921 resultados para Growth Models (economics)
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Aldosterone is an important factor supporting placental growth and fetal development. Recently, expression of placental growth factor (PlGF) has been observed in response to aldosterone exposure in different models of atherosclerosis. Thus, we hypothesized that aldosterone up-regulates growth-adaptive angiogenesis in pregnancy, via increased placental PlGF expression. We followed normotensive pregnant women (n = 24) throughout pregnancy and confirmed these results in a second independent first trimester cohort (n = 36). Urinary tetrahydroaldosterone was measured by gas chromatography-mass spectrometry and corrected for creatinine. Circulating PlGF concentrations were determined by ELISA. Additionally, cultured cell lines, adrenocortical H295R and choriocarcinoma BeWo cells, as well as primary human third trimester trophoblasts were tested in vitro. PlGF serum concentrations positively correlated with urinary tetrahydroaldosterone corrected for creatinine in these two independent cohorts. This observation was not due to PlGF, which did not induce aldosterone production in cultured H295R cells. On the other hand, PlGF expression was specifically enhanced by aldosterone in the presence of forskolin (p < 0.01) in trophoblasts. A pronounced stimulation of PlGF expression was observed with reduced glucose concentrations simulating starvation (p < 0.001). In conclusion, aldosterone stimulates placental PlGF production, enhancing its availability during human pregnancy, a response amplified by reduced glucose supply. Given the crucial role of PlGF in maintaining a healthy pregnancy, these data support a key role of aldosterone for a healthy pregnancy outcome.
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BACKGROUND The process of neurite outgrowth is the initial step in producing the neuronal processes that wire the brain. Current models about neurite outgrowth have been derived from classic two-dimensional (2D) cell culture systems, which do not recapitulate the topographical cues that are present in the extracellular matrix (ECM) in vivo. Here, we explore how ECM nanotopography influences neurite outgrowth. METHODOLOGY/PRINCIPAL FINDINGS We show that, when the ECM protein laminin is presented on a line pattern with nanometric size features, it leads to orientation of neurite outgrowth along the line pattern. This is also coupled with a robust increase in neurite length. The sensing mechanism that allows neurite orientation occurs through a highly stereotypical growth cone behavior involving two filopodia populations. Non-aligned filopodia on the distal part of the growth cone scan the pattern in a lateral back and forth motion and are highly unstable. Filopodia at the growth cone tip align with the line substrate, are stabilized by an F-actin rich cytoskeleton and enable steady neurite extension. This stabilization event most likely occurs by integration of signals emanating from non-aligned and aligned filopodia which sense different extent of adhesion surface on the line pattern. In contrast, on the 2D substrate only unstable filopodia are observed at the growth cone, leading to frequent neurite collapse events and less efficient outgrowth. CONCLUSIONS/SIGNIFICANCE We propose that a constant crosstalk between both filopodia populations allows stochastic sensing of nanotopographical ECM cues, leading to oriented and steady neurite outgrowth. Our work provides insight in how neuronal growth cones can sense geometric ECM cues. This has not been accessible previously using routine 2D culture systems.
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Tissue growth and regeneration are autonomous, stem-cell-mediated processes in which stem cells within the organ self-renew and differentiate to create new cells, leading to new tissue. The processes of growth and regeneration require communication and interplay between neighboring cells. In particular, cell competition, which is a process in which viable cells are actively eliminated by more competitive cells, has been increasingly implicated to play an important role. Here, we discuss the existing literature regarding the current landscape of cell competition, including classical pathways and models, fitness fingerprint mechanisms, and immune system mechanisms of cell competition. We further discuss the clinical relevance of cell competition in the physiological processes of tissue growth and regeneration, highlighting studies in clinically important disease models, including oncological, neurological, and cardiovascular diseases.
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BACKGROUND There are concerns about the effects of in utero exposure to antiretroviral drugs (ARVs) on the development of HIV-exposed but uninfected (HEU) children. The aim of this study was to evaluate whether in utero exposure to ARVs is associated with lower birth weight/height and reduced growth during the first 2 years of life. METHODS This cohort study was conducted among HEU infants born between 1996 and 2010 in Tertiary children's hospital in Rio de Janeiro, Brazil. Weight was measured by mechanical scale, and height was measured by measuring board. Z-scores for weight-for-age (WAZ), length-for-age (LAZ) and weight-for-length were calculated. We modeled trajectories by mixed-effects models and adjusted for mother's age, CD4 cell count, viral load, year of birth and family income. RESULTS A total of 588 HEU infants were included of whom 155 (26%) were not exposed to ARVs, 114 (19%) were exposed early (first trimester) and 319 (54%) later. WAZ were lower among infants exposed early compared with infants exposed later: adjusted differences were -0.52 (95% confidence interval [CI]: -0.99 to -0.04, P = 0.02) at birth and -0.22 (95% CI: -0.47 to 0.04, P = 0.10) during follow-up. LAZ were lower during follow-up: -0.35 (95% CI: -0.63 to -0.08, P = 0.01). There were no differences in weight-for-length scores. Z-scores of infants exposed late during pregnancy were similar to unexposed infants. CONCLUSIONS In HEU children, early exposure to ARVs was associated with lower WAZ at birth and lower LAZ up to 2 years of life. Growth of HEU children needs to be monitored closely.
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We propose a way to incorporate NTBs for the four workhorse models of the modern trade literature in computable general equilibrium models (CGEs). CGE models feature intermediate linkages and thus allow us to study global value chains (GVCs). We show that the Ethier-Krugman monopolistic competition model, the Melitz firm heterogeneity model and the Eaton and Kortum model can be defined as an Armington model with generalized marginal costs, generalized trade costs and a demand externality. As already known in the literature in both the Ethier-Krugman model and the Melitz model generalized marginal costs are a function of the amount of factor input bundles. In the Melitz model generalized marginal costs are also a function of the price of the factor input bundles. Lower factor prices raise the number of firms that can enter the market profitably (extensive margin), reducing generalized marginal costs of a representative firm. For the same reason the Melitz model features a demand externality: in a larger market more firms can enter. We implement the different models in a CGE setting with multiple sectors, intermediate linkages, non-homothetic preferences and detailed data on trade costs. We find the largest welfare effects from trade cost reductions in the Melitz model. We also employ the Melitz model to mimic changes in Non tariff Barriers (NTBs) with a fixed cost-character by analysing the effect of changes in fixed trade costs. While we work here with a model calibrated to the GTAP database, the methods developed can also be applied to CGE models based on the WIOD database.
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For over 3 centuries, diameter-limit harvesting has been a predominant logging method in the northeastern United States. Silvicultural theory asserts that such intensively selective harvesting can lead to genetic degradation. A decrease in softwood productivity has recently been reported in Maine - has a long history of dysgenic selection degraded the genetic resources of Maine softwoods, contributing to a decrease in growth and productivity? This study examines two aspects of potential implications of diameter-limit harvesting: effects on residual phenotypes of red spruce and impacts on genetic diversity of white pine. Radial growth of residual red spruce trees in stands experiencing 50 years of fixed diameter-limit harvesting was measured using annual increment rings and compared with residual red spruce trees in positive selection stands. Trees remaiaing after several rounds of diameter-limit harvesting exhibited sigdicantl y smaller radial sizes throughout their lives, and displayed significantly slower growth rates for the first 80 years of measured growth. These results strongly suggest that the largest and fastest-growing genotypes and their respective gene complexes determining good radial growth have been removed from the diameter-limit stand. Dysgenic selection can be observed in fixed diarneter-limit stands, resulting in a diminished genetic resource and decreased residual stand value. To examine more direct genetic implications of long-term diameter-limit harvesting, microsatellite DNA markers were implemented to study genetic diversity of eastern white pine in Maine. Three age groups of trees were studied: mature trees older than 200 years, juvenile trees 5-30 years old, and embryos. Trees were genotyped at 10 microsatellite loci. Overall genetic diversity levels of eastern white pine in Maine were extremely high, with an average observed heterozygosity of 0.762. Genetic differentiation was minimal among and between all three age groups, although an excess of heterozygotes was shown in the mature and juvenile groups that was not reflected in the embryo group, which actually had a slight heterozygote deficiency. Allele frequencies did not differ significantly between age groups, but did reveal more rare and low frequency alleles in the embryo groups than in the mature group. Overall, low frequency alleles comprise the largest portion of alleles in the sample population, with no common alleles evident overall. These results suggest that significant genetic degradation has either not occurred for white pine, or that the results of dysgenic selection have not yet emerged. It is clear, however, that selective harvesting could result in a loss of low frequency alleles, which are a primary reserve of evolutionary potential in a species. Implications of these studies affect industrial forestry, regional economics, and ecological concerns for the northeast. Long-term diameter-limit harvesting can lead to a degradation of residual phenotypes, and an overall decrease in stand quality. Potentially, a loss of low frequency, locally adapted alleles could result in a decrease of allelic richness and degradation of the regidnal genetic resource. Decreased genetic variation can lead to seriously limited evolutionary potential of species and ecosystems, particularly in rapidly changing environments. Based on these findings, I recommend a reassessment of any harvesting prescription that includes fixed diameter-limit removals, particularly for species that have low natural genetic diversity levels or a limited natural range, such as red spruce. Maintenance of a healthy genetic reserve can avoid effects of dysgenic harvesting.
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This thesis project focused on understanding the basic process controlling cell proliferation in sex-steroid hormone dependent cancers. The availability of inculture models using cloned cell lines offers the greatest advantage for studying the control of this event. Incubation of cloned sex-hormone sensitive cells in medium containing increasing concentrations of sex-hormone stripped serum, results in a dose dependent growth inhibition; this inhibition is reversed by the addition of physiological concentrations of steroid hormones. The mechanisms explaining this phenomenon are not yet fully understood, but different theories propose the existence in serum of a sex hormone binding protein with growth inhibitory properties. We were able to identify a protein that specifically binds sex hormones in rat and horse serum with affinities 10-fold lower to the ones observed with the classic sex-hormone binding globulin (SHBG) in humans. Purification of this protein on a large scale Lowed a more detailed analysis. The putative sex-hormone binding protein has an apparent molecular weight of 386 KDa. SDS-PAGE with commassie staining of the purified product, displayed a pattern non-characteristic of SMG, but all bands cross-reacted with a commercial anti-SMG antibody in western analysis. Titrations of the purified product on cell proliferation assays using sex-hormone dependent lines, resulted in a dose dependent growth inhibition. This inhibition was reversed by the addition of sex hormones. Our results indicate that we have identified and purified a sex-hormone binding protein in serum with characteristics similar to SHBG and with cell growth inhibitory properties. ^
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Anion exchange membranes (AEMs) are a potential method for determining the plant available N status of soils; however, their capacity for use with turfgrass has not been researched extensively. The main objective of this experiment was to determine the relationship between soil nitrate desorbed from AEMs and growth response and quality of turfgrass managed as a residential lawn. Two field experiments were conducted with a bluegrass-ryegrass-fescue mixture receiving four rates of N fertilizer (0, 98, 196, and 392 kg N ha(-1) yr(-1)) with clippings returned or removed. The soils at the two sites were a Paxton fine sandy loam (coarse-loamy, mixed, active, mesic Oxyaquic Dystrudepts) and a variant of a Hinckley gravelly sandy loam (sandy-skeletal, mixed, mesic Typic Udorthents). Anion exchange membranes were inserted into plots and exchanged weekly during the growing seasons of 1998 and 1999. Nitrate-N was desorbed from AEMs and quantified. As N fertilization rates increased, desorbed NO3-N increased. The relationship of desorbed NO3-N from AEMs to clipping yield and turfgrass quality was characterized using quadratic response plateau (QRP) and Cate-Nelson models (C-Ns). Critical levels of desorbed NO3-N ranged from 0.86 to 8.0 microgram cm(-2) d(-1) for relative dry matter yield (DMY) and from 2.3 to 12 microgram cm(-2) d(-1) for turfgrass quality depending upon experimental treatment. Anion exchange membranes show promise of indicating the critical levels of soil NO3-N desorbed from AEMs necessary to achieve maximum turfgrass quality and yield without overapplication of N.
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The goal of this paper is to revisit the influential work of Mauro [1995] focusing on the strength of his results under weak identification. He finds a negative impact of corruption on investment and economic growth that appears to be robust to endogeneity when using two-stage least squares (2SLS). Since the inception of Mauro [1995], much literature has focused on 2SLS methods revealing the dangers of estimation and thus inference under weak identification. We reproduce the original results of Mauro [1995] with a high level of confidence and show that the instrument used in the original work is in fact 'weak' as defined by Staiger and Stock [1997]. Thus we update the analysis using a test statistic robust to weak instruments. Our results suggest that under Mauro's original model there is a high probability that the parameters of interest are locally almost unidentified in multivariate specifications. To address this problem, we also investigate other instruments commonly used in the corruption literature and obtain similar results.
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This study examines the effect of the Great Moderation on the relationship between U.S. output growth and its volatility over the period 1947 to 2006. First, we consider the possible effects of structural change in the volatility process. In so doing, we employ GARCH-M and ARCH-M specifications of the process describing output growth rate and its volatility with and without a one-time structural break in volatility. Second, our data analyses and empirical results suggest no significant relationship between the output growth rate and its volatility, favoring the traditional wisdom of dichotomy in macroeconomics. Moreover, the evidence shows that the time-varying variance falls sharply or even disappears once we incorporate a one-time structural break in the unconditional variance of output starting 1982 or 1984. That is, the integrated GARCH effect proves spurious. Finally, a joint test of a trend change and a one-time shift in the volatility process finds that the one-time shift dominates.
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Dua and Miller (1996) created leading and coincident employment indexes for the state of Connecticut, following Moore's (1981) work at the national level. The performance of the Dua-Miller indexes following the recession of the early 1990s fell short of expectations. This paper performs two tasks. First, it describes the process of revising the Connecticut Coincident and Leading Employment Indexes. Second, it analyzes the statistical properties and performance of the new indexes by comparing the lead profiles of the new and old indexes as well as their out-of-sample forecasting performance, using the Bayesian Vector Autoregressive (BVAR) method. The new indexes show improved performance in dating employment cycle chronologies. The lead profile test demonstrates that superiority in a rigorous, non-parametric statistic fashion. The mixed evidence on the BVAR forecasting experiments illustrates the truth in the Granger and Newbold (1986) caution that leading indexes properly predict cycle turning points and do not necessarily provide accurate forecasts except at turning points, a view that our results support.
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We examine the effects of technology on productivity growth by disaggregating total output into sectoral components, exploring the roles of investment and technology on productivity growth for countries in different income groups. We find that for low-income countries, investment is the most important determinant of productivity growth. While investment plays an important role in determining productivity growth in middle-income countries, additional effects resulting from technological change also emerge. Investment ceases to have a significant effect on productivity growth in high-income countries.
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Based on an order-theoretic approach, we derive sufficient conditions for the existence, characterization, and computation of Markovian equilibrium decision processes and stationary Markov equilibrium on minimal state spaces for a large class of stochastic overlapping generations models. In contrast to all previous work, we consider reduced-form stochastic production technologies that allow for a broad set of equilibrium distortions such as public policy distortions, social security, monetary equilibrium, and production nonconvexities. Our order-based methods are constructive, and we provide monotone iterative algorithms for computing extremal stationary Markov equilibrium decision processes and equilibrium invariant distributions, while avoiding many of the problems associated with the existence of indeterminacies that have been well-documented in previous work. We provide important results for existence of Markov equilibria for the case where capital income is not increasing in the aggregate stock. Finally, we conclude with examples common in macroeconomics such as models with fiat money and social security. We also show how some of our results extend to settings with unbounded state spaces.
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This paper shows how one can infer the nature of local returns to scale at the input- or output-oriented efficient projection of a technically inefficient input-output bundle, when the input- and output-oriented measures of efficiency differ.
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Previous studies (e.g., Hamori, 2000; Ho and Tsui, 2003; Fountas et al., 2004) find high volatility persistence of economic growth rates using generalized autoregressive conditional heteroskedasticity (GARCH) specifications. This paper reexamines the Japanese case, using the same approach and showing that this finding of high volatility persistence reflects the Great Moderation, which features a sharp decline in the variance as well as two falls in the mean of the growth rates identified by Bai and Perronâs (1998, 2003) multiple structural change test. Our empirical results provide new evidence. First, excess kurtosis drops substantially or disappears in the GARCH or exponential GARCH model that corrects for an additive outlier. Second, using the outlier-corrected data, the integrated GARCH effect or high volatility persistence remains in the specification once we introduce intercept-shift dummies into the mean equation. Third, the time-varying variance falls sharply, only when we incorporate the break in the variance equation. Fourth, the ARCH in mean model finds no effects of our more correct measure of output volatility on output growth or of output growth on its volatility.