953 resultados para Discovery and exploration, Spanish


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This work aimed to contribute to drug discovery and development (DDD) for tauopathies, while expanding our knowledge on this group of neurodegenerative disorders, including Alzheimer’s disease (AD). Using yeast, a recognized model for neurodegeneration studies, useful models were produced for the study of tau interaction with beta-amyloid (Aβ), both AD hallmark proteins. The characterization of these models suggests that these proteins co-localize and that Aβ1-42, which is toxic to yeast, is involved in tau40 phosphorylation (Ser396/404) via the GSK-3β yeast orthologue, whereas tau seems to facilitate Aβ1-42 oligomerization. The mapping of tau’s interactome in yeast, achieved with a tau toxicity enhancer screen using the yeast deletion collection, provided a novel framework, composed of 31 genes, to identify new mechanisms associated with tau pathology, as well as to identify new drug targets or biomarkers. This genomic screen also allowed to select the yeast strain mir1Δ-tau40 for development of a new GPSD2TM drug discovery screening system. A library of unique 138 marine bacteria extracts, obtained from the Mid-Atlantic Ridge hydrothermal vents, was screened with mir1Δ-tau40. Three extracts were identified as suppressors of tau toxicity and constitute good starting points for DDD programs. mir1Δ strain was sensitive to tau toxicity, relating tau pathology with mitochondrial function. SLC25A3, the human homologue of MIR1, codes for the mitochondrial phosphate carrier protein (PiC). Resorting to iRNA, SLC25A3 expression was silenced in human neuroglioma cells, as a first step towards the engineering of a neural model for replicating the results obtained in yeast. This model is essential to understand the mechanisms of tau toxicity at the mitochondrial level and to validate PiC as a relevant drug target. The set of DDD tools here presented will foster the development of innovative and efficacious therapies, urgently needed to cope with tau-related disorders of high human and social-economic impact.

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Many disorders are associated with altered serum protein concentrations, including malnutrition, cancer, and cardiovascular, kidney, and inflammatory diseases. Although these protein concentrations are highly heritable, relatively little is known about their underlying genetic determinants. Through transethnic meta-analysis of European-ancestry and Japanese genome-wide association studies, we identified six loci at genome-wide significance (p < 5 × 10(-8)) for serum albumin (HPN-SCN1B, GCKR-FNDC4, SERPINF2-WDR81, TNFRSF11A-ZCCHC2, FRMD5-WDR76, and RPS11-FCGRT, in up to 53,190 European-ancestry and 9,380 Japanese individuals) and three loci for total protein (TNFRS13B, 6q21.3, and ELL2, in up to 25,539 European-ancestry and 10,168 Japanese individuals). We observed little evidence of heterogeneity in allelic effects at these loci between groups of European and Japanese ancestry but obtained substantial improvements in the resolution of fine mapping of potential causal variants by leveraging transethnic differences in the distribution of linkage disequilibrium. We demonstrated a functional role for the most strongly associated serum albumin locus, HPN, for which Hpn knockout mice manifest low plasma albumin concentrations. Other loci associated with serum albumin harbor genes related to ribosome function, protein translation, and proteasomal degradation, whereas those associated with serum total protein include genes related to immune function. Our results highlight the advantages of transethnic meta-analysis for the discovery and fine mapping of complex trait loci and have provided initial insights into the underlying genetic architecture of serum protein concentrations and their association with human disease.

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The academic study of place has been generally defined by two distinct and highly refined discourses within outdoor recreation research: place attachment and sense of place. Place attachment generally describes the intensity of the place relationship, whereas sense of place approaches place from a more holistic and intimate orientation. This study bridges these two methodological and theoretical separate areas of place research together by re-conceptualizing the way in which place relationships are viewed within outdoor recreation research. The Psychological Continuum Model is used to extend the language of place attachment to incorporate more of the philosophy of sense of place while attending to the empirical strength and utility of place attachment. This extension results in the term place allegiance being coined to depict the strong and profound relationships outdoor recreationists build with their places of outdoor recreation. Using a concurrent mixed methods research design, this study explored place allegiance via an online survey (n = 437) and thirteen in-depth qualitative interviews with outdoor recreationists. Results indicate that place allegiance can be measured through a multi-dimensional model of place allegiance that incorporates behaviours, importance, resistance, knowledge and symbolic value. In addition, place allegiance was found to be related to an individual's influence on life course and his/her willingness to exhibit preservation and protection tendencies. Place allegiance plays an important role in acknowledging the importance of authentic place relationships in an effort to confront placelessness. Wilderness recreation is an important avenue for outdoor recreationists to build strong place relationships.

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In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin.

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Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics.

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Several bis-malonatooxidovanadium(IV) complexes of the general type [M(2)(H2(O))(n)][VO(mal)(2)(H(2)O)] (where M = Li(1), Na(2), K(3), Cs(4) and NH4(5); n = 3.5, 1, 3, 1 and 1, respectively) were isolated in good yield and high purity. These complexes were fully characterized by various physicochemical techniques (elemental analysis, UV- Vis, IR, EPR, CV, etc.) complexes 1, 2 and 3 were structurally characterized by single crystal X- ray diffraction technique. In vivo antidiabetic properties of bis- malonato complexes 1, 2, 3 and 5 have been studied using Streptozotocin induced diabetic rats. Significant lowering of blood sugar level has been noticed. At the same time these complexes were found to regulate secondary pathophysiological complications like liver damage and lowering of the total antioxidant status (TAS) in diabetic rats. Results of these study are expected to a expand the possibility of designing new oxidovanadium(IV) complexes of O, O chelating ligands with significant antidiabetic properties