Height variability from the MIROC - IPCC model for the 20th century compared to that of the TOPEX/POSEIDON altimeter

Planetary waves are key to large-scale dynamical adjustment in the global ocean as they transfer energy from the east to the west side of oceanic basins; they connect the forcing in the ocean interior with the variability at its boundaries: and they change the local heat content, thus coupling oceanic, atmospheric, and biological processes. Planetary waves, mostly of the first baroclinic mode, are observed as distinctive patterns in global time series of sea surface height anomaly (SSHA) and heat storage. The goal of this study is to compare and validate large-scale SSHA signals from coupled ocean-atmosphere general circulation Model for Interdisciplinary Research on Climate (MIROC) with TOPEX/POSEIDON satellite altimeter observations. The last decade of the models` time series is selected for comparison with the altimeter data. The wave patterns are separated from the meso- and large-scale SSHA signals by digital filters calibrated to select the same spectral bands in both model and altimeter data. The band-wise comparison allows for an assessment of the model skill to simulate the dynamical components of the observed wave field. Comparisons regarding both the seasonal cycle and the Rossby wave Held differ significantly among basins. When carried within the same basin, differences can occur between equal latitudes in opposite hemispheres. Furthermore, at some latitudes the MIROC reproduces biannual, annual and semiannual planetary waves with phase speeds and average amplitudes similar to those observed by the altimeter, but with significant differences in phase. (C) 2008 Elsevier Ltd. All rights reserved.

Thermal decomposition kinetics of Brazilian limestones: effect of CO2 partial pressure

The influence of the partial pressure of carbon dioxide (CO2) on the thermal decomposition process of a calcite (CI) and a dolomite (DP) is investigated in this paper using a thermogravimetric analyser. The tests were non-isothermal at five different heating rates in dynamic atmosphere of air with 0% and 15% carbon dioxide (CO2). In the atmosphere without CO2, the average activation energies (E-alpha) were 197.4 kJ mol(-1) and 188.1 kJ mol(-1) for CI and DP, respectively. For the DP with 15% CO2, two decomposition steps were observed, indicating a change of mechanism. The values of E-alpha for 15% CO2 were 378.7 kJ mol(-1) for the CI, and 299.8 kJ mol(-1) (first decomposition) and 453.4 kJ mol(-1) (second decomposition) for the DP, showing that the determination of E-alpha for DP should in this case be considered separately in those two distinct regions. The results obtained in this study are relevant to understanding the behaviour changes in the thermal decomposition of limestones with CO2 partial pressure when applied to technologies, such as carbon capture and storage (CCS), in which carbon dioxide is present in high concentrations.

A Novel Method of Evaluating Ureteropelvic Junction Obstruction: Dynamic Near Infrared Fluorescence Imaging Compared to Standard Modalities to Assess Urinary Obstruction in a Swine Model

Purpose: Dynamic near infrared fluorescence imaging of the urinary tract provides a promising way to diagnose ureteropelvic junction obstruction. Initial studies demonstrated the ability to visualize urine flow and peristalsis in great detail. We analyzed the efficacy of near infrared imaging in evaluating ureteropelvic junction obstruction, renal involvement and the anatomical detail provided compared to conventional imaging modalities. Materials and Methods: Ten swine underwent partial or complete unilateral ureteral obstruction. Groups were survived for the short or the long term. Imaging was performed with mercaptoacetyltriglycine diuretic renogram, magnetic resonance urogram, excretory urogram, ultrasound and near infrared imaging. Scoring systems for ureteropelvic junction obstruction were developed for magnetic resonance urogram and near infrared imaging. Physicians and medical students graded ureteropelvic junction obstruction based on magnetic resonance urogram and near infrared imaging results. Results: Markers of vascular and urinary dynamics were quantitatively consistent among control renal units. The same markers were abnormal in obstructed renal units with significantly different times of renal phase peak, start of pelvic phase and start of renal uptake. Such parameters were consistent with those obtained with mercaptoacetyltriglycine diuretic renography. Near infrared imaging provided live imaging of urinary flow, which was helpful in identifying the area of obstruction for surgical planning. Physicians and medical students categorized the degree of obstruction appropriately for fluorescence imaging and magnetic resonance urogram. Conclusions: Near infrared imaging offers a feasible way to obtain live, dynamic images of urine flow and ureteral peristalsis. Qualitative and quantitative parameters were comparable to those of conventional imaging. Findings support fluorescence imaging as an accurate, easy to use method of diagnosing ureteropelvic junction obstruction.

Lumpiness, capital adjustment costs and investment dynamics

Aggregate investment in the US economy displays a hump-shaped pattern in response to shocks, and the autocorrelation of aggregate investment growth is positive for the first few quarters, turning negative for the later quarters. This paper shows that this feature of the data is the natural outcome of a two-sector consumption/investment model designed and calibrated to reproduce plant-level evidence on capita: accumulation. (C) 2012 Elsevier B.V. All rights reserved.

Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data

Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.

Hypoellipticity in spaces of ultradistributions-Study of a model case

In this work we study C (a)-hypoellipticity in spaces of ultradistributions for analytic linear partial differential operators. Our main tool is a new a-priori inequality, which is stated in terms of the behaviour of holomorphic functions on appropriate wedges. In particular, for sum of squares operators satisfying Hormander's condition, we thus obtain a new method for studying analytic hypoellipticity for such a class. We also show how this method can be explicitly applied by studying a model operator, which is constructed as a perturbation of the so-called Baouendi-Goulaouic operator.

The role of the C-terminal region of pulchellin A-chain in the interaction with membrane model systems

Pulchellin is a Ribosome Inactivating Protein containing an A-chain (PAC), whose toxic activity requires crossing the endoplasmic reticulum (ER) membrane. In this paper, we investigate the interaction between recombinant PAC (rPAC) and Langmuir monolayers of dipalmitoyl phosphatidyl glycerol (DPPG), which served as membrane model. Three catalytically active, truncated PACs with increasing deletion of the C-terminal region, possessing 244,239 and 236 residues (rPAC(244), rPAC(239) and rPAC(236)), were studied. rPAC had the strongest interaction with the DPPG monolayer, inducing a large expansion in its surface pressure-area isotherm. The affinity to DPPG decreased with increased deletion of the C-terminal region. When the C-terminal region was deleted completely (rPAC(236)), the interaction was recovered, probably because other hydrophobic regions were exposed to the membrane. Using Polarization Modulated-Infrared Reflection Absorption Spectroscopy (PM-IRRAS) we observed that at a bare air/water interface rPAC comprised mainly alpha-helix structures, the C-terminal region had unordered structures when interacting with DPPG. For rPAC(236) the alpha-helices were preserved even in the presence of DPPG. These results confirm the importance of the C-terminal region for PAC-ER membrane interaction. The partial unfolding only with preserved C-terminal appears a key step for the protein to reach the cytosol and develop its toxic activity. (C) 2011 Elsevier B.V. All rights reserved.

Modeling gene expression regulatory networks with the sparse vector autoregressive model

Abstract Background To understand the molecular mechanisms underlying important biological processes, a detailed description of the gene products networks involved is required. In order to define and understand such molecular networks, some statistical methods are proposed in the literature to estimate gene regulatory networks from time-series microarray data. However, several problems still need to be overcome. Firstly, information flow need to be inferred, in addition to the correlation between genes. Secondly, we usually try to identify large networks from a large number of genes (parameters) originating from a smaller number of microarray experiments (samples). Due to this situation, which is rather frequent in Bioinformatics, it is difficult to perform statistical tests using methods that model large gene-gene networks. In addition, most of the models are based on dimension reduction using clustering techniques, therefore, the resulting network is not a gene-gene network but a module-module network. Here, we present the Sparse Vector Autoregressive model as a solution to these problems. Results We have applied the Sparse Vector Autoregressive model to estimate gene regulatory networks based on gene expression profiles obtained from time-series microarray experiments. Through extensive simulations, by applying the SVAR method to artificial regulatory networks, we show that SVAR can infer true positive edges even under conditions in which the number of samples is smaller than the number of genes. Moreover, it is possible to control for false positives, a significant advantage when compared to other methods described in the literature, which are based on ranks or score functions. By applying SVAR to actual HeLa cell cycle gene expression data, we were able to identify well known transcription factor targets. Conclusion The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than the number of genes, making it possible to naturally infer partial Granger causalities without any a priori information. In addition, we present a statistical test to control the false discovery rate, which was not previously possible using other gene regulatory network models.

Horse spleen segmentation technique as large animal model of preclinical trials

The parenchymal distribution of the splenic artery was studied in order to obtain anatomical basis for partial splenectomy. Thirty two spleens were studied, 26 spleens of healthy horses weighing 320 to 450kg, aged 3 to 12 years and 6 spleens of fetus removed from slaughterhouse. The spleens were submitted to arteriography and scintigraphy in order to have their vascular pattern examined and compared to the external aspect of the organ aiming establish anatomo-surgical segments. All radiographs were photographed with a digital camera and the digital images were submitted to a measuring system for comparative analysis of areas of dorsal and ventral anatomo-surgical segments. Anatomical investigations into the angioarchitecture of the equine spleen showed a paucivascular area, which coincides with a thinner external area, allowing the organ to be divided in two anatomo-surgical segments of approximately 50% of the organ each.

Adhesion molecules of detrusor muscle cells are influenced by a hypercholesterolemic diet or bladder outlet obstruction in a wistar rat model

Abstract Background Cell adhesion molecules (CAMs) are essential for maintaining tissue integrity by regulating intercellular and cell to extracellular matrix interactions. Cadherins and catenins are CAMs that are located on the cell membrane and are important for adherens junction (AJ) function. This study aims to verify if hypercholesterolemic diet (HCD) or bladder outlet obstruction (BOO) promotes structural bladder wall modifications specific to alterations in the expression of cadherins and catenins in detrusor muscle cells. Methods Forty-five 4-week-old female Wistar rats were divided into the following three groups: group 1 was a control group that was fed a normal diet (ND); group 2 was the BOO model and was fed a ND; and group 3 was a control group that was fed a HCD (1.25% cholesterol). Initially, serum cholesterol, LDL cholesterol and body weight were determined. Four weeks later, groups 1 and 3 underwent a sham operation; whereas group 2 underwent a partial BOO procedure that included a suture tied around the urethra. Six weeks later, all rats had their bladders removed, and previous exams were repeated. The expression levels of N-, P-, and E-cadherin, cadherin-11 and alpha-, beta- and gamma-catenins were evaluated by immunohistochemistry with a semiquantitative analysis. Results Wistar rats fed a HCD (group 3) exhibited a significant increase in LDL cholesterol levels (p=0.041) and body weight (p=0.017) when compared to both groups that were fed a normal diet in a ten-week period. We found higher β- and γ-catenin expression in groups 2 and 3 when compared to group 1 (p = 0.042 and p = 0.044, respectively). We also observed Cadherin-11 overexpression in group 3 when compared to groups 1 and 2 (p = 0.002). Conclusions A HCD in Wistar rats promoted, in addition to higher body weight gain and increased serum LDL cholesterol levels, overexpression of β- and γ-catenin in the detrusor muscle cells. Similar finding was observed in the BOO group. Higher Cadherin-11 expression was observed only in the HCD-treated rats. These findings may be associated with bladder dysfunctions that occur under such situations.