314 research outputs found

    Visible-light-driven Ag/Bi3O4Cl nanocomposite photocatalyst with enhanced photocatalytic activity for degradation of tetracycline

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    In this study, a novel Ag/Bi3O4Cl photocatalyst has been synthesized by a facile photodeposition process. Its photocatalytic performance was evaluated from the degradation of tetracycline (TC) under visible light irradiation (λ > 420 nm). The 1.0 wt% Ag/Bi3O4Cl photocatalyst could significantly enhance the degradation of TC compared with pure Bi3O4Cl, with the degradation level reaching 94.2% in 120 minutes. The enhancement of photocatalytic activity could be attributed to the synergetic effect of the photogenerated electrons (e−) of Bi3O4Cl and the surface plasmon resonance (SPR) caused by Ag nanoparticles, which could improve the absorption capacity of visible light and facilitate the separation of photogenerated electron–hole pairs. In addition, electron spin resonance (ESR) analysis and trapping experiments demonstrated that the superoxide radicals (˙O2−), hydroxyl radicals (˙OH) and holes (h+) played crucial roles in the photocatalytic process of TC degradation. The present work provides a promising approach for the development of highly efficient photocatalysts to address current environmental pollution, energy issues and other related areas

    Anomaly Discovery and Arbitrage Trading

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    Our model of anomaly discovery has implications for both asset prices and arbitrageurs\u27 trading. Consistent with existing evidence, the discovery of an anomaly reduces its magnitude. Our evidence based on 99 anomalies is consistent with new predictions that the discovery of an anomaly reduces the correlation between the returns its deciles 1 and 10, leading to diversification benefits for passive investors. These effects become linked to the aggregate trading of hedge funds only after discovery. Hedge funds increase (reverse) their positions in exploiting anomalies when their aggregate wealth increases (decreases), further suggesting that these discovery effects operate through arbitrage trading

    Engineering Clostridium Strain to Accept Unmethylated DNA

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    It is difficult to genetically manipulate the medically and biotechnologically important genus Clostridium due to the existence of the restriction and modification (RM) systems. We identified and engineered the RM system of a model clostridial species, C. acetobutylicum, with the aim to allow the host to accept the unmethylated DNA efficiently. A gene CAC1502 putatively encoding the type II restriction endonuclease Cac824I was identified from the genome of C. acetobutylicum DSM1731, and disrupted using the ClosTron system based on group II intron insertion. The resulting strain SMB009 lost the type II restriction endonuclease activity, and can be transformed with unmethylated DNA as efficiently as with methylated DNA. The strategy reported here makes it easy to genetically modify the clostridial species using unmethylated DNA, which will help to advance the understanding of the clostridial physiology from the molecular level

    Adipose-derived mesenchymal stem cells improve glucose homeostasis in high-fat diet-induced obese mice

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    Introduction Effective therapies for obesity and diabetes are still lacking. The aim of this study was to evaluate whether a single intravenous infusion of syngeneic adipose-derived mesenchymal stem cells (ASCs) can reduce obesity, lower insulin resistance, and improve glucose homeostasis in a high-fat diet-induced obese (DIO) mouse model. Methods Seven-week-old C57BL/6 mice were fed a high-fat diet for 20 weeks to generate the DIO mouse model. Mice were given a single intravenous infusion of ex vivo expanded syngeneic ASCs at 2 × 10 6 cells per mouse. DIO or CHOW mice injected with saline were used as controls. Body weights, blood glucose levels, glucose, and insulin tolerance test results were obtained before and 2 and 6 weeks after cell infusion. Triglyceride (TG), high-density lipoprotein (HDL), and insulin levels in serum were measured. Expressions of genes related to insulin resistance, including peroxisome proliferator-activated receptor γ (PPARγ) and insulin receptor (InsR), and inflammation (IL-6, F4/80, and nucleotide-binding oligomerization domain containing 2, or NOD2), were measured in livers at mRNA level by real-time-polymerase chain reaction analysis. Beta-cell mass in pancrheases from CHOW, DIO, and DIO + ASC mice was quantified. GFP + ASCs were injected, and the presence of GFP + cells in livers and pancreases was determined. Results DIO mice that had received ASCs showed reduced body weights, reduced blood glucose levels, and increased glucose tolerance. ASC treatment was found to reduce TG levels and increase serum HDL levels. In livers, less fat cell deposition was observed, as were increased expression of InsR and PPARγ and reduction in expressions of IL-6 and F4/80. Treated mice showed well-preserved pancreatic β-cell mass with reduced expression of F4/80 and TNF-α compared with DIO controls. GFP + cells were found in liver and pancreas tissues at 1 and 2 weeks after cell injection. Conclusions ASC therapy is effective in lowering blood glucose levels and increasing glucose tolerance in DIO mice. The protective effects of ASCs arise at least in part from suppression of inflammation in the liver. In addition, ASCs are associated with better-preserved pancreatic β-cell mass

    SPIDer: Saccharomyces protein-protein interaction database

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    BACKGROUND: Since proteins perform their functions by interacting with one another and with other biomolecules, reconstructing a map of the protein-protein interactions of a cell, experimentally or computationally, is an important first step toward understanding cellular function and machinery of a proteome. Solely derived from the Gene Ontology (GO), we have defined an effective method of reconstructing a yeast protein interaction network by measuring relative specificity similarity (RSS) between two GO terms. DESCRIPTION: Based on the RSS method, here, we introduce a predicted Saccharomyces protein-protein interaction database called SPIDer. It houses a gold standard positive dataset (GSP) with high confidence level that covered 79.2% of the high-quality interaction dataset. Our predicted protein-protein interaction network reconstructed from the GSPs consists of 92 257 interactions among 3600 proteins, and forms 23 connected components. It also provides general links to connect predicted protein-protein interactions with three other databases, DIP, BIND and MIPS. An Internet-based interface provides users with fast and convenient access to protein-protein interactions based on various search features (searching by protein information, GO term information or sequence similarity). In addition, the RSS value of two GO terms in the same ontology, and the inter-member interactions in a list of proteins of interest or in a protein complex could be retrieved. Furthermore, the database presents a user-friendly graphical interface which is created dynamically for visualizing an interaction sub-network. The database is accessible at . CONCLUSION: SPIDer is a public database server for protein-protein interactions based on the yeast genome. It provides a variety of search options and graphical visualization of an interaction network. In particular, it will be very useful for the study of inter-member interactions among a list of proteins, especially the protein complex. In addition, based on the predicted interaction dataset, researchers could analyze the whole interaction network and associate the network topology with gene/protein properties based on a global or local topology view

    Phylogenetic inference of calyptrates, with the first mitogenomes for Gasterophilinae (Diptera: Oestridae) and Paramacronychiinae (Diptera: Sarcophagidae)

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    The complete mitogenome of the horse stomach bot fly Gasterophilus pecorum (Fabricius) and a near-complete mitogenome of Wohlfahrt's wound myiasis fly Wohlfahrtia magnifica (Schiner) were sequenced. The mitogenomes contain the typical 37 mitogenes found in metazoans, organized in the same order and orientation as in other cyclorrhaphan Diptera. Phylogenetic analyses of mitogenomes from 38 calyptrate taxa with and without two non-calyptrate outgroups were performed using Bayesian Inference and Maximum Likelihood. Three sub-analyses were performed on the concatenated data: (1) not partitioned; (2) partitioned by gene; (3) 3rd codon positions of protein-coding genes omitted. We estimated the contribution of each of the mitochondrial genes for phylogenetic analysis, as well as the effect of some popular methodologies on calyptrate phylogeny reconstruction. In the favoured trees, the Oestroidea are nested within the muscoid grade. Relationships at the family level within Oestroidea are (remaining Calliphoridae (Sarcophagidae (Oestridae, Pollenia + Tachinidae))). Our mito-phylogenetic reconstruction of the Calyptratae presents the most extensive taxon coverage so far, and the risk of long-branch attraction is reduced by an appropriate selection of outgroups. We find that in the Calyptratae the ND2, ND5, ND1, COIII, and COI genes are more phylogenetically informative compared with other mitochondrial protein-coding genes. Our study provides evidence that data partitioning and the inclusion of conserved tRNA genes have little influence on calyptrate phylogeny reconstruction, and that the 3rd codon positions of protein-coding genes are not saturated and therefore should be included

    A New Model for Predicting Dynamic Surge Pressure in Gas and Drilling Mud Two-Phase Flow during Tripping Operations

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    Investigation of surge pressure is of great significance to the circulation loss problem caused by unsteady operations in management pressure drilling (MPD) operations. With full consideration of the important factors such as wave velocity, gas influx rate, pressure, temperature, and well depth, a new surge pressure model has been proposed based on the mass conservation equations and the momentum conservation equations during MPD operations. The finite-difference method, the Newton-Raphson iterative method, and the fourth-order explicit Runge-Kutta method (R-K4) are adopted to solve the model. Calculation results indicate that the surge pressure has different values with respect to different drill pipe tripping speeds and well parameters. In general, the surge pressure tends to increase with the increases of drill pipe operating speed and with the decrease of gas influx rate and wellbore diameter. When the gas influx occurs, the surge pressure is weakened obviously. The surge pressure can cause a significant lag time if the gas influx occurs at bottomhole, and it is mainly affected by pressure wave velocity. The maximum surge pressure may occur before drill pipe reaches bottomhole, and the surge pressure is mainly affected by drill pipe operating speed and gas influx rate
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