FTIR microscopy of biological cells and tissue: data analysis using resonant Mie scattering (RMieS) EMSC algorithm

Transmission and transflection infrared microscopy of biological cells and tissue suffer from significant baseline distortions due to scattering effects, predominantly resonant Mie scattering (RMieS). This scattering can also distort peak shapes and apparent peak positions making interpretation difficult and often unreliable. A correction algorithm, the resonant Mie scattering extended multiplicative signal correction (RMieS-EMSC), has been developed that can be used to remove these distortions. The correction algorithm has two key user defined parameters that influence the accuracy of the correction. The first is the number of iterations used to obtain the best outcome. The second is the choice of the initial reference spectrum required for the fitting procedure. The choice of these parameters influences computational time. This is not a major concern when correcting individual spectra or small data sets of a few hundred spectra but becomes much more significant when correcting spectra from infrared images obtained using large focal plane array detectors which may contain tens of thousands of spectra. In this paper we show that, classification of images from tissue can be achieved easily with a few (<10) iterations but a reliable interpretation of the biochemical differences between classes could require more iterations. Regarding the choice of reference spectrum, it is apparent that the more similar it is to the pure absorption spectrum of the sample, the fewer iterations required to obtain an accurate corrected spectrum. Importantly however, we show that using three different non-ideal reference spectra, the same unique correction solution can be obtained.     

Multivariate image analysis of a set of FTIR microspectroscopy images of aged bovine muscle tissue combining image and design information

In this paper we present an algorithm for analysing sets of FTIR microscopic images of tissue sections. The proposed approach allows one to investigate sets of many FTIR tissue images both with respect to sample information (variation from image to image) and spatial variations of tissues (variation within the image). The algorithm is applied to FTIR microscopy images of beef loin muscles containing myofibre and connective tissue regions. The FTIR microscopy images are taken of sub-samples from five different beef loin muscles that were aged for four different lengths of time. The images were investigated regarding variation due to the ageing length and due to the homogeneity of the connective tissue regions. The presented algorithm consists of the following main elements: (1) pre-processing of the spectra to overcome large quality differences in FTIR spectra and differences due to scatter effects, (2) identification of connective tissue regions in every image, (3) labelling of every connective tissue spectrum with respect to its location in the connective tissue region, and (4) analysis of variations in the FTIR microscopic images in regard to ageing time and pixel position of the spectra in the connective tissue region. Important spectral parameters characterising collagen and proteoglycan structure were determined. Figure Effective optical path length estimated by EMSC     

New background correction approach based on polynomial regressions for on-line liquid chromatography–Fourier transform infrared spectrometry

In the present study a new approach for the chemometric background correction in on-line gradient LC–FTIR is introduced. For this purpose, the spectral changes of the elution mixture during gradient elution were analyzed applying 2D correlation spectroscopy. The fundamentals of the new background correction algorithm, based on polynomial fits calculated from a reference spectra matrix (Polyfit-RSM method) are explained. The Polyfit-RSM approach was applied on blank gradient runs as well as on LC–FTIR data obtained from the injection of a soft drink sample using acetonitrile:water as eluent. Results found were critically assessed and compared to those obtained by two previous background correction methods which are likewise based on the use of a reference spectra matrix (RSM). The Polyfit-RSM method provided lower noise levels throughout the whole spectral range than other alternative background correction methods, an excellent recovery of analyte spectra as well as chromatograms with a low noise level and also free from baseline shifts. A significant finding, which implies a major advantage for the practical applicability of the algorithm, is that the size of the RSMs can be reduced without affecting the accuracy of the correction method.     

Crisp and soft multivariate methods visualize individual cell nuclei in Raman images of liver tissue sections

Raman and infrared spectroscopy have been recognized to be promising tools in clinical diagnostics because they provide molecular contrast without external stains. Here, vertex component analysis (VCA) was applied to Raman and Fourier transform infrared (FTIR) images of liver tissue sections and the results were compared with K-means cluster analysis, fuzzy C-means cluster analysis and principal component analysis. The main components of VCA from three Raman images were assigned to the central vein, periportal vein, cell nuclei, liver parenchyma and bile duct. After resonant Mie scattering correction, VCA of FTIR images identified veins, liver parenchyma, cracks, but no cell nuclei. The advantages of VCA in the context of tissue characterization by vibrational spectroscopic imaging are that the tissue architecture is visualized and the spectral information is reconstructed. Composite images were constructed that revealed a high molecular contrast and that can be interpreted in a similar way like hematoxylin and eosin stained tissue sections.     

Raman mapping and FTIR imaging of lung tissue: congenital cystic adenomatoid malformation

Congenital cystic adenomatoid malformations (CCAMs) are benign masses of non-functional lung tissue developing from an overgrowth of the terminal bronchioles with subsequent suppressing of alveolar growth. For the first time CCAMs are studied by Raman mapping and Fourier transform infrared (FTIR) imaging. Both vibrational spectroscopic methods are able to analyze the biochemical composition of tissues and their pathological changes at the molecular level. Cryosections were prepared on calcium fluoride substrates from CCAMs and from normal lung tissue of two infant patients who underwent surgery. Raman maps were collected at a step size of 100 microm in order to assess the whole tissue section and at a smaller step size of 10 microm in order to resolve details in selected areas. FTIR images were collected in the macroscopic and microscopic modes. Data sets were segmented by cluster analysis and the mean spectra of each cluster were compared. At low lateral resolution a lower red blood cell content and higher lipid content were found in CCAMs than in normal lung tissue. At higher lateral resolution, accumulations of lipids and glycogen were identified in CCAMs. The lipid aggregates contain a high concentration of phosphatidylcholine. It is discussed how the combined application of Raman mapping and FTIR imaging might improve the differential diagnosis of lung malformations and how both modalities might be applied to other bioanalytical and biomedical problems in the future.     

Fourier transform infrared imaging analysis in discrimination studies of squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) of the oral cavity and oropharynx represents more than 95% of all malignant neoplasms in the oral cavity. Histomorphological evaluation of this cancer type is invasive and remains a time consuming and subjective technique. Therefore, novel approaches for histological recognition are necessary to identify malignancy at an early stage. Fourier transform infrared (FTIR) imaging has become an essential tool for the detection and characterization of the molecular components of biological processes, such as those responsible for the dynamic properties of tumor progression. FTIR imaging is a modern analytical technique enabling molecular imaging of a complex biological sample and is based on the absorption of IR radiation by vibrational transitions in covalent bonds. One major advantage of this technique is the acquisition of local molecular expression profiles, while maintaining the topographic integrity of the tissue and avoiding time-consuming extraction, purification, and separation steps. With this imaging technique, it is possible to obtain unique images of the spatial distribution of proteins, lipids, carbohydrates, cholesterols, nucleic acids, phospholipids, and small molecules with high spatial resolution. Analysis and visualization of FTIR imaging datasets are challenging and the use of chemometric tools is crucial in order to take advantage of the full measurement. Therefore, methodologies for this task based on the novel developed algorithm for multivariate image analysis (MIA) are often necessary. In the present study, FTIR imaging and data analysis methods were combined to optimize the tissue measurement mode after deparaffinization and subsequent data evaluation (univariate analysis and MIAs). We demonstrate that it is possible to collect excellent IR spectra from formalin-fixed paraffin-embedded (FFPE) tissue microarrays (TMAs) of OSCC tissue sections employing an optimised analytical protocol. The correlation of FTIR imaging to the morphological tissue features obtained by histological staining of the sections demonstrated that many histomorphological tissue patterns can be visualized in the colour images. The different algorithms used for MIAs of FTIR imaging data dramatically increased the information content of the IR images from squamous cell tissue sections. These findings indicate that intra-operative and surgical specimens of squamous cell carcinoma tissue can be characterized by FTIR imaging.     

Methodology for fiber-optic Raman mapping and FTIR imaging of metastases in mouse brains

The objectives of this study were to optimize the preparation of pristine brain tissue to obtain reference information, to optimize the conditions for introducing a fiber-optic probe to acquire Raman maps, and to transfer previous results obtained from human brain tumors to an animal model. Brain metastases of malignant melanomas were induced by injecting tumor cells into the carotid artery of mice. The procedure mimicked hematogenous tumor spread in one brain hemisphere while the other hemisphere remained tumor free. Three series of sections were prepared consecutively from whole mouse brains: dried, thin sections for FTIR imaging, hematoxylin and eosin-stained thin sections for histopathological assessment, and pristine, 2-mm thick sections for Raman mapping. FTIR images were recorded using a spectrometer with a multi-channel detector. Raman maps were collected serially using a spectrometer coupled to a fiber-optic probe. The FTIR images and the Raman maps were segmented by cluster analysis. The color-coded cluster memberships coincided well with the morphology of mouse brains in stained tissue sections. More details in less time were resolved in FTIR images with a nominal resolution of 25 microm than in Raman maps collected with a laser focus 60 microm in diameter. The spectral contributions of melanin in tumor cells were resonance enhanced in Raman spectra on excitation at 785 nm which enabled their sensitive detection in Raman maps. Possible reasons why metastatic cells of malignant melanomas were not identified in FTIR images are discussed.     

中红外光纤技术用于口腔肿瘤在体原位检测的研究

肿瘤是严重威胁人类健康和生命的疾病,早期诊断和及时治疗是提高肿瘤病人存活率的重要因素,肿瘤的发生和发展一般可分为3个阶段：(1)基因突变;(2)生物分子组成和结构发生改变;(3)细胞和组织形态发生变化,目前常用的影像学方法只能检测较大的肿块,组织标本的病理诊断法需在     

Detection of collagens in brain tumors based on FTIR imaging and chemometrics

Fourier transform infrared (FTIR) imaging has been used as a molecular histopathology tool on brain tissue sections after intracranial implantation and development of glioma tumors. Healthy brain tissue (contralateral lobe) as well as solid and diffuse tumor tissues were compared for their collagen contents. IR spectra were extracted from IR images for determining the secondary structure of protein contents and compared to pure product spectra of collagens (types I, III, IV, V, and VI). Multivariate statistical analyses of variance and correspondence factorial analysis were performed to differentiate healthy and tumor brain tissues as well as their classification according to their secondary structure profiles. Secondary structure profiles revealed that no collagen was present in healthy tissues; they are also significantly different from solid and diffuse tumors (p < 0.05). Solid and diffuse tumors could be discriminated with respect to the secondary structure profile of fibrillar and non-fibrillar collagens, respectively. We can thus propose to develop FTIR imaging for histopathology examination of tumors on the basis of collagen contents.     

纹党参与白条党参红外光谱的SIMCA聚类鉴别方法研究

以纹党参和白条党参的红外光谱为聚类分析的对象,研究了红外光谱结合SIMCA聚类分析法对纹党参和白条党参进行识别与分类的可行性.选取400 ～2 000 cm~(-1)范围内的光谱,通过基线补偿(Offset)和散射校正(MSC)等预处理后,采用SIMCA聚类分析法建立识别模型.结果表明,所建模型对纹党参和白条党参的识别率分别达92%和96%,拒绝率均为100%.用盲样对所建模型进行了测试,测试结果全部正确.该法可实现对纹党参和白条党参的快速鉴别.     

基于临近比较的快速拉曼光谱基线校正方法

拉曼光谱成像技术是基于拉曼散射效应所开发的一项现代检测技术,在现代生产、科学研究过程中使用非常广泛。拉曼光谱信号受荧光效应和仪器等方面的影响,往往会产生基线漂移,严重影响对信号特征的进一步提取。因此,必须对拉曼光谱信号进行基线校正。传统的基线校正方法,只针对单一光谱信号,计算量较大,在处理由大量拉曼信号组成的成像数据时,耗时较长且效果不佳。该文提出一种基于临近比较的快速基线校正方法,根据在相同背景下采集的光谱之间的相关性,实现快速基线校正,提高了拉曼成像数据的处理速度。     

Characterization and analysis of mycobacteria and Gram-negative bacteria and co-culture mixtures by Raman microspectroscopy, FTIR, and atomic force microscopy

The molecular composition of mycobacteria and Gram-negative bacteria cell walls is structurally different. In this work, Raman microspectroscopy was applied to discriminate mycobacteria and Gram-negative bacteria by assessing specific characteristic spectral features. Analysis of Raman spectra indicated that mycobacteria and Gram-negative bacteria exhibit different spectral patterns under our experimental conditions due to their different biochemical components. Fourier transform infrared (FTIR) spectroscopy, as a supplementary vibrational spectroscopy, was also applied to analyze the biochemical composition of the representative bacterial strains. As for co-cultured bacterial mixtures, the distribution of individual cell types was obtained by quantitative analysis of Raman and FTIR spectral images and the spectral contribution from each cell type was distinguished by direct classical least squares analysis. Coupled atomic force microscopy (AFM) and Raman microspectroscopy realized simultaneous measurements of topography and spectral images for the same sampled surface. This work demonstrated the feasibility of utilizing a combined Raman microspectroscopy, FTIR, and AFM techniques to effectively characterize spectroscopic fingerprints from bacterial Gram types and mixtures.

Combination of FTIR spectral imaging and chemometrics for tumour detection from paraffin-embedded biopsies

FTIR spectral imaging was applied on formalin-fixed paraffin-embedded biopsies from colon and skin cancerous lesions. These samples were deposited onto different substrates (zinc selenide and calcium fluoride respectively) and embedded using two types of paraffin. Formalin fixation followed by paraffin embedding is the gold standard in tissue storage. It can preserve molecular structures and it is compatible with immunohistochemistry. However, paraffin absorption bands are significant in the mid-infrared region and can mask some molecular vibrations of the tissue. Direct data processing was applied on spectral images without any chemical dewaxing of the tissues. Extended Multiplicative Signal Correction was used to correct the spectral contribution from paraffin. For this purpose, the signal of paraffin was modelled using Principal Component Analysis and paraffin spectra were removed from the raw images based on an outlier detection. Then, pseudo-colour images were computed by K-means clustering in order to highlight histological structures of interest. This robust chemometrics methodology was applied on the two samples. Tumour areas were successfully demarcated from the rest of the tissue in both colon and skin independently of the embedding material and of the substrate.     

Large-scale synthesis of tungsten oxide nanofibers by electrospinning

We show in this communication that large-scale synthesis of orthorhombic WO3 nanofibers can be obtained via a simple electrospinning method. The morphology and the crystal structure are investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM), FTIR, X-ray diffraction patterns (XRD) and X-ray photoelectron spectra (XPS) spectra. SEM and TEM images showed that the diameter of the obtained WO3 nanofibers is between 100 and 500 nm. The structure of the obtained WO3 nanofibers was characterized by FTIR, XRD, and XPS spectra. The photoluminescence of the obtained WO3 nanofibers were also investigated.     

An emphatic orthogonal signal correction-support vector machine method for the classification of tissue sections of endometrial carcinoma by near infrared spectroscopy

A new application of emphatic orthogonal signal correction (EOSC) for baseline correction of near infrared spectra from reflectance measurements of tissue sections is introduced. EOSC was evaluated and compared with principal component orthogonal signal correction (PC-OSC) by using support vector machine (SVM) classifiers. In addition, some exemplary synthetic data sets were created to characterize EOSC coupled to SVM for classification. Orthogonal experimental design coupled with analysis of variance (ANOVA) was used to determine the significant parameters for optimization, which were the OSC method and number of components for the model. EOSC combined with the SVM gave better predictions with respect to a larger number of components and was not as susceptible to overfitting the data as the classifier built with PC-OSC data. These results were supported by simulations using synthetic data sets. EOSC is a softer signal correction approach that retains more signal variance which was exploited by the SVM. Classification rates of 93 ± 1% were obtained without orthogonal signal correction with the SVM. PC-OSC and EOSC data gave similar peak prediction accuracies of 94 ± 1%. The key advantages demonstrated by EOSC were its resistance to overfitting, fine-tuning capability or softness, and the retention of spectral features after signal correction.     

Baseline correction combined partial least squares algorithm and its application in on-line Fourier transform infrared quantitative analysis

In order to eliminate the lower order polynomial interferences, a new quantitative calibration algorithm “Baseline Correction Combined Partial Least Squares (BCC-PLS)”, which combines baseline correction and conventional PLS, is proposed. By embedding baseline correction constraints into PLS weights selection, the proposed calibration algorithm overcomes the uncertainty in baseline correction and can meet the requirement of on-line attenuated total reflectance Fourier transform infrared (ATR-FTIR) quantitative analysis. The effectiveness of the algorithm is evaluated by the analysis of glucose and marzipan ATR-FTIR spectra. BCC-PLS algorithm shows improved prediction performance over PLS. The root mean square error of cross-validation (RMSECV) on marzipan spectra for the prediction of the moisture is found to be 0.53%, w/w (range 7–19%). The sugar content is predicted with a RMSECV of 2.04%, w/w (range 33–68%).     

层层静电自组装构筑壳聚糖/磷钨酸复合膜的研究

将正电荷的壳聚糖与负电荷的磷钨酸溶液通过静电作用交替沉积在基底上组装复合多层膜。使用紫外可见光谱(UV-Vis)、红外光谱(FTIR)、X-射线光电子能谱(XPS)、原子力显微镜(AFM)和循环伏安法(CV)等手段对复合膜进行了表征。UV-Vis结果显示多层膜在特征吸收峰处的吸光度数值随膜双层数增加逐渐增大，呈良好的线性关系，表明多层膜是均匀组装的；XPS和FTIR结果证实了壳聚糖和磷钨酸被组装到膜上，AFM图形显示膜表面有一定的粗糙度，CV结果说明多层膜保留了磷钨酸的电化学性质。     

Delimitation of squamous cell cervical carcinoma using infrared microspectroscopic imaging

Infrared (IR) spectroscopic imaging coupled with microscopy has been used to investigate thin sections of cervix uteri encompassing normal tissue, precancerous structures, and squamous cell carcinoma. Methods for unsupervised distinction of tissue types based on IR spectroscopy were developed. One-hundred and twenty-two images of cervical tissue were recorded by an FTIR spectrometer with a 64×64 focal plane array detector. The 499,712 IR spectra obtained were grouped by an approach which used fuzzy C-means clustering followed by hierarchical cluster analysis. The resulting false color maps were correlated with the morphological characteristics of an adjacent section of hematoxylin and eosin-stained tissue. In the first step, cervical stroma, epithelium, inflammation, blood vessels, and mucus could be distinguished in IR images by analysis of the spectral fingerprint region (950–1480 cm⁻¹). In the second step, analysis in the spectral window 1420–1480 cm⁻¹ enables, for the first time, IR spectroscopic distinction between the basal layer, dysplastic lesions and squamous cell carcinoma within a particular sample. The joint application of IR microspectroscopic imaging and multivariate spectral processing combines diffraction-limited lateral optical resolution on the single cell level with highly specific and sensitive spectral classification on the molecular level. Compared with previous reports our approach constitutes a significant progress in the development of optical molecular spectroscopic techniques toward an additional diagnostic tool for the early histopathological characterization of cervical cancer.     

Univariate method for background correction in liquid chromatography-Fourier transform infrared spectrometry

An univariate method is proposed for background correction in on-line gradient liquid chromatography-Fourier transform infrared (LC-FTIR) spectrometry using acetonitrile:water as mobile phase components. The method is based on the calculation of the ratio of absorbances (AR) at two characteristic wavenumbers for each spectrum. This parameter is subsequently used to locate the most appropriated eluent spectrum within a reference spectra matrix (RSM) to be subtracted from each spectrum included in the sample chromatogram. To correct minor changes in eluent spectra intensity during the elution of analytes, a correction factor (Kf), defined as the ratio of the absorbance of the sample and the selected eluent spectrum at a defined wavenumber was determined. The performance of the procedure was evaluated by correcting an on-line gradient LC-FTIR injection of a mixture of two pesticides (Atrazine and Diuron). Using the AR of the absorbance at 2248.6 and 2256.3 cm(-1) and a Kf at 2248.6 cm(-1), the correlation factors between FTIR spectra extracted at the peak apex from the LC-FTIR chromatogram and those obtained from pure pesticide standards were 0.975 and 0.94 for Atrazine and Diuron, respectively.     

Fourier-transform mid-infrared FPA imaging of a complex multicellular nematode

Here we report on the application of mid-IR imaging to a complex multicellular organism, a nematode. Despite the increase in sample complexity and sample thickness from previously measured cells and tissue sections, it is still possible, through the application of hierarchical cluster analysis, to elucidate biochemical information and spatial distribution information that can be linked to different tissue types in the nematode, namely somatic and non-striated muscle and the collagen rich cuticle. Comparison of HCA clusters from individuals from different species shows clusters can be associated specifically to a particular species, but that few clusters are shared between individuals from different species. In addition, using a synthetic fibre as a model for the nematode, we also show that the IR spectra can be affected by Mie scattering type baseline oscillations which are especially severe towards the edges of the fibre/nematode, but that these can be, to some extent, corrected for using currently available correction algorithms prior to cluster analysis.