An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning

In the process of drug discovery, drug-induced liver injury (DILI) is still an active research field and is one of the most common and important issues in toxicity evaluation research. It directly leads to the high wear attrition of the drug. At present, there are a variety of computer algorithms based on molecular representations to predict DILI. It is found that a single molecular representation method is insufficient to complete the task of toxicity prediction, and multiple molecular fingerprint fusion methods have been used as model input. In order to solve the problem of high dimensional and unbalanced DILI prediction data, this paper integrates existing datasets and designs a new algorithm framework, Rotation-Ensemble-GA (R-E-GA). The main idea is to find a feature subset with better predictive performance after rotating the fusion vector of high-dimensional molecular representation in the feature space. Then, an Adaboost-type ensemble learning method is integrated into R-E-GA to improve the prediction accuracy. The experimental results show that the performance of R-E-GA is better than other state-of-art algorithms including ensemble learning-based and graph neural network-based methods. Through five-fold cross-validation, the R-E-GA obtains an ACC of 0.77, an F1 score of 0.769, and an AUC of 0.842.     

Role of Natural Compounds and Target Enzymes in the Treatment of Alzheimer’s Disease

Alzheimer’s disease (AD) is a progressive neurological condition. The rising prevalence of AD necessitates the rapid development of efficient therapy options. Despite substantial study, only a few medications are capable of delaying the disease. Several substances with pharmacological activity, derived from plants, have been shown to have positive benefits for the treatment of AD by targeting various enzymes, such as acetylcholinesterase (AChE), butyrylcholinesterase (BuChE), β-secretase, γ-secretase, and monoamine oxidases (MAOs), which are discussed as potential targets. Medicinal plants have already contributed a number of lead molecules to medicine development, with many of them currently undergoing clinical trials. A variety of medicinal plants have been shown to diminish the degenerative symptoms associated with AD, either in their raw form or as isolated compounds. The aim of this review was to provide a brief summary of AD and its current therapies, followed by a discussion of the natural compounds examined as therapeutic agents and the processes underlying the positive effects, particularly the management of AD.     

磷酸氯喹的流动注射逆胶束介导化学发光法测定

在酸性条件下,磷酸氯喹分子中氮原子被质子化后与阴离子AuCl4-形成离子缔合物,该缔合物被二氯甲烷带入鲁米诺的氯化十六烷基三甲基铵逆胶束中,离解出来的AuCl4-立即与鲁米诺产生化学发光.在一定的浓度范围内,发光强度与磷酸氯喹的含量呈线性关系,从而间接测定磷酸氯喹的含量.在优化的实验条件下,线性范围为0.001～15 mg/L,检出限(3σ)为0.02 μg/L,对1.0 mg/L的磷酸氯喹进行11次平行测定,RSD为1.6%.该法已成功用于片剂的分析.     

Single-Stage Extraction and Separation of Co2+ from Ni2+ Using Ionic Liquid of [C4H9NH3][Cyanex 272]

The purpose of this study was to optimize the extraction conditions for separating Co²⁺ from Ni²⁺ using N-butylamine phosphinate ionic liquid of [C₄H₉NH₃][Cyanex 272]. A Box–Behnken design of response surface methodology was used to analyze the effects of the initial pH, extraction time, and extraction temperature on the separation factor of Co²⁺ from sulfuric acid solution containing Ni²⁺. The concentrations of Co²⁺ and Ni²⁺ in an aqueous solution were determined using inductively coupled plasma-optical emission spectrometry. The optimized extraction conditions were as follows: an initial pH of 3.7, an extraction time of 55.8 min, and an extraction temperature of 330.4 K. The separation factor of Co²⁺ from Ni²⁺ under optimized extraction conditions was 66.1, which was very close to the predicted value of 67.2, and the error was 1.7%. The equation for single-stage extraction with high reliability can be used for optimizing the multi-stage extraction process of Co²⁺ from Ni²⁺. The stoichiometry of chemical reaction for ion-exchange extraction was also investigated using the slope method.     

低温等离子体数值模拟方法的分析比较

分析比较了低温等离子体模拟中采用的流体模型、粒子模型和混合模拟方法及在放电特性分析中采用的电路模拟方法。给出了每种方法的基本原理,探讨了它们的适应性。利用粒子模型对外磁镜场作用下四阳极装置辉光放电所产生等离子体进行了模拟,分析了磁场对电子密度径向分布的影响。     

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.     

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.     

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.