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首页> 外文期刊>Scientific reports. >An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution
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An on-chip imaging droplet-sorting system: a real-time shape recognition method to screen target cells in droplets with single cell resolution

机译：片上成像液滴排序系统：具有单个小区分辨率的液滴中屏幕目标单元的实时形状识别方法

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A microfluidic on-chip imaging cell sorter has several advantages over conventional cell sorting methods, especially to identify cells with complex morphologies such as clusters. One of the remaining problems is how to efficiently discriminate targets at the species level without labelling. Hence, we developed a label-free microfluidic droplet-sorting system based on image recognition of cells in droplets. To test the applicability of this method, a mixture of two plankton species with different morphologies (Dunaliella tertiolecta and Phaeodactylum tricornutum) were successfully identified and discriminated at a rate of 10?Hz. We also examined the ability to detect the number of objects encapsulated in a droplet. Single cell droplets sorted into collection channels showed 91?±?4.5% and 90?±?3.8% accuracy for D. tertiolecta and P. tricornutum, respectively. Because we used image recognition to confirm single cell droplets, we achieved highly accurate single cell sorting. The results indicate that the integrated method of droplet imaging cell sorting can provide a complementary sorting approach capable of isolating single target cells from a mixture of cells with high accuracy without any staining.
机译：微流体片上成像电池分子配方与常规细胞分选方法有几个优点，尤其是鉴定具有复杂形态的细胞，例如簇。其中一个问题是如何在没有标签的情况下有效地区分物种级别的目标。因此，我们开发了一种基于液滴中细胞的图像识别的无标记的微流体液滴分类系统。为了测试该方法的适用性，成功地鉴定了两种具有不同形态（Dunaliella Tertiolenta和Phaeodactylylum Tricormutum）的浮游生物种类的混合物并以10·Hz的速率辨别。我们还检查了检测液滴中封装在液滴中的对象数量的能力。分选到收集通道中的单个电池液滴显示出91°？±4.5％和90？±3.8％，分别为D.Tertiolecta和P. Tricornutum的准确度。因为我们使用图像识别来确认单个细胞液滴，所以我们实现了高精度的单细胞分类。结果表明，液滴成像电池分选的综合方法可以提供一种互补分选方法，其能够在没有任何染色的情况下将单个靶细胞与细胞混合物隔离。

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