High-throughput, single-cell optofluidic platform for point-of-care diagnosis

用于即时诊断的高通量单细胞光流控平台

• 批准号: 18F18716
• 负责人: 合田 圭介
• 金额: $ 1.47万
• 依托单位: The University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for JSPS Fellows
• 财政年份: 2018
• 资助国家: 日本
• 起止时间: 2018-10-12 至 2021-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18F18716/
• 关键词: Optofluidics; imaging flow cytometry

Two breakthrough technologies are generated with the completion of this project. The first one is intelligent platelet aggregate classifier (iPAC) that performs high-throughput imaging and intelligent analysis of platelet aggregates produced by different agonists and classifies platelet aggregates by agonist type. Our finding that platelet aggregates can be classified by agonist type through their morphology is unprecedented as it has never been reported previously. The information about the driving factors behind the formation of platelet aggregates is expected to lead to a better understanding of the underlying mechanism of platelet aggregation and open a window on an entirely new class of clinical diagnostics, pharmacometrics, and therapeutics. The second one is the virtual optofluidic time-stretch quantitative phase imaging, which generates “virtual” phase images from their corresponding bright-field images by using a deep neural network trained with numerous pairs of bright-field and phase images and identifies cancer cells from white blood cells based on their bright-field and virtual phase images. The fellow, Dr Yan, has presented his work in a prestigious international conference (Australia and New Zealand Nanofluidics and Microfluidics conference). Meanwhile, 3 manuscripts are generated from this project.

随着该项目的完成，产生了两项突破性技术。第一个是智能血小板聚集体分类器（iPAC），它对不同激动剂产生的血小板聚集体进行高通量成像和智能分析，并按激动剂类型对血小板聚集体进行分类。我们发现血小板聚集体可以通过其形态学按激动剂类型分类，这是前所未有的，因为以前从未报道过。关于血小板聚集体形成背后的驱动因素的信息有望导致更好地理解血小板聚集的潜在机制，并打开一个全新的临床诊断，药物计量学和治疗学的窗口。第二种是虚拟光流体时间拉伸定量相位成像，其通过使用用许多对明场和相位图像训练的深度神经网络从其对应的明场图像生成“虚拟”相位图像，并基于其明场和虚拟相位图像从白色血细胞中识别癌细胞。严博士在一个著名的国际会议（澳大利亚和新西兰纳米流体和微流体会议）上介绍了他的工作。同时，该项目产生了3篇稿件。

项目成果

Isolation and identification of rare cells in whole blood by time-stretch microscopy with a microfluidic sorter

使用微流体分选仪通过时间拉伸显微镜分离和鉴定全血中的稀有细胞

• 发表时间: 2019
• 作者: Qianbin Zhao; Dan Yuan;Shi-Yang Tang;Guolin Yun Sheng Yan;Jun Zhang;Weihua Li;Sheng Yan
• 通讯作者: Sheng Yan

Intelligent classification of platelet aggregates by agonist type

• DOI: 10.7554/elife.52938
• 发表时间: 2020-05
• 期刊: eLife
• 影响因子: 7.7
• 作者: Yuqi Zhou;A. Yasumoto;Cheng Lei;Chun-Jung Huang;H. Kobayashi;Yunzhao Wu;Sheng Yan;Chia‐Wei Sun;Y. Yatomi;K. Goda

Top sheath flow-assisted secondary flow particle manipulation in microchannels with the slanted groove structure

斜槽结构微通道中顶鞘流辅助二次流颗粒操控

• DOI: 10.1007/s10404-018-2174-x
• 发表时间: 2018
• 期刊: Microfluidics and Nanofluidics
• 影响因子: 2.8
• 作者: Zhao Qianbin;Yuan Dan;Tang Shi-Yang;Yun Guolin;Yan Sheng;Zhang Jun;Li Weihua
• 通讯作者: Li Weihua

Virtual optofluidic time-stretch quantitative phase imaging

• DOI: 10.1063/1.5134125
• 发表时间: 2020-04-01
• 期刊: APL PHOTONICS
• 影响因子: 5.6
• 作者: Yan, Haochen;Wu, Yunzhao;Goda, Keisuke
• 通讯作者: Goda, Keisuke