Fusing 1H NMR and Raman experimental data for the improvement of wine recognition models.

The present study proposes the development of new wine recognition models based on Artificial Intelligence (AI) applied to the mid-level data fusion of 1H NMR and Raman data. In this regard, a supervised machine learning method, namely Support Vector Machines (SVMs), was applied for classifying wine samples with respect to the cultivar, vintage, and geographical origin. Because the association between the two data sources generated an input space with a high dimensionality, a feature selection algorithm was employed to identify the most relevant discriminant markers for each wine classification criterion, before SVM modeling. The proposed data processing strategy allowed the classification of the wine sample set with accuracies up to 100% in both cross-validation and on an independent test set and highlighted the efficiency of 1H NMR and Raman data fusion as opposed to the use of a single-source data for differentiating wine concerning the cultivar and vintage.

Rapid diagnosis of celiac disease based on plasma Raman spectroscopy combined with deep learning.

Celiac Disease (CD) is a primary malabsorption syndrome resulting from the interplay of genetic, immune, and dietary factors. CD negatively impacts daily activities and may lead to conditions such as osteoporosis, malignancies in the small intestine, ulcerative jejunitis, and enteritis, ultimately causing severe malnutrition. Therefore, an effective and rapid differentiation between healthy individuals and those with celiac disease is crucial for early diagnosis and treatment. This study utilizes Raman spectroscopy combined with deep learning models to achieve a non-invasive, rapid, and accurate diagnostic method for celiac disease and healthy controls. A total of 59 plasma samples, comprising 29 celiac disease cases and 30 healthy controls, were collected for experimental purposes. Convolutional Neural Network (CNN), Multi-Scale Convolutional Neural Network (MCNN), Residual Network (ResNet), and Deep Residual Shrinkage Network (DRSN) classification models were employed. The accuracy rates for these models were found to be 86.67%, 90.76%, 86.67% and 95.00%, respectively. Comparative validation results revealed that the DRSN model exhibited the best performance, with an AUC value and accuracy of 97.60% and 95%, respectively. This confirms the superiority of Raman spectroscopy combined with deep learning in the diagnosis of celiac disease.

Structural, elastic, electronic, optical and anisotropy properties of newly quaternary Tl2HgGeSe4 via DFPT predictions associated to XPES and RS experiments.

In the present work, we report on theoretical studies of thermodynamic properties, structural and dynamic stabilities, dependence of unit-cell parameters and elastic constants upon hydrostatic pressure, charge carrier effective masses, electronic and optical properties, contributions of interband transitions in the Brillouin zone of the novel Tl2HgGeSe4 crystal. The theoretical calculations within the framework of the density-functional perturbation theory (DFPT) are carried out employing different approaches to gain the best correspondence to the experimental data. The present theoretical data indicate the dynamical stability of the title crystal and they reveal that, under hydrostatic pressure, it is much more compressible along the a-axis than along the c-axis. Strikingly, the charge effective mass values ( m e ∗ and m h ∗ ) vary considerably when the high symmetry direction changes indicating a relative anisotropy of the charge-carrier's mobility. Furthermore, the Young modulus and compressibility are characterized by the maximum and minimum values ( E max and E min ) and ( ß max and ß min ) that are equal to (62.032 and 28.812) GPa and (13.672 and 6.7175) TPa-1, respectively. Additionally, we have performed calculations of the Raman spectra (RS) and reached a good correspondence with the experimental RS spectra of the Tl2HgGeSe4 crystal. The XPES associated to RS constitutes powerful techniques to explore the oxidized states of Se and Ge in Tl2HgGeSe4 system.

Enhancing Micro-Raman Spectroscopy: A Variable Spectral Resolution Instrument Using Zoom Lens Technology.

Raman spectroscopy is a powerful analytical technique based on the inelastic scattering of photons. Conventional macro-Raman spectrometers are suitable for mass analysis but often lack the spatial resolution required to accurately examine microscopic regions of interest. For this reason, the development of micro-Raman spectrometers has been driven forward. However, even with micro-Raman spectrometers, high resolution is required to gain better insight into materials that provide low-intensity Raman signals. Here, we show the development of a micro-Raman spectrometer with implemented zoom lens technology. We found that by replacing a second collimating mirror in the monochromator with a zoom lens, the spectral resolution could be continuously adjusted at different zoom factors, i.e., high resolution was achieved at a higher zoom factor and lower spectral resolution was achieved at a lower zoom factor. A quantitative analysis of a micro-Raman spectrometer was performed and the spectral resolution was analysed by FWHM using the Gaussian fit. Validation was also performed by comparing the results obtained with those of a high-grade laboratory Raman spectrometer. A quantitative analysis was also performed using the ANOVA method and by assessing the signal-to-noise ratio between the two systems.

Ultralow-Frequency Tip-Enhanced Raman Scattering Discovers Nanoscale Radial Breathing Mode on Strained 2D Semiconductors.

Collective excitations including plasmons, magnons, and layer-breathing vibration modes emerge at an ultralow frequency (<1 THz) and are crucial for understanding van der Waals materials. Strain at the nanoscale can drastically change the property of van der Waals materials and create localized states like quantum emitters. However, it remains unclear how nanoscale strain changes collective excitations. Herein, ultralow-frequency tip-enhanced Raman spectroscopy (TERS) with sub-10 nm resolution under ambient conditions is developed to explore the localized collective excitation on monolayer semiconductors with nanoscale strains. A new vibrational mode is discovered at around 12 cm-1 (0.36 THz) on monolayer MoSe2 nanobubbles and it is identified as the radial breathing mode (RBM) of the curved monolayer. The correlation is determined between the RBM frequency and the strain by simultaneously performing deterministic nanoindentation and TERS measurement on monolayer MoSe2. The generality of the RBM in nanoscale curved monolayer WSe2 and bilayer MoSe2 is demonstrated. Using the RBM frequency, the strain of the monolayer MoSe2 on the nanoscale can be mapped. Such an ultralow-frequency vibration from curved van der Waals materials provides a new approach to study nanoscale strains and points to more localized collective excitations to be discovered at the nanoscale.

Effect of CO binding to P450 BM3 F393 mutants on electron density distribution in the heme cofactor.

Resonance Raman spectroscopy has been performed on a set of cytochrome P450 BM3 heme domains in which mutation of the highly conserved Phe393 induces significant variation in heme iron reduction potential. In previous work [Chen, Z., Ost, T.W.B., and Schelvis, J.P.M. (2004) Biochemistry 43, 1798-1808], a correlation between heme vinyl conformation and the heme iron reduction potential indicated a steric control by the protein over the distribution of electron density in the reduced heme cofactor. The current study aims to monitor changes in electron density on the ferrous heme cofactor following CO binding. In addition, ferric-NO complexes have been studied to investigate potential changes to the proximal Cys400 thiolate. We find that binding of CO to the ferrous heme domains results in a reorientation of the vinyl groups to a largely out-of-plane conformation, the extent of which correlates with the size of the residue at position 393. We conclude that FeII dπ back bonding to the CO ligand largely takes away the need for conjugation of the vinyl groups with the porphyrin ring to accommodate FeII dπ back bonding to the porphyrin ligand. The ferrous-CO and ferric-NO data are consistent with a small decrease in σ-electron donation from the proximal Cys400 thiolate in the F393A mutant and, to a lesser extent, the F393H mutant, potentially due to a small increase in hydrogen bonding to the proximal ligand. Phe393 seems strategically placed to preserve robust σ-electron donation to the heme iron and to fine-tune its electron density by limiting vinyl group rotation.

Enhanced Photoluminescence of Plasma-Treated Recycled Glass Particles.

Recycled soda-lime glass powder is a sustainable material that is also often considered a filler in cement-based composites. The changes in the surface properties of the glass particles due to the treatments were analyzed by X-ray photoelectron spectroscopy (XPS) and optical spectroscopy. We have found that there is a relatively high level of carbon contamination on the surface of the glass particles (around 30 at.%), so plasma technology and thermal annealing were tested for surface cleaning. Room temperature plasma treatment was not sufficient to remove the carbon contamination from the surface of the recycled glass particles. Instead, the room temperature plasma treatment of recycled soda-lime glass particles leads to a significant enhancement in their room temperature photoluminescence (PL) by increasing the intensity and accelerating the decay of the photoluminescence. The enhanced blue PL after room-temperature plasma treatment was attributed to the presence of carbon contamination on the glass surface and associated charge surface and interfacial defects and interfacial states. Therefore, we propose blue photoluminescence under UV LED as a fast and inexpensive method to indicate carbon contamination on the surface of glass particles.

The Role of Hydrogen Bonding in the Raman Spectral Signals of Caffeine in Aqueous Solution.

The identification and quantification of caffeine is a common need in the food and pharmaceutical industries and lately also in the field of environmental science. For that purpose, Raman spectroscopy has been used as an analytical technique, but the interpretation of the spectra requires reliable and accurate computational protocols, especially as regards the Resonance Raman (RR) variant. Herein, caffeine solutions are sampled using Molecular Dynamics simulations. Upon quantification of the strength of the non-covalent intermolecular interactions such as hydrogen bonding between caffeine and water, UV-Vis, Raman, and RR spectra are computed. The results provide general insights into the hydrogen bonding role in mediating the Raman spectral signals of caffeine in aqueous solution. Also, by analyzing the dependence of RR enhancement on the absorption spectrum of caffeine, it is proposed that the sensitivity of the RR technique could be exploited at excitation wavelengths moderately far from 266 nm, yet achieving very low detection limits in the quantification caffeine content.

Label-Free Assessment of Neuronal Activity Using Raman Micro-Spectroscopy.

Given the pivotal role of neuronal populations in various biological processes, assessing their collective output is crucial for understanding the nervous system's complex functions. Building on our prior development of a spiral scanning mechanism for the rapid acquisition of Raman spectra from single cells and incorporating machine learning for label-free evaluation of cell states, we investigated whether the Paint Raman Express Spectroscopy System (PRESS) can assess neuronal activities. We tested this hypothesis by examining the chemical responses of glutamatergic neurons as individual neurons and autonomic neuron ganglia as neuronal populations derived from human-induced pluripotent stem cells. The PRESS successfully acquired Raman spectra from both individual neurons and ganglia within a few seconds, achieving a signal-to-noise ratio sufficient for detailed analysis. To evaluate the ligand responsiveness of the induced neurons and ganglia, the Raman spectra were subjected to principal component and partial least squares discriminant analyses. The PRESS detected neuronal activity in response to glutamate and nicotine, which were absent in the absence of calcium. Additionally, the PRESS induced dose-dependent neuronal activity changes. These findings underscore the capability of the PRESS to assess individual neuronal activity and elucidate neuronal population dynamics and pharmacological responses, heralding new opportunities for drug discovery and regenerative medicine advancement.

From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis.

Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we describe how surface-enhanced Raman spectroscopy (SERS) assisted with machine learning (ML) can expand its capabilities to enable interpretable insights into the transcriptome, proteome, and metabolome at the single-cell level. We first review how advances in nanophotonics-including plasmonics, metamaterials, and metasurfaces-enhance Raman scattering for rapid, strong label-free spectroscopy. We then discuss ML approaches for precise and interpretable spectral analysis, including neural networks, perturbation and gradient algorithms, and transfer learning. We provide illustrative examples of single-cell Raman phenotyping using nanophotonics and ML, including bacterial antibiotic susceptibility predictions, stem cell expression profiles, cancer diagnostics, and immunotherapy efficacy and toxicity predictions. Lastly, we discuss exciting prospects for the future of single-cell Raman spectroscopy, including Raman instrumentation, self-driving laboratories, Raman data banks, and machine learning for uncovering biological insights.

Improvement of a low-cost protocol for a simultaneous comparative evaluation of hydrolytic activity between sessile and planktonic cells: Candida albicans as a study model.

Candida albicans is often implicated in nosocomial infections with fatal consequences. Its virulence is contributed to hydrolytic enzymes and biofilm formation. Previous research focused on studying these virulence factors individually. Therefore, this study aimed to investigate the impact of biofilm formation on the hydrolytic activity using an adapted low-cost method. Eleven strains of C. albicans were used. The biofilms were formed on pre-treated silicone discs using 24-well plates and then deposited on the appropriate agar to test each enzyme, while the planktonic cells were conventionally seeded. Biofilms were analysed using Raman spectroscopy, fluorescent and scanning electron microscopy. The adapted method provided an evaluation of hydrolytic enzymes activity in C. albicans biofilm and showed that sessile cells had a higher phospholipase and proteinase activities compared with planktonic cells. These findings were supported by spectroscopic and microscopic analyses, which provided valuable insights into the virulence mechanisms of C. albicans during biofilm formation.

Quantitative analysis of solid dosage forms of Atenolol by Raman spectroscopy.

OBJECTIVE: To develop a Raman spectroscopy-based analytical model for quantification of solid dosage forms of active pharmaceutical ingredient (API) of Atenolol.Significance: For the quantitative analysis of pharmaceutical drugs, Raman Spectroscopy is a reliable and fast detection method. As part of this study, Raman Spectroscopy is explored for the quantitative analysis of different concentrations of Atenolol. METHODS: Various solid-dosage forms of Atenolol were prepared by mixing API with excipients to form different solid-dosage formulations of Atenolol. Multivariate data analysis techniques, such as Principal Component Analysis (PCA) and Partial least square regression (PLSR) were used for the qualitative and quantitative analysis, respectively. RESULTS: As the concentration of the drug increased in formulation, the peak intensities of the distinctive Raman spectral characteristics associated with the API (Atenolol) gradually increased. Raman spectral data sets were classified using PCA due to their distinctive spectral characteristics. Additionally, a prediction model was built using PLSR analysis to assess the quantitative relationship between various API (Atenolol) concentrations and spectral features. With a goodness of fit value of 0.99, the root mean square errors of calibration (RMSEC) and prediction (RMSEP) were determined to be 1.0036 and 2.83 mg, respectively. The API content in the blind/unknown Atenolol formulation was determined as well using the PLSR model. CONCLUSIONS: Based on these results, Raman spectroscopy may be used to quickly and accurately analyze pharmaceutical samples and for their quantitative determination.

Microplastic pollution in the North-east Atlantic Ocean surface water: How the sampling approach influences the extent of the issue.

A lack of standardization in monitoring protocols has hindered the accurate evaluation of microplastic (MP) pollution in the open sea and its potential impacts. As sampling techniques significantly influence the amounts of MPs contained in the sample, the aim of this study was to compare two sampling methods: Manta trawl (size selective approach) and grab sampling (volume selective approach). Both approaches were applied in the open sea surface waters of the North-east Atlantic Ocean. Onshore sample processing was carried out using the innovative tape lifting technique, which affords a series of advantages, including prevention of airborne contamination during analysis, without compromising integrity of the results. The results obtained indicated an MP concentration over four orders of magnitude higher using grab sampling compared to the Manta net approach (mean values equal to 0.24 and 4050 items/m3, respectively). Consequently, the sole quantification of MPs using results obtained with the Manta trawl resulted in a marked underestimation of abundance. Nevertheless, the grab sampling technique is intricately linked to a risk of collecting non-representative water volumes, consequently leading to an overestimation of MPs abundance and a significant inter-sample variability. Moreover, the latter method is unsuitable for use in sampling larger MPs or in areas with low concentrations of MP pollution. The optimal sampling method therefore is dependent on the specific objectives of the study, often resulting in a combination of size and volume selective methods. The results of this study have the potential to contribute to the standardization of monitoring protocols for microplastics, both during the sampling phase and sample processing.

Raman spectroscopy in lung cancer diagnostics: Can an in vivo setup compete with ex vivo applications?

Lung carcinoma remains the leading cause of cancer death worldwide. The tactic to change this unfortunate rate may be a timely and rapid diagnostic, which may in many cases improve patient prognosis. In our study, we focus on the comparison of two novel methods of rapid lung carcinoma diagnostics, label-free in vivo and ex vivo Raman spectroscopy of the epithelial tissue, and assess their feasibility in clinical practice. As these techniques are sensitive not only to the basic molecular composition of the analyzed sample but also to the secondary structure of large biomolecules, such as tissue proteins, they represent suitable candidate methods for epithelial cancer diagnostics. During routine bronchoscopy, we collected 78 in vivo Raman spectra of normal and cancerous lung tissue and 37 samples of endobronchial pathologies, which were subsequently analyzed ex vivo. Using machine learning techniques, namely principal component analysis (PCA) and support vector machines (SVM), we were able to reach 87.2% (95% CI, 79.8-94.6%) and 100.0% (95% CI, 92.1-100.0%) of diagnostic accuracy for in vivo and ex vivo setup, respectively. Although the ex vivo approach provided superior results, the rapidity of in vivo Raman spectroscopy might become unmatchable in the acceleration of the diagnostic process.

Molecular mechanisms behind BRACO19 and human telomeric G-quadruplex interaction.

Human telomeres (HTs) can form DNA G-quadruplex (G4), an attractive target for anticancer and antiviral drugs. HT-G4s exhibit inherent structural polymorphism, posing challenges for understanding their specific recognition by ligands. Here, we aim to explore the impact of different topologies within a small segment of the HT (Tel22) on its interaction with BRACO19, a rationally designed G4 ligand with high quadruplex affinity, already employed in in-vivo treatments. Our multi-technique approach is based on the combined use of a set of contactless spectroscopic tools. Circular dichroism and UV resonance Raman spectroscopy probe ligand-induced conformational changes in the G4 sequence, while UV-visible absorption, coupled with steady-state fluorescence spectroscopy, provides further insights into the electronic features of the complex, exploiting the photoresponsive properties of BRACO19. Overall, we find that modifying the topology of the unbound Tel22 through cations (K+ or Na+), serves as a critical determinant for ligand interactions and binding modes, thus influencing the HT-G4's assembly capabilities. Furthermore, we show how fluorescence serves as a valuable probe for recognizing cation-driven multimeric structures, which may be present in living organisms, giving rise to pathological forms.

Investigation of ion association kinetics in Na2SO4-H2O by excess Raman spectroscopy and 2D correlation Raman spectroscopy.

The ion association of salts aqueous solutions have long captivated the attention of researchers within the field of physical chemistry. In this paper, we have performed a comprehensive analysis of ion interactions in sodium sulfate (Na2SO4) aqueous solutions using a combination of high-resolution techniques, including excess (ERS) and two-dimensional correlation (2DCRS) Raman spectroscopy in conjunction with molecular dynamics (MD) calculations. The Raman spectrum shows that two inflection points in the Raman shift of the O-H vibration are observed with the increase in Na2SO4 concentration. Simultaneously, a new peak of the SO42- vibration appears at first inflection point, representing the formation of ion association. Further analysis based on ERS and 2CRS reveals that these two inflection points correspond respectively to the formation of ion pairs (CIPs) and small ion clusters. Importantly, MD simulations confirm the above experimental results. Our study provides evidence for ion association and clustering in aqueous in salt ion aqueous solutions.

Ultrabroadband two-beam coherent anti-Stokes Raman scattering and spontaneous Raman spectroscopy of organic fluids: A comparative study.

Spontaneous Raman spectroscopy is a well-established diagnostic tool, allowing for the identification of all Raman active species with a single measurement. Yet, it may suffer from low-signal intensity and fluorescent background. In contrast, coherent anti-Stokes Raman scattering (CARS) offers laser-like signals, but the traditional approach lacks the multiplex capability of spontaneous Raman spectroscopy. We present an ultrabroadband CARS setup which aims at exciting the full spectrum (300-3700 cm-1) of biological molecules. A dual-output optical parametric amplifier provides a ~7 fs pump/Stokes and a ~700 fs probe pulse. CARS spectra of DMSO, ethanol, and methanol show great agreement with spontaneous Raman spectroscopy and superiority in fluorescent environments. The spectral resolution proves sufficient to differentiate between the complex spectra of L-proline and hydroxyproline. Moreover, decay constants in the sub picosecond range are determined for individual Raman transitions, providing an additional approach for sample characterization.

Raman spectroscopy: A promising analytical tool used in human reproductive medicine.

Over the past few years, there has been growing interest in developing new methods of embryo quality assessment to improve the outcomes of assisted reproductive technologies in the medical field. Raman microscopy as an increasingly promising analytical tool has been widely used in life sciences, biomedicine and "omics" to study molecular, biochemical components, living cells and tissues due to the label-free and non-destructive nature of the imaging technique. This paper reviews the analytical capability of Raman microscopy and applications of Raman spectroscopy technology mainly in reproductive medicine. The purpose of this review is to introduce the Raman spectroscopy technology, application and underlying principles of the method, to provide an intact picture of its uses in biomedical science and reproductive medicine, to offer ideas for its future application, verification and validation. The focus is on the application of Raman spectroscopy in the reproductive medicine field, including the application in gametes, embryos and spent embryo culture media.

Optically printed plasmonic fiber tip-assisted SERS-based chemical sensing and single biological cell studies.

BACKGROUND: Precise localized printing of plasmonic nanoparticles at desired locations can find a plethora of applications in diverse areas, including nanophotonics, nanomedicine, and microelectronics. The focused laser beam-assisted optical printing technique has illustrated its potential for the localized printing of differently shaped plasmonic particles. However, the technique is either time-consuming or often requires focused optical radiation, limiting its practical applications. While the optothermal printing technique has recently emerged as a promising technique for the direct and rapid printing of plasmonic nanoparticles onto transparent substrates at lower laser intensities, its potential to print the plasmonic nanoparticles to the core of the optical fiber platforms and utilize it for biological cell trapping as well as an analytical platform remains unexplored. RESULTS: Herein, we demonstrate the thermal-convection-assisted printing of the Ag plasmonic nanoparticles from the plasmonic colloidal solution onto the core of single-mode optical fiber and its multi-functional applications. The direct printing of plasmonic structure on the fiber core via the thermal-convection mechanism is devoid of the requirement of any additional chemical ligand to the fiber core. Further, we demonstrated the potential of the developed plasmonic fiber probe as a multifunctional surface-enhanced Raman spectroscopic (SERS) platform for sensing, chemical reaction monitoring, and single-cell studies. The developed SERS fiber probe is found to detect crystal violet in an aqueous solution as low as 100 pM, with a plasmonic enhancement of 107. Additionally, the capability of the fiber-tip platform to monitor the surface plasmon-driven chemical reaction of 4-nitrothiophenol (4NTP) dimerizing into p, p'-dimercaptoazobenzene (DMAB) is demonstrated. Further, the versatility of the fiber probe as an effective platform for opto-thermophoretic trapping of single biological cells such as yeast, along with its Raman spectroscopic studies, is also shown here. SIGNIFICANCE: In this study, we illustrate for the first time the optothermal direct printing of plasmonic nanoparticles onto the core of a single-mode fiber. Further, the study demonstrates that such plasmonic nanoparticle printed fiber tip can act as a multi-functional analytical platform for optothermally trap biological particles as well as monitoring plasmon-driven chemical reactions. In addition, the plasmonic fiber tip can be used as a cost-effective SERS analytical platform and is thus expected to find applications in diverse areas.

Production and SERS characterization of bacteriocin-like inhibitory substances by latilactobacillus sakei in whey permeate powder: exploring natural antibacterial potential.

Bacteriocins are antimicrobial compounds that have awakened interest across several industries due to their effectiveness. However, their large-scale production often becomes unfeasible on an industrial scale, primarily because of high process costs. Addressing this challenge, this work analyzes the potential of using low-cost whey permeate powder, without any supplementation, to produce bacteriocin-like inhibitory substances (BLIS) through the fermentation of Latilactobacillus sakei. For this purpose, different concentrations of whey permeate powder (55.15 gL-1, 41.3 gL-1 and 27.5 gL-1) were used. The ability of L. sakei to produce BLIS was evaluated, as well as the potential of crude cell-free supernatant to act as a preservative. Raman spectroscopy and surface-enhanced Raman scattering (SERS) provided detailed insights into the composition and changes occurring during fermentation. SERS, in particular, enhanced peak definition significantly, allowing for the identification of key components, such as lactose, proteins, and phenylalanine, which are crucial in understanding the fermentation process and BLIS characteristics. The results revealed that the concentration of 55.15 gL-1 of whey permeate powder, in flasks without agitation and a culture temperature of 32.5 °C, presented the highest biological activity of BLIS, reaching 99% of inhibition of Escherichia coli and Staphylococcus aureus with minimum inhibitory concentration of 36-45%, respectively. BLIS production began within 60 h of cultivation and was associated with class II bacteriocins. The results demonstrate a promising approach for producing BLIS in an economical and environmentally sustainable manner, with potential implications for various industries.