Pulsioximetría de pacientes en hemodiálisis, de la unidad de terapia renal – fundación cardioinfantil, análisis para establecer recomendaciones

Introducción. En Colombia, el 80% de los pacientes con enfermedad renal crónica en hemodiálisis tienen fístula arteriovenosa periférica (FAV) que asegura el flujo de sangre durante la hemodiálisis (1), la variabilidad en el flujo de sangre en el brazo de la FAV hacia la parte distal, puede afectar la lectura de la oximetría de pulso (SpO2) (2), llevando a la toma de decisiones equivocadas por el personal de salud. El objetivo de este estudio es aclarar si existe diferencia entre la SpO2 del brazo de la FAV y el brazo contralateral. Materiales y métodos. Se realizó un estudio de correlación entre los valores de SpO2 del brazo con FAV contra el brazo sin FAV, de 40 pacientes que asistieron a hemodiálisis. La recolección de los datos se llevó a cabo, con un formato que incluyó el resultado de la pulsioximetria y variables asociadas, antes, durante y después de la hemodiálisis. Se comparó la mediana de los deltas de las diferencias con pruebas estadísticas T Student – Mann Whitney, aceptando un valor significativo de p < 0,05. Resultados. No se encontraron diferencias estadísticamente significativas de la SpO2 entre el brazo con FAV y el brazo sin FAV, antes, durante y después de la diálisis, sin embargo si se apreció una correlación positiva estadísticamente significativa. Conclusiones. Se encontró correlación positiva estadísticamente significativa, donde no hubo diferencias en el resultado la pulsioximetría entre el brazo con FAV y brazo sin FAV, por lo tanto es válido tomar la pulsioximetría en cualquiera de los brazos.

Cheaters in mutualism networks

Mutualism-network studies assume that all interacting species are mutualistic partners and consider that all links are of one kind. However, the influence of different types of links, such as cheating links, on network organization remains unexplored. We studied two flower-visitation networks (Malpighiaceae and Bignoniaceae and their flower visitors), and divide the types of link into cheaters (i.e. robbers and thieves of flower rewards) and effective pollinators. We investigated if there were topological differences among networks with and without cheaters, especially with respect to nestedness and modularity. The Malpighiaceae network was nested, but not modular, and it was dominated by pollinators and had much fewer cheater species than Bignoniaceae network (28% versus 75%). The Bignoniaceae network was mainly a plant-cheater network, being modular because of the presence of pollen robbers and showing no nestedness. In the Malpighiaceae network, removal of cheaters had no major consequences for topology. In contrast, removal of cheaters broke down the modularity of the Bignoniaceae network. As cheaters are ubiquitous in all mutualisms, the results presented here show that they have a strong impact upon network topology.

UUm Modelo Exploratório, Baseado nas Comunidades Linux, para Desenvolvimento da Tecnologia da Informação no Brasil

presente trabalho objetiva construir um Modelo Exploratório de desenvolvimento de tecnologia da informação, aplicável no Brasil, tendo como referência as formas de organização do trabalho e da produção das comunidades Linux. O Modelo deve ser aplicado em ambiente Internet, ou em outras redes de telecomunicação. Por essa razão, utiliza métodos e técnicas de aprendizado à distância e e-Iearning. A construção do Modelo apoia-se, como alicerce teórico fundamental, no conceito de convivialidade de Illich (1976), no entendimento de Inose e Pierce (1984) sobre comunidades de interesse e democratização da produção de software, nos estudos de Malone (1997, 1998) referentes a modelos de organização em rede, nos estudos de Weber (2000) sobre comunidades de interesse online, na metodologia de capacitação "Pensamento Digital" de Joia (1999-1, 1999-2) e na estratégia pedagógico-metodológica do Australian National Training Authority (T AFE/SA). No entanto, as pesquisas de Matesco (2000, 2001) tomaram exeqüível a idéia da construção do Modelo, tendo que vista que o Modelo Exploratório proposto aplica-se, preferencialmente, a países, regiões, empresas ou organizações dependentes tecnologicamente de seus parceiros negociais e com escassez de recursos para aplicar em pesquisa e desenvolvimento. O caminho metodológico para a construção do Modelo inicia-se com uma sucinta abordagem sobre o sistema operacional Linux, a descrição das formas de organização das comunidades Linux e a identificação das formas de organização do trabalho e da produção no Fordismo-Taylorismo e no pós-Fordismo. Situa o funcionamento das comunidades Linux em relação a essas formas de organização. Descreve o processo de formação do conhecimento no aprendizado à distância e no elearning. Aborda a experiência de outros países com o Linux e com as comunidades Linux. Principalmente, o sucesso obtido pelos países nórdicos em absorção de tecnologia. A seguir, fundamentando-se em duas pesquisas de Matesco (2000,2001), analisa a dependência tecnológica do Brasil e propõe o Modelo Exploratório, cujo objetivo é, prioritariamente, colaborar para a redução dessa dependência, por meio de um processo de formação de conhecimento, baseado no aprendizado à distância e e-Iearning do Linux e na propagação de comunidades Linux, empregando-se o modelo de organização em rede.

A influência do líder de projetos na transmissão da cultura em uma organização em rede

Esta dissertação tem como objetivo principal analisar a forma como os líderes de uma organização que alavanca suas atividades com uma estrutura em rede, transmitem a cultura da empresa central junto às empresas periféricas. Pretende-se investigar também se os líderes mudaram o seu papel em função da mudança da arquitetura organizacional no período considerado por alguns autores como pós-moderno. Como o tema cultura é amplo e complexo, optou-se por enfocar aspectos como a transmissão da missão e objetivos organizacionais, além do estilo de gestão predominante e sua influência no gerenciamento de projetos entre os protagonistas dessas diferentes organizações. Utilizou-se, para tanto, uma base teórico-empírica que buscou definir o conceito de cultura através do estudo do universo simbólico; a questão da liderança e sua relação com estruturas e fontes de poder e controle nas organizações; cultura e liderança no contexto brasileiro; e, por último, o conceito de organizações em rede, explorando também os aspectos de gestão, poder e controle esperado nesse tipo de arquitetura organizacional. Esta pesquisa constitui-se num estudo de caso realizado em uma instituição sem fins lucrativos, que desenvolve projetos sociais com foco em educação. Trata-se de um estudo exploratório, descritivo e explicativo. O método utilizado para a presente pesquisa foi o método qualitativo. Muitos estudos sobre cultura organizacional privilegiam o enfoque qualitativo de pesquisa, uma vez que um grande número de observações não é passível de quantificação. Utilizou-se a técnica de observação participante e de entrevistas semi-estruturadas, além da análise documental, o que possibilitou uma investigação que envolveu a combinação de descrição com interpretação do conteúdo trazido pelos respondentes em relação aos fenômenos observados. Os dados obtidos e a análise realizada frente à fundamentação teórica, indicam que o líder em uma organização em rede transmite a cultura organizacional com o mesmo discurso dominante das organizações com estruturas tradicionais. Acredita-se que este trabalho despertará interesse da comunidade acadêmica, uma vez que os aspectos culturais são normalmente pesquisados dentro da organização e aqui se ressalta a importância de se analisar o contexto no qual a organização está inserida e o papel que o líder assume na gestão das atividades realizadas por terceiros. Estaria o gestor brasileiro disposto a abrir mão do poder e controle que a posição hierárquica lhe confere para trabalhar em uma relação de igualdade com representantes de outras organizações?

Cheaters in mutualism networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Teorias da administração: entre o caos e a complexidade na era global

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Reconstructing past ecological networks: the reconfiguration of seed-dispersal interactions after megafaunal extinction

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

CLEANING ASSOCIATIONS BETWEEN BIRDS AND HERBIVOROUS MAMMALS IN BRAZIL: STRUCTURE AND COMPLEXITY

Birds that remove ectoparasites and other food material from their hosts are iconic illustrations of mutualistic-commensalistic cleaning associations. To assess the complex pattern of food resource use embedded in cleaning interactions of an assemblage of birds and their herbivorous mammal hosts in open habitats in Brazil, we used a network approach that characterized their patterns of association. Cleaning interactions showed a distinctly nested pattern, related to the number of interactions of cleaners and hosts and to the range of food types that each host species provided. Hosts that provided a wide range of food types (flies, ticks, tissue and blood, and organic debris) were attended by more species of cleaners and formed the core of the web. On the other hand, core cleaner species did not exploit the full range of available food resources, but used a variety of host species to exploit these resources instead. The structure that we found indicates that cleaners rely on cleaning interactions to obtain food types that would not be available otherwise (e.g., blood-engorged ticks or horseflies, wounded tissue). Additionally, a nested organization for the cleaner bird mammalian herbivore association means that both generalist and selective species take part in the interactions and that partners of selective species form an ordered subset of the partners of generalist species. The availability of predictable protein-rich food sources for birds provided by cleaning interactions may lead to an evolutionary pathway favoring their increased use by birds that forage opportunistically. Received 30 June 2011, accepted 10 November 2011.

Predicting the connectivity of primate cortical networks from topological and spatial node properties

Abstract Background The organization of the connectivity between mammalian cortical areas has become a major subject of study, because of its important role in scaffolding the macroscopic aspects of animal behavior and intelligence. In this study we present a computational reconstruction approach to the problem of network organization, by considering the topological and spatial features of each area in the primate cerebral cortex as subsidy for the reconstruction of the global cortical network connectivity. Starting with all areas being disconnected, pairs of areas with similar sets of features are linked together, in an attempt to recover the original network structure. Results Inferring primate cortical connectivity from the properties of the nodes, remarkably good reconstructions of the global network organization could be obtained, with the topological features allowing slightly superior accuracy to the spatial ones. Analogous reconstruction attempts for the C. elegans neuronal network resulted in substantially poorer recovery, indicating that cortical area interconnections are relatively stronger related to the considered topological and spatial properties than neuronal projections in the nematode. Conclusion The close relationship between area-based features and global connectivity may hint on developmental rules and constraints for cortical networks. Particularly, differences between the predictions from topological and spatial properties, together with the poorer recovery resulting from spatial properties, indicate that the organization of cortical networks is not entirely determined by spatial constraints.

Cognitive impairment and cortical reorganization in children with benign epilepsy with centrotemporal spikes

Benign epilepsy with centrotemporal spikes (BECTS) is associated with mild cognitive deficits, especially language impairment. This study aimed to clarify whether children with BECTS with left- or right-hemispheric, or bilateral focus have specific neuropsychological language deficits when compared to healthy controls, whether these deficits correlate functionally with language network organization (typical vs. atypical), and whether cofactors such as duration, handedness, and medication have a relevant impact on language reorganization processes.

Cell-demanded liberation of VEGF121 from fibrin implants induces local and controlled blood vessel growth

Although vascular endothelial growth factor (VEGF) has been described as a potent angiogenic stimulus, its application in therapy remains difficult: blood vessels formed by exposure to VEGF tend to be malformed and leaky. In nature, the principal form of VEGF possesses a binding site for ECM components that maintain it in the immobilized state until released by local cellular enzymatic activity. In this study, we present an engineered variant form of VEGF, alpha2PI1-8-VEGF121, that mimics this concept of matrix-binding and cell-mediated release by local cell-associated enzymatic activity, working in the surgically-relevant biological matrix fibrin. We show that matrix-conjugated alpha2PI1-8-VEGF121 is protected from clearance, contrary to native VEGF121 mixed into fibrin, which was completely released as a passive diffusive burst. Grafting studies on the embryonic chicken chorioallantoic membrane (CAM) and in adult mice were performed to assess and compare the quantity and quality of neovasculature induced in response to fibrin implants formulated with matrix-bound alpha2PI1-8-VEGF121 or native diffusible VEGF121. Our CAM measurements demonstrated that cell-demanded release of alpha2PI1-8-VEGF121 increases the formation of new arterial and venous branches, whereas exposure to passively released wild-type VEGF121 primarily induced chaotic changes within the capillary plexus. Specifically, our analyses at several levels, from endothelial cell morphology and endothelial interactions with periendothelial cells, to vessel branching and network organization, revealed that alpha2PI1-8-VEGF121 induces vessel formation more potently than native VEGF121 and that those vessels possess more normal morphologies at the light microscopic and ultrastructural level. Permeability studies in mice validated that vessels induced by alpha2PI1-8-VEGF121 do not leak. In conclusion, cell-demanded release of engineered VEGF121 from fibrin implants may present a therapeutically safe and practical modality to induce local angiogenesis.

Modelo de gestión integral : observatorio ambiental y ordenamiento del territorio

La provincia de Río Negro, Argentina, firma con la Unión Europea un acuerdo de cooperación para la realización del diseño e implementación de un Observatorio del ecosistema litoral y monitoreo de la biodiversidad con miras a establecer las bases para un desarrollo sustentable de la costa atlántica rionegrina. Este proyecto fue elaborado por el Instituto CIFOT y fue desagregado en las siguientes áreas de trabajo: Modelo de Información Espacial, Indicadores ambientales y página web. Los productos finales se obtienen mediante el análisis de variables dentro de un sistema integrado de SIG y Percepción remota, lo que permite evaluar el patrimonio humano natural y productivo, así como las tendencias del comportamiento de ecosistema costero y marino para poder construir un modelo de gestión integral del territorio. Los resultados de cada área de trabajo se integran en el primer Observatorio Ambiental en Argentina, a través de un prototipo de funcionamiento sustentado en un modelo de gestión que contempla la interacción entre el gobierno, entidades educativas y ONGs. El Observatorio permite la toma de decisiones a partir de datos reales en tiempo y forma, como también es la base para la elaboración del plan de ordenamiento de área costera de Río Negro y de un plan de manejo litoral atlántico.

Optimisation of algorithms to compute information theoretic indexes

Analysis of big amount of data is a field with many years of research. It is centred in getting significant values, to make it easier to understand and interpret data. Being the analysis of interdependence between time series an important field of research, mainly as a result of advances in the characterization of dynamical systems from the signals they produce. In the medicine sphere, it is easy to find many researches that try to understand the brain behaviour, its operation mode and its internal connections. The human brain comprises approximately 1011 neurons, each of which makes about 103 synaptic connections. This huge number of connections between individual processing elements provides the fundamental substrate for neuronal ensembles to become transiently synchronized or functionally connected. A similar complex network configuration and dynamics can also be found at the macroscopic scales of systems neuroscience and brain imaging. The emergence of dynamically coupled cell assemblies represents the neurophysiological substrate for cognitive function such as perception, learning, thinking. Understanding the complex network organization of the brain on the basis of neuroimaging data represents one of the most impervious challenges for systems neuroscience. Brain connectivity is an elusive concept that refers to diferent interrelated aspects of brain organization: structural, functional connectivity (FC) and efective connectivity (EC). Structural connectivity refers to a network of physical connections linking sets of neurons, it is the anatomical structur of brain networks. However, FC refers to the statistical dependence between the signals stemming from two distinct units within a nervous system, while EC refers to the causal interactions between them. This research opens the door to try to resolve diseases related with the brain, like Parkinson’s disease, senile dementia, mild cognitive impairment, etc. One of the most important project associated with Alzheimer’s research and other diseases are enclosed in the European project called Blue Brain. The center for Biomedical Technology (CTB) of Universidad Politecnica de Madrid (UPM) forms part of the project. The CTB researches have developed a magnetoencephalography (MEG) data processing tool that allow to visualise and analyse data in an intuitive way. This tool receives the name of HERMES, and it is presented in this document. Analysis of big amount of data is a field with many years of research. It is centred in getting significant values, to make it easier to understand and interpret data. Being the analysis of interdependence between time series an important field of research, mainly as a result of advances in the characterization of dynamical systems from the signals they produce. In the medicine sphere, it is easy to find many researches that try to understand the brain behaviour, its operation mode and its internal connections. The human brain comprises approximately 1011 neurons, each of which makes about 103 synaptic connections. This huge number of connections between individual processing elements provides the fundamental substrate for neuronal ensembles to become transiently synchronized or functionally connected. A similar complex network configuration and dynamics can also be found at the macroscopic scales of systems neuroscience and brain imaging. The emergence of dynamically coupled cell assemblies represents the neurophysiological substrate for cognitive function such as perception, learning, thinking. Understanding the complex network organization of the brain on the basis of neuroimaging data represents one of the most impervious challenges for systems neuroscience. Brain connectivity is an elusive concept that refers to diferent interrelated aspects of brain organization: structural, functional connectivity (FC) and efective connectivity (EC). Structural connectivity refers to a network of physical connections linking sets of neurons, it is the anatomical structur of brain networks. However, FC refers to the statistical dependence between the signals stemming from two distinct units within a nervous system, while EC refers to the causal interactions between them. This research opens the door to try to resolve diseases related with the brain, like Parkinson’s disease, senile dementia, mild cognitive impairment, etc. One of the most important project associated with Alzheimer’s research and other diseases are enclosed in the European project called Blue Brain. The center for Biomedical Technology (CTB) of Universidad Politecnica de Madrid (UPM) forms part of the project. The CTB researches have developed a magnetoencephalography (MEG) data processing tool that allow to visualise and analyse data in an intuitive way. This tool receives the name of HERMES, and it is presented in this document.

Functional and effective connectivity in MEG. Application to the study of epilepsy

Nuestro cerebro contiene cerca de 1014 sinapsis neuronales. Esta enorme cantidad de conexiones proporciona un entorno ideal donde distintos grupos de neuronas se sincronizan transitoriamente para provocar la aparición de funciones cognitivas, como la percepción, el aprendizaje o el pensamiento. Comprender la organización de esta compleja red cerebral en base a datos neurofisiológicos, representa uno de los desafíos más importantes y emocionantes en el campo de la neurociencia. Se han propuesto recientemente varias medidas para evaluar cómo se comunican las diferentes partes del cerebro a diversas escalas (células individuales, columnas corticales, o áreas cerebrales). Podemos clasificarlos, según su simetría, en dos grupos: por una parte, la medidas simétricas, como la correlación, la coherencia o la sincronización de fase, que evalúan la conectividad funcional (FC); mientras que las medidas asimétricas, como la causalidad de Granger o transferencia de entropía, son capaces de detectar la dirección de la interacción, lo que denominamos conectividad efectiva (EC). En la neurociencia moderna ha aumentado el interés por el estudio de las redes funcionales cerebrales, en gran medida debido a la aparición de estos nuevos algoritmos que permiten analizar la interdependencia entre señales temporales, además de la emergente teoría de redes complejas y la introducción de técnicas novedosas, como la magnetoencefalografía (MEG), para registrar datos neurofisiológicos con gran resolución. Sin embargo, nos hallamos ante un campo novedoso que presenta aun varias cuestiones metodológicas sin resolver, algunas de las cuales trataran de abordarse en esta tesis. En primer lugar, el creciente número de aproximaciones para determinar la existencia de FC/EC entre dos o más señales temporales, junto con la complejidad matemática de las herramientas de análisis, hacen deseable organizarlas todas en un paquete software intuitivo y fácil de usar. Aquí presento HERMES (http://hermes.ctb.upm.es), una toolbox en MatlabR, diseñada precisamente con este fin. Creo que esta herramienta será de gran ayuda para todos aquellos investigadores que trabajen en el campo emergente del análisis de conectividad cerebral y supondrá un gran valor para la comunidad científica. La segunda cuestión practica que se aborda es el estudio de la sensibilidad a las fuentes cerebrales profundas a través de dos tipos de sensores MEG: gradiómetros planares y magnetómetros, esta aproximación además se combina con un enfoque metodológico, utilizando dos índices de sincronización de fase: phase locking value (PLV) y phase lag index (PLI), este ultimo menos sensible a efecto la conducción volumen. Por lo tanto, se compara su comportamiento al estudiar las redes cerebrales, obteniendo que magnetómetros y PLV presentan, respectivamente, redes más densamente conectadas que gradiómetros planares y PLI, por los valores artificiales que crea el problema de la conducción de volumen. Sin embargo, cuando se trata de caracterizar redes epilépticas, el PLV ofrece mejores resultados, debido a la gran dispersión de las redes obtenidas con PLI. El análisis de redes complejas ha proporcionado nuevos conceptos que mejoran caracterización de la interacción de sistemas dinámicos. Se considera que una red está compuesta por nodos, que simbolizan sistemas, cuyas interacciones se representan por enlaces, y su comportamiento y topología puede caracterizarse por un elevado número de medidas. Existe evidencia teórica y empírica de que muchas de ellas están fuertemente correlacionadas entre sí. Por lo tanto, se ha conseguido seleccionar un pequeño grupo que caracteriza eficazmente estas redes, y condensa la información redundante. Para el análisis de redes funcionales, la selección de un umbral adecuado para decidir si un determinado valor de conectividad de la matriz de FC es significativo y debe ser incluido para un análisis posterior, se convierte en un paso crucial. En esta tesis, se han obtenido resultados más precisos al utilizar un test de subrogadas, basado en los datos, para evaluar individualmente cada uno de los enlaces, que al establecer a priori un umbral fijo para la densidad de conexiones. Finalmente, todas estas cuestiones se han aplicado al estudio de la epilepsia, caso práctico en el que se analizan las redes funcionales MEG, en estado de reposo, de dos grupos de pacientes epilépticos (generalizada idiopática y focal frontal) en comparación con sujetos control sanos. La epilepsia es uno de los trastornos neurológicos más comunes, con más de 55 millones de afectados en el mundo. Esta enfermedad se caracteriza por la predisposición a generar ataques epilépticos de actividad neuronal anormal y excesiva o bien síncrona, y por tanto, es el escenario perfecto para este tipo de análisis al tiempo que presenta un gran interés tanto desde el punto de vista clínico como de investigación. Los resultados manifiestan alteraciones especificas en la conectividad y un cambio en la topología de las redes en cerebros epilépticos, desplazando la importancia del ‘foco’ a la ‘red’, enfoque que va adquiriendo relevancia en las investigaciones recientes sobre epilepsia. ABSTRACT There are about 1014 neuronal synapses in the human brain. This huge number of connections provides the substrate for neuronal ensembles to become transiently synchronized, producing the emergence of cognitive functions such as perception, learning or thinking. Understanding the complex brain network organization on the basis of neuroimaging data represents one of the most important and exciting challenges for systems neuroscience. Several measures have been recently proposed to evaluate at various scales (single cells, cortical columns, or brain areas) how the different parts of the brain communicate. We can classify them, according to their symmetry, into two groups: symmetric measures, such as correlation, coherence or phase synchronization indexes, evaluate functional connectivity (FC); and on the other hand, the asymmetric ones, such as Granger causality or transfer entropy, are able to detect effective connectivity (EC) revealing the direction of the interaction. In modern neurosciences, the interest in functional brain networks has increased strongly with the onset of new algorithms to study interdependence between time series, the advent of modern complex network theory and the introduction of powerful techniques to record neurophysiological data, such as magnetoencephalography (MEG). However, when analyzing neurophysiological data with this approach several questions arise. In this thesis, I intend to tackle some of the practical open problems in the field. First of all, the increase in the number of time series analysis algorithms to study brain FC/EC, along with their mathematical complexity, creates the necessity of arranging them into a single, unified toolbox that allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them. I developed such a toolbox for this aim, it is named HERMES (http://hermes.ctb.upm.es), and encompasses several of the most common indexes for the assessment of FC and EC running for MatlabR environment. I believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis and will entail a great value for the scientific community. The second important practical issue tackled in this thesis is the evaluation of the sensitivity to deep brain sources of two different MEG sensors: planar gradiometers and magnetometers, in combination with the related methodological approach, using two phase synchronization indexes: phase locking value (PLV) y phase lag index (PLI), the latter one being less sensitive to volume conduction effect. Thus, I compared their performance when studying brain networks, obtaining that magnetometer sensors and PLV presented higher artificial values as compared with planar gradiometers and PLI respectively. However, when it came to characterize epileptic networks it was the PLV which gives better results, as PLI FC networks where very sparse. Complex network analysis has provided new concepts which improved characterization of interacting dynamical systems. With this background, networks could be considered composed of nodes, symbolizing systems, whose interactions with each other are represented by edges. A growing number of network measures is been applied in network analysis. However, there is theoretical and empirical evidence that many of these indexes are strongly correlated with each other. Therefore, in this thesis I reduced them to a small set, which could more efficiently characterize networks. Within this framework, selecting an appropriate threshold to decide whether a certain connectivity value of the FC matrix is significant and should be included in the network analysis becomes a crucial step, in this thesis, I used the surrogate data tests to make an individual data-driven evaluation of each of the edges significance and confirmed more accurate results than when just setting to a fixed value the density of connections. All these methodologies were applied to the study of epilepsy, analysing resting state MEG functional networks, in two groups of epileptic patients (generalized and focal epilepsy) that were compared to matching control subjects. Epilepsy is one of the most common neurological disorders, with more than 55 million people affected worldwide, characterized by its predisposition to generate epileptic seizures of abnormal excessive or synchronous neuronal activity, and thus, this scenario and analysis, present a great interest from both the clinical and the research perspective. Results revealed specific disruptions in connectivity and network topology and evidenced that networks’ topology is changed in epileptic brains, supporting the shift from ‘focus’ to ‘networks’ which is gaining importance in modern epilepsy research.

Phylogenetic analysis of within -host serially-sampled viral data

The primary goal of this dissertation is the study of patterns of viral evolution inferred from serially-sampled sequence data, i.e., sequence data obtained from strains isolated at consecutive time points from a single patient or host. RNA viral populations have an extremely high genetic variability, largely due to their astronomical population sizes within host systems, high replication rate, and short generation time. It is this aspect of their evolution that demands special attention and a different approach when studying the evolutionary relationships of serially-sampled sequence data. New methods that analyze serially-sampled data were developed shortly after a groundbreaking HIV-1 study of several patients from which viruses were isolated at recurring intervals over a period of 10 or more years. These methods assume a tree-like evolutionary model, while many RNA viruses have the capacity to exchange genetic material with one another using a process called recombination. ^ A genealogy involving recombination is best described by a network structure. A more general approach was implemented in a new computational tool, Sliding MinPD, one that is mindful of the sampling times of the input sequences and that reconstructs the viral evolutionary relationships in the form of a network structure with implicit representations of recombination events. The underlying network organization reveals unique patterns of viral evolution and could help explain the emergence of disease-associated mutants and drug-resistant strains, with implications for patient prognosis and treatment strategies. In order to comprehensively test the developed methods and to carry out comparison studies with other methods, synthetic data sets are critical. Therefore, appropriate sequence generators were also developed to simulate the evolution of serially-sampled recombinant viruses, new and more through evaluation criteria for recombination detection methods were established, and three major comparison studies were performed. The newly developed tools were also applied to "real" HIV-1 sequence data and it was shown that the results represented within an evolutionary network structure can be interpreted in biologically meaningful ways. ^