Antiviral treatment alters the frequency of activating and inhibitory receptor-expressing natural killer cells in chronic Hepatitis B virus infected patients

Natural killer (NK) cells play a critical role in innate antiviral immunity, but little is known about the impact of antiviral therapy on the frequency of NK cell subsets. To this aim, we performed this longitudinal study to examine the dynamic changes of the frequency of different subsets of NK cells in CHB patients after initiation of tenofovir or adefovir therapy. We found that NK cell numbers and subset distribution differ between CHB patients and normal subjects; furthermore, the association was found between ALT level and CD158b+ NK cell in HBV patients. In tenofovir group, the frequency of NK cells increased during the treatment accompanied by downregulated expression of NKG2A and KIR2DL3. In adefovir group, NK cell numbers did not differ during the treatment, but also accompanied by downregulated expression of NKG2A and KIR2DL3. Our results demonstrate that treatment with tenofovir leads to viral load reduction, and correlated with NK cell frequencies in peripheral blood of chronic hepatitis B virus infection. In addition, treatments with both tenofovir and adefovir in chronic HBV infected patients induce a decrease of the frequency of inhibitory receptor+ NK cells, which may account for the partial restoration of the function of NK cells in peripheral blood following treatment

New Insights into Traffic Dynamics: A Weighted Probabilistic Cellular Automaton Model

From the macroscopic viewpoint for describing the acceleration behavior of drivers, this letter presents a weighted probabilistic cellular automaton model (the WP model, for short) by introducing a kind of random acceleration probabilistic distribution function. The fundamental diagrams, the spatio-temporal pattern are analyzed in detail. It is shown that the presented model leads to the results consistent with the empirical data rather well, nonlinear velocity-density relationship exists in lower density region, and a new kind of traffic phenomenon called neo-synchronized flow is resulted. Furthermore, we give the criterion for distinguishing the high-speed and low-speed neo-synchronized flows and clarify the mechanism of this kind of traffic phenomena. In addition, the result that the time evolution of distribution of headways is displayed as a normal distribution further validates the reasonability of the neo-synchronized flow. These findings suggest that the diversity and randomicity of drivers and vehicles has indeed remarkable effect on traffic dynamics.Comment: 12 pages, 5 figures, submitted to Europhysics Letter

Diversity of eukaryotic plankton of aquaculture ponds with Carassius auratus gibelio, using denaturing gradient gel electrophoresis

PCR-denaturing gradient gel electrophoresis (DGGE) and canonical correspondence analysis (CCA) were used to explore the relationship between eukaryotic plankton community succession and environmental factors in two aquaculture pond models with gibel carp Carassius auratus gibelio. The main culture species of pond 1 were gibel carp and grass carp, and the combined density was 46224 fingerling/ha (gibel carp/grass carp/silver carp/bighead carp, 17:4:6:1). The main culture species of pond 2 was gibel carp, and the combined density was 37551 fingerling/ha (gibel carp/silver carp/bighead carp, 52:1:1). Water samples were collected monthly. The results showed that the annual average concentrations of TP and PO_4-P in pond 1 were significantly higher than pond 2 (p>0.05). The concentration of chlorophyll a (chl a) has no significantly difference between pond 1 and pond 2. DGGE profiles of 18S rRNA gene fragments from the two ponds revealed that the diversity of eukaryotic plankton assemblages was highly variable. 91 bands and 71 bands were detected in pond 1 and pond 2, respectively. The average Shannon–Wiener index of pond 1 was significantly higher than pond 2. Canonical correspondence analysis (CCA) revealed that temperature played a key role in the structure of the eukaryotic plankton community in both ponds, but the nutrient concentration did not affect it. Our results suggest that DGGE method is a cost-effective way to gain insight into seasonal dynamics of eukaryotic plankton communities in culture ponds, and the increase in the number of filter-feeding silver carp and bighead carp could increase the diversity of the eukaryotic plankton community

Thermosensitive nanofibers loaded with ciprofloxacin as antibacterial wound dressing materials

To obtain wound dressings which could be removed easily without secondary injuries, we prepared thermoresponsive electrospun fiber mats containing poly(di(ethylene glycol) methyl ether methacrylate) (PDEGMA). Blend fibers of PDEGMA and poly(l-lactic acid-co-ε-caprolactone) (P(LLA-CL) were fabricated via electrospinning, and analogous fibers containing the antibiotic ciprofloxacin (CIF) were also prepared. Smooth cylindrical fibers were obtained, albeit with a small amount of beading visible for the ciprofloxacin-loaded fibers. X-ray diffraction showed the drug to exist in the amorphous physical form post-electrospinning. The composite fibers showed distinct thermosensitive properties and gave sustained release of CIF over more than 160h in vitro. The fibers could promote the proliferation of fibroblasts, and by varying the temperature cells could easily be attached to and detached from the fibers. Antibacterial tests demonstrated that fibers loaded with ciprofloxacin were effective in inhibiting the growth of E. coli and S. aureus. In vivo investigations on rats indicated that the composite PDEGMA/P(LLA-CL) fibers loaded with CIF had much more potent wound healing properties than a commercial gauze and CIF-loaded fibers made solely of P(LLA-CL). These results demonstrate the potential of PDEGMA/P(LLA-CL)/ciprofloxacin fibers as advanced wound dressing materials

Observation of two distinct dxz/dyzd_{xz}/d_{yz} band splittings in FeSe

We report the temperature evolution of the detailed electronic band structure in FeSe single-crystals measured by angle-resolved photoemission spectroscopy (ARPES), including the degeneracy removal of the $d_{xz}$ and $d_{yz}$ orbitals at the $\Gamma$/Z and M points, and the orbital-selective hybridization between the $d_{xy}$ and $d_{xz/yz}$ orbitals. The temperature dependences of the splittings at the $\Gamma$/Z and M points are different, indicating that they are controlled by different order parameters. The splitting at the M point is closely related to the structural transition and is attributed to orbital ordering defined on Fe-Fe bonds with a $d$-wave form in the reciprocal space that breaks the rotational symmetry. In contrast, the band splitting at the $\Gamma$ points remains at temperature far above the structural transition. Although the origin of this latter splitting remains unclear, our experimental results exclude the previously proposed ferro-orbital ordering scenario.Comment: 5 pages, 3 figures. New title. Abstract and introduction modifie

Solving 0-1 Knapsack Problem by Greedy Degree and Expectation Efficiency

It is well known that 0-1 knapsack problem (KP01) plays an important role in both computing theory and real life application. Due to its NP-hardness, lots of impressive research work has been performed on many variants of the problem. Inspired by region partition of items, an effective hybrid algorithm based on greedy degree and expectation efficiency (GDEE) is presented in this paper. In the proposed algorithm, initially determinate items region, candidate items region and unknown items region are generated to direct the selection of items. A greedy degree model inspired by greedy strategy is devised to select some items as initially determinate region. Dynamic expectation efficiency strategy is designed and used to select some other items as candidate region, and the remaining items are regarded as unknown region. To obtain the final items to which the best profit corresponds, static expectation efficiency strategy is proposed whilst the parallel computing method is adopted to update the objective function value. Extensive numerical investigations based on a large number of instances are conducted. The proposed GDEE algorithm is evaluated against chemical reaction optimization algorithm and modified discrete shuffled frog leaping algorithm. The comparative results show that GDEE is much more effective in solving KP01 than other algorithms and that it is a promising tool for solving combinatorial optimization problems such as resource allocation and production scheduling