Comparison of molecular images as defined by Raman spectra between normal mucosa and squamous cell carcinoma in the oral cavity

Raman spectroscopy has been effectively applied to clinically differentiate normal and cancerous mucosal tissues. Micro‐Raman spectroscopy provides a tool to better understand the molecular basis for the Raman clinical signal. The objective of the current study was to utilize micro‐Raman spectroscopy to define the molecular/spectral differences between normal and abnormal squamous cell carcinoma (SCC) in oral mucosa (in vitro). Understanding this may help in identifying unique spectra or may be useful for in vivo application of this technology. Micro‐Raman (confocal) spectroscopy was used to obtain molecular images of normal and SCC cells of human oral mucosa. Four fresh flashed‐frozen tumor and four matched normal tongue specimens were studied. The spectra covered a wavenumber range from 300 to 4000 cm⁻¹ with a spectral resolution of 8 cm⁻¹ and a spatial resolution of 1.0 µm. The cells were located within thin sections of tongue mucosa biopsies. The excitation wavelength of 515 nm was used. We were able to obtain Raman images with rich information about the spectroscopic and structural features within the cytoplasm, cell membrane, and cell nuclei. Significant spectral differences were observed between the Raman images of normal and malignant squamous cells. The heterogeneity of tumor cells within the abnormal tissue was also demonstrated. Spectral differences demonstrated between both tissue types have provided important information regarding the origins of specific signals within the cells of each tissue type. In our search for specific spectral biomarkers, we believe that a cell surface protein, greatly upregulated in SCC cells, was discovered at 1583 cm⁻¹. Copyright © 2010 John Wiley & Sons, Ltd.     

Raman spectroscopic analysis of breast cancer tissues: identifying differences between normal,invasive ductal carcinoma and ductal carcinoma in situ of the breast tissue

A relatively non‐destructive method employing Raman spectroscopy for the analysis of histopathological specimens is described. Raman spectroscopy has allowed qualitative analysis of the same specimen used for histopathological evaluation. Breast cancer tissues have been analysed to demonstrate the feasibility of the chemical changes taking place in the biological tissue, which can be identified precisely, and the results are reproducible. Raman analysis of tissue sections provides distinct spectra that can be used to distinguish between the nuclear grades of ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) of the breast. Sixty cases of breast carcinoma including DCIS and IDC and seven cases of normal breast tissues were studied employing the Raman spectroscopic technique. This study reports for the first time spectral differences between DCIS grades. It is concluded that Raman spectroscopy can objectively distinguish between DCIS and IDC grades and is non‐destructive and reproducible. It should become possible in future to use Raman spectroscopy as an informative and quantitative method suitable for classification of grades and diagnosis of breast carcinoma. Copyright © 2007 John Wiley & Sons, Ltd.     

Research on the Raman spectral character and diagnostic value of squamous cell carcinoma of oral mucosa

Early diagnosis of oral carcinomas is essential for successful treatment. The purpose of the present study is to apply near‐infrared Raman spectroscopy to detect oral squamous cell carcinoma (SCC) and leukoplakia (OLK), in order to establish the diagnostic model of the Raman spectra of oral diseases. We collected Raman spectra of normal, OLK and SCC by near‐infrared Fourier transform Raman spectroscopy. The biochemical variations between different lesions were analyzed by the characteristic bands in the subtracted mean spectra. Gaussian radial basis function support vector machines (SVM) were used to classify spectra and establish the diagnostic models. Major differences were observed in the range between 800 and 1800 cm⁻¹. Compared with normal mucosa, high contents of protein, DNA and lipid in SCC and OLK were observed, but the difference between OLK and normal tissue was not as much as that between normal and SCC. SVM displayed a powerful ability in the classifying of normal and SCC, and the specificity, sensitivity and accuracy were 100, 97.56 and 98.75%, respectively. In discriminating between the OLK and normal groups, the three parameters were 85, 68 and 72.5%. The algorithm showed good ability in grouping and modeling of OLK and SCC, and the three parameters were 95, 97.43 and 96.25%. Combined with SVM, near‐infrared Raman spectroscopy can detect biochemical variations in oral normal mucosa, OLK and SCC, and establish diagnostic models accurately. Copyright © 2009 John Wiley & Sons, Ltd.     

Characterizing variability in in vivo Raman spectroscopic properties of different anatomical sites of normal tissue in the oral cavity

Raman spectroscopy is an inelastic light scattering technique that is capable of probing biochemical and biomolecular structures and conformations of tissue. This study aims to characterize the in vivo Raman spectroscopic properties of different normal oral tissues in the fingerprint region (800–1800 cm⁻¹) and to assess distinctive biochemical variations of different anatomical regions in the oral cavity. A specially designed fiber‐optic Raman probe with a ball lens was utilized for real‐time, in vivo Raman measurements of various oral tissue sites (i.e. inner lip, attached gingiva, floor, dorsal tongue, ventral tongue, hard palate, soft palate, and buccal). The semiquantitative non‐negativity‐constrained least squares minimization fitting of reference biochemicals representing oral tissue constituents (i.e. hydroxyapatite, keratin, collagen, DNA, and oleic acid) and partial least squares‐discriminant analysis (PLS‐DA) were employed to assess the significance of inter‐anatomical variability. A total of 402 high‐quality in vivo oral Raman spectra were acquired from 20 subjects. The histological characteristics of different oral tissues were found to have influence on the in vivo Raman spectra and could be grossly divided into three major clusterings: (1) buccal, inner lip, and soft palate; (2) dorsal, ventral tongue, and floor; (3) gingiva and hard palate. The PLS‐DA multiclass algorithms were able to identify different tissue sites with varying accuracies (inner lip 83.1%, attached gingiva 91.3%, floor 86.1%, dorsal tongue 88.8%, ventral tongue 83.1%, hard palate 87.6%, soft palate 83.3%, and buccal mucosa 85.3%), bringing out the similarities among different oral tissues at the biomolecular level. This study discloses that inter‐anatomical variability is significant and should be considered as an important parameter in the interpretation and rendering of Raman diagnostic algorithms for oral tissue diagnosis and characterization. Copyright © 2011 John Wiley & Sons, Ltd.     

In vivo study on the protection of indole‐3‐carbinol (I3C) against the mouse acute alcoholic liver injury by micro‐Raman spectroscopy

Micro‐Raman spectroscopy (MRS) was utilized for the first time to evaluate the effect of indole‐3‐carbinol (I3C) on acute alcoholic liver injury in vivo. In situ Raman analysis of tissue sections provided distinct spectra that can be used to distinguish alcoholic liver injury as well as ethanol‐induced liver fibrosis from the normal state. Sixteen mice with liver diseases including acute liver injury and chronic liver fibrosis, and eight mice with normal liver tissues, and eight remedial mice were studied employing the Raman spectroscopic technique in conjunction with biomedical assays. The biochemical changes in mouse liver tissue when liver injury/fibrosis occurs such as the loss of reduced glutathione (GSH), and the increase of collagen (α‐helix protein) were observed by MRS. The intensity ratio of two Raman peaks (I₁₄₅₀/I₆₆₆) and in combination with statistical analysis of the entire Raman spectrum was found capable of classifying liver tissues with different pathological features. Raman spectroscopy therefore is an important candidate for a nondestructive in vivo screening of the effect of drug treatment on liver disease, which potentially decreases the time‐consuming clinical trials. Copyright © 2008 John Wiley & Sons, Ltd.     

Optical biopsy of breast cancer tissue

In this paper, we report results of Fluorescence Emission Spectra (FES) and Stokes Shift Spectra (SSS) of 19 cancer tissue of invasive ductal carcinoma of different grades in comparison with normal breast tissues (obtained away from tumor regions). We were able to get distinct differences in the spectral features of normal and malignant tissues in terms of the ratios of concentrations of biomolecules like tryptophan, collagen and NADH. The sensitivity and specificity were in the range of 75%. What was all the more important was the parallelism in the spectral features of normal and malignant breast tissue pieces of above set of subjects. The objective of our research is to evolve one such protocol and the first step is the spectral characterization of in vitro optical analyses of excised tumor tissues.     

Nonlinear spectral imaging of human normal skin,basal cell carcinoma and squamous cell carcinoma based on two-photon excited fluorescence and second-harmonic generation

In this work, we use nonlinear spectral imaging based on two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) for analyzing the morphology of collagen and elastin and their biochemical variations in basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and normal skin tissue. It was found in this work that there existed apparent differences among BCC, SCC and normal skin in terms of their thickness of the keratin and epithelial layers, their size of elastic fibers, as well as their distribution and spectral characteristics of collagen. These differences can potentially be used to distinguish BCC and SCC from normal skin, and to discriminate between BCC and SCC, as well as to evaluate treatment responses.     

Near infrared Raman spectroscopic characterization of blood plasma of normal,oral premalignant and malignant conditions—a pilot study

The metabolic end products from cells/tissues that are released into the circulating blood stream and any changes in their level because of pathological conditions may be used as markers in disease diagnosis. Raman spectroscopy has been exploited to characterize the biomolecules present in the blood plasma of clinically confirmed normal group, premalignant (Oral Sub Mucous Fibrosis) and malignant (Oral Squamous Cell Carcinoma) at 784.15 nm. Raman spectral signatures show relatively less intense Raman bands of phenylalanine, lipid and antioxidant beta carotene but higher intense bands for proteins, DNA base components and amino acids (tyrosine and tryptophan) for malignant group than that of normal group. However premalignant group possess high intense Raman bands for amino acids (tyrosine and tryptophan) at 830, 1020 and 1620 cm⁻¹ and protein peaks at 913, 978 and 1646 cm⁻¹ when compared to that of malignant and normal group. Principal component analysis coupled with linear discriminant analysis (PCA‐LDA) yielded a diagnostic sensitivity of 96.3% and 91.2%, and a specificity of 80.0% and 96.7% in the classification of normal from premalignant and normal from malignant, respectively. This indicates that Raman spectroscopy of blood plasma has the potential in classifying normal and oral malignancy conditions. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

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.     

Applications of Raman spectroscopy in dentistry part II: Soft tissue analysis

Raman spectroscopy is rapidly moving from an experimental technique for the analysis of biological molecules to a tool for the real-time clinical diagnosis and in situ evaluation of the oral tissue in medical and dental research. The purpose of this study is to identify various applications of Raman spectroscopy, to evaluate the contemporary status, and to explore future directions in the field of dentistry. Several in-depth applications are presented to illustrate Raman spectroscopy in early diagnosis of soft tissue abnormalities. Raman spectroscopy allows researchers to analyze histological and biochemical composition of biological tissues. The technique not only demonstrates its role in the disclosure of dysplasia and malignancy, but also in performing guided biopsies, diagnosing sialoliths, and assessment of surgical margins. Raman spectroscopy is used to identify the molecular structures and their components to give substantial information about the chemical structure properties of these molecules. In this article, we acquaint the utilization of Raman spectroscopy in analyzing the soft tissues in relation to dentistry.     

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.     

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...     

Raman spectral signatures of mouse mammary tissue and associated lymph nodes: normal,tumor and mastitis

Raman spectroscopy involves the interaction of light with the molecular vibrations and therefore can provide information about molecular structure, tissue composition and changes in its environment. We explored whether Raman spectroscopy can reliably distinguish mammary tumors from normal mammary tissues and other pathological states in mice. We analyzed a large number of Raman spectra from the tumor and normal mammary glands of mice injected with 4T1 tumor cells, which were collected using a high‐resolution (less than 4 cm⁻¹) Raman spectrometer at a fixed (785 nm) laser excitation wavelength and with 60 mW of laser power. The spectra of normal and tumor mammary glands showed consistent differences in the intensity of certain Raman bands and loss of some bands in the tumor spectra. Multivariate statistical methods—principal component analysis (PCA) and discriminant functional analysis (DFA)—were used to separate the data into different groups of mammary tumors, mastitis, lymph nodes contralateral and tumor‐cell‐injected sides, and normal contralateral and tumor‐cell‐injected sides. We demonstrate that this spectroscopic technique has the feasibility of discriminating tumor and mastitis from normal tissues and other pathological states in a short period of time and may detect tumor transformation earlier than the standard histological examination stage. Copyright © 2006 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.     

Evaluation of Raman spectroscopy for prediction of antitumor response to silibinin and its nanoparticulates in DMBA‐induced oral carcinogenesis

Raman spectroscopy is a vibrational spectroscopic technique that can be used to monitor the therapeutic efficacy of anticancer drugs during carcinogenesis in a non‐invasive and label‐free manner. The present study aims to investigate the biochemical changes exerted upon free silibinin (SIL) and its nanoparticulate (SILNPs) treatment against 7,12‐dimethylbenz[a]anthracene (DMBA)‐induced oral carcinogenesis in the fingerprint region of 1800–500 cm⁻¹ using HE‐785 Raman spectrometer. Raman spectra differed significantly between the control and tumor tissues, with tumor tissues characterized by increased intensities of vibrational bands such as nucleic acids, phenylalanine and tryptophan and a lower percentage of lipids when compared to the control tissues. Further, oral administration of free SIL and SILNPs significantly increased lipids and decreased the levels of tryptophan, phenylalanine and nucleic acid contents. Overall, the treatment of nanoparticulate SIL was found to be a more potent antitumor effect than free SIL in preventing the formation of tumor and also brought back the several Raman bands to a normal range in the buccal mucosa of hamsters during DMBA‐induced oral carcinogenesis. In addition, the detailed secondary structure of proteins in the control and experimental groups is also presented. Furthermore, the diagnostic algorithms based on principal component linear discriminant analysis (PC‐LDA) achieved an overall sensitivity of 94–100% and specificity of 76–100%. These results further demonstrate that Raman spectroscopy associated with PC‐LDA diagnostic algorithms could be a valuable tool for rapid and sensitive detection of specific biomolecular changes at the molecular level in response to anticancer drug. Copyright © 2015 John Wiley & Sons, Ltd.     

UV resonance Raman study of TrpZip2 and related peptides: π‐π interactions of tryptophan

Aromatic interactions are important stabilizing forces in proteins but are difficult to detect in the absence of high‐resolution structures. Ultraviolet resonance Raman spectroscopy is used to probe the vibrational signatures of aromatic interactions in TrpZip2, a synthetic β‐hairpin peptide that is stabilized by edge‐to‐face and face‐to‐face tryptophan π‐π interactions. The vibrational markers of isolated edge‐to‐face π‐π interactions are investigated in the related β‐hairpin peptide W2W11. The bands that comprise the Fermi doublet exhibit systematic shifts in position and intensity for TrpZip2 and W2W11 relative to the model peptide, W2W9, which does not form aromatic interactions. Additionally, hypochromism of the B_b absorption band of tryptophan in TrpZip2 leads to a decrease in the relative Raman cross‐sections of B_b‐coupled Raman bands. These results reveal spectral markers for stabilizing tryptophan π‐π interactions and indicate that ultraviolet resonance Raman may be an important tool for the characterization of these biological forces. Copyright © 2012 John Wiley & Sons, Ltd.     

Applications of Raman Spectroscopy in Dentistry: Analysis of Tooth Structure

Abstract: Tooth enamel is the most mineralized tissue in the human body, and in this article the use of Raman spectroscopy for the analysis of tooth structure, a comparison with synthetic apatites, and use in dentistry are described. Spectral peaks that are related to dental hard and soft tissues are discussed, which provide crucial data in understanding the chemical structural properties of dentin and enamel. The Raman spectrum of dentin confirms the presence of crystalline phosphate-based minerals in dentin. Both dentin and enamel consist of two primary components: an inorganic or mineral phase that closely resembles hydroxyapatite and the Raman spectrum of dentin that confirms the presence of crystalline phosphate-based minerals in dentin. Hence, the mineral phase in dentin and enamel may be characterized essentially as nonstoichiometric substituted apatite. The presence of carbonate (A and B type) incorporated in the hydroxyapatite lattice is also confirmed by the presence of spectral bands. The organic phase, which is mainly composed of type I collagen, is confirmed by the spectral bands of amide I and amide II bands, tryptophan, and phenylalanine. Furthermore, these spectral bands associated with organic and inorganic parts of the enamel and dentin are useful in predicting early formation of carries formation.     

Raman spectroscopic investigation of frozen and deparaffinized tissue sections of pediatric tumors: neuroblastoma and ganglioneuroma

Raman spectroscopy is a nondestructive technique that can provide information at the molecular level about the biochemicals in tissues. We have investigated the cellular regions in neuroblastoma and ganglioneuroma using Raman spectroscopy and compared their spectral characteristics with those of the corresponding normal adrenal gland. Thin sections from both the frozen and the corresponding formalin‐fixed paraffin‐processed (FFPP) tissues were studied in conjunction with the pathological examination of the tissues. Investigation of the spectral data shows that the normal adrenal gland tissues have higher levels of carotenoids, lipids, and cholesterol compared with the neuroblastoma and ganglioneuroma frozen tissues. However, in comparison with the frozen tissues, the FFPP tissues show a significant alteration of several biochemicals, including the complete removal of carotenoids, lipids, and cholesterol in the adrenal tissues. A quantitative analysis using chemometric methods of principal component analysis and discriminant function analysis of the Raman spectral data obtained from the frozen tissues show a clear‐cut classification among pathological groups with high sensitivity and specificity. We have validated the classification results of the FFPP tissues against a training set data obtained from the archived FFPP tissues of nine other patients. The validation process correctly identified and grouped the data with the training set of normal adrenal gland (>97% of the time) and neuroblastoma (100% of the time) tissues, whereas the validation was not so strong for ganglioneuroma. This study shows that Raman spectroscopy combined with chemometric methods can be successfully used to distinguish neuroblastoma and ganglioneuroma at cellular level in frozen tissue sections. This study also shows that formalin fixation and paraffinization/deparaffinization of tissues can alter their biochemical composition. Copyright © 2012 John Wiley & Sons, Ltd.     

Discrimination of carotenoid and flavonoid content in petals of pansy cultivars (Viola x wittrockiana) by FT‐Raman spectroscopy

Fourier Transform Raman spectroscopy (FT‐Raman) has been applied for the non‐destructive in‐situ analysis of pigments on differently colored flower petals of pansy cultivars (Viola x wittrockiana). The main target of the present study was to investigate how far the Raman mapping technique through FT‐Raman spectroscopy and cluster analysis of the Raman spectra is a potential method for the direct, in‐situ discrimination of flavonoids (flavonols against anthocyanins) and of carotenoids occurring in flowers, using intact and differently colored flower petal of Viola x wittrockiana for this case study. In order to get more information about the reliability of the direct in‐situ flavonoid detection by the Raman method, pigments extracts of the petals were separated by thin‐layer chromatography (TLC) and investigated by Raman spectroscopy. Hierarchical cluster analysis (HCA) of the Raman spectra from reference pigments (carotenoids, anthocyanins and flavonols), from areas of the flower petals, and from the TLC extracts allowed discriminating the various pigments, in particular flavonoids (flavonols against anthocyanins) and carotenoids. With a two‐dimensional Raman mapping technique, which provides a chemical image of the sample under investigation, we determined by cluster analysis the distribution of carotenoids, anthocyanins and flavonols from the outer layer of the petals, and by integrating through suitable spectral regions selected as characteristic markers for particular pigments their relative concentration could approximately be determined. We found a satisfactory correlation between the patterns seen on the visible images and the patterns on the chemical images obtained by Raman mapping. Copyright © 2011 John Wiley & Sons, Ltd.