483 research outputs found

    Unraveling Brazilian Indian population prostate good health: clinical, anthropometric and genetic features

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    To compare dietary, lifestyle, clinical, anthropometric, genetic and prostatic features of Brazilian Indians and non-Indians (Amazon). 315 men, 228 Indians and 89 non-Indians, ≥40 years old were submitted to digital rectal examination, serum prostate specific antigen (PSA), testosterone, TP53 and GSTP1 genotyping, anthropometric, lifestyle, dietary, personal and familial medical history. Prostatic symptoms were evaluated with the International Prostate Symptom Score (IPSS). Macuxis and Yanomamis represented 43.6% and 14.5% of Indians respectively who spontaneously referred no prostate symptoms. Mean IPSS was 7, range 3-19, with only 15% of moderate symptoms (score 8-19); Mean age was 54.7 years, waist circumference 86.6 cm, BMI 23.9 kg/m2. Yanomamis presented both lower BMI (21.4 versus 24.8 and 23.3, p=0,001) and prostate volume than Macuxis and “other ethnic groups” (15 versus 20, p=0.001). Testosterone (414 versus 502 and 512, p=0.207) and PSA (0.48 versus 0.6 and 0.41, p=0.349) were similar with progressive PSA increase with aging. Val/Val correlated with lower PSA (p=0.0361). Indians compared to control population presented: - TP53 super representation of Arg/Arg haplotype, 74.5% versus 42.5%, p<0.0001. -GSTP1 Ile/Ile 35.3% versus 60.9%; Ile/Val 45.9% versus 28.7%; Val/Val 18.8% versus 10.3%; p=0.0003. Observed specific dietary, lifestyle, anthropometric and genetic profile for TP53 and GSTP1 may contribute to Brazilian Indian population prostate good health.41234435

    Effects of Zn Substitution in the Magnetic and Morphological Properties of Fe-Oxide-Based Core-Shell Nanoparticles Produced in a Single Chemical Synthesis

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    Magnetic, compositional, and morphological properties of Zn-Fe-oxide core-shell bimagnetic nanoparticles were studied for three samples with 0.00, 0.06, and 0.10 Zn/Fe ratios, as obtained from particle-induced X-ray emission analysis. The bimagnetic nanoparticles were produced in a one-step synthesis by the thermal decomposition of the respective acetylacetonates. The nanoparticles present an average particle size between 25 and 30 nm as inferred from transmission electron microscopy (TEM). High-resolution TEM images clearly show core-shell morphology for the particles in all samples. The core is composed by an antiferromagnetic (AFM) phase with a Wüstite (Fe 1-y O) structure, whereas the shell is composed by a Zn x Fe 3-x O 4 ferrimagnetic (FiM) spinel phase. Despite the low solubility of Zn in the Wüstite, electron energy-loss spectroscopy analysis indicates that Zn is distributed almost homogeneously in the whole nanoparticle. This result gives information on the formation mechanisms of the particle, indicating that the Wüstite is formed first, and the superficial oxidation results in the FiM ferrite phase with similar Zn concentration than the core. Magnetization and in-field Mössbauer spectroscopy of the Zn-richest nanoparticles indicate that the AFM phase is strongly coupled to the FiM structure of the ferrite shell, resulting in a bias field (H EB ) appearing below TN FeO , with H EB values that depend on the core-shell relative proportion. Magnetic characterization also indicates a strong magnetic frustration for the samples with higher Zn concentration, even at low temperatures.Fil: Lohr, Javier Hernán. Comisión Nacional de Energía Atómica. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Área de Investigación y Aplicaciones No Nucleares. Gerencia de Física. Laboratorio de Resonancias Magnéticas; ArgentinaFil: de Almeida, Adriele Aparecida. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Comisión Nacional de Energía Atómica. Gerencia del Área de Investigación y Aplicaciones No Nucleares. Gerencia de Física. Laboratorio de Resonancias Magnéticas; ArgentinaFil: Moreno, Mario Sergio Jesus. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche | Comisión Nacional de Energía Atómica. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche; ArgentinaFil: Troiani, Horacio Esteban. Comisión Nacional de Energía Atómica. Gerencia del Área de Investigación y Aplicaciones No Nucleares. Gerencia de Física. Laboratorio de Resonancias Magnéticas; ArgentinaFil: Goya, Gerardo Fabian. Universidad de Zaragoza; EspañaFil: Torres Molina, Teobaldo Enrique. Comisión Nacional de Energía Atómica. Gerencia del Área de Investigación y Aplicaciones No Nucleares. Gerencia de Física. Laboratorio de Resonancias Magnéticas; Argentina. Universidad de Zaragoza; EspañaFil: Fernandez Pacheco, Rodrigo. Universidad de Zaragoza; EspañaFil: Winkler, Elin Lilian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche | Comisión Nacional de Energía Atómica. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche; ArgentinaFil: Vasquez Mansilla, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche | Comisión Nacional de Energía Atómica. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche; ArgentinaFil: Cohen, Renato. Universidade de Sao Paulo; BrasilFil: Nagamine, Luiz C. C. M.. Universidade de Sao Paulo; BrasilFil: Rodriguez, Luis Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche | Comisión Nacional de Energía Atómica. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche; ArgentinaFil: Fregenal, Daniel Eduardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche | Comisión Nacional de Energía Atómica. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche; ArgentinaFil: Zysler, Roberto Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche | Comisión Nacional de Energía Atómica. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche; ArgentinaFil: Lima, Enio Junior. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche | Comisión Nacional de Energía Atómica. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología. Unidad Ejecutora Instituto de Nanociencia y Nanotecnología - Nodo Bariloche; Argentin

    Contribution of the carbohydrate-binding ability of Vatairea guianensis lectin to induce edematogenic activity

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    Vatairea guianensis lectin (VGL), Dalbergiae tribe, is a N-acetyl-galactosamine (GalNAc)/Galactose (Gal) lectin previously purified and characterized. In this work, we report its structural features, obtained from bioinformatics tools, and its inflammatory effect, obtained from a rat paw edema model. The VGL model was obtained by homology with the lectin of Vatairea macrocarpa (VML) as template, and we used it to demonstrate the common characteristics of legume lectins, such as the jellyroll motif and presence of a metal-binding site in the vicinity of the carbohydrate-recognition domain (CRD). Protein-ligand docking revealed favorable interactions with N-acetyl-D-galactosamine, D-galactose and related sugars as well as several biologically relevant N- and O-glycans. In vivo testing of paw edema revealed that VGL induces edematogenic effect involving prostaglandins, interleukins and VGL CRD. Taken together, these data corroborate with previous reports showing that VGL interacts with N- and/or O-glycans of molecular targets, particularly in those presenting galactosides in their structure, contributing to the lectin inflammatory effect. © 2017 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM

    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

    Pervasive gaps in Amazonian ecological research

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