Abstract: We apply a particle tracking technique to track the motion of individual pathogenic Leptospira. We observe and capture images of motile Leptospira by means of CCD and darkfield microscope. Image processing, statistical theories and simulations are used for data analysis. Based on trajectory patterns, mean square displacement, and power spectral density characteristics, we found that the motion modes are most likely to be directed motion mode (70%) and the rest are either normal diffusion or unidentified mode. Our findings may support the fact that why leptospires are very well efficient toward targeting internal tissues as a result of increase in virulence factor.
Abstract: In this work, we consider a deterministic model for
the transmission of leptospirosis which is currently spreading in the
Thai population. The SIR model which incorporates the features of
this disease is applied to the epidemiological data in Thailand. It is
seen that the numerical solutions of the SIR equations are in good
agreement with real empirical data. Further improvements are
discussed.
Abstract: Semiconductor nanomaterials like TiO2 nanoparticles
(TiO2-NPs) approximately less than 100 nm in diameter have become
a new generation of advanced materials due to their novel and
interesting optical, dielectric, and photo-catalytic properties. With the
increasing use of NPs in commerce, to date few studies have
investigated the toxicological and environmental effects of NPs.
Motivated by the importance of TiO2-NPs that may contribute to the
cancer research field especially from the treatment prospective
together with the fractal analysis technique, we have investigated the
effect of TiO2-NPs on colony morphology in the dark condition
using fractal dimension as a key morphological characterization
parameter. The aim of this work is mainly to investigate the cytotoxic
effects of TiO2-NPs in the dark on the growth of human cervical
carcinoma (HeLa) cell colonies from morphological aspect. The in
vitro studies were carried out together with the image processing
technique and fractal analysis. It was found that, these colonies were
abnormal in shape and size. Moreover, the size of the control
colonies appeared to be larger than those of the treated group. The
mean Df +/- SEM of the colonies in untreated cultures was
1.085±0.019, N= 25, while that of the cultures treated with TiO2-NPs
was 1.287±0.045. It was found that the circularity of the control
group (0.401±0.071) is higher than that of the treated group
(0.103±0.042). The same tendency was found in the diameter
parameters which are 1161.30±219.56 μm and 852.28±206.50 μm
for the control and treated group respectively. Possible explanation of
the results was discussed, though more works need to be done in
terms of the for mechanism aspects. Finally, our results indicate that
fractal dimension can serve as a useful feature, by itself or in
conjunction with other shape features, in the classification of cancer
colonies.
Abstract: The study of non-equilibrium systems has attracted
increasing interest in recent years, mainly due to the lack of
theoretical frameworks, unlike their equilibrium counterparts.
Studying the steady state and/or simple systems is thus one of the
main interests. Hence in this work we have focused our attention on
the driven lattice gas model (DLG model) consisting of interacting
particles subject to an external field E. The dynamics of the system
are given by hopping of particles to nearby empty sites with rates
biased for jumps in the direction of E. Having used small two
dimensional systems of DLG model, the stochastic properties at nonequilibrium
steady state were analytically studied. To understand the
non-equilibrium phenomena, we have applied the analytic approach
via master equation to calculate probability function and analyze
violation of detailed balance in term of the fluctuation-dissipation
theorem. Monte Carlo simulations have been performed to validate
the analytic results.
Abstract: We present analysis of spatial patterns of generic
disease spread simulated by a stochastic long-range correlation SIR
model, where individuals can be infected at long distance in a power
law distribution. We integrated various tools, namely perimeter,
circularity, fractal dimension, and aggregation index to characterize
and investigate spatial pattern formations. Our primary goal was to
understand for a given model of interest which tool has an advantage
over the other and to what extent. We found that perimeter and
circularity give information only for a case of strong correlation–
while the fractal dimension and aggregation index exhibit the growth
rule of pattern formation, depending on the degree of the correlation
exponent (β). The aggregation index method used as an alternative
method to describe the degree of pathogenic ratio (α). This study may
provide a useful approach to characterize and analyze the pattern
formation of epidemic spreading
Abstract: The dynamics of Min proteins plays a center role in
accurate cell division. Although the nucleoids may presumably play
an important role in prokaryotic cell division, there is a lack of
models to account for its participation. In this work, we apply the
lattice Boltzmann method to investigate protein oscillation based on a
mesoscopic model that takes into account the nucleoid-s role. We
found that our numerical results are in reasonably good agreement
with the previous experimental results On comparing with the other
computational models without the presence of nucleoids, the
highlight of our finding is that the local densities of MinD and MinE
on the cytoplasmic membrane increases, especially along the cell
width, when the size of the obstacle increases, leading to a more
distinct cap-like structure at the poles. This feature indicated the
realistic pattern and reflected the combination of Min protein
dynamics and nucleoid-s role.