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翻转二维码实现可靠血型鉴定。

Flipped Quick-Response Code Enables Reliable Blood Grouping.

作者信息

Zhang Hong, Liu Ruining, Li Qingmei, Hu Xiaolin, Wu Lixiang, Zhou Ye, Qing Guangchao, Yuan Rui, Huang Junjie, Gu Wei, Ye Yanyao, Qi Chao, Han Mei, Chen Xiaohui, Zhu Xun, Deng Yun, Zhang Liangliang, Chen Hengyi, Zhang Haoran, Gao Weiyin, Liu Yao, Luo Yang

机构信息

Center of Smart Laboratory and Molecular Medicine, School of Medicine, Chongqing University, Chongqing 400044, People's Republic of China.

College of Bioengineering, Chongqing University, Chongqing 400044, People's Republic of China.

出版信息

ACS Nano. 2021 Apr 27;15(4):7649-7658. doi: 10.1021/acsnano.1c01215. Epub 2021 Apr 19.

Abstract

Accurate and rapid blood typing plays a vital role in a variety of biomedical and forensic scenarios, but recognizing weak agglutination remains challenging. Herein, we demonstrated a flipping identification with a prompt error-discrimination (FLIPPED) platform for automatic blood group readouts. Bromocresol green dye was exploited as a characteristic chromatography indicator for the differentiation of plasma from whole blood by presenting a teal color against a brown color. After integrating these color changes into a quick-response (QR) code, prompt typing of ABO and Rhesus groups was automatically achieved and data could be uploaded wirelessly within 30 s using a commercially available smartphone to facilitate blood cross-matching. We further designed a color correction model and algorithm to remove potential errors from scanning angles and ambient light intensities, by which weak agglutination could be accurately recognized. With comparable accuracy and repeatability to classical column assay in grouping 450 blood samples, the proposed approach further demonstrates to be a versatile sample-to-result platform for clinical diagnostics, food safety, and environmental monitoring.

摘要

准确快速的血型鉴定在各种生物医学和法医场景中起着至关重要的作用,但识别微弱凝集仍然具有挑战性。在此,我们展示了一种用于自动血型读数的具有即时错误判别功能的翻转识别(FLIPPED)平台。利用溴甲酚绿染料作为特征性色谱指示剂,通过呈现蓝绿色与棕色形成对比,来区分血浆和全血。将这些颜色变化整合到一个二维码中后,即可自动实现ABO和Rh血型的快速鉴定,并且使用商用智能手机可在30秒内无线上传数据,以促进血液交叉配型。我们还设计了一种颜色校正模型和算法,以消除扫描角度和环境光强度带来的潜在误差,借此能够准确识别微弱凝集。在对450份血样进行血型分组时,该方法具有与经典柱式检测相当的准确性和可重复性,进一步证明是一个适用于临床诊断、食品安全和环境监测的通用型从样本到结果的平台。

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