Mathematical modeling of ventilator-induced lung inflammation.
immune response
macrophages
mathematical modeling
mechanical ventilation
Journal
Journal of theoretical biology
ISSN: 1095-8541
Titre abrégé: J Theor Biol
Pays: England
ID NLM: 0376342
Informations de publication
Date de publication:
07 10 2021
07 10 2021
Historique:
received:
23
11
2020
revised:
20
04
2021
accepted:
22
04
2021
pubmed:
1
5
2021
medline:
7
8
2021
entrez:
30
4
2021
Statut:
ppublish
Résumé
Despite the benefits of mechanical ventilators, prolonged or misuse of ventilators may lead to ventilation-associated/ventilation-induced lung injury (VILI). Lung insults, such as respiratory infections and lung injuries, can damage the pulmonary epithelium, with the most severe cases needing mechanical ventilation for effective breathing and survival. Damaged epithelial cells within the alveoli trigger a local immune response. A key immune cell is the macrophage, which can differentiate into a spectrum of phenotypes ranging from pro- to anti-inflammatory. To gain a greater understanding of the mechanisms of the immune response to VILI and post-ventilation outcomes, we developed a mathematical model of interactions between the immune system and site of damage while accounting for macrophage phenotype. Through Latin hypercube sampling we generated a collection of parameter sets that are associated with a numerical steady state. We then simulated ventilation-induced damage using these steady state values as the initial conditions in order to evaluate how baseline immune state and lung health affect outcomes. We used a variety of methods to analyze the resulting parameter sets, transients, and outcomes, including a random forest decision tree algorithm and parameter sensitivity with eFAST. Analysis shows that parameters and properties of transients related to epithelial repair and M1 activation are important factors. Using the results of this analysis, we hypothesized interventions and used these treatment strategies to modulate the response to ventilation for particular parameters sets.
Identifiants
pubmed: 33930440
pii: S0022-5193(21)00160-0
doi: 10.1016/j.jtbi.2021.110738
pmc: PMC8277755
mid: NIHMS1715265
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
110738Subventions
Organisme : NHLBI NIH HHS
ID : R21 HL146250
Pays : United States
Commentaires et corrections
Type : UpdateOf
Informations de copyright
Copyright © 2021 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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