The impact of fluid mechanics in liver cell therapies
ORAL
Abstract
Cell therapy for liver disease aims to inject donor cells into the vasculature to engraft and regenerate regions of diseased liver. Fluid mechanical stresses are sensed by cells as they transit to the injury site and can lead to upregulation of integrin expression. Integrins are receptors that bind to extracellular matrix, which in turn promotes engraftment of the donor cells into the injured tissue.We combine in silico and in vitro approaches to understand the relationship between fluid flow conditions and the integrin expression.
To mimic the liver circulation, our in vitro system drives flow through a closed tube using a peristaltic pump. We use lubrication theory to model the system, exploiting the small aspect ratio of the tube. The transport of donor cells is modelled via an advection-diffusion equation. We perform parameter sensitivity analysis to determine how the fluid mechanical stresses experienced by the donor cells depend on system parameters, like peristaltic pump settings and system geometry. We relate the predicted cell experienced stress to the experimentally determined integrin expression. We then exploit the theoretical model to determine the mechanical stress experienced by donor cells in in vivo scenarios, predicting levels of integrin expression in vivo.
To mimic the liver circulation, our in vitro system drives flow through a closed tube using a peristaltic pump. We use lubrication theory to model the system, exploiting the small aspect ratio of the tube. The transport of donor cells is modelled via an advection-diffusion equation. We perform parameter sensitivity analysis to determine how the fluid mechanical stresses experienced by the donor cells depend on system parameters, like peristaltic pump settings and system geometry. We relate the predicted cell experienced stress to the experimentally determined integrin expression. We then exploit the theoretical model to determine the mechanical stress experienced by donor cells in in vivo scenarios, predicting levels of integrin expression in vivo.
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Presenters
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Evangelia Antonopoulou
University of Oxford
Authors
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Evangelia Antonopoulou
University of Oxford
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Melissa R Vieira
University of Birmingham
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Alicia El Haj
University of Birmingham
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Sarah L Waters
University of Oxford, Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford