The determination of cystatin C in biological samples via the surface plasmon resonance method

Surface plasmon resonance imaging biosensors have a number of advantages that make them superior to other analytical methods. These include the possibility of label-free detection, speed and high sensitivity to low protein concentrations. The aim of this study was to create and analyze biochips, with the help of which it is possible to test cystatin C in patient urine samples and compare the results with the one-time traditional ELISA method. The main advantage of the surface plasmon resonance imaging method is the possibility of repeated measurements over a long period of time in accordance with clinical practice. The surface of the biochip was spotted with anticystatin C and a negative control of mouse IgG at a ratio of 1:1. The aforementioned biochip was first verified using standard tests and then with patient samples, which clearly confirmed the required sensitivity even for very low concentrations of cystatin C. METHOD SUMMARY Surface plasmon resonance is a sensitive optical method that uses the generation of electromagnetic waves (plasmons) for detection. The propagation of surface plasmons at the metal-dielectric interface is very sensitive to changes in the refractive index, which allows for the monitoring of substance properties very close to the interface. The main advantage of the sensor over other currently used techniques is the possibility of label-free analysis and real-time analysis, with high sensitivity and specificity of the optical method.

Automated summary

Surface plasmon resonance imaging biosensors offer advantages such as label-free detection, high sensitivity to low protein concentrations, and the ability for repeated measurements over time. This study successfully created and analyzed biochips for testing cystatin C in patient urine samples, demonstrating the method's sensitivity even for very low concentrations. The main advantage of surface plasmon resonance imaging is its label-free and real-time analysis capabilities, with high sensitivity and specificity.