| Optical surface plasmon resonance (SPR) is an efficiently biochemicaldetection technology.The highly significant in surface plasmon resonance is an interdisciplinarytechnology, in which the disciplines of optical engineering, mechanical engineering, electronicengineering and biological chemistry were involved. It has drawn a great deal of attention and hasbeen widely used in Agriculture, Food safety, Environment monitoring, Biomedicine andMedicine screening due to the requirement of no analytic labels. It can be used to monitorrefractive index changes at the proximate surface of the surface plasmon resonance biosensor inreal-time, rapid, and high sensitivity. It is strongly recommended to be used as a biological sensingtechnique on the application study of the interaction of biological molecules. Among the study onthe bimolecular dynamics analysis, a practically useful algorithm for studying the biomolecularinteraction between biological macromolecules and ligands immobilized on the surface of thebiosensor plays an important role in obtaining the surface Plasmon resonance curve.Apattern recognition algorithm for analyzing the optical surface plasmon resonance curve wasintroduced. In the previous studies in our group, the centroid algorithm was applied to obtain theresonance dip produced by optical surface Plasmon resonance when a biological analyte wasinjected through over the surface of the biosensor. This centroid algorithm can get good resultswhen the symmetrical curve occurred. However, the results were not at high accuracy when it wasused to calculate the resonance dip from the asymmetrical optical surface Plasmon resonancecurve. This pattern recognition algorithm for getting the resonance dip from the general opticalsurface Plasmon resonance curve overcame the disadvantages of the centroid algorithm to obtainthe high experimental precision and accuracy.The platform established using the Delphi software has made the biomolecular kinetic analysismore clearly and quickly in optical surface plasmon resonance biosensor due to an excellentgraphical user interface, elastic reusable object-oriented programming language and advanceddatabase technology in Delphi software. The calculation of the resonance dip, the communicationsystem, response unit (RU) signals acquisition, concentration measurements, biomolecular kineticanalysis and sensor grams were designed by the Delphi software. The curves for monitoring thebimolecular interaction in real-time, the resonance dip and the parameters setting were displayedon the screen. The clenbuterol hydrochloride was measured by using the optical surface plasmon resonancebiological analysis system designed by the Delphi software to verify the software platform. Inconsequence, the optical surface plasmon resonance curve, optical surface plasmon resonance RUsignal curve and the concentration measurement curve have been validated, respectively. Thecompetitive immuno reaction method for establishing the standard curve of clenbuterolhydrochloride was used. The experimental results show that the software on analysis of opticalsurface plasmon biological data acquisition and processing greatly meets the design requirementsof portable biological analyzer software and the approach to the resonance dip using the patternrecognition provides a theoretical and practical basis for calculating resonance dip. |
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