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Soybean and wheat are important crop species due to their significance for human consumption, animal feed, and industrial use. However, increasing global population and worsening climate change have put a major strain on the production system of these crops. Natural disasters such as flooding and drought can severely impact growth and productivity of these crops. In addition, increased application of synthetic nitrogenous fertilizers to meet the global food demand has led to environment related issues. Therefore, with a goal of understanding mechanisms of flooding and drought tolerance in soybean and nitrogen-use-efficiency in wheat, we explored their physiological and transcriptomic regulation. We characterized the fundamental acclimation responses of soybean to flooding and drought and compared the metabolic and transcriptomic regulation during the stresses in a tissue-specific manner. We demonstrated the dynamic reconfiguration of gene expression and metabolism during flooding, drought, and recovery from these stresses. Our study displayed that flooding triggers more dramatic adjustments than drought at the transcriptional level. We also identified that the soybean genome encodes nine members of group VII ERF genes and characterized their responses in leaves and roots under flooding and drought. Based on the expression patterns, it is estimated that two of the nine genes are promising candidate genes regulating tolerance to submergence and drought. In addition, our genome-scale expression analysis discovered commonly induced ERFs and MAPKs across both stresses (flooding and drought) and tissues (leaves and roots), which might play key roles in soybean survival of flooding and drought. In wheat, we evaluated the effect of three different nitrogen rates on yield and its components across four diverse soft red winter wheat genotypes. The cultivar Sisson displayed superior performance in grain yield and nitrogen use efficiency at low nitrogen levels. Our results suggested that improvement of nitrogen use efficiency in low nitrogen environments can be achieved through the selection of three components: grain number/spike, 1000-seed weight, and harvest index. Overall, this study has advanced our understanding of how plants respond to abiotic stresses such as flooding, drought, and nutrient limitation conditions. / Ph. D. / Soybean and wheat are commercially important crop throughout the world. Soybean is a major source of protein and oil for humans, livestock and industrial products including biofuel production. Similarly, wheat is a major source of food products such as bread, pasta, and cookies. However, increasing global population and worsening climate change have put a major strain on the production system of these crops. Natural disasters such as flooding and drought are on the rise, which have severely impacted soybean growth and productivity. In addition, increased application of synthetic nitrogenous fertilizers in wheat production to meet the global food demand has led to environment related issues. Therefore, a mechanistic understanding of flooding and drought tolerance in soybean and nitrogen use efficiency in wheat is of utmost importance. The knowledge obtained from these studies can aid in the development of new varieties in these crops. Here, we carried out our study on soybean by imposing either complete submergence or restricting water supply to characterize the responses to these stresses in shoot and root systems. We found several compounds and genes that were altered distinctly under these two water-related stresses. In addition, we identified some promising genes that can significantly regulate tolerance in soybean to flooding and drought in soybean. To study wheat nitrogen use efficiency, we selected four diverse soft red winter wheat varieties and grew them under three nitrogen levels. We found that the cultivar Sisson has the lowest yield penalty among the four varieties resulting from low nitrogen conditions. In addition, we also demonstrated that three yield traits (grain number per spike, 1000-seed weight, and harvest index) are important selection targets to develop high nitrogen use efficiency varieties.

RNA-Seq is an increasingly popular approach to transcriptome profiling that uses the capabilities of next generation sequencing technologies and provides better measurement of levels of transcripts and their isoforms. In this thesis, we apply RNA-Seq protocol and transcriptome quantification to estimate gene expression and pathway activity levels. We present a novel method, called IsoDE, for differential gene expression analysis based on bootstrapping. In the first version of IsoDE, we compared the tool against four existing methods: Fisher's exact test, GFOLD, edgeR and Cuffdiff on RNA-Seq datasets generated using three different sequencing technologies, both with and without replicates. We also introduce the second version of IsoDE which runs 10 times faster than the first implementation due to some in-memory processing applied to the underlying gene expression frequencies estimation tool and we also perform more optimization on the analysis. The second part of this thesis presents a set of tools to differentially analyze metabolic pathways from RNA-Seq data. Metabolic pathways are series of chemical reactions occurring within a cell. We focus on two main problems in metabolic pathways differential analysis, namely, differential analysis of their inferred activity level and of their estimated abundance. We validate our approaches through differential expression analysis at the transcripts and genes levels and also through real-time quantitative PCR experiments. In part Four, we present the different packages created or updated in the course of this study. We conclude with our future work plans for further improving IsoDE 2.0.

The rise of internet connected devices has enabled the home with a vast amount of enhancements to make life more convenient. These internet connected devices can be used to form a community of devices known as the internet of things (IoT). There is great value in IoT devices to promote healthy independent living for older adults. Fall-related injuries has been one of the leading causes of death in older adults. For example, every year more than a third of people over 65 in the U.S. experience a fall, of which up to 30 percent result in moderate to severe injury. Therefore, this thesis proposes an IoT-based fall detection system for smart home environments that not only to send out alerts, but also launches interaction models, such as voice assistance and camera monitoring. Such connectivity could allow older adults to interact with the system without concern of a learning curve. The proposed IoT-based fall detection system will enable family and caregivers to be immediately notified of the event and remotely monitor the individual. Integrated within a smart home environment, the proposed IoT-based fall detection system can improve the quality of life among older adults. Along with the physical concerns of health, psychological stress is also a great concern among older adults. Stress has been linked to emotional and physical conditions such as depression, anxiety, heart attacks, stroke, etc. Increased susceptibility to stress may accelerate cognitive decline resulting in conversion of cognitively normal older adults to MCI (Mild Cognitive Impairment), and MCI to dementia. Thus, if stress can be measured, there can be countermeasures put in place to reduce stress and its negative effects on the psychological and physical health of older adults. This thesis presents a framework that can be used to collect and pre-process physiological data for the purpose of validating galvanic skin response (GSR), heart rate (HR), and emotional valence (EV) measurements against the cortisol and self-reporting benchmarks for stress detection. The results of this framework can be used for feature extraction to feed into a regression model for validating each combination of physiological measurement. Also, the potential of this framework to automate stress protocols like the Trier Social Stress Test (TSST) could pave the way for an IoT-based platform for automated stress detection and management.

The diploma thesis "Celebritization of news service and journalism on Czech commercial TV channels" focuses on the growing trend of appointing celebrities as anchormen on news broadcasts. Entertainization and celebritization of news services raises the question of whether these patterns contribute to the professionalization or deprofessionalization of journalism. This work aims to examine the consequences of celebrity presence in newscasting because of the obvious changes in broadcaster representatives. Primarily, this analysis focuses on private channels (Prima, Nova, Barrandov) employing Czech celebrity as anchormen despite their lack of previous media experience or education in the field. The theoretical part introduces the requirements for TV presenters and elaborates on the terms "professionalization" and "celebritization". The methodological part clarifies the selection of presenters researched, as well as the chosen methods of analysis. The qualitative method is utilized to analyze the research portion of this thesis, which mainly addresses the linguistic aspect of the speakers' speech and their non-verbal communication.

Estudos de expressão gênica geralmente envolvem a realização de processos de análise integrados para a obtenção de respostas biológicas de interesse. A realização destes processos frequentemente requer o uso combinado de uma série de ferramentas de software. No entanto, o processo de integração manual de ferramentas pode ser demorado e propenso a erros devido ao crescente número de ferramentas e formatos de dados disponíveis no domínio. De modo a automatizar o processo de integração, algumas abordagens têm sido propostas tanto para a adaptação das ferramentas de análise existentes como serviços web semânticos, quanto para o desenvolvimento de ambientes de suporte à integração (composição) de serviços web semânticos. Embora estas abordagens representem avanços, nenhuma solução adequada para o desenvolvimento e composição de serviços foi especificamente definida para o domínio de genômica funcional. Neste contexto, o principal objetivo deste projeto foi investigar uma solução completa para o desenvolvimento e composição de serviços web semânticos para a análise de expressão gênica. Como parte da solução proposta, definimos uma metodologia integrada para a implementação de serviços web semânticos criados a partir de ferramentas de software existentes e para a anotação semântica destes serviços. Nossa metodologia fornece diretrizes concretas para o desenvolvimento sistemático de serviços, considerando também os principais aspectos técnicos associados ao processo de desenvolvimento. Esta metodologia foi aplicada a um conjunto representativo de serviços que fornecem suporte às principais atividades de análise realizadas em diferentes tipos de dados de expressão gênica. De forma complementar, definimos uma solução completa para a composição semântica de serviços no domínio de análise de expressão gênica. A solução proposta foi implementada em uma plataforma de suporte semi-automático à composição de serviços web semânticos, chamada SemanticSCo. Esta plataforma fornece suporte flexível a todas as atividades envolvidas no processo de composição de serviços, incluindo a criação, publicação, requisição, descoberta, seleção, composição e execução de serviços. Além disto, a plataforma SemanticSCo foi projetada para prover suporte adequado a diferentes tipos de usuários, incluindo biologistas e bioinformatas. Neste sentido, a plataforma fornece aos usuários um alto nível de abstração para a definição de seus processos de análise, permitindo que os mesmos se concentrem mais nas questões de pesquisa biológicas do que nos aspectos subjacentes do processo de composição. Adicionalmente, a plataforma SemanticSCo suporta a definição e incorporação não apenas de serviços simples, definidos em termos de uma única operação, mas também de serviços complexos, definidos em termos de um conjunto de condições que restringem a ordem de invocação de suas operações. Finalmente, de modo a avaliar a plataforma de suporte desenvolvida, definimos diferentes cenários de composição para a análise (integrada) de dados de expressão gênica. O uso da plataforma SemanticSCo facilitou a definição destes cenários, permitindo assim a reprodução dos resultados obtidos a partir de diferentes estudos de expressão gênica previamente documentados na literatura / Gene expression studies usually involve the creation of integrated analysis processes for obtaining responses for a biological question. The creation of such processes often require the combined use of a number of software tools. However, the manual integration of tools can be cumbersome and error prone due to the increasing number of tools and data formats available in the domain. In order to automate the integration process, some approaches have been proposed for the adaptation of existing analysis tools as semantic web services as well as for the development of software environments to support the integration (composition) of semantic web services. Although these approaches present advances, to the best of our knowledge, no suitable solution has been proposed for the development and composition of web services in the functional genomics domain. In this context, this project aimed at investigating a complete solution for the development and composition of semantic web services to support gene expression analysis. As part of the proposed solution, we have defined an integrated methodology for the implementation of semantic web services created from existing software tools and the semantic annotation of such services. Our methodology provides concrete guidelines for the systematic development of services, also taking into account the main technical aspects associated with the development process. This methodology has been applied in the development of a representative set of services that support the main analysis activities performed on different types of gene expression data. Complementary to our methodology, we have defined a complete solution for the semantic composition of web services in the gene expression analysis domain. The proposed solution has been implemented in a software platform to support the semi-automatic composition of semantic web services, named SemanticSCo. This platform provides flexible support to all activities involved in the service composition process including service creation, publication, request, discovery, selection, composition and execution. Additionally, the SemanticSCo platform has been designed to support different types of users, including biologists and bioinformaticians. In this sense, the platform provides users with a high level of abstraction in the definition of their analysis processes, thus allowing them to focus more on biological research issues rather than on underlying details of the composition process. In addition, the SemanticSCo platform supports not only the definition and incorporation of (simple) services defined in terms of a single operation, but also (complex) services defined in terms of a set of conditions that constrain the order in which service operations should be invoked. Finally, in order to evaluate the developed support platform, we have defined a number of composition scenarios for the (integrated) analysis of gene expression data. The use of the SemanticSCo platform has facilitated the definition of these scenarios, thus allowing the reproduction of the results obtained from different gene expression studies previously documented in the literature.

O fungo Aspergillus fumigatus é o segundo maior causador de infecções fúngicas invasivas em pacientes imunocomprometidos e a principal espécie causadora da aspergilose invasiva, doença de alta taxa de mortalidade que atinge principalmente os pulmões e que pode se disseminar pelo organismo. Durante o processo de infecção, o fungo precisa adaptar-se ao organismo do hospedeiro e um dos obstáculos encontrados é a mudança na concentração de dióxido de carbono (CO2), que, de 0,033% no ambiente, chega a até 6% no interior do hospedeiro. As anidrases carbônicas são enzimas envolvidas na hidratação reversível do CO2 e já foram apontadas como importantes na virulência de patógenos como Plasmodium falciparum, Mycobacterium tuberculosis, Helicobacter pylori, Cryptococcus neoformans e Candida albicans. Esse trabalho teve como objetivo avaliar o papel da enzima anidrase carbônica no desenvolvimento e virulência do fungo A. fumigatus, que apresenta quatro homólogos desta enzima (cafA, cafB, cafC e cafD). Para isso, foram utilizadas linhagens de A. fumigatus com os homólogos da enzima deletados (?cafA, ?cafB, ?cafC, ?cafD e ?cafA?cafB) e a linhagem selvagem (?akuBku80), da qual foram originadas as mutantes. Foram realizadas avaliações fenotípicas da estrutura dos conidióforos das diferentes linhagens, determinação da sensibilidade frente a diferentes agentes estressantes (antifúngicos, promotores de apoptose, estresse iônico, nitroativo, oxidativo, e de parede celular) e determinação da expressão gênica global em diferentes concentrações de CO2. Foi verificado que a deleção de cada um dos homólogos da anidrase carbônica de A. fumigatus não interfere na estrutura dos conidióforos deste fungo. Por outro lado, a deleção induziu alteração da sensibilidade do fungo frente a alguns compostos estressantes (ácido acético e peróxido de hidrogênio). Ainda, a análise da expressão gênica revelou um gene envolvido na adaptação do fungo ao aumento da concentração de CO2, o gene cipC, que não apresenta homólogos nas células de mamíferos. Este gene foi caracterizado neste trabalho por meio de sua deleção na linhagem selvagem (?akuBku80) de A. fumigatus e avaliação fenotípica microscópica e de sensibilidade a agentes estressantes (antifúngicos, promotores de apoptose, estresse iônico, nitroativo, oxidativo, e de parede celular). A deleção do gene não interferiu na estrutura do fungo, porém aumentou sua sensibilidade a alguns compostos (calcoflúor e menadiona). Foram realizados, ainda, testes de virulência em modelo animal utilizando-se o mutante ?cipC, os quais revelaram que a deleção deste gene atenua a virulência do fungo. Assim, foi possível concluir que as anidrases carbônicas não são relevantes para o desenvolvimento e virulência de A. fumigatus; porém, este fungo modifica a expressão de seus genes de modo a adaptar-se às variações na concentração atmosférica de CO2. O gene cipC está envolvido nesse processo de adaptação e é importante para o desenvolvimento do fungo e sua virulência, tornando-se um alvo para o estudo de novas terapias para o tratamento da aspergilose invasiva. / The fungus Aspergillus fumigatus is the second cause of fungal infections in immunocompromised patients and it is the main specie which causes invasive aspergillosis, a disease with high mortality rate that mainly affects the lungs and it can spread through the body. During the infectious process, the fungus must adapt to the host and one of the obstacles is the drastic change of the carbon dioxide (CO2) concentration, which is 0.033% in the environment and until 6% inside the host. The carbonic anhydrases are enzymes which are involved in the reversible hydration of carbon dioxide and they have been pointed as important in the virulence of pathogens such as Plasmodium falciparum, Mycobacterium tuberculosis, Helicobacter pylori, Cryptococcus neoformans and Candida albicans. This work aimed to evaluate the role of the enzyme carbonic anhydrase in the development and virulence of the fungus A. fumigatus, which has four homologues of this enzyme (cafA, cafB, cafC e cafD). Therefore, strains, which have the homologues of the enzyme deleted (?cafA, ?cafB, ?cafC, ?cafD and ?cafA?cafB) were used in parallel with the wild strain (?akuBku80), which originated the mutant ones. We did structure phenotypic evaluations of the different strains of conidiophores, sensibility determination against different stressors (antifungal agents, apoptosis, ionic, nitrosative, oxidative, and cell wall stress promoters) and global gene expression determination at different carbon dioxide concentrations. It was verified that the carbonic anhydrases homologues deletion of A. fumigatus did not interfere on the n structure (conidiophore) of this fungus, in the tested conditions. On the other hand, the deletion caused a change in sensibility of the fungus against some stressors (acetic acid and hydrogen peroxide). The gene expression experiments showed a gene involved in the adaptation to the increase of CO2 concentration, the cipC gene. This gene does not have homologues in the mammalian cells. The cipC gene was characterized in this work by its deletion in the A. fumigatus wild strain (?akuBku80) and microscopic phenotypic evaluation and sensibility tests against stressors (antifungal agents, apoptosis, ionic, nitrosative, oxidative, and cell wall stress promoters). The gene deletion did not interfere on the fungus conidiophore structure but increase its sensibility to some compounds (calcoflúor white and menadione). Virulence tests in animal model using the ?cipC mutant were done and they showed that the deletion of this gene attenuates the fungus virulence. In conclusion, the carbonic anhydrases are not relevant to development and virulence of the fungus, which modifies the gene expression to adapt to the variations of atmospheric CO2 concentration. Besides, the cipC gene seems to be involved in this adaptation process. Moreover, the cipC gene showed to be important to the development of the fungus and its virulence, which makes the gene a target for the study of new therapies for the treatment of invasive aspergillosis.

As pesquisas em biologia molecular têm produzido uma grande quantidade de dados, os quais embutem informações sobre diferentes fenômenos biológicos. Neste sentido, a bioinformática se destaca como uma área de pesquisa multidisciplinar que visa, principalmente, o desenvolvimento de ferramentas (sistemas) computacionais para auxiliar na descoberta de conhecimento a partir de dados biológicos. Dentro da bioinformática, a área de genômica funcional procura estudar as funções gênicas através da medição simultânea e em larga escala dos níveis de expressão gênica de um genoma. Diferentes ferramentas são utilizadas no processo de análise de expressão gênica, cada qual provê suporte a uma atividade de análise específica. Embora alguns ambientes de descoberta de conhecimento ofereçam suporte integrado a este processo de análise e exploração de dados, a maior parte das ferramentas de análise é desenvolvida independentemente de outras ferramentas e ambientes de descoberta de conhecimento. Este cenário representa um desafio para biologistas que precisam combinar e integrar diferentes ferramentas, muitas vezes de forma ad hoc, custosa e sujeita a erros. Modelos conceituais, tais como ontologias, têm contribuído para o sucesso do desenvolvimento de sistemas computacionais em diferentes domínios de aplicação. O desenvolvimento de tais modelos tem por objetivo representar corretamente, em alto nível de abstração, conceitos e situações pertinentes a um dado domínio de interesse. Esta representação abstrata facilita não apenas o entendimento de um dado domínio, mas também serve como base para o processo de desenvolvimento do sistema como um todo. O objetivo deste trabalho é investigar o desenvolvimento e o uso de modelos conceituais em geral e ontologias em particular, na integração de ferramentas na área de análise de expressão gênica. De forma específica, este trabalho tem por objetivo propor uma abordagem para a integração semântica de ferramentas de análise de expressão gênica a partir do uso de conectores e de uma ontologia de domínio. Essa abordagem foi aplicada no desenvolvimento de estudos de caso envolvendo a criação de diferentes ambientes integrados para a análise de expressão gênica e mostrou-se eficaz. / Molecular biology researches are increasingly producing large amounts of data regarding underlying biological phenomena. Bioinformatics is a multidisciplinary research field whose main objective is the development of theories and information systems to help the process of knowledge discovery from biological data. Functional genomics is a field of study bioinformatics concerned with the study of gene function through parallel and large scale expression measurements of a genome. A variety of software tools are usually combined and used in a knowledge discovery process, each providing support for a specific data analysis task. Although some tools are already provided as part of an integrated knowledge discovery environment, most of them are developed independently of other software tools and knowledge discovery environments. This scenario poses a problem and a challenge for biologists that need to combine and integrate different tools in an ad hoc, time consuming and error prone process. Conceptual models, such as ontologies, have contributed to the successful development of information systems in different application domains. The development of such models aims at creating a clear and precise description of the elements of a given domain at a high abstraction level. This abstract and high level description not only promotes a shared understanding of the domain, but also serves as basis for the development process of supporting applications in the domain. This work aims at investigating the development and use of conceptual models in general and ontologies in particular to support the integration of gene expression data analysis systems. Specifically, this work proposes an approach for the semantic integration of gene expression analysis tools using connectors and a domain ontology. This approach was applied in the development of a number of case studies aiming at creating integrated environments for gene expression analysis and proved its effectiveness.

Interaktionen zwischen Zellen sowie deren Aktivierung werden im Immunsystem durch verschiedene Zelloberflächenmoleküle reguliert. Inhalt dieser Arbeit war die Untersuchung des kürzlich identifizierten Rezeptor-Ligand-Paares BTLA und HVEM. Zunächst wurden diverse BTLA-spezifische monoklonale Antikörper generiert, mit deren Hilfe erstmals die Lokalisation BTLA-tragender Zellen im Gewebe gezeigt werden konnte. Bei umfassenden Expressionsanalysen fiel auf, dass BTLA auf nahezu allen Leukozytenpopulationen der lymphatischen Organe konstitutiv vorhanden ist, und mit seinem Liganden HVEM koexprimiert wird. Beide Moleküle werden auf verschiedenen Zellpopulationen differenziell exprimiert und aktivierungsabhängig reguliert. Funktionelle Analysen in vitro als auch in vivo ergaben, dass die BTLA-HVEM-Interaktion durch Suppression der T-Zellaktivierung und –proliferation wesentlich zur negativen Regulation der Immunantort beiträgt. Die negative Wirkung von BTLA zeigte sich sowohl bei der Initiation als auch bei bereits fortgeschrittener Aktivierung, unabhängig von der Beteiligung positiver kostimulatorischer Signalwege. Durch Stimulation von T Zellen mit unterschiedlicher BTLA-Oberflächenexpression (verschiedene Subpopulationen oder aus transgenen Mäusen) konnte die strikte Korrelation der negativen Funktion mit der BTLA-Menge auf den Zellen gezeigt werden. Es stellte sich heraus, dass BTLA essentiell für die HVEM-vermittelte Suppression ist und eine wesentliche Beteiligung weiterer HVEM-Interaktionspartner (z.B. CD160) nicht vorliegt. Die Beobachtung von veränderten Lymphozytenpopulationen in BTLA-transgenen Mäusen im Ruhezustand weist zudem auf einen zentralen Beitrag des negativen BTLA-Signals zur Aufrechterhaltung der Homöostase hin. Die ubiquitäre Expression von HVEM und BTLA in Kombination mit der gegenseitigen Modulation beider Interaktionspartner ermöglicht eine flexible Reaktion des Immunsystems auf äußere Einflüsse unter anderem über die negative Regulation durch BTLA / Activation of immune cells is regulated by various cell surface molecules during cell-cell interactions. The aim of this work was the characterization of the recently identified receptor-ligand-pair BTLA and HVEM. Initially, several BTLA-specific monoclonal antibodies were generated. With these antibodies, the localization of BTLA expressing cells in the tissues has been determined for the first time. Further detailed flow cytometric analysis revealed a strong constitutive expression of BTLA on nearly all leukocytes in lymphoid organs. Interestingly, all BTLA-expressing cells co-expressed its ligand HVEM. However, both molecules were differentially expressed on different cell populations in the steady state, but were also regulated in an activation-dependent way. Functional analyses in vitro and in vivo (in an antigen-specific adoptive transfer system) revealed a substantial contribution of the BTLA-HVEM interaction for negative regulation of immune responses by suppressing T cell activation and proliferation. Inhibitory signals of BTLA affect the initial and ongoing activation, irrespective of simultaneous positive signals from other co¬stimulatory pathways. Using wildtype and BTLA-transgenic primary T cells, a strictly linear relationship between the inhibitory function of BTLA and its cell surface levels was observed. The data clearly demonstrate that BTLA expression determined the strength of HVEM-mediated suppression, but also that BTLA is essential for this negative co-stimulation, whereas other HVEM-interaction partners were apparently not involved. Finally, the observed changes in lymphoid cell populations of the BTLA-transgenic mice even in the resting state indicate a prominent role for negative BTLA signals to maintain homeostasis. The ubiquitous expression of HVEM and BTLA together with the reciprocal modulation of both interaction partners supports flexible reaction and regulation of the immune system particularly via the inhibitory function of BTLA.