基于气相色谱-质谱联用的血府逐瘀汤治疗大鼠颅脑损伤的血浆代谢组学研究

该文研究了血府逐瘀汤对颅脑损伤大鼠血浆代谢组的影响,采用气相色谱-质谱联用(GC-MS)技术对治疗组、模型组以及假手术组的血浆代谢物进行检测,定性定量分析了43种重要的代谢物。模型组和假手术组的t检验(t-test)结果显示13种代谢物存在显著差异。正交偏最小二乘-判别分析(OPLS-DA)分析结果也显示模型组和假手术组代谢差异明显。结合变量的投影重要性指标(VIP)及t检验结果,筛选出乳酸、组氨酸、棕榈酸、色氨酸、亚油酸、油酸、硬脂酸作为生物标志物。观测7种标志物在治疗组中第1、3、7、14 d的变化情况。结果显示:治疗组中乳酸、组氨酸、棕榈酸、亚油酸、硬脂酸的相对浓度逐渐降低,色氨酸的相对浓度先降低后升高,油酸的相对浓度先升高后降低,且7种代谢物的相对浓度在第14 d时均接近于假手术组的水平。表明血府逐瘀汤对颅脑损伤具有一定的治疗作用,乳酸、组氨酸、棕榈酸、色氨酸、亚油酸、油酸、硬脂酸7种代谢物可以作为生物标志物监测颅脑损伤的治疗效果及恢复情况。     

色谱指纹图谱与中药质量控制

本文综述了近年来色谱指纹图谱研究中多种色谱技术、相关化学计量学方法的发展及其在中药质量控制中的应用,并对中药质量稳定性和有效性的全面评价方法和可行性进行了初步探讨。提出以色谱指纹图谱为核心,依托现代色谱技术、化学计量学和系统生物学方法,建立中药化学成分信息与药效(毒性)信息相关关系的中药质量控制研究策略,深层次揭示中药的内在作用机理,期望真正实现中药质量的可控、安全和有效。     

过程分析化学的新进展

综述了国外过程分析化学（PAC）的最新进展,内容包括过程量测、传感器、化学计量学等,并展望了PAC的发展趋势。引用文献62篇。     

State-of-the-art advantages and drawbacks on the application of vibrational spectroscopy to monitor alcoholic fermentation (beer and wine)

Wine production is directly linked with the monitoring of the fermentation and critical fermentation parameters such as total sugars and ethanol concentration, and the production of CO₂. Commonly used sensors applied in the wine industry to monitor wine fermentation are those based in single sensors such as temperature probes and manual density measurements (e.g., specific gravity). These sensors are used several times per day and have been the only source of data available from which the stage of the fermentation and the evolution rate could be monitored. Therefore, an ideal method for fermentation process control and monitoring should enable a direct rapid, precise, and accurate determination of several target compounds, with minimal or no sample preparation and reagent consumption. This article reviews the state of the art in the applications of both near and mid infrared spectroscopy to monitor beer and wine fermentation.     

OPLS in batch monitoring – Opens up new opportunities

In batch statistical process control (BSPC), data from a number of “good” batches are used to model the evolution (trajectory) of the process and they also define model control limits, against which new batches may be compared. The benchmark methods used in BSPC include partial least squares (PLS) and principal component analysis (PCA).     

Untargeted metabolomic profiling of seminal plasma in nonobstructive azoospermia men: A noninvasive detection of spermatogenesis

Male factor infertility is involved in almost half of all infertile couples. Lack of the ejaculated sperm owing to testicular malfunction has been reported in 6–10% of infertile men, a condition named nonobstructive azoospermia (NOA). In this study, we investigated untargeted metabolomic profiling of the seminal plasma in NOA men using gas chromatography–mass spectrometry and advance chemometrics. In this regard, the seminal plasma fluids of 11 NOA men with TESE‐negative, nine NOA men with TESE‐positive and 10 fertile healthy men (as a control group) were collected. Quadratic discriminate analysis (QDA) technique was implemented on total ion chromatograms (TICs) for identification of discriminatory retention times. We developed multivariate classification models using the QDA technique. Our results revealed that the developed QDA models could predict the classes of samples using their TIC data. The receiver operating characteristic curves for these models were >0.88. After recognition of discriminatory retention time's asymmetric penalized least square, evolving factor analysis, correlation optimized warping and alternating least squares strategies were applied for preprocessing and deconvolution of the overlapped chromatographic peaks. We could identify 36 discriminatory metabolites. These metabolites may be considered discriminatory biomarkers for different groups in NOA.     

Investigation of the pharmacokinetics and determination of certain cephalosporins in rabbit plasma by a kinetic spectrophotometric method with the aid of chemometrics

This paper describes a kinetic spectrophotometric method for simultaneous determination of three cephalosporin antibiotics,cephradine,cefaclor and cefixime,with the aid of chemometrics. The method relies on their oxidation with KMnO4 to produce green manganate with different kinetic rates in alkaline medium. The proposed method was successfully applied to a pharmacokinetic study of three cephalosporin antibiotics in rabbit plasma via intravenous injections. The results indicated that the amount of cephradin...     

Non‐targeted volatile profiles for the classification of the botanical origin of Chinese honey by solid‐phase microextraction and gas chromatography–mass spectrometry combined with chemometrics

A potential method for the discrimination and prediction of honey samples of various botanical origins was developed based on the non‐targeted volatile profiles obtained by solid‐phase microextraction with gas chromatography and mass spectrometry combined with chemometrics. The blind analysis of non‐targeted volatile profiles was carried out using solid‐phase microextraction with gas chromatography and mass spectrometry for 87 authentic honey samples from four botanical origins (acacia, linden, vitex, and rape). The number of variables was reduced from 2734 to 70 by using a series of filters. Based on the optimized 70 variables, 79.12% of the variance was explained by the first four principal components. Partial least squares discriminant analysis, naïve Bayes analysis, and back‐propagation artificial neural network were used to develop the classification and prediction models. The 100% accuracy revealed a perfect classification of the botanical origins. In addition, the reliability and practicability of the models were validated by an independent set of additional 20 authentic honey samples. All 20 samples were accurately classified. The confidence measures indicated that the performance of the naïve Bayes model was better than the other two models. Finally, the characteristic volatile compounds of linden honey were tentatively identified. The proposed method is reliable and accurate for the classification of honey of various botanical origins.     

Screening of textiles for contraband drugs using portable Raman spectroscopy and chemometrics

The impregnation of items of clothing with drugs of abuse that are then smuggled through airports and ports of entry is a growing problem for law enforcement. This work describes the application of portable Raman spectroscopic techniques for the analysis of a range of natural and artificial fibre items of clothing impregnated with drugs of abuse. Textile pieces were soaked with the solutions of the drugs then left overnight to dry prior to spectroscopic examination. The feasibility of detection of the characteristic Raman spectral bands in the presence of background matrix signals is demonstrated, even for dyed clothing. Definitive evidence for contamination of the items of clothing concerned can be acquired within 20–25 s, without any form of sample pre‐treatment or extraction being necessary. The feasibility of automatic spectral recognition of such illicit materials by Raman spectroscopy has been investigated by searching a database stored on the spectrometer computer and the use of principal component analysis. Copyright © 2014 John Wiley & Sons, Ltd.     

Simultaneous enzymatic kinetic determination of carbamate pesticides with the aid of chemometrics

A method for the simultaneous enzymatic kinetic determination of the pesticides, oxamyl, aldicarb and aminocarb in fruit, vegetables and water samples, has been researched and developed. It was based on enzymatic reaction kinetics and spectrophotometric measurements, and results were interpreted with the aid of chemometrics. The analytical method relies on the inhibitory effect of the pesticides on acetylcholinesterase (AChE), and the use of 5,5′-dithiobis (2-nitrobenzoic) acid (DTNB) as a chromogenic reagent for the thiocholine iodide (TChI) released from the acetylthiocholine iodide (ATChI) substrate. The complex rate equation for the formation of the chromogenic product, P, was solved under certain experimental conditions, and this enabled the absorbance (A _p, at λ _max = 412 nm) from the mixtures of the three pesticide inhibitors to be directly related to their concentrations. The detection limits of the enzymatic kinetic spectrophotometric procedures for the determination of the oxamyl, aldicarb and aminocarb were 0.81, 2.13 and 1.25 ng mL^?1, respectively. Calibration models were constructed for principal component regression (PCR), partial least squares (PLS), and radial basis function-artificial neural network (RBF-ANN), and verified with synthetic samples of the three pesticides. The prediction performance of these models showed generally satisfactory results, and the RBF-ANN one performed slightly better than the other two (RPE_T = 7.59% and average %recovery = 99%). This model was then successfully applied to estimate the amounts of the three compounds in fruit, vegetables and water with satisfactory results.