A two-compartment mathematical model of endotoxin-induced inflammatory and physiologic alterations in swine*
- 1 April 2012
- journal article
- research article
- Published by Ovid Technologies (Wolters Kluwer Health) in Critical Care Medicine
- Vol. 40 (4), 1052-1063
- https://doi.org/10.1097/ccm.0b013e31823e986a
Abstract
Objective: To gain insights into individual variations in acute inflammation and physiology. Design: Large-animal study combined with mathematical modeling. Setting: Academic large-animal and computational laboratories. Subjects: Outbred juvenile swine. Interventions: Four swine were instrumented and subjected to endotoxemia (100 µg/kg), followed by serial plasma sampling. Measurements and Main Results: Swine exhibited various degrees of inflammation and acute lung injury, including one death with severe acute lung injury (PaO2/FIO2 ratio μ200 and static compliance μ10 L/cm H2O). Plasma interleukin-1β, interleukin-4, interleukin-6, interleukin-8, interleukin-10, tumor necrosis factor-α, high mobility group box-1, and NO2-/NO3- were significantly (p μ .05) elevated over the course of the experiment. Principal component analysis was used to suggest principal drivers of inflammation. Based in part on principal component analysis, an ordinary differential equation model was constructed, consisting of the lung and the blood (as a surrogate for the rest of the body), in which endotoxin induces tumor necrosis factor-α in monocytes in the blood, followed by the trafficking of these cells into the lung leading to the release of high mobility group box-1, which in turn stimulates the release of interleukin-1β from resident macrophages. The ordinary differential equation model also included blood pressure, PaO2, and FIO2, and a damage variable that summarizes the health of the animal. This ordinary differential equation model could be fit to both inflammatory and physiologic data in the individual swine. The predicted time course of damage could be matched to the oxygen index in three of the four swine. Conclusions: The approach described herein may aid in predicting inflammation and physiologic dysfunction in small cohorts of subjects with diverse phenotypes and outcomes.Keywords
This publication has 33 references indexed in Scilit:
- Sepsis: Something old, something new, and a systems viewJournal of Critical Care, 2012
- In silico augmentation of the drug development pipeline: examples from the study of acute inflammationDrug Development Research, 2010
- Peritoneal Negative Pressure Therapy Prevents Multiple Organ Injury in a Chronic Porcine Sepsis and Ischemia/Reperfusion ModelShock, 2010
- Mechanistic simulations of inflammation: Current state and future prospectsMathematical Biosciences, 2008
- Circulating high-mobility group box 1 (HMGB1) concentrations are elevated in both uncomplicated pneumonia and pneumonia with severe sepsis*Critical Care Medicine, 2007
- THE ROLE OF INITIAL TRAUMA IN THE HOST'S RESPONSE TO INJURY AND HEMORRHAGEShock, 2006
- Evaluating Disorders with a Complex Genetics Basis. The Future Roles of Meta-analysis and Systems BiologyDigestive Diseases and Sciences, 2005
- Oxygenation Index Predicts Outcome in Children with Acute Hypoxemic Respiratory FailureAmerican Journal of Respiratory and Critical Care Medicine, 2005
- Sepsis Research in the Next Millennium: Concentrate on the Software Rather than the HardwareShock, 2002
- Anti-inflammatory therapies in sepsis and septic shockExpert Opinion on Investigational Drugs, 2000