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Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

Dong X, Foteinou PT, Calvano SE, Lowry SF, Androulakis IP - PLoS ONE (2010)

Bottom Line: Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades.The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components.The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Rutgers University, Piscataway, New Jersey, United States of America.

ABSTRACT

Background: Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions.

Methodology/principal findings: An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades.

Conclusions/significance: The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

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A self-limited inflammatory response (LPS(0) = 350 units).Temporal profiles of essential components that constitute the agent based model resolved within 24 hr.
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pone-0009249-g003: A self-limited inflammatory response (LPS(0) = 350 units).Temporal profiles of essential components that constitute the agent based model resolved within 24 hr.

Mentions: A self-limited inflammatory response to the endotoxin stimulus corresponds to resolved dynamic profiles for all the elements constituting the model. The objective was to produce the dynamic profiles of a successful inflammatory resolution as shown in Figure 3 that qualitatively agreed with the previously models using a deterministic approach [33], [34]. While the inflammatory stimulus, namely LPS agents were successfully cleared within 1 h, the activation of anti-inflammatory cytokines expedited the attenuation of the early pro-inflammatory cytokine TNF-a with subsequent termination of the pro-inflammatory signaling cascade. The correctness of the model was evaluated based on its ability to qualitatively predict the uncontrolled responses as below.


Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

Dong X, Foteinou PT, Calvano SE, Lowry SF, Androulakis IP - PLoS ONE (2010)

A self-limited inflammatory response (LPS(0) = 350 units).Temporal profiles of essential components that constitute the agent based model resolved within 24 hr.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2823776&req=5

pone-0009249-g003: A self-limited inflammatory response (LPS(0) = 350 units).Temporal profiles of essential components that constitute the agent based model resolved within 24 hr.
Mentions: A self-limited inflammatory response to the endotoxin stimulus corresponds to resolved dynamic profiles for all the elements constituting the model. The objective was to produce the dynamic profiles of a successful inflammatory resolution as shown in Figure 3 that qualitatively agreed with the previously models using a deterministic approach [33], [34]. While the inflammatory stimulus, namely LPS agents were successfully cleared within 1 h, the activation of anti-inflammatory cytokines expedited the attenuation of the early pro-inflammatory cytokine TNF-a with subsequent termination of the pro-inflammatory signaling cascade. The correctness of the model was evaluated based on its ability to qualitatively predict the uncontrolled responses as below.

Bottom Line: Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades.The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components.The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Rutgers University, Piscataway, New Jersey, United States of America.

ABSTRACT

Background: Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions.

Methodology/principal findings: An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades.

Conclusions/significance: The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

Show MeSH
Related in: MedlinePlus