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High-throughput“read-on-ski”automated imaging and label-free detection system for toxicity screening of compounds using personalised human kidney organoids
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作者 Qizheng WANG Jun LU +11 位作者 Ke FAN Yiwei XU yucui xiong Zhiyong SUN Man ZHAI Zhizhong ZHANG Sheng ZHANG Yan SONG Jianzhong LUO Mingliang YOU Meijin GUO Xiao ZHANG 《Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)》 SCIE CAS CSCD 2022年第7期564-577,共14页
Organoid models are used to study kidney physiology,such as the assessment of nephrotoxicity and underlying disease processes.Personalized human pluripotent stem cell-derived kidney organoids are ideal models for comp... Organoid models are used to study kidney physiology,such as the assessment of nephrotoxicity and underlying disease processes.Personalized human pluripotent stem cell-derived kidney organoids are ideal models for compound toxicity studies,but there is a need to accelerate basic and translational research in the field.Here,we developed an automated continuous imaging setup with the“read-on-ski”law of control to maximize temporal resolution with minimum culture plate vibration.High-accuracy performance was achieved:organoid screening and imaging were performed at a spatial resolution of 1.1µm for the entire multi-well plate under 3 min.We used the in-house developed multi-well spinning device and cisplatin-induced nephrotoxicity model to evaluate the toxicity in kidney organoids using this system.The acquired images were processed via machine learning-based classification and segmentation algorithms,and the toxicity in kidney organoids was determined with 95%accuracy.The results obtained by the automated“read-on-ski”imaging device,combined with label-free and non-invasive algorithms for detection,were verified using conventional biological procedures.Taking advantage of the close-to-in vivo-kidney organoid model,this new development opens the door for further application of scaled-up screening using organoids in basic research and drug discovery. 展开更多
关键词 Kidney organoid High-throughput microscopy NEPHROTOXICITY Machine learning
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