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Updated: Feb 12, 2026
10:41
Detection of Toxin Translocation into the Host Cytosol by Surface Plasmon Resonance
Published on: January 3, 2012
13.8K
Next-generation advanced surface plasmon resonance biosensor for dopamine detection with ZnO-ag multilayer design:
Trupti Kamani1, Shobhit K Patel2, Yogesh Sharma3
1Department of Physics, Marwadi University, Rajkot 360003, India.
Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
|February 10, 2026
Summary
This study introduces a novel biosensor for rapid and precise dopamine level detection. The Radial Petal-Loop Pattern Refractive Index Biosensor (RPLPRIB) offers high sensitivity and a low limit of detection for critical health monitoring.
Area of Science:
- Biomedical Engineering
- Biosensor Technology
- Neuroscience
Background:
- Dopamine is a crucial neurotransmitter regulating vital physiological functions.
- Imbalances in dopamine levels are linked to various health issues.
- Accurate dopamine measurement is essential for diagnosing and managing health conditions.
Purpose of the Study:
- To develop a highly sensitive and precise biosensor for dopamine detection.
- To design a novel Radial Petal-Loop Pattern Refractive Index Biosensor (RPLPRIB).
- To evaluate the performance of the RPLPRIB for measuring dopamine components.
Main Methods:
- Design and fabrication of a novel Radial Petal-Loop Pattern Refractive Index Biosensor (RPLPRIB).
- Utilizing refractive index changes for dopamine concentration measurement.
- Application of a machine learning approach for data analysis.
Main Results:
- The RPLPRIB demonstrated high sensitivity (1666.66 nm/RIU) and a low limit of detection (0.000190 RIU).
- Achieved substantial quality factor (2077.66) and sensor range (2108.78 RIU) for dopamine detection.
- Machine learning integration yielded a high R-square value (0.991156) with minimal error.
Conclusions:
- The developed RPLPRIB offers a promising tool for accurate and rapid dopamine level determination.
- The biosensor design enhances substrate binding for improved detection limits.
- This technology has significant potential for clinical diagnostics and health monitoring.
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