Geminally biotinylated cyclotriphosphazenes as molecular binding probe

Biotinylated cyclotriphosphazenes polymer (g-BTP) with germinal octopus-like molecular shape has been prepared and characterized by 31P-NMR, 1H-NMR and Matrix-assisted laser desorption ionization-time of flight-mass spectrometry (Maldi-Tof-Ms). Analysis of the size distribution of the complexes showed that the aggregated g-BTP/avidin complexes were rather polydispersed and uniform as compared to complexes formed by random coil biotinylated linear polymer (BLP) and avidin. Binding kinetics studies show that both of g-BTP and BLP can bind avidin very quickly. The binding ability as evaluated by Scatchard plot indicates the binding ability of g-BTP to be about 5.5 times that of BLP

Construction and Synergistic Effect of Recombinant Yeast Co-expressing Pig IL-2/4/6 on Immunity of Piglets to PRRS Vaccination

AbstractIn order to develop cost-effective immunomodulator, the recombinant Pichia pastoris were firstly constructed to co-express porcine IL-2/4/6 genes, and then fermented to feed 45-days Tibetan piglets at different doses to evaluate its effects on immunity of piglets to PRRS vaccination, which simultaneously received intramuscular injection of inactivated PRRS vaccine. The results were found that the leukocytes, IgG and specific antibody to PRRSV, Th and Tc cells increased significantly in the blood of treated piglets in comparison with those of the control (P<0.05); the mRNA expression of TLRs (TLR-2, 3, 4, 7, 9), IFN-γ, IL-2, IL-4, IL-6, IL-7, IL-12 and IL-15 genes were elevated significantly in the immune cells from the blood of treated piglets (P<0.05). Moreover, the growth of the treated piglets also markedly improved whose average net weight gain was significantly higher than the control on 58 days post inoculation (P<0.05). These results suggest that the recombinant yeast can effectively enhance the systematic innate and adaptive immunity of piglets as well as promote the growth of piglet, which could be further developed as cost-effective promising immunomodulator to improve the control of pig PRRS disease

Bulk flow of halos in \Lambda CDM simulation

Analysis of the Pangu N-body simulation validates that the bulk flow of halos follows a Maxwellian distribution which variance is consistent with the prediction of the linear theory of structure formation. We propose that the consistency between the observed bulk velocity and theories should be examined at the effective scale of the radius of a spherical top-hat window function yielding the same smoothed velocity variance in linear theory as the sample window function does. We compared some recently estimated bulk flows from observational samples with the prediction of the \Lambda CDM model we used; some results deviate from expectation at a level of ~ 3\sigma but the discrepancy is not as severe as previously claimed. We show that bulk flow is only weakly correlated with the dipole of the internal mass distribution, the alignment angle between the mass dipole and the bulk flow has a broad distribution peaked at ~ 30-50 deg., and also that the bulk flow shows little dependence on the mass of the halos used in the estimation. In a simulation of box size 1Gpc/h, for a cell of radius 100 Mpc/h the maximal bulk velocity is >500 km/s, dipoles of the environmental mass outside the cell are not tightly aligned with the bulk flow, but are rather located randomly around it with separation angles ~ 20-40 deg. In the fastest cell there is a slightly smaller number of low-mass halos; however halos inside are clustered more strongly at scales > ~ 20 Mpc/h, which might be a significant feature since the correlation between bulk flow and halo clustering actually increases in significance beyond such scales.Comment: Expanded discussion on effect of selection function, in together with other minor revision. ApJ in pres

Low hepatitis B surface antigen and HBV DNA levels predict response to the addition of pegylated interferon to entecavir in hepatitis B e antigen positive chronic hepatitis B

Background: Various treatment combinations of peginterferon (PEG‐IFN) and nucleos(t)ide analogues have been evaluated for chronic hepatitis B (CHB), but the optimal regimen remains unclear. Aims: To study whether PEG‐IFN add‐on increases response compared to entecavir (ETV) monotherapy, and whether the duration of ETV pretreatment influences response. Methods: Response was evaluated in HBeAg positive patients previously treated in two randomized controlled trials. Patients received ETV pretreatment for at least 24 weeks and were then allocated to 24‐48 weeks of ETV+PEG‐IFN add‐on, or continued ETV monotherapy. Response was defined as HBeAg loss combined with HBV DNA <200 IU/mL 48 weeks after discontinuing PEG‐IFN. Results: Of 234 patients, 118 were assigned PEG‐IFN add‐on and 116 continued ETV monotherapy. Response was observed in 38/118 (33%) patients treated with add‐on therapy and in 23/116 (20%) with monotherapy (P = 0.03). The highest response to add‐on therapy compared to monotherapy was observed in PEG‐IFN naive patients with HBsAg levels below 4000 IU/mL and HBV DNA levels below 50 IU/mL at randomization (70% vs 34%; P = 0.01). Above the cut‐off levels, response was low and not significantly different between treatment groups. Duration of ETV pretreatment was associated with HBsAg and HBV DNA levels (both P < 0.005), but not with response (P = 0.82). Conclusions: PEG‐IFN add‐on to ETV therapy was associated with higher response compared to ETV monotherapy in patients with HBeAg positive CHB. Response doubled in PEG‐IFN naive patients with HBsAg below 4000 IU/mL and HBV DNA below 50 IU/mL, and therefore identifies them as the best candidates for PEG‐IFN add‐on (Identifiers: NCT00877760, NCT01532843)

an implementation of parallel eigenvalue computation using dual-level hybrid parallelism

This paper describes a hybrid two-level parallel method with MPI/OpenMP for computing the eigenvalues of dense symmetric matrices on cluster of SMPs environments. The eigenvalue computation is Based on both the Householder tridiagonalization method and

LTmatch: A Method to Abstract Pattern from Unstructured Log

Logs record valuable data from different software and systems. Execution logs are widely available and are helpful in monitoring, examination, and system understanding of complex applications. However, log files usually contain too many lines of data for a human to deal with, therefore it is important to develop methods to process logs by computers. Logs are usually unstructured, which is not conducive to automatic analysis. How to categorize logs and turn into structured data automatically is of great practical significance. In this paper, LTmatch algorithm is proposed, which implements a log pattern extracting algorithm based on a weighted word matching rate. Compared with our preview work, this algorithm not only classifies the logs according to the longest common subsequence(LCS) but also gets and updates the log template in real-time. Besides, the pattern warehouse of the algorithm uses a fixed deep tree to store the log patterns, which optimizes the matching efficiency of log pattern extraction. To verify the advantages of the algorithm, we applied the proposed algorithm to the open-source data set with different kinds of labeled log data. A variety of state-of-the-art log pattern extraction algorithms are used for comparison. The result shows our method is improved by 2.67% in average accuracy when compared with the best result in all the other methods