Molecular and therapeutic characterization of anti-ectodysplasin A receptor (EDAR) agonist monoclonal antibodies.

The TNF family ligand ectodysplasin A (EDA) and its receptor EDAR are required for proper development of skin appendages such as hair, teeth, and eccrine sweat glands. Loss of function mutations in the Eda gene cause X-linked hypohidrotic ectodermal dysplasia (XLHED), a condition that can be ameliorated in mice and dogs by timely administration of recombinant EDA. In this study, several agonist anti-EDAR monoclonal antibodies were generated that cross-react with the extracellular domains of human, dog, rat, mouse, and chicken EDAR. Their half-life in adult mice was about 11 days. They induced tail hair and sweat gland formation when administered to newborn EDA-deficient Tabby mice, with an EC(50) of 0.1 to 0.7 mg/kg. Divalency was necessary and sufficient for this therapeutic activity. Only some antibodies were also agonists in an in vitro surrogate activity assay based on the activation of the apoptotic Fas pathway. Activity in this assay correlated with small dissociation constants. When administered in utero in mice or at birth in dogs, agonist antibodies reverted several ectodermal dysplasia features, including tooth morphology. These antibodies are therefore predicted to efficiently trigger EDAR signaling in many vertebrate species and will be particularly suited for long term treatments.

Mapping, organic matter mass and water volume of a peatland in Serra do Espinhaço Meridional

Peatlands form in areas where net primary of organic matter production exceeds losses due to the decomposition, leaching or disturbance. Due to their chemical and physical characteristics, bogs can influence water dynamics because they can store large volumes of water in the rainy season and gradually release this water during the other months of the year. In Diamantina, Minas Gerais, Brazil, a peatland in the environmental protection area of Pau-de-Fruta ensures the water supply of 40,000 inhabitants. The hypothesis of this study is that the peat bogs in Pau-de-Fruta act as an environment for carbon storage and a regulator of water flow in the Córrego das Pedras basin. The objective of this study was to estimate the water volume and organic matter mass in this peatland and to study the influence of this environment on the water flow in the Córrego das Pedras basin. The peatland was mapped using 57 transects, at intervals of 100 m. Along all transects, the depth of the peat bog, the Universal Transverse Mercator (UTM) coordinates and altitude were recorded every 20 m and used to calculate the area and volume of the peatland. The water volume was estimated, using a method developed in this study, and the mass of organic matter based on samples from 106 profiles. The peatland covered 81.7 hectares (ha), and stored 497,767 m³ of water, representing 83.7 % of the total volume of the peat bog. The total amount of organic matter (OM) was 45,148 t, corresponding to 552 t ha-1 of OM. The peat bog occupies 11.9 % of the area covered by the Córrego das Pedras basin and stores 77.6 % of the annual water surplus, thus controlling the water flow in the basin and consequently regulating the water course.

Digital soil mapping: strategy for data pre-processing

The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM). Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree (DT) models. Three DT models derived from eight predictive covariates, related to relief and organism factors sampled on the original polygons of a soil map and on polygons shrunk by 100 and 160 m were used to predict soil classes. The DT model derived from observations 160 m away from the edge of the polygons on the original map is less complex and has a better predictive performance.

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.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

An appropriate data set size for digital soil mapping in Erechim, Rio Grande do Sul, Brazil

Digital information generates the possibility of a high degree of redundancy in the data available for fitting predictive models used for Digital Soil Mapping (DSM). Among these models, the Decision Tree (DT) technique has been increasingly applied due to its capacity of dealing with large datasets. The purpose of this study was to evaluate the impact of the data volume used to generate the DT models on the quality of soil maps. An area of 889.33 km² was chosen in the Northern region of the State of Rio Grande do Sul. The soil-landscape relationship was obtained from reambulation of the studied area and the alignment of the units in the 1:50,000 scale topographic mapping. Six predictive covariates linked to the factors soil formation, relief and organisms, together with data sets of 1, 3, 5, 10, 15, 20 and 25 % of the total data volume, were used to generate the predictive DT models in the data mining program Waikato Environment for Knowledge Analysis (WEKA). In this study, sample densities below 5 % resulted in models with lower power of capturing the complexity of the spatial distribution of the soil in the study area. The relation between the data volume to be handled and the predictive capacity of the models was best for samples between 5 and 15 %. For the models based on these sample densities, the collected field data indicated an accuracy of predictive mapping close to 70 %.

Surface mapping, organic matter and water stocks in peatlands of the Serra do Espinhaço meridional - Brazil

Peatlands are soil environments that store carbon and large amounts of water, due to their composition (90 % water), low hydraulic conductivity and a sponge-like behavior. It is estimated that peat bogs cover approximately 4.2 % of the Earth's surface and stock 28.4 % of the soil carbon of the planet. Approximately 612 000 ha of peatlands have been mapped in Brazil, but the peat bogs in the Serra do Espinhaço Meridional (SdEM) were not included. The objective of this study was to map the peat bogs of the northern part of the SdEM and estimate the organic matter pools and water volume they stock. The peat bogs were pre-identified and mapped by GIS and remote sensing techniques, using ArcGIS 9.3, ENVI 4.5 and GPS Track Maker Pro software and the maps validated in the field. Six peat bogs were mapped in detail (1:20,000 and 1:5,000) by transects spaced 100 m and each transect were determined every 20 m, the UTM (Universal Transverse Mercator) coordinates, depth and samples collected for characterization and determination of organic matter, according to the Brazilian System of Soil Classification. In the northern part of SdEM, 14,287.55 ha of peatlands were mapped, distributed over 1,180,109 ha, representing 1.2 % of the total area. These peatlands have an average volume of 170,021,845.00 m³ and stock 6,120,167 t (428.36 t ha-1) of organic matter and 142,138,262 m³ (9,948 m³ ha-1) of water. In the peat bogs of the Serra do Espinhaço Meridional, advanced stages of decomposing (sapric) organic matter predominate, followed by the intermediate stage (hemic). The vertical growth rate of the peatlands ranged between 0.04 and 0.43 mm year-1, while the carbon accumulation rate varied between 6.59 and 37.66 g m-2 year-1. The peat bogs of the SdEM contain the headwaters of important water bodies in the basins of the Jequitinhonha and San Francisco Rivers and store large amounts of organic carbon and water, which is the reason why the protection and preservation of these soil environments is such an urgent and increasing need.

The malaria circumsporozoite protein has two functional domains, each with distinct roles as sporozoites journey from mosquito to mammalian host.

Plasmodium sporozoites make a remarkable journey from the mosquito midgut to the mammalian liver. The sporozoite's major surface protein, circumsporozoite protein (CSP), is a multifunctional protein required for sporozoite development and likely mediates several steps of this journey. In this study, we show that CSP has two conformational states, an adhesive conformation in which the C-terminal cell-adhesive domain is exposed and a nonadhesive conformation in which the N terminus masks this domain. We demonstrate that the cell-adhesive domain functions in sporozoite development and hepatocyte invasion. Between these two events, the sporozoite must travel from the mosquito midgut to the mammalian liver, and N-terminal masking of the cell-adhesive domain maintains the sporozoite in a migratory state. In the mammalian host, proteolytic cleavage of CSP regulates the switch to an adhesive conformation, and the highly conserved region I plays a critical role in this process. If the CSP domain architecture is altered such that the cell-adhesive domain is constitutively exposed, the majority of sporozoites do not reach their target organs, and in the mammalian host, they initiate a blood stage infection directly from the inoculation site. These data provide structure-function information relevant to malaria vaccine development.

Mapping the development of the human connectome

From birth to early adulthood the brain undergoes dramatic modifications resulting in network development and optimization. In the present study we investigate the development of the human connectome but measuring myelination trajectories of individual connections over the entire brain structural network using high b-value diffusion imaging and tractography. We found significant changes in several network measures that support increased integration and efficiency. We also observe that the network doesn't myelinate at a uniform rate but with different myelination speeds dependant on the type of cortex.

Contexts and typologies in the analysis of welfare state legitimacy : a social psychological approach to political opinion formation

This dissertation analyses public opinion towards the welfare state across 29 European countries. Based on an interdisciplinary approach combining social psychological, sociological, and public opinion approaches to political opinion formation, it investigates how social position and shared beliefs shape perceived legitimacy of welfare institutions, and how social contexts impact on the processes of opinion formation. Drawing on social representations theory, as well as socialization and self-interest approaches, the dissertation analyses the role of social position in lay support for institutional solidarity. Normative beliefs-defined as preferred views regarding the organisation of social relations-mediate the effect of social position on welfare support. In addition, drawing on public opinion literature, the dissertation analyses opinion formation as a function of country-level structural (e.g., level of social spending, unemployment) and ideological factors (e.g., level of meritocracy). The dissertation comprises two theoretical and four empirical chapters. Three of the empirical chapters use data from the European Social Survey 2008. Using multilevel and typological approaches, the dissertation contributes to welfare attitude literature by showing that normative beliefs, such as distrust or egalitarianism, function as underlying mechanisms that link social position to policy attitudes (Chapter 3), and that characteristics of the national contexts influence the processes of political opinion formation (Chapters 3 and 4). Chapter 5 proposes and predicts a typology of the relationship between attitudes towards solidarity and attitudes towards control, reflecting the two central domains of government intervention. Finally, Chapter 6 examines welfare support in the realm of action and social protest, using data from a survey on Spanish Indigados activists. The findings of this dissertation inform contemporary debates about welfare state legitimacy and retrenchment. - Cette thèse avait pour but d'analyser l'opinion publique envers l'Etat social dans 29 pays européens. Basée sur une approche interdisciplinaire qui combine des perspectives psycho-sociales, sociologiques et d'opinion publique sur la formation d'opinion politique, la thèse étudie comment la position sociale et les croyances partagées façonnent la légitimité perçue des institutions de l'Etat social, et comment les contextes sociaux influencent les processus de formation d'opinion. Basée sur la théorie des représentations sociales, ainsi qu'une approche de socialisation et d'intérêt propre, cette thèse analyse le rôle des positions sociales dans le soutien envers la solidarité institutionnelle. Les croyances normatives-définies comme les visions préférées de l'organisation des rapports sociaux-médiatisent l'effet de la position sociale sur le soutien pour l'Etat social. De plus, s'inspirant de la littérature sur l'opinion publique, la thèse analyse la formation d'opinion en fonction des facteurs structurels (ex. le taux de dépenses sociales, le chômage) et idéologiques (ex. le degré de méritocratie). Cette thèse est composée de deux chapitres théoriques et quatre chapitres empiriques. Trois chapitres empiriques utilisent des données provenant de l'enquête European Social Survey 2008. Appliquant des approches multi-niveux et typoloqiques, la thèse contribue à la littérature sur les attitudes envers l'Etat social en montrant que les croyances normatives, telles que la méfiance ou l'égalitarisme, fonctionnent comme des mécanismes sous-jacents qui relient la position sociale aux attitudes politiques (Chapitre 3), et que les caractéristiques des contextes nationaux influencent les processus de formation d'opinion politique (Chapitres 3 et 4). Le chapitre 5 propose et prédit une typologie sur le rapport entre les attitudes envers la solidarité et celles envers le contrôle, renvoyant à deux domaines centraux de régulation étatique. Enfin, le chapitre 6 examine le soutien à l'Etat social dans le domaine de l'action protestataire, utilisant des données d'une enquête menée auprès des militants espagnols du mouvement des Indignés. Les résultats de cette thèse apportent des éléments qui éclairent les débats contemporains sur la légitimité de l'Etat social et son démantèlement.

Genetic removal of tri-unsaturated fatty acids suppresses developmental and molecular phenotypes of an Arabidopsis tocopherol-deficient mutant. Whole-body mapping of malondialdehyde pools in a complex eukaryote.

Malondialdehyde (MDA) is a small, ubiquitous, and potentially toxic aldehyde that is produced in vivo by lipid oxidation and that is able to affect gene expression. Tocopherol deficiency in the vitamin E2 mutant vte2-1 of Arabidopsis thaliana leads to massive lipid oxidation and MDA accumulation shortly after germination. MDA accumulation correlates with a strong visual phenotype (growth reduction, cotyledon bleaching) and aberrant GST1 (glutathione S-transferase 1) expression. We suppressed MDA accumulation in the vte2-1 background by genetically removing tri-unsaturated fatty acids. The resulting quadruple mutant, fad3-2 fad7-2 fad8 vte2-1, did not display the visual phenotype or the aberrant GST1 expression observed in vte2-1. Moreover, cotyledon bleaching in vte2-1 was chemically phenocopied by treatment of wild-type plants with MDA. These data suggest that products of tri-unsaturated fatty acid oxidation underlie the vte2-1 seedling phenotype, including cellular toxicity and gene regulation properties. Generation of the quadruple mutant facilitated the development of an in situ fluorescence assay based on the formation of adducts of MDA with 2-thiobarbituric acid at 37 degrees C. Specificity was verified by measuring pentafluorophenylhydrazine derivatives of MDA and by liquid chromatography analysis of MDA-2-thiobarbituric acid adducts. Potentially applicable to other organisms, this method allowed the localization of MDA pools throughout the body of Arabidopsis and revealed an undiscovered pool of the compound unlikely to be derived from trienoic fatty acids in the vicinity of the root tip quiescent center.

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

Tonotopic mapping of human auditory cortex.

Since the early days of functional magnetic resonance imaging (fMRI), retinotopic mapping emerged as a powerful and widely-accepted tool, allowing the identification of individual visual cortical fields and furthering the study of visual processing. In contrast, tonotopic mapping in auditory cortex proved more challenging primarily because of the smaller size of auditory cortical fields. The spatial resolution capabilities of fMRI have since advanced, and recent reports from our labs and several others demonstrate the reliability of tonotopic mapping in human auditory cortex. Here we review the wide range of stimulus procedures and analysis methods that have been used to successfully map tonotopy in human auditory cortex. We point out that recent studies provide a remarkably consistent view of human tonotopic organisation, although the interpretation of the maps continues to vary. In particular, there remains controversy over the exact orientation of the primary gradients with respect to Heschl's gyrus, which leads to different predictions about the location of human A1, R, and surrounding fields. We discuss the development of this debate and argue that literature is converging towards an interpretation that core fields A1 and R fold across the rostral and caudal banks of Heschl's gyrus, with tonotopic gradients laid out in a distinctive V-shaped manner. This suggests an organisation that is largely homologous with non-human primates. This article is part of a Special Issue entitled Human Auditory Neuroimaging.

Models that include supercoiling of topological domains reproduce several known features of interphase chromosomes.

Understanding the structure of interphase chromosomes is essential to elucidate regulatory mechanisms of gene expression. During recent years, high-throughput DNA sequencing expanded the power of chromosome conformation capture (3C) methods that provide information about reciprocal spatial proximity of chromosomal loci. Since 2012, it is known that entire chromatin in interphase chromosomes is organized into regions with strongly increased frequency of internal contacts. These regions, with the average size of ∼1 Mb, were named topological domains. More recent studies demonstrated presence of unconstrained supercoiling in interphase chromosomes. Using Brownian dynamics simulations, we show here that by including supercoiling into models of topological domains one can reproduce and thus provide possible explanations of several experimentally observed characteristics of interphase chromosomes, such as their complex contact maps.

Kernel-based mapping of orographic rainfall enhancement in the Swiss Alps as detected by weatherradar

In this paper, we develop a data-driven methodology to characterize the likelihood of orographic precipitation enhancement using sequences of weather radar images and a digital elevation model (DEM). Geographical locations with topographic characteristics favorable to enforce repeatable and persistent orographic precipitation such as stationary cells, upslope rainfall enhancement, and repeated convective initiation are detected by analyzing the spatial distribution of a set of precipitation cells extracted from radar imagery. Topographic features such as terrain convexity and gradients computed from the DEM at multiple spatial scales as well as velocity fields estimated from sequences of weather radar images are used as explanatory factors to describe the occurrence of localized precipitation enhancement. The latter is represented as a binary process by defining a threshold on the number of cell occurrences at particular locations. Both two-class and one-class support vector machine classifiers are tested to separate the presumed orographic cells from the nonorographic ones in the space of contributing topographic and flow features. Site-based validation is carried out to estimate realistic generalization skills of the obtained spatial prediction models. Due to the high class separability, the decision function of the classifiers can be interpreted as a likelihood or susceptibility of orographic precipitation enhancement. The developed approach can serve as a basis for refining radar-based quantitative precipitation estimates and short-term forecasts or for generating stochastic precipitation ensembles conditioned on the local topography.