Monitoring of the Sources of Environmental Pollution with Crude Oil

The possibility of preliminary identification of sources of environmental pollution with crude oil was studied by IR Fourier spectroscopy, gamma-ray spectrometry, chromatography-mass spectrometry, and capillary gas-liquid chromatography with oil samples from six fields of the Khanty-Mansi Autonomous District and samples of soil and ground water contaminated with these oils.     

基于近红外光谱技术与化学计量学的绿茶无损鉴别方法研究

该文利用近红外光谱技术结合化学计量学方法开发了不同品种绿茶的无损鉴别方法。通过近红外光谱技术得到了8个品种绿茶样品的近红外光谱,比较了单一以及优化组合光谱预处理方法对光谱的影响,利用无监督的主成分分析(PCA)与有监督的线性判别分析方法(LDA)分别构建了茶叶品种鉴别模型。结果表明：对比单一预处理方法,优化组合预处理具有更优的鉴别准确性。标准正态变量变换预处理消除了茶叶样品大小不均造成的光谱散射影响,一阶导数预处理实现了变动背景的消除,减少了基线漂移的影响,突出了图谱中的有效信息,采用二者相结合的预处理方式并结合无监督的主成分分析法可实现较为准确的绿茶样品种类鉴别分析,准确率达75.0%。此外,采用有监督的线性判别分析方法处理原始光谱数据,可达到100%的鉴别准确率,但该方法需提供类别的先验知识。因此,采用近红外光谱技术和化学计量学相结合的手段可实现不同品种绿茶的快速无损鉴别。     

Fourier-transform infrared spectroscopy discriminates a spectral signature of endometriosis independent of inter-individual variation

Endometriosis is the growth of endometrial tissue outside of the uterine cavity. Its aetiology remains obscure, and it is difficult to diagnose ranging from asymptomatic to debilitating disease. Mid-infrared (IR) spectroscopy has become recognised as a potential clinical diagnostic tool. Biomolecules absorb mid-IR (4000 cm(-1) to 400 cm(-1)) and from this, a biochemical-cell fingerprint in the form of an absorbance spectrum can be derived. We set out to determine if IR spectroscopy could be used to identify underlying biochemical differences between endometrial tissues growing outside of the uterus (ectopic) from endometrial tissue of the uterus (eutopic). For comparative purposes, endometrial tissues from endometriosis-free women were also obtained (benign eutopic). Attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy or transmission FTIR microspectroscopy was employed for spectral acquisition. Principal component analysis (PCA)-linear discriminant analysis (LDA) was used for chemometric analysis. A clear segregation was exhibited between the three categories independent of inter-individual confounding differences. Importantly, there was a marked difference between eutopic endometrial tissue from patients with or without endometriosis. This indicates that IR spectroscopy coupled with multivariate analysis (e.g., PCA-LDA) may provide a non-invasive diagnostic tool for endometriosis. By analysing the underlying biochemistry of these endometrial tissues, this approach may facilitate a better understanding of this pathology.     

Forensic discrimination of photocopy and printer toners II. Discriminant analysis applied to infrared reflection-absorption spectroscopy

Copy toner samples were analyzed using reflection-absorption infrared microscopy (R-A IR). The grouping of copy toners into distinguishable classes achieved by visual comparison and computer-assisted spectral matching was compared to that achieved by multivariate discriminant analysis. For a data set containing spectra of 430 copy toners, 90% (388/430) of the spectra were initially correctly grouped into the classifications previously established by spectral matching. Three groups of samples that did not classify well contained too few samples to allow reliable classification. Samples from two other pairs of groups were similar and often misclassified. Closer examination of spectra from these groups revealed discriminating features that could be used in separate discriminant analyses to improve classification. For one pair of groups, the classification accuracy improved to 91% (81/89) and 97% (28/29), for the two groups, respectively. The other pair of groups were completely distinguishable from one another. With these additional tests, multivariate discriminant analysis correctly classified 96% of the 430 R-A IR toner spectra into the toner groups found previously by spectral matching.This is publication number 03–03 of the Laboratory Division of the Federal Bureau of Investigation. Names of commercial manufacturers are provided for identification only, and inclusion does not imply endorsement by the Federal Bureau of Investigation.     

Forensic classification of ballpoint pen inks using high performance liquid chromatography and infrared spectroscopy with principal components analysis and linear discriminant analysis

Several varieties of blue ballpoint pen inks were analyzed by high performance liquid chromatography (HPLC) and infrared spectroscopy (IR). The chromatographic data extracted at four wavelengths (254, 279, 370 and 400 nm) was analyzed individually and at a combination of these wavelengths by the soft independent modeling of class analogies (SIMCA) technique using principal components analysis (PCA) to estimate the separation between the pen samples. Linear discriminant analysis (LDA) measured the probability with which an observation could be assigned to a pen class. The best resolution was obtained by HPLC using data from all four wavelengths together, differentiating 96.4% pen pairs successfully using PCA and 97.9% pen samples by LDA. PCA separated 60.7% of the pen pairs and LDA provided a correct classification of 62.5% of the pens analyzed by IR. The results of this study indicate that HPLC coupled with chemometrics provided a better discrimination of ballpoint pen inks compared to IR. The need to develop a suitable IR method for analysing blue ballpoint pen inks has been emphasized and it is hoped that the development of such a method would indeed provide a valuable tool for the non-destructive analysis of blue ballpoint pen ink samples for forensic purposes.     

Applying Fourier-transform infrared spectroscopy and chemometrics to the characterization and identification of lactic acid bacteria

The infrared absorption spectra of 55 lactic acid bacteria belonging to the genera Lactobacillus, Weissella and Carnobacterium were obtained and mathematically analyzed. Sixteen reference strains and 39 food strains isolated from meat and meat products and belonging to the genera Lactobacillus (6 species), Weissella (3 species) and Carnobacterium (2 species) were processed under standardized conditions and their medium infrared spectra obtained using Fourier-transform infrared (FT-IR) spectroscopy. Reproducibility indexes and similarities between FT-IR spectra were calculated using modified correlation coefficients to detect the ranges with the best reproducibility and discrimination properties. Hierarchical cluster analysis and stepwise discriminant analysis (SDA) were subsequently carried out to detect classes and create library groups. Reference strains could be distinguished on the basis of their spectral data and their clustering was in agreement with differences in chemical composition of the cell wall. For the 39 food isolates, the capability of two identification systems was compared. Unknown strains were identified (a) using the linear functions obtained from SDA (canonical variables) of the variables that provide the best discrimination of spectra, and (b) by calculating a differentiation index when a range of the unknown's transformed IR spectrum was compared to all spectra included in a reference library. The system based on the differentiation index obtained a higher rate of identification, allowing for detection of outliers. FT-IR spectroscopy is shown to afford additional information to phenotypic and genotypic data which may help to establish a more robust taxonomic classification.     

Utilization of flash chromatography for the fractionation of coal derived liquids

Summary The suitability of flash chromatography for the fractionation of coal liquids in compound classes has been studied. TLC data obtained from standards were used for establishing the sequence, composition and volume of eluents in order to collect the main components of coal liquids in six fractions of increasing polarity. The method was tested by the fractionation of a SCG coal extract and separations were evaluated by TLC, SEC, and IR and NMR spectroscopy.     

Discrimination of Types of Thermal Sensitive Paper by Characterization of the Inorganic Additives by Fourier Transform Infrared Microscopy,Confocal Raman Microscopy,and Scanning Electronic Microscope-Energy Dispersive Spectroscopy

Identification of thermal sensitive paper is of importance to forensic scientists in the document examination and file source identification. Spectral methods, including infrared spectroscopy, Raman spectroscopy, and energy dispersive spectroscopy have been proven to be accurate and rapid in the investigation of numerous compounds in many studies; therefore, an optimized spectral method was introduced to discriminate the thermal sensitive paper with these instruments in this study. Seventeen samples from different manufactures and markets were collected and analyzed. The results indicated that paper samples could not be discriminated effectively by the organic ingredients (leuco, developer, sensitizer, lubricant, or adhesive). However, based on the difference of the inorganic additives (calcined Kaolin, calcium carbonate, titanium dioxide, and talc), the identification could be more easily realized by their IR characterization. The indicative peaks of the additives in IR and Raman spectra are summarized and tentatively explained. Energy dispersive spectroscopy analysis could also provide indirect evidence of the presence of certain inorganic ingredients. The method using the three instruments in combination proved to be characteristic and accurate and could be applied to the cases relative to the thermal sensitive paper.     

Raman spectroscopic identification of single bacterial cells at different stages of their lifecycle

Early, rapid, and reliable bacterial identification is of great importance in natural environments and in medical situations. Numerous studies have shown that Raman spectroscopy can be used to differentiate between different bacteria under controlled laboratory conditions. However, individual bacteria within a population exhibit macromolecular and metabolic heterogeneity over their lifetime. Therefore it is important to be able to identify and classify specific bacteria at different time points of the growth cycle. In this study, four species of bacteria were used to explore the capability of confocal Raman spectroscopy as a tool for the identification of (and discrimination between) diverse bacterial species at various growth time points. The results show that bacterial cells from different growth time points (as well as from a random growth phase) can be discriminated among the four species using principal component analysis (PCA). The results also show that bacteria selected from different growth phases can be classified with the help of a prediction model based on principal component and linear discriminant analysis (PC-LDA). These findings demonstrate that Raman spectroscopy with the application of a PC-LDA model rooted in chemotaxonomic analysis has potential for rapid sensing of microbial cells in environmental and clinical studies.     

Identification of anthocyanins in wines by liquid chromatography, liquid chromatography-mass spectrometry and nuclear magnetic resonance

Liquid chromatography (LC) was used for the fractionation of particular anthocyanins in glycoside form from methanol extracts of red grape skins and solid phase extracts of red wine. By the combination of nuclear magnetic resonance spectroscopy and LC-mass spectroscopy the identification of 13 anthocyanins in a particular LC fraction and hence the in particular peaks in chromatograms were obtained. Peaks areas in the chromatograms obtained under the semi-quantitaive conditions of the solid phase extracts of red wines Pinot Noir, Cabernet Sauvignon and Merlot from the Coastal wine-growing region in Slovenia, produced in 1999, were used as input data in chemometric analysis. The chemometric methods used were hierarchical clustering analysis and regularised discriminant analysis. The results of both methods give 100% correct classification of wines regarding the vine variety.     

Study of interactions between Gallic Acid and Skin Surface using Infrared Spectroscopy

The transdermal transmission of model substance on the pigskin samples was investigated using the attenuated total reflection (ATR) technique of infrared (IR) spectroscopy. The collected vibrational spectroscopic data were evaluated by multidimensional statistical methods as principal component analysis (PCA), linear discriminant analysis (LDA) and partial least squares (PLS) regression which enable detection of individual substances in the skin, their identification and mutual differentiation. Gallic acid (GA), a natural phenolic anti-oxidant with many potential healing properties suitable e.g. for atopic dermatitis treatment, was used as an analyte. Effect of GA on the skin surface was examined for four different solvents namely ethanol (EtOH), methanol (MeOH), dimethyl sulfoxide (DMSO) and ultrahigh purity water (H₂O). Moreover, the effects of temperature related to GA solubility in H₂O were investigated. During the series of experiments, nonsystematic changes of untreated skin samples were observed; while systematic changes are evident after the skin treatment. The systematic effects correspond to structural changes of the skin constituents during substance penetration.     

Quantitative determination and evaluation of Paris polyphylla var. yunnanensis with different harvesting times using UPLC‐UV‐MS and FT‐IR spectroscopy in combination with partial least squares discriminant analysis

A rapid method was developed and validated by ultra‐performance liquid chromatography–triple quadrupole mass spectroscopy with ultraviolet detection (UPLC‐UV‐MS) for simultaneous determination of paris saponin I, paris saponin II, paris saponin VI and paris saponin VII. Partial least squares discriminant analysis (PLS‐DA) based on UPLC and Fourier transform infrared (FT‐IR) spectroscopy was employed to evaluate Paris polyphylla var. yunnanensis (PPY) at different harvesting times. Quantitative determination implied that the various contents of bioactive compounds with different harvesting times may lead to different pharmacological effects; the average content of total saponins for PPY harvested at 8 years was higher than that from other samples. The PLS‐DA of FT‐IR spectra had a better performance than that of UPLC for discrimination of PPY from different harvesting times.     

液晶聚合物材料的红外光谱表征

红外光谱以高选择性、无破坏性以及高超的分辨和实时跟踪能力成为从分子水平研究液晶聚合物的的重要分析手段,而偏振二向色技术、时间分辨步扫描技术和二维相关分析技术的发展进一步提高了红外光谱分析复杂液晶聚合物的能力。本文介绍了传统傅里叶变换红外光谱及各种新型光谱分析技术（主要是二维相关技术）对液晶聚合物材料表征的研究进展,特别是对于液晶聚合物分子氢键、共聚和共混物相容性以及外场（温度、电场、光场、应力场）作用下液晶分子取向等的研究,并分别进行了具体的应用实例分析。     

Analysis and discrimination of ten different sponges by multi-step infrared spectroscopy

In this study,a convenient method using multi-step infrared spectroscopy,including Fourier transform infrared spectroscopy(FT-IR),second derivative infrared spectroscopy(SD-IR) and two-dimensional correlation infrared spectroscopy(2DCOS-IR),was employed to analyze and discriminate ten marine sponges from two classes collected from the Xisha Islands in the South China Sea.Each sponge had an exclusive macroscopic fingerprint.From the IR spectra,it was noted that the main ingredient of calcareous sponges was calcium carbonate,but that of demosponges was proteins.For sponges from the same genus or having highly similar chemical profile(IR spectral profile),SD-IR and 2DCOS-IR were applied to successfully reveal the tiny differences.It was demonstrated that the multi-step infrared spectroscopy was a feasible and objective approach for marine sponge identification.     

Towards a detailed understanding of bacterial metabolism--spectroscopic characterization of Staphylococcus epidermidis.

Bacteria are a major cause of infection. To fight disease and growing resistance, research interest is focused on understanding bacterial metabolism. For a detailed evaluation of the involved mechanisms, a precise knowledge of the molecular composition of the bacteria is required. In this article, various vibrational spectroscopic techniques are applied to comprehensively characterize, on a molecular level, bacteria of the strain Staphylococcus epidermidis, an opportunistic pathogen which has evolved to become a major cause of nosocomial infections. IR absorption spectroscopy reflects the overall chemical composition of the cells, with major focus on the protein vibrations. Smaller sample volumes-down to a single cell-are sufficient to probe the overall chemical composition by means of micro-Raman spectroscopy. The nucleic-acid and aromatic amino-acid moieties are almost exclusively explored by UV resonance Raman spectroscopy. In combination with statistical evaluation methods [hierarchical cluster analysis (HCA), principal component analysis (PCA), linear discriminant analysis (LDA)], the protein and nucleic-acid components that change during the different bacterial growth phases can be identified from the in vivo vibrational spectra. Furthermore, tip-enhanced Raman spectroscopy (TERS) provides insight into the surface structures and follows the dynamics of the polysaccharide and peptide components on the bacterial cells with a spatial resolution below the diffraction limit. This might open new ways for the elucidation of host-bacteria and drug-bacteria interactions.     

抚顺烟煤及其抽出物的FTIR光谱结构表征

用富立叶变换红外光谱(FTIR)对抚顺烟煤的有机组分进行了测定。通过对谱图的解析,指出抚顺烟煤及其吡啶抽出物和抽提残煤在结构上的异同。以及抽出物各色谱馏分中存在的官能团和官能团之间极性的差异,对原煤整体结构提供了精细的结构信息。     

IR-Spectroscopic Determination of the Maceral Composition of Coal

The maceral composition of coal was determined from the IR spectra by factor analysis. Simulated spectra were obtained.     

Analysis and identification of different animal horns by a three-stage infrared spectroscopy

In this study, a new method, a three-stage infrared spectroscopy (Fourier transform infrared spectroscopy (FT-IR) integrated with second derivative infrared spectroscopy and two-dimensional correlation infrared spectroscopy (2D-IR)) was developed to analyze the organic and inorganic compositions of three different horns (Cornu Antelopis, Cornu Bubali and Pulvis Cornus Bubali Concentratus). In IR spectra, all the three horns had their own macroscopic fingerprints especially for those compositions containing amide groups, CH groups and Ca(3)(PO(4))(2). Their second derivative spectra amplified the differences and revealed the potentially characteristic IR absorption bands 1350-400 cm(-1) to be investigated in 2D-IR. Subsequently, many covered characteristic fingerprints were disclosed in 2D-IR spectra in the range of 1350-400 cm(-1) and the three horns were therefore effectively discriminated. Meanwhile, the analysis results of inorganic constituents were verified by atomic spectroscopy. Furthermore, thirty different horn samples including ten of each horn were also successfully classified by soft independent modeling of class analogy (SIMCA). It was demonstrated that the above three-stage infrared spectroscopy could be applicable for quick, non-destructive and effective analysis and identification of very complicated and similar mixture systems (e.g. traditional Chinese medicines).     

Distinction of malignant melanoma and epidermis using IR micro-spectroscopy and statistical methods

Infrared spectroscopy is widely perceived as a future technology for cancer detection and grading. Malignant melanoma, an aggressive skin cancer, is accessible to non-invasive IR radiation based surface probes for its identification and grading. The present work examines the differences in the IR spectra of melanoma tissues and the surrounding epidermis in skin biopsies with the objective of identifying diagnostic parameters and suitable computational/statistical methods of analysis. Melanoma could be differentiated from the epidermis in biopsies of 55 patients, using parameters derived from absorbance bands originating from molecular vibrations of nucleic acids and/or their bases. Additionally, absorbances from tyrosine and phosphate that are abnormally elevated in malignant melanoma could be used as markers. Two-dimensional plots of these parameters in tandem with advanced statistical methods successfully demonstrate the potential of IR spectroscopy to distinguish between epidermal and melanoma regions with a high classification success. The work underlines the importance of developing data analysis methods in FTIR based diagnosis using melanoma as a model system.     

傅立叶变换离子回旋共振质谱用于金属加工助剂中的成分分析

金属加工助剂是金属加工生产过程中必不可少的化工产品,其组成复杂,易形成螯合物干扰成分分析。该文利用傅立叶变换离子回旋共振质谱(Fourier transform ion cyclotron resonance mass spectrometry,FT-ICR MS)技术的高分辨性能,结合电感耦合等离子体质谱(ICP-MS)、红外光谱(IR)和核磁共振谱(NMR)对一种含未知成分的金属加工助剂进行成分分析。结果表明,该金属加工助剂中含有柠檬酸钠、乙二胺四乙酸(EDTA)与金属铋螯合物。该方法简便、准确,适用于含有金属螯合物的金属加工助剂成分的快速鉴定。