Abstract: The potential of antioxidant activities of the plant
extract Gynura procumbens, Achyranthes aspera and Polygenum
tomentosum were studied by using 1, 1-diphenyl-2-picrylhydrazyl
(DPPH) .Antioxidant activity was qualitatively and quantitatively
determined. In this analysis , Ascorbic acid (Vitamin C) was used as
the standard .The antioxidant activities were observed all three plant
extracts and the EC50 values of G procumbens A.aspera and
P.tomemtosum were 13.7 μg /ml,14.37 μg /ml and 14.35 μg /ml.
Among these plants, G.procumbens is more potent antioxidant
activity then others. Antitumor activities were found with A.aspera
(s2) extracts in the dose of 100ppm in carrot disks and G.procumbens
(s1) and P.tomentosum (s3) in the dose of 1000 ppm. Therefore, these
herbal plants are used in traditional medicines.
Abstract: We present a label-free biosensor based on
electrochemical impedance spectroscopy for the detection of proinflammatory
cytokine Tumor Necrosis Factor (TNF-α). Secretion of
TNF-α has been correlated to the onset of various diseases including
rheumatoid arthritis, Crohn-s disease etc. Gold electrodes were
patterned on a silicon substrate and self assembled monolayer of
dithiobis-succinimidyl propionate was used to develop the biosensor
which achieved a detection limit of ~57fM. A linear relationship was
also observed between increasing TNF-α concentrations and chargetransfer
resistance within a dynamic range of 1pg/ml – 1ng/ml.
Abstract: The ability to distinguish missense nucleotide
substitutions that contribute to harmful effect from those that do not
is a difficult problem usually accomplished through functional in
vivo analyses. In this study, instead current biochemical methods, the
effects of missense mutations upon protein structure and function
were assayed by means of computational methods and information
from the databases. For this order, the effects of new missense
mutations in exon 5 of PTEN gene upon protein structure and
function were examined. The gene coding for PTEN was identified
and localized on chromosome region 10q23.3 as the tumor
suppressor gene. The utilization of these methods were shown that
c.319G>A and c.341T>G missense mutations that were recognized in
patients with breast cancer and Cowden disease, could be pathogenic.
This method could be use for analysis of missense mutation in others
genes.
Abstract: A systems approach model for prostate cancer in prostate duct, as a sub-system of the organism is developed. It is accomplished in two steps. First this research work starts with a nonlinear system of coupled Fokker-Plank equations which models continuous process of the system like motion of cells. Then extended to PDEs that include discontinuous processes like cell mutations, proliferation and deaths. The discontinuous processes is modeled by using intensity poisson processes. The model incorporates the features of the prostate duct. The system of PDEs spatial coordinate is along the proximal distal axis. Its parameters depend on features of the prostate duct. The movement of cells is biased towards distal region and mutations of prostate cancer cells is localized in the proximal region. Numerical solutions of the full system of equations are provided, and are exhibit traveling wave fronts phenomena. This motivates the use of the standard transformation to derive a canonically related system of ODEs for traveling wave solutions. The results obtained show persistence of prostate cancer by showing that the non-negative cone for the traveling wave system is time invariant. The traveling waves have a unique global attractor is proved also. Biologically, the global attractor verifies that evolution of prostate cancer stem cells exhibit the avascular tumor growth. These numerical solutions show that altering prostate stem cell movement or mutation of prostate cancer cells lead to avascular tumor. Conclusion with comments on clinical implications of the model is discussed.
Abstract: In this paper we present a method for gene ranking
from DNA microarray data. More precisely, we calculate the correlation
networks, which are unweighted and undirected graphs, from
microarray data of cervical cancer whereas each network represents
a tissue of a certain tumor stage and each node in the network
represents a gene. From these networks we extract one tree for
each gene by a local decomposition of the correlation network. The
interpretation of a tree is that it represents the n-nearest neighbor
genes on the n-th level of a tree, measured by the Dijkstra distance,
and, hence, gives the local embedding of a gene within the correlation
network. For the obtained trees we measure the pairwise similarity
between trees rooted by the same gene from normal to cancerous
tissues. This evaluates the modification of the tree topology due to
progression of the tumor. Finally, we rank the obtained similarity
values from all tissue comparisons and select the top ranked genes.
For these genes the local neighborhood in the correlation networks
changes most between normal and cancerous tissues. As a result
we find that the top ranked genes are candidates suspected to be
involved in tumor growth and, hence, indicates that our method
captures essential information from the underlying DNA microarray
data of cervical cancer.
Abstract: Quantitative measurements of tumor in general and tumor volume in particular, become more realistic with the use of Magnetic Resonance imaging, especially when the tumor morphological changes become irregular and difficult to assess by clinical examination. However, tumor volume estimation strongly depends on the image segmentation, which is fuzzy by nature. In this paper a fuzzy approach is presented for tumor volume segmentation based on the fuzzy connectedness algorithm. The fuzzy affinity matrix resulting from segmentation is then used to estimate a fuzzy volume based on a certainty parameter, an Alpha Cut, defined by the user. The proposed method was shown to highly affect treatment decisions. A statistical analysis was performed in this study to validate the results based on a manual method for volume estimation and the importance of using the Alpha Cut is further explained.