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A fluorescent lateral flow biosensor for the quantitative detection of Vaspin using upconverting nanoparticles
Muhsin Ali1, Memoon Sajid2, Muhammad Asad Ullah Khalid1
1Department of Mechatronics Engineering, Jeju National University, Jeju, South Korea.
Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
|October 14, 2019
Summary
This study introduces a novel fluorescent biosensor for detecting Vaspin, a protein linked to type-2 diabetes. The ultrasensitive, aptamer-based assay offers a low-cost method for early disease diagnosis.
Area of Science:
- Biomedical Engineering
- Analytical Chemistry
- Biochemistry
Background:
- Vaspin is a serum protein implicated in type-2 diabetes, obesity, and cardiovascular diseases.
- Early and accurate detection of Vaspin is crucial for managing these conditions.
- Existing detection methods may lack the sensitivity or cost-effectiveness required for widespread screening.
Purpose of the Study:
- To develop an ultrasensitive lateral flow biosensor for Vaspin detection.
- To utilize fluorescent upconverting nanoparticles (UCNPs) for enhanced signal amplification.
- To provide a low-cost and rapid diagnostic tool for early type-2 diabetes detection.
Main Methods:
- A lateral flow biosensor was designed using a pair of cognate aptamers for Vaspin detection.
- Upconverting nanoparticles (UCNPs) were conjugated to a secondary aptamer (detection probe).
- A primary aptamer (capture probe) was immobilized on the test zone, enabling a sandwich-type assay.
Main Results:
- The UCNPs-based biosensor demonstrated ultrasensitive detection of Vaspin.
- A wide detection range of 0.1-55 ng/mL was achieved with a limit of detection (LOD) of 39 pg/mL.
- The assay showed high sensitivity, reproducibility, and repeatability, suitable for clinical application.
Conclusions:
- The developed UCNPs-based lateral flow biosensor is a highly sensitive and cost-effective tool for Vaspin detection.
- This technology enables early diagnosis of type-2 diabetes and related conditions.
- The aptamer-based approach is adaptable for detecting other disease biomarkers.

