Raman Spectroscopy Techniques Research Articles

A Review of Non-Destructive Raman Spectroscopy and Chemometric Techniques in the Analysis of Cultural Heritage

Today, there is an increasing concern and effort for protection, conservation, and restoration of cultural heritage materials. Non-invasive analytical methodologies such as Raman spectroscopy offers various advantages such as high speed, robust identification, low cost, and in-site analysis. Previous contributions highlighted the potential of Raman spectroscopy combined with multivariate statistics for identification and quality evaluation of cultural heritage materials such as paints, fiber, dyes, woods, stones, inks, and textile materials. Especially, application of chemometrics and multivariate statistics algorithms opens new horizons for scientists and inspectors. In conclusion, the paper provided an overview of the state-of-the-art uses of multivariate statistically equipped Raman spectroscopy methods for evaluation of cultural heritage and art materials with illustrations from previous research studies.

Feasibility Study of Label-Free Raman Spectroscopy forParathyroid Gland Identification.

We aim to evaluate the feasibility of Raman spectroscopy for parathyroid gland (PG) identification during thyroidectomy. Using a novel side-viewing handheld Raman probe, a total of 324 Raman spectra of four tissue types (i.e., thyroid, lymph node, PG, and lipid) commonly encountered during thyroidectomy were rapidly (< 3 s) acquired from 80 tissue sites (thyroid [n = 10], lymph node [n = 10], PG [n = 40], lipid [n = 20]) of 10 euthanized Wistar rats. Two partial least-squares (PLS)-discriminant analysis (DA) detection models were developed, differentiating the lipid and nonlipid (i.e., thyroid, lymph node, and PG) tissues with an accuracy of 100%, and PG, lymph node, and thyroid could be detected with an accuracy of 98.4%, 93.9%, and 95.4% respectively. This work demonstrates the feasibility of Raman spectroscopy technique for PG identification and protection during thyroidectomy at the molecular level.

Characterization of PbMo0.3W0.7O4 Crystal: A Potential Material for Photocatalysis and Optoelectronic Applications

AbstractPbMo0.3W0.7O4 semiconductor crystal, which contains the balanced ratios of Mo and W, is grown for the first time by Czochralski method. The structural and optical properties of the crystal are investigated in detail in the present study. Structural analysis shows that crystal has tetragonal structure like PbMoO4 and PbWO4 compounds. The optical characteristics are studied by transmission, Raman, FTIR and photoluminescence methods. The bandgap energy is found to be 3.18 eV, and the positions of the conduction and valence bands are determined. The vibrational characteristics are studied by means of Raman and FTIR spectroscopy techniques. Photoluminescence spectrum presents three peaks around 486, 529, and 544 nm which fall into the green emission spectral range. Taking into account the properties of the compound, it is stated that PbMo0.3W0.7O4 (or Pb(MoO4)0.3(WO4)0.7) has the potential to be used in water splitting applications and optoelectronic devices that emit green light.

Challenges in Raman Spectroscopy of (micro)Plastics: The interfering role of colourants

Rising plastic consumption leads to widespread microplastic (MP) contamination. Raman spectroscopy is widely used for MP identification due to its ability to analyse particles as small as 1 μm. However, it faces challenges such as interference from pigments and additives. In this study, we aim to assess the accuracy of Raman micro-spectroscopy in identifying coloured plastic samples by applying various oxidative treatments to eliminate the possible interference effect caused by colourants associated with the sample. Standard and coloured microplastics were analysed using a Raman imaging microscope. Coloured plastics were treated with H2O2 30%, Sodium hypochlorite 5%, and Fenton reagent ( H2O2 30% and Ferrous sulphate 0.2 M) for 24, 48, and 72 hours. The Raman spectra were acquired after treatment to assess the impact of the treatment procedure on the polymer identification. Our results revealed that colourants significantly impact Raman spectra by peak broadening and/or fluorescence effects, which reduces identification accuracy and match scores Red pigments particularly obscure polymer identification. Treatments like oxidation and Fenton's reagent showed limited effectiveness. Additives in plastic samples can affect the accuracy of polymer identification by the Raman spectroscopy technique. Common treatment procedures do not improve the accuracy of identification. In order to improve the reliability of Raman analysis, essential factors such as utilizing multiple excitation lasers and appropriate CCD detectors, establishing a comprehensive reference library of colourants and additives, and employing advanced techniques like time-gated Raman spectroscopy or Surface-Enhanced Raman Spectroscopy (SERS) should be considered.

Drug expiration study using Raman spectroscopy and super paramagnetic clustering

Currently, there is a belief that drugs used after the expiration date no longer work, or even these can cause some damage. In the present work, several types of drugs on the market with different expiration dates are analyzed to find out if these, with the expired expiration date, present spectroscopic differences from those drugs whose expiration date is still valid. This study used the Raman spectroscopy technique to determine the chemical composition of drugs. To measure the drug Raman spectra, Horiba equipment, LabRam HR800, was used with an Olympus confocal microscope focusing a laser of 830 nm and 17 mW on the drugs through a 50 X Leica long-range objective. The Super Paramagnetic Clustering (SPC) method was applied to classify the Raman spectra. In the SPC method, the clustering process is based on a phenomenon of clustering observed in nature at the atomic level and perfectly described by a statistical physics model known as the Potts model, which describes the interacting spins on a crystalline lattice. This clustering method allows for identifying hierarchical structures in the spectra data banks. Fourteen drugs were analyzed, including 2 capsules, 5 tablets, 2 liquid samples, 4 ointments, and one spray with 1 to 3 expired expiration dates. Comparing drugs with expiration dates that are still valid and expired, the SPC results applied to the Raman spectra showed that, although some drugs indicated chemical differences, others indicated no chemical differences, even among those with up to two expired expiration dates. The results showed that Raman spectroscopy and SPC are excellent tools for discriminating between expired and non-expired drugs. The Principal Components Analysis (PCA) was also applied as a cross-checking method of the SPC result, obtaining consistent results. To our knowledge, it is the first preliminary result evaluating the usefulness of Raman spectroscopy and SPC in identifying expired drugs distributed on the market.

Single gold nanowire-nanoparticles conjugated system: Fabrication and sensing application

Single-entity-based sensing platform has many advantages for real-time assays, such as single-molecule analysis, or targets detection in confined environment. In this contribution, a new single Au nanowire (NW) – Au@Pt/Au nanoparticles (Au@Pt/Au NPs) conjugated system was established and used for the detection of thrombin by using surface-enhanced Raman spectroscopy (SERS) technique. This method was mainly based on electrostatic attraction between the capture (thrombin aptamer) and probe molecules (crystal violet, CV) on the surface of Au NW - Au@Pt/Au NPs conjugation, reducing the adsorption of CV molecules on conjugation surface, and resulting the decrease of SERS signals. The addition of thrombin could bind with thrombin aptamer due to specific interaction, leading to the decrease of electrostatic effect from thrombin aptamer for CV diffusion to conjugation surface, and the SERS signals could be recovered. This thrombin sensing method showed high sensitivity and selectivity, and the linear range for thrombin assay was 0.01 nM–100 nM with a detection limit of 1.35 pM. This single Au NW - Au@Pt/Au NPs conjugation has more SERS hotspots and small overall size, which offers unparalleled advantages over other sensing system and can be applicable for real time analysis, especially at single molecule/cell level.

Polyoxometalate/α-Fe2O3/polyaniline composite: Tailored approaches for high-performance supercapacitors

The need for portable, high-performance electronics that have high power or energy density has increased significantly in recent years. In this work, a composite material was coated on stainless steel that consists of polyoxometalate (POM)/α-Fe2O3/polyaniline (PANI) as an electrode material for a symmetric supercapacitor. α-Fe2O3 was prepared using starch as a template while PANI was electrodeposited. The physical and chemical characteristics of the modified electrodes were investigated via Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy and electrochemical techniques such as cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and galvanostatic chargedischarge (GCD) experiments. In 1 M H2SO4, the composite had a specific capacitance of 528 F/g at a current density of 0.2 A/g. In addition, the composite exhibited a high energy density of 73.4 Wh kg−1 at a high-power density of 7.14 kW kg−1 and 91.62 % capacity retention after 10 cycles. The results show that POM/α-Fe2O3/PANI is a promising composite electrode for use as a supercapacitor electrode material.

Rapid and accurate bacteria identification through deep-learning-based two-dimensional Raman spectroscopy

Surface-enhanced Raman spectroscopy (SERS) offers a distinctive vibrational fingerprint of the molecules and has led to widespread applications in medical diagnosis, biochemistry, and virology. With the rapid development of artificial intelligence (AI) technology, AI-enabled Raman spectroscopic techniques, as a promising avenue for biosensing applications, have significantly boosted bacteria identification. By converting spectra into images, the dataset is enriched with more detailed information, allowing AI to identify bacterial isolates with enhanced precision. However, previous studies usually suffer from a trade-off between high-resolution spectrograms for high-accuracy identification and short training time for data processing. Here, we present an efficient bacteria identification strategy that combines deep learning models with a spectrogram encoding algorithm based on wavelet packet transform and Gramian angular field techniques. In contrast to the direct analysis of raw Raman spectra, our approach utilizes wavelet packet transform techniques to compress the spectra by a factor of 1/15, while concurrently maintaining state-of-the-art accuracy by amplifying the subtle differences via Gramian angular field techniques. The results demonstrate that our approach can achieve a 99.64 % and a 90.55 % identification accuracy for two types of bacterial isolates and thirty types of bacterial isolates, respectively, while a 90 % reduction in training time compared to the conventional methods. To verify the model's stability, Gaussian noises were superimposed on the testing dataset, showing a specific generalization ability and superior performance. This algorithm has the potential for integration into on-site testing protocols and is readily updatable with new bacterial isolates. This study provides profound insights and contributes to the current understanding of spectroscopy, paving the way for accurate and rapid bacteria identification in diverse applications of environment monitoring, food safety, microbiology, and public health.

Classification of Vaginal Cleanliness Grades through Surface‐Enhanced Raman Spectral Analysis via The Deep‐Learning Variational Autoencoder–Long Short‐Term Memory Model

In this study, it is aimed to establish a novel method based on a deep‐learning‐guided surface‐enhanced Raman spectroscopy (SERS) technique to achieve rapid and accurate classification of vaginal cleanliness levels. We proposed a variational autoencoder (VAE) approach to enhance spectral quality, coupled with a deep learning algorithm long short‐term memory (LSTM) neural network to analyze SERS spectra produced by vaginal secretions. The performance of various machine learning (ML) algorithms is assessed using multiple evaluation metrics. Finally, the reliability of the optimal model is tested using blind test data (N = 10/group for each cleanliness level). The data quality of the SERS fingerprints of four types of vaginal secretions is significantly improved after VAE decoding and reconstruction. The signal‐to‐noise ratio of the generated spectra increased from the original 2.58–11.13. Among all algorithms, the VAE–LSTM algorithm demonstrates the best prediction ability and time efficiency. Additionally, blind test datasets yielded an overall accuracy of 85%. In this study, it is concluded that the deep‐learning‐guided SERS technique holds significant potential in rapidly distinguishing between different levels of vaginal cleanliness through human vaginal secretion samples. This contributes to the efficient diagnosis of vaginal cleanliness levels in clinical settings.

Green in-situ immobilization of ZnO nanoparticles for functionalization of polyester fabrics

Medical textiles have gained significant interest for their capability to prevent the transmission of infectious diseases and ensure the safety of healthcare professionals. Nevertheless, the incorporation of eco-friendly methods to enhance the functionality of these textiles, achieving both impressive antibacterial features and notable ultraviolet (UV) protection, along with thermal stability for effective use in UV-induced clean chambers, remains a complex undertaking. The main objective of this study is to explore the application of the green chemistry method in immobilizing zinc oxide (ZnO) nanoparticles (NPs) onto polydopamine (PDA)-templated polyester (PET) fabrics for potential use in medical textiles. Specifically, we examined the impact of varying the concentration of the zinc acetate dihydrate as the Zn precursor on the synthesis of ZnO NPs. Nanoparticle morphology and topography were analyzed using SEM and AFM. Elemental and chemical characteristics were further assessed through EDS analysis, FT-IR analysis, Raman spectroscopy, and X-ray diffraction (XRD) techniques. The results indicate that ZnO NPs immobilized on PDA-templated PET fabrics exhibit exceptional antibacterial and UV protection properties. Moreover, the presence of the ZnO/PDA layer on the PET fabric significantly enhances its thermal stability, making it an ideal candidate for medical textile applications.

Enhanced detection of glyphosate with a Co-MOF integrated opto-electrochemical sensor

Abstract This study presents a new method for detecting the organophosphorus pesticide glyphosate using advanced scanning electrodes (SPE) and enhanced fluorescence. Metal-organic frameworks from cobalt ions were synthesized using a solvothermal method. It is characterized using Raman spectroscopy, FT-IR, and X-ray diffraction techniques. The electrocatalytic behavior of the materials was studied using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Differential pulse voltammetry (DPV) examined the positive response of plants to glyphosate over a concentration range of 0.55–5.95 mM with a detection limit of 0.334 mM. The fluorescence enhancement ranges from 0.07 mM to 0.67 mM, and the detection limit is 0.0998 mM. Additionally, the selectivity of the proposed opto-electrochemical sensor was evaluated. This selection demonstrates the sensor's ability to detect glyphosate in complex wastewater matrices. This has important implications for environmental monitoring. By addressing glyphosate contamination, the sensor could significantly advance ecological remediation and monitoring strategies. The selectivity, sensitivity, and ability to operate under harsh conditions represent a significant advance in the development of efficient and reliable glyphosate technology for wastewater treatment and environmental protection. In real-sample matrices, the suggested sensor showed a good recovery of the pesticide that had been spiked.

Current Applications of Raman Spectroscopy in Intraoperative Neurosurgery.

Neurosurgery demands exceptional precision due to the brain's complex and delicate structures, necessitating precise targeting of pathological targets. Achieving optimal outcomes depends on the surgeon's ability to accurately differentiate between healthy and pathological tissues during operations. Raman spectroscopy (RS) has emerged as a promising innovation, offering real-time, in vivo non-invasive biochemical tissue characterization. This literature review evaluates the current research on RS applications in intraoperative neurosurgery, emphasizing its potential to enhance surgical precision and patient outcomes. Following PRISMA guidelines, a comprehensive systematic review was conducted using PubMed to extract relevant peer-reviewed articles. The inclusion criteria focused on original research discussing real-time RS applications with human tissue samples in or near the operating room, excluding retrospective studies, reviews, non-human research, and other non-relevant publications. Our findings demonstrate that RS significantly improves tumor margin delineation, with handheld devices achieving high sensitivity and specificity. Stimulated Raman Histology (SRH) provides rapid, high-resolution tissue images comparable to traditional histopathology but with reduced time to diagnosis. Additionally, RS shows promise in identifying tumor types and grades, aiding precise surgical decision-making. RS techniques have been particularly beneficial in enhancing the accuracy of glioma surgeries, where distinguishing between tumor and healthy tissue is critical. By providing real-time molecular data, RS aids neurosurgeons in maximizing the extent of resection (EOR) while minimizing damage to normal brain tissue, potentially improving patient outcomes and reducing recurrence rates. This review underscores the transformative potential of RS in neurosurgery, advocating for continued innovation and research to fully realize its benefits. Despite its substantial potential, further research is needed to validate RS's clinical utility and cost-effectiveness.

Energy–dependent femtosecond LIPSS on germanium and application in explosives sensing

Abstract In this study, we fabricated laser-induced periodic surface structures (LIPSS) on a germanium surface through laser ablation in air using axicon and femtosecond (fs) pulses. This novel approach permitted the nanoscale material processing outcome refinement via an fs Bessel beam. Our investigations aimed at systematically understanding the formation of periodic structures under various experimental conditions, such as (i) different pulse energies ranging from 50 µJ to 1000 µJ at a constant scan speed and (ii) constant energy with different scan speeds (0.1–3 mm s−1). By adjusting the fluences and scan speeds, we were able to identify the parametric space and alter the periodicity of the low-spatial frequency LIPSS and high-spatial frequency LIPSS on germanium, which were analyzed using field emission scanning electron microscopy. An optimal LIPSS formation over a large area of germanium was achieved at an input energy of 250 µJ and a scan speed of 0.75 mm s−1. Additionally, we measured the contact angles of the Ge nanostructures (GeNSs) to demonstrate their hydrophobic nature and non-wetting properties, providing insights into the behavior of LIPSS. Subsequently, the GeNSs were coated with a ∼15 nm thick gold (Au) film using a thermal deposition method. Utilizing these, the surface-enhanced Raman spectroscopy (SERS) technique detected diverse analytes, such as tetryl (an explosive) at a concentration of 50 µM and thiram (a pesticide) at 500 nM. The SERS enhancement factors for tetryl and thiram molecules on GeNSs coated with a 15 nm-thick Au layer were determined to be 2.5 × 104 and 4.2 × 105, respectively.

Carotenoids dispersed in gypsum rock as a result of algae adaptation to the extreme conditions of the Atacama Desert

The high-altitude pre-Andean region of the Atacama Desert is characterized by its stark volcanic rock formations and unique hydrothermal gypsum outcrops (gypcrete) that it hosts. This study delves into the biomolecular composition of the endolithic phototrophic microbes that thrive within these gypcretes. Using advanced Raman spectroscopy techniques, including Raman imaging (complemented by microscopic and 3D microscopic observations), herein we unveil new insights into the adaptive strategies of these gypsum-inhabiting algae. Our Raman imaging results provide a detailed chemical map of carotenoids associated with microbial colonization. This map reveals a significant gradient in pigment content, highlighting a critical survival mechanism for algae and cyanobacteria in this polyextreme environment. Intriguingly, we detected signals for carotenoids not only in the algae-colonized layer, but also deeper within the gypsum matrix - indicating pigment migration following cell disruption. In addition, we conducted an in-depth analysis of individual algal cells from the Trebouxiaceae family, noting their color variations from green to orange, plus describing the spectral differences in detail. This investigation identified in-vivo pigments (carotenoids, chlorophyll) and lipids at the cellular level, offering a comprehensive view of the molecular adaptations enabling life in one of the Earth’s most extreme habitats.

Electro‐Oxidation of Ibuprofen and Metoprolol Using a Manganese Oxide Platform

AbstractPharmaceutical compounds, such as ibuprofen and metoprolol, are of increasing concern due to their persistence in the environment and potential adverse effects on human health. In this work, we developed an electrochemical sensor system for the determination of ibuprofen and metoprolol based on a modified manganese oxide nanoparticle (MnO2NPs) on a screen‐printed carbon electrode (SPCE). The characterisation of MnO2NPs modifier was investigated via Fourier transform infrared (FTIR), X‐ray diffraction (XRD), scanning electron microscopy (SEM), Raman spectroscopy techniques, Uv/vis spectroscopy, and small‐angle X‐ray scattering spectroscopy. The electrochemical behaviour of the MnO2NPs was studied using differential pulse voltammetry (DPV) and cyclic voltammetry (CV) techniques. The optimum experimental conditions were investigated by examining the effects of scan rates, pH on the CV responses, and electrolytes on the DPV response. The MnO2NPs modified electrode demonstrated enhanced catalytic activity in the electro‐oxidation of both ibuprofen and metoprolol. The oxidation peaks of ibuprofen and metoprolol were observed at +1.14 V and +1.46 V, respectively, for the MnO2NPs/SPCE sensor. The sensor's limit of detection was 3.81 pM and 4.6 pM respectively and its linear response was from 0.97–5.82 pM. Furthermore, interference and stability studies were conducted to evaluate the performance of the MnO2NPs/SPCE sensor under optimum conditions, which resulted in a good performance. The proposed sensor was successfully used for the determination of ibuprofen and metoprolol in the application of real water samples.

Synergistic effects of thermally reduced graphene oxide/zinc oxide composite material on microbial infection for wound healing applications

Infections originating from pathogenic microorganisms can significantly impede the natural wound-healing process. To address this obstacle, innovative bio-active nanomaterials have been developed to enhance antibacterial capabilities. This study focuses on the preparation of nanocomposites from thermally reduced graphene oxide and zinc oxide (TRGO/ZnO). The hydrothermal method was employed to synthesize these nanocomposites, and their physicochemical properties were comprehensively characterized using X-ray diffraction analysis (XRD), High-resolution transmission electron microscopy (HR-TEM), Fourier-transform infrared (FT-IR), Raman spectroscopy, UV-vis, and field-emission scanning electron microscopy (FE-SEM) techniques. Subsequently, the potential of TRGO/ZnO nanocomposites as bio-active materials against wound infection-causing bacteria, including Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli, was evaluated. Furthermore, the investigated samples show disrupted bacterial biofilm formation. A reactive oxygen species (ROS) assay was conducted to investigate the mechanism of nanocomposite inhibition against bacteria and for further in-vivo determination of antimicrobial activity. The MTT assay was performed to ensure the safety and biocompatibility of nanocomposite. The results suggest that TRGO/ZnO nanocomposites have the potential to serve as effective bio-active nanomaterials for combating pathogenic microorganisms present in wounds.

Evaluation of 1064 nm Raman for meat and bone meal species discrimination: From raw form to chemical and physical components

The 1064 nm Raman spectroscopy technique was employed to characterize raw, bone fragments (BF), meat fragments (MF), lipid, and residue of meat and bone meal (MBM) samples. Employing three chemometric algorithms, species discrimination models were optimized for the aforementioned sample types, indicating that the presence of BF favored discriminant analysis for poultry samples, yielding a classification error of 0.000. The species discrimination model constructed using Raman spectra combined with PLS-DA algorithm for residue samples was found to be overall optimal, with classification error for four species samples all below 0.061. A detailed analysis of the BF related spectral variables contributing significantly to PLS-DA discriminant analysis was conducted. Finally, this study established the complementarity of Raman spectroscopy in species discrimination analysis from both a physical and chemical components perspective, laying the theoretical groundwork for the development of a high-precision 1064 nm Raman spectroscopic analysis method for MBM species discrimination.

Heteronuclear coordination polymers with imidazole ligand: Synthesis, characterization and alcohol oxidation activities

Two new heteronuclear Cd(II)/Pd(II) coordination polymers, [Cd2(µ-im)2(Him)4Pd(µ-CN)4]n (1) and [Cd(Him)2Pd(µ-CN)4]n (2) (Him: imidazole), have been synthesized under different conditions and characterized using elemental analysis, thermal analysis, FT-IR and Raman spectroscopy, single-crystal and powder X-ray diffraction techniques.. In 1, the Cd(II) ions are bridged by imidazolate ligands to generate 1D chain structure. Neighbouring 1D chains were linked by [Pd(CN)4]2- ions to form 3D framework. In 2, the metal ions are bridged by cyanide ligands to generate 2D [Cd2Pd2(µ-CN)4]n network. Furthermore, catalytic peroxidative oxidation activity of catalysts 1 and 2 was examined on the oxidation of benzyl alcohol using tertiary-butyl hydroperoxide (t-BuOOH) as the oxygen source. The compound 1 exhibited over 90 % product conversion at 80 °C in 24-hour reaction time. In addition, the catalyst exhibited high selectivity towards benzaldehyde and no over-oxidation product (benzoic acid) was detected.

Identifying changes in vaginal fluid using SERS: Advancing diagnosis of vulvovaginal candidiasis

Vaginal infections, medically termed vaginitis, encompass a spectrum of symptomatic presentations arising from disturbances within the vaginal microflora. The conventional diagnostic approach relies on microscopic examination of wet preparation of vaginal discharge, considered the ‘gold standard’ in clinical practice. Complementary to this, culture-based methodologies are often employed to reinforce diagnostic accuracy. However, challenges such as subjectivity in result interpretation, resource-intensive requirements regarding skilled personnel, and reagent utilization underscore the need for alternative diagnostic strategies.In this article, we demonstrate surface-enhanced Raman spectroscopy (SERS) and partial least squares regression (PLSR) techniques to elucidate the molecular signatures present in vaginal fluids, accounting for various influencing factors, including disruptions in the natural microflora, vaginal irrigation practices, and contraceptive usage. Furthermore, we investigated the spectral manifestations associated with vulvovaginal candidiasis (VVC) relative to control samples. Each clinical specimen underwent meticulous characterization encompassing microbial composition, pH levels, purity, and other pertinent parameters.Our findings unveil significant associations between extraneous inflammatory factors such as vaginal irrigation and diminished sample purity with alterations in SERS signals. Conversely, the day of the menstrual cycle phase exhibits negligible influence on spectral profiles. Notably, VVC samples demonstrated diverse spectral responses correlating with the abundance of pathogenic bacteria. These explorations hold promise in paving the path towards developing a novel intrinsic framework for the diagnosis of vaginitis.

Determination of the effects of novel paraprobiotic supplement of Lactobacillus plantarum on soy dairy-free beverage by physicochemical, antioxidant, sensory analyses, and Raman spectroscopy technique.

Paraprobiotics are inactivated microbial cells that improve the health status of consumers when taken in adequate doses. They can be used instead of probiotics to eliminate disadvantages such as instability in production and storage difficulties. They can also be an alternative nutritional supplement for individuals sensitive to fermented products. In this study, a paraprobiotic supplement obtained from Lactobacillus plantarum was added to a soy dairy-free beverage at two concentrations of 108 and 109 CFU/mL. Then, total soluble solids, pH, color, titratable acidity, antioxidant activity, and total phenolic content of the beverage were measured, and sensory analysis was also performed. The results indicate that paraprobiotic addition significantly increased (p<0.05) the antioxidant activity (75.44±0.23µmol TE/g sample), total phenolic content (834.32±6.69mg GAE/g), protein (3.28±0.18%), fat (2.35±0.06), and ash content (0.57±0.08). These results were also validated using the Raman spectroscopy technique. The paraprobiotic-supplemented soy dairy-free beverage had the highest taste and overall impression values. Since the parabiotic addition did not affect the physicochemical properties of the beverage, manufacturers can develop commercial products containing paraprobiotics without altering the production process. PRACTICAL APPLICATION: Paraprobiotics provide an alternative for individuals sensitive to fermented products but still desire the health benefits of probiotics. They additionally provide practical and technological advantages, including a longer shelf life without a need for a cold chain to preserve the viability and stability of microorganisms. The results of this study can be a reference for the industry to develop food products containing paraprobiotics with increased antioxidative and nutritional properties.