predicted by means of their conditional expectation given the indicators y. Under normality this expectation is linear in y but in general it is an unknown function of y. II is discussed that under nonnormality factor scores can be more precisely predicted by a quadratic

  3. 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.

  4. Climate Prediction Center - Seasonal Outlook

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Forecast Discussion PROGNOSTIC DISCUSSION FOR MONTHLY OUTLOOK NWS CLIMATE PREDICTION CENTER COLLEGE PARK MD INFLUENCE ON THE MONTHLY-AVERAGED CLIMATE. OUR MID-MONTH ASSESSMENT OF LOW-FREQUENCY CLIMATE VARIABILITY IS

  5. Dividend Predictability Around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

    2014-01-01

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

  6. Dividend Predictability Around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schmeling, Maik; Schrimpf, Andreas

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

  7. Decadal climate prediction (project GCEP).

    Science.gov (United States)

    Haines, Keith; Hermanson, Leon; Liu, Chunlei; Putt, Debbie; Sutton, Rowan; Iwi, Alan; Smith, Doug

    2009-03-13

    Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.

  8. Prediction during natural language comprehension

    NARCIS (Netherlands)

    Willems, R.M.; Frank, S.L.; Nijhof, A.D.; Hagoort, P.; Bosch, A.P.J. van den

    2016-01-01

    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

  9. Reliability of windstorm predictions in the ECMWF ensemble prediction system

    Science.gov (United States)

    Becker, Nico; Ulbrich, Uwe

    2016-04-01

    Windstorms caused by extratropical cyclones are one of the most dangerous natural hazards in the European region. Therefore, reliable predictions of such storm events are needed. Case studies have shown that ensemble prediction systems (EPS) are able to provide useful information about windstorms between two and five days prior to the event. In this work, ensemble predictions with the European Centre for Medium-Range Weather Forecasts (ECMWF) EPS are evaluated in a four year period. Within the 50 ensemble members, which are initialized every 12 hours and are run for 10 days, windstorms are identified and tracked in time and space. By using a clustering approach, different predictions of the same storm are identified in the different ensemble members and compared to reanalysis data. The occurrence probability of the predicted storms is estimated by fitting a bivariate normal distribution to the storm track positions. Our results show, for example, that predicted storm clusters with occurrence probabilities of more than 50% have a matching observed storm in 80% of all cases at a lead time of two days. The predicted occurrence probabilities are reliable up to 3 days lead time. At longer lead times the occurrence probabilities are overestimated by the EPS.

  10. Psychometric prediction of penitentiary recidivism.

    Science.gov (United States)

    Medina García, Pedro M; Baños Rivera, Rosa M

    2016-05-01

    Attempts to predict prison recidivism based on the personality have not been very successful. This study aims to provide data on recidivism prediction based on the scores on a personality questionnaire. For this purpose, a predictive model combining the actuarial procedure with a posteriori probability was developed, consisting of the probabilistic calculation of the effective verification of the event once it has already occurred. Cuestionario de Personalidad Situacional (CPS; Fernández, Seisdedos, & Mielgo, 1998) was applied to 978 male inmates classified as recidivists or non-recidivists. High predictive power was achieved, with the area under the curve (AUC) of 0.85 (p <.001; Se = 0.012; 95% CI [0.826, 0.873]. The answers to the CPS items made it possible to properly discriminate 77.3% of the participants. These data indicate the important role of the personality as a key factor in understanding delinquency and predicting recidivism.

  11. Predictive Biomarkers for Asthma Therapy.

    Science.gov (United States)

    Medrek, Sarah K; Parulekar, Amit D; Hanania, Nicola A

    2017-09-19

    Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma. Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.

  12. Are abrupt climate changes predictable?

    Science.gov (United States)

    Ditlevsen, Peter

    2013-04-01

    It is taken for granted that the limited predictability in the initial value problem, the weather prediction, and the predictability of the statistics are two distinct problems. Lorenz (1975) dubbed this predictability of the first and the second kind respectively. Predictability of the first kind in a chaotic dynamical system is limited due to the well-known critical dependence on initial conditions. Predictability of the second kind is possible in an ergodic system, where either the dynamics is known and the phase space attractor can be characterized by simulation or the system can be observed for such long times that the statistics can be obtained from temporal averaging, assuming that the attractor does not change in time. For the climate system the distinction between predictability of the first and the second kind is fuzzy. This difficulty in distinction between predictability of the first and of the second kind is related to the lack of scale separation between fast and slow components of the climate system. The non-linear nature of the problem furthermore opens the possibility of multiple attractors, or multiple quasi-steady states. As the ice-core records show, the climate has been jumping between different quasi-stationary climates, stadials and interstadials through the Dansgaard-Oechger events. Such a jump happens very fast when a critical tipping point has been reached. The question is: Can such a tipping point be predicted? This is a new kind of predictability: the third kind. If the tipping point is reached through a bifurcation, where the stability of the system is governed by some control parameter, changing in a predictable way to a critical value, the tipping is predictable. If the sudden jump occurs because internal chaotic fluctuations, noise, push the system across a barrier, the tipping is as unpredictable as the triggering noise. In order to hint at an answer to this question, a careful analysis of the high temporal resolution NGRIP isotope

  13. 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. © 2014 Wiley Periodicals, Inc.

  14. Earthquake prediction by Kina Method

    International Nuclear Information System (INIS)

    Kianoosh, H.; Keypour, H.; Naderzadeh, A.; Motlagh, H.F.

    2005-01-01

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

  15. Collective motion of predictive swarms.

    Directory of Open Access Journals (Sweden)

    Nathaniel Rupprecht

    Full Text Available Theoretical models of populations and swarms typically start with the assumption that the motion of agents is governed by the local stimuli. However, an intelligent agent, with some understanding of the laws that govern its habitat, can anticipate the future, and make predictions to gather resources more efficiently. Here we study a specific model of this kind, where agents aim to maximize their consumption of a diffusing resource, by attempting to predict the future of a resource field and the actions of other agents. Once the agents make a prediction, they are attracted to move towards regions that have, and will have, denser resources. We find that the further the agents attempt to see into the future, the more their attempts at prediction fail, and the less resources they consume. We also study the case where predictive agents compete against non-predictive agents and find the predictors perform better than the non-predictors only when their relative numbers are very small. We conclude that predictivity pays off either when the predictors do not see too far into the future or the number of predictors is small.

  16. Dividend Predictability Around the World

    DEFF Research Database (Denmark)

    Rangvid, Jesper; Schrimpf, Andreas

    The common perception in the literature, mainly based on U.S. data, is that current dividend yields are uninformative about future dividends. We show that this nding changes substantially when looking at a broad international panel of countries, as aggregate dividend growth rates are found...... that in countries where the quality of institutions is high, dividend predictability is weaker. These ndings indicate that the apparent lack of dividend predictability in the U.S. does not, in general, extend to other countries. Rather, dividend predictability is driven by cross-country dierences in rm...

  17. 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

  18. Practical aspects of geological prediction

    International Nuclear Information System (INIS)

    Mallio, W.J.; Peck, J.H.

    1981-01-01

    Nuclear waste disposal requires that geology be a predictive science. The prediction of future events rests on (1) recognizing the periodicity of geologic events; (2) defining a critical dimension of effect, such as the area of a drainage basin, the length of a fault trace, etc; and (3) using our understanding of active processes the project the frequency and magnitude of future events in the light of geological principles. Of importance to nuclear waste disposal are longer term processes such as continental denudation and removal of materials by glacial erosion. Constant testing of projections will allow the practical limits of predicting geological events to be defined. 11 refs

  19. 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

  20. Predicting emergency diesel starting performance

    International Nuclear Information System (INIS)

    DeBey, T.M.

    1989-01-01

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

  1. Predictive Models and Computational Embryology

    Science.gov (United States)

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

  2. Fatigue life prediction in composites

    CSIR Research Space (South Africa)

    Huston, RJ

    1994-01-01

    Full Text Available Because of the relatively large number of possible failure mechanisms in fibre reinforced composite materials, the prediction of fatigue life in a component is not a simple process. Several mathematical and statistical models have been proposed...

  3. 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.

  4. 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...... the coefficient vectors from each subset should be weighted. It is not computationally feasible to calculate the mean subset coefficient vector for larger problems, and thus we suggest an algorithm to find an approximation to the mean subset coefficient vector. In a comprehensive Monte Carlo simulation study...

  5. EPRI MOV performance prediction program

    International Nuclear Information System (INIS)

    Hosler, J.F.; Damerell, P.S.; Eidson, M.G.; Estep, N.E.

    1994-01-01

    An overview of the EPRI Motor-Operated Valve (MOV) Performance Prediction Program is presented. The objectives of this Program are to better understand the factors affecting the performance of MOVs and to develop and validate methodologies to predict MOV performance. The Program involves valve analytical modeling, separate-effects testing to refine the models, and flow-loop and in-plant MOV testing to provide a basis for model validation. The ultimate product of the Program is an MOV Performance Prediction Methodology applicable to common gate, globe, and butterfly valves. The methodology predicts thrust and torque requirements at design-basis flow and differential pressure conditions, assesses the potential for gate valve internal damage, and provides test methods to quantify potential for gate valve internal damage, and provides test methods to quantify potential variations in actuator output thrust with loading condition. Key findings and their potential impact on MOV design and engineering application are summarized

  6. In silico prediction of genotoxicity.

    Science.gov (United States)

    Wichard, Jörg D

    2017-08-01

    The in silico prediction of genotoxicity has made considerable progress during the last years. The main driver for the pharmaceutical industry is the ICH M7 guideline about the assessment of DNA reactive impurities. An important component of this guideline is the use of in silico models as an alternative approach to experimental testing. The in silico prediction of genotoxicity provides an established and accepted method that defines the first step in the assessment of DNA reactive impurities. This was made possible by the growing amount of reliable Ames screening data, the attempts to understand the activity pathways and the subsequent development of computer-based prediction systems. This paper gives an overview of how the in silico prediction of genotoxicity is performed under the ICH M7 guideline. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. New Tool to Predict Glaucoma

    Science.gov (United States)

    ... In This Section A New Tool to Predict Glaucoma email Send this article to a friend by ... Close Send Thanks for emailing that article! Tweet Glaucoma can be difficult to detect and diagnose. Measurement ...

  8. Dynamical Predictability of Monthly Means.

    Science.gov (United States)

    Shukla, J.

    1981-12-01

    We have attempted to determine the theoretical upper limit of dynamical predictability of monthly means for prescribed nonfluctuating external forcings. We have extended the concept of `classical' predictability, which primarily refers to the lack of predictability due mainly to the instabilities of synoptic-scale disturbances, to the predictability of time averages, which are determined by the predictability of low-frequency planetary waves. We have carded out 60-day integrations of a global general circulation model with nine different initial conditions but identical boundary conditions of sea surface temperature, snow, sea ice and soil moisture. Three of these initial conditions are the observed atmospheric conditions on 1 January of 1975, 1976 and 1977. The other six initial conditions are obtained by superimposing over the observed initial conditions a random perturbation comparable to the errors of observation. The root-mean-square (rms) error of random perturbations at all the grid points and all the model levels is 3 m s1 in u and v components of wind. The rms vector wind error between the observed initial conditions is >15 m s1.It is hypothesized that for a given averaging period, if the rms error among the time averages predicted from largely different initial conditions becomes comparable to the rms error among the time averages predicted from randomly perturbed initial conditions, the time averages are dynamically unpredictable. We have carried out the analysis of variance to compare the variability, among the three groups, due to largely different initial conditions, and within each group due to random perturbations.It is found that the variances among the first 30-day means, predicted from largely different initial conditions, are significantly different from the variances due to random perturbations in the initial conditions, whereas the variances among 30-day means for days 31-60 are not distinguishable from the variances due to random initial

  9. Predictive coding in Agency Detection

    DEFF Research Database (Denmark)

    Andersen, Marc Malmdorf

    2017-01-01

    Agency detection is a central concept in the cognitive science of religion (CSR). Experimental studies, however, have so far failed to lend support to some of the most common predictions that follow from current theories on agency detection. In this article, I argue that predictive coding, a highly...... promising new framework for understanding perception and action, may solve pending theoretical inconsistencies in agency detection research, account for the puzzling experimental findings mentioned above, and provide hypotheses for future experimental testing. Predictive coding explains how the brain......, unbeknownst to consciousness, engages in sophisticated Bayesian statistics in an effort to constantly predict the hidden causes of sensory input. My fundamental argument is that most false positives in agency detection can be seen as the result of top-down interference in a Bayesian system generating high...

  10. Time-predictable Stack Caching

    DEFF Research Database (Denmark)

    Abbaspourseyedi, Sahar

    completely. Thus, in systems with hard deadlines the worst-case execution time (WCET) of the real-time software running on them needs to be bounded. Modern architectures use features such as pipelining and caches for improving the average performance. These features, however, make the WCET analysis more...... addresses, provides an opportunity to predict and tighten the WCET of accesses to data in caches. In this thesis, we introduce the time-predictable stack cache design and implementation within a time-predictable processor. We introduce several optimizations to our design for tightening the WCET while...... keeping the timepredictability of the design intact. Moreover, we provide a solution for reducing the cost of context switching in a system using the stack cache. In design of these caches, we use custom hardware and compiler support for delivering time-predictable stack data accesses. Furthermore...

  11. NASA/MSFC prediction techniques

    International Nuclear Information System (INIS)

    Smith, R.E.

    1987-01-01

    The NASA/MSFC method of forecasting is more formal than NOAA's. The data are smoothed by the Lagrangian method and linear regression prediction techniques are used. The solar activity period is fixed at 11 years--the mean period of all previous cycles. Interestingly, the present prediction for the time of the next solar minimum is February or March of 1987, which, within the uncertainties of two methods, can be taken to be the same as the NOAA result

  12. Prediction of molecular crystal structures

    International Nuclear Information System (INIS)

    Beyer, Theresa

    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 paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol -1 of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

  13. Does Carbon Dioxide Predict Temperature?

    OpenAIRE

    Mytty, Tuukka

    2013-01-01

    Does carbon dioxide predict temperature? No it does not, in the time period of 1880-2004 with the carbon dioxide and temperature data used in this thesis. According to the Inter Governmental Panel on Climate Change(IPCC) carbon dioxide is the most important factor in raising the global temperature. Therefore, it is reasonable to assume that carbon dioxide truly predicts temperature. Because this paper uses observational data it has to be kept in mind that no causality interpretation can be ma...

  14. 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

  15. Prediction of interannual climate variations

    International Nuclear Information System (INIS)

    Shukla, J.

    1993-01-01

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

  16. Postprocessing for Air Quality Predictions

    Science.gov (United States)

    Delle Monache, L.

    2017-12-01

    In recent year, air quality (AQ) forecasting has made significant progress towards better predictions with the goal of protecting the public from harmful pollutants. This progress is the results of improvements in weather and chemical transport models, their coupling, and more accurate emission inventories (e.g., with the development of new algorithms to account in near real-time for fires). Nevertheless, AQ predictions are still affected at times by significant biases which stem from limitations in both weather and chemistry transport models. Those are the result of numerical approximations and the poor representation (and understanding) of important physical and chemical process. Moreover, although the quality of emission inventories has been significantly improved, they are still one of the main sources of uncertainties in AQ predictions. For operational real-time AQ forecasting, a significant portion of these biases can be reduced with the implementation of postprocessing methods. We will review some of the techniques that have been proposed to reduce both systematic and random errors of AQ predictions, and improve the correlation between predictions and observations of ground-level ozone and surface particulate matter less than 2.5 µm in diameter (PM2.5). These methods, which can be applied to both deterministic and probabilistic predictions, include simple bias-correction techniques, corrections inspired by the Kalman filter, regression methods, and the more recently developed analog-based algorithms. These approaches will be compared and contrasted, and strength and weaknesses of each will be discussed.

  17. Predictive value of diminutive colonic adenoma trial: the PREDICT trial.

    Science.gov (United States)

    Schoenfeld, Philip; Shad, Javaid; Ormseth, Eric; Coyle, Walter; Cash, Brooks; Butler, James; Schindler, William; Kikendall, Walter J; Furlong, Christopher; Sobin, Leslie H; Hobbs, Christine M; Cruess, David; Rex, Douglas

    2003-05-01

    Diminutive adenomas (1-9 mm in diameter) are frequently found during colon cancer screening with flexible sigmoidoscopy (FS). This trial assessed the predictive value of these diminutive adenomas for advanced adenomas in the proximal colon. In a multicenter, prospective cohort trial, we matched 200 patients with normal FS and 200 patients with diminutive adenomas on FS for age and gender. All patients underwent colonoscopy. The presence of advanced adenomas (adenoma >or= 10 mm in diameter, villous adenoma, adenoma with high grade dysplasia, and colon cancer) and adenomas (any size) was recorded. Before colonoscopy, patients completed questionnaires about risk factors for adenomas. The prevalence of advanced adenomas in the proximal colon was similar in patients with diminutive adenomas and patients with normal FS (6% vs. 5.5%, respectively) (relative risk, 1.1; 95% confidence interval [CI], 0.5-2.6). Diminutive adenomas on FS did not accurately predict advanced adenomas in the proximal colon: sensitivity, 52% (95% CI, 32%-72%); specificity, 50% (95% CI, 49%-51%); positive predictive value, 6% (95% CI, 4%-8%); and negative predictive value, 95% (95% CI, 92%-97%). Male gender (odds ratio, 1.63; 95% CI, 1.01-2.61) was associated with an increased risk of proximal colon adenomas. Diminutive adenomas on sigmoidoscopy may not accurately predict advanced adenomas in the proximal colon.

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

    Science.gov (United States)

    Heydari, Sepideh; Holroyd, Clay B

    2016-08-01

    The reward positivity is a component of the human ERP elicited by feedback stimuli in trial-and-error learning and guessing tasks. A prominent theory holds that the reward positivity reflects a reward prediction error signal that is sensitive to outcome valence, being larger for unexpected positive events relative to unexpected negative events (Holroyd & Coles, 2002). Although the theory has found substantial empirical support, most of these studies have utilized either monetary or performance feedback to test the hypothesis. However, in apparent contradiction to the theory, a recent study found that unexpected physical punishments also elicit the reward positivity (Talmi, Atkinson, & El-Deredy, 2013). The authors of this report argued that the reward positivity reflects a salience prediction error rather than a reward prediction error. To investigate this finding further, in the present study participants navigated a virtual T maze and received feedback on each trial under two conditions. In a reward condition, the feedback indicated that they would either receive a monetary reward or not and in a punishment condition the feedback indicated that they would receive a small shock or not. We found that the feedback stimuli elicited a typical reward positivity in the reward condition and an apparently delayed reward positivity in the punishment condition. Importantly, this signal was more positive to the stimuli that predicted the omission of a possible punishment relative to stimuli that predicted a forthcoming punishment, which is inconsistent with the salience hypothesis. © 2016 Society for Psychophysiological Research.

  19. Climate Prediction - NOAA's National Weather Service

    Science.gov (United States)

    Statistical Models... MOS Prod GFS-LAMP Prod Climate Past Weather Predictions Weather Safety Weather Radio National Weather Service on FaceBook NWS on Facebook NWS Director Home > Climate > Predictions Climate Prediction Long range forecasts across the U.S. Climate Prediction Web Sites Climate Prediction

  20. Weighted-Average Least Squares Prediction

    NARCIS (Netherlands)

    Magnus, Jan R.; Wang, Wendun; Zhang, Xinyu

    2016-01-01

    Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty from the

  1. Potential Predictability and Prediction Skill for Southern Peru Summertime Rainfall

    Science.gov (United States)

    WU, S.; Notaro, M.; Vavrus, S. J.; Mortensen, E.; Block, P. J.; Montgomery, R. J.; De Pierola, J. N.; Sanchez, C.

    2016-12-01

    The central Andes receive over 50% of annual climatological rainfall during the short period of January-March. This summertime rainfall exhibits strong interannual and decadal variability, including severe drought events that incur devastating societal impacts and cause agricultural communities and mining facilities to compete for limited water resources. An improved seasonal prediction skill of summertime rainfall would aid in water resource planning and allocation across the water-limited southern Peru. While various underlying mechanisms have been proposed by past studies for the drivers of interannual variability in summertime rainfall across southern Peru, such as the El Niño-Southern Oscillation (ENSO), Madden Julian Oscillation (MJO), and extratropical forcings, operational forecasts continue to be largely based on rudimentary ENSO-based indices, such as NINO3.4, justifying further exploration of predictive skill. In order to bridge this gap between the understanding of driving mechanisms and the operational forecast, we performed systematic studies on the predictability and prediction skill of southern Peru summertime rainfall by constructing statistical forecast models using best available weather station and reanalysis datasets. At first, by assuming the first two empirical orthogonal functions (EOFs) of summertime rainfall are predictable, the potential predictability skill was evaluated for southern Peru. Then, we constructed a simple regression model, based on the time series of tropical Pacific sea-surface temperatures (SSTs), and a more advanced Linear Inverse Model (LIM), based on the EOFs of tropical ocean SSTs and large-scale atmosphere variables from reanalysis. Our results show that the LIM model consistently outperforms the more rudimentary regression models on the forecast skill of domain averaged precipitation index and individual station indices. The improvement of forecast correlation skill ranges from 10% to over 200% for different

  2. Prediction of GNSS satellite clocks

    International Nuclear Information System (INIS)

    Broederbauer, V.

    2010-01-01

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

  3. Geophysical Anomalies and Earthquake Prediction

    Science.gov (United States)

    Jackson, D. D.

    2008-12-01

    Finding anomalies is easy. Predicting earthquakes convincingly from such anomalies is far from easy. Why? Why have so many beautiful geophysical abnormalities not led to successful prediction strategies? What is earthquake prediction? By my definition it is convincing information that an earthquake of specified size is temporarily much more likely than usual in a specific region for a specified time interval. We know a lot about normal earthquake behavior, including locations where earthquake rates are higher than elsewhere, with estimable rates and size distributions. We know that earthquakes have power law size distributions over large areas, that they cluster in time and space, and that aftershocks follow with power-law dependence on time. These relationships justify prudent protective measures and scientific investigation. Earthquake prediction would justify exceptional temporary measures well beyond those normal prudent actions. Convincing earthquake prediction would result from methods that have demonstrated many successes with few false alarms. Predicting earthquakes convincingly is difficult for several profound reasons. First, earthquakes start in tiny volumes at inaccessible depth. The power law size dependence means that tiny unobservable ones are frequent almost everywhere and occasionally grow to larger size. Thus prediction of important earthquakes is not about nucleation, but about identifying the conditions for growth. Second, earthquakes are complex. They derive their energy from stress, which is perniciously hard to estimate or model because it is nearly singular at the margins of cracks and faults. Physical properties vary from place to place, so the preparatory processes certainly vary as well. Thus establishing the needed track record for validation is very difficult, especially for large events with immense interval times in any one location. Third, the anomalies are generally complex as well. Electromagnetic anomalies in particular require

  4. 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

  5. Neural Elements for Predictive Coding.

    Science.gov (United States)

    Shipp, Stewart

    2016-01-01

    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 backward 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 forward and backward 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 possible by transgenic neural

  6. Quantifying prognosis with risk predictions.

    Science.gov (United States)

    Pace, Nathan L; Eberhart, Leopold H J; Kranke, Peter R

    2012-01-01

    Prognosis is a forecast, based on present observations in a patient, of their probable outcome from disease, surgery and so on. Research methods for the development of risk probabilities may not be familiar to some anaesthesiologists. We briefly describe methods for identifying risk factors and risk scores. A probability prediction rule assigns a risk probability to a patient for the occurrence of a specific event. Probability reflects the continuum between absolute certainty (Pi = 1) and certified impossibility (Pi = 0). Biomarkers and clinical covariates that modify risk are known as risk factors. The Pi as modified by risk factors can be estimated by identifying the risk factors and their weighting; these are usually obtained by stepwise logistic regression. The accuracy of probabilistic predictors can be separated into the concepts of 'overall performance', 'discrimination' and 'calibration'. Overall performance is the mathematical distance between predictions and outcomes. Discrimination is the ability of the predictor to rank order observations with different outcomes. Calibration is the correctness of prediction probabilities on an absolute scale. Statistical methods include the Brier score, coefficient of determination (Nagelkerke R2), C-statistic and regression calibration. External validation is the comparison of the actual outcomes to the predicted outcomes in a new and independent patient sample. External validation uses the statistical methods of overall performance, discrimination and calibration and is uniformly recommended before acceptance of the prediction model. Evidence from randomised controlled clinical trials should be obtained to show the effectiveness of risk scores for altering patient management and patient outcomes.

  7. PREDICTING DEMAND FOR COTTON YARNS

    Directory of Open Access Journals (Sweden)

    SALAS-MOLINA Francisco

    2017-05-01

    Full Text Available Predicting demand for fashion products is crucial for textile manufacturers. In an attempt to both avoid out-of-stocks and minimize holding costs, different forecasting techniques are used by production managers. Both linear and non-linear time-series analysis techniques are suitable options for forecasting purposes. However, demand for fashion products presents a number of particular characteristics such as short life-cycles, short selling seasons, high impulse purchasing, high volatility, low predictability, tremendous product variety and a high number of stock-keeping-units. In this paper, we focus on predicting demand for cotton yarns using a non-linear forecasting technique that has been fruitfully used in many areas, namely, random forests. To this end, we first identify a number of explanatory variables to be used as a key input to forecasting using random forests. We consider explanatory variables usually labeled either as causal variables, when some correlation is expected between them and the forecasted variable, or as time-series features, when extracted from time-related attributes such as seasonality. Next, we evaluate the predictive power of each variable by means of out-of-sample accuracy measurement. We experiment on a real data set from a textile company in Spain. The numerical results show that simple time-series features present more predictive ability than other more sophisticated explanatory variables.

  8. Lightning prediction using radiosonde data

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-07-01

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

  9. 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...... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...... seen as necessary in order to identify aggregate level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds...

  10. 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.

  11. Predictive Modeling in Race Walking

    Directory of Open Access Journals (Sweden)

    Krzysztof Wiktorowicz

    2015-01-01

    Full Text Available This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers’ training events and they are used to predict the result over a 3 km race based on training loads. The material consists of 122 training plans for 21 athletes. In order to choose the best model leave-one-out cross-validation method is used. The main contribution of the paper is to propose the nonlinear modifications for linear models in order to achieve smaller prediction error. It is shown that the best model is a modified LASSO regression with quadratic terms in the nonlinear part. This model has the smallest prediction error and simplified structure by eliminating some of the predictors.

  12. 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.

  13. BBN predictions for 4He

    International Nuclear Information System (INIS)

    Walker, T.P.

    1993-01-01

    The standard model of the hot big bang assumes a homogeneous and isotropic Universe with gravity described by General Relativity and strong and electroweak interactions described by the Standard Model of particle physics. The hot big bang model makes the unavoidable prediction that the production of primordial elements occurred about one minute after the big band (referred to as big bang or primordial nucleosynthesis BBN). This review concerns the range of the primordial abundance of 4 He as predicted by standard BBN (i.e., primordial nucleosynthesis assuming a homogeneous distribution of baryons). In it the author discusses: (1) Uncertainties in the calculation of Y p (the mass fraction of primordial 4 He), (2) The expected range of Y p , (3) How the predictions stack up against the latest observations, and (4) The latest BBN bounds on Ω B h 2 and N ν . 13 refs., 2 figs

  14. Human motion simulation predictive dynamics

    CERN Document Server

    Abdel-Malek, Karim

    2013-01-01

    Simulate realistic human motion in a virtual world with an optimization-based approach to motion prediction. With this approach, motion is governed by human performance measures, such as speed and energy, which act as objective functions to be optimized. Constraints on joint torques and angles are imposed quite easily. Predicting motion in this way allows one to use avatars to study how and why humans move the way they do, given specific scenarios. It also enables avatars to react to infinitely many scenarios with substantial autonomy. With this approach it is possible to predict dynamic motion without having to integrate equations of motion -- rather than solving equations of motion, this approach solves for a continuous time-dependent curve characterizing joint variables (also called joint profiles) for every degree of freedom. Introduces rigorous mathematical methods for digital human modelling and simulation Focuses on understanding and representing spatial relationships (3D) of biomechanics Develops an i...

  15. Model predictive control using fuzzy decision functions

    NARCIS (Netherlands)

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  16. Evaluating the Predictive Value of Growth Prediction Models

    Science.gov (United States)

    Murphy, Daniel L.; Gaertner, Matthew N.

    2014-01-01

    This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

  17. Ensemble method for dengue prediction.

    Science.gov (United States)

    Buczak, Anna L; Baugher, Benjamin; Moniz, Linda J; Bagley, Thomas; Babin, Steven M; Guven, Erhan

    2018-01-01

    In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

  18. Evoked emotions predict food choice.

    Science.gov (United States)

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

    2014-01-01

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

  19. Ensemble method for dengue prediction.

    Directory of Open Access Journals (Sweden)

    Anna L Buczak

    Full Text Available In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico during four dengue seasons: 1 peak height (i.e., maximum weekly number of cases during a transmission season; 2 peak week (i.e., week in which the maximum weekly number of cases occurred; and 3 total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date.Our approach used ensemble models created by combining three disparate types of component models: 1 two-dimensional Method of Analogues models incorporating both dengue and climate data; 2 additive seasonal Holt-Winters models with and without wavelet smoothing; and 3 simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations.Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week.The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

  20. 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.

  1. Calorimetry end-point predictions

    International Nuclear Information System (INIS)

    Fox, M.A.

    1981-01-01

    This paper describes a portion of the work presently in progress at Rocky Flats in the field of calorimetry. In particular, calorimetry end-point predictions are outlined. The problems associated with end-point predictions and the progress made in overcoming these obstacles are discussed. The two major problems, noise and an accurate description of the heat function, are dealt with to obtain the most accurate results. Data are taken from an actual calorimeter and are processed by means of three different noise reduction techniques. The processed data are then utilized by one to four algorithms, depending on the accuracy desired to determined the end-point

  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. Can we predict nuclear proliferation

    International Nuclear Information System (INIS)

    Tertrais, Bruno

    2011-01-01

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

  4. 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...

  5. The Challenge of Weather Prediction

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 3. The Challenge of Weather Prediction Old and Modern Ways of Weather Forecasting. B N Goswami. Series Article Volume 2 Issue 3 March 1997 pp 8-15. Fulltext. Click here to view fulltext PDF. Permanent link:

  6. Predictability of weather and climate

    National Research Council Canada - National Science Library

    Palmer, Tim; Hagedorn, Renate

    2006-01-01

    ... and anthropogenic climate change are among those included. Ensemble systems for forecasting predictability are discussed extensively. Ed Lorenz, father of chaos theory, makes a contribution to theoretical analysis with a previously unpublished paper. This well-balanced volume will be a valuable resource for many years. High-quality chapter autho...

  7. Evaluation of environmental impact predictions

    International Nuclear Information System (INIS)

    Cunningham, P.A.; Adams, S.M.; Kumar, K.D.

    1977-01-01

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

  8. Using Predictability for Lexical Segmentation.

    Science.gov (United States)

    Çöltekin, Çağrı

    2017-09-01

    This study investigates a strategy based on predictability of consecutive sub-lexical units in learning to segment a continuous speech stream into lexical units using computational modeling and simulations. Lexical segmentation is one of the early challenges during language acquisition, and it has been studied extensively through psycholinguistic experiments as well as computational methods. However, despite strong empirical evidence, the explicit use of predictability of basic sub-lexical units in models of segmentation is underexplored. This paper presents an incremental computational model of lexical segmentation for exploring the usefulness of predictability for lexical segmentation. We show that the predictability cue is a strong cue for segmentation. Contrary to earlier reports in the literature, the strategy yields state-of-the-art segmentation performance with an incremental computational model that uses only this particular cue in a cognitively plausible setting. The paper also reports an in-depth analysis of the model, investigating the conditions affecting the usefulness of the strategy. Copyright © 2016 Cognitive Science Society, Inc.

  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. Predicting response to epigenetic therapy

    DEFF Research Database (Denmark)

    Treppendahl, Marianne B; Sommer Kristensen, Lasse; Grønbæk, Kirsten

    2014-01-01

    of good pretreatment predictors of response is of great value. Many clinical parameters and molecular targets have been tested in preclinical and clinical studies with varying results, leaving room for optimization. Here we provide an overview of markers that may predict the efficacy of FDA- and EMA...

  11. 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

  12. Prediction of electric vehicle penetration.

    Science.gov (United States)

    2017-05-01

    The object of this report is to present the current market status of plug-in-electric : vehicles (PEVs) and to predict their future penetration within the world and U.S. : markets. The sales values for 2016 show a strong year of PEV sales both in the...

  13. Evoked Emotions Predict Food Choice

    NARCIS (Netherlands)

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

    2014-01-01

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

  14. Framework for Traffic Congestion Prediction

    NARCIS (Netherlands)

    Zaki, J.F.W.; Ali-Eldin, A.M.T.; Hussein, S.E.; Saraya, S.F.; Areed, F.F.

    2016-01-01

    Traffic Congestion is a complex dilemma facing most major cities. It has undergone a lot of research since the early 80s in an attempt to predict traffic in the short-term. Recently, Intelligent Transportation Systems (ITS) became an integral part of traffic research which helped in modeling and

  15. Predicting Character Traits Through Reddit

    Science.gov (United States)

    2015-01-01

    and even employers (Res). Companies like Netflix also use personality classification algorithms in order to provide users with predictions of movies...science behind the netflix algorithms that decide what to watch next, August 2013. Reza Zafarani and Huan Liu. Evaluation without ground truth in social media research. Communications Of The ACM, 58(6):54–60, June 2015. 12

  16. Prediction of natural gas consumption

    International Nuclear Information System (INIS)

    Zhang, R.L.; Walton, D.J.; Hoskins, W.D.

    1993-01-01

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

  17. Prediction of Subsidence Depression Development

    Czech Academy of Sciences Publication Activity Database

    Doležalová, Hana; Kajzar, Vlastimil

    2017-01-01

    Roč. 6, č. 4 (2017), s. 208-214 E-ISSN 2391-9361. [Cross-border Exchange of Experience in Production Engineering Using Principles of Mathematics. Rybnik, 07.06.2017-09.06.2017] Institutional support: RVO:68145535 Keywords : undermining * prediction * regression analysis Subject RIV: DH - Mining, incl. Coal Mining OBOR OECD: Mining and mineral processing

  18. 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

  19. Climate Prediction Center - monthly Outlook

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Outlooks monthly Climate Outlooks Banner OFFICIAL Forecasts June 2018 [UPDATED MONTHLY FORECASTS SERVICE ) Canonical Correlation Analysis ECCA - Ensemble Canonical Correlation Analysis Optimal Climate Normals

  20. Climate Prediction Center - Site Index

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Means Bulletins Annual Winter Stratospheric Ozone Climate Diagnostics Bulletin (Most Recent) Climate (Hazards Outlook) Climate Assessment: Dec. 1999-Feb. 2000 (Seasonal) Climate Assessment: Mar-May 2000

  1. 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.

  2. 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…

  3. A prediction for bubbling geometries

    OpenAIRE

    Okuda, Takuya

    2007-01-01

    We study the supersymmetric circular Wilson loops in N=4 Yang-Mills theory. Their vacuum expectation values are computed in the parameter region that admits smooth bubbling geometry duals. The results are a prediction for the supergravity action evaluated on the bubbling geometries for Wilson loops.

  4. 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.

  5. 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 ...

  6. 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...... 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.......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...

  7. Numerical prediction of slamming loads

    DEFF Research Database (Denmark)

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

    2012-01-01

    It is important to include the contribution of the slamming-induced response in the structural design of large vessels with a significant bow flare. At the same time it is a challenge to develop rational tools to determine the slamming-induced loads and the prediction of their occurrence. Today i...

  8. Predictive models of moth development

    Science.gov (United States)

    Degree-day models link ambient temperature to insect life-stages, making such models valuable tools in integrated pest management. These models increase management efficacy by predicting pest phenology. In Wisconsin, the top insect pest of cranberry production is the cranberry fruitworm, Acrobasis v...

  9. 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.

  10. 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

  11. HUMAN DECISIONS AND MACHINE PREDICTIONS.

    Science.gov (United States)

    Kleinberg, Jon; Lakkaraju, Himabindu; Leskovec, Jure; Ludwig, Jens; Mullainathan, Sendhil

    2018-02-01

    Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the variable the algorithm predicts; for instance, judges may care specifically about violent crimes or about racial inequities. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: one policy simulation shows crime reductions up to 24.7% with no change in jailing rates, or jailing rate reductions up to 41.9% with no increase in crime rates. Moreover, all categories of crime, including violent crimes, show reductions; and these gains can be achieved while simultaneously reducing racial disparities. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals. JEL Codes: C10 (Econometric and statistical methods and methodology), C55 (Large datasets: Modeling and analysis), K40 (Legal procedure, the legal system, and illegal behavior).

  12. Ocean eddies and climate predictability.

    Science.gov (United States)

    Kirtman, Ben P; Perlin, Natalie; Siqueira, Leo

    2017-12-01

    A suite of coupled climate model simulations and experiments are used to examine how resolved mesoscale ocean features affect aspects of climate variability, air-sea interactions, and predictability. In combination with control simulations, experiments with the interactive ensemble coupling strategy are used to further amplify the role of the oceanic mesoscale field and the associated air-sea feedbacks and predictability. The basic intent of the interactive ensemble coupling strategy is to reduce the atmospheric noise at the air-sea interface, allowing an assessment of how noise affects the variability, and in this case, it is also used to diagnose predictability from the perspective of signal-to-noise ratios. The climate variability is assessed from the perspective of sea surface temperature (SST) variance ratios, and it is shown that, unsurprisingly, mesoscale variability significantly increases SST variance. Perhaps surprising is the fact that the presence of mesoscale ocean features even further enhances the SST variance in the interactive ensemble simulation beyond what would be expected from simple linear arguments. Changes in the air-sea coupling between simulations are assessed using pointwise convective rainfall-SST and convective rainfall-SST tendency correlations and again emphasize how the oceanic mesoscale alters the local association between convective rainfall and SST. Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability. We use the interactive ensemble simulations to diagnose this relationship, and we find that the presence of mesoscale ocean features significantly enhances this link particularly in ocean eddy rich regions. Finally, we use signal-to-noise ratios to show that the ocean mesoscale activity increases model estimated predictability in terms of convective precipitation and atmospheric upper tropospheric circulation.

  13. Predicting steam generator crevice chemistry

    International Nuclear Information System (INIS)

    Burton, G.; Strati, G.

    2006-01-01

    'Full text:' Corrosion of steam cycle components produces insoluble material, mostly iron oxides, that are transported to the steam generator (SG) via the feedwater and deposited on internal surfaces such as the tubes, tube support plates and the tubesheet. The build up of these corrosion products over time can lead to regions of restricted flow with water chemistry that may be significantly different, and potentially more corrosive to SG tube material, than the bulk steam generator water chemistry. The aim of the present work is to predict SG crevice chemistry using experimentation and modelling as part of AECL's overall strategy for steam generator life management. Hideout-return experiments are performed under CANDU steam generator conditions to assess the accumulation of impurities in hideout, and return from, model crevices. The results are used to validate the ChemSolv model that predicts steam generator crevice impurity concentrations, and high temperature pH, based on process parameters (e.g., heat flux, primary side temperature) and blowdown water chemistry. The model has been incorporated into ChemAND, AECL's system health monitoring software for chemistry monitoring, analysis and diagnostics that has been installed at two domestic and one international CANDU station. ChemAND provides the station chemists with the only method to predict SG crevice chemistry. In one recent application, the software has been used to evaluate the crevice chemistry based on the elevated, but balanced, SG bulk water impurity concentrations present during reactor startup, in order to reduce hold times. The present paper will describe recent hideout-return experiments that are used for the validation of the ChemSolv model, station experience using the software, and improvements to predict the crevice electrochemical potential that will permit station staff to ensure that the SG tubes are in the 'safe operating zone' predicted by Lu (AECL). (author)

  14. Predicting outcome of status epilepticus.

    Science.gov (United States)

    Leitinger, M; Kalss, G; Rohracher, A; Pilz, G; Novak, H; Höfler, J; Deak, I; Kuchukhidze, G; Dobesberger, J; Wakonig, A; Trinka, E

    2015-08-01

    Status epilepticus (SE) is a frequent neurological emergency complicated by high mortality and often poor functional outcome in survivors. The aim of this study was to review available clinical scores to predict outcome. Literature review. PubMed Search terms were "score", "outcome", and "status epilepticus" (April 9th 2015). Publications with abstracts available in English, no other language restrictions, or any restrictions concerning investigated patients were included. Two scores were identified: "Status Epilepticus Severity Score--STESS" and "Epidemiology based Mortality score in SE--EMSE". A comprehensive comparison of test parameters concerning performance, options, and limitations was performed. Epidemiology based Mortality score in SE allows detailed individualization of risk factors and is significantly superior to STESS in a retrospective explorative study. In particular, EMSE is very good at detection of good and bad outcome, whereas STESS detecting bad outcome is limited by a ceiling effect and uncertainty of correct cutoff value. Epidemiology based Mortality score in SE can be adapted to different regions in the world and to advances in medicine, as new data emerge. In addition, we designed a reporting standard for status epilepticus to enhance acquisition and communication of outcome relevant data. A data acquisition sheet used from patient admission in emergency room, from the EEG lab to intensive care unit, is provided for optimized data collection. Status Epilepticus Severity Score is easy to perform and predicts bad outcome, but has a low predictive value for good outcomes. Epidemiology based Mortality score in SE is superior to STESS in predicting good or bad outcome but needs marginally more time to perform. Epidemiology based Mortality score in SE may prove very useful for risk stratification in interventional studies and is recommended for individual outcome prediction. Prospective validation in different cohorts is needed for EMSE, whereas

  15. 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

  16. Branch prediction in the pentium family

    DEFF Research Database (Denmark)

    Fog, Agner

    1998-01-01

    How the branch prediction mechanism in the Pentium has been uncovered with all its quirks, and the incredibly more effective branch prediction in the later versions.......How the branch prediction mechanism in the Pentium has been uncovered with all its quirks, and the incredibly more effective branch prediction in the later versions....

  17. 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...

  18. Semen analysis and prediction of natural conception

    NARCIS (Netherlands)

    Leushuis, Esther; van der Steeg, Jan Willem; Steures, Pieternel; Repping, Sjoerd; Bossuyt, Patrick M. M.; Mol, Ben Willem J.; Hompes, Peter G. A.; van der Veen, Fulco

    2014-01-01

    Do two semen analyses predict natural conception better than a single semen analysis and will adding the results of repeated semen analyses to a prediction model for natural pregnancy improve predictions? A second semen analysis does not add helpful information for predicting natural conception

  19. PI 3-kinase signalling in platelets: the significance of synergistic, autocrine stimulation.

    Science.gov (United States)

    Selheim, F; Holmsen, H; Vassbotn, F S

    2000-03-01

    Phosphoinositide 3-kinases (PI 3Ks) play a key role in regulation of intracellular signalling and cellular function, including cell proliferation, apoptosis, chemotaxis, membrane trafficking and platelet activation. The PI 3Ks are grouped into three classes on the basis on their structure and in vitro substrate specificity. Class I are activated by a variety of agonists which mediate their effect through tyrosine kinase-linked or G-protein-linked receptors. In vivo class I PI 3Ks seem to preferentially phosphorylate the D3 hydroxyls of the inositol moiety of PtdIns(4,5)P2 to produce PtdIns(3,4,5)P3. However, class II PI 3Ks preferentially phosphorylate the D3 hydroxyl of PtdIns and PtdIns(4)P to produce PtdIns(3)P and PtdIns(3,4)P2, respectively. The late accumulation of PtdIns(3,4)P2 has been suggested to play an important role in irreversible platelet aggregation. In human platelets the class II PI 3K isoform HsC2-PI 3K is activated in an integrin alpha IIb beta 3 + fibrinogen-dependent manner. Class III PI 3Ks phosphorylate PtdIns to produce PtdIns(3)P, which play a crucial role in vesicular trafficking. Recent work has suggested that crosstalk between individual receptors and their downstream signal pathways play a central role in PI 3K signalling responses. In this review, we will concentrate on recent advances regarding the regulation of platelet PI 3Ks.

  20. PMA Induces SnoN Proteolysis and CD61 Expression through an Autocrine Mechanism

    Science.gov (United States)

    Li, Chonghua; Peart, Natoya; Xuan, Zhenyu; Lewis, Dorothy E; Xia, Yang; Jin, Jianping

    2014-01-01

    Phorbol-12-myristate-13-acetate, also called PMA, is a small molecule that activates protein kinase C and functions to differentiate hematologic lineage cells. However, the mechanism of PMA-induced cellular differentiation is not fully understood. We found that PMA triggers global enhancement of protein ubiquitination in K562, a myelogenous leukemia cell line and one of the enhanced-ubiquitination targets is SnoN, an inhibitor of the Smad signaling pathway. Our data indicated that PMA stimulated the production of Activin A, a cytokine of the TGF-β family. Activin A then activated the phosphorylation of both Smad2 and Smad3. In consequence, SnoN is ubiquitinated by the APCCdh1 ubiquitin ligase with the help of phosphorylated Smad2. Furthermore, we found that SnoN proteolysis is important for the expression of CD61, a marker of megakaryocyte. These results indicate that protein ubiquitination promotes megakaryopoiesis via degrading SnoN, an inhibitor of CD61 expression, strengths the roles of ubiquitination in cellular differentiation. PMID:24637302

  1. Ace inhibitors and cardiovascular regulation : the importance of autocrine and paracrine mechanisms

    NARCIS (Netherlands)

    Wijngaarden, Jan van

    1992-01-01

    As demonstrated in a large number of clinical studies, angiotensin converting enzyme (ACE) inhibitors are of great value for the treatment of cardiovascular disorders. Although the clinical merits of these drugs are now well recognized, their mechanism of action is not yet completely understood. The

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    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...

  3. The Functional Effect of an Amphiregulin Autocrine Loop on Inflammatory Breast Cancer Progression

    Science.gov (United States)

    2008-03-01

    Darby canine kidney cells (15). Also, using targeted knockout mice, Luetteke et al. reported that specific loss of AR, but not EGF or TGF-a, severely...due to relocalization of E-cadherin in Madin-Darby canine kidney cells (15). Our laboratory has also discovered that AR signaling differs from EGF...growth factor induction of matrix metalloproteinases and their inhibitors in osteosarcoma cells is modulated by the metastasis associated protein CAPL

  4. Autocrine IGF-1 Action in Adipocytes Controls Systemic IGF-1 Concentrations and Growth

    OpenAIRE

    Kl?ting, Nora; Koch, Linda; Wunderlich, Thomas; Kern, Matthias; Ruschke, Karen; Krone, Wilhelm; Br?ning, Jens C.; Bl?her, Matthias

    2008-01-01

    OBJECTIVE?IGF-1 and the IGF-1 receptor (IGF-1R) have been implicated in the regulation of adipocyte differentiation and lipid accumulation in vitro. RESEARCH DESIGN AND METHODS?To investigate the role of IGF-1 receptor in vivo, we have inactivated the Igf-1r gene in adipose tissue (IGF-1RaP2Cre mice) using conditional gene targeting strategies. RESULTS?Conditional IGF-1R inactivation resulted in increased adipose tissue mass with a predominantly increased lipid accumulation in epigonadal fat ...

  5. Alpha-tocopheryl succinate inhibits malignant mesothelioma by disrupting the fibroblast growth factor autocrine loop

    Czech Academy of Sciences Publication Activity Database

    Stapelberg, M.; Gellert, N.; Swettenham, E.; Tomasetti, M.; Witting, P. K.; Procopio, A.; Neužil, Jiří

    2005-01-01

    Roč. 280, č. 27 (2005), s. 25369-25376 ISSN 0021-9258 Institutional research plan: CEZ:AV0Z50520514 Keywords : alpha-tocopheryl succinate * malignant mesothelioma * fibroblast growth factor Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 5.854, year: 2005

  6. Secreted glyceraldehye-3-phosphate dehydrogenase is a multifunctional autocrine transferrin receptor for cellular iron acquisition.

    Science.gov (United States)

    Sheokand, Navdeep; Kumar, Santosh; Malhotra, Himanshu; Tillu, Vikas; Raje, Chaaya Iyengar; Raje, Manoj

    2013-06-01

    The long held view is that mammalian cells obtain transferrin (Tf) bound iron utilizing specialized membrane anchored receptors. Here we report that, during increased iron demand, cells secrete the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) which enhances cellular uptake of Tf and iron. These observations could be mimicked by utilizing purified GAPDH injected into mice as well as when supplemented in culture medium of model cell lines and primary cell types that play a key role in iron metabolism. Transferrin and iron delivery was evaluated by biochemical, biophysical and imaging based assays. This mode of iron uptake is a saturable, energy dependent pathway, utilizing raft as well as non-raft domains of the cell membrane and also involves the membrane protein CD87 (uPAR). Tf internalized by this mode is also catabolized. Our research demonstrates that, even in cell types that express the known surface receptor based mechanism for transferrin uptake, more transferrin is delivered by this route which represents a hidden dimension of iron homeostasis. Iron is an essential trace metal for practically all living organisms however its acquisition presents major challenges. The current paradigm is that living organisms have developed well orchestrated and evolved mechanisms involving iron carrier molecules and their specific receptors to regulate its absorption, transport, storage and mobilization. Our research uncovers a hidden and primitive pathway of bulk iron trafficking involving a secreted receptor that is a multifunctional glycolytic enzyme that has implications in pathological conditions such as infectious diseases and cancer. Copyright © 2013 Elsevier B.V. All rights reserved.

  7. Both Autocrine Signaling and Paracrine Signaling of HB-EGF Enhance Ocular Neovascularization.

    Science.gov (United States)

    Inoue, Yuki; Shimazawa, Masamitsu; Nakamura, Shinsuke; Takata, Shinsuke; Hashimoto, Yuhei; Izawa, Hiroshi; Masuda, Tomomi; Tsuruma, Kazuhiro; Sakaue, Tomohisa; Nakayama, Hironao; Higashiyama, Shigeki; Hara, Hideaki

    2018-01-01

    The incidence of blindness is increasing because of the increase in abnormal ocular neovascularization. Anti-VEGF (vascular endothelial growth factor) therapies have led to good results, although they are not a cure for the blindness. The purpose of this study was to determine what role HB-EGF (heparin-binding epidermal growth factor-like growth factor) plays in ocular angiogenesis. We examined the role played by HB-EGF in ocular neovascularization in 2 animal models of neovascularization: laser-induced choroidal neovascularization (CNV) and oxygen-induced retinopathy. We also studied human retinal microvascular endothelial cells in culture. Our results showed that the neovascularization was decreased in both the CNV and oxygen-induced retinopathy models in HB-EGF conditional knockout mice compared with that in wild-type mice. Moreover, the expressions of HB-EGF and VEGF were increased after laser-induced CNV and oxygen-induced retinopathy, and their expression sites were located around the neovascular areas. Exposure of human retinal microvascular endothelial cells to HB-EGF and VEGF increased their proliferation and migration, and CRM-197 (cross-reactive material-197), an HB-EGF inhibitor, decreased the HB-EGF-induced and VEGF-induced cell proliferation and migration. VEGF increased the expression of HB-EGF mRNA. VEGF-dependent activation of EGFR (epidermal growth factor receptor)/ERK1/2 (extracellular signal-regulated kinase 1/2) signaling and cell proliferation of endothelial cells required stimulation of the ADAM17 (a disintegrin and metalloprotease) and ADAM12. CRM-197 decreased the grades of the fluorescein angiograms and size of the CNV areas in marmoset monkeys. These findings suggest that HB-EGF plays an important role in the development of CNV. Therefore, further investigations of HB-EGF are needed as a potential therapeutic target in the treatment of exudative age-related macular degeneration. © 2017 American Heart Association, Inc.

  8. Autocrine and Paracrine Control of Breast Cancer Growth by Sex Hormone-Binding Globulin

    National Research Council Canada - National Science Library

    Rosner, Wiliam

    2003-01-01

    We propose that the expression of Sex Hormone-Binding Globulin (SHBG) by breast cancer cells is biologically regulated and that this SHBG functions to alter the effects of estrogens within the breast cancer cell...

  9. 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...

  10. 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.

  11. Prediction of dislocation boundary characteristics

    DEFF Research Database (Denmark)

    Winther, Grethe

    Plastic deformation of both fcc and bcc metals of medium to high stacking fault energy is known to result in dislocation patterning in the form of cells and extended planar dislocation boundaries. The latter align with specific crystallographic planes, which depend on the crystallographic......) and it is found that to a large extent the dislocations screen each other’s elastic stress fields [3]. The present contribution aims at advancing the previous theoretical analysis of a boundary on a known crystallographic plane to actual prediction of this plane as well as other boundary characteristics....... Crystal plasticity calculations combined with the hypothesis that these boundaries separate domains with local differences in the slip system activity are introduced to address precise prediction of the experimentally observed boundaries. The presentation will focus on two cases from fcc metals...

  12. 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.

  13. [Predictive factors of anxiety disorders].

    Science.gov (United States)

    Domschke, K

    2014-10-01

    Anxiety disorders are among the most frequent mental disorders in Europe (12-month prevalence 14%) and impose a high socioeconomic burden. The pathogenesis of anxiety disorders is complex with an interaction of biological, environmental and psychosocial factors contributing to the overall disease risk (diathesis-stress model). In this article, risk factors for anxiety disorders will be presented on several levels, e.g. genetic factors, environmental factors, gene-environment interactions, epigenetic mechanisms, neuronal networks ("brain fear circuit"), psychophysiological factors (e.g. startle response and CO2 sensitivity) and dimensional/subclinical phenotypes of anxiety (e.g. anxiety sensitivity and behavioral inhibition), and critically discussed regarding their potential predictive value. The identification of factors predictive of anxiety disorders will possibly allow for effective preventive measures or early treatment interventions, respectively, and reduce the individual patient's suffering as well as the overall socioeconomic burden of anxiety disorders.

  14. 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...

  15. Antipredator defenses predict diversification rates

    Science.gov (United States)

    Arbuckle, Kevin; Speed, Michael P.

    2015-01-01

    The “escape-and-radiate” hypothesis predicts that antipredator defenses facilitate adaptive radiations by enabling escape from constraints of predation, diversified habitat use, and subsequently speciation. Animals have evolved diverse strategies to reduce the direct costs of predation, including cryptic coloration and behavior, chemical defenses, mimicry, and advertisement of unprofitability (conspicuous warning coloration). Whereas the survival consequences of these alternative defenses for individuals are well-studied, little attention has been given to the macroevolutionary consequences of alternative forms of defense. Here we show, using amphibians as the first, to our knowledge, large-scale empirical test in animals, that there are important macroevolutionary consequences of alternative defenses. However, the escape-and-radiate hypothesis does not adequately describe them, due to its exclusive focus on speciation. We examined how rates of speciation and extinction vary across defensive traits throughout amphibians. Lineages that use chemical defenses show higher rates of speciation as predicted by escape-and-radiate but also show higher rates of extinction compared with those without chemical defense. The effect of chemical defense is a net reduction in diversification compared with lineages without chemical defense. In contrast, acquisition of conspicuous coloration (often used as warning signals or in mimicry) is associated with heightened speciation rates but unchanged extinction rates. We conclude that predictions based on the escape-and-radiate hypothesis must incorporate the effect of traits on both speciation and extinction, which is rarely considered in such studies. Our results also suggest that knowledge of defensive traits could have a bearing on the predictability of extinction, perhaps especially important in globally threatened taxa such as amphibians. PMID:26483488

  16. Nonparametric predictive inference in reliability

    International Nuclear Information System (INIS)

    Coolen, F.P.A.; Coolen-Schrijner, P.; Yan, K.J.

    2002-01-01

    We introduce a recently developed statistical approach, called nonparametric predictive inference (NPI), to reliability. Bounds for the survival function for a future observation are presented. We illustrate how NPI can deal with right-censored data, and discuss aspects of competing risks. We present possible applications of NPI for Bernoulli data, and we briefly outline applications of NPI for replacement decisions. The emphasis is on introduction and illustration of NPI in reliability contexts, detailed mathematical justifications are presented elsewhere

  17. Shoulder Dystocia: Prediction and Management

    OpenAIRE

    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.

  18. 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.

  19. Black holes, singularities and predictability

    International Nuclear Information System (INIS)

    Wald, R.M.

    1984-01-01

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

  20. Rainfall prediction with backpropagation method

    Science.gov (United States)

    Wahyuni, E. G.; Fauzan, L. M. F.; Abriyani, F.; Muchlis, N. F.; Ulfa, M.

    2018-03-01

    Rainfall is an important factor in many fields, such as aviation and agriculture. Although it has been assisted by technology but the accuracy can not reach 100% and there is still the possibility of error. Though current rainfall prediction information is needed in various fields, such as agriculture and aviation fields. In the field of agriculture, to obtain abundant and quality yields, farmers are very dependent on weather conditions, especially rainfall. Rainfall is one of the factors that affect the safety of aircraft. To overcome the problems above, then it’s required a system that can accurately predict rainfall. In predicting rainfall, artificial neural network modeling is applied in this research. The method used in modeling this artificial neural network is backpropagation method. Backpropagation methods can result in better performance in repetitive exercises. This means that the weight of the ANN interconnection can approach the weight it should be. Another advantage of this method is the ability in the learning process adaptively and multilayer owned on this method there is a process of weight changes so as to minimize error (fault tolerance). Therefore, this method can guarantee good system resilience and consistently work well. The network is designed using 4 input variables, namely air temperature, air humidity, wind speed, and sunshine duration and 3 output variables ie low rainfall, medium rainfall, and high rainfall. Based on the research that has been done, the network can be used properly, as evidenced by the results of the prediction of the system precipitation is the same as the results of manual calculations.

  1. The Clinical Prediction of Dangerousness.

    Science.gov (United States)

    1985-05-01

    8217 8 ings. Szasz (1963) has argued persuasively that clinical predictions of future dangerous behavior are unfairly focused on the mentally ill...Persons labeled paranoid, Szasz states, are readily commitable, while highly dangerous drunken drivers are not. Indeed, dangerousness such as that...Psychology, 31, 492-494. Szasz , T. (1963). Law, liberty and psychiatry. New York: Macmillan. Taft, R. (1955). The ability to judge people. Psychological

  2. 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].

  3. 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...... 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....

  4. Butterfly valve torque prediction methodology

    International Nuclear Information System (INIS)

    Eldiwany, B.H.; Sharma, V.; Kalsi, M.S.; Wolfe, K.

    1994-01-01

    As part of the Motor-Operated Valve (MOV) Performance Prediction Program, the Electric Power Research Institute has sponsored the development of methodologies for predicting thrust and torque requirements of gate, globe, and butterfly MOVs. This paper presents the methodology that will be used by utilities to calculate the dynamic torque requirements for butterfly valves. The total dynamic torque at any disc position is the sum of the hydrodynamic torque, bearing torque (which is induced by the hydrodynamic force), as well as other small torque components (such as packing torque). The hydrodynamic torque on the valve disc, caused by the fluid flow through the valve, depends on the disc angle, flow velocity, upstream flow disturbances, disc shape, and the disc aspect ratio. The butterfly valve model provides sets of nondimensional flow and torque coefficients that can be used to predict flow rate and hydrodynamic torque throughout the disc stroke and to calculate the required actuation torque and the maximum transmitted torque throughout the opening and closing stroke. The scope of the model includes symmetric and nonsymmetric discs of different shapes and aspects ratios in compressible and incompressible fluid applications under both choked and nonchoked flow conditions. The model features were validated against test data from a comprehensive flowloop and in situ test program. These tests were designed to systematically address the effect of the following parameters on the required torque: valve size, disc shapes and disc aspect ratios, upstream elbow orientation and its proximity, and flow conditions. The applicability of the nondimensional coefficients to valves of different sizes was validated by performing tests on 42-in. valve and a precisely scaled 6-in. model. The butterfly valve model torque predictions were found to bound test data from the flow-loop and in situ testing, as shown in the examples provided in this paper

  5. Prediction of future asset prices

    Science.gov (United States)

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

    2014-12-01

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

  6. Evoked Emotions Predict Food Choice

    OpenAIRE

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

    2014-01-01

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

  7. Predictive Analytics in Information Systems Research

    OpenAIRE

    Shmueli, Galit; 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 well as methods for assessing predictive power. Predictive analytics not only assist in creating practically useful models, they also play an important role alongside explanatory modeling in theory bu...

  8. Seizure Prediction and its Applications

    Science.gov (United States)

    Iasemidis, Leon D.

    2011-01-01

    Epilepsy is characterized by intermittent, paroxysmal, hypersynchronous electrical activity, that may remain localized and/or spread and severely disrupt the brain’s normal multi-task and multi-processing function. Epileptic seizures are the hallmarks of such activity and had been considered unpredictable. It is only recently that research on the dynamics of seizure generation by analysis of the brain’s electrographic activity (EEG) has shed ample light on the predictability of seizures, and illuminated the way to automatic, prospective, long-term prediction of seizures. The ability to issue warnings in real time of impending seizures (e.g., tens of minutes prior to seizure occurrence in the case of focal epilepsy), may lead to novel diagnostic tools and treatments for epilepsy. Applications may range from a simple warning to the patient, in order to avert seizure-associated injuries, to intervention by automatic timely administration of an appropriate stimulus, for example of a chemical nature like an anti-epileptic drug (AED), electromagnetic nature like vagus nerve stimulation (VNS), deep brain stimulation (DBS), transcranial direct current (TDC) or transcranial magnetic stimulation (TMS), and/or of another nature (e.g., ultrasonic, cryogenic, biofeedback operant conditioning). It is thus expected that seizure prediction could readily become an integral part of the treatment of epilepsy through neuromodulation, especially in the new generation of closed-loop seizure control systems. PMID:21939848

  9. 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. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  10. Prediction of Chevrel superconducting phases

    International Nuclear Information System (INIS)

    Savitskij, E.M.; Kiseleva, N.N.

    1978-01-01

    Made is an attempt of predicting the possibility of formation of compounds of Mo 3 Se 4 type structure having critical temperatures of transition into superconducting state more than 4.2 K. Cybernetic method of teaching an electronic computer to form notions is used for prediction. Prediction system constructs logic dependence of forming Chevrel superconducting phase of the Asub(x)Bsub(6)Ssub(8) composition (A being an element of the periodic system; B=Cr, Mo, W, Re) and Asub(x)Bsub(6)Ssub(8) compounds having a critical temperature of more than 4.2 K on the properties of A and B elements. A conclusion is made that W, Re, Cr do not form Chevrel phases of the Asub(x)Bsub(6)Ssub(8) composition as B component. Be, Hg, Ra, B, Ac are the reserve for obtaining Asub(x)Mosub(6)Ssub(8) phases. Agsub(x)Mosub(6)Ssub(8) compound may have a high critical temperature. The ways of a critical temperature increase for Chevrel phases are connected with the search of optimal technological conditions for already known superconducting compounds and also with introduction of impurities fixing a distance between sulfur cubes

  11. Childhood asthma-predictive phenotype.

    Science.gov (United States)

    Guilbert, Theresa W; Mauger, David T; Lemanske, Robert F

    2014-01-01

    Wheezing is a fairly common symptom in early childhood, but only some of these toddlers will experience continued wheezing symptoms in later childhood. The definition of the asthma-predictive phenotype is in children with frequent, recurrent wheezing in early life who have risk factors associated with the continuation of asthma symptoms in later life. Several asthma-predictive phenotypes were developed retrospectively based on large, longitudinal cohort studies; however, it can be difficult to differentiate these phenotypes clinically as the expression of symptoms, and risk factors can change with time. Genetic, environmental, developmental, and host factors and their interactions may contribute to the development, severity, and persistence of the asthma phenotype over time. Key characteristics that distinguish the childhood asthma-predictive phenotype include the following: male sex; a history of wheezing, with lower respiratory tract infections; history of parental asthma; history of atopic dermatitis; eosinophilia; early sensitization to food or aeroallergens; or lower lung function in early life. Copyright © 2014 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  12. Global predictability of temperature extremes

    Science.gov (United States)

    Coughlan de Perez, Erin; van Aalst, Maarten; Bischiniotis, Konstantinos; Mason, Simon; Nissan, Hannah; Pappenberger, Florian; Stephens, Elisabeth; Zsoter, Ervin; van den Hurk, Bart

    2018-05-01

    Extreme temperatures are one of the leading causes of death and disease in both developed and developing countries, and heat extremes are projected to rise in many regions. To reduce risk, heatwave plans and cold weather plans have been effectively implemented around the world. However, much of the world’s population is not yet protected by such systems, including many data-scarce but also highly vulnerable regions. In this study, we assess at a global level where such systems have the potential to be effective at reducing risk from temperature extremes, characterizing (1) long-term average occurrence of heatwaves and coldwaves, (2) seasonality of these extremes, and (3) short-term predictability of these extreme events three to ten days in advance. Using both the NOAA and ECMWF weather forecast models, we develop global maps indicating a first approximation of the locations that are likely to benefit from the development of seasonal preparedness plans and/or short-term early warning systems for extreme temperature. The extratropics generally show both short-term skill as well as strong seasonality; in the tropics, most locations do also demonstrate one or both. In fact, almost 5 billion people live in regions that have seasonality and predictability of heatwaves and/or coldwaves. Climate adaptation investments in these regions can take advantage of seasonality and predictability to reduce risks to vulnerable populations.

  13. 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.

  14. Predicting mortality from human faces.

    Science.gov (United States)

    Dykiert, Dominika; Bates, Timothy C; Gow, Alan J; Penke, Lars; Starr, John M; Deary, Ian J

    2012-01-01

    To investigate whether and to what extent mortality is predictable from facial photographs of older people. High-quality facial photographs of 292 members of the Lothian Birth Cohort 1921, taken at the age of about 83 years, were rated in terms of apparent age, health, attractiveness, facial symmetry, intelligence, and well-being by 12 young-adult raters. Cox proportional hazards regression was used to study associations between these ratings and mortality during a 7-year follow-up period. All ratings had adequate reliability. Concurrent validity was found for facial symmetry and intelligence (as determined by correlations with actual measures of fluctuating asymmetry in the faces and Raven Standard Progressive Matrices score, respectively), but not for the other traits. Age as rated from facial photographs, adjusted for sex and chronological age, was a significant predictor of mortality (hazard ratio = 1.36, 95% confidence interval = 1.12-1.65) and remained significant even after controlling for concurrent, objectively measured health and cognitive ability, and the other ratings. Health as rated from facial photographs, adjusted for sex and chronological age, significantly predicted mortality (hazard ratio = 0.81, 95% confidence interval = 0.67-0.99) but not after adjusting for rated age or objectively measured health and cognition. Rated attractiveness, symmetry, intelligence, and well-being were not significantly associated with mortality risk. Rated age of the face is a significant predictor of mortality risk among older people, with predictive value over and above that of objective or rated health status and cognitive ability.

  15. Developmental dyslexia: predicting individual risk.

    Science.gov (United States)

    Thompson, Paul A; Hulme, Charles; Nash, Hannah M; Gooch, Debbie; Hayiou-Thomas, Emma; Snowling, Margaret J

    2015-09-01

    Causal theories of dyslexia suggest that it is a heritable disorder, which is the outcome of multiple risk factors. However, whether early screening for dyslexia is viable is not yet known. The study followed children at high risk of dyslexia from preschool through the early primary years assessing them from age 3 years and 6 months (T1) at approximately annual intervals on tasks tapping cognitive, language, and executive-motor skills. The children were recruited to three groups: children at family risk of dyslexia, children with concerns regarding speech, and language development at 3;06 years and controls considered to be typically developing. At 8 years, children were classified as 'dyslexic' or not. Logistic regression models were used to predict the individual risk of dyslexia and to investigate how risk factors accumulate to predict poor literacy outcomes. Family-risk status was a stronger predictor of dyslexia at 8 years than low language in preschool. Additional predictors in the preschool years include letter knowledge, phonological awareness, rapid automatized naming, and executive skills. At the time of school entry, language skills become significant predictors, and motor skills add a small but significant increase to the prediction probability. We present classification accuracy using different probability cutoffs for logistic regression models and ROC curves to highlight the accumulation of risk factors at the individual level. Dyslexia is the outcome of multiple risk factors and children with language difficulties at school entry are at high risk. Family history of dyslexia is a predictor of literacy outcome from the preschool years. However, screening does not reach an acceptable clinical level until close to school entry when letter knowledge, phonological awareness, and RAN, rather than family risk, together provide good sensitivity and specificity as a screening battery. © 2015 The Authors. Journal of Child Psychology and Psychiatry published by

  16. Prediction and imitation in speech

    Directory of Open Access Journals (Sweden)

    Chiara eGambi

    2013-06-01

    Full Text Available It has been suggested that intra- and inter-speaker variability in speech are correlated. Interlocutors have been shown to converge on various phonetic dimensions. In addition, speakers imitate the phonetic properties of voices they are exposed to in shadowing, repetition, and even passive listening tasks. We review three theoretical accounts of speech imitation and convergence phenomena: (i the Episodic Theory (ET of speech perception and production (Goldinger, 1998; (ii the Motor Theory (MT of speech perception (Liberman and Whalen, 2000;Galantucci et al., 2006 ; (iii Communication Accommodation Theory (CAT; Giles et al., 1991;Giles and Coupland, 1991. We argue that no account is able to explain all the available evidence. In particular, there is a need to integrate low-level, mechanistic accounts (like ET and MT and higher-level accounts (like CAT. We propose that this is possible within the framework of an integrated theory of production and comprehension (Pickering & Garrod, in press. Similarly to both ET and MT, this theory assumes parity between production and perception. Uniquely, however, it posits that listeners simulate speakers’ utterances by computing forward-model predictions at many different levels, which are then compared to the incoming phonetic input. In our account phonetic imitation can be achieved via the same mechanism that is responsible for sensorimotor adaptation; i.e. the correction of prediction errors. In addition, the model assumes that the degree to which sensory prediction errors lead to motor adjustments is context-dependent. The notion of context subsumes both the preceding linguistic input and non-linguistic attributes of the situation (e.g., the speaker’s and listener’s social identities, their conversational roles, the listener’s intention to imitate.

  17. Comprehensive update of the atomic mass predictions

    International Nuclear Information System (INIS)

    Haustein, P.E.

    1987-01-01

    A project has been completed recently for a comprehensive update of atomic mass predictions. This last occurred in 1976. Over the last 10 years the reliability of these earlier predictions (and others published later) has been analyzed by comparisons of the predictions with new masses from isotopes that were not in the experimental data base when the predictions were prepared. This analysis has highlighted distinct systematic features in various models which frequently result in poor predictions for nuclei that lie far from stability. An overview of the new predictions from models with different theoretical approaches will be presented

  18. Learning to Predict Chemical Reactions

    Science.gov (United States)

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

    2011-01-01

    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, or 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 dataset consisting of 1630 full multi-step 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 non-productive 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. 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

  20. Is quantum theory predictably complete?

    Energy Technology Data Exchange (ETDEWEB)

    Kupczynski, M [Department of Mathematics and Statistics, University of Ottawa, 585 King-Edward Avenue, Ottawa, Ontario K1N 6N5 (Canada); Departement de l' Informatique, UQO, Case postale 1250, succursale Hull, Gatineau, Quebec J8X 3X 7 (Canada)], E-mail: mkupczyn@uottawa.ca

    2009-07-15

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

  1. Focus on astronomical predictable events

    DEFF Research Database (Denmark)

    Jacobsen, Aase Roland

    2006-01-01

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

  2. Making predictions in the multiverse

    International Nuclear Information System (INIS)

    Freivogel, Ben

    2011-01-01

    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.

  3. 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.

  4. Flooding Fragility Experiments and Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Curtis L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Tahhan, Antonio [Idaho National Lab. (INL), Idaho Falls, ID (United States); Muchmore, Cody [Idaho National Lab. (INL), Idaho Falls, ID (United States); Nichols, Larinda [Idaho National Lab. (INL), Idaho Falls, ID (United States); Bhandari, Bishwo [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pope, Chad [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-09-01

    This report describes the work that has been performed on flooding fragility, both the experimental tests being carried out and the probabilistic fragility predictive models being produced in order to use the text results. Flooding experiments involving full-scale doors have commenced in the Portal Evaluation Tank. The goal of these experiments is to develop a full-scale component flooding experiment protocol and to acquire data that can be used to create Bayesian regression models representing the fragility of these components. This work is in support of the Risk-Informed Safety Margin Characterization (RISMC) Pathway external hazards evaluation research and development.

  5. Mach's predictions and relativistic cosmology

    International Nuclear Information System (INIS)

    Heller, M.

    1989-01-01

    Deep methodological insight of Ernst Mach into the structure of the Newtonian mechanics allowed him to ask questions, the importance of which can be appreciated only today. Three such Mach's ''predictions'' are briefly presented, namely: the possibility of the existence of an allpervading medium which could serve as an universal frame of reference and which has actually been discovered in the form of the microwave background radiation, a certain ''smoothness'' of the Universe which is now recognized as the Robertson-Walker symmetries and the possibility of the experimental verification of the mass anisotropy. 11 refs. (author)

  6. Zephyr - the next generation prediction

    DEFF Research Database (Denmark)

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

    2001-01-01

    Technical University. This paper will describe a new project funded by the Danish Ministry of Energy where the largest Danish utilities (Elkraft, Elsam, Eltra and SEAS) are participating. Two advantages can be achieved by combining the effort: The software architecture will be state-of-the-art, using...... the Java2TM platform and Enterprise Java Beans technology, and it will ensure that the best forecasts are given on all prediction horizons from the short range (0-9 hours) to the long range (36-48 hours). This is because the IMM approach uses online data and advanced statistical methods, which...

  7. 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.

  8. Prediction of burnout. Chapter 14

    International Nuclear Information System (INIS)

    Lee, D.H.

    1977-01-01

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

  9. Predicting word sense annotation agreement

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  10. Mechanism and prediction of burnout

    International Nuclear Information System (INIS)

    Hewitt, G.F.

    1977-01-01

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

  11. On predicting monitoring system effectiveness

    Science.gov (United States)

    Cappello, Carlo; Sigurdardottir, Dorotea; Glisic, Branko; Zonta, Daniele; Pozzi, Matteo

    2015-03-01

    While the objective of structural design is to achieve stability with an appropriate level of reliability, the design of systems for structural health monitoring is performed to identify a configuration that enables acquisition of data with an appropriate level of accuracy in order to understand the performance of a structure or its condition state. However, a rational standardized approach for monitoring system design is not fully available. Hence, when engineers design a monitoring system, their approach is often heuristic with performance evaluation based on experience, rather than on quantitative analysis. In this contribution, we propose a probabilistic model for the estimation of monitoring system effectiveness based on information available in prior condition, i.e. before acquiring empirical data. The presented model is developed considering the analogy between structural design and monitoring system design. We assume that the effectiveness can be evaluated based on the prediction of the posterior variance or covariance matrix of the state parameters, which we assume to be defined in a continuous space. Since the empirical measurements are not available in prior condition, the estimation of the posterior variance or covariance matrix is performed considering the measurements as a stochastic variable. Moreover, the model takes into account the effects of nuisance parameters, which are stochastic parameters that affect the observations but cannot be estimated using monitoring data. Finally, we present an application of the proposed model to a real structure. The results show how the model enables engineers to predict whether a sensor configuration satisfies the required performance.

  12. Prediction Reweighting for Domain Adaptation.

    Science.gov (United States)

    Shuang Li; Shiji Song; Gao Huang

    2017-07-01

    There are plenty of classification methods that perform well when training and testing data are drawn from the same distribution. However, in real applications, this condition may be violated, which causes degradation of classification accuracy. Domain adaptation is an effective approach to address this problem. In this paper, we propose a general domain adaptation framework from the perspective of prediction reweighting, from which a novel approach is derived. Different from the major domain adaptation methods, our idea is to reweight predictions of the training classifier on testing data according to their signed distance to the domain separator, which is a classifier that distinguishes training data (from source domain) and testing data (from target domain). We then propagate the labels of target instances with larger weights to ones with smaller weights by introducing a manifold regularization method. It can be proved that our reweighting scheme effectively brings the source and target domains closer to each other in an appropriate sense, such that classification in target domain becomes easier. The proposed method can be implemented efficiently by a simple two-stage algorithm, and the target classifier has a closed-form solution. The effectiveness of our approach is verified by the experiments on artificial datasets and two standard benchmarks, a visual object recognition task and a cross-domain sentiment analysis of text. Experimental results demonstrate that our method is competitive with the state-of-the-art domain adaptation algorithms.

  13. Iowa calibration of MEPDG performance prediction models.

    Science.gov (United States)

    2013-06-01

    This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

  14. 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)

  15. Profit Driven Decision Trees for Churn Prediction

    OpenAIRE

    Höppner, Sebastiaan; Stripling, Eugen; Baesens, Bart; Broucke, Seppe vanden; Verdonck, Tim

    2017-01-01

    Customer retention campaigns increasingly rely on predictive models to detect potential churners in a vast customer base. From the perspective of machine learning, the task of predicting customer churn can be presented as a binary classification problem. Using data on historic behavior, classification algorithms are built with the purpose of accurately predicting the probability of a customer defecting. The predictive churn models are then commonly selected based on accuracy related performan...

  16. Robust predictions of the interacting boson model

    International Nuclear Information System (INIS)

    Casten, R.F.; Koeln Univ.

    1994-01-01

    While most recognized for its symmetries and algebraic structure, the IBA model has other less-well-known but equally intrinsic properties which give unavoidable, parameter-free predictions. These predictions concern central aspects of low-energy nuclear collective structure. This paper outlines these ''robust'' predictions and compares them with the data

  17. Phenology prediction component of GypsES

    Science.gov (United States)

    Jesse A. Logan; Lukas P. Schaub; F. William Ravlin

    1991-01-01

    Prediction of phenology is an important component of most pest management programs, and considerable research effort has been expended toward development of predictive tools for gypsy moth phenology. Although phenological prediction is potentially valuable for timing of spray applications (e.g. Bt, or Gypcheck) and other management activities (e.g. placement and...

  18. Climate Prediction Center - The ENSO Cycle

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > El Niño/La Niña > The ENSO Cycle ENSO Cycle Banner Climate for Weather and Climate Prediction Climate Prediction Center 5830 University Research Court College

  19. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

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

  20. Relationship between water temperature predictability and aquatic ...

    African Journals Online (AJOL)

    Macroinvertebrate taxonomic turnover across seasons was higher for sites having lower water temperature predictability values than for sites with higher predictability, while temporal partitioning was greater at sites with greater temperature variability. Macroinvertebrate taxa responded in a predictable manner to changes in ...

  1. Based on BP Neural Network Stock Prediction

    Science.gov (United States)

    Liu, Xiangwei; Ma, Xin

    2012-01-01

    The stock market has a high profit and high risk features, on the stock market analysis and prediction research has been paid attention to by people. Stock price trend is a complex nonlinear function, so the price has certain predictability. This article mainly with improved BP neural network (BPNN) to set up the stock market prediction model, and…

  2. NEURAL METHODS FOR THE FINANCIAL PREDICTION

    OpenAIRE

    Jerzy Balicki; Piotr Dryja; Waldemar Korłub; Piotr Przybyłek; Maciej Tyszka; Marcin Zadroga; Marcin Zakidalski

    2016-01-01

    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.

  3. 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.

  4. Applications for predictive microbiology to food packaging

    Science.gov (United States)

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

  5. 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

  6. Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

    Science.gov (United States)

    Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

    2015-07-01

    Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

  7. Pretest Predictions for Ventilation Tests

    International Nuclear Information System (INIS)

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

    2007-01-01

    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

  8. The Predictiveness of Achievement Goals

    Directory of Open Access Journals (Sweden)

    Huy P. Phan

    2013-11-01

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

  9. Academic Training: Predicting Natural Catastrophes

    CERN Multimedia

    Françoise Benz

    2005-01-01

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

  10. The PredictAD project

    DEFF Research Database (Denmark)

    Antila, Kari; Lötjönen, Jyrki; Thurfjell, Lennart

    2013-01-01

    Alzheimer's disease (AD) is the most common cause of dementia affecting 36 million people worldwide. As the demographic transition in the developed countries progresses towards older population, the worsening ratio of workers per retirees and the growing number of patients with age-related illnes...... candidates and implement the framework in software. The results are currently used in several research projects, licensed to commercial use and being tested for clinical use in several trials....... objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data...

  11. Prediction and probability in sciences

    International Nuclear Information System (INIS)

    Klein, E.; Sacquin, Y.

    1998-01-01

    This book reports the 7 presentations made at the third meeting 'physics and fundamental questions' whose theme was probability and prediction. The concept of probability that was invented to apprehend random phenomena has become an important branch of mathematics and its application range spreads from radioactivity to species evolution via cosmology or the management of very weak risks. The notion of probability is the basis of quantum mechanics and then is bound to the very nature of matter. The 7 topics are: - radioactivity and probability, - statistical and quantum fluctuations, - quantum mechanics as a generalized probability theory, - probability and the irrational efficiency of mathematics, - can we foresee the future of the universe?, - chance, eventuality and necessity in biology, - how to manage weak risks? (A.C.)

  12. Meditation experience predicts introspective accuracy.

    Directory of Open Access Journals (Sweden)

    Kieran C R Fox

    Full Text Available The accuracy of subjective reports, especially those involving introspection of one's own internal processes, remains unclear, and research has demonstrated large individual differences in introspective accuracy. It has been hypothesized that introspective accuracy may be heightened in persons who engage in meditation practices, due to the highly introspective nature of such practices. We undertook a preliminary exploration of this hypothesis, examining introspective accuracy in a cross-section of meditation practitioners (1-15,000 hrs experience. Introspective accuracy was assessed by comparing subjective reports of tactile sensitivity for each of 20 body regions during a 'body-scanning' meditation with averaged, objective measures of tactile sensitivity (mean size of body representation area in primary somatosensory cortex; two-point discrimination threshold as reported in prior research. Expert meditators showed significantly better introspective accuracy than novices; overall meditation experience also significantly predicted individual introspective accuracy. These results suggest that long-term meditators provide more accurate introspective reports than novices.

  13. Predicting degradability of organic chemicals

    Energy Technology Data Exchange (ETDEWEB)

    Finizio, A; Vighi, M [Milan Univ. (Italy). Ist. di Entomologia Agraria

    1992-05-01

    Degradability, particularly biodegradability, is one of the most important factors governing the persistence of pollutants in the environment and consequently influencing their behavior and toxicity in aquatic and terrestrial ecosystems. The need for reliable persistence data in order to assess the environmental fate and hazard of chemicals by means of predictive approaches, is evident. Biodegradability tests are requested by the EEC directive on new chemicals. Neverthless, degradation tests are not easy to carry out and data on existing chemicals are very scarce. Therefore, assessing the fate of chemicals in the environment from the simple study of their structure would be a useful tool. Rates of degradation are a function of the rates of a series of processes. Correlation between degradation rates and structural parameters are will be facilitated if one of the processes is rate determining. This review is a survey of studies dealing with relationships between structure and biodegradation of organic chemicals, to identify the value and limitations of this approach.

  14. Unrenormalizable theories can be predictive

    CERN Document Server

    Kubo, J

    2003-01-01

    Unrenormalizable theories contain infinitely many free parameters. Considering these theories in terms of the Wilsonian renormalization group (RG), we suggest a method for removing this large ambiguity. Our basic assumption is the existence of a maximal ultraviolet cutoff in a cutoff theory, and we require that the theory be so fine tuned as to reach the maximal cutoff. The theory so obtained behaves as a local continuum theory to the shortest distance. In concrete examples of the scalar theory we find that at least in a certain approximation to the Wilsonian RG, this requirement enables us to make unique predictions in the infrared regime in terms of a finite number of independent parameters. Therefore, this method might provide a way for calculating quantum corrections in a low-energy effective theory of quantum gravity. (orig.)

  15. Lower-limb growth: how predictable are predictions?

    Science.gov (United States)

    Kelly, Paula M; Diméglio, Alain

    2008-12-01

    The purpose of this review is to clarify the different methods of predictions for growth of the lower limb and to propose a simplified method to calculate the final limb deficit and the correct timing of epiphysiodesis. Lower-limb growth is characterized by four different periods: antenatal growth (exponential); birth to 5 years (rapid growth); 5 years to puberty (stable growth); and puberty, which is the final growth spurt characterized by a rapid acceleration phase lasting 1 year followed by a more gradual deceleration phase lasting 1.5 years. The younger the child, the less precise is the prediction. Repeating measurements can increase the accuracy of predictions and those calculated at the beginning of puberty are the most accurate. The challenge is to reduce the margin of uncertainty. Confrontation of the different parameters-bone age, Tanner signs, annual growth velocity of the standing height, sub-ischial length and sitting height-is the most accurate method. Charts and diagrams are only models and templates. There are many mathematical equations in the literature; we must be able to step back from these rigid calculations because they are a false guarantee. The dynamic of growth needs a flexible approach. There are, however, some rules of thumb that may be helpful for different clinical scenarios. For congenital malformations, at birth the limb length discrepancy must be multiplied by 5 to give the final limb length discrepancy. Multiple by 3 at 1 year of age; by 2 at 3 years in girls and 4 years in boys; by 1.5 at 7 years in girls and boys, by 1.2 at 9 years in girls and 11 years in boys and by 1.1 at the onset of puberty (11 years bone age for girls and 13 years bone age for boys). For the timing of epiphysiodesis, several simple principles must be observed to reduce the margin of error; strict and repeated measurements, rigorous analysis of the data obtained, perfect evaluation of bone age with elbow plus hand radiographs and confirmation with Tanner

  16. 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

  17. Earthquake predictions using seismic velocity ratios

    Science.gov (United States)

    Sherburne, R. W.

    1979-01-01

    Since the beginning of modern seismology, seismologists have contemplated predicting earthquakes. The usefulness of earthquake predictions to the reduction of human and economic losses and the value of long-range earthquake prediction to planning is obvious. Not as clear are the long-range economic and social impacts of earthquake prediction to a speicifc area. The general consensus of opinion among scientists and government officials, however, is that the quest of earthquake prediction is a worthwhile goal and should be prusued with a sense of urgency. 

  18. Conditional prediction intervals of wind power generation

    DEFF Research Database (Denmark)

    Pinson, Pierre; Kariniotakis, Georges

    2010-01-01

    A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... on the characteristics of prediction errors for providing conditional interval forecasts. By simultaneously generating prediction intervals with various nominal coverage rates, one obtains full predictive distributions of wind generation. Adapted resampling is applied here to the case of an onshore Danish wind farm...... to the case of a large number of wind farms in Europe and Australia among others is finally discussed....

  19. Sports Tournament Predictions Using Direct Manipulation.

    Science.gov (United States)

    Vuillemot, Romain; Perin, Charles

    2016-01-01

    An advanced interface for sports tournament predictions uses direct manipulation to allow users to make nonlinear predictions. Unlike previous interface designs, the interface helps users focus on their prediction tasks by enabling them to first choose a winner and then fill out the rest of the bracket. In real-world tests of the proposed interface (for the 2014 FIFA World Cup tournament and 2015/2016 UEFA Champions League), the authors validated the use of direct manipulation as an alternative to widgets. Using visitor interaction logs, they were able to determine the strategies people use to perform predictions and identify potential areas of improvement for further prediction interfaces.

  20. The function and failure of sensory predictions.

    Science.gov (United States)

    Bansal, Sonia; Ford, Judith M; Spering, Miriam

    2018-04-23

    Humans and other primates are equipped with neural mechanisms that allow them to automatically make predictions about future events, facilitating processing of expected sensations and actions. Prediction-driven control and monitoring of perceptual and motor acts are vital to normal cognitive functioning. This review provides an overview of corollary discharge mechanisms involved in predictions across sensory modalities and discusses consequences of predictive coding for cognition and behavior. Converging evidence now links impairments in corollary discharge mechanisms to neuropsychiatric symptoms such as hallucinations and delusions. We review studies supporting a prediction-failure hypothesis of perceptual and cognitive disturbances. We also outline neural correlates underlying prediction function and failure, highlighting similarities across the visual, auditory, and somatosensory systems. In linking basic psychophysical and psychophysiological evidence of visual, auditory, and somatosensory prediction failures to neuropsychiatric symptoms, our review furthers our understanding of disease mechanisms. © 2018 New York Academy of Sciences.

  1. Evaluating predictions of critical oxygen desaturation events

    International Nuclear Information System (INIS)

    ElMoaqet, Hisham; Tilbury, Dawn M; Ramachandran, Satya Krishna

    2014-01-01

    This paper presents a new approach for evaluating predictions of oxygen saturation levels in blood ( SpO 2 ). A performance metric based on a threshold is proposed to evaluate  SpO 2 predictions based on whether or not they are able to capture critical desaturations in the  SpO 2 time series of patients. We use linear auto-regressive models built using historical  SpO 2 data to predict critical desaturation events with the proposed metric. In 20 s prediction intervals, 88%–94% of the critical events were captured with positive predictive values (PPVs) between 90% and 99%. Increasing the prediction horizon to 60 s, 46%–71% of the critical events were detected with PPVs between 81% and 97%. In both prediction horizons, more than 97% of the non-critical events were correctly classified. The overall classification capabilities for the developed predictive models were also investigated. The area under ROC curves for 60 s predictions from the developed models are between 0.86 and 0.98. Furthermore, we investigate the effect of including pulse rate (PR) dynamics in the models and predictions. We show no improvement in the percentage of the predicted critical desaturations if PR dynamics are incorporated into the  SpO 2 predictive models (p-value = 0.814). We also show that including the PR dynamics does not improve the earliest time at which critical  SpO 2 levels are predicted (p-value = 0.986). Our results indicate oxygen in blood is an effective input to the PR rather than vice versa. We demonstrate that the combination of predictive models with frequent pulse oximetry measurements can be used as a warning of critical oxygen desaturations that may have adverse effects on the health of patients. (paper)

  2. Potential for western US seasonal snowpack prediction

    Science.gov (United States)

    Kapnick, Sarah B.; Yang, Xiaosong; Vecchi, Gabriel A.; Delworth, Thomas L.; Gudgel, Rich; Malyshev, Sergey; Milly, Paul C. D.; Shevliakova, Elena; Underwood, Seth; Margulis, Steven A.

    2018-01-01

    Western US snowpack—snow that accumulates on the ground in the mountains—plays a critical role in regional hydroclimate and water supply, with 80% of snowmelt runoff being used for agriculture. While climate projections provide estimates of snowpack loss by the end of th ecentury and weather forecasts provide predictions of weather conditions out to 2 weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), crucial for regional agricultural decisions (e.g., plant choice and quantity). Seasonal predictions with climate models first took the form of El Niño predictions 3 decades ago, with hydroclimate predictions emerging more recently. While the field has been focused on single-season predictions (3 months or less), we are now poised to advance our predictions beyond this timeframe. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate the feasibility of seasonal snowpack predictions and quantify the limits of predictive skill 8 month sin advance. This physically based dynamic system outperforms observation-based statistical predictions made on July 1 for March snowpack everywhere except the southern Sierra Nevada, a region where prediction skill is nonexistent for every predictor presently tested. Additionally, in the absence of externally forced negative trends in snowpack, narrow maritime mountain ranges with high hydroclimate variability pose a challenge for seasonal prediction in our present system; natural snowpack variability may inherently be unpredictable at this timescale. This work highlights present prediction system successes and gives cause for optimism for developing seasonal predictions for societal needs.

  3. Similarities and Differences Between Warped Linear Prediction and Laguerre Linear Prediction

    NARCIS (Netherlands)

    Brinker, Albertus C. den; Krishnamoorthi, Harish; Verbitskiy, Evgeny A.

    2011-01-01

    Linear prediction has been successfully applied in many speech and audio processing systems. This paper presents the similarities and differences between two classes of linear prediction schemes, namely, Warped Linear Prediction (WLP) and Laguerre Linear Prediction (LLP). It is shown that both

  4. Radon observation for earthquake prediction

    Energy Technology Data Exchange (ETDEWEB)

    Wakita, Hiroshi [Tokyo Univ. (Japan)

    1998-12-31

    Systematic observation of groundwater radon for the purpose of earthquake prediction began in Japan in late 1973. Continuous observations are conducted at fixed stations using deep wells and springs. During the observation period, significant precursory changes including the 1978 Izu-Oshima-kinkai (M7.0) earthquake as well as numerous coseismic changes were observed. At the time of the 1995 Kobe (M7.2) earthquake, significant changes in chemical components, including radon dissolved in groundwater, were observed near the epicentral region. Precursory changes are presumably caused by permeability changes due to micro-fracturing in basement rock or migration of water from different sources during the preparation stage of earthquakes. Coseismic changes may be caused by seismic shaking and by changes in regional stress. Significant drops of radon concentration in groundwater have been observed after earthquakes at the KSM site. The occurrence of such drops appears to be time-dependent, and possibly reflects changes in the regional stress state of the observation area. The absence of radon drops seems to be correlated with periods of reduced regional seismic activity. Experience accumulated over the two past decades allows us to reach some conclusions: 1) changes in groundwater radon do occur prior to large earthquakes; 2) some sites are particularly sensitive to earthquake occurrence; and 3) the sensitivity changes over time. (author)

  5. Solar Flares and Their Prediction

    Science.gov (United States)

    Adams, Mitzi L.

    1999-01-01

    Solar flares and coronal mass ejection's (CMES) can strongly affect the local environment at the Earth. A major challenge for solar physics is to understand the physical mechanisms responsible for the onset of solar flares. Flares, characterized by a sudden release of energy (approx. 10(exp 32) ergs for the largest events) within the solar atmosphere, result in the acceleration of electrons, protons, and heavier ions as well as the production of electromagnetic radiation from hard X-rays to km radio waves (wavelengths approx. = 10(exp -9) cm to 10(exp 6) cm). Observations suggest that solar flares and sunspots are strongly linked. For example, a study of data from 1956-1969, reveals that approx. 93 percent of major flares originate in active regions with spots. Furthermore, the global structure of the sunspot magnetic field can be correlated with flare activity. This talk will review what we know about flare causes and effects and will discuss techniques for quantifying parameters, which may lead to a prediction of solar flares.

  6. Incorrect predictions reduce switch costs.

    Science.gov (United States)

    Kleinsorge, Thomas; Scheil, Juliane

    2015-07-01

    In three experiments, we combined two sources of conflict within a modified task-switching procedure. The first source of conflict was the one inherent in any task switching situation, namely the conflict between a task set activated by the recent performance of another task and the task set needed to perform the actually relevant task. The second source of conflict was induced by requiring participants to guess aspects of the upcoming task (Exps. 1 & 2: task identity; Exp. 3: position of task precue). In case of an incorrect guess, a conflict accrues between the representation of the guessed task and the actually relevant task. In Experiments 1 and 2, incorrect guesses led to an overall increase of reaction times and error rates, but they reduced task switch costs compared to conditions in which participants predicted the correct task. In Experiment 3, incorrect guesses resulted in faster performance overall and to a selective decrease of reaction times in task switch trials when the cue-target interval was long. We interpret these findings in terms of an enhanced level of controlled processing induced by a combination of two sources of conflict converging upon the same target of cognitive control. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Parallel Prediction of Stock Volatility

    Directory of Open Access Journals (Sweden)

    Priscilla Jenq

    2017-10-01

    Full Text Available Volatility is a measurement of the risk of financial products. A stock will hit new highs and lows over time and if these highs and lows fluctuate wildly, then it is considered a high volatile stock. Such a stock is considered riskier than a stock whose volatility is low. Although highly volatile stocks are riskier, the returns that they generate for investors can be quite high. Of course, with a riskier stock also comes the chance of losing money and yielding negative returns. In this project, we will use historic stock data to help us forecast volatility. Since the financial industry usually uses S&P 500 as the indicator of the market, we will use S&P 500 as a benchmark to compute the risk. We will also use artificial neural networks as a tool to predict volatilities for a specific time frame that will be set when we configure this neural network. There have been reports that neural networks with different numbers of layers and different numbers of hidden nodes may generate varying results. In fact, we may be able to find the best configuration of a neural network to compute volatilities. We will implement this system using the parallel approach. The system can be used as a tool for investors to allocating and hedging assets.

  8. 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.

  9. Predictable repair of provisional restorations.

    Science.gov (United States)

    Hammond, Barry D; Cooper, Jeril R; Lazarchik, David A

    2009-01-01

    The importance of provisional restorations is often downplayed, as they are thought of by some as only "temporaries." As a result, a less-than-ideal provisional is sometimes fabricated, in part because of the additional chair time required to make provisional modifications when using traditional techniques. Additionally, in many dental practices, these provisional restorations are often fabricated by auxillary personnel who may not be as well trained in the fabrication process. Because provisionals play an important role in achieving the desired final functional and esthetic result, a high-quality provisional restoration is essential to fabricating a successful definitive restoration. This article describes a method for efficiently and predictably repairing both methacrylate and bis-acryl provisional restorations using flowable composite resin. By use of this relatively simple technique, provisional restorations can now be modified or repaired in a timely and productive manner to yield an exceptional result. Successful execution of esthetic and restorative dentistry requires attention to detail in every aspect of the case. Fabrication of high-quality provisional restorations can, at times, be challenging and time consuming. The techniques for optimizing resin provisional restorations as described in this paper are pragmatic and will enhance the delivery of dental treatment.

  10. 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.

  11. Collaboratory for the Study of Earthquake Predictability

    Science.gov (United States)

    Schorlemmer, D.; Jordan, T. H.; Zechar, J. D.; Gerstenberger, M. C.; Wiemer, S.; Maechling, P. J.

    2006-12-01

    Earthquake prediction is one of the most difficult problems in physical science and, owing to its societal implications, one of the most controversial. The study of earthquake predictability has been impeded by the lack of an adequate experimental infrastructure---the capability to conduct scientific prediction experiments under rigorous, controlled conditions and evaluate them using accepted criteria specified in advance. To remedy this deficiency, the Southern California Earthquake Center (SCEC) is working with its international partners, which include the European Union (through the Swiss Seismological Service) and New Zealand (through GNS Science), to develop a virtual, distributed laboratory with a cyberinfrastructure adequate to support a global program of research on earthquake predictability. This Collaboratory for the Study of Earthquake Predictability (CSEP) will extend the testing activities of SCEC's Working Group on Regional Earthquake Likelihood Models, from which we will present first results. CSEP will support rigorous procedures for registering prediction experiments on regional and global scales, community-endorsed standards for assessing probability-based and alarm-based predictions, access to authorized data sets and monitoring products from designated natural laboratories, and software to allow researchers to participate in prediction experiments. CSEP will encourage research on earthquake predictability by supporting an environment for scientific prediction experiments that allows the predictive skill of proposed algorithms to be rigorously compared with standardized reference methods and data sets. It will thereby reduce the controversies surrounding earthquake prediction, and it will allow the results of prediction experiments to be communicated to the scientific community, governmental agencies, and the general public in an appropriate research context.

  12. Predicting Well-Being in Europe?

    DEFF Research Database (Denmark)

    Hussain, M. Azhar

    2015-01-01

    Has the worst financial and economic crisis since the 1930s reduced the subjective wellbeing function's predictive power? Regression models for happiness are estimated for the three first rounds of the European Social Survey (ESS); 2002, 2004 and 2006. Several explanatory variables are significant...... happiness. Nevertheless, 73% of the predictions in 2008 and 57% of predictions in 2010 were within the margin of error. These correct prediction percentages are not unusually low - rather they are slightly higher than before the crisis. It is surprising that happiness predictions are not adversely affected...... by the crisis. On the other hand, results are consistent with the adaption hypothesis. The same exercise is conducted applying life satisfaction instead of happiness, but we reject, against expectation, that (more transient) happiness is harder to predict than life satisfaction. Fifteen ESS countries surveyed...

  13. Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    pumps, heat tanks, electrical vehicle battery charging/discharging, wind farms, power plants). 2.Embed forecasting methodologies for the weather (e.g. temperature, solar radiation), the electricity consumption, and the electricity price in a predictive control system. 3.Develop optimization algorithms....... Chapter 3 introduces Model Predictive Control (MPC) including state estimation, filtering and prediction for linear models. Chapter 4 simulates the models from Chapter 2 with the certainty equivalent MPC from Chapter 3. An economic MPC minimizes the costs of consumption based on real electricity prices...... that determined the flexibility of the units. A predictive control system easily handles constraints, e.g. limitations in power consumption, and predicts the future behavior of a unit by integrating predictions of electricity prices, consumption, and weather variables. The simulations demonstrate the expected...

  14. 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

  15. Can we predict shoulder dystocia?

    Science.gov (United States)

    Revicky, Vladimir; Mukhopadhyay, Sambit; Morris, Edward P; Nieto, Jose J

    2012-02-01

    To analyse the significance of risk factors and the possibility of prediction of shoulder dystocia. This was a retrospective cohort study. There were 9,767 vaginal deliveries at 37 and more weeks of gestation analysed during 2005-2007. Studied population included 234 deliveries complicated by shoulder dystocia. Shoulder dystocia was defined as a delivery that required additional obstetric manoeuvres to release the shoulders after gentle downward traction has failed. First, a univariate analysis was done to identify the factors that had a significant association with shoulder dystocia. Parity, age, gestation, induction of labour, epidural analgesia, birth weight, duration of second stage of labour and mode of delivery were studied factors. All factors were then combined in a multivariate logistic regression analysis. Adjusted odds ratios (Adj. OR) with 95% confidence intervals (CI) were calculated. The incidence of shoulder dystocia was 2.4% (234/9,767). Only mode of delivery and birth weight were independent risk factors for shoulder dystocia. Parity, age, gestation, induction of labour, epidural analgesia and duration of second stage of labour were not independent risk factors. Ventouse delivery increases the risk of shoulder dystocia almost 3 times, forceps delivery comparing to the ventouse delivery increases risk almost 3.4 times. Risk of shoulder dystocia is minimal with the birth weight of 3,000 g or less. It is difficult to foretell the exact birth weight and the mode of delivery, therefore occurrence of shoulder dystocia is highly unpredictable. Regular drills for shoulder dystocia and awareness of increased incidence with instrumental deliveries are important to reduce fetal and maternal morbidity and mortality.

  16. Lifestyle Markers Predict Cognitive Function.

    Science.gov (United States)

    Masley, Steven C; Roetzheim, Richard; Clayton, Gwendolyn; Presby, Angela; Sundberg, Kelley; Masley, Lucas V

    2017-01-01

    Rates of mild cognitive impairment and Alzheimer's disease are increasing rapidly. None of the current treatment regimens for Alzheimer's disease are effective in arresting progression. Lifestyle choices may prevent cognitive decline. This study aims to clarify which factors best predict cognitive function. This was a prospective cross-sectional analysis of 799 men and women undergoing health and cognitive testing every 1 to 3 years at an outpatient center. This study utilizes data collected from the first patient visit. Participant ages were 18 to 88 (mean = 50.7) years and the sample was 26.6% female and 73.4% male. Measurements were made of body composition, fasting laboratory and anthropometric measures, strength and aerobic fitness, nutrient and dietary intake, and carotid intimal media thickness (IMT). Each participant was tested with a computerized neurocognitive test battery. Cognitive outcomes were assessed in bivariate analyses using t-tests and correlation coefficients and in multivariable analysis (controlling for age) using multiple linear regression. The initial bivariate analyses showed better Neurocognitive Index (NCI) scores with lower age, greater fitness scores (push-up strength, VO 2 max, and exercise duration during treadmill testing), and lower fasting glucose levels. Better cognitive flexibility scores were also noted with younger age, lower systolic blood pressure, lower body fat, lower carotid IMT scores, greater fitness, and higher alcohol intake. After controlling for age, factors that remained associated with better NCI scores include no tobacco use, lower fasting glucose levels, and better fitness (aerobic and strength). Higher cognitive flexibility scores remained associated with greater aerobic and strength fitness, lower body fat, and higher intake of alcohol. Modifiable biomarkers that impact cognitive performance favorably include greater aerobic fitness and strength, lower blood sugar levels, greater alcohol intake, lower body

  17. SEIZURE PREDICTION: THE FOURTH INTERNATIONAL WORKSHOP

    Science.gov (United States)

    Zaveri, Hitten P.; Frei, Mark G.; Arthurs, Susan; Osorio, Ivan

    2010-01-01

    The recently convened Fourth International Workshop on Seizure Prediction (IWSP4) brought together a diverse international group of investigators, from academia and industry, including epileptologists, neurosurgeons, neuroscientists, computer scientists, engineers, physicists, and mathematicians who are conducting interdisciplinary research on the prediction and control of seizures. IWSP4 allowed the presentation and discussion of results, an exchange of ideas, an assessment of the status of seizure prediction, control and related fields and the fostering of collaborative projects. PMID:20674508

  18. 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.

  19. 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, which...

  20. 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....

  1. Applications of contact predictions to structural biology

    Directory of Open Access Journals (Sweden)

    Felix Simkovic

    2017-05-01

    Full Text Available Evolutionary pressure on residue interactions, intramolecular or intermolecular, that are important for protein structure or function can lead to covariance between the two positions. Recent methodological advances allow much more accurate contact predictions to be derived from this evolutionary covariance signal. The practical application of contact predictions has largely been confined to structural bioinformatics, yet, as this work seeks to demonstrate, the data can be of enormous value to the structural biologist working in X-ray crystallography, cryo-EM or NMR. Integrative structural bioinformatics packages such as Rosetta can already exploit contact predictions in a variety of ways. The contribution of contact predictions begins at construct design, where structural domains may need to be expressed separately and contact predictions can help to predict domain limits. Structure solution by molecular replacement (MR benefits from contact predictions in diverse ways: in difficult cases, more accurate search models can be constructed using ab initio modelling when predictions are available, while intermolecular contact predictions can allow the construction of larger, oligomeric search models. Furthermore, MR using supersecondary motifs or large-scale screens against the PDB can exploit information, such as the parallel or antiparallel nature of any β-strand pairing in the target, that can be inferred from contact predictions. Contact information will be particularly valuable in the determination of lower resolution structures by helping to assign sequence register. In large complexes, contact information may allow the identity of a protein responsible for a certain region of density to be determined and then assist in the orientation of an available model within that density. In NMR, predicted contacts can provide long-range information to extend the upper size limit of the technique in a manner analogous but complementary to experimental

  2. Predicting Process Behaviour using Deep Learning

    OpenAIRE

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

    2016-01-01

    Predicting business process behaviour 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 on explicit process models, and also a novel application of deep learning methods. The approach is evaluated on two real da...

  3. Audiovisual biofeedback improves motion prediction accuracy.

    Science.gov (United States)

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

    2013-04-01

    The accuracy of motion prediction, utilized to overcome the system latency of motion management radiotherapy systems, is hampered by irregularities present in the patients' respiratory pattern. Audiovisual (AV) biofeedback has been shown to reduce respiratory irregularities. The aim of this study was to test the hypothesis that AV biofeedback improves the accuracy of motion prediction. An AV biofeedback system combined with real-time respiratory data acquisition and MR images were implemented in this project. One-dimensional respiratory data from (1) the abdominal wall (30 Hz) and (2) the thoracic diaphragm (5 Hz) were obtained from 15 healthy human subjects across 30 studies. The subjects were required to breathe with and without the guidance of AV biofeedback during each study. The obtained respiratory signals were then implemented in a kernel density estimation prediction algorithm. For each of the 30 studies, five different prediction times ranging from 50 to 1400 ms were tested (150 predictions performed). Prediction error was quantified as the root mean square error (RMSE); the RMSE was calculated from the difference between the real and predicted respiratory data. The statistical significance of the prediction results was determined by the Student's t-test. Prediction accuracy was considerably improved by the implementation of AV biofeedback. Of the 150 respiratory predictions performed, prediction accuracy was improved 69% (103/150) of the time for abdominal wall data, and 78% (117/150) of the time for diaphragm data. The average reduction in RMSE due to AV biofeedback over unguided respiration was 26% (p biofeedback improves prediction accuracy. This would result in increased efficiency of motion management techniques affected by system latencies used in radiotherapy.

  4. Prediction methods and databases within chemoinformatics

    DEFF Research Database (Denmark)

    Jónsdóttir, Svava Osk; Jørgensen, Flemming Steen; Brunak, Søren

    2005-01-01

    MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information...... about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability...

  5. Sports Tournament Predictions Using Direct Manipulation

    OpenAIRE

    Vuillemot , Romain; Perin , Charles

    2016-01-01

    An advanced interface for sports tournament predictions uses direct manipulation to allow users to make nonlinear predictions. Unlike previous interface designs, the interface helps users focus on their prediction tasks by enabling them to first choose a winner and then fill out the rest of the bracket. In real-world tests of the proposed interface (for the 2014 FIFA World Cup tournament and 2015/2016 UEFA Champions League), the authors validated the use of direct manipulation as an alternati...

  6. Understanding predictability and exploration in human mobility

    DEFF Research Database (Denmark)

    Cuttone, Andrea; Jørgensen, Sune Lehmann; González, Marta C.

    2018-01-01

    Predictive models for human mobility have important applications in many fields including traffic control, ubiquitous computing, and contextual advertisement. The predictive performance of models in literature varies quite broadly, from over 90% to under 40%. In this work we study which underlying...... strong influence on the accuracy of prediction. Finally we reveal that the exploration of new locations is an important factor in human mobility, and we measure that on average 20-25% of transitions are to new places, and approx. 70% of locations are visited only once. We discuss how these mechanisms...... are important factors limiting our ability to predict human mobility....

  7. Stock market index prediction using neural networks

    Science.gov (United States)

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

    1994-03-01

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

  8. Decadel climate prediction: challenges and opportunities

    International Nuclear Information System (INIS)

    Hurrell, J W

    2008-01-01

    The scientific understanding of climate change is now sufficiently clear to show that climate change from global warming is already upon us, and the rate of change as projected exceeds anything seen in nature in the past 10,000 years. Uncertainties remain, however, especially regarding how climate will change at regional and local scales where the signal of natural variability is large. Addressing many of these uncertainties will require a movement toward high resolution climate system predictions, with a blurring of the distinction between shorter-term predictions and longer-term climate projections. The key is the realization that climate system predictions, regardless of timescale, will require initialization of coupled general circulation models with best estimates of the current observed state of the atmosphere, oceans, cryosphere, and land surface. Formidable challenges exist: for instance, what is the best method of initialization given imperfect observations and systematic errors in models? What effect does initialization have on climate predictions? What predictions should be attempted, and how would they be verified? Despite such challenges, the unrealized predictability that resides in slowly evolving phenomena, such as ocean current systems, is of paramount importance for society to plan and adapt for the next few decades. Moreover, initialized climate predictions will require stronger collaboration with shared knowledge, infrastructure and technical capabilities among those in the weather and climate prediction communities. The potential benefits include improved understanding and predictions on all time scales

  9. Deterministic prediction of surface wind speed variations

    Directory of Open Access Journals (Sweden)

    G. V. Drisya

    2014-11-01

    Full Text Available 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.

  10. 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.

  11. Stock price prediction using geometric Brownian motion

    Science.gov (United States)

    Farida Agustini, W.; Restu Affianti, Ika; Putri, Endah RM

    2018-03-01

    Geometric Brownian motion is a mathematical model for predicting the future price of stock. The phase that done before stock price prediction is determine stock expected price formulation and determine the confidence level of 95%. On stock price prediction using geometric Brownian Motion model, the algorithm starts from calculating the value of return, followed by estimating value of volatility and drift, obtain the stock price forecast, calculating the forecast MAPE, calculating the stock expected price and calculating the confidence level of 95%. Based on the research, the output analysis shows that geometric Brownian motion model is the prediction technique with high rate of accuracy. It is proven with forecast MAPE value ≤ 20%.

  12. Seasonal climate prediction for North Eurasia

    International Nuclear Information System (INIS)

    Kryjov, Vladimir N

    2012-01-01

    An overview of the current status of the operational seasonal climate prediction for North Eurasia is presented. It is shown that the performance of existing climate models is rather poor in seasonal prediction for North Eurasia. Multi-model ensemble forecasts are more reliable than single-model ones; however, for North Eurasia they tend to be close to climatological ones. Application of downscaling methods may improve predictions for some locations (or regions). However, general improvement of the reliability of seasonal forecasts for North Eurasia requires improvement of the climate prediction models. (letter)

  13. Predictions of High Energy Experimental Results

    Directory of Open Access Journals (Sweden)

    Comay E.

    2010-10-01

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

  14. 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....

  15. Recent Advances in Predictive (Machine) Learning

    Energy Technology Data Exchange (ETDEWEB)

    Friedman, J

    2004-01-24

    Prediction involves estimating the unknown value of an attribute of a system under study given the values of other measured attributes. In prediction (machine) learning the prediction rule is derived from data consisting of previously solved cases. Most methods for predictive learning were originated many years ago at the dawn of the computer age. Recently two new techniques have emerged that have revitalized the field. These are support vector machines and boosted decision trees. This paper provides an introduction to these two new methods tracing their respective ancestral roots to standard kernel methods and ordinary decision trees.

  16. Final Technical Report: Increasing Prediction Accuracy.

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-12-01

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

  17. Computer loss experience and predictions

    Science.gov (United States)

    Parker, Donn B.

    1996-03-01

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

  18. LocTree3 prediction of localization

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  19. 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…

  20. Link Label Prediction in Signed Citation Network

    KAUST Repository

    Akujuobi, Uchenna Thankgod

    2016-01-01

    such as using regression, trust propagation and matrix factorization. These approaches have tried to solve the problem of link label prediction by using ideas from social theories, where most of them predict a single missing label given that labels of other

  1. Predicting Handwriting Difficulties through Spelling Processes

    Science.gov (United States)

    Rodríguez, Cristina; Villarroel, Rebeca

    2017-01-01

    This study examined whether spelling tasks contribute to the prediction of the handwriting status of children with poor and good handwriting skills in a cross-sectional study with 276 Spanish children from Grades 1 and 3. The main hypothesis was that the spelling tasks would predict the handwriting status of the children, although this influence…

  2. Selecting Suitable Candidates for Predictive Maintenance

    NARCIS (Netherlands)

    Tiddens, Wieger Willem; Braaksma, Anne Johannes Jan; Tinga, Tiedo

    2018-01-01

    Predictive maintenance (PdM) or Prognostics and Health Management (PHM) assists in better predicting the future state of physical assets and making timely and better-informed maintenance decisions. Many companies nowadays ambition the implementation of such an advanced maintenance policy. However,

  3. Prediction of twin-arginine signal peptides

    DEFF Research Database (Denmark)

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

    2005-01-01

    expressions, whereas hydrophobicity discrimination of Tat- and Sec- signal peptides is carried out by an artificial neural network. A potential cleavage site of the predicted Tat signal peptide is also reported. The TatP prediction server is available as a public web server at http://www.cbs.dtu.dk/services/TatP/....

  4. Predicting Liaison: an Example-Based Approach

    NARCIS (Netherlands)

    Greefhorst, A.P.M.; Bosch, A.P.J. van den

    2016-01-01

    Predicting liaison in French is a non-trivial problem to model. We compare a memory-based machine-learning algorithm with a rule-based baseline. The memory-based learner is trained to predict whether liaison occurs between two words on the basis of lexical, orthographic, morphosyntactic, and

  5. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

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

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

  6. Towards context aware food sales prediction

    NARCIS (Netherlands)

    Zliobaite, I.; Bakker, J.; Pechenizkiy, M.

    2009-01-01

    Sales prediction is a complex task because of a large number of factors affecting the demand. We present a context aware sales prediction approach, which selects the base predictor depending on the structural properties of the historical sales. In the experimental part we show that there exist

  7. Predictability of Returns and Cash Flows

    OpenAIRE

    Ralph S.J. Koijen; Stijn Van Nieuwerburgh

    2010-01-01

    We review the literature on return and cash-flow growth predictability from the perspective of the present-value identity. We focus predominantly on recent work. Our emphasis is on U.S. aggregate stock return predictability, but we also discuss evidence from other asset classes and countries.

  8. 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…

  9. Variations in roughness predictions (flume experiments)

    NARCIS (Netherlands)

    Noordam, Daniëlle; Blom, Astrid; van der Klis, H.; Hulscher, Suzanne J.M.H.; Makaske, A.; Wolfert, H.P.; van Os, A.G.

    2005-01-01

    Data of flume experiments with bed forms are used to analyze and compare different roughness predictors. In this study, the hydraulic roughness consists of grain roughness and form roughness. We predict the grain roughness by means of the size of the sediment. The form roughness is predicted by

  10. Predicting Information Flows in Network Traffic.

    Science.gov (United States)

    Hinich, Melvin J.; Molyneux, Robert E.

    2003-01-01

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

  11. Predictive user modeling with actionable attributes

    NARCIS (Netherlands)

    Zliobaite, I.; Pechenizkiy, M.

    2013-01-01

    Different machine learning techniques have been proposed and used for modeling individual and group user needs, interests and preferences. In the traditional predictive modeling instances are described by observable variables, called attributes. The goal is to learn a model for predicting the target

  12. 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…

  13. 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

  14. Climate Prediction Center - Atlantic Hurricane Outlook

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News ; Seasonal Climate Summary Archive The 2018 Atlantic hurricane season outlook is an official product of the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC). The outlook is

  15. The relative value of operon predictions

    NARCIS (Netherlands)

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

    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,

  16. Predictive Model of Systemic Toxicity (SOT)

    Science.gov (United States)

    In an effort to ensure chemical safety in light of regulatory advances away from reliance on animal testing, USEPA and L’Oréal have collaborated to develop a quantitative systemic toxicity prediction model. Prediction of human systemic toxicity has proved difficult and remains a ...

  17. Predicting death from surgery for lung cancer

    DEFF Research Database (Denmark)

    O'Dowd, Emma L; Lüchtenborg, Margreet; Baldwin, David R

    2016-01-01

    OBJECTIVES: Current British guidelines advocate the use of risk prediction scores such as Thoracoscore to estimate mortality prior to radical surgery for non-small cell lung cancer (NSCLC). A recent publication used the National Lung Cancer Audit (NLCA) to produce a score to predict 90day mortali...

  18. 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...

  19. PREDICTING ADVERTISING EXPENDITURES USING INTENTION SURVEYS

    NARCIS (Netherlands)

    ALSEM, KJ; LEEFLANG, PSH

    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

  20. Universal LD50 predictions using deep learning

    Science.gov (United States)

    NICEATM Predictive Models for Acute Oral Systemic Toxicity LD50 entry Risa R. Sayre (sayre.risa@epa.gov) & Christopher M. Grulke Our approach uses an ensemble of multilayer perceptron regressions to predict rat acute oral LD50 values from chemical features. Features were genera...