Diagnostic applications of Raman spectroscopy

Surface-Enhanced Raman Spectroscopy and Electrochemistry: The Ultimate Chemical Sensing and Manipulation Combination

One of the lessons we learned from the COVID-19 pandemic is that the need for ultrasensitive detection systems is now more critical than ever. While sensors' sensitivity, portability, selectivity, and low cost are crucial, new ways to couple synergistic methods enable the highest performance levels. This review article critically discusses the synergetic combinations of optical and electrochemical methods. We also discuss three key application fields-energy, biomedicine, and environment. Finally, we selected the most promising approaches and examples, the open challenges in sensing, and ways to overcome them. We expect this work to set a clear reference for developing and understanding strategies, pros and cons of different combinations of electrochemical and optical sensors integrated into a single device.

Fluorescence in depth: integration of spectroscopy and imaging with Raman, IR, and CD for advanced research

Fluorescence spectroscopy serves as a vital technique for studying the interaction between light and fluorescent molecules. It encompasses a range of methods, each presenting unique advantages and applications. This technique finds utility in various chemical studies. This review discusses Fluorescence spectroscopy, its branches such as Time-Resolved Fluorescence Spectroscopy (TRFS) and Fluorescence Lifetime Imaging Microscopy (FLIM), and their integration with other spectroscopic methods, including Raman, Infrared (IR), and Circular Dichroism (CD) spectroscopies. By delving into these methods, we aim to provide a comprehensive understanding of the capabilities and significance of fluorescence spectroscopy in scientific research, highlighting its diverse applications and the enhanced understanding it brings when combined with other spectroscopic methods. This review looks at each technique's unique features and applications. It discusses the prospects of their combined use in advancing scientific understanding and applications across various domains.

Sema-3E/PlexinD1 axis modulates dendritic cell phenotypes and functions: Current status and future implications

This comprehensive research review explores the complex interplay between the Sema-3E/PlexinD1 axis and dendritic cells (DCs), highlighting its critical role in immune modulation with implications for clinical application Critical regulators of immune responses Dendritic cells are central to adaptive immunity, and the Sema-3E /PlexinD1 axis emerges as a key modulator affecting their phenotypes and functions Review delineates the impact of this signaling axis on DC maturation, migration, antigen presentation, and cytokine production, unravels its multifaceted role in shaping the immune response. Recognizing the limitations and gaps in current knowledge, the study highlights the need for further studies to condition downstream signaling events and related information experienced by the Sema-3E/PlexinD1 axis emphasizes the clarity of the immune system. The review concludes by identifying opportunities for translation, focusing on therapeutic and diagnostic potential. It highlights the importance of collaborative, interdisciplinary efforts to address the challenges and harness the therapeutic and pathological potential of targeting the Sema-3E/PlexinD1 axis, thus opening the way for transformative advances in immunology and clinical medicine.

Noninvasive evaluation of the skin barrier in reconstructed human epidermis using speckle analysis: Correlation with Raman microspectroscopy

BACKGROUND

Reconstructed epidermis models, obtained from 3D keratinocytes culture, have gained significant prominence as prototypes for safety and efficacy testing in skin research. To effectively evaluate these models, it is essential to perform molecular and functional characterization. The skin's barrier function is one of the essential aspects of the epidermis that needs to be assessed. A noninvasive method is thus required for the evaluation of the skin barrier in these models. With this perspective, the aim of this feasibility study is to apply the speckle technique for the assessment of the skin barrier in the Reconstructed Human Epidermis (RHE).

MATERIALS AND METHODS

Speckle analysis as well as Raman microspectroscopy were performed on RHE samples at two maturation days, D17 and D20.

RESULTS

Between D17 and D20, our study showed an increase in various Raman parameters, including stratum corneum percentage, lateral lipid packing, lipid-to-protein ratio, and protein secondary structure. Furthermore, the degree of light polarization and the speckle grain size also increased over this period.

CONCLUSION

The speckle technique proved to be effective for evaluating the skin barrier in Reconstructed Human Epidermis (RHE) models. Comparison with Raman validates this approach and provides comprehensive molecular and functional characterization of reconstructive skin models.

Species identification of adult ixodid ticks by Raman spectroscopy of their feces

BACKGROUND

Ticks and tick-borne diseases pose significant challenges to cattle production, thus the species identification of ticks and knowledge on their presence, abundance, and dispersal are necessary for the development of effective control measures. The standard method of inspection for the presence of ticks is the visual and physical examination of restrained animals, but the limitations of human sight and touch can allow larval, nymphal, and unfed adult ticks to remain undetected due to their small size and site of attachment. However, Raman spectroscopy, an analytical tool widely used in agriculture and other sectors, shows promise for the identification of tick species in infested cattle. Raman spectroscopy is a non-invasive and efficient method that employs the interaction between molecules and light for the identification of the molecular constituents of specimens.

METHODS

Raman spectroscopy was employed to analyze the structure and composition of tick feces deposited on host skin and hair during blood-feeding. Feces of 12 species from a total of five genera and one subgenus of ixodid ticks were examined. Spectral data were subjected to partial least squares discriminant analysis, a machine-learning model. We also used Raman spectroscopy and the same analytical procedures to compare and evaluate feces of the horn fly Haematobia irritans after it fed on cattle.

RESULTS

Five genera and one sub-genus at overall true prediction rates ranging from 92.3 to 100% were identified from the Raman spectroscopy data of the tick feces. At the species level, Dermacentor albipictus, Dermacentor andersoni and Dermacentor variabilis at overall true prediction rates of 100, 99.3 and 100%, respectively, were identified. There were distinct differences between horn fly and tick feces with respect to blood and guanine vibrational frequencies. The overall true prediction rate for the separation of tick and horn fly feces was 98%.

CONCLUSIONS

Our findings highlight the utility of Raman spectroscopy for the reliable identification of tick species from their feces, and its potential application for the identification of ticks from infested cattle in the field.

Deep neural network: As the novel pipelines in multiple preprocessing for Raman spectroscopy

Raman spectroscopy is a kind of vibrational method that can rapidly and non-invasively gives chemical structural information with the Raman spectrometer. Despite its technical advantages, in practical application scenarios, Raman spectroscopy often suffers from interference, such as noises and baseline drifts, resulting in the inability to acquire high-quality Raman spectroscopy signals, which brings challenges to subsequent spectral analysis. The commonly applied spectral preprocessing methods, such as Savitzky-Golay smooth and wavelet transform, can only perform corresponding single-item processing and require manual intervention to carry out a series of tedious trial parameters. Especially, each scheme can only be used for a specific data set. In recent years, the development of deep neural networks has provided new solutions for intelligent preprocessing of spectral data. In this paper, we first creatively started from the basic mechanism of spectral signal generation and constructed a mathematical model of the Raman spectral signal. By counting the noise parameters of the real system, we generated a simulation dataset close to the output of the real system, which alleviated the dependence on data during deep learning training. Due to the powerful nonlinear fitting ability of the neural network, fully connected network model is constructed to complete the baseline estimation task simply and quickly. Then building the Unet model can effectively achieve spectral denoising, and combining it with baseline estimation can realize intelligent joint processing. Through the simulation dataset experiment, it is proved that compared with the classic method, the method proposed in this paper has obvious advantages, which can effectively improve the signal quality and further ensure the accuracy of the peak intensity. At the same time, when the proposed method is applied to the actual system, it also achieves excellent performance compared with the common method, which indirectly indicates the effectiveness of the Raman signal simulation model. The research presented in this paper offers a variety of efficient pipelines for the intelligent processing of Raman spectroscopy, which can adapt to the requirements of different tasks while providing a new idea for enhancing the quality of Raman spectroscopy signals.

Quantifying Efficiency of Remote Excitation for Surface-Enhanced Raman Spectroscopy in Molecular Junctions

Surface-enhanced Raman spectroscopy (SERS) is enabled by local surface plasmon resonances (LSPRs) in metallic nanogaps. When SERS is excited by direct illumination of the nanogap, the background heating of the lattice and electrons can prevent further manipulation of the molecules. To overcome this issue, we report SERS in electromigrated gold molecular junctions excited remotely: surface plasmon polaritons (SPPs) are excited at nearby gratings, propagate to the junction, and couple to the local nanogap plasmon modes. Like direct excitation, remote excitation of the nanogap can generate both SERS emission and an open-circuit photovoltage (OCPV). We compare the SERS intensity and the OCPV in both direct and remote illumination configurations. SERS spectra obtained by remote excitation are much more stable than those obtained through direct excitation when the photon count rates are comparable. By statistical analysis of 33 devices, the coupling efficiency of remote excitation is calculated to be around 10%, consistent with the simulated energy flow.

Prospects of Microfluidic Technology in Nucleic Acid Detection Approaches

Conventional diagnostic techniques are based on the utilization of analyte sampling, sensing and signaling on separate platforms for detection purposes, which must be integrated to a single step procedure in point of care (POC) testing devices. Due to the expeditious nature of microfluidic platforms, the trend has been shifted toward the implementation of these systems for the detection of analytes in biochemical, clinical and food technology. Microfluidic systems molded with substances such as polymers or glass offer the specific and sensitive detection of infectious and noninfectious diseases by providing innumerable benefits, including less cost, good biological affinity, strong capillary action and simple process of fabrication. In the case of nanosensors for nucleic acid detection, some challenges need to be addressed, such as cellular lysis, isolation and amplification of nucleic acid before its detection. To avoid the utilization of laborious steps for executing these processes, advances have been deployed in this perspective for on-chip sample preparation, amplification and detection by the introduction of an emerging field of modular microfluidics that has multiple advantages over integrated microfluidics. This review emphasizes the significance of microfluidic technology for the nucleic acid detection of infectious and non-infectious diseases. The implementation of isothermal amplification in conjunction with the lateral flow assay greatly increases the binding efficiency of nanoparticles and biomolecules and improves the limit of detection and sensitivity. Most importantly, the deployment of paper-based material made of cellulose reduces the overall cost. Microfluidic technology in nucleic acid testing has been discussed by explicating its applications in different fields. Next-generation diagnostic methods can be improved by using CRISPR/Cas technology in microfluidic systems. This review concludes with the comparison and future prospects of various microfluidic systems, detection methods and plasma separation techniques used in microfluidic devices.

The Use of Raman Spectroscopy to Monitor Changes in the Intensity of Ratio of Integral Unsaturated Bands in Bio-Greases

Bio-greases were developed on the basis of vegetable oil obtained from Crambe Abyssinic seeds. An important aspect of this research is to monitor changes in their quality taking place under the influence of external factors. Raman spectroscopy was used to identify changes taking place in the bio-lubricant under the influence of mechanical and thermal forces. The performed tests reflected the operating temperature and friction load that may occur during actual operating conditions for the lubricated friction systems. The Raman spectra provided information on qualitative changes in the structure of the tested bio-lubricants at the molecular level. The integral intensity of the bands used to assess the degree of lipid unsaturation was adopted as the evaluation criterion. The influence of the oxidation process under the PetroOxy and wear test conditions on changes in the structure of the bio-lubricants was assessed. Variation in the integral intensity of the bands (I1655/I1440) proves that the structure of vegetable lubricants changes under the influence of the tests performed. Thermal and mechanical forces influence, the bands originating in unsaturated and result in a decrease in the oxidation resistance of vegetable lubricants.

Properties and Characterization Techniques of Graphene Modified Asphalt Binders

Graphene is a carbon-based nanomaterial used in various industries to improve the performance of hundreds of materials. For instance, graphene-like materials have been employed as asphalt binder modifying agents in pavement engineering. In the literature, it has been reported that (in comparison to an unmodified binder) the Graphene Modified Asphalt Binders (GMABs) exhibit an enhanced performance grade, a lower thermal susceptibility, a higher fatigue life, and a decreased accumulation of permanent deformations. Nonetheless, although GMABs stand out significantly from traditional alternatives, there is still no consensus on their behavior regarding chemical, rheological, microstructural, morphological, thermogravimetric, and surface topography properties. Therefore, this research conducted a literature review on the properties and advanced characterization techniques of GMABs. Thus, the laboratory protocols covered by this manuscript are atomic force microscopy, differential scanning calorimetry, dynamic shear rheometer, elemental analysis, Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscopy, thermogravimetric analysis, X-ray diffraction, and X-ray photoelectron spectroscopy. Consequently, the main contribution of this investigation to the state-of-the-art is the identification of the prominent trends and gaps in the current state of knowledge.

Raman spectroscopy as a promising diagnostic method for rheumatoid arthritis

Background: Diagnosis of rheumatoid arthritis (RA) basically relies on clinical symptoms and autoantibodies, especially anti-citrullinated protein antibodies (ACPAs) and rheumatoid factor (RF). However, the lack of autoantibodies is still a dilemma clinically in seronegative RA, especially in the early stage of the disease. This study aimed to provide a unique disease fingerprint with high diagnostic value to discriminate RA based on Raman spectroscopy. Methods: Raman spectroscopy provides a repertoire of biomolecules in serum from RA. Multivariate dimension-reducing methods and machine-learning algorithms were exploited to reveal the intrinsic differences and the potential discrimination power. The underlying differential biomolecules were retrieved by the assignment of Raman peaks. Moreover, the correlations between the spectral differences and RA patient's clinical and immunological manifestations were also analyzed. Results: RA patients exhibited unique Raman spectra characterized by biomolecular alterations during the disease progression. The discrimination power yielded 97.3% sensitivity and 94.8% specificity for RA diagnosis. In the recognition of ACPA-negative RA, the sensitivity and specificity also reached 95.6% and 92.8%, respectively. In particular, the differential Raman spectrum peaks of RA patients mainly represented lipids, amino acids, glycogen, and fatty acids. Further analysis showed that the different serum Raman spectra correlated with the clinical features of RA, including disease duration, RF, anticyclic citrullinated peptide antibodies (anti-CCPs), IgA, IgM, IgG, tender joint count, and swollen joint count (|rs| = 0.15-0.52, p < 0.05). Conclusions: Raman spectroscopy was revealed to be a promising diagnostic method for RA, especially for ACPA-negative patients.

Review of Recent Modern Analytical Technology Combined with Chemometrics Approach Researches on Mushroom Discrimination and Evaluation

Mushroom is a macrofungus with precious fruiting body, as a food, a tonic, and a medicine, human have discovered and used mushrooms for thousands of years. Nowadays, mushroom is also a "super food" recommended by the World Health Organization (WHO) and Food and Agriculture Organization (FAO), and favored by consumers. Discrimination of mushroom including species, geographic origin, storage time, etc., is an important prerequisite to ensure their edible safety and commodity quality. Moreover, the effective evaluation of its chemical composition can help us better understand the nutritional properties of mushrooms. Modern analytical technologies such as chromatography, spectroscopy and mass spectrometry, etc., are widely used in the discrimination and evaluation researches of mushrooms, and chemometrics is an effective means of scientifically processing the multidimensional information hidden in these analytical technologies. This review will outline the latest applications of modern analytical technology combined with chemometrics in qualitative and quantitative analysis and quality control of mushrooms in recent years. Briefly describe the basic principles of these technologies, and the analytical processes of common chemometrics in mushroom researches will be summarized. Finally, the limitations and application prospects of chromatography, spectroscopy and mass spectrometry technology are discussed in mushroom quality control and evaluation.

Chemical Sensor Nanotechnology in Pharmaceutical Drug Research

The increase in demand for pharmaceutical treatments due to pandemic-related illnesses has created a need for improved quality control in drug manufacturing. Understanding the physical, biological, and chemical properties of APIs is an important area of health-related research. As such, research into enhanced chemical sensing and analysis of pharmaceutical ingredients (APIs) for drug development, delivery and monitoring has become immensely popular in the nanotechnology space. Nanomaterial-based chemical sensors have been used to detect and analyze APIs related to the treatment of various illnesses pre and post administration. Furthermore, electrical and optical techniques are often coupled with nano-chemical sensors to produce data for various applications which relate to the efficiencies of the APIs. In this review, we focus on the latest nanotechnology applied to probing the chemical and biochemical properties of pharmaceutical drugs, placing specific interest on several types of nanomaterial-based chemical sensors, their characteristics, detection methods, and applications. This study offers insight into the progress in drug development and monitoring research for designing improved quality control methods for pharmaceutical and health-related research.

Prediction of the postoperative prognosis in patients with non-muscle-invasive bladder cancer based on preoperative serum surface-enhanced Raman spectroscopy

Non-muscle-invasive bladder cancer (NMIBC) is a common urinary tumor and has a high recurrence rate due to improper or inadequate conservative treatment. The early and accurate prediction of its recurrence can be helpful to implement timely and rational treatment. In this study, we explored a preoperative serum surface-enhanced Raman spectroscopy based prognostic protocol to predict the postoperative prognosis for NMIBC patients at the time even before treatment. The biochemical analysis results suggested that biomolecules related to DNA/RNA, protein substances, trehalose and collagen are expected to be potential prognostic markers, which further compared with several routine clinically used immunohistochemistry expressions with prognostic values. In addition, high prognostic accuracies of 87.01% and 89.47% were achieved by using the proposed prognostic models to predict the future postoperative recurrence and recurrent type, respectively. Therefore, we believe that the proposed method has great potential in the early and accurate prediction of postoperative prognosis in patients with NMIBC, which is with important clinical significance to guide the treatment and further improve the recurrence rate and survival time.

A Narrative Review of Recent Advances in Rapid Assessment of Anthocyanins in Agricultural and Food Products

Anthocyanins (ACNs) are plant polyphenols that have received increased attention recently mainly due to their potential health benefits and applications as functional food ingredients. This has also created an interest in the development and validation of several non-destructive techniques of ACN assessments in several food samples. Non-destructive and conventional techniques play an important role in the assessment of ACNs in agricultural and food products. Although conventional methods appear to be more accurate and specific in their analysis, they are also associated with higher costs, the destruction of samples, time-consuming, and require specialized laboratory equipment. In this review article, we present the latest findings relating to the use of several spectroscopic techniques (fluorescence, Raman, Nuclear magnetic resonance spectroscopy, Fourier-transform infrared spectroscopy, and near-infrared spectroscopy), hyperspectral imaging, chemometric-based machine learning, and artificial intelligence applications for assessing the ACN content in agricultural and food products. Furthermore, we also propose technical and future advancements of the established techniques with the need for further developments and technique amalgamations.

Preliminary study for the application of Raman spectroscopy for the identification of Leishmania infected dogs

Raman spectroscopy is a rapid qualitative and quantitative technique that allows the simultaneous determination of several components in biological fluids. This methodology concerns an alternative technique to distinguish between non-healthy and healthy subjects. Leishmaniasis is a zoonosis of world interest, the most important agent is L. infantum. Dogs are the principal reservoirs affected by a broad spectrum of clinical features. During a clinical exam, blood samples were collected in tubes without anticoagulants, from twenty two dogs. One aliquot was used for serological test for Leishmaniasis, one aliquot was subjected to the Raman spectroscopic analysis. Animals were divided into two groups of equal subjects, Leishmania group (LG) constituted by infected dogs, and control group (CG) constituted by healthy dogs. The acquired spectra were different in the region 1200-1370 cm^-1, in which it is possible to distinguish the amide III vibration (~ 1300 cm^-1). In LG, an evident shift to the shortwave region is observed in spectral frequencies of the band centered at ~ 1250 cm^-1. Our results distinguished between LD group and CG. Further studies are necessary to exclude the effect of metabolic modification due to disease on the recorded spectra changes and to consolidate the achievability of Raman spectroscopy as rapid and less expensive diagnosis of Leishmaniasis.

A Molecular Study of Aspirin and Tenofovir Using Gold/Dextran Nanocomposites and Surface-Enhanced Raman Spectroscopy

In this study, we show how surface enhanced Raman spectroscopy (SERS) can be used to monitor the molecular behaviour of aspirin and tenofovir as a means of screening medication for quality control purposes. Gold-coated slides combined with gold/dextran nanoaggregates were used to provide signal enhancement of the drugs using SERS. Aspirin (10% w/v) and tenofovir (20% v/v) were analysed in the presence of the nanomaterials to determine trends in molecular response to changes in gold/dextran concentrations. Qualitative analysis of the functional groups showed specific trends where the peak area increased with polarizability, electron density and decreased atomic radii. Steric hinderance effects also affected the trends in peak area due to the amount of gold/dextran nanoparticles in solution. Statistical analysis provided accurate and precise linear relationships (R² = 0.99) for the ester and adenine functional groups of aspirin and tenofovir, respectively. From the above findings, the combined use of gold nano-scaffolds and gold/dextran nanomaterials amplified the Raman signal from the drugs to allow for systematic evaluation of their molecular properties. Although more experiments to correlate the findings are still needed, this SERS approach shows great potential as a screening method in the quality control of medications.

Real-time Raman analysis of the hydrolysis of formaldehyde oligomers for enhanced collagen fixation

Formaldehyde (FA) is widely applied as a fixative for proteins such as collagen. Current studies have confirmed that the reversible oligomer-to-monomer equilibrium of FA in aqueous solution and the proportion of FA monomer is a significant factor affecting tissue fixation. Since the hydrolysis of FA oligomers is a dynamic process affected jointly by different factors, its real time monitoring has proved to be challenging. In this work, by utilizing the well-established Raman technique as an analytical platform, we identified the factors affecting the hydrolysis of FA oligomers by rationally examining the ν_s (OCO) and ν_as (OCO) modes with varying conditions, such as time, pH, temperature, and FA concentration. The optimized conditions of the highest hydrolysis rate of oligomers into monomers for fixation on collagen and tissues have been found to be relatively low FA concentration (≤5%) in phosphate-buffered saline at pH 9.0 in room temperature. In order to compare the fixation quality of the optimized conditions to that of the conventional conditions used by current medical practices (4% FA concentration in tap water under room temperature), Raman spectroscopy and chemical derivatization methods with o-phthalaldehyde and fluorescent probe FAP-1 have been investigated, and our results revealed that the FA molecules under our optimized conditions have reacted with at least 15% more amino groups within collagen compared to those under the conventional conditions mentioned above. This study provides direct evidence of the FA equilibrium in solution by Raman spectroscopy, which could be applied for the optimal use of FA in medicine, even at an industrial scale.

Identification and assessment of pulmonary Cryptococcus neoformans infection by blood serum surface-enhanced Raman spectroscopy

Cryptococcus neoformans (C. neoformans) is a causative agent for acute pulmonary infection, which can further develop to lethal meningoencephalitis if untreated. The meningoencephalitis infection can be prevented, if timely treatment on pulmonary cryptococcal infection can be implemented based on its early diagnosis and accurate assessment. In this study, blood serum surface-enhanced Raman spectroscopy (SERS) method was investigated on identification and assessment of pulmonary C. neoformans infection. The serum SERS measurements were collected from the mice infected with C. neoformans and the healthy mice, in which the infected mice were further divided into four subgroups according to the duration of infection. Based on those SRES measurements, biochemical differences were analyzed among those different groups to investigate the potential biomarkers for identifying and assessing the pulmonary C. neoformans infection. Furthermore, partial least square (PLS) analysis followed by linear discriminant analysis (LDA) model was employed to identify pulmonary cryptococcal infection and to assess the degrees of infection with the accuracies of 96.7% and 85.3%, respectively. Therefore, our study has demonstrated the great clinical potential of using serum SERS technique for an accurate identification and assessment of pulmonary cryptococcal infection.

Surface-enhanced Raman spectroscopy for analysis of PCR products of viral RNA of hepatitis C patients

In the current study, for a qualitative and quantitative study of Polymerase Chain Reaction (PCR) products of viral RNA of Hepatitis C virus (HCV) infection, surface-enhanced Raman spectroscopy (SERS) methodology has been developed. SERS was used to identify the spectral features associated with the PCR products of viral RNA of Hepatitis C in various samples of HCV-infected patients with predetermined viral loads. The measurements for SERS were performed on 30 samples of PCR products, which included three PCR products of RNA of healthy individuals, six negative controls, and twenty-one HCV positive samples of varying viral loads (VLs) using Silver nanoparticles (Ag NPs) as a SERS substrates. Additionally, on SERS spectral data, the multivariate data analysis methods including Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR) were also carried out which help to illustrate the diagnostic capabilities of this method. The PLSR model is designed to predict HCV viral loads based on biochemical changes observed as SERS spectral features which can be associated directly with HCV RNA. Several SERS characteristic features are observed in the RNA of HCV which are not detected in the spectra of healthy RNA/controls. PCA is found helpful to differentiate the SERS spectral data sets of HCV RNA samples from healthy and negative controls. The PLSR model is found to be 99% accurate in predicting VLs of HCV RNA samples of unknown samples based on SERS spectral changes associated with the Hepatitis C development.

Tracking of the biochemical changes upon pleomorphic adenoma progression using vibrational microspectroscopy

Head and neck tumors can be very challenging to treat because of the risk of problems or complications after surgery. Therefore, prompt and accurate diagnosis is extremely important to drive appropriate treatment decisions, which may reduce the chance of recurrence. This paper presents the original research exploring the feasibility of Fourier transform infrared (FT-IR) and Raman spectroscopy (RS) methods to investigate biochemical alterations upon the development of the pleomorphic adenoma. Principal component analysis (PCA) was used for a detailed assessment of the observed changes and to determine the spectroscopic basis for salivary gland neoplastic pathogenesis. It is implied that within the healthy margin, as opposed to the tumoral tissue, there are parts that differ significantly in lipid content. This observation shed new light on the crucial role of lipids in tissue physiology and tumorigenesis. Thus, a novel approach that eliminates the influence of lipids on the elucidation of biochemical changes is proposed. The performed analysis suggests that the highly heterogeneous healthy margin contains more unsaturated triacylglycerols, while the tumoral section is rich in proteins. The difference in protein content was also observed for these two tissue types, i.e. the healthy tissue possesses more proteins in the anti-parallel β-sheet conformation, whereas the tumoral tissue is dominated by proteins rich in unordered random coils. Furthermore, the pathogenic tissue shows a higher content of carbohydrates and reveals noticeable differences in nucleic acid content. Finally, FT-IR and Raman spectroscopy methods were proposed as very promising methods in the discrimination of tumoral and healthy tissues of the salivary gland.

Novel Insights Into Tissue-Specific Biochemical Alterations in Pediatric Eosinophilic Esophagitis Using Raman Spectroscopy

INTRODUCTION:

Elucidating esophageal biochemical composition in eosinophilic esophagitis (EoE) can offer novel insights into its pathogenesis, which remains unclear. Using Raman spectroscopy, we profiled and compared the biochemical composition of esophageal samples obtained from children with active (aEoE) and inactive EoE (iEoE) with non-EoE controls, examined the relationship between spectral markers and validated EoE activity indices.

METHODS:

In vitro Raman spectra from children with aEoE (n = 8; spectra = 51) and iEoE (n = 6; spectra = 48) and from non-EoE controls (n = 10; spectra = 75) were acquired. Mann-Whitney test was used to assess the differences in their Raman intensities (median [interquartile range]) and identify spectral markers. Spearman correlation was used to evaluate the relationship between spectral markers and endoscopic and histologic activity indices.

RESULTS:

Raman peaks attributable to glycogen content (936/1,449 cm⁻¹) was lower in children with aEoE (0.20 [0.18–0.21]) compared with that in non-EoE controls (0.24 [0.23–0.29]). Raman intensity of proteins (1,660/1,209 cm⁻¹) was higher in children with aEoE compared with that in non-EoE controls (3.20 [3.07–3.50] vs 2.91 [2.59–3.05]; P = 0.01), whereas that of lipids (1,301/1,260 cm⁻¹) was higher in children with iEoE (1.56 [1.49–1.63]) compared with children with aEoE (1.40 [1.30–1.48]; P = 0.02). Raman peaks attributable to glycogen and lipid inversely correlated with eosinophilic inflammation and basal zone hyperplasia. Raman mapping substantiated our findings.

DISCUSSION:

This is the first study to identify spectral traits of the esophageal samples related to EoE activity and tissue pathology and to profile tissue-level biochemical composition associated with pediatric EoE. Future research to determine the role of these biochemical alterations in development and clinical course of EoE can advance our understanding of EoE pathobiology.

Recent Advances in CRP Biosensor Based on Electrical, Electrochemical and Optical Methods

C-reactive protein (CRP) is an acute-phase reactive protein that appears in the bloodstream in response to inflammatory cytokines such as interleukin-6 produced by adipocytes and macrophages during the acute phase of the inflammatory/infectious process. CRP measurement is widely used as a representative acute and chronic inflammatory disease marker. With the development of diagnostic techniques measuring CRP more precisely than before, CRP is being used not only as a traditional biomarker but also as a biomarker for various diseases. The existing commercialized CRP assays are dominated by enzyme-linked immunosorbent assay (ELISA). ELISA has high selectivity and sensitivity, but its limitations include requiring complex analytic processes, long analysis times, and professional manpower. To overcome these problems, nanobiotechnology is able to provide alternative diagnostic tools. By introducing the nanobio hybrid material to the CRP biosensors, CRP can be measured more quickly and accurately, and highly sensitive biosensors can be used as portable devices. In this review, we discuss the recent advancements in electrochemical, electricity, and spectroscopy-based CRP biosensors composed of biomaterial and nanomaterial hybrids.

Point-of-care diagnostics for infectious diseases: From methods to devices

The current widespread of COVID-19 all over the world, which is caused by SARS-CoV-2 virus, has again emphasized the importance of development of point-of-care (POC) diagnostics for timely prevention and control of the pandemic. Compared with labor- and time-consuming traditional diagnostic methods, POC diagnostics exhibit several advantages such as faster diagnostic speed, better sensitivity and specificity, lower cost, higher efficiency and ability of on-site detection. To achieve POC diagnostics, developing POC detection methods and correlated POC devices is the key and should be given top priority. The fast development of microfluidics, micro electro-mechanical systems (MEMS) technology, nanotechnology and materials science, have benefited the production of a series of portable, miniaturized, low cost and highly integrated POC devices for POC diagnostics of various infectious diseases. In this review, various POC detection methods for the diagnosis of infectious diseases, including electrochemical biosensors, fluorescence biosensors, surface-enhanced Raman scattering (SERS)-based biosensors, colorimetric biosensors, chemiluminiscence biosensors, surface plasmon resonance (SPR)-based biosensors, and magnetic biosensors, were first summarized. Then, recent progresses in the development of POC devices including lab-on-a-chip (LOC) devices, lab-on-a-disc (LOAD) devices, microfluidic paper-based analytical devices (μPADs), lateral flow devices, miniaturized PCR devices, and isothermal nucleic acid amplification (INAA) devices, were systematically discussed. Finally, the challenges and future perspectives for the design and development of POC detection methods and correlated devices were presented. The ultimate goal of this review is to provide new insights and directions for the future development of POC diagnostics for the management of infectious diseases and contribute to the prevention and control of infectious pandemics like COVID-19.

Diagnostic accuracy of Raman spectroscopy for prostate cancer: a systematic review and meta-analysis

Background

Although various studies have been conducted to demonstrate the possibility of Raman spectroscopy (RS) as a diagnostic tool for prostate cancer (PC), it is difficult to use it in the real clinical area because of imitations in various research processes. Therefore, we did a systematic review and meta-analysis about the accuracy in diagnostic use of RS for PC.

Methods

A literature search was done using PubMed, Embase, and Cochrane library databases in March 2019 to analyze the accuracy of RS for diagnosis of PC. The accuracy of RS for diagnosis of PC was evaluated by means of pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC).

Results

Five studies were included for qualitative analysis by screening the remaining articles according to the inclusion and exclusion criteria by means of a systematic review. The pooled sensitivity and specificity of RS were 0.89 (95% CI: 0.87-0.91) and 0.91 (95% CI: 0.89-0.93), respectively. The overall PLR and NLR were 9.12 (95% CI: 4.15-20.08) and 0.14 (95% CI: 0.07-0.29), respectively. The DOR of RS demonstrated high accuracy (73.32; 95% CI: 18.43-291.73). The area under the curves (AUCs) of SROC curves was 0.93.

Conclusions

RS is an optical diagnostic method with high potential for diagnosis and grading of PC and has advantages of real-time and convenient use. In order to consider real-time use of RS in an actual clinical setting, more studies for standardization and generalization of RS performance and analytical method must be conducted.

Synergy Effect of Combined Near and Mid-Infrared Fibre Spectroscopy for Diagnostics of Abdominal Cancer

Cancers of the abdominal cavity comprise one of the most prevalent forms of cancers, with the highest contribution from colon and rectal cancers (12% of the human population), followed by stomach cancers (4%). Surgery, as the preferred choice of treatment, includes the selection of adequate resection margins to avoid local recurrences due to minimal residual disease. The presence of functionally vital structures can complicate the choice of resection margins. Spectral analysis of tissue samples in combination with chemometric models constitutes a promising approach for more efficient and precise tumour margin identification. Additionally, this technique provides a real-time tumour identification approach not only for intraoperative application but also during endoscopic diagnosis of tumours in hollow organs. The combination of near-infrared and mid-infrared spectroscopy has advantages compared to individual methods for the clinical implementation of this technique as a diagnostic tool.

A novel method for identifying and distinguishing Cryptococcus neoformans and Cryptococcus gattii by surface-enhanced Raman scattering using positively charged silver nanoparticles

There are approximately 1 million cryptococcal infections per year among HIV+ individuals, resulting in nearly 625,000 deaths. Cryptococcus neoformans and Cryptococcus gattii are the two most common species that cause human cryptococcosis. These two species of Cryptococcus have differences in pathogenicity, diagnosis, and treatment. Cryptococcal infections are usually difficult to identify because of their slow growth in vitro. In addition, the long detection cycle of Cryptococcus in clinical specimens makes the diagnosis of Cryptococcal infections difficult. Here, we used positively charged silver nanoparticles (AgNPs⁺) as a substrate to distinguish between C. neoformans and C. gattii in clinical specimens directly via surface-enhanced Raman scattering (SERS) and spectral analysis. The AgNPs⁺ self-assembled on the surface of the fungal cell wall via electrostatic aggregation, leading to enhanced SERS signals that were better than the standard substrate negatively charged silver nanoparticles (AgNPs). The SERS spectra could also be used as a sample database in the multivariate analysis via orthogonal partial least-squares discriminant analysis. This novel SERS detection method can clearly distinguish between the two Cryptococcus species using principal component analysis. The accuracy of the training data and test data was 100% after a tenfold crossover validation.

Construction of Raman spectroscopic fingerprints for the detection of Fusarium wilt of banana in Taiwan

Banana (Musa sp.) is cultivated worldwide and is one of the most popular fruits. The soil-borne fungal disease Fusarium wilt of banana (FWB), commonly known as Panama disease, is caused by Fusarium oxysporum f. sp. cubense (Foc) and is a highly lethal vascular fungal disease in banana plants. Raman spectroscopy, an emerging laser-based technology based on Raman scattering, has been used for the qualitative characterization of biological tissues such as foodborne pathogens, cancer cells, and melamine. In this study, we describe a Raman spectroscopic technique that could potentially be used as a method for diagnosing FWB. To that end, the Raman fingerprints of Foc (including mycelia and conidia) and Foc-infected banana pseudostems with varying levels of symptoms were determined. Our results showed that eight, eleven, and eleven characteristic surface-enhanced Raman spectroscopy peaks were observed in the mycelia, microconidia, and macroconidia of Foc, respectively. In addition, we constructed the Raman spectroscopic fingerprints of banana pseudostem samples with varying levels of symptoms in order to be able to differentiate Foc-infected bananas from healthy bananas. The rate at which FWB was detected in asymptomatic Foc-infected samples by using the spectral method was 76.2%, which was comparable to the rates previously reported for other FWB detection methods based on real-time PCR assays, suggesting that the spectral method described herein could potentially serve as an alternative tool for detecting FWB in fields. As such, we hope that the developed spectral method will open up new possibilities for the on-site diagnosis of FWB.

Surface-enhanced Raman spectroscopy (SERS) investigations of saliva for oral cancer diagnosis

Saliva could be an optimal sample for non-invasive cancer detection, as it contains plenty of proteins and metabolites which can reflect the health status of an individual. Moreover, pairing it with high-sensitivity, label-free detection techniques could prove successful for early cancer diagnosis. In this study, we explore the enhancement of salivary characteristic Raman bands by using label-free, ultrasensitive surface-enhanced Raman scattering (SERS) based on gold nanoparticles. SERS maps were acquired from dry samples of saliva supernatant mixed with Au colloidal nanoparticles, which was then pipetted on clean glass slides. The SERS spectra presented a high variability of signal intensities and frequency shifts. However, several reproducible SERS spectra showing well-resolved bands were obtained at certain locations on the maps, where Au nanoparticles clustered together during the air-drying. The healthy and oral cancer saliva could be differentiated using principal components analysis based on several SERS bands assigned mainly to amino acids and proteins. Moreover, thiocyanate Raman modes were detected in saliva samples of both smoking and non-smoking volunteers and cancer patients. The analysis indicated that the cancer group displayed an overall higher level of the 2126 cm^-1 band area assigned to C-N stretching vibrations of thiocyanate.

A facile seed growth method to prepare stable Ag@ZrO2 core-shell SERS substrate with high stability in extreme environments

A stable substrate is extraordinarily important for the trace detection of Surface Enhanced Raman Scattering technique. We have designed in this paper a simple seed growth method to prepare Ag@ZrO₂ core-shell nanoparticles as well as regulate the core-shell ratio by adjusted concentration of zirconium propoxides added. The shell thickness effect and spacing on SERS activities have been simulated in different finite time domains, which goes perfectly with those previous experiment results. With Ag@ZrO₂ core-shell nanoparticles adopted as the SERS substrate and R6G as molecular probe, the detection range could reach as great as 10^-8 M. The regression model, obtained through principal component analysis, is adopted for some rapid and precise detection; and the determination coefficient (R²) is going up to 0.9743, proving that the SERS substrate we have prepared has extremely high detection accuracy. To explore the stability of core-shell nanoparticles, we have taken both two different cases of strong acid solution as well as strong alkali solution for the core-shell nanoparticle etching, and this is how a SERS test could be carried out. These experimental results have indicated that the outer zirconia layer could keep the silver surface from oxidation and its stability is ensured, quite crucial for the applied SERS.

A Tunable Freeform-Segmented Reflector in a Microfluidic System for Conventional and Surface-Enhanced Raman Spectroscopy

We present a freeform-segmented reflector-based microfluidic system for conventional Raman and Surface-Enhanced Raman Scattering (SERS) analysis. The segmented reflector is directly designed by a numerical approach. The polymer-based Raman system strongly suppresses the undesirable background because it enables confocal detection of Raman scattering through the combination of a freeform reflector and a microfluidic chip. We perform systematic simulations using non-sequential ray tracing with the Henyey-Greenstein model to assess the Raman scattering behavior of the substance under test. We fabricate the freeform reflector and the microfluidic chip by means of ultra-precision diamond turning and laser cutting respectively. We demonstrate the confocal behavior by measuring the Raman spectrum of ethanol. Besides, we calibrate the setup by performing Raman measurements on urea and potassium nitrate solutions with different concentrations. The detection limit of our microfluidic system is approximately 20 mM according to the experiment. Finally, we implement a SERS microfluidic chip and discriminate 100 µM urea and potassium nitrate solutions.

Raman spectroscopy links differentiating osteoblast matrix signatures to pro-angiogenic potential

Mineralization of bone is achieved by the sequential maturation of the immature amorphous calcium phase to mature hydroxyapatite (HA) and is central in the process of bone development and repair. To study normal and dysregulated mineralization in vitro, substrates are often coated with poly-l-lysine (PLL) which facilitates cell attachment. This study has used Raman spectroscopy to investigate the effect of PLL coating on osteoblast (OB) matrix composition during differentiation, with a focus on collagen specific proline and hydroxyproline and precursors of HA. Deconvolution analysis of murine derived long bone OB Raman spectra revealed collagen species were 4.01-fold higher in OBs grown on PLL. Further, an increase of 1.91-fold in immature mineral species (amorphous calcium phosphate) was coupled with a 9.32-fold reduction in mature mineral species (carbonated apatite) on PLL versus controls. These unique low mineral signatures identified in OBs were linked with reduced alkaline phosphatase enzymatic activity, reduced Alizarin Red staining and altered osteogenic gene expression. The promotion of immature mineral species and restriction of mature mineral species of OB grown on PLL were linked to increased cell viability and pro-angiogenic vascular endothelial growth factor (VEGF) production. These results demonstrate the utility of Raman spectroscopy to link distinct matrix signatures with OB maturation and VEGF release. Importantly, Raman spectroscopy could provide a label-free approach to clinically assess the angiogenic potential of bone during fracture repair or degenerative bone loss.

Identification of new spectral signatures from hepatitis C virus infected human sera

Hepatitis C virus (HCV) infection is one of the leading causes of morbidity and mortality worldwide. Mortality linked with HCV infection can be lowered with effective and prompt diagnosis in early stages of infection. In this study potential of Raman spectroscopy to differentiate between healthy and HCV infected serum samples was investigated. Clear differences were observed in the Raman spectra of HCV infected and healthy sera samples. Using the analysis of variance (ANOVA) and t-test (p < 0.001) on Raman spectra of diseased and healthy samples, we observed eleven unique Raman bands at 676, 825, 853, 936, 1029, 1105, 1155, 1305, 1620, 1654 and 1757 cm^-1 associated with only HCV infected sera and have not been reported in earlier studies. In addition, six Raman bands at 556, 585, 716, 815, 1273 and 1142 cm^-1were observed in healthy sera only. Three Raman bands at 1330, 1526 and 1572 cm^-1 were observed in both type of samples but their intensity was drastically reduced in diseased samples. Various multivariate analysis techniques were employed to demonstrate the robustness of the results. We employed multivariate and unsupervised principal component analysis (PCA) in conjunction with supervised classification linear discriminant analysis (LDA), using ten-fold jackknife cross-validation, in order to develop effective diagnostic algorithm technique (PCA-LDA). Our PCA-LDA model yielded sufficient sensitivity and specificity i.e. correctly identified all infected samples included in this study. Ours results indicate that these unique Raman bands have the potential to be used as biomarkers for optical diagnosis of HCV infection.

Multivariate Statistical Analysis of Surface Enhanced Raman Spectra of Human Serum for Alzheimer’s Disease Diagnosis

Alzheimer’s disease (AD) is the most common form of dementia worldwide and is characterized by progressive cognitive decline. Along with being incurable and lethal, AD is difficult to diagnose with high levels of accuracy. Blood serum from Alzheimer’s disease (AD) patients was analyzed by surface-enhanced Raman spectroscopy (SERS) coupled with multivariate statistical analysis. The obtained spectra were compared with spectra from healthy controls (HC) to develop a simple test for AD detection. Serum spectra from AD patients were further compared to spectra from patients with other neurodegenerative dementias (OD). Colloidal silver nanoparticles (AgNPs) were used as the SERS-active substrates. Classification experiments involving serum SERS spectra using artificial neural networks (ANNs) achieved a diagnostic sensitivity around 96% for differentiating AD samples from HC samples in a binary model and 98% for differentiating AD, HC, and OD samples in a tertiary model. The results from this proof-of-concept study demonstrate the great potential of SERS blood serum analysis to be developed further into a novel clinical assay for the effective and accurate diagnosis of AD.

SERS-based differential diagnosis between multiple solid malignancies: breast, colorectal, lung, ovarian and oral cancer

Purpose

Surface-enhanced Raman scattering (SERS) spectroscopy on serum and other biofluids for cancer diagnosis represents an emerging field, which has shown promising preliminary results in several types of malignancies. The purpose of this study was to demonstrate that SERS spectroscopy on serum can be employed for the differential diagnosis between five of the leading malignancies, ie, breast, colorectal, lung, ovarian and oral cancer.

Patients and methods

Serum samples were acquired from healthy volunteers (n=39) and from patients diagnosed with breast (n=42), colorectal (n=109), lung (n=33), oral (n=17), and ovarian cancer (n=13), comprising n=253 samples in total. SERS spectra were acquired using a 532 nm laser line as excitation source, while the SERS substrates were represented by Ag nanoparticles synthesized by reduction with hydroxylamine. The classification accuracy yielded by SERS was assessed by principal component analysis–linear discriminant analysis (PCA-LDA).

Results

The sensitivity and specificity in discriminating between cancer patients and controls was 98% and 91%, respectively. Cancer samples were correctly assigned to their corresponding cancer types with an accuracy of 88% for oral cancer, 86% for colorectal cancer, 80% for ovarian cancer, 76% for breast cancer and 59% for lung cancer.

Conclusion

SERS on serum represents a promising strategy of diagnosing cancer which can discriminate between cancer patients and controls, as well as between cancer types such as breast, colorectal, lung ovarian and oral cancer.

A Novel Surface Enhanced Raman Catheter for Rapid Detection, Classification, and Grading of Oral Cancer

Fabrication and testing of a novel nanostructured surface-enhanced Raman catheter device is reported for rapid detection, classification, and grading of normal, premalignant, and malignant tissues with high sensitivity and accuracy. The sensor part of catheter is formed by a surface-enhanced Raman scattering (SERS) substrate made up of leaf-like TiO₂ nanostructures decorated with 30 nm sized Ag nanoparticles. The device is tested using a total of 37 patient samples wherein SERS signatures of oral tissues consisting of malignant oral squamous cell carcinoma (OSCC), verrucous carcinoma, premalignant leukoplakia, and disease-free conditions are detected and classified with an accuracy of 97.24% within a short detection-cum-processing time of nearly 25-30 min per patient. Neoplastic grade changes detected using this device correlate strongly with conventional pathological data, enabling correct classification of tumors into three grades with an accuracy of 97.84% in OSCC. Thus, the potential of a SERS catheter device as a point-of-care pathological tool is shown for the rapid and accurate detection, classification, and grading of solid tumors.

The Use of Spectroscopy Handheld Tools in Brain Tumor Surgery: Current Evidence and Techniques

The fundamental principle in the operative treatment of brain tumors involves achieving maximal safe resection in order to improve postoperative outcomes. At present, challenges in visualizing microscopic disease and residual tumor remain an impediment to complete tumor removal. Spectroscopic tools have the theoretical advantage of accurate tissue identification, coupled with the potential for manual intraoperative adjustments to improve visualization of remaining tumor tissue that would otherwise be difficult to detect. The current evidence and techniques for handheld spectroscopic tools in surgical neuro-oncology are explored here.

Speeding Up the Line-Scan Raman Imaging of Living Cells by Deep Convolutional Neural Network

Raman imaging is a promising technique that allows the spatial distribution of different components in the sample to be obtained using the molecular fingerprint information on individual species. However, the imaging speed is the bottleneck for the current Raman imaging methods to monitor the dynamic process of living cells. In this paper, we developed an artificial intelligence assisted fast Raman imaging method over the already fast line scan Raman imaging method. The reduced imaging time is realized by widening the slit and laser beam, and scanning the sample with a large scan step. The imaging quality is improved by a data-driven approach to train a deep convolutional neural network, which statistically learns to transform low-resolution images acquired at a high speed into high-resolution ones that previously were only possible with a low imaging speed. Accompanied with the improvement of the image resolution, the deteriorated spectral resolution as a consequence of a wide slit is also restored, thereby the fidelity of the spectral information is retained. The imaging time can be reduced to within 1 min, which is about five times faster than the state-of-the-art line scan Raman imaging techniques without sacrificing spectral and spatial resolution. We then demonstrated the reliability of the current method using fixed cells. We finally used the method to monitor the dynamic evolution process of living cells. Such an imaging speed opens a door to the label-free observation of cellular events with conventional Raman microscopy.

A roadmap for the clinical implementation of optical-imaging biomarkers

Clinical workflows for the non-invasive detection and characterization of disease states could benefit from optical-imaging biomarkers. In this Perspective, we discuss opportunities and challenges towards the clinical implementation of optical-imaging biomarkers for the early detection of cancer by analysing two case studies: the assessment of skin lesions in primary care, and the surveillance of patients with Barrett's oesophagus in specialist care. We stress the importance of technical and biological validations and clinical-utility assessments, and the need to address implementation bottlenecks. In addition, we define a translational roadmap for the widespread clinical implementation of optical-imaging technologies.

Multivariate discrimination of heat shock proteins using a fiber optic Raman setup for in situ analysis of human perilymph

Raman spectroscopy has proven to be an effective tool for molecular analysis in different applications. In clinical diagnostics, its application has enabled nondestructive investigation of biological tissues and liquids. The human perilymph, for example, is an inner ear liquid, essential for the hearing sensation. The composition of this liquid is correlated with pathophysiological parameters and was analyzed by extraction and mass spectrometry so far. In this work, we present a fiber optic probe setup for the Raman spectroscopic sampling of inner ear proteins in solution. Multivariate data analysis is applied for the discrimination of individual proteins (heat shock proteins) linked to a specific type of hearing impairment. This proof-of-principle is a first step toward a system for sensitive and continuous in vivo perilymph investigation in the future.

Raman spectral signatures of urinary extracellular vesicles from diabetic patients and hyperglycemic endothelial cells as potential biomarkers in diabetes

Raman spectroscopy was applied to the measurement of urinary and in vitro endothelium-derived extracellular vesicles (EVs) isolated by hydrostatic filtration dialysis (HFD) method. Raman spectra obtained for urinary EVs (UEVs) showed distinct differences in the fingerprint region. In contrast, average Raman spectra of endothelium-derived EVs samples were almost identical. Cluster Analysis of UEVs significantly discriminated diabetic samples from control, moreover endothelium-derived EVs revealed stronger similarity between long hyperglycemia and normoglycemia samples compared to short hyperglycemia. Results obtained from Partial Least Squares analysis corresponded well with integral intensities of selected bands. Our proof-of-concept approach demonstrates the potential for Raman spectroscopy to be used both for identification of EVs molecular signatures in urine samples from patients with type 2 diabetes mellitus and good glycemic control and unsatisfactory glycemic control as well as for in vitro hyperglycemic model. This noninvasive technique may be useful in identifying new biomarkers of diabetes and renal complications.

Short-term and long-term effects of osteoporosis on incisor teeth and femoral bones evaluated by Raman spectroscopy and energy dispersive X-ray analysis in ovariectomized rats

There are few published data on the relationship between loss of bone mass due to osteoporosis and poor tooth quality. This study analyzed the effects of osteoporosis on incisor teeth and femoral bones using optical techniques in rats. Twenty female Wistar rats aged 6 months (n = 20) were randomized into two groups: control group, non-ovariectomized rats (n = 10); ovariectomy group, ovariectomized rats to induce osteoporosis (n = 10). Each group was subdivided randomly into two groups containing five rats each as follows. Control group 1: non-ovariectomized rats euthanized at the age of 9 or 3 months post-ovariectomy (n = 5); Control group 2: non-ovariectomized rats euthanized at the age of 1 year or 6 months post-ovariectomy (n = 5); ovariectomy group 1: ovariectomized rats euthanized at the age of 9 months or 3 months post-ovariectomy (n = 5); ovariectomy group 2: ovariectomized rats euthanized at the age of 1 year or 6 months post-ovariectomy (n = 5). The incisor teeth and femoral bones of Wistar rats were removed to perform Raman spectroscopy using an excitation laser at 785 nm. In addition, an energy-dispersive X-ray spectrometer system was used to evaluate calcium (Ca) and phosphorus (P). The main findings included significant changes (p < 0.05) for phosphate and carbonate band areas for both incisor teeth and femur bones. In addition, there was significant negative correlation between the P concentration and phosphate/carbonate ratio (lower P content-larger ratio, p < 0.05) for incisor teeth and femoral bones. The proline and CH₂ wag band areas were significantly reduced only for the incisor teeth (p < 0.05). Therefore, Raman spectroscopy assessed the compositional, physicochemical and structural changes in hard tissue. The current study also pointed out the possible action mechanisms of these changes, bone fracture risk and dental fragility. It is important to emphasize that poor dental quality may also occur due to osteoporosis.

Raman fingerprints for unambiguous identification of organotin compounds

Raman spectra of the different ecotoxicants such as perfluorooctane sulfonate acid, organotin compounds of different families tributyl-, and triphenyl-, as well as chemically close compounds belonging to the same family - such as mono-, di-, and tributyl organotin compounds were analyzed. The comprehensive Raman spectra analysis allowed suggesting the identification scheme for clear recognition of the toxins family and the following intra-group specification. Possibility of unambiguous toxins detection and identification was demonstrated also for complex mixtures of various toxins on a base of control of characteristic peak groups, which can be considered as Raman fingerprints of the listed environmentally hazardous substances.

Advancing Raman microspectroscopy for cellular and subcellular analysis: towards in vitro high-content spectralomic analysis

In the confocal mode, Raman microspectroscopy can profile the biochemical content of biological cells at a subcellular level, and any changes to it by exogenous agents, such as therapeutic drugs or toxicants. As an exploration of the potential of the technique as a high-content, label-free analysis technique, this report reviews work to monitor the spectroscopic signatures associated with the uptake and response pathways of commercial chemotherapeutic agents and polymeric nanoparticles by human lung cells. It is demonstrated that the signatures are reproducible and characteristic of the cellular event, and can be used, for example, to identify the mode of action of the agent as well as the subsequent cell death pathway, and even mechanisms of cellular resistance. Data mining approaches are discussed and a spectralomics approach is proposed.

Qualitative evaluation of ferritin in serum samples by Raman spectroscopy and principal component analysis

Iron molecule is of great importance in the synthesis of hemoglobin which is essential for oxygen transport. Iron levels are quantified by accurately high sensitivity tests, such as serum ferritin (SF). However, common studies to quantify SF are long and strenuous (~ 5 h), for example enzyme-linked immunosorbent assay (ELISA). In this paper, blood serum samples were analyzed by Raman spectroscopy (RS), and a computational analysis of spectra is proposed to detect differences in SF as an alternative procedure. Serum samples were obtained from 22 patients, 9 who were clinically diagnosed with anemia and 13 controls. Patients with anemia had low levels of SF (< 30 ng/ml), and a control group had levels between 30 and 500 ng/ml. The spectra obtained were conditioned with a baseline correction and smoothing, then evaluated by principal component analysis (PCA), and a predictive model was estimated by lineal discrimination analysis (LDA). The results showed a clear differentiation of the study groups by PCA, also 99.69% sensitivity and 100% specificity by LDA. This study suggest that Raman spectroscopy is a fast (~ 5 min) and a powerful tool capable to qualitative differentiate ferritin concentrations.

In-vivo Raman spectroscopy: from basics to applications

For more than two decades, Raman spectroscopy has found widespread use in biological and medical applications. The instrumentation and the statistical evaluation procedures have matured, enabling the lengthy transition from ex-vivo demonstration to in-vivo examinations. This transition goes hand-in-hand with many technological developments and tightly bound requirements for a successful implementation in a clinical environment, which are often difficult to assess for novice scientists in the field. This review outlines the required instrumentation and instrumentation parameters, designs, and developments of fiber optic probes for the in-vivo applications in a clinical setting. It aims at providing an overview of contemporary technology and clinical trials and attempts to identify future developments necessary to bring the emerging technology to the clinical end users. A comprehensive overview of in-vivo applications of fiber optic Raman probes to characterize different tissue and disease types is also given.

Unravelling the Metabolic Progression of Breast Cancer Cells to Bone Metastasis by Coupling Raman Spectroscopy and a Novel Use of Mcr-Als Algorithm

Raman spectroscopy (RS) has shown promise as a tool to reveal biochemical changes that occur in cancer processes at the cellular level. However, when analyzing clinical samples, RS requires improvements to be able to resolve biological components from the spectra. We compared the strengths of Multivariate Curve Resolution (MCR) versus Principal Component Analysis (PCA) to deconvolve meaningful biological components formed by distinct mixtures of biological molecules from a set of mixed spectra. We exploited the flexibility of the MCR algorithm to easily accommodate different initial estimates and constraints. We demonstrate the ability of MCR to resolve undesired background signals from the RS that can be subtracted to obtain clearer cancer cell spectra. We used two triple negative breast cancer cell lines, MDA-MB 231 and MDA-MB 435, to illustrate the insights obtained by RS that infer the metabolic changes required for metastasis progression. Our results show that increased levels of amino acids and lower levels of mitochondrial signals are attributes of bone metastatic cells, whereas lung metastasis tropism is characterized by high lipid and mitochondria levels. Therefore, we propose a method based on the MCR algorithm to achieve unique biochemical insights into the molecular progression of cancer cells using RS.

Application of nanoparticles in cancer detection by Raman scattering based techniques

In vitro detection technique Raman spectroscopy (Rs), in one number times another Rs  based expert ways of art and so on, are useful instruments for cancer  discovery. top gave greater value to Raman spectroscopy  sers is a relatively new careful way for in vitro  and in vivo discovery that takes away bad points of simple Raman spectroscopy (Rs). Raman spectroscopy (RS) and in particular, multiple RS-based techniques are useful for cancer detection. Surface enhanced Raman spectroscopy (SERS) is a relatively new method for both in vitro and in vivo detection, which eliminates the drawbacks of simple RS. Using nanoparticles has elevated the sensitivity and specificity of SERS. SERS has the potential to increase sensitivity, specificity and spatial resolution in cancer detection, especially in cooperation with other diagnostic imaging tools such as magnetic resonance imaging (MRI) and PET-scan polyethylene terephthalate. Developing a hand held instrument for detecting cancer or other illnesses may also be feasible by using SERS. Frequently, novel nanoparticles are used in SERS. With a focus on nanoparticle utilization, we review the benefits of RS in cancer detection and related biomarkers. With a focus on nanoparticles utilizations, the benefits of RS in cancer detection and related biomarkers were reviewed. In addition, Raman applications to detect some of prevalent were discussed. Also more investigated cancers such as breast and colorectal cancer, multiple nanostructures and their possible special biomarkers, especially as SERS nano-tag have been reviewed. The main purpose of this article is introducing of most popular nanotechnological approaches in cancer detection by using Raman techniques. Moreover, have been caught up on detection and reviewed some of the most prevalent and also more investigated cancers such as breast, colorectal cancer, multiple intriguing nanostructures, especially as SERS nano-tag, special cancer biomarkers and related approaches. The main purpose of this article is to introduce the most popular nanotechnological approaches in cancer detection by using Raman techniques.