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Regolith draws intensive research attention because of its importance as the basis for fabricating materials for future human space exploration. Martian regolith is predicted to consist of defect-rich crystal structures due to long-term space weathering. The present report focuses on the structural differences between defect-rich and defect-poor forsterite (Mg2SiO4) – one of the major phases in Martian regolith. In this work, forsterites were synthesized using reverse strike co-precipitation and high-energy ball milling (BM). Subsequent post-processing was also carried out using BM to enhance the defects. The crystal structures of the samples were characterized by X-ray powder diffraction and total scattering using Cu and synchrotron radiation followed by Rietveld refinement and pair distribution function (PDF) analysis, respectively. The structural models were deduced by density functional theory assisted PDF refinements, describing both long-range and short-range order caused by defects. The Raman spectral features of the synthetic forsterites complement the ab initio simulation for an in-depth understanding of the associated structural defects.

Abstract Microplastics (MPs) have been found in a diverse range of organisms across trophic levels. While a majority of the information on organismal exposure to plastics in the environment comes from gastrointestinal (GI) data, the prevalence of MP particles in other tissues is not well understood. Additionally, many studies have not been able to detect the smallest, most prevalent, MPs (1 µm – 5 mm) that are the most likely to distribute to tissues in the body. To address these knowledge gaps, MPs in the GI tract and muscle of Atlantic killifish (Fundulus heteroclitus) collected from two sites (Falmouth and Bourne) on Buzzards Bay, Cape Cod, MA were quantified down to 2 µm in size. Eight fish from Falmouth and 10 fish Bourne site were analyzed. Fourier-transform infrared spectroscopy and Raman spectroscopy were used to identify all particles. The mean concentrations of MPs in the GI tract and muscle from fish collected from Falmouth was 85.5 ± 70.2 and 11 ± 12.5 particles per gram wet weight, respectively. Fish collected from Bourne site had mean particle concentrations of 12.2 ± 18.1 and 1.69 ± 5.36 particles per gram wet weight. Of the 2,008 particles analyzed in various fish tissue samples, only 3.4% (69 particles) were identified as plastic; polymers included nylon, polyethylene, polypropylene, and polyurethane. MPs detected in the GI tract samples also tended to be more diverse in both size and polymer type than those found in the muscle. We found that MPs

Abstract Escalations in wildfire activity are of significant global concern, particularly within vulnerable wetland ecosystems integral to natural carbon sequestration and climate change mitigation. Our understanding and management of future wildfire activity may be better contextualised through the study of historic and ancient fire records, independent of human influence. Methods of study include ‘geothermometry’ - approximating ancient fire intensity from temperature-dependent changes in the chemistry of fossil charcoal. Though well established in their relation to experimental charcoalification, these methods still fail to quantify the true intensity of ancient fires, as a measure of energy release. As a result, their applicability, and contributions to the characterisation of modern fire activity, remain uncertain. Here, we present a novel measure of wildfire energy release, as a proxy for true intensity, through the co-application of cone calorimetry and Raman spectroscopy of charcoal. By applying a range of wildfire heat fluxes to variable peatland fuel mixes, this research demonstrates the complexity in correlating fire behaviour and charcoal microstructure. Further statistical analyses suggest a correlation between spectroscopic results, measures of CO and CO2 release, and fire severity. This offers a principal measure of ancient wildfire intensity, consistent with modern practices in wildfire modelling, monitoring, and management.

Introduction: Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming. Objective: To overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level. Methods: We proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8+ T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically. Results: The entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R2 ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm−1 showed a positive linear correlation with PD-L1 expression level. Conclusions: This study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy.

Abstract Cancer-associated adipocytes (CAAs) have emerged as pivotal players in various cancers, particularly in such as breast cancer, significantly influencing their progression and therapy resistance. Understanding the adipocytes/cancer cells crosstalk is crucial for effective treatment strategies. Raman spectroscopy, a label-free optical technique, offers potential for characterizing biological samples by providing chemical-specific information. In this study, we used Raman spectroscopy and Trajectory Inference methods, specifically the Partition-based graph abstraction algorithm, to investigate the interactions between 3T3-L1 differentiated adipocytes and MDA-MB-231 breast cancer cells in a 2D co-culture model. We demonstrate the existence of subpopulations of adipocytes and the molecular changes associated with CAAs phenotype. This work contributes to understanding the role of CAAs in breast cancer progression and may guide the development of targeted therapies disrupting this interaction.

The Raman effect, or as per its original description, “modified scattering”, is an observation that the number of scattered light waves shifts after photons make nonelastic contact with a molecule. This effect allows Raman spectroscopy to be very useful in various fields. Although it is well known that Raman spectroscopy could be very beneficial in medicine as a diagnostic tool, there are not many applications of Raman spectroscopy in pulmonary medicine. Mostly tumor tissue, sputum and saliva have been used as material for analysis in respiratory medicine. Raman spectroscopy has shown promising results in malignancy recognition and even tumor staging. Saliva is a biological fluid that could be used as a reliable biomarker of the physiological state of the human body, and is easily acquired. Saliva analysis using Raman spectroscopy has the potential to be a relatively inexpensive and quick tool that could be used for diagnostic, screening and phenotyping purposes. Chronic obstructive pulmonary disease (COPD) is a growing cause of disability and death, and its phenotyping using saliva analysis via Raman spectroscopy has a great potential to be a dependable tool to, among other things, help reduce hospitalizations and disease burden. Although existing methods are effective and generally available, Raman spectroscopy has the benefit of being quick and noninvasive, potentially reducing healthcare costs and workload.

Vibrational spectroscopic techniques, such as Fourier transform infrared (FTIR) absorption and Raman spectroscopy (RS), offer unique and detailed biochemical fingerprints by detecting specific molecular vibrations within samples. These techniques provide profound insights into the molecular alterations induced by ionising radiation, which are both complex and multifaceted. This paper reviews the application of rapid and label-free vibrational spectroscopic methods for assessing biological radiation responses. These assessments span from early compartmentalised models such as DNA, lipid membranes, and vesicles to comprehensive evaluations in various living biological models, including tissues, cells, and organisms of diverse origins. The review also discusses future perspectives, highlighting how the field is overcoming methodological limitations. RS and FTIR have demonstrated significant potential in detecting radiation-induced biomolecular alternations, which may facilitate the identification of radiation exposure spectral biomarkers/profiles.

We have investigated the influence of the relative proportions of glass formers in a series of lithium alumino-borosilicate glasses with respect to electrical conductivity (σ) and glass transition temperature (Tg) as functions of glass structure, as determined using Raman spectroscopy. The ternary lithium alumino-borate glass exhibits the highest σ and lowest Tg among all the compositions of the glass series, 30Li2O•3Al2O3• (67−x) B2O3•xSiO2. However, as B2O3 is replaced by SiO2, a shallow minimum in σ, as well as a shallow maximum in Tg, are observed near x = 27, where the Raman spectra indicate that isolated diborate/tetraborate/orthoborate groups are being progressively replaced by danburite/reedmergnerite-like borosilicate network units. Overall, as the glasses become silica-rich, σ is minimized, while Tg is maximized. In general, these findings show correlations among Tg (sensitive to network polymerization), σ (proportional to ionic mobility), and the different borate and silicate glass structural units as determined using Raman spectroscopy.

Abstract Background Breast cancer poses a significant health risk to women worldwide, with approximately 30% being diagnosed annually in the United States. The identification of cancerous mammary tissues from non-cancerous ones during surgery is crucial for the complete removal of tumors. Results Our study innovatively utilized machine learning techniques (Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN)) alongside Raman spectroscopy to streamline and hasten the differentiation of normal and late-stage cancerous mammary tissues in mice. The classification accuracy rates achieved by these models were 94.47% for RF, 96.76% for SVM, and 97.58% for CNN, respectively. To our best knowledge, this study was the first effort in comparing the effectiveness of these three machine-learning techniques in classifying breast cancer tissues based on their Raman spectra. Moreover, we innovatively identified specific spectral peaks that contribute to the molecular characteristics of the murine cancerous and non-cancerous tissues. Conclusions Consequently, our integrated approach of machine learning and Raman spectroscopy presents a non-invasive, swift diagnostic tool for breast cancer, offering promising applications in intraoperative settings.

Abstract Microplastics (MPs) have been identified in diverse settings, including drinking water, freshwater, food, air, and marine environments. This study employed stereomicroscopic and µ-Raman techniques to analyze water samples from ten widely consumed bottled water brands, aiming to detect and characterize MPs. Additionally, the oral consumption of MPs per capita was estimated. The average abundance of MPs ranged from 9 ± 1.00 MPs/L to 3 ± 1.73 MPs/L across all brands. Various MPs shapes were observed, including fibers, fragments, films, and pellets, with fibers being predominant (58.928%). MPs were categorized by color into five groups (red, blue, black, yellow, and transparent), with red comprising approximately 35.714% of the total count. All identified MPs were less than 500 µm in size. µ-Raman analysis validated the presence of eight different polymer types in the samples, namely Polypropylene (PP) (37.5%), Polymethyl methacrylate (PMMA) (3.571%), polystyrene (PS) (33.928%), polycarbonate (PC) (3.571%), polybutylene1 (PB1) (14.2%), Isotactic polypropylene (iPP) (7.142), Nylone 6-α polymorph (αNY6) (5.357%), and polyvinyl alcohol (PVOH) (1.785%). The estimated daily intake of MPs per person was determined to be 0.42 MPs, translating to an annual intake of 153.3 MPs per person. The origin of MPs in bottled water was likely attributed to both raw water sources and packaging materials, underscoring the need for further investigation. Given the potential health implications of human exposure to drinking water MPs, careful consideration should be given to the use of plastic packaging for potable water.

This study explored the synthesis and application of BODIPY-functionalized gold nanoparticles (AuNPs) for the sensitive detection of biothiols via an indicator displacement assay coupled with surface-enhanced Raman scattering (SERS) techniques, alongside their efficacy for in vitro cancer cell imaging. Moreover, the assay allowed for the visible colorimetric detection of biothiols under normal and ultraviolet light conditions. The BODIPY (boron-dipyrromethene) fluorophores were strategically conjugated to the surface of gold nanoparticles, forming a robust nanohybrid that leverages the plasmonic properties of AuNPs for enhanced spectroscopic sensitivity. The detection mechanism exploited the displacement of the BODIPY indicator upon interaction with biothiols, triggering a measurable change in fluorescence and SERS signals. This dual-mode sensing approach provides high selectivity and sensitivity for biothiol detection, with detection limits reaching nanomolar concentrations using fluorescence and femtomolar concentration for cysteine using SERS. Furthermore, the BODIPY-AuNP complexes demonstrated excellent biocompatibility and photostability, facilitating their use in the fluorescence imaging of biothiol presence within cellular environments and highlighting their potential for diagnostic and therapeutic applications in biomedical research.

Purpose: To observe the spectroscopic profile of human lens in different age groups and varying grades of cataract and to use the data to arrive at differentiating molecular biology. Design: An observational cross-sectional study. Methods: The study enrolled 30 patients (30 eyes) with a mean age of 59.6 years diagnosed with immature senile cataracts. The patients underwent small incision cataract surgery, and the harvested lens nuclei were examined under a Raman spectroscope for studying their molecular composition. The relative intensities of the peaks in the Raman spectra were evaluated and compared among different age groups and grades of cataract. A correlation of tyrosine doublet ratio with grade of cataract and age of the subject was calculated. Result: Several Raman spectral peaks were observed in the range of 600 cm-1 to 1800 cm-1 with correspondence to tyrosine, phenylalanine, tryptophan, and amides I and III. A strong negative correlation between the grade of cataract and the ratio of tyrosine doublet was seen (r = -0.805). Also, a negative correlation between age and tyrosine ratio was seen (r = -0.62). The wavenumber/spectral peak of tryptophan was observed only in one sample, and amides I and III were identified, but the intensity of the peak for amide II was very small or absent. Conclusion: It was observed that the buried conformation of tyrosine was predominant in cases with a higher age or grade of cataract. The buried conformation of tryptophan became less in the higher grades of cataract.

Segmented radial seals are modern technologies used in aeronautic engines and space turbopumps. They consist of several circumferential segments assembled as an annular ring freely mounted on the rotor. A circumferential (garter) spring tightens the segments around the shaft. The segments can move radially relative to each other, sliding against a casing and following the dynamic displacements of the rotor. Two similar segmented seals made of different materials were tested. The results showed different leakage flow rates and different correlations between leakage and wear rate. For example, the leakage rate decreases with wear for one seal and increases for the other. For explaining these results, wear was correlated with the microstructure of the materials of the two seals. Profilometric analyses were made for the two seals, highlighting that wear was not localised in the same areas. Raman spectra maps were taken on the pads of the segment in contact with the rotor and microstructural changes caused by friction were enlightened. The evolution of residual stresses was measured for new and worn segments. These findings strengthen the results obtained from profilometric wear analyses. They also allow a more precise understanding of tribological degradation scenarios depending on the operating conditions and the properties of the material.

The study applies both a minimal and an extended approach for a comprehensive picture of chemical components in wall paintings, including evidence of degradation. Pigments and ligands were characterized via a multi-methodological investigation, including optical microscopy, scanning electron microscopy, Raman micro-spectroscopy, GC-MS, and LC-MS/MS. Particularly, the procedure was tested on wall paintings recently excavated from a Roman domus in Santa Maria Capua Vetere. The hypothesis of a very wealthy owner is supported by the evidence of a multi-layer preparation, a rich variety of pigments, and organic ligands (both terpenic resins and animal glue). The absence of calcite in the pictorial layer (via optical and Raman microscopy) and the presence of organic binders (via GC-MS and LC-MS/MS) clearly indicates the a secco technique.

Amber has been used to create decorative items for centuries, but its degradation presents challenges for conservators. This study identifies substances historically used to protect amber objects, especially those from 17th and 18th century Gdansk workshops. Despite their historical value, information on amber conservation is scarce. Traditional substances are noted, but their exact compositions and effects on amber remain unclear. Synthetic resins, introduced in the late 19th century, also degrade, complicating conservation due to their removal difficulty and interference with amber identification. This research aimed to develop methods for detecting and analyzing protective coatings on amber objects using macroscopic and microscopic techniques. Initial methods included analytical photography under visible and UV light and reflectance imaging spectroscopy (RIS) to assess the surface. Raman spectroscopy (RS) and X-ray fluorescence spectroscopy (XRF) were used for detailed analysis. RS provided precise layer-specific information but was sensitive to surface conditions, while XRF quickly identified inorganic compounds but not organic materials. Examining amber objects from Polish collections using this methodology revealed various protective substances, including synthetic resins and nitrocellulose varnishes. This research contributes to amber conservation by proposing a comprehensive material analysis approach, essential for developing effective conservation strategies for these historic objects.

Abstract A novel combined measurements techniques has been designed in this work, enabling the acquisition of laser-induced breakdown spectroscopy (LIBS) and Raman spectral signals at the same point on a sample. The application of this combined technique to the analysis of multi-layered mock-up blocks painted with orpiment and realgar pigments has yielded significant insights. By correlating variations in the emission line intensity of characteristic elements within the LIBS spectra with depth-specific Raman spectra, the number of laser pulses that penetrated the pigment layers has been accurately determined, thereby establishing a method to measure layer thickness. Finally, the technique wasto analysis the actual mural fragment from Mogao Cave 196, determining the types of pigment and the thickness of the pigment layers. Graphical Abstract

Abstract Glucose is the main source of energy for the human brain. This paper presents a non-invasive technique to study metabolic changes caused by glucose in human brain cell lines. In this paper we present the spectroscopic characterization of human normal brain (NHA; astrocytes) and human cancer brain (CRL-1718; astrocytoma and U-87 MG; glioblastoma) control cell lines and cell lines upon supplementation with glucose. Based on Raman techniques we have identified biomarkers that can monitor metabolic changes in lipid droplets, mitochondria and nucleus caused by glucose. We have studied the vibrations at 750 cm−1, 1444 cm−1, 1584 cm−1 and 1656 cm−1 as a function of malignancy grade. We have compared the concentration of cytochrome, lipids and proteins in the grade of cancer aggressiveness in normal and cancer human brain cell lines. Chemometric analysis has shown that control normal, control cancer brain cell lines and normal and cancer cell lines after supplementation with glucose can be distinguished based on their unique vibrational properties. PLSDA (Partial Least Squares Discriminant Analysis) and ANOVA tests have confirmed the main role of cytochromes, proteins and lipids in differentiation of control human brain cells and cells upon supplementation with glucose. We have shown that Raman techniques combined with chemometric analysis provide additional insight to monitor the biology of astrocytes, astrocytoma and glioblastoma after glucose supplementation.

Abstract 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 ( $$m_{e}^{{^{*} }}$$ m e ∗ and $$m_{h}^{{^{*} }}$$ 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 ( $$E^{max}$$ E max and $$E^{\min }$$ E min ) and ( $$\beta^{max}$$ β max and $$\beta^{\min }$$ β 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.

Abstract The present work reports the synthesis of multi-wall carbon nanotubes (MWCNTs) over graphite nanosheets by an easy and simple approach without using any external catalyst. Simply, yellow corn seeds were thermally annealed in a hydrogen atmosphere at 1050 °C for 3 h without any pretreatments. Notably, the growth of MWCNTs was observed to preferentially occur on the outer surface of the corn shell. This uncomplicated approach not only emphasizes the feasibility of synthesizing carbon nanomaterials using agricultural by-products but also underscores the potential applications of these synthesized materials in various fields. Samples were examined through a comprehensive analysis employing various techniques, including scanning electron microscopy (SEM), Raman spectroscopy, FTIR, X-ray diffraction (XRD), and high-resolution transmission electron microscopy (HRTEM). The findings unveiled the formation of rolled graphene accompanied by the presence of vertical multi-wall carbon nanotubes (MWCNTs) positioned over stacked graphene sheets. This detailed characterization provides insights into the structural features and arrangement of the synthesized materials, paving the way for a deeper understanding of their potential applications. The pyrolysis temperature is a crucial factor in the morphological characteristics of the synthesized carbon nanostructures. While graphene cage-like structures were obtained at 800 °C, small carbon nanotubes were grafted to larger ones and formed three-dimensional hierarchical morphologies when the annealing temperature increased to 900 °C. The growth mechanism of the carbon nanotubes was explained based on the jet self-extrusion of the generated gases through the inherent pores of the corn seeds. The current technique employed in manufacturing MWCNTs shows significant promise as a green synthesis method for producing catalyst-free MWCNTs suitable for industrial applications including sensors and energy storage materials.

Abstract The local interaction within poly(vinylidene fluoride)/poly(3,4‐ethyelenedioxythiophene):poly(styrelenesulfonate) (PVDF/PEDOT:PSS) composite films has been explored in this study. Vibrational and impedance spectroscopy were used extensively to investigate the potential interactions within the moieties of PVDF and PEDOT:PSS in the composite. The increased concentration of PEDOT:PSS used as additives enhanced the dielectric constant of the composite films significantly. Both the AC conductivity and the estimated mobility also increased in the composite films with increasing additives. X‐ray absorption spectroscopy gave an insight into the local chain interactions within the polymer composite films. A shift in the C K‐edge toward higher energy confirmed the local interaction of the polymer moieties, suggesting a change in the polymer chain structure due to the possible association of moieties.

Abstract 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.

Abstract Background Early screening and detection of lung cancer is essential for the diagnosis and prognosis of the disease. In this paper, we investigated the feasibility of serum Raman spectroscopy for rapid lung cancer screening. Methods Raman spectra were collected from 45 patients with lung cancer, 45 with benign lung lesions, and 45 healthy volunteers. And then the support vector machine (SVM) algorithm was applied to build a diagnostic model for lung cancer. Furthermore, 15 independent individuals were sampled for external validation, including 5 lung cancer patients, 5 benign lung lesion patients, and 5 healthy controls. Results The diagnostic sensitivity, specificity, and accuracy were 91.67%, 92.22%, 90.56% (lung cancer vs. healthy control), 92.22%,95.56%,93.33% (benign lung lesion vs. healthy) and 80.00%, 83.33%, 80.83% (lung cancer vs. benign lung lesion), repectively. In the independent validation cohort, our model showed that all the samples were classified correctly. Conclusion Therefore, this study demonstrates that the serum Raman spectroscopy analysis technique combined with the SVM algorithm has great potential for the noninvasive detection of lung cancer.

This study proposed a non-destructive method for rapid freshness evaluation of green bean based on Raman spectroscopy. The Raman spectra of green bean with different storage times were collected, its physicochemical indicators reflecting changes in freshness including mass loss rate, total color difference (∆E), hardness, ascorbic acid content and chlorophyll content were measured, and chemometrics methods were used to associate the spectral data with the physicochemical data. The effectiveness of different spectral pretreatments such as baseline correction (BL), Gaussian filter (GF), normalization (NL) and standard normal variable (SNV) was compared, and partial least squares regression (PLSR) and principal component regression (PCR) were used individually to establish freshness prediction models will all or selected wavenumbers. Moreover, the regression coefficient (RC) method was used to select the characteristic Raman wavenumbers. The simplified PLSR model for each freshness indicator showed a correlation coefficient of calibration set (rc) of greater than 0.92, a correlation coefficient of prediction set (rp) of greater than 0.89, and a residual predictive deviation (RPD) of greater than 2.0. The rc and rp of the PCR model were greater than 0.79 and 0.73, respectively. Therefore, the results of this study indicate that Raman spectroscopy allows non-destructive and rapid detection of the freshness of green bean.

Abstract Carbonaceous material (CM) undergoes progressive changes that reflect its thermal history. These changes are in general irreversible and provide valuable information for understanding diagenetic and metamorphic processes of crustal rocks. Among various approaches to quantify these changes, the R2 ratio, area ratio of specific peaks in CM Raman spectra, is widely used to estimate the maximum temperature of intermediate- to moderately high-grade metamorphism. The calculation of the R2 ratio requires peak deconvolution of the original spectrum, and the results depend on the details of how this is carried out. However, a clear protocol for selecting appropriate initial conditions has not been established and obtaining a reliable temperature estimate depends at least in part on the experience and skill of the operator. In this study, we developed a Python code that automatically calculates the R2 ratio from CM Raman spectra. Our code produces R2 ratios that are generally in good agreement with those of Aoya et al. (J Metamorph Geol 28:895–914, 2010, https://doi.org/10.1111/j.1525-1314.2010.00896.x ) for the same Raman data, with much less time and effort than was the case in the previous studies. We have confirmed that the code is also applicable to other previous datasets from both contact and regional metamorphic regions. The overall trend of the recalculated data indicates that samples with R2 greater than ~ 0.7 are not sensitive to the changes in CM maturity and thus should not be used for the calibration of an R2-based geothermometer. We propose a modified geothermometer for contact metamorphism that is strictly applicable to samples with R2 from 0.023 to 0.516, with the proviso that a laser with a wavelength of 532 nm should be used. A slight extrapolation of the newly proposed geothermometer up to R2 of 0.57 provides a temperature estimate that is consistent with the geothermometer of Kaneki and Kouketsu (Island Arc 31:e12467, 2022; https://doi.org/10.1111/iar.12467 ); the boundary between the two geothermometers corresponds to a temperature of 391 °C.

The deprotonation of acetohydroxamic acid(AHA) and its coordination chemistry with uranyl ion(\begin{document}${\mathrm{UO}}_2^{2+ }$\end{document}) in 1.0 mol/L NaClO4 has been investigated with potentiometric titration and Raman spectroscopy at 25 ℃. For the first time, the deprotonations of AHA in aqueous solutions are quantitatively investigated with potentiometric titration method. It is found that in aqueous solution AHA acts as a monobasic acid and the protonation constants calculated to be pKa1=9.24±0.11(errors are given by the HyperQuad software fitting calculations). The determined pKa1 is in good agreement with the previously reported one-step protonation. In a wide pH range from acidic to basic aqueous solutions, the two step-wise protonation of AHA has been found, at the same time, the complexation of U(Ⅵ) with AHA has been re-visited. For AHA at different degrees of deprotonation, various complexes of U(Ⅵ) with AHA at ratios of U(Ⅵ) and AHA from 1∶1 to 1∶3 are recognized by potentiometric titration method. Amongst, the 1∶1 set of complexes consists of UO2A+ and UO2(OH)A, the 1∶2 includes UO2A2 and UO2(OH)\begin{document}${\mathrm{A}}_2^{-} $\end{document}, and the 1∶3 is composed of three complexes UO2\begin{document}${\mathrm{A}}_3^{-} $\end{document}, UO2(OH)\begin{document}${\mathrm{A}}_3^{2-} $\end{document} and UO2(OH)2\begin{document}${\mathrm{A}}_3^{3-} $\end{document}. There are maybe more complex species formed during the titrations, especially in very basic solutions, but those cannot be well quantitatively characterized due to their very low solubilities. The stability constants of the mentioned seven species have been determined by HyperQuad software, with the values of UO2A+ and UO2A2 in good consistence with those reported previously. All other five new-detected complexes are detected in solutions of relatively higher pH values. In the potentiometric titrations at relatively low AHA concentration, both protons of AHA can be deprotonated to form higher proportioned UO2(OH)A in comparison with UO2A2, which is an equal species to UO2A+ in term of releasing/consuming H+ during the titration process. At greatly excessive concentrations of AHA, three complexes, UO2A+, UO2A2, and UO2\begin{document}${\mathrm{A}}_3^{-} $\end{document} are successively formed with only one proton deprotonated A− as the pH being increased; further, two species, UO2(OH)\begin{document}${\mathrm{A}}_3^{2-} $\end{document} and UO2(OH)2\begin{document}${\mathrm{A}}_3^{3-} $\end{document}, are formed with partial of the ligands in the form of completely deprotonated (OH)A2−. The Raman spectroscopic titrations show that the Raman shift of O=U=O moves to lower wavenumbers with the increase in the number of ligands, with 849 cm−1, 828 cm−1 and 807 cm−1 corresponding to the three sets of U(Ⅵ) to AHA ratios of 1∶1, 1∶2, and 1∶3, respectively. Moreover, the results demonstrate that the effect of deprotonation on the Raman shifts of uranyl ion is negligible, but the effect on the Raman intensity is significant. The almost same step-wise Raman shifts at about 21 cm−1 for the three sets of complexes, 1∶1, 1∶2 and 1∶3, indicates a similar coordination mode for all the AHA ligands with different degrees of deprotonation, which provides informative hints for the structures of the complexes.

Abstract Raman spectral references for various formulations of iron gall inks, logwood inks and mixtures of both types were acquired during this study. The samples, either liquid or dry inks and applied on paper, were analysed using a portable Raman spectrometer, both with 852 and 785 nm excitation lines, and a confocal dispersive Raman microscope with two different excitations, namely 785 and 532 nm. It was found that longer wavelengths are more suitable for the analysis of iron gall inks and that the spectral response of logwood inks is relatively more dependent on the excitation line. For the mixtures, it is suggested analyses be performed with both longer and shorter wavelengths, since with a 785 nm line mainly the characteristic features of the metal-polyphenol complex in iron gall inks are detected, while the spectra collected with a 532 nm excitation contain information on the presence of logwood inks. The study was complemented by non-invasive reflectance infrared spectroscopy, which enabled the detection of tannic acid in iron gall inks and in the mixtures, and by micro-Fourier transform infrared (FTIR) spectroscopy to complement the reference set. The study aims to contribute to the development of non-invasive protocols for identification of inks in historic and artistic works on paper, such as manuscripts and drawings. Graphical Abstract

We present DiadFit—an open-source Python3 tool for efficient processing of Raman spectroscopy data collected from fluid inclusions, melt inclusions and silicate melts. DiadFit is optimized to fit the characteristic peaks from CO2 fluids (Fermi diads, hot bands, 13C), gas species such as SO2, N2, solid precipitates (e.g. carbonates), and Ne emission lines with easily tweakable background positions and peak shapes. DiadFit's peak fitting functions are used as part of a number of workflows optimized for quantification of CO2 in melt inclusion vapour bubbles and fluid inclusions. DiadFit can also convert between temperature, pressure and density using various CO2 and CO2-H2O equations of state (EOS), allowing calculation of fluid inclusion pressures (and depths in the crust), conversion of homogenization temperatures from microthermometry to CO2 density, and propagation of uncertainties associated with EOS calculations using Monte Carlo methods. There are also functions to quantify the area ratio of the silicate vs. H2O region of spectra collected on silicate glasses to determine H2O contents in glasses and melt inclusions. Documentation and worked examples are available (https://bit.ly/DiadFitRTD, https://bit.ly/DiadFitYouTube).

Abstract Raman spectroscopy is used to investigate the absorption and dispersion of zearalenone (ZEN) and its derivatives. The C=C stretching vibration modes of ZEN and zearalenol (ZENOL) were appeared at 975–990 cm−1. The C=O vibration mode was present at 1680–1690 cm−1 for ZEN and zearalanone (ZAN), but it was absent for ZENOL and zearalanol (ZANOL) which have –OH group instead of –C=O group in ZEN and ZAN molecular structures. On the basis of this characterization, Raman spectra of specific chemical groups and linkages corresponding to the structural difference of ZEN and its derivatives were identified. These results indicated that Raman spectroscopy can apply for the identification of ZEN and its derivatives and has a potential for the non-destructive rapid detection of these compounds in food.

Abstract This study aimed on the one hand to clarify the quality, authenticity, safety, and other issues related to products of the anabolic-androgenic steroid methandienone advertised on the Internet and personally imported to Japan and on the other hand to evaluate the use of two portable Raman spectrometers in identifying the active pharmaceutical ingredient (API). The study found that all n = 15 samples purchased from 14 websites were problematic regarding their package, labeling, and/or content. Specifically, one sample (6.7%) was confirmed falsified, twelve samples (80%) were found either to be falsified or unlicensed as pharmaceutical product, and two samples (13.3%) were received without information on the manufacturers’ physical address or country of origin, with one sample (6.7%) having no labeling or other accompanying information at all. Both Raman spectrometers were able to identify the API in all samples as confirmed and quantified by ultra-high-performance liquid chromatography–Fourier transform mass spectrometry. Twelve samples contained on average less than 90% of the declared API content. By contacting national regulatory authorities in 44 countries, methandienone products were found to be approved in 1 country and not approved in 21 countries. To prevent health hazards and abuse, measures against the acquisition of anabolic-androgenic steroids from unknown sources are required. Portable Raman spectrometers may be suitable for the non-destructive and quick identification of methandienone in tablets. Graphical Abstract

Abstract Background Autofluorescence (AF)‐Raman spectroscopy is a technology that can detect tumour tissue in surgically excised skin specimens. The technique does not require tissue fixation, staining, labelling or sectioning, and provides quantitative diagnosis maps within 30 min. Objectives To explore the clinical application of AF‐Raman microscopy to detect residual basal cell carcinoma (BCC) positive margins in ex vivo skin specimens excised during real‐time Mohs surgery. To investigate the ability to analyse skin specimens from different parts of the head‐and‐neck areas and detect nodular, infiltrative and superficial BCC. Methods Fifty Mohs tissue layers (50 patients) were investigated: 27 split samples (two halves) and 23 full‐face samples. The AF‐Raman results were compared to frozen section histology, carried out intraoperatively by the Mohs surgeon and postoperatively by dermatopathologists. The latter was used as the standard of reference. Results The AF‐Raman analysis was completed within the target time of 30 min and was able to detect all subtypes of BCC. For the split specimens, the AF‐Raman analysis covered 97% of the specimen surface area and detected eight out of nine BCC positive layers (similar to Mohs surgeons). For the full‐face specimens, poorer contact between tissue and cassette coverslip led to lower coverage of the specimen surface area (92%), decreasing the detection rate (four out of six positives for BCC). Conclusions These preliminary results, in particular for the split specimens, demonstrate the feasibility of AF‐Raman microscopy for rapid assessment of Mohs layers for BCC presence. However, for full‐face specimens, further work is required to improve the contact between the tissue and the coverslip to increase sensitivity.

In this research, a comprehensive study of the effect of doping silicon with gold on the optical properties and morphology of silicon layers was carried out. For this purpose, the methods of Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM) were used. The results of the study showed that the transition from original silicon to gold-doped silicon leads to significant changes in the optical properties and morphology of the layers. Raman spectra showed characteristic peaks in the regions of 144, 304, 402, 464, 522, 948 and 973 cm–1, associated with the violation of long-range order of the crystal lattice and the interaction of gold with silicon. The intensity and position of the peaks in the spectra allowed us to draw conclusions about structural changes, including a decrease in crystallinity and the formation of amorphous and nanocrystalline structures in the samples after treatment at 1373 K. New peaks in the Raman spectra associated with Au-Au stretching and the formation of new bonds Si-Au, confirm the processes in silicon layers when alloyed with gold. SEM studies provided information on the structure, chemical composition and arrangement of n-Si-Au and p-Si-Au samples. The spherical arrangement of gold atoms on the surface of single-crystalline silicon was experimentally established, which indicates the diffusion of gold and the formation of gold silicate, which introduces a positive charge to the interface. Morphological changes included an increase in the number of agglomerates with nanocrystals smaller than 7–9 nm and an increase in the transparency of the layer. These results indicate the possibility of improving the photosensitivity of heterostructures with a Si–Au composite layer due to the quantum-size and plasmonic effects of inclusions containing silicon and gold nanoparticles.

The study of thin-film nanocomposites, including crystalline and amorphous silicon nanoparticles embedded in silicon oxide layers, is a key direction in the field of materials for optoelectronics. This study explored the interest in such composites, including erbium silicide (ErSi2-x), in the context of their applications in non-volatile memory and photovoltaic devices. Particular attention was paid to the structure and properties of such materials, including the analysis of defects in erbium-doped silicon. The results of the study, based on Raman spectroscopy and X-ray phase analysis, made it possible to identify the characteristics of the composition and structure of the studied samples. The identified data confirmed the presence of crystalline phases of Si and Er in the p-Si-Er composite, and also showed the substitution of Er in the p-Si/SiO2 structure. Additionally, X-ray microanalysis data confirmed the presence of Si, O and Er in the expected concentrations in the composite film. Further research showed that the introduction of erbium atoms onto the silicon surface leads to minor changes in some signals and the appearance of new vibrations in the Raman spectra of the samples. The decrease in the intensity of the peaks belonging to silicon is associated with the weakening and breaking of some bonds in the structure of the silicon crystal lattice and due to the formation of new bonds in which erbium atoms participate. Thus, the results of this study represent a significant contribution to the understanding of the properties and potential of thin film nanocomposites for applications in optoelectronics, and also enrich our knowledge of the effect of doping on the structure and properties of silicon materials.

Beef is rich in nutrients and is one of the favored meats among consumers. Market price, consumer willingness to buy and satisfaction are affected by the quality of beef, so it is important to test the quality of beef. At present, traditional beef quality testing methods have the problems of time-consuming, sample damage and complex operation. Recently, non-destructive testing technology has been widely used in beef quality testing because of its advantages of rapidity, high efficiency, non-destructive and environment-friendly. This paper summarises the progress of non-destructive testing technology in beef quality analysis (sensory quality, nutritional quality and other quality), and systematically describes the principles of non-destructive testing techniques such as near-infrared spectroscopy, Raman spectroscopy, hyperspectral imaging, E-tongue and E-nose. The progress of non-destructive testing techniques in beef quality analysis within the last five years is discussed in detail. The existing problems of non-destructive testing technology in beef quality analysis are put forward, and the future application prospect is prospected. It hopes to provide a reference for the research and application of non-destructive testing technology for beef quality.

To evaluate the degree of unsaturation of different varieties of Camellia oil, it was necessary to establish a rapid evaluation method with a narrow iodine value range (iodine value difference less than 10). In this study, a rapid quantitative prediction model for iodine value of oil in high-resolution Raman spectroscopy based on linear regression and gradient descent method was established. The Raman signals (785 nm) about 39 group of Camellia oil samples and 10 group of commercially oils were firstly collected. Then, the intensity ratio of peaks of 1656 cm−1 and 1440 cm−1 (I1656/1440) were selected through smoothing algorithm least squares smoothing filter (Savitzky-Golay), polynomial fitting and deconvolution algorithm Lorentzian. A credible model was obtained through correlation analysis with the iodine value of corresponding oil samples. The coefficient of determination (R2) of the test set of the constructed quantitative model was >0.82, the mean square error (MSE) was

Lignocellulose materials, such as bamboo, rattan, and wood, have been largely used for furniture and crafts. On the other hand, the utilization of lignocellulose-like materials, which have a similar texture and appearance to those from nature, has been increasing recently due to their superior durability. This research aimed to identify the lignocellulose-like material using spectroscopy analysis, such as Raman and Near Infrared (NIR) which is well-known as a non-destructive, quick, and accurate approach for material identification. We investigated 4 types of lignocellulose-like materials that were provided by Dewan Serat Indonesia (The Indonesian Fiber Council) from an industry that produces them. The NIR analysis was performed at wavenumbers 10,000-4,000 cm-1. The natural lignocellulose (bamboo and wood) and the polymers (polyethylene and polyproline) were used as standards. Raman analysis was further employed to identify the composition of selected lignocellulose-like materials by comparing their spectra with the library software. The results showed that the original NIR spectra of lignocellulose-like and those natural materials were different, indicating that the NIR analysis can differentiate those materials. The NIR spectra of lignocellulose-like materials were similar to those of polyethylene spectra. Those lignocellulose-like were also identified as polyethylene due to the similarity of the Raman spectra and their library spectra.

Rabdosia rubescens, a Chinese herbal medicine with anticancer properties, contains two active ingredients: oridonin and ponicidin. Both compounds exhibit antitumor effects by inducing tumor cell apoptosis and autophagy and inhibiting tumor cell proliferation. To further explore the differences in molecular structure and pharmacological properties between the two substances, this study employs Terahertz Time-Domain Spectroscopy (THz-TDS) to investigate the spectral characteristics of oridonin and ponicidin in the frequency range of 0.1 to 2.3 THz. The crystal structures of the two substances are simulated using Materials Studio software and Density Functional Theory (DFT), yielding their spectra and molecular vibration modes, which elucidate the mechanism underlying the peak generation. The consistency between experimental and simulation results confirms the reliability of the experimental findings. Thus, THz spectroscopy can effectively distinguish between these two substances. Finally, a THz detection is performed on Rabdosia rubescens capsules purchased from the market, revealing the presence of absorption peaks for both substances in their absorption spectra. This provides a new approach for detecting active ingredients in Chinese herbal medicines.

We present new insights into the study of the UO2+x/U4O9 equilibrium in UO2 as a function of the hyper-stoichiometry (x) by coupling HERFD-XANES at the uranium M4-edge with micro-Raman spectroscopy mapping. XANES allowed the measurement of uranium speciation in the samples, while Raman spectroscopy was used to individually characterize the composition and localization of the different oxide phases. UO2 pellets were oxidized under dry conditions at temperatures above the UO2+x/U4O9 phase transition to reach hyper-stoichiometries in the range of 0.01 ≤ x ≤ 0.1. Combining both techniques, we could determine the proportions of U4O9 and UO2+x. We show that at a low O/U ratio, U4O9 is present as small clusters inside UO2 grains. As the O/U increases, we found evidence of the formation of a network of U4O9 crystallized inside the UO2+x grains. The variation of the UO2+x phase hyper-stoichiometry (x) was evaluated as a function of the sample oxidation.

Abstract Global energy consumption is increasing yearly, yet the world is trying to move toward carbon neutrality to mitigate global warming. More research is being done on energy storage devices to advance these efforts. One well‐known and widely studied technology is Zn‐ion batteries (ZIBs). Therefore, this paper demonstrates how laser irradiation at wavelengths of 266 and 1064 nm, in the presence of air or water, can enhance the electrochemical performance of metallic zinc anode in alkaline electrolyte. The obtained samples are characterized using X‐ray diffraction analysis, scanning electron microscopy, and Raman spectroscopy. Then, the electrochemical properties are studied by cyclic voltammetry and impedance measurements. Results indicate that the laser processing of the Zn sample increases surface‐specific capacity by up to 30% compared to the non‐irradiated Zn sample. Furthermore, electrochemical measurements reveal enhanced participation of metallic Zn grains in the oxidation and reduction processes in irradiated samples. In future research, integrating laser treatment into electrode preparation processes can become essential for optimizing anode battery materials.

PurposeAn accurate assessment of the surgical margins of tongue squamous cell carcinoma (TSCC), especially the deep muscle tissue, can help completely remove the cancer cells and thus minimize the risk of recurrence. This study aimed to develop a classification model that classifies TSCC and normal tissues in order to aid in the rapid and accurate intraoperative assessment of TSCC surgical deep muscle tissue margins.Materials and methodsThe study obtained 240 Raman spectra from 60 sections (30 TSCC and 30 normal) from 15 patients diagnosed with TSCC. The classification model based on the analysis of Raman spectral data was developed, utilizing principal component analysis (PCA) and linear discriminant analysis (LDA) for the diagnosis and classification of TSCC. The leave-one-out cross-validation was employed to estimate and evaluate the prediction performance model.ResultsThis approach effectively classified TSCC tissue and normal muscle tissue, achieving an accuracy of exceeding 90%. The Raman analysis showed that TSCC tissues contained significantly higher levels of proteins, lipids, and nucleic acids compared to the adjacent normal tissues. In addition, we have also explored the potential of Raman spectroscopy in classifying different histological grades of TSCC.ConclusionThe PCA–LDA tissue classification model based on Raman spectroscopy exhibited good accuracy, which could aid in identifying tumor-free margins during surgical interventions and present a promising avenue for the development of rapid and accurate intraoperative techniques.

A hybrid material, 4-aminopyridinium perchlorate salt [C5H6N2][C5H7N2] ClO4, was synthesized at room temperature by slow evaporation and characterized by single-crystal X-ray, spectroscopic techniques (FT-IR, Raman, and UV–Visible), thermal studies (TGA and DSC). The crystallographic data obtained from single crystal X-ray analysis showed that the compound adopts the monoclinic system, space group P21/n, with the following parameters a = 10.8317(8) Å, b = 9.0529(5) Å, c = 13.7032(9) Å, β = 99.243(3) °, Z = 4 and V = 1326.27(15) Å3. The stability of the supramolecular structure was ensured by hydrogen bonding contacts with N-H…O lengths ranging between 2.749 and 2.940 Å. According to the results of Hirshfeld analysis, O…H interactions constitute the main intermolecular interaction contacts (46 %). The thermal decomposition of the precursors, studied by TGA and DSC analysis, indicates that the compound exhibits thermal stability up to 130 °C, beyond which it degrades. Infrared and Raman spectra were recorded at room temperature, confirming the existence of vibrational modes corresponding to organic and inorganic groups. Additionally, the optical properties of the synthesized compound exhibit UV–Visible absorption and interesting photoluminescence properties. The related HOMO-LUMO orbital energies were also highlighted using TDDFT calculations the B3LYP/6-31G (d,p) level of theory.

Abstract Precise identification of glioblastoma (GBM) microinfiltration, which is essential for achieving complete resection, remains an enormous challenge in clinical practice. Here, the study demonstrates that Raman spectroscopy effectively identifies GBM microinfiltration with cellular resolution in clinical specimens. The spectral differences between infiltrative lesions and normal brain tissues are attributed to phospholipids, nucleic acids, amino acids, and unsaturated fatty acids. These biochemical metabolites identified by Raman spectroscopy are further confirmed by spatial metabolomics. Based on differential spectra, Raman imaging resolves important morphological information relevant to GBM lesions in a label‐free manner. The area under the receiver operating characteristic curve (AUC) for Raman spectroscopy combined with machine learning in detecting infiltrative lesions exceeds 95%. Most importantly, the cancer cell threshold identified by Raman spectroscopy is as low as 3 human GBM cells per 0.01 mm2. Raman spectroscopy enables the detection of previously undetectable diffusely infiltrative cancer cells, which holds potential value in guiding complete tumor resection in GBM patients.

Abstract Background The ligamentum flavum (LF) degeneration is a critical factor in spinal stenosis, leading to nerve compression and pain. Even with new treatment options becoming available, it is vital to have a better understanding of LF degeneration to ensure the effectiveness of these treatments. Objective This study aimed to provide insight into LF degeneration by examining the connections between various aspects of LF degeneration, including histology, microstructure, chemical composition, and biomechanics. Method We analyzed 30 LF samples from 27 patients with lumbar vertebrae, employing magnetic resonance imaging (MRI) to link lumbar disc degeneration grades with fibrosis levels in the tissue. X‐ray diffraction (XRD) analysis assessed microstructural alterations in the LF matrix component due to degeneration progression. Instrumented nanoindentation combined with Raman spectroscopy explored the spatial microbiomechanical and biochemical characteristics of the LF's ventral and dorsal regions. Results Our outcomes revealed a clear association between the severity of LF fibrosis grades and increasing LF thickness. XRD analysis showed a rise in crystalline components and hydroxyapatite molecules with progressing degeneration. Raman spectroscopy detected changes in the ratio of phosphate, proteoglycan, and proline/hydroxyproline over the amide I band, indicating alterations in the extracellular matrix composition. Biomechanical testing demonstrated that LF tissue becomes stiffer and less extensible with increasing fibrosis. Discussion Notably, the micro‐spatial assessment revealed the dorsal side of the LF experiencing more significant mechanical stress, alongside more pronounced biochemical and biomechanical changes compared to the ventral side. Degeneration of the LF involves complex processes that affect tissue histology, chemical composition, and biomechanics. It is crucial to fully understand these changes to develop new and effective treatments for spinal stenosis. These findings can improve diagnostic accuracy, identify potential biomarkers and treatment targets, guide personalized treatment strategies, advance tissue engineering approaches, help make informed clinical decisions, and educate patients about LF degeneration.

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.

Graphene research has developed quite rapidly partially because even a monatomic layer can be visualized with a conventional optical microscope. Although optical properties of multilayer graphene such as optical contrast, reflectance (R), and Raman scattering have been well studied, they are studied independently and the thickness dependence is limited to a rather thin region. In this paper, the evolution of optical properties by thickness from monolayer to multilayer graphene up to 107 nm thick is studied comprehensively. The empirically known change of color of multilayer graphene is confirmed from the R, G and B intensities extracted from the optical images. It is also found that, as far as R for visible light is concerned, multilayer graphene is not necessarily considered as a layered material, and the refractive index for monolayer graphene is applicable even for the thickest multilayer graphene flake in this study. On the other hand, the layered structure and Raman scattering at each layer are essential to reproduce the G-band intensity of Raman scattering (I(G)). Not only the multiple reflection but also the interference of scattered Raman light should be considered for I(G) of multilayer graphene thicker than ∼30 nm.

There are some researches in the literature on the mechanical characteristics of dual-phase (DP) steels used in the automotive industry, but there is no comprehensive research on the corrosion behavior of these steels. In this work, the corrosion behavior of DP steels (DP440, DP590, DP980) exposed to two cycles of accelerated corrosion testing in accordance with Ford CETP 00.00-L-467 was observed. Raman and X-ray diffraction (XRD) techniques were used to classify the corrosion products, and the morphology of the samples was studied using a scanning electron microscope (SEM). Goethite and haematite were the primary chemical compounds determined. In high-mechanical strength DP steels, akaganeite was also identified in corroded specimens. The compounds formed due to corrosion were revealed by SEM images. In this work, according to the results of Raman spectroscopy, which was employed for the first time to reveal corrosion products in high-strength dual-phase steels, it was discovered that corrosion products increased with increasing mechanical strength due to an increasing martensite phase volume percentage. Polarization tests were carried out to support the electrochemical data reported by the Raman analysis. Similarly, an increase in the amount of martensite phase in the microstructure led to a decrease in the material’s corrosion resistance. Polarization experiments were carried out to support the electrochemical data interpreted by Raman analysis. In addition, an increase in the amount of martensite phase in the microstructure led to a decrease in the corrosion resistance of the material. In addition, information regarding the material’s electrochemical performance was obtained through Raman analysis. As shown by Raman, XRD, and polarization tests, the increase in corrosion products formed due to the increase in the amount of martensite led to a decrease in corrosion resistance.

Polydioxanone (PPDX) has gained significant attention as a biocompatible and absorbable polymer used in various medical applications, such as sutures and tissue scaffolds. This research presents a thorough investigation into the degradation mechanisms of PPDX under low pH conditions, simulating physiological environments, e.g., esophagus and stomach. It mainly focuses on the dependence of the PPDX degradation rate on various ambient pH values (7.4 and below), which is a substantial knowledge for successful gastrointestinal treatment. The PPDX suture samples were degraded for up to 6 weeks and analyzed using size exclusion chromatography, differential scanning calorimetry, Raman spectroscopy, scanning electron microscopy, X-ray microtomography, and mechanical property measurements. The results show that the PPDX degradation is significantly accelerated at pH below 1.67. Correlations of the molecular weight, crystallinity, glass transition temperature, Young's modulus, shear modulus, tensile strength, and the 1733 cm−1 Raman peak shoulder area (RPSA1733) indicate that the degradation mechanism does not change with increasing acidity. Measurements of tensile strength, shear modulus, and RPSA1733 were found to be the most suitable parameters for characterizing the PPDX filament's macroscopic integrity. Raman spectroscopy is of particular interest in this regard due to its rapidity and practically no requirements on the sample preparation.

BACKGROUND: In the last decade, there has been a significant increase in interest in non-invasive monitoring of blood glucose levels [1]. This is driven by the desire to reduce patient discomfort, as well as the risk of infections associated with traditional invasive methods [2]. Raman spectroscopy, considered as a promising approach for non-invasive measurements [3], combined with machine learning, has the potential to lead to more accurate and faster diagnostic methods for conditions related to glucose imbalances [4]. AIMS: Development and validation of a new portable glucometer based on Raman spectroscopy using machine learning methods for non-invasive determination of glycated hemoglobin (HbA1c) levels. MATERIALS AND METHODS: The study was conducted on a sample of 100 volunteers of different age groups and genders, with varying health statuses, including individuals with type 1 and type 2 diabetes and those without diabetes. To collect data, we used a portable device developed by us, based on the registration of Raman spectra with laser excitation at 638 nm. The data were analyzed using Support Vector Machine neural networks. RESULTS: After processing the spectroscopic measurements using Support Vector Machine, the system showed sensitivity (95,7%) and specificity (84,2%) in determining HbA1c levels comparable to traditional methods such as high-performance liquid chromatography. It was found that the algorithm is sufficiently adaptive and can be used across a wide range of skin types, regardless of the age and gender of the participants. The results suggest the possibility of using the developed device in clinical practice. CONCLUSION: The developed portable glucometer based on Raman spectroscopy combined with machine learning algorithms could be a promising step towards non-invasive and continuous monitoring of glycemic levels in patients with diabetes.

Abstract In recent years, detecting and quantifying multiple gases have garnered widespread attention across various fields, particularly in volatile organic compound (VOC) detection, which holds significant importance for ecosystems and the medical field. The Raman spectroscopy has been widely used in multi-gas detection due to its advantages in fast response speed and non-destructive detection. This paper reviews the latest research progress of the multi-gas sensing technology in the Raman spectroscopy, focusing on using the hollow-core fiber to enhance the gas signal intensity. The basic principles of the fiber-enhanced Raman spectroscopy are introduced. The detailed discussion includes the system architecture, parameter configuration, and experimental results. Then, the latest advances in the coherent anti-Stokes Raman scattering multi-gas detection technology are reviewed. Finally, the challenges faced by the hollow-core fiber in practical applications are discussed.