IgE-Associated IGHV Genes from Venom and Peanut Allergic Individuals Lack Mutational Evidence of Antigen Selection

Antigen selection of B cells within the germinal center reaction generally leads to the accumulation of replacement mutations in the complementarity-determining regions (CDRs) of immunoglobulin genes. Studies of mutations in IgE-associated VDJ gene sequences have cast doubt on the role of antigen selection in the evolution of the human IgE response, and it may be that selection for high affinity antibodies is a feature of some but not all allergic diseases. The severity of IgE-mediated anaphylaxis is such that it could result from higher affinity IgE antibodies. We therefore investigated IGHV mutations in IgE-associated sequences derived from ten individuals with a history of anaphylactic reactions to bee or wasp venom or peanut allergens. IgG sequences, which more certainly experience antigen selection, served as a control dataset. A total of 6025 unique IgE and 5396 unique IgG sequences were generated using high throughput 454 pyrosequencing. The proportion of replacement mutations seen in the CDRs of the IgG dataset was significantly higher than that of the IgE dataset, and the IgE sequences showed little evidence of antigen selection. To exclude the possibility that 454 errors had compromised analysis, rigorous filtering of the datasets led to datasets of 90 core IgE sequences and 411 IgG sequences. These sequences were present as both forward and reverse reads, and so were most unlikely to include sequencing errors. The filtered datasets confirmed that antigen selection plays a greater role in the evolution of IgG sequences than of IgE sequences derived from the study participants.

Serum levels of soluble receptor for advanced glycation end products and of S100 proteins are associated with inflammatory, autoantibody, and classical risk markers of joint and vascular damage in rheumatoid arthritis

Introduction: The receptor for advanced glycation end products (RAGE) is a member of the immunoglobulin superfamily of cell surface receptor molecules. High concentrations of three of its putative proinflammatory ligands, S100A8/A9 complex (calprotectin), S100A8, and S100A12, are found in rheumatoid arthritis (RA) serum and synovial fluid. In contrast, soluble RAGE (sRAGE) may prevent proinflammatory effects by acting as a decoy. This study evaluated the serum levels of S100A9, S100A8, S100A12 and sRAGE in RA patients, to determine their relationship to inflammation and joint and vascular damage. Methods: Serum sRAGE, S100A9, S100A8 and S100A12 levels from 138 patients with established RA and 44 healthy controls were measured by ELISA and compared by unpaired t test. In RA patients, associations with disease activity and severity variables were analyzed by simple and multiple linear regressions. Results: Serum S100A9, S100A8 and S100A12 levels were correlated in RA patients. S100A9 levels were associated with body mass index (BMI), and with serum levels of S100A8 and S100A12. S100A8 levels were associated with serum levels of S100A9, presence of anti-citrullinated peptide antibodies (ACPA), and rheumatoid factor (RF). S100A12 levels were associated with presence of ACPA, history of diabetes, and serum S100A9 levels. sRAGE levels were negatively associated with serum levels of C-reactive protein (CRP) and high-density lipoprotein (HDL), history of vasculitis, and the presence of the RAGE 82Ser polymorphism. Conclusions: sRAGE and S100 proteins were associated not just with RA inflammation and autoantibody production, but also with classical vascular risk factors for end-organ damage. Consistent with its role as a RAGE decoy molecule, sRAGE had the opposite effects to S100 proteins in that S100 proteins were associated with autoantibodies and vascular risk, whereas sRAGE was associated with protection against joint and vascular damage. These data suggest that RAGE activity influences co-development of joint and vascular disease in rheumatoid arthritis patients.

MnOx/carbon nanotube/reduced graphene oxide nanohybrids as high-performance supercapacitor electrodes

Nanohybrids consisting of both carbon and pseudocapacitive metal oxides are promising as high-performance electrodes to meet the key energy and power requirements of supercapacitors. However, the development of high-performance nanohybrids with controllable size, density, composition and morphology remains a formidable challenge. Here, we present a simple and robust approach to integrating manganese oxide (MnOx) nanoparticles onto flexible graphite paper using an ultrathin carbon nanotube/reduced graphene oxide (CNT/RGO) supporting layer. Supercapacitor electrodes employing the MnOx/CNT/RGO nanohybrids without any conductive additives or binders yield a specific capacitance of 1070 F g−1 at 10 mV s−1, which is among the highest values reported for a range of hybrid structures and is close to the theoretical capacity of MnOx. Moreover, atmospheric-pressure plasmas are used to functionalize the CNT/RGO supporting layer to improve the adhesion of MnOx nanoparticles, which results in theimproved cycling stability of the nanohybrid electrodes. These results provide information for the utilization of nanohybrids and plasma-related effects to synergistically enhance the performance of supercapacitors and may create new opportunities in areas such as catalysts, photosynthesis and electrochemical sensors

Ortho-Dihydroxyl-9,10-anthraquinone dyes as visible-light sensitizers that exhibit a high turnover number for hydrogen evolution

Pt/TiO2 sensitized by the cheap and organic ortho-dihydroxyl-9,10-anthraquinone dyes, such as Alizarin and Alizarin Red, achieved a TON of approximately 10 000 (TOF > 250 h−1 for the first ten hours) during >80 hours of visible light irradiation (>420 nm) for photocatalytic hydrogen evolution when triethanolamine was used as the sacrificial donor. The stability and activity enhancements can be attributed to the two highly serviceable redox reactions involving the 9,10-dicarbonyl and ortho-dihydroxyl groups of the anthracene ring, respectively

Mathematical modeling for improved greenhouse gas balances, agro-ecosystems, and policy development: Lessons from the Australian experience

If the land sector is to make significant contributions to mitigating anthropogenic greenhouse gas (GHG) emissions in coming decades, it must do so while concurrently expanding production of food and fiber. In our view, mathematical modeling will be required to provide scientific guidance to meet this challenge. In order to be useful in GHG mitigation policy measures, models must simultaneously meet scientific, software engineering, and human capacity requirements. They can be used to understand GHG fluxes, to evaluate proposed GHG mitigation actions, and to predict and monitor the effects of specific actions; the latter applications require a change in mindset that has parallels with the shift from research modeling to decision support. We compare and contrast 6 agro-ecosystem models (FullCAM, DayCent, DNDC, APSIM, WNMM, and AgMod), chosen because they are used in Australian agriculture and forestry. Underlying structural similarities in the representations of carbon flows though plants and soils in these models are complemented by a diverse range of emphases and approaches to the subprocesses within the agro-ecosystem. None of these agro-ecosystem models handles all land sector GHG fluxes, and considerable model-based uncertainty exists for soil C fluxes and enteric methane emissions. The models also show diverse approaches to the initialisation of model simulations, software implementation, distribution, licensing, and software quality assurance; each of these will differentially affect their usefulness for policy-driven GHG mitigation prediction and monitoring. Specific requirements imposed on the use of models by Australian mitigation policy settings are discussed, and areas for further scientific development of agro-ecosystem models for use in GHG mitigation policy are proposed.

Identification of bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei reveals distinct temperature-driven patterns

Change in temperature is often a major environmental factor in triggering waterborne disease outbreaks. Previous research has revealed temporal and spatial patterns of bacterial population in several aquatic ecosystems. To date, very little information is available on aquaculture environment. Here, we assessed environmental temperature effects on bacterial community composition in freshwater aquaculture system farming of Litopenaeus vannamei (FASFL). Water samples were collected over a one-year period, and aquatic bacteria were characterized by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and 16S rDNA pyrosequencing. Resulting DGGE fingerprints revealed a specific and dynamic bacterial population structure with considerable variation over the seasonal change, suggesting that environmental temperature was a key driver of bacterial population in the FASFL. Pyrosequencing data further demonstrated substantial difference in bacterial community composition between the water at higher (WHT) and at lower (WLT) temperatures in the FASFL. Actinobacteria, Proteobacteria and Bacteroidetes were the highest abundant phyla in the FASFL, however, a large number of unclassified bacteria contributed the most to the observed variation in phylogenetic diversity. The WHT harbored remarkably higher diversity and richness in bacterial composition at genus and species levels when compared to the WLT. Some potential pathogenenic species were identified in both WHT and WLT, providing data in support of aquatic animal health management in the aquaculture industry.

Dissimilarities in alignment-free methods for phylogenetic analysis based on genomes

Whole genome sequences are generally accepted as excellent tools for studying evolutionary relationships. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignments could not be directly applied to the whole-genome comparison and phylogenomic studies. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. The “distances” used in these alignment-free methods are not proper distance metrics in the strict mathematical sense. In this study, we first review them in a more general frame — dissimilarity. Then we propose some new dissimilarities for phylogenetic analysis. Last three genome datasets are employed to evaluate these dissimilarities from a biological point of view.

Perpendicularly oriented MoSe2/graphene nanosheets as advanced electrocatalysts for hydrogen evolution

By increasing the density of exposed active edges, the perpendicularly oriented structure of MoSe2 nanosheets facilitates ion/electrolyte transport at the electrode interface and minimizes the restacking of nanosheets, while the graphene improves the electrical contact between the catalyst and the electrode. This makes the MoSe2/graphene hybrid perfect as a catalyst in the hydrogen evolution reaction (HER). It shows a greatly improved catalytic activity compared with bare MoSe2 nanosheets.

Preparation of magnetic porous ceramsite and its application in biological aerated filters

Ceramsite plays a significant role as a biological aerated filter (BAF) in the treatment of wastewater. In this study, a mixture of goethite, sawdust and palygorskite clay was thermally treated to form magnetic porous ceramsite (MPC). An optimization experiment was conducted to measure the compressive strength of the MPC. X-ray diffraction (XRD), scanning electron microscopy (SEM), and polarizing microscopy (PM) characterized the pore structure of the MPC. The results show that a combination of goethite, sawdust and palygorskite clay with a mass ratio of 10:2:5 is suitable for the formation of MPC. The compressive strength of MPC conforms to the Chinese national industrial standard (CJ/T 299-2008) for wastewater treatment. The SEM and PM results also show that the uniform and interconnected pores in MPC were well suited for microbial growth. The MPC produced in this study can serve as a biomedium for advanced wastewater treatment.

Visible light enhanced oxidant free dehydrogenation of aromatic alcohols using Au-Pd alloy nanoparticle catalysts

We find that visible light irradiation of gold–palladium alloy nanoparticles supported on photocatalytically inert ZrO2 significantly enhances their catalytic activity for oxidant-free dehydrogenation of aromatic alcohols to the corresponding aldehydes at ambient temperatures. Dehydrogenation is also the dominant process in the selective oxidation of the alcohols to the corresponding aldehydes with molecular oxygen. The alloy nanoparticles strongly absorb light and exhibit superior catalytic and photocatalytic activity when compared to either pure palladium or gold nanoparticles. Analysis with a free electron gas model for the bulk alloy structure reveals that the alloying increases the surface charge heterogeneity on the alloy particle surface, which enhances the interaction between the alcohol molecules and the metal NPs. The increased surface charge heterogeneity of the alloy particles is confirmed with density function theory applied to small alloy clusters. Optimal catalytic activity was observed with a Au : Pd molar ratio of 1 : 186, which is in good agreement with the theoretical analysis. The rate-determining step of the dehydrogenation is hydrogen abstraction. The conduction electrons of the nanoparticles are photo-excited by the incident light giving them the necessary energy to be injected into the adsorbed alcohol molecules, promoting the hydrogen abstraction. The strong chemical adsorption of alcohol molecules facilitates this electron transfer. The results show that the alloy nanoparticles efficiently couple thermal and photonic energy sources to drive the dehydrogenation. These findings provide useful insight into the design of catalysts that utilize light for various organic syntheses at ambient temperatures.

FlexAnalytics: A flexible data analytics framework for big data applications with I/O performance improvement

Increasingly larger scale applications are generating an unprecedented amount of data. However, the increasing gap between computation and I/O capacity on High End Computing machines makes a severe bottleneck for data analysis. Instead of moving data from its source to the output storage, in-situ analytics processes output data while simulations are running. However, in-situ data analysis incurs much more computing resource contentions with simulations. Such contentions severely damage the performance of simulation on HPE. Since different data processing strategies have different impact on performance and cost, there is a consequent need for flexibility in the location of data analytics. In this paper, we explore and analyze several potential data-analytics placement strategies along the I/O path. To find out the best strategy to reduce data movement in given situation, we propose a flexible data analytics (FlexAnalytics) framework in this paper. Based on this framework, a FlexAnalytics prototype system is developed for analytics placement. FlexAnalytics system enhances the scalability and flexibility of current I/O stack on HEC platforms and is useful for data pre-processing, runtime data analysis and visualization, as well as for large-scale data transfer. Two use cases – scientific data compression and remote visualization – have been applied in the study to verify the performance of FlexAnalytics. Experimental results demonstrate that FlexAnalytics framework increases data transition bandwidth and improves the application end-to-end transfer performance.

Multifractal analyses of daily rainfall time series in Pearl River basin of China

The multifractal properties of daily rainfall time series at the stations in Pearl River basin of China over periods of up to 45 years are examined using the universal multifractal approach based on the multiplicative cascade model and the multifractal detrended fluctuation analysis (MF-DFA). The results from these two kinds of multifractal analyses show that the daily rainfall time series in this basin have multifractal behavior in two different time scale ranges. It is found that the empirical multifractal moment function K(q)K(q) of the daily rainfall time series can be fitted very well by the universal multifractal model (UMM). The estimated values of the conservation parameter HH from UMM for these daily rainfall data are close to zero indicating that they correspond to conserved fields. After removing the seasonal trend in the rainfall data, the estimated values of the exponent h(2)h(2) from MF-DFA indicate that the daily rainfall time series in Pearl River basin exhibit no long-term correlations. It is also found that K(2)K(2) and elevation series are negatively correlated. It shows a relationship between topography and rainfall variability.

Expression of high mobility group box 1 in inflamed dental pulp and its chemotactic effect on dental pulp cells

High mobility group box 1 protein (HMGB1) is a chromatin protein which can be released extracellularly, eliciting a pro-inflammatory response and promoting tissue repair process. This study aimed to examine the expression and distribution of HMGB1 and its receptor RAGE in inflamed dental pulp tissues, and to assess its effects on proliferation, migration and cytoskeleton of cultured human dental pulp cells (DPCs). Our data demonstrated that cytoplasmic expression of HMGB1 was observed in inflamed pulp tissues, while HMGB1 expression was confined in the nuclei in healthy dental pulp. The mRNA expression of HMGB1 and RAGE were significantly increased in inflamed pulps. In in vitro cultured DPCs, expression of HMGB1 in both protein and mRNA level was up-regulated after treated with lipopolysaccharide (LPS). Exogenous HMGB1 enhanced DPCs migration in a dose-dependent manner and induced the reorganization of f-actin in DPCs. Our results suggests that HMGB1 are not only involved in the process of dental pulp inflammation, but also play an important role in the recruitment of dental pulp stem cells, promoting pulp repair and regeneration.

Polysaccharopeptide enhanced the anti-cancer effect of gamma-tocotrienol through activation of AMPK

Background Prostate cancer (PCa) frequently relapses after hormone ablation therapy. Unfortunately, once progressed to the castration resistant stage, the disease is regarded as incurable as prostate cancer cells are highly resistant to conventional chemotherapy. Method We recently reported that the two natural compounds polysaccharopeptide (PSP) and Gamma-tocotrienols (γ-T3) possessed potent anti-cancer activities through targeting of CSCs. In the present study, using both prostate cancer cell line and xenograft models, we seek to investigate the therapeutic potential of combining γ-T3 and PSP in the treatment of prostate cancer. Result We showed that in the presence of PSP, γ-T3 treatment induce a drastic activation of AMP-activated protein kinase (AMPK). This was accompanied with inactivation of acetyl-CoA carboxylase (ACC), as evidenced by the increased phosphorylation levels at Ser 79. In addition, PSP treatment also sensitized cancer cells toward γ-T3-induced cytotoxicity. Furthermore, we demonstrated for the first time that combination of PSP and γ-T3 treaments significantly reduced the growth of prostate tumor in vivo. Conclusion Our results indicate that PSP and γ-T3 treaments may have synergistic anti-cancer effect in vitro and in vivo, which warrants further investigation as a potential combination therapy for the treatment of cancer.