核磁共振技术结合化学计量学方法用于蜂蜜的掺假鉴别

采用核磁共振技术(NMR)结合化学计量学分析手段研究了真蜂蜜和掺假蜂蜜的指纹图谱变化情况。采用无监督的主成分分析(PCA)和有监督的偏最小二乘判别分析(PLS-DA)、正交偏最小二乘判别分析(OPLS-DA)等多元统计分析方法从核磁信号中提取各组的分类信息。结果表明:建立的OPLS-DA模型能够区分真假蜂蜜,所建模型对蜂蜜真假判别的解释能力为90.5%,对未知样本的预测能力为75.5%、识别率为89.7%。置换测试验证表明,化学计量学模型具有很好的稳定性和预测性,可信赖性强,且模型稳健。通过OPLS-DA模型的载荷图和相关系数分析找到了对区分掺假蜂蜜有显著作用的标志物。结合相关系数分析,建立了辨别真假蜂蜜的多元线性回归方程。该方法可简单、快速地用于未知蜂蜜的掺假鉴别,为规范蜂蜜市场提供有利的依据。     

LF-NMR结合化学模式识别鉴别油脂种类及餐饮废弃油脂

应用主成分分析(Principal component analysis,PCA)和聚类分析法(Cluster analysis,CA)对9种(27个)常见食用植物油及100个餐饮废油的低场核磁共振(Low-field nuclear magnetic resonance,LF-NMR)(T2)弛豫特性数据进行分析。结果表明:在正常食用油种类区分方面,主成分分析的效果较优,9种食用油在主成分分布图上按种类正确分组,边界清晰。而在正常食用油与餐饮废油的区分方面,聚类分析效果较优,引入30个待测样本后,聚类分析(127个样品,欧式距离=5)的正确率为94.49%,分析误判率为5.51%,分组效果良好。LF-NMR结合化学模式识别可实现对油脂种类及餐饮废弃油脂的鉴别。     

拥挤环境中表面活性剂胶束化过程的低场核磁共振研究

利用长弛豫低场核磁共振(LF-NMR)方法研究了由聚乙二醇(PEG)构建的拥挤溶液环境中表面活性剂的聚集行为。通过Carr-Purcell-Meiboom-Gill(CPMG)脉冲序列所得的回波数据及反演拟合数据对不同的表面活性剂-PEG体系进行分析,结果发现:不同分子量和不同浓度的PEG溶液可用低场核磁共振方法进行区分;高浓度的PEG溶液中均能监测到胶束形成过程,而较低浓度的PEG溶液不利于其胶束化过程监测;NaCl对含有离子型表面活性剂体系的影响较为明显,而对含有非离子型表面活性剂的体系几乎无影响。该研究丰富了低场核磁共振弛豫技术在表面活性剂胶束表征过程中的应用,同时对理解生物体系中分子的自组装及功能也具有重要意义。     

油脂低场核磁(LF-NMR)检测参数的优化试验

适当的低场核磁共振(LF-NMR)检测条件对于保障数据的可靠性具有重要意义.该文研究了大豆油LF-NMR检测过程中仪器参数、样品温度及体积等对检测结果稳定性及重现性的影响.结果表明,将2.5mL油脂样品置于核磁试管中,并在32℃恒温10 min,采样前稳定1min,在TR =2000 ms,τ=200μs,EchoCount=5000个,NS =4次,TD=500050,SW=250 kHz参数条件下采集信号,可保证检测结果稳定可靠.研究结果可为后期应用LF-NMR技术进行油脂品质检测提供适当的检测条件参考.     

6种化学计量学法同时分光光度测定5组分的比较研究及食品分析

优化了在表面活性剂存在下以肉桂基荧光酮同时测定铝、铜、锰、锌、钴的显色折衷条件；比较研究了偏最小二乘、岭回归、多元线性回归、多元逐步回归、目标因子分析和卡尔曼滤波法用于这一体系同时测定此５组分的优缺点，结果表明对于此类所含各组分吸收光谱重叠严重且吸光度加和性欠佳体系，上述６法中以偏最小二乘和岭回归法为最适宜；经用于九种人工合成液和四种食品分析，均获满意结果，分析两种茶叶结果也与ＩＣＰ－ＡＥＳ法一致     

《化学计量学方法》（第二版）简介

《化学计量学方法》（第二版）在第一版的基础上补充了最新出现的化学计量学研究方法和最新的研究成果。该书包括了化学计量学的主要内容，全书共分15章，分别为误差及与数理统计基础、回归分析、相关分析和数据平滑、最优化方法、主成分分析和因子分析、偏最小二乘方法、多元校正及分辨、小波分析、遗传算法和模拟退火算法、人工神经网络法及在化学中的应用、模拟识别方法、化合物结构表征和构效关系研究、组合化学、谱图库检索和结构解析专家系统及实验设计。此外，为方便读者查阅，该书还将常用数据信息列为附表。     

漫反射光谱结合化学计量学方法无损分析彩绘文物颜料

为了对彩绘文物颜料进行无损判别分析,该文采集了12种彩绘常用颜料参考样品的漫反射光谱,根据光谱曲线外形将参考样品分为红黄色系及蓝绿色系两类。使用主成分分析(PCA)分别对两个色系参考样品的光谱数据集进行降维,抽提出最有代表性的3个主成分,利用成分得分散点图确认了颜料间的类间差异,并通过成分矩阵探讨了对该差异贡献率最高的光谱波长区间。在此基础上,采用线性判别分析(LDA)对PCA的分析结果进行建模,拟合判别函数并将其应用于2件颐和园仁寿殿上架彩画文物样品颜料的分析。基于样品判别得分散点图与各类别参考样品间的距离,判定文物使用的颜料分别为铁红和群青。研究表明,该文构建的判别函数能够准确区分颜料的种类,可用于彩绘文物样品的无损分析鉴别。文物样品的污染或老化可能会影响分析,需事先进行表面清理。     

药物水溶解度的QSAR研究和VolSurf参数

药物的水溶解度与其吸收密切相关。本文利用一种新的计算方法,VolSurf,预测药物的水溶解度并测定有利于药物水溶解度的主要分子特征。被测化合物包括26个结构不同的药物,通过偏最小二乘分析法,对药物水溶解度实验值与分子特征进行相关,得到较好的模型(r2=0.90,q2=0.77)。将化合物分为训练集和预测集进行相关分析,结果表明以18个化合物所建立的训练集模型对其余8个化合物有较好的预测能力,预测的标准偏差(SDEP)为0.59。参数分析表明分子与水相互作用的3个局部能量最小值越小,且它们之间的距离越大,对其水溶解度越有利;亲水性占主导因素的分子有高的水溶解度;分子的疏水性越强,在水中的溶解性越弱;大分子的溶解度较小分子溶解度低。     

化学计量学分光光度法同时测定钢铁中镧和铈

在pH 3．0的缓冲溶液中,镧(Ⅲ)、铈(Ⅲ)与偶氮胂-Ⅲ均发生高灵敏度的显色反应,生成稳定的配合物。其λmax均为657 nm,镧(Ⅲ)、铈(Ⅲ)含量在0～1．0 mg·L-1范围内符合比耳定律,两者吸收光谱严重重叠。采用偏最小二乘法和主成分分析法用于普碳钢、铸铁等试样中镧和铈的测定,合成试样分析结果的相对误差小于10％。     

基于氢核磁共振技术和化学计量学方法鉴别蜂蜜品种

利用氢核磁共振(~1H NMR)技术结合化学计量学方法对不同品种的蜂蜜进行鉴别。采集33个洋槐蜜、48个油菜蜜、63个荔枝蜜的核磁指纹图谱,对数据进行不同方式的预处理后,采用有监督的偏最小二乘判别分析(PLS-DA)和正交偏最小二乘判别分析(OPLS-DA)建立判别模型。结果表明,不同的数据预处理方式对模型解释能力和预测能力的影响较大,自标度化(UV)模式更适于蜂蜜核磁数据的分析。建立的OPLS-DA模型可有效地分离判别3种蜂蜜,所建模型对3种蜂蜜的判别解释能力达95.8%,对未知样本的预测能力为90.5%。因此,利用~1H NMR结合OPLS-DA方法可有效地实现不同品种蜂蜜的快速鉴别。     

Simultaneous Determination of Oil and Water in Soybean by LF-NMR Relaxometry and Chemometrics

A fast, non-destructive and eco-friendly method was developed to simultaneously determine the oil and water contents of soybean based on low field nuclear magnetic resonance(LF-NMR) relaxometry combined with chemometrics, such as partial least squares regression(PLSR). The Carr-Purcell-Meiboom-Gill(CPMG) magnetization decay data of ten soybean samples were acquired by LF-NMR and directly applied to the PLSR analysis. Calibration models were established via PLSR with full cross-validation based on the reference values obtained by the Soxhlet extraction method for measuring oil and oven-drying method for measuring water. The results indicate that the calibration models are satisfactory for both oil and water determinations; the root mean squared errors of cross-validation(RMSECV) for oil and water are 0.2285% and 0.0178%, respectively. Furthermore, the oil and water contents in unknown soybean samples were predicted by the PLSR models and the results were compared with the reference values. The relative errors of the predicted oil and water contents were in ranges of 1.25%-4.96% and 0.44%-2.49%, respectively. These results demonstrate that the combination of LF-NMR relaxometry with chemometrics shows great potential for the simultaneous determination of contents of oil and water in soybean with high accuracy.     

Rapid Classification and Recognition Method of the Species and Chemotypes of Essential Oils by ATR-FTIR Spectroscopy Coupled with Chemometrics

In the present work, the applicability of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, coupled with chemometric tools in recognizing essential oils (EOs) for routine control, was evaluated. EOs belonging to Mentha, Cymbopogon, and Lavandula families and to S. rosmarinus and T. vulgaris species were analyzed, and the performance of several untargeted approaches, based on the synergistic combination of ATR-FTIR and Partial Least Squares Discriminant Analysis (PLS-DA), was tested to classify the species and chemotypes. Different spectra pre-processing methods were employed, and the robustness of the built models was tested by means of a Receiver Operating Characteristic (ROC) curve and random permutations test. The application of these approaches revealed fruitful results in terms of sensitivity and specificity, highlighting the potentiality of ATR-FTIR and chemometrics techniques to be used as a sensitive, cost-effective, and rapid tool to differentiate EO samples according to their species and chemotype.     

低场核磁结合偏最小二乘回归预测含油污泥水和油含率

快速准确分析处理过程中含油污泥的含水率和含油率有助于现场评价其原油回收效率和优化处理工艺参数。以Dean-Stark装置测定的含油污泥样品的含水率和含油率作为参考值,利用低场核磁共振结合偏最小二乘回归法建立了样品含水率和含油率校正集模型,考察了回波衰减曲线和横向弛豫时间T2曲线对校正集模型性能的影响。结果表明,采用前者建立的校正集模型性能优于后者;在此基础上,建立了31个样品的含水率和含油率通用校正集模型,其含水率和含油率模型的决定系数(R2)分别为0.965 7和0.978 5,校正标准差(RMSECV)分别为2.73%和2.22%。利用3个不同批次采集的HZ-OS样品对该模型进行验证,对于含水率和含油率模型,其验证集R2分别为0.914 1和0.924 7,预测标准差(RMSEP)分别为1.85%和2.04%,与RMSECV值比较接近,说明该模型的稳定性较好,可用于准确分析样品的含水率和含油率。     

Characterization of Gasoline by 1H Nuclear Magnetic Resonance and Chemometrics

Automotive fuel adulteration is an old and significant problem. One common type of fuel adulteration is the addition of diesel to gasoline. Unsupervised models were developed through hierarchical cluster and principal component analysis models. Supervised models through partial least square discriminant analysis using ¹H nuclear magnetic resonance spectra as the input were used to classify samples as adulterated or unadulterated. Quantitative models were developed using partial least squares to determine the gasoline and diesel concentrations in the samples. This set contained samples composed of pure gasoline and anhydrous ethanol reproducing commercial gasoline and other samples treated with diesel. Hierarchical cluster and principal component analysis did not distinguish between adulterated and unadulterated samples except for the most adulterated materials. However, partial least square discriminant analysis classified 100% of the samples correctly. The partial least square algorithm provided excellent regression models for the gasoline and diesel content. The determination coefficient was 0.9920 for both models, whereas the root mean square error of cross-validation and root mean square error of prediction for the diesel model were 2.32 and 1.42%, respectively, and 2.40 and 1.38% for the gasoline model.     

Metabolic Profiling of Human Colorectal Cancer Using High Resolution 1H Nuclear Magnetic Resonance Spectroscopy

Colorectal cancer (CRC) is the third commonest malignancy cancer worldwide. Clear understandings of global metabolic profiling of the normal mucosa and cancer tissues are vitally important to aid optimizing the clinical management strategy and understanding CRC biology. We studied metabolic characteristics of 20 CRC and 20 distant normal mucosa tissues extracts from 20 patients using high resolution ¹H NMR spectroscopy in conjunction with multivariate analyses, such as principal component analysis (PCA). Compared with distant normal mucosa tissues, lactate, taurine, ornithine and polyamine were present at significantly higher levels in CRC tissue extracts whereas myo‐inositol was present at significantly lower level. Two metabolites ratios such as myo‐inositol/taurine and myo‐inositol/(ornithine+polyamine) appear to be the most valuable biomarkers for the differentiation CRC from normal mucosa tissues. Our data suggested that HR ¹H NMR spectroscopy combined with multivariate analyses is a potentially useful technology for detecting malignant changes in the normal mucosa tissues, the technique may be further exploited for future CRC biomarker research or identification of targets for therapeutic manipulations.     

Influence of the Extraction Method on the Quality and Chemical Composition of Walnut (Juglans regia L.) Oil

The present study investigated and compared the quality and chemical composition of Moroccan walnut (Juglans regia L.) oil. This study used three extraction techniques: cold pressing (CP), soxhlet extraction (SE), and ultrasonic extraction (UE). The findings showed that soxhlet extraction gave a significantly higher oil yield compared to the other techniques used in this work (65.10% with p < 0.05), while cold pressing and ultrasonic extraction gave similar yields: 54.51% and 56.66%, respectively (p > 0.05). Chemical composition analysis was carried out by GC–MS and allowed 11 compounds to be identified, of which the major compound was linoleic acid (C18:2), with a similar percentage (between 57.08% and 57.84%) for the three extractions (p > 0.05). Regarding the carotenoid pigment, the extraction technique significantly affected its content (p < 0.05) with values between 10.11 mg/kg and 14.83 mg/kg. The chlorophyll pigment presented a similar content in both oils extracted by SE and UE (p > 0.05), 0.20 mg/kg and 0.16 mg/kg, respectively, while the lowest content was recorded in the cold-pressed oil with 0.13 mg/kg. Moreover, the analysis of phytosterols in walnut oil revealed significantly different contents (p < 0.05) for the three extraction techniques (between 1168.55 mg/kg and 1306.03 mg/kg). In addition, the analyses of tocopherol composition revealed that γ-tocopherol represented the main tocopherol isomer in all studied oils and the CP technique provided the highest content of total tocopherol with 857.65 mg/kg, followed by SE and UE with contents of 454.97 mg/kg and 146.31 mg/kg, respectively, which were significantly different (p < 0.05). This study presents essential information for producers of nutritional oils and, in particular, walnut oil; this information helps to select the appropriate method to produce walnut oil with the targeted quality properties and chemical compositions for the desired purpose. It also helps to form a scientific basis for further research on this plant in order to provide a vision for the possibility of exploiting these oils in the pharmaceutical, cosmetic, and food fields.     

Liver functional magnetic resonance imaging analysis using a latent variables approach

The liver is a highly vascular organ with a dual blood supply, and it performs a remarkable number of vital functions. Here, we show, through measurement of blood oxygen level‐dependent (BOLD) signal, that liver arterial and hepatic portal blood supplies can be modulated through hyperoxia exposure and by consumption of a standardized meal, respectively. As such, we suggest that hyperoxia modulates the hepatic arterial BOLD signal, whereas a controlled meal changes predominantly the hepatic portal BOLD signal. The hemodynamics of the dual liver blood supplies in response to the aforementioned challenges are complex and variable across subjects, making a general linear model‐based analysis difficult. Therefore, we present the application of two local (at each voxel) hemodynamic response‐independent techniques—principal component analysis and partial least squares—to observe the hypothesized reduction in BOLD contrast during cycles of hyperoxic breathing, when comparing preprandial versus postprandial states in a normally functioning liver. We illustrate the ability of our techniques to differentiate between healthy and diseased livers with an analysis of 17 subjects—11 with normal livers and 6 with liver disease (hepatitis or cirrhosis). Our local analysis can correctly classify all of the subjects. Copyright © 2012 John Wiley & Sons, Ltd.