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Biology subjects

Germano, D. P. J.

Publications and source records attributed to Germano, D. P. J..

2 recordsLinked to original sources

Mathematical modelling of the immune response during endometriosis lesion onset

The immune system is hypothesised to contribute to the onset of endometriosis lesions. However, the precise mechanisms underlying its role are not yet known. We introduce a novel compartmental model that describes the interactions between innate immune cells, specifically macrophages and natural killer cells, and endometrial cells, occurring within the peritoneal fluid during the early stages of (superficial peritoneal) endometriosis lesion onset. Our study focuses on retrograde influx, immune detection, and immune clearance. Results show an increased influx of endometrial cells into peritoneal fluid correlates with heightened pro-inflammatory macrophage activation, but does not lead to an increase in disease. We compare the systems response to changes in immune cytotoxicity and ability to detect ectopic endometrial cells. We predict that reduced cytotoxicity is a key driver of disease. These findings align with the increased immune activation observed clinically. Lastly, we predict that an individual can transition to a diseased state following a reduction in immune system cytotoxicity and/or reduced ability to detect ectopic cells. Due to hysteresis, a significant improvement is then required to restore an individual to the disease-free state. This work provides a valuable framework to explore hypotheses of endometriosis lesion onset and assist in understanding of the disease.

systems biology↗

Free and interfacial boundaries in individual-based models of multicellular biological systems

Coordination of cell behaviour is key to a myriad of biological processes including tissue morphogenesis, wound healing, and tumour growth. As such, individual-based computational models, which explicitly describe inter-cellular interactions, are commonly used to model collective cell dynamics. However, when using individual-based models, it is unclear how descriptions of cell boundaries affect overall population dynamics. In order to investigate this we define three cell boundary descriptions of varying complexities for each of three widely used off-lattice individual-based models: overlapping spheres, Voronoi tessellation, and vertex models. We apply our models to multiple biological scenarios to investigate how cell boundary description can influence tissue-scale behaviour. We find that the Voronoi tessellation model is most sensitive to changes in the cell boundary description with basic models being inappropriate in many cases. The timescale of tissue evolution when using an overlapping spheres model is coupled to the boundary description. The vertex model is demonstrated to be the most stable to changes in boundary description, though still exhibits timescale sensitivity. When using individual-based computational models one should carefully consider how cell boundaries are defined. To inform future work, we provide an exploration of common individual-based models and cell boundary descriptions in frequently studied biological scenarios and discuss their benefits and disadvantages.

biophysics↗