Modeling and Hemofiltration Treatment of Acute Inflammation

Abstract

Abstract:The body responds to endotoxins by triggering the acute inflammatory response system to eliminate the threat posed by gram-negative bacteria (endotoxin) and restore health. However, an uncontrolled inflammatory response can lead to tissue damage, organ failure, and ultimately death; this is clinically known as sepsis. Mathematical models of acute inflammatory disease have the potential to guide treatment decisions in critically ill patients. In this work, an 8-state (8-D) differential equation model of the acute inflammatory response system to endotoxin challenge was developed. Endotoxin challenges at 3 and 12 mg/kg were administered to rats, and dynamic cytokine data for interleukin (IL)-6, tumor necrosis factor (TNF), and IL-10 were obtained and used to calibrate the model. Evaluation of competing model structures was performed by analyzing model predictions at 3, 6, and 12 mg/kg endotoxin challenges with respect to experimental data from rats. Subsequently, a model predictive control (MPC) algorithm was synthesized to control a hemoadsorption (HA) device, a blood purification treatment for acute inflammation. A particle filter (PF) algorithm was implemented to estimate the full state vector of the endotoxemic rat based on time series cytokine measurements. Treatment simulations show that: (i) the apparent primary mechanism of HA efficacy is white blood cell (WBC) capture, with cytokine capture a secondary benefit; and (ii) differential

Mathematical modeling of energy consumption in the acute inflammatory response

“…To the best of our knowledge, this is the first model that incorporates these features. This model builds on several previous models representing various aspects of the acute inflammatory response Reynolds et al (2006), Kumar et al (2004), Chow et al (2005), Day et al (2006), Daun et al (2008), R. S. Parker et al (2016).…”

“…A somewhat more detailed model for the acute inflammatory response was shown to fit data from mice exposed to various inflammation-inducing insults and was used to predict mortality outcomes following endotoxin injection Chow et al (2005), while another work used parameter optimization based on fits to data to demonstrate both that different balances of inflammatory processes could yield similar cytokine dynamics yet with different mortality expectancies, Daun et al (2008). Such models have also been used to study control strategies for inflammation, Day et al (2010), as well as to explore the impact of blood filtration on inflammation, R. S. Parker et al (2016).…”

Mechanistic inferences on metabolic dysfunction in posttraumatic stress disorder from an integrated model and multiomic analysis: role of glucocorticoid receptor sensitivity

“…To analyze the defects in metabolism and its regulation, we integrated the metabolic simulator with the models for HPA axis, inflammation, and hypoxia and simulated metabolic trends. We adapted four submodels published in literature, namely hepatic metabolism and its hormonal regulation (71), HPA axis and inflammation model (2, 60), glucocorticoid receptor model (65), and hypoxia signaling (56). These models were integrated by linking the regulatory nodes according to the interactions reported in the literature (Supplemental Table S3).…”

Characterization of differences in immune responses during bolus and continuous infusion endotoxin challenges using mathematical modelling

“…Several models built upon this foundation by adding specific immune cells and cytokines activated during the inflammatory response (Brady et al, 2018;Chow et al, 2005;Foteinou et al, 2009;Parker et al, 2016;Roy et al, 2007;Su et al, 2009;M. Torres et al, 2019).…”