Ratiometric analysis using Raman spectroscopy as a powerful predictor of structural properties of fatty acids

Gaining insights into the responses of individual yeast cells to ethanol fermentation using Raman tweezers and chemometrics

Saccharomyces cerevisiae is the most common microbe used for the industrial production of bioethanol, and it encounters various stresses that inhibit cell growth and metabolism during fermentation. However, little is currently known about the physiological changes that occur in individual yeast cells during ethanol fermentation. Therefore, in this work, Raman spectroscopy and chemometric techniques were employed to monitor the metabolic changes of individual yeast cells at distinct stages during high gravity ethanol fermentation. Raman tweezers was used to acquire the Raman spectra of individual yeast cells. Multivariate curve resolution-alternating least squares (MCR-ALS) and principal component analysis were employed to analyze the Raman spectra dataset. MCR-ALS extracted the spectra of proteins, phospholipids, and triacylglycerols and their relative contents in individual cells. Changes in intracellular biomolecules showed that yeast cells undergo three distinct physiological stages during fermentation. In addition, heterogeneity among yeast cells significantly increased in the late fermentation period, and different yeast cells may respond to ethanol stress via different mechanisms. Our findings suggest that the combination of Raman tweezers and chemometrics approaches allows for characterizing the dynamics of molecular components within individual cells. This approach can serve as a valuable tool in investigating the resistance mechanism and metabolic heterogeneity of yeast cells during ethanol fermentation.

Protein-metal interactions due to fretting corrosion at the taper junction of hip implants: an in vitro investigation using Raman spectroscopy

Modular hip implants are a clinically successful and widely used treatment for patients with arthritis. Despite ongoing retrieval studies the understanding of the fundamental physico-chemical mechanisms of friction and wear within the head-taper interface is still limited. Here, we Raman-spectroscopically analyze structural features of the biotribological material which is formed within the taper joint between Ti6Al4V and low-carbon cobalt alloy or high-nitrogen steel surfaces in in vitro gross-slip fretting corrosion tests with bovine calf serum. As a function of the fretting duration, we investigate short and long aliphatic chains and their adsorption behavior on the cobalt- and steel-type surfaces. Using the intensity and frequency shifts of the amide I and III Raman bands, we furthermore identify progressive protein folding and unfolding including the secondary structures of α-helix, β-sheet, and random-coil configuration as well as the formation of proteinaceous clusters depending on the hydrophilicity of the metallic surfaces. We additionally find a mixture of chromates and iron oxides with tryptophan and tyrosine at the worn cobalt alloy and high-nitrogen steel surfaces, respectively. Also, for long fretting duration, sp2 hybridized amorphous carbon is formed due to fretting-induced cleavage of proteins. STATEMENT OF SIGNIFICANCE: Despite efforts enhancing the biomedical tribology of hip implants, the impact of the organic environment on friction&wear at the femoral head-stem taper interface is limitedly understood. Using Raman spectroscopy we resolve structural changes within the biotribological material agglomerated at biomedical-grade metal alloys due to organo-metallic interactions during in vitro fretting corrosion tests. Adsorption of short and long aliphatic chains, progressive protein (un)folding and proteinaceous cluster formation depend to a distinguishable extent on the fretting duration and type of alloy. Chromates and iron oxides are mixed with tryptophan and tyrosine, and amorphous carbon is formed resulting from a fretting-induced cleavage of serum proteins. Such information spectroscopically gleaned from biotribological material are vital to improve the design and performance of taper junctions.

Contemporary applications of vibrational spectroscopy in plant stresses and phenotyping

Plant pathogens, including viruses, bacteria, and fungi, cause massive crop losses around the world. Abiotic stresses, such as drought, salinity and nutritional deficiencies are even more detrimental. Timely diagnostics of plant diseases and abiotic stresses can be used to provide site- and doze-specific treatment of plants. In addition to the direct economic impact, this "smart agriculture" can help minimizing the effect of farming on the environment. Mounting evidence demonstrates that vibrational spectroscopy, which includes Raman (RS) and infrared spectroscopies (IR), can be used to detect and identify biotic and abiotic stresses in plants. These findings indicate that RS and IR can be used for in-field surveillance of the plant health. Surface-enhanced RS (SERS) has also been used for direct detection of plant stressors, offering advantages over traditional spectroscopies. Finally, all three of these technologies have applications in phenotyping and studying composition of crops. Such non-invasive, non-destructive, and chemical-free diagnostics is set to revolutionize crop agriculture globally. This review critically discusses the most recent findings of RS-based sensing of biotic and abiotic stresses, as well as the use of RS for nutritional analysis of foods.

New insights into lipid and fatty acid metabolism from Raman spectroscopy

One of the challenges facing biology is to understand metabolic events at a single cellular level. While approaches to examine dynamics of protein distribution or report on spatiotemporal location of signalling molecules are well-established, tools for the dissection of metabolism in single living cells are less common. Advances in Raman spectroscopy, such as stimulated Raman scattering (SRS), are beginning to offer new insights into metabolic events in a range of experimental systems, including model organisms and clinical samples, and across a range of disciplines. Despite the power of Raman imaging, it remains a relatively under-used technique to approach biological problems, in part because of the specialised nature of the analysis. To raise the profile of this method, here we consider some key studies which illustrate how Raman spectroscopy has revealed new insights into fatty acid and lipid metabolism across a range of cellular systems. The powerful and non-invasive nature of this approach offers a new suite of tools for biomolecular scientists to address how metabolic events within cells informs on or underpins biological function. We illustrate potential biological applications, discuss some recent advances, and offer a direction of travel for metabolic research in this area.

Imaging of perivascular adipose tissue in cardiometabolic diseases by Raman spectroscopy: Towards single-cell analysis

Perivascular adipose tissue (PVAT) has emerged as a dynamic organ influencing vascular function and cardiovascular health. In this brief review, an overview of the recent research in the investigation of PVAT is presented, ranging from in vivo studies to single-cell methodologies, in particular those based on Raman spectroscopy. The strengths and limitations of each, emphasizing their contributions to the current understanding of PVAT biology were discussed. Ultimately, the integration of these diverse methodologies promises to uncover new therapeutic targets and diagnostic biomarkers, including those emerging from simple Raman spectroscopy-based measurements of alterations in lipid unsaturation degree, invariably associated with PVAT dysfunction.

Raman microscopy reveals how cell inflammation activates glucose and lipid metabolism

Metabolism of endothelial cells (ECs) depends on the availability of the energy substrates. Since the endothelium is the first line of defence against inflammation in the cardiovascular system and its dysfunction can lead to the development of cardiovascular diseases, it is important to understand how glucose metabolism changes during inflammation. In this work, glucose uptake was studied in human microvascular endothelial cells (HMEC-1) in high glucose (HG), and additionally in an inflammatory state, using Raman imaging. HG state was induced by incubation of ECs with a deuterated glucose analogue, while the EC inflammation was caused by TNF-α pre-treatment. Spontaneous and stimulated Raman scattering spectroscopy provided comprehensive information on biochemical changes, including lipids and the extent of unsaturation induced by excess glucose in ECs., induced by excess glucose in ECs. In this work, we indicated spectroscopic markers of metabolic changes in ECs as a strong increase in the ratio of the intensity of lipids / (proteins + lipids) bands and an increase in the level of lipid unsaturation and mitochondrial changes. Inflamed ECs treated with HG, revealed enhanced glucose uptake, and intensified lipid production i.a. of unsaturated lipids. Additionally, increased cytochrome c signal in the mitochondrial region indicated higher mitochondrial activity and biogenesis. Raman spectroscopy is a powerful method for determining the metabolic markers of ED which will better inform understanding of disease onset, development, and treatment.

Non-invasive identification of combined salinity stress and stalk rot disease caused by Colletotrichum graminicola in maize using Raman spectroscopy

Food security is an emerging problem that is faced by our civilization. There are millions of people around the world suffering from various kinds of malnutrition. The number of people that starve will only increase considering the continuous growth of the world's population. The problem of food security can be addressed by timely detection and identification biotic and abiotic stresses in plants that drastically reduce the crop yield. A growing body of evidence suggests that Raman spectroscopy (RS), an emerging analytical technique, can be used for the confirmatory and non-invasive diagnostics of plant stresses. However, it remains unclear whether RS can efficiently disentangle biotic and abiotic stresses, as well as detect both of them simultaneously in plants. In this work, we modeled a stalk rot disease in corn by inoculating the plant stalks with Colletotrichum graminicola. In parallel, we subjected plants to salt stress, as well as challenging plants with both stalk rot disease and salinity stress simultaneously. After the stresses were introduced, Raman spectra were collected from the stalks to reveal stress-specific changes in the plant biochemistry. We found that RS was able to differentiate between stalk rot disease and salinity stresses with 100% accuracy, as well as predict presence of both of those stresses in plants on early and late stages. These results demonstrate that RS is a robust and reliable approach that can be used for confirmatory, non-destructive and label-free diagnostics of biotic and abiotic stresses in plants.

Direct Counting and Imaging Chain Lengths of Lipids by Stimulated Raman Scattering Microscopy

Direct counting and mapping the chain lengths of fatty acids on a microscopic scale are of particular importance but remain an unsolvable challenge. Although the current hyperspectral stimulated Raman scattering (SRS) microscopy has gained exceptional capability in chemical imaging of the degree of desaturation, the complete lipid characterization, including the carbon chain length quantification, is awaiting a major breakthrough. Here, we pushed the spectral resolution limit of hyperspectral SRS microscopy to 5.4 cm^-1 by employing a highly efficient spectral compressor, which achieved spectral narrowing of the fs laser without much energy loss. The SRS imaging with such high spectral resolution enabled us to differ eight types of saturated lipids with carbon chain lengths from C8:0 to C22:0 by interrogating their subtly red-shifting Raman bands of alkyl C-C gauche stretches between 1070 and 1110 cm^-1. The SRS microscopy with superior spectral resolution will pave the way for comprehensive lipid characterization and contribute to uncovering the abnormal pathways of lipid metabolism in cancer.

Enhanced characterization of breast cancer phenotypes using Raman micro-spectroscopy on stainless steel substrate

Biochemical insights into varying breast cancer (BC) phenotypes can provide a fundamental understanding of BC pathogenesis, while identifying novel therapeutic targets. Raman spectroscopy (RS) can gauge these biochemical differences with high specificity. For routine RS, cells are traditionally seeded onto calcium fluoride (CaF₂) substrates that are costly and fragile, limiting its widespread adoption. Stainless steel has been interrogated previously as a less expensive alternative to CaF₂ substrates, while reporting increased Raman signal intensity than the latter. We sought to further investigate and compare the Raman signal quality measured from stainless steel versus CaF₂ substrates by characterizing different BC phenotypes with altered human epidermal growth factor receptor 2 (HER2) expression. Raman spectra were obtained on stainless steel and CaF₂ substrates for HER2 negative cells - MDA-MB-231, MDA-MB-468 and HER2 overexpressing cells - AU565, SKBr3. Upon analyzing signal-to-noise ratios (SNR), stainless steel provided a stronger Raman signal, improving SNR by 119% at 1450 cm^-1 and 122% at 2925 cm^-1 on average compared to the CaF₂ substrate. Utilizing only 22% of laser power on sample relative to the CaF₂ substrate, stainless steel still yielded improved spectral characterization over CaF₂, achieving 96.0% versus 89.8% accuracy in BC phenotype discrimination and equivalent 100.0% accuracy in HER2 status classification. Spectral analysis further highlighted increased lipogenesis and altered metabolism in HER2 overexpressing cells, which was subsequently visualized with coherent anti-Stokes Raman scattering microscopy. Our findings demonstrate that stainless steel substrates deliver improved Raman signal and enhanced spectral characterization, underscoring its potential as a cost-effective alternative to CaF₂ for non-invasively monitoring cellular biochemical dynamics in translational cancer research.

Direct Measurement of Chocolate Components Using Dispersive Raman Spectroscopy at 1000 nm Excitation

Chocolate is a popular food around the world. Making chocolate-based confectionaries involve multiple processing steps including cocoa bean fermentation, cocoa bean roasting, grinding, and then a controlled crystallization, where the processing conditions yields the desirable polymorph V to give chocolate its characteristic snap and texture. Raman spectroscopy is well known as a technique that can provide a non-contact, non-destructive analysis of chemical composition and molecular structure. Yet, excitation in the visible and near-infrared (532-785 nm) has not been possible for dark or milk chocolate because of the samples' overwhelming fluorescence. New technologies enabling Raman spectroscopy closer to shortwave infrared wavelengths, closer to 1000 nm, are likely to reduce fluorescence of chocolate and other highly fluorescent samples. Based on the successes of 1064 nm excitation to understand chocolate blooming, we hypothesized that 1000 nm excitation would also reduce fluorescence and enable Raman spectroscopy in dark and milk chocolates. We used dispersive Raman spectroscopy at 1000 nm to measure white, milk, and dark chocolate and cocoa nibs. The use of 1000 nm excitation effectively reduced fluorescence, enabling qualitative and quantitative Raman spectroscopy directly on chocolate samples. These feasibility studies indicate that 1000 nm Raman spectroscopy can be used to measure chocolate in a laboratory or process environment.

Serotonergic drugs modulate the phase behavior of complex lipid bilayers

Serotonin is an endogenous neurotransmitter involved in both physiological and pathophysiological processes. Traditionally, serotonin acts as a ligand for G protein-coupled receptors (GPCRs) leading to subsequent cell signaling. However, serotonin can also bind to lipid membranes with high affinity and modulate the phase behavior in 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (POPC)/N-palmitoyl-D-erythro-sphingosylphosphorylcholine (PSM)/cholesterol model membranes mimicking the outer leaflet of the plasma membrane. Here, we investigated if serotonergic drugs containing the pharmacophore from serotonin would also modulate phase behavior in lipid membranes in a similar fashion. We used ²H NMR spectroscopy to explore the phase behavior of POPC/PSM/cholesterol (4/4/2 molar ratio) mixtures in the presence of the serotonergic drugs aripiprazole, BRL-54443, BW-723C86, and CP-135807 at a lipid to drug molar ratio of 10:1. POPC and PSM were perdeuterated in the palmitoyl chain, respectively, and prepared in individual samples. Numerical lineshape simulations of the ²H NMR spectra were used to calculate the order parameter profiles and projected lengths of the saturated acyl chains. All serotonergic drugs induce two components in ²H NMR spectra, indicating that they increased the hydrophobic mismatch between the thickness of the coexisting lipid phases leading to larger domain sizes, relatively similarly to serotonin. AFM force indentation and Raman spectral studies, which interrogate membrane mechanical properties, also indicate changes in membrane order in the presence of these drugs. These findings highlight how serotonergic drugs alter membrane phase behavior and could modulate both target and other membrane proteins, possibly explaining the side effects observed for serotonergic and other clinically relevant drugs.

Integration of surface-enhanced Raman spectroscopy (SERS) and machine learning tools for coffee beverage classification

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for molecule identification. However, profiling complex samples remains a challenge because SERS peaks are likely to overlap, confounding features when multiple analytes are present in a single sample. In addition, SERS often suffers from high variability in signal enhancement due to nonuniform SERS substrate. The machine learning classification techniques widely used for facial recognition are excellent tools to overcome the complexity of SERS data interpretation. Herein, we reported a sensor for classifying coffee beverages by integrating SERS, feature extractions, and machine learning classifiers. A versatile and low-cost SERS substrate, called nanopaper, was used to enhance Raman signals of dilute compounds in coffee beverages. Two classic multivariate analysis techniques, Principal Component Analysis (PCA) and Discriminant Analysis of Principal Components (DAPC), were used to extract the significant spectral features, and the performance of various machine learning classifiers was evaluated. The combination of DAPC with Support Vector Machine (SVM) or K-Nearest Neighbor (KNN) shows the best performance for classifying coffee beverages. This user-friendly and versatile sensor has the potential to be a practical quality-control tool for the food industry.

Surface Chemical and Morphological Analysis of Chitosan/1,3-β-d-Glucan Polysaccharide Films Cross-Linked at 90 °C

The cross-linking temperature of polymers may affect the surface characteristics and molecular arrangement, which are responsible for their mechanical and physico-chemical properties. The aim of this research was to determine and explain in detail the mechanism of unit interlinkage of two-component chitosan/1,3-β-d-glucan matrices gelled at 90 °C. This required identifying functional groups interacting with each other and assessing surface topography providing material chemical composition. For this purpose, various spectroscopic and microscopic approaches, such as attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM), were applied. The results indicate the involvement mainly of the C-C and C-H groups and C=O⋯HN moieties in the process of biomaterial polymerization. Strong chemical interactions and ionocovalent bonds between the N-glucosamine moieties of chitosan and 1,3-β-d-glucan units were demonstrated, which was also reflected in the uniform surface of the sample without segregation. These unique properties, hybrid character and proper cell response may imply the potential application of studied biomaterial as biocompatible scaffolds used in regenerative medicine, especially in bone restoration and/or wound healing.

Raman Study of Pathogenic Candida auris: Imaging Metabolic Machineries in Reaction to Antifungal Drugs

The multidrug-resistant Candida auris often defies treatments and presently represents a worldwide public health threat. Currently, the ergosterol-targeting Amphotericin B (AmB) and the DNA/RNA-synthesis inhibitor 5-flucytosine (5-FC) are the two main drugs available for first-line defense against life-threatening Candida auris infections. However, important aspects of their mechanisms of action require further clarification, especially regarding metabolic reactions of yeast cells. Here, we applied Raman spectroscopy empowered with specifically tailored machine-learning algorithms to monitor and to image in situ the susceptibility of two Candida auris clades to different antifungal drugs (LSEM 0643 or JCM15448T, belonging to the East Asian Clade II; and, LSEM 3673 belonging to the South African Clade III). Raman characterizations provided new details on the mechanisms of action against Candida auris Clades II and III, while also unfolding differences in their metabolic reactions to different drugs. AmB treatment induced biofilm formation in both clades, but the formed biofilms showed different structures: a dense and continuous biofilm structure in Clade II, and an extra-cellular matrix with a “fluffy” and discontinuous structure in Clade III. Treatment with 5-FC caused no biofilm formation but yeast-to-hyphal or pseudo-hyphal morphogenesis in both clades. Clade III showed a superior capacity in reducing membrane permeability to the drug through chemically tailoring chitin structure with a high degree of acetylation and fatty acids networks with significantly elongated chains. This study shows the suitability of the in situ Raman method in characterizing susceptibility and stress response of different C. auris clades to antifungal drugs, thus opening a path to identifying novel clinical solutions counteracting the spread of these alarming pathogens.

Raman Spectroscopy Enables Non-invasive and Confirmatory Diagnostics of Aluminum and Iron Toxicities in Rice

Metal toxicities can be detrimental to a plant health, as well as to the health of animals and humans that consume such plants. Metal content of plants can be analyzed using colorimetric, atomic absorption- or mass spectroscopy-based methods. However, these techniques are destructive, costly and laborious. In the current study, we investigate the potential of Raman spectroscopy (RS), a modern spectroscopic technique, for detection and identification of metal toxicities in rice. We modeled medium and high levels of iron and aluminum toxicities in hydroponically grown plants. Spectroscopic analyses of their leaves showed that both iron and aluminum toxicities can be detected and identified with ∼100% accuracy as early as day 2 after the stress initiation. We also showed that diagnostics accuracy was very high not only on early, but also on middle (day 4-day 8) and late (day 10-day 14) stages of the stress development. Importantly this approach only requires an acquisition time of 1 s; it is non-invasive and non-destructive to plants. Our findings suggest that if implemented in farming, RS can enable pre-symptomatic detection and identification of metallic toxins that would lead to faster recovery of crops and prevent further damage.

Detection of Glutamate Encapsulated in Liposomes by Optical Trapping Raman Spectroscopy

The transmission of neuronal information is propagated through synapses by neurotransmitters released from presynapses to postsynapses. Neurotransmitters released from the presynaptic vesicles activate receptors on the postsynaptic membrane. Glutamate acts as a major excitatory neurotransmitter for synaptic vesicles in the central nervous system. Determining the concentration of glutamate in single synaptic vesicles is essential for understanding the mechanisms of neuronal activation by glutamate in normal brain functions as well as in neurological diseases. However, it is difficult to detect and quantitatively measure the concentration of glutamate in single synaptic vesicles owing to their small size, i.e., ∼40 nm. In this study, to quantitatively evaluate the concentrations of the contents in small membrane-bound vesicles, we developed an optical trapping Raman spectroscopic system that analyzes the Raman spectra of small objects captured using optical trapping. Using artificial liposomes encapsulating glutamate that mimic synaptic vesicles, we investigated whether spontaneous Raman scattered light of glutamate can be detected from vesicles trapped at the focus using optical forces. A 575 nm laser beam was used to simultaneously perform the optical trapping of liposomes and the detection of the spontaneous Raman scattered light. The intensity of Raman scattered light that corresponds to lipid bilayers increased with time. This observation suggested that the number of liposomes increased at the focal point. The number of glutamate molecules in the trapped liposomes was estimated from the calibration curve of the Raman spectra of glutamate solutions with known concentration. This method can be used to measure the number of glutamate molecules encapsulated in synaptic vesicles in situ.

Imaging Sub-Cellular Methionine and Insulin Interplay in Triple Negative Breast Cancer Lipid Droplet Metabolism

Triple negative breast cancer (TNBC) is a particularly aggressive cancer subtype that is difficult to diagnose due to its discriminating epidemiology and obscure metabolome. For the first time, 3D spatial and chemometric analyses uncover the unique lipid metabolome of TNBC under the tandem modulation of two key metabolites - insulin and methionine - using non-invasive optical techniques. By conjugating heavy water (D2O) probed Raman scattering with label-free two-photon fluorescence (TPF) microscopy, we observed altered de novo lipogenesis, 3D lipid droplet morphology, and lipid peroxidation under various methionine and insulin concentrations. Quantitative interrogation of both spatial and chemometric lipid metabolism under tandem metabolite modulation confirms significant interaction of insulin and methionine, which may prove to be critical therapeutic targets, and proposes a powerful optical imaging platform with subcellular resolution for metabolic and cancer research.

Pinpointing Alkane Chain Length, Saturation, and Double Bond Regio- and Stereoisomers by Liquid Interfacial Plasmonic Enhanced Raman Spectroscopy

The lipids with a rich diversity of isomers face a formidable challenge in comprehensive structural analysis. The commonly used mass spectrometry-based techniques usually require a considerable number of molecules with sophisticated chemical derivatization or ion mobility separation, but the co-existing of structurally similar isomers often makes the distinction impossible. Here, we develop an alternative powerful liquid/liquid interfacial surface-enhanced Raman spectroscopy (SERS) strategy at normal temperature and pressure without any sources of ionization or radiation. This strategy generates high-resolution fingerprints in molecular chain length, C═C position, saturation, and regio- and stereoisomers of both glycerides and fatty acids and requires only trace amounts of molecules down to 1 ppb to achieve discrimination and exhibits great potentials to push the identification capability to trace levels or even the single-molecule level. According to experimental data and theoretical simulations, these targets have the amphiphilic and emulsifying properties, exhibit ordered molecular orientation and adsorption patterns, promote the co-assembly with plasmonic nanoarrays at the immiscible liquid/liquid interface, and consequently amplify the detection sensitivity. As a contrast, the typical SERS based on solid/air interfacial plasmonic nanoarrays faces the intrinsic bottleneck of extremely weak intensity and indistinguishable spectral fingerprints of lipid molecules. The vibrational fingerprints exhibit a rich range of well-resolved absorption features that are clearly diagnostic for fine structural changes and pave a new way for straightforward measurement without laborsome sample purification, enrichment, or complex derivatization. Although challenging, its unprecedented resolving power expands the potentials of SERS, serving as an ultimate analytical method to provide insights into the detailed structural features of other lipids under facile conditions in the future.

Raman spectroscopy biochemical characterisation of bladder cancer cisplatin resistance regulated by FDFT1: a review

Bladder cancer is the fourth most common malignancy in males. It can present across the whole continuum of severity, from mild through well-differentiated disease to extremely malignant tumours with poor survival rates. As with other vital organ malignancies, proper clinical management involves accurate diagnosis and staging. Chemotherapy consisting of a cisplatin-based regimen is the mainstay in the management of muscle-invasive bladder cancers. Control via cisplatin-based chemotherapy is threatened by the development of chemoresistance. Intracellular cholesterol biosynthesis in bladder cancer cells is considered a contributory factor in determining the chemotherapy response. Farnesyl-diphosphate farnesyltransferase 1 (FDFT1), one of the main regulatory components in cholesterol biosynthesis, may play a role in determining sensitivity towards chemotherapy compounds in bladder cancer. FDFT1-associated molecular identification might serve as an alternative or appendage strategy for early prediction of potentially chemoresistant muscle-invasive bladder cancer tissues. This can be accomplished using Raman spectroscopy. Developments in the instrumentation have led to it becoming one of the most convenient forms of analysis, and there is a highly realistic chance that it will become an effective tool in the pathology lab. Chemosensitive bladder cancer tissues tend to have a higher lipid content, more protein genes and more cholesterol metabolites. These are believed to be associated with resistance towards bladder cancer chemotherapy. Herein, Raman peak assignments have been tabulated as an aid to indicating metabolic changes in bladder cancer tissues that are potentially correlated with FDFT1 expression.

Visualizing Cancer Cell Metabolic Dynamics Regulated With Aromatic Amino Acids Using DO-SRS and 2PEF Microscopy

Oxidative imbalance plays an essential role in the progression of many diseases that include cancer and neurodegenerative diseases. Aromatic amino acids (AAA) such as phenylalanine and tryptophan have the capability of escalating oxidative stress because of their involvement in the production of Reactive Oxygen Species (ROS). Here, we use D2O (heavy water) probed stimulated Raman scattering microscopy (DO-SRS) and two Photon Excitation Fluorescence (2PEF) microscopy as a multimodal imaging approach to visualize metabolic changes in HeLa cells under excess AAA such as phenylalanine or trytophan in culture media. The cellular spatial distribution of de novo lipogenesis, new protein synthesis, NADH, Flavin, unsaturated lipids, and saturated lipids were all imaged and quantified in this experiment. Our studies reveal ∼10% increase in de novo lipogenesis and the ratio of NADH to flavin, and ∼50% increase of the ratio of unsaturated lipids to saturated lipid in cells treated with excess phenylalanine or trytophan. In contrast, these cells exhibited a decrease in the protein synthesis rate by ∼10% under these AAA treatments. The cellular metabolic activities of these biomolecules are indicators of elevated oxidative stress and mitochondrial dysfunction. Furthermore, 3D reconstruction images of lipid droplets were acquired and quantified to observe their spatial distribution around cells’ nuceli under different AAA culture media. We observed a higher number of lipid droplets in excess AAA conditions. Our study showcases that DO-SRS imaging can be used to quantitatively study how excess AAA regulates metabolic activities of cells with subcellular resolution in situ.

In situ quantitative study of the phase transition in surfactant adsorption layers at the silica-water interface using total internal reflection Raman spectroscopy

Dimethyldodecylamine N-oxide (DDAO), a unique type of surfactant, shows high surface activity with two distinct energy states at the buried hydrophilic silica/aqueous solution interface studied by total internal reflection (TIR) Raman spectroscopy combined with ratiometric and kinetic analysis. Different from other types of surfactant, i.e., ionic and nonionic, the adsorption of DDAO demonstrates a specific critical surface aggregation concentration (csac) at 0.15 mM gives a complete surface coverage of 6.6 ± 0.3 μmol m^-2, much lower than the bulk critical micellization concentration (cmc) at the same conditions (csac ≈ 0.072 cmc). A phase transition of adsorbed layers from liquid crystalline as the intermediate state to the disordered liquid phase is spectroscopically and energetically analyzed. The adsorption of DDAO on silica surfaces is described quantitatively in a potential energy curve.

Raman-Based Diagnostics of Stalk Rot Disease of Maize Caused by Colletotrichum graminicola

Stalk rot caused by Colletotrichum graminicola is a disease of worldwide importance. Stalk rot is difficult to detect at the early stages of infection because the fungus colonizes the tissues inside the maize stem. Current diagnostic methods are time-consuming, laborious, and destructive to the stem tissue. We utilized Raman spectroscopy to follow the development of stalk rot in three different maize genotypes grown either in the field or the greenhouse. We then used the acquired spectra to calibrate statistical models to differentiate amongst the different disease timepoints and the genotypes themselves. This non-invasive spectroscopic method enabled high-accuracy identification of stalk rot based on both stalk and leaf spectra. We additionally found that leaf spectra were favorable for identifying maize by genotype. Finally, we identified Raman bands that showed correlation with the sizes of stalk rot-associated lesions in the stems. We demonstrated that Raman spectroscopy is a viable tool for detection of stalk rot disease, as well as potent for the differentiation of maize genotypes.

Raman spectroscopy-based diagnostics of water deficit and salinity stresses in two accessions of peanut

Water deficit and salinity are two major abiotic stresses that have tremendous effect on crop yield worldwide. Timely identification of these stresses can help limit associated yield loss. Confirmatory detection and identification of water deficit stress can also enable proper irrigation management. Traditionally, unmanned aerial vehicle (UAV)-based imaging and satellite-based imaging, together with visual field observation, are used for diagnostics of such stresses. However, these approaches can only detect salinity and water deficit stress at the symptomatic stage. Raman spectroscopy (RS) is a noninvasive and nondestructive technique that can identify and detect plant biotic and abiotic stress. In this study, we investigated accuracy of Raman-based diagnostics of water deficit and salinity stresses on two greenhouse-grown peanut accessions: tolerant and susceptible to water deficit. Plants were grown for 76 days prior to application of the water deficit and salinity stresses. Water deficit treatments received no irrigation for 5 days, and salinity treatments received 1.0 L of 240-mM salt water per day for the duration of 5-day sampling. Every day after the stress was imposed, plant leaves were collected and immediately analyzed by a hand-held Raman spectrometer. RS and chemometrics could identify control and stressed (either water deficit or salinity) susceptible plants with 95% and 80% accuracy just 1 day after treatment. Water deficit and salinity stressed plants could be differentiated from each other with 87% and 86% accuracy, respectively. In the tolerant accessions at the same timepoint, the identification accuracies were 66%, 65%, 67%, and 69% for control, combined stresses, water deficit, and salinity stresses, respectively. The high selectivity and specificity for presymptomatic identification of abiotic stresses in the susceptible line provide evidence for the potential of Raman-based surveillance in commercial-scale agriculture and digital farming.

Raman spectroscopy enables phenotyping and assessment of nutrition values of plants: a review

Our civilization has to enhance food production to feed world's expected population of 9.7 billion by 2050. These food demands can be met by implementation of innovative technologies in agriculture. This transformative agricultural concept, also known as digital farming, aims to maximize the crop yield without an increase in the field footprint while simultaneously minimizing environmental impact of farming. There is a growing body of evidence that Raman spectroscopy, a non-invasive, non-destructive, and laser-based analytical approach, can be used to: (i) detect plant diseases, (ii) abiotic stresses, and (iii) enable label-free phenotyping and digital selection of plants in breeding programs. In this review, we critically discuss the most recent reports on the use of Raman spectroscopy for confirmatory identification of plant species and their varieties, as well as Raman-based analysis of the nutrition value of seeds. We show that high selectivity and specificity of Raman makes this technique ideal for optical surveillance of fields, which can be used to improve agriculture around the world. We also discuss potential advances in synergetic use of RS and already established imaging and molecular techniques. This combinatorial approach can be used to reduce associated time and cost, as well as enhance the accuracy of diagnostics of biotic and abiotic stresses.

Identification of amyloid beta in small extracellular vesicles via Raman spectroscopy

One of the hallmarks of Alzheimer's disease (AD) pathogenesis is believed to be the production and deposition of amyloid-beta (Aβ) peptide into extracellular plaques. Existing research indicates that extracellular vesicles (EVs) can carry Aβ associated with AD. However, characterization of the EVs-associated Aβ and its conformational variants has yet to be realized. Raman spectroscopy is a label-free and non-destructive method that is able to assess the biochemical composition of EVs. This study reports for the first time the Raman spectroscopic fingerprint of the Aβ present in the molecular cargo of small extracellular vesicles (sEVs). Raman spectra were measured from sEVs isolated from Alzheimer's disease cell culture model, where secretion of Aβ is regulated by tetracycline promoter, and from midbrain organoids. The averaged spectra of each sEV group showed considerable variation as a reflection of the biochemical content of sEVs. Spectral analysis identified more intense Raman peaks at 1650 cm^-1 and 2930 cm^-1 attributable to the Aβ peptide incorporated in sEVs produced by the Alzheimer's cell culture model. Subsequent analysis of the spectra by principal component analysis differentiated the sEVs of the Alzheimer's disease cell culture model from the control groups of sEVs. Moreover, the results indicate that Aβ associated with secreted sEVs has a α-helical secondary structure and the size of a monomer or small oligomer. Furthermore, by analyzing the lipid content of sEVs we identified altered fatty acid chain lengths in sEVs that carry Aβ that may affect the fluidity of the EV membrane. Overall, our findings provide evidence supporting the use of Raman spectroscopy for the identification and characterization of sEVs associated with potential biomarkers of neurological disorders such as toxic proteins.

Estimation of Isentropic Compressibility of Biodiesel Using ELM Strategy: Application in Biofuel Production Processes

Isentropic compressibility is one of the significant properties of biofuel. On the other hand, the complexity related to the experimental procedure makes the detection process of this parameter time-consuming and hard. Thus, we propose a new Machine Learning (ML) method based on Extreme Learning Machine (ELM) to model this important value. A real database containing 483 actual datasets is compared with the outputs predicted by the ELM model. The results of this comparison show that this ML method, with a mean relative error of 0.19 and R 2 values of 1, has a great performance in calculations related to the biodiesel field. In addition, sensitivity analysis exhibits that the most efficient parameter of input variables is the normal melting point to determine isentropic compressibility.

Non-Invasive Identification of Nutrient Components in Grain

Digital farming is a modern agricultural concept that aims to maximize the crop yield while simultaneously minimizing the environmental impact of farming. Successful implementation of digital farming requires development of sensors to detect and identify diseases and abiotic stresses in plants, as well as to probe the nutrient content of seeds and identify plant varieties. Experimental evidence of the suitability of Raman spectroscopy (RS) for confirmatory diagnostics of plant diseases was previously provided by our team and other research groups. In this study, we investigate the potential use of RS as a label-free, non-invasive and non-destructive analytical technique for the fast and accurate identification of nutrient components in the grains from 15 different rice genotypes. We demonstrate that spectroscopic analysis of intact rice seeds provides the accurate rice variety identification in ~86% of samples. These results suggest that RS can be used for fully automated, fast and accurate identification of seeds nutrient components.

Nutraceutical properties of tamarillo fruits: A vibrational study

Tamarillo (tree tomato) is a subtropical tree that produces edible fruits with health-beneficial properties, since it contains several components with potential therapeutic and chemoprotective activity. The present work reports the first complete vibrational study (Raman and infrared) of this edible fruit. This approach allowed us to determine where the most relevant nutraceutical compounds are located in the fruit, as well as their relative amounts. Particular vibrational signatures were obtained for each part of the fruit, reporting different components for the epicarp (outer and inner sections), the pulp and the seeds, especially regarding the content in phenolic compounds, unsaturated fatty acids/esters and polymeric chains from the cuticular wax. Valuable information, at the molecular level was gathered regarding the nutricional value of tamarillo's fruit, for its different fractions. This is expected to pave the way for its introduction as a promising nutraceutical, based on the potential therapeutic properties of its main components.

Rapid characterization of hypanthium and seed in wild and cultivated rosehip: application of Raman microscopy combined with multivariate analysis

Rosehip (pseudo-fruit) of dog rose (Rosa canina L.) is highly valued, and owing to nutritional and sensory properties it has a significant place in the food industry. This work represents an innovative report focusing on the evaluation of the phytochemical composition of rosehips (hypanthium and seed) grown in different locations in Serbia, using Raman microspectroscopy combined with multivariate data analysis. Some significant differences arose between the analysed rosehip samples with regard to the chemical profile of both hypanthium parenchyma cells and seed, although no evident discrimination was recorded between the samples of wild and cultivated rosehip. The differences between the hypanthium samples compared were mainly determined by the content of carotenoids, phenolic compounds and polysaccharides, whereas phenolics, polysaccharides (pectin, cellulose and hemicellulose) and lipids (to a lower extent) contributed to the seed sample discrimination. The differences observed between the rosehip samples may be attributed to abiotic factors (growing, ripening and storage conditions), which had a significant impact on the carotenoid and polyphenols biosynthesis.

Qualitative and quantitative vibrational spectroscopic analysis of macronutrients in breast milk

Raman and attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy were used to analyze 208 breast milk samples as part of a larger research study. Comprehensive qualitative and quantitative analysis was carried out using chemometric methods: principal component analysis (PCA) and partial least squares (PLS) regression. The obtained information on the main macronutrients (protein, fat and carbohydrate) were primarily evaluated in relation to the available metadata of the samples, where study location and respective primary food sources revealed a stronger differentiation in fat composition than its absolute content. The limitations and challenges of using both spectroscopic techniques for the type of analysis are also highlighted.

Raman-Based Diagnostics of Biotic and Abiotic Stresses in Plants. A Review

Digital farming is a novel agricultural philosophy that aims to maximize a crop yield with the minimal environmental impact. Digital farming requires the development of technologies that can work directly in the field providing information about a plant health. Raman spectroscopy (RS) is an emerging analytical technique that can be used for non-invasive, non-destructive, and confirmatory diagnostics of diseases, as well as the nutrient deficiencies in plants. RS is also capable of probing nutritional content of grains, as well as highly accurate identification plant species and their varieties. This allows for Raman-based phenotyping and digital selection of plants. These pieces of evidence suggest that RS can be used for chemical-free surveillance of plant health directly in the field. High selectivity and specificity of this technique show that RS may transform the agriculture in the US. This review critically discusses the most recent research articles that demonstrate the use of RS in diagnostics of abiotic and abiotic stresses in plants, as well as the identification of plant species and their nutritional analysis.

Oral delivery of fish oil in oil-in-water nanoemulsion: development, colloidal stability and modulatory effect on in vivo inflammatory induction in mice

To improve the oral absorption of fish oil and test its anti-inflammatory effect, a fish oil nanoemulsion was developed using cis-4,7,10,13,16,19-docosahexaenoic fatty acid as a biomarker for oral administration. The colloidal stability tests of the fish oil nanoemulsion showed an average size of 155.44 nm ± 6.46 (4 °C); 163.04 nm ± 9.97 (25 °C) and polydispersity index 0.22 ± 0.02 (4 °C), 0.21 ± 0.02 (25 °C), indicating systems with low polydispersity and stable droplets. The fish oil nanoemulsion did not alter the cell viability of the RAW 264.7 macrophages and, at a concentration of 0.024 mg/mL, was kinetically incorporated into the cells after 18 h of contact. The nanoemulsion was maintained in the gastrointestinal region for a significantly shorter period of time (p ≤ 0.05) compared to the intake of fish oil in free form. Inflammatory tests demonstrated that nanoemulsion and fish oil showed less (p ≤ 0.05) neutrophil infiltration after 24h of sepsis induction and there was a significant reduction (p ≤ 0.05) in the volume of paw edema in female adult Balb/c mice who received the nanoemulsion diet compared to the other experimental groups (control, formalin, fish oil and sunflower oil). These results indicate that the fish oil nanoemulsion was significantly effective in the dietary conditions tested here, presenting satisfactory responses in the modulation of inflammatory disorders, demonstrating interesting and beneficial nutraceutical effects.

Robust, universal, and persistent bud secretion adhesion in horse-chestnut trees

Buds of horse-chestnut trees are covered with a viscous fluid, which remains sticky after long-term exposure to heat, frost, radiation, precipitation, deposition of aerosols and particles, attacks by microbes and arthropods. The present study demonstrates that the secretion does not dry out under arid conditions, not melt at 50 °C, and not change significantly under UV radiation or frost at a microscopic level. It is slightly swellable under wet conditions; and, it universally wets and adheres to substrates having different polarities. Measured pull-off forces do not differ between hydrophilic and lipophilic surfaces, ranging between 58 and 186 mN, and resulting in an adhesive strength up to 204 kPa. The mechanical and chemical properties of secretion resemble those of pressure-sensitive adhesives. The Raman, infrared, and nuclear magnetic resonance spectra show the clear presence of saturated aliphatic hydrocarbons, esters, free carboxylic acids, as well as minor amounts of amides and aromatic compounds. We suggest a multi-component material (aliphatic hydrocarbon resin), including alkanes, fatty acids, amides, and tackifying terpenoids embedded in a fluid matrix (fatty acids) comprising nonpolar and polar portions serving the universal and robust adhesive properties. These characteristics matter for ecological-evolutionary aspects and can inspire innovative designs of multifunctional, biomimetic pressure-sensitive adhesives and varnishes.

Design of Chitosan Nanocapsules with Compritol 888 ATO® for Imiquimod Transdermal Administration. Evaluation of Their Skin Absorption by Raman Microscopy

PURPOSE

Design imiquimod-loaded chitosan nanocapsules for transdermal delivery and evaluate the depth of imiquimod transdermal absorption as well as the kinetics of this absorption using Raman Microscopy, an innovative strategy to evaluate transdermal absorption. This nanovehicle included Compritol 888ATO®, a novel excipient for formulating nanosystems whose administration through the skin has not been studied until now.

METHODS

Nanocapsules were made by solvent displacement method and their physicochemical properties was measured by DLS and laser-Doppler. For transdermal experiments, newborn pig skin was used. The Raman spectra were obtained using a laser excitation source at 532 nm and a 20/50X oil immersion objective.

RESULTS

The designed nanocapsules, presented nanometric size (180 nm), a polydispersity index <0.2 and a zeta potential +17. The controlled release effect of Compritol was observed, with the finding that half of the drug was released at 24 h in comparison with control (p < 0.05). It was verified through Raman microscopy that imiquimod transdermal penetration is dynamic, the nanocapsules take around 50 min to penetrate the stratum corneum and 24 h after transdermal administration, the drug was in the inner layers of the skin.

CONCLUSIONS

This study demonstrated the utility of Raman Microscopy to evaluate the drugs transdermal penetration of in the different layers of the skin. Graphical Abstract New imiquimod nanocapsules: evaluation of their skin absorption by Raman Microscopy and effect of the compritol 888ATO® in the imiquimod release profile.

Vibrational Spectroscopic Characterization and Coherent Anti-Stokes Raman Spectroscopy (CARS) Imaging of Artepillin C

In the following work, the vibrational spectroscopic characteristics of artepillin C are reported by means of Fourier transform infrared (FT-IR) and Raman spectroscopies, surface-enhanced Raman scattering (SERS), and coherent anti-Stokes Raman scattering (CARS) microscopy. Artepillin C is an interesting compound due to its pharmacological properties, including antitumor activity. It is found as the major component of Brazilian green propolis, a resinous mixture produced by bees to protect their hives against intruders. Vibrational spectroscopic techniques have shown a strong peak at 1599 cm^-1, assigned to C=C stretching vibrations from the aromatic ring of artepillin C. From these data, direct visualization of artepillin C could be assessed by means of CARS microscopy, showing differences in the film hydration obtained for its neutral and deprotonated states. Raman-based methods show potential to visualize the uptake and action of artepillin C in biological systems, triggering its interaction with biological systems that are needed to understand its mechanism of action.

Raman Spectroscopy Enables Non-Invasive Identification of Peanut Genotypes and Value-Added Traits

Identification of specific genotypes can be accomplished by visual recognition of their distinct phenotypical appearance, as well as DNA analysis. Visual identification (ID) of species is subjective and usually requires substantial taxonomic expertise. Genotyping and sequencing are destructive, time- and labor-consuming. In this study, we investigate the potential use of Raman spectroscopy (RS) as a label-free, non-invasive and non-destructive analytical technique for the fast and accurate identification of peanut genotypes. We show that chemometric analysis of peanut leaflet spectra provides accurate identification of different varieties. This same analysis can be used for prediction of nematode resistance and oleic-linoleic oil (O/L) ratio. Raman-based analysis of seeds provides accurate genotype identification in 95% of samples. Additionally, we present data on the identification of carbohydrates, proteins, fiber and other nutrients obtained from spectroscopic signatures of peanut seeds. These results demonstrate that RS allows for fast, accurate and non-invasive screening and selection of plants which can be used for precision breeding.

Rapid and Noninvasive Typing and Assessment of Nutrient Content of Maize Kernels Using a Handheld Raman Spectrometer

To thrive as a global civilization, food production must meet the demands of our ever-growing population. There are more than a billion people on the planet suffering from malnutrition through poor quality or lack of food. Nutrient content of food can be determined by a variety of methods, which have issues such as slow analysis or sample destruction. Near-infrared (NIR) spectroscopy is a long-standing alternative to these methods. In this work, we demonstrated that Raman spectroscopy (RS), another spectroscopic method, can also be used to assess the nutrient content of maize (Zea mays), one of the most widely cultivated grains in the world. Using a handheld Raman spectrometer, we predicted the content of carbohydrates, fibers, carotenoids, and proteins in six different varieties of maize. This analysis requires only a single maize kernel and is fast (1s), portable, noninvasive, and nondestructive. Moreover, we showed that RS in combination with chemometric methods can be used for highly accurate (approximately 90%) spectroscopic typing of maize, which is important for plant breeders and farmers. Finally, we demonstrate that Raman-based approach is as accurate as NIR analysis. These findings suggest that portable Raman systems can be used on combines and grain elevators for autonomous control of grain quality.

The lipid profile of three Malassezia species assessed by Raman spectroscopy and discriminant analysis

Malassezia yeasts constitute the major eukaryotic cutaneous flora of homoeothermic vertebrates. These lipophilic yeasts are able to cause, trigger, or aggravate common skin diseases under favorable conditions. Species identification and subspecies differentiation is currently based on morphological characteristics, lipid assimilation profile, and molecular tests. Mass spectrometry has been also reported as a reliable, yet costly and labor-intensive, method to classify Malassezia yeasts. Here, we introduce Raman spectroscopy as a new molecular technique able to differentiate three phylogenetically close Malassezia species (M.globosa, M.pachydermatis, and M.sympodialis) by examining their lipid metabolic profile. Using Raman spectroscopy, lipid fingerprints of Malassezia cultures on Leeming-Notman agar, were analyzed by spectral bands assignment and partial least squares discriminant analysis. Our results demonstrate differential utilization of lipid supplements among these three species and the ability of Raman spectroscopy to rapidly and accurately discriminate them by predictive modelling.

Effect of Cerium Precursor in the Synthesis of Ce-MCM-41 and in the Efficiency for Liquid-Phase Oxidation of Benzyl Alcohol

Understanding the effects of synthetic parameters in the catalytic activity of heterogeneous catalysts is of utmost importance when aiming for optimal reaction conditions. Hence, we disclose in this work the synthesis and characterization of cerium-modified MCM-41 materials. In addition, it was observed for the first time, differences in catalytic activity when using different cerium synthetic precursors: CeCl3·7H2O and Ce(NO3)3·6H2O (Ce-MCM-Cl and Ce-MCM-NO3, respectively). A mechanism for cerium incorporation in MCM-41 was proposed, where [Ce(OH)3] species were hydrogen bonded to silicate anions, forming framework Ce-O-Si bonds during condensation and, consequently, causing distortion of the typical hexagonal mesophase. It was also observed that Ce(OH)3 formed aggregated layers with template assemblies during synthesis, resulting in non-framework CeO2 species on the MCM-41 surface after calcination. These CeO2 species were preferentially formed for Ce-MCM-NO3 and were attributed to the nitrate ions’ strong binding to template molecules. In the solvent free liquid-phase oxidation of benzyl alcohol (BzOH), Ce-MCM-Cl achieved better BzOH conversions and benzaldehyde (BzD) yields, while Ce-MCM-NO3 offered increased BzD selectivity. The catalysts’ reusability was also studied over three catalytic runs, where Ce-MCM-NO3 was more resistant than Ce-MCM-Cl towards deactivation. The observed catalytic behavior shows the importance of metal precursors in the obtainment of materials with desirable final properties.