Biomedical Engineering Reference
In-Depth Information
It is of interest to compare the chronic monitoring of glucose
in vivo
using a functionalized
hydrogel-optical fiber biosensor (
Tierney et al., 2009a,b
) with the chronic monitoring of glu-
cose
in vivo
using a percutaneous fiber-optic sensor (
Liao et al., 2008
). Both cases involve
in vivo
monitoring, but two different biosensor techniques are involved. It is important to
mention at the outset, that some of the differences in the binding rate coefficients and fractals
that may arise because of the details in the biosensor monitoring techniques that are involved,
are not presented or accounted for here. However, both cases to be considered and compared
involve the use of dual-fractal analysis, necessary to adequately model the binding kinetics.
It is of interest to note that when a dual-fractal analysis is used, and for the initial phase of
binding as one goes from the hydrogel fiber-optic biosensor (
Tierney et al., 2009a,b
) to the
percutaneous fiber-optic sensor for the continuous glucose monitoring
in vivo
(
Liao et al.,
2008
), the fractal dimension decreases from a value of 1.6830 to 0.7854, and the binding rate
coefficient,
k
1
, however, increases from a rather low value of 0.009881 (
Tierney et al., 2009a,
b
) to 9.509 (
Liao et al., 2008
). This trend is differently presented, in general, throughout the
different chapters in the topic, when the same analyte-receptor biosensor system is being ana-
lyzed. In this case, however, clearly two different analyte-receptor biosensor systems are
being analyzed and compared (which is the purpose of this chapter) and hence that general
trend is not followed.
Similarly, for the second phase of binding as one goes from the hydrogel-fiber-optic biosen-
sor at 25
C(
Tierney e al., 2009a,b
) to the percutaneous fiber-optic sensor for continuous
glucose monitoring
in vivo
(
Liao et al., 2008
), the fractal dimension,
D
f2
, increases very
slightly from a value of 2.8498 to 2.8938 (a change in the third decimal place), and the bind-
ing rate coefficient,
k
2
, exhibits a very substantial change in value from a value of 0.5569 to
19.975. A very small change in the fractal dimension value leads to about a 34 times change
in the binding rate coefficient. This is primarily attributed to the different analyte-receptor
biosensor systems being compared and analyzed.
It is of interest to compare the binding of glucose in a hydrogel fiber-optic biosensor at 37
C
(
Tierney et al., 2009a,b
) to a disposable fiber-optic biosensor (
Lee et al., 2008
). The binding
curve in both these cases is adequately described by a single-fractal analysis. It is seen that as
one goes from the hydrogel fiber-optic biosensor to the disposable glucose biosensor the frac-
tal dimension increases slightly from a value of 2.4497 to 2.8849, the binding rate coefficient
increases by a factor of 100.59 from a value of 0.1819 to 29.942. A small change in the
degree of heterogeneity or the fractal dimension on the biosensor surface leads to an increase
of more than two orders of magnitude in the binding rate coefficient. Once again, a change in
the analyte-receptor biosensor system leads to a very significant change in the binding rate
coefficient even though the change in the degree of heterogeneity on the biosensor surface
is small. In this case, the disposable glucose biosensor exhibits the higher binding rate coef-
ficient, which should be helpful in the monitoring of glucose levels in diabetic patients.
