Classification of iron‐based inks by means of micro‐Raman spectroscopy and multivariate data analysis

In this work, multivariate data analysis methods were applied to the analysis and interpretation of micro‐Raman spectra, collected from a broad set of historical iron‐based ink samples, previously characterised for the content of organic acids (gallic acid, ellagic acid and protocatechuic acid). The proposed method relies on principal component analysis of the noisy spectra typically obtained on original, degraded, organic samples, where fluorescence could affect the Raman signal. The signal components could be distinguished from the noise components and then used to build a linear discriminant analysis (LDA) model, achieving separation of the spectra into three classes. Selection of pure signal factors also improved effectiveness and performances of partial least square regression (PLS) algorithms, allowing quantification of condensed tannic acid residuals. Application of multivariate methods to discriminate signal from noise removes the need for spectral data manipulation (filtering, smoothing and differentiating). The obtained classification method for discrimination of historic inks and the regression method for determination of condensed tannic acid residuals supports the use of Raman analysis of fluorescing organic materials, and may provide information to scholars on ink composition and potentially on its provenance. Copyright © 2013 John Wiley & Sons, Ltd.     

基于拉曼光谱和多元统计学研究蓝色中性笔油墨

拉曼光谱作为一种无损检验的技术手段,近年来广泛用于文件检验领域中的书写材料种类检验。本实验采集了市面上收集到的28支蓝色中性笔油墨的拉曼光谱图,结合化学计量学中的相似度分析法和主成分分析法对谱图进行了分析,两种分析方法得到的分类结果基本一致,采用两种方法可以将28支蓝色中性笔油墨分为五类。实验结果表明,将拉曼光谱法得到的数据结合化学计量学分析方法进行数据分析,比直接比较谱图得到的分类结果更加客观、准确。     

Discrimination of aged mixtures of lipidic paint binders by Raman spectroscopy and chemometrics

This work explores the application of chemometric techniques to Raman spectra to study aged lipidic paint binders. These binders, commonly known as drying oils, were widely used by artists throughout history both individually and in mixtures. We prepared various model samples of the pure binders (linseed, poppy‐seed and walnut oils and egg yolk) and of binary mixtures thereof. These model samples were left to age naturally for six years and further characterized by Raman spectroscopy. A comparative study of the Raman spectral features before and after ageing process was carried out. This showed changes mainly in the bands located at 1267, 1655 and 3011 cm^–1, which correspond to vibrations in cis double bonds. Multivariate analysis was performed by applying principal component analysis and partial least‐squares discriminant analysis on the corresponding Raman spectra to test whether spectral differences allowed samples to be distinguished on the basis of their composition. The CH stretching region was found to be especially useful for discrimination between the different binders. Furthermore, good sensitivity and specificity were found in the discriminant analysis particularly for the identification of binders containing egg yolk. The results of these multivariate analyses demonstrated the potential use of both chemometric approaches in the field of Cultural Heritage for drying oil characterization and identification, and also for gaining a deeper insight into the ageing process. Copyright © 2011 John Wiley & Sons, Ltd.     

Raman spectroscopy measurement of levofloxacin lactate in blood using an optical fiber nano‐probe

Liquid chromatography and mass spectrometry were time‐consuming and expensive as the main methods for the drug analysis at present, and the samples must be pretreated. The Raman spectroscopy measurement methods were fast and simple, so the Raman spectroscopy methods for the drug analysis were explored in this paper. An optical fiber nano‐probe coated with gold nanoparticles was fabricated and used with surface‐enhanced Raman spectroscopy (SERS) to measure levofloxacin lactate. The resulting SERS spectra of levofloxacin lactate in mouse blood that was detected by the optical fiber nano‐probe clearly showed the characteristic wave numbers of levofloxacin lactate, indicating that optical fiber nano‐probes can be used with spectral techniques to analyze drugs in vitro or potentially even in vivo. Copyright © 2015 John Wiley & Sons, Ltd.     

Development of oxidative sample preparation for the analysis of forensic soil samples with near‐IR Raman spectroscopy

Forensic soil samples have been traditionally analysed via examinations of colour, texture and mineral content by physical or chemical methods. These methods leave any organic or water‐soluble fractions unexamined. A range of analytical techniques have been applied in this area and these procedures have been reviewed recently. This study uses Raman Spectroscopy to assess both the mineralogical and the water‐soluble organic fractions in soil samples. Soil samples were collected from both urban and rural environments comprising the city of Bradford, England, and an arable farming district in Lincolnshire. This study demonstrates how, with the use of oxidative preparation methods, Raman spectroscopy can be used to successfully discriminate between soil types using mineralogy as well as the organic and water‐soluble fractions of soils. Copyright © 2011 John Wiley & Sons, Ltd.     

Fourier‐transform Raman analysis of milk powder: a potential method for rapid quality screening

In this work, FT‐Raman spectroscopy was explored as a fast and reliable screening method for the assessment of milk powder quality and the identification of samples adulterated with whey (1–40% w/w). Raman measurements can easily differentiate milk powders without the need of sample preparation, whereas the traditional methods of quality control, including high‐performance liquid chromatography, are laborious and slow. The FT‐Raman spectra of whole, low‐fat, and skimmed milk powder samples were obtained and distinguished from commercial milk powder samples. In addition, the exploratory analysis employing data from Raman spectroscopy and principal component analysis (PCA)allowed the separation of milk powder samples according to type,identifying differences between samples in the same group. Multivariate analysis was also developed to classify the adulterated milk powder samples using PCA and partial least squares discriminate analysis (PLS‐DA). The resulting PLS‐DA model correctly classified 100% of the adulterated samples. These results clearly demonstrate the utility of FT‐Raman spectroscopy combined with chemometrics as a rapid method for screening milk powder. Copyright © 2011 John Wiley & Sons, Ltd.     

Wide area illumination Raman scheme for simple and nondestructive discrimination of seawater cultured pearls

Raman spectroscopy, along with discriminant partial least squares (PLS), was successfully used to discriminate among three different groups of cultured pearls (fresh water, Akoya and South seawater). The discrimination between Akoya and South seawater pearls using XRF (X‐ray fluorescence), one of the most frequently adopted analytical methods in pearl analysis, has been especially difficult owing to their similar mineral compositions. The selective Raman features helped in effectively discriminating between these two pearl groups. The difference in the intensities of the CaCO₃ bands of Akoya and South seawater pearls provided a valuable clue. Along with the selective Raman feature, a reproducible Raman spectral collection achieved using a wide area illumination (WAI) scheme played an important role in the determination of the pearl groups, although the pearls were hard‐surfaced, round, solid samples of different sizes and surface shapes. Unwanted spectral variation originating from sensitivity to sample placement relative to the focal plane and from unsuccessful sample representation due to the probing of a localized area, factors that could possibly deteriorate Raman reproducibility, were substantially lessened using the WAI scheme. ATR (attenuated total reflection) IR spectroscopy requiring direct contact with the pearl could be inadequate for discrimination or classification where large numbers of repeating and reproducible measurements are required. Copyright © 2009 John Wiley & Sons, Ltd.     

Diagnosis of head and neck squamous cell carcinoma using Raman spectroscopy: tongue tissues

Raman spectroscopy is a powerful optical technique capable of providing the structural information at the molecular level. Thus, the technique can be used to detect biochemical changes associated with carcinogenesis and identify the biomolecules involved in cancer. We studied the Raman spectral characteristics of normal, carcinoma in situ, and invasive squamous cell carcinoma (SCC) tissues of tongue, and identified the spectral features that can discriminate these three tissue types. We found that the intensities of Raman bands assignable to tryptophan increase while those attributable to protein keratin decrease when tissue changes from normal to invasive SCC. The variation observed in the intensity of many discriminating peaks including those of tryptophan and keratin as tissue changes from normal to carcinoma in situ and then to invasive SCC suggests that Raman spectroscopy can be used to monitor progression of the disease. We have also analyzed the data with multivariate statistical methods such as principal component analysis and discriminant function analysis. These chemometric methods clearly separate the whole data into three distinct groups consistent with results of pathology. We were able to detect with 91% success rate the normal and carcinoma in situ tissues and with 89% accuracy the invasive SCC tissues of the tongue. Copyright © 2011 John Wiley & Sons, Ltd.     

Raman spectral properties of squamous cell carcinoma of oral tissues and cells

Early diagnosis is the key of the improved survival rates of oral cancer. Raman spectroscopy is sensitive to the early changes of molecular composition and structure that occur in benign lesion during carcinogenesis. In this study, in situ Raman analysis provided distinct spectra that can be used to discriminate between normal and malignant tissues, as well as normal and cancer cells. The biochemical variations between different groups were analyzed by the characteristic bands by comparing the normalized mean spectra. Spectral profiles of normal, malignant conditions show pronounced differences between one another, and multiple Raman markers associated with DNA and protein vibrational modes have been identified that exhibit excellent discrimination power for cancer sample identification. Statistical analyses of the Raman data and classification using principal component analysis (PCA) are shown to be effective for the Raman spectral diagnosis of oral mucosal diseases. The results indicate that the biomolecular differences between normal and malignant conditions are more obviously at the cellular level. This technique could provide a research foundation for the Raman spectral diagnosis of oral mucosal diseases.     

Transcutaneous in vivo Raman spectroscopy of breast tumors and pretumors

Breast cancer is the most common cancer amongst women worldwide. Early detection of this cancer results in better prognosis. Owing to the disadvantages of currently available screening tools for early detection of this cancer, rapid and sensitive alternatives such as optical spectroscopic techniques are being extensively explored. Detection of premalignant lesions using these techniques has been reported. However, premalignant lesions are risk indicators and may not be true predictors of tumor development. Therefore, the current study aims at correlation between spectral changes and tumor appearance. In this context, transcutaneous in vivo spectra were acquired from same carcinogen‐induced rats immediately before carcinogen treatment, 3, 8–10, and 12–14 weeks after carcinogen treatment and from frank tumors. These were analyzed using multivariate statistical tools principal component analysis and principal component linear discriminant analysis. Further, a complex test data set consisting of spectra from rats of varying ages, tumor appearance times, and tumor induction protocols was used to test the feasibility of correctly identifying controls and pretumors using Raman spectroscopy. Results suggest feasibility of distinguishing pretumor spectra from controls. Taking into consideration the heterogeneity of afflicted breast, rat‐wise analysis was performed wherein a rat was declared ‘will develop tumor’, even if one spectrum was found abnormal. Using this criterion, in vivo Raman spectroscopy could predict tumor appearance with 82% sensitivity and 95% specificity. Prospectively, combined with emerging technologies like deep Raman spectroscopy and fiber‐probe‐based whole sample imaging, Raman spectroscopy may prove as an invaluable adjunct to currently available breast cancer screening tools. Copyright © 2015 John Wiley & Sons, Ltd.     

Raman spectroscopy at different excitation wavelengths (1064, 785 and 532 nm) as a tool for diagnosis of colon cancer

Raman spectroscopy is structure sensitive non‐destructive method that allows observing the status of biological tissues with minimal impact. This method has a great potential in the diagnosis of various types of degenerative diseases including cancer damages. Near‐infrared Fourier transform (NIR‐FT)‐Raman (λ_ex ~1064 nm), NIR‐visible (Vis)‐Raman (λ_ex ~785 nm) and Vis‐Raman (λ_ex ~532 nm) spectra of normal and colorectal carcinoma colon tissue samples were recorded in macroscopic mode at 10–20 randomly chosen independent sites. In the cases of NIR‐Vis‐ and Vis‐Raman spectra, enhanced resonance effects were observed for tissue chromophores absorbing in the visible area. Evident spectral differences were noticed for Raman spectra of normal colon tissue samples in comparison with abnormal samples. The average Raman spectra of colon tissue samples were analysed by principal component analysis (PCA) to discriminate normal and abnormal tissues. PCA of combined dataset containing Raman intensities of chosen NIR‐FT, NIR‐Vis or Vis‐Raman bands led to discrimination of normal and abnormal colon tissue samples. Therefore, combination of these three Raman methods can be helpful for recognizing cancer lesions in colon for diagnostic purposes. Copyright © 2014 John Wiley & Sons, Ltd.     

Information‐theoretic chemometric analyses of Raman data for chemical reaction studies

A methodology of multivariate chemometric techniques based on the information‐theoretic approach was applied for elucidating chemical reaction information from a Raman data array R _m×ν that arises from in situ reaction monitoring. This reaction‐induced dynamic dataset R _m×ν can be contaminated by random cosmic ray spikes found in the midst of characteristic spectral variations associated with the disappearance or emergence of Raman active reactants, intermediates and products. Such spurious cosmic spikes were identified and removed using a novel and fast numerical approach based on maximum and minimum spectral entropy principles while preserving the genuine reaction‐induced spectral variations. Subsequently, the band‐target entropy minimization (BTEM) algorithm, a minimum spectral entropy based self‐modeling curve resolution technique, was applied to recover the pure component spectra of Raman active chemical species. Information gain through the chemometric analyses was calculated using information entropies with base 2 logarithm. This sequence of information‐theoretic chemometric analyses (or transinformations) was successfully tested on the reaction spectral data obtained from alcoholysis of acetic anhydride, which contains four Raman active chemical species. It is envisioned that this series of multivariate statistical analyses will be useful in chemical reaction studies and process analytical technology (PAT) applications that utilize in situ Raman spectroscopy to monitor transient dynamic changes in chemical concentrations, and also in Raman microscopy/imaging data containing spatial variations. Copyright © 2010 John Wiley & Sons, Ltd.     

Evidence of marked glycogen variations in the characteristic Raman signatures of human embryonic stem cells

Human embryonic stem cells (hESCs) have typical Raman signatures, but specific factors that contribute to variations in these signatures have not been reported to date. Furthermore, variations due to the passaging that is necessary for hESC culture maintenance could potentially distort these signatures. It is therefore important to characterize the impact of these culture manipulations on the Raman spectra to gain a better understanding of the origins and nature of their variations. Here we report on the Raman microspectroscopy of hESCs samples from maintenance cultures, complemented with periodic acid Schiff (PAS, carbohydrates) and 4′‐6‐diamidino‐2‐phenlyindol (DAPI, nuclei) staining. The component predominantly responsible for variations between spectra was spectrally identified as glycogen. Variations in the Raman map of the 480 cm⁻¹ glycogen marker band corresponded with those of a PAS stain of the same sample area. The 785‐nm Raman microspectra of hESC cultures examined daily after passaging showed that the same nonrandom spectral variances occurred at all time points after passaging. The pattern of these variances was identified as being due to glycogen spectral components. Our results help validate the previously observed spectral signatures of hESCs and further delineate and characterize the variations that can be expected in these signatures under normal maintenance culture conditions, and aid distinguishing them from those corresponding to differentiation, thus providing a benchmark for future studies. Copyright © 2010 John Wiley & Sons, Ltd.     

拉曼光谱检测生物大分子损伤的研究进展

拉曼光谱是基于拉曼散射效应而发展起来的一种光谱分析技术,体现的是分子的振动或转动信息。由于拉曼光谱技术与常规化学分析技术相比,具有对样品无损、样品制备简单和所需样品量少等特点,广泛用于生物大分子结构变化的研究。拉曼光谱不仅可以用于蛋白质、核酸和脂类等生物大分子损伤的快速检测,而且可以用于癌症的诊断与手术治疗。通过对比正常组织与癌变组织的拉曼光谱,可以找到两种组织特征吸收峰的差异,从而为癌症的最终确诊和确定肿瘤切除范围提供重要信息。文章综述了拉曼光谱检测生物大分子损伤的研究进展,介绍了利用表面增强拉曼光谱、傅里叶变换拉曼光谱和紫外共振拉曼光谱等技术在检测蛋白质二级结构、膜脂及DNA损伤中的应用,并展望了未来拉曼光谱技术的发展前景。     

拉曼光谱技术在病理诊断中的研究进展

拉曼光谱技术能够提供与物质特定分子结构相关的光谱信息,可用于识别生物组织微小的生化变异,具有快速、实时、无损、无需样本预处理等优点,在临床病理诊断领域极具应用前景。与常规组织病理学分析相比,拉曼光谱技术能够直接检测活体组织,简化了分析程序,缩短了诊断时间。人体病变组织的细胞分子组成和结构可能发生变化,这为拉曼光谱技术在组织病理诊断中的应用提供了检测依据。基于组织分子组成与结构的差异,结合机器学习和化学计量学方法,拉曼光谱技术可以提供客观的诊断信息,实现快速、低侵入的病理诊断。回顾了近十年来拉曼光谱技术在组织病理诊断中的研究进展,对取得的关键成果进行了总结,阐述了当前离体和活体应用拉曼光谱技术的一些关键问题。针对离体拉曼光谱检测,重点评估福尔马林固定石蜡包埋样本、冷冻样本和新鲜组织样本等离体样本的适用情况;阐述拉曼光谱数据收集的关键技术,包括适用光源、光谱范围,以及病理样本光谱采集的方式等。对于活体拉曼光谱检测,重点介绍了活体检测研究中拉曼光谱技术应用的两种形式:结合医用内窥镜进行体内检测,以及开放手术中的直接检测;综述了临床适用的拉曼系统,重点介绍了当前活体拉曼研究中应用的光纤探头。同...     

Trace level detection and identification of nitro‐based explosives by surface‐enhanced Raman spectroscopy

Methods for rapid identification of explosives and their associated compounds at trace level quantities are needed for security screening applications. In this paper, we apply the surface‐enhanced Raman spectroscopy (SERS) to detect and identify traces (as low as tens of pg) of pentaerythritol tetranitrate (PETN), ethylene glycol dinitrate (EGDN), cyclotrimethylene‐trinitramine (RDX) and trinitrotoluene (TNT) using commercially available substrates (Klarite®, Renishaw diagnostics). High quality spectra were achieved within 10 s with a compact Raman spectrometer. Principal component analysis (PCA) of the data was performed to understand what factors affected the spectral variation across the samples. It was found that 76% of the spectral variation was explained by the first three PCs. Score plots for these components showed that the energetic materials can be clearly classified on the basis of SERS spectra also at trace level quantity. Our measurements further demonstrate the potential for using SERS as fast, in situ analytical tool for safety devices, with a sensitivity which competes and, in some cases, overcomes other techniques. Copyright © 2013 John Wiley & Sons, Ltd.     

Validation of Raman and FTIR Spectroscopy Methods in Forensic Analysis of Questioned Documents

Abstract

Paper is of great interest to the examiner of questioned documents and forensic chemists because its examination can often answer questions concerning the identity of paper, its source or origin, and its date of manufacture. This information is often used to determine whether a document is authentic or fraudulent. Raman and infrared spectroscopy are two complementary spectroscopic techniques that can produce fast and efficient analysis of the paper of questioned documents. Considering the applicability of quantitative methods of analysis and the importance of the fields in which they are used, method validation is fundamental to the quality of the final results. In this study, a validation of infrared and Raman spectroscopy methods used to differentiate paper samples is described.     

人全血的毛细管显微拉曼光谱分析

血液中含有众多生物信息,如激素、酶、抗体等丰富的蛋白质成分。通过对血液中众多生物信息进行检测鉴定可以起到对该血液种属判定、溯源的目的。因此,血液检测技术的发展在诸如刑事案件侦破、物种鉴定、疾症预防等领域具有重要意义。目前,传统血液检测手段多为显微观测、免疫法、DNA/基因检测法等,这些技术会对血液样本造成不可逆转的破坏性,且存在分析周期长、结构装置复杂、试验价格昂贵等问题。随着激光技术的发展,拉曼光谱技术作为一种非线性散射光谱技术,在血液检测技术中得到了应用。在血液检测技术中,拉曼光谱技术通常与共聚焦显微系统结合,对涂在载玻片上或盛放在透明容器中的血液样品进行光谱信号采集。该技术具有快速、无损等优势,但复杂的光路系统及昂贵的实验装置限制了该技术的广泛推广。为提出一种装置简单、操作简便的血液拉曼检测新技术,研究采用基于毛细管的显微拉曼技术方案采集并分析人全血的拉曼信号。血液样品通过毛细管的虹吸效应取样,与载玻片的涂样方式相比毛细管的方案具有模拟人血管、维持血液活性、减小空气对实验过程中血液成分的影响、降低激光对血液样品的灼伤效果等优势。为避开可见光部分荧光较强区域的荧光干扰,研究采用360 nm紫外激光器作为激发光源,防止可见荧光信号的干扰。积分时间设为800 ms,有效避免因激光长时间照射对血液样品的灼伤效果,影响实验数据的稳定性与真实性,光谱平均次数为2次,避免单次测量所带来的数据的不准确性影响。光谱扫描范围为500～1 800 cm-1, 结果表明此范围内可较好的避开可见光部分荧光较强区域的干扰。测得的拉曼光谱信号通过滤波去噪及基线校正进行处理。首先采用5阶离散小波变换滤波,进行1层信号分解,滤除高频噪声信号,保留低频有效信号,从而去除杂散信号,对光谱有效信号进行提取。其次,采用4阶多项式拟合扣除基底的基线校正,实现人全血的毛细管显微拉曼光谱峰值信号的提取。最终,通过查询SDBS数据库以及人血样本通过reishaw共聚焦显微拉曼光谱仪测量所得光谱图进行验证发现测得信号中部分为人体内数种氨基酸成分的拉曼信号。实验研究发现,基于毛细管的显微拉曼实验系统与常规拉曼探头实验系统相比,拉曼信号更稳定、重复性高,可有效提取人全血中的拉曼光谱信号, 而其与高精度的共聚焦显微拉曼系统相比价格便宜、结构简单、易于推广等优点,但信号信噪比、有效信号的峰值强度上仍有进一步的提升,是一种测量人全血拉曼信号的可行方案。     

拉曼光谱方法实现RDX药柱内部压力的无损检测

黑索金(RDX)是目前最为常用的军用炸药,随着新型战斗部的发展,异形的RDX药柱不断出现。为保证战斗部的作战效能,需要发展一种能够在线无损检测RDX药柱内部压力的方法。利用拉曼光谱测量表征RDX药柱的方法并结合第一性原理计算,确定了RDX的特征谱线,研究了拉曼特征谱线随外加压强的移动。在实验中分别测量了10,20和30MPa的样片,并通过15,25和35MPa的样片来验证拟合关系的偏差,发现RDX药柱的拉曼特征谱线的移动与外加压强的大小成很好的线性关系。这样就可以先在实验室标定RDX药柱拉曼特征谱线与外压强之间的线性关系,然后测量具有异形的RDX药柱的拉曼谱线,与标准样品的谱线比较得到谱线移动,根据标定得到的线性关系得到异形RDX药柱的内部压强,从而实现对黑索金内压的无损检测。实验表明该方法具有灵敏度高,一致性好的优点,目前该方法已经在某型战斗部的生产上进行试用。     

Visible Raman spectroscopy for the discrimination of olive oils from different vegetable oils and the detection of adulteration

We have investigated the potential of Raman spectroscopy with excitation in the visible spectral range (VIS Raman) as a tool for the classification of different vegetable oils and the quantification of adulteration of virgin olive oil as an example. For the classification, principal component analysis (PCA) was applied, where 96% of the spectral variation was characterized by the first two components. A significant similarity between sunflower oil and extra‐virgin olive oil was found using this approach. Therefore, sunflower oil is a potential candidate for adulteration in most commercially available olive oils. Beside the classification of the different vegetable oils, we have successfully applied Raman spectroscopy in combination with partial least‐squares (PLS) regression analysis for very fast monitoring of adulteration of extra‐virgin olive oil with sunflower oil. Different mixtures of extra‐virgin olive oil with three different sunflower oil types were prepared between 5 and 100% (v/v) in 5% increments of sunflower oil. While in the present context the adulteration usually refers to the addition of reasonable amounts of the adulterant (given the similarity with the basic product), we show that the technique proposed can also be used for trace analysis of the adulterant. Without using techniques like surface‐enhanced Raman scattering (SERS), a quantitative detection limit down to 500 ppm (0.05%) could be achieved, a limit irrelevant for adulteration in commercial terms but significant for trace analysis. The qualitative detection limit even was at considerably lower concentration values. Based on PCA, a clear discrimination between pure extra‐virgin olive oil and olive oil adulterated with sunflower oil was achieved. The adulterant content was successfully determined using PLS regression with a high correlation coefficient and small root mean‐square error for both prediction and validation. Copyright © 2009 John Wiley & Sons, Ltd.