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探究血小板-纳米颗粒相互作用过程中ADP诱导的聚集动力学:功能动力学分析以阐明安全性和益处

Probing ADP Induced Aggregation Kinetics During Platelet-Nanoparticle Interactions: Functional Dynamics Analysis to Rationalize Safety and Benefits.

作者信息

Bandyopadhyay Souvik K, Azharuddin Mohammad, Dasgupta Anjan K, Ganguli Bhaswati, SenRoy Sugata, Patra Hirak K, Deb Suryyani

机构信息

GlaxoSmithKline Asia Pvt. Ltd., Bangalore, India.

Department of Clinical and Experimental Medicine (IKE), Linköping University, Linköping, Sweden.

出版信息

Front Bioeng Biotechnol. 2019 Jul 18;7:163. doi: 10.3389/fbioe.2019.00163. eCollection 2019.

Abstract

Platelets, one of the most sensitive blood cells, can be activated by a range of external and internal stimuli including physical, chemical, physiological, and/or non-physiological agents. Platelets need to respond promptly during injury to maintain blood hemostasis. The time profile of platelet aggregation is very complex, especially in the presence of the agonist adenosine 5'-diphosphate (ADP), and it is difficult to probe such complexity using traditional linear dose response models. In the present study, we explored functional analysis techniques to characterize the pattern of platelet aggregation over time in response to nanoparticle induced perturbations. This has obviated the need to represent the pattern of aggregation by a single summary measure and allowed us to treat the entire aggregation profile over time, as the response. The modeling was performed in a flexible manner, without any imposition of shape restrictions on the curve, allowing smooth platelet aggregation over time. The use of a probabilistic framework not only allowed statistical prediction and inference of the aggregation signatures, but also provided a novel method for the estimation of higher order derivatives of the curve, thereby allowing plausible estimation of the extent and rate of platelet aggregation kinetics over time. In the present study, we focused on the estimated first derivative of the curve, obtained from the platelet optical aggregometric profile over time and used it to discern the underlying kinetics as well as to study the effects of ADP dosage and perturbation with gold nanoparticles. In addition, our method allowed the quantification of the extent of inter-individual signature variations. Our findings indicated several hidden features and showed a mixture of zero and first order kinetics interrupted by a metastable zero order ADP dose dependent process. In addition, we showed that the two first order kinetic constants were ADP dependent. However, we were able to perturb the overall kinetic pattern using gold nanoparticles, which resulted in autocatalytic aggregation with a higher aggregate mass and which facilitated the aggregation rate.

摘要

血小板是最敏感的血细胞之一,可被一系列外部和内部刺激激活,包括物理、化学、生理和/或非生理因素。在受伤期间,血小板需要迅速做出反应以维持血液止血。血小板聚集的时间曲线非常复杂,尤其是在存在激动剂5'-二磷酸腺苷(ADP)的情况下,使用传统的线性剂量反应模型很难探究这种复杂性。在本研究中,我们探索了功能分析技术,以表征血小板在纳米颗粒诱导的扰动下随时间的聚集模式。这避免了用单一汇总测量来表示聚集模式的需要,并使我们能够将随时间的整个聚集曲线视为反应。建模以灵活的方式进行,不对曲线施加任何形状限制,允许血小板随时间平滑聚集。使用概率框架不仅允许对聚集特征进行统计预测和推断,还提供了一种估计曲线高阶导数的新方法,从而能够合理估计血小板聚集动力学随时间的程度和速率。在本研究中,我们专注于从血小板光学聚集曲线随时间获得的曲线估计一阶导数,并用它来识别潜在的动力学以及研究ADP剂量和金纳米颗粒扰动的影响。此外,我们的方法允许对个体间特征变化的程度进行量化。我们的研究结果表明了几个隐藏特征,并显示了零级和一级动力学的混合,被一个亚稳的零级ADP剂量依赖性过程中断。此外,我们表明两个一级动力学常数是ADP依赖性的。然而,我们能够使用金纳米颗粒扰动整体动力学模式,这导致了具有更高聚集体质量的自催化聚集,并促进了聚集速率。

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