title: Modeling physiologic variability in human endotoxemia.
abstract: The control and management of inflammation is a key aspect of clinical care for critical illnesses such as sepsis. In an ideal reaction to injury, the inflammatory response provokes a strong enough response to heal the injury and then restores homeostasis. When inflammation becomes dysregulated, a persistent inflammatory state can lead to significant deleterious effects and clinical challenges. Thus, gaining a better biological understanding of the mechanisms driving the inflammatory response is of the utmost importance. In this review, we discuss our work with the late Stephen F. Lowry to investigate systemic inflammation through systems biology of human endotoxemia. We present our efforts in modeling the human endotoxemia response with a particular focus on physiologic variability. Through modeling, with a focus ultimately on translational applications, we obtain more fundamental understanding of relevant physiological processes. And by taking advantage of the information embedded in biological rhythms, ranging in time scale from high-frequency autonomic oscillations reflected in heart rate variability to circadian rhythms in inflammatory mediators, we gain insight into the underlying physiology.
authors.affiliation: Department of Biomedical Engineering, Rutgers University, Piscataway, NJ 08854, USA.
authors.forename: Jeremy D
authors.initials: JD
authors.lastname: Scheff
authors.forename: Panteleimon D
authors.initials: PD
authors.lastname: Mavroudis
authors.forename: Panagiota T
authors.initials: PT
authors.lastname: Foteinou
authors.forename: Steve E
authors.initials: SE
authors.lastname: Calvano
authors.forename: Ioannis P
authors.initials: IP
authors.lastname: Androulakis
mesh_terms: D003198:Computer Simulation; D016207:Cytokines / Q000276:immunology*; D019446:Endotoxemia / Q000276:immunology*; D006801:Humans; D018448:Models, Immunological; D015233:Models, Statistical
chemical_list: D016207:Cytokines