In this study, a flow injection analysis (FIA) system with enzymatic detection was proposed for determination of citrate in urine using a lab-made microfluidic chip. A microfluidic device based on polydimethylsiloxane (PDMS) channels was designed and fabricated. And the analytical variables of this method, such as accuracy, precision and interference factors, have been discussed. Furthermore, in order to determinate the citrate concentration in real samples, three univariate calibration models with different standard solutions of citrate and one partial least squares regression (PLSR) model using near ultraviolet (NUV) spectroscopy were established, and the predictive performance of the proposed models was evaluated externally by making the correlation analysis between prediction values and reference values from capillary electrophoresis (CE) of citrate level in real urine samples. The correlation coefficients of three univariate models were 0.9989, 0.9955 and 0.9976 within the range from 0.1 mM to 6 mM and the root-mean-square error of prediction (RMSEP) for univariate models and PLSR model were 0.65 mM and 0.40 mM, respectively. The models were validated and the values of correlation coefficients of prediction found for univariate and multivariate models were 0.85 and 0.88, respectively. Results indicate that multivariate calibration based on NUV/PLS method has improved the practicability greatly comparing with the univariate regression in urinary citrate analysis because of its high sensitivity and validity of prediction. What's more, combining with the advantages of enzymatic detection and microfluidic chip, this method looks more promising in the complex biomedical analysis without tedious pretreatments.
Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Surfaces, Coatings and Films
- Metals and Alloys
- Electrical and Electronic Engineering
- Materials Chemistry