鼻咽癌组织拉曼光谱研究进展

鼻咽癌是东南亚地区及中国南方地区高发的恶性肿瘤,具有独特的地理、种族分布特点,并且存在恶性程度高、预后差、早期诊断困难等问题。拉曼光谱技术是基于非弹性光散射基本原理的一种快速且无损的检测方法,能够在分子振动水平上提供生化成分等信息。综述基于拉曼光谱技术的鼻咽癌组织研究最新进展。主要介绍了国内外小组采用拉曼光谱及表面增强拉曼光谱(SERS)进行鼻咽癌组织检测研究的概况,其中重点介绍该研究小组近期在鼻咽癌组织的高波数拉曼光谱、鼻咽癌组织涂片的拉曼光谱,以及研发的人活体鼻咽癌组织内镜检测装置及其临床实验情况。最后,对鼻咽癌组织拉曼光谱研究的发展前景进行了展望。     

基于拉曼光谱技术的甲状腺疾病检测的研究

基于光学成像与光谱技术的无损检测是生物医学光学交叉领域研究的重要发展方向。其中拉曼光谱技术可获得检测对象的生化成分的“指纹信息”,被广泛应用于面向生物分子,细胞以及生物组织的检测诊断研究。甲状腺疾病尤其肿瘤的临床检测往往涉及多方法和技术手段的结合,且存在一定的诊断难度,因此发展新的检测技术方法具有重要的意义。首先综述了拉曼光谱技术在甲状腺细胞系的单细胞拉曼光谱检测与分析,然后介绍甲状腺病理组织和甲状腺正常组织的拉曼光谱鉴别诊断(特别介绍了本研究小组开展以银纳米粒子为增强基底的甲状腺离体组织SERS光谱研究情况),以及拉曼光谱技术在甲状腺激素等方面的研究概况。最后简要探讨了拉曼光谱技术在该领域的研究应用前景和发展方向。     

噻菌灵在纳米银胶表面吸附的表面增强拉曼光谱研究

噻菌灵(TBZ)属苯并咪唑类杀菌剂,容易在水果、蔬菜及相应的果蔬饮品中形成有毒残留。基于密度泛函理论(DFT)的量子化学计算方法和表面增强拉曼光谱(SERS)技术,从理论和实验角度系统研究了噻菌灵在纳米银胶粒子表面的吸附行为和增强效应。采用柠檬酸钠还原法制备了具有表面增强拉曼散射活性的银纳米溶胶,并对水相的噻菌灵进行了SERS光谱研究。利用TBZ-Ag₄四种吸附模型对噻菌灵与银纳米溶胶的相互作用进行了理论分析。结合FT-Raman光谱和B3LYP/6-311G(d)理论计算的结果,借助Gaussian View5.0程序的图形化功能,对噻菌灵分子的振动模式、FT-Raman振动光谱和SERS光谱进行了系统的指认。研究结果表明：噻菌灵分子的所有原子在同一平面上,属于Cs对称性;其在银纳米溶胶表面具有十分显著的表面增强拉曼活性;分子中的S原子与银胶粒子发生吸附作用,并通过该分子的长轴方向垂直于银纳米银胶表面;可利用SERS光谱方法对痕量的噻菌灵进行快速检测。为研究噻菌灵的特性以及其快速检测提供了理论和实验依据。     

Study of both fingerprint and high wavenumber Raman spectroscopy of pathological nasopharyngeal tissues

High wavenumber (HW) Raman spectroscopy has weaker fluorescence background compared with fingerprint (FP) region. This study aims to evaluate the discrimination feasibility of nasopharyngeal non‐cancerous and nasopharyngeal cancer (NPC) tissue with both FP and HW Raman spectroscopy. HW Raman spectra of nasopharyngeal tissue were obtained for the first time. Raman spectra were collected to differentiate nasopharyngeal non‐cancerous (n = 37) from NPC (n = 41) tissues in FP (800–1800cm⁻¹), HW (2700–3100cm⁻¹), and integrated FP/HW region. First, to assess the utility of this method, the averaged Raman spectral intensities and intensity ratios of corresponding Raman bands were analyzed in HW and FP regions, respectively. The results show that intensities as well as the ratios of specific Raman peaks might be helpful in distinguishing nasopharyngeal non‐cancerous from NPC tissue with the HW Raman spectroscopy, as with FP Raman reported before. The multivariate statistical method based on the combination of principal component analysis–liner discriminant analysis (PCA‐LDA), together with leave‐one‐patient‐out, cross‐validation diagnostic algorithm, was used for discriminating nasopharyngeal non‐cancerous from NPC tissue, generating sensitivities of 87.8%, 85.4%, and 95.1% and specificities of 86.5%, 91.9%, and 89.2%, respectively, with Raman spectroscopy in the FP, HW, and integrated FP/HW regions. The posterior probability of classification results and receiver operating characteristic curves were utilized to evaluate the discrimination of PCA‐LDA algorithm, verifying that HW Raman spectroscopy has a positive effect on the differentiation for the diagnosis of NPC tissue by integrated FP/HW Raman spectroscopy. What's more, the potential of Raman spectroscopy used for differentiating different pathology NPC tissues was also discussed. The results demonstrate that both FP and HW Raman spectroscopy have the potential for diagnosis and detection in early nasopharyngeal carcinoma, and HW Raman spectroscopy may improve the discrimination of NPC tissue compared with FP region alone, providing a promising diagnostic tool for the diagnosis of NPC tissue. Copyright © 2015 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。     

Raman Microscopy and Associated Techniques for Label-Free Imaging of Cancer Tissue

Abstract

Raman spectroscopy can identify cancerous from healthy tissue, with a chemical analysis from the measurement of vibrational bond frequencies. However, to detect small tumors a form of Raman imaging is required. Such imaging—by acquiring a Raman spectrum at each imaging pixel—can detect tumors but is rather slow. Multiphoton versions of Raman—anti-Stokes Raman scattering (CARS) microscopy and stimulated Raman scattering (SRS) microscopy—offer similar accuracies in identifying cancerous tissue and tumor margins but with a far higher speed, which is beneficial for diagnosis of small tumors in tissue. SRS microscopy can also be used to image extrinsic molecules in living cells, such as anti-cancer drugs at typical concentrations.     

动态表面增强拉曼光谱在敌瘟磷快速定量分析中的应用

动态表面增强拉曼光谱是在干态与湿态表面增强拉曼光谱(SERS)检测的基础上发展而来的,不仅具有极好的信号增强,还具有良好的重复性与稳定性。提出了一种基于动态SERS与多元分析方法的敌瘟磷快速定量分析方法。实验中,首先测量100,50,10,5,1,0.5和0.1 mg·L-1敌瘟磷动态SERS谱图,并使用多项式校正方法去除光谱基线漂移。然后,处理后的全范围(600~1 800 cm-1)与特征范围(674~713,890~1 195,1 341~1 399和1 549~1 612 cm-1)光谱分别利用支持向量机回归(SVR)构建定量模型,实现对敌瘟磷的定量分析。同时,实验还评估了主成分分析(PCA)对定量分析结果的影响。实验结果表明特征范围光谱所建立的模型预测误差较小,而数据经过PCA处理后预测误差得到进一步下降。最优回归模型是由特征范围光谱经PCA处理后所构建的模型(RMSECV=0.065 7 mg·L-1),模型能够准确地预测敌瘟磷溶液浓度。为了测试实际检测中的效果,该方法被用来对苹果表面的敌瘟磷残留进行检测,并通过气相色谱法进行验证。结果表明该方法对于同一样本多次检测值波动较小,且检测均值与气相色谱检测值相差较小,相对误差最大仅为5.13%。此外,动态SERS检测可在2 min内完成,且后续数据处理也可在数秒内完成,同时整个过程的试剂消耗仅在2 μL左右。因此,所提出的方法在敌瘟磷快速准确检测具有极大优势。     

Surface-enhanced Raman on gold nanoparticles for the identification of the most common adulterant of Astragali Radix

Adulterant is a common problem in Astragali Radix (a widely used Chinese herbal medicine). In this study, the surface-enhanced Raman technique was used to identify the authentic Astragali Radix and the most common adulterant with the aim to develop a convenient and sensitive method for the adulterant identification. Surface-enhanced Raman spectra combined with multivariate diagnostic algorithm differentiated the authentic Astragali Radix from the adulterant with high sensitivity (100%) and specificity (97.6%). This exploratory work demonstrates that surface-enhanced Raman technology can be used for the rapid and label-free screening of adulterant and has great potential for the quality control of Chinese herbal.     

SERS标记免疫检测研究进展

表面增强拉曼光谱(SERS)用于标记免疫检测是标记免疫学与SERS相结合的一门新型的研究技术。20世纪70年代,SERS现象的发现与证实给拉曼光谱技术的研究注入了新的活力。SERS因具有高灵敏度、较高选择性以及适合水溶液物质结构研究等特点,近年来已在生物医学研究领域中显示出独特的潜在应用前景。在标记免疫领域,SERS标记免疫研究更是得到了迅速的发展,成为了国内外的研究热点。文章从SERS标记免疫检测灵敏度的提高、非特异性吸附的降低、多组分检测等三方面叙述了SERS标记免疫检测的原理、特点、存在问题及最新发展。归纳了目前提高SERS标记免疫检测灵敏度的研究技术,阐述了研究中非特异性吸附带来的负面影响,简介了实验室的多组分研究工作。同时,对SERS标记免疫技术未来的研究方向与发展前景进行了展望。     

Near‐infrared Raman spectroscopy for gastric precancer diagnosis

Raman spectroscopy is a molecular vibrational spectroscopic technique that is capable of optically probing the biomolecular changes associated with neoplastic transformation. The purpose of this study was to apply near‐infrared (NIR) Raman spectroscopy for differentiating dysplasia from normal gastric mucosa tissue. A total of 65 gastric mucosa tissues (44 normal and 21 dysplasia) were obtained from 35 patients who underwent endoscopy investigation or gastrectomy operation for this study. A rapid NIR Raman system was utilized for tissue Raman spectroscopic measurements at 785‐nm laser excitation. High‐quality Raman spectra in the range of 800–1800 cm⁻¹ can be acquired from gastric mucosa tissue within 5 s. Raman spectra showed significant differences between normal and dysplastic tissue, particularly in the spectral ranges of 850–1150, 1200–1500 and 1600–1750 cm⁻¹, which contained signals related to proteins, nucleic acids and lipids. The diagnostic decision algorithm based on the combination of Raman peak intensity ratios of I₈₇₅/I₁₄₅₀ and I₁₂₀₈/I₁₆₅₅ and the logistic regression analysis yielded a diagnostic sensitivity of 90.5% and specificity of 90.9% for identification of gastric dysplasia tissue. This work demonstrates that NIR Raman spectroscopy in conjunction with intensity ratio algorithms has the potential for the noninvasive diagnosis and detection of precancer in the stomach at the molecular level. Copyright © 2009 John Wiley & Sons, Ltd.     

SERS技术用于苹果表面有机磷农药残留的检测

传统农药残留检测方法比较繁琐、耗时、破坏样品,快速、无损、实时在线是农残检测的发展方向。本文利用表面增强拉曼光谱技术,以苹果为载体,有机磷农药甲拌磷和倍硫磷为研究对象,初步探讨了苹果表面甲拌磷和倍硫磷农药的快速无损检测方法。结果表明,运用表面增强拉曼光谱技术,可使两种有机磷农药的特征频率较易识别,并选取甲拌磷的728 cm-1和倍硫磷的1 512 cm-1 处的拉曼信号作为定量分析目标峰,采用内标法建立甲拌磷、倍硫磷的线性回归模型,可以作为定量分析甲拌磷、倍硫磷的参考依据。     

基于底物内标的蜂蜜中硝基呋喃妥因拉曼信号校正方法

针对表面增强拉曼光谱信号重复性欠佳的问题,利用实验室自行搭建的拉曼点检测系统,以蜂蜜中硝基呋喃妥因兽药为检测对象,探讨了基于蜂蜜固有内标的硝基呋喃妥因表面增强拉曼峰强校正方法。首先通过含不同浓度硝基呋喃妥因蜂蜜样品及硝基呋喃妥因标准品的拉曼光谱对比分析,确定739 cm-1处蜂蜜拉曼特征位移作为底物蜂蜜的内标峰,用比值法校正硝基呋喃妥因1 353和1 612 cm-1处拉曼特征峰强用于蜂蜜中硝基呋喃妥因定量分析。相同条件下分别采集了浓度为20 mg·kg-1的硝基呋喃妥因蜂蜜样品表面增强拉曼光谱30次,1 353和1 612 cm-1处硝基呋喃妥因特征峰强相对标准偏差（RSD）分别为11.515 6%和11.162 5%,利用739 cm-1处蜂蜜拉曼特征峰强作为内标分别校正1 353和1 612 cm-1处硝基呋喃妥因拉曼特征峰强后相对标准偏差分别降为4.852 6%和4.733 2%,显著提升了表面增强拉曼特征峰强的重复性和稳定性。因为仪器系统误差及表面增强过程中不可控因素引起的人为误差等对样品表面增强光谱中739 cm-1处蜂蜜特征峰强和1 353和1 612 cm-1处硝基呋喃妥因特征峰强的影响是完全相同的,所以通过内标比值法可以有效消除和减少拉曼信号稳定性和重复性差的问题。最后采集硝基呋喃妥因浓度范围为0.4~20 mg·kg-1的69个蜂蜜样品,基于硝基呋喃妥因1 353和1 612 cm-1处拉曼特征峰强和蜂蜜739 cm-1处拉曼特征峰强比值,分别建立了一元线性回归预测模型和多元线性回归模型,其中基于蜂蜜739 cm-1处内标校正硝基呋喃妥因1 612 cm-1处拉曼特征峰强的一元线性回归模型效果最佳,与校正前相比具有更高的精度和预测能力。该模型校正集决定系数（R2_C）和验证集决定系数（R2_Ｖ）分别为0.971 2和0.969 6,校正集均方根误差（RMSEC）和验证集均方根误差（RMSEP） 分别为1.115 1和1.242 2,相对分析误差（RPD）为4.306 0。结果表明,被测底物本身持有固有内标的样品可无需加入额外的内标物,简单用内标比值法可以有效消除仪器的系统误差以及表面增强剂与样品的混合时间等对拉曼信号强度的影响,显著提高了拉曼特征信号的重复性和稳定性,为表面增强拉曼光谱定量分析提供了技术参考。     

基于表面增强拉曼光谱检测技术的肺癌早期诊断研究

表面增强拉曼光谱技术是近年来快速发展的一种痕量特征标记性物质检测技术,以提高检测灵敏度为目的的表面增强拉曼光谱技术非常适合于生命科学研究。本文利用表面增强拉曼光谱技术对肺癌患者及正常人的唾液样本进行检测,并进行光谱分析,建立了肺癌患者唾液样本的实验模型,对该模型系统分析可为肺癌诊断提供辅助依据。统计学分析效果良好,并发现了分类比较明确的特异性波段1015cm-1～1070cm-1和1250cm-1～1280cm-1。在找出的12个特征峰的基础上应用K-均值方法验证了其判别准确性,结果提示提取的12个特征峰有一定的代表性,能够代表近2000个波数的拉曼光谱图,灵敏度较特异度高,说明该方法适合预防性筛查工作。     

Surface-enhanced Raman spectroscopy: nonlocal limitations

Giant field enhancement and field singularities are a natural consequence of the commonly employed local-response framework. We show that a more general nonlocal treatment of the plasmonic response leads to new and possibly fundamental limitations on field enhancement with important consequences for our understanding of surface-enhanced Raman spectroscopy (SERS). The intrinsic length scale of the electron gas serves to smear out assumed field singularities, leaving the SERS enhancement factor finite, even for geometries with infinitely sharp features. For silver nanogroove structures, mimicked by periodic arrays of half-cylinders (up to 120 nm in radius), we find no enhancement factors exceeding 10 orders of magnitude (10(10)).     

Applications of Raman Spectroscopy in Agricultural Products and Food Analysis: A Review

Abstract

Raman spectroscopy has been gaining popularity as an analytical tool due to advances in development of Raman spectrometry and the power of personal computers. Due to to its narrow and highly resolved bands, Raman spectroscopy allows for nondestructive extraction of chemical and physical information about samples and aids in rapid on-line analysis without any special sample preparation. In this review, Raman spectroscopic techniques such as dispersive Raman spectroscopy, Fourier transform Raman spectroscopy, surface-enhanced Raman spectroscopy, and spatially offset Raman spectroscopy are briefly introduced. In addition, applications of Raman spectroscopy are explored, within various fields of agricultural products and food, including fruits and vegetables, crops, meat and dairy products, oil, as well as beverages. In addition, some discussion on the importance of Raman spectroscopy as fundamental and applied research of agricultural products and food is provided.     

基于表面增强拉曼光谱及密度泛函理论的农药毒死蜱检测研究

毒死蜱作为一种广谱高效有机磷杀虫剂,在农业等领域被广泛使用。但是,环境毒理学研究发现,毒死蜱可直接施于土壤中,与土壤颗粒牢固结合,几乎不会迁移或挥发,而且水溶性低,容易造成药物残留,影响着农副产品食用的安全性,对生态环境具有潜在的危险性,许多国家对毒死蜱在农产品中的残留量有严格的规定。因此,检测毒死蜱残留的生态风险问题是当务之急。表面增强拉曼光谱(SERS)技术具有快捷、高效、灵敏度高等优势,已经成为光谱检测领域的热点研究技术;密度泛函理论被广泛用于分子结构与性质的理论模拟计算及光谱分析。基于表面增强拉曼光谱和密度泛函理论对杀虫剂毒死蜱的拉曼和表面增强拉曼光谱进行理论研究。首先,利用GaussView5.0对毒死蜱分子及加入银团簇基底的分子结构进行构型。其次,对毒死蜱分子采用6-31G基组,并基于密度泛函理论进行结构优化,利用Gaussian09模拟计算出其拉曼及表面增强拉曼光谱,并确定拉曼光谱和SERS光谱峰值归属。最后,从频移量角度分析银团簇Ag₂和Ag₃对毒死蜱拉曼光谱的增强效应,并进行频移量大小对比。研究发现,在两种尺寸银团簇作用下,拉曼光谱在326,463,741,781,1 068,1 294,1 435和1 602 cm-1波数处的特征峰强度均有明显的增强,且随着银团簇结构尺寸增大,拉曼信号增强效果更为明显;在不同银团簇增强作用下,一些特征峰发生偏移,其频移量与银团簇结构相关联,在Ag₂和Ag₃银团簇增强下,表面增强拉曼光谱在463,741～781 cm-1波数处均产生了较大的频移,其余特征峰波数处频移量较小,均在20 cm-1以下,毒死蜱分子分别与Ag₂和Ag₃入侵后的表面增强拉曼光谱进行对比,频移方向有很好的一致性。该研究结果为表面增强拉曼光谱技术在农药残留检测领域的应用提供了理论依据。     

Diagnosis of colorectal cancer using Raman spectroscopy of laser-trapped single living epithelial cells

A single-cell diagnostic technique for epithelial cancers is developed by utilizing laser trapping and Raman spectroscopy to differentiate cancerous and normal epithelial cells. Single-cell suspensions were prepared from surgically removed human colorectal tissues following standard primary culture protocols and examined in a near-infrared laser-trapping Raman spectroscopy system, where living epithelial cells were investigated one by one. A diagnostic model was built on the spectral data obtained from 8 patients and validated by the data from 2 new patients. Our technique has potential applications from epithelial cancer diagnosis to the study of cell dynamics of carcinogenesis.     

基于表面增强拉曼的鸡尾酒中苯甲酸钠和山梨酸钾的同时快速检测

基于实验室自行搭建的拉曼点扫描系统,以市售鸡尾酒为研究对象柠檬酸钠还原硝酸银配制的银溶胶作为表面增强剂,探讨了鸡尾酒中苯甲酸钠和山梨酸钾两种防腐剂的同时快速检测方法。首先确定鸡尾酒中苯甲酸钠拉曼特征峰为846.1,1 007和1 605 cm-1,山梨酸钾拉曼特征峰为1 164,1 389和1 651 cm-1,进而对它们拉曼特征位移强度稳定性及鸡尾酒中两种防腐剂对拉曼特征位移强度的相互影响进行了分析。结果表明,利用该方法采集的鸡尾酒中苯甲酸钠和山梨酸钾表面增强拉曼特征位移强度具有较高的稳定性,而且鸡尾酒中苯甲酸钠和山梨酸钾的拉曼特征位移强度相互影响并不大,具有较高的稳定性。分别制备苯甲酸钠浓度范围为0.154 3~1.5 g·kg-1的42个鸡尾酒样品及山梨酸钾浓度范围为0.062~1.5 g·kg-1的45个鸡尾酒样品,分别建立了苯甲酸钠和山梨酸钾的线性回归模型。选用最佳的苯甲酸钠1 007和1 605 cm-1二元线性回归预测模型与山梨酸钾的1 164和1 651 cm-1二元线性回归预测模型,对不同浓度苯甲酸钠和山梨酸钾43个鸡尾酒样品进行了苯甲酸钠和山梨酸钾同时预测验证。结果显示,鸡尾酒中苯甲酸钠和山梨酸钾预测值与实际值相关系数(r)分别为0.949 3和0.921 8,均方根误差(RMSE)分别为0.088 2和0.142 9 g·kg-1。基于银溶胶表面增强拉曼完全可以实现鸡尾酒中苯甲酸钠和山梨酸钾两种防腐剂的快速同时检测,为液态食品中防腐剂的同时快速监测提供了技术支撑。     

Raman spectroscopy can discriminate distinct glioma subtypes as defined by RNA expression profiling

Raman spectroscopy is a molecular spectroscopic technique that can measure the molecular composition of tissue samples within seconds without any extraction processes or dyes. In microbiology, Raman spectroscopy is used to identify bacteriae. In glioblastoma tissue, it was reported that necrosis, normal brain and tumor can be discriminated using Raman spectroscopy. Therefore, we hypothesized that Raman spectroscopy could discriminate glioblastoma tissue from different glioma subtypes defined by RNA expression profiling. We analyzed 20 glioma samples from two distinct molecular subtypes. Both subtypes consisted of glioblastoma samples showing a variety in glioma grading and typing. The Raman spectroscopic results could be grouped in two distinct clusters in an unsupervised cluster analysis. Further analysis of these clusters showed that they were fully congruent with the two clusters as defined by RNA expression profiling. Conclusion: our results demonstrate that Raman spectroscopy can discriminate between different molecular subtypes of glioma and, therefore, may prove to be a valuable tool in in vitro cancer research. Copyright © 2013 John Wiley & Sons, Ltd.     

Surface-enhanced spectroscopy: Toward practical analysis probe

Surface-enhanced spectroscopy (SES) is a consequence of extreme electromagnetic fields and chemical interactions near a surface. SES is highly sensitive and selective and has been exploited in chemistry, physics, biology, and medicine. It is a rapidly developing technique and is expected to become an important analysis tool. This review introduces theories and concepts of SES techniques including surface-enhanced (SE) Raman scattering, SE infrared absorption, SE chiroptical spectroscopy, and SE fluorescence. Then recent research and applications are discussed to indicate current challenges and future directions.