脉动流
微流控
血流动力学
体外
生物医学工程
心脏病学
材料科学
化学
医学
工程类
纳米技术
生物化学
作者
Lixue Liang,Xueying Wang,Dong Chen,Palaniappan Sethu,Guruprasad A. Giridharan,Yanxia Wang,Yu Wang,Kai‐Rong Qin,Yu Wang,Kai-Rong Qin
出处
期刊:Lab on a Chip
[Royal Society of Chemistry]
日期:2024-01-01
卷期号:24 (9): 2428-2439
被引量:5
摘要
Rotary blood pumps (RBPs) operating at a constant speed generate non-physiologic blood pressure and flow rate, which can cause endothelial dysfunction, leading to adverse clinical events in peripheral blood vessels and other organs. Notably, pulsatile working modes of the RBP can increase vascular pulsatility to improve arterial endothelial function. However, the laws and related mechanisms of differentially regulating arterial endothelial function under different pulsatile working modes are still unclear. This knowledge gap hinders the optimal selection of the RBP working modes. To address these issues, this study developed a multi-element in vitro endothelial cell culture system (ECCS), which could realize in vitro cell culture effectively and accurately reproduce blood pressure, shear stress, and circumferential strain in the arterial endothelial microenvironment. Performance of this proposed ECCS was validated with numerical simulation and flow experiments. Subsequently, this study investigated the effects of four different pulsation frequency modes that change once every 1-4-fold cardiac cycles (80, 40, 80/3, and 20 cycles per min, respectively) of the RBP on the expression of nitric oxide (NO) and reactive oxygen species (ROS) in endothelial cells. Results indicated that the 2-fold and 3-fold cardiac cycles significantly increased the production of NO and prevented the excessive generation of ROS, potentially minimizing the occurrence of endothelial dysfunction and related adverse events during the RBP support, and were consistent with animal study findings. In general, this study may provide a scientific basis for the optimal selection of the RBP working modes and potential treatment options for heart failure.
科研通智能强力驱动
Strongly Powered by AbleSci AI