Multiblock variance partitioning: a new approach for comparing variation in multiple data blocks

More than one multi-informative analytical technique is often applied when describing the condition of a set of samples. Often a part of the information found in these data blocks is redundant and can be extracted from more blocks. This study puts forward a method (multiblock variance partitioning—MVP) to compare the information/variation in different data blocks using simple quantitative measures. These measures are the unique part of the variation only found in one data block and the common part that can be found in more data blocks. These different parts are found using PLS models between predictor blocks and a common response. MVP provides a different view on the information in different blocks than normal multiblock analysis. It will be shown that this has many applications in very diverse fields such as process control, assessor performance in sensory analysis, efficiency of preprocessing methods and as complementary information to an interval PLS analysis. Here the ideas of the MVP approach are presented in detail using a study of red wines from different regions measured with GC-MS and FT-IR instruments providing different kinds of data representations.     

~(13)C代谢通量分析

代谢通量分析(metabolic flux analysis,MFA)是通过确定代谢网络中代谢流分布来表征细胞代谢状态的强有力的工具。鉴于计量学代谢通量分析在处理复杂代谢网络时表现出的局限性,发展了以13C标记实验为基础的13C MFA。本文介绍了13C MFA的原理与方法,总结和评述了13C MFA在实验与数据分析方面的最新进展以及MFA在功能基因组研究中的重要地位,同时对代谢通量分析的发展前景进行了展望。     

Gas solubility and permeability in MFA

An experimental analysis has been performed in this work, aimed to the characterization of thermodynamic and mass transport properties of a semicrystalline fluoro polymer (MFA) obtained from the copolymerization of tetrafluoroethylene (TFE) and perfluoromethylvinylether. Sorption and permeation experiments for two alkanes and corresponding perfluorinated compounds in MFA were performed at two different temperatures and solubility coefficients, as well as diffusivity and permeability, were determined. Experimental data were analyzed through different thermodynamic models to draw general conclusions about properties of MFA polymeric phases. Special attention was devoted to the glassy nature of MFA polymeric mixtures around room temperature. Indeed, analysis of experimental sorption data was performed through the use of specific models for glassy polymeric phases as well as by means of classical equilibrium models for fluid mixtures. Conclusions have been drawn from the aforementioned analysis, which significantly contributes to the discussion of correct location of glass‐transition temperature for PTFE and its copolymers. © 2007 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 45: 1637–1652, 2007     

Uncommon multivariate statistical methods for environmental studies: A review

In this paper we describe the characteristics and the applications of the multivariate methods for spectroscopic and chromatographic techniques independent component analysis (ICA) and two-dimensional correlation spectroscopy (2DCOS) focused to their use in environmental studies. In our opinion, these methods are important because they allow to characterize environmental samples with different aims and scopes from those generally obtained by means of more common multivariate methods such as principal component analysis (PCA) and partial least squares (PLS). The new insights of these methods in recent environmental studies are reviewed and debated.     

Automatic system for rapid analysis of volatile compounds by purge-and-cold-trapping/capillary gas chromatography

A system for automatic analysis of volatile compounds by purge-and-cold-trapping/capillary gas chromatography is described. It is suitable for analysis of volatile compounds in a wide variety of samples, such as water, food products and environmental samples. Possibilities and limitations of the system are evaluated in relation to several parameters. The efficiency of different types of cryogenic trap (open tubular, coated, packed) is also investigated; it depends on purge-flow rate, temperature of trapping, and total purge volume. Examples of the analysis of volatile compounds in foods and water are given.     

A high-performance liquid chromatographic method for the determination of monofluoroacetate

A simple isocratic high-performance liquid chromatographic (HPLC) method for the quantitative analysis of monofluoroacetic acid (MFA), the toxic substance of Dichapetalum cymosum, in plant material, rumen contents (gastric contents), and liver samples is described. A suitable HPLC column that gives optimum sensitivity, accuracy, precision, and separation of MFA is identified. A C-610 organic acid analysis column at ambient temperature with 0.02M H3PO4 as an eluent and ultraviolet detection at 210 nm is utilized to quantitate MFA. Using this method, the average percentage recovery in plant material, bovine liver, and rumen samples is 94.8%, and a detection limit of 12 microg/L is achievable.     

碳点在抗生素分析检测中的应用

抗生素的过度使用对环境造成了极大破坏,对其进行监测控制刻不容缓.常用的分析检测技术,如高效液相色谱(HPLC)、气相色谱(GC)、高效液相色谱-串联质谱(HPLC-MS/MS)等具有高效快速、重现性好、可自动化操作等优点.但对环境样品中抗生素的检测存在样品前处理过程繁琐、检测灵敏度低、实验成本高等问题.结合现有的检测技...     

基于化学模式识别的大蒜傅里叶变换红外光谱指纹图谱多样性

以不同地理居群的大蒜为研究对象,采用傅里叶变换红外光谱法获取各样品的红外谱图及不同波数下各样品的透过率数据,运用主成分分析及聚类分析等统计学方法对谱图数据进行了比较分析。结果发现,不同地理居群大蒜的红外指纹图谱存在差异,统计学分析结果显示25个品种大致可分为4大类(其中2个样品,4号及25号与这4类间有较大差异),此现象一定程度上反映了大蒜种植地居群环境对大蒜理化性质的影响。     

Multivariate Observations of the Distribution of Polychlorinated Biphenyls in Environmental Compartments of Two Harbours

Abstract

The objectives of this study were to identify, classify and categorize polychlorinated biphenyl (PCB) residues in samples collected from the Hamilton and Wheatley Harbour environmental compartments. The study is built around the use of a principal components analysis method, namely the soft independent modelling of class analogy (SIMCA) technique. This multivariate method is widely used for evaluating differences and observing similarities among multiple objects. The results obtained from this work confirm that the gas chromatographic data sets obtained with the samples provide a good approximation of the pattern derived from a determination of the composition of commercial Aroclors in water, sediment and biota samples. The data analysis technique provides insight into the origin of PCB contamination in environmental samples and indicates pathways for the environmental degradation or bioaccumulation of PCBs. This investigation contributes some evidence that multivariate reduction techniques are suitable for the investigation of complex data sets in environmental studies.     

Sensitive trace enrichment of environmental andiandrogen vinclozolin from natural waters and sediment samples using hollow-fiber liquid-phase microextraction

The presence of vinclozolin in the environment as far as the endocrine disruption effects in biota are concerned has raised interest in the environmental fate of this compound. In this respect, the present study attempts to investigate the feasibility of applying a novel quantitative method, liquid-phase microextraction (LPME), so as to determine this environmental andiandrogen in environmental samples such as water and sediment samples. The technique involved the use of a small amount (3 microL) of organic solvent impregnated in a hollow fiber membrane, which was attached to the needle of a conventional GC syringe. The extracted samples were analyzed by gas chromatography coupled with electron-capture detection. Experimental LPME conditions such as extraction solvent, stirring rate, content of NaCl and pH were tested. Once LPME was optimized, the performance of the proposed technique was evaluated for the determination of vinclozolin in different types of natural water samples. The recovery of spiked water samples was from 80 to 99%. The procedure was adequate for quantification of vinclozolin in waters at levels of 0.010 to 50 microg/L (r> 0.994) with a detection limit of 0.001 microg/L (S/N= 3). Natural sediment samples from the Aliakmonas River area (Macedonia, Greece) spiked with the target andiandrogen compound were liquid-liquid extracted and analyzed by the methodology developed in this work. No significant interferences from the samples matrix were noticed, indicating that the reported methodology is an innovative tactic for sample preparation in sediment analysis, with a considerable improvement in the achieved detection limits. The results demonstrated that apart from analyte enrichment, the proposed LPME procedure also serves as clean-up method and could be successfully performed to determine trace amounts of vinclozolin in water and sediment samples.     

Endocrine disrupting compounds and other emerging contaminants in the environment: a survey on new monitoring strategies and occurrence data

An overview of Toxicity Identification and Evaluation (TIE) procedures, used for the effect-based analysis of endocrine disrupting compounds (EDCs) in environmental samples, is presented. Future trends in advanced chemical analysis of EDCs and some emerging contaminants are outlined. The review also gives an overview of concentration levels found in environmental samples and discusses the correlation of calculated estrogenicity (based on chemical analysis of target EDCs) with that measured by various bioassays.     

Identification of discriminatory variables in proteomics data analysis by clustering of variables

This article presents a data analysis method for biomarker discovery in proteomics data analysis. In factor analysis-based discriminate models, the latent variables (LV's) are calculated from the response data measured at all employed instrument channels. Since some channels are irrelevant and their responses do not possess useful information, the extracted LV's possess mixed information from both useful and irrelevant channels. In this work, clustering of variables (CLoVA) based on unsupervised pattern recognition is suggested as an efficient method to identify the most informative spectral region and then it is used to construct a more predictive multivariate classification model. In the suggested method, the instrument channels (m/z value) are clustered into different clusters via self-organization map. Subsequently, the spectral data of each cluster are separately used as the input variables of classification methods such as partial least square-discriminate analysis (PLS-DA) and extended canonical variate analysis (ECVA). The proposed method is evaluated by the analysis of two experimental data sets (ovarian and prostate cancer data set). It is found that our proposed method is able to detect cancerous from healthy samples with much higher sensitivity and selectivity than conventional PLS-DA and ECVA methods.     

Determination of small phosphorus-containing compounds by capillary electrophoresis

The review focuses on the analysis of small phosphorus-containing compounds by capillary electrophoresis (CE) with different detection modes including UV absorption, laser-induced fluorescence, conductometry, amperometry, atomic spectrometry, and mass spectrometry. Determinations of phosphates, organophosphate, and chemical warfare agents in environmental samples such as water, soil and grains are emphasized. To achieve better sensitivity, high-resolving power, and reproducibility, the optimum separation conditions for various analytes (samples) are different. We compare the merits and demerits of the different detection modes for the detection of the analytes. Although the present methods are successful in many cases, there is still a need to develop high-throughput CE techniques for screening numerous environmental samples and sample stacking techniques in CE for the analysis of trace analytes.     

Graphene platforms for the detection of caffeine in real samples

The analysis of food components is of high importance due to food safety and security. Here the electrochemical detection of caffeine was performed on different chemically modified graphene (CMG) surfaces carrying diverse amount of defects and oxygen functionalities. The analytical performances of graphite oxide (GPO), graphene oxide (GO), and electrochemically reduced graphene oxide (ERGO) were compared for the first time for the detection of caffeine. It was found that ERGO showed the most favourable analytical parameters, such as lower oxidation potential, sensitivity, linearity and reproducibility of the response. ERGO was then used for the analysis of real samples. Caffeine levels of soluble coffee, teas and energetic drinks were measured without the need of any sample pre-treatment. Our findings are very important to gain more insight into the applicability of different graphene materials to real samples for sense-and-act analysis.     

The analysis of seasonal air pollution pattern with application of neural networks

Air pollution monitoring includes measuring the concentrations of air contaminants such as nitrogen dioxide, sulfur dioxide, some polycyclic aromatic hydrocarbons(PAHs), suspended particulate matter (PM) and tar substances. The purpose of this study was to determine the possibility of using artificial neural networks for identification of any patterns occurring during heating and nonheating seasons. The samples included in the study were collected over a period of 5 years (1997–2001) in the area of the city of Gdansk and the levels of pollutants measured in the samples collected were used as inputs to two different types of neural networks: multilayer perceptron (MLP) and self-organizing map (SOM). The MLP was used as a tool to predict in what heating season a certain sample was collected, and the SOM was applied for mapping all samples to recognize any similarities between them. This study also presents the comparison between two projection methods—linear (principal component analysis, PCA) and nonlinear (SOM)—in extracting valuable information from multidimensional environmental data. In the research the MLP model with 13-12-1 topology was developed and successfully trained for classification of air samples from different seasons. The sensitivity analysis on the inputs to the MLP indicated benz[α]anthracene, benzo[α]pyrene, PM₁, SO₂, tar substances and PM₁₀ as the most distinctive variables, while PCA pointed to PAHs and PM₁.     

基于石油烃特征比值的多元统计方法进行原油鉴别

基于原油中有生源意义的生物标志物及原油特征多环芳烃的特征比值,采用主成分分析和聚类分析法,对渤海3个不同区块的4种原油,以及其中1种原油风化7d、15d和30d的风化油样和陆地油田1和陆地油田2各1种原油进行鉴别。结果显示:利用主成分分析和聚类分析可以实现大量油样的快速分类鉴别,不仅可以对差异较大的原油进行区分,还可以对原始原油及其风化原油进行很好分辨,但对差异较小的原油,两种分析方法的分辨能力仍有一定局限性。     

Presmectic wetting and supercritical-like phase behavior of octylcyanobiphenyl liquid crystal confined to controlled-pore glass matrices

The influence of controlled-pore glass (CPG) confinement on the phase behavior of octylcyanobiphenyl liquid crystal (LC) is studied by means of x-ray scattering and high precision calorimetry. For CPG samples with pore diameter 2R>24 nm, the smectic order parameter temperature dependence eta(T) reveals apparent presmectic ordering far above the bulk smectic A-nematic (SmA-N) phase transition for both nontreated and silane-treated CPG matrices. The behavior of eta(T) is qualitatively similar in all samples, well obeying the mean field approach (MFA) in which the surface wetting tendency plays the dominant role. In contrast, the critical fluctuations remain important in the specific heat data, which cannot be described within the MFA. We show experimentally that randomness and surface wetting become dominant over finite-size effects for 2R approximately<10 nm, in agreement with theoretical analysis. In nontreated samples, the noncritical character of the static disorder and the interfacial LC-CPG coupling almost completely suppress the quasi-SmA-N and nematic-isotropic phase transitions at 2R approximately 15.1 and approximately 7.5 nm, respectively.