Multifunctional nanoparticles for MR and fluorescence imaging

In the past few years a new generation of multifunctional nanoparticles (NPs) has been proposed for biomedical applications, whose structure is more complex than the structure of their predecessor monofunctional counterparts. The development of these novel NPs aims at enabling or improving the performance in imaging, diagnosis and therapeutic applications. The structure of such NPs comprises several components exhibiting various functionalities that enable the nanoparticles to perform multiple tasks simultaneously, such as active targeting of certain cells or compartmentalization, imaging and delivery of active drugs. This thesis presents two types of bimodal bio-imaging probes and describes their physical and chemical properties, namely their texture, structure, and 1H dynamics and relaxometry, in order to evaluate their potential as MRI contrast agents. The photoluminescence properties of these probes are studied, aiming at assessing their interest as optical contrast agents. These materials combine the properties of the trivalent lanthanide (Ln3+) complexes and nanoparticles, offering an excellent solution for bimodal imaging. The designed T1- type contrast agent are SiO2@APS/DTPA:Gd:Ln or SiO2@APS/PMN:Gd:Ln (Ln= Eu or Tb) systems, bearing the active magnetic center (Gd3+) and the optically-active ions (Eu3+ and Tb3+) on the surface of silica NPs. Concerning the relaxometry properties, moderate r1 increases and significant r2 increases are observed in the NPs presence, especially at high magnetic fields, due to susceptibility effects on r2. The Eu3+ ions reside in a single low-symmetry site, and the photoluminescence emission is not influenced by the simultaneous presence of Gd3+ and Eu3+. The presence of Tb3+, rather than Eu3+ ion, further increases r1 but decreases r2. The uptake of these NPs by living cells is fast and results in an intensity increase in the T1-weighted MRI images. The optical features of the NPs in cellular pellets are also studied and confirm the potential of these new nanoprobes as bimodal imaging agents. This thesis further reports on a T2 contrast agent consisting of core-shell NPs with a silica shell surrounding an iron oxide core. The thickness of this silica shell has a significant impact on the r2 and r2* relaxivities, and a tentative model is proposed to explain this finding. The cell viability and the mitochondrial dehydrogenase expression given by the microglial cells are also evaluated.

Service composition for biomedical applications

A exigente inovação na área das aplicações biomédicas tem guiado a evolução das tecnologias de informação nas últimas décadas. Os desafios associados a uma gestão, integração, análise e interpretação eficientes dos dados provenientes das mais modernas tecnologias de hardware e software requerem um esforço concertado. Desde hardware para sequenciação de genes a registos electrónicos de paciente, passando por pesquisa de fármacos, a possibilidade de explorar com precisão os dados destes ambientes é vital para a compreensão da saúde humana. Esta tese engloba a discussão e o desenvolvimento de melhores estratégias informáticas para ultrapassar estes desafios, principalmente no contexto da composição de serviços, incluindo técnicas flexíveis de integração de dados, como warehousing ou federação, e técnicas avançadas de interoperabilidade, como serviços web ou LinkedData. A composição de serviços é apresentada como um ideal genérico, direcionado para a integração de dados e para a interoperabilidade de software. Relativamente a esta última, esta investigação debruçou-se sobre o campo da farmacovigilância, no contexto do projeto Europeu EU-ADR. As contribuições para este projeto, um novo standard de interoperabilidade e um motor de execução de workflows, sustentam a sucesso da EU-ADR Web Platform, uma plataforma para realizar estudos avançados de farmacovigilância. No contexto do projeto Europeu GEN2PHEN, esta investigação visou ultrapassar os desafios associados à integração de dados distribuídos e heterogéneos no campo do varíoma humano. Foi criada uma nova solução, WAVe - Web Analyses of the Variome, que fornece uma coleção rica de dados de variação genética através de uma interface Web inovadora e de uma API avançada. O desenvolvimento destas estratégias evidenciou duas oportunidades claras na área de software biomédico: melhorar o processo de implementação de software através do recurso a técnicas de desenvolvimento rápidas e aperfeiçoar a qualidade e disponibilidade dos dados através da adopção do paradigma de web semântica. A plataforma COEUS atravessa as fronteiras de integração e interoperabilidade, fornecendo metodologias para a aquisição e tradução flexíveis de dados, bem como uma camada de serviços interoperáveis para explorar semanticamente os dados agregados. Combinando as técnicas de desenvolvimento rápidas com a riqueza da perspectiva "Semantic Web in a box", a plataforma COEUS é uma aproximação pioneira, permitindo o desenvolvimento da próxima geração de aplicações biomédicas.

Mining biomedical information from scientific literature

The rapid evolution and proliferation of a world-wide computerized network, the Internet, resulted in an overwhelming and constantly growing amount of publicly available data and information, a fact that was also verified in biomedicine. However, the lack of structure of textual data inhibits its direct processing by computational solutions. Information extraction is the task of text mining that intends to automatically collect information from unstructured text data sources. The goal of the work described in this thesis was to build innovative solutions for biomedical information extraction from scientific literature, through the development of simple software artifacts for developers and biocurators, delivering more accurate, usable and faster results. We started by tackling named entity recognition - a crucial initial task - with the development of Gimli, a machine-learning-based solution that follows an incremental approach to optimize extracted linguistic characteristics for each concept type. Afterwards, Totum was built to harmonize concept names provided by heterogeneous systems, delivering a robust solution with improved performance results. Such approach takes advantage of heterogenous corpora to deliver cross-corpus harmonization that is not constrained to specific characteristics. Since previous solutions do not provide links to knowledge bases, Neji was built to streamline the development of complex and custom solutions for biomedical concept name recognition and normalization. This was achieved through a modular and flexible framework focused on speed and performance, integrating a large amount of processing modules optimized for the biomedical domain. To offer on-demand heterogenous biomedical concept identification, we developed BeCAS, a web application, service and widget. We also tackled relation mining by developing TrigNER, a machine-learning-based solution for biomedical event trigger recognition, which applies an automatic algorithm to obtain the best linguistic features and model parameters for each event type. Finally, in order to assist biocurators, Egas was developed to support rapid, interactive and real-time collaborative curation of biomedical documents, through manual and automatic in-line annotation of concepts and relations. Overall, the research work presented in this thesis contributed to a more accurate update of current biomedical knowledge bases, towards improved hypothesis generation and knowledge discovery.