Empowering Gliadin Detection: A Visible-Code Semiquantitative Lateral Flow System for Rapid and Reliable Results

Area of Science:

• Food Science
• Biotechnology
• Analytical Chemistry

Background:

• Celiac disease affects 1% of the population, necessitating strict gluten-free diets.
• Gliadin, a gluten protein, is the primary celiac trigger and is hard to detect due to low solubility.
• Current gluten detection methods are often slow and lack portability, complicating dining out for celiac patients.

Purpose of the Study:

• To develop a rapid, portable, and accurate gluten detection system for celiac disease management.
• To overcome the challenges posed by gliadin's low solubility in food matrices.
• To provide a user-friendly tool for identifying hidden gluten in food products.

Main Methods:

• Development of LEO (Lateral flow Enhanced by Optical imaging) system.
• Integration of lateral flow assays with smartphone-based image analysis.
• Utilized IoT-enhanced technology for real-time data processing.

Main Results:

• LEO provides gluten detection results in under 3 minutes.
• Achieved over 98% accuracy and sensitivity below the FDA's 20 ppm threshold for gliadin quantification.
• Successfully identified hidden gluten in mislabeled "gluten-free" restaurant dishes during real-world trials.

Conclusions:

• LEO is a fast, accurate, and user-friendly system for detecting gluten.
• The technology enhances food safety for individuals with celiac disease.
• LEO is suitable for diverse applications including personal, clinical, industrial, and regulatory use.