FTIR Microspectroscopy Coupled with Two-Class Discrimination Segregates Markers Responsible for Inter- and Intra-Category Variance in Exfoliative Cervical Cytology

Screening of neoplastic diseases by statistical analysis of urine fluorescence spectroscopic data. Application of multivariate techniques for enhancing classification

The composition of human fluids is modified during the course of neoplastic diseases. Urine analysis offers the advantage of being a noninvasive method for which samples are easily and routinely collected from patients. In this work, urine fluorescence spectra recorded upon excitation at 405 nm were obtained from healthy volunteers and individuals with different oncologic pathologies. A large number of indexes, i.e., parameters obtained from spectral data which assist spectral features characterization, were developed to classify healthy and pathological populations. The discrimination ability of simple predictive indexes, obtained from spectra pretreated with different normalization procedures and by taking their derivatives, was statistically assessed. In addition, multivariate methods, such as principal component analysis and multivariate curve resolution by alternating least squares, were used to develop more elaborate indexes for distinguishing between healthy and pathological populations. All indexes were systematically evaluated on a statistical basis by in lab-developed routines capable of detecting outliers, judging the normal distribution of the indexes, evaluating variance homogeneity, testing the difference between the means of healthy and pathological populations, as well as performing a receiver operator curve analysis to assess the classification power of each index. Those indexes with the best performances were further combined to perform a linear discriminant analysis, which yielded a powerful classification algorithm with an area under the receiver operator curve of 0.986, a sensitivity of 97.7%, a specificity of 100%, and an overall accuracy of 98.8%. The present study shows that the statistical analysis of urine fluorescence data with a proper combination of multivariate techniques bears a high potential to develop massive screening tests for the early detection of oncologic pathologies.

Fourier-transform infrared microspectroscopy of pulmonary edema fluid for postmortem diagnosis of diabetic ketoacidosis

Determination of the cause of death for diabetic ketoacidosis (DKA), a common and fatal acute complication of diabetes mellitus, is a challenging forensic task owing to the lack of characteristic morphological findings at autopsy. In this study, Fourier-transform infrared (FTIR) microspectroscopy coupled with chemometrics was employed to characterize biochemical differences in pulmonary edema fluid from different causes of death to supplement conventional methods and provide an efficient postmortem diagnosis of DKA. With this aim, FTIR spectra in three different situations (DKA-caused death, other causes of death with diabetes history, and other causes of death without diabetes history) were measured. The results of principal component analysis indicated different spectral profiles between these three groups, which mainly exhibited variations in proteins. Subsequently, two binary classification models were established using an algorithm of partial least squares discriminant analysis (PLS-DA) to determine whether decedents had diabetes and whether the diabetic patients died from DKA. Satisfactory prediction results of PLS-DA models demonstrated good differentiation among these three groups. Therefore, it is feasible to make a postmortem diagnosis of DKA and detect diabetes history via FTIR microspectroscopic analysis of the pulmonary edema fluid.

Identifying muscle hemorrhage in rat cadavers with advanced decomposition by FT-IR microspectroscopy combined with chemometrics

The identification of muscle hemorrhage in a cadaver that is in an advanced stage of decomposition is an important but challenging task. Our study investigated whether Fourier transform infrared (FT-IR) microspectroscopy in conjunction with chemometrics could identify muscle hemorrhage using rat cadavers with advanced decomposition. In this study, an intramuscular blood injection method, instead of a mechanical injury method, was used to construct a muscle hemorrhage model, and the modeling idea of muscle hemorrhage identification was to discriminate and classify hemoglobin-leaking myofibrils from negative myofibrils. First, the optical images of hematoxylin/eosin (H&E) stained hemorrhagic muscle at different postmortem intervals (PMIs) were observed and showed that the morphological features of whole erythrocytes disappeared since the PMI of 4 d. Subsequently, principle component analysis (PCA) was performed and indicated that the biochemical differences in protein structures between fresh erythrocytes and myofibrils can be detected by the IR spectroscopic method. Ultimately, several classification models based on the partial least square discriminant analysis (PLS-DA) algorithm were successfully constructed for different PMIs and PMI ranges and achieved great prediction performances in external validations. This preliminary study demonstrates the feasibility of using FT-IR microspectroscopy combined with chemometrics as a potential approach for identifying muscle hemorrhage in cadavers with advanced decomposition for offering vital evidences in judicial process.

Infrared spectroscopy of live cells from a flowing solution using electrically-biased plasmonic metasurfaces

Spectral cytopathology (SCP) is a promising label-free technique for diagnosing diseases and monitoring therapeutic outcomes using FTIR spectroscopy. In most cases, cells must be immobilized on a substrate prior to spectroscopic interrogation. This creates significant limitations for high throughput phenotypic whole-cell analysis, especially for the non-adherent cells. Here we demonstrate how metasurface-enhanced infrared reflection spectroscopy (MEIRS) can be applied to a continuous flow of live cell solution by applying AC voltage to metallic metasurfaces. By integrating metasurfaces with microfluidic delivery channels and attracting the cells to the metasurface via dielectrophoretic (DEP) force, we collect the infrared spectra of cells in real time within a minute, and correlate the spectra with simultaneously acquired images of the attracted cells. The resulting DEP-MEIRS technique paves the way for rapid SCP of complex cell-containing body fluids with low cell concentrations, and for the development of a wide range of label-free liquid biopsies.

Applications of Fourier transform infrared spectroscopy to pharmaceutical preparations

Introduction: Various pharmaceutical preparations are widely used for clinical treatment. Elucidation of the mechanisms of drug release and evaluation of drug efficacy in biological samples are important in drug design and drug quality control.Areas covered: This review classifies recent applications of Fourier transform infrared (FTIR) spectroscopy in the field of medicine to comprehend drug release and diffusion. Drug release is affected by many factors of preparations, such as drug delivery system and microstructure polymorphism. The applications of FTIR imaging and nano-FTIR technique in biological samples lay a foundation for studying drug mechanism in vivo.Expert opinion: FTIR spectroscopy meets the research needs on preparations to understand the processes and mechanisms underlying drug release. The combination of attenuated total reflectance-FTIR imaging and nano-FTIR accompanied by chemometrics is a potent tool to overcome the deficiency of conventional infrared detection. FTIR shows an enormous potential in drug characterization, drug quality control, and bio-sample detection.

Fourier Transform Infrared Spectroscopy as a Cancer Screening and Diagnostic Tool: A Review and Prospects

Infrared spectroscopy has long been used to characterize chemical compounds, but the applicability of this technique to the analysis of biological materials containing highly complex chemical components is arguable. However, recent advances in the development of infrared spectroscopy have significantly enhanced the capacity of this technique in analyzing various types of biological specimens. Consequently, there is an increased number of studies investigating the application of infrared spectroscopy in screening and diagnosis of various diseases. The lack of highly sensitive and specific methods for early detection of cancer has warranted the search for novel approaches. Being more simple, rapid, accurate, inexpensive, non-destructive and suitable for automation compared to existing screening, diagnosis, management and monitoring methods, Fourier transform infrared spectroscopy can potentially improve clinical decision-making and patient outcomes by detecting biochemical changes in cancer patients at the molecular level. Besides the commonly analyzed blood and tissue samples, extracellular vesicle-based method has been gaining popularity as a non-invasive approach. Therefore, infrared spectroscopic analysis of extracellular vesicles could be a useful technique in the future for biomedical applications. In this review, we discuss the potential clinical applications of Fourier transform infrared spectroscopic analysis using various types of biological materials for cancer. Additionally, the rationale and advantages of using extracellular vesicles in the spectroscopic analysis for cancer diagnostics are discussed. Furthermore, we highlight the challenges and future directions of clinical translation of the technique for cancer.

Comparison of transmission FTIR and ATR spectra for discrimination between beef and chicken meat and quantification of chicken in beef meat mixture using ATR-FTIR combined with chemometrics

Detecting meat adulteration for quality control and accurate labeling is important and needs convenient analytical methods. This study aimed to investigate and compare the application of the transmission and ATR approaches of FTIR followed by principal component analysis (PCA) to not only discriminate between chicken and beef meat but also quantizing chicken portion of mixtures. Two different approaches are presented; spectra preprocessing with focus on wavenumber region of 1700-1071 cm^-1, and no preprocessed where PCA was applied on the whole spectra range of mid-FTIR. The results suggest that applying PCA on specified preprocessed spectra could detect hidden relationships between variables in chicken and beef in both approaches. PCA successfully clustered these kinds of meats when applied on transmission mode spectra without any preprocessing treatment, while applying it on ATR mode's raw spectra failed to cluster them. Additionally, the preprocessed ATR-FTIR spectrum was used to prepare regression models by Partial Least Square Regression (PLS-R) and artificial neural networks (ANN) for predicting presence and percentage of chicken meat in the beef meat mixture. The results demonstrated the superiority of ANN over PLS-R in this assessment with an R2 of 0.999.

An Innovative Platform Merging Elemental Analysis and Ftir Imaging for Breast Tissue Analysis

Histopathology and immunohistology remain the gold standard for breast cancer diagnostic. Yet, these approaches do not usually provide a sufficiently detailed characterization of the pathology. The purpose of this work is to demonstrate for the first time that elemental analysis and Fourier transform infrared spectroscopy microscopic examination of breast tissue sections can be merged into one dataset to provide a single set of markers based on both organic molecules and inorganic trace elements. For illustrating the method, 6 mammary tissue sections were used. Fourier transform infrared (FTIR) spectroscopy images reported a fingerprint of the organic molecules present in the tissue section and laser ablation elemental analysis (LA-ICP-MS) images brought inorganic element profiles. The 6 tissue sections provided 31 10⁶ and 150,000 spectra for FTIR and LA-ICP-MS spectra respectively. The results bring the proof of concept that breast tissue can be analyzed simultaneously by FTIR spectroscopy and laser ablation elemental analysis (LA-ICP-MS) to provide in both case reasonably high resolution images. We show how to bring the images obtained by the two methods to a same spatial resolution and how to use image registration to analyze the data originating from both techniques as one block of data. We finally demonstrates the elemental analysis is orthogonal to all FTIR markers as no significant correlation is found between FTIR and LA-ICP-MS data. Combining FTIR and LA-ICP-MS imaging becomes possible, providing two orthogonal methods which can bring an unprecedented diversity of information on the tissue. This opens a new avenue of tissue section analyses providing unprecedented diagnostic potential.

Fourier transform infrared spectroscopic imaging of wear and corrosion products within joint capsule tissue from total hip replacements patients

Implant debris generated by wear and corrosion is a prominent cause of joint replacement failure. This study utilized Fourier transform infrared spectroscopic imaging (FTIR-I) to gain a better understanding of the chemical structure of implant debris and its impact on the surrounding biological environment. Therefore, retrieved joint capsule tissue from five total hip replacement patients was analyzed. All five cases presented different implant designs and histopathological patterns. All tissue samples were formalin-fixed and paraffin-embedded. Unstained, 5 μm thick sections were prepared. The unstained sections were placed on BaF₂ windows and deparaffinized with xylene prior to analysis. FTIR-I data were collected at a spectral resolution of 4 cm^-1 using an Agilent Cary 670 spectrometer coupled with Cary 620 FTIR microscope. The results of study demonstrated that FTIR-I is a powerful tool that can be used complimentary to the existing histopathological evaluation of tissue. FTIR-I was able to distinguish areas with different cell types (macrophages, lymphocytes). Small, but distinct differences could be detected depending on the state of cells (viable, necrotic) and depending on what type of debris was present (polyethylene [PE], suture material, and metal oxides). Although, metal oxides were mainly below the measurable range of FTIR-I, the infrared spectra of tissues exhibited noticeable difference in their presence. Tens of micrometer sized polyethylene particles could be easily imaged, but also accumulations of submicron particles could be detected within macrophages. FTIR-I was also able to distinguish between PE debris, and other birefringent materials such as suture. Chromium-phosphate particles originating from corrosion processes within modular taper junctions of hip implants could be identified and easily distinguished from other phosphorous materials such as bone. In conclusion, this study successfully demonstrated that FTIR-I is a useful tool that can image and determine the biochemical information of retrieved tissue samples over tens of square millimeters in a completely label free, nondestructive, and objective manner. The resulting chemical images provide a deeper understanding of the chemical nature of implant debris and their impact on chemical changes of the tissue within which they are embedded.

Biochemical detection of fatal hypothermia and hyperthermia in affected rat hypothalamus tissues by Fourier transform infrared spectroscopy

It is difficult to determinate the cause of death from exposure to fatal hypothermia and hyperthermia in forensic casework. Here, we present a state-of-the-art study that employs Fourier-transform infrared (FTIR) spectroscopy to investigate the hypothalamus tissues of fatal hypothermic, fatal hyperthermic and normothermic rats to determine forensically significant biomarkers related to fatal hypothermia and hyperthermia. Our results revealed that the spectral variations in the lipid, protein, carbohydrate and nucleic acid components are highly different for hypothalamuses after exposure to fatal hypothermic, fatal hyperthermic and normothermic conditions. In comparison with the normothermia group, the fatal hypothermia and hyperthermia groups contained higher total lipid amounts but were lower in unsaturated lipids. Additionally, their cell membranes were found to have less motional freedom. Among these three groups, the fatal hyperthermia group contained the lowest total proteins and carbohydrates and the highest aggregated and dysfunctional proteins, while the fatal hypothermia group contained the highest level of nucleic acids. In conclusion, this study demonstrates that FTIR spectroscopy has the potential to become a reliable method for the biochemical characterization of fatal hypothermia and hyperthermia hypothalamus tissues, and this could be used as a postmortem diagnostic feature in fatal hypothermia and hyperthermia deaths.

MIR-biospectroscopy coupled with chemometrics in cancer studies

This review focuses on chemometric techniques applied in MIR-biospectroscopy for cancer diagnosis and analysis over the last ten years of research. Experimental applications of chemometrics coupled with biospectroscopy are discussed throughout this work. The advantages and drawbacks of this association are also highlighted. Chemometric algorithms are evidenced as a powerful tool for cancer diagnosis, classification, and in different matrices. In fact, it is shown how chemometrics can be implemented along all different types of cancer analyses.

Characterization of human breast cancer tissues by infrared imaging

Fourier Transform InfraRed (FTIR) spectroscopy coupled to microscopy (IR imaging) has shown unique advantages in detecting morphological and molecular pathologic alterations in biological tissues. The aim of this study was to evaluate the potential of IR imaging as a diagnostic tool to identify characteristics of breast epithelial cells and the stroma. In this study a total of 19 breast tissue samples were obtained from 13 patients. For 6 of the patients, we also obtained Non-Adjacent Non-Tumor tissue samples. Infrared images were recorded on the main cell/tissue types identified in all breast tissue samples. Unsupervised Principal Component Analyses and supervised Partial Least Square Discriminant Analyses (PLS-DA) were used to discriminate spectra. Leave-one-out cross-validation was used to evaluate the performance of PLS-DA models. Our results show that IR imaging coupled with PLS-DA can efficiently identify the main cell types present in FFPE breast tissue sections, i.e. epithelial cells, lymphocytes, connective tissue, vascular tissue and erythrocytes. A second PLS-DA model could distinguish normal and tumor breast epithelial cells in the breast tissue sections. A patient-specific model reached particularly high sensitivity, specificity and MCC rates. Finally, we showed that the stroma located close or at distance from the tumor exhibits distinct spectral characteristics. In conclusion FTIR imaging combined with computational algorithms could be an accurate, rapid and objective tool to identify/quantify breast epithelial cells and differentiate tumor from normal breast tissue as well as normal from tumor-associated stroma, paving the way to the establishment of a potential complementary tool to ensure safe tumor margins.

Infrared spectroscopic imaging detects chemical modifications in liver fibrosis due to diabetes and disease

The importance of stroma as a rich diagnostic region in tissue biopsies is growing as there is an increasing understanding that disease processes in multiple organs can affect the composition of adjacent connective tissue regions. This may be especially true in the liver, since this organ's central metabolic role exposes it to multiple disease processes. We use quantum cascade laser infrared spectroscopic imaging to study changes in the chemical status of hepatocytes and fibrotic regions of liver tissue that result from the progression of liver cirrhosis to hepatocellular carcinoma and the potentially confounding effects of diabetes mellitus.

Vibrational spectroscopic methods for cytology and cellular research

The use of vibrational spectroscopy, FTIR and Raman, for cytology and cellular research has the potential to revolutionise the approach to cellular analysis. Vibrational spectroscopy is non-destructive, simple to operate and provides direct information. Importantly it does not require expensive exogenous labels that may affect the chemistry of the cell under analysis. In addition, the advent of spectroscopic microscopes provides the ability to image cells and acquire spectra with a subcellular resolution. This introductory review focuses on recent developments within this fast paced field and highlights potential for the future use of FTIR and Raman spectroscopy. We particularly focus on the development of live cell research and the new technologies and methodologies that have enabled this.

Using Fourier transform IR spectroscopy to analyze biological materials

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.

Histology verification demonstrates that biospectroscopy analysis of cervical cytology identifies underlying disease more accurately than conventional screening: removing the confounder of discordance

BACKGROUND

Subjective visual assessment of cervical cytology is flawed, and this can manifest itself by inter- and intra-observer variability resulting ultimately in the degree of discordance in the grading categorisation of samples in screening vs. representative histology. Biospectroscopy methods have been suggested as sensor-based tools that can deliver objective assessments of cytology. However, studies to date have been apparently flawed by a corresponding lack of diagnostic efficiency when samples have previously been classed using cytology screening. This raises the question as to whether categorisation of cervical cytology based on imperfect conventional screening reduces the diagnostic accuracy of biospectroscopy approaches; are these latter methods more accurate and diagnose underlying disease? The purpose of this study was to compare the objective accuracy of infrared (IR) spectroscopy of cervical cytology samples using conventional cytology vs. histology-based categorisation.

METHODS

Within a typical clinical setting, a total of n = 322 liquid-based cytology samples were collected immediately before biopsy. Of these, it was possible to acquire subsequent histology for n = 154. Cytology samples were categorised according to conventional screening methods and subsequently interrogated employing attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy. IR spectra were pre-processed and analysed using linear discriminant analysis. Dunn's test was applied to identify the differences in spectra. Within the diagnostic categories, histology allowed us to determine the comparative efficiency of conventional screening vs. biospectroscopy to correctly identify either true atypia or underlying disease.

RESULTS

Conventional cytology-based screening results in poor sensitivity and specificity. IR spectra derived from cervical cytology do not appear to discriminate in a diagnostic fashion when categories were based on conventional screening. Scores plots of IR spectra exhibit marked crossover of spectral points between different cytological categories. Although, significant differences between spectral bands in different categories are noted, crossover samples point to the potential for poor specificity and hampers the development of biospectroscopy as a diagnostic tool. However, when histology-based categories are used to conduct analyses, the scores plot of IR spectra exhibit markedly better segregation.

CONCLUSIONS

Histology demonstrates that ATR-FTIR spectroscopy of liquid-based cytology identifies the presence of underlying atypia or disease missed in conventional cytology screening. This study points to an urgent need for a future biospectroscopy study where categories are based on such histology. It will allow for the validation of this approach as a screening tool.

Exploiting biospectroscopy as a novel screening tool for cervical cancer: towards a framework to validate its accuracy in a routine clinical setting

Biospectroscopy is an emerging field that harnesses the platform of physical sciences with computational analysis in order to shed novel insights on biological questions. An area where this approach seems to have potential is in screening or diagnostic clinical settings, where there is an urgent need for new approaches to objectively interrogate large numbers of samples in an objective fashion with acceptable levels of sensitivity and specificity. This review outlines the benefits of biospectroscopy in screening for precancer lesions of the cervix due to its ability to separate different grades of dysplasia. It evaluates the feasibility of introducing this technique into cervical screening programs on the basis of its ability to identify biomarkers of progression within derived spectra (‘biochemical‑cell fingerprints’).

Differential effects in mammalian cells induced by chemical mixtures in environmental biota as profiled using infrared spectroscopy

Environmental contaminants accumulate in many organisms and induce a number of adverse effects. As contaminants mostly occur in the environment as mixtures, it remains to be fully understood which chemical interactions induce the most important toxic responses. In this study, we set out to determine the effects of chemical contaminants extracted from Northern Gannet (Morus bassanus) eggs (collected from the UK coast from three sampling years (1987, 1990, and 1992) on cell cultures using infrared (IR) spectroscopy with computational data handling approaches. Gannet extracts were chemically analyzed for different contaminants, and MCF-7 cell lines were treated for 24 h in a dose-related manner with individual-year extracts varying in their polybrominated diphenyl ether (PBDE) to polychlorinated biphenyl (PCB) ratios. Treated cellular material was then fixed and interrogated using attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy; resultant IR spectra were computationally analyzed to derive dose-response relationships and to identify biomarkers associated with each contaminant mixture treatment. The results show distinct biomarkers of effect are related to each contamination scenario, with an inverse relationship with dose observed. This study suggests that specific contaminant mixtures induce cellular alterations in the DNA/RNA spectral region that are most pronounced at low doses. It also suggests alterations in the "biochemical-cell fingerprint" of IR spectra can be indicative of mixture exposures.

Effect of normal variations on disease classification of Raman spectra from cervical tissue

In this paper, we examine how variations in normal tissue can influence disease classification of Raman spectra. Raman spectra from normal areas may be affected by previous disease or proximity to areas of dysplasia. Spectra were acquired in vivo from 172 patients and classified into five tissue categories: true normal (no history of disease), previous disease normal (history of disease, current normal diagnosis), adjacent normal (disease on cervix, spectra acquired from visually normal area), low grade, and high grade. Taking into account the various "normal" states of the tissue before statistical analysis led to a disease classification accuracy of 97%. These results indicate that abnormal changes significantly affect Raman spectra, even when areas are histopathologically normal. The sensitivity of Raman spectroscopy to subtle biochemical differences must be considered in order to successfully implement it in a clinical setting for diagnosing cervical dysplasia and cancer.

Infrared spectroscopy with multivariate analysis to interrogate endometrial tissue: a novel and objective diagnostic approach

BACKGROUND

Endometrial cancer is the most common gynaecological malignancy in the United Kingdom. Diagnosis currently involves subjective expert interpretation of highly processed tissue, primarily using microscopy. Previous work has shown that infrared (IR) spectroscopy can be used to distinguish between benign and malignant cells in a variety of tissue types.

METHODS

Tissue was obtained from 76 patients undergoing hysterectomy, 36 had endometrial cancer. Slivers of endometrial tissue (tumour and tumour-adjacent tissue if present) were dissected and placed in fixative solution. Before analysis, tissues were thinly sliced, washed, mounted on low-E slides and desiccated; 10 IR spectra were obtained per slice by attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy. Derived data was subjected to principal component analysis followed by linear discriminant analysis. Post-spectroscopy analyses, tissue sections were haematoxylin and eosin-stained to provide histological verification.

RESULTS

Using this approach, it is possible to distinguish benign from malignant endometrial tissue, and various subtypes of both. Cluster vector plots of benign (verified post-spectroscopy to be free of identifiable pathology) vs malignant tissue indicate the importance of the lipid and secondary protein structure (Amide I and Amide II) regions of the spectrum.

CONCLUSION

These findings point towards the possibility of a simple objective test for endometrial cancer using ATR-FTIR spectroscopy. This would facilitate earlier diagnosis and so reduce the morbidity and mortality associated with this disease.

Discrimination of zone-specific spectral signatures in normal human prostate using Raman spectroscopy

The prostate gland is the most common site of pathology in human males. Using the urethra as an anatomical reference point, it can be divided into three distinct zones known as the transition zone (TZ), peripheral zone (PZ) and central zone (CZ). The pathological conditions of benign prostatic hypertrophy and/or prostate adenocarcinoma are highly prevalent in this gland. This preliminary study set out to determine whether biochemical intra-individual differences between normal prostate zones could be identified using Raman spectroscopy with subsequent exploratory analyses. A normal (benign) prostate transverse tissue section perpendicular to the rectal surface and above the verumontanum was obtained in a paraffin-embedded block. A 10-µm-thick slice was floated onto a gold substrate, de-waxed and analysed using Raman spectroscopy (200 epithelial-cell and 140 stromal spectra/zone). Raman spectra were subsequently processed in the 1800-367 cm(-1) spectral region employing principal component analysis (PCA) to determine whether wavenumber-intensity relationships expressed as single points in hyperspace might reveal biochemical differences associated with inter-zone pathological susceptibility. Visualisation of PCA scores plots and their corresponding loadings plots highlighted 781 cm(-1) (cytosine/uracil) and 787 cm(-1) (DNA) as the key discriminating factors segregating PZ from less susceptible TZ and CZ epithelia (P < 0.001). Conversely, 1459 cm(-1) (lipids and proteins) and 1003 cm(-1) (phenylalanine) were identified as the key biochemical factor distinguishing TZ from CZ epithelia (P < 0.05). All stromal zones were discriminated by the protein/lipid region (1459 cm(-1) and 1100 cm(-1)) with DNA/RNA region (781 cm(-1) and 787 cm(-1)) only highlighted between PZ and CZ (P < 0.05). This novel approach identifies biochemical markers that may have aetiological functional roles towards susceptibility of human prostate zones to specific pathological conditions.

Distinguishing cell types or populations based on the computational analysis of their infrared spectra

Infrared (IR) spectroscopy of intact cells results in a fingerprint of their biochemistry in the form of an IR spectrum; this has given rise to the new field of biospectroscopy. This protocol describes sample preparation (a tissue section or cytology specimen), the application of IR spectroscopy tools, and computational analysis. Experimental considerations include optimization of specimen preparation, objective acquisition of a sufficient number of spectra, linking of the derived spectra with tissue architecture or cell type, and computational analysis. The preparation of multiple specimens (up to 50) takes 8 h; the interrogation of a tissue section can take up to 6 h (∼100 spectra); and cytology analysis (n = 50, 10 spectra per specimen) takes 14 h. IR spectroscopy generates complex data sets and analyses are best when initially based on a multivariate approach (principal component analysis with or without linear discriminant analysis). This results in the identification of class clustering as well as class-specific chemical entities.

Discrimination of base differences in oligonucleotides using mid-infrared spectroscopy and multivariate analysis

Attenuated total reflection Fourier transform-infrared (ATR-FTIR) spectroscopy was employed to interrogate a panel of simple oligonucleotides designed to contain various base differences; combined with subsequent multivariate analysis, we set out to determine whether the specificity of this approach would point to a novel means for mutation detection. Oligonucleotides were designed that were 15 bases in length and contained various combinations of purines (adenine, guanine) or pyrimidines (cytosine, thymine). These were applied to 1 cm x 1 cm low-E reflective glass slides, and triplicate samples were interrogated using ATR-FTIR spectroscopy. Per oligonucleotide sample, 10 independent spectral acquisitions were obtained. Prior to multivariate analysis, infrared spectra were baseline-corrected and vector normalized over the 1750-760 cm(-1) region specific to the chemical bonds of organic molecules. Spectral categories were then analyzed using principal component analysis (PCA) followed by linear discriminant analysis (LDA). Scores plots revealed that PCA-LDA clearly segregated different oligonucleotide sequences, even in the presence of a single base difference. Loadings plots confirmed the chemical entities associated with distinguishing base differences. These results suggest that mid-IR spectroscopy might have future roles in interrogating polymorphic forms of a DNA template.

Tracking the cell hierarchy in the human intestine using biochemical signatures derived by mid-infrared microspectroscopy

Markers of gastrointestinal (GI) stem cells remain elusive. We employed synchrotron Fourier-transform infrared (FTIR) microspectroscopy to derive mid-infrared (IR) spectra along the length of human GI crypts. Tissue sections (10-μm thick) were floated onto BaF2 windows and image maps were acquired of small intestine and large bowel crypts in transmission mode with an aperture of ≤10 μm×10 μm. Counting upwards in a step-size (≤10 μm) fashion from the crypt base, IR spectra were extracted from the image maps and each spectrum corresponding to a particular location was identified. Spectra were analyzed using principal component analysis plus linear discriminant analysis. Compared to putative crypt base columnar/Paneth cells, those assigned as label-retaining cells were chemically more similar to putative large bowel stem cells and, the small intestine transit-amplifying cells were closest to large bowel transit-amplifying cells; interestingly, the base of small intestine crypts was the most chemically-distinct. This study suggests that in the complex cell lineage of human GI crypts, chemical similarities as revealed by FTIR microspectroscopy between regions putatively assigned as stem cell, transit-amplifying and terminally-differentiated facilitates identification of cell function.