Overweight and obesity promote diabetes and heart disease onset. Triglycerides are key biomarkers for cardiovascular disease, strokes, and other health issues. Scientists have devised methods and instruments for the detection of these molecules in liquid samples. In this study, an enzymatic biosensor was developed using an Arduino-based microfluidic platform, wherein a lipolytic enzyme was immobilized on an ethylene-vinyl acetate polymer through physical adsorption. This low-cost optical biosensor employed a spectrophotometric transducer and was assessed in liquid samples to indirectly detect triglycerides and fatty acids using p-nitrophenol as an indicator. The average triglyceride level detected in the conducted experiments was 47.727 mg/dL. The biosensor exhibited a percentage of recovery of 81.12% and a variation coefficient of 0.791%. Furthermore, the biosensor demonstrated the ability to detect triglyceride levels without the need for sample dilution, ranging from 7.6741 mg/dL to 58.835 mg/dL. This study successfully developed an efficient and affordable enzymatic biosensor prototype for triglyceride and fatty acid detection. The lipolytic enzyme immobilization on the polymer substrate provided a stable and reproducible detection system, rendering this biosensor an exciting option for the detection of these molecules.
Keywords: arduino; enzymatic biosensor; lipase enzyme; microfluidic; optical detector; spectrophotometric transducer; triglycerides.