arXiv subjects

Christopher F. Rowlatt

Publications and source records attributed to Christopher F. Rowlatt.

2 recordsLinked to original sources

arXiv2026

A model of tuberculosis progression using CompuCell3D

Tuberculosis (TB) is an airborne disease caused by the bacterium Mycobacterium tuberculosis (M. tb). Prior to the COVID-19 pandemic, TB was the leading cause of death from an infectious agent globally. However, most people exposed to M. tb do not develop active TB and go on to display symptoms. Instead, in the majority of cases, the bacteria are contained within a granuloma (an aggregation of immune cells) without being eliminated; this is called latent TB. The spatial organisation of the bacteria and immune cells is important in determining whether an individual exposed to M. tb will develop latent or active TB. In this paper, we present a multi-cell, multiscale model of TB progression to investigate the importance of the spatial organisation. This is a novel TB within-host dynamics modelling framework, having been developed using CompuCell3D (CC3D), an open-source computer software used for simulating cellular biological processes both within and between cells. We used this model to compare the generated results with those from a previously developed within-host infectious disease model. We found that, although the results of our CC3D model mostly agree qualitatively with those from the previously developed model, there are quantitative differences. Additionally, we conducted a robustness analysis of key model parameters from the CC3D model to determine their importance to the CC3D model output, using a methodology specifically designed for agent-based models. The model output appears to be robust in response to perturbations in parameters controlling chemotactic movement, but less so in response to perturbations in parameters controlling persistence of movement in cells, cell adhesion and volume constraints. This work compares our CC3D model of TB progression with another agent-based modelling approach to the same problem.

q-bio.QM↗

arXiv2019

A Conservative Finite Element ALE Scheme for Mass-Conserving Reaction-Diffusion Equations on Evolving Two-Dimensional Domains

Mass-conservative reaction-diffusion systems have recently been proposed as a general framework to describe intracellular pattern formation. These systems have been used to model the conformational switching of proteins as they cycle from an inactive state in the cell cytoplasm, to an active state at the cell membrane. The active state then acts as input to downstream effectors. The paradigm of activation by recruitment to the membrane underpins a range of biological pathways - including G-protein signalling, growth control through Ras and PI 3-kinase, and cell polarity through Rac and Rho; all activate their targets by recruiting them from the cytoplasm to the membrane. Global mass conservation lies at the heart of these models reflecting the property that the total number of active and inactive forms, and targets, remains constant. Here we present a conservative arbitrary Lagrangian Eulerian (ALE) finite element method for the approximate solution of systems of bulk-surface reaction-diffusion equations on an evolving two-dimensional domain. Fundamental to the success of the method is the robust generation of bulk and surface meshes. For this purpose, we use a moving mesh partial differential equation (MMPDE) approach. Global conservation of the fully discrete finite element solution is established independently of the ALE velocity field and the time step size. The developed method is applied to model problems with known analytical solutions; these experiments indicate that the method is second-order accurate and globally conservative. The method is further applied to a model of a single cell migrating in the presence of an external chemotactic signal.

math.NA↗