Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling.
Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling.
复制标题
DOI：
10.3389/fphys.2012.00222
复制
发表时间：
2012
影响因子：
4
通讯作者：
Vodovotz Y
中科院分区：
文献类型：
--
作者：
Dick TE;Molkov YI;Nieman G;Hsieh YH;Jacono FJ;Doyle J;Scheff JD;Calvano SE;Androulakis IP;An G;Vodovotz Y
急性炎症通过参与灾难性的反馈回路导致器官衰竭，其中应激组织引起炎症反应，反过来，炎症损伤组织。这种适应不良的炎症反应的表现包括心肺功能障碍，其可以反映在心率降低和呼吸模式变异性上。我们已经开发了信号处理算法，量化生物信号的非线性确定性特征的变化。现在，在NIH计算生物学计划和急性疾病复杂性协会的支持下，两个研究小组对脓毒症中的炎症和心肺功能障碍以及呼吸和呼吸模式变异的神经控制进行了迭代实验和计算建模。这些团队与其他合作者最近组成了一个多机构，跨学科的联盟，其目标是描绘炎症反应和生理变异性之间的基本相互关系。多尺度数学建模和补充生理实验将提供对自主神经机制的深入了解，这些机制可能调节脓毒症的炎症反应，同时降低与脓毒症相关的心率和呼吸模式变异性。这种方法将呼吸和心肺耦合的神经控制的计算模型与结合了联合收割机炎症、心血管功能和心率变异性的模型相结合。由此产生的综合模型将提供机制解释的现象，呼吸窦性心律失常和心-电耦合在正常条件下观察到的，这些属性的损失在败血症。这种方法具有模拟跨尺度生理相互作用的潜力，以改善急性炎症性疾病（如败血症和创伤）的基础知识和临床管理。
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.
登录
查看更多内容
影响因子：
4.4
作者：
Chen, Wei-Lung;Kuo, Cheng-Deng
通讯作者：
Kuo, Cheng-Deng
影响因子：
1.4
作者：
An, Gary;Faeder, James;Vodovotz, Yoram
通讯作者：
Vodovotz, Yoram
影响因子：
8.8
作者：
Abraham, Edward;Singer, Mervyn
通讯作者：
Singer, Mervyn
DOI：
10.1097/ta.0b013e3181848241
发表时间：
2008-10-01
影响因子：
--
作者：
Cancio, Leopoldo C.;Batchinsky, Andriy I.;Holcomb, John B.
通讯作者：
Holcomb, John B.
影响因子：
8.8
作者：
Angus, D C;Linde-Zwirble, W T;Pinsky, M R
通讯作者：
Pinsky, M R