Abstract: Identifying the nature of protein-nanoparticle
interactions and favored binding sites is an important issue in
functional characterization of biomolecules and their physiological
responses. Herein, interaction of silver nanoparticles with lysozyme
as a model protein has been monitored via fluorescence spectroscopy.
Formation of complex between the biomolecule and silver
nanoparticles (AgNPs) induced a steady state reduction in the
fluorescence intensity of protein at different concentrations of
nanoparticles. Tryptophan fluorescence quenching spectra suggested
that silver nanoparticles act as a foreign quencher, approaching the
protein via this residue. Analysis of the Stern-Volmer plot showed
quenching constant of 3.73 μM−1. Moreover, a single binding site in
lysozyme is suggested to play role during interaction with AgNPs,
having low affinity of binding compared to gold nanoparticles.
Unfolding studies of lysozyme showed that complex of lysozyme-
AgNPs has not undergone structural perturbations compared to the
bare protein. Results of this effort will pave the way for utilization of
sensitive spectroscopic techniques for rational design of
nanobiomaterials in biomedical applications.
Abstract: Titanium gels doped with water-soluble cationic porphyrin were synthesized by the sol–gel polymerization of Ti (OC4H9)4. In this work we investigate the spectroscopic properties along with SEM images of tetra carboxyl phenyl porphyrin when incorporated into porous matrix produced by the sol–gel technique.
Abstract: A four element prototype phased array surface probe
has been designed and constructed to improve clinical human
prostate spectroscopic data. The probe consists of two pairs of
adjacent rectangular coils with an optimum overlap to reduce the
mutual inductance. The two pairs are positioned on the anterior and
the posterior pelvic region and two couples of varactors at the input
of each coil undertake the procedures of tuning and matching. The
probe switches off and on automatically during the consecutive
phases of the MR experiment with the use of an analog switch that is
triggered by a microcontroller. Experimental tests that were carried
out resulted in high levels of tuning accuracy. Also, the switching
mechanism functions properly for various applied loads and pulse
sequence characteristics, producing only 10 μs of latency.
Abstract: Fourier transform infrared (FT-IR) spectroscopic imaging
is an emerging technique that provides both chemically and
spatially resolved information. The rich chemical content of data
may be utilized for computer-aided determinations of structure and
pathologic state (cancer diagnosis) in histological tissue sections for
prostate cancer. FT-IR spectroscopic imaging of prostate tissue has
shown that tissue type (histological) classification can be performed to
a high degree of accuracy [1] and cancer diagnosis can be performed
with an accuracy of about 80% [2] on a microscopic (≈ 6μm)
length scale. In performing these analyses, it has been observed
that there is large variability (more than 60%) between spectra from
different points on tissue that is expected to consist of the same
essential chemical constituents. Spectra at the edges of tissues are
characteristically and consistently different from chemically similar
tissue in the middle of the same sample. Here, we explain these
differences using a rigorous electromagnetic model for light-sample
interaction. Spectra from FT-IR spectroscopic imaging of chemically
heterogeneous samples are different from bulk spectra of individual
chemical constituents of the sample. This is because spectra not
only depend on chemistry, but also on the shape of the sample.
Using coupled wave analysis, we characterize and quantify the nature
of spectral distortions at the edges of tissues. Furthermore, we
present a method of performing histological classification of tissue
samples. Since the mid-infrared spectrum is typically assumed to
be a quantitative measure of chemical composition, classification
results can vary widely due to spectral distortions. However, we
demonstrate that the selection of localized metrics based on chemical
information can make our data robust to the spectral distortions
caused by scattering at the tissue boundary.