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Rapid Fluorescence-based Characterization of Single Extracellular Vesicles in Human Blood with Nanoparticle-tracking Analysis
Published on: January 7, 2019
Atomic Fe-Centered Hemin-TiO2 Graphdiyne Nanozyme Sensor for Colorimetric Fingerprinting of Bacterial Extracellular
Jianyu Yang1,2, Xingchen Qiu1, Ruian Tang1
1School of Materials Science and Engineering, Suzhou University of Science and Technology, Suzhou 215009, China.
This study introduces a rapid colorimetric sensor for identifying urinary tract infection pathogens. The novel nanozyme sensor achieves 100% diagnostic accuracy in 30 minutes for point-of-care use.
Area of Science:
- Biomaterials Science
- Nanotechnology
- Analytical Chemistry
Background:
- Accurate identification of urinary pathogens is crucial for managing urinary tract infections (UTIs).
- Bacterial extracellular vesicles (bEVs) are promising diagnostic targets due to pathogen-specific surface antigens.
- Current bEV isolation methods are time-consuming (up to 72 hours), hindering clinical application.
Purpose of the Study:
- To develop a rapid and accurate method for identifying bEVs directly from urine samples.
- To overcome the limitations of traditional bEV isolation techniques for UTI diagnostics.
- To create a point-of-care diagnostic platform for UTIs.
Main Methods:
- Invented a three-dimensional biomimetic nanozyme (TiO2 nanoparticles-bridged Hemin on graphdiyne) for selective bEV capture and enhanced peroxidase-like activity.
- Utilized the nanozyme's specific coordination interactions with lipopolysaccharide O-antigens on bEVs for recognition.
- Employed a colorimetric approach with pH-dependent activity suppression and machine learning for bEV subtype classification.
Main Results:
- The nanozyme selectively captured bEVs and exhibited pH-dependent peroxidase-like activity.
- Distinctive colorimetric fingerprints were generated upon bEV recognition.
- The platform achieved 100.0% diagnostic accuracy within 30 minutes in clinical validations.
Conclusions:
- The intelligent colorimetric sensor array enables rapid and accurate identification of bEVs in UTIs.
- This technology significantly reduces diagnostic time compared to conventional methods.
- The developed platform shows great promise for point-of-care UTI management.
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