Solvent-free catalytic oxidation of benzyl alcohol over Au-Pd bimetal deposited on TiO2: comparison of Rutile, Brookite, and Anatase

TiO2 (P25)-supported Au-Pd bimetal nanoparticles displayed excellent performance in the solvent-free benzyl alcohol catalytic oxidation. However, little research attention has been paid to investigate the effects of TiO2 form on the catalytic activity of Au-Pd/TiO2. In the present research, rutile, brookite, and anatase TiO2 were successfully synthesized and subsequently applied as the carrier to load Au-Pd nanoparticles by the deposition-precipitation method. The experimental results indicated that the benzyl alcohol conversion employing the rutile TiO2-supported Au-Pd catalyst is higher than the conversion of anatase and brookite TiO2-loaded Au-Pd catalysts. However, the Au-Pd/TiO2-rutile displayed the lowest and highest selectivity toward benzaldehyde and toluene, respectively. ICP-AES, XRD, XPS, and TEM were conducted to characterize these catalysts. The corresponding experimental results revealed that the excellent performance of Au-Pd/TiO2-rutile catalyst was attributed to both the smaller Au-Pd nanoparticle size distribution and the higher concentrations of Oα and Pd2+ species on the catalyst surface. In the recycle experiments, the Au-Pd/TiO2-rutile catalyst displayed lower reaction stability compared with the Au-Pd/TiO2-anatase and Au-Pd/TiO2-brookite, which might be due to the coverage of larger amount of aldehyde products on the surface

Accelerated Computation of Free Energy Profile at ab Initio Quantum Mechanical/Molecular Mechanics Accuracy via a Semi-Empirical Reference Potential. I. Weighted Thermodynamics Perturbation

Free energy profile (FE Profile) is an essential quantity for the estimation of reaction rate and the validation of reaction mechanism. For chemical reactions in condensed phase or enzymatic reactions, the computation of FE profile at ab initio (ai) quantum mechanical/molecular mechanics (QM/MM) level is still far too expensive. Semiempirical (SE) method can be hundreds or thousands of times faster than the ai methods. However, the accuracy of SE methods is often unsatisfactory, due to the approximations that have been adopted in these methods. In this work, we proposed a new method termed MBAR+wTP, in which the ai QM/MM free energy profile is computed by a weighted thermodynamic perturbation (TP) correction to the SE profile generated by the multistate Bennett acceptance ratio (MBAR) analysis of the trajectories from umbrella samplings (US). The weight factors used in the TP calculations are a byproduct of the MBAR analysis in the post-processing of the US trajectories, which are often discarded after the free energy calculations. The results show that this approach can enhance the efficiency of ai FE profile calculations by several orders of magnitude

Digital RNA Sequencing Minimizes Sequence-Dependent Bias and Amplification Noise with Optimized Single-Molecule Barcodes

RNA sequencing (RNA-Seq) is a powerful tool for transcriptome profiling, but is hampered by sequence-dependent bias and inaccuracy at low copy numbers intrinsic to exponential PCR amplification. We developed a simple strategy for mitigating these complications, allowing truly digital RNA-Seq. Following reverse transcription, a large set of barcode sequences is added in excess, and nearly every cDNA molecule is uniquely labeled by random attachment of barcode sequences to both ends. After PCR, we applied paired-end deep sequencing to read the two barcodes and cDNA sequences. Rather than counting the number of reads, RNA abundance is measured based on the number of unique barcode sequences observed for a given cDNA sequence. We optimized the barcodes to be unambiguously identifiable, even in the presence of multiple sequencing errors. This method allows counting with single-copy resolution despite sequence-dependent bias and PCR-amplification noise, and is analogous to digital PCR but amendable to quantifying a whole transcriptome. We demonstrated transcriptome profiling of Escherichia coli with more accurate and reproducible quantification than conventional RNA-Seq.Chemistry and Chemical Biolog

A New Least Squares Support Vector Machines Ensemble Model for Aero Engine Performance Parameter Chaotic Prediction

Aiming at the nonlinearity, chaos, and small-sample of aero engine performance parameters data, a new ensemble model, named the least squares support vector machine (LSSVM) ensemble model with phase space reconstruction (PSR) and particle swarm optimization (PSO), is presented. First, to guarantee the diversity of individual members, different single kernel LSSVMs are selected as base predictors, and they also output the primary prediction results independently. Then, all the primary prediction results are integrated to produce the most appropriate prediction results by another particular LSSVM—a multiple kernel LSSVM, which reduces the dependence of modeling accuracy on kernel function and parameters. Phase space reconstruction theory is applied to extract the chaotic characteristic of input data source and reconstruct the data sample, and particle swarm optimization algorithm is used to obtain the best LSSVM individual members. A case study is employed to verify the effectiveness of presented model with real operation data of aero engine. The results show that prediction accuracy of the proposed model improves obviously compared with other three models

採掘地域における活性断層

Taking some related cases as examples, the paper outlines that human mining activities have made some faults reactivated in mining area. Reactivated faults could result in surface fissure, crown hole, gas emission, coal and gas outburst etc. Some of these geological hazards could persistently occur during tens of years even after coal mines have been abandoned. The direct causative factor of fault reactivation should be surface movement in mining area. Coal extracting, ground water draining or recharging could respectively play key roles in promoting surface movement at different developing stages in mining area. A few research methods of reactivated faults have been introduced, and it is emphasized that necessary forecast and prevention of reactivated faults should be taken account into the rebuilding plans in current and abandoned coal mining areas.特集 : 「資源、新エネルギー、環境、防災研究国際セミナー

MicroRNA-374a Inhibits Aggressive Tumor Biological Behavior in Bladder Carcinoma by Suppressing Wnt/β-Catenin Signaling

Background/Aims: microRNA (miR)-374a plays a crucial role in cancer progression by promoting the metastasis and proliferation of various types of malignant tumors. Because its role in bladder cancer is unknown, we investigated whether miR-374a affects the progression of bladder cancer and studied the underlying mechanism. Methods: The Cancer Genome Atlas was used to analyze the clinical relevance of miR-374a. Quantitative PCR, western blotting, and luciferase and immunofluorescence assays were used to detect the expression patterns, downstream targets, and function of miR-374a in bladder cancer cells. Apoptosis was evaluated by flow cytometry after cisplatin treatment. Results: Via in silico analysis, low levels of miR-374a were associated with poor prognosis in bladder cancer patients with distant metastasis. WNT5A was a direct target of miR-374a in two bladder cancer cell lines. miR-374a mimic abrogated the metastatic potential and invasiveness of bladder cancer cells via WNT5A downregulation in both T24 and TCCSUP human bladder cancer cells; the opposite was observed with miR-374a inhibitor. In addition, miR-374a treatment reduced the phosphorylation and nuclear translocation of β-catenin. Cisplatin treatment significantly increased the apoptosis rate. Expression levels of cancer stemness-related proteins were reduced in miR-374a mimic-pretreated cells. Conclusion: Lower expression of miR-374a is associated with poor prognosis and miR-374a improves tumor biological behavior in bladder cancer cells, suggesting that miR-374a might be a novel small-molecule therapeutic target

Multiscale Fluctuation Features of the Dynamic Correlation between Bivariate Time Series

The fluctuation of the dynamic correlation between bivariate time series has some special features on the time-frequency domain. In order to study these fluctuation features, this paper built the dynamic correlation network models using two kinds of time series as sample data. After studying the dynamic correlation networks at different time-scales, we found that the correlation between time series is a dynamic process. The correlation is strong and stable in the long term, but it is weak and unstable in the short and medium term. There are key correlation modes which can effectively indicate the trend of the correlation. The transmission characteristics of correlation modes show that it is easier to judge the trend of the fluctuation of the correlation between time series from the short term to long term. The evolution of media capability of the correlation modes shows that the transmission media in the long term have higher value to predict the trend of correlation. This work does not only propose a new perspective to analyze the correlation between time series but also provide important information for investors and decision makers

PRMT2 promotes dextran sulfate sodium-induced colitis by inhibiting SOCS3 via histone H3R8 asymmetric dimethylation

BACKGROUND AND PURPOSE: There is emerging evidence for critical roles of epigenetic modifiers in development of inflammatory bowel disease (IBD). Protein arginine methyltransferase 2 (PRMT2) is responsible for methylation of arginine residues on histones and targets transcription factors critically involved in many cellular processes, including gene transcription, mRNA splicing, cell proliferation and differentiation. However, its role in colitis remains unknown. In this study, the role and underlying mechanisms of PRMT2 in colitis was studied. EXPERIMENTAL APPROACH: A mouse dextran sulfate sodium (DSS)-induced experimental colitis model was applied to study PRMT2 in colitis. Lentivirus induced PRMT2 silencing or overexpression in vivo was applied to address the role of PRMT2 in colitis. Detailed western blot and expression analysis was done to understand epigenetic changes induced by PRMT2 in colitis. KEY RESULTS: PRMT2 is highly expressed in patients with IBD, inflamed colon of mice and TNF-α stimulated mice gut epithelial cells. PRMT2 overexpression aggravates while knockdown alleviates DSS-induced colitis in mice, suggesting that PRMT2 is a pivotal mediator of colitis development. Mechanistically, PRMT2 mediates colitis by increasing repressive histone mark H3R8 asymmetric methylation (H3R8me2a) at the promoter region of the suppressor of cytokine signaling 3 (SOCS3) promoter. Resultant inhibition of SOCS3 expression and SOCS3-mediated degradation of TNF receptor associated factor 5 (TRAF5) via ubiquitination led to elevated TRAF5 expression and TRAF5-mediated downstream NF-κB/MAPK activation. CONCLUSION AND IMPLICATIONS: Our study demonstrates that PRMT2 acts as a transcriptional co-activator for proinflammatory genes during colitis. Hence targeting PRMT2 may provide a novel therapeutic approach for colitis

Quality Difference between Aged Brine Marinated andQuantitative Marinated Beef

This study aimed to analyze the quality differences of sauced beef with aged brine and quantitative marinating methods by evaluating sensory characteristics, color, shear force, texture, moisture distribution, taste nucleotides, and free amino acids. Results showed that quantitative marinated beef received a higher score in sensory evaluation than aged brine marinated beef. Additionally, quantitative marinated beef had better color, lower shear force and hardness compared to aged brine marinated beef (P<0.05). It also had a higher moisture content and more even moisture distribution. The quantitative marinating method resulted in higher levels of 5′-AMP, 5′-IMP, and 5′-GMP in the beef sauce, which enhanced its umami intensity (P<0.05). Moreover, the total free amino acid content was higher in quantitative marinated beef (475.60 mg/100 g) than aged brine marinated beef (274.66 mg/100 g). These findings suggested that the use of quantitative marinating method can significantly improve the quality of marinated beef products and promote the industry's advancement