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Ensemble Models of Neutrophil Trafficking in Severe Sepsis
A hallmark of severe sepsis is systemic inflammation which activates leukocytes and can result in their misdirection. This leads to both impaired migration to the locus of infection and increased infiltration into healthy tissues. In order to better understand the pathophysiologic mechanisms involve...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3297568/ https://www.ncbi.nlm.nih.gov/pubmed/22412365 http://dx.doi.org/10.1371/journal.pcbi.1002422 |
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author | Song, Sang O. K. Hogg, Justin Peng, Zhi-Yong Parker, Robert Kellum, John A. Clermont, Gilles |
author_facet | Song, Sang O. K. Hogg, Justin Peng, Zhi-Yong Parker, Robert Kellum, John A. Clermont, Gilles |
author_sort | Song, Sang O. K. |
collection | PubMed |
description | A hallmark of severe sepsis is systemic inflammation which activates leukocytes and can result in their misdirection. This leads to both impaired migration to the locus of infection and increased infiltration into healthy tissues. In order to better understand the pathophysiologic mechanisms involved, we developed a coarse-grained phenomenological model of the acute inflammatory response in CLP (cecal ligation and puncture)-induced sepsis in rats. This model incorporates distinct neutrophil kinetic responses to the inflammatory stimulus and the dynamic interactions between components of a compartmentalized inflammatory response. Ensembles of model parameter sets consistent with experimental observations were statistically generated using a Markov-Chain Monte Carlo sampling. Prediction uncertainty in the model states was quantified over the resulting ensemble parameter sets. Forward simulation of the parameter ensembles successfully captured experimental features and predicted that systemically activated circulating neutrophils display impaired migration to the tissue and neutrophil sequestration in the lung, consequently contributing to tissue damage and mortality. Principal component and multiple regression analyses of the parameter ensembles estimated from survivor and non-survivor cohorts provide insight into pathologic mechanisms dictating outcome in sepsis. Furthermore, the model was extended to incorporate hypothetical mechanisms by which immune modulation using extracorporeal blood purification results in improved outcome in septic rats. Simulations identified a sub-population (about [Image: see text] of the treated population) that benefited from blood purification. Survivors displayed enhanced neutrophil migration to tissue and reduced sequestration of lung neutrophils, contributing to improved outcome. The model ensemble presented herein provides a platform for generating and testing hypotheses in silico, as well as motivating further experimental studies to advance understanding of the complex biological response to severe infection, a problem of growing magnitude in humans. |
format | Online Article Text |
id | pubmed-3297568 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-32975682012-03-12 Ensemble Models of Neutrophil Trafficking in Severe Sepsis Song, Sang O. K. Hogg, Justin Peng, Zhi-Yong Parker, Robert Kellum, John A. Clermont, Gilles PLoS Comput Biol Research Article A hallmark of severe sepsis is systemic inflammation which activates leukocytes and can result in their misdirection. This leads to both impaired migration to the locus of infection and increased infiltration into healthy tissues. In order to better understand the pathophysiologic mechanisms involved, we developed a coarse-grained phenomenological model of the acute inflammatory response in CLP (cecal ligation and puncture)-induced sepsis in rats. This model incorporates distinct neutrophil kinetic responses to the inflammatory stimulus and the dynamic interactions between components of a compartmentalized inflammatory response. Ensembles of model parameter sets consistent with experimental observations were statistically generated using a Markov-Chain Monte Carlo sampling. Prediction uncertainty in the model states was quantified over the resulting ensemble parameter sets. Forward simulation of the parameter ensembles successfully captured experimental features and predicted that systemically activated circulating neutrophils display impaired migration to the tissue and neutrophil sequestration in the lung, consequently contributing to tissue damage and mortality. Principal component and multiple regression analyses of the parameter ensembles estimated from survivor and non-survivor cohorts provide insight into pathologic mechanisms dictating outcome in sepsis. Furthermore, the model was extended to incorporate hypothetical mechanisms by which immune modulation using extracorporeal blood purification results in improved outcome in septic rats. Simulations identified a sub-population (about [Image: see text] of the treated population) that benefited from blood purification. Survivors displayed enhanced neutrophil migration to tissue and reduced sequestration of lung neutrophils, contributing to improved outcome. The model ensemble presented herein provides a platform for generating and testing hypotheses in silico, as well as motivating further experimental studies to advance understanding of the complex biological response to severe infection, a problem of growing magnitude in humans. Public Library of Science 2012-03-08 /pmc/articles/PMC3297568/ /pubmed/22412365 http://dx.doi.org/10.1371/journal.pcbi.1002422 Text en Song et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Song, Sang O. K. Hogg, Justin Peng, Zhi-Yong Parker, Robert Kellum, John A. Clermont, Gilles Ensemble Models of Neutrophil Trafficking in Severe Sepsis |
title | Ensemble Models of Neutrophil Trafficking in Severe Sepsis |
title_full | Ensemble Models of Neutrophil Trafficking in Severe Sepsis |
title_fullStr | Ensemble Models of Neutrophil Trafficking in Severe Sepsis |
title_full_unstemmed | Ensemble Models of Neutrophil Trafficking in Severe Sepsis |
title_short | Ensemble Models of Neutrophil Trafficking in Severe Sepsis |
title_sort | ensemble models of neutrophil trafficking in severe sepsis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3297568/ https://www.ncbi.nlm.nih.gov/pubmed/22412365 http://dx.doi.org/10.1371/journal.pcbi.1002422 |
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