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首页> 外文期刊>Microcirculation: The official journal of the Microcirculatory Society >Event-tracking model of adhesion identifies load-bearing bonds in rolling leukocytes.
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Event-tracking model of adhesion identifies load-bearing bonds in rolling leukocytes.

机译:粘附的事件跟踪模型可以识别滚动白细胞中的承重键。

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OBJECTIVES: P-selectin binding to P-selectin glycoprotein ligand-1 (PSGL)-1 mediates leukocyte rolling under conditions of inflammation and injury. The aims of this study were to develop an efficient, high temporal resolution model for direct simulation of leukocyte rolling and conduct a study of load-bearing bonds using the model. MATERIALS AND METHODS: A stochastic pi-calculus-driven event-tracking model of adhesion (ETMA) was developed and compared with experimental data. Multiple simulations for each case were conducted to obtain high-confidence numerical characteristics of leukocyte rolling. RESULTS: Leukocyte rolling and the underlying P-selectin-PSGL-1 bonds were studied under low wall shear rate (25-50 s(-1)) conditions from measured parameters of leukocyte rolling and bond properties. For the first time, the location, number, lifetime, history, and kinetics of load-bearing bonds and their influence on cell rolling were identified and instantaneous cell displacements, translational and rotational velocities, and cell-substrate distances derived. The model explains the commonly observed "stop-start" type rolling behavior and reveals that a few load-bearing bonds are sufficient to support rolling, while a large number of bonds dissociate before becoming load bearing. CONCLUSIONS: ETMA provides a method for more precise, direct simulation of leukocyte rolling at low wall shear rates and sets a foundation upon which further refinements can be introduced.
机译:目的:P-选择素与P-选择素糖蛋白配体1(PSGL)-1的结合在炎症和损伤的情况下介导白细胞滚动。这项研究的目的是开发一种用于直接模拟白细胞滚动的高效,高时间分辨率的模型,并使用该模型进行承载键的研究。材料与方法:建立了随机的pi演算驱动的粘附事件跟踪模型(ETMA),并与实验数据进行了比较。对每种情况进行了多次模拟以获得高可信度的白细胞滚动数值特征。结果:从白细胞滚动和结合特性的测量参数,在低壁剪切速率(25-50 s(-1))条件下研究了白细胞滚动和潜在的P-selectin-PSGL-1键。首次确定了荷重键的位置,数量,寿命,历史和动力学及其对细胞滚动的影响,并得出了瞬时细胞位移,平移和旋转速度以及细胞与基质的距离。该模型解释了通常观察到的“停止-启动”类型的滚动行为,并揭示了一些承重键足以支持滚动,而大量键在成为承重力之前会解体。结论:ETMA提供了一种在低壁剪切速率下更精确,直接模拟白细胞滚动的方法,并为进一步改进奠定了基础。

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