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NPJ Precis Oncol. 2019 Dec 2;3:30. doi: 10.1038/s41698-019-0102-5. eCollection 2019.
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Detection of Clinical Mesenchymal Cancer Cells from Bladder Wash Urine for Real-Time Detection and Prognosis.从膀胱冲洗尿液中检测临床间充质癌细胞以进行实时检测和预后评估。
Cancers (Basel). 2019 Aug 30;11(9):1274. doi: 10.3390/cancers11091274.
4
Rapid and Safe Isolation of Human Peripheral Blood B and T Lymphocytes through Spiral Microfluidic Channels.通过螺旋微流控通道快速安全地分离人外周血 B 和 T 淋巴细胞。
Sci Rep. 2019 May 31;9(1):8145. doi: 10.1038/s41598-019-44677-3.
5
Progress of Inertial Microfluidics in Principle and Application.惯性微流控技术的原理及应用进展。
Sensors (Basel). 2018 Jun 1;18(6):1762. doi: 10.3390/s18061762.
6
Fundamentals of elasto-inertial particle focusing in curved microfluidic channels.弹性惯性颗粒在弯曲微流道中的聚焦基础。
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7
Fundamentals and applications of inertial microfluidics: a review.惯性微流体技术的基础与应用:综述
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8
Separation of blood cells with differing deformability using deterministic lateral displacement(†).利用确定性侧向位移(†)分离具有不同变形能力的血细胞。
Interface Focus. 2014 Dec 6;4(6):20140011. doi: 10.1098/rsfs.2014.0011.
9
A microfluidic pipette array for mechanophenotyping of cancer cells and mechanical gating of mechanosensitive channels.一种用于癌细胞机械表型分析和机械敏感通道机械门控的微流控移液器阵列。
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10
Inertial focusing in microfluidics.微流控中的惯性聚焦
Annu Rev Biomed Eng. 2014 Jul 11;16:371-96. doi: 10.1146/annurev-bioeng-121813-120704. Epub 2014 May 29.

基于密度的阈值模型,用于评估具有曲线微流道的多相混合物中颗粒的分离。

A density-based threshold model for evaluating the separation of particles in heterogeneous mixtures with curvilinear microfluidic channels.

机构信息

Department of Biomedical Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China.

出版信息

Sci Rep. 2020 Nov 4;10(1):18984. doi: 10.1038/s41598-020-75878-w.

DOI:10.1038/s41598-020-75878-w
PMID:33149169
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7643107/
Abstract

Particle separation techniques play an important role in biomedical research. Inertial focusing based microfluidics using nonlinear channels is one of the promising label-free technologies for biological applications. The particle separation is achieved as a result of the combination of inertial lift force (F) and Dean drag force (F). Although the mathematical expressions of F and F have been well derived in prior studies, they are still complicated, which limits their popularity in practice. Recent studies modified these expressions through experiments and proposed a threshold model, which assumes that only particles larger than the threshold will be well focused. Although this threshold model has been used in recent studies, two varying versions of the threshold model (TM1 and TM2) prevents standardisation in practice. In addition, both models were developed with regular low-density particles and may not be applicable to samples with higher density or samples with irregular shapes. Here, we evaluated the threshold models with samples of different densities. Based on these evaluations, we derived a modified model (TM4), which additionally considers the factor of particle density to improve the accuracy of existing models. Our results demonstrated that TM4 could more reliably predict the sorting efficiency of samples within a wider density range.

摘要

粒子分离技术在生物医学研究中起着重要作用。基于非线性通道的惯性聚焦微流控技术是一种很有前途的无标记生物应用技术。粒子分离是由于惯性升力(F)和迪恩曳力(F)的共同作用而实现的。尽管在先前的研究中已经很好地推导出 F 和 F 的数学表达式,但它们仍然很复杂,这限制了它们在实践中的普及。最近的研究通过实验对这些表达式进行了修正,并提出了一个阈值模型,该模型假设只有大于阈值的颗粒才能被很好地聚焦。尽管这个阈值模型在最近的研究中得到了应用,但是两个不同版本的阈值模型(TM1 和 TM2)在实践中阻止了标准化。此外,这两个模型都是用常规的低密度颗粒开发的,可能不适用于密度更高的样品或形状不规则的样品。在这里,我们用不同密度的样品来评估阈值模型。基于这些评估,我们推导出了一个改进的模型(TM4),该模型还考虑了颗粒密度的因素,以提高现有模型的准确性。我们的结果表明,TM4 可以更可靠地预测更广泛密度范围内样品的分选效率。