Early detection of cervical neoplasia by Raman spectroscopy

FABP4 Enhances Lipidic and Fibrotic Cardiac Structural and Ca2+ Dynamic Changes

BACKGROUND

Adipocyte FABP4 (fatty acid-binding protein 4) is augmented in the epicardial stroma of patients with long-standing persistent atrial fibrillation. Because this molecule is released mainly by adipocytes, our objective was to study its role in atrial cardiomyopathy, focusing our attention on fibrosis, metabolism, and electrophysiological changes. These results might clarify the role of adiposity as a mediator of atrial cardiomyopathy.

METHODS

We used several preclinical cellular models, epicardial and subcutaneous stroma primary cell cultures from patients undergoing open heart surgery, human atrial fibroblasts, atrial cardiomyocytes derived from human induced pluripotent stem cells and isolated from adult mice, and Nav1.5 transfected Chinese hamster ovary cells. Fibrosis, glucose, mitochondrial and adipogenesis activity, gene expression, and proteomics were determined by wound healing, enzymatic, colorimetric, fluorescence assays, real-time quantitative polymerase chain reaction, and TripleTOF proteomics. Molecular changes were analyzed by Raman confocal microspectroscopy, calcium dynamics by confocal microscopy, and ion currents by patch clamp. Epicardial, subcutaneous, and atrial fibroblasts and cardiomyocytes were incubated with FABP4 at 100 ng/mL.

RESULTS

Our results showed that FABP4 induced fibrosis, glucose metabolism, and lipid accumulation on epicardial and subcutaneous stroma cells and atrial fibroblasts. Besides, it modified lipid content and calcium dynamics in atrial cardiomyocytes without effects on INa.

CONCLUSIONS

FABP4 exerts fibrotic and metabolic changes on epicardial stroma and modifies lipid content and calcium dynamic on atrial cardiomyocytes. These results suggest its possible role as an atrial cardiomyopathy mediator.

Plasmonic Metasurfaces for Specific SERS Detection of Shiga Toxins

The interest in the development of nanoscale plasmonic technologies has dramatically increased in recent years. The photonic properties of plasmonic nanopatterns can be controlled and tuned via their size, shape, or the arrangement of their constituents. In this work, we propose a 2D hybrid metallic polymeric nanostructure based on the octupolar framework with enhanced sensing property. We analyze its plasmonic features both numerically and experimentally, demonstrating the higher values of their relevant figures of merit: we estimated a surface-enhanced Raman spectroscopy (SERS) enhancement factor of 9 × 107 and a SPR bulk sensitivity of 430 nm/RIU. In addition, our nanostructure exhibits a dual resonance in the visible and near-infrared region, enabling our system toward multispectral plasmonic analysis. Finally, we illustrate our design engineering strategy as enabled by electron beam lithography by the outstanding performance of a SERS-based biosensor that targets the Shiga toxin 2a, a clinically relevant bacterial toxin. To the best of our knowledge, this is the first time that a SERS fingerprint of this toxin has been evidenced.

Deep learning classification of cervical dysplasia using depth-resolved angular light scattering profiles

We present a machine learning method for detecting and staging cervical dysplastic tissue using light scattering data based on a convolutional neural network (CNN) architecture. Depth-resolved angular scattering measurements from two clinical trials were used to generate independent training and validation sets as input of our model. We report 90.3% sensitivity, 85.7% specificity, and 87.5% accuracy in classifying cervical dysplasia, showing the uniformity of classification of a/LCI scans across different instruments. Further, our deep learning approach significantly improved processing speeds over the traditional Mie theory inverse light scattering analysis (ILSA) method, with a hundredfold reduction in processing time, offering a promising approach for a/LCI in the clinic for assessing cervical dysplasia.

Convolution Network with Custom Loss Function for the Denoising of Low SNR Raman Spectra

Raman spectroscopy is a powerful diagnostic tool in biomedical science, whereby different disease groups can be classified based on subtle differences in the cell or tissue spectra. A key component in the classification of Raman spectra is the application of multi-variate statistical models. However, Raman scattering is a weak process, resulting in a trade-off between acquisition times and signal-to-noise ratios, which has limited its more widespread adoption as a clinical tool. Typically denoising is applied to the Raman spectrum from a biological sample to improve the signal-to-noise ratio before application of statistical modeling. A popular method for performing this is Savitsky-Golay filtering. Such an algorithm is difficult to tailor so that it can strike a balance between denoising and excessive smoothing of spectral peaks, the characteristics of which are critically important for classification purposes. In this paper, we demonstrate how Convolutional Neural Networks may be enhanced with a non-standard loss function in order to improve the overall signal-to-noise ratio of spectra while limiting corruption of the spectral peaks. Simulated Raman spectra and experimental data are used to train and evaluate the performance of the algorithm in terms of the signal to noise ratio and peak fidelity. The proposed method is demonstrated to effectively smooth noise while preserving spectral features in low intensity spectra which is advantageous when compared with Savitzky-Golay filtering. For low intensity spectra the proposed algorithm was shown to improve the signal to noise ratios by up to 100% in terms of both local and overall signal to noise ratios, indicating that this method would be most suitable for low light or high throughput applications.

Raman Spectroscopy of Liquid-Based Cervical Smear Samples as a Triage to Stratify Women Who Are HPV-Positive on Screening

Simple Summary

Persistent high-risk human papillomavirus (HPV) infection can lead to cervical precancer and cancer. Recently, HPV testing has been introduced for primary cervical screening, but the HPV DNA test cannot distinguish between transient and persistent HPV infection. Thus, there is an unmet clinical need to develop a new test to identify women with a high-risk persistent HPV infection. Raman spectra were recorded from cervical smear samples (n = 60) and, on the basis of HPV DNA and HPV mRNA test results, a classifier was developed to identify persistent HPV infection. A further blinded independent test set (n = 14) was used to validate the model, and sensitivity of 90% and specificity of 100% were achieved. Improved triage would allow women with a high-risk persistent HPV infection to be referred for immediate treatment, while women with a low-risk transient infection could avoid overtreatment.

Abstract

The role of persistent high-risk human papillomavirus (HPV) infection in the development of cervical precancer and cancer is now well accepted, and HPV testing has recently been introduced for primary cervical screening. However, the low specificity of HPV DNA testing can result in large numbers of women with an HPV-positive result, and additional triage approaches are needed to avoid over-referral to colposcopy and overtreatment. The aim of this study was to assess Raman spectroscopy as a potential triage test to discriminate between transient and persistent HPV infection. HPV DNA status and mRNA status were confirmed in ThinPrep^® cervical samples (n = 60) using the Cobas 4800 and APTIMA HPV test, respectively. Raman spectra were recorded from single-cell nuclei and subjected to partial least squares discriminant analysis (PLSDA). In addition, the PLSDA classification model was validated using a blinded independent test set (n = 14). Sensitivity of 85% and specificity of 92% were achieved for the classification of transient and persistent HPV infection, and this increased to 90% sensitivity and 100% specificity when mean sample spectra were used instead of individual cellular spectra. This study showed that Raman spectroscopy has potential as a triage test for HPV-positive women to identify persistent HPV infection.

Raman spectroscopic study of cervical precancerous lesions and cervical cancer

Early detection of cervical lesions, accurate diagnosis of cervical lesions, and timely and effective therapy can effectively avoid the occurrence of cervical cancer or improve the survival rate of patients. In this paper, the spectra of tissue sections of cervical inflammation (n = 60), CIN (cervical intraepithelial neoplasia) I (n = 30), CIN II (n = 30), CIN III (n = 30), cervical squamous cell carcinoma (n = 30), and cervical adenocarcinoma (n = 30) were collected by a confocal Raman micro-spectrometer (LabRAM HR Evolution, Horiba France SAS, Villeneuve d’Ascq, France). The Raman spectra of six kinds of cervical tissues were analyzed, the dominant Raman peaks of different kinds of tissues were summarized, and the differences in chemical composition between the six tissue samples were compared. An independent sample t test (p ≤ 0.05) was used to analyze the difference of average relative intensity of Raman spectra of six types of cervical tissues. The difference of relative intensity of Raman spectra of six kinds of tissues can reflect the difference of biochemical components in six kinds of tissues and the characteristic of biochemical components in different kinds of tissues. The classification models of cervical inflammation, CIN I, CIN II, CIN III, cervical squamous cell carcinoma, and cervical adenocarcinoma were established by using a support vector machine (SVM) algorithm. Six types of cervical tissues were classified and identified with an overall diagnostic accuracy of 85.7%. This study laid a foundation for the application of Raman spectroscopy in the clinical diagnosis of cervical precancerous lesions and cervical cancer.

Inhibition of Human Cervical Cancer Hela Cell Line by Meat-Derived Lactic Acid Bacteria of Lactobacillus plantarum IIA-1A5 and Lactobacillus acidophilus IIA-2B4

<b>Background and Objective:</b> Two Indonesian lactic acid bacteria of<i> L. plantarum </i>I IA-1A5 and <i>L. acidophilus </i>IIA-2B4 were previously isolated from beef with some functional probiotic properties. Nevertheless, the possibility of these strains to have anticancer activity remains unknown. Current study aimed to evaluate the inhibitory properties of intra-and extracellular protein extracts of these two strains against cervical cancer HeLa cells. <b>Materials and Methods:</b> The intracellular and extracellular proteins extract from <i>L. plantarum </i>IIA-1A5 and <i>L. acidophilus </i>IIA-2B4 were collected and designated as IP-LP, IP-LA, EP-LP and EP-LA, respectively. The effect of these extracts on the viability and morphology of HeLa cells were observed using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay and confocal microscopy, respectively. <b>Results:</b> Both IP-LP and IP-LA inhibited HeLa cells in a concentration-dependent manner, with IC<sub>50</sub> values of 352.62 and 120.97 μg mL<sup>1</sup>, respectively. Meanwhile, the inhibition activity was also observed for EP-LP and EP-LA, <i>albeit</i> very low. The inhibition effect was also confirmed by morphological analysis under confocal electron microscopy which showed the changes in the cell shapes and numbers. <b>Conclusion:</b> Altogether, for the first time this study proposed that the probiotic isolated from Indonesian beef are promising to inhibit cancer cell lines.

Temporal In Vitro Raman Spectroscopy for Monitoring Replication Kinetics of Epstein-Barr Virus Infection in Glial Cells

Raman spectroscopy can be used as a tool to study virus entry and pathogen-driven manipulation of the host efficiently. To date, Epstein-Barr virus (EBV) entry and altered biochemistry of the glial cell upon infection are elusive. In this study, we detected biomolecular changes in human glial cells, namely, HMC-3 (microglia) and U-87 MG (astrocytes), at two variable cellular locations (nucleus and periphery) by Raman spectroscopy post-EBV infection at different time points. Two possible phenomena, one attributed to the response of the cell to viral attachment and invasion and the other involved in duplication of the virus followed by egress from the host cell, are investigated. These changes corresponded to unique Raman spectra associated with specific biomolecules in the infected and the uninfected cells. The Raman signals from the nucleus and periphery of the cell also varied, indicating differential biochemistry and signaling processes involved in infection progression at these locations. Molecules such as cholesterol, glucose, hyaluronan, phenylalanine, phosphoinositide, etc. are associated with the alterations in the cellular biochemical homeostasis. These molecules are mainly responsible for cellular processes such as lipid transport, cell proliferation, differentiation, and apoptosis in the cells. Raman signatures of these molecules at distinct time points of infection indicated their periodic involvement, depending on the stage of virus infection. Therefore, it is possible to discern the details of variability in EBV infection progression in glial cells at the biomolecular level using time-dependent in vitro Raman scattering.

Diagnostic spectro-cytology revealing differential recognition of cervical cancer lesions by label-free surface enhanced Raman fingerprints and chemometrics

Herein we have stepped-up on a strategic spectroscopic modality by utilizing label free ultrasensitive surface enhanced Raman scattering (SERS) technique to generate a differential spectral fingerprint for the prediction of normal (NRML), high-grade intraepithelial lesion (HSIL) and cervical squamous cell carcinoma (CSCC) from exfoliated cell samples of cervix. Three different approaches i.e. single-cell, cell-pellet and extracted DNA from oncology clinic as confirmed by Pap test and HPV PCR were employed. Gold nanoparticles as the SERS substrate favored the increment of Raman intensity exhibited signature identity for Amide III/Nucleobases and carotenoid/glycogen respectively for establishing the empirical discrimination. Moreover, all the spectral invention was subjected to chemometrics including Support Vector Machine (SVM) which furnished an average diagnostic accuracy of 94%, 74% and 92% of the three grades. Combined SERS read-out and machine learning technique in field trial promises its potential to reduce the incidence in low resource countries.

Optical Imaging Approaches to Investigating Radiation Resistance

Radiation therapy is frequently the first line of treatment for over 50% of cancer patients. While great advances have been made in improving treatment response rates and reducing damage to normal tissue, radiation resistance remains a persistent clinical problem. While hypoxia or a lack of tumor oxygenation has long been considered a key factor in causing treatment failure, recent evidence points to metabolic reprogramming under well-oxygenated conditions as a potential route to promoting radiation resistance. In this review, we present recent studies from our lab and others that use high-resolution optical imaging as well as clinical translational optical spectroscopy to shine light on the biological basis of radiation resistance. Two-photon microscopy of endogenous cellular metabolism has identified key changes in both mitochondrial structure and function that are specific to radiation-resistant cells and help promote cell survival in response to radiation. Optical spectroscopic approaches, such as diffuse reflectance and Raman spectroscopy have demonstrated functional and molecular differences between radiation-resistant and sensitive tumors in response to radiation. These studies have uncovered key changes in metabolic pathways and present a viable route to clinical translation of optical technologies to determine radiation resistance at a very early stage in the clinic.

Principal components analysis of Raman spectral data for screening of Hepatitis C infection

In the current study, Raman spectroscopy is employed for the identification of the biochemical changes taking place during the development of Hepatitis C. The Raman spectral data acquired from the human blood plasma samples of infected and healthy individuals is analysed by Principal Components Analysis and the Raman spectral markers of the Hepatitis C Virus (HCV) infection are identified. Spectral changes include those associated with nucleic acidsat720 cm^-1, 1077 cm^-1 1678 (CO stretching mode of dGTP of RNA), 1778 cm^-1 (RNA), with proteins at 1641 cm^-1(amide-I), 1721 cm^-1(CC stretching of proteins) and lipids at 1738 cm^-1(CO of ester group in lipids). These differences in Raman spectral features of blood plasma samples of the patients and healthy volunteers can be associated with the development of the biochemical changes during HCV infection.

An Algorithm for the Removal of Cosmic Ray Artifacts in Spectral Data Sets

Cosmic ray artifacts may be present in all photo-electric readout systems. In spectroscopy, they present as random unidirectional sharp spikes that distort spectra and may have an affect on post-processing, possibly affecting the results of multivariate statistical classification. A number of methods have previously been proposed to remove cosmic ray artifacts from spectra but the goal of removing the artifacts while making no other change to the underlying spectrum is challenging. One of the most successful and commonly applied methods for the removal of comic ray artifacts involves the capture of two sequential spectra that are compared in order to identify spikes. The disadvantage of this approach is that at least two recordings are necessary, which may be problematic for dynamically changing spectra, and which can reduce the signal-to-noise (S/N) ratio when compared with a single recording of equivalent duration due to the inclusion of two instances of read noise. In this paper, a cosmic ray artefact removal algorithm is proposed that works in a similar way to the double acquisition method but requires only a single capture, so long as a data set of similar spectra is available. The method employs normalized covariance in order to identify a similar spectrum in the data set, from which a direct comparison reveals the presence of cosmic ray artifacts, which are then replaced with the corresponding values from the matching spectrum. The advantage of the proposed method over the double acquisition method is investigated in the context of the S/N ratio and is applied to various data sets of Raman spectra recorded from biological cells.

Diagnosis of cervical squamous cell carcinoma and cervical adenocarcinoma based on Raman spectroscopy and support vector machine

In this report, we collected the Raman spectrum of cervical adenocarcinoma and cervical squamous cell carcinoma tissues by a micro-Raman spectroscopy system. We analysed, compared and summarized the characteristics and differences of the normalized mean Raman spectra of the two tissues and pointed out the major differences in the biochemical composition between the two tissues. The PCA-SVM model that was used to distinguish the two types of cervical cancer tissues was established. The accuracy of the model in differentiating cervical adenocarcinoma from cervical squamous cell carcinoma was 93.125%. The results of this study indicate that Raman spectroscopy of cervical adenocarcinoma and cervical squamous cell carcinoma tissue in combination with SVM (support vector analysis) and PCA (principal component analysis) can be useful for the classification of cervical adenocarcinoma and cervical squamous cell carcinoma tissues and for the exploration of the differences in biochemical compositions between the two types of cervical tissue. This study lays a foundation to further study Raman spectroscopy as a clinical diagnostic method for cervical cancer.

Raman-Enhanced Spectroscopy Distinguishes Anal Squamous Intraepithelial Lesions in Human Immunodeficiency Virus-Serodiscordant Couples

HIV-positive individuals are at increased risk for precancerous anal squamous intraepithelial lesions (SILs). Anal cytology and digital rectal examination are performed as screening tools, but extensive training and appropriate instruments are required to follow up on an abnormal anal cytology. Thus, novel approaches to SIL evaluation could improve better health care follow-up by efficient and timely diagnosis to offer treatment options. Recently, Raman-enhanced spectroscopy (RESpect) has emerged as a potential new tool for early identification of SIL. RESpect is a noninvasive, label-free, laser-based technique that identifies molecular composition of tissues and cells. HIV-serodiscordant couples had anal biopsies obtained during high-resolution anoscopy. RESpect was performed on the specimens. Principal component analysis of the data identified differences between normal and abnormal tissue as well as HIV-positive and HIV-negative individuals of each couple even with similar pathologies. RESpect has the potential to change the paradigm of anal pathology diagnosis and could provide insight into different pathways leading to SIL in HIV-serodiscordant couples.

Raman spectroscopy insight into Norovirus encapsulation in Bombyx mori cypovirus cubic microcrystals

Protein and amino acid structures of Norovirus-like particles (NoVLP) have been investigated by Raman spectroscopy before and after encapsulation into Bombyx mori cypovirus (BmCPV) cubic microcrystals, which are usually referred to as cubes or polyhedra. Two different types of tag were used in co-expression, namely VP3 and H1 tags. VP3 tag is derived from a capsid protein VP4 from BmCPV and H1 tag is N-terminal α-helix of BmCPV polyhedrin, respectively. A major capsid protein VP1 of NoVLP G11.4 was fused with H1 or VP3 tags, and then encapsulated into BmCPV polyhedra. Analyses of the spectroscopic data permitted the assignment of conformation-sensitive Raman bands to viral amino acid constituents and the observation of structural similarities or differences between differently tagged samples. Three separate Raman zones were attentioned, namely, the ring-mode structure region (1000-1500 cm^-1), the CO and CC double-bond region and its surroundings (1500-1750 cm^-1), and the high-frequency CH stretching region (2800-3100 cm^-1). Structural fingerprints could be found in specific spectral zones for differently co-expressed samples. One clear characteristic of the H1-tagged VP1 polyhedra was the increase in tyrosine fraction, which played a critical role in binding neighboring strands through its unpaired negatively charged COO^- sites. This feature could consistently be detected in different regions, but it was best represented by Raman signals associated with negatively charged COO^- sites and H1 helices in the double-bond region. Such peculiar chemical features were revealed by two relatively broad bands at 1570 and 1630 cm^-1, which were assigned to COO^- anti-symmetric stretching and amide I in 3₁₀-helix extensions to α-helices at N-termini, respectively. These specific features did not display in the spectrum of the VP3-tagged VP1 polyhedra. Concurrently, a strong reduction of CH bond Raman signal was noticed in the high frequency stretching region of the Raman spectrum upon H1-tagged VP1 polyhedra. The Raman activity most strikingly also represented fingerprints of tagged NoVLP VP1 after its encapsulation into BmCPV polyhedra, opening thus the possibility to in situ advanced experiments in the fields of drug delivery and regenerative medicine.

Resistance and Raman spectroscopy analysis of Parageobacillus thermantarcticus spores after γ-ray exposure

Spores of the genus Bacillus are able to resist ionizing radiations and therefore they are a suitable biological model for studies in Astrobiology, i.e. the multidisciplinary approach to the study of the origin and evolution of life on Earth and in the universe. The resistance to γ-radiation is an important issue in Astrobiology in relation to the search for bacterial species that could adapt to life in space. This study investigates the resistance of spores of the thermophilic bacteria Parageobacillus thermantarcticus to γ-rays. The analysis of spores' response to irradiation at a molecular level is performed by means of Raman spectroscopy that allows to get insights in the sequence of events taking place during inactivation. The role of the γ-rays' dose in the inactivation of spores is also investigated, allowing to highlight the mechanism(s) of inactivation including DNA damage, protein denaturation and calcium dipicolinate levels.

Raman Microspectroscopic Evidence for the Metabolism of a Tyrosine Kinase Inhibitor, Neratinib, in Cancer Cells

Tyrosine kinase receptors are one of the main targets in cancer therapy. They play an essential role in the modulation of growth factor signaling and thereby inducing cell proliferation and growth. Tyrosine kinase inhibitors such as neratinib bind to EGFR and HER2 receptors and exhibit antitumor activity. However, little is known about their detailed cellular uptake and metabolism. Here, we report for the first time the intracellular spatial distribution and metabolism of neratinib in different cancer cells using label-free Raman imaging. Two new neratinib metabolites were detected and fluorescence imaging of the same cells indicate that neratinib accumulates in lysosomes. The results also suggest that both EGFR and HER2 follow the classical endosome lysosomal pathway for degradation. A combination of Raman microscopy, DFT calculations, and LC-MS was used to identify the chemical structure of neratinib metabolites. These results show the potential of Raman microscopy to study drug pharmacokinetics.

Towards automated cancer screening: Label-free classification of fixed cell samples using wavelength modulated Raman spectroscopy

The ability to provide quantitative, objective and automated pathological analysis would provide enormous benefits for national cancer screening programmes, in terms of both resource reduction and improved patient wellbeing. The move towards molecular pathology through spectroscopic methods shows great promise, but has been restricted by spectral quality, acquisition times and lack of direct clinical application. In this paper, we present the application of wavelength modulated Raman spectroscopy for the automated label- and fluorescence-free classification of fixed squamous epithelial cells in suspension, such as those produced during a cervical smear test. Direct comparison with standard Raman spectroscopy shows marked improvement of sensitivity and specificity when considering both human papillomavirus (sensitivity +12.0%, specificity +5.3%) and transformation status (sensitivity +10.3%, specificity +11.1%). Studies on the impact of intracellular sampling location and storage effects suggest that wavelength modulated Raman spectroscopy is sufficiently robust to be used in fixed cell classification, but requires further investigations of potential sources of molecular variation in order to improve current clinical tools.

Diagnostic Bacteriology: Raman Spectroscopy

Current clinical methodology for identification of bacterial infections relies predominantly on culturing microbes from patient material and performing biochemical tests. This can often be an inefficient and lengthy process, which has a significant detrimental effect upon patient care. Techniques used in other aspects of molecular research have the potential to revolutionize the way in which diagnostic tests are used and delivered in the clinical setting. The need for rapid, accurate, and cost-effective molecular techniques in the diagnostic laboratory is imperative to improving patient care, preventing the spread of drug resistance and decreasing the overall burden associated with nosocomial infections. Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) are powerful vibrational spectroscopy techniques that are being developed for highly sensitive pathogen identification in complex clinical samples. Raman spectroscopy is a molecular technique that is capable of probing samples noninvasively and nondestructively. It has been used with high specificity to assess tissue and bacterial samples at the molecular level with diverse clinical and diagnostic applications. SERS has recently developed out of the advances in the Raman spectroscopy arena. This technique is designed to amplify Raman scattering and allows for better differentiation of bacterial isolates. Although the current parameters for the use of SERS require a pure culture and are relatively monoparametric, current breakthroughs and testing are pushing the technology to new levels and thus changing the face of modern bacterial diagnostics.

Raman spectroscopy for accurately characterizing biomolecular changes in androgen-independent prostate cancer cells

Metastatic prostate cancer resistant to hormonal manipulation is considered the advanced stage of the disease and leads to most cancer-related mortality. With new research focusing on modulating cancer growth, it is essential to understand the biochemical changes in cells that can then be exploited for drug discovery and for improving responsiveness to treatment. Raman spectroscopy has a high chemical specificity and can be used to detect and quantify molecular changes at the cellular level. Collection of large data sets generated from biological samples can be employed to form discriminatory algorithms for detection of subtle and early changes in cancer cells. The present study describes Raman finger printing of normal and metastatic hormone-resistant prostate cancer cells including analyses with principal component analysis and linear discrimination. Amino acid-specific signals were identified, especially loss of arginine band. Androgen-resistant prostate cancer cells presented a higher content of phenylalanine, tyrosine, DNA and Amide III in comparison to PNT2 cells, which possessed greater amounts of L-arginine and had a B conformation of DNA. The analysis utilized in this study could reliably differentiate the 2 cell lines (sensitivity 95%; specificity 88%).

Near-infrared Raman spectroscopy for estimating biochemical changes associated with different pathological conditions of cervix

The molecular level changes associated with oncogenesis precede the morphological changes in cells and tissues. Hence molecular level diagnosis would promote early diagnosis of the disease. Raman spectroscopy is capable of providing specific spectral signature of various biomolecules present in the cells and tissues under various pathological conditions. The aim of this work is to develop a non-linear multi-class statistical methodology for discrimination of normal, neoplastic and malignant cells/tissues. The tissues were classified as normal, pre-malignant and malignant by employing Principal Component Analysis followed by Artificial Neural Network (PC-ANN). The overall accuracy achieved was 99%. Further, to get an insight into the quantitative biochemical composition of the normal, neoplastic and malignant tissues, a linear combination of the major biochemicals by non-negative least squares technique was fit to the measured Raman spectra of the tissues. This technique confirms the changes in the major biomolecules such as lipids, nucleic acids, actin, glycogen and collagen associated with the different pathological conditions. To study the efficacy of this technique in comparison with histopathology, we have utilized Principal Component followed by Linear Discriminant Analysis (PC-LDA) to discriminate the well differentiated, moderately differentiated and poorly differentiated squamous cell carcinoma with an accuracy of 94.0%. And the results demonstrated that Raman spectroscopy has the potential to complement the good old technique of histopathology.

Tuberculosis determination using SERS and chemometric methods

Nanostructures have been multiplying the advantages of Raman spectroscopy and further amplify the advantages of Raman spectroscopy is a continuous effort focused on the appropriate design of nanostructures. Herein, we designed different shapes of plasmonic nanostructures such as Vertical, Zig Zag, Slant nanorods and Spherical nanoparticles employing the DC magnetron sputtering system as SERS-active substrates for ultrasensitive detection of target molecules. The fabricated plasmonic nanostructures sensitivity and uniformity were exploited by reference dye analyte. These nanostructures were utilized in the label free detection of infectious disease, Tuberculosis (TB). For the first time, TB detection from serum samples using SERS has been demonstrated. Various multivariate statistical methods such as principal component analysis, support vector machine, decision tree and random forest were developed and tested their ability to discriminate the healthy and active TB samples. The results demonstrate the performance of the SERS spectra, chemometric methods and potential of the method in clinical diagnosis.

Evaluating oral epithelial dysplasia classification system by near-infrared Raman spectroscopy

Until now, the classification system of oral epithelial dysplasia is still based on the architectural and cytological changes, which relies on the observation of pathologists and is relatively subjective. The purpose of present research was to discriminate the oral dysplasia by the near-infrared Raman spectroscope, in order to evaluate the classification system. We collected Raman spectra of normal mucosa, oral squamous cell carcinoma (OSCC) and dysplasia by near-infrared Raman spectroscope. The biochemical variations between different stages were analyzed by the characteristic peaks in the subtracted mean spectra. Gaussian radial basis function support vector machines (SVM) were used to establish the diagnostic models. At the same time, principal component analysis (PCA) and linear discriminant analysis (LDA) were used to verify the results of SVM. Raman spectral differences were observed in the range between 730~1913 cm-1. Compared with normal mucosa, high contents of protein and DNA in oral dysplasia and OSCC were observed. There were no significant or gradual variation of Raman peaks among different dysplastic grades. The accuracies of comparison between mild, moderate, severe dysplasia with OSCC were 100%, 44.44%, 71.15%, which elucidated the low modeling ability of support vector machines, especially for the moderate dysplasia. The analysis by PCA-LDA could not discriminate the stages, either. Combined with support vector machines, near-infrared Raman spectroscopy could detect the biochemical variations in oral normal, OSCC and dysplastic tissues, but could not establish diagnostic model accurately. The classification system needs further improvements.

Feasibility of clinical detection of cervical dysplasia using angle-resolved low coherence interferometry measurements of depth-resolved nuclear morphology

This study sought to establish the feasibility of using in situ depth-resolved nuclear morphology measurements for detection of cervical dysplasia. Forty enrolled patients received routine cervical colposcopy with angle-resolved low coherence interferometry (a/LCI) measurements of nuclear morphology. a/LCI scans from 63 tissue sites were compared to histopathological analysis of co-registered biopsy specimens which were classified as benign, low-grade squamous intraepithelial lesion (LSIL), or high-grade squamous intraepithelial lesion (HSIL). Results were dichotomized as dysplastic (LSIL/HSIL) versus non-dysplastic and HSIL versus LSIL/benign to determine both accuracy and potential clinical utility of a/LCI nuclear morphology measurements. Analysis of a/LCI data was conducted using both traditional Mie theory based processing and a new hybrid algorithm that provides improved processing speed to ascertain the feasibility of real-time measurements. Analysis of depth-resolved nuclear morphology data revealed a/LCI was able to detect a significant increase in the nuclear diameter at the depth bin containing the basal layer of the epithelium for dysplastic versus non-dysplastic and HSIL versus LSIL/Benign biopsy sites (both p < 0.001). Both processing techniques resulted in high sensitivity and specificity (>0.80) in identifying dysplastic biopsies and HSIL. The hybrid algorithm demonstrated a threefold decrease in processing time at a slight cost in classification accuracy. The results demonstrate the feasibility of using a/LCI as an adjunctive clinical tool for detecting cervical dysplasia and guiding the identification of optimal biopsy sites. The faster speed from the hybrid algorithm offers a promising approach for real-time clinical analysis.

Harnessing speckle for a sub-femtometre resolved broadband wavemeter and laser stabilization

The accurate determination and control of the wavelength of light is fundamental to many fields of science. Speckle patterns resulting from the interference of multiple reflections in disordered media are well-known to scramble the information content of light by complex but linear processes. However, these patterns are, in fact, exceptionally rich in information about the illuminating source. We use a fibre-coupled integrating sphere to generate wavelength-dependent speckle patterns, in combination with algorithms based on the transmission matrix method and principal component analysis, to realize a broadband and sensitive wavemeter. We demonstrate sub-femtometre wavelength resolution at a centre wavelength of 780 nm, and a broad calibrated measurement range from 488 to 1,064 nm. This compares favourably to the performance of conventional wavemeters. Using this speckle wavemeter as part of a feedback loop, we stabilize a 780 nm diode laser to achieve a linewidth better than 1 MHz.

Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy

The ability to identify and characterise individual cells of the immune system under label-free conditions would be a significant advantage in biomedical and clinical studies where untouched and unmodified cells are required. We present a multi-modal system capable of simultaneously acquiring both single point Raman spectra and digital holographic images of single cells. We use this combined approach to identify and discriminate between immune cell populations CD4+ T cells, B cells and monocytes. We investigate several approaches to interpret the phase images including signal intensity histograms and texture analysis. Both modalities are independently able to discriminate between cell subsets and dual-modality may therefore be used a means for validation. We demonstrate here sensitivities achieved in the range of 86.8% to 100%, and specificities in the range of 85.4% to 100%. Additionally each modality provides information not available from the other providing both a molecular and a morphological signature of each cell.

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.

HS-AFM and SERS Analysis of Murine Norovirus Infection: Involvement of the Lipid Rafts

Studies on human norovirus are severely hampered by the absence of a cell culture system until the discovery of murine norovirus (MNV). The cell membrane domains called lipid rafts have been defined as a port of entry for viruses. This study is conducted to investigate murine norovirus binding on the mouse leukemic monocyte macrophage cell line. Lipid raft related structures are extracted from cells by detergent treatment resulting detergent-resistant membrane (DRMs) domains. The real-time polymerase chain reaction technique is performed to detect the viral genome, thereby the MNV binding on the DRMs. The interactions between MNV and DRMs are investigated by high-speed atomic force microscopy (HS-AFM) combined with surface-enhanced Raman spectroscopy (SERS). The inoculation of the virus onto cells results in the aggregations of detergent-resistant membrane domains significantly. The characteristic Raman band of MNV is found in inoculated samples. To be sure that these results are originated from specific interactions between DRM and MNV, methyl-β-cyclo-dextrin (MβCD) is applied to disrupt lipid rafts. The MNV binding on DRMs is precluded by the MβCD treatment. The cholesterols chains are defined as a key factor in the interactions between norovirus and DRMs. The authors conclude that the MNV binding involves the presence of DRMs and cholesterol dependent.

Micro-Raman spectroscopic study of thyroid tissues

Thyroid carcinomas are the most common endocrine malignancy. Inconclusive results for the analysis of malignancies are an issue in the diagnosis of thyroid carcinomas; 20% of thyroid cancer diagnoses are indeterminate or suspicious, resulting in a surgical procedure without immediate need. The use of Raman spectroscopy may help improve the diagnosis of thyroid carcinoma. In this study, 30 thyroid samples, including normal thyroid, goiter and thyroid cancer, were analyzed by confocal Raman spectroscopy. Principal component analysis (PCA), linear discriminant analysis (LDA) with cross validation and binary logistic regression (BLR) analysis were applied to discriminate among tissues. Significant discrimination was observed, with a consistent rate of concordant pairs of 89.2% for normal thyroid versus cancer, 85.7% for goiter versus cancer and 80.6% for normal thyroid versus goiter using just the amide III region. Raman spectroscopy was thus proven to be an important and fast tool for the diagnosis of thyroid tissues. The spectral region of 1200-1400cm^-1 discriminated normal versus goiter tissues despite the great similarity of these tissues.

Biochemical fingerprints of human papillomavirus infection and cervical dysplasia using cervical fluids: Spectral pattern investigation

The Pap smear is the primary screening tool for invasive cervical cancer resulting from a persistent infection with oncogenic human papillomavirus (HPV); however, there are the problems such as the inability to distinguish between HPV infection and cervical dysplasia and a low sensitivity remain. We present preliminary findings of a label-free method to detect and classify HPV infection and cervical dysplasia using human cervical fluids. Three experimental groups, defined as normal, HPV-positive, and cervical dysplasia, were evaluated through their Raman spectral patterns for noise-independence, high reproducibility, and uniformity. Clinical diagnosis was performed through liquid-based cervical cytology, HPV test, and cervical histologic examination. Healthy cervical fluids showed a strong Raman intensity at 877 cm^-1 (symmetric C-C stretching), and at 963 cm^-1 (phosphate), compared to a reference Raman peak at 1003 cm^-1 (phenylalanine symmetric ring breath). The HPV-positive cervical fluids showed a strong intensity of a Raman peak at 1448 cm^-1 corresponding to C-H deformation vibration mode and the highest similarity between the central and ring zones among the three groups. The cervical dysplasia fluids showed the presence of strong peaks compared to the control and HPV-positive groups. In addition, different Raman spectra were acquired according to HPV type. Therefore, all ranges of cervical fluid-induced Raman spectra could be used to detect the presence of cervical pre-cancer. Raman peak-gated assessment provides a label-free and nondestructive tool for the clinical diagnosis of HPV infection and cervical precancerous changes.

Role of Raman spectroscopy and surface enhanced Raman spectroscopy in colorectal cancer

Colorectal cancer (CRC) is the fourth most common cancer in the United Kingdom and is the second largest cause of cancer related death in the United Kingdom after lung cancer. Currently in the United Kingdom there is not a diagnostic test that has sufficient differentiation between patients with cancer and those without cancer so the current referral system relies on symptomatic presentation in a primary care setting. Raman spectroscopy and surface enhanced Raman spectroscopy (SERS) are forms of vibrational spectroscopy that offer a non-destructive method to gain molecular information about biological samples. The techniques offer a wide range of applications from in vivo or in vitro diagnostics using endoscopic probes, to the use of micro-spectrometers for analysis of biofluids. The techniques have the potential to detect molecular changes prior to any morphological changes occurring in the tissue and therefore could offer many possibilities to aid the detection of CRC. The purpose of this review is to look at the current state of diagnostic technology in the United Kingdom. The development of Raman spectroscopy and SERS in clinical applications relation for CRC will then be discussed. Finally, future areas of research of Raman/SERS as a clinical tool for the diagnosis of CRC are also discussed.

A micro-Raman spectroscopic investigation of leukemic U-937 cells in aged cultures

Recently it has been shown that micro-Raman spectroscopy combined with multivariate analysis is able to discriminate among different types of tissues and tumoral cells by the detection of significant alterations and/or reorganizations of complex biological molecules, such as nucleic acids, lipids and proteins. Moreover, its use, being in principle a non-invasive technique, appears an interesting clinical tool for the evaluation of the therapeutical effects and of the disease progression. In this work we analyzed molecular changes in aged cultures of leukemia model U937 cells with respect to fresh cultures of the same cell line. In fact, structural variations of individual neoplastic cells on aging may lead to a heterogeneous data set, therefore falsifying confidence intervals, increasing error levels of analysis and consequently limiting the use of Raman spectroscopy analysis. We found that the observed morphological changes of U937 cells corresponded to well defined modifications of the Raman contributions in selected spectral regions, where markers of specific functional groups, useful to characterize the cell state, are present. A detailed subcellular analysis showed a change in cellular organization as a function of time, and correlated to a significant increase of apoptosis levels. Besides the aforementioned study, Raman spectra were used as input for principal component analysis (PCA) in order to detect and classify spectral changes among U937 cells.

Label-free DNA imaging in vivo with stimulated Raman scattering microscopy

Label-free DNA imaging is highly desirable in biology and medicine to perform live imaging without affecting cell function and to obtain instant histological tissue examination during surgical procedures. Here we show a label-free DNA imaging method with stimulated Raman scattering (SRS) microscopy for visualization of the cell nuclei in live animals and intact fresh human tissues with subcellular resolution. Relying on the distinct Raman spectral features of the carbon-hydrogen bonds in DNA, the distribution of DNA is retrieved from the strong background of proteins and lipids by linear decomposition of SRS images at three optimally selected Raman shifts. Based on changes on DNA condensation in the nucleus, we were able to capture chromosome dynamics during cell division both in vitro and in vivo. We tracked mouse skin cell proliferation, induced by drug treatment, through in vivo counting of the mitotic rate. Furthermore, we demonstrated a label-free histology method for human skin cancer diagnosis that provides comparable results to other conventional tissue staining methods such as H&E. Our approach exhibits higher sensitivity than SRS imaging of DNA in the fingerprint spectral region. Compared with spontaneous Raman imaging of DNA, our approach is three orders of magnitude faster, allowing both chromatin dynamic studies and label-free optical histology in real time.

Discrimination and classification of liver cancer cells and proliferation states by Raman spectroscopic imaging

Discrimination of nodular lesions in cirrhotic liver is a challenge in the histopathologic diagnostics. For this reason, there is an urgent need for new detection methods to improve the accuracy of the diagnosis of liver cancer. Raman imaging allows to determine the spatial distribution of a variety of molecules in cells or tissue label-free and to correlate this molecular information with the morphological structures at the same sample location. This study reports investigations of two liver cancer cell lines, - HepG2 and SK-Hep1, - as well as HepG2 cells in different cellular growth phases using Raman micro-spectroscopic imaging. Spectral data of all cells were recorded as a color-coded image and subsequentially analyzed by hierarchical cluster and principal component analysis. A support vector machine-based classification algorithm reliably predicts previously unknown cancer cells and cell cycle phases. By including selectively the Raman spectra of the cytoplasmic lipids in the classifier, the accuracy has been improved. The main spectral differences that were found in the comparative analysis can be attributed to a higher expression of unsaturated fatty acids in the hepatocellular carcinoma cells and during the proliferation phase. This corresponds to the already examined de novo lipogenesis in cells of liver cancer.

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.

Raman spectroscopy for screening and diagnosis of cervical cancer

Cervical cancer is the fourth most common cancer in women worldwide and mainly affects younger women. The mortality associated with cervical cancer can be reduced if the disease is detected at the pre-cancer stage. Current best-practice methods include cytopathology, HPV testing, and histopathology, but these methods are limited in terms of subjectivity, cost, and time. There is an unmet clinical need for new methods to aid clinicians in the early detection of cervical pre-cancer. These methods should be objective and rapid and require minimal sample preparation. Raman spectroscopy is a vibrational spectroscopic technique by which incident radiation is used to induce vibrations in the molecules of a sample and the scattered radiation may be used to characterise the sample in a rapid and non-destructive manner. Raman spectroscopy is sensitive to subtle biochemical changes occurring at the molecular level, enabling spectral variations corresponding to disease onset to be detected. Over the past 15 years, there have been numerous reports revealing the potential of Raman spectroscopy together with multivariate statistical analysis for the detection of a variety of cancers. This paper discusses the recent advances and challenges for cervical-cancer screening and diagnosis and offers some perspectives for the future.

The effect of Lactobacillus casei extract on cervical cancer cell lines

Aim of the study

Lactobacillus casei (L. casei) has been shown to inhibit the proliferation of several types of cancer in vivo, but its effect on cervical cells has not been reported. We incubated cells of the human cervical cell lines Caski and HeLa with extracts of L. casei and investigated its effects on the growth of the cells and possible synergy with anticancer drugs.

Material and methods

Cell-free extracts of L. casei were prepared and purified. Cultures of Caski and HeLa cells adhering to tissue culture plates were treated with L. casei extract. The effects of L. casei extract on the growth of cancer cells and its possible synergy with anti-cancer drugs in cervical cancer cell lines were investigated. The cells were treated with L. casei extract alone, anti-cancer drugs alone [doxorubicin, paclitaxel, 5-fluorouracil (5-FU), and cisplatin], or L. casei extract plus anti-cancer drugs.

Results

L. casei extract had no significant effect on the growth rate of the two cell lines. Anti-cancer drugs alone induced growth inhibition, but there was no synergistic effect of L. casei extract on growth inhibition.

Conclusions

L. casei extract does not have a potent effect on the viability of cervical cancer cells in vitro. In addition, L. casei extract has no synergistic effect on the inhibition of growth of cancer cells in the presence of anti-cancer drugs.

Modulated Raman Spectroscopy for Enhanced Cancer Diagnosis at the Cellular Level

Raman spectroscopy is emerging as a promising and novel biophotonics tool for non-invasive, real-time diagnosis of tissue and cell abnormalities. However, the presence of a strong fluorescence background is a key issue that can detract from the use of Raman spectroscopy in routine clinical care. The review summarizes the state-of-the-art methods to remove the fluorescence background and explores recent achievements to address this issue obtained with modulated Raman spectroscopy. This innovative approach can be used to extract the Raman spectral component from the fluorescence background and improve the quality of the Raman signal. We describe the potential of modulated Raman spectroscopy as a rapid, inexpensive and accurate clinical tool to detect the presence of bladder cancer cells. Finally, in a broader context, we show how this approach can greatly enhance the sensitivity of integrated Raman spectroscopy and microfluidic systems, opening new prospects for portable higher throughput Raman cell sorting.

Current Advances in the Application of Raman Spectroscopy for Molecular Diagnosis of Cervical Cancer

Raman spectroscopy provides a unique biochemical fingerprint capable of identifying and characterizing the structure of molecules, cells, and tissues. In cervical cancer, it is acknowledged as a promising biochemical tool due to its ability to detect premalignancy and early malignancy stages. This review summarizes the key research in the area and the evidence compiled is very encouraging for ongoing and further research. In addition to the diagnostic potential, promising results for HPV detection and monitoring treatment response suggest more than just a diagnosis prospective. A greater body of evidence is however necessary before Raman spectroscopy is fully validated for clinical use and larger comprehensive studies are required to fully establish the role of Raman spectroscopy in the molecular diagnostics of cervical cancer.

The use of wavelength modulated Raman spectroscopy in label-free identification of T lymphocyte subsets, natural killer cells and dendritic cells

Determining the identity of cells of the immune system usually involves destructive fixation and chemical staining, or labeling with fluorescently labeled antibodies recognising specific cell surface markers. Completely label-free identification would be a significant advantage in conditions where untouched cells are a priority. We demonstrate here the use of Wavelength Modulated Raman Spectroscopy, to achieve label-free identification of purified, unfixed and untouched populations of major immune cell subsets isolated from healthy human donors. Using this technique we have been able to distinguish between CD4⁺ T lymphocytes, CD8⁺ T lymphocytes and CD56⁺ Natural Killer cells at specificities of up to 96%. Additionally, we have been able to distinguish between CD303⁺ plasmacytoid and CD1c⁺ myeloid dendritic cell subsets, the key initiator and regulatory cells of many immune responses. This demonstrates the ability to identify unperturbed cells of the immune system, and opens novel opportunities to analyse immunological systems and to develop fully label-free diagnostic technologies.

Single cell confocal Raman spectroscopy of human osteoarthritic chondrocytes: a preliminary study

A great deal of effort has been focused on exploring the underlying molecular mechanism of osteoarthritis (OA) especially at the cellular level. We report a confocal Raman spectroscopic investigation on human osteoarthritic chondrocytes. The objective of this investigation is to identify molecular features and the stage of OA based on the spectral signatures corresponding to bio-molecular changes at the cellular level in chondrocytes. In this study, we isolated chondrocytes from human osteoarthritic cartilage and acquired Raman spectra from single cells. Major spectral differences between the cells obtained from different International Cartilage Repair Society (ICRS) grades of osteoarthritic cartilage were identified. During progression of OA, a decrease in protein content and an increase in cell death were observed from the vibrational spectra. Principal component analysis and subsequent cross-validation was able to associate osteoarthritic chondrocytes to ICRS Grade I, II and III with specificity 100.0%, 98.1%, and 90.7% respectively, while, sensitivity was 98.6%, 82.8%, and 97.5% respectively. The overall predictive efficiency was 92.2%. Our pilot study encourages further use of Raman spectroscopy as a noninvasive and label free technique for revealing molecular features associated with osteoarthritic chondrocytes.

Emerging technology: applications of Raman spectroscopy for prostate cancer

There is a need in prostate cancer diagnostics and research for a label-free imaging methodology that is nondestructive, rapid, objective, and uninfluenced by water. Raman spectroscopy provides a molecular signature, which can be scaled from micron-level regions of interest in cells to macroscopic areas of tissue. It can be used for applications ranging from in vivo or in vitro diagnostics to basic science laboratory testing. This work describes the fundamentals of Raman spectroscopy and complementary techniques including surface enhanced Raman scattering, resonance Raman spectroscopy, coherent anti-Stokes Raman spectroscopy, confocal Raman spectroscopy, stimulated Raman scattering, and spatially offset Raman spectroscopy. Clinical applications of Raman spectroscopy to prostate cancer will be discussed, including screening, biopsy, margin assessment, and monitoring of treatment efficacy. Laboratory applications including cell identification, culture monitoring, therapeutics development, and live imaging of cellular processes are discussed. Potential future avenues of research are described, with emphasis on multiplexing Raman spectroscopy with other modalities.