Agent-Based Model: A Surging Tool to Simulate Infectious Diseases in the Immune System

Agent-based models (ABMs) are capable of constructing individual system components at different levels of representation to describe non-linear relationships between those components. Compared to a traditional mathematical modeling approach, agent-based models have an inherent spatial component with which they can easily describe local interactions and environmental heterogeneity. Furthermore, agent-based model maps interactions among agents inherently to the biological phenomenon by embedding the stochastic nature and dynamics transitions, thereby demonstrating suitability for the development of complex biological processes. Recently, an abundance of literature has presented application of agent-based modeling in the biological system. This review focuses on application of agent-based modeling to progression in simulation of infectious disease in the human immune system and discusses advantages and disadvantages of agent-based modeling application. Finally, potential implementation of agent-based modeling in relation to infectious disease modeling in future research is explored.

Mathematical Model for Two-Spotted Spider Mites System: Verification and Validation

This paper presents and compares four mathematical models with unique spatial effects for a prey-predator system, with Tetranychus urticae as prey and Phytoseiulus persimilis as predator. Tetranychus urticae, also known as two-spotted spider mite, is a harmful plant-feeding pest that causes damage to over 300 species of plants. Its predator, Phytoseiulus persimilis, a mite in the Family Phytoseiidae, effectively controls spider mite populations. In this study, we compared four mathematical models using a numerical simulation. These models include two known models: self-diffusion, and cross-diffusion, and two new models: chemotaxis effect model, and integro diffusion model, all with a Beddington-De Angelis functional response. The modeling results were validated by fitting experimental data. Results demonstrate that interaction scheme plays an important role in the prey-predator system and that the cross-diffusion model fits the real system best. The main contribution of this paper is in the two new models developed, as well as the validation of all the models using experimental data.

A potato late blight resistance gene protects against multiple Phytophthora species by recognizing a broadly conserved RXLR-WY effector

Species of the genus Phytophthora,the plant killer,cause disease and reduce yields in many crop plants.Although many Resistance to Phytophthora infestans(Rpi)genes effective against potato late blight have been cloned,few have been cloned against other Phytophthora species.Most Rpi genes encode nucleotide-binding domain,leucine-rich repeat-containing(NLR)immune receptor proteins that recognize RXLR(Arg-X-Leu-Arg)effectors.However,whether NLR proteins can recognize RXLR effectors from multiple Phytophthora species has rarely been investigated.Here,we identified a new RXLR-WY effector AVRamr3 from P.infestans that is recognized by Rpi-amr3 from a wild Solanaceae species Solanum americanum.Rpi-amr3 associates with AVRamr3 in planta.AVRamr3 is broadly conserved in many different Phytophthora species,and the recognition of AVRamr3 homologs by Rpi-amr3 activates resistance against multiple Phytophthora pathogens,including the tobacco black shank disease and cacao black pod disease pathogens P.parasitica and P.palmivora.Rpi-amr3 is thus the first characterized resistance gene that acts against P.parasitica or P.palmivora.These findings suggest a novel path to redeploy known R genes against different important plant pathogens.