Preparative isotachophoresis with surface enhanced Raman scattering as a promising tool for clinical samples analysis

A surface enhanced Raman scattering (SERS) spectrometry is an interesting alternative for a rapid molecular recognition of analytes at very low concentration levels. The hyphenation of this technique with advanced separation methods enhances its potential as a detection technique. Until now, it has been hyphenated mainly with common chromatographic and electrophoretic techniques. This work demonstrates for a first time a power of preparative isotachophoresis-surface enhanced Raman scattering spectrometry (pITP-SERS) combination on the analysis of model analyte (buserelin) in a complex biological sample (urine). An off-line identification of target analyte was performed using a comparison of Raman spectra of buserelin standard with spectra obtained by the analyses of the fractions from preparative isotachophoretic runs. SERS determination of buserelin was based on the method of standard addition to minimize the matrix effects. The linearity of developed method was obtained in the concentration range from 0.2 to 1.5 nmol L(-1) with coefficient of determination 0.991. The calculated limit of detection is in tens of pico mols per liter.     

Practical understanding and use of surface enhanced Raman scattering/surface enhanced resonance Raman scattering in chemical and biological analysis

The unique ability to obtain molecular recognition of an analyte at very low concentrations in situ in aqueous environments using surface enhanced Raman scattering (SERS) and surface enhanced resonance Raman scattering (SERRS) detection makes these spectroscopies of considerable interest. Improved understanding of the effect coupled to improvements in practical techniques make the use of SERS/SERRS much simpler than has been the case in the past. This article is designed as a tutorial review targeted at aiding in the development of practical applications.     

Automatic identification of novel bacteria using Raman spectroscopy and Gaussian processes

Raman spectroscopy is successfully used for the reliable classification of complex biological samples. Much effort concentrates on the accurate prediction of known categories for highly relevant tasks in a wide area of applications such as cancer detection and bacteria recognition. However, the resulting recognition systems cannot always be directly used in practice since unseen samples might not belong to classes present in the training set. Our work aims to tackle this problem of novelty detection using a recently proposed approach based on Gaussian processes. By learning novelty scores for a large bacteria Raman dataset comprising 50 different strains, we analyze the behavior of this method on an independent dataset which includes known as well as unknown categories. Our experiment reveals that non-parametric methods such as Gaussian processes can be successfully applied to the task of finding unknown bacterial strains, leading to encouraging results motivating their further utilization in this area.     

表面增强拉曼光谱在毒品检测中的应用进展

表面增强拉曼光谱(surfaced-enhanced Raman spectroscopy,SERS)作为一种借助贵金属纳米材料可以增强目标分子信号的拉曼光谱技术,由于其具有指纹识别、高灵敏、高准确度、快速无损、不受水分子干扰等特点,在法庭科学领域中的痕量毒品检测方面逐渐受到人们的关注.SERS不仅用于毒品纯品的检测,对于复杂体系的缴获毒品和人体检材毒品的检测也逐渐成为研究热点.本文重点总结了SERS检测毒品的种类和方法,介绍了用于毒品检测的增强基底的发展,以及基于SERS的检测技术的进展,并对SERS毒品检测数据的分析方法做了概括.最后讨论了SERS在毒品检测面临的主要挑战,并展望了基于SERS毒品痕量检测的未来发展趋势.     

A novel method for human gender classification using Raman spectroscopy of fingernail clippings

This paper illustrates a novel method for human gender classification by measuring the Raman spectrum of fingernail clippings. As Raman spectroscopy reveals the characteristics of vibrational frequencies of the fingernails, it provides unique chemical fingerprints that can be used to describe the molecular structure differences of fingernail between males and females. As the differences of Raman spectra of human fingernails are very subtle, they are enhanced by using a pattern recognition method. In the present study, a combination algorithm of principal component analysis (PCA) and support vector machines (SVM) was implemented to perform the data classification. This combined algorithm provides a classification accuracy of up to 90%. The success of this present method may be used as an alternative rapid tool to identify human gender in forensic applications.     

激光显微拉曼光谱仪在本科实验教学中的应用

拉曼光谱作为一种无损检测的指纹光谱是科研中的主要表征手段。激光显微拉曼光谱实验教学通过测试科研中的样品让学生了解拉曼测试的重要性以及科研的分析方法,构建科学研究和实验教学的桥梁。本实验课程同时安排创新探索实验,培养学生的自主学习兴趣和科研创新能力。通过本实验的学习,让学生们了解目前先进的分析手段和先进的大型仪器,有利于学生综合实验素质及科研能力的培养,为以后从事科学研究及相关工作所需综合能力的培养打下坚实的基础。     

Multiplex optical sensing with surface-enhanced Raman scattering: A critical review

Multiplex analysis permits the detection of several analytical targets at the same time. This approach may permit to draw a rapid and accurate diagnostic about the health of an individual or an environment. Among the analytical techniques with potential for multiplexing surface-enhanced Raman scattering (SERS) offer unique advantages such as ultrasensitive detection down low the deconvolution times, a unique signature containing all the vibrational information of the target molecules, and the possibility of performing the experiments even in very demanding environments such as natural or biological fluids. Here we review the late advances in multiplex SERS including the direct methods, those aided by the surface functionalization of the plasmonic nanoparticles and the use of SERS encoded particles.     

VOCs分子的半导体型传感器识别检测研究进展

具有体积小、功耗低、灵敏度高、硅工艺兼容性好等优点的金属氧化物半导体(MOS)气体传感器现已广泛地应用于军事、科研和国民经济的各个领域。然而MOS传感器的低选择性阻碍了其在物联网(IoT)时代的应用前景。为此,本文综述了解决MOS传感器选择性的研究进展,主要介绍了敏感材料性能提升、电子鼻和热调制三种改善MOS传感器选择性的技术方法,阐述了三种方法目前所存在的问题及其未来的发展趋势。同时,本文还对比介绍了机器嗅觉领域主流的主成分分析(PCA)、线性判别分析(LDA)和神经网络(NN)模式识别/机器学习算法。最后,本综述展望了具有数据降维、特征提取和鲁棒性识别分类性能的卷积神经网络(CNN)深度学习算法在气体识别领域的应用前景。基于敏感材料性能的提升、多种调制手段与阵列技术的结合以及人工智能(AI)领域深度学习算法的最新进展,将会极大地增强非选择性MOS传感器的挥发性有机化合物(VOCs)分子识别能力。     

表面增强拉曼光谱技术在食品检测中的应用研究进展

食品污染是危害公众健康和安全的重要问题,探究灵敏、快速、简单的技术,以便在痕量水平上检测污染物,对保障食品质量安全和风险评价具有十分重要的意义.表面增强拉曼光谱(SERS)是利用光与金、银等纳米结构材料相互作用产生很强的表面等离子激元共振效应,可显著增强吸附在纳米结构表面上分子的拉曼信号,以超灵敏获取样品自身或拉曼探针...     

Raman spectroscopy of endoliths from Antarctic cold desert environments

Six endolithic communities from Antarctic cold desert environments have been analysed by Raman spectroscopy. The extreme conditions that the organisms have to withstand in cold environments leads to the adoption of different survival strategies and adaptation of the geological environment. Production of radiation- and desiccation-protective biomolecules is identifiable but the displacement of potentially protective minerals onto the rock surface has also been detected as a protective mechanism against UV-radiation. In this work, Raman spectroscopy is demonstrated as a valuable technique to determine the organic and inorganic compounds used by microorganisms as protective mechanisms against extreme stress conditions. The data from this study will be useful for construction of molecular recognition biomarkers and remote Raman spectral sensing experiments proposed for terrestrial extremophiles in stressed environments.     

基于非接触式拉曼光谱分析人血与犬血的PCA-LDA鉴别方法

将拉曼光谱分析法与数理统计方法有机结合,构建人血与犬血种属判别模型,实现了不同种属血液样本的高效无损鉴别.采用拉曼光谱的无损测试模式对血液样本进行测试,考察了抗凝管管材、聚焦位置及曝光时间等对血液样本拉曼光谱的影响,在激发波长为632.8 nm,光谱扫描范围为200~1800 cm-1,功率衰减率50%,曝光时间5 s及累加次数为2次的优化条件下,获得了无损检测条件下的血液样本拉曼光谱图.针对血液样本组分复杂、拉曼光谱信号基底背景高等问题,提出了基于小波变换去噪,进行分段多项式基线校正的预处理方法,有效解决了血液样本拉曼光谱谱图的高噪音和基线漂移问题.实验选择30例正常人血和33例比格犬血为样本训练集,5例正常人血和5例比格犬血为测试集,基于主成分分析法(PCA)联合线性判别法(LDA)模型,训练集分类正确率达到95.23%,盲测集分类正确率达90.00%.这种基于非接触式血液样本拉曼光谱和PCA-LDA判断模型的测试方法在进出口检验检疫等涉及血液无损鉴别的领域具有广泛的应用价值和前景.     

表面增强拉曼散射方法检测公共安全类毒物的研究进展

公共安全类毒物直接威胁人们的生命健康安全。表面增强拉曼散射(SERS)技术的超灵敏特点为复杂基质中痕量毒物的快速检测提供了分析策略,极大地拓展了其应用范围,有着广阔的应用前景。该文综述了SERS技术在公共安全类物质检测方面的研究进展,包括对节球藻毒素、芥子气、琥珀胆碱、甲基对硫磷、氰化物、汞离子、亚硝酸盐等毒物的检测。从基底种类的选择和评估、检测限、重复性和实际应用的角度介绍了检测体系的建立过程。分析了这些方法及其在应用中面临的技术挑战与机遇,展望了SERS技术解决现场实际检测难题的发展方向。     

Combined time- and space-resolved Raman spectrometer for the non-invasive depth profiling of chemical hazards

A time-resolved inverse spatially offset Raman spectrometer was constructed for depth profiling of Raman-active substances under both the lab and the field environments. The system operating principles and performance are discussed along with its advantages relative to traditional continuous wave spatially offset Raman spectrometer. The developed spectrometer uses a combination of space- and time-resolved detection in order to obtain high-quality Raman spectra from substances hidden behind coloured opaque surface layers, such as plastic and garments, with a single measurement. The time-gated spatially offset Raman spectrometer was successfully used to detect concealed explosives and drug precursors under incandescent and fluorescent background light as well as under daylight. The average screening time was 50 s per measurement. The excitation energy requirements were relatively low (20 mW) which makes the probe safe for screening hazardous substances. The unit has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than previous picosecond-based systems, to provide a functional platform for in-line or in-field sensing of chemical substances.     

Quantification of casein phosphorylation with conformational interpretation using Raman spectroscopy

Raman spectroscopy is emerging as a powerful method for obtaining both quantitative and qualitative information from biological samples. One very interesting area of research, for which the technique has rarely been used, is the detection, quantification and structural analysis of post-translational modifications (PTMs) on proteins. Since Raman spectra can be used to address both of these questions simultaneously, we have developed near infrared Raman spectroscopy with appropriate chemometric approaches (partial least squares regression) to quantify low concentration (4 microM) mixtures of phosphorylated and dephosphorylated bovine alpha(s)-casein. In addition, we have used these data in conjunction with Raman optical activity (ROA) spectra and NMR to assess the structural changes that occur upon phosphorylation.     

表面增强拉曼光谱法快速检测中成药中吡罗昔康

建立中成药中吡罗昔康的表面增强拉曼光谱快速筛查方法。选取乙酸乙酯为提取剂,以20 mg石墨碳化黑+10 mg N-丙基乙二胺为净化剂,利用拉曼表面增强试剂对吡罗昔康拉曼光谱信号进行增强,进而对中成药中的吡罗昔康进行检测。该方法适用于胶囊、片剂、口服液、固体冲泡颗粒以及凉茶等多种中成药基质中吡罗昔康的检测,检出限为0.5~1.0 mg/kg。该方法检出限低,分析范围广,操作简便、快速,可用于中成药中违禁添加抗风湿解热镇痛类药物吡罗昔康的快速检测。     

食源性致病菌的表面增强拉曼光谱检测技术研究进展

食源性致病菌引起的疾病的快速管控与预防是当前各国面临的食品安全监管难题之一,受到社会各界的广泛关注。目前常用的食源性致病菌检测方法存在步骤复杂、耗时、灵敏度低或选择性差等局限,发展快速、可靠的食源性致病菌检测方法仍是食品安全和公众健康的热点研究领域。表面增强拉曼光谱(SERS)作为一种新型的光谱快检技术,具有灵敏度高、选择性好、快速、无损检测等优点,在食源性致病菌检测方面表现出广阔的应用前景。该文简要介绍了SERS技术的背景、增强机制并总结了用于致病菌检测的活性纳米结构,全面综述了近5年来利用直接或间接SERS法以及SERS与其他技术结合检测食源性致病菌的研究进展,同时讨论了这些方法的优缺点。最后,提出当前SERS技术在实际应用中面临的挑战,并展望了SERS在食源性致病菌检测领域未来可能的发展趋势。     

Monitoring cell culture media degradation using surface enhanced Raman scattering (SERS) spectroscopy

The quality of the cell culture media used in biopharmaceutical manufacturing is a crucial factor affecting bioprocess performance and the quality of the final product. Due to their complex composition these media are inherently unstable, and significant compositional variations can occur particularly when in the prepared liquid state. For example photo-degradation of cell culture media can have adverse effects on cell viability and thus process performance. There is therefore, from quality control, quality assurance and process management view points, an urgent demand for the development of rapid and inexpensive tools for the stability monitoring of these complex mixtures. Spectroscopic methods, based on fluorescence or Raman measurements, have now become viable alternatives to more time-consuming and expensive (on a unit analysis cost) chromatographic and/or mass spectrometry based methods for routine analysis of media. Here we demonstrate the application of surface enhanced Raman scattering (SERS) spectroscopy for the simple, fast, analysis of cell culture media degradation. Once stringent reproducibility controls are implemented, chemometric data analysis methods can then be used to rapidly monitor the compositional changes in chemically defined media. SERS shows clearly that even when media are stored at low temperature (2–8 °C) and in the dark, significant chemical changes occur, particularly with regard to cysteine/cystine concentration.     

仿生视觉色度识别的浓度快速测定

对分光光度计检测设备的依赖,以及通过系列浓度样品测量建立标准曲线的操作限制,极大限制了分光光度法使用场景。 当前日益增长的日常健康监测、大样本量的临床测试、野外环境监测等巨大需求,渴望通过触手可及的设备,实现快速、便捷的样本定量分析。受视觉对色度快速识别的启发,设计了一种深度学习辅助的比色法,利用相机拍照,将样品的色度、亮度等信息与对应浓度建立联系,应用于宽浓度范围测定和多组分体系分析。相比传统的分光光度法,深度学习辅助的比色法对单组分体系、多组分体系检测能力均有显著提升,对KMnO₄单组分体系的浓度检测范围从1×10^-5~9×10^-4 mol/L拓宽到1×10^-6~8×10^-2 mol/L,对Co²⁺、Ni²⁺多组分体系的检测浓度范围也从1×10^-2~1×10^-1 mol/L拓宽到1×10^-2~1.0 mol/L,并且检测效率显著提高,建立宽范围浓度样品的检测模型,可对后续未知样品浓度进行快速检测,为家庭临床检测与野外监测工作,提供了快速、便捷的定量分析手段。     

Immunoassay using surface-enhanced Raman scattering based on aggregation of reporter-labeled immunogold nanoparticles

A one-step homogenous sensitive immunoassay using surface-enhanced Raman scattering (SERS) has been developed. This strategy is based on the aggregation of Raman reporter-labeled immunogold nanoparticles induced by the immunoreaction with corresponding antigens. The aggregation of gold nanoparticles results in a SERS signal increase of the Raman reporter. Therefore, human IgG could be directly determined by measuring the Raman signal of the reporter. The process of aggregation was investigated by transmission electron microscopy (TEM) and UV-Vis absorption spectroscopy. The effects of the temperature, time, and size of gold nanoparticles on the sensitivity of the assay were examined. Using human IgG as a model protein, a wide linear dynamic range (0.1-15 microg mL(-1)) was reached with low detection limit (0.1 microg mL(-1)) under optimized assay conditions. The successful test suggests that the application of the proposed method holds promising potential for simple, fast detection of proteins in the fields of molecular biology and clinical diagnostics.     

An integrated portable Raman sensor with nanofabricated gold bowtie array substrates for energetics detection

An integrated field-portable surface enhanced Raman scattering (SERS) sensing system has been developed and evaluated for quantitative analysis of energetics such as perchlorate (ClO(4)(-)) and trinitrotoluene (TNT) at environmentally relevant concentrations and conditions. The detection system consists of a portable Raman spectrometer equipped with an optical fiber probe that is coupled with novel elevated gold bowtie nanostructural arrays as a sensitive and reproducible SERS substrate. Using the standard addition technique, we show that ClO(4)(-) and TNT can be quantified at concentrations as low as 0.66 mg L(-1) (or ~6.6 μM) and 0.20 mg L(-1) (~0.9 μM), respectively, in groundwater samples collected from selected military sites. This research represents the first step toward the development of a field SERS sensor which may permit rapid, in situ screening and analysis for various applications including national security, chemical, biological and environmental detection.