TH17 functional study in severe asthma using agent based model

Agent-based models of inflammation in translational systems biology: A decade later

Agent-based modeling is a rule-based, discrete-event, and spatially explicit computational modeling method that employs computational objects that instantiate the rules and interactions among the individual components ("agents") of system. Agent-based modeling is well suited to translating into a computational model the knowledge generated from basic science research, particularly with respect to translating across scales the mechanisms of cellular behavior into aggregated cell population dynamics manifesting at the tissue and organ level. This capacity has made agent-based modeling an integral method in translational systems biology (TSB), an approach that uses multiscale dynamic computational modeling to explicitly represent disease processes in a clinically relevant fashion. The initial work in the early 2000s using agent-based models (ABMs) in TSB focused on examining acute inflammation and its intersection with wound healing; the decade since has seen vast growth in both the application of agent-based modeling to a wide array of disease processes as well as methodological advancements in the use and analysis of ABM. This report presents an update on an earlier review of ABMs in TSB and presents examples of exciting progress in the modeling of various organs and diseases that involve inflammation. This review also describes developments that integrate the use of ABMs with cutting-edge technologies such as high-performance computing, machine learning, and artificial intelligence, with a view toward the future integration of these methodologies. This article is categorized under: Translational, Genomic, and Systems Medicine > Translational Medicine Models of Systems Properties and Processes > Mechanistic Models Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Models of Systems Properties and Processes > Organismal Models.

A Mathematical Model for the Macrophage Response to Respiratory Viral Infection in Normal and Asthmatic Conditions

Respiratory viral infections are common in the general population and one of the most important causes of asthma aggravation and exacerbation. Despite many studies, it is not well understood how viral infections cause more severe symptoms and exacerbations in asthmatics. We develop a mathematical model of two types of macrophages that play complementary roles in fighting viral infection: classically [Formula: see text]-[Formula: see text] and alternatively activated macrophages [Formula: see text]-[Formula: see text]. [Formula: see text]-[Formula: see text] destroy infected cells and tissues to remove viruses, while [Formula: see text]-[Formula: see text] repair damaged tissues. We show that a higher viral load or longer duration of infection provokes a stronger immune response from the macrophage system. By adjusting the parameters, we model the differences in response to respiratory viral infection in normal and asthmatic subjects and show how this skews the system toward a response that generates more severe symptoms in asthmatic patients.

Effect of follicular helper T cells on the pathogenesis of asthma

Follicular helper T (TFH) cells are considered to be a separate T helper cell subset, specifically to help memory B cell participate in humoral immunity. It has been reported that there is an association between the imbalance of TFH function and certain autoimmune diseases. However, to the best of our knowledge, the effect of TFH cells on the process of bronchial asthma has not been investigated. The aim of the present study was to investigate the associated markers of TFH cells in bronchial asthma-induced mice. In the current study, sensitized and long-term challenges induced a mouse asthmatic model and were used to investigate the associated markers of TFH cells in the pathogenesis of asthma. The results demonstrated that B cell lymphoma 6, inducible T-cell costimulator (ICOS), ICOS ligand, C-X-C chemokine receptor type 5 (CXCR5) and interleukin (IL)-21 protein and mRNA expression levels were higher in the asthma group, as compared with the control group. Furthermore, the ratio of cluster of differentiation (CD) 4⁺CXCR5⁺/CD4⁺ and CD4⁺CXCR5⁺ICOS⁺/CD4⁺CXCR5⁺ was significantly increased in the asthma group. The results of the current study suggest that TFH cells and associated markers may have a role in the pathogenesis of chronic bronchial asthma.