1,145 research outputs found

    Capacidad antioxidante total y contenido de polifenoles de vinos argentinos

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    Existe evidencia sobre los beneficios del consumo de dietas ricas en frutas y vegetales y una moderada cantidad de vinos tintos en situaciones de salud asociadas a la producción de riesgo oxidativo. Estos efectos protectores se atribuyen a la presencia en los alimentos citados de compuestos con actividad antioxidante, particularmente los polifenoles. En los vinos, los principales compuestos fenólicos son los ácidos galico y cafeico, epicatequina, catequina, cianidina y malvidina-3-glucósidos, rutina, miricetina, quercetina y resveratrol. La Argentina posee regiones muy aptas para la producción vitivinícola siendo el vino obtenido de la Vitis vinifera var. Malbec, uno de los más representativos del país. En la zona del Rio de La Plata y particularmente en Berisso se cultiva la Vitis labrusca var. Isabela de la cual se obtienen el denominado vino de la costa (VC). Existe escasa evidencia sobre la capacidad antioxidante total (CAT) de los vinos Malbec argentinos producidos en diferentes regiones y prácticamente ninguna sobre el vino de la costa. Objetivos: Como parte de un proyecto general del estudio de la capacidad antioxidante de productos naturales, en este trabajo se evalúa la CAT y el contenido de fenoles totales de vinos Malbec de 4 regiones vitivinícolas argentinas y del VC de Berisso utilizando diferentes modelos experimentales

    Super-resolution track-density imaging studies of mouse brain: Comparison to histology

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    The recently proposed track-density imaging (TDI) technique was introduced as a means to achieve superresolution using diffusion MRI. This technique is able to increase the spatial resolution of the reconstructed images beyond the acquired MRI resolution by incorporating information from whole-brain fibre-tracking results. It not only achieves super-resolution, but also provides very high anatomical contrast with a new MRI contrast mechanism. However, the anatomical information-content of this novel contrast mechanism has not yet been assessed. In this work, we perform such a study using diffusion MRI of ex vivo mouse brains acquired at 16.4T, to compare the results of the super-resolution TDI technique with histological staining (myelin and Nissl stains) in the same brains. Furthermore, a modified version of the directionally-encoded colour TDI map using short-tracks is introduced, which reduces the TDI intensity dynamic range, and therefore enhances the directionality colour-contrast. Good agreement was observed between structures visualised in the superresolution TDI maps and in the histological sections, supporting the anatomical information-content of the images generated using the TDI technique. The results therefore show that the TDI methodology does provide meaningful and rich anatomical contrast, in addition to achieving super-resolution. Furthermore, this study is the first to show the application of TDI to mouse brain imaging: the high-resolution, high-quality images demonstrate the useful complementary information that can be achieved using super-resolution TDI

    Atomic and Electronic Structure of a Rashba pp-nn Junction at the BiTeI Surface

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    The non-centrosymmetric semiconductor BiTeI exhibits two distinct surface terminations that support spin-split Rashba surface states. Their ambipolarity can be exploited for creating spin-polarized pp-nn junctions at the boundaries between domains with different surface terminations. We use scanning tunneling microscopy/spectroscopy (STM/STS) to locate such junctions and investigate their atomic and electronic properties. The Te- and I-terminated surfaces are identified owing to their distinct chemical reactivity, and an apparent height mismatch of electronic origin. The Rashba surface states are revealed in the STS spectra by the onset of a van Hove singularity at the band edge. Eventually, an electronic depletion is found on interfacial Te atoms, consistent with the formation of a space charge area in typical pp-nn junctions.Comment: 5 pages, 4 figure

    Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification

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    There is no consensus on how to construct structural brain networks from diffusion MRI. How variations in pre-processing steps affect network reliability and its ability to distinguish subjects remains opaque. In this work, we address this issue by comparing 35 structural connectome-building pipelines. We vary diffusion reconstruction models, tractography algorithms and parcellations. Next, we classify structural connectome pairs as either belonging to the same individual or not. Connectome weights and eight topological derivative measures form our feature set. For experiments, we use three test-retest datasets from the Consortium for Reliability and Reproducibility (CoRR) comprised of a total of 105 individuals. We also compare pairwise classification results to a commonly used parametric test-retest measure, Intraclass Correlation Coefficient (ICC).Comment: Accepted for MICCAI 2017, 8 pages, 3 figure

    Investigating white matter fibre density and morphology using fixel-based analysis

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    Voxel-based analysis of diffusion MRI data is increasingly popular. However, most white matter voxels contain contributions from multiple fibre populations (often referred to as crossing fibres), and therefore voxel-averaged quantitative measures (e.g. fractional anisotropy) are not fibre-specific and have poor interpretability. Using higher-order diffusion models, parameters related to fibre density can be extracted for individual fibre populations within each voxel (‘fixels’), and recent advances in statistics enable the multi-subject analysis of such data. However, investigating within-voxel microscopic fibre density alone does not account for macroscopic differences in the white matter morphology (e.g. the calibre of a fibre bundle). In this work, we introduce a novel method to investigate the latter, which we call fixel-based morphometry (FBM). To obtain a more complete measure related to the total number of white matter axons, information from both within-voxel microscopic fibre density and macroscopic morphology must be combined. We therefore present the FBM method as an integral piece within a comprehensive fixel-based analysis framework to investigate measures of fibre density, fibre-bundle morphology (cross-section), and a combined measure of fibre density and cross-section. We performed simulations to demonstrate the proposed measures using various transformations of a numerical fibre bundle phantom. Finally, we provide an example of such an analysis by comparing a clinical patient group to a healthy control group, which demonstrates that all three measures provide distinct and complementary information. By capturing information from both sources, the combined fibre density and cross-section measure is likely to be more sensitive to certain pathologies and more directly interpretable

    Giant alkali-metal-induced lattice relaxation as the driving force of the insulating phase of alkali-metal/Si(111):B

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    Ab initio density-functional theory calculations, photoemission spectroscopy (PES), scanning tunneling microscopy, and spectroscopy (STM, STS) have been used to solve the 2√3 x 2√3R30 surface reconstruction observed previously by LEED on 0.5 ML K/Si:B. A large K-induced vertical lattice relaxation occurring only for 3/4 of Si adatoms is shown to quantitatively explain both the chemical shift of 1.14 eV and the ratio 1/3 measured on the two distinct B 1s core levels. A gap is observed between valence and conduction surface bands by ARPES and STS which is shown to have mainly a Si-B character. Finally, the calculated STM images agree with our experimental results. This work solves the controversy about the origin of the insulating ground state of alkali-metal/Si(111):B semiconducting interfaces which were believed previously to be related to many-body effectsThis work has received the financial support of the French ANR SURMOTT program (ANR-09-BLAN- 0210-01) and the Spanish MICIIN under Project No. FIS2010-1604

    Estimation of Fiber Orientations Using Neighborhood Information

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    Data from diffusion magnetic resonance imaging (dMRI) can be used to reconstruct fiber tracts, for example, in muscle and white matter. Estimation of fiber orientations (FOs) is a crucial step in the reconstruction process and these estimates can be corrupted by noise. In this paper, a new method called Fiber Orientation Reconstruction using Neighborhood Information (FORNI) is described and shown to reduce the effects of noise and improve FO estimation performance by incorporating spatial consistency. FORNI uses a fixed tensor basis to model the diffusion weighted signals, which has the advantage of providing an explicit relationship between the basis vectors and the FOs. FO spatial coherence is encouraged using weighted l1-norm regularization terms, which contain the interaction of directional information between neighbor voxels. Data fidelity is encouraged using a squared error between the observed and reconstructed diffusion weighted signals. After appropriate weighting of these competing objectives, the resulting objective function is minimized using a block coordinate descent algorithm, and a straightforward parallelization strategy is used to speed up processing. Experiments were performed on a digital crossing phantom, ex vivo tongue dMRI data, and in vivo brain dMRI data for both qualitative and quantitative evaluation. The results demonstrate that FORNI improves the quality of FO estimation over other state of the art algorithms.Comment: Journal paper accepted in Medical Image Analysis. 35 pages and 16 figure

    Diffusion magnetic resonance imaging assessment of regional white matter maturation in preterm neonates

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    PURPOSE: Diffusion magnetic resonance imaging (dMRI) studies report altered white matter (WM) development in preterm infants. Neurite orientation dispersion and density imaging (NODDI) metrics provide more realistic estimations of neurite architecture in vivo compared with standard diffusion tensor imaging (DTI) metrics. This study investigated microstructural maturation of WM in preterm neonates scanned between 25 and 45 weeks postmenstrual age (PMA) with normal neurodevelopmental outcomes at 2 years using DTI and NODDI metrics. METHODS: Thirty-one neonates (n = 17 male) with median (range) gestational age (GA) 32+1 weeks (24+2-36+4) underwent 3 T brain MRI at median (range) post menstrual age (PMA) 35+2 weeks (25+3-43+1). WM tracts (cingulum, fornix, corticospinal tract (CST), inferior longitudinal fasciculus (ILF), optic radiations) were delineated using constrained spherical deconvolution and probabilistic tractography in MRtrix3. DTI and NODDI metrics were extracted for the whole tract and cross-sections along each tract to assess regional development. RESULTS: PMA at scan positively correlated with fractional anisotropy (FA) in the CST, fornix and optic radiations and neurite density index (NDI) in the cingulum, CST and fornix and negatively correlated with mean diffusivity (MD) in all tracts. A multilinear regression model demonstrated PMA at scan influenced all diffusion measures, GA and GAxPMA at scan influenced FA, MD and NDI and gender affected NDI. Cross-sectional analyses revealed asynchronous WM maturation within and between WM tracts.). CONCLUSION: We describe normal WM maturation in preterm neonates with normal neurodevelopmental outcomes. NODDI can enhance our understanding of WM maturation compared with standard DTI metrics alone

    Contralateral cortico-ponto-cerebellar pathways reconstruction in humans in vivo: implications for reciprocal cerebro-cerebellar structural connectivity in motor and non-motor areas

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    Altmetric: 2More detail Article | OPEN Contralateral cortico-ponto-cerebellar pathways reconstruction in humans in vivo: implications for reciprocal cerebro-cerebellar structural connectivity in motor and non-motor areas Fulvia Palesi, Andrea De Rinaldis, Gloria Castellazzi, Fernando Calamante, Nils Muhlert, Declan Chard, J. Donald Tournier, Giovanni Magenes, Egidio D’Angelo & Claudia A. M. Gandini Wheeler-Kingshott Scientific Reports 7, Article number: 12841 (2017) doi:10.1038/s41598-017-13079-8 Download Citation BrainNeuroscience Received: 11 May 2017 Accepted: 18 September 2017 Published online: 09 October 2017 Abstract Cerebellar involvement in cognition, as well as in sensorimotor control, is increasingly recognized and is thought to depend on connections with the cerebral cortex. Anatomical investigations in animals and post-mortem humans have established that cerebro-cerebellar connections are contralateral to each other and include the cerebello-thalamo-cortical (CTC) and cortico-ponto-cerebellar (CPC) pathways. CTC and CPC characterization in humans in vivo is still challenging. Here advanced tractography was combined with quantitative indices to compare CPC to CTC pathways in healthy subjects. Differently to previous studies, our findings reveal that cerebellar cognitive areas are reached by the largest proportion of the reconstructed CPC, supporting the hypothesis that a CTC-CPC loop provides a substrate for cerebro-cerebellar communication during cognitive processing. Amongst the cerebral areas identified using in vivo tractography, in addition to the cerebral motor cortex, major portions of CPC streamlines leave the prefrontal and temporal cortices. These findings are useful since provide MRI-based indications of possible subtending connectivity and, if confirmed, they are going to be a milestone for instructing computational models of brain function. These results, together with further multi-modal investigations, are warranted to provide important cues on how the cerebro-cerebellar loops operate and on how pathologies involving cerebro-cerebellar connectivity are generated
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