三维荧光二阶校正法用于尿液样中氢化可的松的定量测定

本文提出了三维荧光光谱结合二阶校正算法实现人体尿液样中氢化可的松定量测定的新方法。氢化可的松本身的荧光较弱,但与浓硫酸反应后可以生成强荧光的化合物。利用这一特性,采用浓硫酸为氧化剂,设定在激发波长为300-370nm、发射波长为400-580nm范围内测定尿液样中氢化可的松的三维荧光光谱,构建三维响应数据阵,然后运用基于三线性分解的二阶校正算法进行解析。当组分数N取3时,采用基于平行因子分析（PARAFAC）算法的Z-阶校正法的平均回收率为98.6±4.1％,预测残差平方根（RMSEP）为0.0114;采用基于满秩平行因子分析（FRA-PARAFAc）算法的二阶校正法的平均回收率和RMSEP分别为99.3±2.4％和0.0066。两种算法可以得到相近且满意的结果。     

菜籽油热氧化过程中荧光光谱特征的变化研究

为探讨菜籽油热氧化过程中荧光光谱特征的变化规律,采用平行因子分析方法结合二维相关技术解析菜籽油的三维同步荧光光谱,并与油脂氧化化学指标进行相关分析。结果表明:菜籽油具有叶绿素a的荧光特征(Δλ=10 nm,λex=674 nm)和叶绿素b的荧光特征(Δλ=60 nm,λex=620 nm);热氧化过程中,产生了(Δλ=60 nm,λex=448 nm)的特征同步荧光峰。双因子的平行因子分析表明:Δλ为10和60 nm的同步荧光光谱分别为第一、第二主要成分,分别对应叶绿素a和油脂氧化产物的荧光特征;随着热氧化时间的延长,叶绿素a的同步荧光强度降低,而油脂氧化产物的同步荧光强度逐渐升高。二维相关分析表明,叶绿素a热氧化速度、叶绿素b热氧化速度、油脂氧化产物生成速度依次降低。代表叶绿素氧化程度的SFI674和代表油脂氧化产物产量的SFI448与油脂氧化化学指标具有良好的相关性。因此,同步荧光光谱可作为衡量食用油热氧化劣变的指标。     

三维荧光光谱二阶校正方法测定血浆样中喷昔洛韦及泛昔洛韦含量

利用三维荧光光谱即激发发射矩阵荧光光谱与化学计量学的基于平行因子分析(PARAFAC)算法的二阶校正方法相结合,尝试对血浆样中泛昔洛韦及其活性代谢物喷昔洛韦的含量进行同时定量测定.当算法选取组分数为3时,解析得到血浆样中泛昔洛韦和喷昔洛韦的平均回收率分别为(102.4±3.4)%和(105.1±2.3)%.结果表明该分析策略可准确可靠地实现血浆样中泛昔洛韦和喷昔洛韦的直接同时快速定量测定.     

三维荧光二阶校正法用于尿液样和血浆样中左旋多巴的定量测定

本文采用激发发射荧光光谱分别与化学计量学中平行因子分析(PARAFAC)和交替三线性分解(ATLD)二阶校正法相结合,对尿液样和血浆样中左旋多巴含量进行定量测定。实验不需对尿液和血浆预测样进行萃取等分离预处理。在尿液样中,当组分数取2时,用PARAFAC算法和ATLD算法获得的平均回收率分别为(98.9±2.3)%和(99.6±2.8)%。在血浆样中,当组分数取3时,PARAFAC算法和ATLD算法获得的平均回收率分别为(103.1±3.7)%和(99.2±4.2)%。研究结果表明,该法能够解决尿液样和血浆样中左旋多巴因尿液和血浆内源物质与待分析物光谱重叠所引起的难分辨的问题,可用于未知干扰共存下左旋多巴含量的直接快速定量测定。     

交替拟合残差算法与高效液相色谱-二极管阵列检测方法结合同时测定两种抗结核药物

本文利用化学计量学交替拟合残差(AFR)算法与高效液相色谱-二极管阵列检测(HPLC-DAD)方法相结合,同时测定两种抗结核药物异烟肼和吡嗪酰胺的含量。该法与交替三线性分解算法(ATLD)、自加权交替三线性分解(SWATLD)算法相比较,从预测均方差、预测相对误差以及平均回收率等结果来看,其预测结果更接近实际值。研究表明,基于交替拟合残差等算法的二阶校正法,可以迅速准确地给出色谱重叠情况下两个组分的预测结果,是复杂体系成分直接定量分析的一个有力的化学计量学工具。     

三维荧光二阶校正法同时测定水果样中α-萘乙酸和吲哚-3-乙酸

将三维荧光光谱技术与分别基于交替惩罚三线性分解(APTLD)和平行因子分析(PARAFAC)2种算法的二阶校正方法相结合,实现了水果样中α-萘乙酸(NAA)和吲哚-3-乙酸(IAA)含量的直接快速同时定量测定.对于西瓜提取液,在量测体系选取的组分数为3时,采用APTLD二阶校正法所获得的NAA和IAA的平均回收率分别为...     

同步荧光法同时测定溶解态的菲与2-乙基菲

将同步荧光法结合人工神经网络(ANN)和支持向量回归(SVR)用于混合体系中荧光光谱重叠的菲(Phe)和2-乙基菲(2-EP)两组分的同时测定。通过三维同步荧光法结合平行因子(PARAFAC)分析寻得Phe和2-EP的特征波长差Δλ为118 nm。在220~280 nm范围内,以31个波长处荧光强度值作为模型的输入变量用于建立ANN和SVR模型。结果显示,ANN模型分析Phe和2-EP预测样本的回收率分别为92.5%~104.9%和96.1%~104.3%,预测均方根误差(RMSEP)分别为2.08和2.95;SVR模型分析预测样本的回收率分别为98.2%~101.3%和94.9%~104.2%,RMSEP分别为0.74和2.42。实际水样的加标回收实验显示,基体简单的矿泉水中两种模型均取得满意结果;而基体复杂的湖水中样品预测值较实际值低,且SVR模型比ANN的预测性能更加稳健,泛化能力更强。将同步荧光法结合SVR模型应用于Phe和2-EP单独及混合状态下与腐植酸(HA)相互作用的研究,结果显示混合体系中Phe和2-EP与HA的结合系数均小于各自单组分体系,表明Phe和2-EP之间存在竞争吸附。     

交替三线性分解二阶校正法结合高效液相色谱同时测定合成样与增效联磺片中的磺胺嘧啶及磺胺甲噁唑

利用交替三线性分解(ATLD)二阶校正法与高效液相色谱-二极管阵列检测器(HPLC-DAD)联用技术相结合,取色谱洗脱时间为1.0770～1.6237 min(间隔1/75 min),紫外吸收波长为230～316 nm(间隔2 nm),同时测定了在未知干扰物(磺胺(SN))共存下,合成样与增效联磺片中色谱及光谱皆严重重叠的磺胺嘧啶(SD)和磺胺甲噁唑(SM)的含量.当算法因子数N选定为3时,SD与SM的平均回收率分别为98.6±1.4%和100.7±3.7%; 当N=4时,SD与SM的平均回收率分别为101.2±2.1%和96.3±2.8%,增效联磺片中SD和SM的解析含量分别为195 mg/tablet和197 mg/tablet(N=3)以及198 mg/tablet,193 mg/tablet(N=4)(SD和SM药品标示含量均为200 mg/tablet),测定结果与实际结果相一致.     

同步扫描-双波长荧光分光光度法同时测定三种儿茶酚胺类神经递质

提出了用同步扫描-双波长荧光分光光度法同时测定肾上腺素(EP)、去甲肾上腺素素(NEP)和多巴胺(DA)3种儿茶酚胺类神经递质.试验表明:荧光检测宜选定发射波长(λen)与激发波长(λex)的波长差为70 nm(△λ=λem-λex)的条件下进行同步扫描.在λem为385.0 nm时DA的荧光信号不受EP和NEP的干扰,而EP和NEP相互的干扰,采用双波长荧光检测模式可消除.选择测定NEP的波长对为470.0 nm(λem,1)和531.8 nm(λem,2),测定EP的波长对为500.0 nm(λ'em,1)和445.6 nm(λ'em,2).测得荧光强度与3种儿茶酚胺浓度在320 μg·L-1(EP),640 μg·L-1(NEP)及160μg·L-1(DA)内呈线性关系,检出限(3σ/k)依次为0.20,0.97,0.73 μg·L-1.     

导数同步荧光光谱-小波-SGA-LSSVR联用快速测定鸭蛋蛋清中新霉素残留含量

新霉素在巯基乙醇存在的条件下与邻苯二甲醛生成的衍生物具有强荧光特性,可实现鸭蛋蛋清中新霉素残留含量的荧光测定。在模型建立过程中,分析了波长为280～390 nm光谱范围内的三维同步荧光光谱,确定检测鸭蛋蛋清中的新霉素含量的最佳波长差Δλ为110 nm;然后利用db10小波的2层分解对一阶导数同步荧光光谱进行去噪处理,并利用分段遗传算法(SGA)优选出了14个特征波长;最后应用最小二乘支持向量回归(LSSVR)建立了鸭蛋蛋清中的新霉素含量的预测模型,其模型预测集的决定系数(R2)和预测均方根误差(RMSEP)分别为0.9671和1.713。结果表明,SGA能有效提取出鸭蛋蛋清中新霉素对应的特征波长,有利于提高LSSVR模型预测精度,可实现鸭蛋蛋清中新霉素残留含量的快速测定。     

三维荧光二阶校正法用于未知混合物中苯酚含量的测定

将三维荧光光谱技术与秩消失因子分析、广义秩消失因子分析和交替三线性分解3种二阶校正方法相结合,建立了测定未知混合物中苯酚含量的三维荧光二阶校正新方法。设定在激发波长240~280 nm和发射波长280~360 nm范围内测定未知混合物中苯酚的三维荧光光谱,构建三维响应数据阵,运用基于三线性分解的二阶校正算法进行解析。结果表明,当模拟样品的组分数为2时,秩消失因子分析、广义秩消失因子分析和交替三线性分解3种方法测定苯酚的预测均方根误差分别为0.33,1.18和0.15,平均回收率分别为101.6%,115.6%和101.9%;当组分数为3时,3种方法的预测均方根误差则分别为1.61,1.80和0.51,平均回收率分别为134.2%,133.9%和107.1%;将其分别应用于实际样品中苯酚的测定,结果满意,且交替三线性分解法的测定结果优于秩消失因子分析法和广义秩消失因子分析法。     

Determination of captopril in pharmaceutical preparation and biological fluids using two- and three-way chemometrics methods

Spectrophotometric method has been developed for the direct quantitative determination of captopril in pharmaceuticalpreparation and biological fluids(human plasma and urine)samples.The method was accomplished based on parallel factoranalysis(PARAFAC)and partial least squares(PLS).The study was carried out in the pH range from 2.0 to 12.8 and with aconcentration from 0.70 to 61.50 μg mL~(-1)of captopril.Multivariate calibration models such as PLS at various pH and PARAFACwere elaborated from ultraviolet spectra deconvolution and captopril determination.The best models for this system were obtainedwith PARAFAC and PLS at pH 2.0.The applications of the method for determination of real samples were evaluated by analysis ofcaptopril in pharmaceutical preparations and biological fluids with satisfactory results.The accuracy of the method,evaluatedthrough the RMSEP,was 0.5801 for captopril with best calibration curve by PARAFAC and 0.6168 for captopril with PLS at pH 2.0model.     

Second-order calibration of excitation-emission matrix fluorescence spectra for determination of glutathione in human plasma

A rapid non-separative spectroflourimetric method based on the second-order calibration of the excitation-emission data matrix was proposed for the determination of glutathione (GSH) in human plasma. In the phosphate buffer solution of pH 8.0 GSH reacts with ortho-phthaldehyde (OPA) to yield a fluorescent adduct with maximum fluorescence intensity at about 420 nm. To handle the interfering effects of the OPA adducts with aminothiols other than GSH in plasma as well as intrinsic fluorescence of human plasma, parallel factor (PARAFAC) analysis as an efficient three-way calibration method was employed. In addition, to model the indirect interfering effect of the plasma matrix, PARAFAC was coupled with standard addition method. The two-component PARAFAC modeling of the excitation-emission matrix fluorescence spectra accurately resolved the excitation and emission spectra of GSH, plasma (or plasma constituents). The concentration-related PARAFAC score of GSH represented a linear correlation with the concentration of added GSH, similar to that is obtained in simple standard addition method. Using this standard addition curve, the GSH level in plasma was found to be 6.10 ± 1.37 μmol L⁻¹. The accuracy of the method was investigated by analysis of the plasma samples spiked with 1.0 μmol L⁻¹ of GSH and a recovery of 97.5% was obtained.     

Application of unfold principal component analysis and parallel factor analysis to the exploratory analysis of olive oils by means of excitation-emission matrix fluorescence spectroscopy

Discrimination between virgin olive oils and pure olive oils is of primary importance for controlling adulterations. Here, we show the potential usefulness of two multiway methods, unfold principal component analysis (U-PCA) and parallel factor analysis (PARAFAC), for the exploratory analysis of the two types of oils. We applied both methods to the excitation-emission fluorescence matrices (EEM) of olive oils and then compared the results with the ones obtained by multivariate principal component analysis (PCA) based on a fluorescence spectrum recorded at only one excitation wavelength. For U-PCA and PARAFAC, the ranges studied were λ_ex=300-400 nm, λ_em=400-695 nm and λ_ex=300-400 nm, λ_em=400-600 nm. The first range contained chlorophylls, whose peak was much more intense than those of the rest of species. The second range did not contain the chlorophylls peak but only the fluorescence spectra of the remaining compounds (oxidation products and Vitamin E). The three-component PARAFAC model on the second range was found to be the most interpretable. With this model, we could distinguish well between the two groups of oils and we could find the underlying fluorescent spectra of three families of compounds.     

Determination of Riboflavin in Human Plasma by Excitation‐Emission Matrix Fluorescence and Multi‐Way Analysis

Direct determination of riboflavin (Fig. 1), a vitamin, in human plasma was accomplished based on excitation‐emission matrix (EEM) fluorescence measurements and multi‐way chemometrics method based on parallel factor analysis (PARAFAC). The PARAFAC trilinear model, without restrictions and using one factor was used in the data analysis. The excitation wavelength range was from 380 to 460 nm and the emission was recorded from 480 to 600 nm. The calibration set was constructed with sixteen standard solutions in a concentration range of 0.02–0.38 μg mL^?1 for riboflavin. The capabilities of the method for the analysis were evaluated by determination of riboflavin in synthetic and real samples with satisfactory results. The accuracy of the methods, evaluated through the root mean square error of prediction (RMSEP), was 0.0059 for riboflavin by the PARAFAC model. Also, partial least squares (PLS) model was built at one excitation wavelength and used to determine a set of synthetic and real samples. The best model was obtained with PARAFAC. This result shows that molecular fluorescence spectroscopy can be used for the development of robust analytical methods for the direct determination of riboflavin in complex backgrounds such as human plasma.     

Three- and four-way parallel factor (PARAFAC) analysis of photochemically induced excitation-emission kinetic fluorescence spectra

Independently emerging fluorescence profiles of unknown, photochemically induced degradation products of several naturally non-fluorescent pesticides were monitored using single exposure excitation-emission fluorescence spectroscopy. Three-way parallel factor analysis (PARAFAC) was employed to uniquely resolve the pure fluorescent spectra of the overlapping photolysis products. The quantitative utility of EEM photolysis-based determinations was demonstrated by employing four-way PARAFAC models built from EEM time cubes of multiple fenvalerate samples. The 4-way PARAFAC models were then used to predict original pesticide concentrations resulting in conservative limit of detection and root mean square errors of calibration (RMSEC) of 3 microM each.     

Two- and three-way chemometrics methods applied for spectrophotometric determination of lorazepam in pharmaceutical formulations and biological fluids

In this work, direct determination of lorazepam, an anxiolytic and sedative agent, in pharmaceutical formulations and biological fluids (urine and human plasma) was accomplished based on ultraviolet spectrophotometry (260-380 nm) using parallel factor analysis (PARAFAC) and partial least squares (PLS). The study was carried out in the pH range from 1.0 to 12.0 and with a concentration range from 0.50 to 8.75 μg ml⁻¹ of lorazepam. Multivariate calibration models using PLS at different pH and PARAFAC were elaborated for ultraviolet spectra deconvolution and lorazepam quantitation. The best models for the system were obtained with PARAFAC and PLS at pH = 2.05 (PLS-PH2). The capabilities of the method for the analysis of real samples were evaluated by determination of lorazepam in pharmaceutical preparations and biological (urine and plasma) fluids with satisfactory results. The accuracy of the method, evaluated through the root mean square error of prediction (RMSEP), was 0.0429 for lorazepam with best calibration curve by PARAFAC and 0.0467 for lorazepam with PLS model at best pH. The protolytic equilibria of lorazepam at 25 °C and ionic strength of 0.1 M have also been determined spectrophotometrically. Protolytic equilibria of lorazepam were evaluated by DATAN program using the corresponding absorption spectra-pH data. The obtained pK_a values of lorazepam are 1.54 and 11.61 for pK_a1 and pK_a2, respectively.     

Fluorescence determination of metoprolol in human plasma by trilinear decomposition-based calibration techniques

In this study a new spectrofluorimetric method for the direct determination of metoprolol in human plasma is presented and discussed. It is based on the use of fluorescence excitation–emission matrices (EEMs) and second-order calibration performed with parallel factor analysis (PARAFAC) or alternating trilinear decomposition (ATLD). This methodology enables accurate and reliable discrimination of the analyte signal, even in the presence of unknown and uncalibrated fluorescent component(s), which is often referred to as the second-order advantage. No separation or sample pretreatment steps were required. Satisfactory results were obtained. Metoprolol recoveries in plasma were determined as 87±2% and 90±4% with PARAFAC and ATLD, respectively. All RSD values of intra- and interday assays were below 5%. Figure A three-dimensional plot of EEMs for a plasma sample and metoprolol solution     

基于三维荧光光谱的乳制品脂氧化判别方法

为快速、无损判别乳制品脂氧化程度,提出了利用乳制品三维荧光光谱的氧化水平进行判别的方法。该方法用平行因子分析对荧光矩阵进行分解,用载荷向量组确定脂氧化过程中的光敏成分,用不同成分得分向量对样本进行聚类,并建立了不同氧化水平样本的偏最小二乘判别模型。实验采集不同存储环境下氧化程度各异的酸奶样本,找出了核黄素等荧光团在脂氧化过程中的变化规律,选取得分向量建立偏最小二乘判别模型对不同存储阶段氧化程度各异的样本判别分类,其特异度和灵敏度达88.9%以上,验证了该法对评判乳制品脂氧化水平的有效性。     

基于平行因子分析法解析遥感傅里叶变换红外光谱谱图

本研究利用平行因子分析法(PARAFAC)完成了甲苯、苯和甲醇三组分体系的遥感傅里叶变换红外光谱(FTIR)谱图的同时定性定量分析.在有丙酮干扰情况下,定量分析的误差分别在6.61、18.76、16.00以下.将PARAFAC的输出结果作为偏最小二乘法(PLSDA)模型输入,实现了定性分析的自动完成.对主动式下数据定性分析的识别率和拒绝率均为100%,对被动式下数据的拒绝率为90%,识别率为85%.分析结果表明,PARAFAC可以同时进行定性定量分析,避免了干扰物存在的影响,可以满足遥感FTIR对多组分体系的实时、在线监测的需要.