Dynamic Variation of Amino Acid Contents and Identification of Sterols in Xinyang Mao Jian Green Tea

As important biomolecules in Camellia sinensis L., amino acids (AAs) are considered to contribute to the overall green tea sensory quality and undergo dynamic changes during growth. However, limited by analytical capacity, detailed AAs composition in different growth stages remains unclear. To address this question, we analyzed the dynamic changes of 23 AAs during leaf growth in Xinyang Mao Jian (XYMJ) green tea. Using amino acid analyzer, we demonstrated that most AAs are abundant on Pure Brightness Day and Grain Rain Day. After Grain Rain, 23 AAs decreased significantly. Further analysis shows that theanine has a high level on the day before Spring Equinox and Grain Rain, accounting for 44–61% of the total free AAs content in tea leaves. Glu, Pro, and Asp are the second most abundant AAs. Additionally, spinasterol and 22,23-dihydrospinasterol are first purified and identified in ethanol extract of XYMJ by silica gel column chromatography method. This study reveals the relationship between plucking days and the dynamic changes of AAs during the growth stage and proves the rationality of the traditional plucking days of XYMJ green tea.     

手性大孔磷酸镓Hit-5的水热合成与晶体结构

本文采用水热合成法制备了一个三维手性大孔开放骨架磷酸镓Ga16P16O75·4[1,6-C6H18N2]·[C2H10N2]·2H2O(简称Hit-5).反应起始原料摩尔配比为:1 GaOOH:15 H3PO4:7.5 H2N(CH2)6NH2:0.5 C2H8N2:555 H2O.Hit-5属正交晶系,P21212空间群,晶胞参数:a=0.8671(1)nm,b=1.7945(1)nm,c=0.9101(1)nm,β=108.33(1)°,V=1.3443(2)nm3,Z=4.Hit-5的骨架是由Ga3P3六聚体和Ga4P4八聚体两个不同的二级结构单元通过共顶点联接构成三维纳米孔结构,在[001]方向呈现16-元环孔道.     

钾明矾蓄热性能的研究与改善

钾明矾(KAl(SO4)2·12H2O)有较高的潜热和良好的导热性(熔化热232.4kJ/kg,导热系数为0.55W/m·K),熔点为91℃,是中低温相变材料中较有开发价值的一种.但是它的过冷度高达19.8℃,并且由于相变过程伴随着结晶水的蒸发使无机盐的使用寿命大大降低.本文通过冷指法及添加成核剂的方法对硫酸铝钾的过冷现象进行了研究,结果表明成核剂NiSO4·6H2O、MgCl2·6H2O能较好的改善过冷现象,当MgCl2·6H2O的添加量为2;时可使过冷度降为零,且能保持钾明矾的相变温度而不使其降低.利用MgCl2·6H2O具有很强的吸湿性,可以补充相变过程中损失的水分,使相变材料的使用寿命大大提高.     

An unexpected all-metal aromatic tetranuclear silver cluster in human copper chaperone Atox1

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins. Herein we report the formation and crystal structure of a planar square tetranuclear silver cluster when silver ions were mixed with human copper chaperone Atox1. Quantum chemical studies reveal that two Ag 5s¹ electrons in the tetranuclear silver cluster fully occupy the one bonding molecular orbital, with the assumption that this Ag₄ cluster is Ag₄²⁺, leading to extensive electron delocalization over the planar square and significant stabilization. This bonding pattern of the tetranuclear silver cluster represents an aromatic all-metal structure that follows a 4n + 2 electron counting rule (n = 0). This is the first time an all-metal aromatic silver cluster was observed in a protein.

Metal clusters, such as iron–sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins.     

EGFAFS: A Novel Feature Selection Algorithm Based on Explosion Gravitation Field Algorithm

Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As a result, they are not suitable to be processed by simple methods, such as the filter-based method. In this study, we propose a novel feature selection algorithm based on the Explosion Gravitation Field Algorithm, called EGFAFS. To reduce the dimensions of the feature space to acceptable dimensions, we constructed a recommended feature pool by a series of Random Forests based on the Gini index. Furthermore, by paying more attention to the features in the recommended feature pool, we can find the best subset more efficiently. To verify the performance of EGFAFS for FS, we tested EGFAFS on eight gene expression datasets compared with four heuristic-based FS methods (GA, PSO, SA, and DE) and four other FS methods (Boruta, HSICLasso, DNN-FS, and EGSG). The results show that EGFAFS has better performance for FS on gene expression data in terms of evaluation metrics, having more than the other eight FS algorithms. The genes selected by EGFAGS play an essential role in the differential co-expression network and some biological functions further demonstrate the success of EGFAFS for solving FS problems on gene expression data.     

A Novel Method for Pattern Recognition of GIS Partial Discharge via Multi-Information Ensemble Learning

Partial discharge (PD) is the main feature that effectively reflects the internal insulation defects of gas-insulated switchgear (GIS). It is of great significance to diagnose the types of insulation faults by recognizing PD to ensure the normal operation of GIS. However, the traditional diagnosis method based on single feature information analysis has a low recognition accuracy of PD, and there are great differences in the diagnosis effect of various insulation defects. To make the most of the rich insulation state information contained in PD, we propose a novel multi-information ensemble learning for PD pattern recognition. First, the ultra-high frequency and ultrasonic data of PD under four typical defects of GIS are obtained through experiment. Then the deep residual convolution neural network is used to automatically extract discriminative features. Finally, multi-information ensemble learning is used to classify PD types at the decision level, which can complement the shortcomings of the independent recognition of the two types of feature information and has higher accuracy and reliability. Experiments show that the accuracy of the proposed method can reach 97.500%, which greatly improves the diagnosis accuracy of various insulation defects.     

嵌段共聚物自组装的研究进展

嵌段共聚物自组装在光学、电子、信息、化学及生物领域有着广泛的应用前景.本文从实验观测、理论研究和计算机模拟三个方面概述了嵌段共聚物自组装领域的研究进展.在实验观测方面,着重介绍了嵌段共聚物在体相及膜中的自组装及外场调控作用方面的研究进展;理论方面则分别介绍了强分相理论、弱分相理论、自洽场理论、动态密度泛函方法和元胞动力学等在嵌段共聚物自组装领域的应用;计算机模拟方面就 Monte Carlo 模拟、耗散粒子动力学等方法在该领域的应用作了详细的阐述.     

Toxic Effect of Fullerene and Its Derivatives upon the Transmembrane β2-Adrenergic Receptors

Numerous experiments have revealed that fullerene (C₆₀) and its derivatives can bind to proteins and affect their biological functions. In this study, we explored the interaction between fullerine and the β₂-adrenergic receptor (β₂AR). The MD simulation results show that fullerene binds with the extracellular loop 2 (ECL2) and intracellular loop 2 (ICL2) of β₂AR through hydrophobic interactions and π–π stacking interactions. In the C₆₀_in1 trajectory, due to the π–π stacking interactions of fullerene molecules with PHE and PRO residues on ICL2, ICL2 completely flipped towards the fullerene direction and the fullerene moved slowly into the lipid membrane. When five fullerene molecules were placed on the extracellular side, they preferred to stack into a stable fullerene cluster (a deformed tetrahedral aggregate), and had almost no effect on the structure of β₂AR. The hydroxyl groups of fullerene derivatives (C₆₀(OH)_X, X represents the number of hydroxyl groups, X = 4, 8) can form strong hydrogen bonds with the ECL2, helix6, and helix7 of β₂AR. The hydroxyl groups firmly grasp the β₂AR receptor like several claws, blocking the binding entry of ligands. The simulation results show that fullerene and fullerene derivatives may have a significant effect on the local structure of β₂AR, especially the distortion of helix4, but bring about no great changes within the overall structure. It was found that C₆₀ did not compete with ligands for binding sites, but blocked the ligands’ entry into the pocket channel. All the above observations suggest that fullerene and its derivatives exhibit certain cytotoxicity.     

达旦黄-曲通X-100体系共振光散射法测定蛋白质

基于在Triton X-100存在下,蛋白质与达旦黄作用使得体系的共振光散射增强,在λ＝492 nm处光散射强度最大,增强作用的强弱与蛋白质的含量成正比,据此建立了共振光散射测定蛋白质的新方法。此方法对牛血清白蛋白的检出限达到17.7 ng·mL-1,线性范围为0.03～0.9 μg·mL-1,用于合成样与人血清样品的分析,取得了令人满意的结果。同时也研究了人血清白蛋白、鸡蛋白蛋白、溶菌酶、胰蛋白酶与达旦黄的作用。     

Improvement of the Performance of an Acousto-Optical Q-Switched Nd:YAG 946 nm Laser Using a Convex–Plane Cavity

We improve the performance of an acousto-optical Q-switched Nd:YAG 946 nm laser using a convex–plane cavity. We obtain the highest output average power of 2.3 W with a pulse width of 15.3 ns in a 10 kHz 946 nm laser with a convex–plane cavity. The maximum peak power 15.0 kW is about three times higher than that in a plane–plane cavity. Also we investigate the output performances of the pulsed 946 nm laser with the convex–plane cavity at 20 and 50 kHz.