Illuminating disease and enlightening biomedicine: Raman spectroscopy as a diagnostic tool

Non-invasive detection of regulatory T cells with Raman spectroscopy

Regulatory T cells (Tregs) are a type of lymphocyte that is key to maintaining immunological self-tolerance, with great potential for therapeutic applications. A long-standing challenge in the study of Tregs is that the only way they can be unambiguously identified is by using invasive intracellular markers. Practically, the purification of live Tregs is often compromised by other cell types since only surrogate surface markers can be used. We present here a non-invasive method based on Raman spectroscopy that can detect live unaltered Tregs by coupling optical detection with machine learning implemented with regularized logistic regression. We demonstrate the validity of this approach first on murine cells expressing a surface Foxp3 reporter, and then on peripheral blood human T cells. By including methods to account for sample purity, we could generate reliable models that can identify Tregs with an accuracy higher than 80%, which is already comparable with typical sorting purities achievable with standard methods that use proxy surface markers. We could also demonstrate that it is possible to reliably detect Tregs in fully independent donors that are not part of the model training, a key milestone for practical applications.

SERS in 3D cell models: a powerful tool in cancer research

Unraveling the cellular and molecular mechanisms underlying tumoral processes is fundamental for the diagnosis and treatment of cancer. In this regard, three-dimensional (3D) cancer cell models more realistically mimic tumors compared to conventional 2D cell cultures and are more attractive for performing such studies. Nonetheless, the analysis of such architectures is challenging because most available techniques are destructive, resulting in the loss of biochemical information. On the contrary, surface-enhanced Raman spectroscopy (SERS) is a non-invasive analytical tool that can record the structural fingerprint of molecules present in complex biological environments. The implementation of SERS in 3D cancer models can be leveraged to track therapeutics, the production of cancer-related metabolites, different signaling and communication pathways, and to image the different cellular components and structural features. In this review, we highlight recent progress in the use of SERS for the evaluation of cancer diagnosis and therapy in 3D tumoral models. We outline strategies for the delivery and design of SERS tags and shed light on the possibilities this technique offers for studying different cellular processes, through either biosensing or bioimaging modalities. Finally, we address current challenges and future directions, such as overcoming the limitations of SERS and the need for the development of user-friendly and robust data analysis methods. Continued development of SERS 3D bioimaging and biosensing systems, techniques, and analytical strategies, can provide significant contributions for early disease detection, novel cancer therapies, and the realization of patient-tailored medicine.

Modern optical approaches in redox biology: Genetically encoded sensors and Raman spectroscopy

The objective of the current review is to summarize the current state of optical methods in redox biology. It consists of two parts, the first is dedicated to genetically encoded fluorescent indicators and the second to Raman spectroscopy. In the first part, we provide a detailed classification of the currently available redox biosensors based on their target analytes. We thoroughly discuss the main architecture types of these proteins, the underlying engineering strategies for their development, the biochemical properties of existing tools and their advantages and disadvantages from a practical point of view. Particular attention is paid to fluorescence lifetime imaging microscopy as a possible readout technique, since it is less prone to certain artifacts than traditional intensiometric measurements. In the second part, the characteristic Raman peaks of the most important redox intermediates are listed, and examples of how this knowledge can be implemented in biological studies are given. This part covers such fields as estimation of the redox states and concentrations of Fe-S clusters, cytochromes, other heme-containing proteins, oxidative derivatives of thiols, lipids, and nucleotides. Finally, we touch on the issue of multiparameter imaging, in which biosensors are combined with other visualization methods for simultaneous assessment of several cellular parameters.

Distinct spectral signatures unfold ECM stiffness-triggered biochemical changes in breast cancer cells

Cancer progression often accompanies the stiffening of extracellular matrix (ECM) in and around the tumor, owing to extra deposition and cross-linking of collagen. Stiff ECM has been linked with poor prognosis and is known to fuel invasion and metastasis, notably in breast cancer. However, the underlying biochemical or metabolic changes and the cognate molecular signatures remain elusive. Here, we explored Raman spectroscopy to unveil the spectral fingerprints of breast cancer cells in response to extracellular mechanical cues. Using stiffness-tuneable hydrogels, we showed that cells grown on stiff ECM displayed morphological changes with high proliferation. We further demonstrated that Raman Spectroscopy, a label-free and non-invasive technique, could provide comprehensive information about the biochemical environment of breast cancer cells in response to varying ECM stiffness. Raman spectroscopic analysis classified the cells into distinct clusters based on principal component-based linear discriminant analysis (PC-LDA). Multivariate curve resolution-alternating least squares (MCR-ALS) analysis indicated that cells cultured on stiff ECM exhibited elevated nucleic acid content and lesser lipids. Interestingly, increased intensity of Raman bands corresponding to cytochrome-c was also observed in stiff ECM conditions, suggesting mitochondrial modulation. The key findings harboured by spectral profiles were also corroborated by transmission electron microscopy, confirming altered metabolic status as reflected by increased mitochondria number and decreased lipid droplets in response to ECM stiffening. Collectively, these findings not only give the spectral signatures for mechanoresponse but also provide the landscape of biochemical changes in response to ECM stiffening.

Engineering vascularized skin-mimetic phantom for non-invasive Raman spectroscopy

Recent advances in Raman spectroscopy have shown great potential for non-invasive analyte sensing, but the lack of a standardized optical phantom for these measurements has hindered further progress. While many research groups have developed optical phantoms that mimic bulk optical absorption and scattering, these materials typically have strong Raman scattering, making it difficult to distinguish metabolite signals. As a result, solid tissue phantoms for spectroscopy have been limited to highly scattering tissues such as bones and calcifications, and metabolite sensing has been primarily performed using liquid tissue phantoms. To address this issue, we have developed a layered skin-mimetic phantom that can support metabolite sensing through Raman spectroscopy. Our approach incorporates millifluidic vasculature that mimics blood vessels to allow for diffusion akin to metabolite diffusion in the skin. Furthermore, our skin phantoms are mechanically mimetic, providing an ideal model for development of minimally invasive optical techniques. By providing a standardized platform for measuring metabolites, our approach has the potential to facilitate critical developments in spectroscopic techniques and improve our understanding of metabolite dynamics in vivo.

Illuminating the Tiny World: A Navigation Guide for Proper Raman Studies on Microorganisms

Raman spectroscopy is an emerging method for the identification of bacteria. Nevertheless, a lot of different parameters need to be considered to establish a reliable database capable of identifying real-world samples such as medical or environmental probes. In this review, the establishment of such reliable databases with the proper design in microbiological Raman studies is demonstrated, shining a light into all the parts that require attention. Aspects such as the strain selection, sample preparation and isolation requirements, the phenotypic influence, measurement strategies, as well as the statistical approaches for discrimination of bacteria, are presented. Furthermore, the influence of these aspects on spectra quality, result accuracy, and read-out are discussed. The aim of this review is to serve as a guide for the design of microbiological Raman studies that can support the establishment of this method in different fields.

Raman spectroscopy of brain and skin tissue in a minipig model of Huntington's disease

We applied Raman spectroscopy to brain and skin tissues from a minipig model of Huntington's disease. Differences were observed between measured spectra of tissues with and without Huntington's disease, for both brain tissue and skin tissue. There are linked to changes in the chemical composition between tissue types. Using machine learning we correctly classified 96% of test spectra as diseased or wild type, indicating that the test would have a similar accuracy when used as a diagnostic tool for the disease. This suggests the technique has great potential in the rapid and accurate diagnosis of Huntington's and other neurodegenerative diseases in a clinical setting.

For cervical cancer diagnosis: Tissue Raman spectroscopy and multi-level feature fusion with SENet attention mechanism

Cervical cancer ranks among the most prevalent forms of gynecological malignancies. Timely identification of cervical lesions and prompt intervention can effectively prevent the development of cervical cancer or enhance patients' chances of survival. In this study, we propose an innovative method based on Raman spectroscopy, i.e., a multi-level SENet attention mechanism feature fusion architecture (MAFA) for rapid diagnosis of cervical cancer and precancerous lesions. The convolution process of this architecture can extract features from shallow to deep layers, and the attention mechanism is added to achieve the fusion of features from different layers. The added attention mechanism can automatically determine the importance of each layer feature channel and assign weight values to that layer according to the importance of each layer to achieve the purpose of focusing the model on certain waveform features and improve the targeting of model learning. We collected Raman spectra of 212 cervical tissues containing cervical cancer and its precancerous lesions.The experimental results show that MAFA can effectively improve the diagnostic accuracy of VGGNet, GoogLeNet and ResNet models in the validation of Raman spectral data of cervical tissue. Among them, ResNet performed the best, with the highest average accuracy, precision, recall and F1-Score of 82.36%, 84.00%, 82.35% and 82.26%, respectively, when no feature fusion was performed. The evaluation metrics improved by 4.91%, 3.97%, 4.97%, and 5.06%, respectively, after using the MAFA; they also improved by 4.16%, 2.90%, 4.17%, and 4.32%, respectively, compared with the model that directly performs feature fusion without using the attention mechanism. Therefore, the MAFA proposed in this study is better than that of the neural network that directly fuses the features of each convolutional layer. The experimental results show that the performance of the MAFA proposed in this paper is significantly higher than that of traditional deep learning algorithms, indicating that the present architecture can effectively improve the diagnostic accuracy of deep learning networks for cervical cancer.

Single-cell Raman microscopy with machine learning highlights distinct biochemical features of neutrophil extracellular traps and necrosis

The defining biology that distinguishes neutrophil extracellular traps (NETs) from other forms of cell death is unresolved, and techniques which unambiguously identify NETs remain elusive. Raman scattering measurement provides a holistic overview of cell molecular composition based on characteristic bond vibrations in components such as lipids and proteins. We collected Raman spectra from NETs and freeze/thaw necrotic cells using a custom built high-throughput platform which is able to rapidly measure spectra from single cells. Principal component analysis of Raman spectra from NETs clearly distinguished them from necrotic cells despite their similar morphology, demonstrating their fundamental molecular differences. In contrast, classical techniques used for NET analysis, immunofluorescence microscopy, extracellular DNA, and ELISA, could not differentiate these cells. Additionally, machine learning analysis of Raman spectra indicated subtle differences in lipopolysaccharide (LPS)-induced as opposed to phorbol myristate acetate (PMA)-induced NETs, demonstrating the molecular composition of NETs varies depending on the stimulant used. This study demonstrates the benefits of Raman microscopy in discriminating NETs from other types of cell death and by their pathway of induction.

Label-Free Cytometric Evaluation of Mitosis via Stimulated Raman Scattering Microscopy and Spectral Phasor Analysis

Hyperspectral stimulated Raman scattering (SRS) microscopy is a robust imaging tool for the analysis of biological systems. Here, we present a unique perspective, a label-free spatiotemporal map of mitosis, by integrating hyperspectral SRS microscopy with advanced chemometrics to assess the intrinsic biomolecular properties of an essential process of mammalian life. The application of spectral phasor analysis to multiwavelength SRS images in the high-wavenumber (HWN) region of the Raman spectrum enabled the segmentation of subcellular organelles based on innate SRS spectra. Traditional imaging of DNA is primarily reliant on using fluorescent probes or stains which can affect the biophysical properties of the cell. Here, we demonstrate the label-free visualization of nuclear dynamics during mitosis coupled with an evaluation of its spectral profile in a rapid and reproducible manner. These results provide a snapshot of the cell division cycle and chemical variability between intracellular compartments in single-cell models, which is central to understanding the molecular foundations of these fundamental biological processes. The evaluation of HWN images by phasor analysis also facilitated the differentiation between cells in separate phases of the cell cycle based solely on their nuclear SRS spectral signal, which offers an interesting label-free approach in combination with flow cytometry. Therefore, this study demonstrates that SRS microscopy combined with spectral phasor analysis is a valuable method for detailed optical fingerprinting at the subcellular level.

Early screening of cervical cancer based on tissue Raman spectroscopy combined with deep learning algorithms

Cervical cancer is the most common reproductive malignancy in the female reproductive system. The incidence rate and mortality rate of cervical cancer among women in China are high. In this study, Raman spectroscopy was used to collect tissue sample data from patients with cervicitis, cervical precancerous low-grade lesions, cervical precancerous high-grade lesions, well differentiated squamous cell carcinoma, moderately differentiated squamous cell carcinoma, poorly differentiated squamous cell carcinoma and cervical adenocarcinoma. The collected data were preprocessed using an adaptive iterative reweighted penalized least squares (airPLS) algorithm and derivatives. Convolutional neural network (CNN) and residual neural network (ResNet) classification models were constructed to classify and identify seven types of tissue samples. The attention mechanism efficient channel attention network (ECANet) module and squeeze-and-excitation network (SENet) module were combined with the established CNN and ResNet network models, respectively, to make the models have better diagnostic performance. The results showed that efficient channel attention convolutional neural network (ECACNN) had the best discrimination, and the average accuracy, recall, F1 and AUC values after five cross-validations could reach 94.04%, 94.87%, 94.43% and 96.86%, respectively.

Rapid detection and quantification of paracetamol and its major metabolites using surface enhanced Raman scattering

Paracetamol (also known as acetaminophen) is an over-the-counter (OTC) drug that is commonly used as an analgesic for mild pain, headache, cold and flu. While in the short term it is a safe and effective medicine, it is sometimes used for attempted suicides particularly in young adults. In such circumstances it is important for rapid diagnosis of overdoses as antidotes can be given to limit liver damage from one of its primary metabolites N-acetyl-p-benzoquinone imine (NAPQI). Unfortunately, the demand for rapid and sensitive analytical techniques to accurately monitor the abuse of OTC drugs has significantly risen. Ideally these techniques would be highly specific, sensitive, reproducible, portable and rapid. In addition, an ideal point of care (PoC) test would enable quantitative detection of drugs and their metabolites present in body fluids. While Raman spectroscopy meets these specifications, there is a need for enhancement of the signal because the Raman effect is weak. In this study, we developed a surface-enhanced Raman scattering (SERS) methodology in conjunction with chemometrics to quantify the amount of paracetamol and its main primary metabolites (viz., paracetamol sulfate, p-acetamidophenyl β-D-glucuronide and NAPQI) in water and artificial urine. The enhancement of the SERS signals was achieved by mixing the drug or xenometabolites with a gold nanoparticle followed by aggregation with 0.045 M NaCl. We found that the SERS data could be collected directly, due to immediate analyte association with the Au surface and colloid aggregation. Accurate and precise measurements were generated, with a limit of detection (LoD) of paracetamol in water and artificial urine at 7.18 × 10^-6 M and 2.11 × 10^-5 M, respectively, which is well below the limit needed for overdose and indeed normal levels of paracetamol in serum after taking 1 g orally. The predictive values obtained from the analysis of paracetamol in water and artificial urine were also excellent, with the coefficient of determination (Q²) being 0.995 and 0.996, respectively (1 suggests a perfect model). It was noteworthy that when artificial urine was spiked with paracetamol, no aggregating agent was required due to the salt rich medium, which led to spontaneous aggregation. Moreover, for the xenometabolites of paracetamol excellent LoDs were obtained and these ranged from 2.6 × 10^-4 M to 5 × 10^-5 M with paracetamol sulfate and NAPQI having Q² values of 0.934 and 0.892 and for p-acetamidophenyl β-D-glucuronide this was slightly lower at 0.6437.

Raman Spectroscopy for Early Detection of Cervical Cancer, a Global Women’s Health Issue—A Review

This review focuses on recent advances and future perspectives in the use of Raman spectroscopy for cervical cancer, a global women’s health issue. Cervical cancer is the fourth most common women’s cancer in the world, and unfortunately mainly affects younger women. However, when detected at the early precancer stage, it is highly treatable. High-quality cervical screening programmes and the introduction of the human papillomavirus (HPV) vaccine are reducing the incidence of cervical cancer in many countries, but screening is still essential for all women. Current gold standard methods include HPV testing and cytology for screening, followed by colposcopy and histopathology for diagnosis. However, these methods are limited in terms of sensitivity/specificity, cost, and time. New methods are required to aid clinicians in the early detection of cervical precancer. Over the past 20 years, the potential of Raman spectroscopy together with multivariate statistical analysis has been shown for the detection of cervical cancer. This review discusses the research to date on Raman spectroscopic approaches for cervical cancer using exfoliated cells, biofluid samples, and tissue ex vivo and in vivo.

Non-invasive monitoring of T cell differentiation through Raman spectroscopy

The monitoring of dynamic cellular behaviors remains a technical challenge for most established techniques used nowadays for single-cell analysis, as most of them are either destructive, or rely on labels that can affect the long-term functions of cells. We employ here label-free optical techniques to non-invasively monitor the changes that occur in murine naive T cells upon activation and subsequent differentiation into effector cells. Based on spontaneous Raman single-cell spectra, we develop statistical models that allow the detection of activation, and employ non-linear projection methods to delineate the changes occurring over a several day period spanning early differentiation. We show that these label-free results have very high correlation with known surface markers of activation and differentiation, while also providing spectral models that allow the identification of the underlying molecular species that are representative of the biological process under study.

SERS-based antibiotic susceptibility testing: Towards point-of-care clinical diagnosis

Emerging antibiotic resistant bacteria constitute one of the biggest threats to public health. Surface-enhanced Raman scattering (SERS) is highly promising for detecting such bacteria and for antibiotic susceptibility testing (AST). SERS is fast, non-destructive (can probe living cells) and it is technologically flexible (readily integrated with robotics and machine learning algorithms). However, in order to integrate into efficient point-of-care (PoC) devices and to effectively replace the current culture-based methods, it needs to overcome the challenges of reliability, cost and complexity. Recently, significant progress has been made with the emergence of both new questions and new promising directions of research and technological development. This article brings together insights from several representative SERS-based AST studies and approaches oriented towards clinical PoC biosensing. It aims to serve as a reference source that can guide progress towards PoC routines for identifying antibiotic resistant pathogens. In turn, such identification would help to trace the origin of sporadic infections, in order to prevent outbreaks and to design effective medical treatment and preventive procedures.

Fabrication of α-Fe2O3 Nanostructures: Synthesis, Characterization, and Their Promising Application in the Treatment of Carcinoma A549 Lung Cancer Cells

In the present work, iron nanoparticles were synthesized in the α-Fe₂O₃ phase with the reduction of potassium hexachloroferrate(III) by using l-ascorbic acid as a reducing agent in the presence of an amphiphilic non-ionic polyethylene glycol surfactant in an aqueous solution. The synthesized α-Fe₂O₃ NPs were characterized by powder X-ray diffraction, field emission scanning electron microscopy, transmission electron microscopy, atomic force microscopy, dynamic light scattering, energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, and ultraviolet-visible spectrophotometry. The powder X-ray diffraction analysis result confirmed the formation of α-Fe₂O₃ NPs, and the average crystallite size was found to be 45 nm. The other morphological studies suggested that α-Fe₂O₃ NPs were predominantly spherical in shape with a diameter ranges from 40 to 60 nm. The dynamic light scattering analysis revealed the zeta potential of α-Fe₂O₃ NPs as -28 ± 18 mV at maximum stability. The ultraviolet-visible spectrophotometry analysis shows an absorption peak at 394 nm, which is attributed to their surface plasmon vibration. The cytotoxicity test of synthesized α-Fe₂O₃ NPs was investigated against human carcinoma A549 lung cancer cells, and the biological adaptability exhibited by α-Fe₂O₃ NPs has opened a pathway to biomedical applications in the drug delivery system. Our investigation confirmed that l-ascorbic acid-coated α-Fe₂O₃ NPs with calculated IC₅₀ ≤ 30 μg/mL are the best suited as an anticancer agent, showing the promising application in the treatment of carcinoma A549 lung cancer cells.

Quantification of clinical mAb solutions using Raman spectroscopy: Macroscopic vs microscopic analysis

Raman Spectroscopy is well emerged in the field of Analytical Quality Control (AQC) as a rapid and cost-effective technique useful in many applications. The advantage of Raman spectroscopy is the non-invasiveness of measurements that enablesto analyse samples directly in its container. In this study, the potential of Raman spectroscopy was investigated for analysis of clinical preparations of mAbs. Three commercial formulations of monoclonal antibodies (mAbs) Avastin®, Ontruzant® and Tecentriq® corresponding to Bevacizumab (BVC), Trastuzumab (TRS) and Atezolizumab (ATZ) respectively, were analysed in quartz cuvette in macroscopic analysis and through the wall of perfusion bags in microscopic analysis. The spectra have been compared to those of excipients (trehalose and sucrose) and of γ-Globulin, in order to investigate the origin of Raman bands. As expected, Raman spectra were a combination of bands from monoclonal antibodies and correspoding excipients found in formulas. For quantitative analysis of the solutions, models have been constructed using Partial Least Square Regression (PLSR) with Leave K-Out Cross Validation (LKOCV). The quantification performance was comparable for both macroscopic and microscopic analysis, in terms of error and linearity. The results are thus promising for future AQC in situ, in perfusion bags.

Research Progress of Raman Spectroscopy and Raman Imaging in Pharmaceutical Analysis

The analytical investigation of the pharmaceutical process monitors the critical process parameters of the drug, beginning from its development until marketing and postmarketing, and appropriate corrective action can be taken to change the pharmaceutical design at any stage of the process. Advanced analytical methods, such as Raman spectroscopy, are particularly suitable for use in the field of drug analysis, especially for qualitative and quantitative work, due to the advantages of simple sample preparation, fast, nondestructive analysis speed, and effective avoidance of moisture interference. Advanced Raman imaging techniques have gradually become a powerful alternative method for monitoring changes in polymorph distribution and active pharmaceutical ingredient distribution in drug processing and pharmacokinetics. Surface-enhanced Raman spectroscopy (SERS) has also solved the inherent insensitivity and fluorescence problems of Raman, which has made good progress in the field of illegal drug analysis. This review summarizes the application of Raman spectroscopy and imaging technology, which are used in the qualitative and quantitative analysis of solid tablets, quality control of the production process, drug crystal analysis, illegal drug analysis, and monitoring of drug dissolution and release in the field of drug analysis in recent years.

Prospects of Surface-Enhanced Raman Spectroscopy for Biomarker Monitoring toward Precision Medicine

Future precision medicine will be undoubtedly sustained by the detection of validated biomarkers that enable a precise classification of patients based on their predicted disease risk, prognosis, and response to a specific treatment. Up to now, genomics, transcriptomics, and immunohistochemistry have been the main clinically amenable tools at hand for identifying key diagnostic, prognostic, and predictive biomarkers. However, other molecular strategies, including metabolomics, are still in their infancy and require the development of new biomarker detection technologies, toward routine implementation into clinical diagnosis. In this context, surface-enhanced Raman scattering (SERS) spectroscopy has been recognized as a promising technology for clinical monitoring thanks to its high sensitivity and label-free operation, which should help accelerate the discovery of biomarkers and their corresponding screening in a simpler, faster, and less-expensive manner. Many studies have demonstrated the excellent performance of SERS in biomedical applications. However, such studies have also revealed several variables that should be considered for accurate SERS monitoring, in particular, when the signal is collected from biological sources (tissues, cells or biofluids). This Perspective is aimed at piecing together the puzzle of SERS in biomarker monitoring, with a view on future challenges and implications. We address the most relevant requirements of plasmonic substrates for biomedical applications, as well as the implementation of tools from artificial intelligence or biotechnology to guide the development of highly versatile sensors.

DNA damage in preimplantation embryos and gametes: specification, clinical relevance and repair strategies

BACKGROUND

DNA damage is a hazard that affects all cells of the body. DNA-damage repair (DDR) mechanisms are in place to repair damage and restore cellular function, as are other damage-induced processes such as apoptosis, autophagy and senescence. The resilience of germ cells and embryos in response to DNA damage is less well studied compared with other cell types. Given that recent studies have described links between embryonic handling techniques and an increased likelihood of disease in post-natal life, an update is needed to summarize the sources of DNA damage in embryos and their capacity to repair it. In addition, numerous recent publications have detailed novel techniques for detecting and repairing DNA damage in embryos. This information is of interest to medical or scientific personnel who wish to obtain undamaged embryos for use in offspring generation by ART.

OBJECTIVE AND RATIONALE

This review aims to thoroughly discuss sources of DNA damage in male and female gametes and preimplantation embryos. Special consideration is given to current knowledge and limits in DNA damage detection and screening strategies. Finally, obstacles and future perspectives in clinical diagnosis and treatment (repair) of DNA damaged embryos are discussed.

SEARCH METHODS

Using PubMed and Google Scholar until May 2021, a comprehensive search for peer-reviewed original English-language articles was carried out using keywords relevant to the topic with no limits placed on time. Keywords included ‘DNA damage repair’, ‘gametes’, ‘sperm’, ‘oocyte’, ‘zygote’, ‘blastocyst’ and ‘embryo’. References from retrieved articles were also used to obtain additional articles. Literature on the sources and consequences of DNA damage on germ cells and embryos was also searched. Additional papers cited by primary references were included. Results from our own studies were included where relevant.

OUTCOMES

DNA damage in gametes and embryos can differ greatly based on the source and severity. This damage affects the development of the embryo and can lead to long-term health effects on offspring. DDR mechanisms can repair damage to a certain extent, but the factors that play a role in this process are numerous and altogether not well characterized. In this review, we describe the multifactorial origin of DNA damage in male and female gametes and in the embryo, and suggest screening strategies for the selection of healthy gametes and embryos. Furthermore, possible therapeutic solutions to decrease the frequency of DNA damaged gametes and embryos and eventually to repair DNA and increase mitochondrial quality in embryos before their implantation is discussed.

WIDER IMPLICATIONS

Understanding DNA damage in gametes and embryos is essential for the improvement of techniques that could enhance embryo implantation and pregnancy success. While our knowledge about DNA damage factors and regulatory mechanisms in cells has advanced greatly, the number of feasible practical techniques to avoid or repair damaged embryos remains scarce. Our intention is therefore to focus on strategies to obtain embryos with as little DNA damage as possible, which will impact reproductive biology research with particular significance for reproductive clinicians and embryologists.

Graphene Oxide as a Collagen Modifier of Amniotic Membrane and Burnt Skin

Introduction

The aim of this interdisciplinary study was to answer the question of whether active antioxidants as graphene oxide (GO), sodium ascorbate, and L-ascorbic acid modify at a molecular and supramolecular level the tissue of pathological amnion and the necrotic eschar degraded in thermal burn. We propose new solutions of modifiers based on GO that will become innovative ingredients to be used in transplants (amnion) and enhance regeneration of epidermis degraded in thermal burn.

Methods

A Nicolet 6700 spectrophotometer with Omnic software and the EasiDiff diffusion accessory were used in FTIR spectroscopic analysis. A Nicolet Magna-IR 860 spectrometer with an FT Raman accessory was used to record the Raman spectra of the samples. The surface of the samples was examined using a Phenom ProX scanning electron microscope with an energy-dispersive X-ray spectroscopy detector to diagnose and illustrate morphological effects on skin and amnion samples. SAXS measurements were carried out with a compact Kratky camera equipped with the SWAXS optical system.

Results

Characterisation of amide I-III regions, important for molecular structure, on both FTIR and FTR spectra revealed distinct shifts, testifying to organization of protein structure after GO modification. A wide lipid band associated with ester-group vibrations in phospholipids of cell membranes and vibrations of the carbonyl group of GO in the 1,790-1,720 cm^-1 band were observed in the spectra of thermally degraded and GO-modified epidermis and pathological amnion. SAXS studies revealed that GO caused a significant change in the structure of the burnt skin, but its influence on the structure of the amnion was weak.

Conclusion

Modification of burn-damaged epidermis and pathological amnion by means of GO results in stabilization and regeneration of tissue at the level of molecular (FTIR, FTR) and supramolecular (SAXS) interactions.

Using Stable Isotope Probing and Raman Microspectroscopy To Measure Growth Rates of Heterotrophic Bacteria

The suitability of stable isotope probing (SIP) and Raman microspectroscopy to measure growth rates of heterotrophic bacteria at the single-cell level was evaluated. Label assimilation into Escherichia coli biomass during growth on a complex ¹³C-labeled carbon source was monitored in time course experiments. ¹³C incorporation into various biomolecules was measured by spectral "red shifts" of Raman-scattered emissions. The ¹³C- and ¹²C-isotopologues of the amino acid phenylalanine (Phe) proved to be quantitatively accurate reporter molecules of cellular isotopic fractional abundances (f_cell). Values of f_cell determined by Raman microspectroscopy and independently by isotope ratio mass spectrometry (IRMS) over a range of isotopic enrichments were statistically indistinguishable. Progressive labeling of Phe in E. coli cells among a range of ¹³C/¹²C organic substrate admixtures occurred predictably through time. The relative isotopologue abundances of Phe determined by Raman spectral analysis enabled the accurate calculation of bacterial growth rates as confirmed independently by optical density (OD) measurements. The results demonstrate that combining SIP and Raman microspectroscopy can be a powerful tool for studying bacterial growth at the single-cell level on defined or complex organic ¹³C carbon sources, even in mixed microbial assemblages. IMPORTANCE Population growth dynamics and individual cell growth rates are the ultimate expressions of a microorganism's fitness under its environmental conditions, whether natural or engineered. Natural habitats and many industrial settings harbor complex microbial assemblages. Their heterogeneity in growth responses to existing and changing conditions is often difficult to grasp by standard methodologies. In this proof-of-concept study, we tested whether Raman microspectroscopy can reliably quantify the assimilation of isotopically labeled nutrients into E. coli cells and enable the determination of individual growth rates among heterotrophic bacteria. Raman-derived growth rate estimates were statistically indistinguishable from those derived by standard optical density measurements of the same cultures. Raman microspectroscopy can also be combined with methods for phylogenetic identification. We report the development of Raman-based techniques that enable researchers to directly link genetic identity to functional traits and rate measurements of single cells within mixed microbial assemblages, currently a major technical challenge in microbiological research.

Multimodal Label-Free Monitoring of Adipogenic Stem Cell Differentiation Using Endogenous Optical Biomarkers

Stem cell-based therapies carry significant promise for treating human diseases. However, clinical translation of stem cell transplants for effective treatment requires precise non-destructive evaluation of the purity of stem cells with high sensitivity (<0.001% of the number of cells). Here, a novel methodology using hyperspectral imaging (HSI) combined with spectral angle mapping-based machine learning analysis is reported to distinguish differentiating human adipose-derived stem cells (hASCs) from control stem cells. The spectral signature of adipogenesis generated by the HSI method enables identifying differentiated cells at single-cell resolution. The label-free HSI method is compared with the standard techniques such as Oil Red O staining, fluorescence microscopy, and qPCR that are routinely used to evaluate adipogenic differentiation of hASCs. HSI is successfully used to assess the abundance of adipocytes derived from transplanted cells in a transgenic mice model. Further, Raman microscopy and multiphoton-based metabolic imaging is performed to provide complementary information for the functional imaging of the hASCs. Finally, the HSI method is validated using matrix-assisted laser desorption/ionization-mass spectrometry imaging of the stem cells. The study presented here demonstrates that multimodal imaging methods enable label-free identification of stem cell differentiation with high spatial and chemical resolution.

Scale-adaptive Deep Model for Bacterial Raman Spectra Identification

The combination of Raman spectroscopy and deep learning technology provides an automatic, rapid, and accurate scheme for the clinical diagnosis of pathogenic bacteria. However, the accuracy of existing deep learning methods is still limited because of the single and fixed scales of deep neural networks. We propose a deep neural network that can learn multi-scale features of Raman spectra by using the automatic combination of multi-receptive fields of convolutional layers. This model is based on the expert knowledge that the discrimination information of Raman spectra is composed of multi-scale spectral peaks. We enhance the interpretability of the model by visualizing the activated wavenumbers of the bacterial spectrum that can be used for reference in related work. Compared with existing state-of-the-art methods, the proposed method achieves higher accuracy and efficiency for bacterial identification on isolate-level, empiric-treatment-level, and antibiotic-resistance-level tasks. The clinical bacterial identification task requires significantly fewer patient samples to achieve similar accuracy. Therefore, this method has tremendous potential for the identification of clinical pathogenic bacteria, antibiotic susceptibility testing, and prescription guidance.

Metabolomics and metabolites in ischemic stroke

Stroke is a major reason for disability and the second highest cause of death in the world. When a patient is admitted to a hospital, it is necessary to identify the type of stroke, and the likelihood for development of a recurrent stroke, vascular dementia, and depression. These factors could be determined using different biomarkers. Metabolomics is a very promising strategy for identification of biomarkers. The advantage of metabolomics, in contrast to other analytical techniques, resides in providing low molecular weight metabolite profiles, rather than individual molecule profiles. Technically, this approach is based on mass spectrometry and nuclear magnetic resonance. Furthermore, variations in metabolite concentrations during brain ischemia could alter the principal neuronal functions. Different markers associated with ischemic stroke in the brain have been identified including those contributing to risk, acute onset, and severity of this pathology. In the brain, experimental studies using the ischemia/reperfusion model (IRI) have shown an impaired energy and amino acid metabolism and confirmed their principal roles. Literature data provide a good basis for identifying markers of ischemic stroke and hemorrhagic stroke and understanding metabolic mechanisms of these diseases. This opens an avenue for the successful use of identified markers along with metabolomics technologies to develop fast and reliable diagnostic tools for ischemic and hemorrhagic stroke.

Imaging and SERS Study of the Au Nanoparticles Interaction with HPV and Carcinogenic Cervical Tissues

In this work, gold NPs were prepared by the Turkevich method, and their interaction with HPV and cancerous cervical tissues were studied by scanning electron microscopy, energy-dispersive x-ray spectroscopy, confocal and multiphoton microscopy and SERS. The SEM images confirmed the presence and localization of the gold NPs inside of the two kinds of tissues. The light absorption of the gold NPs was at 520 nm. However, it was possible to obtain two-photon imaging (red emission region) of the gold NPs inside of the tissue, exciting the samples at 900 nm, observing the morphology of the tissues. The infrared absorption was probably due to the aggregation of gold NPs inside the tissues. Therefore, through the interaction of gold nanoparticles with the HPV and cancerous cervical tissues, a surface enhanced Raman spectroscopy (SERS) was obtained. As preliminary studies, having an average of 1000 Raman spectra per tissue, SERS signals showed changes between the HPV-infected and the carcinogenic tissues; these spectral signatures occurred mainly in the DNA bands, potentially offering a tool for the rapid screening of cancer.

In situ Analytical Quality Control of chemotherapeutic solutions in infusion bags by Raman spectroscopy

Analytical Quality Control (AQC) in centralised preparation units of oncology centers is a common procedure relying on the identification and quantification of the prepared chemotherapeutic solutions for safe intravenous administration to patients. Although the use of Raman spectroscopy for AQC has gained much interest, in most applications it remains coupled to a flow injection analyser (FIA) requiring withdrawal of the solution for analysis. In addition to current needs for more rapid and cost-effective analysis, the risk of exposure of clinical staff to the toxic molecules during daily handling is a serious concern to address. Raman spectroscopic analysis, for instance by Confocal Raman Microscopy (CRM), could enable direct analysis (non-invasive) for AQC directly in infusion bags. In this study, 3 anticancer drugs, methotrexate (MTX), 5-fluorouracil (5-FU) and gemcitabine (GEM) have been selected to highlight the potential of CRM for withdrawal free analysis. Solutions corresponding to the clinical range of each drug were prepared in 5% glucose and data was collected from infusion bags placed under the Raman microscope. Firstly, 100% discrimination has been obtained by Partial Least Squares Discriminant Analysis (PLS-DA) confirming that the identification of drugs can be performed. Secondly, using Partial Least Squares Regression (PLSR), quantitative analysis was performed with mean % error of predicted concentrations of respectively 3.31%, 5.54% and 8.60% for MTX, 5-FU and GEM. These results are in accordance with the 15% acceptance criteria used for the current clinical standard technique, FIA, and the Limits of Detection for all drugs were determined to be substantially lower than the administered range, thus highlighting the potential of confocal Raman spectroscopy for direct analysis of chemotherapeutic solutions.

Molecular monitoring of glioblastoma's immunogenicity using a combination of Raman spectroscopy and chemometrics

Raman spectroscopy (RS) has been used as a powerful diagnostic and non-invasive tool in cancer diagnosis as well as in discrimination of cancer and immune cells. In this study RS in combination with chemometrics was applied to cellular Raman spectral data to distinguish the phenotype of T-cells and monocytes after incubation with media conditioned by glioblastoma stem-cells (GSCs) showing different molecular background. For this purpose, genetic modulations of epithelial-to-mesenchymal transition (EMT) process and expression of immunomodulator CD73 were introduced. Principal component analysis of the Raman spectral data showed that T-cells and monocytes incubated with tumour-conditioned media (TCMs) of GSCs with inhibited EMT activator ZEB1 or CD73 formed distinct clusters compared to controls highlighting their differences. Further discriminatory analysis performed using linear discriminant analysis (LDA) and support vector machine classification (SVM), yielded sensitivities and specificities of over 70 and 67% respectively upon validation against an independent test set. Supporting those results, flow cytometric analysis was performed to test the influence of TCMs on cytokine profile of T-cells and monocytes. We found that ZEB1 and CD73 influence T-cell and monocyte phenotype and promote monocyte differentiation into a population of mixed pro- and anti-tumorigenic macrophages (MΦs) and dendritic cells (DCs) respectively. In conclusion, Raman spectroscopy in combination with chemometrics enabled tracking T-cells and monocytes.

Biopolymer Patterning-Directed Secretion in Mucoid and Nonmucoid Strains of Pseudomonas aeruginosa Revealed by Multimodal Chemical Imaging

Quinolone, pyocyanin, and rhamnolipid production were studied in Pseudomonas aeruginosa by spatially patterning mucin, a glycoprotein important to infection of lung epithelia. Mass spectrometric imaging and confocal Raman microscopy are combined to probe P. aeruginosa biofilms from mucoid and nonmucoid strains grown on lithographically defined patterns. Quinolone signatures from biofilms on patterned vs unpatterned and mucin vs mercaptoundecanoic acid (MUA) surfaces were compared. Microbial attachment is accompanied by secretion of 2-alkyl-4-quinolones as well as rhamnolipids from the mucoid and nonmucoid strains. Pyocyanin was also detected both in the biofilm and in the supernatant in the mucoid strain only. Significant differences in the spatiotemporal distributions of secreted factors are observed between strains and among different surface patterning conditions. The mucoid strain is sensitive to composition and patterning while the nonmucoid strain is not, and in promoting community development in the mucoid strain, nonpatterned surfaces are better than patterned, and mucin is better than MUA. Also, the mucoid strain secretes the virulence factor pyocyanin in a way that correlates with distress. A change in the relative abundance for two rhamnolipids is observed in the mucoid strain during exposure to mucin, whereas minimal variation is observed in the nonmucoid strain. Differences between mucoid and nonmucoid strains are consistent with their strain-specific phenology, in which the mucoid strain develops highly protected and withdrawn biofilms that achieve Pseudomonas quinolone signal production under limited conditions.

Label-free Raman mapping of saturated and unsaturated fatty acid uptake, storage, and return toward baseline levels in macrophages

Macrophage uptake and metabolism of fatty acids is involved in a large number of important biological pathways including immune activation and regulation of macrophages, as well as pathological conditions including obesity, atherosclerosis, and others lifestyle diseases. There are few methods available to directly probe both the uptake and later redistribution/metabolism of fatty acids within living cells as well as the potential changes induced within the cells themselves. We use Raman imaging and analysis to evaluate the effects of different fatty acids following their uptake in macrophages. The label-free nature of the methods means that we can evaluate the fatty acid dynamics without modifying endogenous cellular behavior and metabolism.

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.

Assessment of Transdermal Delivery of Topical Compounds in Skin Scarring Using a Novel Combined Approach of Raman Spectroscopy and High-Performance Liquid Chromatography

Objective: The goal of any topical formulation is efficient transdermal delivery of its active components. However, delivery of compounds can be problematic with penetration through tough layers of fibrotic dermal scar tissue. Approach: We propose a new approach combining high-performance liquid chromatography (HPLC) and Raman spectroscopy (RS) using a topical of unknown composition against a well-known antiscar topical (as control). Results: Positive detection of compounds within the treatment topical using both techniques was validated with mass spectrometry. RS detected conformational structural changes; the 1,655/1,446 cm^-1 ratio estimating collagen content significantly decreased (p < 0.05) over weeks 4, 12, and 16 compared with day 0. The amide I band, known to represent collagen and protein in skin, shifted from 1,667 to 1,656 cm^-1, which may represent a change from β-sheets in elastin to α-helices in collagen. Confirmatory elastin immunohistochemistry decreased compared with day 0, conversely the collagen I/III ratio increased in the same samples by week 12 (p < 0.05, and p < 0.0001, respectively), in keeping with normal scar formation. Optical coherence tomography attenuation coefficient representing collagen deposition was significantly decreased at week 4 compared with day 0 and increased at week 16 (p < 0.05). Innovation: This study provides a platform for further research on the simultaneous evaluation of the effects of compounds in cutaneous scarring by RS and HPLC, and identifies a role for RS in the therapeutic evaluation and theranostic management of skin scarring. Conclusions: RS can provide noninvasive information on the effects of topicals on scar pathogenesis and structural composition, validated by other analytical techniques.

Discrimination of bacteria using whole organism fingerprinting: the utility of modern physicochemical techniques for bacterial typing

This review compares and contrasts MALDI-MS, FT-IR spectroscopy and Raman spectroscopy for whole organism fingerprinting and bacterial typing.

Rapid discrimination of intact beef, venison and lamb meat using Raman spectroscopy

With increasing demand for fast and reliable techniques for intact meat discrimination, we explore the potential of Raman spectroscopy in combination with three chemometric techniques to discriminate beef, lamb and venison meat samples. Ninety (90) intact red meat samples were measured using Raman spectroscopy, with the acquired spectral data preprocessed using a combination of rubber-band baseline correction, Savitzky-Golay smoothing and standard normal variate transformation. PLSDA and SVM classification were utilized in building classification models for the meat discrimination, whereas PCA was used for exploratory studies. Results obtained using linear and non-linear kernel SVM models yielded sensitivities of over 87 and 90 % respectively, with the corresponding specificities above 88 % on validation against a test set. The PLSDA model yielded over 80 % accuracy in classifying each of the meat specie. PLSDA and SVM classification models in combination with Raman spectroscopy posit an effective technique for red meat discrimination.

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

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

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.

Raman Spectroscopy Reveals That Biochemical Composition of Breast Microcalcifications Correlates with Histopathologic Features

Breast microcalcifications are a common mammographic finding. Microcalcifications are considered suspicious signs of breast cancer and a breast biopsy is required, however, cancer is diagnosed in only a few patients. Reducing unnecessary biopsies and rapid characterization of breast microcalcifications are unmet clinical needs. In this study, 473 microcalcifications detected on breast biopsy specimens from 56 patients were characterized entirely by Raman mapping and confirmed by X-ray scattering. Microcalcifications from malignant samples were generally more homogeneous, more crystalline, and characterized by a less substituted crystal lattice compared with benign samples. There were significant differences in Raman features corresponding to the phosphate and carbonate bands between the benign and malignant groups. In addition to the heterogeneous composition, the presence of whitlockite specifically emerged as marker of benignity in benign microcalcifications. The whole Raman signature of each microcalcification was then used to build a classification model that distinguishes microcalcifications according to their overall biochemical composition. After validation, microcalcifications found in benign and malignant samples were correctly recognized with 93.5% sensitivity and 80.6% specificity. Finally, microcalcifications identified in malignant biopsies, but located outside the lesion, reported malignant features in 65% of in situ and 98% of invasive cancer cases, respectively, suggesting that the local microenvironment influences microcalcification features. This study confirms that the composition and structural features of microcalcifications correlate with breast pathology and indicates new diagnostic potentialities based on microcalcifications assessment. SIGNIFICANCE: Raman spectroscopy could be a quick and accurate diagnostic tool to precisely characterize and distinguish benign from malignant breast microcalcifications detected on mammography.

Immune cell type, cell activation, and single cell heterogeneity revealed by label-free optical methods

Measurement techniques that allow the global analysis of cellular responses while retaining single-cell sensitivity are increasingly needed in order to understand complex and dynamic biological processes. In this context, compromises between sensitivity, degree of multiplexing, throughput, and invasiveness are often unavoidable. We present here a noninvasive optical approach that can retrieve quantitative biomarkers of both morphological and molecular phenotypes of individual cells, based on a combination of quantitative phase imaging and Raman spectroscopy measurements. We then develop generalized statistical tools to assess the influence of both controlled (cell sub-populations, immune stimulation) and uncontrolled (culturing conditions, animal variations, etc.) experimental parameters on the label-free biomarkers. These indicators can detect different macrophage cell sub-populations originating from different progenitors as well as their activation state, and how these changes are related to specific differences in morphology and molecular content. The molecular indicators also display further sensitivity that allow identification of other experimental conditions, such as differences between cells originating from different animals, allowing the detection of outlier behaviour from given cell sub-populations.

Molecular detection of HPV and FT-IR spectroscopy analysis in women with normal cervical cytology

BACKGROUND

The increase in the incidence of Cervical Cancer in the female population worldwide has been an issue that deserves further attention from the scientific community. Several studies have already proven the relationship of its development with the molecular mechanisms that Human Papillomavirus (HPV) induces in cervical cells. The gene amplification provided by molecular biology techniques has been used as the gold standard diagnostic method of this virus because of its high specificity and sensitivity.However, the high investments associated with the acquisition of reagents, equipment and labor demonstrate the need for the development of more accessible techniques that present the same accuracy. FT-IR spectroscopy has been studied as an inexpensive and easily accessible technology that can provide the differentiation of malignant and benign cells. This study aimed to demonstrate the effectiveness and sensitivity of molecular analysis by PCR in relation to cytological analysis and to evaluate the sensitivity of FT-IR spectroscopy in the diagnosis of HPV for cervical cancer prevention.

METHODS

Cervical fluid samples obtained from 50 patients with absence of cellular lesion by cytological analysis were analyzed by molecular and spectroscopic analyzes. Oncotic colpocitology analysis was performed by the Papanicolaou staining, amplification of the L1 viral gene by PCR was performed using primers MY09 and MY11 and biochemical analysis of the fluids by FT-IR was performed using the Spectrum 400 system equipped with a microscope.

RESULTS

Of the 50 patients without evident morphological alteration of the cells, seven were diagnosed by molecular analysis as positive for presence of HPV. Principal component analysis of spectroscopy was not able to separate the negative samples from the HPV positive samples and, therefore, did not present as an effective diagnostic technique.

CONCLUSIONS

We highlight the efficacy, sensitivity and specificity of molecular biology by PCR in the identification of the virus and we emphasize that more studies should be used for the application of FT-IR spectroscopy in the diagnosis of this infection and its application in the prevention of cervical cancer.

Raman Spectroscopy for Rapid Evaluation of Surgical Margins during Breast Cancer Lumpectomy

Failure to precisely distinguish malignant from healthy tissue has severe implications for breast cancer surgical outcomes. Clinical prognoses depend on precisely distinguishing healthy from malignant tissue during surgery. Laser Raman spectroscopy (LRS) has been previously shown to differentiate benign from malignant tissue in real time. However, the cost, assembly effort, and technical expertise needed for construction and implementation of the technique have prohibited widespread adoption. Recently, Raman spectrometers have been developed for non-medical uses and have become commercially available and affordable. Here we demonstrate that this current generation of Raman spectrometers can readily identify cancer in breast surgical specimens. We evaluated two commercially available, portable, near-infrared Raman systems operating at excitation wavelengths of either 785 nm or 1064 nm, collecting a total of 164 Raman spectra from cancerous, benign, and transitional regions of resected breast tissue from six patients undergoing mastectomy. The spectra were classified using standard multivariate statistical techniques. We identified a minimal set of spectral bands sufficient to reliably distinguish between healthy and malignant tissue using either the 1064 nm or 785 nm system. Our results indicate that current generation Raman spectrometers can be used as a rapid diagnostic technique distinguishing benign from malignant tissue during surgery.

Fingerprint-to-CH stretch continuously tunable high spectral resolution stimulated Raman scattering microscope

Stimulated Raman scattering (SRS) microscopy is a label-free method generating images based on chemical contrast within samples, and has already shown its great potential for high-sensitivity and fast imaging of biological specimens. The capability of SRS to collect molecular vibrational signatures in bio-samples, coupled with the availability of powerful statistical analysis methods, allows quantitative chemical imaging of live cells with sub-cellular resolution. This application has substantially driven the development of new SRS microscopy platforms. Indeed, in recent years, there has been a constant effort on devising configurations able to rapidly collect Raman spectra from samples over a wide vibrational spectral range, as needed for quantitative analysis by using chemometric methods. In this paper, an SRS microscope which exploits spectral shaping by a narrowband and rapidly tunable acousto-optical tunable filter (AOTF) is presented. This microscope enables spectral scanning from the Raman fingerprint region to the Carbon-Hydrogen (CH)-stretch region without any modification of the optical setup. Moreover, it features also a high enough spectral resolution to allow resolving Raman peaks in the crowded fingerprint region. Finally, application of the developed SRS microscope to broadband hyperspectral imaging of biological samples over a large spectral range from 800 to 3600 cm^-1 , is demonstrated.

Raman exfoliative cytology for prognosis prediction in oral cancers: A proof of concept study

Oral cancer is associated with high rates of recurrence, attributable to field cancerization. Early detection of advanced field changes that can potentially progress to carcinoma can facilitate timely intervention and can lead to improved prognosis. Previous in vivo studies have successfully detected advanced field effects in oral cancers. Raman exfoliative cytology has previously shown to differentiate normal, oral pre-cancer and cancers. The present study explores Raman-exfoliative-cytology-based detection of field effects. Exfoliated cells were collected from tumor (n = 16) and contralateral-normal appearing mucosa (n = 16) of oral cancer patients, and healthy tobacco habitués (n = 20). After spectral acquisition, specimens were Pap-stained for cytological evaluation. Data analysis, by Principal Component Analysis and Principal Component-Linear Discriminant Analysis, indicate several spectral-misclassifications between contralateral normal and tumor, which were investigated and correlated with spectral, cytological and clinical outcomes. A qualitative analysis by grouping patients with number of misclassifications with tumor (Group 1: 0, Group 2: 1 and Group 3: >1) was explored. Group 3 with highest misclassifications showed spectral and cytological similarity to tumor group - one patient was a case of early inoperable residual disease, despite clear margins on histopathology. Thus, these misclassifications could be indicative of cancer field changes, and can prospectively help to identify patients susceptible to recurrences .

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.

Raman spectroscopy on live mouse early embryo while it continues to develop into blastocyst in vitro

Laser based spectroscopic methods can be versatile tools in investigating early stage mammalian embryo structure and biochemical processes in live oocytes and embryos. The limiting factor for using the laser methods in embryological studies is the effect of laser irradiation on the ova. The aim of this work is to explore the optimal parameters of the laser exposure in Raman spectroscopic measurements applicable for studying live early embryos in vitro without impacting their developmental capability. Raman spectra from different areas of mouse oocytes and 2-cells embryos were measured and analyzed. The laser power and exposure time were varied and further embryo development was evaluated to select optimal conditions of the measurements. This work demonstrates safe laser irradiation parameters can be selected, which allow acquisition of Raman spectra suitable for further analysis without affecting the early mouse embryo development in vitro up to morphologically normal blastocyst. The estimation of living embryo state is demonstrated via analysis and comparison of the spectra from fertilized embryo with the spectra from unfertilized oocytes or embryos subjected to UV laser irradiation. These results demonstrate the possibility of investigating preimplantation mammalian embryo development and estimating its state/quality. It will have potential in developing prognosis of mammalian embryos in assisted reproductive technologies.

Double-edged effects of aluminium ions on amyloid fibrillation of hen egg-white lysozyme

Elucidating the effects of Al(III) ions on amyloid fibrillation is important to understand the association between metal ions and Alzheimer's disease. Here, Raman spectroscopy was applied to investigate amyloid fibrillation of hen egg-white lysozymes during thermal incubation with Al(III) ions or acids, combined with atomic force microscopy and thioflavin T fluorescence assays. Kinetics of conformational changes in lysozymes were assessed by monitoring six characteristic Raman spectral markers. The peak of Phe residues at 1003 cm^-1 and two bands of Trp residues at 759 cm^-1 and 1340-1360 cm^-1 corresponded to the lysozyme tertiary structure, whereas two NC_αC stretching vibrations at 899 cm^-1 and 935 cm^-1 and an amide I band were associated with the lysozyme skeleton. There may be a four-stage transformation mechanism underlying the kinetics of amyloid fibrillation of lysozymes with the thermal/Al(III) treatment. Comparison of kinetics under thermal/Al(III) and thermal/acid conditions revealed double-edged roles of Al(III) ions in amyloid fibrillation of lysozymes. Specifically, in addition to postponing α-helix degradation, Al(III) ions accelerated conformational transformations from α-helices to organized β-sheets. The present investigation sheds light on the controversial effects of Al(III) ions on amyloid fibrillation of lysozymes.

Potential use of MCR-ALS for the identification of coeliac-related biochemical changes in hyperspectral Raman maps from pediatric intestinal biopsies

Raman hyperspectral imaging is an emerging practice in biological and biomedical research for label free analysis of tissues and cells. Using this method, both spatial distribution and spectral information of analyzed samples can be obtained. The current study reports the first Raman microspectroscopic characterisation of colon tissues from patients with Coeliac Disease (CD). The aim was to assess if Raman imaging coupled with hyperspectral multivariate image analysis is capable of detecting the alterations in the biochemical composition of intestinal tissues associated with CD. The analytical approach was based on a multi-step methodology: duodenal biopsies from healthy and coeliac patients were measured and processed with Multivariate Curve Resolution Alternating Least Squares (MCR-ALS). Based on the distribution maps and the pure spectra of the image constituents obtained from MCR-ALS, interesting biochemical differences between healthy and coeliac patients has been derived. Noticeably, a reduced distribution of complex lipids in the pericryptic space, and a different distribution and abundance of proteins rich in beta-sheet structures was found in CD patients. The output of the MCR-ALS analysis was then used as a starting point for two clustering algorithms (k-means clustering and hierarchical clustering methods). Both methods converged with similar results providing precise segmentation over multiple Raman images of studied tissues.

Raman micro-spectroscopy analysis of different sperm regions: a species comparison

STUDY QUESTION

Is Raman micro-spectroscopy a valid approach to assess the biochemical hallmarks of sperm regions (head, midpiece and tail) in four different species?

SUMMARY ANSWER

Non-invasive Raman micro-spectroscopy provides spectral patterns enabling the biochemical characterization of the three sperm regions in the four species, revealing however high similarities for each region among species.

WHAT IS KNOWN ALREADY

Raman micro-spectroscopy has been described as an innovative method to assess sperm features having the potential to be used as a non-invasive selection tool. However, except for nuclear DNA, the identification and assignment of spectral bands in Raman-profiles to the different sperm regions is scarce and controversial.

STUDY DESIGN SIZE, DURATION

Raman spectra from head, midpiece and tail of four different species were obtained. Sperm samples were collected and smeared on microscope slides. Air dried samples were subjected to Raman analysis using previously standardized procedures.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Sperm samples from (i) two donors attending the infertility clinic at the Centre of Reproductive Medicine and Andrology; (ii) two C57BL/6 -TgN (ACTbEGFP) 1Osb adult mice; (iii) two adult Cynomolgus monkeys (Macaca fascicularis) and (iv) two sea urchins (Arbacia punctulata) were used to characterize and compare their spectral profiles. Differences and similarities were confirmed by principal component analysis (PCA).

MAIN RESULTS AND THE ROLE OF CHANCE

Several novel region-specific peaks were identified. The three regions could be differentiated by distinctive Raman patterns irrespective of the species. However, regardless of the specie, their main spectral pattern remains mostly unchanged. These results were corroborated by the PCA analysis and suggest that the basic constituents of spermatozoa are biochemically similar among species.

LIMITATIONS REASONS FOR CAUTION

Further research should be performed in live sperm to validate the detected spectral bands and their use as markers of distinctive regions.

WIDER IMPLICATIONS OF THE FINDINGS

Raman peaks that have never been described in the sperm cell were detected. Particularly important are those that are unique to the midpiece as they might be a reference to the identification of sperm mitochondria, whose function is highly correlated with that of sperm. In the future, Raman micro-spectroscopy has the potential to be applied in assessment of male fertility.

LARGE SCALE DATA

N/A.

STUDY FUNDING AND COMPETING INTEREST(S)

This work was supported by BMBF project 'Sperm Ident' (FKZ:13N13024) and the DAAD-CRUP bilateral exchange program (AI A06/16-57213087). S.A. is a recipient of a fellowship from the Portuguese foundation for science and technology (FCT-SFRH/BPD/110160/2015) and R.DC. is a recipient of a DAAD PhD stipend (91590556). There is no competing interest.

Interaction of 5-S-cysteinyl-dopamine with graphene oxide: an experimental and theoretical study for the detection of a Parkinson's disease biomarker

Spectroscopic and theoretical analysis in the adsorption of 5-S-Cys-DA over GO for the development of platform biosensors with Raman spectroscopy.

Chemometric analysis of integrated FTIR and Raman spectra obtained by non-invasive exfoliative cytology for the screening of oral cancer

FTIR spectroscopy and Raman spectroscopy of biological analytes are increasingly explored as screening tools for early detection of cancer.