Near-infrared micro-Raman spectroscopy for in vitro detection of cervical cancer

Raman analysis of aqueous solutions of ethylene glycol and 1,3-propylene glycol: Fundamental and applied aspects

Aqueous solutions of glycols, on the one hand, are widely used in many applications; on the other hand, they can serve as simple and representative models for studying intra- and intermolecular hydrogen bonds. In this work, we analyze the possibilities and limitations of Raman spectroscopy for fundamental and applied researches of such solutions on the examples of ethylene glycol (EG) and 1,3-propylene glycol (1,3-PG). It is shown that Raman spectroscopy is an effective tool for monitoring temporal changes in the structure of glycol solutions deposited on substrates. This study demonstrates that the water content in the solutions on the substrates decreases rapidly with time, and the rate of this decrease depends on the chemical structure of both glycol and substrate. It was found that the reduction in the water content leads to slight decrease in the contents of gauche-conformers in the backbones of EG and 1,3-PG molecules. It is shown that use of the 1064 nm excitation ensures a reliable Raman analysis of automotive antifreezes containing various dyes, in particular determination of the relative contents of water and glycol.

Diagnostic Accuracy of Raman Spectroscopy Integrated With Polarized Light Microscopy for Calcium Pyrophosphate-Associated Arthritis

OBJECTIVE

We studied the performance of integrated Raman polarized light microscopy (iRPolM) for the identification of calcium pyrophosphate (CPP)-associated arthritis (CPPD).

METHODS

This is a diagnostic accuracy study including 400 consecutive synovial fluid samples from a single hospital in the Netherlands. Accuracy measures were calculated against polarized light microscopy (PLM) and the 2023 American College of Rheumatology (ACR)/EULAR criteria set for CPPD.

RESULTS

The interrater reliability between iRPolM and the 2023 ACR/EULAR criteria set for CPPD was strong (κ = 0.88). The diagnostic performance of iRPolM compared to the 2023 ACR/EULAR criteria set was sensitivity 86.0% (95% confidence interval [CI] 73.3-94.2), specificity 99.1% (95% CI 97.5-99.8), positive likelihood ratio 100.33 (95% CI 32.3-311.3), negative likelihood ratio 0.14 (95% CI 0.07-0.28), positive predictive value 93.5% (95% CI 82.2-97.8), negative predictive value 98.0% (95% CI 82.2-97.8), and accuracy 97.5% (95% CI 95.5-98.8). We allowed rheumatologists to rate the certainty of their microscopic identification of CPP and found a large correspondence between iRPolM and a certain identification (κ = 0.87), whereas only 10% of the uncertain CPP identifications could be confirmed with iRPolM. We identified several novel particle types in synovial fluid analysis, including calcium carbonate crystals, deposited carotenoids, microplastics, and three types of Maltese cross birefringent objects.

CONCLUSION

iRPolM can easily identify CPP crystals with a strong diagnostic performance. PLM alone is not specific enough to reliably resolve complicated cases, and the implementation of Raman spectroscopy in rheumatology practice can be of benefit to patients with suspected CPPD.

Decision-level data fusion based on laser-induced breakdown and Raman spectroscopy: A study of bimodal spectroscopy for diagnosis of lung cancer at different stages

Lung cancer staging is crucial for personalized treatment and improved prognosis. We propose a novel bimodal diagnostic approach that integrates LIBS and Raman technologies into a single platform, enabling comprehensive tissue elemental and molecular analysis. This strategy identifies critical staging elements and molecular marker signatures of lung tumors. LIBS detects concentration patterns of elemental lines including Mg (I), Mg (II), Ca (I), Ca (II), Fe (I), and Cu (II). Concurrently, Raman spectroscopy identifies changes in molecular content, such as phenylalanine (1033 cm-1), tyrosine (1174 cm-1), tryptophan (1207 cm-1), amide III (1267 cm-1), and proteins (1126 cm-1 and 1447 cm-1), among others. The bimodal information is fused using a decision-level Bayesian fusion model, significantly enhancing the performance of the convolutional neural network architecture in classification algorithms, with an accuracy of 99.17 %, sensitivity of 99.17 %, and specificity of 99.88 %. This study provides a powerful new tool for the accurate staging and diagnosis of lung tumors.

Species identification and strain discrimination of fermentation yeasts Saccharomyces cerevisiae and Saccharomyces uvarum using Raman spectroscopy and convolutional neural networks

IMPORTANCE

The use of S. cerevisiae and S. uvarum yeast starter cultures is a common practice in the alcoholic beverage fermentation industry. As yeast strains from different or the same species have variable fermentation properties, rapid and reliable typing of yeast strains plays an important role in the final quality of the product. In this study, Raman spectroscopy combined with CNN achieved accurate identification of S. cerevisiae and S. uvarum isolates at both the species and strain levels in a rapid, non-destructive, and easy-to-operate manner. This approach can be utilized to test the identity of commercialized dry yeast products and to monitor the diversity of yeast strains during fermentation. It provides great benefits as a high-throughput screening method for agri-food and the alcoholic beverage fermentation industry. This proposed method has the potential to be a powerful tool to discriminate S. cerevisiae and S. uvarum strains in taxonomic, ecological studies and fermentation applications.

Evaluation of Raman spectroscopy combined with the gated recurrent unit serum detection method in early screening of gastrointestinal cancer

Gastric and colorectal cancers are significant causes of human mortality. Conventionally, the diagnosis of gastrointestinal tumors has been accomplished through image-based techniques, including endoscopic and biopsy procedures coupled with tissue staining. Most of these methods are invasive. In contrast, Raman spectroscopy has the advantages of being non-invasive and label-free and requiring no additional reagents, making it a potential tool for the detection of serum components. In this study, we collected Raman spectra of serum samples from patients with gastric cancer (n = 93) and colorectal cancer (n = 92) and from healthy individuals (n = 100). Analysis of Raman peak areas revealed that cancer patients had significantly higher peak areas at around 2923 cm-1 compared to normal individuals, which corresponded to the presence of lipids and proteins. We successfully achieved the early screening of gastrointestinal tumors using the improved gated recurrent unit (GRU) algorithm and traditional machine learning methods. The accuracy of identifying digestive tract tumors using different recognition models exceeds 84.72%, with support vector machine (SVM) and GRU achieving 100% accuracy. The use of GRU further demonstrated its ability to differentiate subtypes of gastric and colorectal cancers based on the degree of differentiation and stage, with a recognition accuracy exceeding 95%, which is challenging using traditional machine learning methods. Furthermore, our study revealed that principal component analysis (PCA) dimensionality reduction has a limited impact on the recognition results obtained using different recognition models.

Label-Free Human Disease Characterization through Circulating Cell-Free DNA Analysis Using Raman Spectroscopy

Circulating cell-free DNA (ccfDNA) is a liquid biopsy biomaterial attracting significant attention for the implementation of precision medicine diagnostics. Deeper knowledge related to its structure and biology would enable the development of such applications. In this study, we employed Raman spectroscopy to unravel the biomolecular profile of human ccfDNA in health and disease. We established reference Raman spectra of ccfDNA samples from healthy males and females with different conditions, including cancer and diabetes, extracting information about their chemical composition. Comparative observations showed a distinct spectral pattern in ccfDNA from breast cancer patients taking neoadjuvant therapy. Raman analysis of ccfDNA from healthy, prediabetic, and diabetic males uncovered some differences in their biomolecular fingerprints. We also studied ccfDNA released from human benign and cancer cell lines and compared it to their respective gDNA, confirming it mirrors its cellular origin. Overall, we explored for the first time Raman spectroscopy in the study of ccfDNA and provided spectra of samples from different sources. Our findings introduce Raman spectroscopy as a new approach to implementing liquid biopsy diagnostics worthy of further elaboration.

Molecular Planarization of Raman Probes to Avoid Background Interference for High-Precision Intraoperative Imaging of Tumor Micrometastases and Lymph Nodes

The intraoperative imaging applications of a large number of Raman probes are hampered by the overlap of their signals with the background Raman signals generated by biological tissues. Here, we describe a molecular planarization strategy for adjusting the Raman shift of these Raman probes to avoid interference. Using this strategy, we modify the backbone of thiophene polymer-poly(3-hexylthiophene) (P3HT), and obtain the adjacent thiophene units planarized polycyclopenta[2,1-b;3,4-b']dithiophene (PCPDT). Compared with P3HT whose signal is disturbed by the Raman signal of lipids in tissues, PCPDT exhibits a 60 cm^-1 blueshift in its characteristic signal. Therefore, the PCPDT probe successfully avoids the signal of lipids, and achieves intraoperative imaging of lymph nodes and tumor micrometastasis as small as 0.30 × 0.36 mm. In summary, our study presents a concise molecular planarization strategy for regulating the signal shift of Raman probes, and brings a tunable thiophene polymer probe for high-precision intraoperative Raman imaging.

In situ identification of environmental microorganisms with Raman spectroscopy

Microorganisms in natural environments are crucial in maintaining the material and energy cycle and the ecological balance of the environment. However, it is challenging to delineate environmental microbes' actual metabolic pathways and intraspecific heterogeneity because most microorganisms cannot be cultivated. Raman spectroscopy is a culture-independent technique that can collect molecular vibration profiles from cells. It can reveal the physiological and biochemical information at the single-cell level rapidly and non-destructively in situ. The first part of this review introduces the principles, advantages, progress, and analytical methods of Raman spectroscopy applied in environmental microbiology. The second part summarizes the applications of Raman spectroscopy combined with stable isotope probing (SIP), fluorescence in situ hybridization (FISH), Raman-activated cell sorting and genomic sequencing, and machine learning in microbiological studies. Finally, this review discusses expectations of Raman spectroscopy and future advances to be made in identifying microorganisms, especially for uncultured microorganisms.

Raman Spectroscopy: A Novel Technology for Gastric Cancer Diagnosis

Gastric cancer is usually diagnosed at late stage and has a high mortality rate, whereas early detection of gastric cancer could bring a better prognosis. Conventional gastric cancer diagnostic methods suffer from long diagnostic times, severe trauma, and a high rate of misdiagnosis and rely heavily on doctors’ subjective experience. Raman spectroscopy is a label-free molecular vibrational spectroscopy technique that identifies the molecular fingerprint of various samples based on the inelastic scattering of monochromatic light. Because of its advantages of non-destructive, rapid, and accurate detection, Raman spectroscopy has been widely studied for benign and malignant tumor differentiation, tumor subtype classification, and section pathology diagnosis. This paper reviews the applications of Raman spectroscopy for the in vivo and in vitro diagnosis of gastric cancer, methodology related to the spectroscopy data analysis, and presents the limitations of the technique.

Automated analysis of microplastics based on vibrational spectroscopy: are we measuring the same metrics?

The traditional manual analysis of microplastics has been criticized for its labor-intensive, inaccurate identification of small microplastics, and the lack of uniformity. There are already three automated analysis strategies for microplastics based on vibrational spectroscopy: laser direct infrared (LDIR)-based particle analysis, Raman-based particle analysis, and focal plane array-Fourier transform infrared (FPA-FTIR) imaging. We compared their performances in terms of quantification, detection limit, size measurement, and material identification accuracy and speed by analyzing the same standard and environmental samples. LDIR-based particle analysis provides the fastest analysis speed, but potentially questionable material identification and quantification results. The number of particles smaller than 60 μm recognized by LDIR-based particle analysis is much less than that recognized by Raman-based particle analysis. Misidentification could occur due to the narrow tuning range from 1800 to 975 cm^-1 and dispersive artifact distortion of infrared spectra collected in reflection mode. Raman-based particle analysis has a submicrometer detection limit but should be cautiously used in the automated analysis of microplastics in environmental samples because of the strong fluorescence interference. FPA-FTIR imaging provides relatively reliable quantification and material identification for microplastics in environmental samples greater than 20 μm but might provide an imprecise description of the particle shapes. Optical photothermal infrared (O-PTIR) spectroscopy can detect submicron-sized environmental microplastics (0.5-5 μm) intermingled with a substantial amount of biological matrix; the resulting spectra are searchable in infrared databases without the influence of fluorescence interference, but the process would need to be fully automated.

Investigating the cellular responses of osteosarcoma to cisplatin by confocal Raman microspectroscopy

Confocal Raman Microspectroscopy (CRM) was employed to clarify the cellular response of cisplatin in osteosarcoma (OS) cells with different dosages and incubation times. The K7M2 mouse osteosarcoma cells were treated by cisplatin in 0 μM (UT group), 20 μM (20 T group), and 40 μM (40 T group) doses for 24-h (24H group) and 48-h (48H group), respectively. Raman spectroscopy was utilized to analyze the drug induced variations of intracellular biochemical components in osteosarcoma cells. The spectral results shows that the main changes in its biochemical composition come from nucleic acids. By adopting three different kernel functions (linear, polynomial, and Gaussian radial basis function (RBF)), principal component analysis combined with support vector machine models (PCA-SVM) was built to address the spectral variations among all investigated groups. Meanwhile, multivariate curve resolution alternating least squares (MCR-ALS) was further utilized to discuss on the chemical interpretation on the acquired spectral results. Moreover, Raman spectral images, which is reconstructed by K-means cluster analysis (KCA) with point-scanned hyperspectral dataset, was applied to illustrate the drug induced compositional and morphological variations in each subcellular region. The achieved results not only prove the application potential of Raman based analytical technique in non-labeled intracellular studies, but also illustrate the detailed compositional and structural information of cisplatin induced OS cell responses from the perspective of multivariate analysis and imaging of Raman spectroscopy.

Elucidating Raman Image-Guided Differential Recognition of Clinically Confirmed Grades of Cervical Exfoliated Cells by Dual Biomarker-Appended SERS-Tag

Ultrasensitive detection of cancer biomarkers via single-cell analysis through Raman imaging is an impending approach that modulates the possibility of early diagnosis. Cervical cancer is one such type that can be monitored for a sufficiently long period toward invasive cancer phenotype. Herein, we report a surface-enhanced Raman scattering (SERS) nanotag (SERS-tag) for the simultaneous detection of p16/K-i67, a dual biomarker persisting in the progression of squamous cell carcinoma of human cervix. A nanoflower-shaped SERS-tag, constituted of hybrid gold nanostar with silver tips to achieve maximum fingerprint enhancement from the incorporated reporter molecule, was further functionalized with the cocktail monoclonal antibodies against p16/K-i67. The recognition by the SERS-tag was first validated in cervical squamous cell carcinoma cell line SiHa as a foot-step study and subsequently implemented to different grades of clinically confirmed exfoliated cells including normal cell (NC), high-grade intra-epithelial lesion (HC), and squamous cell carcinoma (CC) samples of the cervix. Precise Raman mapped images were constituted based on the average intensity gradient of the signature Raman peaks arising from different grades of exfoliated cells. We observed a distinct intensity hike of around 10-fold in the single dysplastic HC and CC samples in comparison to NC specimen, which clearly justify the prevalence of p16/Ki-67. The synthesized probe is able to map the abnormal cells within 20 min with high reproducibility and stability for 1 mm × 1 mm mapping area with good contrast. Amidst the challenges in Raman image-guided modality, the technique was further complemented with the gold standard immunocytochemistry (ICC) dual staining analysis. Even though both are time-consuming techniques, tedious steps can be avoided and real-time readout can be achieved using the SERS mapping unlike immunocytochemistry technique. Therefore, the newly developed Raman image-guided SERS imaging emphasizes the approach of uplifting of SERS in practical utility with further improvement for clinical applications for cervical cancer detection in future.

Raman spectral cytopathology for cancer diagnostic applications

Raman spectroscopy can provide a rapid, label-free, nondestructive measurement of the chemical fingerprint of a sample and has shown potential for cancer screening and diagnosis. Here we report a protocol for Raman microspectroscopic analysis of different exfoliative cytology samples (cervical, oral and lung), covering sample preparation, spectral acquisition, preprocessing and data analysis. The protocol takes 2 h 20 min for sample preparation, measurement and data preprocessing and up to 8 h for a complete analysis. A key feature of the protocol is that it uses the same sample preparation procedure as commonly used in diagnostic cytology laboratories (i.e., liquid-based cytology on glass slides), ensuring compatibility with clinical workflows. Our protocol also covers methods to correct for the spectral contribution of glass and sample pretreatment methods to remove contaminants (such as blood and mucus) that can obscure spectral features in the exfoliated cells and lead to variability. The protocol establishes a standardized clinical routine allowing the collection of highly reproducible data for Raman spectral cytopathology for cancer diagnostic applications for cervical and lung cancer and for monitoring suspicious lesions for oral cancer.

Confocal Raman microspectral analysis and imaging of the drug response of osteosarcoma to cisplatin

Confocal Raman microspectral analysis and imaging were used to elucidate the drug response of osteosarcoma (OS) to cisplatin. Raman spectral data were obtained from OS cells that were untreated (UT group) and treated with 20 µM (20T group) and 40 µM (40T group) cisplatin for 24 hours. Statistical analysis of the changes in specific Raman signals was performed using a one-way ANOVA and multiple Tukey's honest significant difference (HSD) post hoc tests. Principal component analysis-linear discriminant analysis (PCA-LDA) was used to highlight the featured cellular drug responses based on the obtained spectral information. For spectral imaging analysis, k-means cluster analysis (KCA) was adopted to clarify the effect of cisplatin dose changes on the subcellular structure and its biochemical composition. The results suggest that the major biochemical changes induced by cisplatin in OS cells undergoing apoptosis are reduced protein and nucleic acid content. Through univariate analysis, the changes in the distribution of nucleic acids in OS cells induced by different doses of cisplatin were obtained. The combination of Raman spectroscopy and multivariate analysis shows that cisplatin mainly acts on the nucleus and causes changes in the secondary structure of proteins. These results indicate that Raman imaging technology has the potential to offer the basis of dose optimization for personalized cancer treatment by helping to understand in vitro cellular drug interactions.

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.

Single Cell Label-Free Probing of Chromatin Dynamics During B Lymphocyte Maturation

Large-scale intracellular signaling during developmental growth or in response to environmental alterations are largely orchestrated by chromatin within the cell nuclei. Chemical and conformational modifications of the chromatin architecture are critical steps in the regulation of differential gene expression and ultimately cell fate determination. Therefore, establishing chemical properties of the nucleus could provide key markers for phenotypic characterization of cellular processes on a scale of individual cells. Raman microscopy is a sensitive technique that is capable of probing single cell chemical composition—and sub-cellular regions—in a label-free optical manner. As such, it has great potential in both clinical and basic research. However, perceived limitations of Raman spectroscopy such as low signal intensity and the difficulty in linking alterations in vibrational signals directly with ensuing biological effects have hampered advances in the field. Here we use immune B lymphocyte development as a model to assess chromatin and transcriptional changes using confocal Raman microscopy in combination with microfluidic devices and correlative transcriptomics, thereby linking changes in chemical and structural properties to biological outcomes. Live B lymphocytes were assessed before and after maturation. Multivariate analysis was applied to distinguish cellular components within each cell. The spectral differences between non-activated and activated B lymphocytes were then identified, and their correlation with known intracellular biological changes were assessed in comparison to conventional RNA-seq analysis. Our data shows that spectral analysis provides a powerful tool to study gene activation that can complement conventional molecular biology techniques and opens the way for mapping the dynamics in the biochemical makeup of individual cells.

New Probe for Porcelain Glazes by Luminescence at Near-Infrared Excitation

Raman spectroscopy is a powerful technique for a wide range of materials, including porcelain, and near-infrared excitation is often used to suppress a fluorescence background from a sample. When we measured the Raman spectra of porcelains at 785 nm excitation, we observed a strong broad band in a high-frequency region, and its origin was not clearly elucidated. In this study, we have measured the spectra of glazed porcelains at 532, 785, and 1064 nm excitation and demonstrated that the broad feature originates from luminescence around 880 nm and not from Raman scattering. We provide experimental evidence showing that the band originates from a thin layer of glaze. Since the band shape depends on the processing temperature, the luminescence spectra can be a nondestructive probe for studying the glass formation of a glaze.

Applicability of Raman spectroscopy on porcine parvovirus and porcine circovirus type 2 detection

Porcine parvovirus (PPV) is one of the major infectious causes of reproductive failure of swine. This disease is characterized by embryonic and fetal infection and death, responsible for important economic losses. PPV is also implicated as a trigger in the development of post-weaning multisystemic wasting syndrome (PMWS) caused by Porcine circovirus type 2 (PCV2). Their detection is PCR-based, which is quite sensitive and specific, but laborious, costly and time-demanding. Therefore, this study aimed to assess Raman spectroscopy (RS) as a diagnostic tool for PPV and PCV2 due to its label-free properties and unique ability to search and identify molecular fingerprints. Briefly, swine testis (ST) cells were inoculated with PPV or PCV2 and in vitro cultured (37 °C, 5% CO₂) for four days. Fixed cells were then submitted to RS investigation using a 633 nm laser. A total of 225 spectra centered at 1300 cm^-1 was obtained for each sample (5 spectra/cell; 15 cells/replicate; 3 replicates) of PPV-, PCV2-infected and uninfected (control) ST cells. Clear statistical discrimination between samples from both virus-infected cells was achieved with a Principal Component - Linear Discriminant Analysis (PCA-LDA) model, reaching sensitivity rates from 95.55% to 97.77%, respectively to PCV2- and PPV-infected cells. These results were then submitted to a Leave-One-Out (LOO) validation algorithm resulting in 99.97% of accuracy. Extensive band assignment was analyzed and compiled for better understanding of PPV and PCV2 virus-cell interaction, demonstrating that specific protein, lipids and DNA/RNA bands are the most important assignments related to discrimination of virus-infected from uninfected cells. In conclusion, these results represent promising bases for RS application on PCV2 and PPV detection for future diagnostic applications.

Raman Microspectroscopic Investigation and Classification of Breast Cancer Pathological Characteristics

Breast cancer is one of the major cancers of women in the world. Despite significant progress in its treatment, an early diagnosis can effectively reduce its incidence rate and mortality. To improve the reliability of Raman-based tumor detection and analysis methods, we conducted an ex vivo study to unveil the compositional features of healthy control (HC), solid papillary carcinoma (SPC), mucinous carcinoma (MC), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC) tissue samples. Following the identification of biological variations occurring as a result of cancer invasion, principal component analysis followed by linear discriminate analysis (PCA-LDA) algorithm were adopted to distinguish spectral variations among different breast tissue groups. The achieved results confirmed that after training, the constructed classification model combined with the leave-one-out cross-validation (LOOCV) method was able to distinguish the different breast tissue types with 100% overall accuracy. The present study demonstrates that Raman spectroscopy combined with multivariate analysis technology has considerable potential for improving the efficiency and performance of breast cancer diagnosis.

Indication of high lipid content in epithelial-mesenchymal transitions of breast tissues

The epithelial-mesenchymal transition (EMT) is a crucial process in cancer progression and metastasis. Study of metabolic changes during the EMT process is important in seeking to understand the biochemical changes associated with cancer progression, not least in scoping for therapeutic strategies aimed at targeting EMT. Due to the potential for high sensitivity and specificity, Raman spectroscopy was used here to study the metabolic changes associated with EMT in human breast cancer tissue. For Raman spectroscopy measurements, tissue from 23 patients were collected, comprising non-lesional, EMT and non-EMT formalin-fixed and paraffin embedded breast cancer samples. Analysis was made in the fingerprint Raman spectra region (600-1800 cm-1) best associated with cancer progression biochemical changes in lipid, protein and nucleic acids. The ANOVA test followed by the Tukey's multiple comparisons test were conducted to see if there existed differences between non-lesional, EMT and non-EMT breast tissue for Raman spectroscopy measurements. Results revealed that significant differences were evident in terms of intensity between the non-lesional and EMT samples, as well as the EMT and non-EMT samples. Multivariate analysis involving independent component analysis, Principal component analysis and non-negative least square were used to analyse the Raman spectra data. The results show significant differences between EMT and non-EMT cancers in lipid, protein, and nucleic acids. This study demonstrated the capability of Raman spectroscopy supported by multivariate analysis in analysing metabolic changes in EMT breast cancer tissue.

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.

Study on the biochemical mechanisms of the micro-wave ablation treatment of lung cancer by ex vivo confocal Raman microspectral imaging

As a highly invasive and the most prevalent malignancy, lung cancer remains the leading cause of cancer-associated mortality worldwide, especially in China. Microwave ablation (MWA) is an effective, safe, and the least invasive ablative treatment modality, which has been increasingly used for the management of unrespectable lung tumors. However, the underlying biochemical mechanisms of MWA treatment remain to be incompletely elucidated. Therefore, to illustrate the complex biochemical responses of lung squamous cell carcinoma (LSCC) to MWA treatment, confocal Raman micro-spectral imaging (CRMI) was applied in combination with multivariate analysis. A total of twelve LSCC tissues were acquired from patients undergoing clinical treatment, and their spectral characteristics were analyzed to determine significant spectral variations following cancer progression and MWA treatment in comparison with healthy lung tissues. Point-scanned Raman datasets were acquired from sectioned tissue samples in both pre-therapy (Pre-MWA group) and post-therapy groups (Post-MWA group) and further analyzed using K-means cluster analysis (KCA) and principal component analysis (PCA) to highlight the detailed compositional variations of the biochemical constituents. The spectral variations of essential amino acids (such as phenylalanine and tryptophan), collagen, and nucleic acids in the cancerous tissues of the Post-MWA group were significantly enhanced compared to those in the Pre-MWA group. The acquired information further confirmed a remarkable increase in the content of nucleic acid, protein, and lipid in the cancerous tissue following MWA treatment and, a comparative spectral imaging investigation indicated that MWA had no noticeable adverse effects on the paracancerous tissues. Thus, the findings not only illustrated the underlying biochemical variability in lung cancer during MWA treatment but also further confirmed the feasibility of a combined analytical procedure for assessing the biochemical responses during thermal ablation, which could be applied to prominently enhance the effectiveness of MWA in lung cancer treatment in clinical settings.

Characterizing glucose, illumination, and nitrogen-deprivation phenotypes of Synechocystis PCC6803 with Raman spectroscopy

Background

Synechocystis sp. PCC6803 is a model cyanobacterium that has been studied widely and is considered for metabolic engineering applications. Here, Raman spectroscopy and Raman chemometrics (Rametrix™) were used to (i) study broad phenotypic changes in response to growth conditions, (ii) identify phenotypic changes associated with its circadian rhythm, and (iii) correlate individual Raman bands with biomolecules and verify these with more accepted analytical methods.

Methods

Synechocystis cultures were grown under various conditions, exploring dependencies on light and/or external carbon and nitrogen sources. The Rametrix™ LITE Toolbox for MATLAB® was used to process Raman spectra and perform principal component analysis (PCA) and discriminant analysis of principal components (DAPC). The Rametrix™ PRO Toolbox was used to validate these models through leave-one-out routines that classified a Raman spectrum when growth conditions were withheld from the model. Performance was measured by classification accuracy, sensitivity, and specificity. Raman spectra were also subjected to statistical tests (ANOVA and pairwise comparisons) to identify statistically relevant changes in Synechocystis phenotypes. Finally, experimental methods, including widely used analytical and spectroscopic assays were used to quantify the levels of glycogen, fatty acids, amino acids, and chlorophyll a for correlations with Raman data.

Results

PCA and DAPC models produced distinct clustering of Raman spectra, representing multiple Synechocystis phenotypes, based on (i) growth in the presence of 5 mM glucose, (ii) illumination (dark, light/dark [12 h/12 h], and continuous light at 20 µE), (iii) nitrogen deprivation (0–100% NaNO₃ of native BG-11 medium in continuous light), and (iv) throughout a 24 h light/dark (12 h/12 h) circadian rhythm growth cycle. Rametrix™ PRO was successful in identifying glucose-induced phenotypes with 95.3% accuracy, 93.4% sensitivity, and 96.9% specificity. Prediction accuracy was above random chance values for all other studies. Circadian rhythm analysis showed a return to the initial phenotype after 24 hours for cultures grown in light/dark (12 h/12 h) cycles; this did not occur for cultures grown in the dark. Finally, correlation coefficients (R > 0.7) were found for glycogen, all amino acids, and chlorophyll a when comparing specific Raman bands to other experimental results.

Raman-Enhanced Spectroscopy (RESpect) Probe for Childhood Non-Hodgkin Lymphoma

Raman-enhanced spectroscopy (RESpect) probe, which enhances Raman spectroscopy technology through a portable fiber-optic device, characterizes tissues and cells by identifying molecular chemical composition showing distinct differences/similarities for potential tumor markers or diagnosis. In a feasibility study with the ultimate objective to translate the technology to the clinic, a panel of pediatric non-Hodgkin lymphoma tissues and non-malignant specimens had RS analyses compared between standard Raman spectroscopy microscope instrument and RESpect probe. Cryopreserved tissues were mounted on front-coated aluminum mirror slides and analyzed by standard Raman spectroscopy and RESpect probe. Principal Component Analysis revealed similarities between non-Hodgkin lymphoma subtypes but not follicular hyperplasia. Standard Raman spectroscopy and RESpect probe fingerprint comparisons demonstrated comparable primary peaks. Raman spectroscopic fingerprints and peaks of pediatric non-Hodgkin lymphoma subtypes and follicular hyperplasia provided novel avenues to pursue diagnostic approaches and identify potential new therapeutic targets. The information could inform new insights into molecular cellular pathogenesis. Translating Raman spectroscopy technology by using the RESpect probe as a potential point-of-care screening instrument has the potential to change the paradigm of screening for cancer as an initial step to determine when a definitive tissue biopsy would be necessary.

Rapid and complete paraffin removal from human tissue sections delivers enhanced Raman spectroscopic and histopathological analysis

Incomplete removal of paraffin and organic contaminants from tissues processed for diagnostic histology has been a profound barrier to the introduction of Raman spectroscopic techniques into clinical practice. We report a route to rapid and complete paraffin removal from a range of formalin-fixed paraffin embedded tissues using super mirror stainless steel slides. The method is equally effective on a range of human and animal tissues, performs equally well with archived and new samples and is compatible with standard pathology lab procedures. We describe a general enhancement of the Raman scatter and enhanced staining with antibodies used in immunohistochemistry for clinical diagnosis. We conclude that these novel slide substrates have the power to improve diagnosis through anatomical pathology by facilitating the simultaneous combination of improved, more sensitive immunohistochemical staining and simplified, more reliable Raman spectroscopic imaging, analysis and signal processing.

Clarifying Glass Luminescence at Near-Infrared Excitation

Glass is a unique material that is often encountered in chemical and biological studies as a convenient sample holder (vial or microscope slide in particular). If the sample is probed with light in fluorescence and Raman spectroscopic experiments, the contribution from glass is often present and can obscure the spectra from the analyte of interest. It is important to understand the nature of glass photoemission properties to control this potential interference. The Raman spectrum of glass is dominated by peaks around 500 and 1000 cm^-1 at the excitation with UV and visible light. A strong broad emission band centered at 880 nm appears when glass is irradiated with near-infrared light, a popular 785 nm laser light in particular. We proved experimentally in this study that this broad band is due to glass photoluminescence and not Raman scattering. In addition, three narrow components were found to contribute to this band, which have different excitation profiles indicating that they originate from three different species or the same species experiencing three different types of local environments. It has been hypothesized that these peaks could be due to the presence of rare earth impurities in the glass. Further study is necessary to identify these luminescent centers.

Raman spectroscopy combined with multivariate analysis to study the biochemical mechanism of lung cancer microwave ablation

Lung cancer is the leading cause of death in cancer patients, and microwave ablation (MWA) has been extensively used in clinical treatment. In this study, we characterized the spectra of MWA-treated and untreated lung squamous cell carcinoma (LSCC) tissues, as well as healthy lung tissue, and conducted a preliminary analysis of spectral variations associated with MWA treatment. The results of characteristic spectral analysis of different types of tissues indicated that MWA treatment induces an increase in the content of nucleic acids, proteins, and lipid components in lung cancer tissues. The discriminant model based on the principal component analysis - linear discriminant analysis (PCA-LDA) algorithm together with leave-one-out cross validation (LOOCV) method yield the sensitivities of 90%, 80%, and 96%, and specificities of 86.2%, 93.8%, and 100% among untreated and MWA-treated cancerous tissue, and healthy lung tissue, respectively. These results indicate that Raman spectroscopy combined with multivariate analysis techniques can be used to explore the biochemical response mechanism of cancerous tissue to MWA therapy.

Continuous-Wave Coherent Raman Spectroscopy via Plasmonic Enhancement

In this paper, we report a successful combination of stimulated Raman spectroscopy (SRS) and surface-enhanced Raman scattering (SERS) using cw laser sources and gold/silica nanoparticles with embedded reporter molecules. We describe the preparation method for our gold/silica nanoparticles as well as the effect of probe wavelength, pump and probe power, polarization and sample concentration on the cwSESRS signal. Altogether, a stable ~12 orders of magnitude enhancement in the stimulated Raman signal is achieved because of the amplification of both pump and probe beams, leading to the detection of pico-molar nanoparticle concentrations, comparable to those of SERS. The coherent Raman spectra matches the incoherent conventional Raman spectra of the reporter molecules. Unlike conventional incoherent SERS this approach generates a coherent stimulated signal of microwatt intensities, opening the field to applications requiring a coherent beam, such as Molecular Holography.

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.

Local-dependency of morphological and optical properties between breast cancer cell lines

Breast cancer is the most malignant type of cancer in women and is a global health problem, with mortality by metastasis being the main factor among others. Currently, detection and diagnosis of breast cancer is achieved through a variety of procedures, such as clinical examination, medical imaging, biopsy, and histopathological analysis. In contrast, spectroscopic analysis has a variety of advantages such as being noninvasive, not destroying biological materials, and not requiring additional histological analysis. In this study, various approaches using Raman spectroscopy, atomic force microscopy (AFM), and optical microscopy were used together to differentiate between and characterize normal breast cell lines (MCF-10A) and breast cancer cell lines (MDA-MB-231, MDA-MB-453). Raman spectra of normal breast cell and breast cancer cell lines confirmed visual differences in the concentrations of various compounds. These spectra were also analyzed using principle component analysis (PCA), and the PCA results showed reliable separation of the three cell lines and the cancer cell lines (MDA-MB-231, MDA-MB-453). With these results, optically synchronizing the AFM morphology, the Raman spectroscopy, and the visible RGB optical transmission intensity provided contrasts for not only conformational differences but also intracellular variation between the normal and cancer cell lines. We observed the inherent characteristic that there is no local difference in cancer cells regardless of morphology in a wide range of optical properties such as absorption, scattering and inelastic scattering.

Raman spectroscopic detection of high-grade cervical cytology: Using morphologically normal appearing cells

This study aims to detect high grade squamous intraepithelial cells (HSIL) by investigating HSIL associated biochemical changes in morphologically normal appearing intermediate and superficial cells using Raman spectroscopy. Raman spectra (n = 755) were measured from intermediate and superficial cells from negative cytology ThinPrep specimens (n = 18) and from morphologically normal appearing intermediate and superficial cells from HSIL cytology ThinPrep specimens (n = 17). The Raman data was subjected to multivariate algorithms including the standard principal component analysis (PCA)-linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) together with random subsets cross-validation for discriminating negative cytology from HSIL. The PCA-LDA method yielded sensitivities of 74.9%, 72.8%, and 75.6% and specificities of 89.9%, 81.9%, and 84.5%, for HSIL diagnosis based on the dataset obtained from intermediate, superficial and mixed intermediate/superficial cells, respectively. The PLS-DA method provided improved sensitivities of 95.5%, 95.2% and 96.1% and specificities of 92.7%, 94.7% and 93.5% compared to the PCA-LDA method. The results demonstrate that the biochemical signatures of morphologically normal appearing cells can be used to discriminate between negative and HSIL cytology. In addition, it was found that mixed intermediate and superficial cells could be used for HSIL diagnosis as the biochemical differences between negative and HSIL cytology were greater than the biochemical differences between intermediate and superficial cell types.

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.

Unique Raman Spectroscopic Fingerprints of B-Cell Non-Hodgkin Lymphoma: Implications for Diagnosis, Prognosis and New Therapies

OBJECTIVE

Raman spectroscopy is a non-invasive laser-based technique that identifies molecular chemical composition of tissues and cells. The objective of the work was to demonstrate that unique Raman spectroscopic fingerprints of B-cell non-Hodgkin lymphoma cells could be distinguished from normal B-cells.

METHODS

Normal B-cells and B-cell non-Hodgkin lymphoma cells were mounted on aluminum slides and analyzed by Raman spectroscopy using Asymmetric Least Squares and Principal Component Analysis.

RESULTS

Clustering by Principal Component Analysis differentiated normal B-cells from B-cell non-Hodgkin lymphoma cells as well as between the different B-cell non-Hodgkin lymphoma cell types.

CONCLUSIONS

Raman spectroscopy technology provided a different paradigm in analyzing tumor cells which could be used for diagnosis as well as contribute new information on unique characteristics of cancer cells to understand pathogenesis and potential novel treatments.

Raman spectral signatures of cervical exfoliated cells from liquid-based cytology samples

It is widely accepted that cervical screening has significantly reduced the incidence of cervical cancer worldwide. The primary screening test for cervical cancer is the Papanicolaou (Pap) test, which has extremely variable specificity and sensitivity. There is an unmet clinical need for methods to aid clinicians in the early detection of cervical precancer. Raman spectroscopy is a label-free objective method that can provide a biochemical fingerprint of a given sample. Compared with studies on infrared spectroscopy, relatively few Raman spectroscopy studies have been carried out to date on cervical cytology. The aim of this study was to define the Raman spectral signatures of cervical exfoliated cells present in liquid-based cytology Pap test specimens and to compare the signature of high-grade dysplastic cells to each of the normal cell types. Raman spectra were recorded from single exfoliated cells and subjected to multivariate statistical analysis. The study demonstrated that Raman spectroscopy can identify biochemical signatures associated with the most common cell types seen in liquid-based cytology samples; superficial, intermediate, and parabasal cells. In addition, biochemical changes associated with high-grade dysplasia could be identified suggesting that Raman spectroscopy could be used to aid current cervical screening tests.

Remote Raman Efficiencies and Cross-Sections of Organic and Inorganic Chemicals

We determined Raman cross-sections of various organic liquids and inorganic polyatomic ions in aqueous solutions with a 532 nm pulsed laser using remote Raman systems developed at the University of Hawaii. Using a calibrated integrating sphere as a light source, we converted the intensity counts in the spectrum of the light from the integrating sphere measured with UH remote Raman instrument to spectral radiance. From these data, a response function of the remote Raman instrument was obtained. With the intensity-calibrated instrument, we collected remote Raman data from a standard 1 mm path length fused silica spectrophotometer cell filled with cyclohexane. The measured value of the differential Raman cross-section for the 801 cm^-1 vibrational mode of cyclohexane is 4.55 × 10^-30 cm² sr^-1 molecule^-1 when excited by a 532 nm laser, in good agreement with the values reported in the literature. Using the measured cyclohexane Raman cross-section as a reference and relative Raman mode intensities of the various ions and organic liquids, we calculated the Raman cross-sections of the strongest Raman lines of nitrate, sulfate, carbonate, phosphate ions, and organic liquids by maintaining same experimental conditions for remote Raman detection. These relative Raman cross-section values will be useful for estimating detection capabilities of remote Raman systems for planetary exploration.

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.

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.

Detection of Vero Cells Infected with Herpes Simplex Types 1 and 2 and Varicella Zoster Viruses Using Raman Spectroscopy and Advanced Statistical Methods

Of the eight members of the herpes family of viruses, HSV1, HSV2, and varicella zoster are the most common and are mainly involved in cutaneous disorders. These viruses usually are not life-threatening, but in some cases they might cause serious infections to the eyes and the brain that can lead to blindness and possibly death. An effective drug (acyclovir and its derivatives) is available against these viruses. Therefore, early detection and identification of these viral infections is highly important for an effective treatment. Raman spectroscopy, which has been widely used in the past years in medicine and biology, was used as a powerful spectroscopic tool for the detection and identification of these viral infections in cell culture, due to its sensitivity, rapidity and reliability. Our results showed that it was possible to differentiate, with a 97% identification success rate, the uninfected Vero cells that served as a control, from the Vero cells that were infected with HSV-1, HSV-2, and VZV. For that, linear discriminant analysis (LDA) was performed on the Raman spectra after principal component analysis (PCA) with a leave one out (LOO) approach. Raman spectroscopy in tandem with PCA and LDA enable to differentiate among the different herpes viral infections of Vero cells in time span of few minutes with high accuracy rate. Understanding cell molecular changes due to herpes viral infections using Raman spectroscopy may help in early detection and effective treatment.

Diagnosis of early-stage esophageal cancer by Raman spectroscopy and chemometric techniques

Esophageal cancer is a disease with high mortality. In order to improve the 5 year survival rate after cancer treatment, it is important to develop a method for early detection of the cancer and for therapy support. There is increasing evidence that Raman spectroscopy, in combination with chemometric analysis, is a powerful technique for discriminating pre-cancerous and cancerous biochemical changes. In the present study, we used Raman spectroscopy to examine early-stage (stages 0 and I) esophageal cancer samples ex vivo. Comparison between the Raman spectra of cancerous and normal samples using a t-test showed decreased concentrations of glycogen, collagen, and tryptophan in cancerous tissue. Partial least squares regression (PLSR) analysis and self-organization maps (SOMs) discriminated the datasets of cancerous and normal samples into two groups, but there was a relatively large overlap between them. Linear discriminant analysis (LDA) based on Raman bands found in the t-test was able to predict the tissue types with 81.0% sensitivity and 94.0% specificity.

Preliminary study of differentiating smears from cancerous and non-cancerous nasopharyngeal tissue using confocal Raman spectroscopy

PURPOSE

Current practice for diagnosing nasopharyngeal carcinoma (NPC) is based on invasive tissue biopsy. This study aims to explore the feasibility of using Raman spectroscopy to differentiate cancerous and non-cancerous nasopharyngeal tissue smears, expecting to realize minimal invasive diagnosis using smears from in vivo mucosa tissue by Raman spectroscopy.

METHODS

Biopsy tissue smears were acquired from 74 patients with pathologically diagnosed nasopharyngeal diseases and measured using confocal Raman spectroscopy.

RESULTS

Both fingerprint region and high wavenumber Raman spectra were acquired with distinguish features. Multivariate statistical analysis was used to differentiate cancerous and non-cancerous groups, achieving a diagnostic sensitivity of 87.2 and specificity of 85.7 % for differentiating NPC from nasopharyngeal non-cancerous smears.

CONCLUSIONS

This work indicates that the method has a unique advantage in microanalysis for tissue smears which may provide a promising minimal invasive (or noninvasive) diagnosing tool for cancer diagnosis.

Sandwich-like mesoporous silica flakes for anticancer drug transport-Synthesis, characterization and kinetics release study

In this paper, we present the technology of synthesis, characterization and release kinetics of anticancer drug molecules from sandwich-like mesoporous silica nanoflakes. Mesoporous silica nanoflakes are a very attractive material due to their versatility, low cytotoxicity, large surface area, high pore volume and unique feature of containing parallel pores openon both sides. Nanosilica flakes were prepared through the formation of a mesoporous silica layer on a graphene oxide surface. After graphene oxide removal, the silica nanostructures were filled by an anticancer drug-methotrexate. Release kinetics studies were performed in different temperatures, imitating the conditions in living organisms. Release data was analyzed using the zero-order model, first-order model, Higuchi model and Korsmeyer-Peppas model. The optical properties of samples, and the kinetics of drug release from the nanostructure, were examined by UV-vis spectrophotometer. Data obtained from long term studies showed that the system can serve as an anticancer drug carrier system, since a significant amount of methotrexate was loaded to the material and released. The mechanism of MTX release from mesoporous silica nanoflakes appeared to be a parallel processes of diffusion through water-filled mesopores and degradation of the mSiO2 matrix. Physical and chemical characterization was undertaken by transmission electron microscopy (TEM) and X-ray dispersion spectroscopy (EDX). The specific surface area of the samples was measured through the adsorption of N2 isotherm, interpreted with the Brunauer-Emmett-Teller model (BET). TGA and UV-vis analyses were conducted in order to estimate the amount of the released drug.

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.

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.