Demirci Bio-Acoustic-MEMS in Medicine Laboratory, Center for Bioengineering, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
PLoS One. 2011;6(7):e21580. doi: 10.1371/journal.pone.0021580. Epub 2011 Jul 21.
High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems.
高通量按需滴系统用于从多种细胞类型的异质混合物中分离和封装单个靶细胞，这是生物技术中的一种新兴方法，在组织工程和再生医学、基因组学和低温生物学中有广泛的应用。然而，细胞在液滴中的封装是一个难以控制的随机过程。统计模型可以提供对底层过程的理解和对相关参数的估计，并能够在高置信度水平下可靠且可重复地控制细胞在分离过程中在液滴中的封装。我们已经对基于微滴的细胞封装过程进行了建模和实验验证，适用于各种细胞加载和靶细胞浓度的组合。在这里，我们从理论上解释并通过实验验证了一种模型，该模型无需使用复杂的外围系统即可从异质混合物中分离和模式化单个靶细胞。
