921 resultados para Growth Models (economics)
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Fully coupled climate carbon cycle models are sophisticated tools that are used to predict future climate change and its impact on the land and ocean carbon cycles. These models should be able to adequately represent natural variability, requiring model validation by observations. The present study focuses on the ocean carbon cycle component, in particular the spatial and temporal variability in net primary productivity (PP) and export production (EP) of particulate organic carbon (POC). Results from three coupled climate carbon cycle models (IPSL, MPIM, NCAR) are compared with observation-based estimates derived from satellite measurements of ocean colour and results from inverse modelling (data assimilation). Satellite observations of ocean colour have shown that temporal variability of PP on the global scale is largely dominated by the permanently stratified, low-latitude ocean (Behrenfeld et al., 2006) with stronger stratification (higher sea surface temperature; SST) being associated with negative PP anomalies. Results from all three coupled models confirm the role of the low-latitude, permanently stratified ocean for anomalies in globally integrated PP, but only one model (IPSL) also reproduces the inverse relationship between stratification (SST) and PP. An adequate representation of iron and macronutrient co-limitation of phytoplankton growth in the tropical ocean has shown to be the crucial mechanism determining the capability of the models to reproduce observed interactions between climate and PP.
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INTRODUCTION: Ruptures of the anterior cruciate ligament are being diagnosed with increasing frequency in skeletally immature individuals. It was our aim to investigate the graft remodelling process following an autologous, transphyseal reconstruction of the anterior cruciate ligament (ACL) in skeletally immature sheep. We hypothesized that the ligamentisation process in immature sheep is quicker and more complete when compared to adult sheep. MATERIALS AND METHODS: Skeletally immature sheep with an age of 4 months underwent a fully transphyseal ACL reconstruction using an autologous tendon. The animals were subsequently sacrificed at 3, 6, 12 and 24 weeks following surgery. Each group was characterised histomorphometrically, by immunostaining (VEGF, SMA), by transmission electron microscopy (TEM) and biomechanically (UFS Roboter). RESULTS: The histomorphometric analysis and presence of VEGF and SMA positive cells demonstrated a rapid return to a ligament like structure. The biomechanical analysis revealed an anteroposterior translation that was still increased even 6 months following surgery. CONCLUSION: As in adult sheep models, the remodeling of a soft tissue graft used for ACL reconstruction results in a biomechanically inferior substitute. However, the immature tissue seems to remodel faster and more complete when compared to adults.
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Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.
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A striking feature of virtually al western industrialized countries sice the middle of the past century has been the persistent growth of their government sector. From the beginning of the century to the late 1970's, the government expenditures' share of gross national product has increased from 7% to 36% in the U.S., 11% to 40% in the U.K., and 3% to 25% in Japan. In Germany, it went from 7% to 42% (1872-1978), while in France it soared from 11% to 59% (1872-1979). The evolution of the number of government employees followed a similar pattern. In the U.S., for instance, the average annual rate of growth of the government labor force over the period 1899-1974 has been 3.17%, compared to a 1.62% average annual growth rate of the working population. Less quantifiable aspects like the number and scope of regulations also refelct a growing public sector.
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Context. According to the sequential accretion model (or core-nucleated accretion model), giant planet formation is based first on the formation of a solid core which, when massive enough, can gravitationally bind gas from the nebula to form the envelope. The most critical part of the model is the formation time of the core: to trigger the accretion of gas, the core has to grow up to several Earth masses before the gas component of the protoplanetary disc dissipates. Aims: We calculate planetary formation models including a detailed description of the dynamics of the planetesimal disc, taking into account both gas drag and excitation of forming planets. Methods: We computed the formation of planets, considering the oligarchic regime for the growth of the solid core. Embryos growing in the disc stir their neighbour planetesimals, exciting their relative velocities, which makes accretion more difficult. Here we introduce a more realistic treatment for the evolution of planetesimals' relative velocities, which directly impact on the formation timescale. For this, we computed the excitation state of planetesimals, as a result of stirring by forming planets, and gas-solid interactions. Results: We find that the formation of giant planets is favoured by the accretion of small planetesimals, as their random velocities are more easily damped by the gas drag of the nebula. Moreover, the capture radius of a protoplanet with a (tiny) envelope is also larger for small planetesimals. However, planets migrate as a result of disc-planet angular momentum exchange, with important consequences for their survival: due to the slow growth of a protoplanet in the oligarchic regime, rapid inward type I migration has important implications on intermediate-mass planets that have not yet started their runaway accretion phase of gas. Most of these planets are lost in the central star. Surviving planets have masses either below 10 M⊕ or above several Jupiter masses. Conclusions: To form giant planets before the dissipation of the disc, small planetesimals (~0.1 km) have to be the major contributors of the solid accretion process. However, the combination of oligarchic growth and fast inward migration leads to the absence of intermediate-mass planets. Other processes must therefore be at work to explain the population of extrasolar planets that are presently known.
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Sirtuins (SIRT1-7) are a highly conserved family of NAD(+)-dependent enzymes that control the activity of histone and nonhistone regulatory proteins. SIRT1 is purposed to promote longevity and to suppress the initiation of some cancers. Nevertheless, SIRT1 is reported to function as a tumor suppressor as well as an oncogenic protein. Our data show that compared with normal liver or surrounding tumor tissue, SIRT1 is strongly overexpressed in human hepatocellular carcinoma (HCC). In addition, human HCC cell lines (Hep3B, HepG2, HuH7, HLE, HLF, HepKK1, skHep1) were screened for the expression of the sirtuin family members and only SIRT1 was consistently overexpressed compared with normal hepatocytes. To determine its effect on HCC growth, SIRT1 activity was inhibited either with lentiviruses expressing short hairpin RNAs or with the small molecule inhibitor, cambinol. Knockdown or inhibition of SIRT1 activity had a cytostatic effect, characterized by an altered morphology, impaired proliferation, an increased expression of differentiation markers, and cellular senescence. In an orthotopic xenograft model, knockdown of SIRT1 resulted in 50% fewer animals developing tumors and cambinol treatment resulted in an overall lower tumor burden. Taken together, our data show that inhibition of SIRT1 in HCC cells impairs their proliferation in vitro and tumor formation in vivo. These data suggest that SIRT1 expression positively influences the growth of HCC and support further studies aimed to block its activity alone or in combination as a novel treatment strategy.
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Cardiomyocytes grow during heart maturation or disease-related cardiac remodeling. We present evidence that the intercalated disc (ID) is integral to both longitudinal and lateral growth: increases in width are accommodated by lateral extension of the plicate tread regions and increases in length by sarcomere insertion within the ID. At the margin between myofibril and the folded membrane of the ID lies a transitional junction through which the thin filaments from the last sarcomere run to the ID membrane and it has been suggested that this junction acts as a proto Z-disc for sarcomere addition. In support of this hypothesis, we have investigated the ultrastructure of the ID in mouse hearts from control and dilated cardiomyopathy (DCM) models, the MLP-null and a cardiac-specific β-catenin mutant, cΔex3, as well as in human left ventricle from normal and DCM samples. We find that the ID amplitude can vary tenfold from 0.2 μm up to a maximum of ~2 μm allowing gradual expansion during heart growth. At the greatest amplitude, equivalent to a sarcomere length, A-bands and thick filaments are found within the ID membrane loops together with a Z-disc, which develops at the transitional junction position. Here, also, the tops of the membrane folds, which are rich in αII spectrin, become enlarged and associated with junctional sarcoplasmic reticulum. Systematically larger ID amplitudes are found in DCM samples. Other morphological differences between mouse DCM and normal hearts suggest that sarcomere inclusion is compromised in the diseased hearts.
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Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.
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We have previously shown that vasculogenesis, the process by which bone marrow-derived cells are recruited to the tumor and organized to form a blood vessel network de novo, is essential for the growth of Ewing’s sarcoma. We further demonstrated that these bone marrow cells differentiate into pericytes/vascular smooth muscle cells(vSMC) and contribute to the formation of the functional vascular network. The molecular mechanisms that control bone marrow cell differentiation into pericytes/vSMC in Ewing’s sarcoma are poorly understood. Here, we demonstrate that the Notch ligand Delta like ligand 4 (DLL4) plays a critical role in this process. DLL4 is essential for the formation of mature blood vessels during development and in several tumor models. Inhibition of DLL4 causes increased vascular sprouting, decreased pericyte coverage, and decreased vessel functionality. We demonstrate for the first time that DLL4 is expressed by bone marrow-derived pericytes/vascular smooth muscle cells in two Ewing’s sarcoma xenograft models and by perivascular cells in 12 out of 14 patient samples. Using dominant negative mastermind to inhibit Notch, we demonstrate that Notch signaling is essential for bone marrow cell participation in vasculogenesis. Further, inhibition of DLL4 using either shRNA or the monoclonal DLL4 neutralizing antibody YW152F led to dramatic changes in blood vessel morphology and function. Vessels in tumors where DLL4 was inhibited were smaller, lacked lumens, had significantly reduced numbers of bone marrow-derived pericyte/vascular smooth muscle cells, and were less functional. Importantly, growth of TC71 and A4573 tumors was significantly inhibited by treatment with YW152F. Additionally, we provide in vitro evidence that DLL4-Notch signaling is involved in bone marrow-derived pericyte/vascular smooth muscle cell formation outside of the Ewing’s sarcoma environment. Pericyte/vascular smooth muscle cell marker expression by whole bone marrow cells cultured with mouse embryonic stromal cells was reduced when DLL4 was inhibited by YW152F. For the first time, our findings demonstrate a role for DLL4 in bone marrow-derived pericyte/vascular smooth muscle differentiation as well as a critical role for DLL4 in Ewing’s sarcoma tumor growth.
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Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.
Resumo:
Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.
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Hepatoma-derived growth factor (HDGF) is overexpressed in lung cancer and the overexpression correlates with aggressive biological behaviors and poor clinical outcomes. We developed anti-HDGF monoclonal antibodies and tested their antitumor activity in lung cancer xenograft models. We also determined biological effects in tumors treated with the antibody alone or in combination with bevacizumab/avastin (an anti-vascular endothelial growth factor antibody) and/or gemcitabine (a chemotherapeutic agent). We found the anti-HDGF was effective to inhibit tumor growth in non-small cell lung cancer xenograft models. In the A549 model, compared with control IgG, tumor growth was substantially inhibited in animals treated with anti-HDGF antibodies, particularly HDGF-C1 (P = 0.002) and HDGF-H3 (P = 0.005). When HDGF-H3 was combined with either bevacizumab or gemcitabine, we observed enhanced tumor growth inhibition, particularly when the three agents were used together. HDGF-H3-treated tumors exhibited significant reduction of microvessel density with a pattern distinctive from the microvessel reduction pattern observed in bevacizumab-treated tumors. HDGF-H3-treated but not bevacizumab-treated tumors also showed a significant increase of apoptosis. Interestingly, many of the apoptotic cells in HDGF-H3-treated tumors are stroma cells, suggesting that the mechanism of the antitumor activity is, at least in part, through disrupting formation of tumor-stroma structures. Our results show that HDGF is a novel therapeutic target for lung cancer and can be effectively targeted by an antibody-based approach.
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Most pancreatic cancer patients present with inoperable disease or develop metastases after surgery. Conventional therapies are usually ineffective in treating metastatic disease. It is evident that novel therapies remain to be developed. Transforming growth factor beta (TGF-beta) plays a key role in cancer metastasis, signaling through the TGF-beta type I/II receptors (TbetaRI/II). We hypothesized that targeting TbetaRI/II kinase activity with the novel inhibitor LY2109761 would suppress pancreatic cancer metastatic processes. The effect of LY2109761 has been evaluated on soft agar growth, migration, invasion using a fibroblast coculture model, and detachment-induced apoptosis (anoikis) by Annexin V flow cytometric analysis. The efficacy of LY2109761 on tumor growth, survival, and reduction of spontaneous metastasis have been evaluated in an orthotopic murine model of metastatic pancreatic cancer expressing both luciferase and green fluorescence proteins (L3.6pl/GLT). To determine whether pancreatic cancer cells or the cells in the liver microenvironment were involved in LY2109761-mediated reduction of liver metastasis, we used a model of experimental liver metastasis. LY2109761 significantly inhibited the L3.6pl/GLT soft agar growth, suppressed both basal and TGF-beta1-induced cell migration and invasion, and induced anoikis. In vivo, LY2109761, in combination with gemcitabine, significantly reduced the tumor burden, prolonged survival, and reduced spontaneous abdominal metastases. Results from the experimental liver metastasis models indicate an important role for targeting TbetaRI/II kinase activity on tumor and liver microenvironment cells in suppressing liver metastasis. Targeting TbetaRI/II kinase activity on pancreatic cancer cells or the cells of the liver microenvironment represents a novel therapeutic approach to prevent pancreatic cancer metastasis.
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Second-generation antipsychotics (SGAs) are increasingly prescribed to treat psychiatric symptoms in pediatric patients infected with HIV. We examined the relationship between prescribed SGAs and physical growth in a cohort of youth with perinatally acquired HIV-1 infection. Pediatric AIDS Clinical Trials Group (PACTG), Protocol 219C (P219C), a multicenter, longitudinal observational study of children and adolescents perinatally exposed to HIV, was conducted from September 2000 until May 2007. The analysis included P219C participants who were perinatally HIV-infected, 3-18 years old, prescribed first SGA for at least 1 month, and had available baseline data prior to starting first SGA. Each participant prescribed an SGA was matched (based on gender, age, Tanner stage, baseline body mass index [BMI] z score) with 1-3 controls without antipsychotic prescriptions. The main outcomes were short-term (approximately 6 months) and long-term (approximately 2 years) changes in BMI z scores from baseline. There were 236 participants in the short-term and 198 in the long-term analysis. In linear regression models, youth with SGA prescriptions had increased BMI z scores relative to youth without antipsychotic prescriptions, for all SGAs (short-term increase = 0.192, p = 0.003; long-term increase = 0.350, p < 0.001), and for risperidone alone (short-term = 0.239, p = 0.002; long-term = 0.360, p = 0.001). Participants receiving both protease inhibitors (PIs) and SGAs showed especially large increases. These findings suggest that growth should be carefully monitored in youth with perinatally acquired HIV who are prescribed SGAs. Future research should investigate the interaction between PIs and SGAs in children and adolescents with perinatally acquired HIV infection.