Independent relations of left ventricular structure with the 24-hour urinary excretion of sodium and aldosterone.

Previous studies reported on the association of left ventricular mass index (LVMI) with urinary sodium or with circulating or urinary aldosterone. We investigated the independent associations of LVMI with the urinary excretion of both sodium and aldosterone. We randomly recruited 317 untreated subjects from a white population (45.1% women; mean age 48.2 years). Measurements included echocardiographic left ventricular (LV) properties, the 24-hour urinary excretion of sodium and aldosterone, plasma renin activity (PRA), and proximal (RNa(prox)) and distal (RNa(dist)) renal sodium reabsorption, assessed from the endogenous lithium clearance. In multivariable-adjusted models, we expressed changes in LVMI per 1-SD increase in the explanatory variables, while accounting for sex, age, systolic blood pressure, and the waist-to-hip ratio. LVMI increased independently with the urinary excretion of both sodium (+2.48 g/m(2); P=0.005) and aldosterone (+2.63 g/m(2); P=0.004). Higher sodium excretion was associated with increased mean wall thickness (MWT: +0.126 mm, P=0.054), but with no change in LV end-diastolic diameter (LVID: +0.12 mm, P=0.64). In contrast, higher aldosterone excretion was associated with higher LVID (+0.54 mm; P=0.017), but with no change in MWT (+0.070 mm; P=0.28). Higher RNa(dist) was associated with lower relative wall thickness (-0.81x10(-2), P=0.017), because of opposite trends in LVID (+0.33 mm; P=0.13) and MWT (-0.130 mm; P=0.040). LVMI was not associated with PRA or RNa(prox.) In conclusion, LVMI independently increased with both urinary sodium and aldosterone excretion. Increased MWT explained the association of LVMI with urinary sodium and increased LVID the association of LVMI with urinary aldosterone.

Climatic extremes improve predictions of spatial patterns of tree species.

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D(2), +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

The implicit theory of historical change in the work of Alan S. Milward

Alan S. Milward was an economic historian who developed an implicit theory ofhistorical change. His interpretation which was neither liberal nor Marxist positedthat social, political, and economic change, for it to be sustainable, had to be agradual process rather than one resulting from a sudden, cataclysmicrevolutionary event occurring in one sector of the economy or society. Benignchange depended much less on natural resource endowment or technologicaldevelopments than on the ability of state institutions to respond to changingpolitical demands from within each society. State bureaucracies were fundamentalto formulating those political demands and advising politicians of ways to meetthem. Since each society was different there was no single model of developmentto be adopted or which could be imposed successfully by one nation-state onothers, either through force or through foreign aid programs. Nor coulddevelopment be promoted simply by copying the model of a more successfuleconomy. Each nation-state had to find its own response to the political demandsarising from within its society. Integration occurred when a number of nation states shared similar political objectives which they could not meet individuallybut could meet collectively. It was not simply the result of their increasinginterdependence. It was how and whether nation-states responded to thesedomestic demands which determined the nature of historical change.

The empirics of spatial competition: evidence from European regions

The New Economic Geography literature allows detailed analysis of the factors that determine the location decisions of firms in integrated markets. However, the competitive process is modelled in a rather rudimentary way, and the empirical evidence has usually been obtained from reduced-form econometric specifications. This study describes a structural model that takes into account strategic interactions between firms. We investigate the relationship between the degree of perceived competition ¿ not only from local firms but from firms in other regions ¿ and geographic concentration. The preliminary results indicate that, in aggregate terms, local firms present stronger competition than firms in other regions. Moreover, it is confirmed that greater geographical concentration of production reduces market power, due to the intensification of local competition; however, its impact on production costs is unclear.

The empirics of spatial competition: evidence from European regions

The New Economic Geography literature allows detailed analysis of the factors that determine the location decisions of firms in integrated markets. However, the competitive process is modelled in a rather rudimentary way, and the empirical evidence has usually been obtained from reduced-form econometric specifications. This study describes a structural model that takes into account strategic interactions between firms. We investigate the relationship between the degree of perceived competition ¿ not only from local firms but from firms in other regions ¿ and geographic concentration. The preliminary results indicate that, in aggregate terms, local firms present stronger competition than firms in other regions. Moreover, it is confirmed that greater geographical concentration of production reduces market power, due to the intensification of local competition; however, its impact on production costs is unclear.

Pedological and isotopic relations of a highland tropical peatland, Mountain Range of the Espinhaço Meridional (Brazil)

The evolution of organic matter sources in soil is related to climate and vegetation dynamics in the past recorded in paleoenvironmental Quaternary deposits such as peatlands. For this reason, a Histosol of the mineralotrophic peatland from the Pau-de-Fruta Special Protection Area - SPA, Espinhaço Meridional, State of Minas Gerais, was described and characterized to evidence the soil constituent materials and properties as related to changes in environmental conditions, supported by the isotopic and elementary characterization of soil C and N and 14C ages. Samples were collected in a depression at 1,350 m asl, where Histosols are possibly more developed due to the great thickness (505 cm). Nowadays, the area is colonized by vegetation physiognomies of the Cerrado Biome, mainly rocky and wet fields (Campo Rupestre and Campo Úmido), aside from fragments of Semidecidual Seasonal Forest, called Capões forests. The results this study showed that early the genesis of the analyzed soil profile showed a high initial contribution of mostly herbaceous organic matter before 8,090 ± 30 years BP (14C age). In the lower-mid Holocene, between 8,090 ± 30 years AP (14C age) to ± 4,100 years BP (interpolated age), the vegetation gradually became more woody, with forest expansion, possibly due to increased humidity, suggesting the existence of a more woody Cerrado in the past than at present. Drier climate conditions than the current were concluded ± 2,500 years BP (interpolated age) and that after 430 years BP (14C age) the forest gave way to grassland, predominantly. After the dry season, humidity increased to the current conditions. Due to these climate fluctuations during the Holocene, three decomposition stages of organic matter were observed in the Histosols of this study, with prevalence of the most advanced (sapric), typical of a deposit in a highly advanced stage of pedogenetic evolution.

Uncertainties in the prediction of spatial variability of soil CO2 emissions and related properties

The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.

Automatic Mapping and Classification of Spatial Environmental Data

The paper deals with the development and application of the generic methodology for automatic processing (mapping and classification) of environmental data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve the problem of spatial data mapping (regression). The Probabilistic Neural Network (PNN) is considered as an automatic tool for spatial classifications. The automatic tuning of isotropic and anisotropic GRNN/PNN models using cross-validation procedure is presented. Results are compared with the k-Nearest-Neighbours (k-NN) interpolation algorithm using independent validation data set. Real case studies are based on decision-oriented mapping and classification of radioactively contaminated territories.

Regression analysis of spatial data.

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

H2O-δD-Fe-III relations of dehydrogenation and dehydration processes in magmatic amphiboles

Stable isotope compositions of a suite of magmatic amphiboles from alkaline basalts and andesitic rocks were examined to constrain the effects of degassing processes on the hydrogen isotope compositions. The Fe3+ (as Fe3+/Fe-total) and H2O contents, as well as the H isotope compositions of the amphiboles, differ markedly (27-58%, 0.5-2.2 wt%, -107 to -15 parts per thousand, respectively) but indicate systematic variations. The observed trends can be explained either as dehydrogenation or dehydration processes, both of which are coupled to oxidation processes, the latter most probably related to O2- substitution within amphiboles. The dehydrogenation-dehydration models can be used to assess the primary compositions of the magmas. As an important example, delta D values of amphiboles of Martian meteorites are discussed in a similar context. Copyright (c) 2006 John Wiley & Sons, Ltd.

Independent relations of left ventricular structure with the 24-h urinary excretion of sodium and aldosterone

Objective: Previous studies reported on the association of left ventricular mass index (LVMI) with urinary sodium or with circulating or urinary aldosterone.We investigated the independent associations of LVMI with the urinary excretion of both sodium and aldosterone. Design and method: We randomly recruited 317 untreated subjects from a White population (45.1%women; mean age 48.2 years).Measurements included echocardiographic left ventricular (LV) properties, the 24 h urinary excretion of sodium and aldosterone, plasma renin activity (PRA), and proximal (RNaprox) and distal (RNadist) renal sodium reabsorption, assessed fromthe endogenous lithium clearance. Inmultivariable-adjusted models,we expressed changes in LVMI per 1 SD increase in the explanatory variables, while accounting for sex, age, systolic blood pressure and the waist-to-hip ratio. Results: LVMI increased independentlywith the urinary excretion of both sodium (+2.48 g/m2; P=0.005) and aldosterone (+2.63 g/m2; P=0.004). Higher sodium excretion was associated with increased mean wall thickness (MWT: +0.126 mm, P=0.054), but with no change in LV end-diastolic diameter (LVID: +0.12mm, P=0.64). In contrast, higher aldosterone excretion was associated with higher LVID (+0.54 mm; P=0.017), but with no change in MWT (+0.070mm; P=0.28).Higher RNadistwas associatedwith lower relativewall thickness (−0.81×10−2, P=0.017), because of opposite trends in LVID(+0.33 mm; P=0.13) and MWT (−0.130mm; P=0.040). LVMI was not associated with PRA or RNaprox. Conclusions: LVMI independently increased with both urinary sodium and aldosterone excretion. IncreasedMWT explained the association of LVMI with urinary sodium and increased LVID the association of LVMI with urinary aldosterone.

The impact of spatial resolution and respiratory motion on MR imaging of atherosclerotic plaque.

PURPOSE: To examine the impact of spatial resolution and respiratory motion on the ability to accurately measure atherosclerotic plaque burden and to visually identify atherosclerotic plaque composition. MATERIALS AND METHODS: Numerical simulations of the Bloch equations and vessel wall phantom studies were performed for different spatial resolutions by incrementally increasing the field of view. In addition, respiratory motion was simulated based on a measured physiologic breathing pattern. RESULTS: While a spatial resolution of > or = 6 pixels across the wall does not result in significant errors, a resolution of < or = 4 pixels across the wall leads to an overestimation of > 20%. Using a double-inversion T2-weighted turbo spin echo sequence, a resolution of 1 pixel across equally thick tissue layers (fibrous cap, lipid, smooth muscle) and a respiratory motion correction precision (gating window) of three times the thickness of the tissue layer allow for characterization of the different coronary wall components. CONCLUSIONS: We found that measurements in low-resolution black blood images tend to overestimate vessel wall area and underestimate lumen area.