A Paper Strip-Based Photoinduced Electrogenerated Chemiluminescence Platform with CTF/PMo12 Heterojunction-Sensitive
Reza Sedghi Mehrbani1, Mehdi Mohhamadian1, Kheibar Dashtian1
1Research Laboratory of Spectrometry & Micro and Nano Extraction, Department of Chemistry, Iran University of Science and Technology, Tehran 16846-13114, Iran.
This study introduces a novel photoinduced electrogenerated chemiluminescence (PECL) test strip for detecting glutamic acid (GA), a key neurotransmitter. The developed method offers sensitive, on-site monitoring for neurological disease diagnostics.
Area of Science:
- Electrochemistry
- Chemiluminescence
- Materials Science
Background:
- Glutamic acid (GA) is a vital neurotransmitter implicated in brain function and neurological disorders.
- Elevated GA levels correlate with conditions like stroke, Parkinson's, epilepsy, and Alzheimer's disease.
- Accurate GA detection is crucial for diagnosis and research.
Purpose of the Study:
- To develop a sensitive and selective photoinduced electrogenerated chemiluminescence (PECL) test strip for glutamic acid detection.
- To integrate the PECL system with smartphone technology for on-site, real-time monitoring.
- To validate the method's safety and feasibility for biological samples.
Main Methods:
- Fabrication of a test strip fiber paper using a covalent triazine framework (CTF)/polyoxometalate (PMo12) heterojunction.
- Utilizing blue-light irradiation and an electric field to drive PECL reactions based on luminol oxidation for GA detection.
- Employing smartphone-based fluorometry to capture PECL signals and RGB values.
Main Results:
- Achieved sensitive detection of GA within a linear range of 0.05-1.7 mM.
- Established a low limit of detection (LOD) of 15 nM for GA.
- Demonstrated satisfactory selectivity for GA detection in biological samples.
Conclusions:
- The PECL test strip offers a safe, feasible, and sensitive method for GA detection.
- Smartphone integration enables on-site, visual, real-time monitoring.
- This approach is suitable for high-throughput point-of-care testing and disease monitoring.
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