(664c) Multi-Scale Dynamics and Feedback in the Pathogen-Induced Host Inflammatory Response

Inflammation is the host response to the presence of pathogens (e.g., bacteria) or acute biological stress, such as endotoxin. In the critical care setting, inflammation is ubiquitous, as it is also a natural process in response to surgical disruption. A healthy response results in the activation of pro- and anti-inflammatory cytokines (e.g., IL6, IL10, TNF, IL1) in a dynamic sequence that provides for suitable inflammation (i.e., enough to kill off the invading pathogen or support the recovery process), followed by a return to baseline. Uncontrolled inflammation leads to tissue damage, (multiple) organ failure, and ultimately death, as a function of both cellular and systemic events. We have previously constructed low-order phenomenological models of the inflammatory response to endotoxin in rats, as a way to study the response to acute biological stress. However, several issues relating to physiological structure and cellular response motivate the need for more detailed and structured models of the inflammatory response cascade.

A key aspect in the local containment of pathogen is tissue macrophage, which eliminate pathogen in tissue. When pathogen burden is high compared to tissue macrophage population, because of high initial load or faster growth rate, there is a clear risk of loss of local containment; recruitment of circulating neutrophils and macrophage occurs as a result of local macrophage signaling molecules entering the blood circulation. Tissue macrophage releases IL1, which in turn activates the entothelial cells and enters the circulation. At low levels, this recruitment signal results in the arrival of neutrophils and macrophage at the local site. Neutrophils release IL1 receptor antagonist (IL1ra) when activated, which results in the downregulation of the recruitment and activation signals. This local feedback signal, one of many present in the cytokine system (e.g., TNF), serves to control the magnitude of the neutrophil and macrophage recruitment, and to some extent the level of local tissue damage. We have constructed a low-order model of IL1/IL1ra/cell response, including feedback, that captures the cell-level dynamics of pathogen-induced inflammation.

When the recruitment signal becomes elevated in the systemic circulation, there is also unanticipated activation of peripheral endothelial beds with consequent recruitment of inflammatory cells to peripheral tissues unaffected by infection, triggering systemic inflammation. For example, a common pathway to death in clinical patients is recruitment of neutrophils and macrophages to the lung, even if the lung is not the primary site of an infection. In order to capture this misregulation of cell recruitment, we coupled the cell-level model to a physiologically-based model. Here the vascular tissue spaces are modeled as CSTRs (first-order ODEs), with endothelial cells lining the extra-vascular space. Flows and tissue volumes are readily available from the literature (e.g., FDA, reference on toxicologic man, etc.). Cytokine clearance takes place from physiologically-accurate tissues (liver and kidney). The resulting model of cytokine, neutrophil, and macrophage trafficking captures the clinically-relevant states of return to health, pathogen-overload, and inflammation-induced death by remote organ failure.

Given that control of circulating cytokine levels can mitigate the systemic side-effects of a local pathogen challenge, a hemoadsorption device is applied as treatment. This device takes blood from the patient and passes it over adsorptive beads that can selectively remove cytokines (e.g., IL6, IL10, TNF, etc.). Using a previously-developed mathematical model of the filter device (DiLeo, et al., Ann. Biomed. Eng., 2009), the effects of treatment duration and initiation time after pathogen invasion can be analyzed. Finally, model-based control is used to regulate flowrate to match desired circulating cytokine levels and to improve subject survival after a pathogen challenge.