Extracellular vesicles may provide an alternative detoxification pathway during skeletal muscle myoblast ageing.

Skeletal muscle (SM) acts as a secretory organ, capable of releasing myokines and extracellular vesicles (SM-EVs) that impact myogenesis and homeostasis. While age-related changes have been previously reported in murine SM-EVs, no study has comprehensively profiled SM-EV in human models. To this end, we provide the first comprehensive comparison of SM-EVs from young and old human primary skeletal muscle cells (HPMCs) to map changes associated with SM ageing. HPMCs, isolated from young (24 ± 1.7 years old) and older (69 ± 2.6 years old) participants, were immunomagnetically sorted based on the presence of the myogenic marker CD56 (N-CAM) and cultured as pure (100% CD56+) or mixed populations (MP: 90% CD56+). SM-EVs were isolated using an optimised protocol combining ultrafiltration and size exclusion chromatography (UF + SEC) and their biological content was extensively characterised using Raman spectroscopy (RS) and liquid chromatography mass spectrometry (LC-MS). Minimal variations in basic EV parameters (particle number, size, protein markers) were observed between young and old populations. However, biochemical fingerprinting by RS highlighted increased protein (amide I), lipid (phospholipids and phosphatidylcholine) and hypoxanthine signatures for older SM-EVs. Through LC-MS, we identified 84 shared proteins with functions principally related to cell homeostasis, muscle maintenance and transcriptional regulation. Significantly, SM-EVs from older participants were comparatively enriched in proteins involved in oxidative stress and DNA/RNA mutagenesis, such as E3 ubiquitin-protein ligase TTC3 (TTC3), little elongation complex subunit 1 (ICE1) and Acetyl-CoA carboxylase 1 (ACACA). These data suggest SM-EVs could provide an alternative pathway for homeostasis and detoxification during SM ageing.

The Deposition by Raffaello Sanzio: New analytical insights on old cross sections for the characterisation of pictorial palette.

In 2020, 500th anniversary of Raffaello Sanzio death, his Deposition (1507), -the altarpiece known also as the Pala Baglioni, today located at the Borghese Gallery in Rome-has been subjected to conservative revision and preventive conservation project. This included in-depth diagnostic campaigns through most modern non-invasive techniques, together with the analysis of old cross sections from the same Pala. These latters, prepared between 1966 and 1972, preserved in ICR laboratory of chemistry and testing materials archive, have been used to deepen the knowledge of Raffaello painting techniques. The use of such cross sections was fundamental to verify the original pictorial film and restoration re-paintings before the conservation intervention in the same years. In this paper, the results of analytical insights on Raffaello pictorial palette are presented. The information is obtained by the analysis of the old ICR stratigraphic sections, through the use of Scanning Electron Microscope with Energy Dispersive X-Ray analysis (SEM-EDX) and micro-Raman (632.8 nm), while Surface Enhanced Raman Scattering (SERS) analysis through colloidal paste has been tested for the identification of organic lake-pigments present in low concentration and for the successful recognition of copper resinate, whose SERS spectrum is here reported for the first time, according to our knowledge. This combined diagnostic approach has made it possible to recognize the pigments employed in the different pictorial layers, such species in traces and those from organic materials, responding to open questions arising previous non-invasive analyses and highlighting further aspects of the illustrious master refined painting technique.

Unsupervised and interpretable discrimination of lithium-bearing minerals with Raman spectroscopy imaging.

As lithium-bearing minerals become critical raw materials for the field of energy storage and advanced technologies, the development of tools to accurately identify and differentiate these minerals is becoming essential for efficient resource exploration, mining, and processing. Conventional methods for identifying ore minerals often depend on the subjective observation skills of experts, which can lead to errors, or on expensive and time-consuming techniques such as Inductively Coupled Plasma Mass Spectrometry (ICP-MS) or Optical Emission Spectroscopy (ICP-OES). More recently, Raman Spectroscopy (RS) has emerged as a powerful tool for characterizing and identifying minerals due to its ability to provide detailed molecular information. This technique excels in scenarios where minerals have similar elemental content, such as petalite and spodumene, by offering distinct vibrational information that allows for clear differentiation between such minerals. Considering this case study and its particular relevance to the lithium-mining industry, this manuscript reports the development of an unsupervised methodology for lithium-mineral identification based on Raman Imaging. The deployed machine-learning solution provides accurate and interpretable results using the specific bands expected for each mineral. Furthermore, its robustness is tested with additional blind samples, providing insights into the unique spectral signatures and analytical features that enable reliable mineral identification.

Investigation of heat-induced pork batter quality detection and change mechanisms using Raman spectroscopy coupled with deep learning algorithms.

Pork batter quality significantly affects its product. Herein, this study explored the use of Raman spectroscopy combined with deep learning algorithms for rapidly detecting pork batter quality and revealing the mechanisms of quality changes during heating. Results showed that heating increased ß-sheet content (from 26.38 to 41.42%) and exposed hidden hydrophobic groups, which formed aggregates through chemical bonds. Dominant hydrophobic interactions further cross-linked these aggregates, establishing a more homogeneous and denser network at 80 °C. Subsequently, convolutional neural networks (CNN), long short-term memory neural networks (LSTM), and CNN-LSTM were comparatively used to predict gel strength and whiteness in batters based on the Raman spectrum. Thereinto, CNN-LSTM provided the optimal results for gel strength (Rp = 0.9515, RPD = 3.1513) and whiteness (Rp = 0.9383, RPD = 3.0152). Therefore, this study demonstrated the potential of Raman spectroscopy combined with deep learning algorithms as non-destructive tools for predicting pork batter quality and elucidating quality change mechanisms.

Examination of primary aromatic amines content in polylactic acid straws and migration into food simulants using SERS with LC-MS.

Polylactic acid (PLA) straws hold eco-friendly potential; however, residual diisocyanates used to enhance the mechanical strength can generate carcinogenic primary aromatic amines (PAAs), posing health risks. Herein, we present a rapid, comprehensive strategy to detecting PAAs in 18 brands of food-grade PLA straws and assessing their migration into diverse food simulants. Surface-enhanced Raman spectroscopy was conducted to rapidly screen straws for PAAs. Subsequently, qualitative determination of migrating PAAs into various food simulants (4 % acetic acid, 10 % ethanol, 50 % ethanol) occurred at 70 °C for 2 h using liquid chromatography-mass spectrometry. Three PAAs including 4,4'-methylenedianiline, 2,4'-methylenedianiline, and 2,4-diaminotoluene were detected in all straws. Specifically, 2,4-diaminotoluene in 50 % ethanol exceeded specific migration limit of 2 µg/kg, raising safety concerns. Notably, PAAs migration to 10 % and 50 % ethanol surpassed that to 4 % acetic acid within a short 2-hour period. Moreover, PLA straws underwent varying degrees of shape changes before and after migration. Straws with poly(butylene succinate) resisted deformation compared to those without, indicating enhanced heat resistance, while poly(butyleneadipate-co-terephthalate) improved hydrolysis resistance. Importantly, swelling study unveiled swelling effect wasn't the primary factor contributing to the increased PAAs migration in ethanol food simulant, as there was no significant disparity in swelling degrees across different food simulants. FT-IR and DSC analysis revealed higher PAAs content in 50 % ethanol were due to highly concentrated polar ethanol disrupting hydrogen bonds and van der Waal forces holding PLA molecules together. Overall, minimizing contact between PLA straws and alcoholic foods is crucial to avoid potential safety risks posed by PAAs.

Rapid detection of fertilizer information based on Raman spectroscopy and machine learning.

The rapid detection of fertilizer nutrient information is a crucial element in enabling intelligent and precise variable fertilizer application. However, traditional detection methods possess limitations, such as the difficulty in quantifying multiple components and cross-contamination. In this study, a rapid detection method was proposed, leveraging Raman spectroscopy combined with machine learning, to identify five types of fertilizers: K2SO4, (CO(NH2)2, KH2PO4, KNO3, and N:P:K (15-15-15), along with their concentrations. Qualitative and quantitative models of fertilizers were constructed using three machine learning algorithms combined with five spectral preprocessing methods. Two variable selection methods were used to optimize the quantitative model. The results showed that the classification accuracy of the five fertilizer solutions obtained by random forest (RF) was 100 %. Moreover, in terms of regression, partial least squares regression (PLSR) outperformed extreme learning machine (ELM) and least squares support vector machine (LSSVM), yielding prediction Rp2 within the range of 0.9843-0.9990 and a root mean square error in the range of 0.0486-0.1691. In addition, this study evaluated the impact of different water types (deionized water, well water, and industrial transition water) on the detection of fertilizer information via Raman spectroscopy. The results showed that while different water types did not notably affect the identification of fertilizer nutrients, they did exert a pronounced effect on the quantification of concentrations. This study highlights the efficacy of combining Raman spectroscopy with machine learning in detecting fertilizer nutrients and their concentration information effectively.

Entrance channels to coproheme in coproporphyrin ferrochelatase probed by exogenous imidazole binding.

Iron insertion into porphyrins is an essential step in heme biosynthesis. In the coproporphyrin-dependent pathway, specific to monoderm bacteria, this reaction is catalyzed by the monomeric enzyme coproporphyrin ferrochelatase. In addition to the mechanistic details of the metalation of the porphyrin, the identification of the substrate access channel for ferrous iron to the active site is important to fully understand this enzymatic system. In fact, whether the iron reaches the active site from the distal or the proximal porphyrin side is still under debate. In this study we have thoroughly addressed this question in Listeria monocytogenes coproporphyrin ferrochelatase by X-ray crystallography, steady-state and pre-steady-state imidazole ligand binding studies, together with a detailed spectroscopic characterization using resonance Raman and UV-vis absorption spectroscopies in solution. Analysis of the X-ray structures of coproporphyrin ferrochelatase-coproporphyrin III crystals soaked with ferrous iron shows that iron is present on both sides of the porphyrin. The kinetic and spectroscopic study of imidazole binding to coproporphyrin ferrochelatase­iron coproporphyrin III clearly indicates the presence of two possible binding sites in this monomeric enzyme that influence each other, which is confirmed by the observed cooperativity at steady-state and a biphasic behavior in the pre-steady-state experiments. The current results are discussed in the context of the entire heme biosynthetic pathway and pave the way for future studies focusing on protein-protein interactions.

Machine Learning-Assisted Near-Infrared Spectral Fingerprinting for Macrophage Phenotyping.

Spectral fingerprinting has emerged as a powerful tool that is adept at identifying chemical compounds and deciphering complex interactions within cells and engineered nanomaterials. Using near-infrared (NIR) fluorescence spectral fingerprinting coupled with machine learning techniques, we uncover complex interactions between DNA-functionalized single-walled carbon nanotubes (DNA-SWCNTs) and live macrophage cells, enabling in situ phenotype discrimination. Utilizing Raman microscopy, we showcase statistically higher DNA-SWCNT uptake and a significantly lower defect ratio in M1 macrophages compared to M2 and naive phenotypes. NIR fluorescence data also indicate that distinctive intraendosomal environments of these cell types give rise to significant differences in many optical features, such as emission peak intensities, center wavelengths, and peak intensity ratios. Such features serve as distinctive markers for identifying different macrophage phenotypes. We further use a support vector machine (SVM) model trained on SWCNT fluorescence data to identify M1 and M2 macrophages, achieving an impressive accuracy of >95%. Finally, we observe that the stability of DNA-SWCNT complexes, influenced by DNA sequence length, is a crucial consideration for applications, such as cell phenotyping or mapping intraendosomal microenvironments using AI techniques. Our findings suggest that shorter DNA-sequences like GT6 give rise to more improved model accuracy (>87%) due to increased active interactions of SWCNTs with biomolecules in the endosomal microenvironment. Implications of this research extend to the development of nanomaterial-based platforms for cellular identification, holding promise for potential applications in real time monitoring of in vivo cellular differentiation.

Effect of hematoma on early degradation behaviour of magnesium after implantation.

The corrosion of magnesium (Mg)-based bioabsorbable implanting devices is influenced by implantation environment which dynamically changes by biological response including wound healing. Understanding the corrosion mechanisms along the healing process is essential for the development of Mg-based devices. In this study, a hematoma model was created in a rat femur to analyze Mg corrosion with hematoma in the early stage of implantation. Pure Mg specimen (99.9%, φ1.2×6 mm) was implanted in rat femur under either hematoma or non-hematoma conditions. After a designated period of implantation, the specimens were collected and weighed. The insoluble salts formed on the specimen surfaces were analyzed using scanning electron microscopy, energy-dispersive X-ray spectroscopy, and Raman spectroscopy on days 1, 3, and 7. The results indicate that hematomas promote Mg corrosion and change the insoluble salt precipitation. The weight loss of the hematoma group (27.31 ± 5.91 µg/mm2) was significantly larger than that of the non-hematoma group (14.77 ± 3.28 µg/mm2) on day 7. In the non-hematoma group, carbonate and phosphate were detected even on day 1, but the only latter was detected on day 7. In the hematoma group, hydroxide was detected on day 1, followed by the formation of carbonate and phosphate on days 3 and 7. The obtained results suggest the hypoxic and acidic microenvironment in hematomas accelerates the Mg corrosion immediately after implantation, and the subsequent hematoma resorption process leads to the formation of phosphate and carbonate with organic molecules. This study revealed the risk of hematomas as an acceleration factor of the corrosion of Mg-based devices leading to the early implant failure. It is important to consider this risk in the design of Mg-based devices and to optimize surgical procedures controlling hemorrhage at implantation and reducing unexpected bleeding after surgery.

Mapping lipid species remodeling in high fat diet-fed mice: Unveiling adipose tissue dysfunction with Raman microspectroscopy.

Dysregulated lipid metabolism in obesity leads to adipose tissue expansion, a major contributor to metabolic dysfunction and chronic disease. Lipid metabolism and fatty acid changes play vital roles in the progression of obesity. In this proof-of-concept study, Raman techniques combined with histochemical imaging methods were utilized to analyze the impact of a high-fat diet (HFD) on different types of adipose tissue in mice, using a small sample size (n = 3 per group). After six weeks of high-fat diet (HFD) feeding, our findings showed hypertrophy, elevated collagen levels, and increased macrophage presence in the adipose tissues of the HFD group compared to the low-fat diet (LFD) group. Statistical analysis of Raman spectra revealed significantly lower unsaturated lipid levels and higher lipid to protein content in different fat pads (brown adipose tissue (BAT), subcutaneous white adipose tissue (SWAT), and visceral white adipose tissue (VWAT)) with HFD. Raman images of adipose tissues were analyzed using Empty modeling and DCLS methods to spatially profile unsaturated and saturated lipid species in the tissues. It revealed elevated levels of ω-3, ω-6, cholesterol, and triacylglycerols in BAT adipose tissues of HFD compared to LFD tissues. These findings indicated that while cholesterol, ω-6/ω-3 ratio, and triacylglycerol levels have risen in the SWAT and VWAT adipose tissues of the HFD group, the levels of ω-3 and ω-6 have decreased following the HFD. The study showed that Raman spectroscopy provided invaluable information at the molecular level for investigating lipid species remodeling and spatial mapping of adipose tissues during HFD.

Metabolic Fingerprinting of Serum and Seminal Plasma of Testicular Cancer Patients Using Raman Spectroscopy: A Pilot Study.

Background: Testicular cancer (TC) is a relatively rare type of cancer in men. Early diagnosis of TC remains challenging. Metabolomics holds promise in offering valuable insights in this regard. In this study, a metabolic fingerprinting approach was employed to identify potential biomarkers in both serum and seminal plasma of TC patients. Methods: A total of 9 patients with testicular cancer and 10 controls were included in the study. The metabolic fingerprinting approach was utilized as a rapid diagnostic tool to analyze the metabolome in serum and seminal plasma of TC patients in comparison to fertile men. Raman spectroscopy was applied for the analysis of metabolites in these biological samples. Results: Principal component analysis (PCA) and functional group analysis showed that the differentiation between serum samples from healthy men and TC patients was not possible. However, when analyzing seminal plasma, a significant difference was found between the two groups (p<0.05). Functional group analysis of serum only showed an increase in tryptophan concentration ratio in TC patients as compared to healthy men (p=0.03). In contrast, in seminal plasma of TC patients, this increase was observed in all analyzed compounds, including phenylalanine, tyrosine, lipids, proteins, phenols (p<0.001). Conclusion: Our study highlights the potential of metabolic fingerprinting as a fast diagnostic tool for screening TC patients, with seminal plasma serving as a valuable biological sample. Furthermore, several potential biomarkers, particularly phenylalanine, were identified in seminal plasma. This research contributes to our understanding of TC pathogenesis and has the potential to pave the way for early detection and personalized treatment approaches.

Twist Angle-Dependent Phonon Hybridization in WSe2/WSe2 Homobilayer.

The emerging moiré superstructure of twisted transition metal dichalcogenides (TMDs) leads to various correlated electronic and optical properties compared to those of twisted bilayer graphene. In such a versatile architecture, phonons can also be renormalized and evolve due to atomic reconstruction, which, in turn, depends on the twist angle. However, observing this reconstruction and its relationship to phonon behavior with conventional, cost-effective imaging methods remains challenging. Here, we used noninvasive Raman spectroscopy on twisted WSe2/WSe2 (t-WSe2) homobilayers to examine the evolution of phonon modes due to interlayer coupling and atomic reconstruction. Unlike in the natural bilayer (NB), ∼0° as well as ∼60° t-WSe2 samples, the nearly degenerate A1g/E2g mode in the twisted samples (1-7°) split into a doublet in addition to the nondegenerate B2g mode, and the maximum splitting is observed around 2-3°. Our detailed theoretical calculations qualitatively capture the splitting and its dependence as a function of the twist angle and highlight the role of the moiré potential in phonon hybridization. Additionally, we found that around the 2° twist angle, the anharmonic phonon-phonon interaction is higher than the natural bilayer and decreases for larger twist angles. Interestingly, we observed anomalous Raman frequency softening and line-width increase with the decreasing temperature below 50 K, pointing to the combined effect of enhanced electron-phonon coupling and cubic anharmonic interactions in moiré superlattice.

Controlled Spread of a Ag Layer from the Core to the Tip along the Branches of AuAg Nanostars for Improved SERS Detection of Okadaic Acid in Shellfish.

Plasmonic Au-Ag nanostars are excellent surface-enhanced Raman scattering (SERS) probes due to bimetallic coupling and the tip effect. However, the existing preparation methods of AuAg nanostars cannot achieve controlled growth of the Ag layer on the branches of nanostars and so cannot display their SERS to the maximum extent, thus limiting its sensitivity in biosensing. Herein, a novel strategy "PEI (polyethylenimine)-guided Ag deposition method" is proposed for synthesizing AuAg core-shell nanostars (AuAg@Ag NS) with a tunable distribution of the Ag layer from the core to the tip, which offers an avenue for investigating the correlation between SERS efficiency and the extent of spread of the Ag layer. It is found that AuAg@Ag NS with a Ag layer coated the whole branch has the strongest SERS performance because the coupling between the tips and Ag layer is maximized. Meanwhile, as a completely closed core-shell structure, AuAg@Ag NS can confine and anchor 4-ATP inside the Ag layer to avoid an unstable SERS signal. By connecting the aptamer, a reliable internal standard nanoprobe with a SERS enhancement factor (EF) up to 1.86 × 108 is prepared. Okada acid is detected through competitive adsorption of this SERS probes, and the detection limit is 36.6 pM. The results gain fundamental insights into tailoring the nanoparticle morphologies and preparation of internal standard nanoprobes and also provide a promising avenue for marine toxin detection in food safety.

Polarized Raman mapping and phase-transition by CW excitation for fast purely optical characterization of VO2 thin films.

Vanadium dioxide has attracted much interest due to the drastic change of the electrical and optical properties it exhibits during the transition from the semiconductor state to the metallic state, which takes place at a critical temperature of about 68 °C. Much study has been especially devoted to developing advanced fabrication methodologies to improve the performance of VO2 thin films for phase-change applications in optical devices. Films structural and morphological characterisation is normally performed with expensive and time consuming equipment, as x-ray diffractometers, electron microscopes and atomic force microscopes. Here we propose a purely optical approach which combines Polarized Raman Mapping and Phase-Transition by Continuous Wave Optical Excitation (PTCWE) to acquire through two simple measurements structural, morphological and thermal behaviour information on polycrystalline VO2 thin films. The combination of the two techniques allows to reconstruct a complete picture of the properties of the films in a fast and effective manner, and also to unveil an interesting stepped appearance of the hysteresis cycles probably induced by the progressive stabilization of rutile metallic domains embedded in the semiconducting monoclinic matrix.

Imaging macular carotenoids and their related proteins in the human retina with confocal resonance Raman and fluorescence microscopy.

Lutein and zeaxanthin are highly concentrated at the central region of the human retina, forming a distinct yellow spot known as the macula lutea. The delivery and retention of the macular pigment carotenoids in the macula lutea involves many proteins, but their exact roles remain incompletely understood. In our study, we examined the distribution of the twelve known macular carotenoid-related proteins within the human macula and the underlying retinal pigment epithelium (RPE) using both fluorescence and Raman modes on our confocal resonance Raman microscope. Additionally, we assessed protein and gene expression through Western blot analysis and a single-cell RNA sequencing database. Our findings revealed that GSTP1, BCO2, and Aster-B exhibited distribution patterns similar to the macular carotenoids, with higher expression levels within the macular region compared to the periphery, while SR-BI and ABCA1 did not exhibit specific distribution patterns within the macula or RPE. Interestingly, LIPC, SR-BI's partner, accumulated specifically in the sub-foveal RPE. All three of these carotenoid transport proteins were found to be highly expressed in the RPE. These results offer valuable insights into the roles these proteins play in the formation of the macula lutea.

Development of SERS Active Nanoprobe for Selective Adsorption and Detection of Alzheimer's Disease Biomarkers Based on Molecular Docking.

Purpose: Development of SERS-based Raman nanoprobes can detect the misfolding of Amyloid beta (Aß) 42 peptides, making them a viable diagnostic technique for Alzheimer's disease (AD). The detection and imaging of amyloid peptides and fibrils are expected to help in the early identification of AD. Methods: Here, we propose a fast, easy-to-use, and simple scheme based on the selective adsorption of Aß42 molecules on SERS active gold nanoprobe (RB-AuNPs) of diameter 29 ± 3 nm for Detection of Alzheimer's Disease Biomarkers. Binding with the peptides results in a spectrum shift, which correlates with the target peptide. We also demonstrated the possibility of using silver nanoparticles (AgNPs) as precursors for the preparation of a SERS active nanoprobe with carbocyanine (CC) dye and AgNPs known as silver nanoprobe (CC-AgNPs) of diameter 25 ± 4 nm. Results: RB-AuNPs probe binding with the peptides results in a spectrum shift, which correlates with the target peptide. Arginine peak appears after the conjugation confirms the binding of Aß 42 with the nanoprobe. Tyrosine peaks appear after conjugated Aß42 with CC-AgNPs providing binding of the peptide with the probe. The nanoprobe produced a strong, stable SERS signal. Further molecular docking was utilized to analyse the interaction and propose a structural hypothesis for the process of binding the nanoprobe to Aß42 and Tau protein. Conclusion: This peptide-probe interaction provides a general enhancement factor and the molecular structure of the misfolded peptides. Secondary structural information may be obtained at the molecular level for specific residues owing to isotope shifts in the Raman spectra. Conjugation of the nanoprobe with Aß42 selectively detected AD in bodily fluids. The proposed nanoprobes can be easily applied to the detection of Aß plaques in blood, saliva, and sweat samples.

Active Surface-Enhanced Raman Spectroscopy (SERS): A Novel Concept for Enhancing Signal Contrast in Complex Matrices Using External Perturbation.

Noninvasive detection of surface-enhanced Raman spectroscopy (SERS) signals from deep within tissue represents a common challenge in many biological and clinical applications including disease diagnosis and therapy monitoring. Such signals are typically weak and not readily discernible from often much larger Raman and fluorescence background signals (e.g., from surrounding tissue). Consequently, suboptimal sensitivity in the detection of SERS signals is often achieved in these situations. Similar issues can arise in SERS measurements in other diffusely scattering samples and complex matrices. Here, we propose a novel concept, active SERS, for the efficient retrieval of SERS signals from deep within complex matrices such as biological tissues that mitigates these issues. It relies on applying an external perturbation to the sample to alter the SERS signal from nanoparticles (NPs) deep inside the matrix. A measurement with and without, or before and after, such perturbation then can provide powerful contrasting data enabling an effective elimination of the matrix signals to reveal more clearly the desired SERS signal without the interfering background and associated artifacts. The concept is demonstrated using ultrasound (US) as an external source of perturbation and SERS NPs inserted deep within a heterogeneous tissue phantom mimicking a cluster of NPs accumulated within a small target lesion. The overall SERS signal intensity induced by the applied US perturbation decreased by ∼21% and the SERS signal contrast was considerably improved by eliminating subtraction artifacts present in a conventional measurement performed at a neighboring spatial location in a heterogeneous tissue sample. Although the technique was demonstrated with SERS gold NPs with a standard Raman label, it is envisaged that active SERS NPs (both the nanoscale metal geometry and Raman label) could be specifically designed to deliver an augmented response to the external stimulus to further enhance the achievable SERS signal contrast and yield even greater improvement in detection sensitivity. The method was demonstrated using transmission Raman spectroscopy; however, it is also applicable to other Raman implementations including spatially offset Raman spectroscopy and conventional Raman spectroscopy performed both at depth and at surfaces of complex matrices.

Self-Referenced Au Nanoparticles-Coated Glass Wafers for In Situ SERS Monitoring of Cell Secretion.

Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for discrimination of bimolecules in complex systems. However, its practical applications face challenges such as complicated manufacturing procedures and limited scalability of SERS substrates, as well as poor reproducibility during detection which compromises the reliability of SERS-based analysis. In this study, we developed a convenient method for simultaneous fabrication of massive SERS substrates with an internal standard to eliminate the substrate-to-substrate differences. We first synthesized Au@CN@Au nanoparticles (NPs) which contain embedded internal standard molecules with a single characteristic peak in the Raman-silent region, and then deposited the NPs on 6 mm glass wafers in a 96-well plate simply by centrifugation for 3 min. The one-time obtained 96 SERS substrates have excellent intrasubstrate uniformity and intersubstrate repeatability for SERS detection by using the internal standard (relative standard deviation = 10.47%), and were able to detect both charged and neutral molecules (crystal violet and triphenylphosphine) at a concentration of 10-9 M. Importantly, cells can be directly cultured on glass wafers in the 96-well plate, enabling real time monitoring of the secretes and metabolism change in response to external stimulation. We found that the release of nucleic acids, amino acids and lipids by MDA-MB-231 cells significantly increased under hypoxic conditions. Overall, our approach enables fast and large-scale production of Au@CN@Au NPs-coated glass wafers as SERS substrates, which are homogeneous and highly sensitive for monitoring trace changes of biomolecules.

Photoinduced Electron-Transfer-Mediated Differential Recognition of Proteins on Plasmonic Surfaces.

Photoinduced enhanced Raman spectroscopy (PIERS) has emerged as an efficient technique for enhancing the vibrational modes of analyte molecules adsorbed on a plasmonic nanoparticle-semiconductor hybrid material through chemical enhancement governed by electron transfer from the semiconductor to the plasmonic nanoparticles under an additional ultraviolet (UV) preirradiation step. The increase in chemical enhancement is imperative in analyzing and detecting pharmaceutically important moieties, such as amino acids and proteins, with a low Raman scattering cross section, even in complex biological environments. Herein, we demonstrate that UV preirradiation induced the creation of additional oxygen vacancies by introducing a low concentration (≈1%) of Ni as a dopant in the 2D platelike morphology of the BiOCl semiconductor; i.e., defect states in the semiconductor can induce charge transfer from the semiconductor to the plasmonic nanoparticles. This phenomenon facilitates electron transfer to the adsorbed analyte on the plasmonic surface. Additionally, we have shown the usefulness of this method in protein immobilization on the substrate surface, followed by the identification of a specific protein in the mixture of proteins. Proteins containing cysteine residues capture these electrons to form a surface-bound thiol group via a transient disulfide electron adduct radical. This allows differential binding of the protein molecules to the semiconductor plasmonic hybrid depending on the concentration of surface cysteine residues in proteins. Through PIERS and principal component analysis, we demonstrate the possibility of probing and distinguishing biomolecules based on their surface composition and secondary structure components even in their mixtures, thus paving the way for efficient analysis of complex biological systems.

SERS aptasensor for simultaneous detection of ochratoxin A and zearalenone utilizing a rigid enhanced substrate (ITO/AuNPs/GO) combined with Au@AgNPs.

The contamination of mycotoxins poses a serious threat to global food security, hence the urgent need for simultaneous detection of multiple mycotoxins. Herein, two SERS nanoprobes were synthesized by embedded SERS tags (4-mercaptopyridine, 4MPy; 4-mercaptobenzonitrile, TBN) into the Au and Ag core-shell structure, and each was coupled with the aptamers specific to ochratoxin A (OTA) and zearalenone (ZEN). Meanwhile, a rigid enhanced substrate Indium tin oxide glass/AuNPs/Graphene oxide (ITO/AuNPs/GO) was combined with aptamer functionalized Au@AgNPs via π-π stacking interactions between the aptamer and GO to construct a surface-enhanced Raman spectroscopy (SERS) aptasensor, thereby inducing a SERS enhancement effect for the effective and swift simultaneous detection of both OTA and ZEN. The presence of OTA and ZEN caused signal probes dissociation, resulting in an inverse correlation between Raman signal intensity (1005 cm-1 and 2227 cm-1) and the concentrations of OTA and ZEN, respectively. The SERS aptasensor exhibited wide linear detection ranges of 0.001-20 ng/mL for OTA and 0.1-100 ng/mL for ZEN, with low detection limits (LOD) of 0.94 pg/mL for OTA and 59 pg/mL for ZEN. Furthermore, the developed SERS aptasensor demonstrated feasible applicability in the detection of OTA and ZEN in maize, showcasing its substantial potential for practical implementation.