4.8 Article

Flipped Quick-Response Code Enables Reliable Blood Grouping

Journal

ACS NANO
Volume 15, Issue 4, Pages 7649-7658

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acsnano.1c01215

Keywords

blood grouping; microfluidic analytical techniques; quick response code; immunologic tests; optical imaging

Funding

  1. National Natural Science Foundation of China [82072383, 81871733, 81670100, 81772061]
  2. Fundamental Research Funds for the Central Universities [2019CDYGZD005, 2019CDXYSG0004]
  3. Open Foundation of Key Laboratory of Wuliangye-flavor Liquor Solid-state Fermentation, China National Light Industry [2019JJ003]
  4. Key Natural Science Foundation of Chongqing [CSTC2020JCYJ-ZDXMX0006, CSTC2016SHMSZTZX10005]
  5. Key Natural Science Foundation of Chongqing Education Commission [KJZD-M202000101]
  6. Postgraduate Supervisor Team Funds for the Chongqing Education Commission [YDSTD1924]

Ask authors/readers for more resources

Accurate and rapid blood typing is crucial in various medical and forensic situations, and a new FLIPPED platform utilizing color changes and QR codes was demonstrated to achieve automatic blood group identification. A color correction model and algorithm were also designed to remove errors from scanning angles and ambient light intensities, improving accuracy in identifying weak agglutination. This approach showed comparable accuracy and repeatability to traditional methods, making it a versatile platform for clinical diagnostics, food safety, and environmental monitoring.
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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available