Rukmini Kumar

THE ACUTE INFLAMMATORY RESPONSE IN DIVERSE SHOCK STATES

A poorly controlled acute inflammatory response can lead to organ dysfunction and death. Severe systemic inflammation can be induced and perpetuated by diverse insults such as the administration of toxic bacterial products (e.g., endotoxin), traumatic injury, and hemorrhage. Here, we probe whether these varied shock states can be explained by a universal inflammatory system that is initiated through different means and, once initiated, follows a course specified by the cellular and molecular mechanisms of the immune and endocrine systems. To examine this question, we developed a mathematical model incorporating major elements of the acute inflammatory response in C57Bl/6 mice, using input from experimental data. We found that a single model with different initiators including the autonomic system could describe the response to various insults. This model was able to predict a dose range of endotoxin at which mice would die despite having been calibrated only in nonlethal inflammatory paradigms. These results show that the complex biology of inflammation can be modeled and supports the hypothesis that shock states induced by a range of physiologic challenges could arise from a universal response that is differently initiated and modulated.

IN SILICO MODELS OF ACUTE INFLAMMATION IN ANIMALS

ABSTRACT Trauma and hemorrhagic shock elicit an acute inflammatory response, predisposing patients to sepsis, organ dysfunction, and death. Few approved therapies exist for these acute inflammatory states, mainly due to the complex interplay of interacting inflammatory and physiological elements working at multiple levels. Various animal models have been used to simulate these phenomena, but these models often do not replicate the clinical setting of multiple overlapping insults. Mathematical modeling of complex systems is an approach for understanding the interplay among biological interactions. We constructed a mathematical model using ordinary differential equations that encompass the dynamics of cells and cytokines of the acute inflammatory response, as well as global tissue dysfunction. The model was calibrated in C57Bl/6 mice subjected to (1) various doses of lipopolysaccharide (LPS) alone, (2) surgical trauma, and (3) surgery + hemorrhagic shock. We tested the models predictive ability in scenarios on which it had not been trained, namely, (1) surgery ± hemorrhagic shock + LPS given at times after the beginning of surgical instrumentation, and (2) surgery + hemorrhagic shock + bilateral femoral fracture. Software was created that facilitated fitting of the mathematical model to experimental data, as well as for simulation of experiments with various inflammatory challenges and associated variations (gene knockouts, inhibition of specific cytokines, etc.). Using this software, the C57Bl/6-specific model was recalibrated for inflammatory analyte data in CD14−/− mice and was used to elucidate altered features of inflammation in these animals. In other experiments, rats were subjected to surgical trauma ± LPS or to bacterial infection via fibrin clots impregnated with various inocula of Escherichia coli. Mathematical modeling may provide insights into the complex dynamics of acute inflammation in a manner that can be tested in vivo using many fewer animals than has been possible previously.