3D-Printed PLA Hollow Microneedles Loaded with Chitosan Nanoparticles for Colorimetric Glucose Detection in Sweat...

Area of Science:

• Biomedical Engineering
• Analytical Chemistry
• Materials Science

Background:

• Diabetes management relies on accurate glucose monitoring.
• Current methods can be invasive, necessitating less invasive alternatives.
• Biosensors offer a promising avenue for continuous and accessible glucose level detection.

Purpose of the Study:

• To develop a novel 3D-printed colorimetric biosensor for glucose detection in sweat.
• To integrate microneedles and chitosan nanoparticles for enhanced glucose sensing.
• To utilize machine learning for accurate glucose concentration prediction from colorimetric data.

Main Methods:

• Fabrication of hollow 3D-printed polylactic acid microneedles loaded with chitosan nanoparticles.
• Encapsulation of glucose oxidase, horseradish peroxidase, and a chromogenic substrate within nanoparticles.
• Colorimetric glucose detection using smartphone imaging and a color recognition application, with data analyzed by a Random Sample Consensus algorithm for linear regression modeling.

Main Results:

• The biosensor demonstrated a linear response range of 0.025–0.375 mM for glucose.
• Achieved a low limit of detection (0.023 mM) and limit of quantification (0.078 mM).
• Exhibited high specificity and recovery rates between 86–112% in spiked artificial sweat samples.

Conclusions:

• The developed 3D-printed microneedle biosensor offers a viable, less invasive approach for glucose detection in sweat.
• The integration of chitosan nanoparticles, microneedles, and machine learning enhances sensing capabilities.
• This technology holds significant potential for practical application in diabetes monitoring and management.