Factors influencing the discrimination and classification of prostate cancer cell lines by FTIR microspectroscopy

The Authentication of Gayo Arabica Green Coffee Beans with Different Cherry Processing Methods Using Portable LED-Based Fluorescence Spectroscopy and Chemometrics Analysis

Aceh is an important region for the production of high-quality Gayo arabica coffee in Indonesia. In this area, several coffee cherry processing methods are well implemented including the honey process (HP), wine process (WP), and natural process (NP). The most significant difference between the three coffee cherry processing methods is the fermentation process: HP is a process of pulped coffee bean fermentation, WP is coffee cherry fermentation, and NP is no fermentation. It is well known that the WP green coffee beans are better in quality and are sold at higher prices compared with the HP and NP green coffee beans. In this present study, we evaluated the utilization of fluorescence information to discriminate Gayo arabica green coffee beans from different cherry processing methods using portable fluorescence spectroscopy and chemometrics analysis. A total of 300 samples were used (n = 100 for HP, WP, and NP, respectively). Each sample consisted of three selected non-defective green coffee beans. Fluorescence spectral data from 348.5 nm to 866.5 nm were obtained by exciting the intact green coffee beans using a portable spectrometer equipped with four 365 nm LED lamps. The result showed that the fermented green coffee beans (HP and WP) were closely mapped and mostly clustered on the left side of PC1, with negative scores. The non-fermented (NP) green coffee beans were clustered mostly on the right of PC1 with positive scores. The results of the classification using partial least squares-discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and principal component analysis-linear discriminant analysis (PCA-LDA) are acceptable, with an accuracy of more than 80% reported. The highest accuracy of prediction of 96.67% was obtained by using the PCA-LDA model. Our recent results show the potential application of portable fluorescence spectroscopy using LED lamps to classify and authenticate the Gayo arabica green coffee beans according to their different cherry processing methods. This innovative method is more affordable and could be easy to implement (in terms of both affordability and practicability) in the coffee industry in Indonesia.

Evaluation of the Cytotoxic Effect of Pd2Spm against Prostate Cancer through Vibrational Microspectroscopies

Regarding the development of new antineoplastic agents, with a view to assess the selective antitumoral potential which aims at causing irreversible damage to cancer cells while preserving the integrity of their healthy counterparts, it is essential to evaluate the cytotoxic effects in both healthy and malignant human cell lines. In this study, a complex with two Pd(II) centers linked by the biogenic polyamine spermine (Pd₂Spm) was tested on healthy (PNT-2) and cancer (LNCaP and PC-3) prostate human cell lines, using cisplatin as a reference. To understand the mechanisms of action of both cisplatin and Pd₂Spm at a molecular level, Fourier Transform Infrared (FTIR) and Raman microspectroscopies were used. Principal component analysis was applied to the vibrational data, revealing the major metabolic changes caused by each drug, which were found to rely on DNA, lipids, and proteins, acting as biomarkers of drug impact. The main changes were observed between the B-DNA native conformation and either Z-DNA or A-DNA, with a higher effect on lipids having been detected in the presence of cisplatin as compared to Pd₂Spm. In turn, the Pd-agent showed a more significant impact on proteins.

Rapid Prediction of Fig Phenolic Acids and Flavonoids Using Mid-Infrared Spectroscopy Combined With Partial Least Square Regression

Mid-infrared spectroscopy using Fourier transform infrared (FTIR) with attenuated total reflectance (ATR) correction was coupled with partial least square regression (PLSR) for the prediction of phenolic acids and flavonoids in fig (peel and pulp) identified with high-performance liquid chromatography-diode array detector (HPLC-DAD), with regards to their partitioning between peel and pulp. HPLC-DAD was used to quantify the phenolic compounds (PCs). The FTIR spectra were collected between 4,000 and 450 cm^-1 and the data in the wavenumber range of 1.175-940 cm^-1, where the deformations of O-H, C-O, C-H, and C=C corresponded to flavanol and phenols, were used for the establishment of PLSR models. Nine PLSR models were constructed for peel samples, while six were built for pulp extracts. The results showed a high-throughput accuracy of such an approach to predict the PCs in the powder samples. Significant differences were detected between the models built for the two fruit parts. Thus, for both peel and pulp extracts, the coefficient of determination (R²) ranged from 0.92 to 0.99 and between 0.85 and 0.95 for calibration and cross-validation, respectively, along with a root mean square error (RMSE) values in the range of 0.46-0.9 and 0.23-2.05, respectively. Residual predictive deviation (RPD) values were generally satisfactory, where cyanidin-3,5-diglucoside and cyanidin-3-O-rutinoside had the higher level (RPD > 2.5). Similar differences were observed based on the distribution revealed by partial least squares discriminant analysis (PLS-DA), which showed a remarkable overlapping in the distribution of the samples, which was intense in the pulp extracts. This study suggests the use of FTIR-ATR as a rapid and accurate method for PCs assessment in fresh fig.

Diagnostic segregation of human breast tumours using Fourier-transform infrared spectroscopy coupled with multivariate analysis: Classifying cancer subtypes

The present study aimed to investigate whether attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy coupled with multivariate analysis could be applied to discriminate and classify among breast tumour molecular subtypes based on the unique spectral "fingerprints" of their biochemical composition. The different breast cancer tissues and normal breast tissues were collected and identified by pathology and ATR-FTIR spectroscopy respectively. The study indicates that the levels of the lipid-to-protein, nucleic acid-to-lipid, phosphate-to-carbohydrate and their secondary structure ratio, including RNA-to-DNA, Amide I-to-Amide II, and RNA-to-lipid ratios were significantly altered among the molecular subtype of breast tumour compared with normal breast tissues, which helps explain the changes in the biochemical structure of different molecular phenotypes of breast cancer. Tentatively-assigned characteristic peak ratios of infrared (IR) spectra reflect the changes of the macromolecule structure in different issues to a great extent and can be used as a potential biomarker to predict the molecular subtype of breast tumour. The present study acts as the first case study to show the successful application of IR spectroscopy in classifying subtypes of breast cancer with biochemical alterations. Therefore, the present study is likely to help to provide a new diagnostic approach for the accurate diagnosis of breast tumours and differential molecular subtypes and has the potential to be used for further intraoperative management.

Combined Effect of Cultivar and Peel Chromaticity on Figs' Primary and Secondary Metabolites: Preliminary Study Using Biochemical and FTIR Fingerprinting Coupled to Chemometrics

Simple Summary

Primary and secondary metabolites are among the markers for addressing fig chemotypic variability. These compounds are mainly driven by the cultivar factor besides chromatic coordinates color as they are highly correlated to these biomarkers. Combined use of chemical analytical procedures and vibrational spectroscopy is of great importance for a better understanding of network connections within the dataset. In this study, we screened 11 fig tree cultivars for their biochemical and spectral fingerprints in a comparative scheme for high resolution discrimination. Analytical methods herein used were also evaluated for their greenness aspects using GAPI eco-scale tool.

Abstract

Figs are a traditional pantry staple for healthy eating in Middle Eastern and North African countries as fig trees grow abundantly in such hot and dry climates. Despite the importance of this species, chemotypic diversity has gone unheeded and therefore its valorization pathways remain poorly documented. For this reason, high-pressure liquid chromatography (HPLC) alongside vibrational spectroscopy were used to investigate the changes of antiradical potency and primary and secondary metabolites in fresh figs with regard to the combined effect of the cultivar factor and the fruit peel chromatic coordinates. Fourier-transform infrared spectroscopy (FTIR) fingerprinting displayed six major peaks assigned to functional groups of the investigated samples with significant differences in their vibration intensities. Biochemical screening revealed highly significant variability (p < 0.05) among the investigated cultivars. Antioxidant activity was found to be higher in free radical scavenging using 2,2-diphenyl-1-picrylhydrazyl (DPPH) compared to ferric reducing ability (FRAP). Chemometric investigations of both biochemical and FTIR fingerprinting showed satisfactory resolutions, and the total phenol contents and chromatic coordinates had the highest scores in the dataset. However, the cultivars’ geographical origin seemed not to have a clear impact on the clustering results. The aforementioned analytical procedures were found to be equally important and can be jointly used for high-resolution screening and discrimination of fig trees.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

The Impact of Preprocessing Methods for a Successful Prostate Cell Lines Discrimination Using Partial Least Squares Regression and Discriminant Analysis Based on Fourier Transform Infrared Imaging

Fourier transform infrared spectroscopy (FT-IR) is widely used in the analysis of the chemical composition of biological materials and has the potential to reveal new aspects of the molecular basis of diseases, including different types of cancer. The potential of FT-IR in cancer research lies in its capability of monitoring the biochemical status of cells, which undergo malignant transformation and further examination of spectral features that differentiate normal and cancerous ones using proper mathematical approaches. Such examination can be performed with the use of chemometric tools, such as partial least squares discriminant analysis (PLS-DA) classification and partial least squares regression (PLSR), and proper application of preprocessing methods and their correct sequence is crucial for success. Here, we performed a comparison of several state-of-the-art methods commonly used in infrared biospectroscopy (denoising, baseline correction, and normalization) with the addition of methods not previously used in infrared biospectroscopy classification problems: Mie extinction extended multiplicative signal correction, Eiler’s smoothing, and probabilistic quotient normalization. We compared all of these approaches and their effect on the data structure, classification, and regression capability on experimental FT-IR spectra collected from five different prostate normal and cancerous cell lines. Additionally, we tested the influence of added spectral noise. Overall, we concluded that in the case of the data analyzed here, the biggest impact on data structure and performance of PLS-DA and PLSR was caused by the baseline correction; therefore, much attention should be given, especially to this step of data preprocessing.

Analysis of Fixed and Live Single Cells Using Optical Photothermal Infrared with Concomitant Raman Spectroscopy

This paper reports the first use of a novel completely optically based photothermal method (O-PTIR) for obtaining infrared spectra of both fixed and living cells using a quantum cascade laser (QCL) and optical parametric oscillator (OPO) laser as excitation sources, thus enabling all biologically relevant vibrations to be analyzed at submicron spatial resolution. In addition, infrared data acquisition is combined with concomitant Raman spectra from exactly the same excitation location, meaning the full vibrational profile of the cell can be obtained. The pancreatic cancer cell line MIA PaCa-2 and the breast cancer cell line MDA-MB-231 are used as model cells to demonstrate the capabilities of the new instrumentation. These combined modalities can be used to analyze subcellular structures in both fixed and, more importantly, live cells under aqueous conditions. We show that the protein secondary structure and lipid-rich bodies can be identified on the submicron scale.

Spectral histopathology of the lung: A review of two large studies

This paper summarizes results from two large lung cancer studies comprising over 700 samples that demonstrate the ability of spectral histopathology (SHP) to distinguish cancerous tissue regions from normal tissue, to differentiate benign lesions from normal tissue and cancerous lesions, and to classify lung cancer types. Furthermore, malignancy-associated changes can be identified in cancer-adjacent normal tissue. The ability to differentiate a multitude of normal cells and tissue types allow SHP to identify tumor margins and immune cell infiltration. Finally, SHP easily distinguishes small cell lung cancer (SCLC) from non-SCLC (NSCLC) and provides a further differentiation of NSCLC into adenocarcinomas and squamous cell carcinomas with an accuracy comparable of classical histopathology combined with immunohistochemistry. Case studies are presented that demonstrates that SHP can resolve interobserver discrepancies in standard histopathology.

An early investigative serum Raman spectroscopy study of meningioma

Meningiomas represent one of the most frequently reported non-glial, primary brain and central nervous system (CNS) tumors. Meningiomas often display a spectrum of anomalous locations and morphological attributes, deterring their timely diagnosis. Majority of them are sporadic in nature and thus the present-day screening strategies, including radiological investigations, often result in misdiagnosis due to their aberrant and equivocal radiological facets. Therefore, it is pertinent to explore less invasive and patient-friendly biofluids such as serum for their screening and diagnostics. The utility of serum Raman spectroscopy in diagnosis and therapeutic monitoring of cancers has been reported in the literature. In the present study, for the first time, to the best of our knowledge, we have explored Raman spectroscopy to classify the sera of meningioma and control subjects. For this exploration, 35 samples each of meningioma and control subjects were accrued and the spectra revealed variance in the levels of DNA, proteins, lipids, amino acids and β-carotene, i.e., a relatively higher protein, DNA and lipid content in meningioma. Subsequent Principal Component Analysis (PCA) and Principal Component-Linear Discriminant Analysis (PC-LDA) followed by Leave-One-Out Cross-Validation (LOOCV) and limited independent test data, in a patient-wise approach, yielded a classification efficiency of 92% and 80% for healthy and meningioma, respectively. Additionally, in the analogous analysis between healthy and different grades of meningioma, similar results were obtained. These results indicate the potential of Raman spectroscopy in differentiating meningioma. As present methods suffer from known limitations, with the prospective validation on a larger cohort, serum Raman spectroscopy could be an adjuvant/alternative approach in the clinical management of meningioma.

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.

Exploring the effect of vitamin E in cancer chemotherapy-A biochemical and biophysical insight

Many oncologists contend that patient undergoing chemotherapy must avoid antioxidant supplementation as it may interfere with the activity of the drug. In the present investigation, we have explored the influence of vitamin E, a well-known antioxidant on Camptothecin (CPT), a potent anti-cancer drug induced cell apoptosis and death of cervical cancer cells. HeLa cells were treated with different concentrations of CPT in presence and absence of 100 μm vitamin E. Treated cells were subjected to cytotoxicity studies, catalase assay, DNA fragmentation assay, clonogenic assay and flow cytometry based apoptosis detection. Also, Raman spectroscopy a label free technique which provides global information, in conjunction with multivariate tools like PCA, PCLDA and FDA, was investigated to explore vitamin E supplementation induced alterations. Our data based on biochemical and biophysical experimental analysis reveals that CPT causes DNA damage along with protein and lipid alteration culminating in cell death. Importantly, Raman spectroscopic analysis could uniquely differentiate the cluster of control and vitamin E control from CPT and CPT + Vit E treated cells. We conclusively prove that presence of vitamin E at 100 μM concentration shows promising antioxidant activity and displays no modulatory role on CPT induced effect, thereby causing no possible hindrance with the efficacy of the drug. Vitamin E may prove beneficial to alleviate chemotherapy associated side effects in patients during clinical settings which may open the doors further for subsequent exploration in in vivo preclinical studies.

Increased optical pathlength through aqueous media for the infrared microanalysis of live cells

The study of live cells using Fourier transform infrared spectroscopy (FTIR) and FTIR microspectroscopy (FT-IRMS) intrinsically yields more information about cell metabolism than comparable experiments using dried or chemically fixed samples. There are, however, a number of barriers to obtaining high-quality vibrational spectra of live cells, including correction for the significant contributions of water bands to the spectra, and the physical stresses placed upon cells by compression in short pathlength sample holders. In this study, we present a water correction method that is able to result in good-quality cell spectra from water layers of 10 and 12 μm and demonstrate that sufficient biological detail is retained to separate spectra of live cells based upon their exposure to different novel anti-cancer agents. The IR brilliance of a synchrotron radiation (SR) source overcomes the problem of the strong water absorption and provides cell spectra with good signal-to-noise ratio for further analysis. Supervised multivariate analysis (MVA) and investigation of average spectra have shown significant separation between control cells and cells treated with the DNA cross-linker PL63 on the basis of phosphate and DNA-related signatures. Meanwhile, the same control cells can be significantly distinguished from cells treated with the protein kinase inhibitor YA1 based on changes in the amide II region. Each of these separations can be linked directly to the known biochemical mode of action of each agent.

Infrared micro-spectroscopy of human tissue: principles and future promises

This article summarizes the methods employed, and the progress achieved over the past two decades in applying vibrational (Raman and IR) micro-spectroscopy to problems of medical diagnostics and cellular biology. During this time, several research groups have verified the enormous information contained in vibrational spectra; in fact, information on protein, lipid and metabolic composition of cells and tissues can be deduced by decoding the observed vibrational spectra. This decoding process is aided by the availability of computer workstations and advanced algorithms for data analysis. Furthermore, commercial instrumentation for the fast collection of both Raman and infrared micro-spectral data has enabled the collection of images of cells and tissues based solely on vibrational spectroscopic data. The progress in the field has been manifested by a steady increase in the number and quality of publications submitted by established and new research groups in vibrational spectroscopy in the biological and biomedical arenas.

Raman exfoliative cytology for oral precancer diagnosis

Oral premalignant lesions (OPLs) such as leukoplakia, erythroplakia, and oral submucous fibrosis, often precede oral cancer. Screening and management of these premalignant conditions can improve prognosis. Raman spectroscopy has previously demonstrated potential in the diagnosis of oral premalignant conditions (in vivo), detected viral infection, and identified cancer in both oral and cervical exfoliated cells (ex vivo). The potential of Raman exfoliative cytology (REC) in identifying premalignant conditions was investigated. Oral exfoliated samples were collected from healthy volunteers (n=20), healthy volunteers with tobacco habits (n=20), and oral premalignant conditions (n=27, OPL) using Cytobrush. Spectra were acquired using Raman microprobe. Spectral acquisition parameters were: λex: 785 nm, laser power: 40 mW, acquisition time: 15 s, and average: 3. Postspectral acquisition, cell pellet was subjected to Pap staining. Multivariate analysis was carried out using principal component analysis and principal component-linear discriminant analysis using both spectra- and patient-wise approaches in three- and two-group models. OPLs could be identified with ∼77% (spectra-wise) and ∼70% (patient-wise) sensitivity in the three-group model while with 86% (spectra-wise) and 83% (patient-wise) in the two-group model. Use of histopathologically confirmed premalignant cases and better sampling devices may help in development of improved standard models and also enhance the sensitivity of the method. Future longitudinal studies can help validate potential of REC in screening and monitoring high-risk populations and prognosis prediction of premalignant lesions.

Identification of morphological and biochemical changes in keratin-8/18 knock-down cells using Raman spectroscopy

Accurate understanding of cellular processes and responses to stimuli is of paramount importance in biomedical research and diagnosis. Raman spectroscopy (RS), a label-free and nondestructive spectroscopic method has the potential to serve as a novel 'theranostics' tool. Both fiber-optic and micro-Raman studies have demonstrated efficacy in diagnostics and therapeutic response monitoring. In the present study, we have evaluated the potential of micro-Raman spectroscopic maps in identifying changes induced by loss of K8/18 proteins in a tongue cancer cell line. Furthermore, we also evaluated the efficacy of less expensive and commercially available fiber probes to identify K8/18 wild and knock-down cell pellets, in view of the utility of cell pellet-based studies. The findings suggest that major differences in the cellular morphology and biochemical composition can be objectively identified and can be utilized for classification using both micro-Raman and fiber-probe-based RS. These findings highlight the potential of fiber-optic probe-based RS in noninvasive cellular phenotyping for diagnosis and therapeutic response monitoring, especially in low-resource settings.

Raman micro-spectroscopy applied to treatment resistant and sensitive human ovarian cancer cells

Despite the many advances intended to enhance the response to treatment, the survival rate of patients with ovarian cancer has only marginally improved in the past few decades. One major cause for this, is the lack of diagnostics for platinum-resistant disease. The goal of this study was to determine whether Raman micro-spectroscopy in conjunction with multivariate statistical analysis could discriminate between chemically fixed cisplatin-resistant (A2780cp) and cisplatin-sensitive (A2780s) human ovarian carcinoma cells. Raman spectra collected from individual cells were pre-processed and subsequently analyzed with Principal Component Analysis - Linear Discriminant Analysis (PCA-LDA). Statistically significant differences (P <  0.0001) were observed between the Raman spectra of A2780s and A2780cp cells. A diagnostic accuracy of 82% was obtained using the PCA-LDA classifier model for the discrimination between the A2780s and A2780cp cells. The loading plot analysis suggests that relative increases in proteins and glutathione in the cisplatin-resistant cells compared to the cisplatin-sensitive cells are most likely the major source of discrimination between the two types of cells. These results support the potential application of Raman spectroscopy in the identification of chemo-resistant tumors prior to treatment.

Hyperspectral Raman imaging of human prostatic cells: An attempt to differentiate normal and malignant cell lines by univariate and multivariate data analysis

Hyperspectral Raman images of human prostatic cells have been collected and analysed with several approaches to reveal differences among normal and tumor cell lines. The objective of the study was to test the potential of different chemometric methods in providing diagnostic responses. We focused our analysis on the ν(CH) region (2800-3100cm^-1) owing to its optimal Signal-to-Noise ratio and because the main differences between the spectra of the two cell lines were observed in this frequency range. Multivariate analysis identified two principal components, which were positively recognized as due to the protein and the lipid fractions, respectively. The tumor cells exhibited a modified distribution of the cytoplasmatic lipid fraction (mainly localized alongside the cell boundary) which may result very useful for a preliminary screening. Principal Component analysis was found to provide high contrast and to be well suited for image-processing purposes. Self-Modelling Curve Resolution made available meaningful spectra and relative-concentration values; it revealed a 97% increase of the lipid fraction in the tumor cell with respect to the control. Finally, a univariate approach confirmed significant and reproducible differences between normal and tumor cells.

Fourier-transform infrared spectroscopy as a novel approach to providing effect-based endpoints in duckweed toxicity testing

Traditional duckweed toxicity tests only measure plant growth inhibition as an endpoint, with limited effects-based data. The present study aimed to investigate whether Fourier-transform infrared (FTIR) spectroscopy could enhance the duckweed (Lemna minor L.) toxicity test. Four chemicals (Cu, Cd, atrazine, and acetochlor) and 4 metal-containing industrial wastewater samples were tested. After exposure of duckweed to the chemicals, standard toxicity endpoints (frond number and chlorophyll content) were determined; the fronds were also interrogated using FTIR spectroscopy under optimized test conditions. Biochemical alterations associated with each treatment were assessed and further analyzed by multivariate analysis. The results showed that comparable x% of effective concentration (ECx) values could be achieved based on FTIR spectroscopy in comparison with those based on traditional toxicity endpoints. Biochemical alterations associated with different doses of toxicant were mainly attributed to lipid, protein, nucleic acid, and carbohydrate structural changes, which helped to explain toxic mechanisms. With the help of multivariate analysis, separation of clusters related to different exposure doses could be achieved. The present study is the first to show successful application of FTIR spectroscopy in standard duckweed toxicity tests with biochemical alterations as new endpoints. Environ Toxicol Chem 2017;36:346-353. © 2016 SETAC.

High wavenumber Raman spectroscopy in the characterization of urinary metabolites of normal subjects, oral premalignant and malignant patients

Urine has emerged as one of the diagnostically potential bio fluids, as it has many metabolites. As the concentration and the physiochemical properties of the urinary metabolites may vary under pathological transformation, Raman spectroscopic characterization of urine has been exploited as a significant tool in identifying several diseased conditions, including cancers. In the present study, an attempt was made to study the high wavenumber (HWVN) Raman spectroscopic characterization of urine samples of normal subjects, oral premalignant and malignant patients. It is concluded that the urinary metabolites flavoproteins, tryptophan and phenylalanine are responsible for the observed spectral variations between the normal and abnormal groups. Principal component analysis-based linear discriminant analysis was carried out to verify the diagnostic potentiality of the present technique. The discriminant analysis performed across normal and oral premalignant subjects classifies 95.6% of the original and 94.9% of the cross-validated grouped cases correctly. In the second analysis performed across normal and oral malignant groups, the accuracy of the original and cross-validated grouped cases was 96.4% and 92.1% respectively. Similarly, the third analysis performed across three groups, normal, oral premalignant and malignant groups, classifies 93.3% and 91.2% of the original and cross-validated grouped cases correctly.

Automated analysis of single cells using Laser Tweezers Raman Spectroscopy

In recent years, significant progress has been made into the label-free detection and discrimination of individual cancer cells using Laser Tweezers Raman Spectroscopy (LTRS). However, the majority of examples reported have involved manual trapping of cells, which is time consuming and may lead to different cell lines being analysed in discrete batches. A simple, low-cost microfluidic flow chamber is introduced which allows single cells to be optically trapped and analysed in an automated fashion, greatly reducing the level of operator input required. Two implementations of the flow chamber are discussed here; a basic single-channel device in which the fluid velocity is controlled manually, and a dual-channel device which permits the automated capture and analysis of multiple cell lines with no operator input. Results are presented for the discrimination of live epithelial prostate cells and lymphocytes, together with a consideration of the consequences of traditional 'batch analysis' typically used for LTRS of live cells.

Can mid-infrared biomedical spectroscopy of cells, fluids and tissue aid improvements in cancer survival? A patient paradigm

This review will take a fresh approach from the patient perspective; offering insight into the applications of mid-infrared biomedical spectroscopy in a scenario whereby the patient presents with non-specific symptoms and via an extensive diagnostic process multiple lesions are discovered but no clear sign of the primary tumour; a condition known as cancer of unknown primary (CUP). With very limited options to diagnose the cancer origin, treatment options are likely to be ineffective and prognosis is consequentially very poor. CUP has not yet been targeted by infrared biospectroscopy, however, this timely, concise dissemination will focus on a series of research highlights and breakthroughs from the field for the management of a variety of cancer-related diseases - many examples of which have occurred within this year alone. The case for integration of mid-infrared (MIR) technology into clinical practice will be demonstrated largely via diagnostic, but also therapeutic and prognostic avenues by means of including cytological, bio-fluid and tissue analysis. The review is structured around CUP but is relevant for all cancer diagnoses. Infrared spectroscopy is fast developing a reputation as a valid and powerful tool for the detection and diagnosis of cancer using a variety of sample formats. The technology will produce data and tools that are designed to complement routine clinical practice; enhancing the ability of the clinician to make a reliable and non-subjective decision and enabling decreased levels of mortality and morbidity and gains in patient quality of life.

Recurrence prediction in oral cancers: a serum Raman spectroscopy study

High mortality rates associated with oral cancers can be primarily attributed to the failure of current histological procedures in predicting recurrence. Identifying recurrence related factors can lead to improved prognosis, optimized treatment and enhanced overall outcomes. Serum Raman spectroscopy has previously shown potential in the diagnosis of cancers, such as head and neck, cervix, breast, oral cancers, and also in predicting treatment response. In the present study, serum was collected from 22 oral cancer subjects [with recurrence (n = 10) and no-recurrence (n = 12)] before and after surgery and spectra were acquired using a Raman microprobe coupled with a 40× objective. Spectral acquisition parameters were as follows: λex = 785 nm, laser power = 30 mW, integration time: 12 s and averages: 3. Data was analyzed in a patient-wise approach using unsupervised PCA and supervised PC-LDA, followed by LOOCV. PCA and PC-LDA findings suggest that recurrent and non-recurrent cases cannot be classified in before surgery serum samples; an average classification efficiency of ∼78% was obtained in after-surgery samples. Mean and difference spectra and PCA loadings indicate that DNA and protein markers may be potential spectral markers for recurrence. RS of post surgery serum samples may have the potential to predict the probability of recurrence in clinics, after prospective large-scale validation.

Method for identification of spectral targets in discrete frequency infrared spectroscopy for clinical diagnostics

Spectroscopic imaging with discrete frequency infrared (DF-IR) has the potential to have a major impact on the clinical utility of IR imaging techniques for biochemical detection of disease. This can be achieved in real time using imaging at selected wavenumbers tuned to molecular absorptions of interest enabling tissue and disease-specific contrast to be obtained from the sample. However, selecting the appropriate wavenumbers to measure for DF-IR is critical, since vital diagnostic information could be missed. Here we demonstrate the application of partial least squares discriminant analysis (PLS-DA) and variable importance for projection (VIP) to identify key diagnostic wavenumber targets for the detection of dysplasia in human colon polyp sections. A small dataset, including 41 regions of interest (25 benign, 16 dysplastic; 5175 spectra in total), was selected from Fourier transform infrared (FT-IR) images of human colon polyp sections. PLS-DA was used to differentiate between benign and cancerous human colon polyp sections (sensitivity 95%, specificity 93% cross-validated), and VIP scores were calculated for all wavenumbers. A second PLS-DA model was then calculated using only variables that VIP identified as significant, reducing the number of wavenumbers to ~25% of the full dataset. The resulting cross-validated sensitivity and specificity (93 and 90%, respectively) indicate that the VIP method selects the key diagnostic wavenumbers for this dataset. Finally, a robust subset of variables was identified by selecting wavenumbers that exceeded the minimum VIP score in >95% of our validation iterations. A cross-validated PLS-DA model using only the robustly selected wavenumber targets (~20% of the original wavenumbers) resulted in sensitivity and specificity of 91 and 82%, respectively, indicating that PLS-DA and VIP are suitable approaches for the selection of wavenumber targets in DF-IR.

A preliminary Raman spectroscopic study of urine: diagnosis of breast cancer in animal models

Analysis of urine by Raman spectroscopy (RS) as an alternative screening and diagnostic tool for breast cancer..

Multivariate statistical methodologies applied in biomedical Raman spectroscopy: assessing the validity of partial least squares regression using simulated model datasets

In the drive towards biomedical applications of Raman spectroscopy, it is critically important to validate the data analysis tools.

Serum based diagnosis of asthma using Raman spectroscopy: an early phase pilot study

The currently prescribed tests for asthma diagnosis require compulsory patient compliance, and are usually not sensitive to mild asthma. Development of an objective test using minimally invasive samples for diagnosing and monitoring of the response of asthma may help better management of the disease. Raman spectroscopy (RS) has previously shown potential in several biomedical applications, including pharmacology and forensics. In this study, we have explored the feasibility of detecting asthma and determining treatment response in asthma patients, through RS of serum. Serum samples from 44 asthma subjects of different grades (mild, moderate, treated severe and untreated severe) and from 15 reference subjects were subjected to Raman spectroscopic analysis and YKL-40 measurements. The force expiratory volume in 1 second (FEV1) values were used as gold standard and the serum YKL-40 levels were used as an additional parameter for diagnosing the different grades of asthma. For spectral acquisition, serum was placed on a calcium fluoride (CaF2) window and spectra were recorded using Raman microprobe. Mean and difference spectra comparisons indicated significant differences between asthma and reference spectra. Differences like changes in protein structure, increase in DNA specific bands and increased glycosaminoglycans-like features were more prominent with increase in asthma severity. Multivariate tools using Principal-component-analysis (PCA) and Principal-component based-linear-discriminant analysis (PC-LDA) followed by Leave-one-out-cross-validation (LOOCV), were employed for data analyses. PCA and PC-LDA results indicate separation of all asthma groups from the reference group, with minor overlap (19.4%) between reference and mild groups. No overlap was observed between the treated severe and untreated severe groups, indicating that patient response to treatment could be determined. Overall promising results were obtained, and a large scale validation study on random subjects is warranted before the routine clinical usage of this technique.

Substrate contributions in micro-ATR of thin samples: implications for analysis of cells, tissue and biological fluids

Low-e microscope slides are a common substrate for biological samples. Typically they are used for transflection infrared microspectroscopy but increasingly they are also being used for micro-ATR experiments since it is assumed that the FTIR-ATR absorbance spectra of cells and tissue on low-e substrates will not contain any spectral contributions from the substrate materials. This, in part, is due to the expectation that all the infrared light will be reflected at the highly reflective surface. At low sample thicknesses, however (e.g. less than 2 μm) the electric field does indeed penetrate through the substrate layers and undergoes absorption, from the glass supporting layer making up the majority of the slide. In this paper we show experimental evidence of the substrate contributions in ATR spectra and also a theoretical model giving insight into the spectral contributions of the substrate as a function of sample thickness.

In vivo Raman spectroscopy of oral buccal mucosa: a study on malignancy associated changes (MAC)/cancer field effects (CFE)

Occurrence of metachronous and synchronous secondary tumors in oral cavities has been associated with poor prognosis and decreased 5-year disease-free survival rates. The origin of secondary tumors in the oral cavity has been primarily attributed to cancer field effects (CFE) or malignancy-associated changes (MAC) in uninvolved areas. Classification of normal, cancerous and pre-cancerous oral lesions by in vivo Raman spectroscopy (RS) has already been demonstrated. In the present study, MAC/CFE in oral buccal mucosa were explored. In vivo Raman spectra from 84 subjects (722 spectra) under five categories - cancer and contralateral normal (opposite side of tumor), healthy controls (no tobacco habit, no cancer), habitués healthy controls (tobacco habit, no cancer) and non-habitués contralateral normal (no tobacco habit with cancer) were acquired. Mean and difference spectra suggest that loss of lipids and additional features representing proteins and DNA are characteristics of all pathological conditions, with respect to healthy controls. Spectral data were analyzed by PC-LDA followed by leave-one-out cross-validation. Results suggest that Raman characteristics of mucosa of healthy controls are exclusive, while those of habitués healthy controls are similar to those of contralateral normal mucosa. It was observed that the cluster of non-habitués contralateral normal mucosa is different from habitués healthy controls, suggesting that malignancy associated changes can be identified and also indicating that transformation of uninvolved oral mucosa due to tobacco habit or malignancy is different. The findings of the study demonstrate the potential of RS in identifying early transformation changes in oral mucosa and the efficacy of this approach in oral cancer applications.

Raman Spectroscopy of Oral Buccal Mucosa: A Study on Age-Related Physiological Changes and Tobacco-Related Pathological Changes

Biophysical techniques play an important role in detecting physiological alterations during pathogenesis. Raman spectroscopy has shown immense potential in identifying several diseased conditions, including oral cancers. Classification of normal, inflammatory, premalignant and malignant conditions has been demonstrated using ex vivo Raman spectroscopy. Feasibility of recording in vivo spectra in clinically implementable time has also been shown. Translation of this technology to clinics requires extensive validation of methodologies, building of robust models and testing the same under stringent conditions as well as on diverse populations. In this context, the ability of Raman spectroscopy in identifying subtle changes in oral mucosa with increasing age, and the influence of these aging related changes on classification with tobacco-related pathological changes was evaluated. A total of 451 spectra from 62 subjects were recorded from buccal mucosa of healthy subjects of 4 different age groups (aged 20–60 years). Also, 478 spectra from 85 subjects belonging to 4 different categories, tobacco exposed mucosa, contralateral normal (opposite side of tumor), premalignant patches and tumors on buccal mucosa were recorded using fiber optic probe-coupled commercial Raman spectrometer. Differences in spectra were explored by unsupervised Principal Component Analysis (PCA) and supervised Linear Discriminant Analysis (LDA), followed by Leave one out cross validation. Results indicate feasibility of classifying early and late age groups. Also, clear classification is observed between healthy and pathological groups, thus inherent heterogeneity in healthy groups seems to have no bearing on classification of normal with abnormal conditions. Findings of the study indicate high sensitivity of Raman spectroscopy in detecting subtle mucosal changes, further supporting efficacy of Raman spectroscopic approaches in oral cancer applications. Prospectively, more vigorous validation studies of Raman methodology would enable routine clinical applications.

The effect of optical substrates on micro-FTIR analysis of single mammalian cells

The study of individual cells with infrared (IR) microspectroscopy often requires living cells to be cultured directly onto a suitable substrate. The surface effect of the specific substrates on the cell growth—viability and associated biochemistry—as well as on the IR analysis—spectral interference and optical artifacts—is all too often ignored. Using the IR beamline, MIRIAM (Diamond Light Source, UK), we show the importance of the substrate used for IR absorption spectroscopy by analyzing two different cell lines cultured on a range of seven optical substrates in both transmission and reflection modes. First, cell viability measurements are made to determine the preferable substrates for normal cell growth. Successively, synchrotron radiation IR microspectroscopy is performed on the two cell lines to determine any genuine biochemically induced changes or optical effect in the spectra due to the different substrates. Multivariate analysis of spectral data is applied on each cell line to visualize the spectral changes. The results confirm the advantage of transmission measurements over reflection due to the absence of a strong optical standing wave artifact which amplifies the absorbance spectrum in the high wavenumber regions with respect to low wavenumbers in the mid-IR range. The transmission spectra reveal interference from a more subtle but significant optical artifact related to the reflection losses of the different substrate materials. This means that, for comparative studies of cell biochemistry by IR microspectroscopy, it is crucial that all samples are measured on the same substrate type.

Figure

Cell separation by PCA due to the refractive index of the substrate used, revealing transmission artifact.

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Application of 1H NMR in the flow surveillance of oil wells

Test-separator units, as traditional methods of well surveillance, mainly suffer from their inherent constraints including the expensive instrumental, mechanical, electrical, piping and safety devices along with technical and protective inspections, repair and operation services, facilities and infrastructures. Other problems are time and cost consuming, uncertainty of well isolation in test separator and need to close the co-line wells, which are diminished using multivariate thermal well testing. A novel approach was proposed and tested to classify the oil samples taken from individual wells by source and type. The novelties of this work were the use of the applied aspects of (1)H NMR spectroscopy in petroleum upstream engineering, the replacement of traditional test methods, the improvement of the confidence of tests and the recognition of multisource streams. The weighed sum method was used to correlate the spectra information, taken from the samples of Iranian offshore oil wells. The experimental results and the field data revealed that the present approach was appropriate for precocious, quick and reliable surveillance of individual oil wells located in an oil field. The model was supported by field experiments and has predicted the accurate productivity of oil wells with respect to the current expensive techniques since 2010.

Synchrotron Radiation Spectroscopic Techniques as Tools for the Medicinal Chemist: Microprobe X-Ray Fluorescence Imaging, X-Ray Absorption Spectroscopy, and Infrared Microspectroscopy

This review updates the recent advances and applications of three prominent synchrotron radiation techniques, microprobe X-ray fluorescence spectroscopy/imaging, X-ray absorption spectroscopy, and infrared microspectroscopy, and highlights how these tools are useful to the medicinal chemist. A brief description of the principles of the techniques is given with emphasis on the advantages of using synchrotron radiation-based instrumentation rather than instruments using typical laboratory radiation sources. This review focuses on several recent applications of these techniques to solve inorganic medicinal chemistry problems, focusing on studies of cellular uptake, distribution, and biotransformation of established and potential therapeutic agents. The importance of using these synchrotron-based techniques to assist the development of, or validate the chemistry behind, drug design is discussed.

Spectral signatures of colonic malignancies in the mid-infrared region: from basic research to clinical applicability

The process of carcinogenesis in the colon progresses through several overlapping stages, making the evaluation process challenging, as well as subjective. Owing to the complexity of colonic tissues and the search for a technique that is rapid and foolproof for precise grading and evaluation of biopsies, many spectroscopic techniques have been evaluated in the past few decades for their efficiency and clinical compatibility. Fourier-transform infrared spectroscopy, being quantitative and objective, has the capacity for automation and relevance to cancer diagnosis. This article highlights investigations on the application of Fourier-transform infrared spectroscopy (particularly microscopy) in colon cancer diagnosis and parallel developments in data analysis techniques for the characterization of spectral signatures of malignant tissues in the colon.

Detection of cervical metastatic lymph nodes in papillary thyroid carcinoma by Fourier transform infrared spectroscopy

Background

A previous study demonstrated that Fourier transform infrared (FTIR) spectroscopy can distinguish thyroid cancer from benign thyroid lesions. The aim of this study was to explore the use of FTIR for identifying metastatic lymph nodes of papillary thyroid cancer in vitro, and distinguishing between metastatic and non-metastatic tissue.

Methods

Some 184 freshly removed cervical lymph nodes were obtained from 22 patients with papillary thyroid cancer undergoing thyroid surgery with lymph node dissection. Samples were measured by FTIR spectroscopy before being processed for histopathological diagnosis. The FTIR spectrum of each sample identified 13 bands from 1000 to 4000 cm−1. The peak position, intensity and full width at half maximum of each absorbent band were measured, and the relative intensity ratios were calculated. The FTIR spectra of metastatic lymph nodes were compared with those of non-metastatic nodes, and a linear discriminant analysis was performed based on these data.

Results

Histopathological examination confirmed 61 metastatic and 123 non-metastatic lymph nodes. The FTIR parameters of metastatic and non-metastatic lymph nodes differed owing to the content or configuration alterations of nucleic acids, proteins, lipids and carbohydrates. The sensitivity for FTIR in diagnosing metastatic lymph nodes was 80·3 per cent, the specificity was 91·9 per cent and the accuracy was 88·0 per cent.

Conclusion

FTIR spectroscopy is a novel technique for detection of metastatic lymph nodes and may prove useful in surgery for papillary thyroid cancer.