Surface Engineered Nanoparticles Coupled with Pattern Recognition Techniques for Rapid Identification and...

Area of Science:

• Analytical Chemistry
• Biochemistry
• Materials Science

Background:

• Thiols, including Cysteine (CYS) and Glutathione (GSH), are vital biomolecules involved in physiological processes.
• Altered thiol levels are linked to diseases like Alzheimer's and Parkinson's, highlighting the need for accurate detection.
• Reliable thiol analysis is essential for early disease diagnosis and ensuring food safety.

Purpose of the Study:

• To develop and characterize a novel sensor for the detection and discrimination of various thiols.
• To utilize metal ion-decorated organic nanoparticles for sensitive thiol analysis.
• To establish a robust method for thiol detection applicable to food safety.

Main Methods:

• Decoration of organic nanoparticles with metal ions.
• Characterization using Dynamic Light Scattering (DLS), Zeta potential, FTIR, XPS, and TEM.
• Detection and discrimination of thiols using photophysical analysis, Linear Discrimination Analysis (LDA), and Hierarchical Clustering Analysis (HCA).

Main Results:

• Metal ion-decorated organic nanoparticles were successfully synthesized and characterized.
• Each thiol exhibited unique binding affinities, creating distinct "fingerprints" for identification.
• The sensor array achieved 100% accuracy in discriminating target thiols with high sensitivity (LOD 1.19–4.20 μM).

Conclusions:

• The developed sensor provides a simple, rapid, sensitive, and stable method for thiol detection.
• This technology shows significant promise for enhancing food safety and enabling early disease detection.
• The unique thiol "fingerprints" allow for quantitative differentiation and accurate analysis.