用人工神经网络方法对多环芳烃的致癌性进行分类

将自适应映射（ＳＯＭ）用于多环芳烃致癌性的分级。采用的输入参数为分子比表面积、代谢活性区及亲电活性区的中心碳原子离域能,分子中脱毒区总数。优化的网络参数包括网络数及网格形状,学习次数和学习率、邻居半径等。在最佳网络参数下,多环芳烃致癌性分类准确度大于９７％。     

句法模式识别研究芳烃致癌(二)——特征曲线的理论解释

从M区键级、超离域能和致癌活性的对应关系,结合致癌反应湾区历程对用句法模式识别方法找出的多环芳烃强致癌信息特征曲线进行了理论解释。     

分子电性距离矢量用于稠环芳烃液相色谱保留值的QSPR研究

采用分子电性距离矢量(Molecular Electronegativity Distance Vector,MEDV)表征稠环芳烃类化合物的分子结构.分别运用多元线性回归(Multiple Linear Regres-sion,MLR)和偏最小二乘回归(PLS)建立了稠环芳烃类化合物结构与其液相色谱(LC)保留值的定量结构一性质关系(QSPR)模型,同时采用内部及外部双重验证的办法对所建模型稳定性能进行分析和验证,建模计算值、留一法交互检验预测值和外部样本预测值的复相关系数Rcum、RLOO、Qext分别为0.9970,0.9950,0.9925(MLR);0.9930,0.9790,0.9917(PLS).结果表明,MEDV能较好地表征该类分子结构信息,所建QSPR模型具有良好的稳定性和预测能力.为稠环芳烃类化合物分离、纯化、检测等方法的建立,提供有效的理论依据.     

硝基芳烃致突变性的二维/三维QSAR比较研究

硝基芳烃是一类来源复杂、种类繁多、应用广泛的有毒有机化学品, 具有很强的毒性. 大部分硝基芳烃具有潜在的致癌性, 因此对其致突变性的评价与预测一直受到广泛的关注. 文中分别应用基于分子轨道参数的传统结构-活性关系方法(QSAR)和比较分子场分析方法(CoMFA)研究了219种硝基芳烃的致突变性与分子结构之间的关系, 从机理解释和预测能力等方面对两种方法进行了比较, 在此基础上建立了具有显著预测能力的定量模型.     

主成分分析-支持向量机用于肝病分类模型

将主成分分析(PCA)用于肝功能检测数据特征提取,然后用支持向量机(SVM)对乙肝、丙肝、肝硬化、正常人样本建立分类模型。采用高斯径向基函数(RBF)为核函数,调节核函数参数C及σ以建立最佳支持向量机模型。该模型对训练集的识别率为99.3%,对预测集的预测率为96.4%。结果表明:PCA-SVM法建立的肝病分类模型能较好的区分乙肝、丙肝、肝硬化及正常人,且分类效果优于传统支持向量机及人工神经网络(ANN)分类模型。     

大麻素Ⅰ型受体拮抗剂的结构特征

以92个具有大麻素受体Ⅰ(CB1)拮抗活性的化合物为训练集, 39个化合物为测试集, 采用Discovery Studio V2.5(DS)软件中的3D构效关系药效团产生(QSAR Pharmacophore Generation)模块建立药效团模型. 获得的最佳药效团模型的构成为一个氢键受体(HBA)、 一个疏水基团(HY)和二个芳环中心(RA), 采用费用函数(Cost function)评价药效团模型, 该模型的Δcost为119.32, 相关性为0.921, 均方根偏差为0.730, Configuration cost为16.1229, 表明模型能较好地预测化合物的活性. 同时针对目前已知的近450个化合物的12种结构类型进行了探讨, 所得结果为进一步设计CB1拮抗剂提供了理论依据.     

β分泌酶抑制剂的药效团模型研究

选择活性跨越0.002至25 μmol•L－1的4类共25个β分泌酶抑制剂作为训练集, 使用Catalyst软件包构建出药效团模型, 并通过对药效团的有效性分析, 筛选得到的最佳模型(correlCorrel＝0.969, Config＝16.32, Δcost＝62.422)由一个环芳香性、一个疏水中心、一个正电荷中心和一个氢键供体组成. 并用其它209个抑制剂组成测试集对模型进行验证, 结果表明该模型显示出较强的预测能力, 能够为进一步的数据库搜索, 寻找新型的β分泌酶抑制剂先导物提供依据.     

基于高光谱技术的培养基上细菌菌落分类方法研究

利用高光谱技术对培养基上细菌(大肠杆菌、李斯特菌和金黄色葡萄球菌)菌落进行快速识别和分类。采集琼脂培养基上细菌菌落的高光谱反射图像(390~1040 nm),在对波段差图像进行大津阈值分割的基础上自动提取细菌菌落光谱,并建立细菌分类检测的全波长和简化偏最小二乘判别( PLS-DA)模型。全波长模型对预测集样本的分类准确率和置信预测分类准确率分别为100%和95.9%。此外,利用竞争性自适应重加权算法( CARS)、遗传算法( GA)和最小角回归算法( LARS-Lasso)进行波长优选并建立对应简化模型。其中,CARS简化模型在精度、稳定性及分类准确率方面均优于GA和LARS-Lasso简化模型,其对预测集样本的分类准确率和置信预测分类准确率分别达到了100%和98.0%。研究表明,高光谱是一种细菌菌落高精度、快速、无损识别检测的有效方法。简化模型中优选的波长可以为开发低成本检测仪器提供理论依据。     

基于最小二乘支持向量机的色谱指纹图谱预测银杏叶总抗氧化活性

在色谱图基线校正和色谱峰匹配基础上,提出以40个银杏叶提取物HPLC指纹图谱的色谱图轮廓作为输入,相应的提取物总抗氧化活性作为输出,建立最小二乘支持向量机回归模型,并对包含10个样本的测试集进行了预测.最小二乘支持向量机的测试集预测误差均方根(RMSEP)为0.0230,预测结果优于目前普遍使用的误差反向传播神经网络和偏最小二乘回归.与采用色谱峰面积为分析变量的模型预测结果比较表明:采用消除干扰后的色谱图全谱轮廓保留了样本的全部信息,预测结果更好     

基于药效团模型的DHODH抑制剂构效关系研究

利用药效团模型研究二氢乳清酸脱氢酶(Dihydroorotate dehydrogenase,DHODH)抑制剂的构效关系,为DHODH抑制剂的虚拟筛选提供新的方法.以31个具有DHODH抑制活性的化合物为训练集化合物,半数抑制浓度(IC50)范围为7~63000 nmol/L,利用Catalyst/HypoGen算法构建DHODH抑制剂药效团模型,通过对训练集化合物多个构象进行叠合,提取药效团特征及三维空间限制构建药效团模型.利用基于CatScramble的交叉验证方法及评价模型对已知活性化合物的活性预测能力,确定较优药效团模型.模型包含1个氢键受体、3个疏水中心,表征了受体配体相互作用时可能发生的氢键相互作用、疏水相互作用和π-π相互作用,4个药效特征在三维空间的排列概括了DHODH抑制剂产生活性的结构特点.所得较优模型对训练集化合物及测试集化合物的计算活性值与实验活性值的相关系数分别为0.8405和0.8788.利用药效团模型对来源于微生物的系列化合物进行虚拟筛选,筛选出59个预测活性较好的化合物,可作为进一步药物研发的候选化合物.     

Dielectric Analysis of Short-Term and Long-Term Curing of Novel Photo-Curing Dental Filling Materials

Highly glass powder filled photo-curing dental filling materials based on acrylic resins are used as an alternative for classical amalgam fillings for almost two decades. To improve the performance of the fillings nowadays nano-particles are introduced in these resins. However, surprisingly less is known about their curing kinetics and how it is affected by the composition of the resin and the kind of the filler. It is shown how the dielectric analysis (DEA) can be used to trace both the short-term photo-curing (Figure 1) as well as the long-term post-curing of such resins when measuring its ion viscosity. Especially if assisted by other thermo-analytical methods the DEA allows for a deeper insight in the processes occurring in the dental filling materials. Long-term measurements over several days using DEA and DMA (dynamic mechanical analysis) exhibit that there are going on significant changes of the properties of the dental material which are relevant for the long-term performance (Figure 2). The DEA is an easy to handle and cost efficient method to investigate the curing kinetic either for dental composite material engineering as well as for quality insurance purposes.     

Thermal decomposition of hydrotalcite with hexacyanoferrate(II) and hexacyanoferrate(III) anions in the interlayer

The mechanism for the decomposition of hydrotalcite remains unsolved. Controlled rate thermal analysis enables this decomposition pathway to be explored. The thermal decomposition of hydrotalcites with hexacyanoferrate(II) and hexacyanoferrate(III) in the interlayer has been studied using controlled rate thermal analysis technology. X-ray diffraction shows the hydrotalcites have a d(003) spacing of 10.9 and 11.1 Å which compares with a d-spacing of 7.9 and 7.98 Å for the hydrotalcite with carbonate or sulphate in the interlayer. Calculations show dehydration with a total loss of 7 moles of water proving the formula of hexacyanoferrate(II) intercalated hydrotalcite is Mg₆Al₂(OH)₁₆[Fe(CN)₆]_0.5·7H₂O and 9.0 moles for the hexacyanoferrate(III) intercalated hydrotalcite with the formula of Mg₆Al₂(OH)₁₆[Fe(CN)₆]_0.66·9H₂O. CRTA technology indicates the partial collapse of the dehydrated mineral. Dehydroxylation combined with CN unit loss occurs in two isothermal stages at 377 and 390°C for the hexacyanoferrate(III) and in a single isothermal process at 374°C for the hexacyanoferrate(III) hydrotalcite.     

不相交主成分分析(PCA)和遗传算法(GA)用于差异表达基因的识别

建立了一种基于不相交主成分分析(Disjoint PCA)和遗传算法(GA)的特征变量选择方法, 并用于从基因表达谱(Gene expression profiles)数据中识别差异表达的基因. 在该方法中, 用不相交主成分分析评估基因组在区分两类不同样品时的区分能力; 用GA寻找区分能力最强的基因组; 所识别基因的偶然相关性用统计方法评估. 由于该方法考虑了基因间的协同作用更接近于基因的生物过程, 从而使所识别的基因具有更好的差异表达能力. 将该方法应用于肝细胞癌(HCC)样品的基因芯片数据分析, 结果表明, 所识别的基因具有较强的区分能力, 优于常用的基因芯片显著性分析(Significance analysis of microarrays, SAM)方法.     

交互移动窗口因子分析法(AMWFA)用于二维数据重叠色谱峰的比较分析

采用交互移动窗口因子分析法(AMWFA), 通过挖掘两个体系中的选择性信息, 获得了不同样本间的共有组分数, 还同时得到了各物质对应的光谱或质谱信息. 详细阐述了本法的原理和计算方法, 并用一个模拟的GC-MS 数据对方法进行了验证.     

超高效液相色谱法结合化学计量学分析评价4种商品人参的质量

建立了快速、灵敏、准确的超高效液相色谱方法,用来分析4种商品人参(人参、红参、人参叶、人参须)中12种人参皂苷的含量,并用化学计量学方法评价了商品人参的质量。采用ACQUITY UPLC^TM BEH C₁₈色谱柱(50 mm×2.1 mm, 1.7 μm),以乙腈-水为流动相进行梯度洗脱。对所建立的测定12种人参皂苷的UPLC方法进行了线性方程、准确度、重复性、回收率等方法学考察。采用聚类分析和主成分分析的化学计量学方法对4种商品人参进行分析,评价了其质量。结果表明聚类分析和主成分分析2种化学计量学方法非常适合大样本、多成分的中药材质量分析。     

Coal analysis by diffuse reflectance near-infrared spectroscopy: Hierarchical cluster and linear discriminant analysis

An extensive study was carried out in coal samples coming from several origins trying to establish a relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding near-infrared spectral data. This research was developed by applying both quantitative (partial least squares regression, PLS) and qualitative multivariate analysis techniques (hierarchical cluster analysis, HCA; linear discriminant analysis, LDA), to determine a methodology able to estimate property values for a new coal sample. For that, it was necessary to define homogeneous clusters, whose calibration equations could be obtained with accuracy and precision levels comparable to those provided by commercial online analysers and, study the discrimination level between these groups of samples attending only to the instrumental variables. These two steps were performed in three different situations depending on the variables used for the pattern recognition: property values, spectral data (principal component analysis, PCA) or a combination of both. The results indicated that it was the last situation what offered the best results in both two steps previously described, with the added benefit of outlier detection and removal.     

Synthesis of the monosubstituted arylcyanoxime and its Na,Tl(I) and Ag(I) compounds

Nitrosation of 2-chlorophenyl acetonitrile with t-butylnitrite under basic conditions (Meyer reaction) resulted in a high-yield preparation of the first substituted arylcyanoxime, 2-chlorophenyl(oximino)acetonitrile, H(2Cl–PhCO) (HL). The obtained cyanoxime is readily deprotonated in solution by metal hydroxides or carbonates with the formation of yellow sodium, tetrabutylammonium, thallium(I) and silver(I) derivatives. The crystal structure of the Tl(I) complex was determined. Thallium(I) salt (TlL) crystallizes in the monoclinic space group P2₁ n with a?=?3.8382(7), b?=?11.0065(18), c?=?20.901(4)?Å, and β?=?92.447(3)°, V?=?882.2(3) ų, Z?=?4; T?=?193?K (Mo?Kα radiation). The structure was solved by direct methods to a final R of 0.0689 (wR2?=?0.1650) for I?>?2σ(I). The crystal structure of the complex is a one-dimensional coordination polymer that consists of centrosymmetric [TlL]₂ dimers in which Tl₂O₂ rhombohedra are connected to each other at 90.72°. The crystal structure of TlL is an interesting example of the ruffled metal-organic network composed of Tl–O–Tl–O zigzag chains with close (3.838?Å) intermetallic distances comparable to those in metallic thallium (3.42?Å). The cyanoxime anion bridges metal centers and acts as a tridentate ligand where oxygen atoms of the oxime group bond to three different Tl(I) cations with three different bond lengths.     

Temporal characterisation of river waters in urban and semi-urban areas using physico-chemical parameters and chemometric methods

Three sampling campaigns were carried out in rivers located at two hydrographic basins affected by urban and semi-urban areas around the Metropolitan area of A Coruña (ca. 500,000 inhabitants, NW-Spain) to study local and temporal variations of 21 physicochemical parameters (pH, conductivity, Cl⁻, SO₄²⁻, SiO₂, Ca²⁺, Mg²⁺, Na⁺, K⁺, hardness, NO₃⁻, NO₂⁻, NH₄⁺, COD, PO₄³⁻, Zn²⁺, Cu²⁺, Mn²⁺, Pb²⁺, alkalinity and acidity) in 23 sampling points. The temporal evolution of the water quality was assessed by matrix augmentation principal components analysis (MA-PCA) and parallel factor analysis (PARAFAC). Moreover, classical principal components analysis (PCA) (one per sampling campaign) was applied with exploratory and comparison purposes. The first factor of the different studies comprised variables associated to the mineral content and it differentiated the samples according to their hydrographic basins. The second factor was mainly associated to organic matter, from domestic wastes and decomposition of natural debris. The temporal evolution of the water quality was mostly related to seasonal increments of the physicochemical parameters defining the decomposition of the organic matter.The three models applied (PCA, MA-PCA and PARAFAC) led to similar conclusions, nonetheless, MA-PCA excelled, since the refolding of scores provided more straightforward and convenient overview of sample time and geographical variations than individual PCA and it is more flexible and adaptable to environmental studies than PARAFAC.     

Optimization of Fish Quality by Evaluation of Total Volatile Basic Nitrogen (TVB-N) and Texture Profile Analysis (TPA) by Near-Infrared (NIR) Hyperspectral Imaging

Hyperspectral images contain both spectral and spatial image information and were investigated to characterize the freshness of fish. However, most studies of this application have focused on spectral signals rather than image features. The goal of this work was to investigate the ability of spectral and image textural variables for predicting the chemical and physical qualities of fish, respectively, and to optimize the variables for the specific quality determination. The chemical (total volatile basic nitrogen, TVB-N) and physical (texture profile analysis, TPA) properties were investigated. Partial least square (PLS) was applied to develop fish quality prediction models with the spectral and textural variables from the hyperspectral images. The results showed that the TVB-N content of fish fillets was accurately predicted using the spectra. Meanwhile, the TPA parameters were determined through the image textural features with high accuracy, which indicated image textural features were highly related with the TPA parameters. Moreover, spectral and textural features were also extracted from fish eyes and gills and were further used to predict the intact fish quality, taking advantage of the freshness sensitivity of the eyes and gills. The results illustrate that spectra from fish eyes and gills are a potential tool to predict the TVB-N content and TPA parameters for intact fish.