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Published on: June 23, 2016
Uricase biofunctionalized plasmonic sensor for uric acid detection with APTES-modified gold nanotopping
Olabisi Abdullahi Onifade1, Fatin Adriena Yusairie2, Muhammad Hafiz Abu Bakar1
1Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia; Wireless and Photonics Research Centre of Excellence, Faculty of Engineering, Universiti Putra Malaysia, 43400, Serdang Selangor, Malaysia.
This study developed a highly sensitive plasmonic sensor for detecting uric acid at the point-of-care. The biofunctionalized sensor demonstrates excellent selectivity and potential for revolutionizing clinical diagnostics.
Area of Science:
- Biosensing and Nanotechnology
- Biomedical Engineering
- Analytical Chemistry
Background:
- Current uric acid detection methods lack sensitivity and selectivity for point-of-care use.
- Plasmonic sensors show promise but require performance enhancements for clinical applications.
Purpose of the Study:
- To develop a biofunctionalized sensor using surface plasmon resonance for quantifying uric acid at physiologically relevant concentrations.
- To improve the sensitivity and selectivity of plasmonic sensors for uric acid detection.
Main Methods:
- Covalent immobilization of uricase enzyme onto the sensor probe using EDC/NHS crosslinking agents.
- Characterization using atomic force microscopy and Fourier transform infrared spectroscopy.
- Analysis of binding kinetics using the Langmuir adsorption isotherm model.
Main Results:
- The sensor demonstrated a high binding affinity (298.83 (mg/dL)-1) and sensitivity (0.0755°/(mg/dL)).
- Achieved a low limit of detection (0.095 mg/dL) and excellent selectivity against common interferents.
- A distinct resonance angle shift of 0.3706° was observed for 0.5 mg/dL uric acid, differentiating it from interferents.
Conclusions:
- The biofunctionalized plasmonic sensor significantly enhances uric acid detection capabilities.
- This technology holds promise for clinical diagnostics and point-of-care applications, potentially transforming healthcare outcomes.
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