Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học quốc tế cung cấp cho các bạn kiến thức về ngành y đề tài: Using an agent-based model to analyze the dynamic communication network of the immune response. | Folcik et al. Theoretical Biology and Medical Modelling 2011 8 1 http content 8 1 1 THEORETICAL BIOLOGY AND MEDICAL MODELLING SOFTWARE Open Access Using an agent-based model to analyze the dynamic communication network of the immune response 13 2 113 13 13 Virginia A Folcik Gordon Broderick Shunmugam Mohan Brian Block Chirantan Ekbote John Doolittle Marc Khoury1 3 Luke Davis1 Clay B Marsh4 1 Correspondence department of Internal Medicine Division of Pulmonary Allergy Critical Care and Sleep Medicine The Ohio State University Medical Center Davis Heart and Lung Research Institute Columbus OH USA 2 BioMed Central Abstract Background The immune system behaves like a complex dynamic network with interacting elements including leukocytes cytokines and chemokines. While the immune system is broadly distributed leukocytes must communicate effectively to respond to a pathological challenge. The Basic Immune Simulator 2010 contains agents representing leukocytes and tissue cells signals representing cytokines chemokines and pathogens and virtual spaces representing organ tissue lymphoid tissue and blood. Agents interact dynamically in the compartments in response to infection of the virtual tissue. Agent behavior is imposed by logical rules derived from the scientific literature. The model captured the agent-to-agent contact history and from this the network topology and the interactions resulting in successful versus failed viral clearance were identified. This model served to integrate existing knowledge and allowed us to examine the immune response from a novel perspective directed at exploiting complex dynamics ultimately for the design of therapeutic interventions. Results Analyzing the evolution of agent-agent interactions at incremental time points from identical initial conditions revealed novel features of immune communication associated with successful and failed outcomes. There were fewer contacts between agents for simulations .
