An insulin monitoring device based on hyphenation between molecularly imprinted micro-solid phase extraction and...

Area of Science:

• Analytical Chemistry
• Materials Science
• Biomedical Engineering

Background:

• Accurate insulin detection is crucial for managing diabetes mellitus.
• Existing methods for ultra-trace insulin detection often lack sensitivity or specificity.
• Molecularly imprinted polymers (MIPs) offer selective recognition capabilities for target analytes.

Purpose of the Study:

• To develop a sensitive and selective molecularly imprinted micro-solid phase extraction (MIP-µSPE) fiber for insulin detection.
• To compare two different grafting methods for MIP film preparation on silica fibers.
• To evaluate the performance of the developed MIP-µSPE fiber, alone and in combination with a complementary sensor, for insulin monitoring in real biological samples.

Main Methods:

• Development of MIP-µSPE fibers using "grafting via surface attached monomer" (Method I) and "grafting via sol-gel" (Method II) approaches.
• Characterization of MIP film properties and evaluation of extraction efficiency.
• Determination of insulin detection limits (LOD) and relative standard deviation (RSD) for both methods.
• Hyphenation of the optimized MIP-µSPE technique with a complementary sensor for enhanced detection.

Main Results:

• Method I (surface attached monomer) demonstrated significantly higher sensitivity for insulin detection (LOD = 0.009 ng/mL) compared to Method II (LOD = 0.064 ng/mL, RSD = 1.21%).
• Neither MIP-µSPE nor the complementary sensor alone was sufficient for monitoring stringent insulin levels in real samples.
• The hyphenated device achieved high detection sensitivity for ultra-trace insulin in human blood serum and Huminsulin injection without non-specific contributions.

Conclusions:

• The "grafting via surface attached monomer" approach is superior for developing sensitive MIP-µSPE fibers for insulin detection.
• A hyphenated MIP-µSPE and sensor system provides a robust platform for accurate ultra-trace insulin quantification.
• This technology holds potential as a marker for assessing the risk of type 2 diabetes mellitus and insulin resistance-related complications.