Simulação computacional do Sistema Imunológico através de sistemas multiagentes: um estudo da resposta imune e da terapêutica antimicrobiana na glomerulonefrite pós-infecciosa (GNPE) por Streptococcus pyogenes

• Ano de defesa: 2013
• Autor(a) principal: Bastos, Carlos Antonio
• Orientador(a): Oliveira, Alcione de Paiva
• Banca de defesa: Gomes, Andréia Patrícia
• 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: Multiagentes; Sistema imunológico artificial; Glomerulonefrite
• Palavras-chave em Inglês: Multi-agent; Artificial immune system; Glomerulonephritis
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://locus.ufv.br/handle/123456789/2648

The Sophisticated homeostasis mechanisms of the immune system are designed to protect us against the millions of microorganisms with which Homo sapiens sapiens lives daily. The Immune System is considered an area of great complexity, deserving therefore a diverstiy of research approaches, among which the computer simulation. This approach is interesting both for medicine, which would have the possibility of meeting new possibilities for treatment of diseases, and for computer science, which, once gaining a better undestanding of Immune System processes, would have inspiration for the construction of algorithms to solve complex problems. The purpose of this work is to create a model of computational experiments to demonstrate the role of the immune response and antimicrobial therapy in post-infectious glomerulonephritis (APSGN) by Streptococcus pyogenes. For this, we attempt to identify the requirements for the extension of AutoSimmune model to simulate the phenomena involved in the installation of APSGN. We added functionality in AutoSimmune tool for simulation of the immune system, implementing the proposed model. We included among others, two environments - the kidneys and upper airways - besides neutrophils. We used the approach of multi- agent systems (MAS) based on autonomous agents, and the model was implemented using Repast Simphony framework, as well as the original tool. In our experiments, we could also simulate the administration of antimicrobials, showing the consequent reduction of the risk to APSGN occurrence. This also opened the possibility of future investigation for the role of antimicrobials in infectious processes.