In situ monitoring of loading and elution processes of cryoprotectants at the single-cell level with Raman spectroscopy.

BACKGROUND: The analysis of cell membrane permeability plays a crucial role in improving the procedures of cell cryopreservation, which will affect the specific parameter settings in loading, removal and cooling processes. However, existing studies have mostly focused on deriving permeability parameters through osmotic theoretical models and cell volume response analysis, and there is still a lack of the direct experimental evidence and analysis at the single-cell level regarding the migration of cryoprotectants. RESULTS: In this work, a side perfusion microfluidics chips combined with Raman spectroscopy system was built to monitor in situ the Raman spectroscopy of extracellular and intracellular solution during loading and elution process with different cryoprotectant solution systems (single and dual component). And it was found that loading a high concentration cryoprotectant solution system through a single elution cycle may result in significant residual protective agent, which can be mitigated by employing a multi-component formula but multiple elution operations are still necessary. Furthermore, the collected spectral signals were marked and analyzed to was perform preliminary relative quantitative analysis. The results showed that the intracellular concentration changes can be accurately quantified by the Raman spectrum and are closely related to the extracellular solution concentration changes. SIGNIFICANCE AND NOVELTY: By using the method of small flow perfusion (≤20 µL/min) in the side microfluidic chip after the gravity sedimentation of cells, the continuous loading and elution process of different cryoprotectants on chip and the spectral acquisition can be realized. The intracellular and extracellular concentrations can be quantified in situ based on the ratio of spectral peak intensities. These results indicate that spectroscopic analysis can be used to effectively monitor intracellular cryoprotectant residues.

Dystrophic calcinosis: structural and morphological composition, and evaluation of ethylenediaminetetraacetic acid ('EDTA') for potential local treatment.

BACKGROUND: To perform a detailed morphological analysis of the inorganic portion of two different clinical presentations of calcium-based deposits retrieved from subjects with SSc and identify a chemical dissolution of these deposits suitable for clinical use. METHODS: Chemical analysis using Fourier Transform IR spectroscopy ('FTIR'), Raman microscopy, Powder X-Ray Diffraction ('PXRD'), and Transmission Electron Microscopy ('TEM') was undertaken of two distinct types of calcinosis deposits: paste and stone. Calcinosis sample titration with ethylenediaminetetraacetic acid ('EDTA') assessed the concentration at which the EDTA dissolved the calcinosis deposits in vitro. RESULTS: FTIR spectra of the samples displayed peaks characteristic of hydroxyapatite, where signals attributable to the phosphate and carbonate ions were all identified. Polymorph characterization using Raman spectra were identical to a hydroxyapatite reference while the PXRD and electron diffraction patterns conclusively identified the mineral present as hydroxyapatite. TEM analysis showed differences of morphology between the samples. Rounded particles from stone samples were up to a few micron in size, while needle-like crystals from paste samples reached up to 0.5 µm in length. Calcium phosphate deposits were effectively dissolved with 3% aqueous solutions of EDTA, in vitro. Complete dissolution of both types of deposit was achieved in approximately 30 min using a molar ratio of EDTA/HAp of ≈ 300. CONCLUSIONS: Stone and paste calcium-based deposits both comprise hydroxyapatite, but the constituent crystals vary in size and morphology. Hydroxyapatite is the only crystalline polymorph present in the SSc-related calcinosis deposits. Hydroxyapatite can be dissolved in vitro using a dosage of EDTA considered safe for clinical application. Further research is required to establish the optimal medium to develop the medical product, determine the protocol for clinical application, and to assess the effectiveness of EDTA for local treatment of dystrophic calcinosis.

Hydrogel-Coated SERS Microneedles for Drug Monitoring in Dermal Interstitial Fluid.

In vivo drug monitoring is crucial for evaluating the effectiveness and safety of drug treatment. Blood sampling and analysis is the current gold standard but needs professional skills and cannot meet the requirements of point-of-care testing. Dermal interstitial fluid (ISF) showed great potential to replace blood for in vivo drug monitoring; however, the detection was challenging, and the drug distribution behavior in ISF was still unclear until now. In this study, we proposed surface-enhanced Raman spectroscopy (SERS) microneedles (MNs) for the painless and real-time analysis of drugs in ISF after intravenous injection. Using methylene blue (MB) and mitoxantrone (MTO) as model drugs, the innovative core-satellite structured Au@Ag SERS substrate, hydrogel coating over the MNs, rendered sensitive and quantitative drug detection in ISF of mice within 10 min. Based on this technique, the pharmacokinetics of the two drugs in ISF was investigated and compared with those in blood, where the drugs were analyzed via liquid chromatography-mass spectrometry. It was found that the MB concentration in ISF and blood was comparable, whereas the concentration of MTO in ISF was 2-3 orders of magnitude lower than in blood. This work proposed an efficient tool for ISF drug monitoring. More importantly, it experimentally proved that the penetration ratio of blood to ISF was drug-dependent, providing insightful information into the potential of ISF as a blood alternative for in vivo drug detection.

Source Tracing of Kidney Injury via the Multispectral Fingerprint Identified by Machine Learning-Driven Surface-Enhanced Raman Spectroscopic Analysis.

Early diagnosis of drug-induced kidney injury (DIKI) is essential for clinical treatment and intervention. However, developing a reliable method to trace kidney injury origins through retrospective studies remains a challenge. In this study, we designed ordered fried-bun-shaped Au nanocone arrays (FBS NCAs) to create microarray chips as a surface-enhanced Raman scattering (SERS) analysis platform. Subsequently, the principal component analysis (PCA)-two-layer nearest neighbor (TLNN) model was constructed to identify and analyze the SERS spectra of exosomes from renal injury induced by cisplatin and gentamycin. The established PCA-TLNN model successfully differentiated the SERS spectra of exosomes from renal injury at different stages and causes, capturing the most significant spectral features for distinguishing these variations. For the SERS spectra of exosomes from renal injury at different induction times, the accuracy of PCA-TLNN reached 97.8% (cisplatin) and 93.3% (gentamicin). For the SERS spectra of exosomes from renal injury caused by different agents, the accuracy of PCA-TLNN reached 100% (7 days) and 96.7% (14 days). This study demonstrates that the combination of label-free exosome SERS and machine learning could serve as an innovative strategy for medical diagnosis and therapeutic intervention.

Novel SERS Probe Based on Ag Nanobean/Cu Foam for Deep-Sea Extreme Environment Biomolecule Detection.

Here, we report on progress made in coupling advances in surface-enhanced Raman scattering (SERS) techniques with a deep-ocean deployable Raman spectrometer. Our SERS capability is provided by development of a Cu foam-loaded silver-nanobean (Ag/Cu foam) which we have successfully coupled to the tip of a Raman probe head capable of insertion into deep-sea sediments and associated fluids. Our purpose is to expand the range of molecular species which can be detected in deep-sea biogeochemical environments, and our initial targets are a series of amino acids reportedly found in pore waters of seep locations. Our work has progressed to the point of a full dock-based end-to-end test of the essential ship tether-ROV-deep-sea Raman system. We show here the initial results from this test as the essential requirement before at sea full ocean depth deployment. We describe in detail the procedures for preparing the Ag/Cu foam bean and demonstrate in our end-to-end test that this, when coupled to the spectrometer probe tip, yields a SERS signal enhancement of 1.2 × 106 for test molecules and detection of amino acids at 10-6 M levels consistent with reported levels of natural occurrence. Each nanobean unit is for single-use sensing since invasion of the sample fluid into the Ag/Cu foam matrix is not reversible. We describe techniques for bean rotation/replacement at depth to allow for multiple analyses at several locations during each ROV dive.

Raman hyperspectroscopy of saliva and machine learning for Sjögren's disease diagnostics.

Sjögren's disease is an autoimmune disorder affecting exocrine glands, causing dry eyes and mouth and other morbidities. Polypharmacy or a history of radiation to the head and neck can also lead to dry mouth. Sjogren's disease is often underdiagnosed due to its non-specific symptoms, limited awareness among healthcare professionals, and the complexity of diagnostic criteria, limiting the ability to provide therapy early. Current diagnostic methods suffer from limitations including the variation in individuals, the absence of a single diagnostic marker, and the low sensitivity and specificity, high cost, complexity, and invasiveness of current procedures. Here we utilized Raman hyperspectroscopy combined with machine learning to develop a novel screening test for Sjögren's disease. The method effectively distinguished Sjögren's disease patients from healthy controls and radiation patients. This technique shows potential for development of a single non-invasive, efficient, rapid, and inexpensive medical screening test for Sjögren's disease using a Raman hyper-spectral signature.

Surface-Area Enhanced Raman Spectroscopy of DNA in Porous Silica: A Quantitative and Reproducible Alternative to Plasmonic-Based SERS.

Despite the success of surface-enhanced Raman spectroscopy (SERS) for detecting DNA immobilized on plasmonic metal surfaces, its quantitative response is limited by the rapid falloff of enhancement with distance from the metal surface and variations in sensitivity that depend on orientation and proximity to plasmonic "hot spots". In this work, we assess an alternative approach for enhancing detection by immobilizing DNA on the interior surfaces of porous silica particles. These substrates provide over a 1000-fold greater surface area for detection compared to a planar support. The porous silica substrate is a purely dielectric material with randomly oriented internal surfaces, where scattering is independent of proximity and orientation of oligonucleotides relative to the silica surface. We characterize the quantitative response of Raman scattering from DNA in porous silica particles with sequences used in previous SERS investigations of DNA for comparison. The results show that Raman scattering of DNA in porous silica is independent of distance of nucleotides from the silica surface, allowing detection of longer DNA strands with constant sensitivity. The surface area enhancement within particles is reproducible (<4% particle-to-particle variation) owing to the uniform internal pore structure and surface chemistry of the silica support. DNA immobilization with a bis-thiosuccinimide linker provides a Raman-active internal standard for quantitative interpretation of Raman scattering results. Despite the high (30 mM) concentrations of immobilized DNA within porous silica particles, they can be used to measure nanomolar binding affinities of target molecules to DNA by equilibrating a very small number of particles with a sufficiently large volume of low-concentration solution of target molecules.

Relationships between conformational and vibrational features of tryptophan characteristic Raman markers.

Tryptophan (Trp) residue provides characteristic vibrational markers to the middle wavenumber spectral region of the Raman spectra recorded from peptides and proteins. In this report, we were particularly interested in eight Trp Raman markers, referred to as Wi (i = 1,…,8). All responsible for pronounced Raman lines, these markers originate from indole moiety, a bicyclic conjugated segment involved in the Trp structure. Numerous investigations have previously attempted to relate the variations observed in the spectral features of these markers to the environmental changes of Trp residues. To emphasize the most important points we can mention (i) the variations in the Raman profile of W4 (∼1360 cm-1) and W5 (∼1340 cm-1), frequently observed as a doublet with variable intensity ratio. These two markers were thought to result from a Fermi-resonance effect between certain planar and nonplanar modes; (ii) the changes observed in the wavenumbers and relative intensities of W4, W7 (∼880 cm-1) and W8 (∼760 cm-1) were supposed to be related to the accessibility of Trp to surrounding water molecules; and (iii) the wavenumber fluctuations of W3 (∼1550 cm-1), taken as a Trp side chain orientational marker. However, some ambiguities still exist regarding the interpretation of these markers, needing further clarification. Herein, upon a joint experimental and theoretical analysis based on a multiconformational approach, attention was paid to the relationships between structural and vibrational features of three indole-containing compounds with increasing structural complexity, i.e., skatole (3-methylindole), tryptophan, and tripeptide Gly-Trp-Gly. This study clearly shows that the existing assignments given to certain Trp Raman markers should be reconsidered, especially those based on the Fermi-resonance origin of W4-W5 (∼1360-1340 cm-1) doublet, as well as the purely environmental dependence of W7 and W8 markers.

Interface-constrained catalytic hairpin assembly permits highly sensitive SERS signaling of miRNA.

The rapid and precise monitoring of peripheral blood miRNA levels holds paramount importance for disease diagnosis and treatment monitoring. In this study, we propose an innovative research strategy that combines the catalytic hairpin assembly reaction with SERS signal congregation and enhancement. This combination can significantly enhance the stability of SERS detection, enabling stable and efficient detection of miRNA. Specifically, our paper-based SERS detection platform incorporates a streptavidin-modified substrate, biotin-labeled catalytic hairpin assembly reaction probes, 4-ATP, and primer-co-modified gold nanoparticles. In the presence of miRNA, the 4-ATP and primer-co-modified gold nanoparticles can specifically recognize the miRNA and interact with the biotin-labeled CHA probes to initiate an interfacial catalytic hairpin assembly reaction. This enzyme-free high-efficiency catalytic process can accumulate a large amount of biotin on the gold nanoparticles, which then bind to the streptavidin on the substrate with the assistance of the driving liquid, forming red gold nanoparticle stripes. These provide a multitude of hotspots for SERS, enabling enhanced signal detection. This innovative design achieves a low detection limit of 3.47 fM while maintaining excellent stability and repeatability. This conceptually innovative detection platform offers new technological possibilities and solutions for clinical miRNA detection.

Optical biosensors for diagnosis of COVID-19: nanomaterial-enabled particle strategies for post pandemic era.

The COVID-19 pandemic underlines the need for effective strategies for controlling virus spread and ensuring sensitive detection of SARS-CoV-2. This review presents the potential of nanomaterial-enabled optical biosensors for rapid and low-cost detection of SARS-CoV-2 biomarkers, demonstrating a comprehensive analysis including colorimetric, fluorescence, surface-enhanced Raman scattering, and surface plasmon resonance detection methods. Nanomaterials including metal-based nanomaterials, metal-organic frame-based nanoparticles, nanorods, nanoporous materials, nanoshell materials, and magnetic nanoparticles employed in the production of optical biosensors are presented in detail. This review also discusses the detection principles, fabrication methods, nanomaterial synthesis, and their applications for the detection of SARS-CoV-2 in four categories: antibody-based, antigen-based, nucleic acid-based, and aptamer-based biosensors. This critical review includes reports published in the literature between the years 2021 and 2024. In addition, the review offers critical insights into optical nanobiosensors for the diagnosis of COVID-19. The integration of artificial intelligence and machine learning technologies with optical nanomaterial-enabled biosensors is proposed to improve the efficiency of optical diagnostic systems for future pandemic scenarios.

Temperature-Caused Changes in Raman Pattern and Protein Profiles of Winter Triticale (x Triticosecale, Wittm.) Field-Grown Seedlings.

Climate change, which causes periods with relatively high temperatures in winter in Poland, can lead to a shortening or interruption of the cold hardening of crops. Previous research indicates that cold acclimation is of key importance in the process of acquiring cereal tolerance to stress factors. The objective of this work was to verify the hypothesis that both natural temperature fluctuations and the plant genotype influence the content of metabolites as well as proteins, including antioxidant enzymes and photosystem proteins. The research material involved four winter triticale genotypes, differing in their tolerance to stress under controlled conditions. The values of chlorophyll a fluorescence parameters and antioxidant activity were measured in their seedlings. Subsequently, the contribution of selected proteins was verified using specific antibodies. In parallel, the profiling of the contents of chlorophylls, carotenoids, phenolic compounds, and proteins was carried out by Raman spectroscopy. The obtained results indicate that a better PSII performance along with a higher photosystem II proteins content and thioredoxin reductase abundance were accompanied by a higher antioxidant activity in the field-grown triticale seedlings. The Raman studies showed that the cold hardening led to a variation in photosynthetic dyes and an increase in the phenolic to carotenoids ratio in all DH lines.

Kidney stone growth through the lens of Raman mapping.

Bulk composition of kidney stones, often analyzed with infrared spectroscopy, plays an essential role in determining the course of treatment for kidney stone disease. Though bulk analysis of kidney stones can hint at the general causes of stone formation, it is necessary to understand kidney stone microstructure to further advance potential treatments that rely on in vivo dissolution of stones rather than surgery. The utility of Raman microscopy is demonstrated for the purpose of studying kidney stone microstructure with chemical maps at ≤ 1 µm scales collected for calcium oxalate, calcium phosphate, uric acid, and struvite stones. Observed microstructures are discussed with respect to kidney stone growth and dissolution with emphasis placed on < 5 µm features that would be difficult to identify using alternative techniques including micro computed tomography. These features include thin concentric rings of calcium oxalate monohydrate within uric acid stones and increased frequency of calcium oxalate crystals within regions of elongated crystal growth in a brushite stone. We relate these observations to potential concerns of clinical significance including dissolution of uric acid by raising urine pH and the higher rates of brushite stone recurrence compared to other non-infectious kidney stones.

UV-Vis quantification of the iron content in iteratively steam and HCl purified single-walled carbon nanotubes.

As-produced carbon nanotubes contain impurities which can dominate the properties of the material and are thus undesired. Herein we present a multi-step purification treatment that combines the use of steam and hydrochloric acid in an iterative manner. This allows the reduction of the iron content down to 0.2 wt. % in samples of single-walled carbon nanotubes (SWCNTs). Remarkably, Raman spectroscopy analysis reveals that this purification strategy does not introduce structural defects into the SWCNTs' backbone. To complete the study, we also report on a simplified approach for the quantitative assessment of iron using UV-Vis spectroscopy. The amount of metal in SWCNTs is assessed by dissolving in HCl the residue obtained after the complete combustion of the sample. This leads to the creation of hexaaquairon(III) chloride which allows the determination of the amount of iron, from the catalyst, by UV-Vis spectroscopy. The main advantage of the proposed strategy is that it does not require the use of additional complexing agents.

Characteristic substance analysis and rapid detection of bacteria spores in cooked meat products by surface enhanced Raman scattering based on Ag@AuNP array substrate.

BACKGROUND: Bacterial spores are the main potential hazard in medium- and high-temperature sterilized meat products, and their germination and subsequent reproduction and metabolism can lead to food spoilage. Moreover, the spores of some species pose a health and safety threat to consumers. The rapid detection, prevention, and control of bacterial spores has always been a scientific problem and a major challenge for the medium and high-temperature meat industry. Early and sensitive identification of spores in meat products is a decisive factor in contributing to consumer health and safety. RESULTS: In this study, we developed a novel and stable Ag@AuNP array substrate by using a two-step synthesis approach and a liquid-interface self-assembly method that can directly detect bacterial spores in actual meat product samples without the need for additional in vitro bacterial culture. The results indicate that the Ag@AuNP array substrate exhibits high reproducibility and Raman enhancement effects (1.35 × 105). The differentiation in the Surface enhanced Raman scattering (SERS) spectra of five bacterial spores primarily arises from proteins in the spore coat and inner membrane, peptidoglycan of cortex, and Ca2⁺-DPA within the spore core. The correct recognition rate of linear discriminant analysis for spores in the meat product matrix can reach 100 %. The average recovery accuracy of the SERS quantitative model was at around 101.77 %, and the limit of detection can reach below 10 CFU/mL. SIGNIFICANCE: It provides a promising technological strategy for the characteristic substance analysis and timely monitoring of spores in meat products.

Unlocking Preclinical Alzheimer's: A Multi-Year Label-Free In Vitro Raman Spectroscopy Study Empowered by Chemometrics.

Alzheimer's disease is a progressive neurodegenerative disorder, the early detection of which is crucial for timely intervention and enrollment in clinical trials. However, the preclinical diagnosis of Alzheimer's encounters difficulties with gold-standard methods. The current definitive diagnosis of Alzheimer's still relies on expensive instrumentation and post-mortem histological examinations. Here, we explore label-free Raman spectroscopy with machine learning as an alternative to preclinical Alzheimer's diagnosis. A special feature of this study is the inclusion of patient samples from different cohorts, sampled and measured in different years. To develop reliable classification models, partial least squares discriminant analysis in combination with variable selection methods identified discriminative molecules, including nucleic acids, amino acids, proteins, and carbohydrates such as taurine/hypotaurine and guanine, when applied to Raman spectra taken from dried samples of cerebrospinal fluid. The robustness of the model is remarkable, as the discriminative molecules could be identified in different cohorts and years. A unified model notably classifies preclinical Alzheimer's, which is particularly surprising because of Raman spectroscopy's high sensitivity regarding different measurement conditions. The presented results demonstrate the capability of Raman spectroscopy to detect preclinical Alzheimer's disease for the first time and offer invaluable opportunities for future clinical applications and diagnostic methods.

Molecular Design Using Selected Concentration Effects in Optically Activated Fluorescent Matrices.

Molecular physics plays a pivotal role in various fields, including medicine, pharmaceuticals, and broader industrial applications. This study aims to enhance the methods for producing specific optically active materials with distinct spectroscopic properties at the molecular level, which are crucial for these sectors, while prioritizing human safety in both production and application. Forensic science, a significant socio-economic field, often employs hazardous substances in analyzing friction ridges on porous surfaces, posing safety concerns. In response, we formulated novel, non-toxic procedures for examining paper evidence, particularly thermal papers. Our laboratory model utilizes a polyvinyl alcohol polymer as a rigid matrix to emulate the thermal paper's environment, enabling precise control over the spectroscopic characteristics of 1,8-diazafluoro-9-one (DFO). We identified and analyzed the cyclodimer 1,8-diazafluoren-9-one (DAK DFO), which is a non-toxic and biocompatible alternative for revealing forensic marks. The reagents used to preserve fingerprints were optimized for their effectiveness and stability. Using stationary absorption and emission spectroscopy, along with time-resolved emission studies, we verified the spectroscopic attributes of the new structures under deliberate aggregation conditions. Raman spectroscopy and quantum mechanical computations substantiated the cyclodimer's configuration. The investigation provides robust scientific endorsement for the novel compound and its structural diversity, influenced by the solvatochromic sensitivity of the DFO precursor. Our approach to monitoring aggregation processes signifies a substantial shift in synthetic research paradigms, leveraging simple chemistry to yield an innovative contribution to forensic science methodologies.

Research on disease diagnosis based on teacher-student network and Raman spectroscopy.

Diabetic nephropathy is a serious complication of diabetes, and primary Sjögren's syndrome is a disease that poses a major threat to women's health. Therefore, studying these two diseases is of practical significance. In the field of spectral analysis, although common Raman spectral feature selection models can effectively extract features, they have the problem of changing the characteristics of the original data. The teacher-student network combined with Raman spectroscopy can perform feature selection while retaining the original features, and transfer the performance of the complex deep neural network structure to another lightweight network structure model. This study selects five flow learning models as the teacher network, builds a neural network as the student network, uses multi-layer perceptron for classification, and selects the optimal features based on the evaluation indicators accuracy, precision, recall, and F1-score. After five-fold cross-validation, the research results show that in the diagnosis of diabetic nephropathy, the optimal accuracy rate can reach 98.3%, which is 14.02% higher than the existing research; in the diagnosis of primary Sjögren's syndrome, the optimal accuracy rate can be reached 100%, which is 10.48% higher than the existing research. This study proved the feasibility of Raman spectroscopy combined with teacher-student network in the field of disease diagnosis by producing good experimental results in the diagnosis of diabetic nephropathy and primary Sjögren's syndrome.

Bilateral efforts to improve SERS detection efficiency of exosomes by Au/Na7PMo11O39 Combined with Phospholipid Epitope Imprinting.

Detection of cancer-related exosomes in body fluids has become a revolutionary strategy for early cancer diagnosis and prognosis prediction. We have developed a two-step targeting detection method, termed PS-MIPs-NELISA SERS, for rapid and highly sensitive exosomes detection. In the first step, a phospholipid polar site imprinting strategy was employed using magnetic PS-MIPs (phospholipids-molecularly imprinted polymers) to selectively isolate and enrich all exosomes from urine samples. In the second step, a nanozyme-linked immunosorbent assay (NELISA) technique was utilized. We constructed Au/Na7PMo11O39 nanoparticles (NPs) with both surface-enhanced Raman scattering (SERS) property and peroxidase catalytic activity, followed by the immobilization of CD9 antibodies on the surface of Au/Na7PMo11O39 NPs. The Au/Na7PMo11O39-CD9 antibody complexes were then used to recognize CD9 proteins on the surface of exosomes enriched by magnetic PS-MIPs. Lastly, the high sensitivity detection of exosomes was achieved indirectly via the SERS activity and peroxidase-like activity of Au/Na7PMo11O39 NPs. The quantity of exosomes in urine samples from pancreatic cancer patients obtained by the PS-MIPs-NELISA SERS technique showed a linear relationship with the SERS intensity in the range of 6.21 × 107-2.81 × 108 particles/mL, with a limit of detection (LOD) of 5.82 × 107 particles/mL. The SERS signal intensity of exosomes in urine samples from pancreatic cancer patients was higher than that of healthy volunteers. This bidirectional MIPs-NELISA-SERS approach enables noninvasive, highly sensitive, and rapid detection of cancer, facilitating the monitoring of disease progression during treatment and opening up a new avenue for rapid early cancer screening.