Simulação baseada em sistemas multiagentes da infecção de macrófagos pelo Trypanosoma cruzi na fase aguda da doença de chagas: a influência do inóculo inicial e do fator de escape

• Ano de defesa: 2014
• Autor(a) principal: Farago, Willian Cordeiro
• Orientador(a): Oliveira, Alcione de Paiva
• Banca de defesa: Fietto, Juliana Lopes Rangel , Lélis, Levi Henrique Santana de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Viçosa
• Programa de Pós-Graduação: Mestrado em Ciência da Computação
• Departamento: Metodologias e técnicas da Computação; Sistemas de Computação
• País: BR
• Palavras-chave em Português: Bioinformática; Sistema imunológico - Simulação (Computadores); Chagas, Doenças de; Trypanosoma cruzi; Imunologia
• Palavras-chave em Inglês: Bioinformatics; Immune system - Simulation (Computers); Chagas Disease; Trypanosoma cruzi; Immunology
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://locus.ufv.br/handle/123456789/2683

This work presents a simulation of the immunological system by means of amulti-agent systems approach. More specifically, it is proposed a simulation study aiming at the acute phase of Chagas disease in relation to the interaction of macrophages and the etiological agent Trypanosoma cruzi. Chagas disease is widespread distribution in South and Central America. Some epidemiological studies estimate a prevalence in these areas of 16 million to 18 million people infected with this disease and 100 million at risk of being infected. Recently, due to globalization, this disease that previously was endemic only in countries of Central and South America is presenting cases in other regions such as North America and Europe. Trypanosoma cruzi is able to make changes in the vertebrate host tissues with significant morbidity according to the infection degree. After modeling using state machines and the implementation in AutoSimmune simulator, simulations were performed varying the inoculum, the amount of parasites, and the escape factor, one of the elements that determine the pathogen virulence. According to the relationship between the computational and the actual time, primary for analysis and interpretation of the results, 546 years of interactions were simulated. The large amount of generated data was essential both to statistically demonstrate the stochastic property of the simulation tool and to strengthen the importance and quantitative advantages of computer simulation techniques, when compared to traditional research methods in vitro and in vivo.