Biomedical Engineering Reference
In-Depth Information
approach to develop optimal structures and as a predictive approach. Another advantage of
the fractal technique is that the analyte-receptor association (as well as the dissociation reac-
tion) is a complex reaction, and the fractal analysis via the fractal dimension and the rate
coefficient provides a useful lumped parameter(s) analysis of the diffusion-limited reaction
occurring on a heterogeneous surface.
In a classical situation, to demonstrate fractality, one should make a log-log plot, and one
should definitely have a large amount of data. It may be useful to compare the fit to some
other forms, such as exponential, or one involving saturation, etc. At present, no independent
proof or physical evidence of fractals in the examples is presented. It is a convenient means
(since it is a lumped parameter) to make the degree of heterogeneity that exists on the surface
more quantitative. Thus, there is some arbitrariness in the fractal model to be presented. The
fractal approach provides additional information about interactions that may not be obtained
by conventional analysis of biosensor data.
There is no nonselective adsorption of the analyte. The present system (environmental
pollutants in the aqueous or the gas phase) being analyzed may be typically very dilute. Non-
selective adsorption would skew the results obtained very significantly. In these types of sys-
tems, it is imperative to minimize this nonselective adsorption. It is also recognized that, in
some cases, this nonselective adsorption may not be a significant component of the adsorbed
material and that this rate of association, which is of a temporal nature, would depend on sur-
face availability. If the nonselective adsorption is to be accommodated into the model, there
would be an increase in the heterogeneity on the surface, as, by its very nature, nonspecific
adsorption is more heterogeneous than specific adsorption. This would lead to higher fractal
dimension values since the fractal dimension is a direct measure of the degree of heterogene-
ity that exists on the surface.
Yoo et al. (2007)
report that the use of living test organisms is a good and reliable method to
analyze the toxicity of unknown samples. They point out that methods that incorporate bio-
luminescent bacteria are able to reliably detect unknown toxicity in water, soil, and sediment
samples. For example, Kim and Gu (2003), and
Lee et al. (2005)
were able to achieve high
throughput toxicity classification using different
E. coli
strains in a single 96-well plate or
the 386-well plate using a Luria-Bertani (LB)-agar matrix.
You et al. (2004)
have developed
a photolithography-based process of cell immobilization using polyvinyl alcohol-
styrylpyridinium (PVA-SbQ) (a water-soluble and negative photosensitive polymer). They
have used this PVA-SbQ for bioluminescent bacteria, and have applied this to fabricating cel-
lular patterns in the microfluidic chip for toxicity monitoring. The emitted light intensity of
bioluminescent bacteria changed in response to the presence of chemicals. Thus, the bacteria
may be used as a toxicity indicator.
Yoo et al. (2007)
obtained a dose-dependent bioluminescent response (binding) of different
concentrations of phenol in the 0-21.28 mM range in solution to the immobilized cells on
