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Almansour, S, 2024. Mathematical modelling of macrophage phenotype selection and its role in inflammation. PhD, Nottingham Trent University.
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Abstract
Macrophages play a wide range of roles in resolving the inflammatory damage that underlies many medical conditions, and have the ability to adopt different phenotypes in response to different environmental stimuli. Categorising macrophage phenotypes exactly is a difficult task, and there is disparity in the literature around the optimal nomenclature to describe these phenotypes; however, what is clear is that macrophages can exhibit both pro- and anti-inflammatory behaviours dependent upon their phenotype, rendering mathematical models of the inflammatory response potentially sensitive to their description of the macrophage populations that they incorporate. Many previous models of inflammation include a single homogenised macrophage population with both pro- and anti-inflammatory functions. Here, we build upon these existing models to include explicit descriptions of distinct macrophage phenotypes and examine the extent to which this influences the inflammatory dynamics that the models emit.
This research aims to provide useful insights into the essential role of macrophage phenotypes in inflammation. We present a series of corresponding mathematical models of increasing biological complexity and examine the resulting dynamics via numerical simulation and bifurcation analysis. We begin by examining three ordinary differential equation (ODE)-based models that describe: a single homogenised macrophage population; two distinct macrophage populations with opposing pro/anti-inflammatory phenotypes; and a variant of the second model that also includes neutrophil-driven dynamics. We then build on these models to construct a partial differential equation(PDE) model that considers macrophage phenotypes to lie on a continuous spectrum of inflammatory activity.
We analyse our models via numerical simulation in Matlab and dynamical systems analysis in XPPAUT. We investigate the different qualitative behaviours presented by our models via Matlab and discuss them in terms of the inflammatory response and its potential outcomes. We also use bifurcation diagrams provided by XPPAUT to investigate how variation in the system’s key parameters influences the switch between chronic and healthy outcomes. We show that models that account for distinct macrophage phenotypes separately can offer more realistic steady state solutions than precursor models do (better capturing the anti-inflammatory activity of tissue-resident macrophages), and that variations in macrophage polarisation can underlie a switch between chronic steady state outcomes and oscillations reminiscent of inflammatory conditions with relapsing-remitting characteristics. Finally, we reflect on the conclusions of our analysis in the context of the ongoing hunt for potential new therapies for inflammatory conditions, highlighting manipulation of macrophage polarisation states as a potential therapeutic target.
| Item Type: | Thesis |
|---|---|
| Creators: | Almansour, S. |
| Contributors: | Name Role NTU ID ORCID |
| Date: | May 2024 |
| Rights: | This work is the intellectual property of the author. You may copy up to 5% of this work for private study, or personal, non-commercial research. Any re-use of the information contained within this document should be fully referenced, quoting the author, title, university, degree level and pagination. Queries or requests for any other use, or if a more substantial copy is required, should be directed in the owner(s) of the Intellectual Property Rights. |
| Divisions: | Schools > School of Science and Technology |
| Record created by: | Laura Ward |
| Date Added: | 17 Jun 2024 12:47 |
| Last Modified: | 17 Jun 2024 12:47 |
| URI: | https://irep.ntu.ac.uk/id/eprint/51573 |
https://orcid.org/0000-0001-5320-2464Actions (login required)
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