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Touchable cell biophysics property recognition platforms enable multifunctional blood smart health care

Authors :
Longfei Chen
Yantong Liu
Hongshan Xu
Linlu Ma
Yifan Wang
Le Yu
Fang Wang
Jiaomeng Zhu
Xuejia Hu
Kezhen Yi
Yi Yang
Hui Shen
Fuling Zhou
Xiaoqi Gao
Yanxiang Cheng
Long Bai
Yongwei Duan
Fubing Wang
Yimin Zhu
Source :
Microsystems & Nanoengineering, Vol 7, Iss 1, Pp 1-13 (2021)
Publication Year :
2021
Publisher :
Nature Publishing Group, 2021.

Abstract

Abstract As a crucial biophysical property, red blood cell (RBC) deformability is pathologically altered in numerous disease states, and biochemical and structural changes occur over time in stored samples of otherwise normal RBCs. However, there is still a gap in applying it further to point-of-care blood devices due to the large external equipment (high-resolution microscope and microfluidic pump), associated operational difficulties, and professional analysis. Herein, we revolutionarily propose a smart optofluidic system to provide a differential diagnosis for blood testing via precise cell biophysics property recognition both mechanically and morphologically. Deformation of the RBC population is caused by pressing the hydrogel via an integrated mechanical transfer device. The biophysical properties of the cell population are obtained by the designed smartphone algorithm. Artificial intelligence-based modeling of cell biophysics properties related to blood diseases and quality was developed for online testing. We currently achieve 100% diagnostic accuracy for five typical clinical blood diseases (90 megaloblastic anemia, 78 myelofibrosis, 84 iron deficiency anemia, 48 thrombotic thrombocytopenic purpura, and 48 thalassemias) via real-world prospective implementation; furthermore, personalized blood quality (for transfusion in cardiac surgery) monitoring is achieved with an accuracy of 96.9%. This work suggests a potential basis for next-generation blood smart health care devices.

Details

Language :
English
ISSN :
20557434
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Microsystems & Nanoengineering
Publication Type :
Academic Journal
Accession number :
edsdoj.8f0d111902324b7a9677ded6116bc89e
Document Type :
article
Full Text :
https://doi.org/10.1038/s41378-021-00329-z