Essential thrombocythemia (ET) is an uncommon situation in which the body produces too many platelets. This can cause blood clots anywhere in the body and results in various symptoms and even strokes or heart attacks. Removing excessive platelets using acoustofluidic methods receives extensive attention due to their high efficiency and high yield. While the damage to the remaining cells, such as erythrocytes and leukocytes is yet evaluated. Existing cell damage evaluation methods usually require cell staining, which are time-consuming and labor-intensive. In this paper, we investigate cell damage by optical time-stretch (OTS) imaging flow cytometry with high throughput and in a label-free manner. Specifically, we first image the erythrocytes and leukocytes sorted by acoustofluidic sorting chip with different acoustic wave powers and flowing speed using OTS imaging flow cytometry at a flowing speed up to 1 m/s. Then, we employ machine learning algorithms to extract biophysical phenotypic features from the cellular images, as well as to cluster and identify images. The results show that both the errors of the biophysical phenotypic features and the proportion of abnormal cells are within 10% in the undamaged cell groups, while the errors are much greater than 10% in the damaged cell groups, indicating that acoustofluidic sorting causes little damage to the cells within the appropriate acoustic power, agreeing well with clinical assays. Our method provides a novel approach for high-throughput and label-free cell damage evaluation in scientific research and clinical settings.

中文翻译：

---

智能成像流式细胞术评估细胞损伤

原发性血小板增多症 (ET) 是一种罕见的情况，患者体内产生过多血小板。这可能会导致身体任何部位出现血栓，并导致各种症状，甚至中风或心脏病发作。使用声流控方法去除过多的血小板由于其高效率和高产率而受到广泛关注。而对剩余细胞（例如红细胞和白细胞）的损害仍在评估中。现有的细胞损伤评估方法通常需要细胞染色，耗时耗力。在本文中，我们通过光学时间拉伸（OTS）成像流式细胞术以高通量和无标记的方式研究细胞损伤。具体来说，我们首先使用OTS成像流式细胞仪以高达1 m/s的流速对声流分选芯片在不同声波功率和流速下分选的红细胞和白细胞进行成像。然后，我们采用机器学习算法从细胞图像中提取生物物理表型特征，并对图像进行聚类和识别。结果表明，未损伤细胞组的生物物理表型特征和异常细胞比例的误差均在10%以内，而损伤细胞组的误差远大于10%，表明声流分选造成的损伤很小。在适当的声功率内对细胞进行检测，与临床测定非常一致。我们的方法为科学研究和临床环境中的高通量和无标记细胞损伤评估提供了一种新方法。