Heterogeneity of Endothelial Cells Impacts the Functionality of Human Pancreatic In Vitro Models

Endothelial cells (ECs) play a crucial role in maintaining tissue homeostasis and functionality. Depending on their tissue of origin, ECs can be highly heterogeneous regarding their morphology, gene and protein expression, functionality, and signaling pathways. Understanding the interaction between organ-specific ECs and their surrounding tissue is therefore critical when investigating tissue homeostasis, disease development, and progression. In vitro models often lack organ-specific ECs, potentially limiting the translatability and validity of the obtained results. The goal of this study was to assess the differences between commonly used EC sources in tissue engineering applications, including human umbilical vein ECs (HUVECs), human dermal microvascular ECs (hdmvECs), and human foreskin microvascular ECs (hfmvECs), and organ-specific human pancreatic microvascular ECs (hpmvECs), and test their impact on functionality within an in vitro pancreas test system used for diabetes research. Utilizing high-resolution Raman microspectroscopy and Raman imaging in combination with established protein and gene expression analyses and exposure to defined physical signals within microfluidic cultures, we identified that ECs exhibit significant differences in their biochemical composition, relevant protein expression, angiogenic potential, and response to the application of mechanical shear stress. Proof-of-concept results showed that the coculture of isolated human islets of Langerhans with hpmvECs significantly increased the functionality when compared with control islets and islets cocultured with HUVECs. Our study demonstrates that the choice of EC type significantly impacts the experimental results, which needs to be considered when implementing ECs into in vitro models.

Combining Multiple Spectroscopic Techniques to Reveal the Effects of Staphylococcus aureus Infection on Human Bone Tissues

Osteomyelitis (OM) and periprosthetic joint infections (PJIs) are major public health concerns in Western countries due to increased life expectancy. Infections usually occur due to bacterial spread through fractures, implants, or blood-borne transmission. The pathogens trigger an inflammatory response that hinders bone tissue regeneration. Treatment requires surgical intervention, which involves the precise removal of infected tissue, wound cleansing, and local and systemic antibiotic administration. Staphylococcus aureus (SA) is one of the most common pathogens causing infection-induced OM and PJIs. It forms antimicrobial-resistant biofilms and is frequently found in healthcare settings. In this proof-of-concept, we present an approach based on multiple spectroscopic techniques aimed at investigating the effects of SA infection on bone tissue, as well as identifying specific markers useful to detect early bacterial colonization on the tissue surface. A cross-section of a human femoral diaphysis, with negative-culture results, was divided into three parts, and the cortical and trabecular regions were separated from each other. Two portions of each bone tissue type were infected with SA for one and seven days, respectively. Multiple techniques were used to investigate the impact of the infection on bone tissue, Brillouin-Raman microspectroscopy and attenuated total reflection Fourier transform infrared spectroscopy were employed to assess and develop a new noninvasive diagnostic method to detect SA by targeting the bone of the host. The results indicate that exposure to SA infection significantly alters the bone structure, especially in the case of the trabecular type, even after just one day. Moreover, Raman spectral markers of the tissue damage were identified, indicating that this technique can detect the effect of the pathogens' presence in bone biopsies and pave the way for potential application during surgery, due to its nondestructive and contactless nature.

Raman spectroscopic analysis of human blood serum of glaucoma patients supplemented with macular pigment carotenoids

As all major dietary carotenoids are contained in blood, it is a suitable substrate to evaluate their content, in vivo. Following 18-month supplementation of open-angle glaucoma patients with macula-pigment carotenoids (Lutein, Zeaxanthin and Meso-Zeaxanthin) in the European Nutrition in Glaucoma Management trial, Raman spectroscopic analysis of the carotenoid content of pre- and post-supplementation participant blood serum was carried out, to investigate the systemic impact of the supplementation regimen and explore a more direct way of quantifying this impact using routine blood tests. Using a 532 nm laser source for optimal response, a consistent increase in serum carotenoid concentration was observed in the supplemented serum, highest in patients with initial high baseline carotenoid content. A shift in the 1519 cm-1 carotenoid peak also revealed differences in the carotenoid structural profile of the two groups. The findings highlight the potential of Raman spectroscopy toquantify and differentiate carotenoids directly in blood serum.

A comparative analysis of stem cell differentiation on 2D and 3D substrates using Raman microspectroscopy

Chondrogenesis is a complex cellular process that involves the transformation of mesenchymal stem cells (MSCs) into chondrocytes, the specialised cells that form cartilage. In recent years, three-dimensional (3D) culture systems have emerged as a promising approach to studying cell behaviour and development in a more physiologically relevant environment compared to traditional two-dimensional (2D) cell culture. The use of these systems provided insights into the molecular mechanisms that regulate chondrogenesis and has the potential to revolutionise the development of new therapies for cartilage repair and regeneration. This study demonstrates the successful application of Raman microspectroscopy (RMS) as a label-free, non-destructive, and sensitive method to monitor the chondrogenic differentiation of bone marrow-derived rat mesenchymal stem cells (rMSCs) in a collagen type I hydrogel, and explores the potential benefits of 3D hydrogels compared to conventional 2D cell culture environments. rMSCs were cultured on 3D substrates for 3 weeks and their differentiation was monitored by measuring the spectral signatures of their subcellular compartments. Additionally, the evolution of high-density micromass cultures was investigated to provide a comprehensive understanding of the process and complex interactions between cells and their surrounding extracellular matrix. For comparison, rMSCs were induced into chondrogenesis in identical medium conditions for 21 days in monolayer culture. Raman spectra showed that rMSCs cultured in a collagen type I hydrogel are able to undergo a distinct chondrogenic differentiation pathway at a significantly higher rate than the 2D culture cells. 3D cultures expressed stronger and more homogeneous chondrogenesis-associated peaks such as collagens, glycosaminoglycans (GAGs), and aggrecan while manifesting changes in proteins and lipidic content. These results suggest that 3D type I collagen hydrogel substrates are promising for in vitro chondrogenesis studies, and that RMS is a valuable tool for monitoring chondrogenesis in 3D environments.

Direct Readout of Homo- vs Heterochiral Ligand Shell of Quantum Dots

The chiroptical activity of various semiconductor inorganic nanocrystalline materials has typically been tested using circular dichroism or circularly polarized luminescence. Herein, we report on a high-throughput screening method for identifying and differentiating chiroptically active quantum-sized ZnO crystals using Raman spectroscopy combined with principal component analysis. ZnO quantum dots (QDs) coated by structurally diverse homo- and heterochiral aminoalcoholate ligands (cis- and trans-1-amino-2-indanolate, 2-amino-1-phenylethanolate, and diphenyl-2-pyrrolidinemethanolate) were prepared using the one-pot self-supporting organometallic procedure and then extensively studied toward the identification of specific Raman fingerprints and spectral variations. The direct comparison between the spectra demonstrates that it is very difficult to make definite recognition and identification between QDs coated with enantiomers based only on the differences in the respective Raman bands' position shifts and their intensities. However, the applied approach involving the principal component analysis performed on the Raman spectra allows the simultaneous differentiation and identification of the studied QDs. The first and second principal components explain 98, 97, 97, and 87% of the variability among the studied families of QDs and demonstrate the possibility of using the presented method as a qualitative assay. Thus, the reported multivariate approach paves the way for simultaneous differentiation and identification of chirotopically active semiconductor nanocrystals.

Analysis of intra-specific variations in the venom of individual snakes based on Raman spectroscopy

The knowledge of variations in the composition of venoms from different snakes is important from both theoretical and practical points of view, in particular, at developing and selecting an antivenom. Many studies on this topic are conducted with pooled venoms, while the existence and significance of variations in the composition of venoms between individual snakes of the same species are emphasized by many authors. It is important to study both inter- and intra-specific, including intra-population, venom variations, because intra-specific variations in the venom composition may affect the effectiveness of antivenoms as strongly as inter-specific. In this work, based on venom Raman spectroscopy with principal component analysis, we assessed the variations in venoms of individual snakes of the Vipera nikolskii species from two populations and compared these intra-specific variations with inter-specific variations (with regard to the other related species). We demonstrated intra-specific (inter- and intra-population) differences in venom compositions which are smaller than inter-specific variations. We also assessed the compositions of V. nikolskii venoms from two populations to explain inter-population differences. The method used is rapid and requires virtually no preparation of samples, used in extremely small quantities, allowing the venoms of individual snakes to be analyzed. In addition, the method is informative and capable of detecting fairly subtle differences in the composition of venoms.

Raman spectroscopy analysis of human amniotic fluid cells from fetuses with myelomeningocele

Prenatal surgery for the treatment of spina bifida (myelomeningocele, MMC) significantly enhances the neurological prognosis of the patient. To ensure better protection of the spinal cord by large defects, the application of skin grafts produced with cells gained from the amniotic fluid is presently studied. In order to determine the most appropriate cells for this purpose, we tried to shed light on the extremely complex amniotic fluid cellular composition in healthy and MMC pregnancies. We exploited the potential of micro-Raman spectroscopy to analyse and characterize human amniotic fluid cells in total and putative (cKit/CD117-positive) stem cells of fetuses with MMC in comparison with amniotic fluid cells from healthy individuals, human fetal dermal fibroblasts and adult adipose derived stem cells. We found that (i) the differences between healthy and MMC amniocytes can be attributed to specific spectral regions involving collagen, lipids, sugars, tryptophan, aspartate, glutamate, and carotenoids, (ii) MMC amniotic fluid contains two particular cell populations which are absent or reduced in normal pregnancies, (iii) the cKit-negative healthy amniocyte subpopulation shares molecular features with human fetal fibroblasts. On the one hand we demonstrate a different amniotic fluid cellular composition in healthy and MMC pregnancies, on the other our work confirms micro-Raman spectroscopy to be a valuable tool for discriminating cell populations in unknown mixtures of cells.

Synovial fluid research based on SERS and SERRS for enhanced detection of biomarkers in staged osteoarthritis

Surface-enhanced (resonance) Raman scattering (SER(R)S) can extremely enhance Raman intensity of samples, which is helpful for detecting synovial fluid (SF) that does not show Raman activity under normal conditions. In this study, SER(R)S spectra of SF from three different osteoarthritis (OA) stages were collected and analyzed for OA progress, finding that the content of collagen increased throughout the disease, while non-collagen proteins and polysaccharides decreased sharply at advanced OA stage accompanied by the increase of phospholipid. The spectral features and differences were enhanced by salting-out and centrifugation. Much more information on biomolecules at different OA stages was disclosed by using SERRS for the first time, these main trace components (β-carotene, collagen, hyaluronic acid, nucleotide, and phospholipid) can be used as potential biomarkers. It indicates that SERRS has a more comprehensive ability to assist SERS in seeking micro(trace) biomolecules as biomarkers and facilitating accurate and efficient diagnosis and mechanism research of OA.

Metabolic profiling of murine radiation-induced lung injury with Raman spectroscopy and comparative machine learning

Radiation-induced lung injury (RILI) is a dose-limiting toxicity for cancer patients receiving thoracic radiotherapy. As such, it is important to characterize metabolic associations with the early and late stages of RILI, namely pneumonitis and pulmonary fibrosis. Recently, Raman spectroscopy has shown utility for the differentiation of pneumonitic and fibrotic tissue states in a mouse model; however, the specific metabolite-disease associations remain relatively unexplored from a Raman perspective. This work harnesses Raman spectroscopy and supervised machine learning to investigate metabolic associations with radiation pneumonitis and pulmonary fibrosis in a mouse model. To this end, Raman spectra were collected from lung tissues of irradiated/non-irradiated C3H/HeJ and C57BL/6J mice and labelled as normal, pneumonitis, or fibrosis, based on histological assessment. Spectra were decomposed into metabolic scores via group and basis restricted non-negative matrix factorization, classified with random forest (GBR-NMF-RF), and metabolites predictive of RILI were identified. To provide comparative context, spectra were decomposed and classified via principal component analysis with random forest (PCA-RF), and full spectra were classified with a convolutional neural network (CNN), as well as logistic regression (LR). Through leave-one-mouse-out cross-validation, we observed that GBR-NMF-RF was comparable to other methods by measure of accuracy and log-loss (p > 0.10 by Mann-Whitney U test), and no methodology was dominant across all classification tasks by measure of area under the receiver operating characteristic curve. Moreover, GBR-NMF-RF results were directly interpretable and identified collagen and specific collagen precursors as top fibrosis predictors, while metabolites with immune and inflammatory functions, such as serine and histidine, were top pneumonitis predictors. Further support for GBR-NMF-RF and the identified metabolite associations with RILI was found as CNN interpretation heatmaps revealed spectral regions consistent with these metabolites.

Raman difference spectroscopy and U-Net convolutional neural network for molecular analysis of cutaneous neurofibroma

In Neurofibromatosis type 1 (NF1), peripheral nerve sheaths tumors are common, with cutaneous neurofibromas resulting in significant aesthetic, painful and functional problems requiring surgical removal. To date, determination of adequate surgical resection margins-complete tumor removal while attempting to preserve viable tissue-remains largely subjective. Thus, residual tumor extension beyond surgical margins or recurrence of the disease may frequently be observed. Here, we introduce Shifted-Excitation Raman Spectroscopy in combination with deep neural networks for the future perspective of objective, real-time diagnosis, and guided surgical ablation. The obtained results are validated through established histological methods. In this study, we evaluated the discrimination between cutaneous neurofibroma (n = 9) and adjacent physiological tissues (n = 25) in 34 surgical pathological specimens ex vivo at a total of 82 distinct measurement loci. Based on a convolutional neural network (U-Net), the mean raw Raman spectra (n = 8,200) were processed and refined, and afterwards the spectral peaks were assigned to their respective molecular origin. Principal component and linear discriminant analysis was used to discriminate cutaneous neurofibromas from physiological tissues with a sensitivity of 100%, specificity of 97.3%, and overall classification accuracy of 97.6%. The results enable the presented optical, non-invasive technique in combination with artificial intelligence as a promising candidate to ameliorate both, diagnosis and treatment of patients affected by cutaneous neurofibroma and NF1.

Exploring the in vitro potential of royal jelly against glioblastoma and neuroblastoma: impact on cell proliferation, apoptosis, cell cycle, and the biomolecular content

Neuroblastoma and glioblastoma are the most commonly seen nervous system tumors, and their treatment is challenging. Relatively safe and easy acquisition of nutraceutical natural products make them suitable candidates for anticancer research. Royal jelly (RJ), a superfood, has many biological and pharmacological activities. This study was conducted to, for the first time, elucidate its anticancer efficiency, even in high doses, on neuroblastoma and glioblastoma cell lines through cell viability, apoptosis, cell cycle and biomolecular content evaluation. We performed experiments with RJ concentrations in the range of 1.25-10 mg mL-1 for 48 h. Cell viability assays revealed a notable cytotoxic effect of RJ in a concentration-dependent manner. Treatment with a high dose of RJ significantly increased the apoptotic cell population of both cell lines. Furthermore, we observed G0-G1 phase arrest in neuroblastoma cells but G2-M arrest in glioblastoma cells. All these cellular changes are closely associated with the alterations of the macromolecular makeup of the cells, such as decreased saturated lipid, protein, DNA and RNA amounts, protein conformational changes, decreased protein phosphorylation and increased protein carbonylation. These cellular changes are associated with RJ triggered-ROS formation. The clear segregation between the control and the RJ-treated groups proved these changes, obtained from the unsupervised and supervised chemometric analysis. RJ has good anticancer activity against nervous system cancers and could be safely used with current treatment strategies.

Adaptive mechanism of the marine bacterium Pseudomonas sihuiensis-BFB-6S towards pCO2 variation: Insights into synthesis of extracellular polymeric substances and physiochemical modulation

Marine bacteria can adapt to various extreme environments by the production of extracellular polymeric substances (EPS). Throughout this investigation, impact of variable pCO2 levels on the metabolic activity and physiochemical modulation in EPS matrix of marine bacterium Pseudomonas sihuiensis - BFB-6S was evaluated using a fluorescence microscope, excitation-emission matrix (EEM), 2D-Fourier transform infrared correlation spectroscopy (2D-ATR-FTIR-COS), FT-NMR and TGA-DSC. From the results at higher pCO2 levels, there was a substantial reduction in EPS production by 58-62.8 % (DW). In addition to the biochemical composition of EPS, reduction in carbohydrates (8.7-47.6 %), protein (7.1-91.5 %), and lipids (16.9-68.6 %) content were observed at higher pCO2 levels. Functional discrepancies of fluorophores (tyrosine and tryptophan-like) in EPS, speckled differently in response to variable pCO2. The 2D-ATR-FTIR-COS analysis revealed functional amides (CN, CC, CO bending, -NH bending in amines) of EPS were preferentially altered, which led to the domination of polysaccharides relevant functional groups at higher pCO2. 1H NMR analysis of EPS confirmed the absence of chemical signals from H-C-COOH of proteins, α, β anomeric protons, and acetyl group relevant region at higher pCO2 levels. These findings can contribute new insights into the influence of pCO2 on the adaptation of marine microbes in future ocean acidification scenarios.

RSPSSL: A novel high-fidelity Raman spectral preprocessing scheme to enhance biomedical applications and chemical resolution visualization

Raman spectroscopy has tremendous potential for material analysis with its molecular fingerprinting capability in many branches of science and technology. It is also an emerging omics technique for metabolic profiling to shape precision medicine. However, precisely attributing vibration peaks coupled with specific environmental, instrumental, and specimen noise is problematic. Intelligent Raman spectral preprocessing to remove statistical bias noise and sample-related errors should provide a powerful tool for valuable information extraction. Here, we propose a novel Raman spectral preprocessing scheme based on self-supervised learning (RSPSSL) with high capacity and spectral fidelity. It can preprocess arbitrary Raman spectra without further training at a speed of ~1 900 spectra per second without human interference. The experimental data preprocessing trial demonstrated its excellent capacity and signal fidelity with an 88% reduction in root mean square error and a 60% reduction in infinite norm ([Formula: see text]) compared to established techniques. With this advantage, it remarkably enhanced various biomedical applications with a 400% accuracy elevation (ΔAUC) in cancer diagnosis, an average 38% (few-shot) and 242% accuracy improvement in paraquat concentration prediction, and unsealed the chemical resolution of biomedical hyperspectral images, especially in the spectral fingerprint region. It precisely preprocessed various Raman spectra from different spectroscopy devices, laboratories, and diverse applications. This scheme will enable biomedical mechanism screening with the label-free volumetric molecular imaging tool on organism and disease metabolomics profiling with a scenario of high throughput, cross-device, various analyte complexity, and diverse applications.

Raman spectroscopy combined with multivariate statistical algorithms for the simultaneous screening of cervical and breast cancers

Breast and cervical cancers are becoming the leading causes of death among women worldwide, but current diagnostic methods have many drawbacks, such as being time-consuming and high cost. Raman spectroscopy, as a rapid, reliable, and non-destructive spectroscopic detection technique, has achieved many breakthrough results in the screening and prognosis of various cancer tumors. Therefore, in this study, Raman spectroscopy technology was used to diagnose breast cancer and cervical cancer. A total of 225 spectra were recorded from 87 patients with cervical cancer, 60 patients with breast cancer, and 78 healthy individuals. The obvious difference in Raman spectrum between the three groups was mainly shown at 809 cm-1 (tyrosine), 958 cm-1 (carotenoid), 1004 cm-1 (phenylalanine), 1154 cm-1 (β-carotene), 1267 cm-1 (Amide III), 1445 cm-1 (phospholipids), 1515 cm-1 (β-carotene), and 1585 cm-1 (C = C olefinic stretch). We used one-way analysis of variance for these peaks and demonstrated that they were significantly different. Then, we combined the detected Raman spectra with multivariate statistical calculations using the principal component analysis-linear discrimination algorithm (PCA-LDA) to discriminate between the three groups of collected serum samples. The diagnostic results showed that the model's accuracy, precision, recall, and F1 score of the model were 92.90%, 92.62%, 92.10%, and 92.36%, respectively. These results suggest that Raman spectroscopy can achieve ultra-sensitive detection of serum, and the developed diagnostic models have great potential for the prognosis and simultaneous screening of cervical and breast cancers.

Cancer detection in dogs using rapid Raman molecular urinalysis

Introduction

The presence of cancer in dogs was detected by Raman spectroscopy of urine samples and chemometric analysis of spectroscopic data. The procedure created a multimolecular spectral fingerprint with hundreds of features related directly to the chemical composition of the urine specimen. These were then used to detect the broad presence of cancer in dog urine as well as the specific presence of lymphoma, urothelial carcinoma, osteosarcoma, and mast cell tumor.

Methods

Urine samples were collected via voiding, cystocentesis, or catheterization from 89 dogs with no history or evidence of neoplastic disease, 100 dogs diagnosed with cancer, and 16 dogs diagnosed with non-neoplastic urinary tract or renal disease. Raman spectra were obtained of the unprocessed bulk liquid urine samples and were analyzed by ISREA, principal component analysis (PCA), and discriminant analysis of principal components (DAPC) were applied using the Rametrix®Toolbox software.

Results and discussion

The procedure identified a spectral fingerprint for cancer in canine urine, resulting in a urine screening test with 92.7% overall accuracy for a cancer vs. cancer-free designation. The urine screen performed with 94.0% sensitivity, 90.5% specificity, 94.5% positive predictive value (PPV), 89.6% negative predictive value (NPV), 9.9 positive likelihood ratio (LR+), and 0.067 negative likelihood ratio (LR-). Raman bands responsible for discerning cancer were extracted from the analysis and biomolecular associations were obtained. The urine screen was more effective in distinguishing urothelial carcinoma from the other cancers mentioned above. Detection and classification of cancer in dogs using a simple, non-invasive, rapid urine screen (as compared to liquid biopsies using peripheral blood samples) is a critical advancement in case management and treatment, especially in breeds predisposed to specific types of cancer.

Raman classification of selected subtypes of acute lymphoblastic leukemia (ALL)

B-cell precursor acute lymphoblastic leukemia (BCP-ALL) with chromosome translocations like KMT2A gene rearrangement (KMT2A-r) and BCR-ABL1 fusion gene have been recognized as crucial drivers in both BCP-ALL leukemogenesis and treatment management. Standard diagnostic protocols for proliferative diseases of the hematopoietic system, like KMT2A-r-ALL, are genetically based and strongly molecularly oriented. Therefore, an efficient diagnostic procedure requires not only experienced and multidisciplinary laboratory staff but also considerable instrumentation and material costs. In recent years, a Raman spectroscopy method has been increasingly used to detect subtle chemical changes in individual cells resulting from stress or disease. Therefore, the objective of this study was to identify Raman signatures for the molecular subtypes and to develop a classification method based on the unique spectroscopic profile of in vitro models that represent specific aberrations aimed at KMT2A-r (RS4;11, and SEM) and the BCR-ABL1 fusion gene (SUP-B15, BV-173, and SD-1). Data analysis was based on chemometric methods, i.e. principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and support vector machine (SVM). The PCA-based multivariate model was used for pattern recognition of each investigated group of cells while PLS-DA and SVM were used to build models for the discrimination of spectra from the studied BCP-ALL molecular subtypes. The results showed that the studied molecular subtypes of ALL have characteristic spectroscopic profiles reflecting their peculiar biochemical state. The content of lipids (1600 cm-1), nucleic acids (789 cm-1), and haemoproteins (754, 1130, and 1315 cm-1), which are crucial in cell metabolism, was indicated as the main source of differentiation between subtypes. Identification of spectroscopic markers of cells with BCR-ABL1 or KMT2A-r may be useful in pharmacological studies to monitor the effectiveness of chemotherapy and further to understand differences in molecular responses between leukemia primary cells and cell lines.

Raman spectroscopy and its plasmon-enhanced counterparts: A toolbox to probe protein dynamics and aggregation

Protein unfolding and aggregation are often correlated with numerous diseases such as Alzheimer's, Parkinson's, Huntington's, and other debilitating neurological disorders. Such adverse events consist of a plethora of competing mechanisms, particularly interactions that control the stability and cooperativity of the process. However, it remains challenging to probe the molecular mechanism of protein dynamics such as aggregation, and monitor them in real-time under physiological conditions. Recently, Raman spectroscopy and its plasmon-enhanced counterparts, such as surface-enhanced Raman spectroscopy (SERS) and tip-enhanced Raman spectroscopy (TERS), have emerged as sensitive analytical tools that have the potential to perform molecular studies of functional groups and are showing significant promise in probing events related to protein aggregation. We summarize the fundamental working principles of Raman, SERS, and TERS as nondestructive, easy-to-perform, and fast tools for probing protein dynamics and aggregation. Finally, we highlight the utility of these techniques for the analysis of vibrational spectra of aggregation of proteins from various sources such as tissues, pathogens, food, biopharmaceuticals, and lastly, biological fouling to retrieve precise chemical information, which can be potentially translated to practical applications and point-of-care (PoC) devices. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Diagnostic Tools > Diagnostic Nanodevices Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

Differentiation of Salivary Gland and Salivary Gland Tumor Tissue via Raman Imaging Combined with Multivariate Data Analysis

Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90% and validated by predicting model-unknown Raman spectra, of which 93% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.

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

IMPORTANCE

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

Precise diagnosis of breast phyllodes tumors using Raman spectroscopy: Biochemical fingerprint, tumor metabolism and possible mechanism

BACKGROUND

Breast fibroadenomas and phyllodes tumors are both fibroepithelial tumors with comparable histological characteristics. However, rapid and precise differential diagnosis is a tough point in clinical pathology. Given the tendency of phyllodes tumors to recur, the difficulty in differential diagnosis with fibroadenomas leads to the difficulty in optimal management for these patients.

METHOD

In this study, we used Raman spectroscopy to differentiate phyllodes tumors from breast fibroadenomas based on the biochemical and metabolic composition and develop a classification model. The model was validated by 5-fold cross-validation in the training set and tested in an independent test set. The potential metabolic differences between the two types of tumors observed in Raman spectroscopy were confirmed by targeted metabolomic analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

A total of 204 patients with formalin-fixed paraffin-embedded (FFPE) tissue samples, including 100 fibroadenomas and 104 phyllodes tumors were recruited from April 2014 to August 2021. All patients were randomly divided into the training cohort (n = 153) and the test cohort (n = 51). The Raman classification model could differentiate phyllodes tumor versus fibroadenoma with cross-validation accuracy, sensitivity, precision, and area under curve (AUC) of 85.58 % ± 1.77 %, 83.82 % ± 1.01 %, 87.65 % ± 4.22 %, and 93.18 % ± 1.98 %, respectively. When tested in the independent test set, it performed well with the test accuracy, sensitivity, specificity, and AUC of 83.50 %, 86.54 %, 80.39 %, and 90.71 %. Furthermore, the AUC was significantly higher for the Raman model than that for ultrasound (P = 0.0017) and frozen section diagnosis (P < 0.0001). When it came to much more difficult diagnosis between fibroadenoma and benign or small-size phyllodes tumor for pathological examination, the Raman model was capable of differentiating with AUC up to 97.45 % and 95.61 %, respectively. On the other hand, targeted metabolomic analysis, based on fresh-frozen tissue samples, confirmed the differential metabolites (including thymine, dihydrothymine, trans-4-hydroxy-l-proline, etc.) identified from Raman spectra between phyllodes tumor and fibroadenoma.

SIGNIFICANCE AND NOVELTY

In this study, we obtained the molecular information map of breast phyllodes tumors provided by Raman spectroscopy for the first time. We identified a novel Raman fingerprint signature with the potential to precisely characterize and distinguish phyllodes tumors from fibroadenoma as a quick and accurate diagnostic tool. Raman spectroscopy is expected to further guide the precise diagnosis and optimal treatment of breast fibroepithelial tumors in the future.

Sub-THz acoustic excitation of protein motion

The application of terahertz radiation has been shown to affect both protein structure and cellular function. As the key to such structural changes lies in the dynamic response of a protein, we focus on the susceptibility of the protein's internal dynamics to mechanical stress induced by acoustic pressure waves. We use the open-boundary molecular dynamics method, which allows us to simulate the protein exposed to acoustic waves. By analyzing the dynamic fluctuations of the protein subunits, we demonstrate that the protein is highly susceptible to acoustic waves with frequencies corresponding to those of the internal protein vibrations. This is confirmed by changes in the compactness of the protein structure. As the amplitude of the pressure wave increases, even larger deviations from average positions and larger changes in protein compactness are observed. Furthermore, performing the mode-projection analysis, we show that the breathing-like character of collective modes is enhanced at frequencies corresponding to those used to excite the protein.

Characterization of Distinct Chondrogenic Cell Populations of Patients Suffering from Microtia Using Single-Cell Micro-Raman Spectroscopy

Microtia is a congenital condition of abnormal development of the outer ear. Tissue engineering of the ear is an alternative treatment option for microtia patients. However, for this approach, the identification of high regenerative cartilage progenitor cells is of vital importance. Raman analysis provides a novel, non-invasive, label-free diagnostic tool to detect distinctive biochemical features of single cells or tissues. Using micro-Raman spectroscopy, we were able to distinguish and characterize the particular molecular fingerprints of differentiated chondrocytes and perichondrocytes and their respective progenitors isolated from healthy individuals and microtia patients. We found that microtia chondrocytes exhibited lower lipid concentrations in comparison to healthy cells, thus indicating the importance of fat storage. Moreover, we suggest that collagen is a useful biomarker for distinguishing between populations obtained from the cartilage and perichondrium because of the higher spectral contributions of collagen in the chondrocytes compared to perichondrocytes from healthy individuals and microtia patients. Our results represent a contribution to the identification of cell markers that may allow the selection of specific cell populations for cartilage tissue engineering. Moreover, the observed differences between microtia and healthy cells are essential for gaining better knowledge of the cause of microtia. It can be useful for designing novel treatment options based on further investigations of the discovered biochemical substrate alterations.

Multivariate curve Resolution-Alternating least squares coupled with Raman microspectroscopy: new insights into the kinetic response of primary oral squamous carcinoma cells to cisplatin

Raman MicroSpectroscopy (RMS) is a powerful label-free tool to probe the effects of drugs at a cellular/subcellular level. It is important, however, to be able to extract relevant biochemical and kinetic spectroscopic signatures of the specific cellular responses. In the present study, a combination of Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Principal Component Analysis (PCA) is used to analyse the RMS data for the example of exposure of primary Oral Squamous Carcinoma Cells (OSCC) to the chemotherapeutic agent cisplatin. Dosing regimens were established by cytotoxicity assays, and the effects of the drug on cellular spectral profiles were monitored from 16 to 72 hours post-exposure using an apoptosis assay, to establish the relative populations of viable (V), early (EA) and late apoptotic/dead (LA/D) cells after the drug treatment. Based on a kinetic model of the progression from V > EA > D, MCR-ALS regression analysis of the RMS responses was able to extract spectral profiles associated with each stage of the cellular responses, enabling a quantitative comparison of the response rates for the respective drug treatments. Moreover, PCA was used to compare the spectral profiles of the viable cells exposed to the drug. Spectral differences were highlighted in the early stages (16 hours exposure), indicative of the initial cellular response to the drug treatment, and also in the late stages (48-72 hours exposure), representing the cell death pathway. The study demonstrates that RMS coupled with multivariate analysis can be used to quantitatively monitor the progression of cellular responses to different drugs, towards future applications for label-free, in vitro, pre-clinical screening.

Label-Free Quantification of Nanoencapsulated Piperonyl Esters in Cosmetic Hydrogels Using Raman Spectroscopy

Raman spectroscopy is a well-established technique for the molecular characterisation of samples and does not require extensive pre-analytical processing for complex cosmetic products. As an illustration of its potential, this study investigates the quantitative performance of Raman spectroscopy coupled with partial least squares regression (PLSR) for the analysis of Alginate nanoencapsulated Piperonyl Esters (ANC-PE) incorporated into a hydrogel. A total of 96 ANC-PE samples covering a 0.4% w/w-8.3% w/w PE concentration range have been prepared and analysed. Despite the complex formulation of the sample, the spectral features of the PE can be detected and used to quantify the concentrations. Using a leave-K-out cross-validation approach, samples were divided into a training set (n = 64) and a test set, samples that were previously unknown to the PLSR model (n = 32). The root mean square error of cross-validation (RMSECV) and prediction (RMSEP) was evaluated to be 0.142% (w/w PE) and 0.148% (w/w PE), respectively. The accuracy of the prediction model was further evaluated by the percent relative error calculated from the predicted concentration compared to the true value, yielding values of 3.58% for the training set and 3.67% for the test set. The outcome of the analysis demonstrated the analytical power of Raman to obtain label-free, non-destructive quantification of the active cosmetic ingredient, presently PE, in complex formulations, holding promise for future analytical quality control (AQC) applications in the cosmetics industry with rapid and consumable-free analysis.

Spectroscopic signature of ZnO NP-induced cell death modalities assessed by non-negative PCA

Selective cytotoxicity of ZnO nanoparticles among different cell types and cancer and non-cancerous cells has been demonstrated earlier. In the view of anticancer potential of ZnO nanoparticles and their presence in numerous industrial products, it is of great importance to carefully evaluate their effects and mechanisms of action in both cancerous and healthy cells. In this paper, the effects of ZnO nanoparticles on cancerous HeLa and non-cancerous MRC-5 cells are investigated by studying the changes in the vibrational properties of the cells using Raman spectroscopy. Both types of cells were incubated with ZnO nanoparticles of average size 40 nm in the doses from the range 10-40 µg/ml for the period of 48 h, after which Raman spectra were collected. Raman modes' intensity ratios I₁₆₅₉/I₁₄₄₄, I₂₈₅₅/I₂₉₃₃ and I₁₃₃₇/I₁₃₀₅ were determined as spectral markers of the cytotoxic effect of ZnO in both cell types. Non-negative principal component analysis was used instead of standard one for analysis and detection of spectral features characteristic for nanoparticle-treated cells. The first several non-negative loading vectors obtained in this analysis coincided remarkably well with the Raman spectra of particular biomolecules, showing increase of lipid and decrease of nucleic acids and protein content. Our study pointed out that Raman spectral markers of lipid unsaturation, especially I₁₂₇₀/I₁₃₀₀, are relevant for tracing the cytotoxic effect of ZnO nanoparticles on both cancerous and non-cancerous cells. The change of these spectral markers is correlated to the dose of applied nanoparticles and to the degree of cellular damage. Furthermore, great similarity of spectral features of increasing lipids to spectral features of phosphatidylserine, one of the main apoptotic markers, was recognized in treated cells. Finally, the results strongly indicated that the degree of lipid saturation, presented in the cells, plays an important role in the interaction of cells with nanoparticles.

Gestational Diabetes Mellitus and Small-for-Gestational-Age: An Insight into the Placental Molecular Biomarkers

Gestational diabetes mellitus (GDM) and small-for-gestational-age (SGA) are two metabolic-related diseases that could affect women during pregnancy. Considering that the chorionic villi (CVs) are crucial structures for the feto-maternal exchange, the alterations in their conformation have been linked to an imbalanced metabolic environment of placenta. In this study, a multidisciplinary approach has been carried out to describe the changes occurring in the placental CVs of GDM and SGA patients. The results revealed higher levels of superoxide dismutase 1 (SOD-1) and catalase (CAT), especially in the GDM placentae, which could be correlated with the hyperglycemic environment characteristic of this pathology. Furthermore, spectroscopy and histologic analyses revealed that both pathologies modify the placental lipid composition altering its structure. However, SGA induces lipid peroxidation and reduces collagen deposition within the CVs. Since the endocannabinoid system (ECS) is involved in placentation and different metabolic activities, the cannabinoid receptor 1 (CB1) and transient receptor potential cation channel subfamily V member 1 (TRPV-1) were analyzed. No changes have been observed either at general or specific levels in the CVs comparing control and pathological samples, suggesting the non-involvement of the cannabinoid system in these two pathologies.

Raman Spectroscopy of Carotenoid Compounds for Clinical Applications-A Review

Carotenoid compounds are ubiquitous in nature, providing the characteristic colouring of many algae, bacteria, fruits and vegetables. They are a critical component of the human diet and play a key role in human nutrition, health and disease. Therefore, the clinical importance of qualitative and quantitative carotene content analysis is increasingly recognised. In this review, the structural and optical properties of carotenoid compounds are reviewed, differentiating between those of carotenes and xanthophylls. The strong non-resonant and resonant Raman spectroscopic signatures of carotenoids are described, and advances in the use of Raman spectroscopy to identify carotenoids in biological environments are reviewed. Focus is drawn to applications in nutritional analysis, optometry and serology, based on in vitro and ex vivo measurements in skin, retina and blood, and progress towards establishing the technique in a clinical environment, as well as challenges and future perspectives, are explored.

Aligned nanofibrous collagen membranes from fish swim bladder as a tough and acid-resistant suture for pH-regulated stomach perforation and tendon rupture

BACKGROUND

Wound closure in the complex body environment places higher requirements on suture's mechanical and biological performance. In the scenario of frequent mechanical gastric motility and extremely low pH, single functional sutures have limitations in dealing with stomach bleeding trauma where the normal healing will get deteriorated in acid. It necessitates to advance suture, which can regulate wounds, resist acid and intelligently sense stomach pH.

METHODS

Based on fish swim bladder, a double-stranded drug-loaded suture was fabricated. Its cytotoxicity, histocompatibility, mechanical properties, acid resistance and multiple functions were verified. Also, suture's performance suturing gastric wounds and Achilles tendon was verified in an in vivo model.

RESULTS

By investigating the swim bladder's multi-scale structure, the aligned tough collagen fibrous membrane can resist high hydrostatic pressure. We report that the multi-functional sutures on the twisted and aligned collagen fibers have acid resistance and low tissue reaction. Working with an implantable "capsule robot", the smart suture can inhibit gastric acid secretion, curb the prolonged stomach bleeding and monitor real-time pH changes in rabbits and pigs. The suture can promote stomach healing and is strong enough to stitch the fractured Achilles tendon.

CONCLUSIONS

As a drug-loaded absorbable suture, the suture shows excellent performance and good application prospect in clinical work.

Raman spectroscopy and supervised learning as a potential tool to identify high-dose-rate-brachytherapy induced biochemical profiles of prostate cancer

High-dose-rate-brachytherapy (HDR-BT) is an increasingly attractive alternative to external beam radiation-therapy for patients with intermediate risk prostate cancer. Despite this, no bio-marker based method currently exists to monitor treatment response, and the changes which take place at the biochemical level in hypo-fractionated HDR-BT remain poorly understood. The aim of this pilot study is to assess the capability of Raman spectroscopy (RS) combined with principal component analysis (PCA) and random-forest classification (RF) to identify radiation response profiles after a single dose of 13.5 Gy in a cohort of nine patients. We here demonstrate, as a proof-of-concept, how RS-PCA-RF could be utilised as an effective tool in radiation response monitoring, specifically assessing the importance of low variance PCs in complex sample sets. As RS provides information on the biochemical composition of tissue samples, this technique could provide insight into the changes which take place on the biochemical level, as result of HDR-BT treatment.

Preeclampsia Correlates with an Increase in Cannabinoid Receptor 1 Levels Leading to Macromolecular Alterations in Chorionic Villi of Term Placenta

Preeclampsia is a human pregnancy-specific disease characterized by abnormal placentation that usually presents with maternal hypertension and proteinuria. The main hallmark of preeclampsia, impaired trophoblast migration, and the subsequent disruption of uterine arteries remodeling lead to several molecular alterations in the placental compartments with those occurring in the chorionic villi being of the utmost importance. Given the essential role of the endocannabinoid system during preimplantation and trophoblast migration, we have combined the histological and hyperspectral imaging analyses to shed light on the involvement of two cannabinoid receptors in the macromolecular alterations related to preeclampsia. The results obtained by immunohistochemistry showed a significant increase in the protein levels of cannabinoid receptor 1 (CB1) in the preeclamptic chorionic villi. However, no changes were reported regarding transient receptor potential vanilloid 1 (TRPV-1) levels either in the bulk placental samples or chorionic villi when comparing control and preeclamptic patients. Histological analysis and Fourier-transform infrared spectroscopy (FTIRI) showed an increase in collagen deposition together with higher levels of lipid peroxidation and phosphorylated compounds in the pathological villi. Since CB1 enhancement has been described as promoting fibrosis and oxidative stress in several tissues, we proposed that the higher receptor abundance in preeclampsia could be triggering similar molecular effects in preeclamptic term placentas.

Analysis of Biologics Molecular Descriptors towards Predictive Modelling for Protein Drug Development Using Time-Gated Raman Spectroscopy

Pharmaceutical proteins, compared to small molecular weight drugs, are relatively fragile molecules, thus necessitating monitoring protein unfolding and aggregation during production and post-marketing. Currently, many analytical techniques take offline measurements, which cannot directly assess protein folding during production and unfolding during processing and storage. In addition, several orthogonal techniques are needed during production and market surveillance. In this study, we introduce the use of time-gated Raman spectroscopy to identify molecular descriptors of protein unfolding. Raman spectroscopy can measure the unfolding of proteins in-line and in real-time without labels. Using K-means clustering and PCA analysis, we could correlate local unfolding events with traditional analytical methods. This is the first step toward predictive modeling of unfolding events of proteins during production and storage.

Quantitative Raman Analysis of Carotenoid Protein Complexes in Aqueous Solution

Carotenoids are naturally abundant, fat-soluble pigmented compounds with dietary, antioxidant and vision protection advantages. The dietary carotenoids, Beta Carotene, Lutein, and Zeaxanthin, complexed with in bovine serum albumin (BSA) in aqueous solution, were explored using Raman spectroscopy to differentiate and quantify their spectral signatures. UV visible absorption spectroscopy was employed to confirm the linearity of responses over the concentration range employed (0.05–1 mg/mL) and, of the 4 Raman source wavelengths (785 nm, 660 nm, 532 nm, 473 nm), 532 nm was chosen to provide the optimal response. After preprocessing to remove water and BSA contributions, and correct for self-absorption, a partial least squares model with R2 of 0.9995, resulted in an accuracy of the Root Mean Squared Error of Prediction for Beta Carotene of 0.0032 mg/mL and Limit of Detection 0.0106 mg/mL. Principal Components Analysis clearly differentiated solutions of the three carotenoids, based primarily on small shifts of the main peak at ~1520 cm−1. Least squares fitting analysis of the spectra of admixtures of the carotenoid:protein complexes showed reasonable correlation between norminal% and fitted%, yielding 100% contribution when fitted with individual carotenoid complexes and variable contributions with multiple ratios of admixtures. The results indicate the technique can potentially be used to quantify the carotenoid content of human serum and to identify their differential contributions for application in clinical analysis.

The structural effects of Vitamin A deficiency on biological macromolecules due to ethanol consumption and withdrawal: An FTIR study with chemometrics

The structural effects of vitamin A-deficiency were examined on the molecular profiles of biomolecules of male rat hippocampus during prolonged ethanol intake/withdrawal using FT-IR spectroscopy coupled with chemometrics. Liquid ethanol diet with/without vitamin A was maintained to adult rats for 3-months. The rats were decapitated at different ethanol withdrawal times and FT-IR spectra were obtained. Ethanol consumption/withdrawal produced significant changes in proteins' conformations, while having insignificant structural effects on lipids. In vitamin A deficiency, ethanol produced structural changes in lipids by lipid ordering especially in the early-ethanol withdrawal. Furthermore, an increase in lipid and protein content, saturated/unsaturated lipid ratio, a decrease in nucleic acids content and decrease in membrane fluidity were observed. These changes were less severe in the presence of Vitamin A. This study is clinically important for individuals with vitamin A deficiency because they have to be more cautious when consuming alcohol to protect themselves from cognitive dysfunctions.

Label-Free Imaging of Lipid Droplets in Prostate Cells Using Stimulated Raman Scattering Microscopy and Multivariate Analysis

Hyperspectral stimulated Raman scattering (SRS) microscopy is a powerful imaging modality for the analysis of biological systems. Here, we report the application of k-means cluster analysis (KMCA) of multi-wavelength SRS images in the high-wavenumber region of the Raman spectrum as a robust and reliable method for the segmentation of cellular organelles based on the intrinsic SRS spectrum. KMCA has been applied to the study of the endogenous lipid biochemistry of prostate cancer and prostate healthy cell models, while the corresponding SRS spectrum of the lipid droplet (LD) cluster enabled direct comparison of their composition. The application of KMCA in visualizing the LD content of prostate cell models following the inhibition of de novo lipid synthesis (DNL) using the acetyl-coA carboxylase inhibitor, 5-(tetradecyloxy)-2-furoic acid (TOFA), is demonstrated. This method identified a reliance of prostate cancer cell models upon DNL for metabolic requirements, with a significant reduction in the cellular LD content after treatment with TOFA, which was not observed in normal prostate cell models. SRS imaging combined with KMCA is a robust method for investigating drug–cell interactions in a label-free manner.

A micro-Raman spectroscopy study of inflammatory condition of human cervix: Probing of Tissues and blood plasma samples

The present study explores the application of the micro-Raman spectroscopy technique to discriminate normal and cervicitis condition from cervical malignancy by analyzing the Raman signatures of tissues and plasma samples of the same subjects. The Raman peaks from tissue samples at 1026 cm^-1,1298 cm^-1 and 1243 cm^-1 are attributed to glycogen, fatty acids and collagen and are found to be reliable signatures capable of identifying cervicitis and normal condition from cervical cancer. The Raman signatures from plasma samples belonging to carbohydrates (578 cm^-1), lipids (1059 cm^-1) and nucleic acids (1077 cm^-1,1341 cm^-1 and 1357 cm^-1) are quite useful to classify various stages of cervix at par with tissue based diagnosis. The PCA-SVM based classification of the spectral data indicates the potential of Raman spectroscopy based liquid biopsy to rule out false diagnosis of cervicitis as cervical malignancy.

A Comparison of PCA-LDA and PLS-DA Techniques for Classification of Vibrational Spectra

Vibrational spectroscopies provide information about the biochemical and structural environment of molecular functional groups inside samples. Over the past few decades, Raman and infrared-absorption-based techniques have been extensively used to investigate biological materials under different pathological conditions. Interesting results have been obtained, so these techniques have been proposed for use in a clinical setting for diagnostic purposes, as complementary tools to conventional cytological and histological techniques. In most cases, the differences between vibrational spectra measured for healthy and diseased samples are small, even if these small differences could contain useful information to be used in the diagnostic field. Therefore, the interpretation of the results requires the use of analysis techniques able to highlight the minimal spectral variations that characterize a dataset of measurements acquired on healthy samples from a dataset of measurements relating to samples in which a pathology occurs. Multivariate analysis techniques, which can handle large datasets and explore spectral information simultaneously, are suitable for this purpose. In the present study, two multivariate statistical techniques, principal component analysis-linear discriminate analysis (PCA-LDA) and partial least square-discriminant analysis (PLS-DA) were used to analyse three different datasets of vibrational spectra, each one including spectra of two different classes: (i) a simulated dataset comprising control-like and exposed-like spectra, (ii) a dataset of Raman spectra measured for control and proton beam-exposed MCF10A breast cells and (iii) a dataset of FTIR spectra measured for malignant non-metastatic MCF7 and metastatic MDA-MB-231 breast cancer cells. Both PCA-LDA and PLS-DA techniques were first used to build a discrimination model by using calibration sets of spectra extracted from the three datasets. Then, the classification performance was established by using test sets of unknown spectra. The achieved results point out that the built classification models were able to distinguish the different spectra types with accuracy between 93% and 100%, sensitivity between 86% and 100% and specificity between 90% and 100%. The present study confirms that vibrational spectroscopy combined with multivariate analysis techniques has considerable potential for establishing reliable diagnostic models.

Raman Spectroscopy in Prostate Cancer: Techniques, Applications and Advancements

Optical techniques are widely used tools in the visualisation of biological species within complex matrices, including biopsies, tissue resections and biofluids. Raman spectroscopy is an emerging analytical approach that probes the molecular signature of endogenous cellular biomolecules under biocompatible conditions with high spatial resolution. Applications of Raman spectroscopy in prostate cancer include biopsy analysis, assessment of surgical margins and monitoring of treatment efficacy. The advent of advanced Raman imaging techniques, such as stimulated Raman scattering, is creating opportunities for real-time in situ evaluation of prostate cancer. This review provides a focus on the recent preclinical and clinical achievements in implementing Raman-based techniques, highlighting remaining challenges for clinical applications. The research and clinical results achieved through in vivo and ex vivo Raman spectroscopy illustrate areas where these evolving technologies can be best translated into clinical practice.

Polystyrene nanoplastics diminish the toxic effects of Nano-TiO2 in marine algae Chlorella sp

Widespread usage of nano-TiO₂ in various commercial products and their consequent release into the seawater pose a severe threat to marine biota. Nanoplastics, a secondary pollutant in the marine environment, could influence adverse effects of nano-TiO₂. The main goal of the present study was to investigate the influence of the differently functionalized polystyrene nanoplastics (COOH-PSNPs, NH2-PSNPs, and Plain-PSNPs) on the acute toxic effects of P25 nano-TiO₂ in marine algae Chlorella sp. Three different concentrations of nano-TiO₂, 0.25, 0.5, and 1 mg/L, mixed with 5 mg/L of the PSNPs were employed in this study. A substantial increase was noted in mean hydrodynamic sizes of nano-TiO₂ when they were mixed with the PSNPs. This hetero-aggregation would reduce the bioavailability of the particles to the algae. The presence of the PSNPs in the mixture reduced the toxicity of nano-TiO₂ significantly. A signficant decline in the oxidative stress parameters like total ROS, superoxide (), and hydroxyl radical generation was noted for the mixture of nano-TiO₂ with the PSNPs in comparison with the pristine counterparts. The lipid peroxidation, and the antioxidant enzyme activities in the cells correlated well with the reactive species generation results. The treatments with the mixture resulted in notable enhancement in the esterase activity in the cells. The Independent Action model suggested antagonistic interactions between PSNPs and nano-TiO₂. The results from this study clearly demonstrate that nano-TiO₂ in presence of the PSNPs exerted significantly reduced cytotoxic effects in Chlorella sp, in comparison with the pristine particles.

Biochemical changes in the cytoplasm of bovine oocytes during the in vitro maturation process: a Raman microscopy study

The sequence and chronology of the main biochemical changes occurring in the cytoplasm of bovine oocytes during the in vitro maturation process were tracked by Raman microscopy applied to cells previously subjected to enzymatic digestion of the zona pellucida. Specific spectral markers for proteins, lipids and carbohydrates were used to evaluate the developmental status of the ooplasm at four different times. Spectral changes revealed that lipid accumulation was dominant during the first six hours of culture while protein content reached the average levels characteristic of mature oocytes within the last four hours of the maturation process. A time-dependent decrease in carbohydrates was also observed. Finally, the carbohydrate-to-protein (P₁₀₃₇/P₁₀₀₂) ratio proved to be sensitive enough to determine the cytoplasmic maturation state of bovine oocytes and promises to be useful in future research aimed at optimizing culture conditions through the promotion of protein accumulation in the ooplasm.

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.

SERS-based DNA methylation profiling allows the differential diagnosis of malignant lymphadenopathy

This study highlights the potential of surface-enhanced Raman scattering (SERS) to differentiate between B-cell lymphoma (BCL), T-cell lymphoma (TCL), lymph node metastasis of melanoma (Met) and control (Ctr) samples based on the specific SERS signal of DNA extracted from lymph node tissue biopsy. Differences in the methylation profiles as well as the specific interaction of malignant and non-malignant DNA with the metal nanostructure are captured in specific variations of the band at 1005 cm^-1, attributed to 5-methylcytosine and the band at 730 cm^-1, attributed to adenine. Thus, using the area ratio of these two SERS marker bands as input for univariate classification, an area under the curve (AUC) of 0.70 was achieved in differentiating between malignant and non-malignant DNA. In addition, DNA from the BCL and TCL groups exhibited differences in the area of the SERS band at 730 cm^-1, yielding an AUC of 0.84 in differentiating between these two lymphadenopathies. Lastly, using multivariate data analysis techniques, an overall accuracy of 94.7% was achieved in the differential diagnosis between the BCL, TCL, Met and Ctr groups. These results pave the way towards the implementation of SERS as a novel tool in the clinical setting for improving the diagnosis of malignant lymphadenopathy.

Raman spectra-based structural classification analysis of quinoidal and derived molecular systems

This work reports a classification analysis method based on the vibrational Raman spectra of 38 quinones and related structures, spectrally ordering and classifying the compounds. The molecular systems are relevant for chemical and biological processes, with applications in pharmacology, toxicology and medicine. The classification strategy uses a combination of principal component analysis with K-means clustering methods. Both theoretical simulations and experimental data are analysed, thus establishing their spectral characteristics, as related to their chemical structures and properties. The protocol introduced here should be broadly applicable in other molecular and solid state systems.

Discrimination of Different Breast Cell Lines on Glass Substrate by Means of Fourier Transform Infrared Spectroscopy

Fourier transform infrared (FTIR) micro-spectroscopy has been attracting the interest of many cytologists and histopathologists for several years. This is related to the possibility of FTIR translation in the clinical diagnostic field. In fact, FTIR spectra are able to detect changes in biochemical cellular components occurring when the cells pass to a pathological state. Recently, this interest has increased because it has been shown that FTIR spectra carried out just in the high wavenumber spectral range (2500-4000 cm^-1), where information mainly relating to lipids and proteins can be obtained, are able to discriminate cell lines related to different tissues. This possibility allows to perform IR absorption measurements of cellular samples deposited onto microscopy glass slides (widely used in the medical environment) which are transparent to IR radiation only for wavenumber values larger than 2000 cm^-1. For these reasons, we show that FTIR spectra in the 2800-3000 cm^-1 spectral range can discriminate three different cell lines from breast tissue: a non-malignant cell line (MCF10A), a non-metastatic adenocarcinoma cell line (MCF7) and a metastatic adenocarcinoma cell line (MDA). All the cells were grown onto glass slides. The spectra were discriminated by means of a principal component analysis, according to the PC1 component, whose values have the opposite sign in the pairwise score plots. This result supports the wide studies that are being carried out to promote the translation of the FTIR technique in medical practice, as a complementary diagnostic tool.

Detecting antimicrobial resistance in Escherichia coli using benchtop attenuated total reflectance-Fourier transform infrared spectroscopy and machine learning

The widespread dissemination of resistance to third-generation cephalosporins in the Enterobacterales through the production of extended-spectrum β-lactamase (ESBL) is considered a critical global crisis requiring urgent attention of clinicians and scientists alike. Rapid diagnostic methods that can identify microbial resistance profiles closer to the point of care are crucial to minimize the overuse of antimicrobial agents and improve patient outcomes. Although Fourier transform infrared (FTIR) microscopy has shown promise in distinguishing between bacterial species, the high cost and technical requirements of the IR microscope may limit broad clinical use. To address the practical needs of a clinical microbiology laboratory, here, we examine the ability of a lower cost portable benchtop attenuated total reflectance (ATR)-FTIR spectrometer to achieve antimicrobial resistance detection, using a simple, clinically aligned sampling protocol. The technical reproducibility was confirmed through multi-day analysis of an Escherichia coli type strain, which serves as quality control. We generated a dataset of 100 E. coli clinical bloodstream isolates with 63 ceftriaxone resistant bla_CTX-M ESBL gene variant strains and developed a classifier for bla_CTX-M genotype detection. After assessing 35 machine learning methods using the training set (n = 71), four methods were further optimised, and the best performing method was evaluated using the held-out testing set (n = 29). A tuned support vector machine model with a polynomial kernel, using the 700-1500 cm^-1 range achieved a sensitivity of 89.2%, and specificity of 66.7% for detecting bla_CTX-M in independent testing, approaching the reported performance of FTIR microscopy. With further algorithm improvement, these data suggest the potential deployment of a portable FTIR spectrometer as a rapid antimicrobial susceptibility prediction platform to enable the efficient use of antimicrobials.

Cytotoxic Effects of 5-Azacytidine on Primary Tumour Cells and Cancer Stem Cells from Oral Squamous Cell Carcinoma: An In Vitro FTIRM Analysis

In the present study, the cytotoxic effects of 5-azacytidine on primary Oral Squamous Cell Carcinoma cells (OSCCs) from human biopsies, and on Cancer Stem Cells (CSCs) from the same samples, were investigated by an in vitro Fourier Transform InfraRed Microscospectroscopy (FTIRM) approach coupled with multivariate analysis. OSCC is an aggressive tumoral lesion of the epithelium, accounting for ~90% of all oral cancers. It is usually diagnosed in advanced stages, and this causes a poor prognosis with low success rates of surgical, as well as radiation and chemotherapy treatments. OSCC is frequently characterised by recurrence after chemotherapy and by the development of a refractoriness to some employed drugs, which is probably ascribable to the presence of CSCs niches, responsible for cancer growth, chemoresistance and metastasis. The spectral information from FTIRM was correlated with the outcomes of cytotoxicity tests and image-based cytometry, and specific spectral signatures attributable to 5-azacytidine treatment were identified, allowing us to hypothesise the demethylation of DNA and, hence, an increase in the transcriptional activity, together with a conformational transition of DNA, and a triggering of cell death by an apoptosis mechanism. Moreover, a different mechanism of action between OSSC and CSC cells was highlighted, probably due to possible differences between OSCCs and CSCs response.

How to draw the line - Raman spectroscopy as a tool for the assessment of biomedicines

Biomedicines are complex biochemical formulations with multiple components that require extensive quality control during manufacturing and in subsequent batch testing. A proof-of-concept study has shown that an application of Raman spectroscopy can be beneficial for a classification of vaccines. However, the complexity of biomedicines introduces new challenges to spectroscopic methodology that require advanced experimental protocols. We further show the impact of analytical protocols on vaccine classification using R as an Open Source data analysis platform. In conclusion, we advocate for standardized and transparent experimental and analytical procedures and discuss current findings and open challenges.

Molecular-level changes induced by hydroxycinnamic acid derivatives in HepG2 cell line: Comparison with pravastatin

Hydroxycinnamic acid derivatives are an important class of polyphenols found in fruits, vegetables, and medicinal plants and widely consumed in human diet. In the present work, alterations of HepG2 cells biochemical profile under the effect of four hydroxycinnamic acid derivatives (caffeic acid, m-coumaric acid, chlorogenic acid and rosmarinic acid) relatively to the effect of pravastatin, a drug often prescribed to inhibit HMG-CoA reductase enzyme, the regulator enzyme in the cholesterol biosynthesis pathway, were reported. The application of FTIR spectroscopy in combination with multivariate analysis by PCA showed a similarity between pravastatin and the four hydroxycinnamic acid derivatives in metabolite profile modification expressed by various changes in proteins region, the phosphate region which mainly corresponds to nucleic acids as well as in lipids regions. FTIR structural analysis in the amide I region, using resolution enhancement methods, such as second derivative and amide I deconvolution method, revealed significant decrease in α-helix/random coil and intermolecular β-sheet decreased while intramolecular β-sheet in treated cells showed an increase. It was also noticed that the intracellular cholesterol as well as esterified ingredients such as cholesterol esters in the cell membrane decreased. Moreover, principal component analysis (PCA) of the spectral data showed that the compounds and pravastatin were well separated from untreated cells showing a different mode of action on HepG2 treated cells for each compound.

Biochemical impact of solar radiation exposure on human keratinocytes monitored by Raman spectroscopy; effects of cell culture environment

Understanding and amelioration of the effects of solar radiation exposure are critical in preventing the occurrence of skin cancer. Towards this end, many studies have been conducted in 2D cell culture models under simplified and unrealistic conditions. 3D culture models better capture the complexity of in vivo physiology, although the effects of the 3D extracellular matrix have not been well studied. Monitoring the instantaneous and resultant cellular responses to exposure, and the influence of the 3D environment, could provide an enhanced understanding of the fundamental processes of photocarcinogenesis. This work presents an analysis of the biochemical impacts of simulated solar radiation (SSR) occurring in immortalised human epithelial keratinocytes (HaCaT), in a 3D skin model, compared to 2D culture. Cell viability was monitored using the Alamar Blue colorimetric assay (AB), and the impact of the radiation exposure, at the level of the biomolecular constituents (nucleic acids and proteins), were evaluated through the combination of Raman microspectroscopy and multivariate statistical analysis. The results suggest that SSR exposure induces alterations of the conformational structure of DNA as an immediate impact, whereas changes in the protein signature are primarily seen as a subsequent response.