Loyola University Maryland

Department of Mathematics and Statistics


Modeling the Inflammatory Response: Wound Healing and Mechanical Ventilation

Dr. Angela Reynolds

Virginia Commenwealth University

April 12, 2013

Room: 309 Knott Hall


The acute inflammatory response, triggered by a variety of biological or physical stresses on an organism, is a delicate system of checks and balances that, although aimed at promoting healing and restoring homeostasis, can result in undesired and occasionally lethal physiological responses. In this talk, I will focus on the role of the inflammatory response in wound healing and mechanical ventilation.

In order to promote wound healing in diabetic patients, we developed an ordinary differential equations model, which tracks fibroblasts, collagen, inflammation and pathogens. The model was validated by comparison to the normal time course of wound healing where appropriate activity for the inflammatory, proliferative, and remodeling phases were recorded and compared to collagen accumulation experiments. The model was then used to investigate the impact of local oxygen levels on wound healing. This model is the first step to creating a patient-specific treatment model.

Additionally, we will look at a multi-scale model for mechanical ventilation focusing on the interplay between gas exchange and inflammatory response. This portion of the multi-scale project is a partial differential equations model of gas exchange with inflammatory stress on a small physiological unit of the lung, referred to as a respiratory unit (RU). Linking multiple RUs with various ventilation/perfusion ratios and taking into account pulmonary venous blood remixing yields our lung-scale model. Using the lung-scale model, we explored the predicted effects of inflammation on ventilation/perfusion distribution and the resulting pulmonary venous partial pressure oxygen level during systemic inflammatory stresses. This model translates changes in inflammation levels to changes in peripheral PO2, which can be measured in real time from patients.

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