(526f) Detection of Glucose and Related Analytes by Biosensors: a Fractal Analysis

A fractal analysis is used to model the binding and dissociation kinetics of connective tissue interstitial glucose, adipose tissue interstitial glucoses, insulin, and other related analytes on biosensor surfaces. The analysis provides insights into diffusion-limited analyte-receptor reactions occurring on heterogeneous biosensor surfaces. Numerical values obtained for the binding and the dissociation rate coefficients are linked to the degree of heterogeneity or roughness (fractal dimension, Df) present on the biosensor chip surface. The binding and the dissociation rate coefficients are sensitive to the degree of heterogeneity on the surface. For example, for the binding of plasma insulin, as the fractal dimension value increases by a factor of 2.47 from Df1 equal to 0.6827 to Df2 equal to 1.6852, the binding rate coefficient increases by a factor of 4.92 from k1 equal to 1.0232 to k2 equal to 5.0388. An increase in the degree of heterogeneity on the probe surface leads to an increase in the binding rate coefficient. A dual-fractal analysis is required to fit the binding kinetics in most of the cases presented. A single fractal analysis is adequate to describe the dissociation kinetics. Affinity (ratio of the binding to the dissociation rate coefficient) values are also presented. Interferents for glucose like uric acid, and ascorbic acid were also detected using glucose biosensors based on carbon nanotube (CNT) nanoelectrode ensembles (NEEs) (Lin et al., 2004).

It is suggested that the roughness on the biosensor surface leads to turbulence which enhances mixing and decreases diffusional limitations leading to an increase in the binding rate coefficient (Martin et al., 1991). The analysis also indicates that along with glucose similar compounds like insulin, acetaminophen, ascorbic acid, and uric acid can also be detected on the same biosensor surface. This may be useful for other diagnosis such as diabetic urine, etc.