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Journal article

Integrated Inflammatory Stress (ITIS) Model

From

Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark1

Department of Applied Mathematics and Computer Science, Technical University of Denmark2

North Carolina State University3

Copenhagen University Hospital Frederiksberg and Bispebjerg4

Roskilde University5

During the last decade, there has been an increasing interest in the coupling between the acute inflammatory response and the Hypothalamic–Pituitary–Adrenal (HPA) axis. The inflammatory response is activated acutely by pathogen- or damage-related molecular patterns, whereas the HPA axis maintains a long-term level of the stress hormone cortisol which is also anti-inflammatory.

A new integrated model of the interaction between these two subsystems of the inflammatory system is proposed and coined the integrated inflammatory stress (ITIS) model. The coupling mechanisms describing the interactions between the subsystems in the ITIS model are formulated based on biological reasoning and its ability to describe clinical data.

The ITIS model is calibrated and validated by simulating various scenarios related to endotoxin (LPS) exposure. The model is capable of reproducing human data of tumor necrosis factor alpha, adrenocorticotropic hormone (ACTH) and cortisol and suggests that repeated LPS injections lead to a deficient response.

The ITIS model predicts that the most extensive response to an LPS injection in ACTH and cortisol concentrations is observed in the early hours of the day. A constant activation results in elevated levels of the variables in the model while a prolonged change of the oscillations in ACTH and cortisol concentrations is the most pronounced result of different LPS doses predicted by the model.

Language: English
Publisher: Springer US
Year: 2017
Pages: 1487-1509
Journal subtitle: A Journal Devoted To Research at the Junction of Computational, Theoretical and Experimental Biology Official Journal of the Society for Mathematical Biology
ISSN: 15229602 and 00928240
Types: Journal article
DOI: 10.1007/s11538-017-0293-2
ORCIDs: Bangsgaard, Elisabeth O. and Hjorth, Poul G.

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