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Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling

Acute inflammation leads to organ failure by engaging catastrophic feedback loops in which stressed tissue evokes an inflammatory response and, in turn, inflammation damages tissue. Manifestations of this maladaptive inflammatory response include cardio-respiratory dysfunction that may be reflected...

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Autores principales: Dick, Thomas E., Molkov, Yaroslav I., Nieman, Gary, Hsieh, Yee-Hsee, Jacono, Frank J., Doyle, John, Scheff, Jeremy D., Calvano, Steve E., Androulakis, Ioannis P., An, Gary, Vodovotz, Yoram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3387781/
https://www.ncbi.nlm.nih.gov/pubmed/22783197
http://dx.doi.org/10.3389/fphys.2012.00222
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author Dick, Thomas E.
Molkov, Yaroslav I.
Nieman, Gary
Hsieh, Yee-Hsee
Jacono, Frank J.
Doyle, John
Scheff, Jeremy D.
Calvano, Steve E.
Androulakis, Ioannis P.
An, Gary
Vodovotz, Yoram
author_facet Dick, Thomas E.
Molkov, Yaroslav I.
Nieman, Gary
Hsieh, Yee-Hsee
Jacono, Frank J.
Doyle, John
Scheff, Jeremy D.
Calvano, Steve E.
Androulakis, Ioannis P.
An, Gary
Vodovotz, Yoram
author_sort Dick, Thomas E.
collection PubMed
description Acute inflammation leads to organ failure by engaging catastrophic feedback loops in which stressed tissue evokes an inflammatory response and, in turn, inflammation damages tissue. Manifestations of this maladaptive inflammatory response include cardio-respiratory dysfunction that may be reflected in reduced heart rate and ventilatory pattern variabilities. We have developed signal-processing algorithms that quantify non-linear deterministic characteristics of variability in biologic signals. Now, coalescing under the aegis of the NIH Computational Biology Program and the Society for Complexity in Acute Illness, two research teams performed iterative experiments and computational modeling on inflammation and cardio-pulmonary dysfunction in sepsis as well as on neural control of respiration and ventilatory pattern variability. These teams, with additional collaborators, have recently formed a multi-institutional, interdisciplinary consortium, whose goal is to delineate the fundamental interrelationship between the inflammatory response and physiologic variability. Multi-scale mathematical modeling and complementary physiological experiments will provide insight into autonomic neural mechanisms that may modulate the inflammatory response to sepsis and simultaneously reduce heart rate and ventilatory pattern variabilities associated with sepsis. This approach integrates computational models of neural control of breathing and cardio-respiratory coupling with models that combine inflammation, cardiovascular function, and heart rate variability. The resulting integrated model will provide mechanistic explanations for the phenomena of respiratory sinus-arrhythmia and cardio-ventilatory coupling observed under normal conditions, and the loss of these properties during sepsis. This approach holds the potential of modeling cross-scale physiological interactions to improve both basic knowledge and clinical management of acute inflammatory diseases such as sepsis and trauma.
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spelling pubmed-33877812012-07-10 Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling Dick, Thomas E. Molkov, Yaroslav I. Nieman, Gary Hsieh, Yee-Hsee Jacono, Frank J. Doyle, John Scheff, Jeremy D. Calvano, Steve E. Androulakis, Ioannis P. An, Gary Vodovotz, Yoram Front Physiol Physiology Acute inflammation leads to organ failure by engaging catastrophic feedback loops in which stressed tissue evokes an inflammatory response and, in turn, inflammation damages tissue. Manifestations of this maladaptive inflammatory response include cardio-respiratory dysfunction that may be reflected in reduced heart rate and ventilatory pattern variabilities. We have developed signal-processing algorithms that quantify non-linear deterministic characteristics of variability in biologic signals. Now, coalescing under the aegis of the NIH Computational Biology Program and the Society for Complexity in Acute Illness, two research teams performed iterative experiments and computational modeling on inflammation and cardio-pulmonary dysfunction in sepsis as well as on neural control of respiration and ventilatory pattern variability. These teams, with additional collaborators, have recently formed a multi-institutional, interdisciplinary consortium, whose goal is to delineate the fundamental interrelationship between the inflammatory response and physiologic variability. Multi-scale mathematical modeling and complementary physiological experiments will provide insight into autonomic neural mechanisms that may modulate the inflammatory response to sepsis and simultaneously reduce heart rate and ventilatory pattern variabilities associated with sepsis. This approach integrates computational models of neural control of breathing and cardio-respiratory coupling with models that combine inflammation, cardiovascular function, and heart rate variability. The resulting integrated model will provide mechanistic explanations for the phenomena of respiratory sinus-arrhythmia and cardio-ventilatory coupling observed under normal conditions, and the loss of these properties during sepsis. This approach holds the potential of modeling cross-scale physiological interactions to improve both basic knowledge and clinical management of acute inflammatory diseases such as sepsis and trauma. Frontiers Research Foundation 2012-07-02 /pmc/articles/PMC3387781/ /pubmed/22783197 http://dx.doi.org/10.3389/fphys.2012.00222 Text en Copyright © 2012 Dick, Molkov, Nieman, Hsieh, Jacono, Doyle, Scheff, Calvano, Androulakis, An and Vodovotz. http://www.frontiersin.org/licenseagreement This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.
spellingShingle Physiology
Dick, Thomas E.
Molkov, Yaroslav I.
Nieman, Gary
Hsieh, Yee-Hsee
Jacono, Frank J.
Doyle, John
Scheff, Jeremy D.
Calvano, Steve E.
Androulakis, Ioannis P.
An, Gary
Vodovotz, Yoram
Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling
title Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling
title_full Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling
title_fullStr Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling
title_full_unstemmed Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling
title_short Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling
title_sort linking inflammation, cardiorespiratory variability, and neural control in acute inflammation via computational modeling
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3387781/
https://www.ncbi.nlm.nih.gov/pubmed/22783197
http://dx.doi.org/10.3389/fphys.2012.00222
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