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BBA - Biomembranes (v.1758, #7)

Editorial Board (pp. ii).

Vibrational microscopic imaging by Rich Mendelsohn; Max Diem (pp. 813-813).

Spatial resolution in infrared microspectroscopic imaging of tissues by Peter Lasch; Dieter Naumann (pp. 814-829).

Spatial resolution is one of the most critical measurement parameters in infrared microspectroscopy. Due to the distinct levels of morphologic heterogeneity in cells and tissues the spatial resolution in a given IR imaging setup strongly affects the character of the infrared spectral patterns obtained from the biomedical samples. This is particularly important when spectral data bases of reference microspectra from defined tissue structures are collected. In this paper we have also pointed out that the concept of spatial resolution in IR imaging is inseparable from the contrast. Based on infrared microspectroscopic transmittance data acquired from an USAF 1951 resolution target we have demonstrated how the spatial resolution can be determined experimentally and some numbers for the spatial resolution of popular IR imaging systems are provided. Finally, we have presented a new computational procedure which is suitable to improve the spatial resolution in IR imaging. A theoretical model of 3D-Fourier self-deconvolution (FSD) is given and advantages or pitfalls of this method are discussed. Based on synchrotron IR microspectroscopic data we have furthermore demonstrated that the technique of 3D-FSD can be successfully applied to increase the spatial resolution in a real IR imaging setup.

Keywords: Abbreviations; FSD; Fourier self-deconvolution; FT-IR; Fourier transform infrared; IR; infrared; MCT; mercury cadmium telluride; MTF; modulation transfer function; PSF; point spread function; SNR; signal-to-noise ratioBiomedical infrared spectroscopy; Spatial resolution; IR microspectroscopy of Tissue

High throughput assessment of cells and tissues: Bayesian classification of spectral metrics from infrared vibrational spectroscopic imaging data by Rohit Bhargava; Daniel C. Fernandez; Stephen M. Hewitt; Ira W. Levin (pp. 830-845).

Vibrational spectroscopy allows a visualization of tissue constituents based on intrinsic chemical composition and provides a potential route to obtaining diagnostic markers of diseases. Characterizations utilizing infrared vibrational spectroscopy, in particular, are conventionally low throughput in data acquisition, generally lacking in spatial resolution with the resulting data requiring intensive numerical computations to extract information. These factors impair the ability of infrared spectroscopic measurements to represent accurately the spatial heterogeneity in tissue, to incorporate robustly the diversity introduced by patient cohorts or preparative artifacts and to validate developed protocols in large population studies. In this manuscript, we demonstrate a combination of Fourier transform infrared (FTIR) spectroscopic imaging, tissue microarrays (TMAs) and fast numerical analysis as a paradigm for the rapid analysis, development and validation of high throughput spectroscopic characterization protocols. We provide an extended description of the data treatment algorithm and a discussion of various factors that may influence decision-making using this approach. Finally, a number of prostate tissue biopsies, arranged in an array modality, are employed to examine the efficacy of this approach in histologic recognition of epithelial cell polarization in patients displaying a variety of normal, malignant and hyperplastic conditions. An index of epithelial cell polarization, derived from a combined spectral and morphological analysis, is determined to be a potentially useful diagnostic marker.

Keywords: Fourier transform infrared (FTIR) spectroscopy; Imaging; Biophotonics; Prostate; Tissue microarray; Bayesian statistics; Likelihood classification; Discriminant; Cancer; Histology; Pathology; ROC

Chemical imaging of biological tissue with synchrotron infrared light by Lisa M. Miller; Paul Dumas (pp. 846-857).

Fourier transform infrared micro-spectroscopy (FTIRM) and imaging (FTIRI) have become valuable techniques for examining the chemical makeup of biological materials by probing their vibrational motions on a microscopic scale. Synchrotron infrared (S-IR) light is an ideal source for FTIRM and FTIRI due to the combination of its high brightness (i.e., flux density), also called brilliance, and broadband nature. Through a 10-μm pinhole, the brightness of a synchrotron source is 100–1000 times higher than a conventional thermal (globar) source. Accordingly, the improvement in spatial resolution and in spectral quality to the diffraction limit has led to a plethora of applications that is just being realized. In this review, we describe the development of synchrotron-based FTIRM, illustrate its advantages in many applications to biological systems, and propose some potential future directions for the technique.

Keywords: Abbreviations; IR; infrared; FTIRM; Fourier transform infrared microspectroscopy; FTIRI; Fourier transform infrared imaging; FPA; focal plane array; MCT; mercury cadmium telluride; S/N; signal-to-noise; S-IR; synchrotron infraredSynchrotron; Infrared; Microspectroscopy; Imaging; Biology; Biomedical

Applications of ATR-FTIR spectroscopic imaging to biomedical samples by S.G. Kazarian; K.L.A. Chan (pp. 858-867).

FTIR spectroscopic imaging in ATR (Attenuated Total Reflection) mode is a powerful tool for studying biomedical samples. This paper summarises recent advances in the applications of ATR-FTIR imaging to dissolution of pharmaceutical formulations and drug release. The use of two different ATR accessories to obtain chemical images of formulations in contact with water as a function of time is demonstrated. The innovative use of the diamond ATR accessory allowed in situ imaging of tablet compaction and dissolution. ATR-FTIR imaging was also applied to obtain images of the surface of skin and the spatial distribution of protein and lipid rich domains was obtained. Chemical images of cross-section of rabbit aorta were obtained using a diamond ATR accessory and the possibility of in situ imaging of arterial samples in contact with aqueous solution was demonstrated for the first time. This experiment opens an opportunity to image arterial samples in contact with solutions containing drug molecules. This approach may help in understanding the mechanisms of treatment of atherosclerosis.

Keywords: FT-IR spectroscopic imaging; Infrared spectroscopy; Drug release; Dissolution; Skin; Aorta

Is photobleaching necessary for Raman imaging of bone tissue using a green laser? by Kurtulus Golcuk; Gurjit S. Mandair; Andrew F. Callender; Nadder Sahar; David H. Kohn; Michael D. Morris (pp. 868-873).

Raman microspectroscopy is widely used for musculoskeletal tissues studies. But the fluorescence background obscures prominent Raman bands of mineral and matrix components of bone tissue. A 532-nm laser irradiation has been used efficiently to remove the fluorescence background from Raman spectra of cortical bone. Photochemical bleaching reduces over 80% of the fluorescence background after 2 h and is found to be nondestructive within 40 min. The use of electron multiplying couple charge detector (EMCCD) enables to acquire Raman spectra of bone tissues within 1–5 s range and to obtain Raman images less than in 10 min.

Keywords: Raman microspectroscopy; Raman imaging; Photobleaching; Bone; EMCCD

Diagnosing benign and malignant lesions in breast tissue sections by using IR-microspectroscopy by Heinz Fabian; Ngoc Anh Ngo Thi; Michael Eiden; Peter Lasch; Jürgen Schmitt; Dieter Naumann (pp. 874-882).

The collection of IR spectra through microscope optics and the visualization of the IR data by IR imaging represent a visualization approach, which uses infrared spectral features as a native intrinsic contrast mechanism. To illustrate the potential of this spectroscopic methodology in breast cancer research, we have acquired IR-microspectroscopic data from benign and malignant lesions in breast tissue sections by point microscopy with spot sizes of 30–40 μm. Four classes of distinct breast tissue spectra were defined and stored in the data base: fibroadenoma (a total of 1175 spectra from 14 patients), ductal carcinoma in situ (a total of 1349 spectra from 8 patients), connective tissue (a total of 464 spectra), and adipose tissue (a total of 146 spectra). Artifical neural network analysis, a supervised pattern recognition method, was used to develop an automated classifier to separate the four classes. After training the artifical neural network classifier, infrared spectra of independent external validation data sets (“unknown spectra�?) were analyzed. In this way, all spectra (a total of 386) taken from micro areas inside the epithelium of fibroadenomas from 4 patients were correctly classified. Out of the 421 spectra taken from micro areas of the in situ component of invasive ductal carcinomas of 3 patients, 93% were correctly identified. Based on these results, the potential of the IR-microspectroscopic approach for diagnosing breast tissue lesions is discussed.

Keywords: Infrared microspectroscopy; Infrared imaging; Artifical neural network; Breast cancer; Cancer diagnostic

Identification of primary tumors of brain metastases by SIMCA classification of IR spectroscopic images by Christoph Krafft; Larysa Shapoval; Stephan B. Sobottka; Kathrin D. Geiger; Gabriele Schackert; Reiner Salzer (pp. 883-891).

Brain metastases are secondary intracranial lesions which occur more frequently than primary brain tumors. The four most abundant types of brain metastasis originate from primary tumors of lung cancer, colorectal cancer, breast cancer and renal cell carcinoma. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy based methods constitute a new approach to determine the origin of brain metastases. IR spectroscopic images of 4 by 4 mm² tissue areas were recorded in transmission mode by a FTIR imaging spectrometer coupled to a focal plane array detector. Unsupervised cluster analysis revealed variances within each cryosection. Selected clusters of five IR images with known diagnoses trained a supervised classification model based on the algorithm soft independent modeling of class analogies (SIMCA). This model was applied to distinguish normal brain tissue from brain metastases and to identify the primary tumor of brain metastases in 15 independent IR images. All specimens were assigned to the correct tissue class. This proof-of-concept study demonstrates that IR spectroscopy can complement established methods such as histopathology or immunohistochemistry for diagnosis.

Keywords: Vibrational imaging; Biomedical spectroscopy; Secondary brain tumors; Chemometric methods; Molecular pathology

Brain tissue characterisation by infrared imaging in a rat glioma model by Nadia Amharref; Abdelilah Beljebbar; Sylvain Dukic; Lydie Venteo; Laurence Schneider; Michel Pluot; Richard Vistelle; Michel Manfait (pp. 892-899).

Pathological changes associated with the development of brain tumor were investigated by Fourier transform infrared microspectroscopy (FT-IRM) with high spatial resolution. Using multivariate statistical analysis and imaging, all normal brain structures were discriminated from tumor and surrounding tumor tissues. These structural changes were mainly related to qualitative and quantitative changes in lipids (tumors contain little fat) and were correlated to the degree of myelination, an important factor in several neurodegenerative disorders. Lipid concentration and composition may thus be used as spectroscopic markers to discriminate between healthy and tumor tissues. Additionally, we have identified one peculiar structure all around the tumor. This structure could be attributed to infiltrative events, such as peritumoral oedema observed during tumor development. Our results highlight the ability of FT-IRM to identify the molecular origin that gave rise to the specific changes between healthy and diseased states. Comparison between pseudo-FT-IRM maps and histological examinations (Luxol fast blue, Luxol fast blue-cresyl violet staining) showed the complementarities of both techniques for early detection of tissue abnormalities.

Keywords: Abbreviations; FT-IRM; Fourier transform infrared microspectroscopy; H&E; Hematoxylin and eosin; LFB; Luxol fast blue; LFB-CV; LFB counterstained with cresyl violet; ZnSe; Zinc Selenide; MCT; Mercury–cadmium–telluride; SNV; Standard normal variate; PCA; Principal component analysis; KM; K-meansBrain tumor; Glioma; Peritumoral infiltration; FT-IR microspectroscopy; Multivariate statistical analysis; Early diagnosis

A Fourier transform infrared microspectroscopic imaging investigation into an animal model exhibiting glioblastoma multiforme by K.R. Bambery; E. Schültke; B.R. Wood; S.T. Rigley MacDonald; K. Ataelmannan; R.W. Griebel; B.H.J. Juurlink; D. McNaughton (pp. 900-907).

Glioblastoma multiforme (GBM) is a highly malignant human brain tumour for which no cure is available at present. Numerous clinical studies as well as animal experiments are under way with the goal being to understand tumour biology and develop potential therapeutic approaches. C6 cell glioma in the adult rat is a frequently used and well accepted animal model for the malignant human glial tumour. By combining standard analytical methods such as histology and immunohistochemistry with Fourier Transform Infrared (FTIR) microspectroscopic imaging and multivariate statistical approaches, we are developing a novel approach to tumour diagnosis which allows us to obtain information about the structure and composition of tumour tissues that could not be obtained easily with either method alone. We have used a “Stingray�? FTIR imaging spectrometer to analyse and compare the compositions of coronal brain tissue sections of a tumour-bearing animal and those from a healthy animal. We have found that the tumour tissue has a characteristic chemical signature, which distinguishes it from tumour-free brain tissue. The physical-chemical differences, determined by image and spectral comparison are consistent with changes in total protein absorbance, phosphodiester absorbance and physical dispersive artefacts. The results indicate that FTIR imaging analysis could become a valuable analytic method in brain tumour research and possibly in the diagnosis of human brain tumours.

Keywords: Animal model; Brain tumour; Focal plane array detector (FPA); Fourier transform infrared (FTIR) micro-spectroscopy

Cell-cycle-dependent variations in FTIR micro-spectra of single proliferating HeLa cells: Principal component and artificial neural network analysis by Susie Boydston-White; Melissa Romeo; Tatyana Chernenko; Angela Regina; Miloš Miljković; Max Diem (pp. 908-914).

We have previously reported spectral differences for cells at different stages of the eukaryotic cell division cycle. These differences are due to the drastic biochemical and morphological changes that occur as a consequence of cell proliferation. We correlate these changes in FTIR absorption and Raman spectra of individual cells with their biochemical age (or phase in the cell cycle), determined by immunohistochemical staining to detect the appearance (and subsequent disappearance) of cell-cycle-specific cyclins, and/or the occurrence of DNA synthesis. Once spectra were correlated with their cells' staining patterns, we used methods of multivariate statistics to analyze the changes in cellular spectra as a function of cell cycle phase.

Keywords: Cell cycle; Infrared micro-spectroscopy; Artificial neural network; Principal component analysis

Infrared micro-spectroscopic studies of epithelial cells by Melissa Romeo; Brian Mohlenhoff; Michael Jennings; Max Diem (pp. 915-922).

We report results from a study of human and canine mucosal cells, investigated by infrared micro-spectroscopy, and analyzed by methods of multivariate statistics. We demonstrate that the infrared spectra of individual cells are sensitive to the stage of maturation, and that a distinction between healthy and diseased cells will be possible. Since this report is written for an audience not familiar with infrared micro-spectroscopy, a short introduction into this field is presented along with a summary of principal component analysis.

Keywords: Infrared micro-spectroscopy; Oral mucosa (buccal) cell; Canine ectocervical cell; Principal component analysis (PCA); Spectral cytology

Determination of molecular conformation and permeation in skin via IR spectroscopy, microscopy, and imaging by Richard Mendelsohn; Carol R. Flach; David J. Moore (pp. 923-933).

Skin tissue, in addition to its specific use in dermal research, provides an excellent model for developing the techniques of vibrational microscopy and imaging for biomedical applications. In addition to permitting characterization of various regions of skin, the relative paucity of major biological constituents in the stratum corneum (the outermost layer of skin), permits us to image, with microscopic resolution, conformational alterations and concentration variations in both the lipid and protein components. Thus we are able to monitor the effects of exogenous materials such as models for drug delivery agents (liposomes) and permeation enhancers (DMSO) on stratum corneum lipid organization and protein structure. In addition, we are able to monitor protein conformational changes in single corneocytes. The current article demonstrates these procedures, ranging from direct univariate measures of lipid chain conformational disorder, to factor analysis which permits us to image conformational differences between liposomes that have permeated through the stratum corneum from those which have remained on the surface in a reservoir outside the skin.

Keywords: Stratum corneum; IR microscopy and imaging; Lipid phase behavior; Liposome permeation

Fourier transform infrared imaging spectroscopy investigations in the pathogenesis and repair of cartilage by Xiaohong Bi; Xu Yang; Mathias P.G. Bostrom; Nancy Pleshko Camacho (pp. 934-941).

Significant complications in the management of osteoarthritis (OA) are the inability to identify early cartilage changes during the development of the disease, and the lack of techniques to evaluate the tissue response to therapeutic and tissue engineering interventions. In recent studies several spectroscopic parameters have been elucidated by Fourier transform infrared imaging spectroscopy (FT-IRIS) that enable evaluation of molecular and compositional changes in human cartilage with progressively severe OA, and in repair cartilage from animal models. FT-IRIS permits evaluation of early-stage matrix changes in the primary components of cartilage, collagen and proteoglycan on histological sections at a spatial resolution of ∼6.25 μm. In osteoarthritic cartilage, the collagen integrity, monitored by the ratio of peak areas at 1338 cm⁻¹/Amide II, was found to correspond to the histological Mankin grade, the gold standard scale utilized to evaluate cartilage degeneration. Apparent matrix degradation was observable in the deep zone of cartilage even in the early stages of OA. FT-IRIS studies also found that within the territorial matrix of the cartilage cells (chondrocytes), proteoglycan content increased with progression of cartilage degeneration while the collagen content remained the same, but the collagen integrity decreased. Regenerative (repair) tissue from microfracture treatment of an equine cartilage defect showed significant changes in collagen distribution and loss in proteoglycan content compared to the adjacent normal cartilage, with collagen fibrils demonstrating a random orientation in most of the repair tissue. These studies demonstrate that FT-IRIS is a powerful technique that can provide detailed ultrastructural information on heterogeneous tissues such as diseased cartilage and thus has great potential as a diagnostic modality for cartilage degradation and repair.

Keywords: Infrared imaging; Cartilage; Collagen; Proteoglycan; Osteoarthritis

Infrared imaging microscopy of bone: Illustrations from a mouse model of Fabry disease by Adele L. Boskey; Michel Goldberg; Ashok Kulkarni; Santiago Gomez (pp. 942-947).

Bone is a complex tissue whose composition and properties vary with age, sex, diet, tissue type, health and disease. In this review, we demonstrate how infrared spectroscopy and infrared spectroscopic imaging can be applied to the study of these variations. A specific example of mice with Fabry disease (a lipid storage disease) is presented in which it is demonstrated that the bones of these young animals, while showing typical spatial variation in mineral content, mineral crystal size, and collagen maturity, do not differ from the bones of age- and sex-matched wild type animals.

Keywords: Infrared microscopic imaging; Bone; Hydroxyapatite; Fabry disease

FTIR-microspectroscopy of prion-infected nervous tissue by Ariane Kretlow; Qi Wang; Janina Kneipp; Peter Lasch; Michael Beekes; Lisa Miller; Dieter Naumann (pp. 948-959).

The family of transmissible spongiform encephalopathies (TSE), also termed prion diseases, is a group of fatal, neurodegenerative diseases characterized by the accumulation of a misfolded protein, the disease-associated prion protein PrP^Sc. This glycoprotein differs in secondary structure from its normal, cellular isoform PrP^C, which is physiologically expressed mostly by neurons. Scrapie is a prion disease first described in the 18th century in sheep and goats, and has been established as a model in rodents to study the pathogenesis and pathology of prion diseases. Assuming a multitude of molecular parameters change in the tissue in the course of the disease, FTIR microspectroscopy has been proposed as a valuable new method to study and identify prion-affected tissues due to its ability to detect a variety of changes in molecular structure and composition simultaneously. This paper reviews and discusses results from previous FTIR microspectroscopic studies on nervous tissue of scrapie-infected hamsters in the context of histological and molecular alterations known from conventional pathogenesis studies. In particular, data from studies reporting on disease-specific changes of protein structure characteristics, and also results of a recent study on hamster dorsal root ganglia (DRG) are discussed. These data include an illustration on how the application of a brilliant IR synchrotron light source enables the in situ investigation of localized changes in protein structure and composition in nervous cells or tissue due to PrP^Sc deposition, and a demonstration on how the IR spectral information can be correlated with results of complementary studies using immunohistochemistry and x-ray fluorescence techniques. Using IR microspectroscopy, some neurons exhibited a high accumulation of disease-associated prion protein evidenced by an increased amount of β-sheet at narrow regions in or around the infected nervous cells. However, not all neurons from terminally diseased hamsters showed PrP^Sc deposition. Generally, the average spectral differences between all control and diseased DRG spectra are small but consistent as demonstrated by independent experiments. Along with studies on the purified misfolded prion protein, these data suggest that synchrotron FTIR microspectroscopy is capable of detecting the misfolded prion protein in situ without the necessity of immunostaining or purification procedures.

Keywords: Scrapie; PrP; ^Sc; PrP; ^C; Synchrotron infrared microspectroscopy; Dorsal root ganglia; Chemical mapping

Molecular determination of liver fibrosis by synchrotron infrared microspectroscopy by Kan-Zhi Liu; Angela Man; R. Anthony Shaw; Binhua Liang; Zhaolin Xu; Yuwen Gong (pp. 960-967).

Liver fibrosis is an adaptive response to various injuries and may eventually progress to cirrhosis. Although there are several non-invasive methods available to monitor the progression of liver fibrogenesis, they cannot reliably detect fibrosis in its early stages, when the process can be stopped or reversed by removing or eliminating the underlying etiological agent that cause the hepatic injury. In this study, early fibrosis alterations were characterized biochemically, morphologically, and spectroscopically in a rat bile duct ligation (BDL) model. Progressive elevations in serum alanine transaminase (ALT), aspartate transaminase (AST), and bilirubin levels in the BDL rats were found indicating the dynamic deterioration of hepatocellular function. Immunofluorescence microscopy using monoclonal anti-collagen III antibody further revealed abnormal intertwined networks of collagen fibres surrounding the portal areas and extending into the lobules towards the central veins in all BDL samples starting from week one. Synchrotron infrared microspectroscopy of liver sections was exploited to generate false color spectral maps based upon a unique and strong collagen absorption at 1340 cm^− 1, revealing a collagen distribution that correlated very well with corresponding images provided by immunofluorescence imaging. We therefore suggest that infrared microspectroscopy may provide an additional and sensitive means for the early detection of liver fibrosis.

Keywords: Liver fibrosis; Cirrhosis; Infrared; Mapping; Collagen

In-vitro analysis of normal and aneurismal human ascending aortic tissues using FT-IR microspectroscopy by F. Bonnier; S. Rubin; L. Ventéo; C.M. Krishna; M. Pluot; B. Baehrel; M. Manfait; G.D. Sockalingum (pp. 968-973).

FTIR microspectroscopy has shown to be a proven tool in the investigation of many tissue types. We have used this spectroscopic approach to analyse structural differences between normal and aneurismal aortic tissues and also aortas from patients with congenital anomalies like aortic bicuspid valves. Spectral analysis showed important variations in amide I and II regions, related to changes in alpha-helix and beta-sheet secondary structure of proteins that seem to be correlated to structural modifications of collagen and elastin. These proteins are the major constituents of the aortic wall associated to smooth muscular cells. The amide regions have thus been identified as a marker of structural modifications related to these proteins whose modifications can be associated to a given aortic pathological situation. Both univariate (total absorbance image and band ratio) and multivariate (principal components analysis) analyses of the spectral information contained in the infrared images have been performed. Differences between tissues have been identified by these two approaches and allowed to separate each group of aortic tissues. However, with univariate band ratio analysis, the pathological group was found to be composed of samples from aneurismal aortas associated or not with an aortic bicuspid valve. In contrast, PCA was able to separate these two types of aortic pathologies. For other groups, PCA and band ratio analysis can differentiate between normal, aneurismal, and none dilated aortas from patients with a bicuspid aortic valve.

Keywords: FTIR microspectroscopy; Aortic tissue; Aneurysm; Aortic bicuspid valve; PCA analysis

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BBA - Biomembranes (v.1758, #7)