多元曲线分辨-交替最小二乘方法在联用数据分辨中的应用

通过对模拟数据和高效毛细管电泳实验数据的分析,讨论了多元曲线分辨-交替最小二乘方法(MCR-ALS)在毛细管电泳-二极管阵列检测(CE-DAD)联用数据分辨中的应用.讨论了几种因素对MCR-ALS单个数据矩阵分辨结果的影响,包括待分析物光谱间的相似程度、浓度曲线的重叠程度以及由渐进因子分析(EFA)所得到的浓度初始值等.MCR-ALS还可用于多个数据矩阵的同时分析,即二阶MCR-ALS.结果表明,与一阶MCR-ALS相比,二阶MCR-ALS方法能够更好地解决各种分辨问题,得到合理和满意的分辨结果.     

紫外光谱法结合多元曲线分辨研究黄芩苷的转化规律

采用紫外光谱法采集不同工艺条件下黄芩苷转化过程的光谱数据, 结合多元曲线分辨-交替最小二乘法(MCR-ALS)处理获得的数据, 得到黄芩苷转化反应过程中各组分的光谱图和浓度随时间变化曲线. 结果表明, 黄芩苷转化过程符合两步连续一级反应模型; 根据不同时间点采集的多级质谱和飞行时间质谱信息, 推断了黄芩苷转化产物和可能的转化途径, 转化产物主要包括黄芩苷的同分异构体、 黄芩素和黄芩素二聚体. 对黄芩苷转化规律的研究有助于黄芩制剂的质量控制.     

荧光光谱法结合多元曲线分辨-交替最小二乘法研究伞形花内酯与牛血清白蛋白的相互作用

在模拟人体生理条件下(pH=7.4), 用荧光光谱法结合多元曲线分辨-交替最小二乘法(MCR-ALS)研究伞形花内酯与牛血清白蛋白(BSA)的相互作用. 采用两种不同的试剂滴加模式对伞形花内酯与BSA的相互作用进行研究, 对经典的荧光光谱数据矩阵加以扩展, 增加了实验数据的信息量; 进而应用MCR-ALS对该扩展的荧光光谱矩阵进行迭代计算, 较好地分辨出作用过程中浓度变化趋势图, 并计算出伞形花内酯与BSA的表观结合常数和结合比. 通过同步荧光光谱法发现伞形花内酯对BSA的构象有一定的影响.     

荧光光谱结合多元曲线分辨-交替最小二乘法研究十二烷基三甲基溴化铵与牛血清白蛋白的相互作用

模拟pH=7.4的人体生理条件,用荧光光谱法结合多元曲线分辨-交替最小二乘法(MCR-ALS),研究表面活性剂十二烷基三甲基溴化铵(CTAB)与牛血清白蛋白(BSA)的相互作用。为增加实验数据的信息量,本实验采用顺序不同的两种滴加方式得到扩展的荧光光谱数据矩阵;进而采用渐进因子分析法(EFA)得到作用体系中各组分浓度变化曲线的初值,再应用MCR-ALS对该扩展荧光光谱矩阵进行迭代计算,较好地分辨出动态作用中各种物质的浓度变化趋势图,并由此曲线推断出CTAB与BSA的表观结合常数和结合比。     

修正样条小波最小二乘法用于分辨高噪声重叠峰

采用连续样条小波变换确定重叠信号的组分峰的数目和峰位置,将样条小波最小二乘法加以改进,使其成为既能滤出噪声又能分峰的新方法.对信噪比为1的重叠峰进行处理,得到满意结果.该方法只需对信号进行一次处理,处理速度快,且数据点无须为2n(n∈Z).应用于毛细管电泳电导信号的处理,得到满意结果.     

多元曲线分辨结合在线红外用于3-氨基-4-氨基肟基呋咱的合成反应机理

利用红外光谱在线监测丙二睛、亚硝酸钠和盐酸羟胺合成3-氨基-4-氨基肟基呋咱的反应过程,采用多元曲线分辨-交替最小二乘法（MCR-ALS）、直观推导式演进特征投影法(HELP)等化学计量学方法对反应过程所获得的实时红外光谱数据矩阵进行解析,得到了各组分纯物质的浓度变化曲线和对应的红外光谱,并将多元曲线分辨 交替最小二乘法与直观推导式演进特征投影法的分析结果进行比较,得出可相互验证的一致结论,据此推出该反应合理的反应机理。 2种方法得到的反应物与生成物的光谱与原光谱的相似度近似于1,说明该解析方法具有准确性和可靠性。 结果表明,化学计量学结合红外光谱可有效的应用于3-氨基-4-氨基肟基呋咱合成过程的机理推断。     

化学计量学和红外光谱研究3,5-二氨基-1,2,4-三唑合成机理

通过红外光谱在线监测3,5-二氨基-1,2,4-三唑(DAT)的合成过程,应用多元曲线分辨-交替最小二乘法(MCR-ALS)对过程中获得的光谱数据矩阵进行解析,推导出合理的反应机理.反应以水为背景,依次加入二氰二胺与二盐酸肼固体,用红外探头监测反应全过程.用MCR-ALS法对所得光谱数据进行解析,得到反应物、中间体和产...     

多元曲线分辨方法和红外光谱用于奥克托今合成机理

通过红外光谱在线监测1,5-二乙酰基-3,7-二硝基-1,3,5,7-四氮杂环辛烷（简写DADN）合成奥克托今(HMX)的反应过程,利用渐进因子分析(EFA)、多元曲线分辨 交替最小二乘法(MCR-ALS)和直观推导式演进特征投影法(HELP)等化学计量学方法对反应过程获得的光谱信息进行解析,得到了各组分浓度变化曲线和对应的红外光谱,并将MCR-ALS和HELP两种方法的分析结果进行比较,得出可相互验证的一致结论,从而推测出该反应合理的反应机理。 所得结果与文献报道吻合,表明化学计量学方法结合在线红外光谱是研究奥克托今合成机理的有效手段。     

多元曲线分辨等方法和红外光谱用于二硝基五亚甲基四胺的合成反应机理研究

通过红外光谱在线监测强酸催化下硝酰胺、甲醛和氨水合成二硝基五亚甲基四胺(DPT)的反应过程, 利用渐进因子分析(EFA)、直观推导式演进特征投影法(HELP)和多元曲线分辨-交替最小二乘法(MCR-ALS)等化学计量学方法对反应过程获得的红外光谱信息进行解析, 得到了各组分纯物质的浓度变化曲线和对应的红外光谱, 并把多元曲线分辨-交替最小二乘法与直观推导式演进特征投影法的分析结果进行比较, 得出可相互验证的一致结论, 以此推测出该反应合理的反应机理. 化学计量学方法对在线红外光谱信息的分辨可以快速有效地反映DPT合成过程中各组分的浓度和红外光谱变化情况, 对其反应机理研究具有重要指导意义.     

Voltammetric,UV–Vis Spectrometric and Fluorescence Study of the Interaction of Ractopamine and DNA with the Aid of Multivariate Curve Resolution‐Alternating Least Squares

Interaction of a steroid drug, Ractopamine (RAC), and DNA was investigated by electroanalysis‐differential pulse and cyclic voltammetry (DPV and CV), and UV‐vis and fluorescence spectroscopy. DPV showed that RAC intercalated with DNA, and CV indicated that the reaction mechanism of RAC and dsDNA involved irreversible oxidation with the loss of two H⁺ and a transfer of two electrons. Reaction binding parameters were obtained. Pure spectra of RAC, DNA and the RAC‐DNA complex, and their concentrations were extracted by multivariate curve resolution‐alternating least squares method (MCR‐ALS). Concentration profiles indicated quantitatively the course of the reaction.     

Chemometric Assisted UV-Spectrophotometric Methods Using Multivariate Curve Resolution Alternating Least Squares and Partial Least Squares Regression for Determination of Beta-Antagonists in Formulated Products: Evaluation of the Ecological Impact

In this study, UV-spectrophotometry coupled with chemometrics has been utilized to enhance the sustainability of quality control analysis of beta antagonists. First, we developed and optimized two eco-friendly chemometric-assisted methods without preliminary separation utilizing (1) multivariate curve resolution alternating least squares (MCR-ALS) and (2) well-established partial least squares regression (PLSR) multivariate calibration for the resolution and quantification of the most commonly prescribed beta antagonists in active pharmaceutical ingredients or commercial pharmaceutical products. The performance of the two proposed chemometric methods was computed and compared. Second, a comprehensive qualitative and quantitative evaluation of the eco-friendliness of the developed methods was performed utilizing the following greenness assessment tools: Green Analytical Procedure Index (GAPI), Analytical Eco-scale assessment (AES) tool, Raynie and Driver’s assessment tool and Analytical GREEnness Metric (AGREE). The models showed satisfactory recovery with a range from 99.83% to 101.12% for MCR-ALS and from 99.66% to 101.54% for PLSR. The optimized models were employed for green analysis of the investigated beta-blockers in single or co-formulated formulations without prior separation. The predictivity of the proposed MCR-ALS and the well-established PLSR method were very comparable. Nevertheless, the MCR-ALS method has the ability to recover the pure spectra of the studied analytes and the interferences as well. The proposed chemometric methods are fast, precise and do not need any sample pretreatment. In addition, they can be used as a benign substitute for the traditional methods used for the analysis of the investigated drugs in pharmaceutical products without harmful impacts on human health and the environment. They also provide advantages in terms of low solvent usage, reduced energy consumption and short analysis time, making them a safe and sustainable approach for quality control analysis.     

Flexible Implementation of the Trilinearity Constraint in Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) of Chromatographic and Other Type of Data

Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) can analyze three-way data under the assumption of a trilinear model using the trilinearity constraint. However, the rigid application of this constraint can produce unrealistic solutions in practice due to the inadequacy of the analyzed data to the characteristics and requirements of the trilinear model. Different methods for the relaxation of the trilinear model data requirements have been proposed, like in the PARAFAC2 and in the direct non-trilinear decomposition (DNTD) methods. In this work, the trilinearity constraint of MCR-ALS is adapted to different data scenarios where the profiles of all or some of the components of the system are shifted (not equally synchronized) or even change their shape among different slices in one of their data modes. This adaptation is especially useful in gas and liquid chromatography (GC and LC) and in Flow Injection Analysis (FIA) with multivariate spectroscopic detection. In a first data example, a synthetic LC-DAD dataset is built to investigate the possibilities of the proposed method to handle systematic changes (shifts) in the retention times of the elution profiles and the results are compared with those obtained using alternative methods like ATLD, PARAFAC, PARAFAC2 and DNTD. In a second data example, multiple wine samples were simultaneously analyzed by GC-MS where elution profiles presented large deviations (shifts) in their peak retention times, although they still preserve the same peak shape. Different modelling scenarios are tested and the results are also compared. Finally, in the third example, sample mixtures of acid compounds were analyzed by FIA under a pH gradient and monitored by UV spectroscopy and also examined by different chemometric methods using a different number of components. In this case, however, the departure of the trilinear model comes from the acid base speciation of the system depending on the pH more than from the shifting of the FIA diffusion profiles.     

Multivariate analytical sensitivity in the determination of selenium, copper, lead and cadmium by stripping voltammetry when using soft calibration

A new approach to the multivariate sensitivity concept based on the determination of the capability of discrimination of a method of analysis is shown. Thus the analytical sensitivity is defined in this work by the analyte concentration that a analytical method is able to discriminate, which implies the estimation of the ‘false noncompliance’ and ‘false compliance’. In this approach the estimation of the multivariate analytical sensitivity is independent of scale factors and calibration models, and allows one to study the behavior of a analytical method for several concentrations and matrix. The estimation of this parameter in the simultaneous determination of selenium, copper, lead and cadmium by stripping voltammetry when using soft calibration is carried out, showing that different multivariate analytical sensitivities are obtained for each metal.     

中药的补血作用与Fe元素含量相关性研究

目的通过对不同药效的中药Fe元素含量分析,探讨中药的补血作用与Fe元素含量的相关性。方法按中药药效选取药材并分组,每组样品微波消解后采用原子吸收光谱仪进行Fe元素含量测定。结果补血药组Fe元素含量最高,是其他组的1.5~5倍。结论中药的补血作用与Fe元素水平相关。     

7种补益中药微量元素的含量及溶出率测定

用原子吸收光谱法测定了7种补益中药中锌，铜，锰，铁，钙和镁含量及溶出率。结果显示，这6种元素的含量普遍较高，溶出率多数在80％以下，但在不同的中药中有一定的差异。     

Identification and quantification of carbamate pesticides in dried lime tree flowers by means of excitation-emission molecular fluorescence and parallel factor analysis when quenching effect exists

A non-separative, fast and inexpensive spectrofluorimetric method based on the second order calibration of excitation-emission fluorescence matrices (EEMs) was proposed for the determination of carbaryl, carbendazim and 1-naphthol in dried lime tree flowers. The trilinearity property of three-way data was used to handle the intrinsic fluorescence of lime flowers and the difference in the fluorescence intensity of each analyte. It also made possible to identify unequivocally each analyte. Trilinearity of the data tensor guarantees the uniqueness of the solution obtained through parallel factor analysis (PARAFAC), so the factors of the decomposition match up with the analytes. In addition, an experimental procedure was proposed to identify, with three-way data, the quenching effect produced by the fluorophores of the lime flowers. This procedure also enabled the selection of the adequate dilution of the lime flowers extract to minimize the quenching effect so the three analytes can be quantified. Finally, the analytes were determined using the standard addition method for a calibration whose standards were chosen with a D-optimal design.     

Phospholipidomic identification of potential plasma biomarkers associated with type 2 diabetes mellitus and diabetic nephropathy

Type 2 diabetes mellitus (T2DM) and its attendant complications, such as diabetic nephropathy (DN), impose a significant societal and economic burden. The investigation of discovering potential biomarkers for T2DM and DN will facilitate the prediction and prevention of diabetes. Phospholipids (PLs) and their metabolisms are closely allied to nosogenesis and aggravation of T2DM and DN. The aim of this study is to characterize the human plasma phospholipids in T2DM and DN to identify potential biomarkers of T2DM and DN. Normal phase liquid chromatography coupled with time of flight mass spectrometry (NPLC-TOF/MS) was applied to the plasma phospholipids metabolic profiling of T2DM and DN. The plasma samples from control (n = 30), T2DM subjects (n = 30), and DN subjects (n = 52) were collected and analyzed. The significant difference in metabolic profiling was observed between healthy control group and DM group as well as between control group and DN group by the help of partial least squares discriminant analysis (PLS-DA). PLS-DA and one-way analysis of variance (ANOVA) were successfully used to screen out potential biomarkers from complex mass spectrometry data. The identification of molecular components of potential biomarkers was performed on Ion trap-MS/MS. An external standard method was applied to quantitative analysis of potential biomarkers. As a result, 18 compounds in 7 PL classes with significant regulation in patients compared with healthy controls were regarded as potential biomarkers for T2DM or DN. Among them, 3 DM-specific biomarkers, 8 DN-specific biomarkers and 7 common biomarkers to DM and DN were identified. Ultimately, 2 novel biomarkers, i.e., PI C18:0/22:6 and SM dC18:0/20:2, can be used to discriminate healthy individuals, T2DM cases and DN cases from each other group.     

Integration of metabolomics and network pharmacology to validate the mechanism of Schisandra chinensis（Turcz.）Baill - Acorus tatarinowii Schott ameliorating the Alzheimer's disease by regulating the aromatase activity to affect local estrogen in brain of AD model rats

Alzheimer's disease (AD) is a latent and progressive neurodegenerative disease. Schisandra chinensis（Turcz.）Baill - Acorus tatarinowii Schott (Sc-At) are effective in treating neurological disorders.Purpose of this study is to explore the mechanism of Sc-At in AD treatment. First, untargeted ultra-performance liquid chromatography quadrupole-time of flight/mass spectrometer (UPLC-QTOF/MS) metabolomics was employed to detect the rat brain metabolism. Then, network pharmacology was used to determine the potential anti-AD targets. Bioinformatics, and molecular docking were conducted for further analysis. A MetScape study examined the association between differential metabolites and potential targets. Finally, the targeted ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) metabolomics and the potential protein activity studies were carried out to elucidate the mechanisms. The results showed that Sc-At improved the neuronal cell alignment disorder in hippocampal CA1 region of AD rats. In brain metabolomics, 30 differential metabolites were screened in the study model versus blank group. The network pharmacology analyzed 54 targets of Sc-At anti-AD where, 14 were correlated with amyloid β-protein (Aβ). Aromatase was selected as an important hub target having the best binding power in molecular docking simulation predictions and also correlated with Aβ. Further tests showed that the brain aromatase activity, and the downstream product 17β-Estradiol levels were elevated in AD rats treated with Sc-At. This work may provide new perspectives for the pharmacological effects and the action mechanisms of natural compounds extracts in treating AD progression.