Dynamical modeling of pro- and anti-inflammatory cytokines in the early stage of septic shock.

Q2 Medicine In Silico Biology Pub Date : 2020-01-01 DOI:10.3233/ISB-200474
J Tallon, B Browning, F Couenne, C Bordes, F Venet, P Nony, F Gueyffier, V Moucadel, G Monneret, M Tayakout-Fayolle
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引用次数: 3

Abstract

A dynamical model of the pathophysiological behaviors of IL18 and IL10 cytokines with their receptors is tested against data for the case of early sepsis. The proposed approach considers the surroundings (organs and bone marrow) and the different subsystems (cells and cyctokines). The interactions between blood cells, cytokines and the surroundings are described via mass balances. Cytokines are adsorbed onto associated receptors at the cell surface. The adsorption is described by the Langmuir model and gives rise to the production of more cytokines and associated receptors inside the cell. The quantities of pro and anti-inflammatory cytokines present in the body are combined to give global information via an inflammation level function which describes the patient's state. Data for parameter estimation comes from the Sepsis 48 H database. Comparisons between patient data and simulations are presented and are in good agreement. For the IL18/IL10 cytokine pair, 5 key parameters have been found. They are linked to pro-inflammatory IL18 cytokine and show that the early sepsis is driven by components of inflammatory character.

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感染性休克早期促炎性和抗炎性细胞因子的动力学模型。
IL18和IL10细胞因子及其受体的病理生理行为的动力学模型是针对早期败血症病例的数据进行测试的。该方法考虑了周围环境(器官和骨髓)和不同的子系统(细胞和细胞因子)。血细胞、细胞因子和周围环境之间的相互作用通过质量平衡来描述。细胞因子被吸附在细胞表面的相关受体上。Langmuir模型描述了这种吸附,并在细胞内产生更多的细胞因子和相关受体。机体中存在的促炎性和抗炎性细胞因子的数量结合起来,通过炎症水平功能提供全局信息,该功能描述了患者的状态。参数估计数据来自败血症48 H数据库。在病人数据和模拟之间的比较提出,并在很好的协议。对于IL18/IL10细胞因子对,我们发现了5个关键参数。它们与促炎il - 18细胞因子有关,表明早期败血症是由炎症性成分驱动的。
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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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