Journal of Raman Spectroscopy最新文献

Lysophosphatidic acid (LPA) has significant potential as a biomarker for diagnosis of ovarian cancer in female patients because it is present throughout all phases of the illness. Regrettably, there is not a clinically useful test for this biomarker yet. In this work, an ultra-detection of LPA molecule by Raman spectroscopy-based molecularly imprinted polymer (MIP) in serum samples is reported. β-CD was synthesized to facilitate the collection of Raman spectroscopy and combined with MIP to denote it as β-CD-MIP for the adsorption of LPA with high sensitivity and selectivity. Linear regression model in serum samples shows peaks at 1100 and 1116 cm⁻¹, respectively. A satisfactory linear fit was seen with LPA concentration log I = 3.7 log C + 1255.74 and with spiked serum log I = 4.6 log C + 327.22, respectively. The literature survey suggests the threshold LPA level in healthy person is 1.50 μM/L whereas the LPA level rises in patients with benign ovarian cancer tumor as 7.90 μM/L. This LPA level rises to 16.99 μM/L in ovarian cancer patients. On the basis of the band intensity, the limit of detection of the β-CD-MIP sensor for LPA was recorded as 0.003 μM/L. The binding constant of β-CD-MIP for LPA in serum was 0.031–0.003 μM/L, respectively. β-CD-MIP gel was optimized, characterized, and successfully applied on spiked serum samples. The findings of this research show that this substrate has a lot of potential for ultradetection of trace amounts of LPA molecule from the serum samples. The MIP sensor is robust, recyclable, efficient, and selective.

Habitual consumption of areca/betel nut in Southeast Asia has been associated with oral submucous fibrosis (OSMF) and its malignant transformation to oral squamous cell carcinoma. The current study aimed to assess the molecular alterations in fibroblast cell lines after treatment with areca nut. Areca nut extract (ANE) was prepared and characterized for its active ingredient, arecoline. ANE-treated cells were subjected to cell viability, proliferation, migration, morphologic changes, and transcript of OSMF genes (col1a1, col1a2, hsp47, timp1, timp2, timp3, and timp4). Further, liquid chromatography–mass spectrometry (LCMS) of cell lysate and Raman microspectroscopy (RMS) of fixed cells were performed for metabolomics/lipidomics and biomolecular alterations in the nucleus and periphery of ANE-treated cells. We compared and integrated the data from both techniques and observed that the cells treated with ANE mimicked OSMF and could be used as an in vitro model. LCMS showed a significant alteration in 17 metabolites and 165 lipid molecules in the cells treated with ANE. Further, 40 molecules in the nucleus and 29 in the periphery were found to be altered in these cells when subjected to RMS. Molecules associated with pathways such as the transfer of acetyl groups into mitochondria, amino sugar metabolism, and the Warburg effect were modulated the most upon ANE treatment. Acetyl CoA was found to be common in most of the altered pathways. Besides, the pathways affecting carbohydrate metabolism were also altered significantly. Targeting these molecules and pathways can help to prevent the malignant transformation of OSMF.

Amyloid fibrillation kinetics of proteins associated with neurodegenerative diseases has been extensively studied using Raman spectroscopy. The normalization factor for the spectra is crucial for obtaining correct kinetics of Raman indicators, especially vibrational band intensities. Here, we compared the concentration dependences between the absorption at 280 nm in UV–vis spectroscopy and the phenylalanine (Phe) Raman band intensity at 1003 cm⁻¹ in amyloid fibrillation kinetics of lysozyme. The former exhibits better performance as normalization factor. Using this new normalization factor, the effect of pH value on the transformation of hen egg-white lysozyme (HEWL) tertiary and secondary structures was studied subsequently. With increasing acidity, the unfolding of tertiary structures and the transformation of secondary structures are significantly accelerated. Notably, the populations of various secondary structures in the final state remain in the pH < 2.0 solutions, indicating that the branching ratios of “on-pathway” to amyloid fibrils and “off-pathway” to gel-like aggregates are independent on the pH value in the range of 1.1–1.9.

Cation-π interactions, often found in protein assemblies, are characterized by favorable electrostatic interactions between an aromatic π-electron surface and a positively charged species. There are evidences that reveal the importance of cation-π interactions between arginine and aromatic residues in protein structure and function. In this paper, the effect of cation-π interactions on the aggregation propensity of peptides derived from human islet polypeptide (hIAPP) was explored using UV resonance Raman and fluorescence spectroscopy. By employing an analog of hIAPP_22–29 in which Phe-23 is replaced with tryptophan (NWGAILSS), we were able to demonstrate an increase in the amyloidogenic propensity of this mutant in the presence of Zn²⁺ that is attributable to cation-π interactions. In contrast, no cation-π interactions were observed when the cationic F23R analog of hIAPP_22–29 (NRGAILSS) was allowed to interact with NWGAILSS. From these observations, it was surmised that in these peptides, the dominant interaction between arginine and tryptophan involves the π-cloud of the guanidino group and the indole ring, not cation-π interactions. The spectroscopic data, supported by density functional theory-based simulation results, suggest that arginine-tryptophan interaction involves π-π stacking where the guanidino group is oriented parallel to the indole ring. These hydrophobic interactions, coupled with the hydrotropic effect of the guanidine functionality of arginine, led to a delay in the aggregation kinetics of NWGAILSS. These unique interactions were further exploited to design a peptide inhibitor of full-length amylin self-assembly.

Density functional theory (DFT) calculations were performed to examine the impact of exchange–correlation (XC) functionals and van der Waals corrections (specifically the D3 method) on the structural and vibrational properties of the SrCl₂–NaCl and ZrF₄–LiF salt systems. Multiple XC functionals, including the local density approximation (LDA), the generalized gradient approximation using the Perdew–Burke–Ernzerhof (PBE) model, and its modified form suitable for solids (PBEsol), the dispersion-corrected PBE-D3 and PBEsol-D3, were considered. Of these functionals, LDA was found to exhibit the highest degree of error, while PBEsol and PBE-D3 displayed the least error. Underestimated lattice parameters compared with experimental values were observed to result in higher force constants, leading to an overprediction of vibrational frequencies. Conversely, an overestimation of lattice parameters was associated with lower vibrational frequencies. The methodology presented in this study yielded results that are in good agreement with experiment, irrespective of the method (finite differences vs. density functional perturbation theory) employed for calculating infrared and Raman spectra. It was further demonstrated that for alkali halides with weak Raman scattering, utilizing a supercell constructed from primitive cells better predicts Raman features than does the use of conventional cells.

Raman spectroscopy is a popular tool for characterizing complex biological materials and their geological remains. Ordination methods, such as principal component analysis (PCA), use spectral variance to create a compositional space, the ChemoSpace, grouping samples based on spectroscopic manifestations reflecting different biological properties or geological processes. PCA allows to reduce the dimensionality of complex spectroscopic data and facilitates the extraction of informative features into formats suitable for downstream statistical analyses, thus representing a first step in the development of diagnostic biosignatures from complex modern and fossil tissues. For such samples, however, there is presently no systematic and accessible survey of the impact of sample, instrument, and spectral processing on the occupation of the ChemoSpace. Here, the influence of sample count, unwanted signals and different signal-to-noise ratios, spectrometer decalibration, baseline subtraction, and spectral normalization on ChemoSpace grouping is investigated and exemplified using synthetic spectra. Increase in sample size improves the dissociation of groups in the ChemoSpace, and our sample yields a representative and mostly stable pattern in occupation with less than 10 samples per group. The impact of systemic interference of different amplitude and frequency, periodical or random features that can be introduced by instrument or sample, on compositional biological signatures is reduced by PCA and allows to extract biological information even when spectra of differing signal-to-noise ratios are compared. Routine offsets ($�\pm$1 cm⁻¹) in spectrometer calibration contribute in our sample to less than 0.1% of the total spectral variance captured in the ChemoSpace and do not obscure biological information. Standard adaptive baselining, together with normalization, increases spectral comparability and facilitates the extraction of informative features. The ChemoSpace approach to biosignatures represents a powerful tool for exploring, denoising, and integrating molecular information from modern and ancient organismal samples.

Systemic amyloidosis is a group of diseases in which misfolded proteins aggregate as fibrous amyloid proteins with a β-sheet structure and deposit in organs, resulting in organ failure. Most types of amyloidosis have a poor prognosis, and prompt diagnosis is essential for treatment. Systemic immunoglobulin light-chain (AL) amyloidosis is a type of amyloidosis that occurs when abnormal immunoglobulin light-chain proteins are deposited in various organs and tissues. The deposition of amyloid proteins in tissues has traditionally been confirmed using Congo red staining and polarised light microscopy, which show apple-green birefringence. In this study, we aimed to verify whether amyloid deposition in the heart, kidney, rectum, duodenum and skin can be detected using Raman microspectroscopy. Serial sections were prepared from formalin-fixed paraffin-embedded tissue biopsy samples obtained from patients with systemic amyloidosis. One of the serial sections was stained with Congo red to confirm the deposition of amyloid proteins using polarised light microscopy, whereas the other was left unstained for Raman microspectroscopy. A characteristic peak at Raman shift of 1665–1680 cm⁻¹, which may represent a β-sheet structure of amyloid proteins, was recorded in the area where the amyloid deposition had been confirmed by Congo red staining. Based on the peak at 1640–1680 cm⁻¹, a colour map was obtained to detect amyloid protein-positive regions. Thus, amyloid protein detection using Raman microspectroscopy may be useful for rapid diagnosis of amyloidosis.

Core (Co)/shell (Co-oxide) nanoparticles assembly exhibits interesting magnetic properties that depend on the inorganic shell characteristic (composition and crystalline structure). Assemblies of pure and partially oxidized cobalt (core/shell) nanoparticles, ~9 nm in diameter, were prepared and analyzed by techniques probing the matter at macroscale to nanoscale: UV–visible-near-infrared (NIR) transmission, FTIR, Raman microspectroscopy, and transmission electron microscopy. Attention is paid to compare nonoxidized and (partially) oxidized Co nanoparticles, coated with lauric acid as stabilizing agent (ligands). The approximately 1 nm disordered inorganic coating is perfectly detected by transmission electron microscopy, UV–visible–NIR, infrared, and Raman spectroscopy. The Raman spectrum is sensitive to laser wavelength and power due to the local heating induced by the laser, which modifies the interaction between the organic chains and the nanoparticle inorganic shell. For comparison, nanoparticle films were analyzed under heating from room temperature to 300°C. The “fusion” (dynamic disorder) of lauric (dodecanoic) chains is observed concomitantly with the merging of very low wavenumber Lambs' modes into a Rayleigh wing, which is consistent with an increase in the topological nanoparticle disorder. Hydroxylation or water adsorption is observed for Co film. The UV–visible–NIR and Raman spectra of the Co-oxide shell do not correspond to that of CoO (rock salt) nor to that of Co₃O₄ (spinel) but has some similarity to that of 2D delafossite (CoOOH) phase.

Analytical and real-time technology in pharmaceutical manufacturing process is an important need to ensure that manufactured drugs are safe and effective. Raman spectroscopy is an emerging technique that is able to perform quantitative analysis nondestructively due to the molecular structure of many drugs. Monitoring the content uniformity and quantification of active pharmaceutical ingredient (API) in the tablet preparation process, without the assistance of solvent, is one of the key concerns in the formulation design in order to provide stable, pure, and homogenous finished products. In this study, we investigated the possibility of using Raman data as an analytical method to quantify API, the intra- and inter-sample uniformity of content in the tableting process of Metformin hydrochloride tablets (C₄H₁₁N₅.HCl). Analysis of all standard samples for prediction of API uniformity represents an acceptable accuracy and precision with a relative standard deviation of 2.55%. Further investigation of tablets regarding to relative Raman intensity of some characteristic peaks demonstrates the amount of API content with an accuracy of ≥96%. These values have a good adaption with pharmacopeia monograph. Findings reveal that the Raman method can be routinely utilized for quantifying API, controlling the content uniformity and the stability of drugs in different stages of manufacturing.