MORE INFORMATION on the BASIC IMMUNE SIMULATOR
The Basic Immune Simulator was created using the Recursive Porous Agent Simulation Toolkit (RePast) available online as open source software at repast.sourceforge.net. The program is written in Java, with Classes representing the agents (immune cell types). Borland JBuilder 2005 was used to write the JAVA code for the simulation.
The simulation was created using the agent-based modeling approach, also known as individual based modeling, bottom-up modeling or pattern-oriented modeling. The agents were created to represent the basic cell types of the immune system.
Abstraction is a necessary part of creating any model. In this model abstraction was used to simplify the representations of cytokines and chemokines. All cytokines/chemokines were divided into two groups: signals that upregulate the immune response (type 1) and signals that down regulate the immune response (type 2). For example, cytokine 1 (CK1) and cytokine 2 (CK2) represent all cytokines and chemokines produced by T-helper-1 and T-helper-2 lymphocytes.
The model has three zones of activity, each representing locations in the body where the immune response developes.
Zone 1 (picture) represents the parenchymal cells (yellow dots) or the functional cells of any tissue. Parenchymal cells are different for each tissue. In order for a tissue to maintain homeostasis its cells must be functioning. When the cells of a tissue become stressed, they release many different signals (depending on the stressor) and the cells of the innate immune system that are nearby sense the stress signals (red diffusing signal). Dendritic cells follow the signal to its source, and gather antigen in the vicinity of the stressed cells. They release chemokines to attract other cells of the innate immune system from the circulation, such as natural killer (NK) cells and macrophages. NK cells and macrophages immediately respond to the signal and follow it to the problem. These cellular events are represented by agents representing the respective cell types. 
Dendritic cells possessing the antigen fragments that they have collected migrate via the lymphatics into lymph nodes. The lymphatic tissue is represented by Zone 2 (picture). The lymphoid cells reside in lymph nodes, awaiting the influx of soluble antigen or the arrival of dendritic cells that present the antigen to the various types of lymphocytes. In animals with adaptive immune systems the lymphoid cells may travel around through the lymphatics, but since there is only a representation of one lymph node the cells within it move randomly, behavior that has been observed in vivo. When a dendritic cell encounters a lymphoid cell that has receptors that recognize the antigens it is presenting, proliferation of the lymphoid cells occurs. The lymphoid cells represented by agents in the model include, B lymphocytes and cytotoxic T lymphocytes. Contact between antigen-cognate B lymphocytes and Thelper lymphocytes is necessary for antibody production and this requirement is also present in the model.
After the lymphoid cells proliferate they migrate into the blood, represented by Zone 3 (picture) and from there they travel back into the infection site (Zone 1) where they carry out their functions associated with infected cell killing. 
The actual rules for behavior for all of the agents represented in the model have been depicted using state diagrams. The rules for the behavior of agents in any particular state are widely accepted conclusions from data published in immunology literature, and the majority of the information is textbook knowledge.
The state diagrams are included in a manuscript that has been submitted for publication. This information and the computer code for the model will be made public when the manuscript is published.
Simulation ”runs” or experiments begin with the entry of values for all of the starting parameters. All of the parameters have default values so it is not necessary to make choices about every initial parameter. Once started, the runs proceed in intervals called “ticks”. At each tick every agent present in all three environments (sequentially) gets a turn to sense what is in its immediate environment and react to what it perceives. The behavior of the agents is programmed into rules, and the behavior that the agent executes in response to what it perceives may change the environment. The ticks control progression of the immune response but do not correspond to uniform quantities of time. However, the proper order of immunological events is preserved. This allows experiments to be done in microseconds. Using the simulator fifty experiments can be done in one day versus the weeks it would take in a laboratory
In each Zone, the agents are contained in a 2-dimensional grid that operates as a torus. Each agent has the ability to probes the eight locations around it, its “Moore Neighborhood”. Because dendritic cells are highly developed to probe and survey their environment, the agents representing them have a Moore Neighborhood with a radius of 2, so they can probe 24 surrounding locations. Each location in the grid may contain more than one agent or none at all. Another one of the behaviors of the agents is signal production, and the signals diffuse through the environment, eventually dissipating. This is consistent with cytokines that may be washed away by interstitial fluids, degraded or taken up via receptors on cells. The quantities of all of the agent types in each of the zones including the numbers of agents in particular states and the quantities of all of the signals present are plotted as the simulation progresses so the user may observe the outcome of the simulation as it occurs. The simulator stops after a number (an input parameter) of ticks have been executed.
