5 resultados para Advanced characterization methods

em RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal


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Neurological disorders are a major concern in modern societies, with increasing prevalence mainly related with the higher life expectancy. Most of the current available therapeutic options can only control and ameliorate the patients’ symptoms, often be-coming refractory over time. Therapeutic breakthroughs and advances have been hampered by the lack of accurate central nervous system (CNS) models. The develop-ment of these models allows the study of the disease onset/progression mechanisms and the preclinical evaluation of novel therapeutics. This has traditionally relied on genetically engineered animal models that often diverge considerably from the human phenotype (developmentally, anatomically and physiologically) and 2D in vitro cell models, which fail to recapitulate the characteristics of the target tissue (cell-cell and cell-matrix interactions, cell polarity). The in vitro recapitulation of CNS phenotypic and functional features requires the implementation of advanced culture strategies that enable to mimic the in vivo struc-tural and molecular complexity. Models based on differentiation of human neural stem cells (hNSC) in 3D cultures have great potential as complementary tools in preclinical research, bridging the gap between human clinical studies and animal models. This thesis aimed at the development of novel human 3D in vitro CNS models by integrat-ing agitation-based culture systems and a wide array of characterization tools. Neural differentiation of hNSC as 3D neurospheres was explored in Chapter 2. Here, it was demonstrated that human midbrain-derived neural progenitor cells from fetal origin (hmNPC) can generate complex tissue-like structures containing functional dopaminergic neurons, as well as astrocytes and oligodendrocytes. Chapter 3 focused on the development of cellular characterization assays for cell aggregates based on light-sheet fluorescence imaging systems, which resulted in increased spatial resolu-tion both for fixed samples or live imaging. The applicability of the developed human 3D cell model for preclinical research was explored in Chapter 4, evaluating the poten-tial of a viral vector candidate for gene therapy. The efficacy and safety of helper-dependent CAV-2 (hd-CAV-2) for gene delivery in human neurons was evaluated, demonstrating increased neuronal tropism, efficient transgene expression and minimal toxicity. The potential of human 3D in vitro CNS models to mimic brain functions was further addressed in Chapter 5. Exploring the use of 13C-labeled substrates and Nucle-ar Magnetic Resonance (NMR) spectroscopy tools, neural metabolic signatures were evaluated showing lineage-specific metabolic specialization and establishment of neu-ron-astrocytic shuttles upon differentiation. Chapter 6 focused on transferring the knowledge and strategies described in the previous chapters for the implementation of a scalable and robust process for the 3D differentiation of hNSC derived from human induced pluripotent stem cells (hiPSC). Here, software-controlled perfusion stirred-tank bioreactors were used as technological system to sustain cell aggregation and dif-ferentiation. The work developed in this thesis provides practical and versatile new in vitro ap-proaches to model the human brain. Furthermore, the culture strategies described herein can be further extended to other sources of neural phenotypes, including pa-tient-derived hiPSC. The combination of this 3D culture strategy with the implemented characterization methods represents a powerful complementary tool applicable in the drug discovery, toxicology and disease modeling.

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Ovarian cancer is within the most lethal gynecological malignancies in woman. Therefore, many investigators study its biological aspects with the purpose of discovering more rapid diagnostic methods and efficient treatment. Resembling many other tumors, in ovarian cancer, aberrant glycosylation occurs with the appearance of novel or altered carbohydrate structures. These can be terminal motifs, such as the Lewis determinants, or entire carbohydrate sequences, which have been related to tumorigenesis and its outcome.(...)

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RESUMO: Introdução: A espondilite anquilosante (EA) é uma doença inflamatória crónica caracterizada pela inflamação das articulações sacroilíacas e da coluna. A anquilose progressiva motiva uma deterioração gradual da função física e da qualidade de vida. O diagnóstico e o tratamento precoces podem contribuir para um melhor prognóstico. Neste contexto, a identificação de biomarcadores, assume-se como sendo muito útil para a prática clínica e representa hoje um grande desafio para a comunidade científica. Objetivos: Este estudo teve como objetivos: 1 - caracterizar a EA em Portugal; 2 - investigar possíveis associações entre genes, MHC e não-MHC, com a suscetibilidade e as características fenotípicas da EA; 3 - identificar genes candidatos associados a EA através da tecnologia de microarray. Material e Métodos: Foram recrutados doentes com EA, de acordo com os critérios modificados de Nova Iorque, nas consultas de Reumatologia dos diferentes hospitais participantes. Colecionaram-se dados demográficos, clínicos e radiológicos e colhidas amostras de sangue periférico. Selecionaram-se de forma aleatória, doentes HLA-B27 positivos, os quais foram tipados em termos de HLA classe I e II por PCR-rSSOP. Os haplótipos HLA estendidos foram estimados pelo algoritmo Expectation Maximization com recurso ao software Arlequin v3.11. As variantes alélicas dos genes IL23R, ERAP1 e ANKH foram estudadas através de ensaios de discriminação alélica TaqMan. A análise de associação foi realizada utilizando testes da Cochrane-Armitage e de regressão linear, tal como implementado pelo PLINK, para variáveis qualitativas e quantitativas, respetivamente. O estudo de expressão génica foi realizado por Illumina HT-12 Whole-Genome Expression BeadChips. Os genes candidatos foram validados usando qPCR-based TaqMan Low Density Arrays (TLDAs). Resultados: Foram incluídos 369 doentes (62,3% do sexo masculino, com idade média de 45,4 ± 13,2 anos, duração média da doença de 11,4 ± 10,5 anos). No momento da avaliação, 49,9% tinham doença axial, 2,4% periférica, 40,9% mista e 7,1% entesopática. A uveíte anterior aguda (33,6%) foi a manifestação extra-articular mais comum. Foram positivos para o HLA-B27, 80,3% dos doentes. Os haplótipo A*02/B*27/Cw*02/DRB1*01/DQB1*05 parece conferir suscetibilidade para a EA, e o A*02/B*27/Cw*01/DRB1*08/DQB1*04 parece conferir proteção em termos de atividade, repercussão funcional e radiológica da doença. Três variantes (2 para IL23R e 1 para ERAP1) mostraram significativa associação com a doença, confirmando a associação destes genes com a EA na população Portuguesa. O mesmo não se verificou com as variantes estudadas do ANKH. Não se verificou associação entre as variantes génicas não-MHC e as manifestações clínicas da EA. Foi identificado um perfil de expressão génica para a EA, tendo sido validados catorze genes - alguns têm um papel bem documentado em termos de inflamação, outros no metabolismo da cartilagem e do osso. Conclusões: Foi estabelecido um perfil demográfico e clínico dos doentes com EA em Portugal. A identificação de variantes génicas e de um perfil de expressão contribuem para uma melhor compreensão da sua fisiopatologia e podem ser úteis para estabelecer modelos com relevância em termos de diagnóstico, prognóstico e orientação terapêutica dos doentes. -----------ABSTRACT: Background: Ankylosing Spondylitis (AS) is a chronic inflammatory disorder characterized by inflammation in the spine and sacroiliac joints leading to progressive joint ankylosis and in progressive deterioration of physical function and quality of life. An early diagnosis and early therapy may contribute to a better prognosis. The identification of biomarkers would be helpful and represents a great challenge for the scientific community. Objectives: The present study had the following aims: 1- to characterize the pattern of AS in Portuguese patients; 2- to investigate MHC and non-MHC gene associations with susceptibility and phenotypic features of AS and; 3- to identify candidate genes associated with AS by means of whole-genome microarray. Material and Methods: AS was defined in accordance to the modified New York criteria and AS cases were recruited from hospital outcares patient clinics. Demographic and clinical data were recorded and blood samples collected. A random group of HLA-B27 positive patients and controls were selected and typed for HLA class I and II by PCR-rSSOP. The extended HLA haplotypes were estimated by Expectation Maximization Algorithm using Arlequin v3.11 software. Genotyping of IL23R, ERAP1 and ANKH allelic variants was carried out with TaqMan allelic discrimination assays. Association analysis was performed using the Cochrane-Armitage and linear regression tests as implemented in PLINK, for dichotomous and quantitative variables, respectively. Gene expression profile was carried out using Illumina HT-12 Whole-Genome Expression BeadChips and candidate genes were validated using qPCR-based TaqMan Low Density Arrays (TLDAs). Results: A total of 369 patients (62.3% male; mean age 45.4±13.2 years; mean disease duration 11.4±10.5 years), were included. Regarding clinical disease pattern, at the time of assessment, 49.9% had axial disease, 2.4% peripheral disease, 40.9% mixed disease and 7.1% isolated enthesopathic disease. Acute anterior uveitis (33.6%) was the most common extra-articular manifestation. 80.3% of AS patients were HLA-B27 positive. The haplotype A*02/B*27/Cw*02/DRB1*01/DQB1*05 seems to confer susceptibility to AS, whereas A*02/B*27/Cw*01/DRB1*08/DQB1*04 seems to provide protection in terms of disease activity, functional and radiological repercussion. Three markers (two for IL23R and one for ERAP1) showed significant single-locus disease associations. Association of these genes with AS in the Portuguese population was confirmed, whereas ANKH markers studied did not show an association with AS. No association was seen between non-MHC genes and clinical manifestations of AS. A gene expression signature for AS was established; among the fourteen validated genes, a number of them have a well-documented inflammatory role or in modulation of cartilage and bone metabolism. Conclusions: A demographic and clinical profile of patients with AS in Portugal was established. Identification of genetic variants of target genes as well as gene expression signatures could provide a better understanding of AS pathophysiology and could be useful to establish models with relevance in terms of susceptibility, prognosis, and potential therapeutic guidance.

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In recent years, new methods of clean and environmentally friendly energy production have been the focus of intense research efforts. Microbial fuel cells (MFCs) are devices that utilize naturally occurring microorganisms that feed on organic matter, like waste water, while producing electrical energy. The natural habitats of bacteria thriving in microbial fuel cells are usually marine and freshwater sediments. These microorganisms are called dissimilatory metal reducing bacteria (DMRB), but in addition to metals like iron and manganese, they can use organic compounds like DMSO or TMAO, radionuclides and electrodes as terminal electron acceptors in their metabolic pathways.(...)

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Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.