A data-driven model of the role of energy in sepsis

被引:2
|
作者
Ramirez-Zuniga, Ivan [1 ,6 ]
Rubin, Jonathan E. [1 ]
Swigon, David [1 ,5 ]
Redl, Heinz [3 ,4 ]
Clermont, Gilles [1 ,2 ]
机构
[1] Univ Pittsburgh, Dept Math, Pittsburgh, PA 15260 USA
[2] Univ Pittsburgh, Dept Crit Care Med, Pittsburgh, PA USA
[3] Ludwig Boltzmann Inst Expt & Clin Traumatol, AUVA Trauma Res Ctr, Vienna, Austria
[4] Vienna Univ Technol, Vienna, Austria
[5] Univ Pittsburgh, Med Ctr, McGowan Inst Regenerat Med, Pittsburgh, PA USA
[6] Univ Tennessee, Dept Pediat, Hlth Sci Ctr, Memphis, TN 38163 USA
关键词
Computational modeling; Ordinary differential equations; Sepsis; Bioenergetics; Bayesian parameter estimation; ACUTE INFLAMMATORY RESPONSE; MITOCHONDRIAL DYSFUNCTION; CLINICAL-TRIALS; PARAMETER;
D O I
10.1016/j.jtbi.2021.110948
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Exposure to pathogens elicits a complex immune response involving multiple interdependent pathways. This response may mitigate detrimental effects and restore health but, if imbalanced, can lead to negative outcomes including sepsis. This complexity and need for balance pose a challenge for clinicians and have attracted attention from modelers seeking to apply computational tools to guide therapeutic approaches. In this work, we address a shortcoming of such past efforts by incorporating the dynamics of energy production and consumption into a computational model of the acute immune response. With this addition, we performed fits of model dynamics to data obtained from non-human primates exposed to Escherichia coli. Our analysis identifies parameters that may be crucial in determining survival outcomes and also highlights energy-related factors that modulate the immune response across baseline and altered glucose conditions. (C) 2021 Elsevier Ltd. All rights reserved.
引用
收藏
页数:24
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