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一种用于自动评估镰状红细胞瞬时镰变动力学的计算机视觉增强微流控方法框架。

A framework of computer vision-enhanced microfluidic approach for automated assessment of the transient sickling kinetics in sickle red blood cells.

作者信息

Qiang Yuhao, Xu Mengjia, Patel Pochron Mira, Jupelli Madhulika, Dao Ming

机构信息

Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States.

Department of Data Science, Ying Wu College of Computing, New Jersey Institute of Technology, Newark, NJ, United States.

出版信息

Front Phys. 2024;12. doi: 10.3389/fphy.2024.1331047. Epub 2024 Mar 14.

Abstract

The occurrence of vaso-occlusive crisis greatly depends on the competition between the sickling delay time and the transit time of individual sickle cells, i.e., red blood cells (RBCs) from sickle cell disease (SCD) patients, while they are traversing the circulatory system. Many drugs for treating SCD work by inhibiting the polymerization of sickle hemoglobin (HbS), effectively delaying the sickling process in sickle cells (SS RBCs). Most previous studies on screening anti-sickling drugs, such as voxelotor, rely on testing of sickling characteristics, often conducted under prolonged deoxygenation for up to 1 hour. However, since the microcirculation of RBCs typically takes less than 1 minute, the results of these studies may be less accurate and less relevant for in vitro-in vivo correlation. In our current study, we introduce a computer vision-enhanced microfluidic framework designed to automatically capture the transient sickling kinetics of SS RBCs within a 1-min timeframe. Our study has successfully detected differences in the transient sickling kinetics between vehicle control and voxelotor-treated SS RBCs. This approach has the potential for broader applications in screening anti-sickling therapies.

摘要

血管闭塞性危象的发生很大程度上取决于镰状细胞延迟时间与单个镰状细胞(即镰状细胞病患者的红细胞)在循环系统中运行时间之间的竞争。许多治疗镰状细胞病的药物通过抑制镰状血红蛋白(HbS)的聚合起作用,有效延迟镰状细胞(SS红细胞)的镰变过程。以前大多数关于筛选抗镰变药物(如voxelotor)的研究依赖于镰变特性测试,通常在长达1小时的长时间脱氧条件下进行。然而,由于红细胞的微循环通常不到1分钟,这些研究结果可能不太准确,与体外-体内相关性的关联性也较低。在我们目前的研究中,我们引入了一个计算机视觉增强的微流控框架,旨在在1分钟的时间范围内自动捕捉SS红细胞的瞬时镰变动力学。我们的研究成功检测到了载体对照和voxelotor处理的SS红细胞之间瞬时镰变动力学的差异。这种方法在筛选抗镰变疗法方面具有更广泛的应用潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d84e/11008125/e70f5fb5bcec/nihms-1977432-f0001.jpg

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