In 2015, an estimated 46.8 million people were living with dementia, a number predicted to increase to 74.7 million by 2030 and 131.5 million by 2050. Whilst there are numerous causes for the development of dementia, Alzheimer's disease is by far the most common, accounting for approximately 50-70% of all cases. Current therapeutic agents against Alzheimer's disease are palliative in nature, managing symptoms without addressing the underlying cause and thus disease progression and patient death remain a certainty. Whilst the main underlying cause for the development of Alzheimer's disease was originally thought to be an abnormal deposition of insoluble amyloid-β peptide derived plaques within the brain, the failure of several high-profile therapeutic agents, which were shown to reduce the plaque burden without improving cognition, has recently prompted a shift in focus to soluble oligomeric forms of amyloid-β peptide. Such soluble oligomers have been shown to be toxic in their own right and to precede plaque deposition. Soluble amyloid-β oligomers have been identified in various subcellular compartments, including the mitochondria, where they form a complex with the 17β-HSD10 enzyme resulting in cytotoxicity. Interestingly, hallmarks of this toxicity have been shown to be dependent on the catalytic activity of the 17β-HSD10 enzyme, suggesting two therapeutic approaches may hold merit in treating Alzheimer's disease: disrupting the interaction between the 17β-HSD10 enzyme and amyloid-β peptide, or directly inhibiting the catalytic activity of the 17β-HSD10 enzyme. In 2006, Frentizole was identified as a small molecule capable of disrupting the 17β-HSD10/amyloid interaction. The work described herein details the generation of a robust screening assay allowing the catalytic activity of the 17β-HSD10 enzyme to be measured in vitro. This assay was subsequently employed for small molecule screening using two methodologies; first in a targeted approach using compounds derived from the Frentizole core scaffold, and second in an explorative manner using a diverse library of compounds supplied by the National Cancer Institute. As a result, a range of novel small molecule inhibitors of the 17β-HSD10 enzyme have been identified and the most promising characterised in terms of potency and mechanism of action. De-selection assays were developed to allow the efficient triage of hit compounds and work was begun on a cellular based assay which would allow the ability of compounds of interest to reverse a disease relevant phenotype to be assessed in a cellular environment. As such, we now have a number of hit compounds which will form the basis for the generation of subsequent series of derivatives with improved potency and specificity, as well as the robust assays required to measure such criteria, potentially leading to the generation of novel therapeutic agents against Alzheimer's disease.

Submitted by Guilherme Batista do Nascimento null (guilhermebn@msn.com) on 2018-03-16T12:24:54Z No. of bitstreams: 1 Tese_Guilherme_Batista_do_Nascimento.pdf: 1770231 bytes, checksum: ad03948ecc7b09b89d46d26b7c9e3bf8 (MD5) / Approved for entry into archive by Alexandra Maria Donadon Lusser Segali null (alexmar@fcav.unesp.br) on 2018-03-16T19:03:02Z (GMT) No. of bitstreams: 1 nascimento_gb_dr_jabo.pdf: 1770231 bytes, checksum: ad03948ecc7b09b89d46d26b7c9e3bf8 (MD5) / Made available in DSpace on 2018-03-16T19:03:02Z (GMT). No. of bitstreams: 1 nascimento_gb_dr_jabo.pdf: 1770231 bytes, checksum: ad03948ecc7b09b89d46d26b7c9e3bf8 (MD5) Previous issue date: 2018-02-22 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A implementação de dados de sequenciamento de nova geração - “next-generation sequence” (NGS) em programas de melhoramento genético animal representa a mais recente ferramenta na utilização de dados genotípicos nos modelos de associação genômica, tendo em vista que todo polimorfismo é considerado nas associações entre registros fenotípicos e dados de sequenciamento. Como em toda nova tecnologia, a prospecção das variantes ainda representa um desafio no sentido computacional e de viabilidade dos custos para sua implementação em larga escala. Diante desses desafios, neste trabalho buscou-se meios de explorar os benefícios na utilização da NGS nas predições genômicas e superar as limitações inerentes a esse processo. Registros fenotípicos e genotípicos (Illumina Bovine HD BeadChip) de 2.279 animais da raça Gir (Bos taurus indicus) foram disponibilizados pela Embrapa Gado de Leite (MG) e utilizados para as análises de associação genômica. Além disso, dados de sequenciamento de 53 animais do 1000 “Bulls Project” deram origem à população de referência de imputação. Visando verificar a eficiência de imputação, foram testados diferentes cenários quanto a sua acurácia de imputação por meio da análise “leave-one-out”, utilizando apenas os dados de sequenciamento, que apresentaram eficiências de até 84%, no cenário com todos os 51 animais disponíveis após o controle de qualidade. Também foram verificadas as influências das variantes em baixa frequência na acurácia de imputação em diferentes regiões do genoma. Com a escolha da melhor estrutura da população de referência de imputação e aplicação dos controles de qualidade nos dados de NGS e genômicos, foi possível imputar os 2.237 animais genotipados, que passaram pelo controle de qualidade para dados de sequenciamento e realizar análise de associação genômica para as características produção de leite (PL305), teor de gordura (PG305), proteína (PP305) e sólidos totais (PS305), mensuradas aos 305 dias em animais da raça Gir leiteiro. Para tal, foram utilizados os valores genéticos desregredidos (dEBV) como variável resposta no modelo de regressão múltipla. Regiões de 1Mb que contivessem 100 ou mais variantes com “False Discovery Rate” (FDR) inferior a 0,05, foram consideradas significativas e submetidas a análise de enriquecimento por meio dos termos MeSh (“Medical Subject Headings”). As três regiões significativas (FDR<0,05) para PS305 foram observadas nos cromossomos 11, 12 e 28 e a única região significativa em PG305 foi no cromossomo 6. Tais regiões apresentaram variantes associadas com vias metabólicas da produção de leite, ausentes nos painéis comerciais de genotipagem, podendo representar genes candidatos a seleção. / - Implementing "next-generation sequence" (NGS) data in animal breeding programs represents the latest tool in the use of genotypic data in genomic association models, since all polymorphisms are considered in the associations between phenotypic records and sequencing data. As with any new technology, variant prospecting still represents a computational and cost-effective challenge for large-scale implementation. Front to these challenges, this work sought ways to explore the benefits of using NGS in genomic predictions and overcome the inherent limitations of this process. Phenotypic and genotypic (Illumina Bovine HD BeadChip) records of 2,279 Gir animals (Bos taurus indicus) were made available by Embrapa Gado de Leite (MG) and used for genomic association analysis. In addition, sequence data of 53 animals from the 1000 Bulls Project gave rise to the imputation reference population. In order to verify the imputation efficiency, different scenarios were tested for their imputation accuracy through the leave-one-out analysis, using only the sequencing data, which presented efficiencies of up to 84%, in the scenario with all the 51 animals available after quality control. Influences from the low-frequency variants on the accuracy of imputation in different regions of the genome were also verified. After identifying the best reference population structure of imputation and applying the quality controls in the NGS and genomic data, it was possible to impute the 2 237 genotyped animals that passed in the quality control to sequencing data and perform genomic association analysis for (PL305), fat content (PG305), protein (PP305) and total solids (PS305), measured at 305 days in dairy Gir animals. For this, unregulated genetic values (dEBV) were used as response variable in the multiple regression model. Regions of 1Mb containing 100 or more variants with a False Discovery Rate (FDR) lower than 0.05 were considered statistically significant and submitted to pathways enrichment analysis using the MeSh (Medical Subject Headings) terms. The three significant regions (FDR <0.05) for PS305 were observed on chromosomes 11, 12 and 28 and only one significant region in PG305, was on chromosome 6. These regions presented variants associated with metabolic pathways of milk production, absent in the panels genotyping, and may represent genes that are candidates for selection / convênio Capes/Embrapa (edital 15/2014)

Conselho Nacional de Desenvolvimento Científico e Tecnológico / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A tese pretende estabelecer o que estaria o mais próximo possível de uma lógica da descoberta para as ciências sociais. A narrativa dessas disciplinas não seria neutra nem objetiva, mas procuraria produzir, retoricamente, os efeitos de neutralidade e objetividade, evitando a heroicização, a vilanização e a vitimização dos agentes. Isso decorreria da necessidade de o cientista social validar sua narrativa perante um auditório ideal ou potencialmente universal, abrigando, em princípio, todo o tipo de valores. Essa pluralidade de visões de mundo não permite que os agentes sejam ingenuamente tratados como heróis, vilões ou vítimas. Com isso, o autor do texto de ciências sociais procuraria simular um ponto de vista de Deus, como ironista supremo, que tudo vê, acima dos participantes imperceptivos de seu relato. Foi feito um estudo de caso a partir do debate sobre populismo no Brasil, no qual foram identificados quatro pontos básicos em torno dos quais girou a controvérsia: o das estruturas prototípicas, o da estruturação imaginária, o da estrutura intersubjetiva e a dinâmica da relação entre grande teoria e pesquisa empírica. / The aim of this thesis is to get as close as possible to a logic of discovery for the social sciences. Those disciplines do not have a neutral and objective narrative, but try to achieve, rhetorically, neutrality and objectivity effects, avoiding to portrait agents as heroes, villains or victims. It follows from the need to validate scientific narratives in face of an ideally or potentially universal auditory, withholding, in principle, all kinds of values. Such plurality of world visions makes it difficult to naively treat agents as heroes, villains, or victims. As a consequence, the social scientist simulates a Gods Eye view, placing himself in a Supreme Ironist perspective, who sees everything from above, whose vision reaches beyond what nonperceptive agents can see. To make my point, I took as case study the Brazilian controversy over populism. Based on it, four main topics of development were identified: one refered to the prototypical theoretic structures, other to its imaginary structuration, another to its intersubjective structure, and a last one to the relationship of empirical research to grand theory.

As estrategias de passes têm sido sempre de interesse para a pesquisa de futebol. Desde os inícios do futebol, os técnicos tem usado olheiros, gravações de vídeo, exercícios de treinamento e feeds de dados para coletar informações sobre as táticas e desempenho dos jogadores. No entanto, a natureza dinâmica das estratégias de passes são bastante complexas para refletir o que está acontecendo dentro do campo e torna difícil o entendimento do jogo. Além disso, existe uma demanda crecente pela deteção de padrões e analise de estrategias de passes popularizado pelo tiki-taka utilizado pelo FC. Barcelona. Neste trabalho, propomos uma abordagem para abstrair as sequências de pases e agrupálas baseadas na geometria da trajetória da bola. Para analizar as estratégias de passes, apresentamos um esquema de visualização interátiva para explorar a frequência de uso, a localização espacial e ocorrência temporal das sequências. A visualização Frequency Stripes fornece uma visão geral da frequencia dos grupos achados em tres regiões do campo: defesa, meio e ataque. O heatmap de trajetórias coordenado com a timeline de passes permite a exploração das formas mais recorrentes no espaço e tempo. Os resultados demostram oito trajetórias comunes da bola para sequências de três pases as quais dependem da posição dos jogadores e os ângulos de passe. Demonstramos o potencial da nossa abordagem com utilizando dados de várias partidas do Campeonato Brasileiro sob diferentes casos de estudo, e reportamos os comentários de especialistas em futebol. / Passing strategies analysis has always been of interest for soccer research. Since the beginning of soccer, managers have used scouting, video footage, training drills and data feeds to collect information about tactics and player performance. However, the dynamic nature of passing strategies is complex enough to reflect what is happening in the game and makes it hard to understand its dynamics. Furthermore, there exists a growing demand for pattern detection and passing sequence analysis popularized by FC Barcelona’s tiki-taka. We propose an approach to abstract passing strategies and group them based on the geometry of the ball trajectory. To analyse passing sequences, we introduce a interactive visualization scheme to explore the frequency of usage, spatial location and time occurrence of the sequences. The frequency stripes visualization provide, an overview of passing groups frequency on three pitch regions: defense, middle, attack. A trajectory heatmap coordinated with a passing timeline allow, for the exploration of most recurrent passing shapes in temporal and spatial domains. Results show eight common ball trajectories for three-long passing sequences which depend on players positioning and on the angle of the pass. We demonstrate the potential of our approach with data from the Brazilian league under several case studies, and report feedback from a soccer expert.

A presente tese analisa a maneira como a probabilidade influencia a formação da decisão sobre os fatos (contexto de descobrimento), bem como a motivação acerca dessas decisões (contexto justificativo). Mediante prévia análise da relevância da verdade no processo judicial, demonstra-se também que no terreno processual somente é possível falar em probabilidade, o que implica a ideia de um modelo probabilístico do juízo de fato, cujo núcleo é o módulo da escolha entre as alternativas possíveis. Portanto, são oferecidos critérios para a escolha das alternativas, os quais são denominados como diretrizes probatórias. De outro lado, a fim de que o convencimento do juiz a respeito dos fatos seja o mais racional possível, também é examinada a obrigatoriedade da motivação das decisões judiciais. Para tanto, é realizada abordagem à luz do Estado Constitucional e, ao final, demonstra-se que a probabilidade igualmente conforma o contexto justificativo, pois faz com que a motivação seja um discurso probatório racional. / This thesis examines how probability influences the fact-finding process (context of discovery) and the motivation about the trial of facts (context of justification). Considering the analysis of the relevance of truth in the judicial process, also in the procedural field only probability is taken into account, which implies the idea of a probabilistic model of factual judgment, whose core is the module of choice among the possible alternatives. Therefore, guidelines are offered for the choice of alternatives, which are called as evidentiary guidelines. On the other hand, in order to achieve the most rational conviction of the trier, mandatory legal motivation is also examined. The approach focuses on the Constitutional State and, in the end, is shown that the probability also conforms the context of justification, in order to make the legal motivation as a rational evidence speech.

O crescimento do uso de sistemas de posicionamento global (GPS) e outros sistemas de localização espacial tornaram possível o rastreamento de objetos móveis, produzindo um grande volume de um novo tipo de dado, chamado trajetórias de objetos móveis. Existe, entretanto, uma forte lacuna entre a quantidade de dados extraídos destes dispositivos, dotados de sistemas GPS, e a descoberta de conhecimento que se pode inferir com estes dados. Um tipo de descoberta de conhecimento em dados de trajetórias de objetos móveis é a classificação. A classificação de trajetórias é um tema de pesquisa relativamente novo, e poucos métodos tem sido propostos até o presente momento. A maioria destes métodos foi desenvolvido para uma aplicação específica. Poucos propuseram um método mais geral, aplicável a vários domínios ou conjuntos de dados. Este trabalho apresenta um novo método de classificação que transforma as trajetórias em séries temporais, de forma a obter características mais discriminativas para a classificação. Experimentos com dados reais mostraram que o método proposto é melhor do que abordagens existentes. / The growing use of global positioning systems (GPS) and other location systems made the tracking of moving objects possible, producing a large volume of a new kind of data, called trajectories of moving objects. However, there is a large gap between the amount of data generated by these devices and the knowledge that can be inferred from these data. One type of knowledge discovery in trajectories of moving objects is classification. Trajectory classification is a relatively new research subject, and a few methods have been proposed so far. Most of these methods were developed for a specific application. Only a few have proposed a general method, applicable to multiple domains or datasets. This work presents a new classification method that transforms the trajectories into time series, in order to obtain more discriminative features for classification. Experiments with real trajectory data revealed that the proposed approach is more effective than existing approaches.

abstract: Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning of the relevant patterns This dissertation proposes TS representations and methods for supervised TS analysis. The approaches combine new representations that handle translations and dilations of patterns with bag-of-features strategies and tree-based ensemble learning. This provides flexibility in handling time-warped patterns in a computationally efficient way. The ensemble learners provide a classification framework that can handle high-dimensional feature spaces, multiple classes and interaction between features. The proposed representations are useful for classification and interpretation of the TS data of varying complexity. The first contribution handles the problem of time warping with a feature-based approach. An interval selection and local feature extraction strategy is proposed to learn a bag-of-features representation. This is distinctly different from common similarity-based time warping. This allows for additional features (such as pattern location) to be easily integrated into the models. The learners have the capability to account for the temporal information through the recursive partitioning method. The second contribution focuses on the comprehensibility of the models. A new representation is integrated with local feature importance measures from tree-based ensembles, to diagnose and interpret time intervals that are important to the model. Multivariate time series (MTS) are especially challenging because the input consists of a collection of TS and both features within TS and interactions between TS can be important to models. Another contribution uses a different representation to produce computationally efficient strategies that learn a symbolic representation for MTS. Relationships between the multiple TS, nominal and missing values are handled with tree-based learners. Applications such as speech recognition, medical diagnosis and gesture recognition are used to illustrate the methods. Experimental results show that the TS representations and methods provide better results than competitive methods on a comprehensive collection of benchmark datasets. Moreover, the proposed approaches naturally provide solutions to similarity analysis, predictive pattern discovery and feature selection. / Dissertation/Thesis / Ph.D. Industrial Engineering 2012

abstract: Signal processing techniques have been used extensively in many engineering problems and in recent years its application has extended to non-traditional research fields such as biological systems. Many of these applications require extraction of a signal or parameter of interest from degraded measurements. One such application is mass spectrometry immunoassay (MSIA) which has been one of the primary methods of biomarker discovery techniques. MSIA analyzes protein molecules as potential biomarkers using time of flight mass spectrometry (TOF-MS). Peak detection in TOF-MS is important for biomarker analysis and many other MS related application. Though many peak detection algorithms exist, most of them are based on heuristics models. One of the ways of detecting signal peaks is by deploying stochastic models of the signal and noise observations. Likelihood ratio test (LRT) detector, based on the Neyman-Pearson (NP) lemma, is an uniformly most powerful test to decision making in the form of a hypothesis test. The primary goal of this dissertation is to develop signal and noise models for the electrospray ionization (ESI) TOF-MS data. A new method is proposed for developing the signal model by employing first principles calculations based on device physics and molecular properties. The noise model is developed by analyzing MS data from careful experiments in the ESI mass spectrometer. A non-flat baseline in MS data is common. The reasons behind the formation of this baseline has not been fully comprehended. A new signal model explaining the presence of baseline is proposed, though detailed experiments are needed to further substantiate the model assumptions. Signal detection schemes based on these signal and noise models are proposed. A maximum likelihood (ML) method is introduced for estimating the signal peak amplitudes. The performance of the detection methods and ML estimation are evaluated with Monte Carlo simulation which shows promising results. An application of these methods is proposed for fractional abundance calculation for biomarker analysis, which is mathematically robust and fundamentally different than the current algorithms. Biomarker panels for type 2 diabetes and cardiovascular disease are analyzed using existing MS analysis algorithms. Finally, a support vector machine based multi-classification algorithm is developed for evaluating the biomarkers' effectiveness in discriminating type 2 diabetes and cardiovascular diseases and is shown to perform better than a linear discriminant analysis based classifier. / Dissertation/Thesis / Ph.D. Electrical Engineering 2012

abstract: Research on government innovation has focused on identifying factors that contribute to higher levels of innovation adoption. Even though various factors have been tested as contributors to high levels of innovation adoption, the independent variables have been predominantly contextual and community characteristics. Previous empirical studies shed little light on chief executive officers' (CEOs) attitudes, values, and behavior. Result has also varied with the type of innovation examined. This research examined the effect of CEOs' attitudes and behaviors, and institutional motivations on the adoption of sustainability practices in their municipalities. First, this study explored the relationship between the adoption level of sustainability practices in local government and CEOs' entrepreneurial attitudes (i.e. risk taking, proactiveness, and innovativeness) and discovery skills (i.e. associating, questioning, experimenting, observing, and networking) that have not been examined in prior research on local government innovation. Second, the study explored the impact of organizational intention to change and isomorphic pressures (i.e., coercive, mimetic, and normative pressures) and the availability and limit of organizational resources on the early adoption of innovations in local governments. Third, the study examines how CEOs' entrepreneurial attitudes and discovery skills, and institutional motivations account for high and low sustaining levels of innovation over time by tracking how much their governments have adopted innovations from the past to the present. Lastly, this study explores their path effects CEOs' entrepreneurial attitudes, discovery skills, and isomorphic pressures on sustainability innovation adoption. This is an empirical study that draws on a survey research of 134 CEOs who have influence over innovation adoption in their local governments. For collecting data, the study identified 264 municipalities over 10,000 in population that have responded to four surveys on innovative practices conducted by the International City/County Management Association (ICMA) in past eight years: the Reinventing local government survey (2003), E-government survey (2004), Strategic practice (2006), and the Sustainability survey (2010). This study combined the information about the adoption of innovations from four surveys with CEOs' responses in the current survey. Socio-economic data and information about variations in form of government were also included in the data set. This study sheds light on the discovery skills and institutional isomorphic pressures that influence the adoption of different types of innovations in local governments. This research contributes to a better understanding of the role of administrative leadership and organizational isomorphism in the dynamic of innovation adoption, which could lead to improvements in change management of organizations. / Dissertation/Thesis / Ph.D. Public Administration 2013

Filariasis and onchocerciasis are debilitating diseases affecting 120 million people globally. The massive socio-economic impact of these diseases energized the international community to declare a goal of eliminating filariasis 2020. This resulted in a dramatic increase in the efforts to eliminate filariasis and onchocerciasis, employing a strategy of mass drug administration (MDA). However, these programs rely upon the small arsenal of drugs. This leaves these programs vulnerable to failure in the face of developing resistance and local intolerance to the current drug regimens. Thus, new drugs against these infections are critically needed. A homologue of the ecdysone receptor (EcR), a master regulator of development in insects, has been identified in B. malayi. The potential of the EcR as a drug target has been underscored by work in the agricultural industry, where insecticides targeting the ecdysone developmental pathway are effective and non-toxic to non-target species. As the EcR is absent in humans, it represents an attractive potential chemotherapeutic target. The first study investigates the hypothesis that the ecdysone receptor controls the embryogenesis and molting in the filarial parasite. In-vitro embryogram and in-vivo phenotypic studies were conducted to delineate the effect of 20-hydroxyecdysone on the Brugia malayi parasites. The results suggest that the hormone accelerates embryogenesis and causes precocious molts, resulting in the death of the parasite. Further, transcriptomic and proteomic analysis of the ecdysone treated worms provided evidence that the up-regulated genes participate in embryogenesis. Based upon the validation of the ecdysone receptor as a potential drug target, subsequent studies focused on the development of a drug discovery model to screen for agonists and antagonists of the B. malayi ecdysone receptor. A stable cell line was created to aid the high throughput screening to rapidly identity agonist and antagonist compounds. A total of 7 agonists and 2 antagonists were identified. A homology model of the BmEcR ligand-binding domain was created as an alternate method for virtual screening of small molecules as well as to study the ligand-receptor interactions. The hits identified with the assay were docked in the active site of the BmEcR homology model providing an excellent correspondence of data between the molecular assay and the virtual screening method.