Adaptive immunity is related to coronary artery disease severity after acute coronary syndrome in subjects with metabolic syndrome

Metabolic syndrome (MetS) is an inflammatory state associated with high coronary disease risk. Inflammation and adaptive immunity modulate atherosclerosis and plaque instability. We examined early changes in anti-oxidized lowdensity lipoprotein (LDL) (anti-oxLDL) autoantibodies (Abs) in patients with MetS after an acute coronary syndrome (ACS). Patients of both genders (n=116) with MetS were prospectively included after an acute yocardial infarction (MI) or hospitalization due to unstable angina. Anti-oxLDL Abs (IgG class) were assayed at baseline, three and six weeks after ACS. The severity of coronary disease was evaluated by the Gensini score. We observed a decrease in anti-oxLDL Abs titers (p<0.002 vs. baseline), mainly in males (p=0.01), in those under 65 y (p=0.03), and in subjects with Gensini score above median (p=0.04). In conclusion, early decrease in circulating anti-oxLDL Abs is associated with coronary disease severity among subjects with MetS.

Dengue virus type 3 adaptive changes during epidemics in São Jose de Rio Preto, Brazil, 2006–2007

Global dengue virus spread in tropical and sub-tropical regions has become a major international public health concern. It is evident that DENV genetic diversity plays a significant role in the immunopathology of the disease and that the identification of polymorphisms associated with adaptive responses is important for vaccine development. The investigation of naturally occurring genomic variants may play an important role in the comprehension of different adaptive strategies used by these mutants to evade the human immune system. In order to elucidate this role we sequenced the complete polyprotein-coding region of thirty-three DENV-3 isolates to characterize variants circulating under high endemicity in the city of São José de Rio Preto, Brazil, during the onset of the 2006-07 epidemic. By inferring the evolutionary history on a local-scale and estimating rates of synonymous (dS) and nonsynonimous (dN) substitutions, we have documented at least two different introductions of DENV-3 into the city and detected 10 polymorphic codon sites under significant positive selection (dN/dS > 1) and 8 under significant purifying selection (dN/dS < 1). We found several polymorphic amino acid coding sites in the envelope (15), NS1 (17), NS2A (11), and NS5 (24) genes, which suggests that these genes may be experiencing relatively recent adaptive changes. Furthermore, some polymorphisms correlated with changes in the immunogenicity of several epitopes. Our study highlights the existence of significant and informative DENV variability at the spatio-temporal scale of an urban outbreak.

Human Abuses of Coral Reefs- Adaptive Responses and Regime Transitions

During the last few decades, coral reefs have become a disappearing feature of tropical marine environments, and those reefs that do remain are severely threatened. It is understood that humans have greately altered the environment under which these ecosystems previously have thrived and evoloved. Overharvesting of fish stocks, global warming and pollution are some of the most prominent threats, acting on coral reefs at several spatial and temporal scales. Presently, it is common that coral reefs have been degraded into alternative ecosystem regimes, such as macroalgae-dominated or sea urchin-barren. Although these ecosystems could potentially return to coral dominance in a long-term perspective, when considdering current conditions, it seems likely that they will persist in their degraded states. Thus, recovery of coral reefs cannot be taken for granted on a human timescale. Multiple stressors and disturbances, which are increasingly characteristic of coral reef environments today, are believed to act synergistically and produce ecological surprises. However, current knowledge of effects of compounded disturbances and stress is limited. Based on five papers, this thesis investigates the sublethal response of multiple stressors on coral physiology, as well as the effects of compounded stress and disturbance on coral reef structure and function. Adaptive responses to stress and disturbance in relation to prior experience are highlighted. The thesis further explores how inherent characteristics (traits) of corals and macroalgae may influence regime expression when faced with altered disturbance regimes, in particular overfishing, eutrophication, elevated temperature, and enhanced substrate availability. Finally, possibilities of affecting the resilience of macroalgae-dominaed reefs and shifting the community composition towards a coral-dominated regime are explored.

Processing of spectrally resolved x-ray images of inertial confinement fusion implosion cores recorded with multimonochromatic x-ray imagers

[EN] We discuss the processing of data recorded with multimonochromatic x-ray imagers (MMI) in inertial confinement fusion experiments. The MMI records hundreds of gated, spectrally resolved images that can be used to unravel the spatial structure of the implosion core. In particular, we present a new method to determine the centers in all the array of images, a better reconstruction technique of narrowband implosion core images, two algorithms to determine the shape and size of the implosion core volume based on reconstructed broadband images recorded along three-quasiorthogonal lines of sight, and the removal of artifacts from the space-integrated spectra.

An adaptive solar radiation numerical model

[EN]A numerical model for the evaluation of solar radiation in different locations is presented. The solar radiation model is implemented taking into account the terrain surface using two-dimensional adaptive meshes of triangles that are constructed using a refinement/derefinement procedure in accordance with the variations of terrain surface and albedo. The selected methodology defines the terrain characteristics with a minimum number of points so that the computational cost is reduced for a given accuracy. The model can be used in atmospheric sciences as well as in other fields such as electrical engineering, since it allows the user to find the optimal location for maximum power generation in photovoltaic or solar thermal power plants...

Adaptive finite element simulation of stack pollutant emissions over complex terrains

[EN]A three-dimensional finite element model for the pollutant dispersion is presented. In these environmental processes over a complex terrain, a mesh generator capable of adapting itself to the topographic characteristics is essential. The first stage of the model consists on the construction of an adaptive tetrahedral mesh of a rectangular region bounded in its lower part by the terrain and in its upper part by a horizontal plane. Once the mesh is constructed, an adaptive local refinement of tetrahedra is used in order to capture the plume rise. Wind measurements are used to compute an interpolated wind field, that is modified by using a mass-consistent model and perturbing its vertical component to introduce the plume rise effect...

Adaptive multiscale biological signal processing

Biological processes are very complex mechanisms, most of them being accompanied by or manifested as signals that reflect their essential characteristics and qualities. The development of diagnostic techniques based on signal and image acquisition from the human body is commonly retained as one of the propelling factors in the advancements in medicine and biosciences recorded in the recent past. It is a fact that the instruments used for biological signal and image recording, like any other acquisition system, are affected by non-idealities which, by different degrees, negatively impact on the accuracy of the recording. This work discusses how it is possible to attenuate, and ideally to remove, these effects, with a particular attention toward ultrasound imaging and extracellular recordings. Original algorithms developed during the Ph.D. research activity will be examined and compared to ones in literature tackling the same problems; results will be drawn on the base of comparative tests on both synthetic and in-vivo acquisitions, evaluating standard metrics in the respective field of application. All the developed algorithms share an adaptive approach to signal analysis, meaning that their behavior is not dependent only on designer choices, but driven by input signal characteristics too. Performance comparisons following the state of the art concerning image quality assessment, contrast gain estimation and resolution gain quantification as well as visual inspection highlighted very good results featured by the proposed ultrasound image deconvolution and restoring algorithms: axial resolution up to 5 times better than algorithms in literature are possible. Concerning extracellular recordings, the results of the proposed denoising technique compared to other signal processing algorithms pointed out an improvement of the state of the art of almost 4 dB.

Adaptive T-spline refinement for isogeometric analysis in planar geometries

[EN]We present a new strategy, based on the meccano method [1, 2, 3], to construct a T-spline parameterization of 2D geometries for the application of isogeometric analysis. The proposed method only demands a boundary representation of the geometry as input data. The algorithm obtains, as a result, high quality parametric transformation between 2D objects and the parametric domain, the unit square. The key of the method lies in defining an isomorphic transformation between the parametric and physical T-mesh finding the optimal position of the interior nodes by applying a new T-mesh untangling and smoothing procedure. Bivariate T-spline representation is calculated by imposing the interpolation conditions on points sited both on the interior and on the boundary of the geometry…

Wind ensamble forecasting using an adaptive mass-consistent model

[EN]Ensemble forecasting [1] is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in [2]. The wind _eld forecasting is based on a mass-consistent model and a log-linear wind pro_le using as input data the resulting forecast wind from Harmonie [3], a Non-Hydrostatic Dynamic model. The mass-consistent model parameters are estimated by using genetic algorithms [4]. The mesh is generated using the meccano method [5] and adapted to the geometry. The main source of uncertainties in this model is the parameter estimation and the in- trinsic uncertainties of the Harmonie Model…

Tetrahedral mesh optimization combining boundary and inner node relocation and adaptive local refinement

[EN]This work introduces a new technique for tetrahedral mesh optimization. The procedure relocates boundary and inner nodes without changing the mesh topology. In order to maintain the boundary approximation while boundary nodes are moved, a local refinement of tetrahedra with faces on the solid boundary is necessary in some cases. New nodes are projected on the boundary by using a surface parameterization. In this work, the proposed method is applied to tetrahedral meshes of genus-zero solids that are generated by the meccano method. In this case, the solid boundary is automatically decomposed into six surface patches which are parameterized into the six faces of a cube with the Floater parameterization...

Adaptive Finite Element Method with a local element parametrization nested meses

[EN]This work presents a novel approach to solve a two dimensional problem by using an adaptive finite element approach. The most common strategy to deal with nested adaptivity is to generate a mesh that represents the geometry and the input parameters correctly, and to refine this mesh locally to obtain the most accurate solution. As opposed to this approach, the authors propose a technique using independent meshes : geometry, input data and the unknowns. Each particular mesh is obtained by a local nested refinement of the same coarse mesh at the parametric space…

Ensemble wind forecasting based on the HARMONIE model and adaptive finite elements in complex orography

[EN]Ensemble forecasting is a methodology to deal with uncertainties in the numerical wind prediction. In this work we propose to apply ensemble methods to the adaptive wind forecasting model presented in. The wind field forecasting is based on a mass-consistent model and a log-linear wind profile using as input data the resulting forecast wind from Harmonie, a Non-Hydrostatic Dynamic model used experimentally at AEMET with promising results. The mass-consistent model parameters are estimated by using genetic algorithms. The mesh is generated using the meccano method and adapted to the geometry…