ArticleMicrosystems & nanoengineering2021
Touchable cell biophysics property recognition platforms enable multifunctional blood smart health care.
Article in Microsystems & nanoengineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 26 citations in OpenAlex.
- Innovations in skin microphysiological systems for nonclinical testing and FDA modernization.Microsystems & nanoengineering · 2026Review
- A Miniature Modular Fluorescence Flow Cytometry System.Biosensors · 2024Article
- A microfluidic hemostatic diagnostics platform: Harnessing coagulation-induced adaptive-bubble behavioral perception.Cell reports. Medicine · 2023Article
- Design and Fabrication of a Fully-Integrated, Miniaturised Fluidic System for the Analysis of Enzyme Kinetics.Micromachines · 2023Article
- Portable Prussian Blue-Based Sensor for Bacterial Detection in Urine.Sensors (Basel, Switzerland) · 2022Article
- Space-time-regulated imaging analyzer for smart coagulation diagnosis.Cell reports. Medicine · 2022Article
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Authors and funding
19 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.