870 resultados para common factor models
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Voluntary physical activity improves memory and learning ability in rodents, whereas status epilepticus has been associated with memory impairment. Physical activity and seizures have been associated with enhanced hippocampal expression of BDNF, indicating that this protein may have a dual role in epilepsy. The influence of voluntary physical activity on memory and BDNF expression has been poorly studied in experimental models of epilepsy. In this paper, we have investigated the effect of voluntary physical activity on memory and BDNF expression in mice with pilocarpine-incluced epilepsy. Male Swiss mice were assigned to four experimental groups: pilocarpine sedentary (PS), pilocarpine runners (PRs), saline sedentary (SS) and saline runners (SRs). Two days after pilocarpine-induced status epilepticus, the affected mice (PR) and their running controls (SR) were housed with access to a running wheel for 28 days. After that, the spatial memory and the expression of the precursor and mature forms of hippocampal BDNF were assessed. PR mice performed better than PS mice in the water maze test. In addition, PR mice had a higher amount of mature BDNF (14 kDa) relative to the total BDNF (14 kDa + 28 kDa + 32 kDa forms) content when compared with PS mice. These results show that voluntary physical activity improved the spatial memory and increased the hippocampal content of mature BDNF of mice with pilocarpine-induced status epilepticus. (C) 2009 Elsevier B.V. All rights reserved.
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The molecular mechanism of factor Xa (FXa) inhibition by Alboserpin, the major salivary gland anticoagulant from the mosquito and yellow fever vector Aedes albopictus, has been characterized. cDNA of Alboserpin predicts a 45-kDa protein that belongs to the serpin family of protease inhibitors. Recombinant Alboserpin displays stoichiometric, competitive, reversible and tight binding to FXa (picomolar range). Binding is highly specific and is not detectable for FX, catalytic site-blocked FXa, thrombin, and 12 other enzymes. Alboserpin displays high affinity binding to heparin (K(D) similar to 20 nM), but no change in FXa inhibition was observed in the presence of the cofactor, implying that bridging mechanisms did not take place. Notably, Alboserpin was also found to interact with phosphatidylcholine and phosphatidylethanolamine but not with phosphatidylserine. Further, annexin V (in the absence of Ca(2+)) or heparin outcompetes Alboserpin for binding to phospholipid vesicles, suggesting a common binding site. Consistent with its activity, Alboserpin blocks prothrombinase activity and increases both prothrombin time and activated partial thromboplastin time in vitro or ex vivo. Furthermore, Alboserpin prevents thrombus formation provoked by ferric chloride injury of the carotid artery and increases bleeding in a dose-dependent manner. Alboserpin emerges as an atypical serpin that targets FXa and displays unique phospholipid specificity. It conceivably uses heparin and phosphatidylcholine/phosphatidylethanolamine as anchors to increase protein localization and effective concentration at sites of injury, cell activation, or inflammation.
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Diabetic patients have increased susceptibility to infection, which may be related to impaired inflammatory response observed in experimental models of diabetes, and restored by insulin treatment. The goal of this study was to investigate whether insulin regulates transcription of cytokines and intercellular adhesion molecule 1 (ICAM-1) via nuclear factor-kappa B (NF-kappa B) signaling pathway in Escherichia coli LIPS-induced lung inflammation. Diabetic male Wistar rats (alloxan, 42 mg/kg, iv., 10 days) and controls were instilled intratracheally with saline containing LPS (750 mu g/0.4 mL) or saline only. Some diabetic rats were given neutral protamine Hagedorn insulin (4 IU, s.c.) 2 h before LIPS. Analyses performed 6 h after LPS included: (a) lung and mesenteric lymph node IL-1 beta, TNF-alpha, IL-10, and ICAM-1 messenger RNA (mRNA) were quantified by real-time reverse transcriptase-polymerase chain reaction; (b) number of neutrophils in the bronchoalveolar lavage (BAL) fluid, and concentrations of IL-1 beta, TNF-alpha, and IL-10 in the BAL were determined by the enzyme-linked immunosorbent assay; and (c) activation of NF-kappa B p65 subunit and phosphorylation of I-kappa B alpha were quantified by Western blot analysis. Relative to controls, diabetic rats exhibited a reduction in lung and mesenteric lymph node IL-1 beta (40%), TNF-alpha (similar to 30%), and IL-10 (similar to 40%) mRNA levels and reduced concentrations of IL-1 beta (52%), TNF-alpha (62%), IL-10 (43%), and neutrophil counts (72%) in the BAL. Activation of NF-kappa B p65 subunit and phosphorylation of I-kappa B alpha were almost suppressed in diabetic rats. Treatment of diabetic rats with insulin completely restored mRNA and protein levels of these cytokines and potentiated lung ICAM-1 mRNA levels (30%) and number of neutrophils (72%) in the BAL. Activation of NF-kappa B p65 subunit and phosphorylation of I-kappa B alpha were partially restored by insulin treatment. In conclusion, data presented suggest that insulin regulates transcription of proinflammatory (IL-1 beta, TNF-alpha) and anti-inflammatory (IL-10) cytokines, and expression of ICAM-1 via the NF-kappa B signaling pathway.
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immunodeficiency (CVID), the most common symptomatic primary immunodeficiency in adulthood. Different authors report high prevalences of autoimmune diseases in CVID, and several mechanisms have been proposed to explain this apparent paradox. Genetic predisposition, under current surveillance, innate and adaptive immunity deficiencies leading to persistent/recurrent infections, variable degrees of immune dysregulation, and possible failure in central and peripheral mechanisms of tolerance induction or maintenance may all contribute to increased autoimmunity. Conclusions Data on the clinical/immunological profile of affected patients and treatment are available mostly concerning autoimmune cytopenias, the most common autoimmune diseases in CVID. Treatment is based on conventional alternatives, in association with short experience with new agents, including rituximab and infliximab. Benefits of early immunoglobulin substitutive treatment and hypothetical premature predictors of autoimmunity are discussed as potential improvements to CVID patients` follow-up.
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Common variable immunodeficiency (CVID) is a primary immunodeficiency characterized by hypogammaglobulinemia and recurrent infections. Herein we addressed the role of unfolded protein response (UPR) in the pathogenesis of the disease. Augmented unspliced X-box binding protein 1 (XBP-1) mRNA concurrent with co-localization of IgM and BiP/GRP78 were found in one CVID patient. At confocal microscopy analysis this patient`s cells were enlarged and failed to present the typical surface distribution of IgM, which accumulated within an abnormally expanded endoplasmic reticulum. Sequencing did not reveal any mutation on XBP-1, neither on IRE-1 alpha that could potentially prevent the splicing to occur. Analysis of spliced XBP-1, IRE-1 alpha and BiP messages after LPS or Brefeldin A treatment showed that, unlike healthy controls that respond to these endoplasmic reticulum (ER) stressors by presenting waves of transcription of these three genes, this patient`s cells presented lower rates of transcription, not reaching the same level of response of healthy subjects even after 48 h of ER stress. Treatment with DMSO rescued IgM and IgG secretion as well as the expression of spliced XBP-1. Our findings associate diminished splicing of XBP-1 mRNA with accumulation of IgM within the ER and lower rates of chaperone transcription, therefore providing a mechanism to explain the observed hypogammaglobulinemia. (C) 2008 Elsevier Ltd. All rights reserved.
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Linear mixed models were developed to handle clustered data and have been a topic of increasing interest in statistics for the past 50 years. Generally. the normality (or symmetry) of the random effects is a common assumption in linear mixed models but it may, sometimes, be unrealistic, obscuring important features of among-subjects variation. In this article, we utilize skew-normal/independent distributions as a tool for robust modeling of linear mixed models under a Bayesian paradigm. The skew-normal/independent distributions is an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal distribution, skew-t, skew-slash and the skew-contaminated normal distributions as special cases, providing an appealing robust alternative to the routine use of symmetric distributions in this type of models. The methods developed are illustrated using a real data set from Framingham cholesterol study. (C) 2009 Elsevier B.V. All rights reserved.
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In many statistical inference problems, there is interest in estimation of only some elements of the parameter vector that defines the adopted model. In general, such elements are associated to measures of location and the additional terms, known as nuisance parameters, to control the dispersion and asymmetry of the underlying distributions. To estimate all the parameters of the model and to draw inferences only on the parameters of interest. Depending on the adopted model, this procedure can be both algebraically is common and computationally very costly and thus it is convenient to reduce it, so that it depends only on the parameters of interest. This article reviews estimation methods in the presence of nuisance parameters and consider some applications in models recently discussed in the literature.
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The aim of this study was to investigate how electricallyheated houses can be converted to using wood pellet and solarheating. There are a large number of wood pellet stoves on themarket. Many stoves have a water jacket, which gives anopportunity to distribute the heat to domestic hot water and aradiator heating system. Three typical Swedish houses with electric resistanceheating have been studied. Fourteen different system conceptsusing wood pellet stoves and solar heating systems have beenevaluated. The systems and the houses have been simulated indetail using TRNSYS. The houses have been divided in up to 10different zones and heat transfer by air circulation throughdoorways and open doors have been simulated. The pellet stoveswere simulated using a recently developed TRNSYS component,which models the start- and stop phases, emissions and thedynamic behaviour of the stoves. The model also calculates theCO-emissions. Simulations were made with one stove without awater jacket and two stoves with different fractions of thegenerated heat distributed in the water circuit. Simulations show that the electricity savings using a pelletstove are greatly affected by the house plan, the systemchoice, if the internal doors are open or closed and thedesired level of comfort. Installing a stove with awater-jacket connected to a radiator system and a hot waterstorage has the advantage that heat can be transferred todomestic hot water and be distributed to other rooms. Suchsystems lead to greater electricity savings, especially inhouses having a traditional layout. It was found that not allrooms needed radiators and that it was more effective in mostcases t use a stove with a higher fraction of the heatdistributed by the water circuit. The economic investigation shows that installing a woodpellet stove without a water jacket gives the lowest totalenergy- and capital costs in the house with an open plan (fortoday's energy prices and the simulated comfort criteria). Inthe houses with a traditional layout a pellet stove givesslightly higher costs than the reference house having onlyelectrical resistance heating due to the fact that less heatingcan be replaced. The concepts including stoves with a waterjacket all give higher costs than the reference system, but theconcept closest to be economical is a system with a bufferstore, a stove with a high fraction of the heat distributed bythe water circuit, a new water radiator heating system and asolar collector. Losses from stoves can be divided into: flue gas lossesincluding leakage air flow when the stove is not in operation;losses during start and stop phases; and losses due to a highair factor. An increased efficiency of the stoves is importantboth from a private economical point of view, but also from theperspective that there can be a lack of bio fuel in the nearfuture also in Sweden. From this point of view it is alsoimportant to utilize as much solar heat as possible. Theutilization of solar heat is low in the simulated systems,depending on the lack of space for a large buffer store. The simulations have shown that the annual efficiency ismuch lower that the nominal efficiency at full power. Thesimulations have also shown that changing the control principlefor the stove can improve efficiency and reduce theCO-emissions. Today's most common control principle for stovesis the on/off control, which results in many starts and stopsand thereby high CO-emissions. A more advanced control varyingthe heating rate from maximum to minimum to keep a constantroom temperature reduces the number of starts and stops andthereby the emissions. Also the efficiency can be higher withsuch a control, and the room temperature will be kept at a moreconstant temperature providing a higher comfort.
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This paper investigates common nonlinear features in multivariate nonlinear autore-gressive models via testing the estimated residuals. A Wald-type test is proposed and itis asymptotically Chi-squared distributed. Simulation studies are given to examine thefinite-sample properties of the proposed test.
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AIMS/HYPOTHESIS: Soluble tumor necrosis factor receptors 1 and 2 (sTNFR1 and sTNFR2) contribute to experimental diabetic kidney disease, a condition with substantially increased cardiovascular risk when present in patients. Therefore, we aimed to explore the levels of sTNFRs, and their association with prevalent kidney disease, incident cardiovascular disease, and risk of mortality independently of baseline kidney function and microalbuminuria in a cohort of patients with type 2 diabetes. In pre-defined secondary analyses we also investigated whether the sTNFRs predict adverse outcome in the absence of diabetic kidney disease. METHODS: The CARDIPP study, a cohort study of 607 diabetes patients [mean age 61 years, 44 % women, 45 cardiovascular events (fatal/non-fatal myocardial infarction or stroke) and 44 deaths during follow-up (mean 7.6 years)] was used. RESULTS: Higher sTNFR1 and sTNFR2 were associated with higher odds of prevalent kidney disease [odd ratio (OR) per standard deviation (SD) increase 1.60, 95 % confidence interval (CI) 1.32-1.93, p < 0.001 and OR 1.54, 95 % CI 1.21-1.97, p = 0.001, respectively]. In Cox regression models adjusting for age, sex, glomerular filtration rate and urinary albumin/creatinine ratio, higher sTNFR1 and sTNFR2 predicted incident cardiovascular events [hazard ratio (HR) per SD increase, 1.66, 95 % CI 1.29-2.174, p < 0.001 and HR 1.47, 95 % CI 1.13-1.91, p = 0.004, respectively]. Results were similar in separate models with adjustments for inflammatory markers, HbA1c, or established cardiovascular risk factors, or when participants with diabetic kidney disease at baseline were excluded (p < 0.01 for all). Both sTNFRs were associated with mortality. CONCLUSIONS/INTERPRETATIONS: Higher circulating sTNFR1 and sTNFR2 are associated with diabetic kidney disease, and predicts incident cardiovascular disease and mortality independently of microalbuminuria and kidney function, even in those without kidney disease. Our findings support the clinical utility of sTNFRs as prognostic markers in type 2 diabetes.
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Using vector autoregressive (VAR) models and Monte-Carlo simulation methods we investigate the potential gains for forecasting accuracy and estimation uncertainty of two commonly used restrictions arising from economic relationships. The Örst reduces parameter space by imposing long-term restrictions on the behavior of economic variables as discussed by the literature on cointegration, and the second reduces parameter space by imposing short-term restrictions as discussed by the literature on serial-correlation common features (SCCF). Our simulations cover three important issues on model building, estimation, and forecasting. First, we examine the performance of standard and modiÖed information criteria in choosing lag length for cointegrated VARs with SCCF restrictions. Second, we provide a comparison of forecasting accuracy of Ötted VARs when only cointegration restrictions are imposed and when cointegration and SCCF restrictions are jointly imposed. Third, we propose a new estimation algorithm where short- and long-term restrictions interact to estimate the cointegrating and the cofeature spaces respectively. We have three basic results. First, ignoring SCCF restrictions has a high cost in terms of model selection, because standard information criteria chooses too frequently inconsistent models, with too small a lag length. Criteria selecting lag and rank simultaneously have a superior performance in this case. Second, this translates into a superior forecasting performance of the restricted VECM over the VECM, with important improvements in forecasting accuracy ñreaching more than 100% in extreme cases. Third, the new algorithm proposed here fares very well in terms of parameter estimation, even when we consider the estimation of long-term parameters, opening up the discussion of joint estimation of short- and long-term parameters in VAR models.
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In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the period 1976-1992. We also test a conditional APT modeI by using the difference between the 3-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from individual securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be important for the appropriate pricing of the portfolios.
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Using the Pricing Equation in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) which relies on the fact that its logarithm is the serial-correlation ìcommon featureîin every asset return of the economy. Our estimator is a simple function of asset returns, does not depend on any parametric function representing preferences, is suitable for testing di§erent preference speciÖcations or investigating intertemporal substitution puzzles, and can be a basis to construct an estimator of the risk-free rate. For post-war data, our estimator is close to unity most of the time, yielding an average annual real discount rate of 2.46%. In formal testing, we cannot reject standard preference speciÖcations used in the literature and estimates of the relative risk-aversion coe¢ cient are between 1 and 2, and statistically equal to unity. Using our SDF estimator, we found little signs of the equity-premium puzzle for the U.S.
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Although there has been substantial research on long-run co-movement (common trends) in the empirical macroeconomics literature. little or no work has been done on short run co-movement (common cycles). Investigating common cycles is important on two grounds: first. their existence is an implication of most dynamic macroeconomic models. Second. they impose important restrictions on dynamic systems. Which can be used for efficient estimation and forecasting. In this paper. using a methodology that takes into account short- and long-run co-movement restrictions. we investigate their existence in a multivariate data set containing U.S. per-capita output. consumption. and investment. As predicted by theory. the data have common trends and common cycles. Based on the results of a post-sample forecasting comparison between restricted and unrestricted systems. we show that a non-trivial loss of efficiency results when common cycles are ignored. If permanent shocks are associated with changes in productivity. the latter fails to be an important source of variation for output and investment contradicting simple aggregate dynamic models. Nevertheless. these shocks play a very important role in explaining the variation of consumption. Showing evidence of smoothing. Furthermore. it seems that permanent shocks to output play a much more important role in explaining unemployment fluctuations than previously thought.
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Using the Pricing Equation, in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) mimicking portfolio which relies on the fact that its logarithm is the ìcommon featureîin every asset return of the economy. Our estimator is a simple function of asset returns and does not depend on any parametric function representing preferences, making it suitable for testing di§erent preference speciÖcations or investigating intertemporal substitution puzzles.