Orientador: Cláudia Valéria Seullner Brandão / Resumo: O objetivo deste estudo foi comparar e avaliar a aplicação de célula tronco mesenquimal de tecido adiposo (CTM-TA) e plasma rico em plaquetas aquecido alogênico (PRP-AA) perilacrimal em cães com ceratoconjuntivite seca (CCS), bem como, se há diferença na resposta segundo o grau de gravidade da afecção. Foram analisados 20 cães com produção lacrimal <15mm/min e distribuídos aleatoriamente em dois grupos (n=10). O grupo 1 tratado com CTM-TA (5x106 e 3x106 células) (GCTM-TA) e com grupo 2 PRP-AA (0,7mL e 0,3mL) (GPRP-AA), ambos injetados perilacrimal nas glândulas lacrimal principal e da terceira pálpebra, respectivamente. Todos os olhos foram avaliados em quatro momentos (M0 M15, M30, M60 dias). As variáveis avaliadas foram: osmolaridade da lágrima; teste lacrimal de Schirmer (TLS); sensibilidade corneal; tempo de ruptura do filme lacrimal (TRFL); pressão intraocular; espessura corneal; e biopsia da conjuntiva bulbar, além das variáveis clínico-oftalmológicas. Houve melhora nos dois grupos a partir de M15 (p<0,05) na qualidade do filme lacrimal, avaliada por meio da osmolaridade e TRFL, sem diferença entre os grupos. A produção de lágrima aumentou, entretanto notou-se diferença significativa nos animais com CCS discreta no GPRP-AA a partir do M30, e nos cães com CCS grave no GCTM-TA a partir do M30 e no GPRP-AA a partir do M60. Verificou-se melhora dos sinais clínicos da inflamação em ambos os grupos. Aplicação única perilacrimal de CTM-TA e PRP aquecido alogênicos normaliza a ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The aim of the study was to compare and evaluate the application of allogenic mesenchymal stem cell adipose tissue derived (MSCs-AD) and inativate platelet-rich plasma allogenic (PRP-IA), perilacrimal in dogs with keratoconjunctivitis sicca (KCS), and if there is difference in the response according to the degree of severity of the condition. Twenty dogs with lacrimal production <15mm/min randomly assigned to two groups were used. Group treated with MSCs-AD (5x106 and 3x106) (GMSCs-AD) and with PRP-IA (0.7ml and 0.3ml) (GPRP-IA), both intralacrimal in the main lacrimal glands and third eyelid, respectively. The eyes were evaluated in four moments after application (M0 M15, M30, M60). The variables evaluated were: tear osmolarity e; Schirmer's tear test (STT); sensitivity corneal; tear film break time (TBUT); intraocular pressure; corneal thickness; and biopsy of the bulbar conjunctiva, in addition to clinical-ophthalmologic variables. There was improvement in two groups at M15 (p <0.05) on tear film quality, assessed by osmolarity and TBUT, with there was no difference between groups. STT increased, however, statistical difference was only observed in animals with mild KCS in the GPRP-IA from the M30 and in the intense KCS at M30 in the G MSCs-AD and at M60 in the GPRP-IA. There was an improvement in the clinical signs of inflammation in both groups. The unique Intralacrimal application of MSCs-AD and PRP-IA normalizes tear film quality and improves clinical signs of inflamma... (Complete abstract click electronic access below) / Doutor

Molecular biology has entered an era of systematic and automated experimentation. High-throughput techniques have moved biology from small-scale experiments focused on specific genes and proteins to genome and proteome-wide screens. One result of this endeavor is the compilation of complex networks of interacting proteins. Molecular biologists hope to understand life's complex molecular machines by studying these networks. This thesis addresses tree open problems centered upon their analysis and quality assessment. First, we introduce power graph analysis as a novel approach to the representation and visualization of biological networks. Power graphs are a graph theoretic approach to lossless and compact representation of complex networks. It groups edges into cliques and bicliques, and nodes into a neighborhood hierarchy. We demonstrate power graph analysis on five examples, and show its advantages over traditional network representations. Moreover, we evaluate the algorithm performance on a benchmark, test the robustness of the algorithm to noise, and measure its empirical time complexity at O (e1.71)- sub-quadratic in the number of edges e. Second, we tackle the difficult and controversial problem of data quality in protein interaction networks. We propose a novel measure for accuracy and completeness of genome-wide protein interaction networks based on network compressibility. We validate this new measure by i) verifying the detrimental effect of false positives and false negatives, ii) showing that gold standard networks are highly compressible, iii) showing that authors' choice of confidence thresholds is consistent with high network compressibility, iv) presenting evidence that compressibility is correlated with co-expression, co-localization and shared function, v) showing that complete and accurate networks of complex systems in other domains exhibit similar levels of compressibility than current high quality interactomes. Third, we apply power graph analysis to networks derived from text-mining as well to gene expression microarray data. In particular, we present i) the network-based analysis of genome-wide expression profiles of the neuroectodermal conversion of mesenchymal stem cells. ii) the analysis of regulatory modules in a rare mitochondrial cytopathy: emph{Mitochondrial Encephalomyopathy, Lactic acidosis, and Stroke-like episodes} (MELAS), and iii) we investigate the biochemical causes behind the enhanced biocompatibility of tantalum compared with titanium.

Molecular biology has entered an era of systematic and automated experimentation. High-throughput techniques have moved biology from small-scale experiments focused on specific genes and proteins to genome and proteome-wide screens. One result of this endeavor is the compilation of complex networks of interacting proteins. Molecular biologists hope to understand life's complex molecular machines by studying these networks. This thesis addresses tree open problems centered upon their analysis and quality assessment. First, we introduce power graph analysis as a novel approach to the representation and visualization of biological networks. Power graphs are a graph theoretic approach to lossless and compact representation of complex networks. It groups edges into cliques and bicliques, and nodes into a neighborhood hierarchy. We demonstrate power graph analysis on five examples, and show its advantages over traditional network representations. Moreover, we evaluate the algorithm performance on a benchmark, test the robustness of the algorithm to noise, and measure its empirical time complexity at O (e1.71)- sub-quadratic in the number of edges e. Second, we tackle the difficult and controversial problem of data quality in protein interaction networks. We propose a novel measure for accuracy and completeness of genome-wide protein interaction networks based on network compressibility. We validate this new measure by i) verifying the detrimental effect of false positives and false negatives, ii) showing that gold standard networks are highly compressible, iii) showing that authors' choice of confidence thresholds is consistent with high network compressibility, iv) presenting evidence that compressibility is correlated with co-expression, co-localization and shared function, v) showing that complete and accurate networks of complex systems in other domains exhibit similar levels of compressibility than current high quality interactomes. Third, we apply power graph analysis to networks derived from text-mining as well to gene expression microarray data. In particular, we present i) the network-based analysis of genome-wide expression profiles of the neuroectodermal conversion of mesenchymal stem cells. ii) the analysis of regulatory modules in a rare mitochondrial cytopathy: emph{Mitochondrial Encephalomyopathy, Lactic acidosis, and Stroke-like episodes} (MELAS), and iii) we investigate the biochemical causes behind the enhanced biocompatibility of tantalum compared with titanium.