System Dynamics Modelling of the Processes Involving the Maintenance of the Naive T Cell Repertoire

The study of immune system aging, i.e. immunosenescence, is a relatively new research topic. It deals with understanding the processes of immunodegradation that indicate signs of functionality loss possibly leading to death. Even though it is not possible to prevent immunosenescence, there is great benefit in comprehending its causes, which may help to reverse some of the damage done and thus improve life expectancy. One of the main factors influencing the process of immunosenescence is the number and phenotypical variety of naive T cells in an individual. This work presents a review of immunosenescence, proposes system dynamics modelling of the processes involving the maintenance of the naive T cell repertoire and presents some preliminary results.Comment: 6 pages, 2 figures, 1 table, 9th Annual Workshop on Computational Intelligence (UKCI 2009), Nottingham, U

Long Term and Short Term Effects of Perturbations in a Immune Network Model

In this paper we review the trajectory of a model proposed by Stauffer and Weisbuch in 1992 to describe the evolution of the immune repertoire and present new results about its dynamical behavior. Ten years later this model, which is based on the ideas of the immune network as proposed by Jerne, has been able to describe a multi-connected network and could be used to reproduce immunization and aging experiments performed with mice. Besides its biological implications, the physical aspects of the complex dynamics of this network is very interesting {\it per se}. The immunization protocol is simulated by introducing small and large perturbations (damages), and in this work we discuss the role of both. In a very recent paper we studied the aging effects by using auto-correlation functions, and the results obtained apparently indicated that the small perturbations would be more important than the large ones, since their cumulative effects may change the attractor of the dynamics. However our new results indicate that both types of perturbations are important. It is the cooperative effects between both that lead to the complex behavior which allows to reproduce experimental results.Comment: 15 pages, 5 figure

On the Aging Dynamics in an Immune Network Model

Recently we have used a cellular automata model which describes the dynamics of a multi-connected network to reproduce the refractory behavior and aging effects obtained in immunization experiments performed with mice when subjected to multiple perturbations. In this paper we investigate the similarities between the aging dynamics observed in this multi-connected network and the one observed in glassy systems, by using the usual tools applied to analyze the latter. An interesting feature we show here is that the model reproduces the biological aspects observed in the experiments during the long transient time it takes to reach the stationary state. Depending on the initial conditions, and without any perturbation, the system may reach one of a family of long-period attractors. The pertrubations may drive the system from its natural attractor to other attractors of the same family. We discuss the different roles played by the small random perturbations (noise) and by the large periodic perturbations (immunizations)

The Symmetrical Immune Network Theory and a New HIV Vaccine Concept

The symmetrical immune network theory is based on Jerne’s network hypothesis. An improved version of the theory is presented. The theory is characterized by symmetrical stimulatory, inhibitory and killing interactions between idiotypic and antiidiotypic immune system components. In this version killing is ascribed to IgM antibodies, while IgG antibodies are stimulatory. In the symmetrical immune network theory T cells make specific T cell factors, that have a single V region, and are cytophilic for non-specific accessory cells (A cells, including macrophages and monocytes) and play a role in the system switching between stable steady states. A recurring theme in the theory is the concept of co selection. Co-selection is the mutual positive selection of individual members from within two diverse populations, such that selection of members within each population is dependent on interaction with (recognition of) one or more members within the other population. Prior to exposure to an antigen, antigen-specific and antiidiotypic T cells are equally diverse. This equality is a form of symmetry. Immune responses with the production of IgG involve co selection of the antigen-specific and antiidiotypic classes with the breaking of this diversity symmetry, while induction of unresponsiveness involves co-selection without the breaking of diversity symmetry. The theory resolves the famous I-J paradox of the 1980s, based on co selection of helper T cells with some affinity for MHC class II and suppressor T cells that are anti-anti-MHC class II. The theory leads to three experimentally testable predictions concerning I-J. The theory includes a model for HIV pathogenesis, and suggests that polyclonal IgG from many donors given in immunogenic form may be an effective vaccine for protection against infection with HIV. Surprisingly, a mathematical model that simulates the autonomous dynamics of the system is the same as one that models a previously described neural network